Proteome-wide identification of predominant subcellular protein localizations in a bacterial model organism

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

A Practical Guide to Small Protein Discovery and Characterization Using Mass Spectrometry

Small proteins of up to ∼50 amino acids are an abundant class of biomolecules across all domains of life. Yet due to the challenges inherent in their size, they are often missed in genome annotations, and are difficult to identify and characterize using standard experimental approaches. Consequently, we still know few small proteins even in well-studied prokaryotic model organisms. Mass spectrometry (MS) has great potential for the discovery, validation, and functional characterization of small proteins. However, standard MS approaches are poorly suited to the identification of both known and novel small proteins due to limitations at each step of a typical proteomics workflow, i.e., sample preparation, protease digestion, liquid chromatography, MS data acquisition, and data analysis. Here, we outline the major MS-based workflows and bioinformatic pipelines used for small protein discovery and validation. Special emphasis is placed on highlighting the adjustments required to improve detection and data quality for small proteins. We discuss both the unbiased detection of small proteins and the targeted analysis of small proteins of interest. Finally, we provide guidelines to prioritize novel small proteins, and an outlook on methods with particular potential to further improve comprehensive discovery and characterization of small proteins.

Towards the characterization of the hidden world of small proteins in Staphylococcus aureus, a proteogenomics approach

Small proteins play essential roles in bacterial physiology and virulence, however, automated algorithms for genome annotation are often not yet able to accurately predict the corresponding genes. The accuracy and reliability of genome annotations, particularly for small open reading frames (sORFs), can be significantly improved by integrating protein evidence from experimental approaches. Here we present a highly optimized and flexible bioinformatics workflow for bacterial proteogenomics covering all steps from (i) generation of protein databases, (ii) database searches and (iii) peptide-to-genome mapping to (iv) visualization of results. We used the workflow to identify high quality peptide spectrum matches (PSMs) for small proteins (≤ 100 aa, SP100) in Staphylococcus aureus Newman. Protein extracts from S. aureus were subjected to different experimental workflows for protein digestion and prefractionation and measured with highly sensitive mass spectrometers. In total, 175 proteins with up to 100 aa (SP100) were identified. Out of these 24 (ranging from 9 to 99 aa) were novel and not contained in the used genome annotation.144 SP100 are highly conserved and were found in at least 50% of the publicly available S. aureus genomes, while 127 are additionally conserved in other staphylococci. Almost half of the identified SP100 were basic, suggesting a role in binding to more acidic molecules such as nucleic acids or phospholipids.

Bacterial riboproteogenomics: the era of N-terminal proteoform existence revealed

With the rapid increase in the number of sequenced prokaryotic genomes, relying on automated gene annotation became a necessity. Multiple lines of evidence, however, suggest that current bacterial genome annotations may contain inconsistencies and are incomplete, even for so-called well-annotated genomes. We here discuss underexplored sources of protein diversity and new methodologies for high-throughput genome reannotation. The expression of multiple molecular forms of proteins (proteoforms) from a single gene, particularly driven by alternative translation initiation, is gaining interest as a prominent contributor to bacterial protein diversity. In consequence, riboproteogenomic pipelines were proposed to comprehensively capture proteoform expression in prokaryotes by the complementary use of (positional) proteomics and the direct readout of translated genomic regions using ribosome profiling. To complement these discoveries, tailored strategies are required for the functional characterization of newly discovered bacterial proteoforms.

Tools for the Recognition of Sorting Signals and the Prediction of Subcellular Localization of Proteins From Their Amino Acid Sequences

At the time of translation, nascent proteins are thought to be sorted into their final subcellular localization sites, based on the part of their amino acid sequences (i.e., sorting or targeting signals). Thus, it is interesting to computationally recognize these signals from the amino acid sequences of any given proteins and to predict their final subcellular localization with such information, supplemented with additional information (e.g., k-mer frequency). This field has a long history and many prediction tools have been released. Even in this era of proteomic atlas at the single-cell level, researchers continue to develop new algorithms, aiming at accessing the impact of disease-causing mutations/cell type-specific alternative splicing, for example. In this article, we overview the entire field and discuss its future direction.

