ABUNDANCE OF nifH GENES IN URBAN, AGRICULTURAL, AND PRISTINE
PRAIRIE STREAMS EXPOSED TO DIFFERENT LEVELS OF NITROGEN
LOADING
A Thesis by
Ingrid Rocio Caton
B.A., Pontificia Universidad Javeriana, 2002
Submitted to Department of Biological Sciences
and the faculty of the Graduate School of
Wichita State University
in partial fulfillment of
the requirements for the degree of
Master Of Science
May 2007
© Copyright 2007 by Ingrid Rocio Caton
All Rights Reserved
ABUNDANCE OF nifH GENES IN URBAN, AGRICULTURAL, AND PRISTINE
PRAIRIE STREAMS EXPOSED TO DIFFERENT LEVELS OF NITROGEN
LOADING
I have examined the final copy of this Thesis for form and content and
recommend that it be accepted in partial fulfillment of the requirement for the
degree of Master of Science with a major in Biological Sciences.
___________________________
Mark A. Schneegurt, Committee Chair
We have read this Thesis
and recommend its acceptance:
___________________________________
Christopher M. Rogers, Committee Member
________________________________
Jason W. Ferguson, Committee Member
iii
DEDICATION
To mom and dad,
Thanks for believing in me, for helping me with my childhood dreams,
I did this because of you both.
Mamita y papito los adoro con toda mi alma,
To Todd,
wonderful, smart, kind, charming, sweet cori, my best friend.
Because you inspire me.
Con todo mi amor, para el unico y gran amor de mi vida.
Gracias por todos tus consejos,
Por no dejarme desfallecer.
To Carter,
My smarty sweetie Milo drinker
And last but no least my brothers: Daniel y Jorge,
Because you two made my life easy and we
are a great team, all my love.
iv
ACKNOWLEDGEMENTS
The author would to thank Dr. Mark Schneegurt for his guidance and support
of this research. His patience and advice are greatly appreciated. Thanks also to
Dr. Chris Rogers and Dr. Jason Ferguson, for serving as a committee members
and for their annotations and suggestions. Dr. Walter Dodds and KSU Research
Group and Dr. David Graham and KU Research Group for their continous work
on the LINX project and their information about the streams..
Todd Caton, who taught me everything I need to know about the lab. Also
he performed sampling and ARA analyses. His guidance, unconditional support,
advice, technical assistance and good humor made my research much easier.
Monica Rueda, for her constant support and advice. Gracias primita.
I would like to thank Sarah Castro for performing the standard curves for
archaea, I hope you remember me when you are working for NASA. A number of
WSU undergraduate and graduate students who participated in different aspects
of this project: Brandon Litzner, Daniel Guztner, Sarah Castro, Brooke Landon,
Lisa Witte. To all my fellows that are part of the Biology Department.
A Number of faculty members, whose advice provided invaluable
knowledge and support as well as technical assistance: Bobbie Pettriess, the late
Darren Francisco, Dr. Peer Moore-Jansen, Dr. David McDonald, Dr. Kent
Thomas, Dr. Karen Brown, Dr. Li Jia, Dr. Jeff May.
Special thanks to Maria Russell for all her support, because she is the one
who solves any problem.
v
Most importantly to my husband for being with me whenever I needed
him; my son, Carter because he made me forget bad moments and frustrations
during my research, and last but not least, my parents, Yolanda and Eufracio,
and my brothers for their constant support and encouragement.
Thank you all.
vi
ABSTRACT
Ecosystem processes drive biogeochemical cycles that influence input and
losses of nutrients in the biosphere. Through human activities the environment
has been highly enriched with nutrients, especially nitrogen.
In most
ecosystems, nitrogen availability should be limited, but soils and aquatic
ecosystems have been anthropogenically impacted. In streams, availability of
nutrients, geochemical characteristics, hydrodynamics, and human activities
influence the metabolic activities and structure of microbial communities. The
aim of the current study is to contrast gene abundance and metabolic responses
of N2-fixing guilds exposed to chronic nitrogen loading in three different types of
Kansas prairie streams: urban, agricultural, and pristine. Nitrogen-fixation activity
was expected to be negatively correlated to the level of fixed nitrogen, while nifH
(nitrogenase gene) abundance would be unchanged. A combination of processlevel and molecular techniques were applied to study nitrogen fixation in these
small prairie streams. Nitrogen fixation activity was measured with acetylene
reduction assays.
Rates of acetylene reduction for urban, agricultural, and
pristine prairie streams were 1.5 to 93.5, 2.1 to 112.8, and 2.9 to 81.9 fmol N2/g
soil/h, respectively. The highest rates were found in leaf litter, sediments and
algal biofilms.
Samples of sediments and leaf litter were field-frozen for
molecular analyses of the nitrogen-fixing microbial guild. Direct DNA extracts
were examined by SYBR real-time PCR to determine the abundance of nifH,
given a detection limit of 2 x 102 nifH gene copies/g sample. The abundance of
bacterial 16S rRNA was between 1.0 x 106 to 1.0 x 1012 gene copies per gram
vii
sample. The abundance of archaeal 16S rRNA was between 1.0 x 108 to 1.0 x
1012 gene copies per gram sample. The abundance of nifH genes ranged
between 1.0 x 103 to 1.0 x 107 gene copies per gram in all streams. The assay
was quantitative over at least 8 orders of magnitude, from 1 ng to 0.1 pg of nifH
target. This study provides a link between the abundance of nifH genes and
nitrogen-fixation activity. An understanding of the effects of nitrogen pollution on
nitrogen cycling guilds in small streams will increase our ability to overcome the
challenges of nutrient pollution. This work was supported by Kansas NSF
EPSCoR Ecological Genomics.
viii
TABLE OF CONTENTS
Chapter
Page
1. INTRODUCTION AND LITERATURE REVIEW………………………..1
Nitrogen fixation…………………………………………………………….4
Nitrogenase enzyme……………………………………………………….8
Acetylene reduction assay………………………………………………..10
nif genes…………………………………………………………………….12
nifH genes…………………………………………………………………..14
Nitrogen fixation organisms……………………………………………….17
Real time PCR………………………………………………………………20
Streams………………………………………………………………………24
2. AIM…………………………………………………………………….…...…31
Hypotheses……………………………………………………………….....33
Objectives…………………………………………………………………....35
3. METHODOLOGY……………………………………………………………36
Study sites……………………………………………………………………36
Sample collection……………………………………………………………37
Acetylene reduction assays……………………………………………….38
DNA extraction……………………………………………………………...39
ix
TABLE OF CONTENTS (Cont.)
Real-time PCR………………………………………………………………41
Real-time PCR inhibition assay……………………………………………45
4. RESULTS AND DISCUSSION…………………………………………….47
Acetylene reduction assays………………………………………………..47
Gene abundance by real time PCR……………………………………….41
5. CONCLUSIONS……………………………………………………………..58
6. LIST OF REFERENCES……………………………………………………63
7. APPENDICES……………………………………………….……………….73
Appendix A: tables………………………………………….……………….74
Appendix B: figures…………………………………………….……………93
x
LIST OF TABLES
Table
Page
1. Nitrogen cycle gene probes
6
2. The nif gene products and their role (known or proposed)
in nitrogen fixation
13
3. The vnf gene products and their role (known or proposed)
in nitrogen fixation
14
4. Nitrogen-fixing organisms
18
5. Chemical and physical parameters of the six streams in this study
67
6. Assessment of nifH abundance by real-time PCR and nitrogen
fixation by ARA in 2003 Campus Creek (Urban) stream
68
7. Assessment of nifH abundance by real-time PCR and nitrogen
fixation by ARA in 2004 Wal-Mart ditch (Urban) strea
69
8. Assessment of nifH abundance by real-time PCR and nitrogen
fixation by ARA in 2003 North Creek (Agricultural) stream
70
9. Assessment of nifH abundance by real-time PCR and nitrogen
fixation by ARA in 2004 Natalie’s Creek (Agricultural) stream
71
10. Assessment of nifH abundance by real-time PCR and nitrogen
fixation by ARA in 2003 Kings Creek-N4D (Pristine) stream
72
11. Assessment of nifH abundance by real-time PCR and nitrogen
fixation by ARA in 2004 Kings Creek-K2A (Pristine) stream
73
12. Comparison of gene abundance between archaea, bacteria and
diazotrophs in 2003 Kings Creek-N4D (Pristine) stream
74
13. Comparison of gene abundance between archaea, bacteria and
diazotrophs in 2004 Kings Creek-K2A (Pristine) stream
75
14. Comparison of gene abundance between archaea, bacteria and
diazotrophs in 2003 North Creek (Agricultural) stream
76
xi
15. Comparison of gene abundance between archaea, bacteria and
diazotrophs in 2004 Natalie’s Creek (Agricultural) stream
77
16. Comparison of gene abundance between archaea, bacteria and
diazotrophs in 2003 Campus Creek (Urban) stream
78
17. Comparison of gene abundance between archaea, bacteria and
diazotrophs in 2004 Wal-Mart Ditch (Urban) stream
79
18. Real-time PCR efficiency test in 2003 North Creek(Agricultural)
stream by comparison of the amplification rates (Ct values)
80
19. Real-time PCR efficiency test in 2004 Natalie’s Creek (Agricultural)
stream by comparison of the amplification rates (Ct values)
81
20. Real-time PCR efficiency test in 2003 Campus Creek(Urban)
stream by comparison of the amplification rates (Ct values)
82
21. Real-time PCR efficiency test in 2004 Wal-mart Ditch (Urban)
stream by comparison of the amplification rates (Ct values)
83
22. Real-time PCR efficiency test in 2003 Kings Creek-N4D (Pristine)
stream by comparison of the amplification rates (Ct values)
84
23. Real-time PCR efficiency test in 2004 Kings Creek-K2A (Pristine)
stream by comparison of the amplification rates (Ct value
85
xii
LIST OF FIGURES
Figure
Page
1. Diagram of the different steps involved in nitrogen cycle
2
2. Biochemical reaction of dinitrogen being converted into ammonium
5
3. Correlation of acetylene reduction and nitrogen fixation
11
4. Sampling sites for all three types of streams each year: 2003 and 2004
86
5. 2003 Campus Creek stream ARA
87
6. 2004 Walmart – Ditch stream ARA
88
7. 2003 North Creek stream ARA
89
8. 2004 Natalie’s Creek stream ARA
90
9. 2003 Kings Creek N4D stream ARA
91
10.
2004 Kings Creek K2A ARA
92
11.
nifH real-time PCR
93
12.
Real-time PCR nifH melting curve
94
13.
Standard curve for nifH genes
95
14.
Standard curve for archaeal 16S rRNA genes
96
15.
Standard curve for bacterial 16S rRNA genes
97
xiii
LIST OF ABBREVIATIONS / NOMENCLATURE
ADP
Adenosin diphosphate
ARA
Acetylene reduction assay
ATP
Adenosin triphosphate
bp
Basepair
CH≡CH
Acetylene
C2H2
Acetylene
C2H4
Ethylene
CH2=CH2
Ethylene
CO
Carbon monoxide
CO2
Carbon dioxide
Da
Daltons
DNA
Deoxyribonucleic acid
e-
Electron
g
Gram
Fe
Iron
fg
Fentogram
f
Fento
FeMo-co
Iron molybdenum cofactor
G+C
Guanine and cytosine
h
Hour
H2
Hydrogen
xiv
H2O
Water
Kb
Kilobases
kD
KiloDaltons
Km2
Square kilometer
L
Liter
M
Molar/mol
Mg
Magnesium
mg
Miligram
min
Minute
ml
Mililiter
mM
Milimolar
MoFe
Molybdenum -Iron
N
Nitrogen
N
North
N2
Dinitrogen
15
Radiolabel nitrogen
N
NH3
Ammonia
NH4
Ammonium
NO3
Nitrate
N2O
Dinitrogen oxide
O2
Oxygen
P
Phosphorus
PCR
Polymerase chain reaction
xv
Pi
Inorganic phosphorus
pg
Picogram
S
Sulfur
Spp
Specie
V
Vanadium
v/v
Volume to volume
W
West
wk
Week
w/v
Weight to volume
xvi
LIST OF SYMBOLS
α
Alfa
β
Beta
γ
Gamma
δ
Delta
µ
Micro
%
Percentage
o
Degree
°C
Degree Celsius
A
Absorbance
xvii
CHAPTER 1
INTRODUCTION
“Every child deserves to grow up with water that is pure to drink, lakes that are
safe for swimming, rivers that are teeming with fish. We have to act now to
combat these pollution challenges with new protections to give our children the
gift of clean, safe water in the 21st century. ”President Clinton, 23 February 1999,
Baltimore (27)
In aquatic environments, microbial communities play an important role in
keeping biogeochemical cycles in a constant balance. Nevertheless, the
metabolic abilities of each microbe in its natural environment are not well
understood, nor are their specific roles in microbial communities. Microbes may
have several functions that involve enzymatic complexes, with a large diversity of
functional genes likely to be important in protein-enzyme expression; they may
act in response to different factors that control their distribution in the
environment, as associated with different microbial assemblages.
The nitrogen cycle, one of the biogeochemical cycles, consists of a series
of oxidation-reduction reactions that include transformations of several
nitrogenous compounds that are carried out by microorganisms via enzyme
complexes, as illustrated in Figure 1. Microorganisms are primarily implicated
and metabolism of nitrogen is directly related to productivity in diverse
ecosystems (15, 27, 118). In most ecosystems, nitrogen availability is limited.
Nitrogen may become available through different sources, from decomposition of
organic matter through ammonification, or fixation of molecular nitrogen by
microorganisms (109).
AMMONIFICATION &
ASSIMILATION
NITRIFICATION
OXIC
ORG N
NH4+
NO2-
NO3-
ANOXIC
N2O
N2 FIXATION
N2
DENITRIFICATION
Figure 1. Diagram of the different steps involved in the nitrogen cycle
Nitrogen that is available for uptake by microorganisms in different
ecosystems can come from inorganic sources, in the form of dinitrogen, nitrate,
nitrite and ammonium, or different organic sources, likely to be in nitrogenous
biomolecule types from the decomposition of organic matter. In streams,
inorganic N can be easily assimilated by microorganisms and leads to high
concentrations of biomass and dissolved organic nitrogen (28, 118). While some
microorganisms fix nitrogen from the atmosphere, other microorganisms perform
denitrification and return nitrogen to the atmosphere in order to maintain the flux.
However, with anthropogenic inputs of nitrogen, this process may be affected
and become unbalanced (79). Several processes take place during the nitrogen
2
cycling process: fixation of molecular nitrogen, ammonification, nitrification,
nitrogen assimilation and denitrification.
Nitrification or ammonia oxidation is performed in the presence of oxygen
by autotrophic ammonia-oxidizing bacteria. There are two steps to this process;
ammonia is oxidized into nitrite and finally nitrite is oxidized into nitrate. This form
of nitrogen does not attach to soil particles very well; therefore, nitrate can leach
from the soils to surface and ground waters, creating contamination processes
such as eutrophication. Furthermore, nitrate's reduction in soils affects
agricultural crops, where farmers lose about 30% of fertilizers that have been
added to the land. Moreover, if the process is not completed, by-products such
as nitric oxide and nitrous oxide are produced and released to the atmosphere,
increasing the greenhouse effect and diminishing the ozone layer (74).
Denitrification occurs in strictly anaerobic conditions and numerous
organisms contribute to the process through reduction reactions (8). This is the
conversion of nitrate into nitrogen gas; by-products of this process also raise
contamination in the environment (6, 74). This part of cycle creates the balance
of the cycle, besides controlling the availability of nitrogen in the ecosystem.
Many different organisms are able to perform ammonification. During this
process organic nitrogen is converted into ammonia. The ammonia released from
decomposed organic matter is incorporated into amino acids by living organisms
in order to produce biomolecules such as vitamins, proteins, and nucleic acids
(4).
3
Studies in molecular biology have opened an enormous window that
makes it possible to study and understand the nitrogen cycle’s catalytic
reactions, performed by enzymes, and coded by different genes found in
microbial populations of natural assemblages, as shown in Table 1 (59, 118).
Nitrogen fixation
Globally, nitrogen fixation can occur in three different ways: first, is
atmospheric nitrogen fixation by lightning that accounts for about 5%-8% of the
total nitrogen fixed. Second, is industrial fixation by the Haber-Bosch process,
that requires a lot of energy and the method by which fertilizers are made,
accounting for about 50% of the nitrogen is fixed The third way is called
biological nitrogen fixation, as carried out by free-living microbes or those in
symbiotic associations with plants, accounting for the rest of the nitrogen fixed in
the environment.
Biological nitrogen fixation is the process by which gaseous dinitrogen
from the atmosphere is reduced to ammonia through a biochemical pathway in
which the reduction is catalyzed by the enzyme nitrogenase (94). Nitrogenase
reduces molecular N2 into ammonium (NH4) with the simultaneous reduction of
protons to hydrogen (108). The process of fixing molecular nitrogen is a
characteristic only found in prokaryotes, the bacteria and archaea, including
aerobic, microaerophilic, facultative, and strictly anaerobic microorganisms that
have the ability to fix nitrogen (108). Nitrogen fixation occurs in a vast array of
4
different environments such as seagrass (108), plant rhizospheres (79),
rhizosphere sediments (80), marine environments (35, 116), hypersaline lakes
(96), rice roots (103), salt marshes (4, 58), forest ecosystems (93, 109), guts of
diverse termites (73), hydrothermal vents (65), soils from Antarctica (75, 87),
freshwaters (59) and other aquatic environments (29, 118). Nitrogen fixation
usually occurs under anaerobic conditions (40).
N2-fixation processes require ATP, reduced ferrodoxin and other
cytochromes and coenzymes. In this reaction 8 e- are used, because of the NH3
+ H2 formed as a final product. As shown in Figure 2, this chemical reaction is
highly energy expensive. It requires significant amounts of reducing power along
with energy from ATP (6, 16).
