1254
DOI 10.1002/pmic.200800244
Proteomics 2009, 9, 1254–1273
RESEARCH ARTICLE
Exploring membrane and cytoplasm proteomic
responses of Alkalimonas amylolytica N10 to different
external pHs with combination strategy of de novo
peptide sequencing
Quanhui Wang1, Huiming Han1, Yanfen Xue1, Zhong Qian2, 3, Bo Meng2, 3, Fuli Peng2, 3,
Zhuowei Wang2, 3, Wei Tong2, 3, Chuanqi Zhou2, 3, Qian Wang2, 3, Yonghao Guo1, Gang Li1,
Siqi Liu2, 3* and Yanhe Ma1
1
State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences,
Beijing, P. R. China
2
Center of Proteomic Analysis, Beijing Genomics Institute, Chinese Academy of Sciences, Beijing, P. R. China
3
Beijing Proteomics Institute, Shunyi, Beijing, P. R. China
Identification of differentially proteomic responses to external pHs would pave an access for
understanding of survival mechanisms of bacteria living at extreme pH environment. We cultured
Alkalimonas amylolytica N10 (N10), a novel alkaliphilic bacterium found in Lake Chahannor, in
media with three different pHs and extracted the correspondent membrane and cytoplasm proteins for proteomic analysis through 2-DE. The differential 2-DE spots corresponding to the
altered pHs were delivered to MALDI TOF/TOF MS for protein identification. Since the genomic
data of strain N10 was unavailable, we encountered a problem at low rate of protein identification
with 18.1%. We employed, therefore, a combined strategy of de novo sequencing to analyze MS/MS
signals generated from MALDI TOF/TOF MS. A significantly improved rate of protein identification was thus achieved at over than 70.0%. Furthermore, we extensively investigated the expression of these pH-dependent N10 genes using Western blot and real-time PCR. The conclusions
drawn from immunoblot and mRNA measurements were mostly in agreement with the proteomic observations. We conducted the bioinformatic analysis to all the pH-dependent N10 proteins
and found that some membrane proteins participated in iron transport were differentially
expressed as external pH elevated and most of differential proteins with increased or bell-shape
mode of pH-dependence were involved in bioenergetic process and metabolism of carbohydrates,
fatty acid, amino acids, and nucleotides. Our data thus provide a functional profile of the pHresponsive proteins in alkaliphiles, leading to elucidation of alkaliphilic-adaptive mechanism.
Received: March 14, 2008
Revised: September 12, 2008
Accepted: September 26, 2008
Keywords:
Alkalimonas amylolytica N10 / Alkaliphile / De novo sequencing / Membrane and
cytoplasmic protein / 2-DE
Correspondence: Dr. Yanhe Ma, State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of
Sciences, Beijing 100101, P. R. China
E-mail: [email protected]
Fax: 186-10-64807616
Abbreviations: N10, Alkalimonas amylolytica N10; SPITC, 4-sulfophenyl isothiocyanate
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
1
Introduction
On the basis of current knowledge, the ability of alkaliphiles
to survive and grow in alkaline environment is mostly de-
* Additional corresponding author: Dr. Siqi Liu,
E-mail: [email protected]
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Proteomics 2009, 9, 1254–1273
pendent upon the regulations of pH homeostasis driven by
the proteins of cytoplasm membranes. The best-understood
response to high pH is Na1/H1 antiporters (Nha) on
membrane which catalyzes electrogenic exchange of cytoplasmic Na1 for extracytoplasmic H1 [1–9]. Besides contribution of those antiporter proteins to pH homeostasis,
three mechanisms are postulated: (i) the proteins and polymers on cell surfaces may contribute to pH homeostasis, for
instance, the mutated teichuronopeptide leading to unstable
pH in cytoplasm [10–14]; (ii) the increased metabolic acids
generated by deamination of amino acids can perform the
buffer effects [15, 16]; and (iii) the respiration and ATP
synthase coupling with H1 play an essential role in homeostasis of pH [17–21]. These hypotheses are still in argument due to diversity of alkaliphiles as well as of survival
conditions. It is generally accepted that the expression of
bacterial proteins widely responds to the alternations of environmental pH and forms an adaptive network to maintain
stable pH in cytoplasm. The alkaliphilic bacterium, Alkalimonas amylolytica N10 (N10), is a gram-negative proteobacterium that was isolated from Lake Chahannor in China
[22]. This bacterium has a respiration-based metabolism
and grows at NaCl concentrations up to 7% in a range of
pH from 7.5 to 11. Recent study has revealed strain N10 to
be an ideal model for understanding of survival mechanisms of alkaliphiles, even detailed investigation was just at
initial phase [4, 5].
During recent years, proteomic approaches have been
employed to investigate the pH-dependent proteins in bacteria. A number of reports were focused on proteomic analysis in neutraphilic bacteria, such as Escherichia coli (E. coli)
that grows over a wide range of external pH from 4.4 to 9.2
[15, 16, 23]. Under aerobic conditions, the abundance of several amino acid metabolic enzymes as well as several periplasmic proteins such as OmpA, MalE, YceI, and OmpX in E.
coli were significantly elevated responding to increased
external pHs. Stancik et al. [16] hypothesized that these
changes might direct overall amino acid catabolism into the
pathways of ammonia removal and acids production. While
under anaerobic conditions, Yohannes et al. [23] reported that
the levels of metabolic enzymes and another five periplasmic
proteins, such as ProX, OppA, DegQ, MalB, and MglB were
high-pH induced in E. coli. It is generally accepted that
modulations for multiple metabolic pathways of amino acid
in E. coli can minimize the influence of external pH to cytoplasm pH. As compared to neutraphilic bacteria, alkaliphiles
survive in much higher pH environment. Do the two kinds
of bacteria follow similar molecular mechanism of adaptation to different external pHs? With limited genomic information of alkaliphiles, the protein expression of alkaliphilic
bacteria under different pH conditions has not been extensively studied yet. Analysis of 2-DE to pH-dependent proteins
in Bacillus pseudofirmus OF4, an extremely alkaliphilic bacterium, was one of a few reports, but limited proteins were
identified in this study [13]. The proteome profile of another
alkaliphile, Oceanobacillus iheyensis HTE831, was processed,
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
1255
but no information of pH-dependent proteins was obtained
[24]. More proteomic surveys, therefore, are highly expected
to explore the proteins involved in pH homeostasis in alkaliphilic bacteria.
Proteomic identification by MS is mainly dependent on
genomic data. One potential obstacle to comprehensive
assessments of proteins is still the relative paucity of
available genomic data for live species. With the development of accurate MS, the characterization of interested
proteins could be annotated using a de novo sequencing
strategy, in which partial or complete peptide sequences
are directly derived from tandem MS/MS signals. There
are two strategies to deduce amino acid sequences from
MS/MS signals, de novo sequencing of underivative and
derivative peptides. For instance, Yergey et al. [25] have
employed MALDI TOF/TOF MS to measure the underivative peptides generated from bacteria and successfully
annotated the mass signals with de novo sequencing analysis. To annotate the underivative signals, PEAKS has been
proved being a powerful de novo software to treat the mass
data generated from different types of MS, such as QTOF,
TOF–TOF, IT, Orbi-Trap, and FTMS instruments [26]. On
the other hand, interpretation of native tryptic peptides is
sometime difficult because of the complication of MS/MS
spectra, which includes many different types of product
ions. Use of certain chemical derivation agent prior to
mass spectrometric analysis can diminish this problem. Nterminal sulfonation of peptides with 4-sulfophenyl isothiocyanate (SPITC) introduces a negative charge as dominant y-type ion, which improves fragmentation and interpretation of MS/MS spectra [27–29]. This approach, however, is still in some limits due to lack of recognizable
fragmentation pattern to apply to the amino acid residues
in SPITC peptides and a severe dip in the intensity of
peaks after the derivatized amino acid. Hence, a combined
strategy of general algorithm and chemical modification
appears to be more accurate and efficient for de novo sequencing of tandem mass signals.
In this communication, we adopted a de novo sequencing
strategy, dealing with the tandem mass signals of peptides
treated with/without SPITC derivatization, to analyze the
differential proteomes of strain N10 responding to distinct
external pHs. We cultured the strain N10 cells in three pH
media, 8.4, 9.4, and 10.4, respectively, and then identified
differential proteomes using electrophoretic system and MS.
