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Search Results: 1 - 10 of 172416 matches for " Jason E. McDermott "
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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.
A three-way comparative genomic analysis of Mannheimia haemolytica isolates
Paulraj K Lawrence, Weerayuth Kittichotirat, Jason E McDermott, Roger E Bumgarner
BMC Genomics , 2010, DOI: 10.1186/1471-2164-11-535
Abstract: During our comparative genomic sequence analysis of three Mannheimia haemolytica isolates, we identified a number of genes that are unique to each strain. These genes are "high value targets" for future studies that attempt to correlate the variable gene pool with phenotype. We also identified a number of high confidence single nucleotide polymorphisms (hcSNPs) spread throughout the genome and focused on non-synonymous SNPs in known virulence genes. These SNPs will be used to design new hcSNP arrays to study variation across strains, and will potentially aid in understanding gene regulation and the mode of action of various virulence factors.During our analysis we identified previously unknown possible type III secretion effector proteins, clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated sequences (Cas). The presence of CRISPR regions is indicative of likely co-evolution with an associated phage. If proven functional, the presence of a type III secretion system in M. haemolytica will help us re-evaluate our approach to study host-pathogen interactions. We also identified various adhesins containing immuno-dominant domains, which may interfere with host-innate immunity and which could potentially serve as effective vaccine candidates.Mannhemia haemolytica is a weakly haemolytic, Gram-negative bacterium and the principal casual agent associated with the respiratory-disease complex in ruminants. M. haemolytica is a normal commensal of the upper respiratory tract and tonsillar crypts in healthy ruminants. However, in the case of animals with compromised pulmonary defense mechanisms and stress, it can migrate into the lungs and cause acute fibrinous pleuropneumonia or pasteurellosis, commonly known as "shipping fever" [1-3]. Young animals are more susceptible than adults leading to sudden death with or without clinical signs [4]. Outbreaks of Pasteurellosis caused by M. haemolytica result in substantial economic losses to the globa
Suppressed Expression of T-Box Transcription Factors Is Involved in Senescence in Chronic Obstructive Pulmonary Disease
George K. Acquaah-Mensah ,Deepti Malhotra ,Madhulika Vulimiri,Jason E. McDermott,Shyam Biswal
PLOS Computational Biology , 2012, DOI: 10.1371/journal.pcbi.1002597
Abstract: Chronic obstructive pulmonary disease (COPD) is a major global health problem. The etiology of COPD has been associated with apoptosis, oxidative stress, and inflammation. However, understanding of the molecular interactions that modulate COPD pathogenesis remains only partly resolved. We conducted an exploratory study on COPD etiology to identify the key molecular participants. We used information-theoretic algorithms including Context Likelihood of Relatedness (CLR), Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE), and Inferelator. We captured direct functional associations among genes, given a compendium of gene expression profiles of human lung epithelial cells. A set of genes differentially expressed in COPD, as reported in a previous study were superposed with the resulting transcriptional regulatory networks. After factoring in the properties of the networks, an established COPD susceptibility locus and domain-domain interactions involving protein products of genes in the generated networks, several molecular candidates were predicted to be involved in the etiology of COPD. These include COL4A3, CFLAR, GULP1, PDCD1, CASP10, PAX3, BOK, HSPD1, PITX2, and PML. Furthermore, T-box (TBX) genes and cyclin-dependent kinase inhibitor 2A (CDKN2A), which are in a direct transcriptional regulatory relationship, emerged as preeminent participants in the etiology of COPD by means of senescence. Contrary to observations in neoplasms, our study reveals that the expression of genes and proteins in the lung samples from patients with COPD indicate an increased tendency towards cellular senescence. The expression of the anti-senescence mediators TBX transcription factors, chromatin modifiers histone deacetylases, and sirtuins was suppressed; while the expression of TBX-regulated cellular senescence markers such as CDKN2A, CDKN1A, and CAV1 was elevated in the peripheral lung tissue samples from patients with COPD. The critical balance between senescence and anti-senescence factors is disrupted towards senescence in COPD lungs.
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.