N2 + 8e- + 16 ATP + 16 H2O
2NH3 + H2 +16 ADP + 16 Pi + 8H+
Figure 2. Biochemical reaction of dinitrogen being converted into ammonium
The nitrogenase enzyme complex has low specificity for natural substrates
and can metabolize similar triple bond compounds; this made it possible to
develop techniques that allow researchers to measure nitrogen fixation
processes in the laboratory and in the field. This technique is called the acetylene
reduction assay (ARA). The N-N triple bond is highly stable, making the nitrogen
fixation process energetically expensive; the energy demand is 16 mol of ATP
per mol of N2 fixed (108). Also, nitrogen fixation involves a large amount of DNA
(about 20 kb), because of the assembly and function of the proteins. And,
5
because of the regulation by multiple genes, overall nitrogenase expression is
highly genetically regulated (114, 115).
TABLE 1
NITROGEN CYCLE GENE PROBES
Transformation
Gene(s)a
Protein
N2 fixation
nifHDK
Nitrogenase
Nitrite assimilation
nir
Nitrite reductase
Nitrate assimilation
narB, nasA
Assimilatory nitrate reductase
Ammonium assimilation
glnA
Glutamine synthetase
Nitrate respiration and
nirS
Nitrate reductase
denitrification
nirK
Nitrite reductase
norB
Nitric oxide reductase
nosZ
Nitrous oxide reductase
Organic N metabolism
ure
Urease
Ammonium
amo
Ammonia monooxygenase
ntc
Nitrogen regulatory protein
oxidation/nitrification
Nitrogen regulation
(cyanobacteria)
a
Nitrogen cycle genes for which probes or PCR primers have been designed.
6
Environmental conditions and changes in biogeochemical cycles can
affect the rate of nitrogen fixation. For example, higher rates of nitrogen fixation
have been observed in humid tropical forests and lower rates in arid systems
(91). Nitrogen fixation is regulated at the level of transcription, depending on
environmental oxygen and ammonium levels. There are different microorganisms
that have the capability to fix atmospheric nitrogen (N2) into ammonia by using
this nitrogenase enzyme complex, which ultimately, will be utilized by plants for
biomass formation (94). This step of the nitrogen cycle is biologically important,
because of the input of fixed nitrogen in various terrestrial, aquatic, and marine
ecosystems (107, 114, 115).
Nitrogenase Enzyme
Biological fixation of dinitrogen is catalyzed by an enzyme complex found
in prokaryotes called nitrogenase. The activity of nitrogenase is important for
maintaining the equilibrium of the nitrogen cycle (14). Nitrogenase activity is also
critical because nitrogen is a limiting element during biological processes despite
many reservoirs such as igneous rocks and atmospheric nitrogen (65, 89, 114).
Nitrogenase has shown a high conservational level of its structure and role
among a wide microbial distribution (24).
The nitrogenase system is composed of two subunits of metallo-proteins.
The larger component, subunit I or dinitrogenase, performs the nitrogen
reduction, and is also referred to as MoFe protein or component I. Component I
7
has a molecular weight of about 220 to 250 kD. This tetramer has two metallocomplex heterodimers known as a P-cluster and the iron molybdenum cofactor
(FeMo-co) that are encoded by the nifD and nifK genes. One subunit has an α-β
pair and each pair has one P-cluster and one FeMo-co molecule. The FeMo-co
molecule has one homocitrate and one MoFe3-S3 group. The P-cluster is located
in the interface between the α-β-subunit; it possesses a similar structure to the
FeMo-co and consists in 8 Fe and 7 S. This group is the electron transfer
intermediate (14, 24, 48, 89, 94, 114).
The smaller component, subunit II or component II, also known as
dinitrogenase reductase, has a molecular weight of about 60-70 kD. This subunit
pairs ATP hydrolysis to interprotein electron transport and is composed of two
identical subunits that are encoded by the nifH gene. This component has two
identical α-subunits that contain a single 4Fe-4S group bound between the
subunits' interface. It also has two Mg-ATP-binding sites localized in each of the
subunits. This part is the obligate electron donor to the MoFe complex. Moreover
this subunit is in charge of the biosynthesis of FeMo-co and the maturation of the
apo-MoFe protein (14, 24, 31, 48, 89, 94, 114).
There are different varieties of nitrogenase that have been categorized
depending on the type of metal group that is important for the active or binding
site of the enzyme. The first family of nitrogenases has two components of COdehydrogenase that couples the oxidation of CO to CO2 and reduces O2 to a
superoxide form, O2-. The second family contains a manganese component, an
oxidoreductase, which oxidizes O2- , providing electrons to the dininitrogen, and
8
reduces the MoFe group. The third families are more alike because they have a
metal group in the active site; this includes molybdenum (Mo), vanadium (V), or
iron (Fe) only. Component I and component II contain Fe-S centers and
coordinate between the subunits (114). If the subunits have a bridge of Mo-Fe-S
they are called conventional nitrogenases. In alternative nitrogenases, Mo in the
active group is replaced with V or Fe (48, 114).
Although the conventional nitrogenase is well known and it is the most
common nitrogenase found in biological systems, there are two alternative
systems that differ genetically, have a third subunit, δ, that is coded by vnfG and
anfG genes, are less effective than the conventional system, and also differ in
substrate specificity (14, 89). These alternative V- and Fe-only-containing
nitrogenases are encoded by the vnf and anf genes respectively and present an
hexameric structure that is encoded by the vnfDGK and anfDGK operons(89).
Nitrogenase is extremely sensitive to O2 that can inhibit the reaction (14,
106, 114, 115). Also, the nitrogenase complex is regulated by other external
factors such as darkness, light, amount of fixed nitrogen, nitrogen available in the
environment, and regulation through allosteric sites, existing co-factors, chaperon
presence, transcription, and pre- and posttranslational events (20, 34, 52, 103,
106).
This enzyme also catalyses the reduction of a variety of substrates and
usually these kinds of substrates tend to have a triple bond in their chemical
structure, such as N2O, cyanide, methyl isocyanide, azide, cyclopropene,
cyanamid, diazarine and acetylene. The latter is the best example, where the
9
product of the acetylene reduction (CH≡CH or C2H2) is ethylene (CH2=CH2 or
C2H4) (14, 94).
Acetylene reduction assay
Acetylene reduction is the most useful method to measure nitrogenase
activities or N2 fixation in different types of environmental samples, wherein
ethylene can be detected at very low concentrations using a gas chromatography
unit equipped with a flame ionization detector. While the
15
N fixation method
measures the net assimilation of N2 into biomass and does not give an overall
count for nitrogen losses during the incubation periods, ARA measures the total
amount of nitrogen that has been fixed during nitrogen fixation by diazotrophic
communities (94). The ARA is the most well-known method used by microbial
ecologists for measuring nitrogenase activity in natural samples in situ and in
vitro (41, 53, 94). This technique was developed in the late 1960’s by Stewart et
al. (1967) and Hardy et al. (1968) in order to aid studies on N2 fixation in field
samples by symbiotic associations (7, 41, 97). Since then, more studies have
shown that this method is extremely sensitive, detecting <1 µmole of C2H4 per
sample, making it 103 times more sensitive than the
15
N-method. It is relatively
inexpensive (acetylene, assay hardware and a gas chromatograph are less
expensive than
15
N-substrates, separations, and mass spectrometry), it requires
short incubation times at room temperature, because of the stability of the
substrate, has high specificity where there is direct chemical conversion from
10
acetylene to ethylene (where ethylene is the most significant product in the
reaction), and it is very simple to use as an index of N2 fixation in environmental
samples in comparison with
15
N-method (7, 8, 36, 41, 47, 62, 76, 77, 92, 94, 97,
102, 106). Also, gas chromatography is a less demanding and faster technique.
ARA is an indirect, quantitative method that relates acetylene molecules reduced
with N2 fixed using a conversion factor of 3.8 to 1; in other words, 3.8 molecules
of acetylene reduced is equivalent to 1 dinitrogen molecule fixed. Using gas
chromatography, the final concentration of ethylene produced can be measured,
and is proportional to the amount of nitrogen fixed following the conversion factor
given above. On this basis, the reduction of acetylene to ethylene occurs three
times or faster than the reduction of dinitrogen to ammonia in the environment,
and as a result, different numbers of electrons are required for these two
reactions to occur (from 2 to 8 respectively) and this is shown stoichiometrically
in Figure 3 (6, 41, 48, 94). Prior studies with 15N2 have shown that the conversion
factor can range between 1.9 and 6.3 molecules of acetylene reduced per N2
molecule fixed (77). Also the conversion factor is influenced by the saturation
level of the nitrogenase with acetylene, plus the physiological state of the
diazotrophic population in that specific environment (94).
C2H2 + 2H+ + 2e-
C2H4
N2 + 8H+ + 8e-
2NH3 + H2
Figure 3. Correlation of acetylene reduction and nitrogen fixation
11
nif Genes
There are ~20 genes that encode for the nitrogen fixation pathway.
Moreover, the process is highly energetically expensive, as it requires about 20
kb of DNA to encode for all of the genes required for the assembly and
expression of the enzyme complex (114). Table 2 presents descriptions and
roles of the genes that are involved in regulation of the expression of the
conventional enzyme complex (31).
In addition to the conventional complex, the alternative enzyme shows a
different group of genes that are given in Table 3, that includes an explanation of
the different genes involved in the regulation of the expression of this alternative
system (89). Among diazotrophic populations, there are differences in the
structural organization of the nif genes. For example the nifHDK operon is
responsible for the transcription of the enzyme in gamma- and alphaproteobacteria. However in some slow-growing symbiotic associations, the
transcription is associated with two separate operons, nifH and nifDK (24, 115)
Having a metabolically diverse set of genes in the microbes’ genomes
should provide advantages over other members of the microbial community;
however, it has been shown that the nifH genes do not confer this characteristic
for the population of nitrogen-fixing organisms. NifH, a nitrogen fixation gene, can
serve to identify the distribution of the nitrogen-fixing organisms in specific
environments by measuring their abundance (50).
12
TABLE 2
THE nif GENE PRODUCTS AND THEIR ROLE (KNOWN OR PROPOSED) IN
NITROGEN FIXATION
GENE
IDENTITY AND/OR ROLE OF GENE PRODUCT
nifH
Fe protein. Dinitrogenase reductase. Obligate electron donor to
MoFe protein during nitrogenase turnover. Also required for
FeMo-co biosynthesis and apo-MoFe protein maturation.
α subunit of MoFe protein (dinitrogenase). Forms a α2β2 tetramer
with the β subunit FeMo-co. The site of substrate reduction,
FeMo-co is within the α subunit of dinitrogenase.
β subunit of dinitrogenase. P-clusters are present at each αβ
subunit interface.
Unknown
Chaperone for the apo-MoFe protein. nafY is also a FeMo-co
carrier and is proposed to aid in the insertion of FeMo-co into
apo-MoFe protein eg. Klebsiella pneumoniae.
Forms α2β2 tetramer with nifN. Required for FeMo-co synthesis.
Proposed to function as scaffold on which FeMo-co is
synthesized.
Required for FeMo-co synthesis. Tetramer with nifE.
Involved in FeMo-co synthesis. Accumulates an FeSMocontaining precursor.
Molecular scaffold for the formation of Fe-S cluster for
nitrogenase components.
Involved in mobilization of S for the Fe-S cluster synthesis and
repair.
Homocitrate synthase involved in FeMo-co synthesis.
Involved in stability of dinitrogenase. Propose to protect.
Unknown.
Required for maturation of nifH.
Flavodoxin. Physiological electron donor to nifH in
K.pneumoniae.
Negative regulatory element.
Positive regulatory element.
Required for FeMo-Co synthesis. Its metabolic product, nifB-co,
is the specific Fe and S donor to FeMo-co.
Ferredoxin. In R. capsulatus, serves as electron donor to
nitrogenase.
Involved in FeMo-co synthesis. Proposed to function in early
MoO4 2- processing.
Pyruvate: flavodoxin (ferredoxin) oxidoreductase. Electron donor
to Fe protein in K pneumoniae.
nifD
nifK
nifT
nifY/
nafY
nifE
nifN
nifX
nifU
nifS
nifV
nifW
nifZ
nifM
nifF
nifL
nifA
nifB
fdxN
nifQ
nifJ
13
TABLE 3
THE vnf GENE PRODUCTS AND THEIR ROLE (KNOWN OR PROPOSED) IN
NITROGEN FIXATION
GENE
IDENTITY AND/OR ROLE OF GENE PRODUCT
vnfA
vnfE
vnfN
vnfX
Positive regulatory element.
Proposed to function in FeV-co biosynthesis. Analogous to nifE.
Proposed to function in FeV-co biosynthesis. Analogous to nifN.
Involved in FeV-co biosynthesis. Accumulates a FeSV precursor
to FeV-co.
Vnf-Fe protein. Obligate electron donor to VFe protein, also
involved in FeV-co biosynthesis.
Ferredoxin-like protein. Putative electron donor to VnfH,
α subunit of Vfe protein.
δ subunit of mature VFe protein. Possibly involved in the insertion
of FeV-co into apo-VFe protein.
β subunit of VFe protein.
Involved in FeY-co biosynthesis or insetion.
vnfH
vnfFd
vnfD
vnfG
vnfK
vnfY
nifH Genes
Knowing that only a small percentage of microbial populations are
culturable in the laboratory, nifH genes provide an alternative method, via
molecular evolutionary analyses, to study diazotrophic diversity in the
environment (103, 107). The nifH gene is one of the structural genes of the
nitrogenase complex. This gene is part of the nifHDK operon, and is the gene
product that performs nitrogen fixation. NifH genes have been highly conserved
through evolution (103). Current research on the distribution of nifH genes and
comparative genomics suggests that the nitrogenase enzyme could be
14
transferred by lateral gene transfer mechanisms, as evidenced by the
relationship between Gram-positive bacteria with low G+C content and the delta
subdivision of proteobacteria (24, 30, 103, 114). The nifH gene has one of the
largest
non-ribosomal
database
sequences
of
diverse
uncultivated
microorganisms from the environment (24). The nifH gene provides phylogenetic
uniqueness that allows construction of trees of relatedness for diazotrophic
organisms.
nifH genes cluster into four basic groups depending on the
characteristics of the nitrogenase enzyme. Cluster I consists of the conventional
molybdenum- and vanadium-containing nitrogenase from cyanobacteria and
proteobacteria (α, β, and γ) as well as γ-proteobacteria vnfH; this is the most
studied cluster and is associated with strictly aerobic organisms that perform
aerobic respiration. Cluster II is the second alternative nitrogenase that does not
contain either Mo or V and includes methanogen nitrogenases and bacterial
anfH; this presents great homology to the cluster I, and includes mostly obligate
anaerobes, such as methanogens, clostridia, and sulfate-reducing bacteria.
Cluster III includes nifH sequences from diverse groups of distantly related
microorganisms, where most are strict anaerobes such as clostridia (low G+C,
Gram-positive) and sulfate reducers (δ-proteobacteria). Cluster IV is a divergent,
loosely coherent group of nif-like sequences from archaea and distantly related
chlorophyllide reductase genes. This includes nifH-like and nifD-like homologues
in organisms that do not necessarily fix nitrogen. Many microorganisms have
multiple copies of the nitrogenase genes and group into cluster IV (65, 85, 103,
114, 115). For example Clostridium pasteurianum has six nifH copies plus one
15
alternative nitrogenase encoded by anfH, similar to some species of
cyanobacteria (103, 117).
Because nifH universal primers have some level of degeneracy, specificity
may be reduced (109). In order to analyze biological processes in specific
ecosystems without cultivation, gene markers are necessary. For nitrogen
fixation analysis of nifH, nitrogen reductase genes have been used with PCRbased techniques that can amplify environmental samples as well as pure
cultures (64, 103, 109, 115, 116). The great conservation of nifH genes through
evolution makes them valuable molecular tools to examine biological nitrogen
fixation in the environment, and to determine phylogenetic distributions within the
four clusters (65, 117). However, not all of the organisms in any specific taxon
are nitrogen-fixing organisms again suggesting that there is lateral or horizontal
gene transfer. The notion of lateral gene transfer contributes to new explanations
of the variation of microbial genomes; the number of copies of functional genes
also gives an explanation for finding non-nitrogen-fixing organisms in the same
phylogenetic cluster of organisms that can fix nitrogen (17, 116). This opens up a
discussion for probing the two main theories about the origin of nifH genes
(nitrogenase genes) and the evolution of nitrogen fixation; the first stating that
nifH genes have been highly conserved through evolution, coming from the
common ancestors, even though they are unevenly distributed among
prokaryotes, and the second suggests that there is some lateral gene transfer
that explains the distribution of the capacity of nitrogen fixation among
16
prokaryotes, supported by plasmids found in diazotrophs in marine environments
(43, 65, 117).
Nitrogen-fixing organisms
Nitrogenase is widely found in different prokaryotic organisms, including
phototrophs such as cyanobacteria and sulfur bacteria, and chemotrophs, such
as
Azotobacter
spp.,
Bacillus
spp.,
methanogens,
methane-oxidizers,
Azospirillum spp., and Rizhobium spp. (6, 24, 79, 95). Diazotrophs are classified
in two large groups: as free-living organisms shown in Table 4 and as those
forming symbiotic associations with plants such as: Rhizobium spp. and
Bradyrhizobium spp. Symbiotic associations are important for agriculture,
because they are responsible for a significant amount of nitrogen fixed in the soil.
Plants associated with Rhizobium spp. have shown fixation rates of about ~220
lbs of N2 fixed per crop acre per year (83).
Recent studies on nitrogenase in different ecosystems have shown that
nitrogenase genes are diverse in the environment, suggesting the presence of
nitrogen-fixing communities in different types of ecosystems (95). It has been
shown that the presence of different types of nitrogenases is not evenly
distributed among the prokaryotes.
