Comprehensive Proteomic Analysis of Shigella flexneri 2a Membrane Proteins Candong Wei, Jian Yang, Junping Zhu, Xiaobing Zhang, Wenchuan Leng, Jing Wang, Ying Xue, Lilian Sun, Weijun Li, Jin Wang, and Qi Jin* State Key Laboratory for Molecular Virology and Genetic Engineering, Institute of Pathogen Biology, CAMS, Beijing 100730, Peoples Republic of China, and Institute for Viral Disease Control and Prevention, China CDC, Beijing 100050, Peoples Republic of China Received April 17, 2006
Shigella flexneri is the causative agent of most shigellosis cases in developing countries. We used different proteolytic enzymes to selectively shave the protruding proteins on the surface of purified bacterial membrane sheets or vesicles, and recovered peptides were subsequently identified using 2-D LC-MS/MS. As a result, a total of 666 proteins were unambiguously assigned, including 159 integral membrane proteins, 35 outer membrane proteins and 114 proteins previously annotated as hypothetical. The former had an average grand average hydrophobicity score of 0.362 and were predicted to separate within a pH range of 4.1-10.6 with molecular mass 8-148 kDa, which represents the largest validated set of integral membrane proteins in this organism to date. A functional classification revealed that a large proportion of the identified proteins were involved in cell envelope biogenesis and energy production and conversion. For the first time, this work provides a global view of the S. flexneri 2a membrane subproteome. Keywords: Shigella flexneri • membrane subproteome • 2-D LC-MS/MS
Introduction Shigella flexneri is the main causative agent of endemic shigellosis in developing countries and the most frequently isolated species worldwide. Serotype 2a is its predominant serotype.1,2 Gram-negative bacterial membrane proteins act as highly active mediators between the cell and its environment and could be valuable candidate targets of pharmacological agents. To date, more than 50% of known drug targets are membrane proteins.3 The membrane subproteome is thus an intensive area of research. However, membrane proteins possess hydrophilic hydropathy values so that they, especially integral membrane proteins, are commonly missed in conventional research such as 2-DE studies.4, 5 It is vital to solve this problem. Gel-free proteomic approaches coupling orthogonal liquid chromatography with MS/ MS6,7 are emerging as powerful complementary tools for the analysis of complex protein mixtures, with the potential to overcome the limitations of the 2-DE-based approach with respect to hydrophobic proteins.8-11 More recently, Yates and others applied a multidimensional protein identification technology (MudPIT) to the proteome of Saccharomyces cerevisiae and identified 1484 proteins, including 131 proteins with three or more predicted transmembrane domains (TMDs).9 Hancock et al. have published a study on the use of multiple enzyme digests in parallel for improved characterization of proteins.12 Direct identification of proteins using different protease diges* To whom correspondence should be addressed. Tel: +86 10 67877732. Fax: +86 10 67877736. E-mail:
[email protected].
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tion strategies provide an automated, high-throughput system for the analysis of protein complexes. Nonetheless, the global view of Shigella membrane subproteome has not been clearly elucidated to date. Most recently, using immunoproteomics, Ying et al. identified 22 immunoreactive OMPs in S. flexneri 2a 2457T.13 In this study, we applied an optimized procedure to quickly and selectively identify the proteins that are completely or partially bound on the membrane, based on their specific orientation. The purified bacterial membrane sheets were sequentially treated with proteases to selectively digest protruding membrane proteins with different orientations, and the peptide mixtures generated were separated by 2-D HPLC and identified online by ESI-MS. For the first time, a comprehensive subproteome reference map and database of the membrane proteins of S. flexneri has been established.
