UNIVERSITY OF COPENHAGEN
FACULTY OF SCIENCE
PhD Thesis
Thomas Thyge Thomsen, M.Sc. Biology
Peptide antibiotics for ESKAPE pathogens
Past, present and future perspectives of antimicrobial peptides for the
treatment of serious Gram-negative and Gram-positive infections.
This PhD thesis has been submitted to the PhD school of The Faculty of Science, University of
Copenhagen, Denmark, 4. January 2016.
Academic advisors
Kim Rewitz, Ph.D., Associate Professor
Department of Biology
Cell and Neurobiology
University of Copenhagen, Denmark
Anders Løbner-Olesen, Ph.D., Professor
Department of Biology
Functional Genomics
University of Copenhagen, Denmark
Assessment committee
Hanne Ingmer, Professor (chair)
Health Department
University of Copenhagen
Volker Loeschcke, Professor
Department of Biosciences – Genetics, Ecology and
Evolution
Aarhus University, Denmark
Gabriele Bierbaum, Professor. Dr.
Institute of Medical Microbiology, Immunology and
Parasitology
University of Bonn
Submitted
04.01.2016
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ACKNOWLEDGEMENTS
I would like to give special thanks to my supervisors on this project. Kim Rewitz has provided
excellent support as my main supervisor and it would be hard to find a person with more dedication
to science and his students. He has provided expert knowledge to all work regarding Drosophila
and experimental procedures and supported me during all aspects of my PhD. Anders LøbnerOlesen has provided excellent guidance and discussion on all my microbiological work. Anders has
maintained focused and supportive during times when the project seemed less successful, which has
helped me keep focused.
Much of the work in this thesis could not have been carried out without the work of Håvard Jenssen
and Biljana Mojsoska; Thank you guys for your work on peptide synthesis and discussion. I wish to
thank Paul Robert Hansen and Alberto Oddo for their collaborations and for excellent discussions.
Also a special thanks you to Stefano Donadio for his interest in collaborations and discussion along
the way.
Furthermore I would like to thank all the people from the two labs where I have worked. The
Rewitz Lab; Erik Thomas Danielsen, Morten Møller, Julie Lilith Hentze, Anne Færch Jørgensen,
Morten Rose and all the other students and people from the neurobiology section. ALO Lab; Jakob
Frimodt-Møller for sharing the ups and down during our PhD, Louise Bjørn, Maria Schei Haugan,
Godefroid Charbon, Henrik Jakobsen, Michaela Lederer, Rasmus Nielsen Klitgaard, Luis Clàudio
Nascimento da Silva, Susanne Kjelstrup, Linette Skov, Christopher Campion and all the other
students from the ALO lab.
Finally I wish to thank my family for support during my PhD.
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ABSTRACT
Multi-drug resistance to antibiotics represents a global health challenge that results in increased
morbidity and mortality rates. The annual death-toll is >700.000 people world-wide, rising to ~10
million by 2050. New antibiotics are lacking, and few are under development as return on
investment is considered poor compared to medicines for lifestyle diseases. According to the WHO
we could be moving towards a post-antibiotic era in which previously treatable infections become
fatal. Of special importance are multidrug resistant bacteria from the ESKAPE group (Enterococcus
faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter, Pseudomonas aeruginosa
and Enterobacter). As a consequence of widespread multi-drug resistance, researchers have sought
for alternative sources of antimicrobials. Antimicrobial peptides are produced by almost all living
organisms as part of their defense or innate immune system and are therefore of interest for
development of novel antimicrobials.
This thesis aimed at developing new or improved peptide-based antimicrobials, capable of killing or
inhibiting the proliferation of important multidrug resistant bacteria. Further we sought to analyze in
vivo efficacy and toxicity by utilizing of the fruit fly Drosophila melanogaster as a whole animal
model. This was carried out by testing of antimicrobial peptides targeting Gram-positive bacteria
exemplified by the important human pathogen methicillin resistant S. aureus (MRSA).
The peptide BP214 was developed from a cecropin-mellitin hybrid peptide and proved effective in
killing colistin resistant Gram-negative A. baumannii in vitro. The molecule was improved with
regard to toxicity, as measured by hemolytic ability. Further, this peptide is capable of specifically
killing non-growing cells of colistin resistant A. baumannii, also known as persisters.
Using D. melanogaster as an in vivo efficacy model it was demonstrated that the Lantibiotic NAI107, currently undergoing pre-clinical studies, rescues D. melanogaster from MRSA infection with
similar efficacy to last resort antimicrobial vancomycin. Furthermore, it was shown that this
antimicrobial has similar capability to BP214 in killing non-growing cells of S. aureus. However,
for NAI-107 this is independent of genotype and underscores its potential for future development.
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ABSTRACT – DANISH
Multiresistente bakterier er et voksende globalt sundhedsproblem. På verdensplan dør mere end
700.000 mennesker årligt som følge af infektioner med multiresistente bakterier. Udvikling af nye
antibiotika er mangelfuld fordi det for medicinal industrien bedre kan betale sig, at udvikle medicin
til behandling af livsstil sygdomme. Ifølge WHO kan vi snart befinde os i en post antibiotika æra,
hvor behandling af infektioner ikke længere er mulig. Særligt problematiske er bakterier fra
ESKAPE gruppen (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae,
Acinetobacter, Pseudomonas aeruginosa and Enterobacter). Som en konsekvens af multiresistente
bakterier har det været nødvendigt at finde alternativer til de kendte antibiotika. Næsten alle levende
organismer producere antimikrobielle peptider som forsvar eller innate immun forsvar imod
mikroorganismer hvilket gør disse stoffer interessante for udviklingen af nye antibiotika.
Dette Ph.d. projekt havde til formål at udvikle nye eller forbedrede peptid baserede antimikrobielle
stoffer, som kunne inhibere eller dræbe multiresistente bakterier. Vi ønskede at benytte banan fluen
Drosophila melanogaster som en simple model til at vurdere in vivo effektiviteten og toksiciteten af
peptider. Dette gjorde vi ved at inficere Drosophila med den Gram-positive bakterie methicillinresistent S. aureus (MRSA) og behandle med antimikrobielle peptider mod Gram-positive bakterier.
Med udgangspunkt i et cecropin-mellitin hybrid peptid, udviklede vi BP214, som effektivt kan slå
colistin resistente stammer af Gram-negative A. Baumannii ihjel in vitro. BP214 havde en forbedret
toksicitet profil i forhold til tidligere molekyler. Dette blev målt ved hemolytisk kapabilitet.
Endvidere har vi vist at BP214 specifikt kan slå ikke voksende (”persisters”) celler af colistin
resistente A. baumannii ihjel.
I Drosophila in vivo modellen påviser vi at peptidet NAI-107 med samme effektivitet som
vancomycin redder Drosophila fra infektioner med MRSA. Nai-107 er allerede under udvikling til
fremtidig brug som antibiotika. Vi viser yderligere at NAI-107 ligesom BP214 kan slå ikke
voksende celler af S. aureus ihjel. Ulig BP214 er denne egenskab for NAI-107 uafhængig af
bakteriernes genotype hvilket understreger dets egenskaber som fremtidens antibiotika.
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LIST OF PAPERS
Paper I
“An all-D amphipathic undecapeptide shows promising activity against
colistin-resistant strains of Acinetobacter baumannii and a dual mode of
action” by Alberto Oddo, Thomas TT, Susanne Kjelstrup, Ciara
Gorey, Henrik Franzyk, Niels Frimodt-Møller, Anders Løbner-Olesen,
and Paul Hansen [AAC01966-15].
Paper II
“Modulation of backbone flexibility for effective dissociation of
antibacterial and hemolytic activity in cyclic antimicrobial peptides
without loss of potency” by Alberto Oddo, Thomas T. Thomsen, Hanna
M. Britt, Anders Løbner-Olesen, Peter W. Thulstrup, John M.
Sanderson, and Paul R. Hansen. Submitted to ACS Medicinal Chemistry
Letters
Paper III
“The Lantibiotic Nai-107 efficiently rescues Drosophila melanogaster
from infection with methicillin-resistant Staphylococcus aureus
USA300” by Thomas T. Thomsen, Biljana Mojsoska, Joao Cruz,
Stefano Donadio, Håvard Jenssen, Anders Løbner-Olesen, Kim Rewitz.
Submitted to Antimicrobial Agents and Chemotherapy.
Papers not included in the thesis (see appendix)
Paper I
“Rapid selection of Plasmodium falciparum chloroquine resistance
transporter gene and multidrug resistance gene-1 haplotypes associated
with past chloroquine and present artemether-lumefantrine use in
Inhambane District, southern Mozambique.” By Thomsen TT, Madsen
LB, Hansson HH, Tomás EV, Charlwood D, Bygbjerg IC, Alifrangis M
Am J Trop Med Hyg. 2013 Mar; 88(3):536-41. doi: 10.4269/ajtmh.120525. Epub 2013 Feb 4.
Paper II
“Collateral Resistance and Sensitivity Modulate Evolution of HighLevel Resistance to Drug Combination Treatment in Staphylococcus
aureus.” by Rodriguez de Evgrafov M, Gumpert H, Munck C, Thomsen
TT, Sommer MO. Mol Biol Evol. 2015 May; 32(5):1175-85. doi:
10.1093/molbev/msv006. Epub 2015 Jan 23.
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LIST OF FIGURES
Figure 1. Drug Development and Resistance: Adapted from (9) ...................................................... 11 Figure 2. Generalized representation of Gram-negative and Gram-positive membranes: Adapted
from (13, 14) ...................................................................................................................................... 13 Figure 3. Antibiotic targets: ............................................................................................................... 15 Figure 4. Vertical and horizontal gene transfer: Adapted from (37) ................................................. 18 Figure 5. Resistance mechanisms: ..................................................................................................... 19 Figure 6. Peptidoglycan synthesis inhibition in S. aureus: Adapted from (80) ................................. 24 Figure 7. Lysylphosphatidylglycerol (L-PG) synthesis: Adapted from (86) ..................................... 25 Figure 8. Structure of Important β-Lactam antibiotics: Adapted from (98) ...................................... 27 Figure 9. Polymyxin Mechanism of action: Adapted from (107) ...................................................... 29 Figure 10. Bacteriocins mechanism of action: An overview. From (131) ........................................ 32 Figure 11. Lantibiotics: From (155) ................................................................................................... 34 Figure 12. Structures of host defence peptides. Adapted from (122, 166) ........................................ 35 Figure 13. Overview of the pore formation models: Adapted from (173) ......................................... 36 Figure 14. Peptides and Peptoids; Adapted from Mojsoska et al. (197) ............................................ 38 Figure 15. Drosophila Immunity:....................................................................................................... 42 Figure 16. Lipid II of Gram-positive and Gram-negative bacteria: Adapted from (24, 235). ......... 123 7
Table of Content
ACKNOWLEDGEMENTS ................................................................................................... 3 ABSTRACT ......................................................................................................................... 4 ABSTRACT – DANISH ....................................................................................................... 5 LIST OF PAPERS ...............................................................................................................6 Papers not included in the thesis (see appendix) ............................................................................................................ 6 LIST OF FIGURES ..............................................................................................................7 INTRODUCTION - ANTIBIOTICS ..................................................................................... 10 Historical overview ......................................................................................................................................................... 10 Spectrum of activity........................................................................................................................................................ 12 Antibiotic targets ............................................................................................................................................................ 14 Antibiotic resistance ....................................................................................................................................................... 16 Genetics of resistance .................................................................................................................................................. 16 Mechanism of resistance .............................................................................................................................................. 18 Multidrug-resistance (MDR) ......................................................................................................................................... 21 MDR Gram-positive bacteria:...................................................................................................................................... 21 MDR Gram-negative bacteria: ..................................................................................................................................... 27 PEPTIDE ANTIBIOTICS: A PART OF THE SOLUTION................................................... 30 Bacteriocins ..................................................................................................................................................................... 31 Lipid II targeting antimicrobial peptides...................................................................................................................... 33 Host defense peptides ..................................................................................................................................................... 35 Modified or synthetic: peptides and peptoids .............................................................................................................. 37 ALTERNATIVE IN VIVO MODELS ................................................................................... 39 PAPER I ............................................................................................................................ 43 8
An all-D amphipathic undecapeptide shows promising activity against colistin-resistant strains of Acinetobacter
baumannii and a dual mode of action ........................................................................................................................... 43 PAPER II ........................................................................................................................... 75 Modulation of backbone flexibility for effective dissociation of antibacterial and hemolytic activity in cyclic
antimicrobial peptides without loss of potency ............................................................................................................ 75 PAPER III .......................................................................................................................... 83 The Lantibiotic Nai-107 efficiently rescues Drosophila melanogaster from infection with methicillin-resistant
Staphylococcus aureus USA300 ..................................................................................................................................... 83 DISCUSSION .................................................................................................................. 118 Amphiphilic cationic peptides and peptoids ............................................................................................................... 118 Lipid-II targeting peptides ........................................................................................................................................... 120 A Drosophila in vivo efficacy model of infection......................................................................................................... 123 CONCLUSIONS .............................................................................................................. 124 FUTURE PERSPECTIVES .............................................................................................. 126 The cecropin-mellitin hybrid BP214.......................................................................................................................... 126 Lantibiotics and other Lipid II targeting antimicrobials ............................................................................................ 127 BIBLIOGRAPHY ............................................................................................................. 129 APPENDIX: PAPERS NOT INCLUDED IN THESIS ....................................................... 145 PAPER I .......................................................................................................................... 145 Rapid Selection of Plasmodium falciparum Chloroquine Resistance Transporter Gene and Multidrug Resistance
Gene-1 Haplotypes Associated with Past Chloroquine and Present Artemether-Lumefantrine Use in Inhambane
District, Southern Mozambique .................................................................................................................................. 145 PAPER II ......................................................................................................................... 152 Collateral Resistance and Sensitivity Modulate Evolution of High-Level Resistance to Drug Combination
Treatment in Staphylococcus aureus .......................................................................................................................... 152 9
INTRODUCTION - ANTIBIOTICS
Historical overview
The first antimicrobial compounds to be mass produced and used on a large scale in
clinical settings were the Sulfonamides or “sulpha drugs”. These synthetic compounds containing a
sulfonamide group, inhibit the enzyme dihydropteroate synthetase (DHPS) involved in folate
biosynthesis, and were first synthesized by Alfred Bertheim and Paul Ehrlich in 1907 (1), however
Gerhard Domagk is credited for the discovery of the first commercially available sulfonamide used
in the clinical setting “Prontocil”, for which he later received the Nobel Prize in 1939 (2).
The Discovery of penicillin in 1928 by Alexander Fleming (3), is by many recognized
as the first true antibiotic, a term coined by Selman Waksman as a compounds produced by or
derived from microorganisms that in dilute concentration effectively inhibit the growth of or
effectively kill other microorganisms (4). Today the words antibiotics or antimicrobials are often
used interchangeably for compounds used in the treatment of bacterial, protozoan or other
infections by pathogenic microorganisms. The active compound of penicillin was isolated and set in
production thanks to ground breaking work by Howard Florey and Ernst Boris Chain (5), for which
they alongside Sir Alexander Fleming received the Nobel Prize in 1945. Devastating diseases
previously untreatable, such as streptococcal and chlamydial infections suddenly became treatable
with the introduction of penicillin. The discovery of antibiotics sparked a new era in the treatment
of infectious diseases and paved the way for modern medicine, through the golden era of antibiotics
drug discovery from the 1940-1960´s.
During these decades, there was a huge expansion in the arsenal against bacterial
infections through the continued discovery of new compounds. Gerhard Domagk and Alexander
Fleming`s work was followed by many pioneering scientists. Especially, the work of Selman
Waksman, whom paved the way for new methodologies in antibiotic discovery (6) and whom was
originally accredited for the discovery of streptomycin, the first treatment for one of human
history`s greatest pathogens, Tuberculosis. This discovery earned him the name “Father of
10
Antibiotics” and the Nobel Prize, although his PhD student Albert Schatz predominantly was the
discoverer (7).
During this relatively short period in history most of today’s known classes of
antibiotics were discovered (Figure 1. Top). With antibiotics covering some of history`s most
important human pathogens (Tuberculosis, Cholera, Malaria etc.) and it has been said that in 1969,
the then US Surgeon General William Stewart told the US Congress “that it was time to close the
books on infectious diseases" (8). Although, Stewart most likely never said such a thing, it clearly
illustrates the general assumption at the time, that infectious diseases would pose a problem no
more. Without the work of these groundbreaking microbiologists and their coworkers, modern
medicine could not have developed to the point of today. Antibiotic treatment is the foundation for
surgeries, cancer treatments and treatment of chronic diseases like diabetes and cystic fibrosis.
Without efficacious antimicrobials clinical medicine as we know it could be jeopardized.
Figure 1. Drug Development and Resistance: Adapted from (9)
Top: Introduction of major classes of antibiotics. Bottom: First time resistance to the class of antibiotic was
observed in the clinical setting. Observation of resistance is not equal to loss of clinical efficacy against all clinical
isolates. Not all classes or antibiotics are included.
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Spectrum of activity
Antibiotics have historically been grouped in two groups based on their spectrum of
activity. Broad spectrum antibiotics cover bacterial species of both Gram-positive and Gramnegative origin making them useful in treatment where the causative pathogen is unknown.
Whereas, narrow spectrum antibiotics like vancomycin used against Gram-positive bacteria are
used when the causative agent is known and therefore treatment will have less impact on the normal
flora of the patient. Narrow spectrum antibiotics can minimize unwanted side effects on the
bacterial microflora of the patient as the causative agent is known (10-12).
The spectrum of activity is highly dependent upon the structural difference of the
bacterial membrane between Gram-negative and Gram-positive bacteria (Figure 2). Although most
antimicrobials cross the bacterial membrane via passive transport through porin`s or other
transporters, the Gram-negative bacteria are generally considered more difficult to kill by
antimicrobials due to their outer membrane (13). The bacterial cell membrane is a bilayer composed
of phospholipids such as Phosphatidylglycerol, Cardiolipin (Diphosphatidylglycerol), and/or
Phosphatidylethanolamine. Gram-negative bacteria have both an inner and an outer membrane; in
the periplasmic space a thin layer of peptidoglycan (cell wall) is connected to the outer membrane
via lipoproteins (murein lipoprotein). The outer membrane of the Gram-negative bacteria is on the
inward facing side composed of phospholipids similar to the inner membrane, whereas the outward
facing side contains lipopolysaccharide (LPS). The Gram-positive bacteria on the other hand do not
contain an outer membrane. However, they do have a thick cell wall (peptidoglycan), through
which lippotechoic acids and wall techoic acids traverse. Both Gram-negative and Gram-positive
bacteria may include an S-layer (capsule) consisting of protein or glycoproteins that acts as an
additional protective layer (14). Bacterial membranes also incorporate various efflux systems for
the transport of substance such as toxic compounds and waste products, these are discussed briefly
later (15).
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Figure 2. Generalized representation of Gram-negative and Gram-positive membranes: Adapted from (13, 14)
The Gram-negative bacterial membrane is composed of an Outer membrane covered with lipopolysaccharide
(LPS) and with large porin crossing the outer membrane. Below the outer membrane is the periplasmic space on
top of a thin layer of peptidoglycan, under which is found the inner cell membrane. The Gram-positive
membrane is made up of a thick multiple layer peptidoglycans, with wall techoic acids and lippotechoic acids.
Gram-positive bacteria contain a single underlying cell membrane. See text for detailed description.
Further, antibiotics can be either bactericidal i.e. exert their effect by killing the
bacterium or they can be bacteriostatic i.e. exert their effect by inhibiting growth of the bacteria
thereby allowing for the immune system of the host to clear the infection. These definitions are not
unambiguous and mainly apply in vitro and on organismal level, whereas the definitions become
more arbitrary in clinical setting (16). Some compounds act bactericidal against some pathogens,
while being bacteriostatic against others; exemplified by the antibiotic chloramphenicol that is
bacteriostatic against S. aureus, but bactericidal against S. pneumoniae (17).
13
Antibiotic targets
Interestingly, most of the known antibiotics inhibit relatively few pathways in the
bacterial cell; I) Folic acid synthesis, II) transcription, III) DNA replication, IV) protein synthesis
inhibitors and V) cell wall synthesis inhibitors (Figure 3). Most of these compounds were
discovered by cultivation and purification from the natural producers, or they are chemical
derivatives of such compounds (18-20). Historically new compounds have been based on the
structure of previously developed antibiotics and so, has the targets remained the same for many
new antibiotics, but with slight modification to the molecules and their affinity for the target (19,
20). An example of such development, are the generally considered broad spectrum β-lactam
antibiotics the Cephalosporin’s; divided into 1st, 2nd, 3rd, 4th and 5th generation cephalosporin’s
depending on their spectrum of activity and structural changes to the compounds (20, 21).
The sulfa drugs are inhibitors of the essential folic acid synthesis pathway in bacteria
and can be exemplified by the combination therapy of sulfamethoxazole-trimethoprim. In the folate
synthesis pathway; the dihydropteroate synthetase (DHPS) enzyme synthesizes Dihydropteroic
acid, from Para-aminobenzoic Acid (PABA) and Pteridine. Dihydropteroic acid is in turn is used to
synthesize Dihydrofolic acid by Dihydrofolate Synthetase. Finally dihydrofolate reductase (DHFR)
synthesizes Tetrahydrofolic Acid from Dihydrofolic acid. Sulfamethoxazole inhibit the DHPS
enzyme, whereas trimethoprim inhibits the DHFR enzyme (22). The Rifamycins (e.g. Rifampicin)
inhibits transcription by binding to the DNA-dependent RNA polymerase holoenzyme before the
unwinding of the DNA (closed complex) and keep it in the closed state. If the RNA polymerase has
already opened the DNA for transcription (open complex) the newly transcribed RNA blocks the
rifampicin binding site and therefore transcription continues (14). The quinolones and
fluoroquinolones (e.g. Ciprofloxacin) inhibits the DNA topoisomerase II (E. coli DNA gyrase) and
topoisomerase IV. The function of these enzymes is to introduce either negative or positive
supercoils in the DNA respectively. This is mediated through introduction of double strand breaks
which are re-ligated after introduction of the supercoil. Binding of the fluoroquinolone to the DNA
Gyrase blocks re-ligation of the DNA (23). Protein synthesis inhibitors target either the 30S
(aminoglycosides and tetracycline’s) or the 50S subunit (macrolides, chloramphenicol’s and
clindamycin) of the 70S initiator complex necessary for protein synthesis. With most of the protein
synthesis inhibiting antibiotics acting on the elongation of the polypeptide synthesis (18). The cell
14
wall inhibitors can be exemplified by the historically important β-lactam antibiotics (Penicillin’s,
cephalosporin’s, carbapenem’s and monobactam’s) targeting the conserved penicillin binding
proteins (PBPs). PBP are involved in cross linking of peptidoglycan precursor Lipid II in
peptidoglycan synthesis (24). Other inhibitors of cell wall synthesis include the glycopeptide
antibiotic vancomycin (discussed later) which inhibit peptidoglycan synthesis through a different
mechanisms than β-lactams.
Figure 3. Antibiotic targets:
An overview of the major cellular targets of most antibiotics targeting either Gram-negative or Gram-positive
bacteria. Sulphonamides and Trimethoprim inhibit folic acid synthesis (22). Rifamycins (Rifampicin) inhibit
DNA-dependent RNA polymerase (25). Quinolones and fluoroquinolones inhibit the DNA gyrase and
topoisomerase IV (23). Protein synthesis inhibitors include Aminoglycosides, tetracycline’s, macrolides,
chloramphenicol’s and clindamycin, which interact with ribosomal subunits 30S and 50S (18). The β-lactams
(Penicillin’s, cephalosporin’s, carbapenem`s and monobactam`s) and glycopeptide`s inhibit cell wall synthesis
(26). Not all antibiotic drug classes are represented here.
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Antibiotic resistance
History has shown that after the introduction of new compounds, so follows the
development and dissemination of resistance (Figure 1. bottom). We are today faced with the dire
consequences of untreatable human pathogens that are capable of surviving treatment with all
known antibiotics. This can in part be attributed to decades of uncontrolled antibiotic consumption,
both from the agricultural and human setting (9, 27), but also to the mere fact that evolution and
selection is an intrinsic part of this process. Resistance evolves as a natural selective advantage,
where an organism capable of overcoming an antibiotic perturbation will flourish while other
individuals succumb to the perturbation (28). In the case of antibiotics, these compounds will
inherently drive selection of resistant microorganisms if the genetic background is present in the
population. Once a resistant pathogen has gained foothold, it can spread throughout the population,
and if this resistance profile poses no detrimental side effects, then over time such genotypes will
become continually more prevalent (28).
Genetics of resistance
Most bacteria like Escherichia coli and Staphylococcus aureus contain a single
circular chromosome (29, 30). Exceptions to this do exist, as Vibrio cholera has two chromosomes
(31) and Burkholderia cepacia has three (32). Bacteria are an intricate part of the human biology as
normal commensals of our intestinal and skin flora (12). While most bacteria are important to our
normal health, some have developed as pathogenic species or are opportunistic pathogens and
therefore the target of antibiotic treatment (33, 34). Bacteria generally have short generation times
and unprecedented abundance in nature. Therefore, the evolutionary adaptability of these organisms
is truly remarkable, which is also why, resistance development is a continuing problem.
As for all organisms, the genetic makeup is highly important in the evolutionary
process, and changes to the DNA will accommodate fitness advantages, fitness loss or be neutral
(28). Changes to the genetic makeup, may in turn change the amino acid composition of the protein
targets of antibiotics, such that the interaction of the antibiotic with its target is compromised.
Therefore, modifications to the DNA are highly important to the evolutionary processes. These are
16
driven through minor or major modifications of the genetic makeup. Point mutations, insertions or
deletions of single or multiple bases in the DNA are usually considered as minor and of less
importance to resistance development and dissemination. While, major rearrangements of the DNA
by gene duplication/deletion homologous or non-homologous recombination or inversions of
chromosomal sections have much more pronounced effect on resistance development and
dissemination (35, 36). What truly set bacteria apart from higher organisms is their unprecedented
ability to acquire new genetic material either as addition to their genomes or in the form of extrachromosomal genetic material such as plasmids via horizontal gene transfer [Figure 4 (35, 37)].
Acquisition of new genetic material through horizontal gene transfer is accommodated by uptake of
free DNA from the environment (Transformation; through natural competence), phage transduction
or conjugation (transfer of DNA or plasmids between bacteria), not discussed in detail here [Figure
4 (37)]. Of special importance to these processes is that the acquired material can be integrated on
the chromosome or plasmids via integrons or transposons (35). Acquired genes can then be passed
to daughter cells by vertical gene transfer or passed on to other species via horizontal gene transfer
(Fig 3) (37).
17
Figure 4. Vertical and horizontal gene transfer: Adapted from (37)
Horizontal gene transfer through phage transduction, natural competence (uptake of DNA from environment)
or conjugation (here exemplified by plasmid transfer from one species to another). Genetic material can be
insertion into DNA/Plasmids via integrons or transposons (tn) as exemplified here. Genes and mutations are
passed to the next generation through vertical gene transfer or are passed on via horizontal gene transfer.
Mechanism of resistance
The genetic basis of resistance has to translate into bacteria survival by counteracting
the effect of the antibiotic. This can be accommodated in several ways or by combinations of these
in which changes to the genetic material or acquisition of new genetic material, results in either: i)
modification to the antibiotic target, ii) Limiting access to the antibiotic target and/or iii)
modification of the antibiotic. A generalized overview of these mechanisms can be seen in Figure.
5. Below, some examples of these mechanisms are given, they should be considered as examples
and not a comprehensive review, as resistance to many antibiotics is often accommodated through a
combination of these mechanisms.
