Staphylococcus aureus - American Chemical Society

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Staphylococcus aureus Surface Proteins Involved in Adaptation to Oxacillin Identified Using a Novel Cell Shaving Approach Nestor Solis,† Benjamin L. Parker,‡,⊥ Stephen M. Kwong,§ Gareth Robinson,∥ Neville Firth,§ and Stuart J. Cordwell*,†,‡ †

School of Molecular Bioscience, ‡Discipline of Pathology, School of Medical Sciences, and §School of Biological Sciences, The University of Sydney, New South Wales 2006, Australia ∥ Snepo Research, 2/5-21 Mary Street, Surry Hills, New South Wales 2010, Australia S Supporting Information *

ABSTRACT: Staphylococcus aureus is a Gram-positive pathogen responsible for a variety of infections, and some strains are resistant to virtually all classes of antibiotics. Cell shaving proteomics using a novel probability scoring algorithm to compare the surfaceomes of the methicillin-resistant, laboratory-adapted S. aureus COL strain with a COL strain in vitro adapted to high levels of oxacillin (APT). APT displayed altered cell morphology compared with COL and increased aggregation in biofilm assays. Increased resistance to β-lactam antibiotics was observed, but adaptation to oxacillin did not confer multidrug resistance. Analysis of the S. aureus COL and APT surfaceomes identified 150 proteins at a threshold determined by the scoring algorithm. Proteins unique to APT included the LytR-CpsA-Psr (LCP) domain-containing MsrR and SACOL2302. Quantitative RT-PCR showed increased expression of sacol2302 in APT grown with oxacillin (>6-fold compared with COL). Overexpression of sacol2302 in COL to levels consistent with APT (+ oxacillin) did not influence biofilm formation or β-lactam resistance. Proteomics using iTRAQ and LC−MS/MS identified 1323 proteins (∼50% of the theoretical S. aureus proteome), and cluster analysis demonstrated elevated APT abundances of LCP proteins, capsule and peptidoglycan biosynthesis proteins, and proteins involved in wall remodelling. Adaptation to oxacillin also induced urease proteins, which maintained culture pH compared to COL. These results show that S. aureus modifies surface architecture in response to antibiotic adaptation. KEYWORDS: Surfaceome, cell shaving proteomics, LytR-CpsA-Psr (LCP) domain, mass spectrometry, antibiotic resistance, Staphylococcus aureus

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proteins.11−13 The predominant class of cell wall-associated proteins is the LPXTG family, whose members are covalently anchored to the membrane by a sortase-dependent mechanism.14 These proteins contain both an N- and C-terminal (LPXTG) signal that allows membrane translocation through the general secretory (Sec) pathway and attachment to the peptidoglycan lipid precursor.15,16 Major LPXTG proteins include immunoglobulin-binding protein A (Spa), the Staphylococcus aureus surface protein family (SasBCDFGH15,17−20), and the iron-regulated surface determinant family (IsdABCH21−25). A subclass of the LPXTG family is the serineaspartate (SD) repeat-containing ECM binding proteins that include methicillin-resistance protein Pls,26,27 fibrinogen-binding clumping factors A and B (CflAB28−31), Ebh,32,33 collagenbinding protein (Cna), bone-sialoprotein-binding protein (Bbp), and fibronectin-binding proteins FnbAB.34−36 The cell wall-associated LytR-CpsA-Psr (LCP) domain-containing proteins have been associated with virulence, antibiotic

INTRODUCTION Staphylococcus aureus is responsible for a variety of diseases in humans that range from mild skin conditions to systemic failures, including bacteremia and infective endocarditis.1 Because a major route for infection is via nosocomial acquisition, it is disturbing that strains with resistance to virtually all known classes of antibiotics are now widely distributed.2−5 Several S. aureus genomes have been sequenced, including the methicillin-resistant (MRSA) COL strain,6,7 which contains ∼2700 genes. Methicillin resistance is largely mediated by the presence of the staphylococcal chromosomal cassette (SCC) mec element, which contains the mecA gene that encodes penicillin-binding protein 2′ (PBP2′ or PBP2A).8 S. aureus produces a range of virulence-associated proteins, including toxins, lipases, and proteases.1,9,10 The molecular effectors responsible for the establishment of infection are biopolymers located on the cell surface, including proteins, polysaccharides. and lipoteichoic acid. Cell wall adhesins or microbial surface components recognizing adherence matrix molecules (MSCRAMMs) are a subset of proteins that enable colonization via interactions with extracellular matrix (ECM) © XXXX American Chemical Society

Received: January 30, 2014

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dx.doi.org/10.1021/pr500107p | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

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16 h at 37 °C with shaking under aerobic conditions. An aliquot was diluted to an OD600 ∼ 0.1 in TSB containing 4% NaCl (mimicking human skin conditions) and 4 mg/L oxacillin (Sigma-Aldrich, St. Louis, MO) and grown at 37 °C with shaking. Cells were grown to the end of exponential phase before an aliquot was taken and diluted again to OD600 ∼ 0.1 in TSB/NaCl, with this passage containing 8 mg/L oxacillin. This process was repeated with doubled concentrations of oxacillin under identical conditions until the final concentration of oxacillin in the media was 1600 mg/L. Cells from this oxacillinadapted COL strain (referred to as APT) were collected by centrifugation. COL was inoculated directly in TSB/NaCl + 1600 mg/L oxacillin (TSB/NaCl + Oxa) and did not grow.

resistance, autolysis, biofilm production, and cell wall damage and repair, potentially via teichoic acid biosynthesis and incorporation into peptidoglycan.37,38 S. aureus encodes three LCP proteins: MsrR (SACOL1398), which appears to have the major role of the three in septation, antibiotic resistance, and virulence, with SACOL1065 (SA0908) being associated with regulation of autolysis and SACOL2302 (SA2103) enhancing the properties conferred by the other two LCP proteins.39 Additional surface-associated proteins are classified as cytoplasmic membrane proteins lipoproteins and noncovalent cell wall proteins, including the LysM domain family40 (e.g., murein hydrolases Sle1 and LytN, elastin-binding protein EbpS, and autolysin Aaa41−44). S. aureus virulence also relies on resistance against oxidative stress and an ability to acquire trace nutrients, particularly iron, from the host environment.45 Attempts to characterize the surface proteome of S. aureus have concentrated largely on cell shaving proteomics,46−55 where surface-exposed peptide epitopes are released by intact cell protease treatment combined with analysis by liquid chromatography coupled to tandem mass spectrometry (LC− MS/MS). The significant abundance of intracellular proteins can, however, complicate the identification of surface-exposed molecules. A variety of strategies that enrich for hydrophobic species or peptidoglycan have been employed to reduce false positives (reviewed in ref 56); however, contamination by intracellular species is prevalent. Cell shaving is further complicated by moonlighting proteins,57,58 which are those that are generally considered intracellular (e.g., lacking any defined signal sequence) yet are consistently identified in surface studies. Such proteins must have nonclassical secretion mechanisms or can rebound to the surface of the organism following the lysis of other cells (recycling theory). Moonlighting proteins may perform different functions when they are surface-associated (e.g., enolase and glyceraldehyde-3-phosphate dehydrogenase from Streptococcus pneumoniae enable adherence to host cells59,60) and/or provide new vaccine targets.61 The use of laboratory strains for characterization of virulence factors has been challenged because in vitro passage can attenuate the pathogenic phenotype. We performed in vitro adaptation62 of the methicillin-resistant (yet laboratory adapted) S. aureus COL strain to increasingly higher levels of oxacillin under osmotic stress.62 The COL and oxacillinadapted (APT) strains were compared using cell shaving proteomics employing a novel statistical scoring method based on the principles of hypergeometric distributions and Bayesian inference. Surface-exposed proteins identified from APT alone included the LCP protein SACOL2302. Genetic overexpression of sacol2302 in COL did not confer APT phenotypes of increased biofilm formation or antibiotic resistance. Quantitative iTRAQ proteomics showed that adaptation to oxacillin involved cell wall remodelling, capsule production, and increased urease expression, which were consistent with APT morphology and biofilm production.