Controlling the Response: Predictive Modeling of a Highly Central, Pathogen-Targeted Core Response Module in Macrophage Activation
Jason E. McDermott,Michelle Archuleta,Brian D. Thrall,Joshua N. Adkins,Katrina M. Waters
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0014673
Abstract: We have investigated macrophage activation using computational analyses of a compendium of transcriptomic data covering responses to agonists of the TLR pathway, Salmonella infection, and manufactured amorphous silica nanoparticle exposure. We inferred regulatory relationship networks using this compendium and discovered that genes with high betweenness centrality, so-called bottlenecks, code for proteins targeted by pathogens. Furthermore, combining a novel set of bioinformatics tools, topological analysis with analysis of differentially expressed genes under the different stimuli, we identified a conserved core response module that is differentially expressed in response to all studied conditions. This module occupies a highly central position in the inferred network and is also enriched in genes preferentially targeted by pathogens. The module includes cytokines, interferon induced genes such as Ifit1 and 2, effectors of inflammation, Cox1 and Oas1 and Oasl2, and transcription factors including AP1, Egr1 and 2 and Mafb. Predictive modeling using a reverse-engineering approach reveals dynamic differences between the responses to each stimulus and predicts the regulatory influences directing this module. We speculate that this module may be an early checkpoint for progression to apoptosis and/or inflammation during macrophage activation.
Identification and Validation of Ifit1 as an Important Innate Immune Bottleneck
Jason E. McDermott, Keri B. Vartanian, Hugh Mitchell, Susan L. Stevens, Antonio Sanfilippo, Mary P. Stenzel-Poore
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0036465
Abstract: The innate immune system plays important roles in a number of disparate processes. Foremost, innate immunity is a first responder to invasion by pathogens and triggers early defensive responses and recruits the adaptive immune system. The innate immune system also responds to endogenous damage signals that arise from tissue injury. Recently it has been found that innate immunity plays an important role in neuroprotection against ischemic stroke through the activation of the primary innate immune receptors, Toll-like receptors (TLRs). Using several large-scale transcriptomic data sets from mouse and mouse macrophage studies we identified targets predicted to be important in controlling innate immune processes initiated by TLR activation. Targets were identified as genes with high betweenness centrality, so-called bottlenecks, in networks inferred from statistical associations between gene expression patterns. A small set of putative bottlenecks were identified in each of the data sets investigated including interferon-stimulated genes (Ifit1, Ifi47, Tgtp and Oasl2) as well as genes uncharacterized in immune responses (Axud1 and Ppp1r15a). We further validated one of these targets, Ifit1, in mouse macrophages by showing that silencing it suppresses induction of predicted downstream genes by lipopolysaccharide (LPS)-mediated TLR4 activation through an unknown direct or indirect mechanism. Our study demonstrates the utility of network analysis for identification of interesting targets related to innate immune function, and highlights that Ifit1 can exert a positive regulatory effect on downstream genes.
Topological analysis of protein co-abundance networks identifies novel host targets important for HCV infection and pathogenesis
Jason E McDermott, Deborah L Diamond, Courtney Corley, Angela L Rasmussen, Michael G Katze, Katrina M Waters
BMC Systems Biology , 2012, DOI: 10.1186/1752-0509-6-28
Abstract: We analyzed global proteomics data sets from a cell culture study of HCV infection and from a clinical study of liver biopsies from HCV-positive patients. Using lists of proteins known to be interaction partners with pathogen proteins we show that the most differentially regulated proteins in both data sets are indeed enriched in pathogen interactors. We then use these data sets to generate co-abundance networks that link proteins based on similar abundance patterns in time or across patients. Analysis of these co-abundance networks using a variety of network topology measures revealed that both degree and betweenness could be used to identify pathogen interactors with better accuracy than differential regulation alone, though betweenness provides the best discrimination. We found that though overall differential regulation was not correlated between the cell culture and liver biopsy data, network topology was conserved to an extent. Finally, we identified a set of proteins that has high betweenness topology in both networks including a protein that we have recently shown to be essential for HCV replication in cell culture.The results presented show that the network topology of protein co-abundance networks can be used to identify proteins important for viral replication. These proteins represent targets for further experimental investigation that will provide biological insight and potentially could be exploited for novel therapeutic approaches to combat HCV infection.Recent advances in high-throughput methods for taking global measurements of transcript or protein levels from biological samples have driven the field of systems biology. A common application of such methods is to identify genes or proteins that are likely to be involved in the disease process being studied to direct further experimental investigation. These 'targets' are potential mediators of important aspects of the disease, or may be downstream responses to the disease process. Targets are genera
