Time-Resolved Analysis of Cytosolic and Surface-Associated Proteins

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Journal of Proteome Research

Time-resolved analysis of cytosolic and surface associated proteins of Staphylococcus aureus HG001 under planktonic and biofilm conditions Martin Moche, Rabea Schlueter, Jörg Bernhardt, Kristina Plate, Katharina Riedel, Michael Hecker, and Dörte Becher * P

Institute for Microbiology Ernst-Moritz-Arndt-University Greifswald, Germany

Keywords: Staphylococcus aureus, colony biofilm, cell-surface proteome, biotinylation approach, 15 P

P

N metabolic labeling, mass spectrometry

*Correspondence: Prof. Dörte Becher, Institute for Microbiology, Ernst-Moritz-ArndtUniversity-Greifswald, Friedrich-Ludwig-Jahn-Straße 15, 17487 Greifswald, Germany E-mail: [email protected] 15TU

U15T

Phone: +49 3834 864230

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Abstract Staphylococcal biofilms are associated with persistent infections due to their capacity to protect bacteria against the host’s immune system and antibiotics. Cell-surface associated proteins are of great importance during biofilm formation. In the present study, an optimized biotinylation approach for quantitative GeLC-MS based analysis of the staphylococcal cellsurface proteome was applied and the cytoplasmic protein fraction was analyzed in order to elucidate proteomic differences between colony biofilms and planktonic cells. The experimental setup enabled a time-resolved monitoring of the proteome under both culture conditions and the comparison of biofilm cells to planktonic cells at several time points. This allowed discrimination of differences attributed to delayed growth phases from responses provoked by biofilm conditions. Biofilm cells expressed CcpA-dependent catabolic proteins earlier than planktonic cells and strongly accumulated proteins that belong to the SigB stress regulon. The amount of the cellsurface protein and virulence gene regulator Rot decreased within biofilms and MgrAdependent regulations appeared more pronounced. Biofilm cells simultaneously up-regulated activators (e.g. SarZ) as well as repressors (e.g. SarX) of RNAIII. A decreased amount of high-affinity iron uptake systems and an increased amount of the iron-storage protein FtnA possibly indicated a lower demand of iron in biofilms.

Introduction Staphylococcus aureus is an opportunistic Gram-positive pathogen that predominantly colonizes the anterior nasal cavity but also the perineum or the groin of estimated 30-40 % of the human population. 1, 2 Although colonization occurs asymptomatically in most cases, it is P

P

the leading cause of soft tissue infections and one of the most important pathogens in nosocomial infections. 3, 4 S. aureus is able to attach to biotic and abiotic surfaces and to grow P

P

in multicellular aggregates known as biofilms. Compared to planktonically growing cells, 2 ACS Paragon Plus Environment

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biofilms exhibit decreased susceptibility to virtually all antibiotics and biofilm-associated infections are difficult to treat. 5 Approximately 60 % of the chronic wound infections contain P

P

biofilms and S. aureus is one of the predominant pathogens in these infections. 6 P

P

Biofilm development is a concerted action controlled by a complex network of regulators that also controls metabolism and virulence gene expression. Influence on biofilm formation has been reported for many regulators including SarA, agr (RNAIII and AgrA), MgrA, SigB, Rot, CcpA, CodY, Spx, CidR, LytSR, IcaR, TcaR, LuxS, and Rbf. 7–20 As a consequence, P

P

formation of staphylococcal biofilms can be induced by many environmental factors such as availability of specific nutrients (e.g. glucose), high salinity, suboptimal temperature, iron depletion, hypoxia, or extreme pH and biofilms respond to numerous endogenous and exogenous signals. 9–12 The interactions of these regulators and their influence on target gene P

P

expression have been widely studied using knockout mutants, transcriptome analyses, electrophoretic mobility shift assay, or northern blots. 8, 9, 11, 12, 15, 19 Nevertheless, there is a P

P

considerable knowledge gap on how regulatory pathways interact in wild type cells in complex situations such as nutrient limitation under biofilm conditions. Biofilm formation is characterized by three phases: primary surface attachment, biofilm maturation and biofilm detachment. For primary surface attachment, proteinaceous adhesins as well as extracellular DNA (eDNA) are of great importance. S. aureus is equipped with a large repertoire of such partially multifunctional adhesins (e.g. ClfA, ClfB, FnbA, FnbB, SdrC) that recognize specific biotic ligands on host cells or other bacteria.

21–23 P

P

Besides, the

presence of eDNA is of predominant importance for adhesion. 24 It is released by cell lysis, a P

P

process that is controlled by a holin/antiholin system constituted by CidABC and LrgAB or by the action of autolysins like the bifunctional Atl. 13, 24 P

Once the bacteria are attached, the biofilm maturates by accumulation of cells and structuring of the biofilm colonies. Within biofilms, staphylococci are most often embedded in an exopolysaccharide made from N-acetylglucosamine, the polysaccharide intercellular 3 ACS Paragon Plus Environment


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adhesin (PIA). Expression of PIA synthesizing proteins IcaADBC is affected by nutrient and oxygen availability, cell density and several stress responses. Some strains of S. aureus are able to form biofilms independently from PIA with the aid of their cell-surface proteins. 16, 25, P

26 P

Cell-surface proteins that promote biofilm accumulation include ClfB, FnbA, FnbB and

SasC, and SasG. 26–30 Expression of these proteins is either directly or indirectly influenced by P

P

multiple regulators including SigB, SarA, Rot, and MgrA. Transcription of fnbA for instance was observed to be altered in mutant strains of ccpA, sigB, sarA, walR and saeR. 31–35 P

Knock out of sarA strongly impairs biofilm formation primarily due to increased extracellular proteolytic activity. This process is poorly understood but appears to be dependent on the interaction of SarA with the two-component system SaeSR. 36, 37 Increased P

P

proteolytic activity in the extracellular milieu prevents accumulation of critical proteins involved in biofilm formation. 37 In order to assure nutrient supply to the inner layers of a P

P

biofilm, liquid conducting channels are formed. S. aureus expresses small surfactant peptides, the so called phenol soluble modulins (PSMs) that are involved in this process. 38 Biofilm P

P

structuring is further affected by extracellular proteases and nucleases that degrade the biofilm matrix. 39 Additionally, all three mechanisms contribute to detachment of cells from matured P

P

biofilms and hence, biofilm dispersal. Extracellular proteases can be upregulated in a quorum sensing dependent manner whereby RNAIII represses Rot posttranscriptionally and derepresses proteases like Aur, SspA, SspB and others. 40–42 This process is also SigBP

P

dependent since SigB represses RNAIII as well as extracellular nucleases. 43–45 The high P

P

degree of cross-linking of regulatory pathways leads to pronounced differences in the biofilm forming capacities of different strains of S. aureus. The USA300 lineage for instance expresses RNAIII at high levels and is unable to form biofilms in absence of SigB. 45 P

P

Conversely; RNAIII mutants tend to accumulate in biofilms. 46 P

In the present study we compared the proteome of planktonically grown S. aureus HG001 from shake flask cultures to colony biofilms grown on dialysis membranes in a time-resolved 4 ACS Paragon Plus Environment

