Proteome-wide selected reaction monitoring assays for the human pathogen Streptococcus pyogenes

Integrated mass spectrometry-based multi-omics for elucidating mechanisms of bacterial virulence

Despite being considered the simplest form of life, bacteria remain enigmatic, particularly in light of pathogenesis and evolving antimicrobial resistance. After three decades of genomics, we remain some way from understanding these organisms, and a substantial proportion of genes remain functionally unknown. Methodological advances, principally mass spectrometry (MS), are paving the way for parallel analysis of the proteome, metabolome and lipidome. Each provides a global, complementary assay, in addition to genomics, and the ability to better comprehend how pathogens respond to changes in their internal (e.g. mutation) and external environments consistent with infection-like conditions. Such responses include accessing necessary nutrients for survival in a hostile environment where co-colonizing bacteria and normal flora are acclimated to the prevailing conditions. Multi-omics can be harnessed across temporal and spatial (sub-cellular) dimensions to understand adaptation at the molecular level. Gene deletion libraries, in conjunction with large-scale approaches and evolving bioinformatics integration, will greatly facilitate next-generation vaccines and antimicrobial interventions by highlighting novel targets and pathogen-specific pathways. MS is also central in phenotypic characterization of surface biomolecules such as lipid A, as well as aiding in the determination of protein interactions and complexes. There is increasing evidence that bacteria are capable of widespread post-translational modification, including phosphorylation, glycosylation and acetylation; with each contributing to virulence. This review focuses on the bacterial genotype to phenotype transition and surveys the recent literature showing how the genome can be validated at the proteome, metabolome and lipidome levels to provide an integrated view of organism response to host conditions.

Host-Pathogen Adhesion as the Basis of Innovative Diagnostics for Emerging Pathogens

Infectious diseases are an existential health threat, potentiated by emerging and re-emerging viruses and increasing bacterial antibiotic resistance. Targeted treatment of infectious diseases requires precision diagnostics, especially in cases where broad-range therapeutics such as antibiotics fail. There is thus an increasing need for new approaches to develop sensitive and specific in vitro diagnostic (IVD) tests. Basic science and translational research are needed to identify key microbial molecules as diagnostic targets, to identify relevant host counterparts, and to use this knowledge in developing or improving IVD. In this regard, an overlooked feature is the capacity of pathogens to adhere specifically to host cells and tissues. The molecular entities relevant for pathogen–surface interaction are the so-called adhesins. Adhesins vary from protein compounds to (poly-)saccharides or lipid structures that interact with eukaryotic host cell matrix molecules and receptors. Such interactions co-define the specificity and sensitivity of a diagnostic test. Currently, adhesin-receptor binding is typically used in the pre-analytical phase of IVD tests, focusing on pathogen enrichment. Further exploration of adhesin–ligand interaction, supported by present high-throughput “omics” technologies, might stimulate a new generation of broadly applicable pathogen detection and characterization tools. This review describes recent results of novel structure-defining technologies allowing for detailed molecular analysis of adhesins, their receptors and complexes. Since the host ligands evolve slowly, the corresponding adhesin interaction is under selective pressure to maintain a constant receptor binding domain. IVD should exploit such conserved binding sites and, in particular, use the human ligand to enrich the pathogen. We provide an inventory of methods based on adhesion factors and pathogen attachment mechanisms, which can also be of relevance to currently emerging pathogens, including SARS-CoV-2, the causative agent of COVID-19.

Generation of a mouse SWATH-MS spectral library to quantify 10148 proteins involved in cell reprogramming

Murine models are amongst the most widely used systems to study biology and pathology. Targeted quantitative proteomic analysis is a relatively new tool to interrogate such systems. Recently the need for relative quantification on hundreds to thousands of samples has driven the development of Data Independent Acquisition methods. One such technique is SWATH-MS, which in the main requires prior acquisition of mass spectra to generate an assay reference library. In stem cell research, it has been shown pluripotency can be induced starting with a fibroblast population. In so doing major changes in expressed proteins is inevitable. Here we have created a reference library to underpin such studies. This is inclusive of an extensively documented script to enable replication of library generation from the raw data. The documented script facilitates reuse of data and adaptation of the library to novel applications. The resulting library provides deep coverage of the mouse proteome. The library covers 29519 proteins (53% of the proteome) of which 7435 (13%) are supported by a proteotypic peptide.

Proteomic Applications in Antimicrobial Resistance and Clinical Microbiology Studies

Sequences of the genomes of all-important bacterial pathogens of man, plants, and animals have been completed. Still, it is not enough to achieve complete information of all the mechanisms controlling the biological processes of an organism. Along with all advances in different proteomics technologies, proteomics has completed our knowledge of biological processes all around the world. Proteomics is a valuable technique to explain the complement of proteins in any organism. One of the fields that has been notably benefited from other systems approaches is bacterial pathogenesis. An emerging field is to use proteomics to examine the infectious agents in terms of, among many, the response the host and pathogen to the infection process, which leads to a deeper knowledge of the mechanisms of bacterial virulence. This trend also enables us to identify quantitative measurements for proteins extracted from microorganisms. The present review study is an attempt to summarize a variety of different proteomic techniques and advances. The significant applications in bacterial pathogenesis studies are also covered. Moreover, the areas where proteomics may lead the future studies are introduced.

A quantitative Streptococcus pyogenes-human protein-protein interaction map reveals localization of opsonizing antibodies

A fundamental challenge in medical microbiology is to characterize the dynamic protein–protein interaction networks formed at the host–pathogen interface. Here, we generate a quantitative interaction map between the significant human pathogen, Streptococcus pyogenes, and proteins from human saliva and plasma obtained via complementary affinity-purification and bacterial-surface centered enrichment strategies and quantitative mass spectrometry. Perturbation of the network using immunoglobulin protease cleavage, mixtures of different concentrations of saliva and plasma, and different S. pyogenes serotypes and their isogenic mutants, reveals how changing microenvironments alter the interconnectivity of the interaction map. The importance of host immunoglobulins for the interaction with human complement proteins is demonstrated and potential protective epitopes of importance for phagocytosis of S. pyogenes cells are localized. The interaction map confirms several previously described protein–protein interactions; however, it also reveals a multitude of additional interactions, with possible implications for host–pathogen interactions involving other bacterial species.

