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Search Results: 1 - 10 of 1842 matches for " Fred Heffron "
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Analysis of Cells Targeted by Salmonella Type III Secretion In Vivo
Kaoru Geddes,Frank Cruz III,Fred Heffron
PLOS Pathogens , 2007, DOI: 10.1371/journal.ppat.0030196
Abstract: The type III secretion systems (TTSS) encoded in Salmonella pathogenicity island-1 and -2 (SPI-1 and -2) are virulence factors required for specific phases of Salmonella infection in animal hosts. However, the host cell types targeted by the TTSS have not been determined. To investigate this, we have constructed translational fusions between the ?-lactamase reporter and a broad array of TTSS effectors secreted via SPI-1, SPI-2, or both. Secretion of the fusion protein to a host cell was determined by cleavage of a specific fluorescent substrate. In cultured cells, secretion of all six effectors could be observed. However, two to four days following i.p. infection of mice, only effectors secreted by SPI-2 were detected in spleen cells. The cells targeted were identified via staining with nine different cell surface markers followed by FACS analysis as well as by conventional cytological methods. The targeted cells include B and T lymphocytes, neutrophils, monocytes, and dendritic cells, but not mature macrophages. To further investigate replication in these various cell types, Salmonella derivatives were constructed that express a red fluorescent protein. Bacteria could be seen in each of the cell types above; however, most viable bacteria were present in neutrophils. We find that Salmonella is capable of targeting most phagocytic and non-phagocytic cells in the spleen but has a surprisingly high preference for neutrophils. These findings suggest that Salmonella specifically target splenic neutrophils presumably to attenuate their microbicidal functions, thereby promoting intracellular survival and replication in the mouse.
Accurate Prediction of Secreted Substrates and Identification of a Conserved Putative Secretion Signal for Type III Secretion Systems
Ram Samudrala,Fred Heffron,Jason E. McDermott
PLOS Pathogens , 2009, DOI: 10.1371/journal.ppat.1000375
Abstract: The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates—effector proteins—are not. We have used a novel computational approach to confidently identify new secreted effectors by integrating protein sequence-based features, including evolutionary measures such as the pattern of homologs in a range of other organisms, G+C content, amino acid composition, and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from the plant pathogen Pseudomonas syringae and validated on a set of effectors from the animal pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) after eliminating effectors with detectable sequence similarity. We show that this approach can predict known secreted effectors with high specificity and sensitivity. Furthermore, by considering a large set of effectors from multiple organisms, we computationally identify a common putative secretion signal in the N-terminal 20 residues of secreted effectors. This signal can be used to discriminate 46 out of 68 total known effectors from both organisms, suggesting that it is a real, shared signal applicable to many type III secreted effectors. We use the method to make novel predictions of secreted effectors in S. Typhimurium, some of which have been experimentally validated. We also apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis, identifying the majority of known secreted proteins in addition to providing a number of novel predictions. This approach provides a new way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal.
Coordinated Regulation of Virulence during Systemic Infection of Salmonella enterica Serovar Typhimurium
Hyunjin Yoon,Jason E. McDermott,Steffen Porwollik,Michael McClelland,Fred Heffron
PLOS Pathogens , 2009, DOI: 10.1371/journal.ppat.1000306
Abstract: To cause a systemic infection, Salmonella must respond to many environmental cues during mouse infection and express specific subsets of genes in a temporal and spatial manner, but the regulatory pathways are poorly established. To unravel how micro-environmental signals are processed and integrated into coordinated action, we constructed in-frame non-polar deletions of 83 regulators inferred to play a role in Salmonella enteriditis Typhimurium (STM) virulence and tested them in three virulence assays (intraperitoneal [i.p.], and intragastric [i.g.] infection in BALB/c mice, and persistence in 129X1/SvJ mice). Overall, 35 regulators were identified whose absence attenuated virulence in at least one assay, and of those, 14 regulators were required for systemic mouse infection, the most stringent virulence assay. As a first step towards understanding the interplay between a pathogen and its host from a systems biology standpoint, we focused on these 14 genes. Transcriptional profiles were obtained for deletions of each of these 14 regulators grown under four different environmental conditions. These results, as well as publicly available transcriptional profiles, were analyzed using both network inference and cluster analysis algorithms. The analysis predicts a regulatory network in which all 14 regulators control the same set of genes necessary for Salmonella to cause systemic infection. We tested the regulatory model by expressing a subset of the regulators in trans and monitoring transcription of 7 known virulence factors located within Salmonella pathogenicity island 2 (SPI-2). These experiments validated the regulatory model and showed that the response regulator SsrB and the MarR type regulator, SlyA, are the terminal regulators in a cascade that integrates multiple signals. Furthermore, experiments to demonstrate epistatic relationships showed that SsrB can replace SlyA and, in some cases, SlyA can replace SsrB for expression of SPI-2 encoded virulence factors.
