Time-resolved quantitative proteome profiling of host-pathogen interactions: The response of Staphylococcus aureus RN1HG to internalisation by human airway epithelial cells

Time-Resolved Proteome Analysis of Listeria monocytogenes during Infection Reveals the Role of the AAA+ Chaperone ClpC for Host Cell Adaptation

The cellular proteome comprises all proteins expressed at a given time and defines an organism's phenotype under specific growth conditions. The proteome is shaped and remodeled by both protein synthesis and protein degradation. Here, we developed a new method which combines metabolic and chemical isobaric peptide labeling to simultaneously determine the time-resolved protein decay and de novo synthesis in an intracellular human pathogen. We showcase this method by investigating the Listeria monocytogenes proteome in the presence and absence of the AAA+ chaperone protein ClpC. ClpC associates with the peptidase ClpP to form an ATP-dependent protease complex and has been shown to play a role in virulence development in L. monocytogenes. However, the mechanism by which ClpC is involved in the survival and proliferation of intracellular L. monocytogenes remains elusive. Employing this new method, we observed extensive proteome remodeling in L. monocytogenes upon interaction with the host, supporting the hypothesis that ClpC-dependent protein degradation is required to initiate bacterial adaptation mechanisms. We identified more than 100 putative ClpC target proteins through their stabilization in a clpC deletion strain. Beyond the identification of direct targets, we also observed indirect effects of the clpC deletion on the protein abundance in diverse cellular and metabolic pathways, such as iron acquisition and flagellar assembly. Overall, our data highlight the crucial role of ClpC for L. monocytogenes adaptation to the host environment through proteome remodeling. IMPORTANCE Survival and proliferation of pathogenic bacteria inside the host depend on their ability to adapt to the changing environment. Profiling the underlying changes on the bacterial proteome level during the infection process is important to gain a better understanding of the pathogenesis and the host-dependent adaptation processes. The cellular protein abundance is governed by the interplay between protein synthesis and decay. The direct readout of these events during infection can be accomplished using pulsed stable-isotope labeling by amino acids in cell culture (SILAC). Combining this approach with tandem-mass-tag (TMT) labeling enabled multiplexed and time-resolved bacterial proteome quantification during infection. Here, we applied this integrated approach to investigate protein turnover during the temporal progression of adaptation of the human pathogen L. monocytogenes to its host on a system-wide scale. Our experimental approach can easily be transferred to probe the proteome remodeling in other bacteria under a variety of perturbations.

Single-Cell and Time-Resolved Profiling of Intracellular Salmonella Metabolism in Primary Human Cells

The intracellular pathogen Salmonella enterica has evolved an array of traits for propagation and invasion of the intestinal layers. It remains largely elusive how Salmonella adjusts its metabolic states to survive inside immune host cells. In this study, single-cell Raman biotechnology combined with deuterium isotope probing (Raman-DIP) have been applied to reveal metabolic changes of the typhoidal Salmonella Typhi Ty2, the nontyphoidal Salmonella Typhimurium LT2, and a clinical isolate Typhimurium D23580. By initially labeling the Salmonella strains with deuterium, we employed reverse labeling to track their metabolic changes in the time-course infection of THP-1 cell line, human monocyte-derived dendritic cells (MoDCs) and macrophages (Mf). We found that, in comparison with a noninvasive serovar, the invasive Salmonella strains Ty2 and D23580 have downregulated metabolic activity inside human macrophages and dendritic cells and used lipids as alternative carbon source, perhaps a strategy to escape from the host immune response. Proteomic analysis using high sensitivity mass spectrometry validated the findings of Raman-DIP analysis.

In vivo Proteomics Approaches for the Analysis of Bacterial Adaptation Reactions in Host-Pathogen Settings

Proteome profiling of bacteria internalized by host cells is still a challenging task, due to low amounts of bacterial proteins in host-pathogen settings and the high amounts of contaminating host proteins. Here, we describe a workflow for the enrichment of intracellular bacteria by fluorescence activated cell sorting which in combination with highly sensitive LC-MS/MS allows monitoring of about 1200 proteins from 2 to 4 × 10⁶ internalized bacterial cells as starting material.