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Scanning Electron Microscopy (SEM)

S. aureus COL and APT were grown in 20 mL cultures (TSB and TSB/NaCl + Oxa) and washed extensively with PBS (pH 7.4). Cells were resuspended in PBS and adhered onto 1% polyethyleneimine (PEI)-coated plastic slides for 20 min. Excess cells were removed, and slides were fixed with 2.5% glutaraldehyde in PBS for 20 min at room temperature. Slides were washed three times with PBS for 5 min each. One milliliter of 1% OsO4 in PBS was added to each slide and incubated for 30 min at room temperature. Excess OsO4 was removed, and slides were washed three times for 5 min each with deionized water to remove trace osmium. Dehydration of samples was performed by rinses in ethanol for 5 min each as follows: two washes with 30% ethanol, two washes with 50% ethanol, two washes with 70% ethanol, two washes with 95% ethanol, and two washes with 100% ethanol. Excess 100% ethanol was removed, and 0.5 mL of bis(trimethylsilyl)amine (HMDS) was added to each slide for 3 min. Samples were left in a desiccator overnight to remove HMDS fumes. Slides were mounted on stubs, sputter-coated with gold/platinum, and examined by SEM using a Hitachi S4500 FEG-SEM equipped with a Bruker X-Flash 4010 SDD EDS detector, and digital images were acquired using Esprit EDS software. All microscopy was performed at the Australian Microscopy and Microanalysis Research Facility (AMMRF). Cell Shaving of S. aureus Utilizing Trypsin

Surface-exposed peptides of S. aureus were enriched as described previously, with modifications.51 Cells were harvested at midexponential phase by centrifugation at 1500g for 15 min at 4 °C. Cell pellets were washed three times with ice-cold wash buffer (20 mM Tris-HCl and 150 mM NaCl, pH 7.6) followed by resuspension in 4 mL of shaving buffer (20 mM Tris-HCl, 150 mM NaCl, 10 mM CaCl2, and 1 M D-arabinose, pH 7.6).56,63 All experiments were performed in biological duplicates. A false positive control strategy was implemented by splitting the suspension in two equal aliquots as per ref 51. One aliquot was digested with 10 μg of sequencing-grade porcine trypsin (Promega, Madison, WI) for 15 min at 37 °C with gentle inversion, whereas the parallel batch was incubated under identical conditions without trypsin (trypsin treatment of the supernatants was performed after removal of cells by centrifugation). Cells were removed by centrifugation at 1000g for 15 min at 4 °C, and supernatants were dialyzed against ultrapure water at 4 °C using a mini-dialysis kit with a 1 kDa cutoff (GE LifeSciences, Uppsala, Sweden). Peptides were lyophilized using a SpeedVac vacuum concentrator and desalted using home-packed R2 columns (POROS, Applied Biosystems, Foster City, CA) prior to LC−MS/MS. R2 columns were activated in 100% acetonitrile (CH3CN),

MATERIALS AND METHODS

Bacterial Strains, Growth, and Adaptation to Oxacillin

Methicillin-resistant S. aureus COL (COL) was maintained in tryptic soy broth (TSB) for all experiments. For in vitro adaptation to high concentrations of oxacillin, we employed the method of Martins et al.62 A single colony from strain COL was inoculated from a TSB agar plate into TSB and incubated for B



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μg), tobramycin (TOB, 10 μg), trimethoprim (W, 5 μg), neomycin (N, 30 μg), ceftazidime (CAZ, 30 μg), florfenicol (FFC, 30 μg), and compound sulfonamides (S3, 300 μg).

equilibrated twice with 100 μL of 0.1% trifluoroacetic acid (TFA), loaded with 100 μL of sample (resuspended in 0.1% TFA), washed twice with 100 μL of 0.1% TFA, and eluted with 100 μL of 70% CH3CN/0.1% TFA. Samples were then lyophilized and kept at −20 °C until analysis by LC−MS/MS.

Generation of Altered pH by S. aureus

S. aureus COL and APT were compared for their ability to control pH. Strains were grown overnight from single colonies into TSB starter cultures and inoculated to an OD600 ∼ 0.1 in their test media. A 1 mL aliquot was taken each hour for a measurement of optical density and pH measurement as cultures were grown at 37 °C with shaking. Measurements of culture pH were compared to the rate of bacterial growth. All biological replicates (n = 4) contained technical replicates (n = 3), and statistical analyses were performed in GraphPad Prism with one-way ANOVA and post-testing.

Construction of S. aureus COL2302+

Construction of the overexpressing strain was performed as described in Kwong et al.64 sacol2302 was PCR-amplified from S. aureus COL genomic DNA using the primers COL2302-F (5′-GGA GCT CTA AGT AAT AAA GCA TGT C-3′) and COL2302-R (5′-GGA GCT CAA AGT GTT ATC ACC TTC3′) and cloned into pSK5487 via the SacI site. Sequencing was used to confirm the orientation and integrity of the cloned fragment. Plasmid selection in Escherichia coli was performed using 100 μg/mL ampicillin and in S. aureus, 10 μg/mL chloramphenicol. Overexpression was also validated by RTPCR using a Qiagen RNA extraction kit according to the manufacturer’s protocols for Gram-positive organisms. Reverse transcription was performed using SYBR Green with a Qiagen kit according to the manufacturer’s protocols. Primers for RTPCR were designed against 16S RNA and sacol2302 (SigmaAldrich). sacol2302 primers were ORF2302-QF (5′-TCG GCG GTG TTG ATG TAG TA-3′) and ORF2302-QR (5′-GAT GAT GGG CTT GCA ATC TT-3′). 16S RNA primers were 16S-QF (5′-AAG CCG GTG GAG TAA CCT TT-3′) and 16S-QR (5′-ACC TTC CGA TAC GGC TAC CT-3′).

Quantitative Proteomics by iTRAQ Labeling

S. aureus COL and APT were grown to midlog phase at 37 °C with shaking. Cells were collected at 6000g for 15 min at 4 °C. Pellets were washed twice with ice-cold PBS and collected by centrifugation. Cells were lyophilized overnight and kept at −80 °C until required. Twenty milligrams of dry weight cells was resuspended in 1% SDS containing 100 mM dithiothreitol (DTT), and the suspension was tip-probe sonicated for 1 min with 1 min rest periods on ice. One microliter of benzonase (Sigma-Aldrich) was added to the lysate for 20 min at room temperature. Cell debris was removed by centrifugation for 15 min at 4 °C at 16 000g. Protein supernatants were reduced with 20 mM DTT for 60 min at 37 °C followed by alkylation with iodoacetamide (IAA; 10 mM) for 30 min at room temperature in the dark. One-hundred microliters of sample was mixed with ice-cold water/methanol/chloroform in a ratio of 3:4:1 to precipitate proteins. Proteins were resuspended in 6 M urea, 2 M thiourea, and 500 mM triethylammoniumbicarbonate (TEAB) and quantified using the Qubit protocol (Life Technologies, Carlsbad, CA). Samples were next diluted 10fold and digested with trypsin in a ratio of 1:50 enzyme/sample for 16 h at room temperature. Lipids were precipitated using formic acid (FA) to a final concentration of 2% for 15 min in the cold, and lipid pellets were removed by centrifugation at 16 000g for 15 min at 4 °C. Peptide purification was performed using hydrophilic lipophilic balance (HLB) cartridges 60 cm3 (Waters Corp., Bedford, MA) after supernatants were acidified with TFA to a final 0.1%. Cartridges were activated with 100% methanol (1 volume) followed by 100% CH3CN (1 volume). The cartridges were equilibrated with 0.1% TFA (2 volumes) and loaded with peptide sample. Sample was reapplied three times to ensure maximum binding, washed with 0.1% TFA, and finally eluted with 70% CH 3CN/0.1% TFA (1 volume) with three applications to ensure maximum removal. Samples were then lyophilized. Peptides were resuspended in 50 mM TEAB, and an aliquot was quantified using Qubit. Labeling of 150 μg of sample per channel was performed as per the manufacturer’s protocol. Samples were combined and diluted to 1 mL in a final concentration of 0.1% of TFA and purified by HLB as described above. Labeled samples were lyophilized and stored at −80 °C until required. Samples were fractionated by hydrophilic interaction liquid chromatography (HILIC) using an Agilent 1200 chromatography system. Fractionation was performed using a 20 cm, 320 μm i.d. column packed with TSK-Amide 80 HILIC resin, 3 μm particle size. Samples were resuspended in 100% buffer B (90% CH3CN/0.1% TFA) and separated using a linear gradient as

Biofilm/Cell Aggregation Assays

Extracellular aggregation was evaluated by a modified crystal violet biofilm assay. Wells (96-well plate format) were inoculated with 200 μL of overnight culture and allowed to grow aerobically without shaking for 48 h. Optical density (OD600) was acquired to determine growth. The plate was then rinsed three times with PBS, and remaining aggregates were fixed by incubating the plate for 1.5 h at 60 °C. Staining was performed with 150 μL of 0.025% crystal violet for 20 min. Excess stain was removed with water, and the contents of each well were resuspended with 150 μL of 100% ethanol. The absorbance at 600 nm was acquired and indicated the amount of extracellular material adherent to each well. A ratio of the crystal violet reading to the final growth reading was calculated. All four biological replicates were analyzed in technical duplicate (n = 8), and statistical analysis was performed using GraphPad Prism with one-way ANOVA and post-testing. Calibrated Dichotomous Sensitivity (CDS) Disc Diffusion Assays

To assay the difference in antibiotic resistance profiles between COL, APT, and COL2302+, CDS disc diffusion assays were performed. For each plate, 20 mL of Sensitest Agar (Oxoid, Basingstoke, UK) was poured and allowed to dry briefly. Three colonies from each strain were inoculated into 5 mL of sterile PBS and used to flood three plates to create an even bacterial lawn. After drying, each plate was stamped with six antibiotic discs (Oxoid). A total of 18 antibiotics were tested per strain in technical triplicate and biological duplicate. The plates were incubated at 37 °C for 16 h, and zones of inhibition were measured. Antibiotics tested were amikacin (AK, 30 μg), ampicillin (AMP, 10 μg), chloramphenicol (C, 30 μg), ciprofloxacin (CIP, 5 μg), gentamicin (CN, 10 μg), kanamycin (K, 30 μg), nalidixic acid (NA, 30 μg), netilmicin (NET, 30 μg), spectinomycin (SH, 100 μg), streptomycin (S, 10 μg), tetracycline (TE, 30 μg), ticarcillin/clavulanic acid (TIM, 75/10 C