Experimental Section Reagents. All reagents were purchased from Sigma-Aldrich Co. (St. Louis, Missouri) with the exception of HPLC grade acetonitrile and formic acid, which were purchased from Merck KGaA (Darmstadt, Germany) and modified sequencing grade trypsin and proteinase K, which were purchased from Roche Diagnostics Co. (Indianapolis, Indiana). Bacterial Strain and Growth Conditions. Frozen S. flexneri 2a, strain 301 (kindly provided by the ICDC, China CDC) cell stocks were streaked onto tryptic soy agar containing 0.01% Congo red. An individual red colony was subsequently trans10.1021/pr0601741 CCC: $33.50
2006 American Chemical Society
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Shigella flexneri 2a Membrane Subproteome
ferred into tryptic soy broth (TSB) and grown overnight at 37 °C and 200 rpm with rotary shaking. The overnight culture was diluted 0.2 mL to 200 mL fresh TSB and incubated at same conditions as above until OD600 ) 1.2. Cells were harvested by 8 min centrifugation at 2500 × g and 4 °C and then washed two times by ice-cold 50 mM Tris/Hcl, pH 7.3. The pelleted cells were frozen at -20 °C until needed. Membrane Proteins Preparation. Membrane extraction was performed as previously described14 with some changes. Briefly, the bacterial cells were ruptured by ultrasonication and the unbroken cells were removed by centrifugation at 4000 × g for 10 min. The supernatant was diluted with ice cold 0.1 M sodium carbonate (pH 11.5) to a final pH 11 and stirred slowly on ice for 1 h. The carbonate treated membranes were collected by ultracentrifugation in a Beckman SW 40Ti rotor at an average of 115 000 × g for 1 h at 4 °C. The supernatant was discarded and the membrane pellet was resuspended and washed twice in ice-cold 50 mM Tris/Hcl, pH 7.3. At last, the washed membrane sheets were pelleted by ultracentrifugation at an average of 115 000 × g for 45 min and stored at -20 °C for subsequent analysis. Sample Digestion. Following a slightly modified protocol of Wu et al.15 for MudPIT analysis, purified membrane pellets from Shigella were resuspended in 0.1 M sodium carbonate containing 7 M Urea and 2 M Thiourea, then digested using proteinase K (PK). The digested supernatant was collected as MP_both. In the following sections, this method is termed MP_direct. In another type of sample preparation, the purified membrane sheets were resuspended in 0.1 M sodium carbonate with intermittent vortexing and sonication. The proteins were reduced in the presence of 10 mM DTT at 37 °C for 45 min, and then alkylated in the presence of 30 mM iodoacetamide at room temperature in the dark for 30 min. The suspension was diluted 10 times with 0.1 M sodium carbonate and 2 M NaCl buffer, and then stirred slowly on ice for 1 h. The membrane sheets were collected by ultracentrifugation as above. Subsequently, the isolated membranes were predigested with trypsin (1:100 w/w) overnight in a 50 mM Tris/HCl buffer, pH 8.5, at 37 °C. On the next day, the supernatant were collected as MP_outer. At the same time, the membranes were pelleted by ultracentrifugation at 115 000 × g and washed two times with ice-cold 1 M sodium carbonate. The predigested membrane sheets were then digested using PK following Wu’s protocol. Subsequently, the supernatant was collected as MP_inner. The membrane sheets were digested overnight using an excess of PK in 0.1 M sodium carbonate at 37 °C, and pelleted again. After carbonate washing, the membrane sheets were resuspended in 60% methanol and 40% 25 mM ammonium bicarbonate buffer with intermittent vortexing and sonication, and were digested overnight by trypsin at 37 °C. On the next day, the supernatant was collected as MP_tmd. In the following sections, this method is termed MP_complex. Finally, all the collected supernatants were filtered through 10 kDa cutoff filters (Microcon YM-10, Millipore) and desalted using column (HLB 3cc, Waters). All peptide fractions were concentrated with a Speed-vac centrifuge (Savant) and solubilized in 0.1% formic acid for the following 2D LC-MS/MS analysis. Protein identification by 2D LC-MS/MS. Orthogonal 2D LC-MS/MS analysis was performed using a ProteomeX Workstation (Thermo Finnigan), which consists of a strong cation exchange column (BioBasic SCX, Thermo Hypersil-Keystone) and two parallel C18 reversed-phase microcapillary columns