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.

Comparative bioinformatic and proteomic approaches to evaluate the outer membrane proteome of the fish pathogen Yersinia ruckeri

Yersinia ruckeri is the aetiological agent of enteric redmouth (ERM) disease and is responsible for significant economic losses in farmed salmonids. Enteric redmouth disease is associated primarily with rainbow trout (Oncorhynchus mykiss, Walbaum) but its incidence in Atlantic salmon (Salmo salar) is increasing. Outer membrane proteins (OMPs) of Gram-negative bacteria are located at the host-pathogen interface and play important roles in virulence. The outer membrane of Y. ruckeri is poorly characterised and little is known about its composition and the roles of individual OMPs in virulence. Here, we employed a bioinformatic pipeline to first predict the OMP composition of Y. ruckeri. Comparative proteomic approaches were subsequently used to identify those proteins expressed in vitro in eight representative isolates recovered from Atlantic salmon and rainbow trout. One hundred and forty-one OMPs were predicted from four Y. ruckeri genomes and 77 of these were identified in three or more genomes and were considered as "core" proteins. Gel-free and gel-based proteomic approaches together identified 65 OMPs in a single reference isolate and subsequent gel-free analysis identified 64 OMPs in the eight Atlantic salmon and rainbow trout isolates. Together, our gel-free and gel-based proteomic analyses identified 84 unique OMPs in Y. ruckeri. SIGNIFICANCE: Yersinia ruckeri is an important pathogen of Atlantic salmon and rainbow trout and is of major economic significance to the aquaculture industry worldwide. Disease outbreaks are becoming more problematic in Atlantic salmon and there is an urgent need to investigate in further detail the cell-surface (outer membrane) composition of strains infecting each of these host species. Currently, the outer membrane of Y. ruckeri is poorly characterised and very little is known about the OMP composition of strains infecting each of these salmonid species. This study represents the most comprehensive comparative outer membrane proteomic analysis of Y. ruckeri to date, encompassing isolates of different biotypes, serotypes, OMP-types and hosts of origin and provides insights into the potential roles of these diverse proteins in host-pathogen interactions. The study has identified key OMPs likely to be involved in disease pathogenesis and makes a significant contribution to furthering our understanding of the cell-surface composition of this important fish pathogen that will be relevant to the development of improved vaccines and therapeutics.

Proteomic Analysis and Functional Validation of a Brassica oleracea Endochitinase Involved in Resistance to Xanthomonas campestris

Black rot is a severe disease caused by the bacterium Xanthomonas campestris pv. campestris (Xcc), which can lead to substantial losses in cruciferous vegetable production worldwide. Although the use of resistant cultivars is the main strategy to control this disease, there are limited sources of resistance. In this study, we used the LC-MS/MS technique to analyze young cabbage leaves and chloroplast-enriched samples at 24 h after infection by Xcc, using both susceptible (Veloce) and resistant (Astrus) cultivars. A comparison between susceptible Xcc-inoculated plants and the control condition, as well as between resistant Xcc-inoculated plants with the control was performed and more than 300 differentially abundant proteins were identified in each comparison. The chloroplast enriched samples contributed with the identification of 600 additional protein species in the resistant interaction and 900 in the susceptible one, which were not detected in total leaf sample. We further determined the expression levels for 30 genes encoding the identified differential proteins by qRT-PCR. CHI-B4 like gene, encoding an endochitinase showing a high increased abundance in resistant Xcc-inoculated leaves, was selected for functional validation by overexpression in Arabidopsis thaliana. Compared to the wild type (Col-0), transgenic plants were highly resistant to Xcc indicating that CHI-B4 like gene could be an interesting candidate to be used in genetic breeding programs aiming at black rot resistance.