17
TABLE 4
NITROGEN-FIXING ORGANISMS
ENVIRONMENTS
MICROORGANISMS
Strict anaerobes
Clostridium spp.
Desulfovibrio spp.
Desulfotomaculum spp.
Methanogens e.g., Methanococcus spp.
Chromatium spp.
Chlorobium spp.
Thiopedia spp.
Ectothiospira spp.
Klebsiella spp.
Bacillus spp.
Enterobacter spp.
Citrobacter spp.
Escherichia spp.
Propionibacterium spp.
Rhosopirillum spp.
Rhodopseudomonas spp.
Mycobacterium spp.
Thiobacillus spp.
Spirillum spp.
Aquaspirillum spp.
Methanosinus spp.
Rhizobium spp.
Plectonema spp.
Lyngbya spp.
Oscillatoria spp.
Spirulina spp.
Azotobacter spp.
Azotococcus spp.
Azomonas spp.
Beijerinckia spp.
Derxia spp.
Anabaena spp.
Nostoc spp.
Calothrix spp.
7 other genera of blue-green algae
Phototrophic anaerobes
Facultative (aerobic when not
fixing)
Facultative phototrophs
Microaerophiles (normal
aerobes when not fixing)
Microaerophilic phototrophs
Aerobes
Aerobic phototrophs
18
Nitrogen-fixing organisms can have all three types of nitrogenases, such
as Azotobacter vinelandii which has all three types, Mo-, V-, and Fe-like, of
nitrogenases, while some organisms can have either Mo-Fe or Mo-V containing
nitrogenases such as Rhodobacter capsulatum, Rhodosopirillum rubrum, and
Anabaena variabilis. There are some other instances in which the organism only
contains Mo-like nitrogenase; for example K. pneumoniae, one of best-known
and studied diazotrophs. On the other hand, diazotrophs containing only V-like or
Fe-like alternative nitrogenases have not been found (89).
As
mentioned,
nitrogenases
are
sensitive
to
oxygen;
therefore,
microorganisms must have different mechanisms to protect their nitrogenases
while fixing nitrogen. Nitrogen fixation occurs in different microbial populations,
including
strict
anaerobes,
facultative
aerobes
growing
anaerobically,
microaerobic organisms, and strict aerobes, each possessing a distinct
mechanism to maintain their system active when nitrogen fixation is needed.
Strict aerobes, like Azotobacter spp. have the advantage of respiring faster that
many other microorganisms, and they can modify the structural conformation of
the enzyme complex which aids them during nitrogen fixation. Some other plantassociated microorganisms contain hemoglobin, the oxygen-carrying enzyme,
that supplies them with the necessary oxygen flow for energy requirements
without affecting the nitrogenase complex. Finally, the cyanobacteria genera
have two groups. One produces heterocysts, filamentous cells with a heavy cell
wall that perform N2 fixation and transfer fixed nitrogen to vegetative cells, while
the vegetative cells carry out photosynthesis to produce energy that is, in turn,
19
exported to the heterocysts. In contrast, non-heterocystous cyanobacteria show
an alternative system using the day-night cycle, in which case, photosynthesis is
performed during the day, while energy and O2 are produced and the
nitrogenase system is turned off; in darkness or during the night, stored energy
obtained during photosynthesis is used to carry out nitrogen fixation, and
accordingly the N2-fixing system is turned back on (14, 106).
Real Time PCR
In order to analyze biological processes in specific ecosystems without
cultivation, gene markers are necessary. For nitrogen fixation analysis, nifH,
nitrogen reductase, genes have been used with PCR-based techniques that can
amplify from environmental samples as well as pure cultures (44, 64, 103, 113,
116, 117). Several studies have tried to estimate the abundance of numerous
genes that are involved in nitrogen cycling, such as nifH, through diverse
methods. Additionally, the target sequences for nitrogen-fixing guilds have been
defined previously and PCR primers are available that target nifH, a functional
gene coding for the dinitrogenase reductase subunit of nitrogenase, a key
enzyme in nitrogen fixation by nitrogen-fixing microorganisms (95, 100).
Quantifying the abundance of gene pools of functional populations provides an
approach for determining how diazotrophic communities are distributed in the
environment (70).
20
Molecular ecology has available numerous methods that make it possible
to analyze the composition of nitrogenase genes in different ecosystems, for
example, PCR amplification of nifH gene fragments followed by restriction
fragment length polymorphism (RFLP) analysis (81, 109), terminal restriction
fragment length polymorphism or TRFLP (56), DNA macroarrays (50, 95, 100),
touchdown PCR amplification, cloning, and sequencing of nifH genes (2, 96, 99,
103), PCR amplification of nifH gene fragments followed by DGGE, and
amplimer cloning and sequencing (58, 80, 88). Initially these investigations were
mainly concentrated on PCR amplification followed by analysis of clone libraries.
This is time consuming, expensive, and exhaustive. In addition, numerous “new”
sequences appear every time a new environment is investigated. Performing
quantitative
biocomplexity
methods
spatially
would
and
allow
investigators
to
compare
ecosystem
temporally (50, 95), with the purpose of
understanding the role of nitrogen-fixing organisms in the nitrogen cycle in
different ecosystems. Because of this, it is necessary to quantify nitrogenase
activity expression using in situ methods combined with gene abundance and
perhaps gene expression analyses (65).
In order to evaluate nifH gene abundance, real-time PCR has great
potential. Despite the fact that, real-time PCR was developed for clinical
microbiology, in order to detect pathogenic organisms in short periods of time,
the scientific community is implementing and applying this new technology in
academic research. Valasek and Repa in 2005 showed the rapid increase of
scientific publications, 3500, in Medline that used real-time PCR as a major
21
procedure (104). In fact, real-time PCR is being applied in different disciplines
and studies such as
those in plants to detect transgenic or pathogenic
organisms (37), gene expression and metabolic regulation (105), quantification of
ammonia-oxidizing bacteria (44, 74), quantification of archaeal populations (98),
gene abundance of dinitrifiers implicated in nitrite reduction (39), metanotroph
abundance in soils (54), detection of methanogenic communities (112),
quantification of fungal DNA in soils (33), quantification of genes involved in
biodegradation (5, 46, 66, 111), dinoflagellate, bacteria, and algae in aquatic
environments (1, 82, 111, 119), gene abundance in activated sludges (25), and
the abundance of bacteria and archaea in soils (32, 55, 98),
Real-time PCR (a type of quantitative PCR) monitors amplicon production
during each cycle using a fluorescent probe that emits fluorescence during the
reaction as an indicator of the extent of amplification of the target. The
fluorescent signal is directly proportional to the amplification of the target
(number of new copies made). The equipment monitors the signal’s increase
until it reaches the exponential level, which determines the threshold cycle. By
definition, the threshold cycle is the first cycle in which there is a significant
increase in fluorescence above the background or a specified threshold value.
Through threshold cycle measurement, comparative quantification analysis
allows the determination of the concentration of target amplicons. The higher the
starting DNA copy number, the quicker (fewer cycles) the amplicon threshold is
reached.
22
Real-time PCR has several advantages. For example, it eliminates post
processing of PCR products that can allow cross-contamination. The targets can
be quantified, and the number of cycles reduced. Monitoring amplification in real
time, rapidly and with high sensitivity and quantification power, it has a dynamic
range that is at least five orders of magnitude, and theoretically a single gene
copy can be detected (104). There are several fluorescent systems that use a
reporter dye for real-time PCR such as hydrolysis probes, TaqMan probes (69),
scorpions, molecular beacons, hybridizing probes, and DNA binding agents, such
as SYBR Green I (45, 60, 61, 86, 104).
SYBR Green I, a dye that intercalates non-specifically to all doublestranded DNA, is a good and simple choice for real-time PCR. This dye has been
widely used, because of its many advantages: low-cost in comparison with the
other chemical technologies, availability commercially. Standardized in-house
protocols allows confirmation of the desired product (amplicon) from primer-dimer
or non-specific amplification by melting curve analyses (38). The melting curve,
generated by the real-time PCR equipment, is a plot of fluorescence versus
temperature, when performed with an intercalating dye such as SYBR Green I.
The melting temperature of a specific DNA sequence, which is a function of the
number of base pairs and %GC content, is defined as the temperature at which
50% of the DNA is in double-stranded form and 50% is in single-stranded form.
23
Streams
Quantification of nutrient dynamics is an important factor in understanding
processes such as eutrophication (the enrichment of natural waters with
inorganic materials and organic matter, especially nitrogen and phosphorus
compounds), oligotrophication (waters poor in nutrients), retention of nutrient
material in the system, and natural ecosystem roles. These factors are
significant, because ecosystem processes are related to biogeochemical cycles
that influence input and losses of nutrients in the environment (6, 28, 68, 74, 78,
91). Eutrophication processes maintain an excessive growth of photosynthetic
organisms that becomes unmanageable (6, 71). During the past 10 years,
eutrophication has become an enormous concern, because of the rapid ten-fold
increase in aquatic environments around the world (9, 71). The eutrophication
process occurs in aquatic ecosystems from the inputs of nutrients from run-off
processes e. g. agriculture and discharges of untreated or poorly treated waste
waters, resulting in degraded environments, stimulated biological productivity,
and algal blooms, that increase the level of eutrophication. As a result, oxygen
available in the ecosystem decreases, creating a hypoxic zone, loss of flora and
fauna, and alteration of diverse food webs; at this point, the environment has
been seriously altered with a large global impact (9, 74).
Hypoxia, dissolved oxygen concentrations lower than required by
indigenous organisms, is the most severe consequence of eutrophication, and
happens when all dissolved oxygen is used up for degradation of the organic
24
matter, as a result of the stimulating effects of nutrient input. Hypoxic zones show
different levels of stratification that can occur permanently, seasonally,
temporarily, or sporadically (9). In the hypoxic zones, the amount of dissolved
oxygen is less than 2 mg/L or two parts per million. The largest hypoxic areas are
localized in the Baltic Sea and the shelf of the Black Sea (84). During the hypoxic
process, organic matter sinks in the bodies of water and it is decomposed at the
bottom. Finally, oxygen is consumed by respiration and it can not be replenished,
because the conditions of the ecosystem have already changed. Hypoxic areas
have been moving throughout ecosystems over a long period of time. At the end
of the 20th century, several coastal ecosystems have shown large hypoxic zones
that have received nutrients, mainly through run-off from agriculture fields, wellknown contamination influenced by land-usage, and nitrogen leaching as nitrate
to the ground and surface waters (74). Biological productivity is mediated by
nutrient cycling, temperature, salinity, and light conditions. Biological production
is closely associated with stratification in bodies of water and the food chain
where the most important limiting nutrient is often nitrogen (57, 84).
There are two significant examples of hypoxic zones in North America: the
Gulf of Mexico and the Chesapeake Bay. In the Gulf of Mexico, high
concentrations of nitrogen have created a large zone of low oxygen
concentration of about 20,000 Km2. The Gulf of Mexico is influenced by a
number of streams that reach the Mississipi and Atchafalaya Rivers. These two
rivers discharge around 80% of the nutrients into the gulf, mainly N and P. This
hypoxic zone has been documented since 1970’s; however information about the
25
depletion of oxygen has been known since mid-1930’s (84). The second example
is the Chesapeake Bay, the largest estuary in the United States, one time called
“the immense protein factory” by H. L. Mencken (9), because of its productivity,
that has an economic and social impact in more than six states. In the 1960’s,
the large increase of microalgal and cyanobacterial blooms and low
concentrations of oxygen in the Bay area showed an overloading of nutrients in
the region. Jaworski, in 1990 (49), established that the quality of waters that
arrived to the Bay was obviously overenriched, mainly because of poor treatment
before being dumped from wastewater treatment plants. In 1996 and 1997,
Cornwell and Davison et al. showed that between the mid-1950’s and mid1980’s, pollution due to anthropogenic inputs and the usage of the land for
agriculture, plus the input of organic fertilizers and pesticides like atrazine, almost
doubled and tripled in each case. This demonstrated that the Bay ecosystem has
been being contaminated for 20 or more years (9, 21, 22, 49, 84, 91). There are
several effects due to the hypoxia occurring in the Chesapeake Bay: reduction in
the abundance and diversity of flora and fauna and the overall productivity is also
affected in the deeper habitats. This estuary is the nursing area of many species
of fish, crustaceans, etc, whose nursery area has been affected, because of
changes in the environment.
Input of nutrients plays a role in the pollution of coastal and freshwaters. P
and N sources should be controlled. N is key in terms of productivity and quality
of water and P concentration may also control primary producers as well. In
marine environments, salinity may limit the concentrations of N and P for
26
biological production. P is limiting in lower salinity, while N is limiting in higher
salinity (9, 27-29, 84). Total N and P inputs are from point sources such as
domestic effluents, sewer leakage, septic tanks, livestock manure and slurry,
discharge by wastewater treatment plants, factories, etc, while most of the rest
of the input is from non-point sources such as diffusion from the landscape,
agriculture, forest and urban/suburban areas, and atmospheric deposition (9).
Biogeochemical cycles, such as those for nitrogen, phosphorus, carbon,
iron, and silica, play an important role in the turnover of all the different nutrients
that are released to bodies of water. If there is positive feedback in the
ecosystems within the habitats, there is restoration and a rapid recycling of P and
N in the affected environment (6, 9, 28, 68, 78, 91). On the other hand, studying
the retention time in-stream would give a perspective of loss of nutrients during
the movement from smaller streams to marine environments.
At this point, the headwaters, watersheds and the catchment’s areas
become a critical point to facilitate the study of nutrient increase of eutrophication
and hypoxic processes in aquatic environments, particularly streams. Several
factors, including the availability of nutrients, geochemical characteristics,
hydrodynamics and human impacts, are the main aspects that control metabolic
activities and abundance of microbial communities, as well as ecosystem
function and contamination problems. Streams are key interfaces between
terrestrial zones and downstream zones in aquatic ecosystems, because they
transport and regulate concentrations of nutrients that will be drained into lakes,
rivers, seas and oceans, increasing or decreasing contamination (20, 29, 78).
27
The flux of nitrogen is directly related to the flux and turnover of carbon, where
nitrogen is a key element in biological ecosystems. Nitrogen is key in terms of
productivity and quality of water in streams. Phosphorus concentration may also
limit primary producers in streams. Nitrogen is the most significant nutrient
affecting production in aquatic ecosystems (28, 29, 84). Nitrogen limitations can
affect net primary productivity; also the water flux is directly related to inputs and
losses of nitrogen and productivity is correlated with the dynamics of freshwater
discharge (84, 91).
Due to eutrophication, macro and micro communities are affected at
different levels (84). A problem due to contamination, increased concentration of
nitrogen and phosphorus, is the abundance of algae blooms that create toxic
environments in different ecosystems. The streams’ retention of nutrients is
affected by the areas adjacent to the stream, such as urban and agricultural
areas (27). Nutrient transportation between different watersheds is regulated by a
number of factors such as land use, management practices, vegetation
characteristics, soil composition, and the interface areas between the watersheds
and the land, that affect water composition and transport downstream, and
retention time in the streams (28, 78, 91). Loss of nitrogen in the environment is
related to water flux in the stream and with the biogeochemical characteristics of
the soil in adjacent areas. This occurs because of the mineralization of NH4 from
N2, leaching of NO3, and dissolved organic nitrogen, and mineralization of NH4
from organic matter. This is observable in soils that are heavily impacted by
human activities such as agriculture, recreation, urbanization, etc (84, 91). On
28
other hand, in undisturbed streams such as the Konza prairie streams, losses
and inputs of nitrogen would be very low due to a natural biosphere and
equilibration of water flux and the ecosystems' biophysical controls (42).
Headwater streams have an important role in processes such as storage,
regeneration and nutrient transport in the water network. These smaller streams
have better retention and processing of nitrogen, perhaps because these collect
more pollution from adjacent ecosystems (78). Canalizing bigger streams could
be an alternative that would increase nutrient retention in smaller streams (91).
Studies of stream chemistry and behavior are useful tools for understanding
point sources during the eutrophication process. There are strategic targets for
understanding the total input and output of nutrients and cycling within the
ecosystem (9, 28).
A new controversy has arisen in the last years of the 20th century, where
the theory of eutrophication by anthropogenic input of nutrients has been subject
to disagreement. The increase of low oxygen areas has been noticed since
1970’s; these transitions could respond to changes in different factors that could
help the problem. Variation in climatic effects, greater freshwater flow, mass
stratification, and ecosystem response are some of the variables that can
increase or decrease the hypoxic areas (9, 84).
The biosphere has been highly enriched in nutrients, especially nitrogen;
this became a worldwide problem, where anthropogenic inputs of nitrogen in the
form of fertilizers in terrestrial and aquatic ecosystems lead to an environmental
and human health dilemma. It has been determined that increases in nitrate
29
concentrations are the major cause of eutrophic, hypoxic and anoxic zones in the
lower portions of the water column in marine environments (63).
Eutrophication and hypoxic zones are a challenge for the scientific
community; even though the process is reversible the restoration of the
numerous ecosystems that have been affected will take many years of work.
There are some improvements, because of public and political commitments,
control, and regulation, and the generation of scientific models to treat these
complex ecosystems would be a strategy to make progress in the reestablishment of the natural environment. Although nutrient reductions have
been seen in some areas, it has required the control of emissions and input of
nutrients as a result of land usage, and a better model for landscape or
agriculture usage, with some innovative biological tools.
30
CHAPTER 2
AIM
Contrast gene abundance and metabolic responses of N2-fixing
microorganisms to chronic nitrogen loading in three different types of Kansas
prairie streams: urban, agricultural, and pristine.