(BioBasic-18, 100 × 0.18 mm, Thermo Hypersil-Keystone). The solutions used were as follows: 3% ACN/0.1% formic acid (buffer A&C), ACN/0.1% formic acid (buffer B). A sample of the desired peptides digest was loaded onto the SCX column. Then each of 200 µL 2, 5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 100, and 500 mM NH4Cl was used to displace peptide fractions from the SCX column onto the RP column, respectively. Each case was synchronized with a 140 min RP gradient. The RP gradient program includes three successively linear gradients: a 40-min gradient to 20% buffer B followed by a 40-min gradient to 40% buffer B and then a 20-min gradient to 100% buffer B. The flow rate through the column was 2 µL/min. Eluting peptides were electrosprayed into the mass spectrometer with a distally applied spray voltage of 3.4 kV. The column eluate was continuously analyzed during the whole 14step chromatography program. One full range mass-scan (3502000 m/z) was followed by three data-dependent MS scans on the three most intense ions with dynamic exclusion at 35% normalized collision energy. Both HPLC pump and mass spectrometer were controlled by the Xcalibur software (Thermo Electron). Protein Identification. Data files from the chromatography runs were batch searched against the S. flexneri proteome database using the SEQUEST algorithm16 contained within Bioworks v3.1 software. The criteria used for protein identification were as follows. For positive identification of any individual protein, a minimum of two peptides was required. The minimum cross-correlation coefficients (Xcorr) of 1.9, 2.2, and 3.75 for singly, doubly, and triply charged precursor ions respectively and a minimum ∆Cn of 0.1 were both required for individual peptides. Physicochemical Characteristics and Subcellular Localization of the Identified Proteins. The full set of S. flexneri 2a ORFs was downloaded from the NCBI databases, including 4443 ORFs.17 All identified proteins were analyzed by the PSORTb v2.0 algorithm using the version for Gram negative bacteria (available at http://www.psort.org/psortb/). This analysis was performed to predict the bacterial protein subcellular localization, which was presently the most precise localization prediction method available.18 The codon adaptation indices (CAI) and hydrophilicity of the proteins were calculated with the standalone version of program CodonW (John Peden, http://bioweb.pasteur.fr/seqanal/interfaces/codonw.html). The hydrophilicity was given as a GRAVY (Grand Average of Hydropathicity) score,19 which is calculated as the sum of hydropathy values of all the amino acids, divided by the number of residues in the sequence. The TMHMM 2.0 program, based on a hidden Markov model (http://www.cbs.dtu.dk/ services/TMHMM/), was used to predict protein transmembrane topology.20 The protein functional family was categorized according to the COG annotation terms (http:// www.ncbi.nlm.nih.gov/COG/).21
Results and Discussion High-Throughput Identification of Membrane Proteins with 2D LC-MS/MS. To avoid false-positive hits, we applied strict criteria for peptide and protein identification. Supplementary Table S1 shows the identified proteins in details. In total, 666 unique proteins were identified, which included 114 proteins previously annotated as hypothetical or conserved hypothetical. All proteins associated with membranes could be considered membrane proteins. Thus, membrane proteins are a heterogeneous mixture of integral membrane proteins with Journal of Proteome Research • Vol. 5, No. 8, 2006 1861
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Wei et al. Table 1. Subcellular Localization of S. flexneri Proteins by PSORTb V2.0a OM
EC
all ORFs 732 proteins MP_direct 57 identified MP_complex 136 total 159
75 23
14 1516 119 1987 4443 3 113 8 127 331
31 35
2 3
C
173 226
P
UNKb
CM
19 24
167 219
total
528 666
a Abbreviations for localization sites: C, cytoplasm; CM, integral cytoplasmic membrane; P, periplasm; OM, outer membrane; EC, extracellular and UNK, unknown. b PSORTb preferred a result of “unknown” to avoid potential false positive results when not enough information is available to make a prediction.18
Figure 1. Plot of GRAVY score and pI vs TMDs of 149 identified proteins.