Our results revealed that 26 pH-dependent 2-DE spots were
identified in the membrane fractions, and 46 pH-dependent
2-DE spots were detected in the cytoplasmic fractions. With
traditional search of MASCOT, only 18.1% spots were identified, whereas by using de novo approach, the identification
rate increased to 73.6%, which reached the same level of
efficiency and reliability as conventional database-search
strategy. This investigation, therefore, paces a primary step
towards quantitatively and functionally exploring the pH-dependent molecules in alkaliphiles, even though its genomic
data are unavailable.
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2
Q. Wang et al.
Materials and methods
2.1 Culture conditions for the strain N10
The strain N10 was cultured in Horikoshi I medium at 377C.
To maintain the pH stability during culturing, a tri-buffer
system, containing 50 mM TRICINE, 50 mM CHES, and
50 mM CAPS, was used for preparation of medium. The
changes of the medium pH were controlled within 0.2 U and
other conditions were remained stable during cell culture. To
monitor growth curves of bacteria, aliquots were withdrawn
from the culture media at intervals followed by OD measurement at 600 nm. The growth rate constant at log phase of
growth was determined by plotting OD values at log scale
against time. The cells were harvested at midterm of log
phase by centrifuge with 60006g at 47C for 10 min. The cell
pellets were stored at 2807C until use.
2.2 Preparation of membrane and cytoplasmic
proteins
After washed with 2% NaCl and 1.0 M Tris-HCl, pH 8.0, the
cell pellets were suspended in 50 mM Tris-HCl, pH 8.0,
containing protease inhibitor PMSF (1 mmol/mL) and RNase
(1 mg/mL). The bacterial cells were disrupted by supersonication (750 W) at 30% intensity. The cell debris was
removed by centrifugation at 60006g and 47C. The membrane fractions were obtained from ultracentrifugation with
170 0006g (SW32.1Ti, Beckman) at 47C for 2 h. The supernatants generated from ultracentrifugation were used as the
cytoplasmic fractions.
The membrane fractions were washed three times with
50 mM Tris-HCl, pH 8.0, and cold acetone, followed by
resuspension in the buffer containing 7 M urea, 2 M thiourea, and 50 mM Tris-HCl, pH 8.0, with varied detergents, 2%
Triton X-100, 4% CHAPS, 2% ASB-14, 2% SB3-10, or 2%
SDS, respectively. After incubated at room temperature for
30 min, the suspensions were centrifuged at 40 0006g and
47C for 20 min. The supernatants were directly taken for
measurement of protein concentrations and 1-D SDS-PAGE
to detect the extraction efficiency. The membrane fractions
would be solubilized in the lysis buffer for 2-DE.
The proteins in the cytoplasmic fractions obtained from
ultracentrifugation were precipitated by adding 10% TCAacetone stored at 2207C followed by centrifugation at
40 0006g and 47C for 30 min. After washed with cold acetone for three times and dehydrated by vacuum, the protein
pellets were solubilized in lysis buffer containing 8 M urea,
4% CHAPS, 10 mM DTT, 2 mM EDTA, 1 mM PMSF, and
0.5% pharmalyte 4–7 followed by 2-DE.
2.3 2-DE
Approximate 100 mg proteins for silver staining or 1000 mg
proteins for CBB staining were loaded on IPG strips (18 cm,
pH 4–7), respectively, and rehydrated in the buffer contain© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Proteomics 2009, 9, 1254–1273
ing 8 M urea, 4% CHAPS, 65 mM DTT, and 0.5% pharmalyte 4–7 for 8 h. IEF of the IPG strips was carried out with a
program of gradient voltage at 500, 1000, and 8000 V, each
for 1 h and finally remained at 8000 V until the value of V6h
reached to 80 000. Prior to the second dimension, the IPG
strips were equilibrated by two equilibration steps: (i) 50 mM
Tris-HCl, pH 8.8, 6 M urea, 30% v/v glycerol, 2% w/v SDS, a
trace of bromophenol blue, and 1% w/v DTT on a rocking
table for 15 min, followed by (ii) 50 mM Tris-HCl, pH 8.8,
6 M urea, 30% v/v glycerol, 2% w/v SDS, a trace of bromophenol blue, and 2.5% w/v iodoacetamide for 15 min. The
treated strips were placed to 12% acrylamide gel
(230623061.0 mm3), and run at 2.5 W/gel for 30 min and
then at 15 W/gel for 5 h in ETTAN system II (Amersham
Pharmacia Biotech). The staining approaches of silver (silver
nitrate, Sigma) and CBB (Brilliant R-250, Sigma) were
employed to detect the proteins on 2-DE gels. At a certain
pH, the proteins were extracted from three independent cultures and employed to 2-DE, respectively, and each extraction
was replicated for two times.
2.4 Analysis of the electrophoretic images
The silver nitrate stained gels were scanned by Powerlook
2000 (UMAX) and the images of 2-DE were processed using
the 2-D Imagemaster software (Amersham Pharmacia Biotech). The 2-DE spots were automatically drawn by the program with assistant of manual check. Several key parameters
were set as constant to acquire high quality of image data,
such as smooth at 2.0, min area at 57.0 and saliency at 550.0.
The 2-DE images obtained from the bacteria cultured at
pH 9.4 were set as the reference. To avoid individual errors
either from samples or from operations, the relative spot
volumes were normalized at each gel, and the differential
spots were evaluated upon the comparison of the relative
spot volumes among these 2-DE images. The average volume for each spot was the mean value of six replicates. The
criteria were established to judge a differential spot, (i) significant difference of spot volume over two-fold between any
two gels at distinct pHs, and (ii) shared by all the parallel
gels.
2.5 In-gel tryptic digestion and SPITC treatment
The pH-dependently differential 2-DE spots were manually
excised, and the gel particles were reduced with 10 mM
DTT and alkylated with 55 mM IAM. In-gel digestions were
processed with 0.01 mg trypsin (Sigma, USA) at 377C overnight.
In protein identification using treatment of SPITC derivative, the protein abundance of each spot was a critical
factor. Thus 2-DE gels were loaded with more proteins and
stained with CBB. The spot digestives were mixed with
SPITC (10 mg/mL, pH 9.0) in 1:2 v/v, and incubated at
567C for 30 min [25]. The reactions were stopped by 0.1%
TFA.
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Proteomics 2009, 9, 1254–1273
2.6 Protein identification by MALDI TOF/TOF MS
2.8 Real-time PCR
The tryptic digestives generated from the differential 2-DE
spots were first spotted onto Anchorchip (Bruker, Germany)
and mixed with 1.0 mL of 1.6 mM CHCA [30]. After washed
with 0.1% TFA, the crystallized samples were subjected to
UltraFlex MALDI TOF/TOF MS (Bruker). The spectra were
acquired in reflection mode with mass range of 700–4000
and the machine parameters set as, ion source 25 kV for
PMF and 8.0 kV for tandem MS/MS, lens 9.5 kV for PMF
and 3.5 kV for tandem MS/MS, reflector 26.3 kV for PMF
and 29.5 kV for tandem MS/MS, lift 19.0 kV. The peaks with
ratio of S/N over 5 were automatically labeled by FlexAnalysis (Bruker). The PMF peaks with mass intensity
more than 5000 were selected for further MS/MS. The data
of MS were further analyzed through MASCOT 2.2.04 and
Biotools 2.1 (Bruker), and PMF data were combined with
corresponding tandem MS/MS data for database search
against Eubacterial proteins in NCBInr 20060521. The following parameters were used for database searches: monoisotopic mass accuracy ,100 ppm, MS/MS tolerance
0.4 Da, parent charge 11, missed cleavages 1, carbamidomethylation of cysteine as fixed modification, oxidation of
methionine, N-terminal pyroglutamylation (peptide), and
N-terminal acetylation (protein) as variable modifications.
The results with protein score more than 75 (p,0.05) base
on PMF and MS/MS signals were considered to be identified.