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N-terminal pyroglutamation. Result files were imported into Scaffold v3 (Proteome Software, Portland, OR) and searched again with the embedded X!Tandem software utilizing identical parameters. Peptide spectral matches were validated using PeptideProphet and ProteinProphet with a minimum probability of 90% confidence (low-probability peptides were manually verified) at the peptide level and 99% at the protein level, with at least one peptide per protein (those with one peptide were manually validated). For iTRAQ experiments, RAW files were directly imported into Proteome Discoverer v1.3 (Thermo Scientific) and searched with the in-house Mascot server using the following parameters: MS tolerance of 10 ppm; MS/MS tolerance of 0.02 Da; HCD fragmentation; enzyme: trypsin; and variable modifications of methionine (oxidation), cysteine (carbamidomethylation), and 4-plex iTRAQ tags on N-termini and lysine (K). Peptide spectral matches were then filtered only to highquality, unambiguous matches, with a minimum of two peptides per protein in each individual experiment and with a protein false discovery rate (FDR) to a maximum of 1%. Quantification was performed by the separate module in Proteome Discoverer for iTRAQ tags using default parameters. For each experiment, the median value for each peptide spectral match log ratio was computed to obtain a peptide sequence log ratio. Following this, all peptide sequence log ratios belonging to a protein were computed into a final protein log ratio as a median. Biological triplicate iTRAQ experimental log ratios were combined to a final protein log ratio by means of a weighted average. Every protein log ratio in a particular experiment was multiplied by the number of peptides for that protein. Then, for all experiments, these values were added and divided by the total number of peptides for that protein observed in each experiment, resulting in a final protein log ratio that reflects the weighted average of all three experiments. This can be summarized as follows

follows: sample loading for 10 min with 100% buffer B at 12 μL/min, sample elution from 100% buffer B to 60% buffer B for 25 min at 6 μL/min, and ending in a column re-equilibration step for 20 min. Peptide elution was monitored by a multiwavelength detector at 280 ± 4, 254 ± 4, 260 ± 4, and 230 ± 4 nm. All samples were lyophilized and stored at −20 °C until mass spectrometric analysis. All iTRAQ experiments were performed in biological triplicate. LC−MS/MS of Peptides from Cell Shaving

Peptides were resuspended in 0.1% FA, separated on a Dionex Ultimate 3000, eluted, and ionized directly into a Thermo LTQ Orbitrap Velos mass spectrometer (Thermo Scientific, San Jose, CA). LC was performed using a two-column setup. Peptides were loaded onto a trap column (0.5 cm, 150 μm i.d., C18) in 5% buffer B (90% CH3CN/0.1% FA) for 8 min at a flow rate of 5 μL/min. Following valve switching, peptides were eluted onto an analytical column (15 cm, 75 μm i.d., C18Aq Reprosil) and separated over a linear gradient of 5% buffer B to 60% buffer B over 90 min at a flow rate of 300 nL/min. Eluted peptides were sprayed by electrospray ionization (ESI) directly into the mass spectrometer at 200 °C. The top 20 most abundant ions were selected for MS/MS by collision-induced dissociation (CID) using the following parameters: full-scan MS in the orbital trap between 350 and 2000 m/z at 60 000 resolution, MS/MS events in the linear ion trap using a normalized collision energy of 35, isolation width of 3.0 amu, and minimum charge state of +2. All samples were acquired in triplicate injections, and data were written to .RAW files and later converted to .mgf format using Mascot Distiller with default parameters. LC−MS/MS of iTRAQ-Labeled Peptides

Peptides were analyzed by an Ultimate 3000 coupled to an LTQ Orbitrap Velos as described above with modifications to the MS/MS data acquisition. The top eight most abundant ions were selected in full scan (350 − 2000 m/z) at 60 000 resolution and fragmented using higher energy collisional dissociation (HCD) in a dedicated HCD cell followed by scanning in the orbital trap at 8000 resolution (110−2000 m/ z). iTRAQ-labeled peptides were also resolved on a onecolumn system (3 μm particle size, 50 cm × 50 μm i.d., C18) utilizing an Easy-nLC-1000 UPLC (Thermo Scientific) with a linear gradient of 0−40% buffer B (80% CH3CN/0.1% FA) at 250 nL/min coupled directly to an LTQ Orbitrap (Thermo Scientific) over 150 min. The mass spectrometer was set up in tandem between CID (normalized collision energy 35) and HCD (normalized collision energy 55) using a top seven method in positive ion mode with full-scan MS ranging between 400 and 1800 m/z at 30 000 resolution and at 7500 resolution for HCD scans.

⎛ ∑r ni × q ⎞ i i⎟ log 2(final protein ratio) = log 2⎜⎜ r ⎟ ∑ n ⎝ ⎠ i i

(1)

where i is the experiment number, ni is the number of peptides for a protein in experiment i, qi is the protein ratio for a protein in experiment i, and r is the last experiment. To establish thresholds, all proteins were sorted by log ratio, and their ranks and percentiles calculated and converted to zscores. These rank-based zscores were plotted against their respective log ratios, and thresholds were drawn where the function stopped behaving in a linear fashion (typically close to z ∼ 2). Proteins deemed to be changing were analyzed by STRING v9.05 to establish their potential interactions and functions.65

Database Searching and Analysis

Hypergeometric Distribution and Bayesian Inference Statistical Analysis of Cell Shaving Data

For cell shaving experiments, data files were searched with an in-house Mascot Server (Matrix Science, London, UK) using the S. aureus COL database (SACOL) from the High-quality Annotated and Manual Annotation of Proteins server (HAMAP) concatenated with a reverse database. Parameters for searching were MS tolerance of 3 Da; MS/MS tolerance of 0.8 Da; enzyme: semitrypsin (to capture N- or C-terminal exposed peptides); up to three missed cleavages (because of short duration of trypsin incubation in cell shaving, the digestion may not be complete); and variable modifications of methionine (oxidation), cysteine (carbamidomethylation), and

Once all identifications for the cell shaved and false positive control were obtained, a scoring system was devised to calculate the probabilities of proteins being surface-exposed. First, all identified proteins had their localizations predicted according to LocateP,66 SurfG+, 67 and PSORTb 3.0;68 this is herein referred to as ppredicted. These probabilities were given a maximum value of 0.9, a minimum value of 0.1, and a value of 0.5 for unknown localization. Probabilities for each protein identified by proteomic analysis were performed by comparing peptide numbers from the cell shaved data (ns) versus the false positive D



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larger cell size compared with COL, and this effect was more pronounced when APT was grown in oxacillin. APT also showed evidence of increased extracellular material and aggregation. To examine whether the extracellular material contributed to enhanced biofilm formation, we performed crystal violet biofilm assays in 96−well plates, using the biofilm-forming Staphylococcus epidermidis RP62A strain as a positive control (Figure 2). These data were consistent with our SEM observations and

control (nc). We proposed that truly surface-exposed proteins would be over-represented by peptides identified in the shaved fraction compared to the control,51 and as such, the probability of a protein being surface-exposed is higher if there is a greater representation of peptides in the cell shaving data. This was modeled with a discrete probability model using sums of combinations by comparing shaved peptides against control peptides, namely, a hypergeometric distribution. The overall sum of these probabilities is termed pexperimental. The formula for each individual protein is summarized as follows m

pexperimental = 1 −

∑ k= m 2

⎛ nc ⎞⎛ ns ⎞ ⎜ ⎟⎜ ⎟ ⎝ k ⎠⎝ m − k ⎠ ⎛nT ⎞ ⎜ ⎟ ⎝m⎠

(2)

where nc is the number of control peptides, ns is the number of shaved peptides, nT = nc + ns, and m = 0.4nT (to the closest higher integer). If, however, there were insufficient peptides for calculations, for example, one peptide derived from the cell shaved and zero from the control, then probability was assigned to be 0.9, or 0.1 if the inverse situation was true. When the number of peptides was equal between both, then the pexperimental value was 0.5. The experimental probability based on the proteomic data was then combined with the predicted probability based on sequence analysis in equal weighting using Bayes’ Theorem to obtain a final adjusted probability (padjusted) that reflects the likelihood of a particular protein being surface-exposed and accounts for localization conflicts. Using Bayes’ Theorem, it is found that

Figure 2. Crystal violet biofilm assay shows S. aureus APT increases production of extracellular material. The ratio of absorbance between crystal violet (adherent material) and optical density (growth amount) shows that APT grown in TSB supplemented with oxacillin has a higher degree of extracellular aggregation compared to the ica-negative strain, COL. RP62A is a S. epidermidis positive control for biofilm formation (error bars = SEM).

padjusted = (pexperimental )(ppredicted )

showed that APT grown in TSB/NaCl + Oxa was capable of enhanced biofilm formation compared with COL. APT grown without oxacillin, however, demonstrated lower levels of biofilm formation, consistent with those observed in COL. Biofilm formation in S. aureus has generally been attributed to the ica operon;69 however, S. aureus COL contains a mutation in icaC, rendering it effectively biofilm negative. Sequencing of the icaC gene in COL and APT showed that both retain the frameshift mutation at position 910 (Supporting Information Figure S1), which suggests the extracellular aggregation observed in APT and induced by growth in high levels of oxacillin occurs via an ica-independent mechanism.

