Optimizing metaproteomics database construction: lessons from a study of the vaginal microbiome.

Metaproteomics, a method for untargeted, high-throughput identification of proteins in complex samples, provides functional information about microbial communities and can tie functions to specific taxa. Metaproteomics often generates less data than other omics techniques, but analytical workflows can be improved to increase usable data in metaproteomic outputs. Identification of peptides in the metaproteomic analysis is performed by comparing mass spectra of sample peptides to a reference database of protein sequences. Although these protein databases are an integral part of the metaproteomic analysis, few studies have explored how database composition impacts peptide identification. Here, we used cervicovaginal lavage (CVL) samples from a study of bacterial vaginosis (BV) to compare the performance of databases built using six different strategies. We evaluated broad versus sample-matched databases, as well as databases populated with proteins translated from metagenomic sequencing of the same samples versus sequences from public repositories. Smaller sample-matched databases performed significantly better, driven by the statistical constraints on large databases. Additionally, large databases attributed up to 34% of significant bacterial hits to taxa absent from the sample, as determined orthogonally by 16S rRNA gene sequencing. We also tested a set of hybrid databases which included bacterial proteins from NCBI RefSeq and translated bacterial genes from the samples. These hybrid databases had the best overall performance, identifying 1,068 unique human and 1,418 unique bacterial proteins, ~30% more than a database populated with proteins from typical vaginal bacteria and fungi. Our findings can help guide the optimal identification of proteins while maintaining statistical power for reaching biological conclusions. IMPORTANCE Metaproteomic analysis can provide valuable insights into the functions of microbial and cellular communities by identifying a broad, untargeted set of proteins. The databases used in the analysis of metaproteomic data influence results by defining what proteins can be identified. Moreover, the size of the database impacts the number of identifications after accounting for false discovery rates (FDRs). Few studies have tested the performance of different strategies for building a protein database to identify proteins from metaproteomic data and those that have largely focused on highly diverse microbial communities. We tested a range of databases on CVL samples and found that a hybrid sample-matched approach, using publicly available proteins from organisms present in the samples, as well as proteins translated from metagenomic sequencing of the samples, had the best performance. However, our results also suggest that public sequence databases will continue to improve as more bacterial genomes are published.

LipidOz enables automated elucidation of lipid carbon-carbon double bond positions from ozone-induced dissociation mass spectrometry data.

Lipids play essential roles in many biological processes and disease pathology, but unambiguous identification of lipids is complicated by the presence of multiple isomeric species differing by fatty acyl chain length, stereospecifically numbered (sn) position, and position/stereochemistry of double bonds. Conventional liquid chromatography-mass spectrometry (LC-MS/MS) analyses enable the determination of fatty acyl chain lengths (and in some cases sn position) and number of double bonds, but not carbon-carbon double bond positions. Ozone-induced dissociation (OzID) is a gas-phase oxidation reaction that produces characteristic fragments from lipids containing double bonds. OzID can be incorporated into ion mobility spectrometry (IMS)-MS instruments for the structural characterization of lipids, including additional isomer separation and confident assignment of double bond positions. The complexity and repetitive nature of OzID data analysis and lack of software tool support have limited the application of OzID for routine lipidomics studies. Here, we present an open-source Python tool, LipidOz, for the automated determination of lipid double bond positions from OzID-IMS-MS data, which employs a combination of traditional automation and deep learning approaches. Our results demonstrate the ability of LipidOz to robustly assign double bond positions for lipid standard mixtures and complex lipid extracts, enabling practical application of OzID for future lipidomics.

MS1Connect: a mass spectrometry run similarity measure.

MOTIVATION: Interpretation of newly acquired mass spectrometry data can be improved by identifying, from an online repository, previous mass spectrometry runs that resemble the new data. However, this retrieval task requires computing the similarity between an arbitrary pair of mass spectrometry runs. This is particularly challenging for runs acquired using different experimental protocols. RESULTS: We propose a method, MS1Connect, that calculates the similarity between a pair of runs by examining only the intact peptide (MS1) scans, and we show evidence that the MS1Connect score is accurate. Specifically, we show that MS1Connect outperforms several baseline methods on the task of predicting the species from which a given proteomics sample originated. In addition, we show that MS1Connect scores are highly correlated with similarities computed from fragment (MS2) scans, even though these data are not used by MS1Connect. AVAILABILITY AND IMPLEMENTATION: The MS1Connect software is available at https://github.com/bmx8177/MS1Connect. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Proteomic Signatures of Antimicrobial Resistance in Yersinia pestis and Francisella tularensis.