This research is just a portion of a collaborative project with Kansas State
University and University of Kansas as part of the Lotic IntersiteNitrogen
Experiment, known as LINX. The LINX study of nitrogen cycling in streams
involves simulation modeling, field tracer
15
N-nitrate additions and intersite
comparison, with the idea that among streams, variability in nutrient uptake is
related to retention and cycling of N, in addition to understanding the key aspects
that control energy flow and food webs in different ecosystems that have had
distinct impacts due to humans activities. The LINX project also wants to link
biological processes with the gene level, using genetic markers to monitor Ncycling guilds in different compartments and locations along streams, and finally
to compare watershed types, N-cycling patterns, and associated gene
abundance over time and N loading. Studies completed by Dodds et al. at
Kansas State University, have shown that the first LINX study demonstrated how
small streams are key in the retention process of N compounds such as
ammonium and nutrient uptake is controlled by the flow and depth of the stream.
LINX researchers hopes to understand how human disturbance impacts and
31
affects the N retention structure of streams, as well as channel morphology,
hydraulics, and biological activity, and why this is a key factor in contamination of
larger bodies of water, that leads to eutrophication (8, 68, 72, 78).
Biomes have been highly augmented with nutrients, especially nitrogen, by
human activities. In most ecosystems, nitrogen availability should be limited, but
soils and aquatic environments have been heavily impacted by human activities
such as agriculture, recreation, and urbanization. In streams, the availability of
nutrients, geochemical characteristics, hydrodynamics, and human activities
influence the metabolic activities and structure of microbial communities.
A
combination of process-level and molecular microbial ecology techniques have
been applied to study nitrogen fixation in small prairie streams with different
nitrogen impact histories, from pristine to heavily polluted. Nitrogen fixation was
measured with acetylene reduction assays. Simultaneous sampling of sediments
and leaf litter was performed for molecular analyses of the nitrogen-fixing
microbial guild. Direct DNA extracts were examined using real-time PCR of a
nitrogenase complex gene, nifH, to determine the abundance of nitrogen-fixing
organisms. This study has provided a link between the abundance of nifH genes
and nitrogen fixation activity. An understanding of the effect of nitrogen pollution
on nitrogen cycling communities in small streams will increase our ability to
overcome the challenges of nutrient pollution.
32
Hypothesis
1. Nitrogen fixation activity in stream sediments is negatively correlated to level
of nitrogen loading in the stream.
2. nifH abundance in stream sediments will be unchanged by nitrogen loading in
the stream.
The first hypothesis was chosen because nitrogen fixation activity is partly
regulated by the concentration of fixed nitrogen in the environment. If nitrogen
loads are high, the expected result is low levels of nitrogen fixation activity. On
the other hand if nitrogen is a limiting nutrient, diazotrophic activity will be
expected to be higher, because of the essential nature of fixed nitrogen.
Microbial communities are highly structured in specific environments, but
changes in the environment may impact abundance and activity levels of
microorganisms in the microbial community. Nitrogen addition in an oligotrophic
environment may be a selecting factor against nitrogen-fixing microorganisms,
because of the energy costs of maintaining that system in addition to evidence of
diazotrophs being poor competitors in the environment (4, 79).
The second hypotheses was selected because of results reported by
Piceno and Lovell in 1999 (79) that demonstrated that diazotrophic assemblages
did not change when the environmental conditions and nutrient resources
(including fixed nitrogen addition) were changed during an extended period of
33
time, at least two months (4). This suggests that this microbial guild does not
change based on environmental nutrient conditions (79, 80).
34
Objectives
1. Quantify N2-fixation activity in the sediments of prairie streams with different
nitrogen loading using the acetylene reduction assay.
2. Extract total DNA from various sediment fractions from urban, agricultural,
and pristine stream samples with different nitrogen loading.
3. Measure the abundance of nifH genes in sediments and leaf samples from
the three different types of streams using real-time PCR.
35
CHAPTER 3
METHODOLOGY
Study Sites
This study was conducted in the Flint Hills region of Northeast Kansas,
USA, which is home to the largest area of remaining tallgrass prairie in the Great
Plains. The primary uses of the land in this area are cattle grazing, and
agriculture (72). Six different streams were selected from among three general
land-use categories: pristine/reference, agriculture, and urban, based on nitrogen
loading. Kings Creek-N4D sampled in 2003 (39o 05.271’N, 96o 35.067’ W) is
located in watershed N4D at the Konza Prairie Biological Station. It is an
unimpacted tallgrass prairie stream grazed by Bos bioson (native grazer) and
burned every four years, and it was burned two years prior this study. This
stream is bottomed with cobble and characterized by a predominantly open
canopy. Kings Creek-K2A, sampled in 2004 (39o06.008’ N, 96o 34.454’ W), is
located in watershed K2A on the Konza Prairie Biological Station. This ungrazed,
unimpacted tallgrass prairie stream is biennially burned, most recently one year
prior this study. It is bottomed with cobble and characterized by a predominantly
open canopy. It is a perennial reach. North Creek, sampled in 2003 (39o
12.741’N, 96o 35.584’ W), is located at the Kansas State University Farm, north
of Manhattan, Kansas. This stream drains a watershed with mixed land use (26%
native vegetation, 30% agriculture, and 45% urban) flowing trough a reach
36
surrounded by row crop agriculture. It is bottomed with silt and lies within a
straightened stream channel. Natalie’s Creek, sampled in 2004 (39o13.723’ N,
96o 39.530’ W), is located in Manhattan, Kansas. This stream drains an
unfertilized, annually burned (burned one year prior this study), prairie grass
cattle pasture. It is bottomed with cobble with similar shading to that of the
pristine prairie streams. Campus Creek, sampled in 2003 (39o11.577N, 96o
34.722’ W), drains a watershed dominated by the campus of Kansas State
University, Manhattan, Kansas. This stream is bottomed with cobble and sand,
and is impacted by human activities (e.g. livestock). There is some riparian
vegetation for some of the reach. Wal-Mart Ditch, sampled in 2004 (39o11.135’
N, 96o 33.500’ W), is canal of the Big Blue River and is fed by the drainage
system of the City of Manhattan, Kansas. Most of the watershed area (92%) is
composed of urban land use with the rest (8%) in native vegetation. This stream
has been canalized with concrete as the streambed. Cyanobacterial and green
algal biofilms were present during the sampling process in this stream. Table 5
shows additional parameters of the study sites (72).
Sample Collection
Stream sediment, leaf litter and algal mat samples were collected cleanly
from each stream between May and July in 2003 and 2004. Global positioning
system (GPS) coordinates were recorded at each site (given above). Sediment
samples were collected at different depths, designated: top, to a depth of 1cm
37
within the sediment, and bottom, to a depth of 3-5 cm within the sediment. Leaf
litter samples were taken at each of the stations when possible and in other
cases along the entire reach area, and algal mat samples were taken randomly,
if present in the stream (Figure 4). Samples for molecular analyses were placed
in Whirl-Pak bags or sterile polypropylene tubes and frozen immediately in the
field and transported on dry ice, and stored at -80°C prior to analysis. Samples
for nitrogen fixation activity by acetylene reduction were collected in ~250-ml
Mason jars fitted with rubber septa. Samples were collected in 10-ml BD
Vacutainer tubes when the amount of material available was small (algal mat
samples). The samples for nitrogen fixation assays were transported at room
temperature. Samples were taken from four different stations in each stream:
above: above the release point; high: located right after the release point; middle:
located in the middle of the reach; and low: located downstream, almost at the
end of the reach. The sampling sites are shown in Figure 4.
Acetylene Reduction Assays
The acetylene reduction assay (or ARA) is widely used, because it is a
simple, low-cost method, with high sensitivity and a fast response. The
conversion of acetylene to ethylene by nitrogenase can be used as a surrogate
for nitrogen fixation. Samples were assayed either in Mason jars or BD
Vacutainer tubes. Acetylene gas generated from calcium carbide was injected
38
into the headspace (to 10% v/v) of the jars or tubes. Samples were incubated at
room temperature for for 1, 3, 7, and 14 d after collection.
The ethylene content of 0.2 ml aliquots of the headspace gas was
determined by gas chromatography. The gas samples were analyzed for
ethylene on a Hewlett Packard 6890 series gas chromatograph equipped with a
hydrogen flame ionization detector and a microbore DB5-equivalent column.
Ethylene peaks were measured and nitrogenase activity was determined from
the accumulation of ethylene in the samples at each of the mentioned incubation
times by using linear regression analysis of a standard curve generated with
diluted ethylene gas. Adjustments were made for the trace amount of ethylene
found in the acetylene gas. The amount of nitrogen reduction was estimated
according to Jensen et al., 1983 by using a conversion factor of 3.8 acetylene
molecules reduced per one dinitrogen molecule reduced (51). The acetylene
reduction assays for 2003 were performed in duplicates and acetylene reduction
assays for 2004 were performed with six replicates to account for variance.
DNA Extraction
New approaches in microbial ecology have relied on molecular techniques
where DNA, as a template, is the most important element and it’s purification a
critical step. High quality, purity, and cleanliness are very important
characteristics for later use of the DNA in further genetic analyses such as PCR,
real-time PCR, cloning, and sequencing. DNA was directly extracted from
39
sediment, leaf litter, and algal mat samples using the protocol of Bürgmann et al.
(2001) with some modifications as follows. Enviromental samples (0.5 g) were
weighed in 2-ml sterile microtubes, and 0.75 g of glass silica/zirconia beads (0.2
mm) were placed into the same tube. Extraction buffer (1.25 ml) was added to
the 2-ml microtube containing the soil and beads. The composition of the
extraction buffer was as follows: 0.2% CTAB (w/v), 1 mM DTT (dithiothreitol), 0.2
M sodium phosphate buffer [pH 8.0], 0.1 M sodium chloride, and 50 mM EDTA.
The sample tubes were processed with a bead-beater Genie (Scientific
Industries, Inc.) Cell Disruptor at 4 °C, at maximum speed, for 2 to 3 min. After
processing, the tubes were centrifuged at 16,000 x g for 5 min. Then, the
supernatant was transferred into a new sterile 2-ml microtube. The supernatant
was subjected to phenol and chloroform-isoamyl alcohol extractions that were
performed separately (12). Buffer-equilibrated phenol [350 µL; pH 8.0] was
added to the supernatant, well-mixed by vortexing, and centrifuged for 5 min at
16,000 x g. Then, the supernatant was transferred into a new, sterile, 2-ml
microtube and 350 µL of water-equilibrated chloroform-isoamyl alcohol (24:1 v/v)
was added, the mixture was mixed by vortexing, and then centrifuged at 16,000 x
g for 5 min. An aliquot of the aqueous phase (700 µL) was incubated for 1 h with
750 µL of precipitation solution. The precipitation solution contained 20% (w/v)
polyethyleneglycol 6000 in 2.5 M sodium chloride solution. DNA was pelleted by
centrifugation at 16,000 x g for 30 min at room temperature. The pellet was
washed with 70% ice-cold ethanol once, air dried for 5 min at room temperature
and resuspended in 100 to 300 µL of TE buffer [pH 8.0]. The TE buffer contained
40
10 mM Tris-HCl and 1 mM EDTA. No further purification procedures were
needed. The purity of the extracted DNA was assessed spectrophotometrically
by measuring A260/A280 (DNA to protein) and A260/A230 (DNA to humic acids)
ratios with a Genesys 5 spectrophotometer.
Real-time PCR
Real-time PCR was performed using a Smart Cycler II System (Cepheid
Technology). Real–time PCR was performed using SYBR Premix EX Taq
(Perfect Real Time, TaKara Mirus Bio) in accordance with the manufacturer’s
instructions. The reaction mixture was set up as follows (per reaction): SYBR
Premix EX Taq (2x), 12.5 µL; PCR forward primer (10 µM), 0.5 µL; PCR reverse
primer (10 µM), 0.5 µL; template DNA extract (≤400 ng), 2 µL; dH2O, 9.5 µL; for a
total volume of 25 µL. The final concentration of SYBR was was 1x and the
primers, 0.2 µM. The SYBR Premix EX Taq contained 25 mM TAPS [pH 9.3], 50
mM KCl, 2 mM MgCl2, 1 mM 2-mercaptoethanol, and 200 µM of each dATP,
dGTP, dTTP, and dCTP. The primer set used for this analysis was UNIFF
forward primer 19F (Ueda et al. 1995) (UF) (5’-GCIWTYTAYGGIAARGGIGG-3’)
and Zehr and McReynolds et al. (1989) nifdn (ZR) (3’-ADNGCCATCATYTCNCC5’), where I is inosine, R is either A or G, W is either A or T, Y is either C or T,
and N is either A, C, G, or T (64, 103, 116). This set of primers has significant
degeneration, but these technical considerations have been reviewed previously
(113, 117). This set of primers has been used in several investigations of nifH
41
diversity from different sample types, such as forest soils, rice fields, marine
sediments (23, 64, 103, 116, 118). This primer set generates a PCR fragment of
464-bp, which is very important during the real-time PCR process, because the
size of the amplicon is within the desired range. To increase the process’
efficiency, the amplicon should be between 100 to 500 bp in size. The PCR
program consisted of 60 s at 95 °C, and then 45 cycles of 5 s at 95 °C
(denaturation), 30 s at 50 °C (annealing), and 15 s at 72° C (elongation), and
finally a hold at 72 °C for 60 s. Random samples were assayed three to six times
(or more when possible) to determine the typical deviation between samples from
different extractions of the same sample, and from a single DNA extraction. The
negative control was deionized sterile water and the positive control was
Cyanothece sp. ATCC 51142 genomic DNA. These were included in each realtime PCR experiment.
Two other gene markers were used during this project with the purpose of
comparing the abundance of bacteria, archaea, and diazotrophic community
members. EUB 338 foward: 5’-ACTCCTACGGGAGGCAGCAG-3’, and EUB 518
reverse: 5’-ATTACCGCGGCTGG-3’ (32) target bacterial 16S rRNA gene
sequences. This primer set generates a PCR fragment of 200 bp. The PCR
program consisted of 60 s at 95 °C, and then 30 cycles of 5 s at 95 °C
°
(denaturation), 40 s at 53 C (annealing), and 15 s at 72 °C (elongation), and
finally a hold at 72 °C for 60 s. The archaeal 16S rRNA gene primer set used for
analysis with real-time PCR was ARC787F: 5’-ATTAGATACCCSBGTAGTCC-3’
(positions 787-806), and ARC1059R: 5’-GCCATGCACCWCCTCT-3’ (positions
42
1044-1059) (112).
This primer set generates a PCR fragment of 273 bp. The
PCR program consisted of 60 s at 95°C, and then 30 cycles of 5 s at 95 °C
(denaturation), 40 s at 57 °C (annealing), and 15 s at 72 °C (elongation), and
finally a hold at 72 °C for 60 s.
Cyanothece sp. ATCC 51142 contains the target gene nifH and 16S rRNA
genes that match the universal bacterial primer set. Thus, this diazotroph is a
good positive control and external standard for quantification. In the case of
archaea, a strain of Haloarcula sp. (GCr37; MO-60) isolated from the Great Salt
Plains of Oklahoma was used as a positive control. This strain has been
identified and characterized in the Archaea domain (19). Gene abundance was
determined using a standard nifH curve built from real-time PCR amplification of
a ten-fold dilution series of genomic DNA generated in triplicate from Cyanothece
sp. ATCC 51142 as follows: 1.0 x 103, 1.0 x 102, 1.0 x 101, 1.0, 1.0 x 10-1, 1.0 x
10-2, and 1.0 x 10-3 pg/µL. All the standard curves were constructed by using pure
genomic DNA dilutions. The standard curve was obtained by plotting the Ct
value, which is defined as the cycle number at which the threshold point is
crossed, versus the logarithm of the starting quantity of genes or concentration of
template DNA. The threshold value was set at 30 fluorescence units based on
the logarithmic increase of the target molecule, where this exceeds the
background fluorescence. The Ct is automatically calculated by the instrument. In
the case of the two other gene markers, Cyanothece sp. ATCC 51142 and
Haloarcula sp. (GCr37; MO-60) were used to build the same types of standard
curves. The calculated number of nifH gene copies in a sample was based in the
43
assumption made by Gruntzig et al. (2001) that suggests that only one copy of
the nifH gene is present per microbial genome (39). Deionized water was used
as a negative control. The number of nifH genes was assessed using the relation
between DNA-target molecular weight and gene copy number derived from the
standard curve as described by Ausubel et al. (3, 111). The conversion formula
relates gene copies and molecular weight of the amplicon. The abundance of the
nifH gene was calculated based on the average molecular weight of doublestranded DNA’s per base pair, which is 649 Da. The nifH gene has 464 base
pairs, consequently the molecular weight of the gene is 649 x 464 = 301,136 Da.
As a result, one nifH gene weights 301,136 Da. This number is then divided by
Avogadro’s number with the purpose of calculating the mass in grams of DNA.
301,136 /6.023 x 1023 = 4.99976 x 10-19 grams, where Avogadro’s number =
6.023 x 1023 molecules/mol. The same calculation was done for bacterial 16S
rRNA gene copy number as follow: 649 x 200 = 129,800 Da. As a result, one
bacterial 16S rRNA gene weighs 129,800/6.023 x 1023 = 2.1550 x 10-19 grams.
Finally, the calculation was done for archaeal 16S rRNA gene copy number as
follow: 649 x 272 = 176,528 Da. As a result, one archaeal 16S rRNA gene
weighs 176,528/6.023 x 1023 = 2.9308 x 10-19 grams.
The PCR product was analyzed by gel electrophoresis using a 2%
agarose gel in a horizontal electrophoresis chamber and TAE buffer. The gel was
run at 90 volts for 1 h. DNA bands were visualized using a UV transilluminator
after staining with a 0.5 µg/ml ethidium bromide solution for 30 min. The melting
curve of PCR amplicons generated by the real-time PCR thermocycler, gives a
44
melting temperature (Tm) of the double stranded DNA after amplification and
helps to determine whether the products are true amplicons or artifacts of the
protocol (primer dimers). At temperatures below the melting point of the doublestranded DNA, SYBR Green I will bind to the PCR products and emit a brightly
fluorescence. As the Tm is reached the double stranded DNA will denature and
become single-stranded DNA. Therefore it will release the SYBR Green I,
causing a rapid decline in the fluorescence emitted. Plotting the negative first
derivative of relative fluorescence units, d(RFU), versus temperature change, dT,
allows one to evaluate the melting peak and Tm for the amplified product (111).