Proteogenomics in Aid of Host-Pathogen Interaction Studies: A Bacterial Perspective

By providing useful tools to study host-pathogen interactions, next-generation omics has recently enabled the study of gene expression changes in both pathogen and infected host simultaneously. However, since great discriminative power is required to study pathogen and host simultaneously throughout the infection process, the depth of quantitative gene expression profiling has proven to be unsatisfactory when focusing on bacterial pathogens, thus preferentially requiring specific strategies or the development of novel methodologies based on complementary omics approaches. In this review, we focus on the difficulties encountered when making use of proteogenomics approaches to study bacterial pathogenesis. In addition, we review different omics strategies (i.e., transcriptomics, proteomics and secretomics) and their applications for studying interactions of pathogens with their host.

A global Staphylococcus aureus proteome resource applied to the in vivo characterization of host-pathogen interactions

Data-independent acquisition mass spectrometry promises higher performance in terms of quantification and reproducibility compared to data-dependent acquisition mass spectrometry methods. To enable high-accuracy quantification of Staphylococcus aureus proteins, we have developed a global ion library for data-independent acquisition approaches employing high-resolution time of flight or Orbitrap instruments for this human pathogen. We applied this ion library resource to investigate the time-resolved adaptation of S. aureus to the intracellular niche in human bronchial epithelial cells and in a murine pneumonia model. In epithelial cells, abundance changes for more than 400 S. aureus proteins were quantified, revealing, e.g., the precise temporal regulation of the SigB-dependent stress response and differential regulation of translation, fermentation, and amino acid biosynthesis. Using an in vivo murine pneumonia model, our data-independent acquisition quantification analysis revealed for the first time the in vivo proteome adaptation of S. aureus. From approximately 2.15 × 10⁵  S. aureus cells, 578 proteins were identified. Increased abundance of proteins required for oxidative stress response, amino acid biosynthesis, and fermentation together with decreased abundance of ribosomal proteins and nucleotide reductase NrdEF was observed in post-infection samples compared to the pre-infection state.

High-throughput proteomics and the fight against pathogens

Pathogens pose a major threat to human and animal welfare. Understanding the interspecies host-pathogen protein-protein interactions could lead to the development of novel strategies to combat infectious diseases through the rapid development of new therapeutics. The first step in understanding the host-pathogen crosstalk is to identify interacting proteins in order to define crucial hot-spots in the host-pathogen interactome, such as the proposed pharmaceutical targets by means of high-throughput proteomic methodologies. In order to obtain holistic insight into the inter- and intra-species bimolecular interactions, apart from the proteomic approach, sophisticated in silico modeling is used to correlate the obtained large data sets with other omics data and clinical outcomes. Since the main focus in this area has been directed towards human medicine, it is time to extrapolate the existing expertise to a new emerging field: the 'systems veterinary medicine'. Therefore, this review addresses high-throughput mass spectrometry-based technology for monitoring protein-protein interactions in vitro and in vivo and discusses pathogen cultivation, model host cells and available bioinformatic tools employed in vaccine development.

Costs of life - Dynamics of the protein inventory of Staphylococcus aureus during anaerobiosis

Absolute protein quantification was applied to follow the dynamics of the cytoplasmic proteome of Staphylococcus aureus in response to long-term oxygen starvation. For 1,168 proteins, the majority of all expressed proteins, molecule numbers per cell have been determined to monitor the cellular investments in single branches of bacterial life for the first time. In the presence of glucose the anaerobic protein pattern is characterized by increased amounts of glycolytic and fermentative enzymes such as Eno, GapA1, Ldh1, and PflB. Interestingly, the ferritin-like protein FtnA belongs to the most abundant proteins during anaerobic growth. Depletion of glucose finally leads to an accumulation of different enzymes such as ArcB1, ArcB2, and ArcC2 involved in arginine deiminase pathway. Concentrations of 29 exo- and 78 endometabolites were comparatively assessed and have been integrated to the metabolic networks. Here we provide an almost complete picture on the response to oxygen starvation, from signal transduction pathways to gene expression pattern, from metabolic reorganization after oxygen depletion to beginning cell death and lysis after glucose exhaustion. This experimental approach can be considered as a proof of principle how to combine cell physiology with quantitative proteomics for a new dimension in understanding simple life processes as an entity.