many transmembrane regions, and peripheral membrane proteins that are associated with the membrane and potential significance in vaccine studies. Our experiments led to the identification of a much wider range of proteins in the membrane fraction than those identified using the conventional 2-DE-based method.22 We first categorized the identified proteins according to their physicochemical characteristics such as molecular weight (MW), isoelectric point (pI), codon adaptation index (CAI) and grand average hydrophobicity (GRAVY) scores. The detailed distribution patterns of these identified proteins are shown in Supporting Information Figure S1, respectively. In this study, the smallest and largest MW were 5 kDa and 170 kDa, pI 3.7 and 11.8, CAI 0.143 and 0.849, and GRAVY scores -1.12 and +1.27, respectively. Regardless of their hydropathy and abundance, 554 proteins (83%), ranging from MW 10 to 100 kDa and pI 4 to 10, were compatible with general 1-D or 2-D PAGE. The other 112 proteins exceeded the separation capability of 2-DE. However, taking GRAVY and CAI values into account, there will be more proteins beyond the general 2-DE separation limits. For example, of the 554 proteins, 114 exhibited positive GRAVY scores. The 63 proteins with GRAVY scores >+0.4 are so hydrophobic that they are susceptible to precipitation during IEF and are rarely detected on 2-DE.23, 24 Moreover, bioinformatic analysis of the identified proteins using the hidden Markov model topology predictor TMHMM 2.0 indicates that 267 of the 666 proteins are integral membrane proteins. We focused on the 149 proteins (22% of all in silico) with at least two predicted transmembrane domains, which criterion was necessary to ensure that secreted proteins were not included.20 Figure 1 shows their distribution patterns. Evidently, our optimized methods provide a technology platform that is not biased against the protein class with high hydrophobicity and/or many transmembrane helices. Purified Cell Membranes. Alkaline extraction is commonly used to remove trapped or loosely bound proteins by the opening of vesicles into flat membrane sheets.14 Wu et al. obtained significant results using this method,15 but it is not absolute. Fisher et al. argued that membrane vesicle formation was not the reason for the inefficient removal of contaminating proteins, and obtained mainly soluble or peripheral proteins.25 The subcellular localization catalogs based on the PSORTb algorithm allowed us to better identify the Shigella membrane subproteome. First, all of 4443 annotated ORFs were subjected to the PSORTb v2.0 program to predict their cellular localization 1862
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Figure 2. Global view of identified CMPs in the two individual experiments. A. Venn diagram comparing set of proteins identified by MP_direct, MP_complex. and both experiment. B. Plot of CAI and pI vs molecular weight of identified CMPs.