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manner. S. aureus HG001 is a derivative of the well-characterized methicillin sensitive strain S. aureus NCTC 8325 that belongs to the same lineage (CC8) as the methicillin-resistant strain S. aureus COL and the highly virulent strain S. aureus USA300. 47, P

48 P

In contrast to

other members of the S. aureus 8325 lineage, S. aureus HG001 was complemented with an intact gene encoding RsbU that is needed for SigB activation and possesses an exoprotein pattern much more similar to that of typical wild-type S. aureus. 49 P

P

Colony biofilms were introduced as a model for biofilm growth of staphylococci by Resch and coworkers. 50 Thereby, biofilm formation is induced in cells plated on a solid surface P

P

rested on nutrient agar. In order to provide comprehensive coverage of the most important subproteomes invoked in biofilms formation, we investigated the cell-surface proteins using an optimized biotinylation approach and whole cell extracts of both, planktonic and colony biofilms at several time points. This provides an overview of the physiological state of the cells and the resulting cell-surface proteome to allow comparison of both culture systems in a time-dependent manner. In this report, we highlight the adaption of S. aureus to nutrient limitation under planktonic as well as biofilm conditions in a time-line experiment and provide an proteomic in depth analysis of the changes in the regulatory network that lead to the pleiotropic changes in the expression of effector proteins under both conditions.

Material and Methods Cultivation of bacteria S. aureus strain HG001 was used for all experiments of this study. A detailed description of the strain can be found in Herbert et al. 2010. 49 S. aureus was cultivated in P

P

BioExpress1000 (Cambridge Isotope Laboratories, Inc., Andover) that contains either 15 P

P

14 P

P

N- or

N-labeled compounds in a purity of 98 % and was supplemented with 0.15 % glucose and

0.9 % sodium chloride. Each sample was prepared in

14 P

N-containing and a second time in

P



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15 P

P

N-labeled medium. The

15 P

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N-labeled samples were used to prepare the internal standard as

P

described below. Planktonic cells were grown in flasks under agitation (130 rpm) at 37°C with a medium to volume ratio of 1:5 while biofilm cells were grown on NADIR dialysis membranes as described in Resch et al. 50, 51 An overnight culture of the bacteria was diluted to an OD 540 of P

P

R

R

0.03. 100 µL of this cell suspension were used to inoculate 30 mL medium and cells were grown to an optical density of 0.6. Samples were collected and bacteria were used for inoculation of planktonic and biofilm cultures. To this end, the cell suspension was again diluted to an OD 540 of 0.03 and 100 µL of the dilution were used to inoculate 30 mL medium R

R

or the corresponding nutrient agar plates made from 30 mL of the same medium coagulated with 1.8 % select agar (Invitrogen TM ). CFU counting revealed approximately 3×10 7 colony P

P

P

P

forming units in 100 µL of the inoculum. Samples were harvested at four different time points. First, growing planktonic cells at OD 540 = 0.6, also used for inoculation of the main R

R

cultures, were analyzed, and biofilms as well as planktonic cells were harvested after 8, 12, and 24 hours of growth. Experiments were performed with three biological replicates of each condition. Preparation of whole cell protein extracts with internal 15N-standard Cells of biofilm cultures were suspended by removing the dialysis membranes from the nutrient agar plates, placing them in a 50ml-tube containing 30 mL of cold, 50 mM TEAB (Fluka), and vortexing them for 1 min. Cell suspensions from biofilm and planktonic cultures were sedimented by centrifugation (10,000 × g, 10 min, 4°C). Cells were washed by suspension in 50 mM TEAB and repeated sedimentation. Subsequently, cells were resuspended in TEAB (0.2 g cells per mL TEAB) and subjected to mechanical cell disruption. To this end, 0.5 mL of each cell suspension were transferred into a culture tube prefilled with 0.5 mL glass beads (Sartorius Stedim Biotech, Göttingen, Ø 0.1-0.11 mm) and homogenized 6 ACS Paragon Plus Environment

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two times at 6,800 rpm for 30 s using the Precellys 24 (Bertim Technologies, Montigny-leBretonneux, France) with intermittent cooling. The protein concentration of the cell extracts was determined using Roti ® -Nanoquant as described by the manufacturer. An internal protein P

P

standard was prepared by mixing equal amounts of total protein from each 15 N-labeled extract. P

Fifteen µg protein of each sample obtained from cultivation in

14 P

P

P

N-medium was mixed with

fifteen µg 15 N-protein of the standard and subjected to GeLC-MS analysis. P

P

Enrichment of cell-surface proteins by the biotinylation approach Cell-surface proteomic samples were prepared by a biotinylation approach optimized on the basis of Hempel et al. 52, 53 Cells were washed once in PBS (pH 8) and 0.1 g (fresh weight) P

P

deposited cells were resuspended in 1 mL PBS (pH 8, 4°C). Cells were labelled with SulfoNHS-SS-biotin (Thermo Scientific, Germany) at a concentration of 1.5 mM under agitation for one hour on ice. Cells were sedimented (20,000 × g, 1 min, 4°C). The supernatant was discarded and reactive Sulfo-NHS-SS-biotin was eliminated by resuspension of the cells in 1 mL PBS (pH 8) containing 0.5 M glycine. This was repeated three times. Finally, cells were resuspended in 0.2 mL PBS (pH 8) containing 5 % (w/v) iodoacetamide and stored at -80°C. Equal volumes of all suspensions containing

15 P

N-labelled cells were mixed to obtain a

P

standard with cells from each physiological state. 0.2 mL of the 0.2 mL of each

14 P

P

15 P

P

15 P

P

N-

N-standard was added to

N-sample resulting in a sample that originated from approximately 0.2 g

fresh cells. Cell disruption was performed as described for preparation of cytoplasmic protein extracts. Subsequently, 100 µl PBS (pH 8) containing 20 % (w/v) CHAPS and 20 % (w/v) ASB-14 were added and the samples were homogenized using the Precellys 24 as described for cell disruption. Samples were incubated on ice for 30 min to allow solubilization of hydrophobic proteins. After sedimentation of cell debris (15,800 × g, 30 min, 4°C), the protein extract (supernatant) was incubated with 150 µL NeutrAvidin High Capacity Agarose beads (Thermo Scientific, Germany) that had been washed with PBS (pH 8) containing 1 % 7 ACS Paragon Plus Environment


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(v/v) NP-40. NeutrAvidin agarose was washed four times with PBS (pH 8) containing 1 % (v/v) NP-40 and 6 % (w/v) CHAPS and two times with PBS (pH 8) containing 1 % (v/v) NP40 and 2 % (w/v) SDS to remove unspecifically bound proteins. The elution of biotinylated proteins was accomplished by addition of 1 mL β-mercaptoethanol (5 %) in water. The eluted proteins were subjected to acetone precipitation (20 % sample, 80 % acetone, -20°C, overnight). The precipitated proteins were deposited by centrifugation (10,000 × g, 30 min, 4°C) and washed in absolute ethanol. The protein pellets were dried using a SpeedVac (Eppendorf) and dissolved in 15 µL HTH (6 M urea, 2 M thiourea in water). Finally, 8 µL of SDS sample buffer were added and the samples were subjected to GeLC-MS analyses. GeLC-MS analysis Proteins were separated by SDS-PAGE. 54 Gel lanes were divided into 12 pieces for P