Functional Genomics Approaches to Studying Symbioses between Legumes and Nitrogen-Fixing Rhizobia

Biological nitrogen fixation gives legumes a pronounced growth advantage in nitrogen-deprived soils and is of considerable ecological and economic interest. In exchange for reduced atmospheric nitrogen, typically given to the plant in the form of amides or ureides, the legume provides nitrogen-fixing rhizobia with nutrients and highly specialised root structures called nodules. To elucidate the molecular basis underlying physiological adaptations on a genome-wide scale, functional genomics approaches, such as transcriptomics, proteomics, and metabolomics, have been used. This review presents an overview of the different functional genomics approaches that have been performed on rhizobial symbiosis, with a focus on studies investigating the molecular mechanisms used by the bacterial partner to interact with the legume. While rhizobia belonging to the alpha-proteobacterial group (alpha-rhizobia) have been well studied, few studies to date have investigated this process in beta-proteobacteria (beta-rhizobia).

Comparative Genomics of Completely Sequenced Lactobacillus helveticus Genomes Provides Insights into Strain-Specific Genes and Resolves Metagenomics Data Down to the Strain Level

Although complete genome sequences hold particular value for an accurate description of core genomes, the identification of strain-specific genes, and as the optimal basis for functional genomics studies, they are still largely underrepresented in public repositories. Based on an assessment of the genome assembly complexity for all lactobacilli, we used Pacific Biosciences' long read technology to sequence and de novo assemble the genomes of three Lactobacillus helveticus starter strains, raising the number of completely sequenced strains to 12. The first comparative genomics study for L. helveticus—to our knowledge—identified a core genome of 988 genes and sets of unique, strain-specific genes ranging from about 30 to more than 200 genes. Importantly, the comparison of MiSeq- and PacBio-based assemblies uncovered that not only accessory but also core genes can be missed in incomplete genome assemblies based on short reads. Analysis of the three genomes revealed that a large number of pseudogenes were enriched for functional Gene Ontology categories such as amino acid transmembrane transport and carbohydrate metabolism, which is in line with a reductive genome evolution in the rich natural habitat of L. helveticus. Notably, the functional Clusters of Orthologous Groups of proteins categories “cell wall/membrane biogenesis” and “defense mechanisms” were found to be enriched among the strain-specific genes. A genome mining effort uncovered examples where an experimentally observed phenotype could be linked to the underlying genotype, such as for cell envelope proteinase PrtH3 of strain FAM8627. Another possible link identified for peptidoglycan hydrolases will require further experiments. Of note, strain FAM22155 did not harbor a CRISPR/Cas system; its loss was also observed in other L. helveticus strains and lactobacillus species, thus questioning the value of the CRISPR/Cas system for diagnostic purposes. Importantly, the complete genome sequences proved to be very useful for the analysis of natural whey starter cultures with metagenomics, as a larger percentage of the sequenced reads of these complex mixtures could be unambiguously assigned down to the strain level.

Identification of AHL- and BDSF-Controlled Proteins in Burkholderia cenocepacia by Proteomics

We used comparative proteome analysis to determine the target genes of the two quorum sensing (QS) circuits in the opportunistic pathogen Burkholderia cenocepacia: the N-acyl homoserine lactone (AHL)-based CepIR system and the BDSF (B urkholderia diffusible signal factor, cis-2-dodecenoic acid)-based RpfFR system. In this book chapter, we focus on the description of the practical procedure we currently use in the laboratory to perform a sensitive GeLC-MS/MS shotgun proteomics experiment; we also briefly describe the downstream bioinformatic data analysis.

An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics

Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations. Our strategy toward accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs (a modified six-frame translation considering alternative start codons) in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics data set against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and single amino acid variations (SAAVs) identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin. We release iPtgxDBs for B. henselae, Bradyrhizobium diazoefficiens and Escherichia coli and the software to generate both proteogenomics search databases and integrated annotation files that can be viewed in a genome browser for any prokaryote.