18
Figure 5. Resistance mechanisms:
Modification of the target; changes the affinity of the antibiotic for the target, this can also be mediated through
production of multiple variants of the target (not shown). Limiting access to the target; mediated through efflux
of the antibiotic or lowered permeability of the cell. Modification of the antibiotic; by enzymatic activity the
antibiotic can be degraded or modified to an inactive form. The genetic background for these mechanisms can
be chromosomally or plasmid encoded. See text below for specific examples.
Modificationofthetarget
Resistance to several important antibiotics is accommodated through changes to the
target of the antibiotic, thereby changing the affinity of the antibiotic to the target. Rifampicin
resistance is acquired by mutations to the RNA polymerase beta-subunit (rpoB) gene in E. coli (38)
and Mycobacterium tuberculosis (25, 39). Fluoroquinolone (ex. Ciprofloxacin) resistance is
mediated through sequential acquisition of mutations in the gyrA, gyrB genes (DNA gyrase,
primarily target of fluoroquinolones in Gram-negative bacteria) and parC, parE genes
(topoisomerase IV genes, primarily target of fluoroquinolones in Gram-positive bacteria) depending
on the individual fluoroquinolone and bacterial strain (23). This mode of protection can also be
accommodated through carriage of alternative copies of the target protein, inducible when needed
and enabling the bacterium to survive. In methicillin-resistant Staphylococcus aureus (MRSA) the
mobile genetic element SCCmec (staphylococcal cassette chromosome mec) harboring the mecA
19
gene that encodes an alternative penicillin binding protein (PBP2a) induced by β-lactams and with
low affinity for β-lactam antibiotics (40, 41).
Limitingaccesstothetarget
Many antibiotics exert their effect by interaction with intracellular target (Figure 5).
Limiting access to the intracellular environment of the cell is an important determinant of antibiotic
resistance. In bacteria, efflux mechanisms are highly diverse and important resistance determinants
reviewed in detail elsewhere (15). Usually efflux is accommodated through molecule specific or
multidrug non-specific extrusion of antibiotics via passive or active transport across the membrane
(15). Resistance through efflux is highly problematic in antimicrobial and cancer treatment, but in
bacteria transporters are mainly of the passive type, in contrast to resistance to anticancer
compounds in mammalian cells (42). In bacteria transporters are highly diverse in nature and
divided into five major families; I) The major facilitator family (MF), II) The ATP-binding cassette
(ABC) family, III) the resistance-nodulating division (RND), IV) the drug/metabolite transporter
(DMT) family and V) the multidrug and toxic compound extrusion (MATE) family (15). Nonspecific multidrug-resistance determinants are usually chromosome encoded and most likely not
evolutionary intended for drug transport. Whereas efflux of antibiotics by drug specific transporters
and often found on plasmids (15). The plasmid carried tet genes of E. coli encode the membrane
associated Tet proteins (MF family), that are antiporter that extrude tetracycline in exchange of a H+
(43, 44). Likewise chloramphenicol resistance can be accommodated by carriage of the gene (cmlA)
encoding a protein transporter (MF family) that accommodates efflux of chloramphenicol (45). In
Salmonella enterica multidrug resistance to quinolones, chloramphenicol and tetracycline`s has
been shown to be mediated through overexpression of AcrAB-TolC (RND transporter) (46).
Importantly, resistance by limiting access of the antibiotic can also be mediated by
changing the permeability of the membrane. In the Gram-negative bacterium Pseudomonas
aeruginosa imipenem resistance is mediated via several mechanisms among which loss of the outer
membrane porin, OprD, is a major facilitator (47). Likewise, elevated tolerance to vancomycin in
the Gram-positive bacterium S. aureus can be mediated through thickening of the cell, as first
observed by Hiramatsu et al. (48).
20
Modificationoftheantibiotic
Resistance to antibiotic compounds by degradation or modification of the active
compound is of huge clinical importance. Chloramphenicol resistance can be mediated by carriage
of a constitutive active (E. coli) or inducible (S. aureus) chloramphenicol acetyltransferase cat gene
(49, 50). This encodes the CAT enzyme that is capable of transferring an acetyl group from AcetylCoenzyme A to chloramphenicol, blocking binding of chloramphenicol to the ribosomal subunit.
Likewise aminoglycoside resistance is mediated by aminoglycoside modifying enzymes such as
acetyltransferase (AAC), adenylyl transferases (ANT) or phosphotransferases (APH) that modify
aminoglycosides (51). Finally and with almost premonition of the future Sir Alexander Flemming
himself discovered the production of β-lactamase enzymes capable of hydrolyzing β-lactam
antibiotics such as penicillin (52).
Multidrug-resistance (MDR)
Resistance development in many human pathogens has been on an unprecedented
scale, as resistance has evolved into multidrug resistance. This has led to increased global morbidity
and mortality and we are today facing the possibility of an post antibiotic era (53). Especially
bacterial strains belonging to the ESKAPE group of pathogens (Enterococcus faecium,
Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter, Pseudomonas aeruginosa and
Enterobacter) are of importance to this pandemic (54). These pathogens encompassing both Gramnegative and Gram-positive bacteria often carry MDR determining genes residing on genetic
resistance island (RI) of complex evolutionary origin that are encoded on the chromosome or
plasmids (29, 55-57).
MDR Gram-positive bacteria:
The widespread MDR among Gram-positive bacteria can be exemplified by the
important opportunistic pathogen S. aureus. This bacterium is a normal commensal carried in 30%
of the human population (58). The bacterium causes a wide variety of infections such as soft tissue
21
and skin infections to life-threatening endocarditis (34). Prior to the introduction of penicillin, S.
aureus caused bacteremia killed 80% of patients (59). The discovery of penicillin led to its
widespread use against S. aureus, but by the mid-1940s penicillin resistance through plasmid borne
penicillinases was widespread (60). As alternative treatment, the semisynthetic penicillin
(methicillin), resistant to degradation, was marketed in 1959. By 1961 methicillin resistant S.
aureus (MRSA) had been described in England (61). The MRSA genotype is caused by carriage of
the SCCmec element of which 11 types have been described (59). The SCCmec elements all share
common features; i) they insert into the same site of the orfX gene on the chromosome of S. aureus,
ii) they contain a mecA gene (PBP2a) controlled by the regulatory genes mecI and mecR and the
cassette chromosome recombinase (ccr) which mediate excision and integration of the SCCmec
element, iii) excision and integration is mediated through recognition of the insertion site sequence
found within specific inverted and direct repeats, recognized by the ccr-encoded DNA recombinase
(59). The MRSA strains evolved from previously treatable background of methicillin sensitive S.
aureus (MSSA).
Several different lineages of MRSA have since evolved and are presently divided into
three major groups; healthcare-associated MRSA (HA-MRSA), community-associated MRSA (CAMRSA) and recently livestock-associated MRSA (LA-MRSA) (62, 63). While they all carry the
SCCmec cassette rendering them resistant to virtually all β-lactam antibiotics, they differ in their
ability to cause infection. HA-MRSA and LA-MRSA have both been shown to cause infection in
hospitalized patients as nosocomial infections (63, 64), although LA-MRSA is considered less
virulent in humans (62). This is in contrast to the recently emerged strains of CA-MRSA such as
USA300, capable of causing infections in otherwise healthy adults (65, 66). The differences among
MRSA lineages are mainly associated with differences in virulence between the isolates from the
different lineages. Virulence of MSSA and MRSA are dependent on multifactorial mechanism such
as; toxin production, adhesive properties of the cell and immune evasion to name a few (63). MRSA
strains are problematic because they apart from their SCCmec genotype often carry resistance
determinants to other important antibiotics for treatment of S. aureus infections. Co-carriage of
resistance to aminoglycosides by enzymatic degradation or alteration of the antibiotic has been
found in up to 70% of MRSA isolated in Europe (57). For these reasons treatment of MRSA usually
include treatment with glycopeptide antibiotics (vancomycin) and oxazolidinones such as linezolid.
22
Vancomycin resistance has been reported either as intermittent-vancomycin resistant
S. aureus (VISA) (48) or as vancomycin resistant S. aureus (VRSA) (67). Furthermore, vancomycin
resistance through horizontal gene transfer of the vanA gene cluster has been reported and this
originates from another important Gram-positive pathogen vancomycin-resistant Enterococcus
faecalis (VRE) (68-70). The vanA gene cluster encodes a ligase responsible for synthesis of an
alternative pentapeptide on the peptidoglycan precursor Lipid-II, in which the dipeptide (D-Ala-DAla) is substituted for D-Ala-D-Lac (Figure 6) thereby changing affinity for vancomycin (71).
Induction of the vanA gene cluster is controlled by the VanS-VanR two-component system in
response to extracellular glycopeptide, which was first described in E. faecium (72). Ekstracellular
vancomycin is sensed by VanS (sensor kinase) when vancomycin is bound to D-Ala-D-Ala, VanS
phosphorylates the response regulator (VanR), which in turn regulate expression of the vanHAX
genes responsible for the D-Ala-D-Lac dipeptide substitution (72, 73).
Linezolid is being used increasingly as treatment for MRSA but also in the treatment
of VRE (74) and has been considered unlikely of resistance development. This is due to the
synthetic nature of the molecule whereby enzymatic degradation by preexisting enzymes in nature
would be unlikely (75). Furthermore, linezolid targets and binds to 23S rRNA of the 50S ribosomal
subunit encoded in the ribosomal DNA (rDNA) genes, which are present in multiple copies. This
has been expected to slow resistance through mutation (74). Linezolid resistance is rare (76),
however it has been reported as mutations in multiple 23S rRNA genes. No cross resistance through
mutations has been found to other protein synthesis inhibitors (77). Further linezolid resistance has
been reported through carriage of a Cfr rRNA methyltransferase that modifies the 23S rRNA at
base position A2503 by addition of a methyl group (78, 79).
23
Figure 6. Peptidoglycan synthesis inhibition in S. aureus: Adapted from (80)
Peptidoglycan precursor Lipid II is synthesized in the cytosol of S. aureus. Here depicted after initial synthesis of
UDP-MurNac-pentapeptide. MraY (phospho-MurNac-pentapeptide translocase) facilitates the transfer of the
UDP-MurNac-pentapeptide to the undecaprenyl phosphate (Lipid carrier), resulting in Lipid I formation. MurG
(glycosyltransferase) forms the glycosylic linkage between the MurNac (N-acetylmuramic-acid) and GlcNac (Nacetyl-D-glycosamine) creating Lipid II. Lipid II in transported to the outside of the membrane, where PBP
(penicillin binding protein) facilitates crosslinking of the Lipid II subunits into polymeric peptidoglycan. PBP
can be blocked by Penicillin, but carriage of the mecA gene from the SCCmec element, will facilitate crosslinking
in presence of penicillin, due to the lowered affinity of PBP2a to penicillin. Vancomycin, can bind to the D-ala-Dala dipeptide, thereby inhibiting peptidoglycan synthesis by PBP2a. Carriage of the vanA gene cluster facilitates
the synthesis of alternative dipeptide D-ala-D-lac with lowered affinity for vancomycin, resulting in vancomycin
resistance
24
The current last resort antibiotic in use for treatment of serious VISA, VRSA, VRE
and vancomycin resistant Enterococcus faecium, is the lipopeptide antibiotic daptomycin.
Daptomycin interacts with the bacterial membrane in a Ca2+ and phosphatidylglycerol (PG)
dependent manner through electrostatic interactions (81, 82). This causes membrane instability and
mislocalization of cell division proteins (83). As for vancomycin and linezolid, resistance to
daptomycin has been reported, either in VISA strains with overlapping cross resistance to
vancomycin through cell wall thickening (84) or through changes to genes such as the mprF gene
encoding the MprF protein (lysylphosphatidylglycerol synthetase). Dysfunctional regulation of this
gene accommodates synthesis of lysylphosphatidylglycerol (L-PG) instead of the normal PG,
thereby changing the overall net charge of the bacterial membrane [(85) Figure 7].
Figure 7. Lysylphosphatidylglycerol (L-PG) synthesis: Adapted from (86)
The staphylococcal cell wall with peptidoglycan (Orange) and underlying negatively charged
phosphatidylglycerol (PG) containing membrane (Black). Dysfunctional expression of the MprF protein
facilitates synthesis of Lysylphosphatidylglycerol (L-PG). L-Lysine is believed to be derived from Lysyl-tRNA.
L-PG renders the bacterium resistant to Daptomycin and other electrostatic interacting antimicrobials such as
host innate immune defence peptides like Defensins.
25
Because of the continuous development and dissemination of resistant isolates, it is of
importance to develop new strategies for combating important Gram-positive pathogens. And while
restriction of antibiotic consumption in the UK has been shown to reduce infection rates with
bacterial infections such as MRSA (87), there is a continued need to develop new or improved
antibiotics for Gram-positive infections. The newest antibiotic for serious Gram-positive infections
is telavancin, but like so many drugs before, this is a derivative of the previously developed
antibiotic vancomycin (88).
26
MDR Gram-negative bacteria:
The Gram-negative bacterial pathogens are by far the most important and costly in our
society today, as the vast majority of nosocomial infections are caused by MDR Gram-negative
infections (89). The highly problematic strains carry Extended Spectrum β-Lactamase (ESBL) and
carbapenemase genes. These encode β-Lactamase enzymes with capacity to hydrolyze several
generation of the β-Lactam antibiotics such as penicillin’s, cephalosporin`s and the last the resort βlactams the carbapenem`s [(90-92) Figure 8]. Important bacterial strains encompass the
enterobacteria such as E. coli sequence type ST131 carrying the CTX-M-15 (ESBL) gene (93) and
K. pneumoniae carbapenemase (KPC) ST258 strain (91, 94). Although several inhibitors of ESBL
enzymes have been developed, such as tazobactam and clavulanic acid (95), resistance to such
inhibitors has been described in E coli. (96) and KPC (97).
Figure 8. Structure of Important β-Lactam antibiotics: Adapted from (98)
The figure shows 1. The structure of the D-ala-D-Ala dipeptide on the Lipid II peptidoglycan precursor that penicillin
binding protein (PBP) recognizes for the transpeptidation reaction. 2. Overall structure of penicillin 3. Overlay of the
penicillin structure with the D-Ala-D-Ala structure. With penicillin recognized as substrate, the PBP gets trapped in its
acetylated form and is rendered incapable of performing the transpeptidation step (99). 4. Cephalosporin overall
structure. 5. Meropenem structure (carbapenem drug). 6. Tazobactam structure; an inhibitor of several β-Lactamase
enzymes (not discussed in detail). R, R1, R2 and X designate the positions where penicillin’s and cephalosporin’s have
been modulated for development of new generations of antibiotics.
27
Other highly important MDR Gram-negative bacteria include P. aeruginosa and
Acinetobacter baumannii (21, 100). A. Baumannii is a relatively new problem in the hospital
settings, but is becoming a growing problem in immunocompromised patients (101). It is the
causative agents of a wide variety of infections such as skin and soft tissue infections, urinary tract
infections and life threatening pneumonias (102). Because A. baumannii is a less frequent cause of
serious infection compared to MDR E. coli, K. pneumoniae and P. aeruginosa, it is often
misdiagnosed and the success of initial antimicrobial therapy against A. baumannii is compromised
(103). The recent development of A. baumannii as an important nosocomial infection is largely
attributable to its ability to acquire resistance determining genes and the fact that it is well adapted
to survive in the environment (100). The ability of A. baumannii to acquire resistance genes can be
exemplified by the AYE strain described by Fournier et al. (104). This strain contains an 86kilobase resistance island that includes resistance to many β-lactams, fluoroquinolones,
tetracycline’s, aminoglycosides and more. A major part of the genes were acquired via horizontal
gene transfer (104). Such resistance islands have been associated with widespread MDR resistance
is other Gram-negative pathogens like K. pneumoniae and especially the dissemination of ESBL
and carbapenemase genes (55).
Carbapenemase resistance has led to the re-introduction of the peptide antibiotics,
colistin (polymyxin E) and polymyxin B. Discovered in 1949 (polymyxin E), but used very limited
due to their unattractive toxicity profile (105). These antimicrobial peptides are now used
exclusively as last resort antibiotics against MDR Gram-negative infections that are resistant to all
other antibiotics (105). As they were developed and approved prior to the introduction of modern
standards for clinical approval by the United States Food and Drug Administration (FDA) and
European Medicines Agency (EMA), they have not undergone the same vigorous clinical testing as
newer compounds. Therefore less is known about optimal dosing, pharmacokinetics and
pharmacodynamics (106). Polymyxins are cationic amphipathic circular peptides and kill bacteria
through disruption of the bacterial membrane (Figure 9). Specifically polymyxins disrupt membrane
integrity via electrostatic interaction with the anionic charged LPS layer of the outer membrane,
while displacing Mg+ and Ca2+, leading to cell leakage and cell lysis (107).
28
Figure 9. Polymyxin Mechanism of action: Adapted from (107)
The binding of colistin to the anionic charged LPS layer of gram-negative bacteria causes displacement of
cations. Disrupting membrane stability, leads to influx of more colistin molecules and disruption of the inner
bacterial membrane.
Historically it has been considered unlikely that colistin resistance would develop.
However, genomic resistance to colistin has been reported in A. baumannii and K. pneumoniae as
changes to the LPS layer (108-111). In A. Baumannii, colistin resistance is acquired through
complete loss of LPS (109) or by changes in the two-component PmrA-PmrB system (polymyxin
resistance A and B). The PmrA-PmrB two-component system is a major regulator of LPS
modifying gene products. PmrA-PmrB is normally induced by external signals such as low pH,
high Fe3+ or high Al3+. When induced the sensor kinase PmrB auto-phosphorylates and transfers the
phosphoryl group to the response regulator PmrA. Phosphorylated PmrA regulates LPS modifying
genes through DNA binding (112). Colistin resistance through mutations in PmrA-PmrB is
mediated via point mutations in pmrB (113), constitutive activation of PmrA (114) or upregulation
of pmrAB (113). These changes can lead to addition of phosphoethanolamine to the Lipid A through
expression of the pmrC gene (112, 115). In K. pneumoniae, resistance can also be mediated through
changes in the PhoP-PhoQ (nonspecific acid phosphatase) two-component system (110), involved
29
in sensing of Mg2+ and Ca2+, and which can cross talk through the PmrA-PmrB two component
system (116). Further, PhoP-PhoQ has been shown to regulate the Pagp gene responsible for
modification to Lipid A thereby changing the overall negative charge of the membrane (117). Lipid
A, being the inner most part of LPS anchoring it to the bacterial outer membrane.
However, of the outmost importance is the new discovery of plasmid mediated
colistin resistance in E. coli, encoded in the mcr-1 gene, which result in the addition of
phosphoethanolamine to the Lipid A rendering the bacterium colistin resistant (118). This
mechanism is essentially the same as in A. Baumannii PmrA-PmrB mutants (113). The discovery of
colistin resistance via horizontal gene transfer seriously underscores the foreseeable future of a post
antibiotic era. Transfer of the mcr-1 gene to already MDR carbapenemase carrying Gram-negative
pathogens could render these strains untreatable. As described, horizontal gene transfer has already
been ascribed to the rapid emergence and spread of the global MDR pandemic (35) and will
undoubtedly increase the prevalence of colistin resistance. Therefore, the continued development of
new or improved antimicrobials is of the outmost importance, especially against Gram-negative
bacteria of the ESKAPE group (106).
Peptide antibiotics: a part of the solution
The first antimicrobial peptide (AMP) to be described in detail was Gramicidin.
Discovered around the same time as penicillin (1939), by a French microbiologist René Dubos
while working with the peptide producer Bacillus brevis (119). Gramicidin was the first
commercially produced true antibiotic and proved especially efficient at killing gram-positive
bacteria. However, Gramicidin had limited applications because of its hemolytic ability and
therefore it was only applicable as topical treatment. Another such important AMP used is
bacitracin (120), like colistin it is a non-ribosomal synthesized naturally produced mixture of
antimicrobial peptides, but unlike colistin has broad spectrum activity. AMPs have been isolates
from single celled to multicellular organisms (121) and are usually composed of 10-100 amino
acids (122). They are highly diverse in structure and activity and because of their widespread
distribution in nature they have been proposed as new sources of antibiotics (122, 123).
30
Bacteriocins
Bacteriocins are a highly diverse group of AMP from bacteria. They are ribosomal
synthesized AMPs and serve as a means of inhibiting/killing closely related bacteria, while the
producer itself is immune (124). Because bacteriocins are produced intracellularly, they are usually
synthesized in an inactive pre-peptide form, which is transported through the membrane via ABCtransporters. This inactive pre-peptide incorporates a leader sequence which is cleaved off either
intracellularly, during or after export, rendering the peptide active (125, 126). The producer strain is
immune to its own bacteriocins, via co-expression of immunity proteins (124, 127). Bacteriocins
have been divided into many different classes depending on their structure, mode of action and
spectrum of activity, but recently it was suggested to change this system to contain only 3 classes;
Class I (Lanthionine-containing bacteriocins/lantibiotics), Class II (Non-lanthionine-containing
bacteriocins and Class III, the bacteriolysins (not discussed here) (125). Bacteriocins target a variety
of cellular processes, but generally speaking the bacteriocins targeting Gram-positive bacteria act
on the bacterial membrane. These can be exemplified by the lantibiotic nisin (128) (described in the
next section) and Lactococcocin A (129, 130) (Figure 10). Whereas many Gram-negative targeting
bacteriocins target intracellular processes such as DNA replication, transcription or protein
metabolism (131). Microcin B17 (MccB17) inhibits DNA gyrase (topoisomerase II) (132), microcin
J25 (MccJ25) inhibit the RNA polymerase (133) and microcin MccC7-51 inhibit protein synthesis
(Figure 9).
31
Figure 10. Bacteriocins mechanism of action: An overview. From (131)
The Bacteriocins Nisin and Lactococcocin both act on Gram-Positive bacteria, by pore formation. Nisin also inhibit
peptidoglycan synthesis. Nisin in known for its interaction with Lipid II (128), whereas Lactococcocin binds to units of
the mannose-phosphotransferase system (Man-PTS)(134). Microcins (MccB17, MccJ17 and MccC7-51) target DNA
gyrase, RNA polymerase and protein synthesis respectively (131). MccB17 cross the outer membrane through the porin
OmpF and are actively taken up by the inner membrane protein SbmA (135). MccJ25 binds to outer membrane receptor
FhuA (Ferrichrome receptor) and cross the inner membrane through SbmA or TonB (135). MccC7-51 like MccB17
crosses the outer membrane through OmpF porin, but utilizes a YejBEF-transporter to cross the inner membrane (136)
32
Lipid II targeting antimicrobial peptides
The Lipid II precursor of peptidoglycan synthesis is not a new target of antibiotics, as
already discussed antibiotics such as vancomycin and telavancin also utilizes this cell wall target.
However, the class of peptide antimicrobials known as lantibiotics has gained renewed interest
because of the widespread multidrug-resistance among Gram-positive bacteria (137, 138).
Lantibiotics are named so, for containing uncommon amino acids such as lanthionine
and methyllanthionine introduced via posttranslational modified ring-structures of the precursor
peptide (139, 140) (Figure 11). Lantibiotic are produced from gene clusters encoded on the
chromosome, on conjugative elements or plasmids (138). The overall structure is composed of
several genes involved in their synthesis, modification, export and immunity (designated as lan for
Lantibiotic). The lanA gene encodes the inactive pre-peptide form and modifying enzymes are
encoded in the lanBC, lanM or others. An ABC-transporters gene (LanT) encodes the transporter
and immunity is encoded in the lanI and lanH genes (141). The inactive pre-peptide incorporates a
leader sequence which is either cleaved off intracellularly by proteases encoded in the lanP gene (if
present) or other cellular proteases not encoded in the lan gene cluster (141). Several lantibiotics
have activity against important Gram-positive pathogens and especially the activity against MRSA
and VRE have sparked renewed interest in lantibiotics (137). Nisin is one of the best described
lantibiotics to date. It was discovered in 1928 from its natural producer Lactococcus lactis, but was
not isolated before the 1940s (142, 143). Nisin has never been applied to clinical settings, but it has
been used extensively as an additive by the food production industry (144). The mode of action of
nisin has been described as multimodal; by inhibition of peptidoglycan synthesis and pore
formation via binding to Lipid II (128, 145) in which aggregation of Lipid II in the membrane
seems to play an important role (146-149). Nisin initially bind through electrostatic interactions, but
this is considered of less importance to antimicrobial activity compared to Lipid II binding (145).
Several other lantibiotics have been discovered; such as mutacin 1140 (150),
planosporicin and microbisporicin also known as NAI-107 (151, 152), gallidermin, mersacidin and
many more (137, 139). Mutacin and mersacidin inhibit peptidoglycan synthesis, but do not form
pores like Nisin, however they do binds to Lipid II like most lantibiotics (149, 153, 154). NAI-107
also binds to Lipid II, with no apparent pore formation; rather it seems to disrupt membrane
33
function through interruption of protein localization thereby disorganizing the membrane (155).
These lantibiotics are just a few examples of antimicrobials from this group with growing interest
for clinical development (137, 156). The consensus between lantibiotics ability to kill by
multimodal mechanisms via Lipid II binding, their general low toxicity and that resistance
development has been slow, has been used to argue for their development as novel clinical therapies
(125, 157). Furthermore other antimicrobial peptides have been found to target Lipid II, such as the
defensin plectasin (80) and the recently discovered bacteriocin teixobactin. Teixobactin also target
the Lipid III precursor of wall techoic acid synthesis and has pronounced effect against VRSA and
VRE emphasizes the non-protein Lipid II and Lipid III precursors as a good target of novel
therapeutics (158).
Figure 11. Lantibiotics: From (155)
The Nisin-like lipid II binding motif is highlighted in green and lipid II binding motifs similar to that found in
mersacidin are marked red.
34
Host defense peptides
Innate immunity peptides of multicellular organisms or “host defense peptides” are
widespread in nature as part of almost all living organisms immune defense (121, 122, 159). Innate
immunity peptides capable of killing bacteria, such as the Cecropins from the moth Hyalophora
cecropia (160, 161), LL-37 part of the Human innate immunity (162) and defensins of invertebrate
and mammalian origin have become of interest in development of novel therapeutics (163, 164).
Currently more than 2000 antimicrobial peptides of eukaryotic origin have been reported (121,
165). These peptides, although similar in their antimicrobial activity, are highly diverse in sequence
and structure (122). Major structural classes include; α-helical peptides, β-sheet peptides, extended
peptides (enriched for certain amino acids) and looped peptides (122, 166) (Figure 12).
Figure 12. Structures of host defence peptides. Adapted from (122, 166)
A. Bovine Indolicidine (extended structure) (167). B. Bovine Lactoferricin B (β-sheet structure (168)). C. Human βdefensin-1 (mixed structure; both α-helix and β-sheet (169)). D. Drosophila melanogaster, Drosomycin (mixed
structure (170)). E. Amphibian magainin (α-helix structure (171)). F. Insect Thanatin (Loop structure (172). Structures
are from the Antimicrobial peptide database (http://aps.unmc.edu/AP/main.php) (121). Peptide database numbers; A.
1G89, B. 1LFC, C. 1IJV, D. 1MYN, E. 2MAG and F. 8TFV (121).
35
Innate immunity AMPs like many bacteriocins are often cationic and amphiphilic and
interacts with membranes through electrostatic interactions; creating pores that disrupt membrane
integrity (122). Several models of pore formation and membrane disruption have been proposed.
These can generally be divided into three models; i) the barrel-stave model ii) the carpet model and
iii) the toroidal model [(166, 173) Figure 13]. Furthermore, antimicrobial peptides of both
prokaryotic and eukaryotic origin and with novel mechanistic actions other than direct bacterial
killing have been reported; such as immunomodulatory peptides (174-178), anti-virulence peptides
(179, 180) and many more (121).