The total RNA in the N10 bacteria cultured at a certain pH was
extracted by Trizol reagent according to the operation protocol, and the extraction was repeated from three independent
cultures. Genomics contamination in total RNA was carefully
removed by DNase (Takara) treatment for 30 min at 377C. The
library of cDNAs was reversely transcribed from mRNA using
random primers. Quantification of PCR reactions was conducted in an ABI PRISM 7300 system with programmed parameters: heating at 957C for 3 min followed by 40 cycles of
four-stage temperature profile of 957C for 15 s, 607C for 20 s,
727C for 15 s, and 807C for 30 s. Each sample was replicated
for four times. The melting curves for each PCR reaction were
carefully analyzed to avoid non-specific amplifications in PCR
products. The relative expression of genes were calculated
with 22DDCt formula normalized with 16 s rRNA level.
2.7 De novo sequencing analysis based upon tandem
mass signals
The tryptic digestions were divided into two groups, one
directly delivered to MS, and the other one treated with
SPITC followed by analysis of MS. The samples treated
by SPITC were desalted using PosR2 tips and eluted with
70% ACN mixed with 15 mg/mL CHCA and 0.1% TFA
followed by spotting onto Anchorchip and MS. The tandem spectra with/without SPITC treatment were analyzed
by PEAKS for auto de novo and SPIDER homology
search. In addition, we manually analyzed the mass
spectra from the samples treated with SPITC for de novo
sequencing and confirmed the proteins by MS BLAST.
Several stringent criteria for de novo sequencing were
established: (i) a deduced sequence should be longer than
seven amino acids; (ii) a protein should be identified
upon at least two unique peptides; (iii) for MS BLAST,
the threshold scores should be higher than 68, 102, 143,
and 177 corresponding to high scoring pair values (HSP),
1, 2, 3, and 4, respectively, and for SPIDER homology
search threshold scores should be more than 90%; (iv) all
the deduced peptides should be gained from multiple
preparation of samples, at least two. The final list of
identifications was a sum of the results obtained from the
two approaches.
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
2.9 Western blot analysis
Based upon proteomic results, we selected four proteins to
generate the correspondent antibodies, ATP synthase subunit
beta (AtpD), catalase-peroxidase (HPI), Fe31 dicitrate receptor
(FecA), and Protease DO (DegQ). The partial gene sequences
were amplified by PCR using the strain N10 genomic DNA as
template, and the primers were designed according to de novo
peptides or conserved domains as listed in Table 1. These
truncated genes with size be 516 bp (AtpD), 606 bp (HPI),
339 bp (FecA), and 471 bp (DegQ) were inserted into
pET28a(1) vector and expressed in E. coli BL-21 strain.
Recombinant proteins were purified through Ni21 affinity
chromatography. New Zealand rabbits were immunized by
approximate 500 mg purified recombinant proteins. These
antibodies were partially purified by protein-A affinity column, and the purified antibodies were directly used as primary antibodies in Western blot. The same amount of strain
N10 proteins from three independent cultures at different pH
media were loaded onto SDS-PAGE (12% polyacrylamide)
with two replicates for each sample, subsequently transferred
onto PVDF membranes. The PVDF membranes were blocked
in TTBS buffer containing 5% fat free milk at 377C for 60 min
and incubated with primary antibodies at room temperature
for 2 h. The secondary antibody was goat antirabbit conjugated with horseradish peroxidase (HRP, Santa Cruz, CA).
Immuno-recognized bands were visualized by enhanced
chemiluminescent (ECL) using the reagents made in Amersham Biosciences (Uppsala, Sweden).
3
Results
3.1 The pH-dependent growth curves of strain N10
The growth curves of strain N10 in the different pH media
were generated by sigmoidal plot based upon OD600 values
and culturing time. The average growth rates at the distinct
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Q. Wang et al.
Proteomics 2009, 9, 1254–1273
Table 1. Primers sequences designed for real-time PCR
Primers
Gene
Sequence (50 –30 )
Peptides for
primer design
pP1
pP2
§P3
§P4
pP5
pP6
§P7
§P8
pP9
pP10
§P11
§P12
pP13
pP14
§P15
§P16
pP17
pP18
§P19
§P20
pP21
pP22
§P23
§P24
§P25
§P26
77359363
77359363
77359363
77359363
HPI
HPI
HPI
HPI
SdhA
SdhA
SdhA
SdhA
DegQ
DegQ
DegQ
DegQ
FecA
FecA
FecA
FecA
AtpD
AtpD
AtpD
AtpD
16S
16S
GARACNGARCAYGAYAC
TTRTCRTCNCCRTAYTC
GGGTGAAACGGAAAGTGGTTTGCT
TGGCGAAACTTGGCATTCTCACTG
GARTAYTTYGCNGARAC
RTCNARCATCATYTCYTC
AAGAGCCGTTATTTAGGGCCGGAT
TTGGCTTTCAGCTCGCTGATTTCG
GCNCAYATHAAYACNGG
CCNCCCATCATRTARTG
AAATGTGGCAGTTTCACCCAACCG
TTCAGCAGGTAACCACCTTCACCA
GTNACNAAYGCNCAYGT
TCNCCRAAYTCDATCAT
TGATCGCCTCAGAGTCGGTGATTT
ACTGACAATGCCAGAGGTAACCGT
GCNCCNGAYGAYTGGTA
TCRTCNGTRTANACCCA
CAGCTCAATGCGGCTTTGCACATA
ACCGAGTTTGGTTTGCGTGTGATG
TAYGGNCARATGAAYGA
TCRTCCATNCCNARDAT
TTTACGTGCCTGCGGATGACTTGA
AGGTCTTGTACTTTGGGTAGCGCA
AAGAAGCGATGTTCCGGCTCAGTA
TCGCGTTGCGTCGAATTAAACCAC
ETEHDT
EYGDDN
EYFAET
EEMMLD
AHINTG
HYMMGG
VTNAHV
MLEFGE
APDDWY
WVYTDD
VYGQMN
ILGMDE
Published gene
Published gene
p, Primers for gene clone; §, primers for real-time PCR.
external pHs were calculated from the three parallel growth
curves. The pH-dependent growth curve was further made
by plotting the average rates against pHs, as shown in Fig. 1.
All the data, the growth curves and the pH-dependent profile, revealed that the strain N10 growth exhibited a pH-dependent bell-mode with the optimal pH at about 9.4 in the
tribuffered Horikoshi I media. Compared of the optimal
growth rate at pH 9.4, there was about 50% decline of the
growth rates at external pH values of 8.0 or 10.5. In this
study, we selected three representative pH media, 8.4, 9.4,
and 10.4, to culture strain N10 for analysis of the pH-dependent proteomes.
3.2 The 2-DE images of the membrane proteins in
strain N10 grown in different pH media
The proteomic techniques, particularly in separation of
hydrophobic proteins, are still at a prototype stage. We tested
the solubility of the strain N10 membrane fractions in the
lysis buffers with five different detergents as described
above, and evaluated the extraction efficiency of membrane
proteins through 1-D SDS-PAGE. To compare the extraction
efficiency, SDS was used as a control. As shown in Supporting Information Fig. S1, although Triton X-100, CHAPS, and
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Figure 1. The pH-dependent growth curve of strain N10. The
culture conditions for strain N10 are described in Section 2. The
curve was generated upon the growth rates of strain N10 at the
different pH media. Error bars represent SEM (n = 3).
SB3-10 exhibited solubilization capacity to the strain N10
membrane proteins, ASB-14 appeared as a better detergent
to powerfully solubilize these proteins. Hence, this detergent
was taken as an extraction detergent through the whole
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Proteomics 2009, 9, 1254–1273
study. We employed 2-DE to separate the proteins extracted
from strain N10 membrane fractions, and found that
approximate 400 spots averagely appeared on each 2-DE gel
stained by silver nitrate (Fig. 2). On the basis of image analysis, we recognized that 20 differential 2-DE spots presented
at pH range from 8.4 to 9.4, including 15 up-regulated and 5
down-regulated, and 20 differential spots at pH range from
9.4 to 10.4, including 8 up-regulated and 12 down-regulated.
Thus overall, we totally defined 26 differential 2-DE spots
responding to the elevated medium pH from 8.4 to 10.4,
including 8 increased, 6 decreased, and 12 spots with the
irregular patterns of spot volume changes. All the detailed
information of 2-DE images is listed in Supporting Information Tables S1 and S2.