Characterizing host-pathogen protein interactions can help elucidate the molecular basis of bacterial infections. Here, the authors use an integrative proteomics approach to generate a quantitative map of protein interactions between Streptococcus pyogenes and human saliva and plasma.

Purple: A Computational Workflow for Strategic Selection of Peptides for Viral Diagnostics Using MS-Based Targeted Proteomics

Emerging virus diseases present a global threat to public health. To detect viral pathogens in time-critical scenarios, accurate and fast diagnostic assays are required. Such assays can now be established using mass spectrometry-based targeted proteomics, by which viral proteins can be rapidly detected from complex samples down to the strain-level with high sensitivity and reproducibility. Developing such targeted assays involves tedious steps of peptide candidate selection, peptide synthesis, and assay optimization. Peptide selection requires extensive preprocessing by comparing candidate peptides against a large search space of background proteins. Here we present Purple (Picking unique relevant peptides for viral experiments), a software tool for selecting target-specific peptide candidates directly from given proteome sequence data. It comes with an intuitive graphical user interface, various parameter options and a threshold-based filtering strategy for homologous sequences. Purple enables peptide candidate selection across various taxonomic levels and filtering against backgrounds of varying complexity. Its functionality is demonstrated using data from different virus species and strains. Our software enables to build taxon-specific targeted assays and paves the way to time-efficient and robust viral diagnostics using targeted proteomics.

Greedy de novo motif discovery to construct motif repositories for bacterial proteomes

BACKGROUND

Bacterial surfaces are complex systems, constructed from membranes, peptidoglycan and, importantly, proteins. The proteins play crucial roles as critical regulators of how the bacterium interacts with and survive in its environment. A full catalog of the motifs in protein families and their relative conservation grade is a prerequisite to target the protein-protein interaction that bacterial surface protein makes to host proteins.

RESULTS

In this paper, we propose a greedy approach to identify conserved motifs in large sequence families iteratively. Each iteration discovers a motif de novo and masks all occurrences of that motif. Remaining unmasked sequences are subjected to the next round of motif detection until no more significant motifs can be found. We demonstrate the utility of the method through the construction of a proteome-wide motif repository for Group A Streptococcus (GAS), a significant human pathogen. GAS produce numerous surface proteins that interact with over 100 human plasma proteins, helping the bacteria to evade the host immune response. We used the repository to find that proteins part of the bacterial surface has motif architectures that differ from intracellular proteins.

CONCLUSIONS

We elucidate that the M protein, a coiled-coil homodimer that extends over 500 A from the cell wall, has a motif architecture that differs between various GAS strains. As the M protein is known to bind a variety of different plasma proteins, the results indicate that the different motif architectures are responsible for the quantitative differences of plasma proteins that various strains bind. The speed and applicability of the method enable its application to all major human pathogens.

Rapid determination of quaternary protein structures in complex biological samples

The understanding of complex biological systems is still hampered by limited knowledge of biologically relevant quaternary protein structures. Here, we demonstrate quaternary structure determination in biological samples using a combination of chemical cross-linking, high-resolution mass spectrometry and high-accuracy protein structure modeling. This approach, termed targeted cross-linking mass spectrometry (TX-MS), relies on computational structural models to score sets of targeted cross-linked peptide signals acquired using a combination of mass spectrometry acquisition techniques. We demonstrate the utility of TX-MS by creating a high-resolution quaternary model of a 1.8 MDa protein complex composed of a pathogen surface protein and ten human plasma proteins. The model is based on a dense network of cross-link distance constraints obtained directly in a mixture of human plasma and live bacteria. These results demonstrate that TX-MS can increase the applicability of flexible backbone docking algorithms to large protein complexes by providing rich cross-link distance information from complex biological samples.

Protein structure determination in complex biological samples is still challenging. Here, the authors develop a computational modeling-guided cross-linking mass spectrometry method, obtaining a high-resolution model of a 1.8 MDa protein assembly from cross-links detected in a mixture of human plasma and bacteria.

Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial

Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.

Mass Spectrometry-based Structural Analysis and Systems Immunoproteomics Strategies for Deciphering the Host Response to Endotoxin

One cause of sepsis is systemic maladaptive immune response of the host to bacteria and specifically, to Gram-negative bacterial outer-membrane glycolipid lipopolysaccharide (LPS). On the host myeloid cell surface, proinflammatory LPS activates the innate immune system via Toll-like receptor-4/myeloid differentiation factor-2 complex. Intracellularly, LPS is also sensed by the noncanonical inflammasome through caspase-11 in mice and 4/5 in humans. The minimal functional determinant for innate immune activation is the membrane anchor of LPS called lipid A. Even subtle modifications to the lipid A scaffold can enable, diminish, or abolish immune activation. Bacteria are known to modify their LPS structure during environmental stress and infection of hosts to alter cellular immune phenotypes. In this review, we describe how mass spectrometry-based structural analysis of endotoxin helped uncover major determinations of molecular pathogenesis. Through characterization of LPS modifications, we now better understand resistance to antibiotics and cationic antimicrobial peptides, as well as how the environment impacts overall endotoxin structure. In addition, mass spectrometry-based systems immunoproteomics approaches can assist in elucidating the immune response against LPS. Many regulatory proteins have been characterized through proteomics and global/targeted analysis of protein modifications, enabling the discovery and characterization of novel endotoxin-mediated protein translational modifications.