Figure 13. Overview of the pore formation models: Adapted from (173)
In the barrel-stave model: the peptide (hydrophilic in red and hydrophobic in blue) attach to and aggregate in the
membrane and insert into the membrane. With the hydrophobic part aligned with the lipid core region and the
hydrophilic region pointing to the centre. The carpet model: The peptides create a carpet structure by orientation in
parallel to the lipid bilayer, with the hydrophobic regions binding to the lipid surface, leading to disrupting of the
membrane. The toroidal model: the peptides aggregate and cause the membrane to bend so the membrane is disrupted
and the pore centre is lined with the peptide and head groups of the lipid bilayer.
36
Because microorganisms have co-evolved as an intricate part of the intestinal and skin
microflora of multicellular organisms (12) and some of these organisms have evolved into
pathogenic or opportunistic pathogens, they have had to co-evolve defences against host defence
peptides (181, 182). Many of these mechanisms are equivalent to the mechanisms evolved for
coping with antibiotics. Membrane modifications and AMP repulsion; membrane modifications as
protection mechanisms against peptide antimicrobials have already been discussed for A. baumannii
(PmrA-PmrB), K. pneumoniae (PhoP-PhoQ) and as production of L-PG in S. aureus. Capsule (Slayer) production have also been shown to be important for K. pneumoniae protection against
AMPs such as lactoferrin and defensins (183). Similar to these mechanisms the dlt operon
(dltABCD genes) is responsible for D-alanine incorporation into techoic and lippotechoic acids of S.
aureus, thereby reducing the negative change of the membrane and providing protection against
AMPs such as nisin and gallidermin (184). Efflux of AMPs; In Clostridium difficile it has been
shown that the crpABC operon encoding an ABC transporter that provides resistance to gallidermin
and nisin (185) and in E. coli intrinsic resistance to the microcin J25 is provided through the global
regulatory protein Lrp (Leucine-responsive regulatory protein) which is a positive regulator of an
efflux pump YojI (ABC transporter) (186). Degradation of AMPs; The production of proteases
such as elastase from P. aeruginosa and E. faecalis or the protease aureolysin from S. aureus
provides protection from the broad spectrum human AMP LL-37 by enzymatic degradation (187,
188). Because of such mechanisms and many more, as reviewed elsewhere (181, 182, 189), AMPs
are not necessarily and readily applicable directly from the producer organisms.
Modified or synthetic: peptides and peptoids
The complexity and universally widespread distribution of peptides, of both bacterial
and mammalian origin underlines the potential of peptides for the development of novel
therapeutics. Because of the immense development of MDR resistance; research into development
and discovery of these compounds is both a necessity and an obvious course for development of
new antimicrobials. New technologies have provided ways of manipulating peptides to create
molecules of diverse structure and applicability (165, 190, 191). In this way several attempts has
been made to modify polymyxins to improve their efficacy while lowering toxicity (192).
37
Lantibiotics has also been proposed for manipulation (125). Further, hybrid molecules such as the
Cecropin-mellitin hybrids have been created (193) and peptides targeting novel pathways such as
DNA replication machinery of S. aureus (194).
Antimicrobial peptides can be chemically synthesized as linear molecules (195) or be
made cyclic either by chemical modification or by use of in vivo synthesis (196). Peptides can be
used as the basis for peptide mimetics such as peptoids [(197, 198) Figure 14]. Peptoids like
circularization of linear peptides has the advantage, that it renders the molecule less prone to
degradation by enzymatic digestion (197, 199). Similarly incorporation of
D-amino
acids,
glycosylation, or phosphorylation of peptides can be utilized to lower a peptides susceptibility to
protease degradation (200, 201). The possibilities of peptide synthesis seem unlimited as
technological development has provided methodologies for modifying these molecules.
Figure 14. Peptides and Peptoids; Adapted from Mojsoska et al. (197)
Chemical structure of peptides to the left and peptoid structure to the right.
Therefore, one major question remains; with the immense discovery of new molecules
and with the methodologies at hand to manipulate these into new and novel antimicrobial peptides,
why have so few antimicrobial peptides been approved for clinical therapy? The answer to this
question might just be (as described) low interest from the pharmaceutical industry. But of more
importance could be that many of the peptides that are brought into clinical development fail due to
toxicity problems. Or molecules are rushed into clinical development, where they fail before being
optimized properly and are eventually abandoned (202). The solution to this could be to have more
38
cost effective methodologies for discovering and testing of toxicity and efficacy in vivo, prior to
engaging in expensive and highly regulated mammalian in vivo experiments.
Alternative in vivo models
Clinical trials inevitably have to pass through mammalian efficacy and toxicity
models, before any antibiotic compound is approved for human trials. Mammalian infections
models are highly regulated by legislative laws. They are also expensive for development and this
poses a problem in large scale drug screening (19, 203). During the last decades, several alternative
methodologies has been developed for in vivo drug development and screening using nonmammalian models. High throughput screening of large drug libraries was classically carried out in
vitro to discover new compounds that effectively kill/inhibit the proliferation of bacteria (204).
Classical toxicity screens are usually performed in vitro and encompass hemolysis assays and cell
proliferation assays in which immortalized cell lines are used (197, 205). However, using this
approach there is a possibility of underestimating toxicity that would have been discovered in a
whole animal context. Moy et al (206) devised a Caenorhabditis elegans in vivo model that can be
utilized for screening of large drug libraries. This method found a variety of drugs/pro-drugs
capable of killing/inhibiting growth, virulence inhibitors and immune modulators while also
screening for toxicity (206). This model is powerful for large scale screening as it is inexpensive
and C. elegans is easy to grow and rear in the laboratory. However, in this model screening is
performed by ingestion of molecules and only molecules that are not degraded or toxic through the
digestive system will be discovered.
Insect models are becoming widely used for the analysis of host-pathogen
interactions. Among these models two stand out; the greater wax moth Galleria mellonella and the
fruit fly Drosophila melanogaster. These models have applicable potential for drug development
and screening of antimicrobials. The larvae of G. mellonella have been explored as a model for
pathogenicity, through oral or direct injection of bacterial pathogens (207, 208). This model has
several advantages; it is cheap to rear and easily handled in the laboratory, no ethical clearance is
39
needed, it has a short life cycle and it can be kept at temperatures from 15-37°C (207, 209). Evans
et al. demonstrated that G. mellonella can be utilized to study virulence of Streptococcus
pneumoniae, as the model discriminates between strains with known differences in virulence (210).
In line with this Peleg et al. reported on the use of G. mellonella as a model for analysing
pathogenicity of A. baumannii and testing of antibiotics (211, 212). Several other bacterial
pathogens such as P. aeruginosa (213) and E. coli (214) have undergone similar studies in G.
mellonella.
Drosophila has previously been proposed as a good model for the discovery of
antimicrobials and screening of toxicity (215, 216). It has been extensively applied by Ross Cagan
for the discovery and screening of combinatorial chemo therapy (217, 218), and by Willoughby et
al. (219) to screen for new chemotherapeutics.
Drosophila, has been used extensively for genetic screening to unravel important
aspects of cellular biology in a whole animal context (220). Its genetic tractability through the
development of advanced methodologies for genetic manipulation has propelled it as a highly
valuable model organism for elucidating important aspects of the genetic regulation of cellular
biology (221, 222). Like G. mellonella, Drosophila has a fast generation time of only 10 days, is
cheap to rear and has no ethical constraints, making it attractive as an initial model for efficacy and
toxicity testing in whole animals.
Since the Nobel Prize winning discovery of the Toll like receptor by Jules A. Hoffman
and coworkers (223), Drosophila has provided valuable information to the control of innate
immunity and its regulation (224, 225). Initially, Drosophila was described as being bi-partite in the
IMD (immune Deficient) and the TOLL pathway (226, 227) (Figure 15), however newer evidence
points towards a more complex interaction between the two pathways. The Toll pathway is the
major regulator of the immune defense towards Gram-positive bacteria and fungi in Drosophila
(226, 228-231), while the IMD pathway mainly functions as a regulator of the immune response
against Gram-negative bacteria (224, 227, 231, 232). The Drosophila innate immune system has
highly conserved homology with its mammalian counterparts; from the recognition of PAMP
(pathogen-associated molecular patterns) by the PGRP`s (peptidoglycan recognizing proteins) to the
nuclear localization and transcription of immunity associate genes, such as innate immunity
40
peptides cecropins and defensin, by Jun N-terminal kinase (JNK), Dorsal-related immunity factor
(DIF), DORSAL etc. [Figure 15 (230, 231, 233-238)]. However, major differences are present. In
mammals the activation of TOLL relies on direct binding of the receptor to the invading
microorganism, whereas Drosophila relies on the secreted PGRP`s to translate recognition through
TOLL into cellular signal transduction and activation of immunity genes (233, 234, 236, 237).
Further, the secreted mammalian PGRPs act in direct bactericidal fashion (235). The major nuclear
activators of transcription are however conserved, although the mammalian regulatory system is
much more complex (239).
Research within the field of insect innate immunity in Drosophila has sprouted the
development of several techniques for infecting Drosophila by ingestion or injection with bacteria
(240-246). It has been demonstrated that infection with the important pathogenic bacteria Vibrio
cholera in Drosophila in many aspects compare to infection in humans (247). Others have applied
Drosophila to gain insight into virulence of P. aeruginosa (246), virulence and treatment of S.
aureus (248-250) and many more bacterial species (243). However, virulence studies for
comparison of Drosophila infection with human infection remain controversial, since some studies
have shown that non-pathogenic Gram-positive bacteria kill Drosophila (243, 251).
41
Figure 15. Drosophila Immunity:
Left side: Toll pathway activation leading to transcription of antimicrobial peptide genes such as Drosomycin
and defensin. Gram-positive bacteria are detected via binding of PGRP-SA and PGRP-SD (Peptidoglycan
Recognizing Proteins) to Lysine-type peptidoglycan and east by B-Glucan binding to GNBP (Gram negative
binding protein). Virulence factors from yeast and Gram-positive bacteria, such as proteases, are detected via
Persephone. Detection of bacteria and/or their virulence factors confers signalling through the TOLL receptor
via binding of spätzle to the receptor. Full length spätzle is cleaved by Spe (spätzle-processing enzyme) which is
induces either directly by Persephone or through a serine protease cascade by PGRP. Right side: IMD pathway
induction through PRRP-Le (-LF/LB/LCx etc.) by binding to DAP-type peptidoglycan of Gram-negative
bacteria. This binding confers signalling through IMD (Immune deficiency), which through a complex signalling
cascade lead to induction of antimicrobial peptides and stress and wound responsive genes. For more detailed
description al the steps in the signalling cascade (231).
42
Paper I
An all-D amphipathic undecapeptide shows promising activity against colistin-resistant
strains of Acinetobacter baumannii and a dual mode of action
Alberto Oddo,a‡ Thomas T. Thomsen,b‡ Susanne Kjelstrup,b Ciara Gorey,a Henrik Franzyk,a Niels
Frimodt-Møller,c Anders Løbner-Olesen,b Paul R. Hansena
Antimicrob. Agents Chemother.AAC.01966-15; Accepted manuscript posted online 16 November
2015,
‡These authors contributed equally to this work.
Department of Drug Design and Pharmacology , University of Copenhagen,
Copenhagen, Denmarka; Dept. of Biology, Section for Functional Genomics and
Center for Bacterial Stress Response (BASP), University of Copenhagen,
Copenhagen, Denmarkb; Department of Clinical Microbiology, Rigshospitalet,
Copenhagen, Denmarkc
43
AAC Accepted Manuscript Posted Online 16 November 2015
Antimicrob. Agents Chemother. doi:10.1128/AAC.01966-15
Copyright © 2015, American Society for Microbiology. All Rights Reserved.
1
An all-D amphipathic undecapeptide shows promising activity against colistin-
2
resistant strains of Acinetobacter baumannii and a dual mode of action
3
4
5
6
Alberto Oddo,a#‡ Thomas T. Thomsen, b‡ Susanne Kjelstrup,b Ciara Gorey,a Henrik
7
Franzyk,a Niels Frimodt-Møller,c Anders Løbner-Olesen,b# Paul R. Hansena#
8
9
Department of Drug Design and Pharmacology , University of Copenhagen,
10
Copenhagen, Denmarka; Dept. of Biology, Section for Functional Genomics and
11
Center for Bacterial Stress Response (BASP), University of Copenhagen,
12
Copenhagen, Denmarkb; Department of Clinical Microbiology, Rigshospitalet,
13
Copenhagen, Denmarkc
14
15
16
17
#Address correspondence to Alberto Oddo, [email protected]; Anders
18
Løbner-Olesen, [email protected]; Paul R. Hansen, [email protected]
19
20
21
‡These authors contributed equally to this work.
22
23
24
25
44
26
ABSTRACT
27
Multiple strains of Acinetobacter baumannii have developed multidrug-resistance
28
(MDR), leaving colistin as the only effective treatment. The cecropin-α-melittin
29
hybrid BP100 (KKLFKKILKYL-NH2) and its analogs have previously shown activity
30
against a wide array of plant and human pathogens. In this study we investigated the
31
in vitro antibacterial activity of eighteen BP100 analogs (four known and fourteen
32
new) against MDR A. baumannii ATCC BAA-1605, as well as against a number of
33
other clinically relevant human pathogens. Selected peptides were further evaluated
34
against strains of A. baumannii that acquired resistance to colistin due to mutations of
35
the lpxC, lpxD, pmrA or pmrB genes. The novel analogue BP214 showed
36
antimicrobial activity at 1-2 μM concentration and a hemolytic EC50 >150 μM. The
37
lower activity of its enantiomer suggests a dual, specific and non-specific mode of
38
action. Interestingly, colistin behaved antagonistically to BP214 when challenging
39
pmrAB and lpxC mutants.
40
41
LIST OF ABBREVIATIONS
42
AMP, antimicrobial peptide; CAMP, cationic antimicrobial peptide; DCM,
43
dichloromethane; DIC, N,N’-diisopropylcarbodiimide; DIEA, diisopropylethylamine;
44
DMF, N,N’-dimethylformamide; Et2O, diethyl ether; EtOH, ethanol; Fmoc, fluoren-9-
45
ylmethoxycarbonyl; HATU, O-(7-azabenzotriazol-1-yl)-1,1,3,3,-tetramethylaminium
46
hexafluorophosphate;
47
lipopolysaccharide; MeCN, acetonitrile; MDR, multidrug-resistant; MHB, Müller-
48
Hinton broth; MIC, minimum inhibitory concentration; MRSA, methicillin-resistant
49
Staphylococcus
aureus;
HOAt,
PBS,
1-hydroxy-7-aza-benzotriazole;
phosphate-buffered
saline;
LPS,
PTFE,
45
50
polytetrafluoroethylene; RBC, red blood cells; TFA, trifluoroacetic acid; TIS,
51
triisopropylsilane; VRE, vancomycin-resistant Enterococcus faecium.
52
53
INTRODUCTION
54
Multidrug-resistant (MDR) Acinetobacter baumannii infections often occur in
55
intensive care units, where patients are typically immunosuppressed or have been
56
subjected to invasive procedures (1). The therapy outcome is further threatened by the
57
common coexistence of multiple heteroresistant subpopulations (2, 3).
58
Due to the growing prevalence of carbapenem resistance (4, 5), the importance of
59
colistin as last-resort treatment is increasingly critical. Unfortunately, colistin-
60
resistant clinical isolates of A. baumannii have been reported several times (6-8).
61
Polymyxins are well known for binding to the LPS of Gram-negative bacteria with
62
concomitant displacement of Ca2+ and Mg2+ ions (9). From a chemical perspective,
63
this interaction is very specific, and studies on polymyxin nonapeptides (i.e. lacking
64
the lipidated N-terminal amino acid) have revealed that the enantiomers are inactive
65
(10). This specificity provides the basis for both the high activity and selectivity of
66
polymyxins against Gram-negative bacteria. Unfortunately, it also provides pathogens
67
with a clear escape route: known mechanisms (11) behind colistin resistance in A.
68
baumannii consist indeed of i) the addition of ethanolamine to the lipid A moiety of
69
the lipopolysaccharide (LPS) mediated by the pmrA, pmrB, pmrAB and pmrC genes
70
(12) and ii) loss of LPS due to mutations in the lpxA, lpxC, and lpxD genes (13).
71
Its high specificity ultimately makes the self-promoted uptake process very effective
72
but also very delicate, and colistin appears to work in an “all-or-nothing” fashion:
73
susceptible strains are typically inhibited at concentrations <0.5 μM, whereas resistant
74
strains appear unaffected at concentrations <128 μM.
46
75
Many studies in recent years have focused on modifying polymyxins to address their
76
shortcomings (9, 14), but only a few have dealt with identifying a novel lead for their
77
potential replacement. We envisaged that a less specific antimicrobial peptide could
78
offer the advantage of better robustness and reliability in the critical clinical scenario
79
whereby a last-resort drug is employed. This was based on the assumption that the
80
activity of a peptide able to rapidly kill bacteria of different genera, both Gram-
81
positive and -negative, could not depend on a single molecular target. This
82
characteristic was envisaged to lower the survival probability of heteroresistant
83
populations, as well as overcoming resistance mechanisms based on target
84
modification.
85
Given the previous reports (15, 16) of cecropin-α-melittin hybrids showing activity
86
against colistin-resistant strains of A. baumannii, we developed an interest in the BP-
87
peptide family (17-19). In the present study we investigated the in vitro antibacterial
88
activity of eighteen BP100 (KKLFKKILKYL-NH2) analogs, four known and fourteen
89
new, against MDR A. baumannii ATCC BAA-1605, as well as against a number of
90
other clinically relevant human pathogens. Selected peptides were then evaluated
91
against four colistin-susceptible and -resistant clinical isolates of A. baumannii. We
92
report that BP214, a novel analogue, showed only slightly reduced activity compared
93
to colistin and a hemolytic EC50 >150 μM. The peptide displayed rapid bactericidal
94
properties and its high activity was maintained also against colistin-resistant strains
95
featuring mutated lpxC, pmrA and pmrB genes.
96
97
MATERIALS AND METHODS
98
Solid-phase peptide synthesis. Disposable 5 ml polypropylene reactors fitted with a
99
PTFE filter were acquired from Thermo Scientific. Hypogel RAM 200 resin and
47
100
Fmoc-protected amino acids were purchased from Iris Biotech GmbH. The resin was
101
allowed to swell overnight in DMF, then washed with DMF (5×). The Fmoc-group
102
was removed by treatment with a 20% v/v piperidine solution in DMF (3 × 4 min),
103
then the resin was washed with DMF (3×), DCM (3×) and DMF again (5×). Chain
104
elongation was achieved with single couplings using 3.5 equiv. of amino acid, HOAt
105
and HATU each, and 7 equiv. of DIEA (based on declared resin loading). Fmoc-
106
protected amino acids were dissolved in DMF together with HOAt (both at a
107
concentration of 0.4 M); they were then activated by the sequential addition of the
108
HATU solution (0.4 M in DMF) and of DIEA (pure), and the mixture was
109
immediately transferred into the reactor. After 2h, the resin was washed with DMF
110
(3×), DCM (3×) and DMF again (5×), then Fmoc-removal with piperidine was
111
performed as above. Cycles of amino acid coupling and Fmoc-removal were
112
alternated until the chain elongation process was completed. After the last
113
deprotection cycle for the N-terminal amino acid, the resin was additionally washed
114
with EtOH (5×) and dried in vacuo. The release from the solid support and the
115
cleavage of the side-chain protecting groups were performed by treatment with a
116
TFA:H2O:TIS (95:2.5:2.5) solution for 2h. The cleavage solution was collected and
117
concentrated down to ~300 μl with a gentle stream of N2, then the peptide was
118
precipitated (and washed) with Et2O (3×). After spontaneous evaporation of the
119
residual Et2O, the residue was dissolved in H2O:MeCN (8.5:1.5) and freeze-dried.
120
121
Peptoid synthesis. Peptide-peptoid hybrids have been synthesized via the
122
submonomer approach as previously described (20). Briefly, bromoacetic acid (20
123
equiv., 0.6M in DMF) was coupled (2 × 20 min) to the free N-terminus of the
124
growing resin-bound peptide after preactivation (3 min) with diisopropylcarbodiimide
48
125
(DIC, 19 eq.). After washing with DMF (10x), a solution of the appropriate amine (20
126
equiv., 1M in DMF) was added and the reactor was placed on a shaker for 2h.
127
128
Peptide purity and identity. The verification was performed using analytical HPLC
129
and MALDI-ToF-MS. The α-cyano-4-hydroxycinammic acid matrix was used for
130
MALDI-ToF-MS experiments. Peptides were purified via preparative HPLC; purity
131
was ≥ 95% for all peptides tested.
132
133
Hemolytic activity. Peptide-induced hemolysis was determined in triplicate by
134
mixing 75 μl of peptide solution in PBS with 75 μl of a 0.5% RBC (blood type 0+)
135
suspension in PBS, incubating the mixture at 37 ˚C for 1h and then measuring
136
hemoglobin release with a spectrophotometer (λ = 414 nm). Results were normalized
137
with respect of a positive (melittin) and negative (PBS) control.
138
139
Determination of antimicrobial activity. MIC (Minimum Inhibitory Concentration)
140
values were determined in triplicate using the tube microdilution method according to
141
CLSI guidelines. Bacterial inocula were prepared by diluting an overnight culture
142
1:100 with preheated MHB-II. The suspension was allowed to reach OD600 = 0.2-0.4
143
and then diluted down to 1 · 106 CFU/ml.
144
Tests against colistin-resistant strains were performed using two alternative
145
procedures. When colistin was maintained through all stages, including the final test
146
tubes, the overnight culture and all following dilutions were made using a colistin-
147
enriched (10 μg/ml colistin sulfate) MHB-II medium. Alternatively, colistin was
148
present only in overnight culture medium and all following dilutions were performed
149
with standard MHB-II medium.
49
150
Peptide solutions were mixed with an equal volume of bacterial suspension in a
151
polypropylene microtiter plate and incubated at 37 ºC for 16h. Inhibition of bacterial
152
growth was assessed visually.
153
Peptides were tested as TFA-salts against Escherichia coli ATCC 25922 (ref. strain),
154
Staphylococcus aureus ATCC 33591 (MRSA), Enterococcus faecium ATCC 700221
155
(VRE), Pseudomonas aeruginosa ATCC 27853 (ref. strain), Klebsiella pneumoniae
156
ATCC 700603 (MDR) and Acinetobacter baumannii ATCC BAA-1605 (MDR).
157
ATCC strains were obtained commercially. Selected peptides were tested against
158
additional strains of A. baumannii, namely ATCC 19606, Ab-167 (MDR, colistin-
159
susceptible clinical isolate) (21), Ab-176 (MDR, colistin-susceptible clinical isolate)
160
(21), CS01 (colistin-susceptible clinical isolate) (8), Ab-167R (strain Ab-167
161
containing an ISAba1 insertion at nucleotide 321 of lpxC) (22), Ab-176R (strain Ab-
162
176 with a G739T substitution at nucleotide 739 of the lpxD gene producing a
163
premature stop codon) (22), RC64 (derivative of ATCC 19606 containing R134C and
164
A227V mutations in pmrB) (23), CR17 (colistin-resistant derivative of CS01
165
containing an M12K mutations in pmrA) (8).
166
167
Time-course experiments. Time-kill curves were measured by growing single
168
colonies of ATCC 19606 or RC64 in MHB-II. In the case of RC64, the growth
169
medium was supplemented with colistin sulfate (10 μg/ml) to prevent reversal of
170
resistance. For stationary phase experiments, overnight cultures were used directly.
171
For exponential phase experiments, the overnight cultures were diluted 1:100 in 50 ml
172
of preheated (37 °C) MHB-II (with the addition of colistin sulfate in the case of
173
RC64) and transferred into Erlenmeyer flasks placed in a water bath under shaking.
174
When the cultures reached OD600 = 0.5 they were divided into fresh flasks and treated
50
175
with the test compound. Spot-plating was performed in triplicate at time points of 0,
176
1, 3 and 5h by transferring 10 μl of a 10-fold diluted suspension on a plate containing
177
MHB-II medium. In persister assays the procedure was the same, but the cultures
178
were divided at two time points, i.e. before and after ciprofloxacin treatment. Spot-
179
plating was performed as above.
180
181
RESULTS
182
The antimicrobial activity of all peptides investigated in this study is presented in
183
Table 1 along with the hemolytic activity observed at 150 μM. For consistency with
184
previous literature, the “BP” designation has been maintained also for the novel
185
sequences presented in this study, with a new numeration starting from 201. BP100
186
and RW-BP100 have been synthesized and tested to ensure comparability with
187
previously reported data.
188
In this discussion the term “persister” will be used to describe metabolically inactive
189
bacteria that survive antibiotic treatment (24). The term “heteroresistant” describes
190
metabolically active subpopulations that display a lower susceptibility to antibiotics
191
due to phenotypic variations (25).
192
Design of optimized analogs. The BP-peptide family comprises numerous analogs
193
with varying degrees of antimicrobial and hemolytic activity. Our design approach
194
was based on combining elements from different analogs, as well as introducing novel
195
modifications.
196
BP201-206 are BP100 analogs featuring single and double Lys→Arg substitutions. A
197
second set of analogs (BP207-209) was designed by introducing stereochemical
198
modifications that included unprecedented D/L-amino acid combinations and
199
peptoids. BP210 was based on the structure of RW-BP100, but the bulky aromatic
51
200
group (2-Nal for Trp) was moved from position 10 to position 4. We included the
201
previously reported BP143 (KKLfKKILKYL-NH2) and BP157 (KKLFKkilkyl-NH2)
202
in our initial screening against clinically relevant human pathogens. These peptides
203
were selected on the basis of their low toxicity and good activity previously published
204
against phytopathogenic strains of the Pseudomonas genus (18).
205
Among the novel sequences, BP203 stood out as a net improvement: by introducing a
206
single arginine in position 9 we were able to match and surpass the high activity of
207
RW-BP100 without any detectable increment in toxicity to RBC. BP207-209 did not
208
produce any encouraging results and were not further investigated. BP143 showed
209
similar or identical activity profile to the more hemolytic BP100, while BP157 proved
210
considerably less active.
211
Analogs BP211-213 were designed by combining elements of BP203 with elements
212
from the less hemolytic BP143 and BP157. Partial D-amino acid substitution did not
213
result in any reduction of hemolysis, which was instead slightly increased. Finally,
214
BP214 was designed as the all-D BP203 enantiomer and behaved similarly.
215
Activity against colistin-resistant A. baumannii strains. The peptides BP202,
216
BP203, BP211, BP213 and BP214 showed good activity against MDR A. baumannii
217
ATCC BAA-1605, differing degrees of selectivity between Gram-positive and -
218
negative bacteria, and caused <50% hemolysis at 150 μM concentration. These
219
peptides, along with BP100 and RW-BP100, were tested against a wider array of
220
colistin-susceptible and -resistant strains of A. baumannii (Table 2). Overall, the
221
resistant mutants proved 4- to 16-fold less susceptible to BP-peptides than their parent
222
strains and practically insusceptible to colistin. However, the all-D BP214 showed
223
even higher activity than BP203 and the overall highest of the series. Together with
224
RW-BP100, it proved the least affected by the lack or modification of the LPS.
52
225
Susceptibility tests against colistin-resistant strains were carried out both in standard
226
MHB-II medium and in a modified version containing 10 μg/ml of colistin sulfate.
227
With the exception of RW-BP100, the presence of colistin resulted in a marked
228
antagonistic effect to BP-peptides when challenging pmr mutants.
229
Time-course experiments. The most interesting analog, BP214, was selected for
230
further investigation and compared to colistin. Time-course experiments were carried
231
out with stationary and exponentially growing cultures of A. baumannii ATCC 19606
232
and RC64 (Figure 1 and 2). For practical reasons, tests on exponentially growing
233
cultures were carried out from an initial bacterial concentration of approx. 5 × 108
234
CFU/ml (OD600 ≈ 0.5); tested peptide concentrations were however based on
235
multiples of the MIC values determined for a standard 5 × 105 CFU/ml inoculum
236
(Table 2).