In Vitro Metabolic Labeling of Intestinal Microbiota for Quantitative Metaproteomics

Intestinal microbiota is emerging as one of the key environmental factors influencing or causing the development of numerous human diseases. Metaproteomics can provide invaluable information on the functional activities of intestinal microbiota and on host-microbe interactions as well. However, the application of metaproteomics in human microbiota studies is still largely limited, in part due to the lack of accurate quantitative intestinal metaproteomic methods. Most current metaproteomic microbiota studies are based on label-free quantification, which may suffer from variability during the separate sample processing and mass spectrometry runs. In this study, we describe a quantitative metaproteomic strategy, using in vitro stable isotopically ((15)N) labeled microbiota as a spike-in reference, to study the intestinal metaproteomes. We showed that the human microbiota were efficiently labeled (>95% (15)N enrichment) within 3 days under in vitro conditions, and accurate light-to-heavy protein/peptide ratio measurements were obtained using a high-resolution mass spectrometer and the quantitative proteomic software tool Census. We subsequently employed our approach to study the in vitro modulating effects of fructo-oligosaccharide and five different monosaccharides on the microbiota. Our methodology improves the accuracy of quantitative intestinal metaproteomics, which would promote the application of proteomics for functional studies of intestinal microbiota.

Staphylococcus aureus Transcriptome Architecture: From Laboratory to Infection-Mimicking Conditions

Staphylococcus aureus is a major pathogen that colonizes about 20% of the human population. Intriguingly, this Gram-positive bacterium can survive and thrive under a wide range of different conditions, both inside and outside the human body. Here, we investigated the transcriptional adaptation of S. aureus HG001, a derivative of strain NCTC 8325, across experimental conditions ranging from optimal growth in vitro to intracellular growth in host cells. These data establish an extensive repertoire of transcription units and non-coding RNAs, a classification of 1412 promoters according to their dependence on the RNA polymerase sigma factors SigA or SigB, and allow identification of new potential targets for several known transcription factors. In particular, this study revealed a relatively low abundance of antisense RNAs in S. aureus, where they overlap only 6% of the coding genes, and only 19 antisense RNAs not co-transcribed with other genes were found. Promoter analysis and comparison with Bacillus subtilis links the small number of antisense RNAs to a less profound impact of alternative sigma factors in S. aureus. Furthermore, we revealed that Rho-dependent transcription termination suppresses pervasive antisense transcription, presumably originating from abundant spurious transcription initiation in this A+T-rich genome, which would otherwise affect expression of the overlapped genes. In summary, our study provides genome-wide information on transcriptional regulation and non-coding RNAs in S. aureus as well as new insights into the biological function of Rho and the implications of spurious transcription in bacteria.

The major human pathogen Staphylococcus aureus can survive under a wide range of conditions, both inside and outside the human body. The goal of this study was to determine how S. aureus adapts to such different conditions and, additionally, we wanted to identify general factors governing the staphylococcal transcriptome architecture. Therefore, we performed a precise analysis of all RNA transcripts of S. aureus across experimental conditions ranging from in vitro growth in different media to internalization by eukaryotic host cells. We systematically mapped all transcription units, annotated non-coding RNAs, and assigned promoters controlled by particular RNA polymerase sigma factors and transcription factors. By a comparison with data available for the related Gram-positive bacterium Bacillus subtilis, we made key observations concerning the abundance and origin of antisense RNAs. Intriguingly, these findings support the view that many antisense RNAs in a bacterium like B. subtilis could be byproducts of spurious promoter recognition by condition-specific alternative sigma factors. We also report that the transcription termination factor Rho prevents widespread antisense transcription, presumably caused by pervasive transcription initiation in the A+T-rich genome of S. aureus. Altogether our study presents new perspectives on the biological significance of antisense and pervasive transcription in bacteria.