All the digestives from these differential spots were
delivered to MALDI TOF/TOF MS for protein identification,
however, we were disappointed at the low rates of protein
identification, only 7 of 26 spots being verified as the bacterial proteins, even though a number of spots could release
the mass signals in high quality (Table 2).
3.3 The 2-DE images of the cytoplasmic proteins in
strain N10 grown at different pH media
Averagely, we were able to detect approximate 600 2-DE
spots/gel stained with silver nitrate from each preparation of
strain N10 cytoplasmic fraction (Fig. 3). Based upon the
similar strategy of image analysis described above, we found
that 37 differential 2-DE spots presented at pH range from
8.4 to 9.4, including 23 up-regulated and 14 down-regulated,
and 38 differential spots at pH range from 9.4 to 10.4,
including 8 up-regulated and 30 down-regulated. Thus overall, we totally defined 46 differential 2-DE spots responding
to the elevated medium pH from 8.4 to 10.4, including 10
increased, 12 decreased and 24 2-DE spots with irregular
patterns of spot volume changes. All the detailed information is listed in Supporting Information Tables S1 and S2.
We encountered the same obstacle in protein identification for these differential 2-DE spots, only 6 out of 46 spots
were identified as the bacterial proteins (Table 2).
3.4 Interpretation of MALDI TOF/TOF MS data with
combined strategy of de novo sequencing
As described above, it is clear that protein identification with
conventional database-search strategy could not achieve
satisfactory rates for identifying the strain N10 proteins. Of
72 differential 2-DE spots, including membrane and cytoplasm fraction, only 13 spots were directly identified by MS.
To overcome the obstacle in annotation of mass data, we
developed the combined de novo sequencing strategy to analyze the MALDI TOF/TOF MS signals. The 59 spots failed in
the first round of identification, 19 in membrane fraction
and 40 in cytoplasm fraction, were thus further considered
for protein identification through de novo sequencing. To
have relatively high quantity of these differential proteins, we
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
1259
re-ran 2-DE with heavy sample loading and stained the gels
with CBB. The CBB-stained spots were selected for de novo
sequencing base on two criteria, (i) the spots should display a
consistent pH-dependent mode in both silver and CBB
staining; and (ii) the spots at primary determination of
MALDI TOF/TOF MS should emit the acceptable signals
which were permeable for tandem MS. Thus, 49 out of 59
spots, 17 in membrane fraction and 32 in cytoplasmic fraction, were qualified for further de novo analysis.
In the peptide samples with SPITC treatment, high certainty of peptide sequences were obtained from 36 of 49
spots based upon PEAKS auto de novo and manual analysis.
As shown in Fig. 4, the two sequences were deduced from
the tandem MS/MS spectra, as KGYLVTNAHVLR and
DASDLLLNLKDGR and confirmed to be protease DO. As
comparison of the results obtained from SPIDER homology
search and MS BLAST, 33 results were identified as the bacterial proteins and the other 3 were not matched to the relevant proteins even though they were annotated to certain
amino acid sequences upon high quality MS/MS signals.
In the peptide samples without SPITC treatment, high
quality of tandem MS/MS spectra were obtained from 25 of
49 digestives, and further analyzed by PEAKS for auto de
novo. As shown in Fig. 5, the two sequences were deduced
from the tandem MS/MS spectra, as FTSPLVLPDADLR and
LALLFDEVQTGVGR, and confirmed to be N-succinyl diaminopimelate aminotransferase. Based upon the defined
criteria, 22 spots were identified as the bacterial proteins
after SPIDER homology search, with search score over 90%
(Table 3). Scores of percentage elicited from PEAKS software
indicates the homolog degree of unknown peptide sequence
to the corresponding one in database, the higher the closer.
Additionally, these identified proteins have similar theoretical molecular masses as the apparent values on 2-DE gels.
Gathering all the searching data from the two approaches, totally 40 spots were identified and the identification rate was as high as 81.6% (40/49). Carefully looking into
each set of data, we found that 15 spots were identified by
both ways, whereas 7 spots were only found in the samples
treated without SPITC and 18 spots were only confirmed
through the samples with SPITC treatment. It is obviously
that SPITC derivatization treatment seems to present relatively high identification rate (68.8%) as compared with the
untreated samples (45.8%). For instance, no convinced
searching result was achieved for spot 25 without SPITC
treatment, because only one peptide was deduced from MS/
MS spectra. After treated with SPITC, four peptides with
high certainty were deduced from the same spot, thus 3hydroxybutyrate dehydrogenase was confirmed via PEAKSSPIDER with search score as high as 99%. However, some
spots were still missed in identification in the SPITC-treated
samples, while only caught in the untreated samples
through PEAKS-SPIDER analysis. Once spots volume is too
low, the SPITC treatment usually causes peptide loss due to
poor PMF signals released, which are infeasible to get tandem mass spectra. For instance, spot 71 treated with SPITC
www.proteomics-journal.com
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Q. Wang et al.
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Proteomics 2009, 9, 1254–1273
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Proteomics 2009, 9, 1254–1273
Figure 2. The 2-DE images of
strain N10 membrane proteins
from the bacteria cultured in
three pH media, 8.4 (A), 9.4 (B),
and 10.4 (C), respectively. The
pH-dependent 2-DE spots were
labeled with numbers.
Table 2. Proteins identified by MALDI-TOF/TOF MS
Spots
no.
Protein
Sequence
coverage
(%)
Matched
peptides
6
9
10
11
12
19
28
Cell division inhibitor
GroEL
GroEL
GroEL
RNA polymerase, subunit A
24
24
24
24
27
9
11
11
11
6
6.5/29.2
5.1/56.0
5.1/57.1
5.1/57.1
4.8/36.3
41
13
18
7
33
38
42
46
48
ATP synthase beta subunit
Methylmalonate-semialdehyde dehydrogenase
Succinate dehydrogenase
catalytic subunit
Catalase-peroxidase
Catalase-peroxidase
Seryl-tRNA synthetase
Elongation factor Tu
66
GroEL
33
Scores
Species
5.5/33.1
4.80/61.8
4.84/61.8
4.88/61.8
5.0/41.3
106
102
98
98
110
4.9/50.3
5.2/54.5
4.9/35.1
5.4/54.5
184
112
Psychromonas sp. CNPT3
Buchnera aphidicola
Shewanella MR-4
Shewanella sp. ANA-3
Pseudoalteromonas
tunicata
Marinomonas sp. MED121
Marinobacter sp. ELB17
18
5.5/65.2
5.3/66.0
79
Alteromonas macleodii
11
11
13
50
10
10
6
15
5.8/80.9
5.7/80.9
5.5/50.1
5.0/43.4
5.6/34.2
5.5/28.3
5.9/47.1
5.5/49.3
101
101
82
96
21
8
4.8/57.1
4.9/60.4
96
Alkalilimnicola ehrlichei
A. ehrlichei
Vibrio cholerae
Pseudoalteromonas
atlantica
Shewanella sp. ANA-3
could not offer any high quality of tandem MS/MS spectrum;
whereas two peptides were deduced from this same spot
without the SPITC treatment, leading to a convincing search
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
pI/mass (kDa)
Theoretical Experimental
result as acety-CoA acetyltransferase. In addition, the conclusion elicited from one approach would be strengthened by
the evidence obtained from the other one. A combined
www.proteomics-journal.com
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© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Proteomics 2009, 9, 1254–1273
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Proteomics 2009, 9, 1254–1273
Figure 3. The 2-DE images of
strain N10 cytoplasmic proteins
from the bacteria cultured in
three pH media, 8.4 (A), 9.4 (B),
and 10.4 (C), respectively. The
pH-dependent 2-DE spots were
labeled with numbers.
strategy was therefore profitable to avoid missing interpretation caused by a single de novo approach. Putting all the
identified proteins together, either from direct databasesearch or from de novo sequencing, we finally reaped a satisfactory rate of protein identification at 73.6% (all the identification results listed in Table 3, and all the spectra listed in
Supporting Information Fig. S2), which was close to the
efficiency of protein identification using conventional strategy upon searching genomic databases.