Antimicrobial resistance (AMR) is a well-recognized, widespread, and growing issue of concern. With increasing incidence of AMR, the ability to respond quickly to infection with or exposure to an AMR pathogen is critical. Approaches that could accurately and more quickly identify whether a pathogen is AMR also are needed to more rapidly respond to existing and emerging biological threats. We examined proteins associated with paired AMR and antimicrobial susceptible (AMS) strains of Yersinia pestis and Francisella tularensis, causative agents of the diseases plague and tularemia, respectively, to identify whether potential existed to use proteins as signatures of AMR. We found that protein expression was significantly impacted by AMR status. Antimicrobial resistance-conferring proteins were expressed even in the absence of antibiotics in growth media, and the abundance of 10-20% of cellular proteins beyond those that directly confer AMR also were significantly changed in both Y. pestis and F. tularensis. Most strikingly, the abundance of proteins involved in specific metabolic pathways and biological functions was altered in all AMR strains examined, independent of species, resistance mechanism, and affected cellular antimicrobial target. We have identified features that distinguish between AMR and AMS strains, including a subset of features shared across species with different resistance mechanisms, which suggest shared biological signatures of resistance. These features could form the basis of novel approaches to identify AMR phenotypes in unknown strains.

Assessment of the Utility of the Oral Fluid and Plasma Proteomes for Hydrocodone Exposure.

INTRODUCTION: Non-medical use and abuse of prescription opioids is a growing problem in both the civilian and military communities, with minimal technologies for detecting hydrocodone use. This study explored the proteomic changes that occur in the oral fluid and blood plasma following controlled hydrocodone administration in 20 subjects. METHODS: The global proteomic profile was determined for samples taken at four time points per subject: pre-exposure and 4, 6, or 168 hours post-exposure. The oral fluid samples analyzed herein provided greater differentiation between baseline and response time points than was observed with blood plasma, at least partially due to significant person-to-person relative variability in the plasma proteome. RESULTS: A total of 399 proteins were identified from oral fluid samples, and the abundance of 118 of those proteins was determined to be significantly different upon metabolism of hydrocodone (4 and 6 hour time points) as compared to baseline levels in the oral fluid (pre-dose and 168 hours). CONCLUSIONS: We present an assessment of the oral fluid and plasma proteome following hydrocodone administration, which demonstrates the potential of oral fluid as a noninvasive sample that may reveal features of hydrocodone in opioid use, and with additional study, may be useful for other opioids and in settings of misuse.

Polysaccharide-based liquid storage and transport media for non-refrigerated preservation of bacterial pathogens.

The preservation of biological samples for an extended time period of days to weeks after initial collection is important for the identification, screening, and characterization of bacterial pathogens. Traditionally, preservation relies on cold-chain infrastructure; however, in many situations this is impractical or not possible. Thus, our goal was to develop alternative bacterial sample preservation and transport media that are effective without refrigeration or external instrumentation. The viability, nucleic acid stability, and protein stability of Bacillus anthracis Sterne 34F2, Francisella novicida U112, Staphylococcus aureus ATCC 43300, and Yersinia pestis KIM D27 (pgm-) was assessed for up to 28 days. Xanthan gum (XG) prepared in PBS with L-cysteine maintained more viable F. novicida U112 cells at elevated temperature (40°C) compared to commercial reagents and buffers. Viability was maintained for all four bacteria in XG with 0.9 mM L-cysteine across a temperature range of 22-40°C. Interestingly, increasing the concentration to 9 mM L-cysteine resulted in the rapid death of S. aureus. This could be advantageous when collecting samples in the built environment where there is the potential for Staphylococcus collection and stabilization rather than other organisms of interest. F. novicida and S. aureus DNA were stable for up to 45 days upon storage at 22°C or 40°C, and direct analysis by real-time qPCR, without DNA extraction, was possible in the XG formulations. XG was not compatible with proteomic analysis via LC-MS/MS due to the high amount of residual Xanthomonas campestris proteins present in XG. Our results demonstrate that polysaccharide-based formulations, specifically XG with L-cysteine, maintain bacterial viability and nucleic acid integrity for an array of both Gram-negative and Gram-positive bacteria across ambient and elevated temperatures.

Proteomic analysis of four Clostridium botulinum strains identifies proteins that link biological responses to proteomic signatures.