Real-time PCR inhibition assay
An inhibition assay was performed in order to determine whether humic
acids or other contaminants from the DNA extraction process would inhibit the
real-time PCR assays of sediment and soil samples. To test the inhibition rates,
an engineered strain of Pseudomonas fluorescens, R8 Tn5 pho mutant M1, that
contains a gene for kanamycin resistance, was used (101, 110). Each of the
DNA extraction samples from the different streams types were subjected to the
inhibition assay using the same conditions.
The Pseudomonas fluorescens R8 Tn5 pho mutant M1 was growth in LB
media supplemented with 50 µg/ml kanamycin. Genomic DNA was extracted by
freeze-thaw with liquid nitrogen, followed by purification with phenol and
45
chloroform-isoamyl alcohol as described in Sambrock et al. (90) and the DNA
was stored at -20 0C until further analysis.
Real-time PCR for the inhibition assay was carried out as described above
with the following modifications: the efficiency test uses 2 µL of soil/sediment
DNA extract as a template with a concentration of ≤400 ng and 2 µL of Ps.
fluorescens, R8 Tn5 pho mutant M1, for a total of 4 µL of DNA; dH2O, 7.5 µL;
total of 25 µL per reaction. Ps. fluorescens R8 Tn5 pho mutant M1 DNA extract
by itself was used as positive control and sterile deionized water was used as a
negative control. The primer set employed for this assay includes homologous
primers
to
determinant
an
aminoglycoside
that
yields
a
phosphotransferase
370-bp
GCTGACGGAATTTATGCCTCTTC-3’
amplicon,
(positions
kanamycin-resistance
using
572-594),
KanR:
and
KanF:
5’5’-
CACCATGAGTGACGACTGAATCC-3’ (positions 224-246) (101). The PCR
program consisted of 60 s at 95 °C, and then 30 cycles of 5 s at 95 °C
(denaturation), 30 s at 63 °C (annealing), and 15 s at 72 °C (elongation), and
finally a hold at 72 °C for 60 s. Then, the results were analyzed by the
fluorescence of the product amplified and its melting curve.
The efficiency
percentage between the inhibition assay and the positive control was calculated
by taking the positive control as 100% efficiency.
46
CHAPTER 4
RESULTS AND DISCUSSION
There were three types of prairie streams studied each year that exhibited
diverse characteristics and interfaces, and presented different nitrogen
concentrations that ranged from 0.9 µg/L to 2900 µg/L of NO3-N (Table 5) (72). It
should be kept in mind that each stream is an independent environment and
there may be no direct correlation between streams and between year of
sampling within streams.
Acetylene Reduction Assays
Nitrogenase activity showed substantial variance within streams each
year. During each year, 2003 and 2004, activity was measured with six
replicates. The rates of ethylene production varied during incubation, with the 1wkincubations showing the highest rates of acetylene reduction.
When the
means for the different incubation times were calculated, the values had a
tendency to decrease and show irregularities with time. The pattern of reduction
of acetylene to ethylene reached its highest plateau after one week and
decreased by two weeks.
Control samples of leaf litter were analyzed without the addition of
acetylene, since it has been suggested that leaf litter along with organic matter
could give rise to false positives when nitrogen fixation is measured by acetylene
47
reduction assays. It has been suggested that the decomposition of leaf material
may release small quantities of ethylene gas to the environment. Samples of leaf
litter from the low and high areas of the streams were collected and incubated for
the same periods of time as mentioned above. After the incubation and analysis
by gas chromatography, there was no evidence of ethylene present in any of the
samples. This indicates that even if some leaf matter could potentially release
ethylene during decay, it did not happen in these samples, and therefore the
acetylene reduction analysis was acceptable.
The acetylene reduction assays showed high variability among the three
different stream types each year.
As a result, the nitrogen fixation activity
between the same type of stream each year showed significant differences as a
consequence of the vast geochemical, nutrient concentration and geographic
differences (72).
The urban stream in 2003 (Figure 5) showed low rates of nitrogenase
activity: from 1.5 to 2.5 fmol of nitrogen reduced per gram of soil per hour. In this
stream, 'low' miscellaneous leaf litter had the highest activity, 2.5 fmol N2/g soil/h
among all of the samples. At the urban stream in 2004 (Figure 6), rates varied
from 2.3 to 93.5 fmol N2/g soil/h, the highest rates being exhibited by green algal
samples. It is important to note that this stream showed high amounts of
gelatinous algal biofilm at the time of sampling. Furthermore, this particular
stream had a basin made of concrete and good water flow. Sediment availability
was very low; additionally, sediment samples did not show any considerable
differences; the nitrogenase activity was around 3.0 fmol N2/g soil/h.
48
The agricultural stream in 2003 (Figure 7) gave rates of nitrogen fixation
from 4.5 to 14.8 fmol N2/g soil/h, with the higher rates found in leaf litter. The
sediment samples showed some consistency, with the highest rate being 7.6
fmol N2/g soil/h. At the agricultural stream in 2004 (Figure 8) rates of nitrogen
fixation varied from 2.1 to 112.8 fmol N2/g soil/h.
The highest rates were
displayed by green algal samples. Again, the sediment samples were consistent
with rates from 2.1 to 5.6 fmol N2/g soil/h.
The pristine Konza prairie stream in 2003 (Figure 9) showed a lot of
variance between samples, from 3.9 to 81.9 fmol N2/g soil/h, with the highest
activity in leaf litter samples. This particular stream did not have much sediment,
so gravel samples were taken along with leaf litter. The pristine Konza prairie
stream in 2004 (Figure 10) showed high variance between samples, from 2.9 to
78.1 fmol N2/g soil/h. The number of samples taken was small in this stream,
because of the nature of the collection site. This stream had very little leaf litter,
and the basin was made entirely of rock with little sediment deposition. However,
the highest activity was found in a sediment sample from the low segment of the
reach. The leaf fraction showed activities of about 9.2 fmol N2/g soil/h.
Even with the great variation in these results, it may be concluded that the
highest activity levels were exhibited by either leaf litter samples or sediment
samples, depending on the year or stream examined. Possibly as a
consequence of the very diverse conditions of each independent environment, an
absolute comparison between streams or years can not be made. However,
nitrogenase activity showed a pattern of variation inversely correlated to the
49
amount of nitrogen available in the stream. In other words, streams that showed
the highest nitrogen fixation activities were those which have not had high
nitrogen loading, in this case, the pristine streams in both years. Nitrogenase
activity was detected in all of the samples; nevertheless the highest activity levels
were obtained after 1-wk incubation; examining rates before or after that specific
time frame, gave lower activity.
Streams play an important role in the environment and understanding how
the microbial communities cooperate in the dynamics of these ecosystems is
extremely important. Human input may affect these close relationships between
microbial populations and their habitat, creating a disturbed system where
performing natural activities results in less efficient biogeochemical cycling. The
aim of this project was to contrast gene abundance and metabolic responses of
N2-fixing microorganisms to chronic nitrogen loading in three different types of
prairie streams: urban, agricultural, and pristine.
The results of this investigation agree with my first hypothesis, that nitrogen
fixation activity would be negatively correlated to level of nitrogen loading.
Analysis of the acetylene reduction assays on the streams suggested that
nitrogen fixation activity occurs to a greater extent where nutrients were not as
available as in those streams where nutrient overload has taken place. As seen
in the pristine environment (Tables 6 to 11) the diazotrophic community fixed
nitrogen at a slightly greater rate than in the impacted streams.
Perhaps the excess of nitrogen, one of the limiting nutrients in aquatic
environments, in the agricultural and urban streams causes some biological
50
processes are inhibited; therefore, nitrogen fixation activity was reduced in
comparison with the pristine stream. When nitrogen stops being a limiting factor
in aquatic environments, diazotrophs decrease their typical activity and use the
fixed nitrogen present in the environment. A possible explanation for this is that
this process is highly energetic; the nitrogen-fixers may be inhibited by the
nitrogen overload, or nitrogen may play a key role in the genetic regulation since
gene expression and degradation of the enzyme is controlled by fixed nitrogen
availability (28, 96, 99, 106, 107).
Gene Abundance by Real Time PCR
At the same time that samples were taken for nitrogen-fixation assays,
flash-frozen samples were collected. DNA extracted from these samples was
analyzed by real-time PCR to quantify microbial genes.
DNA extracted from a representative nitrogen-fixing organism, Cyanothece
sp. ATCC 51142, was used to test the specificity of the PCR primers for
nitrogenase and rRNA genes. A dilution series of Cyanothece sp. ATCC 51142
was evaluated to establish the detection limit for real-time PCR. Several
reactions at different concentrations of DNA were tested until the fluorescence
increased enough to pass the threshold value (30 fluorescence units) (Fig. 11).
The data was used for building a standard curve that relates the fluorescence
yield to the added mass of the control organism DNA and the number of gene
copies, assuming that each microorganism will have one copy of the target gene.
51
Standard curves were built for each of the primer sets, nifH genes, universal
bacterial 16S rRNA genes and universal archaeal 16S rRNA genes. For the nifH
primers, a linear response was observed over about seven orders of magnitude,
ranging from 200 to 2 x 109 nifH gene copies (r2 = 0.989; Fig. 13). For the
universal archaeal 16S rRNA gene primers, a linear response was observed over
about ten orders of magnitude, ranging from 430 to 4.3 x 1012 archaeal16S rRNA
gene copies (r2 = 0.98; Fig. 14). And finally, for the universal bacterial 16S rRNA
gene primers, a linear response was observed over more than six orders of
magnitude, ranging from 4.6 x 103 to 4.6 x 1012 bacterial gene copies (r2 = 0.99;
Fig. 15). Figure 15 shows data through 4.6 x 106 gene copies, because it was
essential to achieve a nearly linear fit for the curve.
Multiple real-time PCR assays were performed on different dates using
representative samples from each stream in order to determine the inherent insample real-time PCR variance. Standard deviations were calculated using data
collected from multiple real-time PCR iterations performed on different dates from
one extraction of the same sample and from different extractions from the same
sample.
For example, when an agricultural sample from 2003 was tested
numerous times using real-time PCR, the following threshold values were
obtained: 23.24, 22.81, 21.66, 24.67, 24.43, 22.87, 22.06, 21.69, 22.13, 23.83,
23.42, and 23.52. Then the median was calculated as 22.98, with a standard
deviation of 0.97 cycles, or 2-fold variance.
The samples exhibited standard deviations from 0.1 to 1.2 Ct, allowing us to
conclude that the samples did not show high variation between identical real-time
52
PCR assays. As a result, it was determined not to run multiple real-time PCR
assays for each of the samples. Again, this data suggests that the extraction
process was highly reliable for analysis by real-time PCR; real-time PCR was
also highly consistent for quantifying gene abundance.
The abundance of the genes need to display at least a two- to three-fold
difference in gene copy number, in order to conclude that the samples were
substantially different. For example the abundance of nifH genes during 2003 in
the agricultural stream (Table 8) shows differences between sediment samples,
9.3 x 103 gene copies, and leaf fractions, 1.0 x 107 gene copies, where the
differences observed were above three-fold increment covering gene counting
error.
In the urban stream in 2003, the sediments in the lower part of the reach
showed the greatest abundance of nifH genes, 1.0 x 105 gene copies per gram of
sediment wet weight (or other sample type, i.e., algal biomass, leaf litter, etc)
(Table 6 and 16). However in the 2004 samples, the abundance of nifH was very
low, below the detectable level of <2.0 x 102 gene copies per gram. Only algal
mat samples showed an abundant diazothrophic community (Table 7 and 17).
In the agricultural steam in 2003, the greatest nifH abundance was found in
leaf litter, about 1.0 x 107 gene copies per gram. The other samples showed
differences of two- to four-fold (Table 8 and 14). In the 2004 agricultural stream
samples, only the low reach sediments and a few algal mat samples showed
high numbers of genes, 1.0 to 2.0 x 106 gene copies per gram (Table 9 and 15).
53
During this year, the abundance of genes in the sediments fell below the
detectable level.
In the pristine stream during 2003, the greatest nifH abundance was found
in leaf litter, about 3.37 x 106 gene copies per gram (Table 10 and 12), while
gene abundance was relatively high among all of the samples for this year,
including sediments. During 2004, the number of pristine stream samples
collected was lower, because of the stream conditions; there was much gravel
and rock, but very little leaf litter or sediments. For this stream, 2.02 x 106 gene
copies per gram was the highest number of nifH genes found in this year (Table
11 and 13).
Assuming that the DNA extraction protocol was 100% efficient, and that
each nitrogen-fixing organism possesses one nifH gene per cell, the gene copy
numbers obtained for each stream and each year may be related to the number
of organisms found per gram of sediment (or other sample type, i.e., algal
biomass, leaf litter, etc).
The samples used for measuring the abundance of nifH genes, were used
to measure the abundance of universal archaeal and bacterial 16S rRNA genes.
In the 2003 urban stream, the abundance of bacteria ranged from 2.6 x 108 to 3.3
x 1010 gene copies per gram and the abundance of archaea was from 9.5 x 108
to 1.1 x 1012 gene copies per gram (Table 16). In the urban stream in 2004, the
abundance of bacteria was 3.9 x 109 to 4.0 x 1012 gene copies per gram and the
abundance of archaea was 5.6 x 109 to 2.8 x 1011 gene copies per gram (Table
17).
54
In the agricultural streams, the bacterial abundance in 2003 ranged from
5.5 x 106 to 7.1 x 1010 gene copies per gram and in 2004 ranged from 5.0 x 107
to 6.0 x 1010 gene copies per gram (Table 14). The abundance of archaea in
2003 was about 1.2 x 108 to 2.0 x 1012 gene copies per gram and in 2004 was
1.8 x 109 to 6.5 x 1011 gene copies per gram (Table 15).
Finally, during 2003 in the pristine stream, the abundance of bacteria
ranged from 3.7 x 109 to 1.7 x 1011 gene copies per gram (Table 12), and in 2004
ranged from 3.6 x 109 to 2.5 x 1011 gene copies per gram. The archaea
abundance was 1.8 x 109 to 1.1 x 1012 gene copies per gram, during 2003 and
from 2.2 x 107 to 2.7 x 1011 gene copies per gram during 2004 (Table 13).
The abundance of archaea as well as bacteria was very consistent
throughout all the sites and samples. Both were always found in great quantity,
and their abundance was much more than the specialized diazotrophs or
nitrogen fixers about 1 million-fold (≥1.0 x 106).
Results from this research strongly support the second hypothesis
proposed. Although the amount of nutrients (i.e., nitrogen) fluctuates between
streams, the microbial population of diazotrophs remained unchanged; this may
be because nifH genes may not produce a selective disadvantage in these
microbial communities under normal conditions. All of the streams showed an
abundance of nitrogen-fixers as well as archaea and bacteria. The abundance of
different microbial communities such as bacteria and archaea remained
unvarying in all the environments according to the data obtained from gene
counting, approximately 1.0 x 108 to 1.0 x 1012 gene copies per gram (Tables 12-
55
17). Nevertheless, if a microbial community, such as diazotrophs, has the genetic
machinery for a specific metabolic activity, in this case nitrogen fixation, it does
not mean that the expression of it will occur in all of the cases, as observed in
this study. Although we are examining nitrogen fixation activities and gene
abundance, the two cannot be directly correlated because one link is still
missing: gene expression.
In order to test for the presence of any inhibitory substance coming from the
extraction process that could inhibit the real-time PCR reaction, a set of tests
were run using a kanamycin-resistance gene, which is not found in the natural
environment. Some of the DNA extractions were spiked with DNA from a known
strain of Pseudomonas M1, which carried a kanamycin-resistance gene. Each
environmental sample was tested to see if it inhibited the amplification of the
exogenous kanamycin gene. The difference between the test samples and the
pure Pseudomonas was not significant based on amplification times or Ct. All of
the reactions amplified very efficiently. The range of amplification efficiency for all
the streams’ samples was between 98.9% and 99.9% (Tables 18-23).
This study demonstrates the potential of new molecular technology such as
real-time PCR for quantifying the abundance of microbial guilds in particular
environments.
This method is fast and reliable. In addition, it is remarkably
sensitive, needing as little as 1 pg of target DNA and can be analyzed to give
quantitative data. About 200 nifH gene copies per gram fix this was the detection
limit by this technique. It is important to remember that this molecular approach
56
offers benefits relative to culture-based microbiology and a new window to
understanding the undiscovered world of as-yet ill described microbial ecology.
57
CHAPTER 5
CONCLUSIONS
The acetylene reduction assays showed high variability in nitrogen fixation
rates among the three different stream types each year. Also the assays indicate
lowlevels of nitrogenase activity in the streams, fentograms per gram of sediment
per hour. These values are consistent with reported data from other aquatic and
terrestrial environments, where the activity of the enzyme was very low. In
addition, variability of the ARA results among different samples has been
reported in studies on root nodules in plants and the rhizosphere of marsh grass
(13, 102).
Overall the acetylene reduction assay has been widely used for
measuring the activity of nitrogenase, and this method is easy to perform and
inexpensive, nevertheless, the technique maynot reflect nitrogen fixation under
natural environmental conditions per se. However, other studies have
demonstrated that the activity associated with the reduction of C2H4 to C2H2 was
indeed correlated with in situ nitrogenase activity. Under natural conditions the
end product, ammonia, combines with other products of metabolic processes,
providing a source of reductant and ATP that does not happen under laboratory
conditions (36, 47, 62, 102, 106).