P

samples from whole cell extracts and into 10 pieces for analysis of cell-surface protein samples. Gel pieces were destained and equilibrated for tryptic digestion with 30 % acetonitrile in aqueous solution containing 200 mM ammonium bicarbonate. Gel pieces were dried in a vacuum centrifuge for 30 min and covered with trypsin solution (2 µg mL -1 , P

P

Promega). After complete rehydration at 4°C, access trypsin solution was removed and the digest proceeded for 14 h at 37°C. Gel pieces were covered with 100 µL water and incubated in an ultrasonic bath for 15 min. The supernatants were transferred into vials and concentrated to 10 µL or 50 µL for the cytoplasmic proteins or the enriched cell-surface proteins, respectively. LC-MS analysis was done as described previously. 52 In brief, peptides were P

P

separated with a 80 min gradient using a NanoAcquity (Waters) equipped with a C18 reversed phase trapping column and a 100 mm long analytical column. A survey scan was acquired with an Orbitrap Classic at resolution 30,000 followed by CID fragment spectra of the five most abundant precursor ions.


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Data analysis Database search was done using Sorcerer TM -Sequest ® against the S. aureus NCTC 8325 P

P

P

P

database (uid57795) downloaded from NCBI (ftp://ftp.ncbi.nlm.nih.gov/genomes/). Common laboratory contaminants were included and a decoy database consisting of the reverse sequences was attached (in total 5,866 sequences). Trypsin was specified to cut after lysine and arginine allowing two missed cleavages. The maximum mass error tolerance was set to 10 ppm for precursor ions and 1 amu for fragment ions. Oxidation of methionine and in case of cell-surface proteomic samples also carbamidomethylation of cysteine were considered as variable modifications with a maximum of three modifications per peptide. A second database 15

search was done determining the mass shift of

P

P

N-labeled amino acids as static

modifications. Sequest output files of both searches were merged and filtered using DTASelect 2.0.25 as described previously. 53 The ratios of peak areas between P

14

P

P

P

N- and

the 15 N-peptides were determined using Census as described previously. 55 Relative protein P

P

P

14

amounts were calculated by division of the

P

P

P

N/ 15 N-ratios between samples. If the P

P

chromatographic peaks of all identified peptides of a protein were exclusively visible as the 15 P

P

N-labeled peptide but not as the

14 P

P

N-peptide, the protein was designated as not present in

the sample (OFF). LocateP was used to predict the subcellular localization of identified proteins. 56 Median P

P

normalization was performed on the relative quantitative values. In the case of cell-surface proteome samples, only proteins predicted to be non-cytoplasmic were taken into account to determine the median. Quantification was carried out if

14 P

N/ 15 N-ratios could be determined

P

P

P

by Census with a coefficient of determination of R 2 ≤0.7 for at least two peptides of a given P

P

protein and if the protein could be quantified in at least two of three replicates. Significance of differences in the protein amount between samples was evaluated using LIMMA and rank products as described by Schwämmle et al. 2013. 57 LIMMA was conducted using R and rank P

P

products were calculated in MeV (TM4) with a critical p-value of 0.05. 58, 59 9 P

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Data visualization in treemaps For interpretation, proteome data were visualized in Voronoi Treemaps using Paver (Decodon) relying on the functional protein categorization obtained from TheSeed for S. aureus NCTC 8325. 60, 61 Additional information on biological functions was obtained from P

P

Uniprot ( http://www.uniprot.org/ ), Microbes Online ( http://www.microbesonline.org ) and 15T

15T

15T

15T

KEGG ( http://www.genome.jp/kegg-bin/get_htext?ko00001.keg ) or research publications as 15T

15T

indicated in Table S3. 62–64 To increase the clustering of functionally linked proteins in the P

P

Voronoi Treemaps, an operon prediction was implemented on the basis of Microbes Online ( http://www.microbesonline.org/operons/ ). Proteins of unknown function were excluded 15T

15T

from visualization in Voronoi Treemaps. Furthermore, a regulon map was created in order to uncover the influence of regulatory proteins on the proteome composition. Publically available data of multiple references were implemented as indicated in Table S4. For visualization in treemaps, data acquired from both subproteomes were combined based on the LocateP subcellular localization prediction. Quantitative values for cytoplasmic proteins were exclusively adopted from analyses of whole cell extracts. Quantitative values for proteins with a predicted non-cytoplasmic localization were depicted from results achieved by the biotinylation approach. Data for proteins with non-cytoplasmic localization that could not be quantified from surface proteome analyses but from whole cell extracts were adopted from analyses of whole cells extracts. Biofilm assay in 96 well plates In order to investigate the effect of glucose and sodium chloride to induce biofilm formation in S. aureus HG001, static biofilm assays were carried out as essentially described in Merritt et al. 2005. 65 96 well microplates made from polystyrene (Biorad) were sterilized P

P

with 70 % ethanol for one hour. Microplates were dried and the outer two rows of wells were filled with water in order to minimize variations arising from unequal distribution of oxygen. 10 ACS Paragon Plus Environment

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Eight wells per condition were filled with BioExpress1000 supplemented with glucose and sodium chloride as indicated. The wells were inoculated with overnight cultures to an OD 540 R

R

of 0.05. Experiments were carried out in two different microplates with eight replicates per condition each. Microplates were covered, incubated for 24 hours at 37°C and cell density was measured as OD 540 . The supernatant was removed and wells were washed three times R

R

with 300 µL 0.9 % NaCl using a HandyStep ® electronic (Brand) with a 5 ml syringe at the P

P

lowest speed possible. Biofilms were stained for 15 min with 300 µL crystal violet (0.1 % (w/v) in H 2 0, filtered). The staining solution was removed and wells were washed twice as R

R

described above. Remaining dye at biofilms was quantitatively solubilized with cool acetic acid (33 % in H 2 O dest ) for 15 min under gentle shaking. Subsequently, 100 µL of the solution R

R

R

R

were transferred into new microplates and the absorbance was measured at 590 nm, which had been determined to be the maximum absorbance of the crystal violet used.

Results and Discussion: In contrast to other laboratory biofilm models (flow cells and flow-through systems), cells are not exposed to shear forces within colony biofilms. High oxygen levels alter the physiology of colony biofilms compared to most natural biofilms. Nevertheless, the model offers several advantages for proteomic comparison to planktonic cells. The proportion of dead cells is relatively low (only 10 %). 66 Similar to shake flask cultures, the concentration of P

P

nutrients decreases over time, which leads to comparable growth phases (lag phase, exponential growth, and stationary phase) and allows discrimination between changes attributed to the growth phase from changes due to the biofilm conditions. In contrast to flowthrough systems, where fresh medium is continuously provided to the biofilms, exhaustion of nutrients facilitates development of dormant cells, which exhibit increased antibiotic resistance well known from biofilms. 5, 67 Furthermore, cultivation of colony biofilms requires P

P



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less medium than cultivation of biofilms in flow-through systems. This makes isotopic labeling feasible and allows accurate relative protein quantification by mass spectrometry.