3.5 Validation of the pH-dependent proteomes via
Western blot and real-time PCR
We extended the study for further validation of the proteomic
observations with two different approaches, Western blot and
real-time PCR (Figs. 6 and 7). Genes of six proteins DegQ,
FecA, HPI, AtpD, Gi 77359363 (hypothetical outer membrane protein), and SdhA (succinate dehydrogenase catalytic
subunit) from 42 unique identifications were chosen for realtime PCR, including 2 up-regulated, 2 down-regulated, and 2
uncontinuously changed ones responding to rising external
pHs. The five pairs of PCR primers were designed according
to the correspondent peptides of de novo sequences, while
PCR primers of atpD gene was derived from the conserved
motifs of correspondent protein (Table 1). All the PCR reactions generated the mainly amplified products with as close
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
lengths of bp as designed. Furthermore, as depicted in Fig. 7,
the values of cycle threshold indicated that the pH-dependent tendency of five genes at mRNA level presented similar
patterns as observed from proteomic determinations. These
results evidenced that these genes elicited from de novo peptide sequencing were a virtual part of strain N10 genome and
their transcription and translation were affected by the
external pH in the similar patterns.
Four antibodies specific against the strain N10 proteins
were generated from our laboratory, and individually
employed in Western blot experiments. As shown in Fig. 6,
most of the immune-reactive intensities responding to the
external pHs were in similar pattern to the spot volume
changes of the correspondent 2-DE spots. Thus, the evidence
from Western blot offered additional support for the pH-dependent proteomes of the strain N10.
3.6 The functional analysis to the pH-dependent
proteins of strain N10
By using topological analysis, such as PSORTb, SignalP,
SecretomeP, and TMMTOP, and reference search to predict
the cellular locations of the identified proteins in the membrane fractions, we found 40.9% (9/22) of identifications
belonged to membrane proteins containing either helical
domain(s) or signal peptide(s), and 45.5% (10/22) were verwww.proteomics-journal.com
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
1187.807
1829.731
2098.863
1229.122
1333.538
1452.294
1615.577
854.424
974.156
1212.438
1623.486
1502.818
1686.735
836.546
917.666
1179.253
1363.748
1371.358
1470.488
1865.828
1207.303
1801.134
1889.979
4
8
13
14
15
17
22
1131.125
1391.810
LLGVEGDTLGQYVHSGR d
EESAALGAAAVEAAFDDPRd
999.561
1381.864
1444.100
3
d
VVPEPLGGAHR
TFANDVALVGGTAR
MSLQAGAK
VMGTPASVR
KALLDDVHLR
QAAGVSNALYRQPKd
GVQADRREDEREARd
GLVTPVLR
ELLEDPTR
QYQDVFEQRd
EAAKPAAAAAPAAVSGDRd
TLVYWSDVSR
GLLLNDYLAGER
WVYTDDLTGNNR
FSYHENDANLSYR
YSTLAVGYGTR
RFQDLTVEYGDDNTR d
LLDLVDHSLNVELGPGYSR
VGVLDDLLR
MEMQVLSQFLR
VLGAAANPQAVNYR
SNVQLSEQY
LGGNELTVDYVHLGR
MLNALEEFVQNDLPLR
GAAPMAMSLDGSNAWHWDR
MPPDETDSLTVYNDMLEVNVTDQQRd
VIPEPLGGAHR*r
SFANDEAIVGGIAR*r
VINVEGDTLGAYVHGGR*r
EDFAAEVAAQMEAA*
VVADFLSSVGVDR*
ITAVMPYFGYAR*r
QLDEADLAIIDKR*r
QKFDNPVVVSPDIGGVVR*r
NSADVINFVR*
MAIQAGAQ*
VGMVPGSVR*r
KALLDDVHFR*
TLVYWSDVSR*
GLLLAEYEAGE–*
WVYTDSLTGNNR*
LSRYENDANISYR*r
GLVTPVL–*
ELLEDPTR*
QYQEVFEKR*
–AKAAPAAAPAAAMGDR*r
KVGIDSNALYRQPK*r
–DDAREA-*
SNVTTSEQFR*
–GTEITVDFFNLGR*
MIDSLEQFIELDIPI–*r
–ALSLDQKNAWVWD–*
QVVDETENLKVYNDYLATLVADQQR*r
VFELNIDDLIR*
EIEDVLSTFVNSPR*
VIGEAAQPRAVNYT*r
–STLAIGYGAR*
RFTQLVTVEYGDTNTK*r
LLNEKTMWLNAEIGPGYK*
ELDNGKINLYTR*r
VQYGPNSTSEAFDFGDGR*r
–EYAG–*
Homology matched peptide sequence
Dihydrolipoyltranssuccinate transferase
244*/90r
145*/99r
Acetyl-CoA carboxylase alpha subunit
Idiomarina loihiensis
A. macleodii
Elongation factor Ts
133*/90r
Pseudoalteromonas
tunicatca
Ribose-phosphate
I. baltica
pyrophosphokinase
Alanine dehydrogenase
Idiomarina baltica
P. haloplanktis
239*/99r
132*/90r
Succinyl-CoA
synthetase
subunit beta
A. macleodii
Fe31 dicitrate
receptor
274*/90r
112*/90r
Pseudoalteromonas
haloplanktis
Hypothetical outer
membrane protein
110*/90r
A. macleodii
Polysaccharide
biosynthesis/
export protein
135*/90r
P. atlantica
Shewanella
woodyi
Species
TonB transporter
TonB-dependent
receptor
Protein
287*/99r
151*/99r
Score
37.9/34.9
34.3/30.9
35.4/34.0
45.8/39.7
42.5/41.3
46.0/56.2
76.3/77.0
28.1/29.0
24.3/20.1
26.7/29.0
84.0/82.3
Mass (kDa)
experimental/
theoretical
Q. Wang et al.
18
VVADFLSSVGVDR
LTAVNPYFGHPRd
QMTLADLALLDKRd
QDEPTVPTVSPDLGRVRd
NSADAVSFLR
1224.369
1642.860
1903.150
2073.648
2926.465
2
ELDNGTVQLYTRd
VAYGLVGDTQSFDFGDGRd
MSYAAAEYAGNLEKEGRd
1408.723
1903.838
1859.900
1
De novo peptide sequence
Precursor
ions
Spots
no.
Table 3. Proteins identified by de novo
1264
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© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
1027.525
1189.158
1899.986
43, 44
47
1249.675
1569.849
1258.363
2402.820
36
52
1692.219
2649.029
3233.161
32
1349.590
1789.146
1073.529
1275.619
1319.881
1349.714
1413.848
1565.652
1683.862
5, 29,
30, 31,
39
51
1790.823
1619.134
1739.186
1973.333
2240.470
24
25
1739.747
1933.353
760.608
945.059
969.530
1176.429
1370.577
1429.544
1563.787
21, 67
49
Precursor
ions
Spots
no.