Perhaps the end product of acetylene
reduction, ethylene, diffuses in the closed environment, behaving as an inhibitor
of the process. Although there are some biases affecting the technique, it gives
an estimate of activity that can be extrapolated to field conditions. A suggestion
for further analysis would be to implement a different system that measures the
58
activity directly in the field without any disturbance of the environment or use
heavy nitrogen (15N2) techniques coupled with measuring the expression of the
enzyme, which could be some more accurate in situ (11).
Nitrogen fixation activity appeared to be much higher in the leaf litter
fractions in 2003 and in the sediment fractions in 2004, and the algal mat
fractions showed high activity and nifH abundance as expected. The algal biofilm
consisted of cyanobacteria and possibly diatoms, as described by O’brien et al.
(27, 72). During the different sampling years the stream’s conditions were very
diverse. All of them presented very low discharge to intermittent flows
approximately six months of the year, and different concentrations of NO3⎯ (Table
4). The dissimilarity of the sites ranged from perennial reaches with a cobble
bottom and a open canopy to deep incised channels with a silt bottom and
overhanging vegetation (27, 72).
N2-fixation activity appears to be negatively correlated with nitrogen loading
in the streams. In other words the higher the availability of nitrogen in the
environment, the lower the rate of nitrogen fixation. The rate of nitrogen fixation is
driven by the amount of dissolve nitrogen in the environment (13). Previous
studies have demonstrated that a high concentration of NH4+ in sediments
inhibits nitrogenase activity by minimizing energy consumption (26). Research
developed by Capone et al. (1982), showed that when NH4+ was removed from
the system the ability of diazotrophs to fix nitrogen increases (18). Conversely,
Piceno and Lovell (79) and Bagwell and Lovell (4) published that some
diazothrophic
communities
have
the
59
ability
to
perform
their
process
independently of the amount of nutrients in the system. Also it was determined
that the population of nitrogen-fixers was very diverse and highly specialized
according to their niche. This suggests that there are some predominant
nitrogen-fixers that might be inhibited by nitrogen in the surroundings, while
others work efficiently and independently of what it is in the environment.
Enzymatic activity does not provide any information about how abundant or
diverse these microorganisms are in the stream system, and how they contribute
to the global nitrogen cycle by performing nitrogen fixation. The development of
new molecular tools allows us to determine the abundance of this community in
this particular environment, without depending on culture-based techniques, that
provides a better understanding of the diversity and structure of the guild (3, 13,
22, 91). Using a fairly new molecular approach, real-time PCR, the abundance of
several gene markers such as, 16S rRNAs and nifH was determined. The
abundance of bacterial 16S rRNA was between 1.0 x 106 to 1.0 x 1012 gene
copies per gram sample. The abundance of archaeal 16S rRNA was between 1.0
x 108 to 1.0 x 1012 gene copies per gram sample. The abundance of nifH genes
ranged from 1.0 x 103 to 1.0 x 107 gene copies per gram sample in all streams.
The detection limit for nifH abundance was 2 x 102 gene copies per gram
sample. The difference between nifH gene abundance and bacterial and
archaeal 16S rRNA gene abundance suggests that for every 10,000 to 1,000,000
microorganisms only 1 is a N2-fixing organism. As mentioned above this new
approach is still under development, consequently, there is not very much
research on quantifying the abundance of nitrogen-fixers. One of the most recent
60
publications by Boström et al. (10) presented quantification of Nodularia spp., the
main nitrogenase-containing organisms in surface waters. This was performed in
samples from the Baltic Sea proper. They showed that the abundance of
Nodularia spp was about 3.4 x 106 nifH copies per liter of water.
According to the data presented here, it was presumed that N2-fixation
activity was not directly correlated with nifH gene abundance in these
environments. According to the data, N2-fixing organisms were more or less
abundant in all of the streams, although the number of organism varied from
stream to stream. Nevertheless, it was shown that they were present under all
conditions in the different environments. However, the number of organisms can
not be directly associated with nitrogenase activity measurements, because
expression of the gene or enzyme is not being measure. In other words, it will be
necessary to measure mRNA levels to calculate the expression of the gene by
using reverse-transcriptase real-time PCR, which is suitable, sensitive and
quantitative (60, 61, 104). Recent studies on nifH expression developed by You
et al. (2005) presented diazotroph abundance as free-cells and symbiotic
organisms.
The abundance of nifH transcripts in endophytic cells was 6.7
pmol/1012 cells to 5.0 pmol/1010 cells versus only 10 pmol/1010 cells in free
diazotrophs. It was demonstrated that nitrogen fixation activity in rice was
regulated by oxygen concentration and light for endophytic microorganisms (67)
Finally nifH genes have been highly conserved among microbial species in
numerous and distinct environments and they likely do not produce a selective
disadvantage in these microbial communities under normal conditions (50). The
61
retention of the gene may provide a potential survival mechanism when
fluctuations occur, and this will allow diazotrophs to maintain homeostasis when
the niche faces drastic changes from low to high N and vice versa (4, 13, 58, 79,
80).
62
CHAPTER 6
REFERENCES
63
LIST OF REFERENCES
1.
Audermand C, Reece K.S, and Burreson E.M. 2004. Real-time PCR for
detection and quantification of the prostistan parasite Perkinsus marinus in
environmental waters. Applied and Environmental Microbiology 70:66116618.
2.
Auman A. J, Speake C. C, and Lidstrom M. E. 2001. nifH sequences
and nitrogen fixation in type I and type II methanotrophs. Applied and
Environmental Microbiology 67:4009-4016.
3.
Ausubel F. M, Brent R, Kingston R. E, Moore D. D, Seidman J. D,
Smith J. A, and Struhl K. 1992. Short protocols in molecular biology.,
p. A2-A4. Greene Publishing Associates and John Wiley and Sons.
4.
Bagwell C. E, and Lovell C. R. 2000. Persistence of selected Spartina
alterniflora rhizoplane diazotrophs exposed to natural and manipulated
environmental variability. Applied and Environmental Microbiology
66:4625-4633.
5.
Baldwin B. R, Nakatsu C. H, and Nies L. 2003. Detection and
enumeration of aromatic oxygenase genes by multiplex and real-time
PCR. Applied and Environmental Microbiology 69:3350-3358.
6.
Bartha R, and Atlas R. M. 1998. Microbial ecology fundamentals and
applications, Fourth Edition ed. Benjamin/Cummings Science Publishing.
7.
Berger M. C, and Peters G. A. 1974. The Azolla, Anabaena Azollae
relationship. Plant Physiology 53:820-824.
8.
Bernot M. J, Dodds W. K, Gardner W. S, McCarthy M. J, Sobolev D,
and Tank J. L. 2003. Comparing denitrification estimates for a Texas
estuary by using acetylene inhibition and membrane inlet mass
spectrometry. Applied and Environmental Microbiology 69:5950-5956.
9.
Boesch D. F, Brinsfield R. B, and Magniene R. E. 2001. Chesapeake
Bay eutriphication: scientific understanding ecosystem restoration, and
challenges for agriculture. Journal Environmental Quality 30:303-320.
10.
Boström K. H, Riemann L, Zweifel U. L, and Hagström Å. 2007.
Nodularia sp. nifH gene transcripts in the Baltic Sea proper. Journal of
Plankton Research 29:391-399.
11.
Buckley D. H, Huangyutitham V, Hsu S-F, and Nelson T. A. 2007.
Stable isotope probing with 15N2 reveals novel non-cultivated diazotrophs
in soil. Applied and Environmental Microbiology 10:1128.
64
12.
Burgman, H., M. Pesaro, F. Widmer, and J. Zeyer. 2001. A strategy for
optimizing quality and quantity form DNA extracted from soil. Journal of
Microbiological Methods 45:7-20.
13.
Burns J. A, Zehr J. P, and Capone D. G. 2002. Nitrogen-fixing
phyloptypes of Chesapeake Bay and Neuse River estuary sediments.
Microbial Ecology 44:336-343.
14.
Burris R.H. 1991. Minirieview: nitrogenases. The Journal of Biological
Chemistry 266:9339-9342.
15.
Cabello P, Roldan M. D, and Moreno-Vivian C. 2004. Review, nitrate
reduction and the nitrogen cycle in archaea. Microbiology 150:3527-3546.
16.
Cale M. H, and Ludden P.W. 2000. Regulation of biological nitrogen
fixation. American Society For Nutritional Sciences 96:1081-1084.
17.
Cantera J. J. L, Kawasaki H, and Seki T. 2004. The nitrogen-fixing (nifH)
of Rhodopseudomonas palustris: a case of lateral gene transfer?
Microbiology 150:2237-2246.
18.
Capone D. G, and Carpenter E. J. 1982. Perfussion method for assaying
microbial activities in sediments: applicability to studies of N2 fixation by
acetylene reduction. Applied and Environmental Microbiology 43:14001405.
19.
Caton T. M. 2003. Initial isolation and characterization of aerobic
heterotrophic prokaryotes from the Great Salt Plains, Oklahoma. Wichita
state University, Wichita.
20.
Christiansen J, Cash V. L, Seefeldts L. C, and Dena D. R. 2000.
Isolation and characterization of an acetylene-resistant nitrogenase. The
Journal of Biological Chemistry 275:11459- 11464.
21.
Cornwell J. C, Coley D. J, Owens M, and Stevenson J. C. 1996. A
sediment chronology of eutrophication of Chesapeake Bay. Estuaries
19:488-499.
22.
Davidson S. G, Merwin Jr J. G, G. Power, and Shivers Jr F. R. 1997.
Chesapeake waters: four centuries of controversy, concern, and
legislation, Tidewater Publication, Centreville, MD.
23.
Davis R, Leaman L, Petrovich R, Shah V. K, Roberts G. P, and
Ludden W. 1995. Purification and characterization of the alternative
nitrogenases form the photosynthetic bacterium Rhodospirillum rubrum.
Journal of Bacteriology 178:1445-1450.
65
24.
Dedysh S. N, Ricke P, and Liesack W. 2004. nifH and nifD phylogenies:
an evolutionary basis for understanding nitrogen fixation capabilities of
methanotrophic bacteria. Microbiology 150:1301-1313.
25.
Dionisi M. H, Harms G, Layton A.C, Gregory I.R, Parker J, Hawkins S.
A, Robinson K.G, and Sayler G. S. 2003. Power analysisfor real-time
PCR quantification of genes in activated sludge and analysis of the
vaariability introduced by DNA extraction. Applied and Environmental
Microbiology 69:6597-6604.
26.
Dixon R, and Kahn D. 2004. Genetic regulation of biological nitrogen
fixation. Nature Reviews Microbiology 2:612-631.
27.
Dodds W. K, Evans-White M. A, Gerlanc N. M, Gray L, Gudder A. D,
Kemp J. M, Lopez A. L, Stagliano D, Strauss E. A, Tank J. L, Whiles
M. R, and Wollheim W. M. 2000. Quantification of the nitrogen cycle in a
prairie stream. Ecosystems 3:574-589.
28.
Dodds W. K, Lopez A. J, Bowden W. B, Gregory S, Grimm N. B,
Hamilton S. K, Hershey A. E, Marti E, McDoell W. H, Meyer J. L,
Morrall D, Mulholland P. H, Peterson B. J, Tank J. L, Valett M. H,
Webster J. R, and Wollheim W. 2002. N uptake as a function of
concentration in streams. Journal of North American Benthological Society
21:206-220.
29.
Dodds W. K, and Welch E. B. 2000. Establishing nutrient criteria in
streams. Journal of North American Benthological Society 19:186-196.
30.
Doolittle W. F. 1999. Lateral genomics. Trends in Biochemical Sciences
24:M5-M8.
31.
Dos Santos P. C, Dean D.R, Hu Y, and Ribbe M. W. 2004. Formation
and in sertion of the nitrogenase iron-molybdenum cofactor. Chemistry
Reviews 104:1159-1173.
32.
Fierer N, Jackson J.A, Vilgalys R, and Jackson R. B. 2005.
Assessment of soils microbial community structure by use of taxonspecific quantitative PCR assays. Applied and Environmental Microbiology
71:4117-4120.
33.
Filion M, St-Arnaud M, and Jabaji-Hare S.H. 2003. Direct quantification
of fungal DNA from soil substrate using real-time PCR. Journal of
Microbiological Methods 53:67-76.
66
34.
Fischer H-M, Schneider K, Babst M, and Hennecke H. 1999. GroEl
chaperoins are required for the formation of a functional nitrogenase in
Bradyrhizobium japonicum. Archives of Microbiology 171:279-289.
35.
Flacon L. I, Carpenter E. J, Cipriano F, Bergman B, and Capone D. G.
2004. N2 fixation by unicellular bacteriplankton from Atlantic and Pacific
oceans: phylogeny and in situ rates. Applied and Environmental
Microbiology 70:765-770.
36.
Flett R. J, Rudd W. M, and Hamilton R. D. 1975. Acetylene reduction
assay for nitrogen fixation in freshwaters: a note of caution. Applied
Microbiology 29:580-583.
37.
Gachon C, Mingam A, and Charrier B. 2004. Real-time PCR: what
relevance to plant studies. Journal of Experimental Botany 55:1445-1454.
38.
Giglio S, Monis P. T, and Saint C. P. 2003. Demonstration of preferential
binding of SYBR Green I to specific DNA fragments in rela-time multiplex
PCR. Nucleic Acids Research 31.
39.
Gruntzig V, Nold S.C, Zhou J, and Tiedje J. M. 2001. Pseudomonas
stuzeri nitrite reductase gene abundance in environmental samples
measured by real-time PCR. Applied and Environmental Microbioogy
67:760-768.
40.
Halbleib C. M, and Ludden P.W. 2000. Regulation of nitrogen fixation.
Recent Advances in Nutritional Sciences:1081-1084.
41.
Hardy R. W. F, Holsten R. D, Jackson E. K, and Burns R. C. 1968. The
acetylene-ethylene assay for N2 fixation: laboratory and field evaluation.
Plant Physiology 43:1185-1207.
42.
Hedin L. O, Armesto J. J, and Johnson A. H. 1995. Patterns of nutrient
loss from unpolluted, old-growth temperate forests: evaluation of
biogeochemical theory. Ecology 76:493-509.
43.
Henson B. J, Watson L. E, and Barnum S. R. 2004. The evolutionary
history of nitrogen fixation, as assessed by nifD. Journal of Molecular
Evolution 58:390-399.
44.
Hermansson A, and Lindgren P.E. 2001. Quantification of ammoniaoxidizing nacteria in arable soil by real-time PCR. Applied and
Environmental Microbiology 67:972-976.
67
45.
Hernadez M, Rodriguez-Lazaro D, Esteve T, Prat S, and Pla M. 2003.
Development of melting temperature-based SYBR Green I polymerase
chain reaction methods for multiplex genetically modified organism
detection. Analytical Biochemistry 323:164-170.
46.
Hristova K. R, Lutenegger C. M, and Scow K. M. 2001. Detection and
quantification of methyl tert-butyl ether-degrading strain PM1 by real-time
PCR TaqMan PCR. Applied and Environmental Microbiology 67:51545160.
47.
Huang Chi-Y, Boyer J. S, and Vanderhoef L. N. 1975. Acetylene
reduction (nitrogen fixation) and metabolic activities af soyben having
various leaf and nodule water potentials. Plant Physiology 56:222-227.
48.
Igarashi R. Y, and Lance C. S. 2003. Nitrogen fixation: the mechanism
of the Mo-dependent nitrogenase. Critical Reviews in Biochemistry and
Molecular Biology 38:351-384.
49.
Jaworski N. A. 1990. Retrospective of the water quality issues of upper
Potomac estuary. Aquatic Sciences 3:11-40.
50.
Jenkins B. D, Steward G. F, Short S. M, Ward B. B, and Zehr J. P.
2004. Fingerprinting diazotroph communities in the Chesapeake Bay by
using a DNA macroarray. Applied and Environmental Microbiology
70:1767-1776.
51.
Jensen B.B, and Cox R. P. 1983. Direct measurements of steady-state
kinetics of cyanobacterial N2 uptake by memebrane leak mass
spectrometry and comparison bewteen nitrogen fixation and acetylene
reduction. Applied and Environmental Microbiology 45:1331-1337.
52.
Klaus M, and Oelze J. 1999. Control by light of whole-cell nitrogenase
activity and of nitrogenase and bacteriochlorophyll a formation in
Rhodobacter capsulatus strain B10S. Archives of Microbiology 171:243248.
53.
Koch B, Evans H. J, and Russell S. 1967. Reduction of acetylene and
nitrogen gas by breis andcell-free extracts of soybean roots nodules.
Plant Physiology 42:466-468.
54.
Kolb S, Knief C, Stubner S, and Conrad R. 2003. Quantitaive detection
of metanotrophs in soil by novel pmoA-targeted real time PCR assays.
Applied and Environmental Microbiology 69:2423-2429.
68
55.
Lee S.Y, Bollinger J, Bezdicek D, and Ogram A. 1996. Estimation of the
abundance of an uncultured soil bacteial strain by a competitive
quantitative PCR method. Applied and Environmental Microbiology
62:3787-3793.
56.
Liu W. T, Marsh T. L, Cheng H, and Forney L. J. 1997. Characterization
of microbial diversity by determining terminal restriction fragment length
polymorphism of genes encoding 16S rRNA. Applied and Environmental
Microbiology 63.
57.
Lohrenz S. E, Fahnenstiel G. L, Redalje D. G, Lang G. A, Chen X, and
Dagg M. J. 1997. Variations in primary production of northern Gulf of
Mexico continental shelf waters linked to nutrient inputs from the Mississipi
River. Marine Ecology Progress Series 155:435-454.
58.
Lovell C. R, Piceno Y. M, Quattro J. M, and Bagwell C. E. 2000.
Molecular analysis of diazotroph diversity in therhizosphere of the smooth
cordgrass, Spartina alterniflora. Applied and Environmental Microbiology
66:3814-3822.