237
Both colistin and BP214 appeared affected by the higher bacterial inoculum, although
238
to different extents. At 1× MIC the bactericidal effect of BP214 was moderate and,
239
after less than 3h, the bacterial population showed full recovery (Figure 1A); this
240
behavior is compatible with heteroresistance phenomena (3) or with peptide
241
sequestration by membrane debris. At 4× MIC and above, BP214 was able to reduce
242
the number of CFU of the colistin-susceptible ATCC 19606 strain to below our
243
detection level (Figure 1A). The >3-Log reduction in CFU/ml clearly indicates a
244
bactericidal action. Colistin proved visibly affected by the high bacterial
245
concentrations and/or heteroresistance phenomena (Figure 1B), being unable to
246
eradicate a growing culture even after 5h at 64× MIC concentrations. None of the
247
tested concentrations of BP214 had any effect on stationary phase ATCC 19606 cells
248
(Fig. 1C). Even at high concentrations, colistin only had a modest effect on stationary
249
phase cells (Fig. 1D).
53
250
A different picture emerged when BP214 challenged the colistin-resistant pmrB-
251
mutant RC64. Concentrations of BP214 corresponding to 4× MIC and above could
252
reduce the number of CFU/ml in the culture to below our detection level for both
253
exponential- (Figure 2A) and stationary-phase (Figure 2B) cultures.
254
We found that ciprofloxacin induced persister formation in both ATCC 19606 and
255
RC64 cultures (Figure 3). After BP214 was added (t = 2h), no bactericidal effect was
256
observed for ATCC 19606, whereas the CFU/ml of RC64 were reduced to below our
257
detection limit. Overall, the susceptibility of persisters to BP214 was thus quite
258
similar to stationary-phase cultures.
259
260
DISCUSSION
261
As previous studies have highlighted the worrying ease with which colistin-resistant
262
mutants of A. baumannii can be isolated (22), more robust alternatives are needed.
263
From a drug design perspective, colistin’s case indicates that a LPS-dependent
264
mechanism of action might be a disadvantageous approach for achieving selectivity
265
against Gram-negative bacteria – and this appears to apply particularly well to A.
266
baumannii. On the other hand, the LPS is a constitutive element of the Gram-negative
267
cell-wall and thus an attractive (and obligate) target. Furthermore, the partial or
268
complete loss of LPS has been connected to increased susceptibility to many
269
antibiotics and decreased virulence (11, 26); therefore, pmr mutants of A. baumannii
270
have been suggested to be of higher clinical importance (11). From this perspective, it
271
is clear that colistin-resistant strains are not intrinsically more threatening or virulent,
272
but they become clinically important due to the increasing prevalence of carbapenem
273
resistance and the role of colistin as last-resort treatment (4, 27).
54
274
We envisaged that a highly attractive alternative to colistin for the treatment of A.
275
baumannii infections would be able to i) strongly interact with wild-type and
276
modified LPS, while ii) being able to exert a bactericidal effect also via alternative
277
mechanisms. Ideally, such a peptide should also be short, non-toxic and resistant to
278
proteolysis.
279
Due to their small size and good antimicrobial activity, the BP-series of cecropin-α-
280
melittin hybrids posed as a good starting point. Our synthetic approach to improved
281
BP100 analogs has been described in the Results section and MIC values for all
282
compounds are presented in Table 1 and 2.
283
As hypothesized, the broad-spectrum BP-peptides resulted overall less affected than
284
colistin by modifications or loss of the LPS. This proved true in particular for RW-
285
BP100, as the full arginine substitution grants it an advantage in electrostatic
286
interactions, due to the higher basicity of the guanidino-group (pKa = 12.5) versus
287
primary amino-groups (pKa = 10.5). The superior hydrogen bonding capability, as
288
well as the increased size and lipophilicity of Trp versus Tyr, can also be expected to
289
play a role in stabilizing peptide-membrane interactions. Taken together, these
290
characteristics make RW-BP100 a potent and non-specific membrane-active agent, as
291
further evidenced by its high hemolytic activity. At the same time, however, RW-
292
BP100 did not provide any significant advantage over its less hemolytic analogues
293
against colistin-susceptible strains.
294
Our efforts in designing an AMP that would ideally be equally active against colistin-
295
susceptible and -resistant strains of A. baumannii have resulted in the identification of
296
BP214 (Figure 4). This all-D undecapeptide displayed robust activity (MIC ≈ 4 μg/ml
297
as TFA-salt, ≈ 2 μM peptide conc.) against several strains – including clinically
55
298
important pmr mutants – and a modest hemolytic EC50 >150 μM. The evaluation of
299
this peptide in microbiological assays lead to several interesting observations.
300
In time-course experiments, remarkable differences were observed between
301
exponential- and stationary-phase cultures of the colistin-susceptible ATCC 19606
302
and its pmrB mutant RC64. Specifically, stationary-phase culture of the susceptible
303
strain proved immune to BP214 and only moderately susceptible to high
304
concentrations of colistin, while RC64 proved instead susceptible to BP214.
305
Interestingly, persisters left after ciprofloxacin treatment behaved identically.
306
Previous studies have shown differences in cell shape and membrane appearance
307
between exponential- and stationary-phase cultures of colistin-susceptible and -
308
resistant strains of A. baumannii (28). Upon entering a stationary phase, A. baumannii
309
considerably changes its transcriptome and up-regulates maintenance and protective
310
processes, several of which can play a role in determining the susceptibility to
311
membrane-active agents (29-31). In this perspective, it is plausible that the fitness
312
cost involved in colistin-resistance would prevent RC64 from dedicating sufficient
313
resources to these protective mechanisms (11). Another possibility, as shown for lpx
314
mutants, is related to the zeta potential of the bacterial outer membrane. Colistin-
315
susceptible strains have shown a less negative potential in stationary than in
316
exponential phase, whereas resistant mutants behaved oppositely (32).
317
In terms of in vitro MIC, the enantiomeric pair BP203 and BP214 behaved very
318
similarly against most species (Table 1). This is expected for membrane-active
319
peptides that do not bind specifically to any target – e.g. cecropin, melittin and their
320
hybrids (33). However, moderate but consistent differences in MIC were observed
321
against several A. baumannii strains (Table 2), indeed suggesting the presence of
322
binding targets with strict chiral requirements – as it is the case for e.g. colistin and
56
323
drosocin (10, 34). Ultimately, all BP-peptides are able to kill bacteria via non-
324
specific, amphipathicity-driven membrane damage; additionally, as far as A.
325
baumannii is concerned, BP214 appeared able to interact with certain structural
326
elements also in a more specific fashion. For wild-type strains and pmr mutants, the
327
high number of stereocenters in the saccharide portion of the LPS may very well
328
account for the observed enantiomeric discrimination. Moreover, being a prominent
329
feature of the cell wall, the LPS can be expected to play a major role in determining
330
the susceptibility of Gram-negative bacteria to membrane active agents in general.
331
Accordingly, LPS-deficient lpx mutants proved consistently less susceptible than
332
LPS-modified pmr mutants towards the investigated BP-peptides – again, with the
333
exception of the RW-analog.
334
However, the lpxC mutant Ab-167R proved unexpectedly very susceptible to BP214.
335
Interestingly, the same strain had been previously reported to be 100-fold less
336
susceptible to LL-37 than its parent strain, whereas other mutants proved as
337
susceptible (22). BP203 also resulted 16-fold less active than its enantiomer. While
338
the advantages of RW-BP100 can be rationalized as described above, for LL-37,
339
BP203 and BP214 the same task is more arduous without assuming the presence of
340
specific binding targets other than the LPS. The existence of such structures has been
341
hypothesized before in order to explain the higher anionic zeta potential of stationary-
342
phase lpxA mutants than their parent strains (32). The lower susceptibility of Ab-176R
343
suggests that these structures might be constitutive but lost, modified or masked as a
344
consequence of lpxD mutation.
345
Further insight was provided by the observed antagonism between colistin and BP-
346
peptides when challenging pmr mutants (Table 2). Due to the cationic nature of all
347
these compounds, the sequestration of BP-peptides by colistin does not appear
57
348
probable. However, previous studies have shown that, although unable to exert a
349
bactericidal effect, colistin can still effectively bind to the outer membrane of resistant
350
A. baumannii cells (28). A plausible explanation is therefore that colistin and BP-
351
peptides compete for binding to the modified LPS, but the former is not able to
352
translate binding into bacterial killing. However, most BP-peptides were heavily
353
affected by the presence of colistin, confirming that the latter is a high-affinity ligand
354
also for the modified LPS.
355
Several observations support this competitive model: i) thanks to its stronger
356
cationicity and/or non-specific membrane-activity, RW-BP100 appeared unperturbed
357
by the presence of colistin; ii) the presence of colistin at high concentration raises the
358
MIC of BP-peptides for pmr mutants virtually to the same level as for the LPS-
359
deficient lpx mutants – as in both cases LPS-binding is not possible; iii) this
360
antagonism was generally not observed for lpx mutants. However, the activity of
361
BP214 against Ab-167R made again an exception. This was the only case in which
362
competition between colistin and BP-peptides was observed when challenging an lpx
363
mutant. By definition, a competitive binding implies the presence of a defined target
364
available in limited quantity. This is confirmed by the activity difference between
365
BP214 and its enantiomer. Clearly, for an lpx mutant this target cannot be the LPS.
366
The competition between BP214 and colistin in the case of Ab-167R leads to
367
additional interesting considerations. To our knowledge, it has never been shown
368
before that colistin can bind other intrinsic membrane targets with high affinity. The
369
prominence of the LPS is presumably the reason why this phenomenon has not been
370
observed before.
371
From a structural perspective, the advantage of BP214 over colistin might stem from
372
the higher flexibility of linear peptides compared to macrocycles (35). Being more
58
373
rigid, colistin can bind the LPS paying a lower entropic penalty and thus with higher-
374
affinity; however, this rigidity prevents it from binding to a modified partner without
375
substantial differences. The more flexible BP214 cannot bind with as high an affinity,
376
but is able of modifying its conformation easily, resulting in more robust
377
antimicrobial activity. This hypothesis however remains to be demonstrated.
378
In conclusion, under optimal conditions colistin’s activity against susceptible A.
379
baumannii strains remains unrivaled, but its performance drops dramatically in a
380
variety of other relevant scenarios. Colistin-resistant strains are becoming
381
increasingly common and virtually immune to the drug at viable concentrations. Due
382
to its toxicity to kidneys, increasing dosages constitutes a serious collateral risk for
383
patients. The advantages of slightly less active but more reliable agents should thus be
384
carefully taken into consideration.
385
BP214 is one such agent and arguably the most promising member of its family
386
identified to date. Its dual mode of action, both specific and non-specific, resulted in a
387
potent and very robust antimicrobial activity. Being composed of D-amino acids only,
388
BP214 can be expected to be proteolytically stable and potentially suitable for oral
389
administration (36).
390
Overall, BP214 displayed attractive antimicrobial properties and, most importantly,
391
its small size and chemical simplicity hold promise of ample improvement potential.
392
These characteristics make BP214 an attractive lead for the development of novel
393
antimicrobials targeting threatening Gram-negative pathogens, and especially A.
394
baumannii.
395
396
ACKNOWLEDGEMENTS
59
397
This study has been funded by the Marie Curie Actions under the Seventh Framework
398
Programme for Research and Technological Development of the EU (Grant
399
Agreement N° 289285). Financial support from the Augustinus Foundation is also
400
kindly acknowledged. The authors wish to thank Jytte M. Andersen for excellent
401
technical support. Prof. McConnell of the University of Seville, Spain, and Prof. Luis
402
Rivas of the University of Madrid, Spain, are gratefully acknowledged for providing
403
the clinical isolates mentioned in Table 2.
404
405
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62
577
Figure 1. Time-kill curves for colistin and BP214 against A. baumannii ATCC 19606
578
in exponential (A, B) and stationary phase (C, D). Each data point is the average of
579
readings from at least three independent experiments. (A, C) (BP214) , control; ,
580
1× MIC; , 2× MIC; , 4× MIC; , 8× MIC. (B, D) (colistin) , control; , 16×
581
MIC; , 32× MIC; , 64× MIC.
582
583
Figure 2. Time-kill curves for BP214 against A. baumannii RC64 in exponential (A)
584
and stationary phase (B). Each data point is the average of readings from at least three
585
independent experiments. (A, B) (BP214) , control; , 1× MIC; , 2× MIC; , 4×
586
MIC; , 8× MIC.
587
588
Figure 3. Determination of the time-efficiency of BP214 in clearing ATCC 19606
589
(A) and RC64 (B) persisters left after 2h of ciprofloxacin treatment. Each data point is
590
the average of readings from at least three independent experiments. (A, B) ,
591
control; , ciprofloxacin, 2× MIC; , ciprofloxacin, 2× MIC + BP214, 4× MIC
592
(added at t = 2 h); , ciprofloxacin, 2× MIC + BP214, 8× MIC (added at t = 2 h).
593
594
Figure 4. Structures of the lead compound BP100 (top) and the novel analog BP214
595
(bottom).
596
63
TABLE 1 Antimicrobial (MIC in μg/mL, and in μM concentration in brackets) and
hemolytic (% hemolysis at 150 μM concentration) activity of all peptides investigated in this
study. Lower-case letters indicate D-amino acids. Underlined portions of the sequence
E. coli
P. aeruginosa
K. pneumoniae
A. baumanniia
BP100
KKLFKKILKYL-NH2
33%
134.5 (64)
67 (32)
17 (8)
33.5 (16)
17 (8)
8.5 (4)
RW-BP100
RRLFRRILRWL-NH2
100%
18.5 (8)
18.5 (8)
4.5 (2)
18.5 (8)
18.5 (8)
18.5 (8)
BP143
KKLfKKILKYL-NH2
< 8%
134.5 (64)
67 (32)
8.5 (4)
33.5 (16)
17 (8)
8.5 (4)
269 (128)
134.5 (64)
33.5 (16)
134.5 (64)
67 (32)
33.5 (16)
137.5 (64)
275 (128)
275 (128)
137.5 (64)
137.5 (64)
69 (32)
Compound
Sequence
S. aureus
E. faecium
%HA (150 μM)
identify peptoid residues, e.g. F = NPhe. All experiments were performed in triplicate.
BP157
KKLFKkilkyl-NH2
8%
BP201
RKLFKRILKYL-NH2
45%
BP202
KRLFRKILKYL-NH2
44%
8.5 (4)
8.5 (4)
17 (8)
17 (8)
8.5 (4)
4.5 (2)
BP203
KKLFKKILRYL-NH2
31%
33.5 (16)
8.5 (4)
8.5 (4)
17 (8)
8.5 (4)
4 (2)
BP204
KRLFRKILRYL-NH2
69%
70.5 (32)
35 (16)
70.5 (32)
70.5 (32)
35 (16)
17.5 (8)
BP205
KKLFRRILKYL-NH2
63%
8.5 (4)
8.5 (4)
34.5 (16)
17 (8)
8.5 (4)
4.5 (2)
BP206
RRLFKKILKYL-NH2
68%
34.5 (16)
17 (8)
34.5 (16)
17 (8)
17 (8)
4.5 (2)
BP207
KKLFKKiLKYL-NH2
N/D
>269 (>128)
269 (128)
269 (128)
269 (128)
269 (128)
134.5 (64)
BP208
KKLFKKILKYL-NH2
N/D
>269 (>128)
269 (128)
134 (64)
134 (64)
269 (128)
134 (64)
BP209
KKLFKKLLKFL-NH2
N/D
>269 (>128)
269 (128)
269 (128)
269 (128)
>269 (>128)
>269 (>128)
BP210
RRL(2-Nal)RRILRYL-NH2
100%
37 (16)
18.5 (8)
73.5 (32)
147 (64)
37 (16)
37 (16)
BP211
KKLfKKILRYL-NH2
43%
17 (8)
17 (8)
4.5 (2)
8.5 (4)
8.5 (4)
4 (2)
BP212
KKL(D-2-Nal)KKILKYL-NH2
85%
17 (8)
17 (8)
4.5 (2)
8.5 (4)
8.5 (4)
4.5 (2)
KKLFKkilryl-NH2
< 8%
134.5 (64)
67 (32)
33.5 (16)
67 (32)
33.5 (16)
17 (8)
kklfkkilryl-NH2
42%
33.5 (16)
8.5 (4)
8.5 (4)
33.5 (16)
8.5 (4)
4 (2)
BP213
BP214
A. baumannii ATCC BAA-1605
a
64
TABLE 2 Antimicrobial activity (MIC in μg/mL as TFA salt) of BP100, RW-BP100,
BP202, 203, 211, 213 and 214 against selected colistin-susceptible and -resistant strains of A.
baumannii. Colistin sulfate is included as a reference. Values within brackets were obtained
when employing a colistin-enriched medium (10 μg/ml colistin sulfate concentration). All
tests were performed in triplicate.
Acinetobacter baumannii
Compound
Colistin-susceptible
Ab-167
Ab-176
ATCC 19606
Colistin-resistant
CS01
Ab-167R
Ab-176R
RC64
CR17
BP100
8.5
17
8.5
8.5
17 (33.5)
67 (67)
8.5 (67)
33.5 (67)
RW-BP100
8.5
4.5
8.5
8.5
8.5 (4.5)
17 (17)
8.5 (8.5)
4.5 (8.5)
BP202
4.5
8.5
4.5
4.5
33.5 (17)
33.5 (33.5)
17 (33.5)
17 (33.5)
BP203
4.5
17
8.5
8.5
67 (33.5)
67 (67)
8.5 (33.5)
33.5 (67)
BP211
4.5
17
8.5
17
33.5 (33.5)
67 (67)
4.5 (33.5)
17 (67)
BP213
8.5
17
17
17
33.5 (17)
67 (67)
17 (134.5)
67 (269)
BP214
2
4.5
4.5
2
8.5 (17)
33.5 (33.5)
4.5 (17)
8.5 (33.5)
Colistin
0.5
0.5
0.25
0.25
>128
>128
128
>128
65
66
67
68
69
70
71
72
73
74
Paper II
Submitted to ACS Medicinal Chemistry Letters
Modulation of backbone flexibility for effective dissociation of antibacterial and hemolytic
activity in cyclic antimicrobial peptides without loss of potency
Alberto Oddo1,2, Thomas T. Thomsen3, Hannah M Britt2, Anders Løbner-Olesen3, Peter W
Thulstrup4, John M Sanderson2 and Paul Robert Hansen1,*
1
University of Copenhagen, Department of Drug Design and Pharmacology, Universitetsparken 2,
2100, Copenhagen, Denmark
2
Durham University, Department of Chemistry, South Road, DH1 3LE, Durham, United Kingdom.
3
University of Copenhagen, Department of Biology, Ole Maaløes Vej 5, 2200, Copenhagen,
Denmark
4
University of Copenhagen, Department of Chemistry, Universitetsparken 5, 2100, Copenhagen,
Denmark
75
76
77
78
79
80
81
82
Paper III
Submitted to Antimicrobial Agents and Chemotherapy
The Lantibiotic Nai-107 efficiently rescues Drosophila melanogaster from infection with
methicillin-resistant Staphylococcus aureus USA300
by Thomas T. Thomsen1, Biljana Mojsoska2, Joao C. S. Cruz3, Stefano Donadio34, Håvard
Jenssen2, Anders Løbner-Olesen1, Kim Rewitz1.
1
Department of Biology University of Copenhagen, Denmark
2
Department of Science, Systems and Models, Roskilde University, Denmark
3
Ktedogen, Milano, Italy.
4
Naicons Srl, Milano, Italy.
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The Lantibiotic NAI-107 efficiently rescues Drosophila
melanogaster from infection with methicillin-resistant
Staphylococcus aureus USA300
Thomas T. Thomsen1, Biljana Mojsoska2, João C. S. Cruz3, Stefano Donadio34, Håvard Jenssen2,
Anders Løbner-Olesen1*, Kim Rewitz1*.
1
Department of Biology University of Copenhagen, Denmark
2
Department of Science, Systems and Models, Roskilde University, Denmark
3
Ktedogen, Milano, Italy.
4
Naicons Srl, Milano, Italy.
*Correspondence: [email protected], [email protected]
Key words: Antibacterial peptides; Drug screening; Antibiotics
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Abstract
We used the fruit fly Drosophila melanogaster as a cost-effective in vivo model to evaluate the efficacy
of novel antibacterial peptides and peptoids for treatment of methicillin-resistant staphylococcus
aureus (MRSA) infections. A panel of peptides with known antibacterial activity in vivo and/or in vitro
was tested in Drosophila. Although most antibacterials that were effective in vitro failed to rescue
lethal effects of S. aureus infections in vivo, we found that two lantibiotics, Nisin and NAI-107 rescued
adult flies from fatal infections. Furthermore, NAI-107 rescued mortality of infection with the MRSA
strain USA300 with equivalent efficacy to vancomycin, a widely applied antibiotic for the treatment of
serious MRSA infections. These results establish Drosophila as a useful model for in vivo drug
evaluation of antibacterial peptides. Further, the data shows that NAI-107 has the ability to kill nongrowing stationary phase bacteria in vitro, which vancomycin is incapable of.
Introduction
Since the golden era of antibiotic drug development during the 1940-1960`s, development and spread
of multidrug resistance have become a huge burden to societies. Today resistance to almost all known
antibiotics has emerged with the sequential introduction of new or improved antibiotics in the clinical
and agricultural setting (1, 2). Therefore, continued development of new or improved antibiotics is of
great importance to human health. However, new antibiotics are lacking and few are under
development for treatment of multidrug resistant (MDR) infectious bacteria, as drug development is
costly and success from in vitro discovery to clinical settings is limited.
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Bacterial infections with MRSA (Methicillin Resistant Staphylococcus aureus) are no longer sporadic
in distribution and prevalence (3, 4). MRSA strains are associated with both community (CA-MRSA)
and hospital (HA-MRSA) acquired infections, with the highly β-lactam resistant USA300 CA-MRSA
clone accounting for close to 80% of all MRSA infections in the USA (5). High level β-lactam
resistance is due to acquisition of SCCmec elements (Staphylococcal Cassette Chromosome) including
the mecA gene, which encodes an alternative version of the penicillin binding protein (PBP2A), that is
inducible (6, 7) and has a lowered affinity for β-lactam antibiotics (8). Often SCCmec elements are
associated with carriage of resistance genes to other antibiotics including aminoglycoside modifying
enzymes such as acetyltransferase, adenylyltransferase or phosphotransferase (9). Due to this
resistance, MRSA treatment usually includes glycopeptide antibiotics such as vancomycin or
oxazolidinones such as linezolid. However, failure in vancomycin treatment has been reported in
vancomycin-intermediate S. aureus (VISA) (10) and vancomycin resistant S. aureus (VRSA) (11). On
the other hand, linezolid resistance is rare (12), but has been observed as mutations in the ribosomal
DNA, or through carriage of the Cfr rRNA methyltransferase gene (13, 14). Furthermore, resistance to
the last resort antibiotic daptomycin has been reported (15, 16). Given the increasing frequency of
resistance to these antibiotics, it is important to develop improved or novel therapeutics, and to
consider new strategies to contain the spread of the growing resistance problem.
Peptide based antibiotics has been proposed as the next generation of antimicrobial compounds because
of their wide distribution in nature as part of innate immunity. These molecules are often amphipathic
and interact with the bacterial membrane to disrupt its function. The cationic peptide colistin, a
bacteriocin currently used for treatment of highly resistant gram-negative infections, is part of the
polymyxins that are derived from natural producers such as Paenibacillus polymyxa (17). Another
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bacteriocin, nisin, has been used in the food industry for decades against harmful bacteria such as S.
aureus, Listeria monocytogenes and Clostridium botulinum (18). Nisin belongs to a subgroup known as
lantibiotics, named so, for containing uncommon amino acids such as lanthionine, methyllanthionine,
didehydroalanine or didehydroaminobutyric acid (19). Nisin was described to disrupt membrane
integrity through a dual mode of action: By inhibiting cell wall synthesis through binding to the cell
wall precursor lipid-II and by subsequent pore formation (20-22), although new evidence points
towards a more complex mechanism that includes aggregation of Lipid-II (23). Peptides may be used
directly as antimicrobials or could pose as templates for development of small molecule mimetics such
as peptoids, which can accommodate improvements to toxicity and are intrinsically less prone to
degradation by proteases (24). The gap from in vitro drug screening to the large scale efficacy testing
necessary for clinical development is hampered by the expensive, labor-intensive and highly regulated
infection models in mammals. It is therefore of interest to develop improved cost-effective methods
with high predictive value for screening of antimicrobial compounds before these are put into large
scale production. Although the fruit fly Drosophila has been extensively used in drug discovery (25,
26), its application for screening of antibacterial compounds has been limited (27-29). Drosophila is a
powerful genetic model for studying disease mechanism and during the past decades it has been used
extensively in elucidating the mechanisms of innate immunity, leading to the discovery of the
conserved role of the Toll receptors (30) and the immune deficiency (IMD) pathway (31). Studies of
innate immunity in Drosophila have sprouted development of various methods for infecting flies with
important human pathogens (28, 32-34). Here, we evaluate the therapeutic potential of antimicrobial
peptides and peptoids in vivo by screening efficacy and toxicity in a Drosophila model infected with S.
aureus 8325-4 (35) and MRSA USA300 (36). Tests were performed with a range of different peptides
including the lantibiotics nisin A (37) and NAI-107 (38, 39) currently undergoing preclinical studies.
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These are usually produced by gram-positive bacteria and characterized as ribosomally synthesized
peptides containing ring structures, introduced through the thioether containing lanthionine and
methyllanthionine residue (40). Further, a panel of amphipathic cationic peptides previously shown to
have good in vitro or in vivo efficacy were tested: GN2, GN4 (41, 42), HHC-9 (43), HHC-36 (44) and
peptoids: GN-2 Npm9, GN-2 Ntrp5-8 Nlys1-4, GN-4 (45). We found that NAI-107 rescued an otherwise
lethal infection with MRSA USA300 and with an efficacy equivalent to vancomycin. Further, nisin
provide transient protection from infection, while the majority of the peptides and peptoids show no
protection from infection or were highly toxic to the host.
Materials and methods
Bacteria and growth media
The S. aureus strains 8325-4 (35) and USA300 (36) was used as indicated in the individual
experiments. Bacterial cultures were grown in cation adjusted Müller Hinton Broth (MHB-II ) at the
indicated temperature.
Growth rate determination:
The growth rate of the S. aureus was examined at 37°C in vitro, to determine the growth period
required for obtaining balanced cultures, here defined as cultures grown exponential for no less than 6
generations. Prior to injection of bacteria into the fly in vivo model, the inoculum was prepared as
balanced cultures grown at 37°C. Since flies used in our in vivo infection model are kept at 29°C, we
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also tested the in vitro generation at this temperature. In vitro growth rate was defined in MHB-II, by
optical density measurements at 600 nanometers (OD600) at 10 minute intervals. Further we determined
the in vivo generation time by CFU/animal measurements after infection, by counting of colony
forming units (CFU) after crushing flies infected with bacteria at various time points, and plating on
Manitol Salt Agar (MSA). This was performed in triplicate experiments; 3 individual flies were
crushed in phosphate buffered saline (PBS) and 10x dilution series were prepared, from which 10µl
was spot plated on MSA. The mean value of each experiment was determined as CFU/Fly and plotted.
Minimum inhibitory concentration
Minimum inhibitory concentrations (MIC) of all tested compounds were performed according to
protocols using the micro-broth dilution methodology (46) with minor modification. S. aureus was
grown in 10 ml MHB-II overnight at 37°C with shaking, then diluted 1:100 in fresh MHB-II and grown
to OD = 0.2-0.4. Cultures were then diluted 1:10 and grown to OD = 0.2-0.4. These steps were
performed to ensure balanced growth of cultures as explained. Finally, dilutions was made to 1 x 106
Colony Forming Units (CFU)/ml, and further diluted 1:1 in microtiter plates in MHB-II + drug,
leading to a final inoculum of 5 x 105 CFU/ml. MIC`s were determined in triplicates, if more than one
value was found, the highest was set as the MIC to be conservative.