(pexperimental )(ppredicted ) + (1 − pexperimental )(1 − ppredicted )

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RESULTS

Adaptation to Oxacillin Induces Surface Changes and Cellular Aggregation

S. aureus COL was adapted to gradual increments of oxacillin to a maximum of 1600 mg/L, which is well beyond the natural capability of oxacillin resistance in this organism. We first compared the cell morphologies of COL and the oxacillinadapted APT strain labeled with OsO4 using SEM (Figure 1). APT grown in TSB displayed a different surface structure and

Development of a Scoring Approach for Surface-Exposed Proteins Based on Cell Shaving Using a False Positive Control

We employed a hypergeometric distribution based on the principle that the abundance of peptides derived from truly surface-exposed proteins in cell shaved fractions will be greater than that found in the false positive control. The formula in eq 2 calculates the probability of the protein being surface-exposed on the basis of the proteomic data. The equation assumes that if the number of peptides identified by cell shaving (ns) is equal to (or less than) that in the false positive control (nc) then the protein is not likely to be truly surface-exposed. If a protein has an ns ≫ nc, then it is far more likely that the protein is surfaceexposed. This was modeled such that 40% of the total number of peptides for a protein (that is, 0.4(nc + ns)) would be the number tested for each probability. This is an arbitrary value

Figure 1. S. aureus adaptation to oxacillin alters cell morphology and increases extracellular material. Scanning electron microscopy (SEM) of S. aureus COL and APT as well as APT grown in TSB supplemented with 1600 mg/L oxacillin. E



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Table 1. Number of Proteins and Peptides Identified by Cell Shaving of S. aureus COL and APT in TSB and APT in TSB/NaCl + Oxa (Shave) Using a False Positive Control (Control)a COL proteins

peptides

PSE cytoplasmic unknown PSE cytoplasmic unknown

APT/TSB

APT/OXA

control

shave

control

shave

control

shave

58 185 25 1042 1243 203

74 193 28 1449 1167 181

34 25 3 499 75 6

40 8 2 714 17 3

12 37 5 97 101 16

24 42 7 220 126 23

a

Subcellular localizations were predicted using LocateP, PSORTb, and SurfG+. PSE, predicted surface exposed; unknown, localization algorithms were inconclusive.

three in the shaved group are not as confidently assigned a probability compared to a protein with 10 and 15 peptides in each group even though the comparative ratio remains the same. The ability to identify the majority of peptide sequences in a single fraction by LC−MS/MS is paramount. We utilized high-speed CID in an LTQ-Orbitrap Velos to enable the identification of the majority of peptide species in a single LC run. The relatively low complexity of supernatants obtained from cell shaving and the false positive control allows the confident identification of a significant proportion of peptide sequences, which generates sufficient coverage required for the calculations employed in the hypergeometric model. Localization predictions can also be used to adjust the probabilities. In this study, localizations were predicted using three algorithms: PSORTb, LocateP, and SurfG+. Probabilities were given as 0.9 for surface, 0.5 for unknown (or conflicting between software), and 0.1 for cytoplasmic. Utilizing simple Bayesian inference (note that predicted and proteomic information were given equal weighting), a final adjusted probability can be calculated from the two sets of data, and a threshold can be devised to separate low-scoring from highscoring proteins. This threshold can be applied at the discretion of the investigator according both to the organism in question and the quality of the cell shaving data.

and was chosen on the basis of our observations (number of peptides from known surface-exposed proteins in cell shaved and false positive fractions) and to generate a wide enough distribution of scores (between 0 and 1) to apply a meaningful final threshold to the complete data set. This is best represented with an example, as follows: a protein has 20 peptides identified by cell shaving and 10 peptides in the false positive control (ns = 20 and nc = 10) and hence nT = 30. The first question is to determine what the probability would be that from 40% of the total peptides (0.4 × 30 = 12) half derive from the shaved and half from the false positive (that is, the protein is as likely to be surface-exposed as not). This equates to the probability of selecting six peptides from the shaved list and six from the control out of the 30 in total. This is a combinatorial problem where the selection of six peptides from the 20 in the shaved set is multiplied by the ways of selecting six peptides from the 10 in the control, which is then divided by the total ways of selection, or 12 peptides from the total of 30 ⎛ 20 ⎞⎛10 ⎞ ⎜ ⎟⎜ ⎟ ⎝ 6 ⎠⎝ 6 ⎠ = 0.094107 ⎛ 30 ⎞ ⎜ ⎟ ⎝12 ⎠

This means that there is a low chance of selecting equal numbers of peptides from the shaved and control fractions (as would be expected for a ratio of 2:1). Next, the case for selecting seven from the shaved and five from the control is calculated. This is then iterated until the case of 12 peptides being selected from the shaved and 0 from the control is calculated. Finally, all of these probabilities are summed to generate the final probability (in the example, 0.8190). However, caveats exist where 40% of the total is not an integer and when the distribution is symmetrical. This results in a difficult selection to identify where half of the total number of peptides begins. Consequently, 40% of the total was always rounded up or given +1, and symmetrical distributions were always commenced on the second equal number (Supporting Information Figure S2). As can be seen, selection commenced such that the distribution, if symmetrical, was always on the second half. In practical terms, this meant that in the previous example the first test would not be at ns = 6 and nc = 6 but rather at ns = 7 and nc = 5. Of course, this skews the probability to be higher for proteins that have substantially higher number of peptides for ns than nc; however, this still remains consistent with the central assumption regarding cell shaving data. Furthermore, the fewer number of peptides identified for a particular protein, the less robust the probability is. This means that proteins with cases such as two peptides in the control and

Cell Shaving Proteomics of S. aureus COL and APT Reveals Different Surface-Exposed Epitopes

S. aureus COL and APT (both grown in TSB) and APT grown in TSB/NaCl + Oxa were subjected to intact cell tryptic shaving and a false positive control strategy,51 and the released peptides were analyzed by LC−MS/MS. A total of 28 661 MS/ MS spectra representing 316 unique proteins were identified (Table 1 and Supporting Information Data S1) across all experiments. Despite identical numbers of starting cells, trypsin digestion strategies, and LC−MS conditions, substantially more identifications were achieved at both the protein and peptide levels for S. aureus COL than for APT in either TSB alone or in the presence of oxacillin. Increased identifications for COL suggest that the APT strain undergoes less cell lysis during the false positive control strategy and/or that lower numbers of recovered shaved peptides may result from reduced protein surface-exposure. Both may occur because of increased wall polysaccharide or peptidoglycan, consistent with the morphological appearance of the APT cells (Figure 1). The identifications shown in Table 1 reflect raw data for each peptide test set, and no subtraction or statistical probabilities were calculated. For each individual protein, we next calculated a probability score based on the number of peptides identified in the false positive control (control) and cell shaved (shave) F



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Figure 3. Cell shaving using a false positive control and probability-based scoring algorithm in S. aureus COL and APT as well as APT grown in TSB supplemented with oxacillin. Following calculation of probabilities, it can be seen that COL displays a large number of proteins predicted to be cytoplasmic, with most proteins clustered near p ∼ 0.65. Because of the nature of the calculation, this is the median of the data set and was selected for filtering. PSE, predicted to be surface-exposed by LocateP, SurfG+, and PSORTb.

Figure 4. Application of a probability threshold eliminates proteins with low scores and yields a higher confidence data set. (A) Number of peptides derived from proteins in the predicted classes is displayed and shows that the vast majority of the epitopes are derived from PSE proteins. It can also be seen that at p < ∼0.7 for COL and APT (supplemented with oxacillin) there is an increase in the number of peptides derived from proteins predicted to be cytoplasmic, and this established the threshold. (B) Final confidently identified proteins and peptides prior to and postapplication of the filtering threshold.

G



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Table 2. Number of Proteins and Peptides Identified by Cell Shaving of S. aureus COL and APT in TSB and APT in TSB/NaCl + Oxa (Shave) Using a False Positive Control (Control) after Their Respective Probability Threshold Filters Were Applieda COL proteins

peptides

PSE cytoplasmic unknown PSE cytoplasmic unknown

APT/TSB

APT/OXA

control

shave

control

shave

control

shave

34 50 9 650 260 78

50 74 11 1111 456 97

24 14 1 262 34 1

10 8 2 714 17 3

9 9 2 84 22 5

21 26 5 202 66 17

a

Subcellular localizations were predicted using LocateP, PSORTb, and SurfG+. PSE, predicted surface exposed; unknown, localization algorithms were inconclusive.

data sets, and this was adjusted according to predicted localization according to the LocateP, PSORTb, and SurfG+ (Figure 3). All conditions show a distribution that concentrates at high probabilities (p ∼ 0.95), low probability (p ∼ 0.32), and proteins with midvalue probabilities (p ∼ 0.70). A threshold was next employed based on a sliding scale of probabilities dictated by the overall numbers and distributions of peptides identified in each experiment. Thresholds selected were p > 0.7 for COL, p > 0.4 for APT/TSB, and p > 0.7 for APT/TSB + NaCl + Oxa (Figure 4) because the mean probability for COL is ∼ 0.645, whereas the lack of identified peptides belonging to predicted cytoplasmic proteins in the APT strain allowed for a more relaxed threshold. These thresholds also occur at a ratio of 2:1 for peptides predicted to be surface-exposed (Figure 4A). Although all predicted protein groups decrease in their overall number of peptide and protein identifications following the application of a threshold, the highest reduction was observed in proteins predicted to be cytoplasmic that are thus more likely to be contaminants resulting from cell lysis (Figure 4B). The weighting given by the scoring algorithm to predicted surface exposed (PSE) and non-PSE (including cytoplasmic proteins and those without predicted or with conflicting localizations) is equal, and the overall prevalence of PSE proteins likely reflects the efficient enrichment provided by the cell shaving method. Nevertheless, there remain multiple identified proteins that are predicted to be intracellular, thus providing stronger evidence for these as true moonlighting proteins. The final numbers of identified proteins across all strains after filtering thresholds were applied are cytoplasmic, 76; PSE, 62; and unknown, 12 (Table 2 and Figure 4). The vast majority of peptides used to identify these proteins were derived, however, from PSE proteins (Table 2). Comparing the proteins confidently identified by cell shaving between COL and APT showed that most were identified in strain COL and only very few were unique to APT (12 proteins), APT grown in the presence of oxacillin (two proteins), and one protein identified in APT under both conditions but not in COL (Figure 5). All 150 identified proteins are shown in Table 3. Only 21 proteins were common to all three conditions, and these clustered predominantly into two major functional categories: pathogenesis (including adhesion and ECM-binding proteins such as ClfA/ClfB, LytM, Pls, and SasF) and those involved in cell wall organization (including antibiotic-resistance proteins Pbp2 and MecA as well as elastin-binding protein EbpS). Proteins identified by cell shaving in both COL and APT included the fibronectin-binding proteins FnbA and FnbB, ECM-binding protein, serine-aspartate repeat proteins SdrC and SdrD, and SasG. Proteins that were unique to the APT/ TSB data set included the bifunctional autolysin (atl,

