Systems analysis of multiple regulator perturbations allows discovery of virulence factors in Salmonella

<p>Abstract</p> <p>Background</p> <p>Systemic bacterial infections are highly regulated and complex processes that are orchestrated by numerous virulence factors. Genes that are coordinately controlled by the set of regulators required for systemic infection are potentially required for pathogenicity.</p> <p>Results</p> <p>In this study we present a systems biology approach in which sample-matched multi-omic measurements of fourteen virulence-essential regulator mutants were coupled with computational network analysis to efficiently identify <it>Salmonella </it>virulence factors. Immunoblot experiments verified network-predicted virulence factors and a subset was determined to be secreted into the host cytoplasm, suggesting that they are virulence factors directly interacting with host cellular components. Two of these, SrfN and PagK2, were required for full mouse virulence and were shown to be translocated independent of either of the type III secretion systems in <it>Salmonella </it>or the type III injectisome-related flagellar mechanism.</p> <p>Conclusions</p> <p>Integrating multi-omic datasets from <it>Salmonella </it>mutants lacking virulence regulators not only identified novel virulence factors but also defined a new class of translocated effectors involved in pathogenesis. The success of this strategy at discovery of known and novel virulence factors suggests that the approach may have applicability for other bacterial pathogens.</p

A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm

The twentieth century was marked by extraordinary advances in our understanding of microbes and infectious disease, but pandemics remain, food and waterborne illnesses are frequent, multidrug-resistant microbes are on the rise, and the needed drugs and vaccines have not been developed. The scientific approaches of the past—including the intense focus on individual genes and proteins typical of molecular biology—have not been sufficient to address these challenges. The first decade of the twenty-first century has seen remarkable innovations in technology and computational methods. These new tools provide nearly comprehensive views of complex biological systems and can provide a correspondingly deeper understanding of pathogen-host interactions. To take full advantage of these innovations, the National Institute of Allergy and Infectious Diseases recently initiated the Systems Biology Program for Infectious Disease Research. As participants of the Systems Biology Program, we think that the time is at hand to redefine the pathogen-host research paradigm

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data

<p>Abstract</p> <p>Background</p> <p>The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates.</p> <p>Results</p> <p>VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (<it>Yersinia pestis </it>Pestoides F and <it>Synechococcus </it>sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data.</p> <p>Conclusions</p> <p>VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at <url>https://www.biopilot.org/docs/Software/Vespa.php</url>.</p

Identification of Widespread Adenosine Nucleotide Binding in Mycobacterium tuberculosis

SummaryComputational prediction of protein function is frequently error-prone and incomplete. In Mycobacterium tuberculosis (Mtb), ∼25% of all genes have no predicted function and are annotated as hypothetical proteins, severely limiting our understanding of Mtb pathogenicity. Here, we utilize a high-throughput quantitative activity-based protein profiling (ABPP) platform to probe, annotate, and validate ATP-binding proteins in Mtb. We experimentally validate prior in silico predictions of >240 proteins and identify 72 hypothetical proteins as ATP binders. ATP interacts with proteins with diverse and unrelated sequences, providing an expanded view of adenosine nucleotide binding in Mtb. Several hypothetical ATP binders are essential or taxonomically limited, suggesting specialized functions in mycobacterial physiology and pathogenicity

Modeling Transport in Gas Chromatography Columns for the Micro-ChemLab

The gas chromatography (GC) column is a critical component in the microsystem for chemical detection ({mu}ChemLab{trademark}) being developed at Sandia. The goal is to etch a meter-long GC column onto a 1-cm{sup 2} silicon chip while maintaining good chromatographic performance. Our design strategy is to use a modeling and simulation approach. We have developed an analytical tool that models the transport and surface interaction process to achieve an optimized design of the GC column. This analytical tool has a flow module and a separation module. The flow module considers both the compressibility and slip flow effects that may significantly influence the gas transport in a long and narrow column. The separation module models analyte transport and physico-chemical interaction with the coated surface in the GC column. It predicts the column efficiency and performance. Results of our analysis will be presented in this paper. In addition to the analytical tool, we have also developed a time-dependent adsorption/desorption model and incorporated this model into a computational fluid dynamics (CFD) code to simulate analyte transport and separation process in GC columns. CFD simulations can capture the complex three-dimensional flow and transport dynamics, whereas the analytical tool cannot. Different column geometries have been studied, and results will be presented in this paper. Overall we have demonstrated that the modeling and simulation approach can guide the design of the GC column and will reduce the number of iterations in the device development