Omics Approaches for the Study of Adaptive Immunity to Staphylococcus aureus and the Selection of Vaccine Candidates

Staphylococcus aureus is a dangerous pathogen both in hospitals and in the community. Due to the crisis of antibiotic resistance, there is an urgent need for new strategies to combat S. aureus infections, such as vaccination. Increasing our knowledge about the mechanisms of protection will be key for the successful prevention or treatment of S. aureus invasion. Omics technologies generate a comprehensive picture of the physiological and pathophysiological processes within cells, tissues, organs, organisms and even populations. This review provides an overview of the contribution of genomics, transcriptomics, proteomics, metabolomics and immunoproteomics to the current understanding of S. aureus‑host interaction, with a focus on the adaptive immune response to the microorganism. While antibody responses during colonization and infection have been analyzed in detail using immunoproteomics, the full potential of omics technologies has not been tapped yet in terms of T-cells. Omics technologies promise to speed up vaccine development by enabling reverse vaccinology approaches. In consequence, omics technologies are powerful tools for deepening our understanding of the “superbug” S. aureus and for improving its control.

Shotgun proteomics of bacterial pathogens: advances, challenges and clinical implications

Mass spectrometry-based proteomics is increasingly used in analysis of bacterial pathogens. Simple experimental set-ups based on high accuracy mass spectrometry and powerful biochemical and bioinformatics tools are capable of reliably quantifying levels of several thousand bacterial proteins in a single experiment, reaching the analytical capacity to completely map whole proteomes. Here the authors present the state-of-the-art in bacterial pathogen proteomics and discuss challenges that the field is facing, especially in analysis of low abundant, modified proteins from organisms that are difficult to culture. Constant improvements in speed and sensitivity of mass spectrometers, as well as in bioinformatic and biochemical workflows will soon allow for comprehensive analysis of regulatory mechanisms of pathogenicity and enable routine application of proteomics in the clinical setting.

Challenges and Strategies for Proteome Analysis of the Interaction of Human Pathogenic Fungi with Host Immune Cells

Opportunistic human pathogenic fungi including the saprotrophic mold Aspergillus fumigatus and the human commensal Candida albicans can cause severe fungal infections in immunocompromised or critically ill patients. The first line of defense against opportunistic fungal pathogens is the innate immune system. Phagocytes such as macrophages, neutrophils and dendritic cells are an important pillar of the innate immune response and have evolved versatile defense strategies against microbial pathogens. On the other hand, human-pathogenic fungi have sophisticated virulence strategies to counteract the innate immune defense. In this context, proteomic approaches can provide deeper insights into the molecular mechanisms of the interaction of host immune cells with fungal pathogens. This is crucial for the identification of both diagnostic biomarkers for fungal infections and therapeutic targets. Studying host-fungal interactions at the protein level is a challenging endeavor, yet there are few studies that have been undertaken. This review draws attention to proteomic techniques and their application to fungal pathogens and to challenges, difficulties, and limitations that may arise in the course of simultaneous dual proteome analysis of host immune cells interacting with diverse morphotypes of fungal pathogens. On this basis, we discuss strategies to overcome these multifaceted experimental and analytical challenges including the viability of immune cells during co-cultivation, the increased and heterogeneous protein complexity of the host proteome dynamically interacting with the fungal proteome, and the demands on normalization strategies in terms of relative quantitative proteome analysis.

A proteomic perspective of the interplay of Staphylococcus aureus and human alveolar epithelial cells during infection

Infectious diseases caused by pathogens such as Staphylococcus aureus are still a major threat for human health. Proteome analyses allow detailed monitoring of the molecular interplay between pathogen and host upon internalization. However, the investigation of the responses of both partners is complicated by the large excess of host cell proteins compared to bacterial proteins as well as by the fact that only a fraction of host cells are infected. In the present study we infected human alveolar epithelial A549 cells with S. aureus HG001 pMV158GFP and separated intact bacteria from host cell debris or infected from non-infected A549 cells by cell sorting to enable detailed proteome analysis. During the first 6.5h in the intracellular milieu S. aureus displayed reduced growth rate, induction of the stringent response, adaptation to microaerobic conditions as well as cell wall stress. Interestingly, both truly infected host cells and those not infected but exposed to secreted S. aureus proteins and host cell factors showed differences in the proteome pattern compared to A549 cells which had never been in contact with S. aureus. However, adaptation reactions were more pronounced in infected compared to non-infected A549 bystander cells.