Gene Transfer Agent Promotes Evolvability within the Fittest Subpopulation of a Bacterial Pathogen

The Bartonella gene transfer agent (BaGTA) is an archetypical example for domestication of a phage-derived element to permit high-frequency genetic exchange in bacterial populations. Here we used multiplexed transposon sequencing (TnSeq) and single-cell reporters to globally define the core components and transfer dynamics of BaGTA. Our systems-level analysis has identified inner- and outer-circle components of the BaGTA system, including 55 regulatory components, as well as an additional 74 and 107 components mediating donor transfer and recipient uptake functions. We show that the stringent response signal guanosine-tetraphosphate (ppGpp) restricts BaGTA induction to a subset of fast-growing cells, whereas BaGTA particle uptake depends on a functional Tol-Pal trans-envelope complex that mediates outer-membrane invagination upon cell division. Our findings suggest that Bartonella evolved an efficient strategy to promote genetic exchange within the fittest subpopulation while disfavoring exchange of deleterious genetic information, thereby facilitating genome integrity and rapid host adaptation.

Comparative Subcellular Proteomics Analysis of Susceptible and Near-isogenic Resistant Bombyx mori (Lepidoptera) Larval Midgut Response to BmNPV infection

The molecular mechanism of silkworm resistance to Bombyx mori nucleopolyhedrovirus (BmNPV) infection remains largely unclear. Accumulating evidence suggests that subcellular fractionation combined with proteomics is an ideal technique to analyse host antiviral mechanisms. To clarify the anti-BmNPV mechanism of the silkworm, the near-isogenic line BC9 (resistant strain) and the recurrent parent P50 (susceptible strain) were used in a comparative subcellular proteomics study. Two-dimensional gel electrophoresis (2-DE) combined with mass spectrometry (MS) was conducted on proteins extracted from the cytosol, mitochondria, and microsomes of BmNPV-infected and control larval midguts. A total of 87 proteins were successfully identified from the three subcellular fractions. These proteins were primarily involved in energy metabolism, protein metabolism, signalling pathways, disease, and transport. In particular, disease-relevant proteins were especially changed in microsomes. After infection with BmNPV, differentially expressed proteins (DEPs) primarily appeared in the cytosolic and microsomal fractions, which indicated that these two fractions might play a more important role in the response to BmNPV infection. After removing genetic background and individual immune stress response proteins, 16 proteins were identified as potentially involved in repressing BmNPV infection. Of these proteins, the differential expression patterns of 8 proteins according to reverse transcription quantitative PCR (RT-qPCR) analyses were consistent with the 2-DE results.

Spatiotemporal Models of the Asymmetric Division Cycle of Caulobacter crescentus

The spatial localization of proteins within the cytoplasm of bacteria is an underappreciated but critical aspect of cell cycle regulation for many prokaryotes. In Caulobacter crescentus-a model organism for the study of asymmetric cell reproduction in prokaryotes-heterogeneous localization of proteins has been identified as the underlying cause of asymmetry in cell morphology, DNA replication, and cell division. However, significant questions remain. Firstly, the mechanisms by which proteins localize in the organelle-free prokaryotic cytoplasm remain obscure. Furthermore, how variations in the spatial and temporal dynamics of cell fate determinants regulate signaling pathways and orchestrate the complex programs of asymmetric cell division and differentiation are subjects of ongoing research. In this chapter, we review current efforts in investigating these two questions. We describe how mathematical models of spatiotemporal protein dynamics are being used to generate and test competing hypotheses and provide complementary insight about the control mechanisms that regulate asymmetry in protein localization and cell division.