The promise of targeted proteomics for quantitative network biology

Proteomics is a powerful tool for obtaining information on a large number of proteins with regard to their expression levels, interactions with other molecules, and posttranslational modifications. Whereas nontargeted, discovery proteomics uncovers differences in the proteomic landscape under different conditions, targeted proteomics has been developed to overcome the limitations of this approach with regard to quantitation. In addition to technical advances in instruments and informatics tools, the advent of the synthetic proteome composed of synthetic peptides or recombinant proteins has advanced the adoption of targeted proteomics across a wide range of research fields. Targeted proteomics can now be applied to measurement of the dynamics of any proteins of interest under a variety of conditions as well as to estimation of the absolute abundance or stoichiometry of proteins in a given network. Multiplexed targeted proteomics assays of high reproducibility and accuracy can provide insight at the quantitative level into entire networks that govern biological phenomena or diseases. Such assays will establish a new paradigm for data-driven science.

Streptococcus pyogenes Infection and the Human Proteome with a Special Focus on the Immunoglobulin G-cleaving Enzyme IdeS

Infectious diseases are characterized by a complex interplay between host and pathogen, but how these interactions impact the host proteome is unclear. Here we applied a combined mass spectrometry-based proteomics strategy to investigate how the human proteome is transiently modified by the pathogen Streptococcus pyogenes, with a particular focus on bacterial cleavage of IgG in vivo. In invasive diseases, S. pyogenes evokes a massive host response in blood, whereas superficial diseases are characterized by a local leakage of several blood plasma proteins at the site of infection including IgG. S. pyogenes produces IdeS, a protease cleaving IgG in the lower hinge region and we find highly effective IdeS-cleavage of IgG in samples from local IgG poor microenvironments. The results show that IdeS contributes to the adaptation of S. pyogenes to its normal ecological niches. Additionally, the work identifies novel clinical opportunities for in vivo pathogen detection.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses

Liquid chromatography coupled to tandem mass spectrometry is the main method for high-throughput identification and quantification of peptides and inferred proteins. Within this field, data-independent acquisition (DIA) combined with peptide-centric scoring, exemplified by SWATH-MS, emerged as a scalable method to achieve deep and consistent proteome coverage across large-scale datasets. Here we discuss the adaptation of statistical concepts developed for discovery proteomics based on spectrum-centric scoring to large-scale DIA experiments analyzed with peptide-centric scoring strategies and provide guidance on their application. We show that optimal tradeoffs between sensitivity and specificity require careful considerations of the relationship between proteins in the samples and proteins represented in the spectral library. We propose the application of a global analyte constraint to prevent accumulation of false positives across large-scale datasets. Furthermore, to increase the quality and reproducibility of published proteomic results, well-established confidence criteria should be reported for detected peptide queries, peptides and inferred proteins.

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.

Development of Large-scale Cross-linking Mass Spectrometry

Cross-linking mass spectrometry (CLMS) provides distance constraints to study the structure of proteins, multiprotein complexes and protein-protein interactions which are critical for the understanding of protein function. CLMS is an attractive technology to bridge the gap between high-resolution structural biology techniques and proteomic-based interactome studies. However, as outlined in this review there are still several bottlenecks associated with CLMS which limit its application on a proteome-wide level. Specifically, there is an unmet need for comprehensive software that can reliably identify cross-linked peptides from large data sets. In this review we provide supporting information to reason that targeted proteomics of cross-links may provide the required sensitivity to reliably detect and quantify cross-linked peptides and that a reporter ion signature for cross-linked peptides may become a useful approach to increase confidence in the identification process of cross-linked peptides. In addition, the review summarizes the recent advances in CLMS workflows using the analysis of condensin complex in intact chromosomes as a model complex.

Targeted Proteomics and Absolute Protein Quantification for the Construction of a Stoichiometric Host-Pathogen Surface Density Model

Sepsis is a systemic immune response responsible for considerable morbidity and mortality. Molecular modeling of host-pathogen interactions in the disease state represents a promising strategy to define molecular events of importance for the transition from superficial to invasive infectious diseases. Here we used the Gram-positive bacterium Streptococcus pyogenes as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the S. pyogenes surface, the surface virulence factor M-protein, and adhered human blood plasma proteins. The workflow relies on stable isotope labeled reference peptides and selected reaction monitoring mass spectrometry analysis of a wild-type strain and an M-protein deficient mutant strain, to generate absolutely quantified protein stoichiometry ratios between S. pyogenes and interacting plasma proteins. The stoichiometry ratios in combination with a novel targeted mass spectrometry method to measure cell numbers enabled the construction of a stoichiometric surface density model using protein structures available from the protein data bank. The model outlines the topology and density of the host-pathogen protein interaction network on the S. pyogenes bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from S. pyogenes introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of S. pyogenes in human blood plasma represents a scalable framework that can continuously be refined with the emergence of new results. Future integration of new results will improve the understanding of protein-protein interactions and their importance for bacterial virulence. Furthermore, we anticipate that the general properties of the developed workflow will facilitate the production of stoichiometric surface density models for other types of host-pathogen interactions.

A Proteomic Perspective on the Bacterial Adaptation to Cold: Integrating OMICs Data of the Psychrotrophic Bacterium Exiguobacterium antarcticum B7

Since the publication of one of the first studies using 2D gel electrophoresis by Patrick H. O’Farrell in 1975, several other studies have used that method to evaluate cellular responses to different physicochemical variations. In environmental microbiology, bacterial adaptation to cold environments is a “hot topic” because of its application in biotechnological processes. As in other fields, gel-based and gel-free proteomic methods have been used to determine the molecular mechanisms of adaptation to cold of several psychrotrophic and psychrophilic bacterial species. In this review, we aim to describe and discuss these main molecular mechanisms of cold adaptation, referencing proteomic studies that have made significant contributions to our current knowledge in the area. Furthermore, we use Exiguobacterium antarcticum B7 as a model organism to present the importance of integrating genomic, transcriptomic, and proteomic data. This species has been isolated in Antarctica and previously studied at all three omic levels. The integration of these data permitted more robust conclusions about the mechanisms of bacterial adaptation to cold.