[Proteomics in infectious diseases]

Infectious diseases have a high incidence in the population, causing a major impact on global health. In vitro culture of microorganisms is the first technique applied for infection diagnosis which is laborious and time consuming. In recent decades, efforts have been focused on the applicability of "Omics" sciences, highlighting the progress provided by proteomic techniques in the field of infectious diseases. This review describes the management, processing and analysis of biological samples for proteomic research.

Quantitative proteomics in the field of microbiology

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research.

Comparative proteome analysis reveals conserved and specific adaptation patterns of Staphylococcus aureus after internalization by different types of human non-professional phagocytic host cells

Staphylococcus aureus is a human pathogen that can cause a wide range of diseases. Although formerly regarded as extracellular pathogen, it has been shown that S. aureus can also be internalized by host cells and persist within these cells. In the present study, we comparatively analyzed survival and physiological adaptation of S. aureus HG001 after internalization by two human lung epithelial cell lines (S9 and A549), and human embryonic kidney cells (HEK 293). Combining enrichment of bacteria from host-pathogen assays by cell sorting and quantitation of the pathogen's proteome by mass spectrometry we characterized S. aureus adaptation during the initial phase between 2.5 h and 6.5 h post-infection. Starting with about 2 × 10⁶ bacteria, roughly 1450 S. aureus proteins, including virulence factors and metabolic enzymes were identified by spectral comparison and classical database searches. Most of the bacterial adaptation reactions, such as decreased levels of ribosomal proteins and metabolic enzymes or increased amounts of proteins involved in arginine and lysine biosynthesis, enzymes coding for terminal oxidases and stress responsive proteins or activation of the sigma factor SigB were observed after internalization into any of the three cell lines studied. However, differences were noted in central carbon metabolism including regulation of fermentation and threonine degradation. Since these differences coincided with different intracellular growth behavior, complementary profiling of the metabolome of the different non-infected host cell types was performed. This revealed similar levels of intracellular glucose but host cell specific differences in the amounts of amino acids such as glycine, threonine or glutamate. With this comparative study we provide an impression of the common and specific features of the adaptation of S. aureus HG001 to specific host cell environments as a starting point for follow-up studies with different strain isolates and regulatory mutants.

Data visualization in environmental proteomics

From raw data to gene expression profiles, from single cultures to complex microbial communities, environmental proteomics works with data of different complexity levels that need to be interpreted in detail or in its entirety. Although data visualization is closely connected with data analysis approaches, this work will solely focus on data visualization. Complementing traditional tools such as bar charts or line graphs, scientists and visualization professionals have been provided sophisticated visualization tools. Many rules and concerns regarding the display of single but also complex data will be reviewed and discussed. Visual approaches such as microcharts, heat maps, stream graphs, and tree maps will be brought to the reader's attention and demonstrated by utilizing real data sets.

Metabolic footprint analysis uncovers strain specific overflow metabolism and D-isoleucine production of Staphylococcus aureus COL and HG001

During infection processes, Staphylococcus aureus is able to survive within the host and to invade tissues and cells. For studying the interaction between the pathogenic bacterium and the host cell, the bacterial growth behaviour and its metabolic adaptation to the host cell environment provides first basic information. In the present study, we therefore cultivated S. aureus COL and HG001 in the eukaryotic cell culture medium RPMI 1640 and analyzed the extracellular metabolic uptake and secretion patterns of both commonly used laboratory strains. Extracellular accumulation of D-isoleucine was detected starting during exponential growth of COL and HG001 in RPMI medium. This non-canonical D-amino acid is known to play a regulatory role in adaptation processes. Moreover, individual uptake of glucose, accumulation of acetate, further overflow metabolites, and intermediates of the branched-chain amino acid metabolism constitute unique metabolic footprints. Altogether these time-resolved footprint analyses give first metabolic insights into staphylococcal growth behaviour in a culture medium used for infection related studies.