Microorganisms alter gene and protein expression in response to environmental conditions to adapt and survive. Whereas the genetic composition of a microbe represents an organism's biological potential, the proteins expressed provide a functional readout of the organism's response to the environment. Understanding protein expression patterns in response to specific environmental conditions furthers fundamental knowledge about a microbe, which can be especially useful for understudied organisms such as Clostridium botulinum examined herein. In addition, protein expression patterns that reproducibly occur in certain growth conditions hold potential in fields such as microbial forensics, in which determination of conditions in which an unknown possible biothreat sample had been grown may be important. To investigate the identity and reproducibility of protein profile patterns for varied strains, we defined the proteomic profiles of four Group I strains of Clostridium botulinum, a Category A biothreat agent and the organism responsible for the production of the botulinum neurotoxin (BoNT), in two different culture media grown for five days. The four C. botulinum strains produced one of three neurotoxins (BoNT/A, /B, or /F), and their protein profiles were compared to that of a fifth non-toxigenic strain of C. sporogenes. These strains each had DNA sequences available to assist in accurate protein identification. Differing culture growth phase, bacterial strain, and growth medium resulted in reproducible protein profiles, which were used to calculate relative protein abundance ratios as an internally normalized metric of microbial growth in varying conditions. The resulting protein profiles provide functional information about how four Group I C. botulinum strains and a C. sporogenes strain respond to the culture environment during growth and explores the feasibility of using these proteins to characterize unknown samples.

Salmonella-Mediated Inflammation Eliminates Competitors for Fructose-Asparagine in the Gut.

Salmonella enterica elicits intestinal inflammation to gain access to nutrients. One of these nutrients is fructose-asparagine (F-Asn). The availability of F-Asn to Salmonella during infection is dependent upon Salmonella pathogenicity islands 1 and 2, which in turn are required to provoke inflammation. Here, we determined that F-Asn is present in mouse chow at approximately 400 pmol/mg (dry weight). F-Asn is also present in the intestinal tract of germfree mice at 2,700 pmol/mg (dry weight) and in the intestinal tract of conventional mice at 9 to 28 pmol/mg. These findings suggest that the mouse intestinal microbiota consumes F-Asn. We utilized heavy-labeled precursors of F-Asn to monitor its formation in the intestine, in the presence or absence of inflammation, and none was observed. Finally, we determined that some members of the class Clostridia encode F-Asn utilization pathways and that they are eliminated from highly inflamed Salmonella-infected mice. Collectively, our studies identify the source of F-Asn as the diet and that Salmonella-mediated inflammation is required to eliminate competitors and allow the pathogen nearly exclusive access to this nutrient.

Measurement of Fructose-Asparagine Concentrations in Human and Animal Foods.

The food-borne bacterial pathogen, Salmonella enterica, can utilize fructose-asparagine (F-Asn) as its sole carbon and nitrogen source. F-Asn is the product of an Amadori rearrangement following the nonenzymatic condensation of glucose and asparagine. Heating converts F-Asn via complex Maillard reactions to a variety of molecules that contribute to the color, taste, and aroma of heated foods. Among these end derivatives is acrylamide, which is present in some foods, especially in fried potatoes. The F-Asn utilization pathway in Salmonella, specifically FraB, is a potential drug target because inhibition of this enzyme would lead to intoxication of Salmonella in the presence of F-Asn. However, F-Asn would need to be packaged with the FraB inhibitor or available in human foods. To determine if there are foods that have sufficient F-Asn, we measured F-Asn concentrations in a variety of human and animal foods. The 400 pmol/mg F-Asn found in mouse chow is sufficient to intoxicate a Salmonella fraB mutant in mouse models of salmonellosis, and several human foods were found to have F-Asn at this level or higher (fresh apricots, lettuce, asparagus, and canned peaches). Much higher concentrations (11 000-35 000 pmol/mg dry weight) were found in heat-dried apricots, apples, and asparagus. This report reveals possible origins of F-Asn as a nutrient source for Salmonella and identifies foods that could be used together with a FraB inhibitor as a therapeutic agent for Salmonella.

Insights into PG-binding, conformational change, and dimerization of the OmpA C-terminal domains from Salmonella enterica serovar Typhimurium and Borrelia burgdorferi.