Figure 5. Strain overlap of surface-exposed proteins identified by cell shaving. The overlap by strain and growth medium shows that APT in oxacillin contains only two proteins exclusive to its surface. A higher number of proteins belonging to COL comprise mainly proteins predicted to be cytoplasmic but satisfying the probability thresholds.

SACOL1062), virulence factor EsxA (esxA, SACOL0271), immunodominant staphylococcal antigen B (isaB, SACOL2660), 77 kDa membrane protein (SACOL2002), fibrinogen binding-related protein (ecb, SACOL1164), Nacetylmuramoyl-L-alanine amidase (sle1, SACOL0507), and V8 protease (sspA, SACOL1057). When all thresholds were removed, one of these proteins, encoding a 15.5 kDa putative surface protein (SACOL2197), was specific to APT/TSB. This suggests the proteins identified as APT/TSB-specific by the threshold method may be at higher abundance in APT than in COL and hence are identified by more peptides in the shaved versus control data sets. The vast majority of the proteins identified solely in COL were predicted to be of cytoplasmic localization but were scored with high probability because of their proteomic characterization, and as such, they typically have functions associated with metabolism. Two proteins were exclusive to the APT (TSB/NaCl + Oxa) data set and correspond to acyl carrier protein (acpP, SACOL1247) and a LCP domain-containing protein (SACOL2302), whereas a second LCP protein (MsrR, SACOL1398) was identified in both APT data sets but not in COL. Because only three LCP proteins are encoded in the S. aureus COL genome, these data strongly suggest a role for these proteins in the adaptation to high levels of oxacillin. SACOL2302 is a 35 kDa PSE protein that was identified by five peptides (15% sequence coverage) in H



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Table 3. Identification of Proteins from Cell Shaving and the Application of a Probability Score (padjusted, Averaged from Replicate Experiments) in S. aureus COL and APT (grown in TSB) and APT Grown in Oxacillin (APT/OXA) pathway category pathogenesis

cell wall organization and folding

other/unknown

cell cycle cell wall organization and folding defense

DNA replication metabolism

other/unknown

gene name

UniProt accession

0263 0610 2291 2652 0856 2668 0050 1522 0778 0033 1490 2666 2584 1897 2088 2173 2365 1513 0594 0586 2236

lytM sdrE ssaA2 clf B clfA sasF pls ebpS ltaS mecA pbp2

Q5HJ99 Q5HIB2 Q5HDQ9 Q5HCR7 Q5HHM8 Q5HCQ1 Q5HJU7 Q5HFU2 Q5HHV4 Q5HJW3 Q5HFX3 Q5HCQ3 Q5HCY1 Q5HET4 Q5HEA4 Q5HE23 Q5HDI7 Q5HFV0 Q5HIC7 Q5HID5 Q5HDW1

1198 1484 1609 0816 1368 0570 1637 1304 0829 1737 0792 1760 2114 1215 2129 1922 0554 0544 2623 1699 0564 0957 2398 2194 1560

ftsA gpsB pbp3 secA katA clpC dnaK recA trxB polA

SACOL no.

1070 1673 0426 2104 0944 2665 2603 2150 1532 1225

isaA prsA sceD asp23 hup tuf rplL rplB

ackA carB deoC2 hemL2 hpt prsA mqo2

nirB hysA

qoxA alaS upp

sasB

Q5HGP6 Q5HFX8 Q5HFK8 Q5HHR7 Q5HG86 P0C281 Q5HFI0 Q5HGE6 Q5HHQ4 Q5HF83 Q5HHU0 Q5HF63 Q5HE78 Q5HGM9 Q5HE63 Q5HER0 Q5HIG5 Q5HIH5 Q5HCU5 Q5HFB9 Q5HIF5 Q5HHD1 Q5HDF6 Q5HE02 Q5HFQ6 Q5HH23 Q5HFE4 Q5HIU0 Q5HE88 Q5HHE4 Q5HCQ4 Q5HCW3 Q5HE44 Q5HFT3 Q5HGL9

name Common to All Glycyl-glycine endopeptidase LytM Serine-aspartate repeat-containing protein E Staphylococcal secretory antigen SsaA2 Clumping factor B Clumping factor A LPXTG cell wall surface anchor family protein Methicillin resistant surface protein Elastin-binding protein EbpS Lipoteichoic acid synthase Penicillin-binding protein 2′ Penicillin-binding protein 2 N-acetylmuramoyl-L-alanine amidase domain protein Immunodominant staphylococcal antigen A IsaA Foldase protein PrsA Probable transglycosylase SceD Alkaline shock protein 23 Uncharacterized lipoprotein SACOL2365 DNA-binding protein HU Elongation factor Tu 50S ribosomal protein L7/L12 50S ribosomal protein L2 Unique to COL Cell division protein FtsA Cell cycle protein GpsB Penicillin-binding protein 3 Protein translocase subunit SecA 1 Catalase ATP-dependent Clp protease ATP-binding subunit Chaperone protein DnaK Protein RecA Thioredoxin reductase DNA polymerase I Ribonucleoside-diphosphate reductase Acetate kinase Putative aldehyde dehydrogenase SACOL2114 Carbamoyl-phosphate synthase large chain Deoxyribose-phosphate aldolase 2 Glutamate-1-semialdehyde 2,1-aminomutase 2 Hypoxanthine-guanine phosphoribosyltransferase Ribose-phosphate pyrophosphokinase Probable malate:quinone oxidoreductase 2 GTPase Obg Pyridoxal biosynthesis lyase PdxS Putative peptidyl-prolyl cis−trans isomerase Nitrite reductase [NAD(P)H], large subunit Hyaluronate lyase 2-oxoisovalerate dehydrogenase, E2 component, dihhydrolipoamide acetyltransferase Probable quinol oxidase subunit 2 Alanyl-tRNA synthetase Probable acetyl-CoA acyltransferase Uracil phosphoribosyltransferase NADH dehydrogenase-like protein SACOL0944 Phage infection protein, putative Putative uncharacterized protein SasB protein Putative uncharacterized protein Putative uncharacterized protein I

padjusted (average) 0.8427 0.9502 0.9258 0.8796 0.7387 0.9625 0.9738 0.8404 0.7452 0.9946 0.9065 0.9625 0.7984 0.7537 0.9237 0.9517 0.8759 0.7734 0.8373 0.9450 0.8449 0.9625 0.9625 0.9625 0.9625 0.7277 0.9186 0.9079 0.9625 0.7257 0.9625 0.9625 0.8155 0.9625 0.9625 0.9625 0.9625 0.9625 0.9625 0.9625 0.9625 0.9418 0.8155 0.9625 0.9625 0.9625 0.9625 0.9625 0.8623 0.9625 0.9625 0.9625 0.8324 0.9625 0.9283 0.7837