Aureolib - a proteome signature library: towards an understanding of staphylococcus aureus pathophysiology

Gel-based proteomics is a powerful approach to study the physiology of Staphylococcus aureus under various growth restricting conditions. We analyzed 679 protein spots from a reference 2-dimensional gel of cytosolic proteins of S. aureus COL by mass spectrometry resulting in 521 different proteins. 4,692 time dependent protein synthesis profiles were generated by exposing S. aureus to nine infection-related stress and starvation stimuli (H2O2, diamide, paraquat, NO, fermentation, nitrate respiration, heat shock, puromycin, mupirocin). These expression profiles are stored in an online resource called Aureolib (http://www.aureolib.de). Moreover, information on target genes of 75 regulators and regulatory elements were included in the database. Cross-comparisons of this extensive data collection of protein synthesis profiles using the tools implemented in Aureolib lead to the identification of stress and starvation specific marker proteins. Altogether, 226 protein synthesis profiles showed induction ratios of 2.5-fold or higher under at least one of the tested conditions with 157 protein synthesis profiles specifically induced in response to a single stimulus. The respective proteins might serve as marker proteins for the corresponding stimulus. By contrast, proteins whose synthesis was increased or repressed in response to more than four stimuli are rather exceptional. The only protein that was induced by six stimuli is the universal stress protein SACOL1759. Most strikingly, cluster analyses of synthesis profiles of proteins differentially synthesized under at least one condition revealed only in rare cases a grouping that correlated with known regulon structures. The most prominent examples are the GapR, Rex, and CtsR regulon. In contrast, protein synthesis profiles of proteins belonging to the CodY and σ(B) regulon are widely distributed. In summary, Aureolib is by far the most comprehensive protein expression database for S. aureus and provides an essential tool to decipher more complex adaptation processes in S. aureus during host pathogen interaction.

Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology

The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes ((13)C, (15)N, (36)S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

Sulfur-34S stable isotope labeling of amino acids for quantification (SULAQ34) of proteomic changes in Pseudomonas fluorescens during naphthalene degradation

The relative quantification of proteins is one of the major techniques used to elucidate physiological reactions. Because it allows one to avoid artifacts due to chemical labeling, the metabolic introduction of heavy isotopes into proteins and peptides is the preferred method for relative quantification. For eukaryotic cells, stable isotope labeling by amino acids in cell culture (SILAC) has become the gold standard and can be readily applied in a vast number of scenarios. In the microbial realm, with its highly versatile metabolic capabilities, SILAC is often not feasible, and the use of other (13)C or (15)N labeled substrates might not be practical. Here, the incorporation of heavy sulfur isotopes is shown to be a useful alternative. We introduce (34)S stable isotope labeling of amino acids for quantification and the corresponding tools required for spectra extraction and disintegration of the isotopic overlaps caused by the small mass shift. As proof of principle, we investigated the proteomic changes related to naphthalene degradation in P. fluorescens ATCC 17483 and uncovered a specific oxidative-stress-like response.

Proteomics approaches for the analysis of enriched microbial subpopulations and visualization of complex functional information

Advances in the separation of microbial subpopulations and in proteomics technologies have paved the way for the global molecular characterization of microbial cells that share common functional characteristics. Quantitative characterization of the dynamics of microbial proteomes enables an unprecedented view of the adaptive responses of microbes to environmental stimuli or during interaction with other species or host cells. However, the intrinsic complexity of such data requires sophisticated visualization methods for the display, mining, interpretation and efficient exploitation of these data resources. In this review, we discuss how new approaches in data visualization such as streamgraphs, network graphs or Voronoi treemaps are being used in the field to provide new insights into the functional complexity of microbial cells, populations and multispecies consortia.