Salmonella enterica serovar Typhimurium can induce both humoral and cell-mediated responses when establishing itself in the host. These responses are primarily stimulated against the lipopolysaccharide and major outer membrane (OM) proteins. OmpA is one of these major OM proteins. It comprises a N-terminal eight-stranded ß-barrel transmembrane domain and a C-terminal domain (OmpACTD ). The OmpACTD and its homologs are believed to bind to peptidoglycan (PG) within the periplasm, maintaining bacterial osmotic homeostasis and modulating the permeability and integrity of the OM. Here we present the first crystal structures of the OmpACTD from two pathogens: S. typhimurium (STOmpACTD ) in open and closed forms and causative agent of Lyme Disease Borrelia burgdorferi (BbOmpACTD ), in closed form. In the open form of STOmpACTD , an aspartate residue from a long ß2-α3 loop points into the binding pocket, suggesting that an anion group such as a carboxylate group from PG is favored at the binding site. In the closed form of STOmpACTD and in the structure of BbOmpACTD , a sulfate group from the crystallization buffer is tightly bound at the binding site. The differences between the closed and open forms of STOmpACTD , suggest a large conformational change that includes an extension of α3 helix by ordering a part of ß2-α3 loop. We propose that the sulfate anion observed in these structures mimics the carboxylate group of PG when bound to STOmpACTD suggesting PG-anchoring mechanism. In addition, the binding of PG or a ligand mimic may enhance dimerization of STOmpACTD , or possibly that of full length STOmpA.

Investigation of Yersinia pestis Laboratory Adaptation through a Combined Genomics and Proteomics Approach.

The bacterial pathogen Yersinia pestis, the cause of plague in humans and animals, normally has a sylvatic lifestyle, cycling between fleas and mammals. In contrast, laboratory-grown Y. pestis experiences a more constant environment and conditions that it would not normally encounter. The transition from the natural environment to the laboratory results in a vastly different set of selective pressures, and represents what could be considered domestication. Understanding the kinds of adaptations Y. pestis undergoes as it becomes domesticated will contribute to understanding the basic biology of this important pathogen. In this study, we performed a parallel serial passage experiment (PSPE) to explore the mechanisms by which Y. pestis adapts to laboratory conditions, hypothesizing that cells would undergo significant changes in virulence and nutrient acquisition systems. Two wild strains were serially passaged in 12 independent populations each for ~750 generations, after which each population was analyzed using whole-genome sequencing, LC-MS/MS proteomic analysis, and GC/MS metabolomics. We observed considerable parallel evolution in the endpoint populations, detecting multiple independent mutations in ail, pepA, and zwf, suggesting that specific selective pressures are shaping evolutionary responses. Complementary LC-MS/MS proteomic data provide physiological context to the observed mutations, and reveal regulatory changes not necessarily associated with specific mutations, including changes in amino acid metabolism and cell envelope biogenesis. Proteomic data support hypotheses generated by genomic data in addition to suggesting future mechanistic studies, indicating that future whole-genome sequencing studies be designed to leverage proteomics as a critical complement.

Improved proteomic analysis following trichloroacetic acid extraction of Bacillus anthracis spore proteins.

Proteomic analysis of bacterial samples provides valuable information about cellular responses and functions under different environmental pressures. Analysis of cellular proteins is dependent upon efficient extraction from bacterial samples, which can be challenging with increasing complexity and refractory characteristics. While no single method can recover 100% of the bacterial proteins, selected protocols can improve overall protein isolation, peptide recovery, or enrichment for certain classes of proteins. The method presented here is technically simple, does not require specialized equipment such as a mechanical disrupter, and is effective for protein extraction of the particularly challenging sample type of Bacillus anthracis Sterne spores. The ability of Trichloroacetic acid (TCA) extraction to isolate proteins from spores and enrich for spore-specific proteins was compared to the traditional mechanical disruption method of bead beating. TCA extraction improved the total average number of proteins identified within a sample as compared to bead beating (547 vs 495, respectively). Further, TCA extraction enriched for 270 spore proteins, including those typically identified by first isolating the spore coat and exosporium layers. Bead beating enriched for 156 spore proteins more typically identified from whole spore proteome analyses. The total average number of proteins identified was equal using TCA or bead beating for easily lysed samples, such as B. anthracis vegetative cells. As with all assays, supplemental methods such as implementation of an alternative preparation method may simplify sample preparation and provide additional insight to the protein biology of the organism being studied.

Identification of Salmonella Typhimurium Deubiquitinase SseL Substrates by Immunoaffinity Enrichment and Quantitative Proteomic Analysis.