Table 3. Continued
d
d
YENLDLLTLRd
TGQNLPEATLDAALRd
NLQGADLHPQTR
LYPDGTLPQNNMNVGR
NGPGPFTALGTYEGDR
GSQGAELFVTDLNEEALER
VEADPATFLPSPGTLTRd
VVYQDFTR
–YHAFLDGR
d
LVMLVGGDVSLR
AGTDAYGTALAEGGVGYSGCLAELR
–HLGEALAATSEGR
LEWLELNDLMEVAYSTAVAANWR
SRSQQNMEMWQFHPTGLAGAGTLVTESMR
EWLAPSGSEGSR
DWAGNEPER
VDLVFGSNSLLR d
NLQGADLTPQTR d
DQVNLTVPFAPGR d
YKDPEYFAETFR
ADYSVQPEEMMLDR
GFSADDFALSHPGGSAVRd
QSHQVLLADLLLLR d
HLATQVDVLDGGWTAR
–DTGATGGLGFAVAQTLAAR
–VLVNNAGLQHVAR
LATLGAGR
GDVLLGVNR d
GVVALNLKR
GNQTLYVLLR d
QGYLVTNAHVLR
DASDLLLNLQDGR
NLVDQMLEFGELR
De novo peptide sequence
YENIDIITIR*r
TGELLPQATLDAIAK*r
NVQGADIHPET–*r
IWPDGSIPKDN–*
–PSPHTALGTYLGL–*
–GAELIVTDINEEAIER*r
INAEDPETFTPSPGTITR*r
EWLAPSDNPESR*r
DWEGNEPER*r
VDLVFGSNSILR*r
–DLGPKTR*
–DITVPFAPGR*r
HKDPEYFNEVF*r
DYAVAPEEMMLDR*r
–HLGETLSAQSEAR*
IECLELDNLMETAYATAVAANFR*r
AGISMQDMEMWQFHPTGIAGAGVLVTEGCR*r
LLMLVNDVSLR*r
QGTDHGTAIAEGGVGYSCIAEVR*r
VVYQDFTR*r
–FHAFLDGR*
VATMGAG*
GDIIVGVNR*r
GSVALKIKR*r
DNTSLYLILR*r
KGYIVTNNHVI–*r
–EILIGLHDGR*
NLVKQIIEHGEVR*r
GFSADDFALSHPGGSLGR*r
–QGHRILVADI–*
NITGQTMVLDGGWTAR*r
–ITGGASGIGFGIAEFL–*r
–ILVNNAGIQHV*
Homology matched peptide sequence
123*/99r
109*/90r
132*/90r
Alteromonadales bacterium
Isocitrate dehydrogenase
Glucose/sorbosone
dehydrogenase
Leucine dehydrogenase
I. loihiensis
I. loihiensis
I. loihiensis
40.5/35.9
43.2/41.9
41.5/37.0
51.7/49.5
62.0/56.5
42.1/36.9
67.5/63.9
I. baltica
I. baltica
83.4/79.7
32.5/79.7
33/34.1
29.3/27
50.1/49.6
Mass (kDa)
experimental/
theoretical
A. ehrlichei
A. amylolytica
P. atlantica
Shewanella pealeana
Species
Acetyl-CoA carboxy- I. loihiensis
lase biotin carboxylase
Phosphoglyceromutase
118*/90r
95*/90r
2-Keto-4-pentenoate
hydratase
Succinate dehydrogenase catalytic
subunit
267*/99r
181*/99r
Catalase-peroxidase
GutQ
3-Hydroxybutyrate
dehydrogenase
Protease Do
Protein
419*/99r
109*/90r
261*/99r
316*/99r
Score
Proteomics 2009, 9, 1254–1273
1265
www.proteomics-journal.com
894.805
1428.232
1557.339
2186.869
1528.437
2655.06
1347.700
1861.137
1106.536
1250.468
1431.014
1443.761
1517.817
989.655
1725.692
1811.609
2915.128
1027.287
1352.554
1462.730
1915.256
913.670
1546.542
2172.486
1602.698
1969.995
1240.851
1550.980
1497.716
54
56
57
58
60
61
62
63
64
71
74
76
d
d
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
d
d
ASPSTMDTGDFGGVR
VFGDAFETLSR
LFADGDQGVASDMAR
QSNSEMADELAPVSYSSRd
CFAQDTSPMYGLGRd
VVAELGAVR
SVGPYTALVQDGPSR
DSLGSDAFVPDEVLTSHAVGR
VTVNNPSVSGFEGR
VQSFPVDQYSLEEFAR
LLHVDFQR
SDALYTLDAEVR
LGLLFLTGR
SVVTFNGWTLDELSR
VPTPVVLLVEDEEVTR d
CPDPSNFQWGYDVLEALDWEMNQR
FTSPLVLPDADLRd
LALLFDEVGATGVGRd
LFLTASAEVR
LGDLLHDLQAR
LLLEGENVSSTLR
KRHAVFATTVEENPALR
TQQGHAAANLVPLLASNR
VNLLTGNADELLTR
LALANTYYLAGMLNDPR
YAGAPFLR
FLAQHPAEFDPR d
RHPPPTGDLLALDR d
ANMLAADQTDSPVLVQASAGAR
De novo peptide sequence
Antioxidant,
AhpC/Tsa family
76*/90r
Acetyl-CoA acetyltransferase
Enoyl-CoA hydratase/isomerase
109*/99r
INSGTFNDEIAPVTVSSR*r
CYAQDTADEYGLGR*r
IFGEAFETLSA*r
LFASGDKGVAVDWAR*r
ALGLEMDTGNFGGVR*r
Leucyl aminopeptidase
140*/99r
222*/9r
VIAEIGAVR*r
AKGPYTALVPNGPAR*r
NSIGSDAFVADEIITGH–*r
V. cholerae
Vibrio vulnificus
I. loihiensis
I. baltica
18.0/16.3
29.6/28.0
42.1/41.1
62.0/55.2
24.4/22.9
Uncharacterized
conserved
secreted protein
I. loihiensis
109*/90r
29.6/22.9
Ribosomal protein L25 A. macleodii
31.4/26.9
41.5/42.8
103*/99r
P. haloplanktis
P. haloplanktis
34.6/24.4
Aerobic respiration
control protein
N-succinyldiaminopimelate
147*/99r
P. tunicata
33.7/32.3
39.0/38.6
40.5/38.2
Mass (kDa)
experimental/
theoretical
319*/99r
Cytidine monophosphate (CMP)
kinase
137*/90r
Nitrilase/cyanide
hydratase
177*/90r
Azotobacter
vinelandii
P. atlantica
ABC-type Fe31
transporter
151*/99r
VNLVTGKADALLTR*r
VAIANTYYLAGMSDITR*r
–ATTVEENPAIR*
VQQGHAAANLTPLIASNR*r
IYLTASAQER*
IEDLLYDIQAR*
IILEGEDVSQAIR*r
FTPSLVIPEADIR*r
ALLEFDEVQTGVGR*r
VGLIFLTGR*r
–VITFNGWELDENSR*r
–TPVILIVEDEDVTR*r
LNLVSLFEAEGYKVIEAIDGEDWHAK*r
IMHIDFQR*r
SEAIFNLDASVR*r
VTVDTPTSEGFEG*r
–QSFPVDAYSKELF–*r
Species
Oceanobacter
Protein
Fructose-bisphosphate aldolase
339*/99r
Score
YAGAPFLR*r
FLAENPAEFDPR*r
FTRPPTGDILAIDR*r
AIMMAADKTDSPVIVQASAGAR*r
Homology matched peptide sequence
Q. Wang et al.
, SPITC treated peptides; d, peptides without SPITC treatment; *, MS BLAST search; r, SPIDER homology search.
Precursor
ions
Spots
no.
Table 3. Continued
1266
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Proteomics 2009, 9, 1254–1273
1267
Figure 4. Identification of pH-dependent 2-DE spots treated with SPITC and measured by MALDI-TOF/TOF MS followed by data annotation
with de novo sequencing. (A) The localized 2-DE images of spot 21 (circled), which displayed the increased spot volumes responding to
elevated pHs. (B) The PMF signals of spot 21 digestives treated without SPITC. (C) The PMF signals of spot 21 treated with SPITC. (D) and (E)
The MS/MS spectra corresponding to the parent ions 1370.751 and 1429.728, and the parent ions with or without SPITC were shown as
bold fonts in the MS/MS spectra. Two peptides were elicited from de novo sequencing, KGYLVTNAHVLR and DASDLLLNLKDGR. The protein corresponding to these peptides was annotated as protease DO by MS BLAST.
ified as the proteins associated with cytoplasmic membrane
(Table 4). Hence totally 86.4% (19/22) of the membrane
identifications, at least, were deemed part of strain N10
membrane. Although a relatively low amount of transmembrane proteins were identified, the high percent of membrane-bound or -associated proteins still denotes a successful
preparation of strain N10 membrane fraction as well as an
accepted separation of membrane proteins by 2-DE. On the
other hand, high portion of the identified proteins in cytoplasm fractions, approximately 45.2% (14/31), were likely to
be associated with strain N10 membrane (Table 4). It is
obviously that the expression status of strain N10 membrane
and membrane-associated proteins was delicately regulated
by external pH.