Diverse Secreted Effectors Are Required for Salmonella Persistence in a Mouse Infection Model
Afshan S. Kidwai, Ivy Mushamiri, George S. Niemann, Roslyn N. Brown, Joshua N. Adkins, Fred Heffron
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0070753
Abstract: Salmonella enterica serovar Typhimurium causes typhoid-like disease in mice and is a model of typhoid fever in humans. One of the hallmarks of typhoid is persistence, the ability of the bacteria to survive in the host weeks after infection. Virulence factors called effectors facilitate this process by direct transfer to the cytoplasm of infected cells thereby subverting cellular processes. Secretion of effectors to the cell cytoplasm takes place through multiple routes, including two separate type III secretion (T3SS) apparati as well as outer membrane vesicles. The two T3SS are encoded on separate pathogenicity islands, SPI-1 and -2, with SPI-1 more strongly associated with the intestinal phase of infection, and SPI-2 with the systemic phase. Both T3SS are required for persistence, but the effectors required have not been systematically evaluated. In this study, mutations in 48 described effectors were tested for persistence. We replaced each effector with a specific DNA barcode sequence by allelic exchange and co-infected with a wild-type reference to calculate the ratio of wild-type parent to mutant at different times after infection. The competitive index (CI) was determined by quantitative PCR in which primers that correspond to the barcode were used for amplification. Mutations in all but seven effectors reduced persistence demonstrating that most effectors were required. One exception was CigR, a recently discovered effector that is widely conserved throughout enteric bacteria. Deletion of cigR increased lethality, suggesting that it may be an anti-virulence factor. The fact that almost all Salmonella effectors are required for persistence argues against redundant functions. This is different from effector repertoires in other intracellular pathogens such as Legionella.
Gene set analyses for interpreting microarray experiments on prokaryotic organisms
Nathan L Tintle, Aaron A Best, Matthew DeJongh, Dirk Van Bruggen, Fred Heffron, Steffen Porwollik, Ronald C Taylor
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-469
Abstract: We extend five methods of gene set analysis from use on experiments with multiple replicates, for use on experiments with few replicates. We then use simulated and real data to compare these methods with each other and with the Fisher's exact test (FET) method. As a result of the simulation we find that a method named MAXMEAN-NR, maintains the nominal rate of false positive findings (type I error rate) while offering good statistical power and robustness to a variety of gene set distributions for set sizes of at least 10. Other methods (ABSSUM-NR or SUM-NR) are shown to be powerful for set sizes less than 10. Analysis of three sets of experimental data shows similar results. Furthermore, the MAXMEAN-NR method is shown to be able to detect biologically relevant sets as significant, when other methods (including FET) cannot. We also find that the popular GSEA-NR method performs poorly when compared to MAXMEAN-NR.MAXMEAN-NR is a method of gene set analysis for experiments with few replicates, as is common for prokaryotes. Results of simulation and real data analysis suggest that the MAXMEAN-NR method offers increased robustness and biological relevance of findings as compared to FET and other methods, while maintaining the nominal type I error rate.DNA microarrays measuring gene expression continue to grow in popularity, furthering our understanding of the genetic operation of organisms spanning humans to prokaryotes. Questions remain, however, about how best to interpret the wealth of gene-by-gene transcriptional levels measured in microarrays. Over the past few years, many statistical methods of analyzing gene expression data in the context of gene sets have been proposed to simplify and increase the impartiality of gene expression data analysis. Gene set methods are designed to aid the investigator in making biological sense of gene expression data by viewing genes under study in the context of a priori identified, biologically relevant, gene sets. Gene sets are gro
Systems analysis of multiple regulator perturbations allows discovery of virulence factors in Salmonella
Hyunjin Yoon, Charles Ansong, Jason E McDermott, Marina Gritsenko, Richard D Smith, Fred Heffron, Joshua N Adkins
BMC Systems Biology , 2011, DOI: 10.1186/1752-0509-5-100
Abstract: 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 Salmonella 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 Salmonella or the type III injectisome-related flagellar mechanism.Integrating multi-omic datasets from Salmonella 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.The interactions between intracellular pathogen and host can be complex involving sophisticated offensive and defensive strategies by both organisms. Developing a systems level understanding of the virulence program of a pathogen, both in terms of the regulatory pathways and the virulence-related proteins that execute this program is important to effectively combat persistent and adapting pathogens [1-3]. Combining high-throughput characterization of proteins and gene transcripts under multiple different conditions relevant to virulence provides a wealth of information that can be mined to provide useful leads for further investigation or used as the basis of predictive models.Salmonella enterica serovar Typhimurium (STM) is a facultative intracellular bacterial pathogen with a broad host range capable of infecting birds, reptiles, mice, humans and other mammals. In humans, it is a leading causative agent