(Table 1). The analysis revealed that 732 ORFs (16%) were predicted to encode integral cytoplasmic membrane proteins (CMPs), which were lower level than the average 20-30% of ORFs in the various genomes.26 On the other hand, of the 666 identified proteins, 159 (22% of all in silico) proteins were CMPs and 35 proteins (47% of all in silico) were OMPs. Figure 2 shows the overview of identified CMPs in the two individual experiments. Because the average coverage when PSORTb v2.0 is applied to Gram-negative proteome is 56.7%,18 there would be actually more CMPs identified in our experiments. In our MP_direct experiment, by directly digesting the isolated membrane with the nonspecific PK at high pH, a total of 331 proteins were identified. To be disappointed, there included only 54
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Shigella flexneri 2a Membrane Subproteome Table 2. Functional Categorization of S. flexneri Membrane Subproteomea COG
J K L D O M N (U) P T C G E F H I Q (V) R S
functional categories
ALL
ID
CMP
OMP
information storage and processing translation, ribosomal structure and biogenesis transcription DNA replication, recombination and repair cellular processes cell division and chromosome partitioning posttranslational modification, protein turnover, chaperones cell envelope biogenesis, outer membrane cell motility and secretion inorganic ion transport and metabolism signal transduction mechanisms metabolism energy production and conversion carbohydrate transport and metabolism amino acid transport and metabolism nucleotide transport and metabolism coenzyme metabolism lipid metabolism secondary metabolites biosynthesis, transport and catabolism poorly characterized general function prediction only function unknown anonymous NO related COG
1276 181 277 818 960 47 142 232 143 246 150 1446 265 356 381 81 147 96 120 791 478 313 559
112 63 24 25 236 16 32 79 43 43 23 269 75 59 57 13 18 21 26 93 60 33 55
1 0 0 1 81 4 6 18 16 24 13 80 22 24 18 1 1 3 11 28 22 6 3
0 0 0 0 29 0 1 20 5 3 0 2 0 0 0 0 1 1 0 3 1 2 3
a ALL indicates all annotated ORFs; ID, all proteins identified in our experiments; CMP, integral cytoplasmic membrane proteins identified in our experiments; OMP, outer membrane proteins identified in our experiments.
proteins (7.7% of all in silico) with more than one TMD and 57 CMPs (7.8% of all in silico). The reasonable assumption is that the presence of excess membrane-associated or -bound proteins interfered with the identification of integral membrane proteins, which are usually less abundant. Therefore, both sample pretreatment and analysis methods have to be optimized. In our MP_complex experiment, the pelleted membrane sheets were first prewashed with high salt and high pH buffer in the presence of DTT, to render them devoid of loosely bound cytosolic proteins and depleted of peripheral membrane proteins. After that the prewashed membrane sheets could be converted into membrane vesicles again in low salt and near neutral pH buffer. Through adjusting the pH value of digestion buffer, those peptide loops protruded on certain side of the lipid bilayer could be sequentially and selectively shaved by protease. It would induce more low-abundance hydrophobic or highly membrane-bound proteins to be identified at last. In fact, much more CMPs were identified (136 CMPs vs 57 CMPs) in MP_complex experiment. And we can quickly notice that the extremes of the Shigella integral membrane subproteome were well represented in our data. Integral membrane proteins with both acidic and basic pI or low and high abundance are represented in our data set. For example, the average GRAVY score of all 57 identified integral CMPs in the MP_direct experiment was 0.26. In contrast, the average GRAVY score of 136 integral CMPs in the MP_complex experiment was 0.38, indicating that a high number of very hydrophobic proteins were detectable by this approach. These strengthened our assumption above. Besides, to the best of our knowledge, that represents by far the largest validated set of integral membrane proteins in Shigella membrane proteomic studies. Noticeably, with the optimized method, 138 proteins identified in the MP_direct experiment were washed off and 335 new proteins were identified, including 102 integral CMPs and 12 OMPs. In particular, seven low-abundance proteins (CAI 0.7) (EF-Tu, GroEL, RecA, DnaK, and two ribosomal proteins S1 and L7/L12), though all localized to the cytoplasm calculated by PSORTb program, were found to be immunogenic in some other bacteria.35,36 Six OMPs, including AtpA, AtpD, ManX, TolC, YaeT, and Pic, all of which were first detected in S. flexneri by immunoproteomic analysis in Ying’s research,13 were also identified in our experiment. AtpA and AtpD are metabolic enzymes that could be particularly attractive antibiotic targets by virtue of their role in microbial physiology and their high conservation among various pathogens.37 