59.
MacGregor B. J, Van Mooy B, Baker B. J, Mellon M, Moisander P. H,
Paerl H. W, Zehr J, Hollander D, and Stahl D. A. 2001. Microbiological,
molecular biological, and stable isotopic evidence for nitrogen fixation in
the open waters of lake of Michigan. Environmental microbiology 3:205219.
60.
Mackay I. M. 1998. Review: real-time PCR in the microbiology laboratory.
European Society by the Clinical Microbiology and Infectious diseases
CMI 10:190-212.
61.
MacKay I. M, Arden K. E, and Nitsche A. 2002. Real-time PCR in
virology. Nucleic Acids Research 30:1292-1305.
62.
Manhart J. R, and Wong P.P. 1980. Nitrate effect on nitrogen fixation
(acetylene reduction). Plant Physiology 65.
63.
McIsaac, G. F., David M. B, Gertner G. Z, and Goolsby A. D. 2002.
Relating net nitrogen input in the Mississippi River basin to nitrate flux in
the lower Mississippi river: a comparison of approaches. Journal of
Environmental Quality 31:1610-1622.
64.
McReynolds L. A, and Zehr J. P. 1989. Use of degenerate
oligonucleotides for amplification of the nifH gene from the marine
cyanobacterium Trichodesmium thiebautti. Applied and Environmental
Microbiology 55:2522-2526.
69
65.
Mehta M. P, Butterfield D. A, and Baross J. A. 2003. Phylogenetic
diversity of nitrogenase (nifH) genes in deep-sea and hydrotermal vent
environments of the Juan de Fuca ridge. Applied and Environmental
Microbiology 69:960-970.
66.
Mesarch M. B, Nakatsu C.H, and Nies L. 2000. Development of catechol
2,3-dioxygenase-specific primers for monitoring bioremediation by
competitive quantitative PCR. Applied and Environmental Microbiology
66:678-683.
67.
Mu You, Nishiguchi T, Saito A, Isawa T, and Mits H. 2005. Expression
of the nifH gene of a Herbaspirillum endophyte in wild rice species: daily
rhythm during the light-dark cycle. Applied and Environmental
Microbiology 71:8183–8190.
68.
Mulholland P. J, Fellows C. S, Tank J. L, Grimm N. B, Webster J. R,
Hamilton S. K, Marti E, Ashkenas L, Bowden B, Dodds W. K,
McDowell W. H, Paul M. J. M, and P. B. J. 2001. Inter-biome comparison
of factors controlling stream metabolism. Freshwater Biology 46:15031517.
69.
Nadkarni M. A, Martin E, Jacques N. A, and Hunter N. 2002.
Determination of bacerial load by real-time PCR using a broad-range
(universal) probe and primer set. Microbiology 148:257-266.
70.
Neufeld J. D, Drisoll B.T, Knowles R, and Archibald F. S. 2001.
Quatifyng functional gene popualtions: comparing gene abundance and
corresponding enzymatic activity using denitrification and nitrogen fixation
in pul and paper mill effluent treatment systems. Canadian Journal of
Microbiology 47:925-934.
71.
Nixon S. W. 1995. Coastal marine eutrophication: A definition, social,
causes, and future concerns. Ophelia 41:199-219.
72.
O'Brien M. J, Dodds W. K, Wilson K. C, Murdock J. N, and Eichmiller
J. 2006. The saturation of N cycling in streams: 15N experiments across a
broad gradient of nitrate concentrations. In U. Data (ed.).
73.
Ohkuma M, Noda S, and Kudo T. 1999. Phylogenetic diversity of
nitrogen fixation genes in the symbiotic microbial community in the gut of
diverse termites. Applied and Environmental Microbiology 65:4926-4934.
70
74.
Okano Y, Hristova K. R, Leutenegger C.M, Jackson L. E, Denison F.
R, Gebreyesus B, Lebauer D, and Scow K.M. 2004. Application of realtime PCR to study effects of ammonium on population size of ammoniaoxidizing bacteria in soil. Applied and Environmental Microbiology
70:1008-1016.
75.
Olson J. B, Steppe T.F, Litaker R.W, and Paerl H. W. 1998. N2-fixing
microbial consortia associated with the ice cover of Lake Bonney,
Antarctica. Microbial Ecology 36:231-238.
76.
Pelegri S. P, Rivera-Monroy V. H, and Twilley R. R. 1997. A comparison
of nitrogen fixation (acetylene reduction) among three species of
mangrove litter, sediments and pneumatophores in South Florida, USA.
Hydrobiologia 356:73-79.
77.
Pelegri S.P, and Twilley R. R. 1998. Heterotrophic nitrogen fixation
(acetylene reduction) during leaf-litter decomposition of two mangrove
species from South Florida, USA. Marine Biology 131:53-61.
78.
Peterson B. J, Wollheim W. M, Mulholland P. J, Webster J. R, Meyer
J. L, Tank J. L, Marti E, Bowden W. B, Valett H. M, Hershey A. E,
McDowell W. H, Dodds W. K, Hamilton S. K, Gregory S, and Morall D.
D. 2001. Control of nitrogen export from watersheds by headwater
streams. Science 292:86-90.
79.
Piceno Y. M, and Lovell C. R. 2000. Stability in natural bacterial
communities: I. Nutrients addition effects on rhizospheres diazotroph
assemblage composition. Microbial Ecology 39:32-40.
80.
Piceno Y. M, Noble P. A, and Lovell C. R. 1999. Spatial and temporal
assessment of diazotroph assemblage composition in vegetated salt
marsh sediments using denaturing gradient gel electrophoresis analysis.
Microbial Ecology 38:157-167.
81.
Poly F, Ranjard L, Nazaret S, Gourbiere F, and Monrozier L.J. 2001.
Comparison of nifH gene pools in soils and soil microenvironments with
contransting properties. Applied and Environmental Microbiology 67:22552262.
82.
Popels L. C, Cary S. C, Hutchins D.A, Forbes R, Pustizzi F, Gobler
C.J, and Coyne K. J. 2003. The use of quantitative polymerase chain
reaction for the detection and enumeration of the harmful alga Aurecoccus
anophagafferens in environmental samples along the United States East
Coast. Limnology and Oceanography: methods 1:92-102.
71
83.
Prithi R. 2005. Molecular analysis of the microbial guild fixing nitrogen in
ricefields. Wichita State University, Wichita, Kansas.
84.
Rabalais A. N, Turner R. E, and Wiseman Jr. W. J. 2001. Hypoxia in the
Gulf of Mexico. Journal of Environmental Quality 30:320-329.
85.
Raymond J, Siefert J.L, Staples C.R, and Blankenship R. E. 2003. The
natural history of nitrogen fixation. Molecular Biology and Evolution
21:541-554.
86.
Rengajaran K, Cristol S. M, Mehta M, and Nickerson J. M. 2002.
Quantifying DNA concentrations using fluorometry: a comparison of
fluorophores. Molecular Vision 8:416-421.
87.
Rodriguez-Diaz M, Lebbe L, Rodelas B, Heurman J, De Vos P, and
Logan N. A. 2005. Paenibacillus wynnii sp. nov., a novel species
harbouring the nifH gene, isolated from Alexander Island, Antarctica.
International Journal of Systematic and Evolutionary Microbiology
55:2093-2099.
88.
Rosado A.S, Duarte G. F, Seldin L, and Van Elsas J.D. 1998. Generic
diversity of nifH gene sequences in Paenibacillus azotofixans strains and
soil samples analyzed by denaturing gradient gel electrophoresis of PCRamplified gene Fragments. Applied and Environmental Microbiology
64:2770-2779.
89.
Rubio L. M, and Ludden P. W. 2005. Maturation of nitrogenase: a
biochemical puzzle. Journal of Bacteriology 187:405-414.
90.
Sambrook J, Fritsch E. F, and Maniatis T. 1989. Molecular Cloning.
Cold Spring Harbor Laboratory Press.
91.
Schimel D. S, Braswell B. H, and Parton W. J. 1997. Equilibration of the
terrestrial water, nitrogen, and carbon cycles. Proceedings of the National
Academy of Sciences 94:8280-8283.
92.
Schneegurt M. A, Sherman D. M, Nayar S, and Sherman L.A. 1994.
Oscillating behavior of carbohydrate granule formation and dinitrogen
fixation in the Cyanobacterium Cyanothece sp. strain ATCC 51142.
Journal of Bacteriology 176:1586-1597.
93.
Shaffer B. T, Widmer F, Porteous L. A, and Seidler R. J. 2000.
Temporal and spatial distribution of the nifH Gene of N2 fixing bacteria in
forests and clearcuts in western Oregon. Microbial Ecology 39:12-21.
72
94.
Staal M, Lintel-Hekkert S-te, Harren F, and Stal L. 2001. Nitrogenase
activity in cyanobacteria measured by the acetylene reduction assay: a
comparison between batch incubation and on-line monitoring.
Environmental Microbiology 3:343-351.
95.
Steward G. F, Jenkins B. D, Ward B. B, and Zehr J. P. 2004.
Development and testing of a DNA macroarray to assess nitrogenase
(nifH) gene diversity. . Applied and Environmental Microbiology 70:14551465.
96.
Steward G. F, Zehr J. P, Jellison R, Montoya J. P, and Hollibaugh J. T.
2003. Vertical distribution of nitrogen-fixing phylotypes in a meromictic,
hypersaline lake. Microbial Ecology 47:30-40.
97.
Stewart W. D. P, Fitzgerald G. P, and Burris R. H. 1967. In situ studies
on N2 fixation using acetylene reduction technique. Biochemistry 58:20712078.
98.
Takai K, and Horikoshi K. 2000. Rapid detection and quantification of
members of the archaeal community by quantitative PCR using
fluorogenic probes. Applied and Environmental Microbiology 66:50665072.
99.
Tamas I, Svircev Z, and Andersson G. E. 2000. Determinative value of a
portion of the nifH sequence for the genera Nostoc and Anabaena
(Cyanobacteria). Current Microbiology 41:197-200.
100.
Taroncher-Oldenburg G, Griner E. M, Francis C. A, and Ward B. B.
2003. Oligonucleotide microarray for the study of functional gene giversity
in the nitrogen cycle in the environment. Applied and Environmental
Microbiology 69:1159-1171.
101.
Taylor L. A, and Rose R. E. 1988. A correction in the nucleotide
sequence of the Tn903 kanamycin resitance determinant in pUC4K.
Nucleic Acids Research 16:358.
102.
Tjepkema J. D, Schwintzer C. R, and Monz C. A. 1988. Time course of
acetylene reduction in nodules of five actinorhizal genera. Plant
Physiology 86:581-583.
103.
Ueda T, Suga Y, Yahiro N, and Matsuguchi T. 1995. Remarkable N2fixing bacterial diversity detected in rice roots by molecular evolutionary
analysis of nifH gene sequences. Journal of Bacteriology 177:1414-1417.
73
104.
Valasek M. A, and Repa J.J. 2005. The power of real-time PCR.
Advances in Physiology Education 29.
105.
Vandenbroucke I. I, Vandesopele J, Paepe A. P, and Messiaen L.
2001. Quantification of splice variants using real-time PCR. Nucleic Acids
Research 29:e 68.
106.
Vanderhoef L. N, Leibson P. J, Musil R. J, Huang C-Y, Fiehweg R. E,
Williams J. W, Wackwitz D. L, and Mason K. T. 1975. Diurnal variation
in algal acetylene reduction (nitrogen fixation) in situ. Plant Physiology
55:273-276.
107.
Vitousek P. M, and Howarth R. W. 1991. Nitrogen limitation on land in
the sea: how can it occur? Biogeochemistry 13:87-115.
108.
Welsh D. T. 2000. Review, nitrogen fixation in seagrass meadows:
regulation, plant-bacteria interactions and significance to primary
productivity. Ecology Letters 3:58-71.
109.
Widmer F, Shaffer B. T, Porteous L. A, and Seidler R. J. 1999. Analysis
of nifH gene pool complexity in soil and litter at a Douglas Fir forest site in
the Oregon cascade mountain range. Applied and Environmental
Microbiology 65:374-380.
110.
Williams V, and Fletcher M. 1996. Pseudomonas fluorescens adhesion
and transport through porous media are affected by lipopolysacharide
composition. Applied and Environmental Microbiology 62:100-104.
111.
Yongmei S, Polishchuk E. A, Radoja U, and Cullens W. R. 2004.
Identification and quatification of arsC genes in environmental samples by
using real-time PCR. Journal of Microbiological Methods 58:335=349.
112.
Yu Y, Lee Ch, and Hwang S. 2005. Group-specific primer and porbe sets
to detect methanogenic communities using quantitative real-time
polymerase chain reaction. Biotechnology and Bioengineering 89:670679.
113.
Zehr J. P, and Capone D.G. 1996. Problems and promises of assaying
the genetic potential for nitrogen fixation in marine environment. Microbial
Ecology 32:263-281.
114.
Zehr J. P, Jenkins B. D, Short S. M, and Steward G. F. 2003.
Minireview: nitrogenase gene diversity and microbial community structure:
a cross-system comparison. Environmental Microbiology 5:539-554.
74
115.
Zehr J. P, Jenkins B. D, Short S. M, and Steward G. F. 2003.
Nitrogenase gene diversity and microbial community structure: a crosssystem comparison. Environmental Microbiology 5:539-554.
116.
Zehr J. P, Mellon M, Braun S, Litaker W, Steppe T, and Paerl H. W.
1995. Diversity of heterotrophic nitrogen fixation genes in a marine
cyanobacterial mat. Applied and Environmental Microbiology 61:25272532.
117.
Zehr J. P, Mellon M.T, and Hiorns W. D. 1997. Phylogeny of
cyanobactrial nifH genes: evolutionary implications and potential
application to natural assemblages. Microbiology 143:1443-1450.
118.
Zehr J. P, and Ward B. B. 2002. Nitrogen cycling in the ocean:new
perspectives on processes and paradigms. Applied and Environmental
Microbiology 68:1015-1024.
119.
Zhang H, and Lin S. 2005. Development of a cob-18S rRNA gene realtime PCR assay for quantifying Pfiesteria shumwayae in the natural
environment. Applied and Environmental Microbiology 71:7053-7063.
75
CHAPTER 7
APPENDICES
76
APPENDIX A: TABLES
TABLE 5
CHEMICAL AND PHYSICAL PARAMETERS OF THE SIX STREAMS IN THIS
STUDY
NO3-N
NH4+-N
DON
WIDTH
DEPTH
(µg/L)
(µg/L)
(µg/L)
(m)
(m)
CAMPUS CREEK
2900.0
7.8
N.A.
2.56
0.08
WALMART DITCH
277.0
28.3
472
2.10
0.05
AG. NORTH CREEK
35.0
31.7
111
0.77
0.02
NATALIES CREEK
6.0
3.1
156
1.20
0.04
KINGS CREEK-N4D
8.6
0.0
196
2.40
0.07
KINGS CREEK-K2A
0.9
6.7
85
2.50
0.09
STREAM
N.A. = Data not available
AG = agricultural
77
TABLE 6
ASSESSMENT OF nifH ABUNDANCE BY REAL-TIME PCR AND NITROGEN
FIXATION BY ARA IN 2003 CAMPUS CREEK (URBAN) STREAM
nifH gene copies
N2 reduced
# gene/g sample
fmol/g sample/h
MIDDLE SEDIMENT BOTTOM
1.3 X 104
1.5
MIDDLE SEDIMENT TOP
<2.0 x 102
1.6
LOW MISCELANEOUS
2.3 x 104
2.5
LOW SEDIMENT TOP
3.4 x 104
2.1
LOW SEDIMENT BOTTOM
1.1 x 105
1.5
HIGH SEDIMENT TOP
2.0 x 103
1.9
SAMPLES
78
TABLE 7
ASSESSMENT OF nifH ABUNDANCE BY REAL-TIME PCR AND NITROGEN
FIXATION BY ARA IN 2004 WAL-MART DITCH (URBAN) STREAM
nifH gene copies
N2 reduced
# gene/g sample
fmol/g sample/h
ABOVE SEDIMENT
<2.0 x 102
2.3
MIDDLE SEDIMENT
<2.0 x 102
2.6
LOW SEDIMENT
<2.0 x 102
3.0
GREEN ABOVE
<2.0 x 102
93.5
MIDDLE "CUP"
7.8 x 106
62.7
LOW GREEN
<2.0 x 102
69.7
SAMPLES
79
TABLE 8
ASSESSMENT OF nifH ABUNDANCE BY REAL-TIME PCR AND NITROGEN
FIXATION BY ARA IN 2003 NORTH CREEK (AGRICULTURAL) STREAM
nifH gene copies
N2 reduced
# gene/g sample
fmol/g sample/h
ABOVE RELEASE SEDIMENT TOP
1.8 x 105
5.6
ABOVE RELEASE SED BOTTOM
5.5 x 104
4.5
HIGH SEDIMENT TOP
<2.0 x 102
7.1
HIGH SEDIMENT BOTTOM
1.9 x 105
6.2
MIDDLE SEDIMENT TOP
2.4 x 104
7.6
MIDDLE SEDIMENT BOTTOM
9.3 x 103
6.2
LOW LEAF FRACTIONS
1.0 x 107
14.8
SAMPLES
SED = sediment
80
TABLE 9
ASSESSMENT OF nifH ABUNDANCE BY REAL-TIME PCR AND NITROGEN
FIXATION BY ARA IN 2004 NATALIE’S CREEK (AGRICULTURAL) STREAM
nifH gene copies
N2 reduced
# gene/g sample
fmol/g sediment/h
ABOVE SEDIMENT
<2.0 x 102
2.1
MIDDLE SEDIMENT
<2.0 x 102
2.3
LOW SEDIMENT
1.6 x 106
5.6
MIDDLE GREEN
6.8 x 104
112.8
LOW GREEN
2.4 x 106
82.8
SAMPLES
81
TABLE 10
ASSESSMENT OF nifH ABUNDANCE BY REAL-TIME PCR AND NITROGEN
FIXATION BY ARA IN 2003 KINGS CREEK-N4D (PRISTINE) STREAM
nifH gene copies
N2 reduced
# gene/g sample
fmol/g sample/h
ABOVE SEDIMENT TOP
2 x 105
3.9
ABOVE UPPER LEAF LITTER
1.3 x 106
81.9
HIGH SEDIMENT BOTTOM
4.0 x 104
18.6
MIDDLE SEDIMENT TOP
1.5 x 106
NA*
MIDDLE SEDIMENT BOTTOM
2.5 x 106
NA*
LOW SEDIMENT BOTTOM
1.6 x 105
13.3
LOW LEAF LITTER
1.7 x 106
63.3
SAMPLES
* Due to the characteristics of the stream there was not enough sediment to run
the acetylene reduction assay in this particular area.