Ubiquitination is a key protein post-translational modification that regulates many important cellular pathways and whose levels are regulated by equilibrium between the activities of ubiquitin ligases and deubiquitinases. Here, we present a method to identify specific deubiquitinase substrates based on treatment of cell lysates with recombinant enzymes, immunoaffinity purification, and global quantitative proteomic analysis. As a model system to identify substrates, we used a virulence-related deubiquitinase, SseL, secreted by Salmonella enterica serovar Typhimurium into host cells. Using this approach, two SseL substrates were identified in the RAW 264.7 murine macrophage-like cell line, S100A6 and heterogeneous nuclear ribonuclear protein K, in addition to the previously reported K63-linked ubiquitin chains. These substrates were further validated by a combination of enzymatic and binding assays. This method can be used for the systematic identification of substrates of deubiquitinases from other organisms and applied to study their functions in physiology and disease.

Salmonella serotype determination utilizing high-throughput genome sequencing data.

Serotyping forms the basis of national and international surveillance networks for Salmonella, one of the most prevalent foodborne pathogens worldwide (1-3). Public health microbiology is currently being transformed by whole-genome sequencing (WGS), which opens the door to serotype determination using WGS data. SeqSero (www.denglab.info/SeqSero) is a novel Web-based tool for determining Salmonella serotypes using high-throughput genome sequencing data. SeqSero is based on curated databases of Salmonella serotype determinants (rfb gene cluster, fliC and fljB alleles) and is predicted to determine serotype rapidly and accurately for nearly the full spectrum of Salmonella serotypes (more than 2,300 serotypes), from both raw sequencing reads and genome assemblies. The performance of SeqSero was evaluated by testing (i) raw reads from genomes of 308 Salmonella isolates of known serotype; (ii) raw reads from genomes of 3,306 Salmonella isolates sequenced and made publicly available by GenomeTrakr, a U.S. national monitoring network operated by the Food and Drug Administration; and (iii) 354 other publicly available draft or complete Salmonella genomes. We also demonstrated Salmonella serotype determination from raw sequencing reads of fecal metagenomes from mice orally infected with this pathogen. SeqSero can help to maintain the well-established utility of Salmonella serotyping when integrated into a platform of WGS-based pathogen subtyping and characterization.

Mutations in global regulators lead to metabolic selection during adaptation to complex environments.

Adaptation to ecologically complex environments can provide insights into the evolutionary dynamics and functional constraints encountered by organisms during natural selection. Adaptation to a new environment with abundant and varied resources can be difficult to achieve by small incremental changes if many mutations are required to achieve even modest gains in fitness. Since changing complex environments are quite common in nature, we investigated how such an epistatic bottleneck can be avoided to allow rapid adaptation. We show that adaptive mutations arise repeatedly in independently evolved populations in the context of greatly increased genetic and phenotypic diversity. We go on to show that weak selection requiring substantial metabolic reprogramming can be readily achieved by mutations in the global response regulator arcA and the stress response regulator rpoS. We identified 46 unique single-nucleotide variants of arcA and 18 mutations in rpoS, nine of which resulted in stop codons or large deletions, suggesting that subtle modulations of ArcA function and knockouts of rpoS are largely responsible for the metabolic shifts leading to adaptation. These mutations allow a higher order metabolic selection that eliminates epistatic bottlenecks, which could occur when many changes would be required. Proteomic and carbohydrate analysis of adapting E. coli populations revealed an up-regulation of enzymes associated with the TCA cycle and amino acid metabolism, and an increase in the secretion of putrescine. The overall effect of adaptation across populations is to redirect and efficiently utilize uptake and catabolism of abundant amino acids. Concomitantly, there is a pronounced spread of more ecologically limited strains that results from specialization through metabolic erosion. Remarkably, the global regulators arcA and rpoS can provide a "one-step" mechanism of adaptation to a novel environment, which highlights the importance of global resource management as a powerful strategy to adaptation.

A Multi-Omic View of Host-Pathogen-Commensal Interplay in Salmonella-Mediated Intestinal Infection.

The potential for commensal microorganisms indigenous to a host (the 'microbiome' or 'microbiota') to alter infection outcome by influencing host-pathogen interplay is largely unknown. We used a multi-omics "systems" approach, incorporating proteomics, metabolomics, glycomics, and metagenomics, to explore the molecular interplay between the murine host, the pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium), and commensal gut microorganisms during intestinal infection with S. Typhimurium. We find proteomic evidence that S. Typhimurium thrives within the infected 129/SvJ mouse gut without antibiotic pre-treatment, inducing inflammation and disrupting the intestinal microbiome (e.g., suppressing Bacteroidetes and Firmicutes while promoting growth of Salmonella and Enterococcus). Alteration of the host microbiome population structure was highly correlated with gut environmental changes, including the accumulation of metabolites normally consumed by commensal microbiota. Finally, the less characterized phase of S. Typhimurium's lifecycle was investigated, and both proteomic and glycomic evidence suggests S. Typhimurium may take advantage of increased fucose moieties to metabolize fucose while growing in the gut. The application of multiple omics measurements to Salmonella-induced intestinal inflammation provides insights into complex molecular strategies employed during pathogenesis between host, pathogen, and the microbiome.