A systematic review of strategies to recruit and retain primary care doctors

Background There is a workforce crisis in primary care. Previous research has looked at the reasons underlying recruitment and retention problems, but little research has looked at what works to improve recruitment and retention. The aim of this systematic review is to evaluate interventions and strategies used to recruit and retain primary care doctors internationally. Methods A systematic review was undertaken. MEDLINE, EMBASE, CENTRAL and grey literature were searched from inception to January 2015.Articles assessing interventions aimed at recruiting or retaining doctors in high income countries, applicable to primary care doctors were included. No restrictions on language or year of publication. The first author screened all titles and abstracts and a second author screened 20%. Data extraction was carried out by one author and checked by a second. Meta-analysis was not possible due to heterogeneity. Results 51 studies assessing 42 interventions were retrieved. Interventions were categorised into thirteen groups: financial incentives (n=11), recruiting rural students (n=6), international recruitment (n=4), rural or primary care focused undergraduate placements (n=3), rural or underserved postgraduate training (n=3), well-being or peer support initiatives (n=3), marketing (n=2), mixed interventions (n=5), support for professional development or research (n=5), retainer schemes (n=4), re-entry schemes (n=1), specialised recruiters or case managers (n=2) and delayed partnerships (n=2). Studies were of low methodological quality with no RCTs and only 15 studies with a comparison group. Weak evidence supported the use of postgraduate placements in underserved areas, undergraduate rural placements and recruiting students to medical school from rural areas. There was mixed evidence about financial incentives. A marketing campaign was associated with lower recruitment. Conclusions This is the first systematic review of interventions to improve recruitment and retention of primary care doctors. Although the evidence base for recruiting and care doctors is weak and more high quality research is needed, this review found evidence to support undergraduate and postgraduate placements in underserved areas, and selective recruitment of medical students. Other initiatives covered may have potential to improve recruitment and retention of primary care practitioners, but their effectiveness has not been established

Multicopy Single-Stranded DNA Directs Intestinal Colonization of Enteric Pathogens

Multicopy single-stranded DNAs (msDNAs) are hybrid RNA-DNA molecules encoded on retroelements called retrons and produced by the action of retron reverse transcriptases. Retrons are widespread in bacteria but the natural function of msDNA has remained elusive despite 30 years of study. The major roadblock to elucidation of the function of these unique molecules has been the lack of any identifiable phenotypes for mutants unable to make msDNA. We report that msDNA of the zoonotic pathogen Salmonella Typhimurium is necessary for colonization of the intestine. Similarly, we observed a defect in intestinal persistence in an enteropathogenic E. coli mutant lacking its retron reverse transcriptase. Under anaerobic conditions in the absence of msDNA, proteins of central anaerobic metabolism needed for Salmonella colonization of the intestine are dysregulated. We show that the msDNA-deficient mutant can utilize nitrate, but not other alternate electron acceptors in anaerobic conditions. Consistent with the availability of nitrate in the inflamed gut, a neutrophilic inflammatory response partially rescued the ability of a mutant lacking msDNA to colonize the intestine. These findings together indicate that the mechanistic basis of msDNA function during Salmonella colonization of the intestine is proper production of proteins needed for anaerobic metabolism. We further conclude that a natural function of msDNA is to regulate protein abundance, the first attributable function for any msDNA. Our data provide novel insight into the function of this mysterious molecule that likely represents a new class of regulatory molecules

Multicopy Single-Stranded DNA Directs Intestinal Colonization of Enteric Pathogens

Multicopy single-stranded DNAs (msDNAs) are hybrid RNA-DNA molecules encoded on retroelements called retrons and produced by the action of retron reverse transcriptases. Retrons are widespread in bacteria but the natural function of msDNA has remained elusive despite 30 years of study. The major roadblock to elucidation of the function of these unique molecules has been the lack of any identifiable phenotypes for mutants unable to make msDNA. We report that msDNA of the zoonotic pathogen Salmonella Typhimurium is necessary for colonization of the intestine. Similarly, we observed a defect in intestinal persistence in an enteropathogenic E. coli mutant lacking its retron reverse transcriptase. Under anaerobic conditions in the absence of msDNA, proteins of central anaerobic metabolism needed for Salmonella colonization of the intestine are dysregulated. We show that the msDNA-deficient mutant can utilize nitrate, but not other alternate electron acceptors in anaerobic conditions. Consistent with the availability of nitrate in the inflamed gut, a neutrophilic inflammatory response partially rescued the ability of a mutant lacking msDNA to colonize the intestine. These findings together indicate that the mechanistic basis of msDNA function during Salmonella colonization of the intestine is proper production of proteins needed for anaerobic metabolism. We further conclude that a natural function of msDNA is to regulate protein abundance, the first attributable function for any msDNA. Our data provide novel insight into the function of this mysterious molecule that likely represents a new class of regulatory molecules

Comparative Omics-Driven Genome Annotation Refinement: Application across Yersiniae

Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. The annotation process is now performed almost exclusively in an automated fashion to balance the large number of sequences generated. One possible way of reducing errors inherent to automated computational annotations is to apply data from omics measurements (i.e. transcriptional and proteomic) to the un-annotated genome with a proteogenomic-based approach. Here, the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species. Transcriptomic and proteomic data derived from highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis Pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 incorrect (i.e., observed frameshifts, extended start sites, and translated pseudogenes) protein-coding sequences within the three current genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus the discovery of many translated pseudogenes, including the insertion-ablated argD, underscores a need for functional analyses to investigate hypotheses related to divergence. Refinements included the discovery of a seemingly essential ribosomal protein, several virulence-associated factors, a transcriptional regulator, and many hypothetical proteins that were missed during annotation