Absolute quantification of myosin heavy chain isoforms by selected reaction monitoring can underscore skeletal muscle changes in a mouse model of amyotrophic lateral sclerosis

Skeletal muscle fibers contain different isoforms of myosin heavy chain (MyHC) that define distinctive contractile properties. In light of the muscle capacity to adapt MyHC expression to pathophysiological conditions, a rapid and quantitative assessment of MyHC isoforms in small muscle tissue quantities would represent a valuable diagnostic tool for (neuro)muscular diseases. As past protocols did not meet these requirements, in the present study we applied a targeted proteomic approach based on selected reaction monitoring that allowed the absolute quantification of slow and fast MyHC isoforms in different mouse skeletal muscles with high reproducibility. This mass-spectrometry-based method was validated also in a pathological specimen, by comparison of the MyHC expression profiles in different muscles from healthy mice and a genetic mouse model of amyotrophic lateral sclerosis (ALS) expressing the SOD1(G93A) mutant. This analysis showed that terminally ill ALS mice have a fast-to-slow shift in the fiber type composition of the tibialis anterior and gastrocnemius muscles, as previously reported. These results will likely open the way to accurate and rapid diagnoses of human (neuro)muscular diseases by the proposed method. Graphical Abstract Methods for myosin heavy chain (MyHC) quantification: a comparison of classical methods and selected reaction monitoring (SRM)-based mass spectrometry approaches.

A large-scale targeted proteomics assay resource based on an in vitro human proteome

Targeted proteomics approaches are of value for deep and accurate quantification of protein abundance. Extending such methods to quantify large numbers of proteins requires the construction of predefined targeted assays. We developed a targeted proteomics platform-in vitro proteome-assisted multiple reaction monitoring (MRM) for protein absolute quantification (iMPAQT)-by using >18,000 human recombinant proteins, thus enabling protein absolute quantification on a genome-wide scale. Our platform comprises experimentally confirmed MRM assays of mass tag (mTRAQ)-labeled peptides to allow for rapid and straightforward measurement of the absolute abundance of predefined sets of proteins by mass spectrometry. We applied iMPAQT to delineate the quantitative metabolic landscape of normal and transformed human fibroblasts. Oncogenic transformation gave rise to relatively small but global changes in metabolic pathways resulting in aerobic glycolysis (Warburg effect) and increased rates of macromolecule synthesis. iMPAQT should facilitate quantitative biology studies based on protein abundance measurements.

Towards comprehensive and quantitative proteomics for diagnosis and therapy of human disease

Given superior analytical features, MS proteomics is well suited for the basic investigation and clinical diagnosis of human disease. Modern MS enables detailed functional characterization of the pathogenic biochemical processes, as achieved by accurate and comprehensive quantification of proteins and their regulatory chemical modifications. Here, we describe how high-accuracy MS in combination with high-resolution chromatographic separations can be leveraged to meet these analytical requirements in a mechanism-focused manner. We review the quantification methods capable of producing accurate measurements of protein abundance and posttranslational modification stoichiometries. We then discuss how experimental design and chromatographic resolution can be leveraged to achieve comprehensive functional characterization of biochemical processes in complex biological proteomes. Finally, we describe current approaches for quantitative analysis of a common functional protein modification: reversible phosphorylation. In all, current instrumentation and methods of high-resolution chromatography and MS proteomics are poised for immediate translation into improved diagnostic strategies for pediatric and adult diseases.

Saliva-Induced Clotting Captures Streptococci: Novel Roles for Coagulation and Fibrinolysis in Host Defense and Immune Evasion

Streptococcal pharyngitis is among the most common bacterial infections, but the molecular mechanisms involved remain poorly understood. Here we investigate the interactions among three major players in streptococcal pharyngitis: streptococci, plasma, and saliva. We find that saliva activates the plasma coagulation system through both the extrinsic and the intrinsic pathways, entrapping the bacteria in fibrin clots. The bacteria escape the clots by activating host plasminogen. Our results identify a potential function for the intrinsic pathway of coagulation in host defense and a corresponding role for fibrinolysis in streptococcal immune evasion.

Human SRMAtlas: A Resource of Targeted Assays to Quantify the Complete Human Proteome

The ability to reliably and reproducibly measure any protein of the human proteome in any tissue or cell type would be transformative for understanding systems-level properties as well as specific pathways in physiology and disease. Here, we describe the generation and verification of a compendium of highly specific assays that enable quantification of 99.7% of the 20,277 annotated human proteins by the widely accessible, sensitive, and robust targeted mass spectrometric method selected reaction monitoring, SRM. This human SRMAtlas provides definitive coordinates that conclusively identify the respective peptide in biological samples. We report data on 166,174 proteotypic peptides providing multiple, independent assays to quantify any human protein and numerous spliced variants, non-synonymous mutations, and post-translational modifications. The data are freely accessible as a resource at http://www.srmatlas.org/, and we demonstrate its utility by examining the network response to inhibition of cholesterol synthesis in liver cells and to docetaxel in prostate cancer lines.

Dinosaur: A Refined Open-Source Peptide MS Feature Detector

In bottom-up mass spectrometry (MS)-based proteomics, peptide isotopic and chromatographic traces (features) are frequently used for label-free quantification in data-dependent acquisition MS but can also be used for the improved identification of chimeric spectra or sample complexity characterization. Feature detection is difficult because of the high complexity of MS proteomics data from biological samples, which frequently causes features to intermingle. In addition, existing feature detection algorithms commonly suffer from compatibility issues, long computation times, or poor performance on high-resolution data. Because of these limitations, we developed a new tool, Dinosaur, with increased speed and versatility. Dinosaur has the functionality to sample algorithm computations through quality-control plots, which we call a plot trail. From the evaluation of this plot trail, we introduce several algorithmic improvements to further improve the robustness and performance of Dinosaur, with the detection of features for 98% of MS/MS identifications in a benchmark data set, and no other algorithm tested in this study passed 96% feature detection. We finally used Dinosaur to reimplement a published workflow for peptide identification in chimeric spectra, increasing chimeric identification from 26% to 32% over the standard workflow. Dinosaur is operating-system-independent and is freely available as open source on https://github.com/fickludd/dinosaur.