Mass Spectrometry-Based Bacterial Proteomics: Focus on Dermatologic Microbial Pathogens

The composition of human skin acts as a natural habitat for various bacterial species that function in a commensal and symbiotic fashion. In a healthy individual, bacterial flora serves to protect the host. Under certain conditions such as minor trauma, impaired host immunity, or environmental factors, the risk of developing skin infections is increased. Although a large majority of bacterial associated skin infections are common, a portion can potentially manifest into clinically significant morbidity. For example, Gram-positive species that typically reside on the skin such as Staphylococcus and Streptococcus can cause numerous epidermal (impetigo, ecthyma) and dermal (cellulitis, necrotizing fasciitis, erysipelas) skin infections. Moreover, the increasing incidence of bacterial antibiotic resistance represents a serious challenge to modern medicine and threatens the health care system. Therefore, it is critical to develop tools and strategies that can allow us to better elucidate the nature and mechanism of bacterial virulence. To this end, mass spectrometry (MS)-based proteomics has been revolutionizing biomedical research, and has positively impacted the microbiology field. Advances in MS technologies have paved the way for numerous bacterial proteomes and their respective post translational modifications (PTMs) to be accurately identified and quantified in a high throughput and robust fashion. This technological platform offers critical information with regards to signal transduction, adherence, and microbial–host interactions associated with bacterial pathogenesis. This mini-review serves to highlight the current progress proteomics has contributed toward the understanding of bacteria that are associated with skin related diseases, infections, and antibiotic resistance.

A Peptidomimetic Antibiotic Targets Outer Membrane Proteins and Disrupts Selectively the Outer Membrane in Escherichia coli

Increasing antibacterial resistance presents a major challenge in antibiotic discovery. One attractive target in Gram-negative bacteria is the unique asymmetric outer membrane (OM), which acts as a permeability barrier that protects the cell from external stresses, such as the presence of antibiotics. We describe a novel β-hairpin macrocyclic peptide JB-95 with potent antimicrobial activity against Escherichia coli. This peptide exhibits no cellular lytic activity, but electron microscopy and fluorescence studies reveal an ability to selectively disrupt the OM but not the inner membrane of E. coli. The selective targeting of the OM probably occurs through interactions of JB-95 with selected β-barrel OM proteins, including BamA and LptD as shown by photolabeling experiments. Membrane proteomic studies reveal rapid depletion of many β-barrel OM proteins from JB-95-treated E. coli, consistent with induction of a membrane stress response and/or direct inhibition of the Bam folding machine. The results suggest that lethal disruption of the OM by JB-95 occurs through a novel mechanism of action at key interaction sites within clusters of β-barrel proteins in the OM. These findings open new avenues for developing antibiotics that specifically target β-barrel proteins and the integrity of the Gram-negative OM.

ESCCAR international congress on Rickettsia and other intracellular bacteria

The European Society for the study of Chlamydia, Coxiella, Anaplasma and Rickettsia (ESCCAR) held his triennial international meeting in Lausanne. This meeting gathered 165 scientists from 28 countries and all 5 continents, allowing efficient networking and major scientific exchanges. Topics covered include molecular and cellular microbiology, genomics, as well as epidemiology, veterinary and human medicine. Several breakthroughs have been revealed at the meeting, such as (i) the presence of CRISPR (the "prokaryotic immune system") in chlamydiae, (ii) an Anaplasma effector involved in host chromatin remodelling, (iii) the polarity of the type III secretion system of chlamydiae during the entry process revealed by cryo-electron tomography. Moreover, the ESCCAR meeting was a unique opportunity to be exposed to cutting-edge science and to listen to comprehensive talks on current hot topics.

Dynamical Localization of DivL and PleC in the Asymmetric Division Cycle of Caulobacter crescentus: A Theoretical Investigation of Alternative Models