Top-down proteomics reveals a unique protein S-thiolation switch in Salmonella Typhimurium in response to infection-like conditions.

Characterization of the mature protein complement in cells is crucial for a better understanding of cellular processes on a systems-wide scale. Toward this end, we used single-dimension ultra-high-pressure liquid chromatography mass spectrometry to investigate the comprehensive "intact" proteome of the Gram-negative bacterial pathogen Salmonella Typhimurium. Top-down proteomics analysis revealed 563 unique proteins including 1,665 proteoforms generated by posttranslational modifications (PTMs), representing the largest microbial top-down dataset reported to date. We confirmed many previously recognized aspects of Salmonella biology and bacterial PTMs, and our analysis also revealed several additional biological insights. Of particular interest was differential utilization of the protein S-thiolation forms S-glutathionylation and S-cysteinylation in response to infection-like conditions versus basal conditions. This finding of a S-glutathionylation-to-S-cysteinylation switch in a condition-specific manner was corroborated by bottom-up proteomics data and further by changes in corresponding biosynthetic pathways under infection-like conditions and during actual infection of host cells. This differential utilization highlights underlying metabolic mechanisms that modulate changes in cellular signaling, and represents a report of S-cysteinylation in Gram-negative bacteria. Additionally, the functional relevance of these PTMs was supported by protein structure and gene deletion analyses. The demonstrated utility of our simple proteome-wide intact protein level measurement strategy for gaining biological insight should promote broader adoption and applications of top-down proteomics approaches.

Salmonella modulates metabolism during growth under conditions that induce expression of virulence genes.

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a facultative pathogen that uses complex mechanisms to invade and proliferate within mammalian host cells. To investigate possible contributions of metabolic processes to virulence in S. Typhimurium grown under conditions known to induce expression of virulence genes, we used a metabolomics-driven systems biology approach coupled with genome-scale modeling. First, we identified distinct metabolite profiles associated with bacteria grown in either rich or virulence-inducing media and report the most comprehensive coverage of the S. Typhimurium metabolome to date. Second, we applied an omics-informed genome-scale modeling analysis of the functional consequences of adaptive alterations in S. Typhimurium metabolism during growth under our conditions. Modeling efforts highlighted a decreased cellular capability to both produce and utilize intracellular amino acids during stationary phase culture in virulence conditions, despite significant abundance increases for these molecules as observed by our metabolomics measurements. Furthermore, analyses of omics data in the context of the metabolic model indicated rewiring of the metabolic network to support pathways associated with virulence. For example, cellular concentrations of polyamines were perturbed, as well as the predicted capacity for secretion and uptake.

A multi-omic systems approach to elucidating Yersinia virulence mechanisms.

The underlying mechanisms that lead to dramatic differences between closely related pathogens are not always readily apparent. For example, the genomes of Yersinia pestis (YP) the causative agent of plague with a high mortality rate and Yersinia pseudotuberculosis (YPT) an enteric pathogen with a modest mortality rate are highly similar with some species specific differences; however the molecular causes of their distinct clinical outcomes remain poorly understood. In this study, a temporal multi-omic analysis of YP and YPT at physiologically relevant temperatures was performed to gain insights into how an acute and highly lethal bacterial pathogen, YP, differs from its less virulent progenitor, YPT. This analysis revealed higher gene and protein expression levels of conserved major virulence factors in YP relative to YPT, including the Yop virulon and the pH6 antigen. This suggests that adaptation in the regulatory architecture, in addition to the presence of unique genetic material, may contribute to the increased pathogenecity of YP relative to YPT. Additionally, global transcriptome and proteome responses of YP and YPT revealed conserved post-transcriptional control of metabolism and the translational machinery including the modulation of glutamate levels in Yersiniae. Finally, the omics data was coupled with a computational network analysis, allowing an efficient prediction of novel Yersinia virulence factors based on gene and protein expression patterns.