The Size of the Human Proteome: The Width and Depth

This work discusses bioinformatics and experimental approaches to explore the human proteome, a constellation of proteins expressed in different tissues and organs. As the human proteome is not a static entity, it seems necessary to estimate the number of different protein species (proteoforms) and measure the number of copies of the same protein in a specific tissue. Here, meta-analysis of neXtProt knowledge base is proposed for theoretical prediction of the number of different proteoforms that arise from alternative splicing (AS), single amino acid polymorphisms (SAPs), and posttranslational modifications (PTMs). Three possible cases are considered: (1) PTMs and SAPs appear exclusively in the canonical sequences of proteins, but not in splice variants; (2) PTMs and SAPs can occur in both proteins encoded by canonical sequences and in splice variants; (3) all modification types (AS, SAP, and PTM) occur as independent events. Experimental validation of proteoforms is limited by the analytical sensitivity of proteomic technology. A bell-shaped distribution histogram was generated for proteins encoded by a single chromosome, with the estimation of copy numbers in plasma, liver, and HepG2 cell line. The proposed metabioinformatics approaches can be used for estimation of the number of different proteoforms for any group of protein-coding genes.

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.

Quantitative Profiling of Protein Tyrosine Kinases in Human Cancer Cell Lines by Multiplexed Parallel Reaction Monitoring Assays

Protein tyrosine kinases (PTKs) play key roles in cellular signal transduction, cell cycle regulation, cell division, and cell differentiation. Dysregulation of PTK-activated pathways, often by receptor overexpression, gene amplification, or genetic mutation, is a causal factor underlying numerous cancers. In this study, we have developed a parallel reaction monitoring-based assay for quantitative profiling of 83 PTKs. The assay detects 308 proteotypic peptides from 54 receptor tyrosine kinases and 29 nonreceptor tyrosine kinases in a single run. Quantitative comparisons were based on the labeled reference peptide method. We implemented the assay in four cell models: 1) a comparison of proliferating versus epidermal growth factor-stimulated A431 cells, 2) a comparison of SW480Null (mutant APC) and SW480APC (APC restored) colon tumor cell lines, and 3) a comparison of 10 colorectal cancer cell lines with different genomic abnormalities, and 4) lung cancer cell lines with either susceptibility (11-18) or acquired resistance (11-18R) to the epidermal growth factor receptor tyrosine kinase inhibitor erlotinib. We observed distinct PTK expression changes that were induced by stimuli, genomic features or drug resistance, which were consistent with previous reports. However, most of the measured expression differences were novel observations. For example, acquired resistance to erlotinib in the 11-18 cell model was associated not only with previously reported up-regulation of MET, but also with up-regulation of FLK2 and down-regulation of LYN and PTK7. Immunoblot analyses and shotgun proteomics data were highly consistent with parallel reaction monitoring data. Multiplexed parallel reaction monitoring assays provide a targeted, systems-level profiling approach to evaluate cancer-related proteotypes and adaptations. Data are available through Proteome eXchange Accession PXD002706.

Elucidating Host-Pathogen Interactions Based on Post-Translational Modifications Using Proteomics Approaches

Microbes with the capability to survive in the host tissue and efficiently subvert its innate immune responses can cause various health hazards. There is an inherent need to understand microbial infection patterns and mechanisms in order to develop efficient therapeutics. Microbial pathogens display host specificity through a complex network of molecular interactions that aid their survival and propagation. Co-infection states further lead to complications by increasing the microbial burden and risk factors. Quantitative proteomics based approaches and post-translational modification analysis can be efficiently applied to gain an insight into the molecular mechanisms involved. The measurement of the proteome and post-translationally modified proteome dynamics using mass spectrometry, results in a wide array of information, such as significant changes in protein expression, protein abundance, the modification status, the site occupancy level, interactors, functional significance of key players, potential drug targets, etc. This mini review discusses the potential of proteomics to investigate the involvement of post-translational modifications in bacterial pathogenesis and host-pathogen interactions.

Streptococcus pneumoniae proteomics: determinants of pathogenesis and vaccine development

Streptococcus pneumoniae is a major pathogen that is responsible for a variety of invasive diseases. The bacteria gain entry initially by establishing a carriage state in the nasopharynx from where they migrate to other sites in the body. The worldwide distribution of the bacteria and the severity of the diseases have led to a significant level of interest in the development of vaccines against the bacteria. Current vaccines, based on the bacterial polysaccharide, have a number of limitations including poor immunogenicity and limited effectiveness against all pneumococcal serotypes. There are many challenges in developing vaccines that will be effective against the diverse range of isolates and serotypes for this highly variable bacterial pathogen. This review considers how proteomic technologies have extended our understanding of the pathogenic mechanisms of nasopharyngeal colonization and disease development as well as the critical areas in developing protein-based vaccines.

Comparison of Different Sample Preparation Protocols Reveals Lysis Buffer-Specific Extraction Biases in Gram-Negative Bacteria and Human Cells

We evaluated different in-solution and FASP-based sample preparation strategies for absolute protein quantification. Label-free quantification (LFQ) was employed to compare different sample preparation strategies in the bacterium Pseudomonas aeruginosa and human embryonic kidney cells (HEK), and organismal-specific differences in general performance and enrichment of specific protein classes were noted. The original FASP protocol globally enriched for most proteins in the bacterial sample, whereas the sodium deoxycholate in-solution strategy was more efficient with HEK cells. Although detergents were found to be highly suited for global proteome analysis, higher intensities were obtained for high-abundant nucleic acid-associated protein complexes, like the ribosome and histone proteins, using guanidine hydrochloride. Importantly, we show for the first time that the observable total proteome mass of a sample strongly depends on the sample preparation protocol, with some protocols resulting in a significant underestimation of protein mass due to incomplete protein extraction of biased protein groups. Furthermore, we demonstrate that some of the observed abundance biases can be overcome by incorporating a nuclease treatment step or, alternatively, a correction factor for complementary sample preparation approaches.