There were three pH-dependent proteins, DegQ, GroEL,
and HPI, were coidentified in membrane and cytoplasmic
fraction. According to theoretical prediction and other investigations, these proteins are mainly located at cytoplasm but
also partially attached with membrane. DegQ appeared on a
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
single spot on the gels and displayed the similar values of pI
and molecular mass in the two fractions. The pH-dependent
pattern of the cytoplasmic DegQ was consistent with that of
the membrane associated. On the 2-DE gels of strain N10
membrane proteins, three spots were found as GroEL and
exhibited bell-mode changes responding to elevated pH
values, while only a single spot of this protein was detected
on the 2-DE gels of the strain N10 cytoplasmic fraction and
showed its spot volumes increased as the external pH elevated. The conflict of pH-dependent patterns was likely
caused by the modification status of GroEL proteins, because
all the GroEL spots were recognized from different pI values
with similar molecular mass. A single spot of HPI was verified in strain N10 membrane fraction, and appeared in
attenuated trend in its spot volume as pH increased. However, six spots of HPI were found on the 2-DE gels of the
strain N10 cytoplasmic proteins, leading to a problem of how
to describe its pH-dependent mode. Therefore, we adopted
Western blot and real-time PCR to specifically monitor the
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Proteomics 2009, 9, 1254–1273
Figure 5. Identification of pH-dependent 2-DE spots treated without SPITC and measured by MALDI-TOF/TOF MS followed by data annotation with de novo sequencing. (A) The localized 2-DE images of spot 60 (circled), which displayed the bell-mode change responding to
elevated pHs. (B) The PMF signals of spot 60 digestives treated without SPITC. (C) and (D) The MS/MS spectra corresponding to the parent
ions 1443.763 and 1517.814 in Fig. 5B, and the parent ions were shown as bold fonts in the MS/MS spectra. Two peptides were elicited from
de novo sequencing, FTSPLVLPDADLR and LALLFDEVQTGVGR, and the corresponding protein was annotated as N-succinyl diaminopimelate aminotransferase by both MS BLAST and SPIDER homology search.
Figure 6. Confirmation of some
results generated from 2-DE and
MALDI-TOF/TOF
MS
using
Western blot. The protocol of
Western blot was described in
Section 2. Upper panels show
Western blot images and lower
panels exhibit the localized 2-DE
images, respectively. For the
proteins, FecA (Fe31 dicitrate
receptor), AtpD (ATP synthase
beta subunit), and DegQ (protease DO), the single differential
spots were identified, whereas
the protein of HPI (catalase-peroxidase) was found in several
differential spots, distributed
along varied pIs and MWs. The
results were obtained from
three replicates.
expression changes of this enzyme responding to external
pHs. As shown in Figs. 6 and 7, the expression of HPI was
inhibited due to alkalinizing culture medium.
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
The differential strain N10 proteins responding to external pHs, either in membrane or in cytoplasmic fraction,
are broadly divided into six functional groups (Table 4),
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Proteomics 2009, 9, 1254–1273
1269
Figure 7. Comparison of expression of the pHdependent N10 genes at mRNA and protein. The
graphics on left side show the six pH-dependent
N10 proteins at relative spots volumes, which
were generated from the 2-DE images with silver
staining. The graphics on right side reveal the
same six pH-dependent N10 genes at relative
expression intensity, which were produced by
real-time PCR. The SDs for the 2-DE images were
estimated from 6 parallel runs, and for the realtime PCR were calculated upon 12 parallel
experiments.
(i) transporters, (ii) bioenergetic generation, (iii) metabolism,
(iv) protein process, (v) stress proteins, and (vi) others. Specifically, differential proteins of the strain N10 membrane
were mainly in three functional groups, transporter proteins
(4/20), bioenergetic generation proteins (4/20), and metabolism enzymes (5/20); the differential proteins of the strain
N10 cytoplasm were mainly in two groups, metabolism
enzymes (10/24) and stress proteins (6/24). Overall, for the
unique differential proteins both in membrane and cytoplasm, there were four dominant functional categories,
12.2% (5/41) in transporters, including four inorganic iron
transporters, 14.6% (6/41) in bioenergetic generation, 36.6%
(15/41) in metabolism, and 14.6% (6/41) in stress reactions,
respectively.
We further examined which kind of pH-dependent proteins participated in biological process. As illustrated in Table
4, several observations deserve to be mentioned. Firstly, several solute transporters, especially in iron transport show
pH-dependent expression as external pH changed; secondly,
a large percent of proteins up regulated or favorable in
expression at optimal pH were the enzymes partaking in
bioenergetic process and metabolism of carbohydrates, fatty
acid, amino acids or nucleotides; thirdly, several enzymes
with deaminases activity in amino acid metabolism pathway
exhibited bell-shape expression mode, which might contribute to cytoplasm acidification.
4
Discussion
In bacterial proteomic investigation, unavailability of genomic data often makes a technique barrier in interpretation of
mass spectrometric data. This prompted us to propose a hypothesis that the pH-dependent strain N10 proteins sepa© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
rated by 2-DE could be identified by a combined strategy of de
novo sequencing [31]. We analyzed the tryptic digestions
treated with/without SPITC by high resolution of MS; then
we adopted the stringent criteria to search the peptides with
de novo sequencing; finally we employed other biochemical
approaches, such as real-time PCR and Western blot, to confirm the proteomic conclusions. As described above, our
effort has gained a satisfied result of which more than 70% of
the differential 2-DE spots were identified as the bacterial
proteins. There have been a few of reports regarding alkaliphilics proteomic analysis upon 2-DE so far. Gilmour et al.
[13] taken 2-DE to analyze the pH-dependent proteins in B.
pseudofirmus OF4 grew at pH 7.5 and 10.5, but identified only
five differential proteins with N-terminal sequencing due to
lack of its genomic sequence. According to the strategy
reported in this study, we are confident to improve such low
identification rate regardless of genomic availability.
Through the combined de novo strategy to the strain N10
proteome, our study for the first time has globally surveyed
the pH-dependent proteins in an alkaliphilic bacterium. Are
these data consistent with other early observations? As compared of the published data regarding pH-responsible proteins in neutraphilic or in alkaliphilic bacteria, four differential proteins found in this study, alkyl hydroperoxide
reductase, succinyl-CoA synthetase, dihydrolipoyltranssuccinase and a hypothetical outer membrane protein were also
found in E. coli, but demonstrated as an acid-induced mode
[15, 16]. Although only three unique pH-dependent proteins
were found in B. pseudofirmus OF4, which were not detected
in this study, several strain N10 pH-dependent proteins possessed as similar biochemical properties as surface layer
protein, butyryl-CoA dehydrogenase and a-keto acid dehydrogenase [13]. Importantly, we have identified several
amino acid deaminases which were favorably expressed
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Proteomics 2009, 9, 1254–1273
Table 4. Subcellular localization and function analysis of proteins identified
Protein
Function
SignalP
TMMH
no.