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Time kill assay
Time kill assays were performed as previously described (47). Minor changes were made in the
protocol, since we wanted to analyse time kill responses in both exponential and stationary phase
cultures. Exponential cultures of USA300 grown at 37°C and drugs were tested at OD600 = 0.4 and
stationary phase cultures were defined as overnight cultures grown at 37°C with shaking and with a
growth period of 16 hours prior to addition of drug. Counting of CFU were performed by spot plating
of 10 µl culture. The supernatant was removed by centrifugation and pellet resuspended in PBS before
series of 10 fold dilutions. Time point 24 hours was performed by pelleting 250 µl of culture, and
resuspending in 100 µl PBS before plating of the whole sample, for some treatment groups.
Injection assay
Injection assays was performed as previously described (33) using a nanoject-II microinjecter, but with
minor modification in preparation of bacterial inoculum to obtain balanced cultures as explained. Flies
were reared on standard bloomington formulation at 25°C under a 12:12 light:dark cycle and constant
humidity. Only adult male flies (Oregon genotype) 4-7 days old were used for injection experiments.
Initial experiments with strain 8325-4 were performed in duplicates with groups of 25-30 animals in
each experiment. For USA300 experiments were performed in triplicates (nisin only in doublicates). S.
aureus inoculum was prepared as balanced exponentially growing cultures. Inoculum was prepared by
resuspending cells in 10 mM MgSO4 at an OD600 = 0.06 and kept on ice, giving an inoculum dose of
100-400 CFU (8325-4) and 250-700 CFU (USA300) in the flies after injecting 18.4 nl. Bacterial
injections were administered in soft tissue surrounding the front legs, drug treatment was administered
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in the lower thorax. After injection of bacteria, flies were kept at 29°C and followed for 48-96 hours to
determine mortality. Drug delivery was performed 3 hours post infection in all animals, at the
concentrations indicated for individual experiments. Flies which died within 3 hours of injection, were
considered to have died from handling and disregarded. It is important to note that when drug
concentrations were calculated, we performed a rough approximation of the fluid content of a fly. Fly
fluid content was measured by drying out 10 groups of 50 flies and comparing dry weight to wet
weight. This resulted in an average fluid content of 0.58 µl per adult fly. For simplicity and because we
assumed that the compounds would not distribute to all fluids we used 0.5 µl fluid as our measure for
calculating drug concentrations in the flies. Further we assumed rapid distribution of the compound in
the open circulatory system of Drosophila and a slow clearance of the compounds by malphigian
tubules. Therefore antimicrobial drug concentrations are given as the highest concentration obtained in
multiples of the MIC.
Statistics and graphical Plots:
Plotting of data was performed using GraphPad Prism 5. All in vivo survival plots were performed
using Caplan Meier analysis on pooled data for repetitive experiments. Statistical analysis was carried
out with GraphPad Prism 5 build in Log-Rank (Mantel cox) Test for comparison of survival curves.
Experiments with p values < 0.05 was considered significant.
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RNA preparation and quantitative PCR:
Isolation of total RNA for quantitative PCR was prepared by the use of RNeasy Mini Kit (Qiagen)
according to manufacturer’s instructions. Biological samples were collected as 10 adult male flies
pooled for each replicate and time point. To reduce contamination with genomic DNA, all samples
were treated on-column with DNase. Total RNA concentrations were measures on a Qubit™ 3.0
fluorometer and equivalent amounts of RNA was used for cDNA synthesis for each sample. cDNA
synthesis was performed using the SuperScript III First-Strand Synthesis kit (Invitrogen) kit according
to manufacturer’s instructions. qPCR was performed on a Mx3000P qPCR System (Agilent
Technologies) platform using the following program; 95°C for10 min, followed by 45 cycles of 95°C
for 15 sec, 60°C for 15 sec and 72°C for 15 sec. Dissociation curve analysis was applied to all
reactions. Primers are described in the supplemental material (Table S1). We used Rpl23 as
housekeeping gene while performing the assay to normalize expression as previously described (48).
Compounds
Ampicillin sodium salt 99% (ROTH Art-Nr: K029.2 EG-Nr: 2007081) was used as control for efficacy
and toxicity in in vitro and in vivo experiments. Vancomycin was acquired from Hospira as
vancomycin hydrocloride for intravenous treatment (lot# 467918E01). The peptides GN-2, GN-4
HHC-9 and HHC-36 all amidated in C-terminus, nisin A and peptoids were above 95% purity and
synthesized in the lab of Håvard Jenssen, Roskilde University Denmark. NAI-107 is a complex of
congeners produced by Microbispora sp. 107891 and was prepared as previously described (49). The
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distribution of congeners for the batch used in the curent study was as follows: A1+A2 = 80.8%, F1+F2
= 9.4%, B1+B2 = 4.
Results
Determination of the growth of S. aureus in vitro and in vivo in a Drosophila infection model
We determined the growth rate of the S. aureus strains 8325-4 and MRSA USA300 in cation adjusted
Müller Hinton Broth (MHB-II) media at 29°C, because all successive in vivo experiments were
performed at this temperature. Strain 8325-4 had a generation time of 57 minutes while USA300 had a
generation time of 44 min. The in vivo growth rate of the same strains was determined by injection of
bacteria into the flies at time 0 and samples were collected between time 0-3, 4-6 and 12 hours post
infection (Fig. 1A). Three flies were crushed and serial dilutions were made in PBS, before plating on
S. aureus selective mannitol salt agar (MSA) to determine the number of colony forming units (CFU).
USA300 had a generation time of 54 minutes, whereas 8325-4 had a generation time of 104 minutes in
vivo. Drosophila infected with USA300 died rapidly with no surviving flies after 24 hrs. Whereas flies
infected with approximately the same number of 8325-4 lived significantly longer (Fig. 1B). We
suggest that these differences in viability reflect the different in vivo growth rates of USA300 and
8325-4 bacteria.
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Figure 1. In vivo growth rate and killing of flies by the two isolates: A. in vivo growth rate USA300 = 54 min,
8325-4 = 104 min clearly demonstrate difference in proliferation. B. USA300 kills close to 100% within 24
hours, while isolate 8325-4 kills approximately 50% within 24 hours (p < 0.0001). Slight differences are
observed in starting inoculum (see materials and methods). Survival data are compiled results from all in vivo
experiments presented in figures 2 and 5.
Minimum inhibitory concentrations for antimicrobial peptides and peptoids
We determined the minimal inhibitory concentrations (MIC; Table 1) for the two strains. The MIC
values for S. aureus 8325-4 of amphipathic cationic peptides GN-2, GN-4, HHC-9 and HHC-36 and
the Lantibiotic nisin were in the range of 4-10 µg/ml, while those of GN-2 and GN-4 peptoids were
higher (16-64 µg/ml). On the other hand, the MIC of NAI-107 against strain 8325-4 was only 0.06
µg/ml, showing that NAI-107 is highly efficient in inhibiting in vitro growth of S. aureus. The MIC of
NAI-107 for S. aureus USA300 was lower compared to vancomycin when determined as molar
concentrations (0.11µM versus 1.38 µM; Table 1).
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Table 1. Minimum inhibitory concentrations (MICs) of compounds tested: The molecular weight used for
calculating μM concentrations are given in the table, as well as MICs for the compounds in both μg/ml and μM.
MIC for some compounds was not performed on both isolates (Na). Sequences of nisin and NAI-107 are not
included as they contain ring structures making a linear sequence misleading.
Identification of nisin and NAI-107 as efficacious treatment for systemic S. aureus infections in a
Drosophila in vivo model
To evaluate the therapeutic potential of the antimicrobial peptides and peptoids, we determined their
ability to rescue flies with an otherwise lethal systemic S. aureus 8325-4 infection. In order to establish
the appropriate dosages, we made the following reasoning: Because insects are known to have an open
circulatory system, we assumed that the administered compound would be rapidly and uniformly
distributed in the hemolymph of the fly. This was determined to be 0.5 µl (see Materials and Methods)
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and we also assumed that compound elimination through the Malpighian tubules proceeds slowly.
Under these assumptions, the highest concentration achieved for each compound can be expressed as
multiples of the MIC. For example 1xMIC nisin [10µg/ml] is equivalent to injection of 2.5 mg nisin/kg
fly; this numbers for all drugs can be seen in (Table 2). Ampicillin was chosen as control, as β-lactams
in general are considered nontoxic to the host and can be administered in high concentrations, in our
case >1000xMIC. Ampicillin efficiently promoted survival of 8325-4 infected flies (p<0.001; Fig. 2A)
when monitoring over a 70 hours period and with no detrimental lethal effects to control animals (p =
0.15); here defined as no difference in survival when comparing flies injected with 10 mM. MgSO4 to
those injected with both MgSO4 and drug.
Table 2. Antimicrobial peptide dosages: We calculated the concentration of compound injected in
mg/kg Fly, based on the data in table 2. All data presented are based on 1xMIC of the compounds.
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The two lantibiotics NAI-107 and nisin showed good efficacy in effectively rescuing or delaying
mortality of infected flies over a 96 hours period (Fig. 2 B and C). NAI-107 at 1xMIC had no positive
effect survival of the flies (Fig. 2B) and the same was found for 3xMIC (not shown). Treatment with
10xMIC of NAI-107 rescued around 20-30% of flies (p<0.001) and with no difference in the survival
of control animals (p = 0.62; not shown). We therefore tested NAI-107 at 100xMIC, and this
concentration rescued more than 70% (p < 0.0001) of the infected flies, without lethal effects to
controls (p = 0.62; Fig. 2B). Compared to NAI-107, nisin showed a difference in both efficacy and
lethality to control animals. While 1xMIC nisin delayed bacterial killing of flies (p<0.001), it produced
signs of lethal side effects (p = 0.018; Fig. 2C). Higher concentrations of 3xMIC nisin also rescued a
considerable fraction of infected animals (p = 0.0002; not shown), but showed pronounced detrimental
effects to control animals (p = 0.0056). These adverse effects were exacerbated when using 10xMIC
nisin, which resulted in the killing of 50% of control animals injected with nisin alone (p<0.0001; Fig.
2C) and also resulted in increased mortality of infected flies. Therefore, nisin was not tested at
100xMIC.
In contrast to NAI-107 and nisin, the GN-4 peptide, which possesses good in vitro efficacy against S.
aureus [Table 1; (41)], did not rescue infected flies at 1x and 3xMIC (p>0.005; Fig. 2D). When applied
at 10xMIC, GN-4 showed no adverse effects to the survival of control flies. However, the results
indicate that administration of this peptide to animals infected with bacteria may reduce the survival
because a higher number of the animals treated with the peptide after infection died, although this was
not statistically significant. The GN-4 peptoid showed pronounced detrimental side effects even at
1xMIC (Fig. 2E) therefore the peptoids were abandoned after a single experiment. The GN-2 peptide
had similar effect to that of the GN-4 peptide (supplemental data Fig. S1) and the two GN-2 peptoids
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(supplemental Fig. S2 and S3) clearly showed lethalk effects in both control and infected animals.
Injection of peptides HHC-9 and HHC-36 in the absence of infection caused no obvious side effects,
while treatment with these peptides did not rescue infected flies (supplemental Fig. S4 and S5
respectively), but they caused a moderate decrease in survival of infected flies that may indicate
detrimental effects of peptides, although the results were somewhat ambiguous.
We also noted adverse behavioral response that could be indicating neurotoxicity in flies injected with
high concentrations of nisin, GN-2 and GN-4 along with the peptoids, but not for NAI-107. Animals
reacted to injection with these compounds by being partially paralyzed for up to 10 hours post injection
(not shown). This paralysis was not manifested as complete immobilization but as uncoordinated
movements and an inability to walk or fly.
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Figure 2. In vivo efficacy of compounds against S. aureus 8325-4 in a Drosophila whole-animal
model: Graphs show survival of flies treated with subset of peptides. Y-axis show fraction survival
compared to time in Hours (x-axis). Flies were counted at time points 0, 3, 6, 12, 24, 48 – 120 hours.
The individual figure legends indicate the treatment groups: Flies are either injected with MgSO4 or
isolate 8325-4 at time 0, the + indicate treatment at time point 3 hours (dotted line). Flies were counted
prior to injection with compound. Compound concentrations [C] are given as approximated
concentration in animals.
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Treatment with nisin and NAI-107 reduces the immune response of S. aureus infected D.
melanogaster
To further test drug efficacy of the two lantibiotics nisin and NAI-107 in vivo, we examined the
immune response of both treated and non-treated infected animals. We rationalized that infected
animals treated with these compounds would mount less of an immune response provided that bacterial
proliferation in the host was inhibited. To test this we used flies infected with S. aureus strain 8325-4.
We applied NAI-107 (100xMIC) while nisin due to its adverse effects was only applied at 3xMIC.
Samples in triplicate were taken at 6 and 12 hours post infection and processed as described in
Materials and methods. Oregon flies not exposed to infection with S. aureus served as control. As a
measure of immune response we analyzed expression of Drosomycin (Drs), Cecropin A1 (CecA1) and
Attacin-B (AttB) genes, which have all been implicated in the immune response of Drosophila to
infection by Gram-positive bacteria (50, 51). In general we observed that animals that received any
form of treatment had elevated transcription of immune response genes (Fig. 3), this is most likely
because any injection into the body of the flies, damages the tissue thereby elevating the immune
response. Further, it is highly plausible that injection of any protein like structure will elicit some
degree of immune response. Another general observation was a higher expression level of immune
responsive genes in infected untreated animals compared to animals treated with nisin and NAI-107
(Fig. 3).
The response of the three immune response genes differed. Drosomycin expression increased 30-180fold within 6 hours post infection and remained at that level at 12 hours (Fig 3A). Treatment with NAI107 and nisin decreased Drs expression approximately 10-fold relative to non-treated infected flies
after 12 hours (Fig. 3A). Expression of Cecropin A1 followed the same pattern as observed for Drs
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except that maximal induction was only around 20-fold (Fig. 3B). The attacin B expression level was
different. Gene expression was increased considerately in all flies injected with peptides and
irrespective of a concurrent S. aureus infection (Fig. 3C). Because injection with MgSO4 did not result
in the same fold increase of attB induction (Fig. 3C) we conclude that the attB gene is initially induced
by either the pathogen or the administered peptides. The S. aureus infection further increased attB
expression to more than 1000-fold relative to the control at 12 hours. Concurrent administration of
nisin or NAI-107 reduced expression to the level observed for the peptides alone or even below (Fig.
3C).
Some compounds, including nisin, have previously been associated with immunomodulatory actions in
mice (52). Consistent with this, we observed a moderate elevation in the expression of Drosomycin,
Cecropin A1 and Attacin B in flies injected with nisin compared to MgSO4 injected control flies.
However, whether this is due to true immunomodulatory action or because of the observed toxicity is
unclear.
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Figure 3. Induction of immune pathway genes in animals infected with S. aureus 8325-4: (A)
Drosomycin. (B) Cecropin A1 (C) Attacin B were used as read out AMP genes for verification of
efficacy of compounds able to rescue/prolong infection. Ribosomal protein L23 was used as reference
gene. A non-infected control was used as reference of normal expression; these values were set as 1.
Flies infected with S. aureus 8325-4 were sampled for qPCR, 6 and 12 hours post infection. Drug
treatment was performed at 3 hours and injection of MgSO4 was used as control injection fluid.
NAI-107 kills non growing MRSA strain USA300 in vitro
After initial experiments with S. aureus strain 8325-4, we chose to test the kill-rate efficiency of the
two lantibiotics along with vancomycin against MRSA strain USA300 (36, 53). We performed time kill
experiments on exponentially growing and non-growing stationary phase USA300 cells (Fig. 4). We
tested both nisin and NAI-107 at 1x, 3x, and 10xMIC, and included NAI-107 at 100xMIC. Nisin was
not tested at higher concentrations than 10xMIC, because we had already shown Nisin to be
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detrimental to animals at much lower levels. As control we included vancomycin in these experiments.
Treatment of exponentially growing cells (Fig. 4A) with vancomycin, showed that concentrations from
3xMIC to 10xMIC reduced the viable cell count in CFU/ml from 1*108 to 1*106 (2 log`s) within the
first 5 hours of treatment. When applying vancomycin at 10xMIC the response was more rapid and
resulted in a further decrease in CFU/ml to 1*104-1*103 (Fig. 4A). When treating exponentially
growing cells with NAI-107 10xMIC reduced CFU/ml by 3 log`s within the first 5 hours (Fig. 4C),
with a further slight decrease in CFU/ml over the next 19 hours. When applying a concentration of
100xMIC the response was more rapid, with a drop in CFU/ml of more than 6 log`s within 5 hours.
Because 100xMIC of NAI-107 is equimolar to 10xMIC vancomycin (Table 1), this demonstrates that
NAI-107 is equally or more efficient than vancomycin in killing USA300 in vitro. Treatment of
exponentially growing cells with nisin 3xMIC reduced viable counts by 4 log`s (Fig. 4E) and 10xMIC
nisin reduced viable cell count below detection. However, nisin treated cells re-grew and by 24 hours
the 10xMIC treated culture was at 1*104 CFU/ml. At 1xMIC none of the tested compounds were able
to reduce viable cell counts.
Next, we tested the compounds ability to kill stationary phase bacteria. NAI-107 at 100xMIC
efficiently killed the majority of the culture within 5 hours of treatment, i.e. the CFU count was reduced
from 1*1010 to 1*102 CFU/ml, and remained at that level until 24 hours (Fig. 4D). Nisin at 10xMIC
was somewhat less efficient and the CFU count was reduced 6 logs from 1*1010 to 1*104 CFU/ml
within the first 5 hours of treatment (Fig 4 F). However, as observed for exponentially growing cells,
the nisin treated stationary phase cells re-grew by 24 hours (Fig. 4F). Nisin was not tested at higher
concentrations due to the aforementioned lethal effects. Overall these data show NAI-107`s capability
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to kill the cell regardless of growth state. This is in contrast to vancomycin (Fig. 4B), which at
equimolar concentrations to NAI-107 is unable to effectively kill non growing cells.
Figure 4. In vitro kill rate experiments against USA300: (A-B) vancomycin, (CD) NAI-107 and (EF) Nisin treated exponential phase (A, C, E) and stationary phase cultures (B, D, F). Cell counts are
given as log transformed colony forming units per ml (CFU), plotted against time in hours (x-axis).
Right hand figure legends show control group USA300 or USA300 treated with compound at the given
concentration [C]. Dotted line indicates the lower detection limit.
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NAI-107 effeciently rescues flies from infection with USA300
We proceeded to evaluate the in vivo efficacy of lantibiotics relative to vancomycin in Drosophila
infected with USA300 (Fig. 5). Flies were treated with nisin at 1xMIC, and 10xMIC assuming liquid
content of a fly beeing approximately 0.5µl (for details see materials and methods). Although nisin did
not rescue flies over the duration of the experiment, it did delay mortality by doubling the mean
survival time (p < 0.0001) at both concentrations tested (Fig. 5A). However, mortality was increased in
the control group injected with 10xMIC relative to the MgSO4 injected control (p = 0.0008; Fig 5A). A
single dose of 100xMIC NAI-107 rescued 50-60% of USA300-infected animals over a 96 hours period
(p<0.0001), equivalent to the survival found for vancomycin treatment in equimolar concentrations, i.e.
10xMIC (p = 0.94; Fig. 5B). Positive effects on the survival of USA300 infected animals, were also
found at dosages of NAI-107 as low as 3xMIC (p<0.0001; Fig. S6). Similar to NAI-107, vancomycin
showed no adverse effect at the concentrations tested here (Fig. 5B). Taken toghether these results
demonstrate that NAI-107 delay killing of D. melanogaster by systemic USA300 infections with an
efficiency similar to vancomycin and with no apparent adverse effects. This highlights the potential of
NAI-107 as a candidate for systemically administered application.
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Figure 5. Efficacy of Nisin and Nai-107 in vivo against USA300: (A) Nisin prolonged the lifespan at all
concentrations (B) NAI-107 rescues 50-60% of flies at 100xMIC (p<0.001), comparison of vancomycin with
NAI-107 produced no difference in the response between the drugs (p=0.94). Antibiotics are injected at time 3
hours post infection (dotted line).
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Discussion
We have used Drosophila melanogaster as a model organism for testing the efficacy and adverse
effects of antimicrobial peptides. We examined several cationic antimicrobial peptides previously
reported to have either in vitro or in vivo efficacy against S. aureus. Furthermore, the two lantibiotics
nisin and NAI-107 were included. We found that both lantibiotics, can delay or even rescue lethal
injections with wild type S. aureus 8325-4 isolate, but more importantly also the MRSA USA300
isolate.
Amphipathic peptides
None of the cationic amphipathic peptides previously tested in vitro and/or in vivo against both gramnegative and gram-positive bacteria (41) had any positive effect on the survival of S. aureus infected
flies. These peptides are believed to work through pore formation, thereby disrupting the integrity of
the bacterial membrane(s). Although this does not exclude the possibility that peptides may be effective
in mammalian models, our data do not support their use in whole-animal infections. There were
indications that the GN peptides even had negative effects on survival of infected flies. Suprisingly, the
peptoids based on GN peptides were highly detrimental to animals. The explanation for this, could be
ascribed to the peptoids having high MIC, and therefore had to be injected in higher concentrations
compared to native compounds to reach the same integer of MIC. Consistent with our findings, adverse
effects for most of the compounds in the >100 µg/ml range have previously been reported from cell
based assays (45). Two of the cationic amphipatic peptides tested here, HHC-9 and HHC-36, had
marked negative effect on the survival of infected flies. This contradicts previous data in which HHC-
107
36 was found to have in vivo efficacy against S. aureus in a well-established mouse intra-peritoneal
model (44). Although we expected the HHC compounds to be able to clear or delay infection in
Drosophila, our results indicate that they are detrimental to flies when injected at high concentrations.
The number of experiments performed previously for the HHC peptides, especially in vivo, are limited,
which makes it difficult to explain the differences observed in the two infection models. One main
difference is, however, that both bacteria and peptides are delivered systemically into circulation in the
Drosophila infection model, while both bacteria and peptides are injected into the body cavity in the
intra-peritoneal mouse model. It is not clear wether the peptides enter circulation in the mouse to the
same extent as bacteria does, and this could skew data obtained through counting of colony forming
units in peritoneal fluid only. However, we argue that injection of peptides into the hemocoel of a fly
provides access to more diverse tissues due to the fly physiology beeing less compartmentalized, which
could be a reason for the differences seen in adverse effects. Adverse effects should not be considered
as a definite rejection of compounds, since they can be used for further structure relationship studies
and development of better compounds. Despite our data arguing that the potential of several of these
compounds for systemic use are limited, these compounds may be further developed into topical usage,
as is the case for the systemically toxic peptide antibiotic bacitracin, which has been highly successful
in topical ointments (54, 55).
Lantibiotics
Lantibiotics remain of interest for development of new therapeutics. Nisin is one of the best studied
lantibiotics (19) and has recently gained new interest as a therapeutic since it was proven effective
108
against MRSA (56, 57). A newly discovered lantibiotic interesting for clinical development is NAI-107
(38). It is currently undergoing preclinical studies, and it has already proven effective in vivo against
multi-drug resistant S. aureus (39, 58).
Our results reinforces the notion that nisin may have therapeutic potential in clinical settings, although
systemic application seems limited due the observed lethality. In our Drosophila model, nisin is
detrimental even at relatively low concentrations, which contrasts previous in vivo findings from rats
(59). However, our study utilizes injection into the circulatory system of whole animals, while the
Reddy et al. study utilized administration through oral dosing, inevitably changing the bioavailability
of a compound (60). Despite the apparent side effects to flies, a single injection of nisin delays death
due to infection in doses equivalent to the MIC of the compound, demonstrating in vivo efficacy at low
doses, which may be improved by multiple dosing. Therefore, further studies are needed to address the
intricate interactions of nisin with eukaryotic cell systems. Although the bacterial target of nisin has
been characterized (22, 61, 62), the interplay of nisin with other molecules of eukaryotic cells remain
poorly understood. Perhaps nisin, because of its poor bioavailability and fast degradation (63), could be
modified chemically to address these issues (19, 64), and in this context it would be of importance to
know more about adverse effects.
Due to the low MIC of NAI-107 to S. aureus, we expected good in vivo efficacy at low doses of the
compound. However, NAI-107 only seemed to delay infection at doses around 10xMIC. Higher doses
of NAI-107, however, resulted in remarkable in vivo efficacy with no signs of detrimental side effects.
This is in accordance with previous findings that the effects of NAI-107 is concentration dependent
(58). Further, it should be acknowledged that low MIC in in vitro experiments not necessarily translates
into the same efficiencies in vivo, since pharmacodynamics and kinetics come into play.
109
Nisin was clearly less potent than NAI-107, although they both bind to lipid-II (65) and rapidly kill
bacteria. Nisin has been described to work through disruption of cell wall synthesis and pore formation,
by binding to Lipid-II (20, 21, 61), although new evidense points to nisin working through aggregation
of Lipid-II in the membrane (23). Evidence also points towards NAI-107 having a dual mode of action
through binding to the Lipid-II cell wall precursor and destabilizing membrane integrity but also
interfering with protein localization and promoting disorganization in the cell (65). Our in vitro data
support the findings that the two compounds mode of action differ; Nisin rapidly kills exponentially
growing cultures, whereas NAI-107 has a prolonged, but lower initial effect in vitro. Furthermore, in
vitro treated nisin cultures re-grow by 24 hours, which fits with the in vivo data that nisin only doubles
the life expectansy of infected flies. Nisin`s aparent side effects may be due to it`s ability to create
pores by non-specific interaction with membranes (66), which could mean that it will do so in
eukaryotic membranes as well. Our in vitro and in vivo data support that NAI-107 can be applied in
concentrations where it not only effectively kills growing bacteria, but also might prove efficient
against persistent non growing bacteria.
In conclusion, we provide evidence for the use of Drosophila as a model for in vivo efficacy testing of
antimicrobial peptides. We have clearly shown, that infected animals can be rescued by treatment with
certain antimicrobial peptides. Further, we have demonstrated Drosophila as a putative model for
assessing adverse effects of antimicrobial peptides. The Drosophila model presented here was adapted
from previously developed methodologies (33, 67) to provide researchers with a relativly cheap method
for efficacy evaluation of lead compound antimicrobials discovered through more appropriate drug
screens. To the best of our knowledge Drosophila has not previously been used for the testing of
antimicrobial peptide efficacy and toxicity. Drosophila does not allow for high throughput screening of
110
large drug libraries by injection, as this procedure is relatively labor intensive, compared to drug
screening methodologies developed in the worm Caenorhabditis elegans (68), but our method is
applicable to lead compounds discovered following such screens. Therefore, as an initial model for
efficacy testing of lead compounds Drosophila could prove interesting for further analysis, especially
regarding it as whole-animal model for toxicity screening, as classical toxicity screens usually involve
hemolysis and metabolic cell based assays performed on imortalized cell lines.
Between the compounds tested by us, the lantibiotic NAI-107 was superior to Nisin, but equivalent to
vancomycin. Nai-107`s ability to kill non growing bacteria is to our knowledge the first time this has
been reported for this particular lantibiotic.
Acknowledgements
This work was supported by the Danish Council for Independent Research | Technology and
Production Sciences (FTP) grant 11-106387 to Professor Anders Løbner-Olesen. The research was also
partially supported by the European Community's Seventh Framework Programme (FP7/2007-2013)
under grant agreement N°289285 held by Stefano Donadio and partially funded by The Federation of
European Microbiological Societies under grant agreement IT-SIMGBM2014-1. J.C.S.C. supported by
grant agreement N°289285 and IT-SIMGBM2014-1 held by João S. C. Cruz.