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Table 3. continued pathway category

pathogenesis

protein synthesis

transcription

transport

cell wall organization and folding other/unknown

pathogenesis

SACOL no. 0985 0851 0489 0487 0377 0270 0119 1933 0815 2421 0317/0390 2006 0907 0095 2676 1970 1942 1587 1962 2207 2223 2237 2228 2221 2112 1726 2224 1254 1274 1665 0539 1222 0175 1457 0914 1062 0507 2557 1164 0303 0281 0912 0271 2660 2002 2197 1057

gene name

sasD

hlgC

seb spa sasA sspB2 vraR efp gatC rplM rplR rplW rplX rpmD rpmE rpmI rplF rpsP rpsB greA purR rpoZ crr

atl sle1

esxA isaB map sspA

metabolism other/unknown

1247 2302

acpP

adhesion

0858 0608 0609 2505 1500 0024 2509

empbp sdrC sdrD sasG

other/unknown

sasH fnbB

UniProt accession

name

Unique to COL Surface protein, putative Putative uncharacterized protein Putative uncharacterized protein Putative uncharacterized protein Putative uncharacterized protein Staphyloxanthin biosynthesis protein, putative Cell wall surface anchor family protein Uncharacterized protein SACOL1933 Uncharacterized protein SACOL0815 Gamma-hemolysin component C Lipase 2 Uncharacterized leukocidin-like protein 2 Staphylococcal enterotoxin B Immunoglobulin G binding protein A Serine-rich adhesin for platelets Staphopain A Response regulator protein VraR Elongation factor P Aspartyl/glutamyl-tRNA(Asn/Gln) amidotransferase subunit C 50S ribosomal protein L13 50S ribosomal protein L18 50S ribosomal protein L23 50S ribosomal protein L24 50S ribosomal protein L30 50S ribosomal protein L31 type B 50S ribosomal protein L35 50S ribosomal protein L6 30S ribosomal protein S16 30S ribosomal protein S2 Transcription elongation factor GreA Pur operon repressor DNA-directed RNA polymerase subunit omega PTS system glucose-specific EIICBA component Glucose-specific phosphotransferase enzyme IIA Fe-S assembly ATPase SufC Unique to APT/TSB Q5HH31 Bifunctional autolysin Q5HIL2 N-acetylmuramoyl-L-alanine amidase Sle1 Q5HD07 Conserved domain protein Q5HGT0 Fibrinogen binding-related protein Q5HJ61 Acid phosphatase 5′-nucleotidase, lipoprotein family Q5HJ81 Putative uncharacterized protein Q5HHH4 UPF0337 protein SACOL0912 Q5HJ91 Virulence factor EsxA Q5HCQ9 Immunodominant staphylococcal antigen B Q5HEI2 77 kDa membrane protein Q5HDZ9 Surface protein, putative Q5HH35 Glutamyl endopeptidase Unique to APT/NaCl/OXA Q5HGK0 Acyl carrier protein Q5HDP8 Transcriptional regulator, LCP domain-containing protein Common between COL and APT/TSB Q5HHM6 Extracellular matrix protein-binding protein Emp Q5HIB4 Serine-aspartate repeat-containing protein C Q5HIB3 Serine-aspartate repeat-containing protein D Q5HD57 Cell wall surface anchor family protein Q5HFW3 Putative uncharacterized protein Q5HJX2 5′-nucleotidase family protein Q5HD53 Fibronectin binding protein B Q5HHA4 Q5HHN2 Q5HIM8 Q5HIN0 Q5HIY8 Q5HJ92 Q5HJN4 Q5HEP9 Q5HHR8 Q5HDD4 Q5HJ48 Q5HEH9 Q5HHH9 Q5HJQ8 Q5HCP3 Q5HEL3 Q5HEP0 Q5HFN0 Q5HEM1 Q5HDZ0 Q5HDX4 Q5HDW0 Q5HDW9 Q5HDX6 Q5HE80 Q5HF93 Q5HDX3 Q5HGJ4 Q5HGH6 Q5HFF2 Q5HII0 Q5HGM2 Q5HJI3 Q5HFZ9 Q5HHH2

J

padjusted (average) 0.9658 0.7837 0.8623 0.8161 0.9625 0.9418 0.8623 0.8623 0.9625 0.9625 0.9625 0.9625 0.9625 0.9118 0.9625 0.9625 0.9625 0.9625 0.9625 0.8623 0.9625 0.7620 0.8623 0.7837 0.9625 0.7620 0.8462 0.7620 0.8947 0.9464 0.9625 0.9625 0.9625 0.9625 0.9186 0.5875 0.4951 0.6409 0.6127 0.4829 0.4731 0.5951 0.4800 0.5994 0.5216 0.9625 0.6835 0.7510 0.8039 0.9625 0.9625 0.9597 0.9625 0.9625 0.9625 0.9406



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Table 3. continued pathway category

pathogenesis

protein synthesis

cell cycle defense

metabolism

other/unknown

pathogenesis protein synthesis

transcription

SACOL no. 2295 0723 0669 2418 2581 2511 0591 2240 1642

gene name

fnbA rpsL rpsJ rpsT

1199 2563 1759 1753 1762 1016 1622 1104 2218 1745 1102 1788 0444 1722 0272 1288 0583 1278 0585 0545 2217 2212 1276 2220 2238 2225 1516 2222

ftsZ clpL

1398

msrR

fabI glyS pdhC adk pyk pdhA

tig esaA inf B rplK frr rplJ rplY infA rplQ tsf rplO rplD rpsH rpsA rpsE

UniProt accession

name

Common between COL and APT/TSB Q5HDQ5 Staphyloxanthin biosynthesis protein, putative Q5HI03 LysM domain protein Q5HI54 Putative uncharacterized protein Q5HDD7 Immunoglobulin-binding protein Sbi Q5HCY4 Staphylococcal secretory antigen SsaA1 Q5HD51 Fibronectin-binding protein A Q5HID0 30S ribosomal protein S12 Q5HDV7 30S ribosomal protein S10 Q5HFH5 30S ribosomal protein S20 Common between COL and APT/OXA Q5HGP5 Cell division protein FtsZ Q5HD02 ATP-dependent Clp protease ATP-binding subunit ClpL Q5HF64 Putative universal stress protein SACOL1759 Q5HF68 Universal stress protein family Q5HF61 Probable thiol peroxidase Q5HH75 Enoyl-(Acyl-carrier-protein) reductase [NADPH] Q5HFJ5 Glycyl-tRNA synthetase Q5HGY9 Dihydrolipoyllysine-residue acetyltransferase Q5HDX9 Adenylate kinase Q5HF76 Pyruvate kinase Q5HGZ1 Pyruvate dehydrogenase E1 component subunit alpha Q5HF36 Putative uncharacterized protein Q5HIS3 Putative uncharacterized protein Q5HF97 Trigger factor Q5HJ90 Protein EsaA Q5HGG2 Translation initiation factor IF-2 Q5HID8 50S ribosomal protein L11 Q5HGH2 Ribosome-recycling factor Q5HID6 50S ribosomal protein L10 Q5HIH4 50S ribosomal protein L25 Q5HDY0 Translation initiation factor IF-1 Q5HDY5 50S ribosomal protein L17 Q5HGH4 Elongation factor Ts Q5HDX7 50S ribosomal protein L15 Q5HDV9 50S ribosomal protein L4 Q5HDX2 30S ribosomal protein S8 Q5HFU7 30S ribosomal protein S1 Q5HDX5 30S ribosomal protein S5 Common between APT/TSB and APT/OXA Q5HG57 Regulatory protein MsrR, LCP domain-containing protein

padjusted (average) 0.7537 0.7510 0.7457 0.9814 0.9625 0.9625 0.8505 0.7537 0.7094 0.9625 0.9695 0.9286 0.7537 0.7440 0.9625 0.8039 0.7345 0.7217 0.7180 0.7126 0.9625 0.9210 0.7537 0.7565 0.9625 0.9332 0.9124 0.9124 0.9124 0.8957 0.8230 0.7928 0.7614 0.7597 0.7508 0.7344 0.7305 0.9625

promoter. Analysis by q-PCR showed that the overexpressing strain (termed COL2302+) increased sacol2302 expression ∼7fold compared with COL, which was consistent with the number of copies of pSK5487 and with the levels observed in APT grown in TSB/NaCl + Oxa (Figure 6A). COL, APT, and COL2302+ were next grown in liquid media under aerobic conditions to determine if SACOL2302 was responsible for oxacillin adaptation. All strains were able to grow in TSB alone; however, the addition of NaCl and oxacillin inhibited both COL and COL2302+, whereas APT was able to grow (data not shown). This suggests that increased abundance of SACOL2302 alone is not sufficient for growth in oxacillin. The strains were also tested for their ability to form biofilms or cellular aggregation. Overexpression of SACOL2302 resulted in a modest but nonsignificant increase in extracellular material, as determined by crystal violet biofilm assay (Figure 6B); however, this was significantly less than that observed for APT grown in oxacillin, suggesting that SACOL2302 alone

the APT/NaCl + Oxa shaved data set (Supporting Information Figure S3). Because of its presence exclusively on the surface of APT when grown in salt and oxacillin (even when no thresholds were applied), we hypothesized that it may be linked to the APT phenotypes of antibiotic resistance, aggregation, and biofilm formation. Increased Expression of sacol2302 Occurs in S. aureus APT, but Overexpression in COL Does Not Confer the APT Phenotype

We first wished to validate the cell shaving data by determining whether sacol2302 was expressed at higher levels in APT. Quantitative RT-PCR (q-PCR) showed that sacol2302 expression increased ∼6-fold in APT (TSB/NaCl + Oxa) and 3-fold in APT without oxacillin compared with the COL strain (Figure 6A). To establish if SACOL2302 is responsible for the APT phenotype, we generated a COL strain containing a multicopy vector with sacol2302 under the control of its natural K



Article

Figure 6. SACOL2302 overexpression does not induce antibiotic resistance or cellular aggregation. (A) Construction of COL2302+ shows confirmed overexpression of SACOL2302 (all values relative to 16S RNA), and expression of SACOL2302 is elevated in APT to levels comparative to COL2302+ in oxacillin-supplemented media. (B) Overexpression of SACOL2302 does not influence the amount of extracellular material/cellular aggregation. (C) Zones of inhibition from CDS disc diffusion assays. COL and COL2302+ show identical profiles for β-lactams, with APT showing higher levels of resistance.