Induction of biofilm formation and microscopic investigation of colony biofilms In order to identify stimuli that induce biofilm formation of S. aureus HG001, we investigated the influence of glucose and sodium chloride on biofilms in microplates. Cells were grown at 37°C for 24 hours in 96 well microplates filled with different media as indicated. Optical density was measured in order to detect differences in growth yield that potentially cause varying amounts of biofilm and the biofilms were investigated semiquantitatively by a method employing crystal violet staining. Glucose and sodium chloride synergistically induced biofilm formation (Fig. S1). In order to induce biofilm formation but maintaining physiological conditions, BioExpress1000 medium was supplemented with 0.15% glucose and 0.9% sodium chloride for proteomic comparison of colony biofilms to planktonic cultures. Cell-surface protein enrichment and proteome coverage Treatment of intact cells with Sulfo-NHS-SS-biotin and subsequent extraction of labeled proteins with NeutrAvidin resulted in an enrichment of non-cytoplasmic proteins by a factor of ten as exemplarily shown in Fig. S2 by comparison of normalized spectral abundance factors (NSAF) of whole cell extracts and cell-surface proteome fractions. The method enriched lipoproteins, sortase-anchored proteins, and membrane proteins with extracellular domains but was less beneficial for enrichment of secretory released proteins. Both proteomic fractions were analyzed from seven physiological states. These are the exponential, transient, early stationary and late stationary phase of planktonic cultures as visible in Fig. S3 A and samples from biofilms harvested after 8 hours, 12 hours, and 24 hours of growth. GeLC-MS analysis of whole cell extracts resulted in identification of 1,188 12 ACS Paragon Plus Environment

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predicted cytoplasmic and 246 non-cytoplasmic proteins. A quantification efficiency between light and heavy isoforms of 77-87 % on the peptide level led to quantification of 90-99 % of the identified proteins within a given sample. For reliable quantification, a protein needed to be quantified in at least two of three replicates. In average 80 % of the identified cytoplasmic proteins and 65 % of the non-cytoplasmic proteins fulfilled these requirements within data from whole cell extracts. Analysis of enriched cell-surface proteome fractions resulted in identification of 880 predicted cytoplasmic proteins and 236 non-cytoplasmic proteins. In average 63 % of the predicted cytoplasmic proteins and 75 % of the non-cytoplasmic proteins could be quantified from these samples in at least two of three replicates of a given physiological state. The non-cytoplasmic proteins are of special interest. In the enriched cell-surface proteomic fractions, 115 of these proteins could be quantified in samples from all seven physiological states. From analyses of whole cell extracts, data for only 75 non-cytoplasmic proteins fulfilled the requirements for this high quantification frequency. This is of importance since relative quantification depends on quantification of the proteins in both samples to be compared. Altogether, cell-surface proteome enrichment resulted in an increased quantification frequency of 102 non-cytoplasmic proteins. The method was most advantageous for analysis of lipoproteins, of which 27 (48 % of this protein class) could be quantified more frequently than by analysis of whole cell extracts. Twelve of these 27 proteins could be quantified in samples from all physiological states after enrichment but never from data revealed by analyses of whole cell extracts. Growth phase-dependent proteomic changes in planktonic cultures Compared to the exponential growth phase, the amount of TCA cycle enzymes was increased after 8 hours (transient growth phase) and later (Fig. 1). Simultaneously, enzymes capable to degrade the amino acids glycine (glycine cleavage system), alanine (Ald2), 13 ACS Paragon Plus Environment


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arginine (arginase pathway), glutamine (GlnA) and glutamate (GluD), histidine (at least HutG), serine (SAOUHSC_02839) and threonine (Kbl and SAOUHSC_00535) were expressed more strongly in the late phases. This indicates usage of secondary carbon sources for energy production, most of which can be fed into the TCA and is in accordance with Becher et al. 2009, who investigated S. aureus COL growing in BioExpress1000 without supplements. 68 P

P

Similar to other Gram-positive bacteria, the catabolite control protein A (CcpA) ensures usage of the carbon source that facilitates fastest growth in staphylococci. 69 CcpA represses P

P

enzymes needed for catabolism of secondary carbon sources as long as glucose is present and represses TCA cycle enzymes. In S. aureus, CcpA has an impact on virulence gene expression and biofilm formation. 14, P

31, 70

The amount of CcpA-dependent catabolic enzymes was

P

increased in planktonic cells after 8 hours (Fig. 2) and later. In contrast, ribosomal proteins and proteins involved in tRNA processing decreased in the transition to the stationary phase (Fig. 1). This stringent response is widely controlled by (p)ppGpp (Fig. 2). 71 Simultaneously, P

P

proteins involved in de novo purine and pyrimidine synthesis accumulated (Fig. 1). This is surprising since nucleic acid biosynthesis, a main sink of purines and pyrimidines, is higher in fast growing cells and de novo synthesis should be downregulated in the stationary phase as it was found by others in Bacillus subtilis or Streptomyces coelicolor. 72–74 However, this effect P

P

seems to be medium specific since it was already observed in BioExpress1000 by Becher et al. 2009. 68 P

Beside CcpA and (p)ppGpp-dependent regulations, the alternative RNA polymerase sigma factor B (SigB) has a pronounced regulatory impact on adaption of the staphylococcal proteome in the stationary phase. In planktonic cultures, SigB activity appeared moderate. Strictly SigB-dependent proteins such as SAOUHSC_02582, SAOUHSC_02441, or SAOUHSC_02443 were accumulated upon 12 hours of growth and typically reached a twofold increase after 24 hours. 75 This moderate increase of SigB target proteins perfectly 14 P

P


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matches the findings of Becher et al. 2009 despite the altered medium composition and the different strain. 68 P

SarA is a virulence gene regulator that influences expression of cell-surface and exoproteins. Trancription of sarA is growth phase dependent. It is initiated from three different promoters. Two of the corresponding transcripts are maximally expressed in the early exponential growth phase and the third in the early stationary phase. 76 The latter one P

P

appears to be SigB-dependent and is needed for maximal sarA transcription. 32 In planktonic P

P

cells, the amount of the SarA protein was maximal in the exponential phase (inoculum) and lowest in the transient phase (after 8 hours of growth, Fig. 3). This fits well to the mentioned transcription profile of sarA and the finding that proteins whose expression is negatively affected by SarA, were accumulated in the transient phase (Fig. 2). In the postexponential phase, SarA facilitates transcription of RNAII and RNAIII, encoded in the agr gene locus. 33 RNAII contains the open reading frames agrA, agrB, agrC and agrD P

P

that encode an autoinducing quorum sensing system, whereas RNAIII is the main effector molecule of agr that like SarA, influences expression of many cell-surface associated and extracellular proteins including important virulence factors. 77 AgrA, the quorum sensingP