82
TABLE 11
ASSESSMENT OF nifH ABUNDANCE BY REAL-TIME PCR AND NITROGEN
FIXATION BY ARA IN 2004 KINGS CREEK-K2A (PRISTINE) STREAM
nifH gene copies
N2 reduced
# gene / g sample
fmol/g sample/h
ABOVE GREEN
10.0 x 103
2.9
MIDDLE SEDIMENT
2.3 x 104
3.2
LOW SEDIMENT
1.0 x 106
78.1
LEAVES POOL
3.0 x 104
9.2
SAMPLES
83
TABLE 12
COMPARISON OF GENE ABUNDANCE BETWEEN ARCHAEA, BACTERIA
AND DIAZOTROPHS IN 2003 KINGS CREEK-N4D (PRISTINE) STREAM
SAMPLES
nifH
Archaea
Bacteria
# gene/g
# gene/g
# gene/g
ABOVE SEDIMENT TOP
4.0 x 105
1.8 x 109
1.1 x 1011
ABOVE UPPER LEAF LITTER
2.5 x 106
1.0 x 1012
3.4 x 1010
HIGH SEDIMENT BOTTOM
8.0 x 104
1.5 x 1011
3.7 x 109
MIDDLE SEDIMENT BOTTOM
5.0 x 106
1.1 x 1011
1.4 x 1011
LOW SEDIMENT BOTTOM
3.2 x 105
9.2 x 109
1.7 x 1011
LOW LEAF LITTER
3.4 x 106
6.4 x 1010
5.8 x 1010
84
TABLE 13
COMPARISON OF GENE ABUNDANCE BETWEEN ARCHAEA, BACTERIA
AND DIAZOTROPHS IN 2004 KINGS CREEK-K2A (PRISTINE) STREAM
SAMPLES
nifH
Archaea
Bacteria
# gene/g
# gene/g
# gene/g
ABOVE GREEN
2.0 x 104
2.7 x 1011
2.5 x 1011
MIDDLE SEDIMENT
4.6 x 104
2.2 x 107
3.6 x 109
LOW SEDIMENT
2.0 x 106
8.7 x 109
9.8 x 1010
LEAVES POOL
6.0 x 104
1.6 x 1010
1.0 x 1010
85
TABLE 14
COMPARISON OF GENE ABUNDANCE BETWEEN ARCHAEA, BACTERIA
AND DIAZOTROPHS IN 2003 NORTH CREEK (AGRICULTURAL) STREAM
SAMPLES
nifH
Archaea
Bacteria
# gene/g
# gene/g
# gene/g
ABOVE RELEASE SED. BOTTOM
9.0 x 103
2.0 x 1012
2.3 x 107
HIGH SEDIMENT BOTTOM
1.2 x 102
1.6 x 1011
7.1 x 1010
MIDDLE SEDIMENT BOTTOM
1.2 x 102
1.2 x 108
5.5 x 106
LOW LEAF FRACTIONS
3.0 x 102
3.2 x 109
2.4 x 108
SED = Sediment
86
TABLE 15
COMPARISON OF GENE ABUNDANCE BETWEEN ARCHAEA, BACTERIA
AND DIAZOTROPHS IN 2004 NATALIE’S CREEK (AGRICULTURAL) STREAM
SAMPLES
nifH
Archaea
Bacteria
# gene/g
# gene/g
# gene/g
ABOVE SEDIMENT
<2.0 x 102
6.5 X 1011
4.3 X 1010
MIDDLE SEDIMENT
<2.0 x 102
1.8 X109
5.0 X 107
LOW SEDIMENT
3.1 X 106
1.7 X 1011
6.0 X 1010
87
TABLE 16
COMPARISON OF GENE ABUNDANCE BETWEEN ARCHAEA, BACTERIA
AND DIAZOTROPHS IN 2003 CAMPUS CREEK (URBAN) STREAM
SAMPLES
nifH
Archaea
Bacteria
# gene/g
# gene/g
# gene/g
MIDDLE SEDIMENT BOTTOM
2.5 X 104
9.0 X 1010
2.2 X 1010
LOW MISCELANEOUS
4.5 X 104
9.5 X 108
2.6 X 108
LOW SEDIMENT BOTTOM
2.2 X 105
1.1 X 1012
3.3 X 1010
HIGH SEDIMENT TOP
4.0 X 103
2.1 X 1010
5.0 X 109
88
TABLE 17
COMPARISON OF GENE ABUNDANCE BETWEEN ARCHAEA, BACTERIA
AND DIAZOTROPHS IN 2004 WAL-MART DITCH (URBAN) STREAM
SAMPLES
nifH
Archaea
Bacteria
# gene/g
# gene/g
# gene/g
ABOVE SEDIMENT
<2.0 x 102
3.6 X 1010
1.1 X 1010
MIDDLE SEDIMENT
<2.0 x 102
5.5 X 109
4.0 X 109
LOW SEDIMENT
<2.0 x 102
1.9 X 1010
3.9 X 109
MIDDLE "CUP"
1.6 X 107
2.8 X 1011
4.0 X 1012
89
TABLE 18
REAL-TIME PCR EFFICIENCY TEST IN 2003 NORTH CREEK
(AGRICULTURAL) STREAM BY COMPARISON OF THE AMPLIFICATION
RATES (CT VALUES)
SAMPLES
SOIL+Ps M1
Ps M1
EFFICIENCY %
HIGH SEDIMENT BOTTOM
12.93
12.60
98.97
ABOVE RELEASE SED BOTTOM
13.18
12.90
98.98
LOW LEAF FRACTIONS
13.83
12.60
98.90
ABOVE RELEASE SED TOP
14.74
14.37
98.97
HIGH SEDIMENT TOP
12.82
12.73
98.99
MIDDLE SEDIMENT TOP
12.75
12.73
99.00
MIDDLE SEDIMENT BOTTOM
13.13
12.73
98.97
SED= Sediment
SOIL+Ps M1= samples of soil extraction with genomic DNA of Pseudomonas
fluorescens, R8 Tn5 pho mutant M1
Ps M1= genomic DNA of Pseudomonas fluorescens, R8 Tn5 pho mutant M1
90
TABLE 19
REAL-TIME PCR EFFICIENCY TEST IN 2004 NATALIE’S CREEK
(AGRICULTURAL) STREAM BY COMPARISON OF THE AMPLIFICATION
RATES (CT VALUES)
SAMPLES
SOIL+Psm1
PsM1
EFFICIENCY %
ABOVE SED 2004
13.14
12.73
98.97
MIDDLE SED 2004
12.61
12.60
99.00
LOW SED 2004
12.81
12.90
99.01
MIDDLE GREEN 2004
13.09
12.73
98.97
LOW GREEN 2004
12.58
12.73
99.01
SED= Sediment
SOIL+Ps M1= samples of soil extraction with genomic DNA of Pseudomonas
fluorescens, R8 Tn5 pho mutant M1
Ps M1= genomic DNA of Pseudomonas fluorescens, R8 Tn5 pho mutant M1
91
TABLE 20
REAL-TIME PCR EFFICIENCY TEST IN 2003 CAMPUS CREEK (URBAN)
STREAM BY COMPARISON OF THE AMPLIFICATION RATES (CT VALUES)
SAMPLES
SOIL+Psm1
PsM1
EFFICIENCY %
MIDDLE SEDIMENT BOTTOM
12.74
12.90
99.01
MIDDLE SEDIMENT TOP
12.92
12.60
98.97
LOW MISCELANEOUS
12.59
12.56
99.00
LOW SEDIMENT TOP
12.25
12.90
99.05
LOW SEDIMENT BOTTOM
12.75
12.90
99.01
HIGH SEDIMENT TOP
14.67
14.82
99.01
SOIL+Ps M1= samples of soil extraction with genomic DNA of Pseudomonas
fluorescens, R8 Tn5 pho mutant M1
Ps M1= genomic DNA of Pseudomonas fluorescens, R8 Tn5 pho mutant M1
92
TABLE 21
REAL-TIME PCR EFFICIENCY TEST IN 2004 WAL-MART DITCH (URBAN)
STREAM BY COMPARISON OF THE AMPLIFICATION RATES (CT VALUES)
SAMPLES
SOIL+Psm1
PsM1
EFFICIENCY %
ABOVE SEDIMENT
12.10
12.60
99.04
MIDDLE SEDIMENT
12.99
12.73
98.98
LOW SEDIMENT
12.60
12.73
99.01
GREEN ABOVE
13.31
14.37
99.07
MIDDLE "CUP"
13.16
12.73
98.97
LOW GREEN
13.59
14.37
99.05
SOIL+Ps M1= samples of soil extraction with genomic DNA of Pseudomonas
fluorescens, R8 Tn5 pho mutant M1
Ps M1= genomic DNA of Pseudomonas fluorescens, R8 Tn5 pho mutant M1
93
TABLE 22
REAL-TIME PCR EFFICIENCY TEST IN 2003 KINGS CREEK-N4D (PRISTINE)
STREAM BY COMPARISON OF THE AMPLIFICATION RATES (CT VALUES)
SAMPLES
SOIL+PsM1
PsM1
EFFICIENCY %
ABOVE SEDIMENT TOP
13.33
12.60
98.94
ABOVE UPPER LEAF LITTER
14.42
13.70
98.95
HIGH SEDIMENT TOP
13.23
12.73
98.96
HIGH SEDIMENT BOTTOM
14.30
13.70
98.96
MIDDLE SEDIMENT TOP
14.20
14.37
99.01
MIDDLE SEDIMENT BOTTOM
14.24
13.70
98.96
LOW LEAF LITTER
13.88
13.70
98.99
LOW SEDIMENT TOP
14.56
14.37
98.99
LOW SEDIMENT BOTTOM
14.69
14.37
98.98
SOIL+Ps M1= samples of soil extraction with genomic DNA of Pseudomonas
fluorescens, R8 Tn5 pho mutant M1
Ps M1= genomic DNA of Pseudomonas fluorescens, R8 Tn5 pho mutant M1
94
TABLE 23
REAL-TIME PCR EFFICIENCY TEST IN 2004 KINGS CREEK-K2A (PRISTINE)
STREAM BY COMPARISON OF THE AMPLIFICATION RATES (CT VALUES)
SAMPLES
SOIL+PsM1
PsM1
EFFICIENCY %
ABOVE GREEN
12.59
12.56
99.00
MIDDLE SEDIMENT
14.21
14.37
99.01
LOW SEDIMENT
12.63
12.73
99.01
LEAVES POOL
12.41
12.87
99.04
SOIL+Ps M1= samples of soil extraction with genomic DNA of Pseudomonas
fluorescens, R8 Tn5 pho mutant M1
Ps M1= genomic DNA of Pseudomonas fluorescens, R8 Tn5 pho mutant M1
95
APPENDIX B: GRAPHS
FIGURE 4
SAMPLING SITES FOR ALL THREE TYPES OF STREAMS EACH YEAR: 2003
AND 2004
ABOVE
RELEASE
15
NO3
RELEASE
HIGH
MIDDLE
LOW
96
FIGURE 5
2003 Campus Creek Stream ARA
Low Top
fmol N2 reduced/g /h
3.0
Low Bottom
2.5
Mid Top
2.0
Mid Bottom
1.5
High Top
High Bottom
1.0
Above Top
0.5
Above Bottom
Low Misc.
0.0
Sample site
Leaf Fraction
Mean values of acetylene reduction assays obtained for Campus Creek
(39o11.577N, 96o 34.722’ W) in year 2003. Values represent means of six
repetitions of samples analyzed at 7, 14, 21 and 28 days after collection. “Low”
samples are farthest from the
15
N release, “Mid” samples are closest, and
“Above” samples are above the release. The leaf litter value is pooled from
samples collected along the entire reach.
97
FIGURE 6
2004 Wal- Mart Ditch Stream ARA
fmol N2 reduced/g /h
100.0
Above Sediment
80.0
Middle
60.0
Low
Above green
40.0
Middle "cup"
20.0
Low green
0.0
Sample site
Mean values of acetylene reduction assays obtained for the WAL-MART Ditch
stream during 2004 (39o11.135’ N, 96o 33.500’ W). Values represent means of
six repetitions of samples analyzed at 7, 14, 21 and 28 days after collection. The
“Low” samples are farthest from the
15
N release, “Mid” samples are closest, and
“Above” samples are above the release. The “Green” samples correspond to
algae present on the site. The “Middle cup” sample corresponds to a concrete
gap in the stream.
98
FIGURE 7
fmol N2 reduced/g /h
2003 North Creek Stream ARA
16.0
Low Top
14.0
Low Bottom
12.0
Mid Top
10.0
Mid Bottom
8.0
High Top
6.0
High Bottom
4.0
Above Top
2.0
Above Bottom
0.0
Leaf Fractions
Sample site
Mean values of acetylene reduction assays obtained for the North Creek year
2003 (39o 12.741’N, 96o 35.584’ W). Values represent means of six repetitions of
samples analyzed at 7, 14, 21 and 28 days after collection. “Low” samples are
farthest from the
15
N release, “Mid” samples are closest, and “Above” samples
are above the release. The leaf fraction value is pooled from samples collected
along the entire reach.
99
FIGURE 8
2004 Natalie’s Creek Stream ARA
fmol N2 reduced/g /h
120.0
100.0
Above Sediment
80.0
Middle Sediment
60.0
Low Sediment
Low Green
40.0
MiddleGreen
20.0
0.0
Sample site
Mean values of acetylene reduction assays obtained for the Natalie’s Creek year
2004 (39o13.723’ N, 96o 39.530’ W). Values represent means of six repetitions
of samples analyzed at 7, 14, 21 and 28 days after collection. “Low” samples are
farthest from the
15
N release, “Mid” samples are closest, and “Above” samples
are above the release. The “Green” samples correspond to algae present on the
sample site.
100
FIGURE 9
2003 Kings Creek-N4D ARA
Low leaves
Low slime
fmol N2 reduced/g /h
100.0
Low deep
High leaves
80.0
High slime
60.0
High deep
Upper leaves
40.0
Upper slime
Upper deep
20.0
Under rock
0.0
Sample site
Side gravel
Riffle
Mean values of acetylene reduction assays obtained the Kings Creek-N4D year
2003 (39o 05.271’N, 96o 35.067’ W). Values represent means of six repetitions of
samples analyzed at 7, 14, 21 and 28 days after collection. “Low” samples are
farthest from the
15
N release, “Mid” samples are closest, and “Above” samples
are above the release. The leaf litter value is pooled from samples collected
along the entire reach.
101
FIGURE 10
2004 Kings Creek-K2A ARA
fmol N2 reduced/g /h
80.0
70.0
60.0
Above Green
50.0
Middle Sediment
40.0
Leaves
30.0
Low
20.0
10.0
0.0
Sample site
Mean values of acetylene reduction assays obtained the Kings Creek-K2A year
2004 (39o06.008’ N, 96o 34.454’ W). Values represent means of six repetitions of
samples analyzed at 7, 14, 21 and 28 days after collection. “Low” samples are
farthest from the
15
N release, “Mid” samples are closest, and “Above” samples
are above the release. The “Green” samples correspond to algae present on the
sample site.
102
FIGURE 11
NifH real-time PCR amplification plots of relative fluorescence units (RFU) for
SYBR Green vs. cycle number. The threshold was automatically set at 30 RFU.
103
FIGURE 12
Real-time PCR nifH melting curve plotting the negative derivate of relative
fluorescence units with respect to temperature as –d(RFU)/dT versus
temperature.
104
FIGURE 13
STANDARD CURVE OF nifH GENES
40
Y = -3.73428 Log X + 47.12556
r²= 0.989
Treshold Cycle (Ct)
35
30
25
20
15
10
1e+3
1e+4
1e+5
1e+6
1e+7
1e+8
1e+9
nifH gene copies
Ct vs Gene copies
Linear regresion
Standard curve obtained by plotting log nifH gene copy number versus the
threshold cycle. Data were generated from figure 10.
105
1e+10
FIGURE 14
STANDARD CURVE OF ARCHAEAL 16S rRNA
38
Y = -3.269 Log X + 61.81580
r2 = 0.98
36
Treshold Cycle (Ct)
34
32
30
28
26
24
22
1e+7
1e+8
1e+9
1e+10
1e+11
1e+12
Archaeal 16S rRNA gene copies
Ct vs Gene copies
Linear regresion
Standard curve obtained by plotting log archaeal 16S rRNA gene copy number
versus the threshold cycle.
106
FIGURE 15
STANDARD CURVE OF BACTERIAL 16S rRNA
35
Y = -3.23107 Log X + 52.39463
2
r = 0.99
Treshold Cycle (Ct)
30
25
20
15
10
1e+6
1e+7
1e+8
1e+9
1e+10
1e+11
1e+12
1e+13
Bacterial 16S rRNA gene copies
Ct vs Gene copies
Linear regresion
Standard curve obtained by plotting log bacterial 16S rRNA gene copy number
versus the threshold cycle.
107