Figure 7. iTRAQ analysis showed accurate quantification for normally distributed ratios and threshold determination on the basis of rank-based zscores. (A) Log ratios of proteins are displayed in the histogram and are centered around zero and normally distributed. (B) Plotting rank-based zscore against log ratios enabled the placement of ratio thresholds outside areas where nonlinear regressions are encountered.

disc diffusion assays confirmed that APT has increased resistance (smaller zones of inhibition) to ampicillin, ticarcillin/clavulanic acid, and nalidixic acid (all β-lactams) compared to COL (Figure 6C). APT, however, showed

does not confer the increased aggregation phenotype. We next investigated whether SACOL2302 influenced antibiotic resistance to β-lactams and if adaptation to high levels of oxacillin induced multidrug resistance as previously described.62 CDS L



Article

Figure 8. Functional cluster analysis (STRING) maps of proteins significantly altered in abundance in S. aureus APT compared with COL, as determined by iTRAQ quantitative proteomics. (A) Proteins less abundant in APT compared with COL. Seven clusters were observed: nitrate/ nitrite reduction (I), type VII secretion (II), iron uptake (III), pathogenesis (IV), pyruvate metabolism (V), and glycolysis (VI). (B) Proteins more abundant in APT compared with COL. Eight clusters were observed: urease enzymes (VIII), redox enzymes (IX), capsular polysaccharide biosynthesis (X), oligopeptide and ABC transporters (XI), branched chain amino acid biosynthesis (XII), lysine biosynthesis (XIII), cell wall biosynthesis (XIV), and pathogenesis/aggregation/adhesion (XV).

reduction (NIR and nar operons; cluster I), pyruvate metabolism and glycolysis/gluconeogenesis (L-lactate dehydrogenases Ldh1 and Ldh2, hydroxymethylglutaryl-CoA synthetase (MvaS), formate acetyltransferase (PflB), pyruvate formate-lyase-activating enzyme (PflA), D-lactate dehydrogenase (LdhD), and SrrA (SACOL1535), which is part of the SrrA/SrrB two-component regulatory system; clusters V and VI), and purine metabolism (including nine proteins of the pur operon: PurACDFHKLMQ; cluster VII). Other clusters were associated with type VII secretion (including EsxA, EsaA, EssB, EssC, SACOL0279, SACOL0281, and SACOL0487; cluster II) and iron uptake (transferrin receptor SstD, iron ABC transporter SirA, and SACOL2167; cluster III). There is also reduced abundance of proteins associated with pathogenesis (cluster IV), namely, protein A (Spa), repressor of toxins (Rot), 5′-nucleotidase family protein (SasH), immunodominant staphylococcal antigen B (IsaB), and the staphylococcal accessory regulator R (SarR). STRING also identified eight major clusters of functionally related proteins that were present in APT at elevated abundance compared with COL (Figure 8B). These clusters included capsular polysaccharide production (cluster X), including six members encoded by the cap5 operon (Cap5BEFMOL), which is implicated in the formation of extracellular material in S. aureus; cell envelope and transport (cluster XI), in particular OppDF and SACOL0995, which are involved in oligopeptide transport; and amino acid biosynthesis (clusters XII and XIII), predominantly including proteins involved in branched chain amino acid and lysine biosynthesis that are both important components for peptidoglycan biosynthesis. Two significant clusters (XIV and XV) were associated with cell wall integrity, and not surprisingly, they included proteins involved in β-lactam resistance such as PBP2′, bifunctional autolysin (Atl), FmtA, penicillin binding protein 2 (PBP2), peptidoglycan elongation proteins MurA2 and transglycosylase domain protein Mgt, teicoplanin resistance

equivalent sensitivity, or was more sensitive, to all other classes of antibiotics (Supporting Information Figure S4), which is in contrast to ref 62 and suggests that oxacillin adaptation may not confer multidrug resistance. COL2302+ displayed no difference in its resistance profile compared to COL with the exception of chloramphenicol, the resistance marker for the pSK5487 plasmid. Quantitation by iTRAQ and LC−MS/MS Shows Adaptation to High Levels of Oxacillin Induces Significant Changes in the S. aureus COL Proteome

We next examined the effect of adaptation to high levels of oxacillin on the whole proteome using quantitation by iTRAQ labeling coupled to LC−MS/MS. The minimum requirements for accurate quantitation were proteins with two or more unambiguous identified peptides that contained no variable modifications and that satisfied the FDR. A total of 1802 proteins were identified with high confidence (corresponding to 67% of the theoretical S. aureus COL proteome), of which 1323 were quantified using an average of six peptides per protein (Supporting Information Data S2). Peptide spectral matches were combined to generate final peptide log ratios for robustness, and these were iterated to determine protein log ratios. The frequency plot depicting protein log ratios (Figure 7A) displays a normal distribution around zero. The log ratio thresholds for biologically significant abundance changes were selected by rank-based z-scores (Figure 7B). Loss of linearity suggests that the data no longer follows normal distributions and are hence of biological relevance. A total of 216 proteins were considered to be significantly different in abundance between COL and APT (128 more abundant and 88 less abundant in APT compared with COL). STRING cluster analysis was performed separately on the increased and decreased proteins (Figure 8). STRING identified seven major clusters that were enriched in proteins present in APT at lower abundance than in COL (Figure 8A). These included proteins involved in nitrate/nitrite M



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Figure 9. S. aureus APT generates less acid in its environment than COL in relation to growth rate. (A) Growth curves of COL and APT while shaking in liquid media show a slower growth rate for the adapted strain. (B) Rate of pH drop (linear regions) was divided by the growth rate (linear regions), and a significant difference between the acidity of the environment of APT compared to COL was observed.

surface-associated functions in addition to their cytoplasmic role are now well-accepted.59−61 Therefore, it is not a simple task of removing any identified proteins that do not contain a signal sequence from the surface-exposed category, and indeed, one of the best uses for cell shaving is to highlight novel moonlighting proteins. We described a false positive control using a parallel batch of cells incubated under identical conditions as those undergoing cell shaving but without the protease.51 Cells were removed, and supernatants were treated with protease; any identified peptides were, therefore, a result of shedding or lysis. Peptides in the false positive control could be subtracted from the shaving data, leading to an enrichment of true surface proteins. This approach, however, is not ideal, as abundant surface proteins may be false negatives because peptides from these proteins will also be present in the control. Another study compared the ratio of peptides identified by cell shaving and in false positive controls, and if it was >2, the protein was considered to be truly surface-exposed.70 We attempted to score each protein in cell shaving experiments with regard to their probability of being truly surface-exposed. Although the algorithm does not provide absolute proof, it can be readily applied to sort higher scoring proteins for further investigation. In this study, low-scoring proteins were eliminated according to a threshold, and remaining cytoplasmic proteins with a score above this threshold could represent moonlighting proteins. Cell shaving and assignment of probability scores and thresholds generated profiles of COL and APT that allowed a qualitative comparison of their surface topologies. The surfaceomes of COL and APT were generally similar, with the differences found in COL mainly related to predicted intracellular proteins and those common across strains related to virulence and adhesion.51,55 Another cell shaving study stated that the S. aureus surface proteome is heterogeneous, with only a small number of proteins consistent across a multitude of strains.71 Because APT was generated from COL by oxacillin adaptation, we anticipate that they are nearly identical genetically, meaning that phenotypic differences likely result from changes in protein abundance (e.g., APT displays

protein TcaA, and the LCP domain-containing proteins MsrR, SACOL1065, and SACOL2302, which was consistent with the data generated by cell shaving and q-PCR. Additional virulenceassociated proteins that were more abundant in APT compared with COL included signal peptidases (SpsA and SpsB), clumping factor A (ClfA), and a 77 kDa membrane protein (SACOL2002). The final major cluster (cluster VIII) included the urease proteins UreBCDEFG, which suggested adaptation to high levels of oxacillin influenced the production of ammonia and may perturb culture pH. This was validated by growth of COL and APT and monitoring their rate of growth and culture pH by means of a micro-pH probe (Figure 9). Culture acidity as a function of growth rate was much lower for the APT strain (irrespective of culture conditions) when compared with COL. Comparison of the growth curves and culture pH over time also showed that the culture pH of COL at the completion of exponential phase growth was significantly lower than for APT grown in TSB or in TSB + NaCl + Oxa. During stationary phase growth, all strains displayed equal culture acidity. These data suggest that excess ammonia produced by the urease system in APT may counteract acidic byproducts liberated during aerobic respiration in the COL strain.