P

dependent response regulator accumulated in planktonic cells (Fig. 3) reflecting increased cell density in the late phases but the impact of RNAIII on the stationary phase proteome is difficult to evaluate since multiple regulators control almost all RNAIII-targets. Both membrane anchored lipases (Geh and Lip2) whose expression is positively influenced by RNAIII, strongly accumulated (Table S2) but a clear induction of the agr regulon was not obvious. 33 P

In planktonic cultures, adaption of the cell-surface proteome in the stationary phase was further characterized by increased expression of several proteins involved in high-affinity iron-uptake (e.g. IsdE and IsdI, around 2fold). The amount of the nucleic acid binding protein 15 ACS Paragon Plus Environment


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IsaB was remarkably increased (25fold, Table S2). 78 Composition of cell-surface proteins P

P

involved in adhesion to host factors changed considerably. The amount of clumping factor B (ClfB) and the fibronectin-binding proteins (FnbA and FnbB) decreased (approximately 2fold) indicating them to be mainly expressed during growth. SdrC, SdrD, and SasG, that are reported to promote adherence to human nasal epithelial cells, were accumulated in the late phases (approximately 4fold). 22, P

79 P

Significant changes were also observed for cytoplasmic

enzymes involved in metabolism of vitamins, cofactors, and prosthetic groups. Proteins involved in folate salvage, thiamine synthesis and degradation, as well as biotin, molybdenum cofactor, and porphyrin biosynthesis accumulated in the stationary phase (Fig. 1). These findings again, are in accordance with Becher et al. 2009. 68 P

In the transition to the stationary phase, the optical density decreased in planktonic cultures but remained stable in the stationary phase (Fig. S3 A). Concurrently, the amount of cytoplasmic proteins in the cell-surface proteome was increased compared to the inoculum (Fig. S3 B) and was generally much higher compared to biofilm cells (Fig. S3 C). This suggests lysis of a subpopulation of the planktonic cells and rebinding of cytoplasmic proteins to the cell-surface of remaining cells. It is remarkable that almost all enzymes capable to cleave peptidoglycan were found in higher amounts in the cell-surface proteome of biofilm cells in every growth phase (Fig. S3 D). This suggests the cell lysis to be controlled by a different mechanism. Recently, the staphylococcal Cid/Lrg holin/antiholin system was discovered. 80 The Cid/Lrg-system was shown to have a great influence on survival of P

P

S. aureus in the stationary phase and to affect biofilm formation by its influence on eDNA release. 13, 81 During growth on glucose, catabolite repression leads to overflow metabolism P

P

resulting in formation of acetic acid and its excretion into the culture supernatant. 82 Under this P

P

conditions, CidR induces transcription of the autolysis activating holin cidABC. 83 High levels P

P

of a second transcript spanning cidBC are further produced in a SigB-dependent manner while transcription of the antiholin lrgAB is inhibited by SigB-activity. 84 Due to the membrane 16 P


P

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localization of CidAB and LrgAB, CidC was the only protein of the Cid/Lrg-system that was identified and quantified sufficiently in our study. Its amount was generally higher in planktonic cultures compared to the biofilms (Fig S3 D) indicating a higher amount of the cotranscribed proteins CidA and CidB. This suggests the cell lysis to be attributed to the overflow metabolism and might indicate an addiction of planktonic cells to form biofilms in the medium used. Comparison of colony biofilms to planktonic cultures The growth phase dependent changes in the proteome of biofilm cells shared several features observed in planktonic cultures. If growing planktonic cultures are compared to stationary planktonic cultures (Fig. 1) and matured biofilms (Fig. 4), the amounts of many proteins are changed in the same direction in both culture systems. This concerns many proteins involved in energy metabolism, vitamin and cofactor biosynthesis, purine and pyrimidine metabolism, proteolysis, quorum sensing, many nutrient transport proteins and others. This demonstrates the general comparability of the culture systems although it becomes obvious the cells in biofilms grow slower, the extent of distinct regulations is different (Fig. 5), and proteins of several functional groups are differentially expressed due to the biofilm conditions. While planktonic cultures reached the maximal biomass (wet weight of cells) from a defined volume of medium after 8 hours, this maximum was observed after 24 hours in the biofilms (Fig. S6). Surprisingly, biofilms developed higher biomass from equal amounts of medium provided, which might be attributed to the cell lysis in planktonic cultures. Central metabolism Glucose is well accessible in planktonic cultures and leads to overflow metabolism characterized by acetate excretion. 82, 85 In the biofilm model, glucose diffuses slowly out of P

P

the agar and might be poorly accessible in the upper layers of the biofilm. This limitation 17 ACS Paragon Plus Environment


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Page 18 of 51

most probably leads to complete oxidation of glucose in the biofilms as supported by the finding that TCA cycle enzymes were much higher expressed throughout the culturing period. In contrast to a previous investigation of colony biofilms, we did not find the proteins of the glycolysis or the pentose phosphate cycle to be upregulated, which might be dependent on the medium used and the investigated growth phases. 51 In our study, the amount of P

P

gluconeogenic enzymes was higher in the biofilms (Fig. 5; Table S1). The amount of the phosphoenolpyruvate carboxykinase PckA was 4fold increased after 24 hours and the fructose-1,6-bisphosphatase Fbp was undetectable in all samples except for biofilm samples after 24 hours of growth (Fig. S7). The probably decreased availability of carbon sources in the biofilms led to an earlier and stronger expression of catabolic enzymes for usage of secondary carbon sources. This includes amino acid catabolism, proteins involved in the diaminopimelate pathway, the acetyl-CoA synthetase AcsA (involved in acetate catabolism), as well as the Fad proteins for fatty acid degradation (Figs. 5; S7). Expression of these catabolic enzymes is predominantly CcpA-dependent and their accumulation was elevated in biofilm cells (Fig. 6). The results of Gaupp et al. 2010 demonstrate that upregulation of the TCA is advantageous under nutrient limited conditions and that mutation of the succinate dehydrogenase (sdhCAB), which blocks the TCA, results in decreased growth yield under aerobic conditions. 86 P

Unlike biofilms from flow cells, arginine catabolism appears to primarily proceed by the arginase pathway in the colony biofilms. 87 This is in accordance to previous studies and P

indicates aerobic growth. 50, P

51 P

P

The (p)ppGpp-dependent stringent response was more

pronounced in biofilms at the late sample points (Fig. 6). In contrast to planktonic cultures, the amount of (p)ppGpp-synthesizing enzymes RelA2 and Ndk accumulated. 71 Their amount P

P

increased twofold in biofilms after 24 hours (Table S1). This coincided with pronounced stringent response and reflects malnutrition of cells within colony biofilms.