A Comprehensive Subcellular Proteomic Survey of Salmonella Grown under Phagosome-Mimicking versus Standard Laboratory Conditions
Roslyn N. Brown,James A. Sanford,Jea H. Park,Brooke L. Deatherage,Boyd L. Champion,Richard D. Smith,Fred Heffron,Joshua N. Adkins
International Journal of Proteomics , 2012, DOI: 10.1155/2012/123076
Abstract: Towards developing a systems-level pathobiological understanding of Salmonella enterica, we performed a subcellular proteomic analysis of this pathogen grown under standard laboratory and phagosome-mimicking conditions in vitro. Analysis of proteins from cytoplasmic, inner membrane, periplasmic, and outer membrane fractions yielded coverage of 25% of the theoretical proteome. Confident subcellular location could be assigned to over 1000 proteins, with good agreement between experimentally observed location and predicted/known protein properties. Comparison of protein location under the different environmental conditions provided insight into dynamic protein localization and possible moonlighting (multiple function) activities. Notable examples of dynamic localization were the response regulators of two-component regulatory systems (e.g., ArcB and PhoQ). The DNA-binding protein Dps that is generally regarded as cytoplasmic was significantly enriched in the outer membrane for all growth conditions examined, suggestive of moonlighting activities. These observations imply the existence of unknown transport mechanisms and novel functions for a subset of Salmonella proteins. Overall, this work provides a catalog of experimentally verified subcellular protein locations for Salmonella and a framework for further investigations using computational modeling. 1. Introduction The pursuit of a systems-level understanding of bacterial physiology requires not only knowledge about the identity, function, and relative abundance of proteins, but also insight into the subcellular localization of these proteins. Subcellular protein localization is linked to protein function, potential protein-protein interactions, and to interactions between a cell and its exterior environment. The observation of proteins in unexpected cellular compartments gives clues about the presence of possible alternate functions. Hence, there is a growing appreciation for the presence of bacterial “moonlighting proteins,” that is, those proteins that have a secondary function depending on subcellular location [1–3]. Experimentally verified localization also provides a foundation for describing proteins that are “hypothetical,” uncharacterized, or that contain domains of unknown function. Furthermore, with the increasing use of systems biology approaches, including genome-scale models of metabolism [4] and regulation to study microbial functions, experimentally founded protein localization on a global scale is necessary to produce more accurate model constraints. Subcellular proteomics has emerged as
Global Systems-Level Analysis of Hfq and SmpB Deletion Mutants in Salmonella: Implications for Virulence and Global Protein Translation
Charles Ansong, Hyunjin Yoon, Steffen Porwollik, Heather Mottaz-Brewer, Brianne O. Petritis, Navdeep Jaitly, Joshua N. Adkins, Michael McClelland, Fred Heffron, Richard D. Smith
PLOS ONE , 2009, DOI: 10.1371/journal.pone.0004809
Abstract: Using sample-matched transcriptomics and proteomics measurements it is now possible to begin to understand the impact of post-transcriptional regulatory programs in Enterobacteria. In bacteria post-transcriptional regulation is mediated by relatively few identified RNA-binding protein factors including CsrA, Hfq and SmpB. A mutation in any one of these three genes, csrA, hfq, and smpB, in Salmonella is attenuated for mouse virulence and unable to survive in macrophages. CsrA has a clearly defined specificity based on binding to a specific mRNA sequence to inhibit translation. However, the proteins regulated by Hfq and SmpB are not as clearly defined. Previous work identified proteins regulated by hfq using purification of the RNA-protein complex with direct sequencing of the bound RNAs and found binding to a surprisingly large number of transcripts. In this report we have used global proteomics to directly identify proteins regulated by Hfq or SmpB by comparing protein abundance in the parent and isogenic hfq or smpB mutant. From these same samples we also prepared RNA for microarray analysis to determine if alteration of protein expression was mediated post-transcriptionally. Samples were analyzed from bacteria grown under four different conditions; two laboratory conditions and two that are thought to mimic the intracellular environment. We show that mutants of hfq and smpB directly or indirectly modulate at least 20% and 4% of all possible Salmonella proteins, respectively, with limited correlation between transcription and protein expression. These proteins represent a broad spectrum of Salmonella proteins required for many biological processes including host cell invasion, motility, central metabolism, LPS biosynthesis, two-component regulatory systems, and fatty acid metabolism. Our results represent one of the first global analyses of post-transcriptional regulons in any organism and suggest that regulation at the translational level is widespread and plays an important role in virulence regulation and environmental adaptation for Salmonella.