Identification of a Set of Conserved Eukaryotic Internal Retention Time Standards for Data-independent Acquisition Mass Spectrometry

Accurate knowledge of retention time (RT) in liquid chromatography-based mass spectrometry data facilitates peptide identification, quantification, and multiplexing in targeted and discovery-based workflows. Retention time prediction is particularly important for peptide analysis in emerging data-independent acquisition (DIA) experiments such as SWATH-MS. The indexed RT approach, iRT, uses synthetic spiked-in peptide standards (SiRT) to set RT to a unit-less scale, allowing for normalization of peptide RT between different samples and chromatographic set-ups. The obligatory use of SiRTs can be costly and complicates comparisons and data integration if standards are not included in every sample. Reliance on SiRTs also prevents the inclusion of archived mass spectrometry data for generation of the peptide assay libraries central to targeted DIA-MS data analysis. We have identified a set of peptide sequences that are conserved across most eukaryotic species, termed Common internal Retention Time standards (CiRT). In a series of tests to support the appropriateness of the CiRT-based method, we show: (1) the CiRT peptides normalized RT in human, yeast, and mouse cell lysate derived peptide assay libraries and enabled merging of archived libraries for expanded DIA-MS quantitative applications; (2) CiRTs predicted RT in SWATH-MS data within a 2-min margin of error for the majority of peptides; and (3) normalization of RT using the CiRT peptides enabled the accurate SWATH-MS-based quantification of 340 synthetic isotopically labeled peptides that were spiked into either human or yeast cell lysate. To automate and facilitate the use of these CiRT peptide lists or other custom user-defined internal RT reference peptides in DIA workflows, an algorithm was designed to automatically select a high-quality subset of datapoints for robust linear alignment of RT for use. Implementations of this algorithm are available for the OpenSWATH and Skyline platforms. Thus, CiRT peptides can be used alone or as a complement to SiRTs for RT normalization across peptide spectral libraries and in quantitative DIA-MS studies.

Complete Removal of Extracellular IgG Antibodies in a Randomized Dose-Escalation Phase I Study with the Bacterial Enzyme IdeS--A Novel Therapeutic Opportunity

IdeS is a streptococcal protease that cleaves IgG antibodies into F(ab’)₂ and Fc fragments with a unique degree of specificity, thereby providing a novel treatment opportunity of IgG-driven autoimmune conditions and antibody mediated transplant rejection. Here we report the results from a first in man, double blinded and randomized study with single ascending doses of IdeS in healthy, male subjects. Twenty healthy subjects were given intravenous single ascending doses of IdeS. With impressive efficacy IdeS cleaved the entire plasma IgG-pool only minutes after dosing. IgG reached nadir 6-24 hours after dosing and then slowly recovered. The half-life of IdeS was 4.9 (±2.8) hours at 0.24 mg/kg with the main fraction eliminated during 24 hours. Already two hours after IdeS-dosing, the phagocytic capacity of IgG/IgG-fragments was reduced to background levels. Importantly, IdeS has the capacity to inactivate Fc-mediated effector function in vivo, was considered safe with no serious adverse events, and without dose limiting toxicity in this study. The complete, rapid, but temporary removal of IgG provides a new potent therapeutic opportunity in IgG-mediated pathogenic conditions.

Building high-quality assay libraries for targeted analysis of SWATH MS data

Targeted proteomics by selected/multiple reaction monitoring (S/MRM) or, on a larger scale, by SWATH (sequential window acquisition of all theoretical spectra) MS (mass spectrometry) typically relies on spectral reference libraries for peptide identification. Quality and coverage of these libraries are therefore of crucial importance for the performance of the methods. Here we present a detailed protocol that has been successfully used to build high-quality, extensive reference libraries supporting targeted proteomics by SWATH MS. We describe each step of the process, including data acquisition by discovery proteomics, assertion of peptide-spectrum matches (PSMs), generation of consensus spectra and compilation of MS coordinates that uniquely define each targeted peptide. Crucial steps such as false discovery rate (FDR) control, retention time normalization and handling of post-translationally modified peptides are detailed. Finally, we show how to use the library to extract SWATH data with the open-source software Skyline. The protocol takes 2-3 d to complete, depending on the extent of the library and the computational resources available.

Reproducible and consistent quantification of the Saccharomyces cerevisiae proteome by SWATH-mass spectrometry

Targeted mass spectrometry by selected reaction monitoring (S/MRM) has proven to be a suitable technique for the consistent and reproducible quantification of proteins across multiple biological samples and a wide dynamic range. This performance profile is an important prerequisite for systems biology and biomedical research. However, the method is limited to the measurements of a few hundred peptides per LC-MS analysis. Recently, we introduced SWATH-MS, a combination of data independent acquisition and targeted data analysis that vastly extends the number of peptides/proteins quantified per sample, while maintaining the favorable performance profile of S/MRM. Here we applied the SWATH-MS technique to quantify changes over time in a large fraction of the proteome expressed in Saccharomyces cerevisiae in response to osmotic stress. We sampled cell cultures in biological triplicates at six time points following the application of osmotic stress and acquired single injection data independent acquisition data sets on a high-resolution 5600 tripleTOF instrument operated in SWATH mode. Proteins were quantified by the targeted extraction and integration of transition signal groups from the SWATH-MS datasets for peptides that are proteotypic for specific yeast proteins. We consistently identified and quantified more than 15,000 peptides and 2500 proteins across the 18 samples. We demonstrate high reproducibility between technical and biological replicates across all time points and protein abundances. In addition, we show that the abundance of hundreds of proteins was significantly regulated upon osmotic shock, and pathway enrichment analysis revealed that the proteins reacting to osmotic shock are mainly involved in the carbohydrate and amino acid metabolism. Overall, this study demonstrates the ability of SWATH-MS to efficiently generate reproducible, consistent, and quantitatively accurate measurements of a large fraction of a proteome across multiple samples.