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Biofilm cells strongly accumulated the formate dehydrogenase SAOUHSC_02582 (up to 10fold) and the aldehyde dehydrogenase AldA. Furthermore, AldH and a putative alcohol dehydrogenase YhfP were found in increased amounts (Table S1). This raises the question if fermentative processes were elevated in at least the inner parts of the biofilms. The formate acetyltransferase (PflB) and its activating protein (PflA) were not detectable at all but transcription of these proteins in colony biofilms was previously observed to be induced. 50 P

P

Hence, increased fermentative activity in the biofilms is possible but not evident from the proteomic data. Alternatively, the formate dehydrogenase could act as a formate detoxifying enzyme, maintain the intracellular pH, and produce NADH/H+ which in turn could be used for respiration as detailed in Leibig et al. 2011. 88 Strong accumulation of formate P

P

dehydrogenase is a common feature of colony biofilms as supported by previous studies. 50, 51 P

Interestingly, the urease proteins were also found in higher amount under biofilm conditions. Compared to exponentially growing planktonic cells, the urease subunits UreE and UreG were found to be accumulated up to 9fold in planktonic cells and up to 14fold in the biofilms with a maximum after 12 hours of growth in both culture systems (Table S1). Increased expression of urease has been found previously in both, staphylococcal colony biofilms as well as in biofilms from flow cells. 50, 87 Urease cleaves urea into ammonia and P

P

carbon dioxide. It has been hypothesized that this reaction counteracts acidification and contributes to regulation of the pH too. 50 Urease was also found to be upregulated in a P

P

sdhCAB mutant that strongly accumulates acetate in the growth medium. 86 Increased P

P

expression of formate dehydrogenase and urease might indicate that pH maintenance is challenging to cells within biofilms and that biofilm cells might be exposed to the cytotoxic metabolites ammonium and formic acid.



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Page 20 of 51

SigB response SigB-dependent proteins, commonly summarized as general stress response, continuously accumulated in the biofilms. Transcription of the formate dehydrogenase SAOUHSC_02582 and the alkyl hydroperoxidase SAOUHSC_02774 is solely mediated by SigB and can be regarded as marker for SigB activity. 75 Compared to planktonic cells, both proteins were P

P

expressed more strongly in biofilms (1.8fold to 10fold) at any time point sampled indicating these differences to be attributed to the applied biofilm conditions. The phosphatase RsbU that renders the anti-anti-sigma factor RsbV active, steadily accumulated in biofilms reaching a twofold higher amount compared to planktonic cells after 24 hours (Fig. 7, upper panel). Biofilm cells exhibited a dramatically increased yellow pigmentation commonly attributed to staphyloxanthin (Fig. S8). Transcription of staphyloxanthin synthesizing proteins is SigBdependent, due to a SigB-promoter upstream of crtO. 89, 90 CrtN was accumulated in biofilms P

P

after 24 hours, but undetectable in samples from planktonic cells (Table S1). The strong SigB response had a profound influence on the composition of the proteome. Among the SigB-dependent proteins that were more abundant in biofilms are the staphylococcal accessory regulator A (SarA), the alkaline shock protein 23 (Asp23) but also cell-surface proteins such as the staphylococcal secretory antigen SsaA2 or the transglycosylases IsaA and SceD. 53 SceD was found with an up to 20fold and IsaA with an up P

P

to 3fold higher amount in biofilms. Beside the dependence on SigB, the amount of IsaA is growth phase dependent with highest levels in the late exponential phase. In S. aureus strain 113, which is a SigB mutant, Resch et al. found a 2.5fold increased amount of IsaA in in colony biofilms after 8 hours of growth but in lowered amount after 48 hours. 51 The medium P

P

used in this study contained a comparably high amount of 0.67 % (w/v) glucose and IsaA is reported to be downregulated by CcpA in the presence of glucose, which might explain this inconsistency. 31 P


Page 21 of 51

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SigB is integrated in the regulatory network that controls virulence gene expression and influences expression of downstream regulators including SarA, RNAIII, and Rot (Fig. 8). SarA regulon SigB activity increases transcription of the virulence gene regulator sarA. 32, 136 SarA is a P

P

positive regulator of biofilm formation by downregulating an extracellular nuclease and proteases. 17 Compared to planktonic cells, the amount of SarA was approximately 1.5fold P

P

increased in biofilms at any time point sampled (Fig. 7, lower panel), which is consistent with the findings of Resch et al. 2006. 51 Nevertheless, this was not reflected by the amount of the P

P

quantified SarA-dependent proteins (Fig. 6) as determined by Dunman et al. 2001. 33 SarA P

activity is modulated by phosphorylation and oxidation. 115,

137

P

P

P

Additionally, expression of

most SarA target genes is influenced by other regulators such as agr, Rot, or MgrA. 138–140 P

P

Posttranscriptional modification and activity of the mentioned regulators possibly explain this inconsistency. Since SarA facilitates RNAIII and icaR expression, both of which have antibiofilm effects, inhibition of SarA-dependent gene expression might be necessary to ensure biofilm growth. 8, 132 P

agr regulon The quorum sensing responsive agr gene locus regulates virulence gene expression and contributes to biofilm dispersal and biofilm structuring by regulation of extracellular proteases and phenol-soluble modulin surfactant peptides (PSMs). 7, 38, 141 While expression of the agrP

P

dependent virulence factors is regulated by the agr effector molecule RNAIII, expression of PSMs is directly controlled by the response regulator AgrA. 142 Compared to planktonic cells, P

P

the amount of the autoinduced response regulator AgrA was increased in biofilms after 24 hours (Fig. 7, lower panel), reflecting the higher cell density in the biofilms. This high level of AgrA combined with the up to 4fold increased amount of SarZ (Fig. 7, lower panel) potentially elevates RNAIII transcription (Fig. 8) in the biofilms but the cells simultaneously 21 ACS Paragon Plus Environment


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Page 22 of 51

possessed increased amount of SarX (Fig. 7) and increased SigB activity. 33, 143 Both of which P

P

are reported to have a repressive effect on RNAIII. 9, 136, 144 This concurrent upregulation of P

P

RNAIII-inducing and RNAIII-inhibiting regulators in the biofilms suggests a model which limits RNAIII-dependent expression of virulence genes following extreme cell density in biofilms. Such a mechanism would avoid hypervirulence of biofilms but ensure the quorum sensing dependent accumulation of AgrA-dependent PSMs, necessary for biofilm structuring. Rot regulon Transcription of the repressor of toxins (Rot) is known to be reduced by SigB activity, especially in the postexponential phase. 43 Additionally, a repressive effect of SarA on rot was P

P

reported and expression of the rot mRNA is reduced posttranscriptionally by RNAIII (Fig. 8). 40,

41, 107

P

After 12 hours, the amount of Rot was 3.5fold decreased in biofilms

P

compared to planktonic cells (Fig. 7). Although Rot was identified with only one peptide in some other biofilm samples, quantification of this peptide indicated a continuous depletion of Rot in biofilms. Such a decrease of Rot in colony biofilms was not observed neither by previous transcriptomic studies, nor by gel-based proteomic investigations. 50, P

51 P

Since the

amount of Rot decreased earlier than the amount of AgrA in the biofilms exceeded the level in planktonic cells (Fig. 7, lower panel), downregulation of Rot by several regulatory pathways (Fig. 8) is likely. The impact of Rot on gene expression is versatile. To some extent, Rot opposes the action of RNAIII. 40, 41 It is reported to repress extracellular proteases such as staphopain B (SspB) or P