Current antibiotic targets include only a few known metabolic enzymes, so several potential targets may be latent in our identified membrane protein data set (Supporting Information Table S1). More importantly, our proteomic profile identified apparatuses comprising multiple protein factors such as membrane porin, general secretory pathway, multidrug efflux pump, and bacterial secretion systems. Porins are an unusual class of membrane proteins that allow passive diffusion of solutes across the membrane.38 In our present study, many porins were identified, including classical nonspecific porins (OmpF and OmpC), the slow porins (OmpA)39 and other porins (NmpC, OmpW, and OmpX). Interestingly, OmpA (CAI ) 0.761), which has a high copy number, is highly conserved among the Enterobacteriaceae and could induce specific humoral and cytotoxic responses in the absence of adjuvant.40 Another identified porin protein, NmpC (pI 4.2, CAI ) 0.584), which could functionally replace the OmpF or OmpC porin, is quiescent in wild-type E. coli K-12 because of the insertion of the IS5 element.41 As far as we know, many of these porins have been detected at the protein level in S. flexneri for the first time, and could be valuable candidate vaccine targets. The type III secretion system (TTSS) is an essential basic virulence determinant in many Gram-negative pathogens. It usually comprises a TTS apparatus (TTSA) spanning the membrane, translocators and effectors, specific chaperones and transcription activators.42 Shigella uses a TTSS to invade colonic 1864
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epithelium cells and trigger apoptosis in macrophages. In our present study, many components of TTSS were identified (Supporting Information Table S1). During infection, Shigella uses effectors secreted via the TTSS to direct various cellular signaling pathways and modify the innate immune activation of the host. Actin-based motility and camouflage against autophagic recognition, initiated by IcsA and IcsB effector proteins respectively, are indispensable survival strategies.43 Efforts to identify the activity of novel bacterial effectors or new functions of known TTSS-secreted bacterial effectors will provide clues to understanding the pathogenesis of Shigella and other invasive microbes. Assembly of the supramolecular structure requires prior formation of its integral outer membrane secretin ring component, and this is mediated by MxiM, which is known as a pilot protein and is anchored to the inner leaflet of the outer membrane.44 MxiM could therefore be a new candidate target for blocking TTSS formation in Shigella and other pathogenic bacteria. These pre-synthesized Ipa effectors require Spa chaperones to maintain them in a secretion-component state. As far as we know, the Spa13 and Spa24 chaperones have been identified for the first time in Shigella. It will be interesting to explore their function further. Many of these effectors and chaperones, which are tightly bound with TTSA and thereby extracted together with the spanning membrane machinery, play an important role in initiating the function of TTSS. The importance of the membrane-associated proteins that we identified should not be underestimated.
Conclusions We have provided the most extensive survey and detailed reference map of the Shigella membrane subproteome to date, combing a sequential protease digestion strategy with highthroughput 2-D LC-MS/MS analysis. Our results also provide an important basis for future functional studies of membrane proteins. These integral and lipid-linked membrane proteins may be key molecules in designing strategies against bacterial infection.
Acknowledgment. This work is supported by the grants from the National Basic Research Priorities Program (2005CB522904) and the High Technology Research and development Program (2001AA223011) from the Ministry of Science and Technology of China. Supporting Information Available: Distribution patterns and pI of S. flexneri proteins (Figure S1), list of S. flexneri 2a proteins identified in 2D LC-MS/MS analysis (Table S1). This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Girard, M. P.; Steele, D.; Chaignat, C. L.; Kieny, M. P. A review of vaccine research and development: human enteric infections. Vaccine 2006, 24, 2732-2750. (2) Kotloff, K. L.; Winickoff, J. P.; Ivanoff, B.; Clemens, J. D.; Swerdlow, D. L.; Sansonetti, P. J.; Adak, G. K.; Levine, M. M. Global burden of Shigella infections: implications for vaccine development and implementation of control strategies. Bull. World Health Organ. 1999, 77, 651-666. (3) Drews, J. Drug discovery: a historical perspective. Science 2000, 287, 1960-1964. (4) Santoni, V.; Molloy, M.; Rabilloud, T. Membrane proteins and proteomics: un amour impossible? Electrophoresis 2000, 21, 1054-1070.
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PR0601741
Journal of Proteome Research • Vol. 5, No. 8, 2006 1865