Mass spectrometry-based proteomic quest for diabetes biomarkers

Diabetes mellitus (DM) is a metabolic disorder characterized by chronic hyperglycemia, which affects hundreds of millions of individuals worldwide. Early diagnosis and complication prevention of DM are helpful for disease treatment. However, currently available DM diagnostic markers fail to achieve the goals. Identification of new diabetic biomarkers assisted by mass spectrometry (MS)-based proteomics may offer solution for the clinical challenges. Here, we review the current status of biomarker discovery in DM, and describe the pressure cycling technology (PCT)-Sequential Window Acquisition of all Theoretical fragment-ion (SWATH) workflow for sample-processing, biomarker discovery and validation, which may accelerate the current quest for DM biomarkers. This article is part of a Special Issue entitled: Medical Proteomics.

DIANA--algorithmic improvements for analysis of data-independent acquisition MS data

MOTIVATION

Data independent acquisition mass spectrometry has emerged as a reproducible and sensitive alternative in quantitative proteomics, where parsing the highly complex tandem mass spectra requires dedicated algorithms. Recently, targeted data extraction was proposed as a novel analysis strategy for this type of data, but it is important to further develop these concepts to provide quality-controlled, interference-adjusted and sensitive peptide quantification.

RESULTS

We here present the algorithm DIANA and the classifier PyProphet, which are based on new probabilistic sub-scores to classify the chromatographic peaks in targeted data-independent acquisition data analysis. The algorithm is capable of providing accurate quantitative values and increased recall at a controlled false discovery rate, in a complex gold standard dataset. Importantly, we further demonstrate increased confidence gained by the use of two complementary data-independent acquisition targeted analysis algorithms, as well as increased numbers of quantified peptide precursors in complex biological samples.

AVAILABILITY AND IMPLEMENTATION

DIANA is implemented in scala and python and available as open source (Apache 2.0 license) or pre-compiled binaries from http://quantitativeproteomics.org/diana. PyProphet can be installed from PyPi (https://pypi.python.org/pypi/pyprophet).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A repository of assays to quantify 10,000 human proteins by SWATH-MS

Mass spectrometry is the method of choice for deep and reliable exploration of the (human) proteome. Targeted mass spectrometry reliably detects and quantifies pre-determined sets of proteins in a complex biological matrix and is used in studies that rely on the quantitatively accurate and reproducible measurement of proteins across multiple samples. It requires the one-time, a priori generation of a specific measurement assay for each targeted protein. SWATH-MS is a mass spectrometric method that combines data-independent acquisition (DIA) and targeted data analysis and vastly extends the throughput of proteins that can be targeted in a sample compared to selected reaction monitoring (SRM). Here we present a compendium of highly specific assays covering more than 10,000 human proteins and enabling their targeted analysis in SWATH-MS datasets acquired from research or clinical specimens. This resource supports the confident detection and quantification of 50.9% of all human proteins annotated by UniProtKB/Swiss-Prot and is therefore expected to find wide application in basic and clinical research. Data are available via ProteomeXchange (PXD000953-954) and SWATHAtlas (SAL00016-35).

Lactic acid bacterial symbionts in honeybees - an unknown key to honey's antimicrobial and therapeutic activities

Could honeybees' most valuable contribution to mankind besides pollination services be alternative tools against infections? Today, due to the emerging antibiotic-resistant pathogens, we are facing a new era of searching for alternative tools against infections. Natural products such as honey have been applied against human's infections for millennia without sufficient scientific evidence. A unique lactic acid bacterial (LAB) microbiota was discovered by us, which is in symbiosis with honeybees and present in large amounts in fresh honey across the world. This work investigates if the LAB symbionts are the source to the unknown factors contributing to honey's properties. Hence, we tested the LAB against severe wound pathogens such as methicillin-resistant Staphylococcus aureus (MRSA), Pseudomonas aeruginosa and vancomycin-resistant Enterococcus (VRE) among others. We demonstrate a strong antimicrobial activity from each symbiont and a synergistic effect, which counteracted all the tested pathogens. The mechanisms of action are partly shown by elucidating the production of active compounds such as proteins, fatty acids, anaesthetics, organic acids, volatiles and hydrogen peroxide. We show that the symbionts produce a myriad of active compounds that remain in variable amounts in mature honey. Further studies are now required to investigate if these symbionts have a potential in clinical applications as alternative tools against topical human and animal infections.

Statistical approach of functional profiling for a microbial community

BACKGROUND

Metagenomics is a relatively new but fast growing field within environmental biology and medical sciences. It enables researchers to understand the diversity of microbes, their functions, cooperation, and evolution in a particular ecosystem. Traditional methods in genomics and microbiology are not efficient in capturing the structure of the microbial community in an environment. Nowadays, high-throughput next-generation sequencing technologies are powerfully driving the metagenomic studies. However, there is an urgent need to develop efficient statistical methods and computational algorithms to rapidly analyze the massive metagenomic short sequencing data and to accurately detect the features/functions present in the microbial community. Although several issues about functions of metagenomes at pathways or subsystems level have been investigated, there is a lack of studies focusing on functional analysis at a low level of a hierarchical functional tree, such as SEED subsystem tree.

RESULTS

A two-step statistical procedure (metaFunction) is proposed to detect all possible functional roles at the low level from a metagenomic sample/community. In the first step a statistical mixture model is proposed at the base of gene codons to estimate the abundances for the candidate functional roles, with sequencing error being considered. As a gene could be involved in multiple biological processes the functional assignment is therefore adjusted by utilizing an error distribution in the second step. The performance of the proposed procedure is evaluated through comprehensive simulation studies. Compared with other existing methods in metagenomic functional analysis the new approach is more accurate in assigning reads to functional roles, and therefore at more general levels. The method is also employed to analyze two real data sets.