P

hemolysins such as Hla and to activate expression of the staphylococcal surface protein A (Spa), the coagulase (Coa) and others. 139 Transcription of SspB is known to be strongly P

P

repressed by Rot. 139 In accordance to these findings, we found the amount of SspB at the P

P

surface of biofilm cells to be 5fold increased after 12 hours and 3.5fold after 24hours. The extracellular protease SspB inhibits biofilm formation at the early steps but is involved in the 22 ACS Paragon Plus Environment

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dispersal of biofilms. 7, P

41, 42 P

The biofilms already matured as it became possible to harvest

enough biomass for proteomic analyses (after 8 hours). The decreased amount of Rot and hence, the increased amount of SspB might contribute to biofilm spreading as suggested by other authors. 42, 44 Decreased amount of Rot and increased amount of SspB was also observed P

P

in biofilms from flow cells compared to the exponential growth phase of planktonic cultures and appears to be a common feature of mature biofilms. 87 P

Furthermore, Rot is reported to increase the expression of SarS and its target Spa as well as ClfB, SdrC and Coa (Fig. 8). 139 The amount of these proteins was lower in our colony P

P

biofilms (Fig. 7, lower panel for SarS, Fig. 10 for ClfB and SdrC). Spa and Coa were undetectable in cell-surface proteome samples of biofilms but were identified at the surface of planktonic cells (Table S2). In interaction with the response regulator SaeR, Rot controls expression of superantigen-like proteins (Ssls) involved in immune evasion. 127 This correlates P

P

well with the finding, that Ssl1 was enriched at the surface of planktonic cells but if detectable, expressed much more weakly at the surface of biofilm cells (Table S2). Altogether, these findings indicate a profound influence of the reduced amount of Rot on virulence gene expression in biofilms. MgrA regulon Beside Rot, MgrA is another member of the MarR-like SarA-family and influences antibiotic resistance, autolysis and biofilm development. 16, 108, 145 Like SarA and SarZ, MgrAP

P

activity is modulated by phosphorylation and oxidation. 115 Compared to planktonic cells, the P

P

amount of MgrA was slightly higher in biofilms (1.5fold after 24 hours). MgrA directly induces transcription of the multidrug efflux pump AbcA. 145 Amount of AbcA was higher in P

P

biofilms (Table S1 or S2). This is also true for the MgrA targets SarX and SarZ (Fig. 7, lower panel), whose transcription is induced by MgrA (Fig. 8). 143, 144 SarX is a negative regulator of P

P

agr and consequently of RNAIII-dependent virulence factors. 144 SarZ is known to repress P


P


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Page 24 of 51

sarS and to activate RNAIII transcription. 143 Indeed, the amount of SarS was significantly P

P

decreased in biofilms at any time point (Fig. 7, lower panel) but this may also be Rotdependent. In summary, several MgrA-dependent proteins were upregulated in the biofilms although the MgrA-regulon as determined by Luong and colleagues as presented in Fig. 6 does not appear consistently induced. 140 P

Fur regulon Fur represses high-affinity iron-uptake systems in the presence of intracellular Fe 2+ . 146 The P

P

P

P

amount of the iron-uptake regulator Fur was slightly increased (1.5fold) in the biofilms (Fig. 7, lower panel). Amounts of high affinity iron uptake proteins (whose genes contain Fur boxes) were lower in biofilms, whereas the iron-storage protein FtnA was more abundant (Fig. 9). The amounts of the iron-binding proteins slightly increased (2fold) in planktonic cells in the course of the cultivation but decreased in the biofilms (Table S2). Decreased amounts of the iron-binding proteins possibly indicate a lower demand for iron in the slower growing biofilm cells. This result is supported by the findings of Beenken et al., who investigated staphylococcal biofilms from flow cells and Park et al., who investigated colony biofilms of Pseudomonas aeruginosa. 87, P

147 P

In host environments, where iron is a growth-

limiting nutrient, iron-uptake systems are usually upregulated. 148–150 Thus, a possibly lower P

P

demand for iron during biofilm growth might be an additional advantage of the biofilm lifestyle in vivo. Cell wall proteins Several sortase-anchored cell wall proteins including FnbA, FnbB, ClfB, SasC, SasG or the strain-specific Bap promote primary attachment and accumulation of biofilms. 26–28, P

79 P

Some of these proteins (e.g. ClfA and FnbAB) are well characterized and were found to be multifunctional but their regulation is poorly understood. Against the above mentioned physiological background, we observed several cell wall proteins to be differentially 24 ACS Paragon Plus Environment

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expressed between biofilms and planktonic cultures. At the surface of biofilm cells, SasF became accumulated (8fold, Fig. 10). SasF protects the staphylococci from the bactericidal effect of free long-chain unsaturated fatty acids. 151 P

P

ClfA was 4fold more abundant in biofilms after 8 hours but approximated the level of planktonic cells after 24 hours (Fig. 10). Hence, the difference in amount of ClfA appears growth phase dependent similar to SasG, which accumulated over time in both culture systems. The amount of the adhesins ClfB, SdrC, and SdrD was reduced at the surface of biofilm cells, whereby the amount of ClfB continuously decreased resulting in an up to 4fold lower amount compared to planktonic cells after 24 hours (Fig. 10). In a previous study, SdrC and SdrD were found in higher amount in the secretome of colony biofilms of S. aureus strain 113. 51 The underlying regulation of these proteins is unknown. SdrC, SdrD as well as ClfB P

P

contribute to adherence to human desquamated nasal epithelial cells. 22 From this point of P

P

view, the planktonic cells expressed higher levels of surface proteins capable to promote adhesion to host cells, whereas the biofilm cells accumulated the protective SasF. The fibronectin-binding proteins (FnbA and FnbB) were hardly detectable at the surface of biofilm cells but well quantifiable in cell-surface proteome preparations of planktonic cells, where they were highest expressed in the exponential growth phase (Table S2). Their low amount in the colony biofilms is remarkable, because they are reported to promote biofilm accumulation. 26 SarA is believed to induce their transcription and expression of fnbA is P

P

reported be higher following increased SigB-activity. 26,

32, 33, 152, 153

P

P

However, this was not

visible in our protein accumulation data. ClfA, ClfB, FnbA, and FnbB antagonize colony spreading as determined by Tsompanidou et al. 2012. 154 In our study, single colonies visible P

P

after 8 hours affiliated to a dense bacterial lawn after 24 hours. Low levels of these proteins compared to planktonic cultures might be necessary to allow spreading of colony biofilms.