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Supplemental Material
Supplemental Figure 1. In vivo efficacy of peptides and peptoids: Graphs show survival of flies treated with
GN-2 (S1), GN-2 peptoids (S2 and S3), HHC-9 (S4), HHC-36 (S5) and NAI-107 (S6). Y-axis show fraction
survival compared to time in Hours (x-axis). Flies were counted at time points 0, 3, 6, 12, 24, 48 – 120 hours.
Right side figure legends represent treatment groups: Flies are injected with MgSO4, bacterial isolate 8325-4 or
USA300 at time 0, + indicate peptide/peptoid treatment at time point 3 hours (dotted line). Compound
concentrations [C] are given as approximated concentration in animals.
116
Table S1. Primer sequences: Forward (FW) and Reverse (RV) primers are shown in right column. Gene
annotations as CG numbers are indicated, according to flybase.org.
117
Discussion
Important pathogens from the ESKAPE group, pose an eminent and growing problem
globally. Resistance to colistin the last resort drug for serious Gram-negative infections has been
found in A. baumannii and K. pneumoniae caused by LPS modifications through mutation (107,
109, 110, 114, 252). However, the discovery of horizontally transferrable genetic element carrying
the mcr-1 gene in E. coli seriously jeopardizes future treatment with colistin (118). Furthermore,
evidence of failure to the important antibiotics vancomycin, linezolid and daptomycin is increasing
in the important Gram-positive bacteria E. Faecalis and S. aureus (67, 69, 74, 77, 84, 85).
Bacteriocins and host defense peptides are widespread and universally spread throughout nature as
part of organisms defenses against invading microorganisms (122). For these reasons antimicrobial
peptides are of interest for the development of the next generation of novel antibiotics.
Amphiphilic cationic peptides and peptoids
We have applied solid phase synthesis to develop the BP214 peptide into a lead
candidate with some promising characteristics in vitro (253). BP214 follow in the footsteps of other
Cecropin-mellitin hybrid molecules that effectively kill colistin resistant strains of A. baumannii
(160, 254). Several such molecules have even been tested in the mouse peritoneal sepsis model with
some efficacy (161). The BP214 peptide was developed from BP100 (195) and RW-BP100 peptides
(193). By analytical and combinatorial approach we developed a panel of lead compounds with
characteristic from both peptides (253). The BP214 peptide proved highly effective in killing
colistin resistant A. baumannii. Interestingly BP214 selectively kills non-growing colistin resistant
A. baumannii, while unable to kill non-growing wild type cells. BP214 is able to kill all growing
cells, irrespective of genotype. Theoretically this could have a selective capability of the compound,
not previously seen i.e. BP214 will kill all colistin resistant A. baumannii while leaving persisters of
wild type origin. If this applies to other colistin resistant Gram-negative bacteria such as E. coli or
K. pneumoniae it is contemplated if this might lower detrimental side effects to the commensal
flora.
The spectrum of activity for BP214 is more broad than narrow, as it also has a fairly
low MIC towards E. faecium [Table 1 (253)]. However, the MIC towards S. aureus is significantly
118
higher. The overall broad spectrum of the BP214 cecropin-mellitin hybrid is comparable with
previous findings that cecropins target both Gram-positive and Gram-negative species (255) and
mellitin is non-selective in nature (256, 257) and other cecropin-mellitin hybrids share these
characteristic (193). Our data seems to be in line with this even after modifications of the molecule.
Regarding the toxicity of the compound, BP214 is relatively non-toxic as measured by hemolytic
ability. However, based on our own data indicating toxicity of cationic amphiphilic molecules using
the Drosophila in vivo efficacy model, it seems likely that BP214 could be toxic to eukaryotic cells.
Other cecropin-mellitin hybrids have been reported to have relatively high hemolytic ability on
mouse blood cells (161).
In vivo efficacy of antimicrobial peptides is generally hampered by the in vivo
sequestration by blood serum and proteolytic degradation by proteases (161, 187, 201). In this
regard it is of high interest that BP214 consists of only D-amino acids that retain antimicrobial
activity while displaying low hemolytic ability (253). The D-amino acids should render the molecule
less prone to degradation (200, 258) thereby expanding a possible application to include oral
therapy. These same features are apparent for molecules such as the circular antimicrobial peptides
described in paper II, which were modulated to retain activity, while lowering toxicity in hemolytic
ability. With respect to sequestration by serum this remains to be discovered, but it seems plausible
that this issue would have to be addressed for further development.
It has previously been argued that synthetic compounds could be expected to slow
development of resistance (74). This might be further accommodated by the incorporation of Damino acids. As BP214 is active against A. baumannii resistant to colistin through PmrA-PmrB
mutations and loss of LPS, it seems that these highly relevant mechanisms for bacterial resistance
towards cationic molecules have been circumvented. However, it would be of interest to examine
whether the changes to the LPS in K. pneumoniae due to PhoP-PhoQ mutations associated with
increased resistance to antimicrobial peptides such as colistin, have the same impact on activity of
BP214 (110). On the negative side; BP214`s relative broad spectrum activity, but low activity to S.
aureus, might cross select for resistance genotypes such as the VISA strains or strains with
dysfunctional expression of MprF and the dlt operon (84-86, 259, 260) as these changes relate to
changes in membrane charge. The broad spectrum AMP bacitracin has been associated with
selection of highly resistant MRSA strains (261). Circular peptides as described in Paper II, with
119
efficacy towards Gram-positive bacteria such as VRE, could possibly have similar effect on
selection of Gram-positive bacteria, but because of the narrow spectrum, would most likely not
select for resistant Gram-negative bacteria.
With respect to the amphiphilic and cationic peptides and peptoids developed against
S. aureus. Previous studies reported low toxicity in cell based assays and in mouse peritoneal model
(197, 262). We find clear and not fully understood differences with regard to toxicity. As explained
we believe that some of our findings indicate neurotoxic effects, these would not necessarily have
been seen in the HeLa cell based assays (197). Since we do not know anything about
pharmacokinetics and pharmacodynamics of HHC peptides in the mouse peritoneal model (262),
we speculate that the peptides do not leave the peritoneum and enter circulation in this model
leaving toxicities unobserved. There is also the possibility that the Drosophila model described is
hyper sensitive to toxic effects, as the Drosophila circulatory system is less compartmentalized.
However, a whole animal model, intuitively encompass a more realistic physiological environment
and more complexity than cell based assays. This reasoning is based on the fact that the whole
animal model encompasses infection, host pathogen interaction and treatment in one. This is in line
with our findings that several already proven antimicrobials are non-toxic in this model (NAi-107,
vancomycin and ampicillin). Further, the peptides and peptoids are toxic, but only when injected
after infection which would by left undescribed in most cell based assays where cells are subjected
to peptides but without any pathogen interaction. Peptides might not interfere with cell viability, but
stress the cells or otherwise interfere with important cellular functions. The phenotypes described
regarding possible neurotoxicity, certainly imply that several compounds interfere with neuronal
physiology. We speculate if this could be because of the molecules general electrostatic interaction
with membranes.
Lipid-II targeting peptides
In paper III we have shown that the two Lantibiotics nisin and NAI-107 targeting the
peptidoglycan cell wall precursor Lipid II can rescue or postpone lethality of USA300 infection in a
Drosophila in vivo efficacy model. Nisin has previously been reported as non-toxic (144, 157) but
has been tested limited in vivo. One experiments showed that nisin A was unable to control
120
infection by L. monocytogenes while nisin V showed efficacy (263). Campion et al (263) described
reoccurrence of bacteria after treatment with nisin A, which is in line with our data that nisin A is
unable to rescue infection and only prolong survival. Further this is underlined by in vitro
experiments showing re-growth of nisin treated bacterial cultures. NAI-107 was shown to have
prolonged effect in vitro and in vivo, in line with previous studies, showing prolonged post
antibiotic effects in vivo (264). NAI-107 also rescued animals from infection without any observed
detrimental effects, consistent with observations by Lepak et al. demonstrating no toxicity in a
murine thigh infection model (264). In the study by Lepak et al. NAI-107 was injected at doses
ranging from 5 to 80 mg/kg, our maximum dose of NAI-107 was 16 mg/kg well within this range
and the low toxicity is comparable. NAI-107 has been found superior to several reference
compounds including vancomycin (265), contradicting our data. However, our experiments only
included injection of a single dose of each compound. The previously reported superiority might be
explained by the ability of NAI-107 to kill non-growing cells, but this will have to be further
explored. Further the Jabes et al study showed that a single dose of NAI-107 (40mg/kg) prevented
regrowth over 96 hours (265). Our data for NAI-107 in the Drosophila model seems to support
these findings, but because we used lower doses this might explain why we did not rescue all
animals. Finally, we showed that both nisin and NAI-107 has the capability of effectively killing
stationary phase cultures of S. aureus, emphasizing yet another potential for these lantibiotics. Since
this property is not found for many widely used antibiotics such as vancomycin and β-lactams it
could pose as an important characteristic against persistent infections. Several Lipid II targeting
compounds, like NAI-107 are of growing interest as the next generation of antimicrobials for
clinical therapy (137). Like the newly discovered teixobactin (158), NAI-107 efficiently kills highly
drug resistant strains such as MRSA and VRE (265). The killing of stationary phase cultures has not
been reported for teixobactin, although it might have been tested.
Nisin has been shown to be rapidly degraded by pancreatic proteases through oral
administration (144, 157). This could indicate that it would be sensitive to other proteases as well.
Indeed nisin has been shown to be degradable by aureolysin (187). So far no protease capable of
degrading NAI-107 has been found, but elevated MIC has been found for VISA and VRSA
(personal communication with Stefano Donadio). Nisin resistance in S. aureus has been described
as
D-alanylation
of techoic acids by changing expression or copy number of the dlt operon,
production of L-PG by MprF, upregulation of the BraRS two-component system and similar
121
systems (266-268). Generally the overall picture is that lantibiotic resistance is accommodated
through changes in the cell membrane architecture (266). These mechanisms are in many aspects
parallel to resistance mechanism to peptides acting on the cell wall of Gram-negative bacteria such
as colistin (108-110, 112, 113, 182, 252). We expect that similar mechanisms might be found for
NAI-107, but to our knowledge this has not been described. Furthermore, the resistance profiles
found for lantibiotics such as nisin emphasizes the possibility of lantibiotics selecting for cross
resistance to antibiotics such as daptomycin in Gram-positive bacteria. Although NAI-107 has been
shown to have activity against some Gram-negative bacteria (265), most lantibiotics are not active
against Gram-negative bacteria because of their outer membrane (138, 139). Therefore, cross
selection of resistance seems unlikely. However, given the historical evidence of drug resistance
development, it would be wise not to underestimate such development.
Interestingly we have also found that NAI-107 has activity against LPS deficient (108,
109) strains of A. baumannii (unpublished data), and that NAI-107 in combination with colistin has
synergistic effects against A. baumannii (unpublished data). This is consistent with observations of
Cui et al. demonstrating that vancomycin in combination with colistin have synergistic effects
against carbapenem resistant A. baumannii (269). This is most likely due to colistin permeabilizing
and accommodating penetrance of vancomycin/NAI-107 through the outer membrane, thereby
gaining access to the underlying peptidoglycan layer of Gram-negative bacteria. Although Gramnegative bacteria have slightly different composition of the pentapeptide on the peptidoglycan
precursor Lipid II, the D-ala-D-ala binding motif of vancomycin is the same [Figure 16 (24)]. This
opens for the possibility of combining these compounds to produce broad spectrum combination
treatments using colistin or perhaps similar compounds (e.g. BP214) in combination with Lipid II
targeting antimicrobials.
122
Figure 16. Lipid II of Gram-positive and Gram-negative bacteria: Adapted from (24, 235).
Overall composition of the peptidoglycan precursor Lipid II of Gram-positive and Gram-negative bacteria.
The Gram-positive bacilli have similar Lipid II to Gram-negative bacteria. The major difference between
Lipid II is the substitution of L-lys with meso-DAP in the pentapeptide (235).
A Drosophila in vivo efficacy model of infection
The Drosophila in vivo model presented in paper III has several benefits compared to
the tightly regulated and expensive mammalian models normally used (270). We have provided
evidence for the use of this model for analysis of efficacy and toxicity in vivo. Because in vivo
testing of many of the compounds has been limited, it is difficult to evaluate the results by
comparison to previous studies. Several of the discrepancies found will need further evaluation of
the model in comparison to established mammalian models. However, we do show that the two
lantibiotics in this model compare to previous findings from mice, both regarding toxicity and
efficacy of NAI-107. On the other hand, we do find nisin to be toxic, which was not found by
Campion et al. (263) when tested in mice. As already discussed all the amphipathic cationic
peptides and peptoids tested were not efficacious in this model and several proved lethal. At least
for the HHC36 peptide, this is different to previous findings from mice (262). However, to evaluate
systemic toxicity in mice, we argue that HHC36 should be injected into the circulatory system
instead of the peritoneum. As a whole animal model system Drosophila seems to encompass
several important aspects of antimicrobial drug testing, but the model suffers from one major
drawback. Because Drosophila has an ideal maximum temperature of 29°C, it does not
accommodate optimal bacterial growing temperature at 37°C which is encountered by human
pathogens in the body. Finally, it should be noted as previously discussed, that this model might be
123
more sensitive to toxic/lethal effects and therefore it should be used as an addition to other models
and not as an alternative.
Conclusions
Our data support previous findings of Lipid II acting molecules as good candidates for
clinical development. Importantly, we have shown that NAI-107 unlike vancomycin and other
important antibiotics has the ability to kill non-growing bacteria in vitro and at concentrations
comparable to doses tested in mice in vivo (264). Although NAI-107 already has been tested in vivo
with good efficacy, experiments with NAI-107 provided evidence of our Drosophila models
applicability and this adds to the growing evidence of NAI-107 as a lead molecule. Because of the
low cost of the Drosophila model, we have been able to experiment on large numbers of animals
and we have been able to reproduce the data several times. Our Drosophila experiments have also
shed light on possible problems with classical toxicity screenings using cell lines. We are not
arguing that the usage of cell lines should be disregarded in the developmental process; merrily we
are arguing that an intermediate in vivo model might be useful to antimicrobial development before
undertaking expensive and labor intensive in vivo experiments on mammalian models. Especially
since it seems that many previous peptides fail in clinical trials because of toxicity issues (202). It
has certainly been argued by others that compounds are often rushed into clinical development and
therefore fail in this process (20). Especially insect models such as the one presented here or the G.
mellonella model (211) could be combined with models such as the C. elegans model for large scale
drug screening (206) and toxicity evaluation. The larvae of Drosophila can also be grown in 96 well
based systems, which could be applicable to large scale screening as performed for C. elegans.
BP214 was shown to encompass several interesting characteristics such low hemolytic
ability and incorporation of D-amino acids while retaining activity against A. baumannii and to a
certain extent also E. coli and K. pneumoniae. Further, the evidence points to BP214 interacting
with the membrane via mechanisms that are not solely dependent on LPS. For this reason the
molecule retains its activity against LPS modified A. baumannii resistant to the last resort antibiotic
colistin. Finally, BP214 is capable of killing non-growing cells of colistin resistant A. baumannii,
implying that AMP resistance through LPS modification renders the cell more susceptible to certain
124
cell disrupting compounds like BP214 when in stationary phase. This discovery could be interesting
for future drug development.
125
Future perspectives
The cecropin-mellitin hybrid BP214
BP214 remains as an interesting candidate for further development. As we have only
scratched the surface of this cecropin-mellitin hybrid. The data presented in paper I, does provide
interesting and positive insight for further development of this molecule. It would be of interest to
continue working with BP214 as this molecule might give insight into future aspects of
antimicrobial peptide development. Especially since we are now experiencing what can only be
expected to be the beginning of colistin treatment failure (118). This discovery certainly adds to the
growing body of evidence that we could be moving towards a post-antibiotic era and for this reason
it is of huge importance to develop new antibiotics with novel applications.
We are hoping to undertake a larger project for further investigation of BP214 as a
lead candidate. We would like to do more structure activity analysis, to determine the optimal
length of BP214 by synthesis of C and N terminal truncated versions of the molecule. Furthermore,
alanine scanning or incorporation of non proteinogenic amino acids (including peptoids) could be
further explored for optimization. Addition of sidechain and the distribution of these could be
another means of creating molecules with improved characteristics. However, such work would
have to be in collaboration with other people such as Professor Paul Robert Hansen with whom we
have collaborated on paper I and II.
For BP214 to have wide applicability it would need to have activity against other
Gram-negative bacteria (E. coli, K. pneumoniae and P. aeruginosa). Such compound would also
have to undergo vigorous in vitro and in vivo toxicity and efficacy testing. This could be performed
using hemolysis and cell proliferation assays, but with the addition of the Drosophila or G.
mellonella models as intermediary in vivo platforms. It would be of high interest to include analysis
of BP214 having synergistic effects with molecules such as NAI-107 and vancomycin. Further, the
molecule might be optimized to kill non-growing cells regardless of genotype which might increase
its impact as a therapeutic option. If BP214 could be optimized to incorporate these characteristics
in a lead molecule it might be tested for in vivo efficacy on mammalian models such as the, mouse
126
peritoneal sepsis model (161). Further, the investigation of toxicity in both insect and a mammalian
model might explain some of the major differences found in paper III.
Because BP214 most likely interact with bacterial membranes through electrostatic
interactions and selectively kill non-growing colistin resistant A. baumannii, it seems that the
colistin resistance genotype causes collateral damage to the membrane when cells are in stationary
phase. Because it is often difficult to describe the interaction of AMP with membranes, it might be
possible to gain insight into these mechanisms through resistance development studies. By an
evolutionary approach where bacterial cells are grown at continually increasing concentration of
BP214 we could select for tolerance/resistance to BP214. Such mutants can be subjected to full
genome sequencing and compared to wild type cells. Such studies would be of general interest
given that peptide antibiotic`s such as colistin and polymyxin are used increasingly, and in this
respect it is of interest to know how resistance to peptide antimicrobials might force bacterial cells
to fundamentally change the overall architecture of the bacterial membrane. Studying the
toxicology and efficacy of peptide antimicrobials is also of importance for future development and
understanding of peptide based antimicrobials.
Lantibiotics and other Lipid II targeting antimicrobials
For the future, it seems evident that peptide based antibiotics and especially the
lantibiotics and/or other Lipid II targeting antibiotics will become useful in clinical therapy for
treatment of highly drug resistant strains such as USA300 and VRE. As NAI-107 is patented by
Naicons (Naicons Srl. Milan, Italy) we can only hope to be part of future development through
continued collaboration with Stefano Donadio. Our findings that NAI-107 kills stationary phase
bacteria might be utilized for future development. It has already been proposed that lantibiotics has
potential for bioengineering of new compounds (125, 131) and in this respect it could be important
to determine the characteristics that make NAI-107 efficacious against stationary phase cultures. As
many lantibiotics have been demonstrated to function through binding of Lipid II, it would be
interesting to understand what governs activity against stationary phase cultures. It would also be of
interest to try and understand how future resistance might develop. Resistance development to nisin
has been described as slow. It would be interesting to undertake evolutionary studies in which S.
127
aureus are grown at continually increasing concentrations of NAI-107 and as for BP214 evaluate
resistance through full genome sequencing. Teixobactin was described as killing bacteria without
detectable resistance (158), but this statement seems overestimated given the historical evidence of
resistance development.
It seems evident that the continued overuse of last resort antibiotics such colistin (118)
has to be managed on a global scale. Colistin is used increasingly in clinical medicine (105) and in
agricultural settings (118), driving selection of resistance determinants. New and novel antibiotics
are desperately needed to avoid a problematic post antibiotic era (53), which is moving continually
closer. Antimicrobial peptides such as lantibiotics or other host defense peptides have been
proposed as the solution (122, 125, 131, 262). However, the latest antibiotics approved, such as
telavancin, are representatives of older drug classes. This might be because previous attempts of
peptide development has been rushed (202). Therefore we need to further understand the biology of
these molecules; their interaction with membranes, resistance development and their toxicities, so
that we may develop them into next generation of antimicrobials. Especially how these compounds
relate to previously developed antibiotics. Do they select for similar resistance profiles or do they
force collateral damage to the cell and can this be further explored as a means of antibiotic
development.
128
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Appendix: Papers not Included in Thesis
Paper I
Rapid Selection of Plasmodium falciparum Chloroquine Resistance Transporter
Gene and Multidrug Resistance Gene-1 Haplotypes Associated with Past
Chloroquine and Present Artemether-Lumefantrine Use in Inhambane District,
Southern Mozambique
Thomas T. Thomsen, Laura B. Madsen, Helle H. Hansson, Elsa V. E. Toma´ s, Derek Charlwood,
Ib C. Bygbjerg, and Michael Alifrangis. Am. J. Trop. Med. Hyg., 88(3), 2013, pp. 536–541
145
Am. J. Trop. Med. Hyg., 88(3), 2013, pp. 536–541
doi:10.4269/ajtmh.12-0525
Copyright © 2013 by The American Society of Tropical Medicine and Hygiene
Rapid Selection of Plasmodium falciparum Chloroquine Resistance Transporter Gene
and Multidrug Resistance Gene-1 Haplotypes Associated with Past Chloroquine and Present
Artemether-Lumefantrine Use in Inhambane District, Southern Mozambique
Thomas T. Thomsen, Laura B. Madsen, Helle H. Hansson, Elsa V. E. Tomás, Derek Charlwood,
Ib C. Bygbjerg, and Michael Alifrangis*
Centre for Medical Parasitology, Department of International Health, Immunology and Microbiology, and Centre for Health Research
and Development, Faculty of Life Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Infectious Disease,
Copenhagen University Hospital, Copenhagen, Denmark; Mozambican-Danish Rural Malaria Project,
Morrumbene, Inhambane Province, Mozambique
Abstract. Chloroquine (CQ) use in Mozambique was stopped in 2002 and artemether-lumefantrine (AL) was
implemented in 2008. In light of no use of CQ and extensive use of AL, we determined the frequency of molecular
markers of Plasmodium falciparum drug resistance/tolerance to CQ and AL in persons living in Linga-Linga, an isolated
peninsula and in Furvela village, which is located 8 km inland. The P. falciparum chloroquine resistance transporter gene
CVMNK wild type increased in frequency from 43.9% in 2009 to 66.4% in 2010 (P £ 0.001), and combined P. falciparum
multidrug resistance gene 1 N86-184F-D1246 haplotype increased significantly between years (P = 0.039). The combination of P. falciparum chloroquine resistance transporter gene CVMNK and P. falciparum multidrug resistance gene NFD
increased from 24.3% (2009) to 45.3% in (2010, P = 0.017). The rapid changes observed may largely be caused by
decreased use of CQ and large-scale use of AL. In the absence of a clear AL-resistance marker and the (almost)
continent-wide use of AL in sub-Saharan Africa, and when considering CQ reintroduction, continued monitoring of
these markers is needed.
INTRODUCTION
of the Pfcrt gene, resulting in wild type CVMNK and CQresistant haplotypes CVIET and SVMNT.13 In Africa, the
CVIET haplotype is the dominant mutant haplotype.14
By monitoring the temporal prevalence of Pfcrt K76,
Kublin and others showed the reemergence of fully CQsensitive parasite populations after several years since cessation
of CQ use in Malawi.15 Since this study, studies in Tanzania,16
Kenya,17 Senegal,18 and Mozambique19 have shown similar
trends of reemergence of CQ sensitivity, and it is tempting to
consider reintroduction of CQ in combination with another
antimalarial drug in areas where CQ resistance has decreased
and possibly reserved for malaria treatment of targeted
populations, such as pregnant women, as has been suggested
by others.20
Another marker of antimalarial drug resistance is the P.
falciparum multidrug resistance gene-1 (Pfmdr-1) implicated
in resistance/tolerance to almost all antimalarial drugs including CQ, amodiaquine (AQ) and most importantly, the
artemisinins. It has recently been shown that certain combinations of SNPs in the Pfmdr-1 gene, mainly at codons 86,
184, and 1246, are emerging in areas where the ACT drug
combination artemether-lumefantrine (AL) is being widely
used21,22 and suggested that certain Pfmdr-1 haplotypes may
be markers of emergence of ACT tolerance.23
The Ministry of Health of Mozambique introduced SP-AQ
in late 2002 to replace CQ monotherapy as first-line treatment against uncomplicated malaria.24 In 2006, this combination was replaced with the ACT combination artesunate–SP.
However, already in 2008, the policy was changed to AL
because of widespread SP resistance in the country.19
Chloroquine resistance in Mozambique was reported for
the first time in 1983, followed by a number of studies
reporting it throughout most of the country.25,26 In 1999,
before abandonment of CQ, a study found that the Pfcrt
K76T mutation was prevalent in 90% of infected children in
Mozambique.27 In 2001–2002, a trial conducted in southern
Mozambique estimated a clinical efficacy for CQ of only
Malaria remains one of the major killers in the tropical and
sub-tropical world today, even though recent years have
shown progress in its control. The World Health Organization
estimated a decrease in malaria cases from 244 million to
216 million during 2005–and 2010, and estimated mortality
decreased from 781,000 in 2009 to 655,000 in 2010.1,2 This significant decrease in malaria-associated morbidity and mortality is largely attributed to large-scale malaria control efforts
such as distribution of insecticide-treated nets, indoor residual
spraying, intermittent preventive treatment in vulnerable
groups, and implementation of highly efficacious artemisininbased combination therapies (ACT) for the treatment of
uncomplicated Plasmodium falciparum malaria in most
malaria-endemic countries. The large-scale improvements are
highly dependent on continued reliability of efficacious ACTs.
However, P. falciparum ACT resistance has emerged along
the Thailand-Cambodia and Thailand-Myanmar borders,3–6 and
it might eventually be found in Africa, as happened with chloroquine (CQ) and sulfadoxine-pyrimethamine (SP).7–9 Resistance
to CQ in malaria-endemic Africa became as prevalent as malaria
and the drug has not been officially used for several years in most
malaria-endemic countries. Depending on fitness costs in the
parasites associated with acquired drug resistance, the latent
period without a certain drug pressure may result in the
reemergence of drug-sensitive P. falciparum parasites.10
Resistance to CQ is mainly associated with a single nucleotide polymorphism (SNP) in the P. falciparum chloroquine
resistance transporter (Pfcrt) gene, resulting in an amino acid
change from threonine to lysine mutation at codon 76
(K76T).11,12 There are three main haplotypes in codons 72–76
*Address correspondence to Michael Alifrangis, Centre for Medical
Parasitology, Institute for International Health, Immunology and
Microbiology, CSS, Øster Farimagsgade 5, Building 22+23, PO Box
2099, 1014 Copenhagen K, Denmark. E-mail: [email protected]
536
146
537
SELECTION OF PFCRT AND PFMDR-1 HAPLOTYPES IN MOZAMBIQUE
MATERIALS AND METHODS
Study site. The peninsula of Linga Linga (23 °43¢1.29²S,
35 °24¢15.04²E) is located in Inhambane District and 500 km
north of Maputo and opposite the district capital of
Morrumbene, which is 6 km west (across the Morrumbene
Bay). The residents are mainly fishermen or involved in
the artisanal manufacture of raffia baskets, hats and bags.
Furvela Village is 8 km west of Linga Linga on the mainland.
Furvela has approximately 4,500 inhabitants, and Linga Linga
is somewhat smaller with approximately 1,000 inhabitants. At
the onset of the study in 2007, there was no health center on
the peninsula proper, but one was established in 2009. Otherwise, the nearest health centers were situated in the village of
Coche, 5 km north of Linga Linga, or in Morrumbene. The
project received ethical clearance from the National Bioethics
Committee of Mozambique (reference 123/CNBS/06) on
August 2, 2006.