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DISCUSSION The importance of S. aureus as a pathogen and the increase in prevalence of antibiotic resistance means that there is a critical need for identifying novel drug targets and vaccine candidates. Surface-exposed proteins are crucial in pathogenesis and host interactions; thus, they are potential targets for new antimicrobials or may form the basis for better pathogen control. Cell shaving aims to release surface-exposed epitopes and thus provides insight into topology. This technique has been used mainly for organisms with thick cell walls, namely, Gram-positive bacteria, fungi, and certain Archaea.46−56 The major technical caveat with this approach is how best to minimize cell lysis during shaving and then how to account for peptides generated from intracellular proteins. This is further confounded because moonlighting proteins that may perform N



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enhanced aggregation despite the maintenance of icaC mutation). Alternatively, those proteins unique to COL may contain only short and/or few surface-exposed regions and are thus effectively masked by the increase in polysaccharide capsule apparent on the APT surface. PSORTb analysis of the COL genome identified 47 predicted cell wall proteins, of which 36 were identified here. Of these, the majority (23/36) were identified in both COL and APT, which is consistent with their genetic relationship. High-scoring proteins in APT and COL included the cytoplasmic proteins DNA-binding protein HU, alkaline shock protein 23, elongation factor Tu, and ribosomal proteins L7/L12 and L2. EF-Tu has been noted on the surface of several species including Acinetobacter baumannii,72 has been associated with the staphylococcal surface following incubation with human serum,55 and may mediate binding of Lactobacillus to intestinal epithelia.73 The LCP domain-containing protein, SACOL2302, was one of only two proteins unique to the APT surface. A second of the three LCP proteins (MsrR) was also the only protein found in APT under both growth conditions, yet it was not found in COL. MsrR has been suggested to attenuate the global virulence factor regulator sarA (staphylococcal accessory regulator A), and increased expression of alpha-toxin transcripts occur in a ΔmsrR strain.74 Quantitation by iTRAQ, however, showed statistically significant increases in APT SarA levels (Supporting Information Data S2). Some proteins in the SarA regulon75 (e.g., autolysin) responded to oxacillin adaptation in a manner consistent with our observed changes in SarA, whereas others (e.g., IsaA, lipase 2) remained unaltered. SarA is also influenced by (and influences) other regulators, including SarR, SrrA, and Rot. We observed a significantly reduced abundance of Rot and the SarA repressor SarR, which thus contributes to elevated SarA in APT. SrrA was present at reduced abundance in APT. SrrA is part of a two-component regulatory system that controls virulence factor expression in response to environmental oxygen.76 Under anaerobic conditions, SrrA represses transcription of the accessory gene regulator (agr) and protein A (spa) while enhancing spa expression during aerobic growth.77 Here, we observed a very significant APT-associated reduction in Spa, consistent with the aerobic growth model. msrR deletion decreased resistance to oxacillin, and elevated msrR expression was observed during antibiotic stress,74 which are consistent with our observations. MsrR is also involved in teicoplanin resistance by modulating the architecture of the cell wall via adjusting levels of teichoic acids.78 In ref 78, however, msrR deletion increased cell size and induced cell envelope remodelling, which are similar effects to those that we observed in APT when MsrR protein levels were elevated. We hypothesized that LCP proteins, and SACOL2302 in particular, may contribute to the APT phenotype. Overexpression of sacol2302, however, did not generate the APT phenotype in COL, although a very minor (but not statistically significant) increase in aggregation was observed. We also confirmed that SACOL2302 did not contribute to β-lactam resistance. These data suggest that the mechanisms leading to increased aggregation and changes in cell morphology are multifactorial. Our data are thus consistent with a report that explored the roles of LCP proteins in aggregation, virulence, and resistance in a methicillin-sensitive strain by means of single, double, and triple deletions of sa0908 (sacol1065), sa2103 (sacol2302), and msrR.39 This report showed that SACOL2302 enhanced properties conferred by MsrR in cell division, septum formation, and antibiotic resistance and by SACOL1065 in

autolysis. SACOL1065, similar to MsrR and SACOL2302, was also present at elevated abundance in APT and correlated with a strong induction of the bifunctional autolysin (Atl). This suggests that during adaptation to oxacillin all three LCP proteins contribute to increased aggregation, antibiotic resistance, and cell wall remodelling. Previous work62 that generated an oxacillin-adapted S. aureus suggested multidrug resistance was conferred. Our data, however, conflict with ref 62 because only enhanced resistance to β-lactams was observed and the APT strain was generally more sensitive to all other classes of antibiotic. This difference potentially results from clonal evolution as the strain in ref 62 may have adapted via enhanced multidrug efflux, whereas APT generated the same phenotype via independent mechanisms (e.g., LCP proteins). We additionally observed no enhanced abundance of multidrug efflux systems in the iTRAQ analysis other than a single putative cation efflux protein (SACOL2416) that was present at increased abundance in APT. We observed changes in APT cell wall morphology, and six proteins encoded by the cap5 operon associated with capsular polysaccharide production were elevated. Capsule is an S. aureus virulence determinant that aids in avoiding phagocytosis, and expression is environmentally sensitive, with signals including iron and CO2.79−81 cap5 expression is thought to be positively regulated by the arl locus via mgrA;82 however, we observed no abundance changes associated with mgrA or arlRS that could fit this observation. A recent report in a vancomycinintermediate S. aureus (VISA) suggested that capsular polysaccharide is not linked to antibiotic resistance and may simply be a secondary effect induced by high sigma factor B (SigB) activity.83 Elevated cap5M expression associated with SigB has also been reported.84 We observed increased APT abundance of several SigB-associated proteins in addition to Cap5M, including clumping factor A and Ahp1. Also consistent with ref 84 are the elevated abundance of proteins associated with lysine biosynthesis as well as those involved in the synthesis of nonpolar amino acids and the reduced abundances of proteins involved in amino acid biosynthesis associated with pyruvate. The previous report84 suggested that synthesis of peptidoglycan precursors that rely on these pathways likely takes precedence over the synthesis of other amino acids that may not be critical for viability. Not surprisingly, APTassociated proteins also included penicillin-binding protein 2A, the classic marker for determining β-lactam resistance in staphylococcal species, as well as FmtA (involved in autolysis), MurA2 and Mgt (elongation of peptidoglycan), and TcaA (teicoplanin resistance). Intriguingly, heavily encapsulated S. aureus strains show reduced invasion of epithelial cells, and this is presumed to be due to the masking of surface proteins required for this process.85 Increased abundance of cap5 proteins and peptidoglycan precursors, which lead to increased capsule and thicker cell walls, is likely to be a major contributor to the reduced numbers of identified peptides and proteins we observed in APT by cell shaving. This does, however, provide additional confidence regarding the identified epitopes and their surface exposure. Moonlighting proteins identified in APT may thus also be more likely to result from rebinding to the capsule itself rather than being bound to the cell wall. A reduction in abundance of purine biosynthesis proteins was observed in APT. In S. aureus, the pur regulon has been associated with vancomycin resistance and is hypothesized to generate increased ATP availability that could be utilized for production of thicker cell walls.86 Biochemical assays, however, O



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suggest no relationship with vancomycin resistance and therefore the role of purine biosynthesis in antibiotic resistance remains uncertain.87 Proteins involved in type VII secretion (EsxA, EssABC, and others) were also reduced in abundance. S. aureus esxAB mutants are defective in dissemination and colonization,88 suggesting adaptation to oxacillin may compromise some elements of virulence. Other virulence determinants reduced in abundance in APT included SasH, Spa, and IsaB. Nitrate respiration enzymes were also reduced in APT. These proteins are involved in the uptake of nitrate and conversion into ammonia, which can be used to synthesize glutamine and glutamate. Conversely, reduced ammonia generated via nitrate seems to be compensated for by increased abundances of urease proteins (UreBCDEFG) that catalyze ammonia production from urea, generating increased culture pH. Monitoring of culture pH showed that APT indeed retained a higher pH compared with COL, suggesting that maintenance of pH is important in adaptation to oxacillin. A relationship between elevated expression of the urease gene cluster and several similar environmental stresses has also been observed, including in daptomycin-resistant S. aureus,89 following treatment with berberine chloride90 and during acid shock.91 Urease and ammonia production have also been observed at increased levels in S. aureus biofilms compared with planktonic growth.92 It is therefore possible that increased APT aggregation depends upon the activation of urease to maintain pH.

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CONCLUSIONS

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ASSOCIATED CONTENT

Article

AUTHOR INFORMATION

Corresponding Author

*Phone: (612) 9351-6050; Fax: (612) 9351-4726; E-mail: [email protected]. Present Address ⊥

(B.L.P.) Garvan Institute of Medical Research, Sydney, New South Wales 2010, Australia.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS Parts of this work were funded by a National Health and Medical Research Council of Australia (NHMRC) Project Grant to N.F., S.K., and S.J.C. (NHMRC 571029). N.S. is the recipient of an Australian Postgraduate Award. This work was facilitated by access to the Australian Microscopy and Microanalysis Research Facility (AMMRF) at the University of Sydney.

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ABBREVIATIONS APT, S. aureus COL adapted to oxacillin; CID, collisioninduced dissociation; COL, S. aureus COL; ECM, extracellular matrix; HCD, higher energy collisional dissociation; LCP, LytR-CpsA-Psr domain; PSE, predicted surface exposed

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REFERENCES

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A probability scoring mechanism was applied to compare the surfaceomes of S. aureus COL and COL adapted in vitro to oxacillin (APT). Lower numbers of surface-exposed proteins were identified in APT, most likely because of its thicker cell wall and increased capsule, as observed in SEM and confirmed by iTRAQ analysis that showed increases in Cap5, wall remodelling and peptidoglycan precursor synthesis, and assembly proteins. Aggregation and antibiotic resistance were also influenced by elevated abundance of LCP proteins; however, overexpression of SACOL2302 alone did not generate the APT phenotype in strain COL. APT did not demonstrate multidrug resistance against non-β-lactams. This study provides molecular targets involved in the generation of S. aureus antibiotic resistance that are associated with cell morphology and biofilm formation that may ultimately be useful for further study in a clinical setting.

S Supporting Information *

Peptide identification parameters from cell shaving and iTRAQ analysis; icaC frameshift mutation in S. aureus COL is maintained in APT; difference between symmetrical and asymmetrical distributions for the cell shaving probability scoring algorithm; MS/MS of five peptides identified from SACOL2302; and results of CDS disc diffusion assays for all antibiotics tested. This material is available free of charge via the Internet at http://pubs.acs.org. The algorithm for cell shaving analysis has been compiled into a program that is available free of charge at https://github.com/mehwoot/ cellshaving. P



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