Mutations of Francisella novicida that Alter the Mechanism of Its Phagocytosis by Murine Macrophages
Xin-He Lai,Renee L. Shirley,Lidia Crosa,Duangjit Kanistanon,Rebecca Tempel,Robert K. Ernst,Larry A. Gallagher,Colin Manoil,Fred Heffron
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0011857
Abstract: Infection with the bacterial pathogen Francisella tularensis tularensis (F. tularensis) causes tularemia, a serious and debilitating disease. Francisella tularensis novicida strain U112 (abbreviated F. novicida), which is closely related to F. tularensis, is pathogenic for mice but not for man, making it an ideal model system for tularemia. Intracellular pathogens like Francisella inhibit the innate immune response, thereby avoiding immune recognition and death of the infected cell. Because activation of inflammatory pathways may lead to cell death, we reasoned that we could identify bacterial genes involved in inhibiting inflammation by isolating mutants that killed infected cells faster than the wild-type parent. We screened a comprehensive transposon library of F. novicida for mutant strains that increased the rate of cell death following infection in J774 macrophage-like cells, as compared to wild-type F. novicida. Mutations in 28 genes were identified as being hypercytotoxic to both J774 and primary macrophages of which 12 were less virulent in a mouse infection model. Surprisingly, we found that F. novicida with mutations in four genes (lpcC, manB, manC and kdtA) were taken up by and killed macrophages at a much higher rate than the parent strain, even upon treatment with cytochalasin D (cytD), a classic inhibitor of macrophage phagocytosis. At least 10-fold more mutant bacteria were internalized by macrophages as compared to the parent strain if the bacteria were first fixed with formaldehyde, suggesting a surface structure is required for the high phagocytosis rate. However, bacteria were required to be viable for macrophage toxicity. The four mutant strains do not make a complete LPS but instead have an exposed lipid A. Interestingly, other mutations that result in an exposed LPS core were not taken up at increased frequency nor did they kill host cells more than the parent. These results suggest an alternative, more efficient macrophage uptake mechanism for Francisella that requires exposure of a specific bacterial surface structure(s) but results in increased cell death following internalization of live bacteria.
Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium
Charles Ansong, Nikola Toli?, Samuel O Purvine, Steffen Porwollik, Marcus Jones, Hyunjin Yoon, Samuel H Payne, Jessica L Martin, Meagan C Burnet, Matthew E Monroe, Pratap Venepally, Richard D Smith, Scott N Peterson, Fred Heffron, Michael McClelland, Joshua N Adkins
BMC Genomics , 2011, DOI: 10.1186/1471-2164-12-433
Abstract: We experimentally annotated the bacterial pathogen Salmonella Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in Salmonella and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in Salmonella pathogenesis. We also characterized post-translational features in the Salmonella genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our in vivo proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function.This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of Salmonella as a resource for systems analysis.Many aspects of modern biological research are dependent on accurate identification of the protein-coding genes in each genome, as well as the nature of the mature functional protein products, a process commonly referred to as genome annotation. With the exponential increase in the number of sequenced prokaryotic genomes afforded by advances in genome sequencing technologies over the last decade, present day prokaryotic genome annotation is essentially an automated high-throughput process that relies heavily on de novo gene prediction programs [1-3].While de novo gene prediction programs have significantly improved for prokaryotic genomes consider
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