CONCLUSIONS

metaFunction is a powerful tool in accurate profiling functions in a metagenomic sample.

Targeted mass spectrometry analysis of neutrophil-derived proteins released during sepsis progression

Early diagnosis of severe infectious diseases is essential for timely implementation of lifesaving therapies. In a search for novel biomarkers in sepsis diagnosis we focused on polymorphonuclear neutrophils (PMNs). Notably, PMNs have their protein cargo readily stored in granules and following systemic stimulation, an immediate increase of neutrophil-borne proteins can be observed into the circulation of sepsis patients. We applied a combination of mass spectrometry (MS) based approaches, LC-MS/MS and selected reaction monitoring (SRM), to characterise and quantify the neutrophil proteome in healthy or disease conditions. With this approach we identified a neutrophil-derived protein abundance pattern in blood plasma consisting of 20 proteins that can be used as a protein signature for severe infectious diseases. Our results also show that SRM is highly sensitive, specific, and reproducible and, thus, a promising technology to study a complex, dynamic and multifactorial disease such as sepsis.

Treatment with p33 curtails morbidity and mortality in a histone-induced murine shock model

Collateral damage caused by extracellular histones has an immediate impact on morbidity and mortality in many disease models. A significant increase in the levels of extracellular histones is seen in critically ill patients with trauma and sepsis. We showed that histones are released from necrotic cells in patients with invasive skin infections. Under in vitro conditions, endogenous p33, an endothelial surface protein also known as the gC1q receptor, interacts with histones released from damaged endothelial cells. Functional analyses have revealed that recombinantly expressed p33 completely neutralizes the harmful features of histones, i.e. hemolysis of erythrocytes, lysis of endothelial cells and platelet aggregation. We also noted that mice treated with a sublethal dose of histones developed severe signs of hemolysis, thrombocytopenia and lung tissue damage already 10 min after inoculation. These complications were fully counteracted when p33 was administered together with the histones. Moreover, application of p33 significantly improved survival in mice receiving an otherwise lethal dose of histones. Together, our data suggest that treatment with p33 is a promising therapeutic approach in severe infectious diseases.

Functional and structural properties of a novel protein and virulence factor (Protein sHIP) in Streptococcus pyogenes

Streptococcus pyogenes is a significant bacterial pathogen in the human population. The importance of virulence factors for the survival and colonization of S. pyogenes is well established, and many of these factors are exposed to the extracellular environment, enabling bacterial interactions with the host. In the present study, we quantitatively analyzed and compared S. pyogenes proteins in the growth medium of a strain that is virulent to mice with a non-virulent strain. Particularly, one of these proteins was present at significantly higher levels in stationary growth medium from the virulent strain. We determined the three-dimensional structure of the protein that showed a unique tetrameric organization composed of four helix-loop-helix motifs. Affinity pull-down mass spectrometry analysis in human plasma demonstrated that the protein interacts with histidine-rich glycoprotein (HRG), and the name sHIP (streptococcal histidine-rich glycoprotein-interacting protein) is therefore proposed. HRG has antibacterial activity, and when challenged by HRG, sHIP was found to rescue S. pyogenes bacteria. This and the finding that patients with invasive S. pyogenes infection respond with antibody production against sHIP suggest a role for the protein in S. pyogenes pathogenesis.

Building a pipeline to discover and validate novel therapeutic targets and lead compounds for Alzheimer's disease

Cognitive decline, Alzheimer's disease (AD) and other causes are major public health problems worldwide. With changing demographics, the number of persons with dementia will increase rapidly. The treatment and prevention of AD and other dementias, therefore, is an urgent unmet need. There have been considerable advances in understanding the biology of many age-related disorders that cause dementia. Gains in understanding AD have led to the development of ante-mortem biomarkers of traditional neuropathology and the conduct of several phase III interventions in the amyloid-β cascade early in the disease process. Many other intervention strategies are in various stages of development. However, efforts to date have met with limited success. A recent National Institute on Aging Research Summit led to a number of requests for applications. One was to establish multi-disciplinary teams of investigators who use systems biology approaches and stem cell technology to identify a new generation of AD targets. We were recently awarded one of three such grants to build a pipeline that integrates epidemiology, systems biology, and stem cell technology to discover and validate novel therapeutic targets and lead compounds for AD treatment and prevention. Here we describe the two cohorts that provide the data and biospecimens being exploited for our pipeline and describe the available unique datasets. Second, we present evidence in support of a chronic disease model of AD that informs our choice of phenotypes as the target outcome. Third, we provide an overview of our approach. Finally, we present the details of our planned drug discovery pipeline.

A comprehensive analysis of the Streptococcus pyogenes and human plasma protein interaction network

Streptococcus pyogenes is a major human bacterial pathogen responsible for severe and invasive disease associated with high mortality rates. The bacterium interacts with several human blood plasma proteins and clarifying these interactions and their biological consequences will help to explain the progression from mild to severe infections. In this study, we used a combination of mass spectrometry (MS) based techniques to comprehensively quantify the components of the S. pyogenes-plasma protein interaction network. From an initial list of 181 interacting human plasma proteins defined using liquid chromatography (LC)-MS/MS analysis we further subdivided the interacting protein list using selected reaction monitoring (SRM) depending on the level of enrichment and protein concentration on the bacterial surface. The combination of MS methods revealed several previously characterized interactions between the S. pyogenes surface and human plasma along with many more, so far uncharacterised, possible plasma protein interactions with S. pyogenes. In follow-up experiments, the combination of MS techniques was applied to study differences in protein binding to a S. pyogenes wild type strain and an isogenic mutant lacking several important virulence factors, and a unique pair of invasive and non-invasive S. pyogenes isolates from the same patient. Comparing the plasma protein-binding properties of the wild type and the mutant and the invasive and non-invasive S. pyogenes bacteria revealed considerable differences, underlining the significance of these protein interactions. The results also demonstrate the power of the developed mass spectrometry method to investigate host-microbial relationships with a large proteomics depth and high quantitative accuracy.