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Conclusion Cell-surface protein enrichment allowed quantification of proteins involved in nutrient uptake, transmembrane transport, adhesion, virulence and cell division which were less abundant in analyses of whole cell extracts. The time-resolved proteomic approach revealed a detailed picture of the response of S. aureus to nutrient limitation in complex medium and growth under biofilm conditions. Implementation of regulon analysis into a treemap proved to be a valuable tool to assign pleiotropic changes observed in the proteome to the action of certain regulators. Nevertheless, this method relies on the current knowledge about cell regulation and responsible regulators, which is still limited. A profound influence of CcpA, (p)ppGpp, and SigB on the adaption of the staphylococcal proteome to the stationary growth phase could be highlighted. These responses were more pronounced in colony biofilms. Biofilm cells accumulated SarZ and SarX, both of which are MgrA-dependent and act positively and negatively on the expression of RNAIII, respectively. Additionally, matured biofilms were characterized by depletion of Rot and ultimately expressed a large number of effector proteins differently from their planktonic counterparts.

Supporting material: This material is available free of charge via the internet at http://pubs.acs.org . 15T

Fig. S 1: Biofilm formation in microplates. Fig. S 2 Abundance ranking Fig. S 3: Autolysis Fig. S 4: Legend Functional Categorization Fig. S 5: Legend Regulon Map Fig. S 6: Fresh weight of cells 26 ACS Paragon Plus Environment

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Fig. S 7: Energy metabolism biofilm vs planktonic Fig. S 8: Pigmentation of staphylococci Table S1 Quantification of proteins identified in whole cell extracts Table S2 Quantification of proteins identified in cell-surface proteome samples Table S3 Functional Categorization Table S4 Regulon Map This material is available free of charge via the internet at http://pubs.acs.org . 15T

The

mass

spectrometry

ProteomeXchange

proteomics

Consortium 165 P

P

via

data the

1 5T

have

PRIDE

been partner

deposited repository

to

the

with

the

dataset identifier PXD001395.

Acknowledgements: We are grateful to Christian Lassek for constructive discussions and Holger Kock for critical reading the manuscript and for editing of the text. This work was funded by the DFG and is part of the SFB Transregio 34.

References (1)

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López-Aguilera, S.; Goñi-Yeste, M. D. M.; Barrado, L.; González-RodríguezSalinas, M. C.; Otero, J. R.; Chaves, F. Staphylococcus aureus nasal colonization in medical students: Importance in nosocomial transmission. Enferm. Infecc. Microbiol. Clin. 2013, 31, (8), 500-5.

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Figures

Abstract figure



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Fig. 1: Treemap organized into functional categories: The exponential growth phase (OD 0.6) of planktonically grown S. aureus is compared to the transient phase (after 8 hours of growth). Each cell represents a single protein. The cells are clustered into functional groups of proteins as visible in more detail in Fig. S4 and Table S3. The relative protein amount is color-coded. Blue indicates reduced amount and red increased amount in the transient phase. Saturated colors indicate fold changes of at least five. Dark gray cells represent proteins that are known to be involved in the accordant biological process but could not be identified or quantified.


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Fig. 2: Regulon treemap comparing the exponential growth phase (OD 0.6) of planktonically grown S. aureus to the transient phase (after 8 hours of growth). A legend for the regulon treemap is given is Fig. S5. Each cell represents a single protein. The cells are clustered into groups of target proteins that were found to be subject to the same regulatory influence of a certain regulator in the underlying studies of regulator mutants which are indicated in Table S4. Negative regulatory influence of a given regulator on a cluster of target protein is indicated with minus and positive regulatory influence is indicated with plus behind the abbreviated name of the regulator. The relative protein amount is color-coded. Red indicates higher protein amount in the transient phase and blue indicates higher protein amount in the exponential phase. Saturated colors indicate fold changes of at least five. Dark gray cells represent proteins that are known to belong to given regulons but could not be identified or quantified.



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Fig. 3: The amount of regulatory proteins in planktonically S. aureus HG001 grown to the transient phase (8h), early stationary phase (12h) and late stationary phase (24h) is shown in relation to the amount in growing planktonic cells (OD 0.6) used for inoculation. The data are obtained by analysis of whole cell extracts. Statistically significant differences (critical p-value = 0.05) are indicated with asterisks.


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Fig. 4: Treemap organized into functional categories: Colony biofilms of S. aureus after 24 hours of growth are compared to growing planktonic cells (OD 0.6) used for inoculation. Each cell represents a single protein. The cells are clustered into functional groups of proteins as visible in more detail in Fig. S4 and Table S3. The relative protein amount is color-coded. Blue indicates reduced amount and red increased amount in the matured biofilms. Saturated colors indicate fold changes of at least five. Dark gray cells represent proteins that are known to be involved in the accordant biological process but could not be identified or quantified.



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Fig. 5: Treemap organized into functional categories: Biofilms of S. aureus are compared to planktonic cultures after 24 hours of growth. Each cell represents a single protein. The cells are clustered into functional groups of proteins as visible in more detail in Fig. S4 and Table S3. The relative protein amount is color-coded. Blue indicates reduced amount and red increased amount in the matured biofilms. Saturated colors indicate fold changes of at least five. Dark gray cells represent proteins that are known to be involved in the accordant biological process but could not be identified or quantified.


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Fig. 6: Regulon treemap comparing colony biofilms of S. aureus to planktonic cells after 24 hours of growth. A legend for the regulon treemap is given is Fig. S5. Each cell represents a single protein. The cells are clustered into groups of target proteins that were found to be subject to the same regulatory influence of a certain regulator in the underlying studies of regulator mutants which are indicated in Table S4. Negative regulatory influence of a given regulator on a target protein is indicated with minus and positive regulatory influence is indicated with plus behind the abbreviated name of the regulator. The relative protein amount is color-coded. Red indicates higher protein amount in the biofilms and blue indicates higher protein amount in planktonic cells. Saturated colors indicate fold changes of at least five. Dark gray cells represent proteins that are known to belong to the given regulon but could not be identified or quantified.



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Fig. 7: Amount of regulatory proteins in colony biofilms of S. aureus HG001 in relation to growing planktonic cells (OD 0.6) used for inoculation (upper chart) and in relation to planktonic cells of the same strain after 8 hours, 12 hours, and 24 hours of growth (lower chart). The data are obtained by analysis of whole cell extracts. Statistically significant differences (critical p-value = 0.05) are indicated with asterisks.


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Fig.8: Model of the regulatory network controlling biofilm formation and expression of virulence factors in S. aureus. Information is based on currently available publications as indicated with numbers that correspond to the list of references. Regulatory pathways of prominent importance are highlighted with bold lines. Selected general functions of specific regulons are indicated and corresponding target proteins that could be quantified in the present study are highlighted in bold.



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Fig. 9: Amount of proteins involved in acquisition and intracellular storage (FtnA) of iron is compared between colony biofilms and planktonic cells of S. aureus after 8 hours, 12 hours and 24 hours of growth (biofilm/planktonic). Statistically significant differences (critical p-Value = 0.05) are indicated with asterisks.


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Fig. 10: Amount of selected cell wall anchored proteins in colony biofilms and planktonic cells of S. aureus after 8 hours, 12 hours and 24 hours of growth is shown in relation to the amount in growing planktonic cells (OD 0.6, 0h) used for inoculation. The differences are statistically significant as determined by LIMMA (critical p-value = 0.05).


Time-Resolved Analysis of Cytosolic and Surface-Associated Proteins

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