Protein-based stable isotope probing (protein-SIP) in functional metaproteomics

The community phenotype as the sum of molecular functions of organisms living in consortia strongly depends on interactions within these communities. Therefore, the analyses of the most significant molecules in terms of the phenotype, the proteins, have to be performed on samples without disrupting the meta-species environment. Due to the increasing genomic information, proteins provide insights into a potential molecular function and the phylogenetic structure of the community. Unfortunately, the lists of identified proteins are often based first on the technical capacity of the used methods or instruments, and second on the interpretation of them by the assignment of molecular functions to proteins in databases. Especially in non-model organisms the functions of many proteins are often not known and an increasing number of studies indicate a significant amount of uncertainty. To decrease the dependency on assumptions and to enable functional insights by metaproteome approaches, the metabolic labeling from an isotopically labeled substrate can be used. Since the metabolites deriving from the substrate are very rarely species-specific, the incorporation of the stable isotope into proteins can be used as a surrogate marker for metabolic activity. The degree of incorporation can be determined accurately on the peptide level by mass spectrometry; additionally, the peptide sequence provides information on the metabolic active species. Thereby, protein-stable isotope probing (protein-SIP) adds functional information to metaproteome approaches. The classical metaproteome approaches will be reviewed with an emphasis on their attempts towards functional interpretation. The gain from functional insights into metaproteomics by using metabolic labeling of stable isotopes of carbon, nitrogen, and sulfur is reviewed with a focus on the techniques of measurement, calculation of incorporation and data processing.

Global relative and absolute quantitation in microbial proteomics

Proteomic studies are designed to yield either qualitative information on proteins (identification, distribution, posttranslational modifications, interactions, structure and function) or quantitative information (abundance, distribution within different localizations, temporal changes in abundance due to synthesis and degradation or both). To this end these studies can draw upon a wide range of qualitative and quantitative gel-based and gel-free techniques. This review summarizes current proteomic workflows for global relative or absolute protein quantitation and their application in microbial physiology.

Viable Staphylococcus aureus quantitation using ¹⁵N metabolically labeled bacteriophage amplification coupled with a multiple reaction monitoring proteomic workflow

A multiple reaction monitoring liquid chromatography method with tandem mass spectrometric detection for quantitation of Staphylococcus aureus via phage amplification detection is described. This phage amplification detection method enables rapid and accurate quantitation of viable S. aureus by detecting an amplified capsid protein from a specific phage. A known amount of metabolically labeled (15)N reference bacteriophage, utilized as the input phage and as the internal standard for quantitation, was spiked into S. aureus samples. Following a 2-h incubation, the sample was subjected to a 3-min rapid trypsin digest and analyzed by high-throughput liquid chromatography tandem mass spectrometric detection targeting peptides unique to both the (15)N (input phage) and (14)N (progeny phage) capsid proteins. Quantitation was achieved by comparing peak areas of target peptides from the metabolically labeled (15)N bacteriophage peptide internal standard with that of the wild-type (14)N peptides that were produced by phage amplification and subsequent digestion when the host bacteria was present. This approach is based on the fact that a labeled species differs from the unlabeled one in terms of its mass but exhibits almost identical chemical properties such as ion yields and retention times. A 6-point calibration curve for S. aureus concentration was constructed with standards ranging from 5.0 × 10(4) colony forming units (CFU) ml(-1) to 2.0 × 10(6) CFU ml(-1), with the (15)N reference phage spiked at a concentration of 1.0 × 10(9) plaque forming units (PFU) ml(-1). Amplification with (15)N bacteriophage coupled with LC-MS/MS detection offers speed (3 h total analysis time), sensitivity (LOD: < 5.0 × 10(4) CFU ml(-1)), accuracy, and precision for quantitation of S. aureus.

Advanced tool for characterization of microbial cultures by combining cytomics and proteomics

Flow cytometry approaches are applicable to recover sub-populations of microbial cultures in a purified form. To examine the characteristics of each sorted cell population, Omics technologies can be used for comprehensively monitoring cellular physiology, adaptation reactions, and regulated processes. In this study, we combined flow cytometry and gel-free proteomic analysis to investigate an artificial mixed bacterial culture consisting of Escherichia coli K-12 and Pseudomonas putida KT2440. Therefore, a filter-based device technique and an on-membrane digestion protocol were combined in conjunction with liquid chromatography and mass spectrometry. This combination enabled us to identify 903 proteins from sorted E. coli K-12 and 867 proteins from sorted P. putida KT2440 bacteria from only 5 x 10(6) cells of each. Comparative proteomic analysis of sorted and non-sorted samples was done to prove that sorting did not significantly influence the bacterial proteome profile. We further investigated the physicochemical properties, namely M (r), pI, hydropathicity, and transmembrane helices of the proteins covered. The on-membrane digestion protocol applied did not require conventional detergents or urea, but exhibited similar recovery of all protein classes as established protocols with non-sorted bacterial samples.