Sample collection and preparation. After an initial census,
an all-age malaria prevalence survey was performed. Seven
locations in Linga Linga based on local knowledge were chosen for establishment of the survey. At each location, residents were informed the day before the survey. In addition, a
survey of school-age children was undertaken. After informed
consent was obtained, survey teams collected cross-sectional
samples from as many volunteers as possible, including small
children whose parents consented. Blood samples were collected in March–April 2009 and April 2010 in the village of
Linga Linga, and in May 2010 in the village of Furvela. A
similar protocol was adopted in the latter village,28–30 and five
locations were used as sites for the survey.
Finger prick blood was used for preparation of thick
and thin blood films and added to 1.5-mL Eppendorf tubes
containing EDTA (Militom-14; VWR-Bie & Berntsen,
Denmark). Blood samples were allowed to separate into
serum and blood clot until clear separation was observed.
Plasma was transferred into Eppendorf tubes and the blood
clot was used for various molecular analyses of the parasites.
Blood slides stained with 5% Giemsa for 20 minutes were
read by technicians at the malaria reference laboratory in
Maputo. Two hundred fields were examined before a slide
was declared negative. Numbers of parasites per 500 leukocytes were counted and converted to densities per microliter
of blood, assuming a density of 8,000 leukocytes/mL. Only
blood slide–positive samples for P. falciparum were used for
molecular analysis. The age of donors ranged from 1 to 79 years,
and the degree of P. falciparum positivity varied markedly
between years and when age groups were compared.
DNA extraction and SNP analysis of Pfcrt and Pfmdr-1
genes. DNA was extracted by using the NucleoSpin Genomic
DNA Bloodpure Kit (Macherey-Nagel, Düren, Germany).
Extraction was performed according to the manufacturer’s instructions.
Pfcrt genotyping was performed by using a nested polymerase chain reaction, followed by sequence-specific oligonucleotide probe (SSOP)–enzyme-linked immunosorbent assay as
described.31 A set of P. falciparum laboratory isolates were
used for positive controls: 3D7 and HB3 as CVMNK controls,
FCR3 and DD2 as CVIET controls, and 7G8 as an SVMNT
control. Genotyping of Pfmdr-1 SNPs was performed by using
published polymerase chain reaction–restriction fragment
length polymorphism protocols,32,33 with minor modifications
as described23 and 3D7 (N86-Y184-D1246), FCR3 (86Y-Y1841246D), DD2 (86F-184Y-1246D), and 7G8 (N86-184F-1246Y)
used as positive controls. Blood donors from Denmark who
were never exposed to malaria were used as P. falciparumnegative controls.
Statistical analysis. Statistical analysis was performed in 2 2
contingency tables, and chi-square test statistics or Fisher’s
exact test were applied when appropriate. For analysis of
Pfcrt haplotypes, samples were considered to be mixed, but
as containing a majority haplotype, when the optical density
(OD) value of the weakly reacting Pfcrt SSOP was less than
half the OD value of the strongly reacting Pfcrt SSOP. Conversely, if the OD value of the weakly reacting Pfcrt SSOP
was higher than half the OD value of the strongly reacting
Pfcrt SSOP, the infection was categorized as mixed with no
dominant haplotype. To analyze for a possible temporal
change in the frequency of the Pfcrt CVMNK haplotype, all
infections containing CVMNK only or as the majority in
mixed CVMNK/CVIET infections were tested against single
CVIET infections. The analysis of temporal change in the
prevalence of Pfcrt CVMNK haplotype were performed by
comparing all infections containing CVMNK including all
mixed CVMNK/CVIET haplotype infections against single
CVIET infections.
Prevalence of Pfmdr-1 SNPs was examined individually for
codons 86, 184, and 1246 where the genotypes N86, 184F, and
D1246 including mixed infections were compared against single 86Y, Y184, and 1246Y genotype infections, respectively.
For frequency analysis, all mixed infections were omitted.
Possible changes in frequency of constructed 86–184–1246
haplotypes were analyzed by excluding infections with one
or more mixed genotype. Finally, analysis of the temporal
frequency of constructed Pfcrt-Pfmdr-1 haplotypes was
performed by omitting all mixed Pfmdr-1 infections and for
+
47%.26 Another study conducted in the same district in 2002–
2003 demonstrated a frequency of the mutant CVIET haplotype to be > 90%.24 Since CQ was officially abandoned in
2002, the CQ drug pressure has most likely waned in subsequent years. However, since the 4-aminoquinoline analog AQ
(combined with SP) replaced CQ, this may have ensured
some level of sustained drug pressure.
In a recent report by Raman and others over a five-year
period (2006–2010), the prevalence of the Pfcrt K76T mutation was determined in children living in Gaza Province in
southern Mozambique.19 Overall, there was a striking
decrease in the prevalence of the K76T mutation from > 95%
in the four zones of Gaza Province in 2006 to 17.5–37.3% in
2010. The study also examined the prevalence of SNPs in the
Pfmdr1-gene, but only regarding the N86Y mutation, in which
a reduction was observed from > 70% to 25.8–48.8%.19 Other
studies from Mozambique have, to the best of our knowledge,
not assessed SNP prevalence changes in the Pfmdr-1 gene.
Therefore, temporal changes in selection of polymorphisms
in this gene remains to be elucidated. This need is especially
important in light of the suggested relationship between certain Pfmdr-1 haplotypes and emergence of ACT tolerance.
We therefore analyzed the distribution and investigated
short-term temporal change of SNPs in the Pfcrt codons 72–
76 and Pfmdr-1 codons 86, 184, and 1246 in persons living in
Linga Linga, an isolated peninsula of Mozambique and in the
village of Furvela located 8 km inland from Linga Linga.
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THOMSEN AND OTHERS
Pfcrt, mixed infections where a majority haplotype could not
be determined.
RESULTS
Sample collection. In 2009 and 2010, of 435 and 385 samples collected from donors in Linga Linga, 159 (36.6%) and
108 (28.1%) were P. falciparum positive by microscopy,
respectively. In addition, 336 samples were collected in
Furvela in 2010, of which 111 (33.0%) were P. falciparum
positive by microscopy.
Frequency and prevalence of codon72–76 haplotypes of
the Pfcrt gene in study sites of Mozambique in 2009–2010. Of
the P. falciparum-positive sample set, 136 (85.5%) and 195
(91.1%) samples were successfully haplotyped at codon 72–
76 of the Pfcrt gene in samples from 2009 (Linga Linga only)
and 2010 (Linga Linga, n = 97 and Furvela, n = 98), respectively. For the 2010 samples, no significant difference in
frequency and prevalence of the Pfcrt haplotypes between
Linga Linga and Furvela was observed (c2 = 0.01, P = 0.91
and c2 = 1.07, P = 0.30 for comparison of frequency and
prevalence, respectively), wherefore the samples from the
two villages were pooled.
The frequency of P. falciparum infections carrying the Pfcrt
wild type CVMNK haplotype (including mixed CVMNK/
CVIET infections in which CVMNK was the majority haplotype) versus mutant CVIET haplotype infections showed a
significant increase of CVMNK haplotype from 43.9% in
2009 to 66.4% in 2010 (c2 = 13.1, P £ 0.001) (Figure 1A).
Likewise, the prevalence of infections carrying the Pfcrt wild
type CVMNK haplotype including mixed CVMNK/CVIET
infections versus pure mutant CVIET haplotype infections
increased significantly from 60.0% in 2009 to 74.9% in 2010
(c2 = 8.02, P = 0.005) (Figure 1B).
Prevalence and frequency of SNPs at codons 86, 184,
and 1246 of the Pfmdr-1 gene. The temporal prevalence of
SNPs at codons 86, 184, and 1246 was analyzed by comparing
the distribution from 2009 and 2010 for codons 86 and 184
(Figure 2A and B). Except for codon 184 (see below), the
data from Linga Linga and Furvela in 2010 were pooled
because of a lack of significance between the settings. Prevalence of P. falciparum infections carrying the N86 wild type
(including mixed 86N/Y infections) increased significantly
from 64.7% in 2009 to 84.1% in 2010 (c2 = 16.3, P £ 0.001),
and prevalence of the D1246 wild type genotype remained
> 98% (c2 = 0.163, P = 0.67). For the 184F mutant type
(including mixed 184F/Y infections), the prevalence was
21.5% in Linga Linga in 2009, which increased to 34.3% in
2010 (c2 = 4.41, P = 0.036) and to 51.0% in Furvela.
The frequency of the Pfmdr-1 genotypes (disregarding
mixed genotype infections) from Linga Linga and Furvela in
2010 was pooled because data was not significant between
the settings. The frequency of the N86 wild type increased
significantly from 52.9% to 73.0% (c2 = 8.93, P = 0.003),
whereas for the 184F mutant type, only an insignificant
increase from 18.5% to 26.3% was seen (c2 = 2.07, P =
0.150), and no change was observed in D1246, which remained
stable at 98% between the years (c2 = 0.161, P = 0.688).
Frequency of constructed haplotypes at codon 86, 184,
and 1246 of the Pfmdr-1 gene. The construction of Pfmdr-1
86–184–1246 haplotypes (excluding mixed SNPs at one or
more codons) showed several different haplotypes and tem-
Figure 1. A, Frequency and B, Prevalence of Plasmodium
falciparum chloroquine resistance transporter gene codon 72–76
haplotypes, CVMNK (wild type) and CVIET (mutant type) in
Linga Linga (2009) and Linga Linga with Furvela village (2010)
of Mozambique.
poral changes in the distribution (Figure 2C). The frequency
of the single mutant 86Y–Y184–D1246 (YYD) haplotype
decreased significantly from 47.8% in 2009 to 24.5% in 2010
(c2 = 10.32, P = 0.001), whereas the frequency of the single
mutant NFD haplotype increased significantly between the
years (c2 = 4.27, P = 0.039).
Frequency of combined Pfcrt-Pfmdr-1 haplotypes. The
Pfcrt haplotypes (CVMNK or CVIET) were combined with
the constructed Pfmdr-1 haplotypes omitting samples that
were mixed with no clear majority infection (for Pfcrt), or
mixed or negative in one or more of the Pfmdr-1 codons. Of
the remaining 165 samples (2009: n = 76, 2010: n = 89), analysis showed a significant increase in infections carrying the
Pfcrt-Pfmdr-1 combination CVMNK-NFD from 24.3% in
2009 to 45.3% in 2010 (c2 = 5.66, P = 0.017).
DISCUSSION
The use of CQ to treat uncomplicated malaria in Mozambique
was officially abandoned in 2002. Most likely, as everywhere
else in the malaria-endemic world where CQ has been
replaced by other antimalarial drugs, some informal use of
CQ has subsequently been ongoing because of the low price
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SELECTION OF PFCRT AND PFMDR-1 HAPLOTYPES IN MOZAMBIQUE
Figure 2. Prevalence of Plasmodium falciparum multidrug resistance gene-1 codon 86 and 184 genotypes and frequency of the combined codon 86–184–1246 haplotypes in Linga Linga (2009) and Linga
Linga with Furvela village (2010) of Mozambique. A, Prevalence
of codon 86 genotypes. B, Prevalence of codon184 genotypes. C, Frequency of 86–184–1246 haplotypes (excluding mixed infections).
of CQ and good fever compliance. Furthermore, in Mozambique,
the analog 4-aminoquinoline amodiaquine combined with SP
replaced CQ, for a few years, which might have impacted Pfcrt
and Pfmdr-1 haplotypes. However, because of improved
malaria diagnostics such as the use of rapid diagnostic tests,
and since 2008 better treatment options, e.g., ACTs, and possi-
bly lower malaria prevalence, CQ drug pressure would
decrease. Given that there are fitness costs for malaria parasites associated with CQ resistance,34 it is expected that the
prevalence of sensitive parasites in vivo will increase.
Although the validity of the Pfcrt 76T mutation as a predictive marker of CQ treatment failure remains doubtful because
of confounding factors such as host immunity, monitoring
the emergence of wild type Pfcrt 76K parasites in indigenous
P. falciparum populations more adequately illustrates the
temporal advancement of parasite sensitivity to CQ. A study
in southern Mozambique in 2001 and 2003 reported frequencies of the mutant Pfcrt CVIET haplotype > 90% at the time
of official abandonment of CQ.24 In the present study, from a
remote setting in Mozambique, the frequency of the Pfcrt
CVMNK wild type increased from 44% to 66% within a single year. This finding is consistent with the recent study by
Raman and others, in which the prevalence of the pure K76
wild type in the southern province of Gaza, Mozambique,
increased from < 5% at baseline in 2006 to 65–80% in 2010.19
Thus, both studies confirms the trend of a substantial increase
in P. falciparum susceptibility to CQ in Mozambique, similarly to other studies conducted in other parts of the east
African region such as Malawi,15 Kenya,35 and Tanzania.16
However, recent studies in 2009–2010 in Mwanza, Tanzania,
and Iganga, Uganda found a striking difference of 59.5% and
0% in the prevalence of Pfcrt CVMNK wild types, respectively.36 Thus, the re-emergence of CQ susceptibility appears
to evolve at different rates probably because of co-varying
factors such as treatments given (also dependent on differences in diagnostic practices and transmission intensity) and
the continued use of CQ and/or related drugs maintaining the
drug pressure on Pfcrt, e.g., amodiaquine. In adition, the ACT
drug combination AL has been shown to select for Pfcrt
wild types.37 Therefore, large-scale implementation of AL as
first-line treatment in most sub-Saharan countries may as well
facilitate re-emergence of CQ sensitivity in P. falciparum.
In this study we also describe a selection of N86 and 184F
and the combined N86–184F–D1246 Pfmdr-1 haplotype
NFD. This finding is similar to our previous findings in
Tanzania, where the N86 and 184F prevalence increased significantly over a five-year period.23 Recently, Baliraine and
Rosenthal determined the prevalence of single Pfmdr-1 N86,
184F, and D1246 and combined NFD haplotype before either
AL, artesunate-AQ, or AQ + SP treatment, and compared
with prevalence up to 120 days after treatment in primarily
new infections.38 Only in the AL group, the prevalence of the
N86, 184F and D1246, but as well the NFD haplotype were
much higher compared with pre-treatment prevalence38 indicating a survival advantage of these parasites. This finding
does not indicate an immediate potential risk of clinical failures after AL treatment; AL still remains highly efficacious in
Africa. However, the NFD haplotype in particular may be
considered as a marker of increased tolerance to AL.
When combining the Pfcrt and the Pfmdr-1 haplotypes, the
present study showed a strong selection of the Pfcrt-Pfmdr-1
CVMNK-NFD haplotype. This finding might be caused by
decreased use of CQ. However, we propose that selection of
this particular haplotype is as well largely a consequence of
large-scale AL use. Baring in mind the small scale of this
study and several confounding factors such as impact of other
drugs, our findings are only indicative. Therefore, there is a
continued need and urgency to monitor these two markers in
149
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THOMSEN AND OTHERS
the light of a possible reintroduction of CQ in combination
with another drug or alone for vulnerable groups such as
pregnant women and because of the (almost) African-wide
use of AL, in the absence of a better molecular marker for
AL resistance.
Received August 27, 2012. Accepted for publication December 15, 2012.
Published online February 4, 2013.
Acknowledgments: We thank the study participants, including their
parents or guardians; the village leaders of Linga Linga and Furvela;
District Health Authorities of Morrumbene; and the MOZDAN
team for their assistance during the surveys; and Ulla Abildtrup
(Centre for Medical Parasitology, Copenhagen, Denmark) for excellent technical assistance.
Authors’ addresses: Thomas T. Thomsen, Section for Functional Genomics, Department of Biology, University of Copenhagen, Ole Maaløes
Vej 5, 2200 Copenhagen N, Denmark, E-mail: thomas.thomsen@
bio.ku.dk. Laura B. Madsen, Helle H. Hansson, Ib C. Bygbjerg, and
Michael Alifrangis, Centre for Medical Parasitology, Institute for
International Health, Immunology and Microbiology, CSS, Øster
Farimagsgade 5, 1014 Copenhagen K, Denmark, E-mails: lmadsen@
sund.ku.dk, [email protected], [email protected], and micali@sund
.ku.dk. Elsa V. E. Tomás, Mozambican-Danish Rural Malaria Project,
Morrumbene, Inhambane Province, Mozambique, E-mail: erzeliatomas@
yahoo.com.br. Derek Charlwood, Centre for Health Research and
Development, Faculty of Life Sciences, University of Copenhagen,
Frederiksberg, Denmark, and Instituto Nacional de Saudé, Avenida
Eduardo Mondalane, Maputo, Mozambique, E-mail: jdcharlwood@
gmail.com.
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151
Paper II
Collateral Resistance and Sensitivity Modulate Evolution of High-Level Resistance
to Drug Combination Treatment in Staphylococcus aureus
Mari Rodriguez de Evgrafov,a Heidi Gumpert,a Christian Munck,a Thomas T. Thomsen,a and
Morten O.A. Sommer.a,b Mol. Biol. Evol. 32(5):1175–1185
a
Department of Systems Biology, Technical University of Denmark, DK-2800 Lyngby, Denmark
b
The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2970 Hørsholm,
Denmark
Corresponding author: Morten O.A. Sommer, Department of Systems Biology, Technical University of Denmark, DK2800 Lyngby, Denmark, Tel.: +45 4525 2507; email:[email protected]
152
Collateral Resistance and Sensitivity Modulate Evolution
of High-Level Resistance to Drug Combination Treatment
in Staphylococcus aureus
Mari Rodriguez de Evgrafov,1 Heidi Gumpert,1 Christian Munck,1 Thomas T. Thomsen,1 and
Morten O.A. Sommer*,1,2
1
Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark
The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark
*Corresponding author: E-mail: [email protected].
Associate editor: Miriam Barlow
2
As drug-resistant pathogens continue to emerge, combination therapy will increasingly be relied upon to treat infections
and to help combat further development of multidrug resistance. At present a dichotomy exists between clinical practice,
which favors therapeutically synergistic combinations, and the scientific model emerging from in vitro experimental
work, which maintains that this interaction provides greater selective pressure toward resistance development than other
interaction types. We sought to extend the current paradigm, based on work below or near minimum inhibitory
concentration levels, to reflect drug concentrations more likely to be encountered during treatment. We performed a
series of adaptive evolution experiments using Staphylococcus aureus. Interestingly, no relationship between drug
interaction type and resistance evolution was found as resistance increased significantly beyond wild-type levels.
All drug combinations, irrespective of interaction types, effectively limited resistance evolution compared with monotreatment. Cross-resistance and collateral sensitivity were found to be important factors in the extent of resistance
evolution toward a combination. Comparative genomic analyses revealed that resistance to drug combinations was
mediated largely by mutations in the same genes as single-drug-evolved lineages highlighting the importance of the
component drugs in determining the rate of resistance evolution. Results of this work suggest that the mechanisms
of resistance to constituent drugs should be the focus of future resistance evolution work.
Key words: resistance evolution, antibiotic resistance, drug combinations.
Introduction
antibiotics (Cottarel and Wierzbowski 2007; Read et al.
2011) as well as improving treatment outcomes in a variety
of diseases, such as TB and HIV (Gilliam et al. 2006; Lennox
et al. 2009; Huang et al. 2012; Vilchèze and Jacobs 2012;
Freedberg et al. 2013). Combination therapy relies upon spontaneous resistance being rare and multiplicative so the likelihood of an organism gaining resistance to multiple drugs in a
single instance is less than the prospect of resistance to any
one of the component drugs acting alone (Fischbach 2011).
This reasoning assumes that resistance acquisition is an independent event for each component of the mixture.
A major goal of resistance evolution research has been the
search for the most effective yet resistance limiting combinations or treatment strategies (Yeh et al. 2006; Chait et al. 2007;
Hegreness et al. 2008; Michel et al. 2008; Bollenbach et al.
2009; Torella et al. 2010; Imamovic and Sommer 2013;
Pena-Miller et al. 2013). Outcomes of nearly a decade
worth of experimental in vitro work have suggested that
drug interactions (Chait et al. 2007; Hegreness et al. 2008;
Michel et al. 2008; Torella et al. 2010; Palmer and Kishony
2013; Pena-Miller et al. 2013) are a key factor in limiting or
driving resistance evolution, particularly during the early
stages of resistance development. Specifically, combinations
ß The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please
e-mail: [email protected]
153
Mol. Biol. Evol. 32(5):1175–1185 doi:10.1093/molbev/msv006 Advance Access publication January 23, 2015
1175
Article
Antibiotic resistance poses a severe threat to public health
(Read et al. 2011; World Health Organization 2012). Left unresolved antibiotic resistance will increase the cost of healthcare,
threaten medical advancement, scale back progress against
certain infectious diseases and lead to greater morbidity and
mortality (World Health Organization 2012). The increasing
presence of antibiotic-resistant organisms has led to greater
numbers of treatment failures for Gram-positive pathogens,
such as methicillin-resistant Staphylococcus aureus, vancomycin-resistant Enterococcus, and multidrug-resistant tuberculosis (Cornaglia 2009; Woodford and Livermore 2009). The
problem posed by resistant organisms is exacerbated by limited development of new antibiotics (Cottarel and
Wierzbowski 2007; Fischbach 2011; Thaker et al. 2013).
However, the arrival of new antibiotics provides only shortterm relief as resistance quickly follows (Clatworthy et al.
2007; Read et al. 2011). Thus, the long-term key to controlling
this threat lies in managing the unavoidable resistance
adaptation (Read et al. 2011).
Combination therapy, the concurrent use of two or more
drugs, is one such resistance management strategy, which has
proven instrumental in prolonging the useful lifespan of
Downloaded from http://mbe.oxfordjournals.org/ at Royal Library/Copenhagen University Library on December 8, 2015
Abstract
MBE
de Evgrafov et al. . doi:10.1093/molbev/msv006
Results
Classification of Selected Drug Combinations
Drug combinations are characterized according to the epistatic interactions between their component drugs. The fractional inhibitory concentration index (FICI) is used to describe
these interactions and is based on the Loewe additivity zero
interaction theory (Berenbaum 1978). The index, determined
for a given effect level, is the sum of the fractional inhibition of
each drug in a combination relative to the drug acting alone.
The interactions of each of our drug combinations were
tested using the WT strain prior to commencing the resistance adaption experiments. The interaction types at an
effect level of 90% were as follows: doxycycline–erythromycin
(FICI 0.58 0.04), doxycycline–ciprofloxacin (FICI = 0.81 0.14), and fusidic acid–erythromycin (FICI = 0.75 0.15)
were synergistic, ciprofloxacin–ampicillin was additive
(FICI = 0.99 0.11) and fusidic acid–amikacin was antagonistic (FICI = 1.69 0.1). Previous work performed in Escherichia
coli, and performed again here (supplementary data S1,
Supplementary Material online) characterized the interaction
between doxycycline and ciprofloxacin as strongly antagonistic (Yeh et al. 2006; Toprak et al. 2011; Lazar et al. 2013);
however, this combination was found to be synergistic
when tested in our S. aureus strain Newman, underscoring
the dependence of drug epistatic interactions on the specific
target organism.
Resistance Evolution of Populations
A wild-type (WT) S. aureus strain Newman population was
challenged and adapted in three replicate lineages designated
as A, B, and C to increasing concentrations of six individual
antibiotics and five antibiotic combinations (table 1). An additional three replicate lineages, also designated as A, B and C,
were passaged in media only. Adaptation was performed according to the following protocol (fig. 1). Briefly, the WT
organism was inoculated into 12 different conditions with
increasing concentrations of antibiotic(s) and allowed to
grow for 18 h. At the end of the growth period, optical density
(OD) measurements were taken and the most resistant culture from each replicate was reinoculated in fresh media at
the drug concentration it was selected from. The recultured
organisms were then used as inoculum for the next resistance
challenge. A total of five resistance evolution periods, referred
to as exposures, were performed. A total of ten inoculations
(fresh media tube and exposure), equivalent to an average
cumulative number of cell divisions (CCD) of 1.16 1013 (Lee
et al. 2011), were performed. A total of 36 lineages (18 single
drug, 15 combination, and 3 media only evolved) were yielded
through the evolution process.
Adaptation to single agents increased steadily with each
exposure (fig. 2) for most populations and after five exposures
four of six single-drug-evolved populations were able to grow
in concentrations of at least 10 mg/ml (supplementary data
S1, Supplementary Material online). Lineages evolved to
erythromycin and amikacin developed resistance quickly
and were able to grow in antibiotic concentrations greater
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with antagonistic or suppressive interactions, where drugs in a
mixture interfere with each other and the overall therapeutic
effect is less than the component drugs working alone, have
been shown to slow down resistance adaption better than
those that act in a synergistic manner, where treatment
outcomes are better than what would be expected from
summing the effect of the component drugs acting alone
(Chait et al. 2007; Hegreness et al. 2008; Michel et al. 2008;
Torella et al. 2010; Pena-Miller et al. 2013). The rationale for
this hypothesis is that the mutations conferring resistance to
a single drug will have a more pronounced effect on the
fitness of the organism in the presence of a synergistic
combination because of the cooperative interaction of the
components in the mixture (Hegreness et al. 2008; Michel
et al. 2008). However, results of the in vitro work conflict
with clinical practice where synergistic combinations are
the preferred treatment regime (Cottarel and Wierzbowski
2007).
There are caveats to the paradigm that has emerged from
these findings. These include the absence of the role of epistasis in driving resistance evolution (Trindade et al. 2009; Hall
and MacLean 2011; Borrell et al. 2013) as well as the foundation being based on experimental work performed at or near
WT minimum inhibitory concentration (MIC) levels (Yeh
et al. 2006; Chait et al. 2007; Michel et al. 2008; Pena-Miller
et al. 2013). Recent work has suggested that a better understanding of epistasis among relevant resistance conferring
mutations could lead to the design of better treatment regimens (Trindade et al. 2009; Borrell et al. 2013). Moreover,
clinically relevant resistance associated with treatment failures
usually occurs in association with concentrations substantially
greater than WT MIC levels (Anon 2013). Finally, emphasis on
resistance adaptation at or near WT MIC levels may not accurately reflect the phenomena observed during the treatment of chronic bacterial infections, such as TB or cystic
fibrosis. Despite the progress made through the aforementioned laboratory experiments, there is still a great need for a
better understanding of the evolution of multidrug resistance
(Palmer and Kishony 2013) before allowing these findings to
shape or change therapeutic strategies aiming to control resistance evolution.
We proposed testing the generality of the current paradigm by extending the concentration range and adaptation
time frame considered while using the same model organism
and drug combinations originally used to construct it
(Hegreness et al. 2008; Michel et al. 2008). We hypothesized
that at elevated concentrations resistance evolution is driven
by response to individual component drugs rather than drug
interactions. To test our hypotheses, we evolved populations
of S. aureus strain Newman, a medically relevant Gram-positive species, in the presence of six different antibiotics and
five different combinations. The drugs and combinations
used are well characterized, are clinically relevant, and have
diverse modes of action (table 1). We performed genomic
sequencing to determine the mutations involved in resistance
adaptation. Finally, we considered the role of mutations in
resistance toward drug combinations.
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Resistance Evolution Dependent on Collateral Resistance . doi:10.1093/molbev/msv006
Table 1. Antibiotics Used and Their Modes of Action.