Cell-fate asymmetry in the predivisional cell of Caulobacter crescentus requires that the regulatory protein DivL localizes to the new pole of the cell where it up-regulates CckA kinase, resulting in a gradient of CtrA~P across the cell. In the preceding stage of the cell cycle (the "stalked" cell), DivL is localized uniformly along the cell membrane and maintained in an inactive form by DivK~P. It is unclear how DivL overcomes inhibition by DivK~P in the predivisional cell simply by changing its location to the new pole. It has been suggested that co-localization of DivL with PleC phosphatase at the new pole is essential to DivL's activity there. However, there are contrasting views on whether the bifunctional enzyme, PleC, acts as a kinase or phosphatase at the new pole. To explore these ambiguities, we formulated a mathematical model of the spatiotemporal distributions of DivL, PleC and associated proteins (DivJ, DivK, CckA, and CtrA) during the asymmetric division cycle of a Caulobacter cell. By varying localization profiles of DivL and PleC in our model, we show how the physiologically observed spatial distributions of these proteins are essential for the transition from a stalked cell to a predivisional cell. Our simulations suggest that PleC is a kinase in predivisional cells, and that, by sequestering DivK~P, the kinase form of PleC enables DivL to be reactivated at the new pole. Hence, co-localization of PleC kinase and DivL is essential to establishing cellular asymmetry. Our simulations reproduce the experimentally observed spatial distribution and phosphorylation status of CtrA in wild-type and mutant cells. Based on the model, we explore novel combinations of mutant alleles, making predictions that can be tested experimentally.

Proteomic profiling of the outer membrane fraction of the obligate intracellular bacterial pathogen Ehrlichia ruminantium

The outer membrane proteins (OMPs) of Gram-negative bacteria play a crucial role in virulence and pathogenesis. Identification of these proteins represents an important goal for bacterial proteomics, because it aids in vaccine development. Here, we have developed such an approach for Ehrlichia ruminantium, the obligate intracellular bacterium that causes heartwater. A preliminary whole proteome analysis of elementary bodies, the extracellular infectious form of the bacterium, had been performed previously, but information is limited about OMPs in this organism and about their role in the protective immune response. Identification of OMPs is also essential for understanding Ehrlichia's OM architecture, and how the bacterium interacts with the host cell environment. First, we developed an OMP extraction method using the ionic detergent sarkosyl, which enriched the OM fraction. Second, proteins were separated via one-dimensional electrophoresis, and digested peptides were analyzed via nano-liquid chromatographic separation coupled with mass spectrometry (LC-MALDI-TOF/TOF). Of 46 unique proteins identified in the OM fraction, 18 (39%) were OMPs, including 8 proteins involved in cell structure and biogenesis, 4 in transport/virulence, 1 porin, and 5 proteins of unknown function. These experimental data were compared to the predicted subcellular localization of the entire E. ruminantium proteome, using three different algorithms. This work represents the most complete proteome characterization of the OM fraction in Ehrlichia spp. The study indicates that suitable subcellular fractionation experiments combined with straightforward computational analysis approaches are powerful for determining the predominant subcellular localization of the experimentally observed proteins. We identified proteins potentially involved in E. ruminantium pathogenesis, which are good novel targets for candidate vaccines. Thus, combining bioinformatics and proteomics, we discovered new OMPs for E. ruminantium that are valuable data for those investigating new vaccines against this organism. In summary, we provide both pioneering data and novel insights into the pathogenesis of this obligate intracellular bacterium.

MS-GF+ makes progress towards a universal database search tool for proteomics

Mass spectrometry (MS) instruments and experimental protocols are rapidly advancing, but the software tools to analyze tandem mass spectra are lagging behind. We present a database search tool MS-GF+ that is sensitive (it identifies more peptides than most other database search tools) and universal (it works well for diverse types of spectra, different configurations of MS instruments and different experimental protocols). We benchmark MS-GF+ using diverse spectral datasets: (i) spectra of varying fragmentation methods; (ii) spectra of multiple enzyme digests; (iii) spectra of phosphorylated peptides; (iv) spectra of peptides with unusual fragmentation propensities produced by a novel alpha-lytic protease. For all these datasets, MS-GF+ significantly increases the number of identified peptides compared to commonly used methods for peptide identifications. We emphasize that while MS-GF+ is not specifically designed for any particular experimental set-up, it improves upon the performance of tools specifically designed for these applications (e.g., specialized tools for phosphoproteomics).