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
Conserved host response to highly pathogenic avian influenza virus infection in human cell culture, mouse and macaque model systems
Jason E McDermott, Harish Shankaran, Amie J Eisfeld, Sarah E Belisle, Gabriele Neuman, Chengjun Li, Shannon McWeeney, Carol Sabourin, Yoshihiro Kawaoka, Michael G Katze, Katrina M Waters
BMC Systems Biology , 2011, DOI: 10.1186/1752-0509-5-190
Abstract: In the present study, we employed a multivariate modeling approach to characterize and compare the transcriptional regulatory networks between these three model systems after infection with a highly pathogenic avian influenza virus of the H5N1 subtype. Using this approach we identified functions and pathways that display similar behavior and/or regulation including the well-studied impact on the interferon response and the inflammasome. Our results also suggest a primary response role for airway epithelial cells in initiating hypercytokinemia, which is thought to contribute to the pathogenesis of H5N1 viruses. We further demonstrate that we can use a transcriptional regulatory model from the human cell culture data to make highly accurate predictions about the behavior of important components of the innate immune system in tissues from whole organisms.This is the first demonstration of a global regulatory network modeling conserved host response between in vitro and in vivo models.The 1918 influenza virus pandemic was one of the most devastating in history, and is estimated to have killed over 50 million people worldwide [1]. The continued circulation of highly pathogenic avian H5N1 viruses and the emergence of the 2009 H1N1 pandemic virus has revived concerns about another lethal pandemic [2,3]. Although H5N1 viruses are largely zoonotic, human infections have occurred, with mortality approaching 60% [4], and there have been reports of limited human-to-human transmission [5-8]. Thus, there is a considerable need to understand the processes that drive pathogenicity of influenza, both in terms of viral dynamics and the host response to infection.The selection of the appropriate model to study viral pathogenicity is essential to maintain relevance with human disease. Given their considerable similarity to humans, macaques are an excellent choice for studying the host response to influenza infection [9]. However, they are expensive, genetically diverse, and not amenabl
ACCEPT-NMR: A New Tool for the Analysis of Crystal Contacts and Their Links to NMR Chemical Shift Perturbations  [PDF]
Ivan V. Sergeyev, Ann E. McDermott
Journal of Crystallization Process and Technology (JCPT) , 2013, DOI: 10.4236/jcpt.2013.31003
Abstract:

We have developed an open-source cross-platform software toolkit entitled ACCEPT-NMR (Automated Crystal Contact Extrapolation/Prediction Toolkit for NMR) as a helpful tool to automate many of the complex tasks required to find and visualize crystal contacts in structures of biomolecules and biomolecular assemblies. This toolkit provides many powerful features geared toward NMR spectroscopy and related disciplines, such as isotopic labeling, advanced visualization options, and reporting tools. Using this software, we have undertaken a survey of available chemical shift data in the literature and deposited in the BMRB, and show that the mere presence of one or more crystal contacts to a residue confers an approximately 65% likelihood of significant chemical shift perturbations (relative to solution NMR chemical shifts). The presence of each additional crystal contact subsequently increases this probability, resulting in predictive accuracies in excess of 80% in many cases. Conversely, the presence of a significant experimental chemical shift perturbation indicates a >60% likelihood of finding one or more crystal contacts to a particular residue. Pinpointing sites likely to experience large CSPs is critical to mapping solution NMR chemical shifts onto solid-state NMR data as a basis for preliminary assignments, and can thus simplify the assignment process for complex biomolecules. Mapping observed CSPs onto the molecular structure, on the other hand, can indicate the presence of crystal interfaces where no crystal structure is available. Finally, by detecting sites critical to intermolecular interfaces, ACCEPT-NMR can help guide experimental approaches (e.g. isotopic labeling schemes) to detect and probe specific inter-subunit interactions.

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