SecretomeP
score
Fraction
Response
to pH
Ratiop
1–25
1–25
N
0
1
0
0.92
,0.5
,0.5
M
M
M
D
D
D
0.33
0.71
0.17
0.89
0.47
0.00
0.29
0.42
0.00
1–39
1–35
0
1
0.71
,0.5
M
C
U
B
1.09
3.14
2.12
0.26
2.31
0.81
N
0
0.58
M
B
2.81
0.43
1.20
N
0
,0.5
M
B
2.46
0.41
1.00
N
N
N
0
1
0
,0.5
,0.5
,0.5
M
M
C
B
B
B
10.48
..2
1.76
0.26
0.77
0.38
2.75
..2
0.66
N
0
,0.5
C
B
2.08
0.17
0.35
N
N
1–22
N
0
0
0
0
,0.5
,0.5
0.71
,0.5
M
C
C
C
U
B
B
B
1.76
4.05
2.12
2.17
3.72
0.40
0.40
0.80
6.55
1.62
0.84
1.73
N
0
,0.5
M
U
2.12
2.08
2.97
N
N
N
0
0
0
0.68
,0.5
,0.5
C
C
C
D
B
B
0.37
2.13
1.84
1.15
0.38
0.41
0.68
0.81
0.74
N
N
N
0
0
3
,0.5
0.55
,0.5
M
C
M
U
U
B
2.37
2.32
5.41
2.78
1.57
0.39
6.60
3.63
2.11
N
0
,0.5
C
B
3.40
0.29
0.97
N
1
,0.5
C
U
2.71
1.82
4.93
N
0
,0.5
M
B
2.07
0.40
0.29
N
0
,0.5
C
B
2.70
0.22
0.58
N
N
N
0
0
0
,0.5
,0.5
,0.5
M
C
C
B
B
B
3.35
4.41
1.17
0.65
0.30
0.49
2.18
1.34
0.570
N
N
0
0
0.86
,0.5
M&C
M&C
D
B
0.48
4.18
0.16
0.53
0.06
2.23
pH 9.4/8.4
pH 10.4/9.4 pH 10.4/8.4
Transporter/binding proteins
118071623
109899297
88795561
88795920
109897917
TonB-dependent receptor
TonB transporter
Polysaccharide biosynthesis/export
protein
Fe31 dicitrate receptor
ABC-type Fe31 transporter
Proton transport and bioenergetic process
77360587
87121037
88860143
75197628
85711265
56178979
Dihydrolipoyltranssuccinate transferase
Succinyl-CoA synthetase subunit
beta
Alanine dehydrogenase
ATP synthase beta subunit
Succinate dehydrogenase catalytic
subunit
Isocitrate dehydrogenase
Metabolism of carbohydrate
109692189
119473218
104782544
94501443
GutQ
Phosphoglyceromutase
Glucose/sorbosone dehydrogenase
Fructose-bisphosphate aldolase
Metabolism of amino acids
24373246
85712094
56460422
77359165
Methylmalonate-semialdehyde
dehydrogenase
2-Keto-4-pentenoate hydratase
Leucine dehydrogenase
N-succinyldiaminopimelateaminotransferase
Metabolism of fatty acid and lipid
109898293
56459980
56460789
56461386
37676700
3-Hydroxybutyrate dehydrogenase
Acetyl-CoA acetyltransferase
Acetyl-CoA carboxylase, alpha
subunit
Acetyl-CoA carboxylase, biotin
carboxylase
Enoyl-CoA hydratase/isomerase
Metabolism of nucleotides and nucleic acids
85713258
88859274
Ribose-phosphate pyrophosphokinase
Cytidine monophosphate (CMP)
kinase
Protein synthesis
88796910
95110328
77361813
Elongation factor Ts
Seryl-tRNA synthetase
Elongation factor Tu
Stress proteins
114320678
28190315
Catalase-peroxidase
GroEL
© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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Proteomics 2009, 9, 1254–1273
Table 4. Continued
Protein
88796772
88793692
85713338
119776645
Function
SignalP
TMMH
no.
SecretomeP
score
Fraction
Response
to pH
Ratiop
pH 9.4/8.4
pH 10.4/9.4 pH 10.4/8.4
Ribosomal protein L25
Protease Do
Leucyl aminopeptidase
Antioxidant, AhpC/Tsa family
N
1–27
N
N
0
2
0
1
,0.5
,0.5
,0.5
,0.5
C
M&C
C
C
B
U
B
U
1.15
1.61
1.41
1.24
0.28
2.13
0.31
3.12
0.32
3.44
0.43
3.86
Cell division inhibitor
Hypothetical outer membrane
protein
RNA polymerase subunit A
Nitrilase/cyanide hydratase
Aerobic respiration control protein
Uncharacterized conserved
secreted protein
N
1–20
0
N
,0.5
0.94
M
M
D
D
0.43
0.13
0.43
0.62
0.18
0.81
N
N
N
1–22
0
0
0
1
,0.5
,0.5
,0.5
0.93
M
C
C
C
B
B
B
B
3.08
3.36
2.21
2.04
0.42
0.62
0.23
0.2
1.29
2.09
0.50
0.40
Others
90409439
77359363
2625019
67155556
77359507
56460530
M, membrane fraction; C, cytoplasm fraction; M&C, membrane fraction and cytoplasm fraction; D, down-regulated as external pH
increased; U, up-regulated as external pH increased; B, bell-shape mode as external pH increased; N, “NO”; p, average value from six
replicates; , proteins in membrane fraction without signal peptide or THMM domains but might be membrane associated according to
their function or literature reports.
at pH 9.4 and might contribute to cytoplasm acidification as
predicted in previous studies. These proteins displayed as
base-induced expression mode in E. coli but the upper limit
of pH in those studies were not higher than 9.2 [16, 23].
Over the past decade people have recognized the
importance of monovalent cations in pH homeostasis of
alkaliphile, typically as Na1-specific antiporters. Na1/H1
antiporters (Nhas) electrogenically exchange a larger number of influx H1 than the number of efflux Na1 during a
turnover so that cytoplasmic acidification relative to the
outside can be achieved [32, 33]. We have identified a gene
of Na1(Li1)/H1 antiporter from strain N10, and characterized its transport functions [5]. In this study, nevertheless,
the Nha protein was detected neither from membrane nor
from cytoplasm. Considering 2-DE is not effective for
analysis of membrane proteins, we further separated the
strain N10 membrane proteins by SDS-PAGE and identified the pH-dependent proteins by LC-MS/MS [34]. There
was still no mass signal correspondent with the Nha protein. Hence the proteomic technique seems not a causal
factor on detecting of the Nha proteins. We apprehend to
attribute such observation to low abundance of the Nha
proteins in strain N10 or the Nha protein expression
insensitive to external pH. Meanwhile, we have acknowledged that several membrane and membrane-associated
proteins were confirmed in a mode of pH-dependent
expression as listed in Tables 3 and 4. Of these proteins,
four works for inorganic iron uptake, such as Fe31 dicitrate
receptor (FecA), TonB-dependent receptor (CirA), TonB
transporter, and ABC type Fe31 transporter (AfuA). The
pH-dependent expression of iron ion transporters is probably due to its low solubility at high pH conditions. Inter© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
estingly, the antioxidant enzyme, HPI, was attenuated in
its expression at high pH. The phenomenon could be
resulted from lower oxidative stress induced by Fe31 in
alkaline environment, at least partially.
Although a decrease of the extracellular H1 concentration is unfavorable for production of ATP, an alkaliphle can
survive well even under pH 11. The phenomenon implies
that alkaliphilic bacteria possess the specific machinery of
energy generation that is dramatically different from that of
neutralophiles. The molecular mechanisms of energy generation in alkaliphiles are still in arguments. It was found
that the protein expression of NADH dehydrogenase, succinate dehydrogenase, and F1Fo-ATP synthase was not affected
by elevated pH in Bacillus firmus OF4, whereas cytochrome c
and cytochrome caa3 were increased two-fold at pH 10.5 as
compared with at pH 7.5 [35–37]. By contrast, high pH
repressed the expression of cytochrome c, NADH dehydrogenases I and II, but induced the expression of F1Fo-ATP
synthase and cytochrome d in E. coli [38, 39]. Our data listed
in Table 4 provided additional information which revealed
the proteins involved in bioenergy and metabolism in strain
N10 dominantly responded to changes of external pH.
Firstly, subunit beta of F1Fo-ATP synthase exhibited bellmode expression, which was different from the observation
in B. firmus OF4 but partially consistent with that of E. coli.
Secondly, three tricarboxylic acid cycle (TCA) enzymes displayed a pH-dependent expression mode that remained peak
expression at pH 9.4. This prompts a puzzle whether the
TCA pathway was more active at the optimal growth pH environment than at other conditions. Thirdly, a number of
metabolic enzymes in carbohydrate, fatty acid and amino
acid were up-regulated or bell-regulated as pH increased.
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Q. Wang et al.
The metabolites generated from these enzymes would
merge into the network of bioenergy generation, and adjust
respiration efficiency and ATP synthesis. In spite of proteomic results which led to a draft of protein responses to environmental pH, we have fully realized that more details are
urgently required to explore how these molecules in strain
N10 work together to tolerate the external pH changes.
This work was supported by grants from the Chinese Academy of Sciences (Knowledge Innovation Program, KSCX2-SW33), from NSFC (30621005), and from the Ministry of Sciences
and Technology of China (973 programs, 2003CB716001,
2004CB719605, 2007CB707801, 2007CB714301).
The authors have declared no conflict of interest.
5
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