Antibiotic Name
Amikacin
Ampicillin
Ciprofloxacin
Erythromycin
Doxycycline
Fusidic acid
Abbreviation
AMI
AMP
CPR
ERY
DOX
FUS
Class
Aminoglycoside
Beta lactam
Quinolone
Macrolide
Tetracycline
Other
Abbreviation
Interaction
FUS-AMI
CPR-AMP
DOX-CPR
DOX-ERY
FUS-ERY
Antagonistic
Additive
Synergistic
Synergistic
Synergistic
Concentraon
X
Y
X+Y
Wild Type
S. aureus
Newman
Exposure 1
Exposure 2
Exposure 3
FIG. 1. Adaptation of Staphylococcus aureus to individual drugs and drug pairs. An overnight culture of WT S. aureus was used to inoculate microtiter
plates containing different drugs or combinations with increasing concentrations or media only. Three replicate populations were recreated for each
condition. The highest concentration where growth was present was recultured in fresh media and then used to inoculate the next concentration
challenge, referred here to as exposure. A total of five exposures were performed for each condition.
than 100 mg/ml. Adaptation to doxycycline and ampicillin
was much slower, with populations tolerating less than
3 mg/ml after five exposures. Adaptation by four of the five
combination-evolved populations (ciprofloxacin–ampicillin,
fusidic acid–amikacin, doxycycline–erythromycin, and doxycycline–ciprofloxacin) was similar to their slowest evolving
single drug counterparts, whereas lineages evolved to the
fusidic acid–erythromycin combination were approximately
10 less than their slowest evolving single drug counterpart
(fig. 2 and supplementary data S1, Supplementary Material
online).
Resistance Profiles of Adapted Lineages
Following resistance adaptation, four isolates from each of the
adapted populations were profiled for their individual resistances. Results show that all isolates exhibited a substantial
increase in resistance following five exposures (fig. 3 and supplementary data S1, Supplementary Material online). In many
cases, the IC90 values of the isolates were 100 greater than
the WT value and in the case of the fusidic acid isolates more
than a 1,000 larger. Exceptions to this trend were observed
in the ampicillin, ciprofloxacin–ampicillin, and fusidic
acid–erythromycin isolates where IC90 values were only
10–30 the WT value. Increased resistance differed among
isolates evolved to the same drug(s) and in some cases this
difference was considerable (fig. 3). We attributed the differences observed within a given drug(s) group to be the result
of genotypic changes acquired by the isolates through
adaption.
The fusidic acid–amikacin isolates (antagonistic interaction, supplementary data S1, Supplementary Material online)
had the greatest increase in resistance improvement followed
closely by isolates adapted to doxycycline–ciprofloxacin (synergistic interaction, supplementary data S1, Supplementary
Material online). Isolates evolved to ciprofloxacin–ampicillin
(additive interaction, supplementary data S1, Supplementary
Material online) had the least resistance improvement, an
average of 11 the WT MIC value. These results contrast
with previous reports based on sub-MIC adaptations, which
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Combination
Amikacin and fusidic acid
Ampicillin and ciprofloxacin
Ciprofloxacin and doxycycline
Erythromycin and doxycycline
Erythromycin and fusidic acid
Target
30S ribosome
Cell wall
DNA synthesis
50S ribosome
30S ribosome
Protein synthesis
de Evgrafov et al. . doi:10.1093/molbev/msv006
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FIG. 3. Gain in IC90 value of the most evolved lineages following resistance adaptation. Isolates are grouped according to drug pairs: (A) FUS-ERY, (B)
CPR-AMP, (C) DOX-ERY, (D) FUS-AMI, and (E) DOX-CPR. Each column is an average of four biological replicates. Error bars reflect the SEM of the
replicates. Differences within a drug(s) group suggest that resistance adaptation is a complex process. Adaptation of the combination-evolved isolates
mirrors that of the least evolved single drug isolates.
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FIG. 2. Change in drug tolerance during adaptation. Each bar is an average of three replicate lineages and reflects the average concentration that the
adapted population can grow in following exposure to ever increasing concentrations. Populations are grouped according to drug pairs: (A) FUS-ERY,
(B) CPR-AMP, (C) DOX-ERY, (D) FUS-AMI, and (E) DOX-CPR. Dashed lines represent clinical breakpoints, taken from the EUCAST website, for each
individual drug. There is no established clinical breakpoint value for ampicillin used on Staphylococcus aureus.
Evolvability Index Value
Resistance Evolution Dependent on Collateral Resistance . doi:10.1093/molbev/msv006
10
FUS-ERY
1
CPR-AMP
FUS-AMI
0.1
DOX-CPR
0.01
0.5
1.0
1.5
DOX-ERY
WT FICI
suggest that antagonistic or suppressive combinations limit
resistance evolution best (Hegreness et al. 2008; Michel et al.
2008; Pena-Miller et al. 2013). In general, the extent of resistance attained by the combination-evolved isolates was similar to that of the slowest evolved corresponding single drug
isolates, highlighting the importance of individual components in resistance evolution during combination therapy.
We quantified these observations using the evolvability
index (Munck et al. 2014), which describes how resistance
evolution toward an individual drug is impacted as a result
of being used in a combination compared with being used
alone. The evolvability index is determined by taking the average of the relative change in resistance development for
each component drug of a drug combination-evolved lineage
and dividing it by the relative change in resistance development in the single-drug-evolved lineages (Munck et al. 2014)
(eq. 2). An evolvability index value of 1 signifies that the
combination-evolved isolate developed resistance to the
same extent as the individual drug-evolved isolates did to
the component drugs. A value greater than 1 indicates that
the combination-evolved isolate evolved to be more resistant
than its corresponding single-drug-evolved isolates, whereas a
value of less than 1 means that the combination-evolved
isolates evolved less than the single-drug-evolved isolates. It
is important to note that the evolvability index assumes that
the exposure time to each component or combination is the
same. Comparisons where this is not the case are not accurate
measures of resistance evolution. Nevertheless, this simplification provides a clear and quantitative means to compare
how different combinations drive resistance adaptation
across experiments and organisms.
All but three of our combination-evolved isolates had
evolvability index values of less than 1 meaning that overall
the combinations were effective at limiting resistance evolution relative to their constituent drugs alone (fig. 4 and supplementary data S1, Supplementary Material online). Isolates
with evolvability index values greater than 1 were the
ciprofloxacin–ampicillin isolate C (2.3) and the doxycycline–ciprofloxacin isolates B (1.38) and C (1.59). Each of
these isolates had component IC90 values that greatly exceeded those of the corresponding single-drug-evolved isolates (supplementary fig. S1, Supplementary Material online).
Elevated evolvability index values were also determined for
fusidic acid isolate B (0.96) and doxycycline–erythromycin
isolates B (0.86) and C (0.84) and were likely due to strong
resistance to one component drug (supplementary fig. S1,
Supplementary Material online). The smallest evolvability
index values (<0.2) belonged to the fusidic acid–erythromycin isolates, which suggests that this combination limited resistance evolution best.
WT epistatic drug interactions were not found to be significantly correlated to the extent of resistance evolution
observed. One explanation could be that drug interactions
are not static but rather affected by resistance evolution.
To assess the evolutionary stability of the epistatic drug
interactions, we determined the FICI values for our combinations for the evolved isolates. These data show that changes in
the drug interaction profiles had taken place (supplementary
fig. S2, Supplementary Material online). For example, the interaction between doxycycline and ciprofloxacin postadaptation became antagonistic in each of the three replicate
isolates. A similar shift was observed for two of the three
fusidic acid–erythromycin isolates. The interaction between
fusidic acid and erythromycin remained synergistic; however,
the FICI values increased as a result of adaptation. An inconclusive interaction existed between ciprofloxacin and ampicillin following adaptation with one isolate demonstrating
synergism whereas another displayed antagonism. FICI
values for fusidic acid and amikacin decreased slightly below
the WT value for two of the three isolates; however, the third
isolate showed strong antagonism between the two drugs.
These findings are in agreement with a recent study of E. coli
exposed to erythromycin and doxycycline showing that drug
interactions are strongly modulated by evolution (Pena-Miller
et al. 2013). Drug interactions can predict resistance evolution
for sub-MIC adaptation; however, our data suggest that these
interactions change in response to resistance adaptation
causing their reliability as resistance evolution predictors to
become less certain.
Instead, we decided to investigate the role of cross-resistance in driving resistance evolution as there appeared to be a
relationship between the resistance evolution of combination
isolates and their corresponding constituent drug isolates.
Moreover, cross-resistance has been suggested to play an important role in rates of adaptation (Szybalski 1954; Hegreness
et al. 2008; Michel et al. 2008; Yeh et al. 2009; Imamovic and
Sommer 2013; Lazar et al. 2013, 2014; Oz et al. 2014). Using
the same combination pairings all single-drug-evolved isolates
were exposed to the other respective component drug, that
is, lineages evolved to drug A were exposed to drug B to test
for cross-resistance in combination AB.
Overall, adaptation to a single antibiotic frequently resulted in the cross-resistance to another (fig. 5). The amikacin-evolved isolates had strong (410 WT) cross-resistance
to fusidic acid and in the case of one replicate the IC90 value
was nearly 100 times that of the WT. Isolates evolved to
ampicillin displayed limited to negligible cross-resistance or
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FIG. 4. Evolvability index values for each drug combination isolate. The
evolvability index quantifies how being used in a combination impacted
the resistance evolution to the individual component drugs of a
combination. Values are grouped according to WT drug interaction.
FUS-ERY, DOX-CPR, and DOX-ERY were all synergistic, CPR-AMP was
additive, and FUS-AMI was antagonistic. Variation among replicates
within the same drug pair reflects the individuality of resistance
adaptation.
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Whole-Genome Sequence Analysis
log(Fold IC90 change)
2
Tested against
AMI
1
AMP
CPR
DOX
ERY
FUS
0
AMP
CPR
DOX
ERY
FUS
Lineage evolved to
FIG. 5. Single-drug-evolved isolates tested for cross-resistance to their
corresponding component drug. All single-drug-evolved isolates were
tested to their corresponding component drug to test for cross-resistance or sensitivity. Each column is an average of four biological replicates and represents the gain or loss in WT IC90 value by drugs adapted
to drug A tested against drug B. Error bars reflect the SD of the replicates. The isolates tested are listed below the x axis, whereas the drug
they are tested against is given in the legend. Isolates evolved to fusidic
acid displayed considerable sensitivity to erythromycin and moderate
cross-resistance to amikacin. Isolates evolved to amikacin had strong
cross-resistance to fusidic acid.
collateral sensitivity (Imamovic and Sommer 2013; Lazar et al.
2013) to ciprofloxacin and vice versa. The ciprofloxacinevolved isolates, however, did display considerable
(30 WT) cross-resistance to doxycycline. Adaptation to
doxycycline resulted in strong (410 WT IC90) cross-resistance to both erythromycin and ciprofloxacin. Isolates
evolved to erythromycin displayed strong (410 WT IC90)
cross-resistance to doxycycline and moderate (<5 WT IC90)
cross-resistance to fusidic acid. The extent of cross-resistance
displayed by isolates evolved to ciprofloxacin, doxycycline,
and erythromycin is consistent with the elevated evolvability
indices calculated for the corresponding combinations.
Finally, adaptation to fusidic acid resulted in collateral sensitivity to erythromycin with IC90 values well below the WT
value. This collateral sensitivity likely explains the comparatively slow evolution of resistance observed for isolates
evolved to the fusidic acid–erythromycin combination. The
fusidic acid-evolved isolates also displayed moderate
(<5 WT IC90) cross-resistance to amikacin. The combinations for which the component drugs did not confer collateral
sensitivity exhibited significantly higher evolvability index
values (P < 0.05, Mann–Whitney), suggesting that collateral
sensitivity interactions between component drugs are important for determining resistance evolution toward drug
combinations.
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AMI
To explore the molecular basis of the drug resistance observed
in our experiments, we sequenced the genomes of our most
evolved isolates (18 from the single-drug-evolved isolates, 15
from the combination-evolved isolates, and 3 from the media
only-evolved isolates) and our ancestral WT. The sequenced
isolates were then analyzed in groups based on the drug(s)
they were evolved to. In general, the resistance phenotypes
observed in the isolates could be readily explained by the
presence of expected resistance mutations in their genomes.
An overlap of canonical resistance mutations was observed
in both the combination-evolved and single-drug-evolved isolates (fig. 6 and supplementary data S2, Supplementary
Material online). For example, two of three fusidic acid–erythromycin-evolved isolates (A and B) and two of three erythromycin-evolved isolates (A and B) had mutations in the rplD
gene, which codes for ribosomal protein L4. Mutations in this
gene have previously been associated with macrolide resistance in several bacterial species (Tait-Kamradt et al. 2000;
Canu et al. 2002; Zaman et al. 2007), including S. aureus
(Prunier et al. 2002). The mutations observed in the rplD
gene of all four isolates are well-documented amino acid substitutions (Canu et al. 2002; Diner and Hayes 2009) that result
in the alteration of the macrolide-binding site (Gregory and
Dahlberg 1999; Gabashvili et al. 2001; Diner and Hayes 2009).
The resistance conferred by these mutations, however, varied
considerably (fig. 3 and supplementary fig. S1, Supplementary
Material online) and appeared to be a function of quantity.
Both erythromycin isolate B and fusidic acid–erythromycin
isolate B had multiple single nucleotide polymorphism (SNPs)
in the rplD gene, whereas erythromycin isolate A and fusidic
acid–erythromycin isolate A each had only one SNP.
Erythromycin isolate C had no ribosomal protein mutations
but attained considerable resistance to erythromycin through
an alternate means.
Mutations in the fusA gene, known to confer fusidic acid
resistance in S. aureus (Besier et al. 2003), were observed in all
isolates evolved to fusidic acid as well as the amikacin-evolved
isolates. fusA gene mutations have previously been found to
confer aminoglycoside resistance in S. aureus (Norstr€om et al.
2007). The fusA gene mutations observed in the amikacinevolved lineages conferred both high levels of amikacin and
fusidic acid resistance, highlighting how cross-resistance can
undermine the effect of drug combinations (figs. 2 and 5). It
should be noted that fusidic acid and amikacin do not share
overlapping binding sites. Fusidic acid binds to elongation
factor G in complex with the ribosome (Turnidge and
Collignon 1999), whereas amikacin binds to the 30S ribosome
(Wright 2007).
The ciprofloxacin-, ampicillin-, and ciprofloxacin–ampicillin-evolved isolates shared a mix of well-documented canonical and lesser-known mutations. For example, all three
isolates evolved to ampicillin and ciprofloxacin–ampicillin
isolate B had mutations in the pbpA gene, which codes for
penicillin-binding protein 1 (Wada and Watanabe 1998).
Ciprofloxacin–ampicillin isolates A and C had mutations in
an uncharacterized transport protein (NWMN600), which
Resistance Evolution Dependent on Collateral Resistance . doi:10.1093/molbev/msv006
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may have helped provide resistance to ampicillin in the absence of mutations in penicillin-binding proteins (supplementary fig. S1, Supplementary Material online). Correspondingly,
all isolates evolved to ciprofloxacin and ciprofloxacin–ampicillin had mutations in the parC gene, which codes for DNA
topoisomerase IV subunit A, and is known to confer low-level
resistance to ciprofloxacin (Janoir et al. 1996). The ciprofloxacin-evolved isolates had additional mutations in the gyrA
gene, which is responsible for higher levels of quinolone resistance (Ferrero et al. 1995). When parC and gyrA mutations
are both present an organism has high-level quinolone
resistance (Janoir et al. 1996; Kaneko et al. 2000) (fig. 3).
The deficiency of gyrA gene mutations manifested in
the tolerance of ciprofloxacin by the ciprofloxacin–
ampicillin-evolved lineages (supplementary fig. S1,
Supplementary Material online). Reduced fitness was not
observed for most of the isolates (supplementary data S1,
Supplementary Material online).
All isolates evolved to doxycycline and its corresponding
combinations, with the exception of one, had mutations in
the rpsJ gene, which codes for the 30S ribosomal protein S10.
Doxycycline targets the 30S ribosomal subunit and inhibits
the binding of aminoacyl-transfer RNA (tRNA) to the mRNA
ribosome complex. Ribosomal protein S10 is involved in the
binding of tRNA to the ribsosome (Yaguchi et al. 1980) and
mutations in this gene have previously been shown to confer
high level tetracycline resistance in Neisseria gonorrhoeae (Hu
et al. 2005). Doxycycline–ciprofloxacin isolate A was the only
isolate without an rpsJ gene mutation. This isolate had the
least resistance to doxycycline (supplementary fig. S1,
Supplementary Material online) of all the doxycycline combination-evolved isolates. Moreover, the overall IC90 improvement by this isolate was 10 less than other two
replicate isolates.
It should be noted that a variety of auxiliary mutations
were observed in both the single-drug- and combinationdrug-evolved isolates and appear to support the principal
target mutations. These supplementary mutations were assessed and grouped according to function (supplementary
data S2, Supplementary Material online). Instances of
shared auxiliary mutations between the single-drug- and
combination-evolved isolates were limited; however, the numerical distribution of these mutations was approximately
equal among all sequenced isolates. Many of the auxiliary
mutations were part of a larger stress response network,
which likely participated in or aided resistance. For example,
all isolates evolved to ciprofloxacin–ampicillin had mutations
in the relA gene, which initiates the stringent response under
environmental stress. This controls the production of the
alarmone ppGpp, which in turn serves as a regulator of a
variety of metabolic pathways and processes and has been
shown to play an essential role in decreased sensitivity to
penicillin (Kusser and Ishiguro 1985, 1987; Rodionov and
Ishiguro 1995; Wu et al. 2010) and quinolones (Viducic
et al. 2006). relA mutations were also observed in fusidic
acid–amikacin isolate A and erythromycin isolate B.
In spite of the auxiliary mutations observed in the evolved
strains, mutations associated with resistance to individual
drugs dominated the mutations found in the combinationevolved isolates. Speed of resistance development by
combination-evolved lineages was a function of how these
mutations interacted to cause either cross-resistance or
cross-sensitivity. In the case of the doxycycline–ciprofloxacinand doxycycline–erythromycin-evolved isolates, the mutations required for resistance to the constituent drugs resulted
in considerable cross-resistance between the single-drugevolved isolates and culminating in elevated evolvability
values for the combination-evolved isolates. A similar
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FIG. 6. Primary target genes affected by resistance adaptation. The most evolved isolates were sequenced and compared with the ancestral WT and the
media adapted lineages to identify mutations resulting from resistance adaptation. Canonical resistance mutations were observed in both the singledrug- and combination-evolved isolates. Mutations associated with resistance to individual drugs dominated the mutations observed in the combination-evolved isolates.
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de Evgrafov et al. . doi:10.1093/molbev/msv006
situation was observed for the fusidic acid–amikacin-evolved
isolates, where the same single resistance mutation was required for both constituent drugs resulting in cross-resistance
between the single-drug-evolved isolates. In contrast, adaptation to fusidic acid and erythromycin resulted in strong cross
sensitivity and was reflected in the reduced evolvability values
of the combination-evolved isolates. Our findings stress the
importance of collateral effects in limiting resistance
evolution and not drug interactions.
Discussion
Materials and Methods
Bacteria and Reagents
A drug sensitive S. aureus strain Newman was adapted to five
antibiotics: Amikacin sulfate (Sigma), ampicillin sodium salt
(Sigma), ciprofloxacin hydrochloride (AppliChem), erythromycin (Sigma), fusidic acid sodium salt (Sigma), and doxycycline hyclate (TCI) and the following drug pair combinations:
fusidic acid–amikacin, fusidic acid–erythromycin, ampicillin–
ciprofloxacin, doxycycline–ciprofloxacin, and doxycycline–
erythromycin. Drug stock solutions were prepared weekly.
All evolution and MIC experiments were performed using a
modified Luria broth (LB) media. The salt content was reduced to 4 g/l instead of 5 g/l.
Evolution of Antibiotic Resistance
A WT IC90 was established for each antibiotic. Drug pair
combinations were a 1:1 IC90 mixture of the component
drugs. WT IC90s were also established for each drug pair.
All evolution experiments began one dilution step below
their respective IC90 concentration. Evolution experiments
involved challenging a WT organism with increasing concentrations, in steps of the square root of 2, of individual drugs or
drug combinations. All evolution experiments were performed in triplicate in a modified Luria–Bertani (LB) broth
in microtiter plates. Each experiment included both negative
and positive control wells. The positive control was the inoculating strain in LB media only. Following an 18-h growth
period at 37 C, the microtiter plates were measured for
OD at wavelength 600 nm (OD600). The value of the experimental positive control was used to normalize the evolution
data. A cut off of 60% inhibition was used to determine the
starting concentration of the next experiment. This concentration was referred to as the experimental MIC. The 60%
inhibition value was chosen based on pre-experimental work
that found that this value consistently ensured a resistant
population was used in subsequent exposure experiments.
The replicate with the best growth at the experimental
MIC concentration was used as seed material for the next
experiment. The selected seed was added to fresh LB media
containing the appropriate drug(s) concentration and allowed to grow over night. The overnight culture was then
used to inoculate the next challenge experiment. A portion of
this culture was saved. The challenge process was repeated a
total of five times for each individual drug and drug combination. The same adaptation procedure was used for the
media only evolved populations.
IC90 Determination
Following adaptation, isolates of the adapted populations
were profiled for their individual resistances. IC90 determination was performed according to standardized methods
(Andrews 2001). Briefly, lineages from the fifth exposure
were plated on nonselective media and allowed to grow overnight. Four individual isolates were then randomly selected
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We sought to extend the current scientific paradigm by expanding the concentration ranges considered to envelope
concentrations likely to be encountered during clinical treatment. The motivation for this pursuit stems from the fact
that treatment failure typically occurs at elevated concentrations. We pursued our study using the same drugs, combinations, and organism previously employed to develop the
existing model for predicting resistance evolution based on
drug interactions. We hypothesized that at concentrations
above WT MIC, resistance evolution to drug combinations
would be driven by the constituent drugs and collateral sensitivity interactions.
We were unable to reproduce the expected correlation
between resistance evolution, as measured by evolvability,
and drug interactions, as assessed by the fractional inhibitory
combination index, at drug concentrations above WT MIC.
We hypothesize that this is due to the fact that drug interactions are modulated by resistance evolution. The dynamic
nature of drug interactions challenges their use as reliable
predictors of long-term resistance evolution.
Results of our experimental evolution and genome sequencing work suggest that the evolutionary responses to
individual constituent drugs are better predictors of resistance evolution. A drug pair where adaptation to one constituent drug confers cross-resistance to the other or where
both constituent drugs share the same resistance mutations
will undermine the effect of the combination and will likely
have greater resistance evolution due to cross-resistance. In
contrast, a pair where resistance evolution to one constituent
results in collateral sensitivity to the other will have slower or
reduced evolution due to the incompatibility of the individual
resistance profiles. Finally, in between these two poles is the
case where resistance to constituent drugs is unrelated/independent. Resistance to this drug pair is achieved in a measured fashion by individually acquiring mutations for each of
component drugs.
In conclusion, we find that above WT MIC levels, individual
constituent drugs and their associated resistance mutations
are reliable predictors of a combination’s potential resistance
evolution. Mutations associated with resistance to one
constituent drug of a combination have the power to
either promote or obstruct resistance to another component
in the same combination. We suggest that rather than continuing to focus on drug interactions, further research should
consider the mutations that will arise from resistance adaptation and pursue those combinations with diverging
evolutionary trajectories, as these combinations will likely
limit resistance evolution best.
Resistance Evolution Dependent on Collateral Resistance . doi:10.1093/molbev/msv006
Calculation of Evolvability Index
The evolvability index assesses how resistance evolution
toward a combination compares with individual drug resistance evolution. The index is determined by summing a combination-evolved strain’s resistance to each of its component
drugs relative to the resistance development of the corresponding single-drug-evolved lineages and then taking an average. Each individual fraction can be used to assess how
resistance evolution to an individual component is
impacted as a result of being used in a combination.
The evolvability index is calculated as:
1 IC90½AAB IC90½BAB
Evolvability Index ¼
þ
; ð2Þ
IC90½BB
n IC90½AA
where the n is the number of components in a mixture and is
used to determine an average value. IC90[A]AB refers to the
IC90 of the AB-evolved lineage tested against drug A.
Calculation of CCD
Using the equation set forth by Lee et al (2011), n is the
number of generations for each growth step. In our case,
there are two growth steps—the resistance experiment and
the test tube pregrowth period prior to each resistance experiment. n values were calculated for each evolved lineage
and the two growth steps.
We performed growth kinetic experiments that allowed us
to calculate a generation time (G in min1) for each strain.
These values were then used to determine the number of
generations for each strain in an 8-h period (assumed log
growth phase) or n.
In the Lee equation, CCD is
M
X
N0 ð2N 1Þ;
ð1Þ
I¼1
where N0 is the initial number of cells in each well or test tube
during evolution. We used representative values of N0, reflecting each growth condition, for each strain to calculate the
CCD for the test tube and resistance experiment periods. The
subsequent CCD values were multiplied by 5 to reflect the
number of evolution periods for each growth condition. A
CCD value was calculated for each replicate lineage (supplementary data S1, Supplementary Material online). The average CCD value in the text comes from adding the two growth
conditions together.
Data Analysis
The OD600 data were analyzed using Excel and Prism
(GraphPad Software). Briefly, negative control values were
subtracted from all growth wells yielding dose–response
values. These data were then normalized by the positive control data and then used to determine the fraction of inhibition, calculated as: 1 normalized dose response of strain X.
Inhibition data were plotted in Prism and IC90 read from
graph.
Sequencing
Genomic DNA from our most evolved strains and WT was
isolated using either an UltraClean Microbial DNA Isolation
Kit (MoBio Laboratories, Inc.) or a modified chloroform/
phenol extraction method. Briefly, lysostaphin in conjunction
with proteinase K was used to disrupt the cell wall. The extracted DNA was sheared into 200-bp fragments using a
Covaris E210 and barcoded libraries were constructed for
Illumina or IonTorrent sequencing. Illumina sequencing was
performed by Partners HealthCare Center for Personalized
Genetic Medicine (Cambridge, Massachusetts) and by
Sequencing, Informatics and Modeling Group at The Novo
Nordisk Foundation Center for Biosustainability, Technical
University of Denmark (Hørsholm, Denmark). IonTorrent sequencing was performed by DTU Multi-Assay Core (Kongens
Lyngby, Denmark). All reads were aligned to S. aureus subsp.
aureus str. Newman (NC_009641.1) using Bowtie2 version
2.0.0-b6 with the default options (Langmead and Salzberg
2012). An average of 99.6% (minimum 97.5%) of the
genome was covered with an average read coverage of
125 40 (CI95) (supplementary data S2, Supplementary
Material online), as determined using BEDTools (Quinlan
and Hall 2010). Variant calling for SNPs and INDELs was
done using SAMTools version 0.1.17 with the –B,-L 1,000
options(Li et al. 2009). Only SNPs with a phred score of at
least 30 and where at least 80% of the reads aligned at the site
had the variant were used. INDELs were verified by aligning
constructed contigs around INDEL sites to the reference
genome (Zerbino and Birney 2008; Li and Durbin 2009).
The BioCyc database collection (Karp et al. 2005) was used
to identify and annotate mutation sites.
Supplementary Material
Supplementary data S1 and S2 and figures S1 and S2 are
available at Molecular Biology and Evolution online (http://
www.mbe.oxfordjournals.org/).
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from each plate and grown in nonselective liquid media for
4–5 h before being used to inoculate additional IC90 experiments. All single-drug isolates were tested against the agent
they had been adapted to as well as their corresponding drug
combination and matching component drug. Combinationevolved isolates were tested against the combination to
which they had been adapted and the commensurate component drugs. In both the population and single isolate experiments, the inoculum size for each well was approximately
104 cells. All IC90 experiments were performed in 96-well
microtiter plates in quadruplicate using 2-fold dilution
steps. Positive, isolate in LB media only, and negative controls
were included in each test. Inoculated plates were placed on
an orbital shaker (300 rpm) and incubated at 37 C for at least
16 h. After the allotted growth period, OD600 was read on a
BioTek Epoch plate reader.
MBE
de Evgrafov et al. . doi:10.1093/molbev/msv006
Acknowledgments
The authors thank Elizabeth Rettedal for discussion and
advice and Gautam Dantas for input on the manuscript.
This work was supported by the Danish Free Research
Councils for Health and Disease. M.O.A.S. further acknowledges support from the Novo Nordisk Foundation, the
Lundbeck Foundation, and the European Union FP7HEALTH-2011-single-stage grant agreement 282004, EvoTAR.
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