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Khare S.,Texas A&M University | Khare S.,U.S. Food and Drug Administration | Lawhon S.D.,Texas A&M University | Drake K.L.,Seralogix | And 10 more authors.
PLoS ONE | Year: 2012

Survival and persistence of Mycobacterium avium subsp. paratuberculosis (MAP) in the intestinal mucosa is associated with host immune tolerance. However, the initial events during MAP interaction with its host that lead to pathogen survival, granulomatous inflammation, and clinical disease progression are poorly defined. We hypothesize that immune tolerance is initiated upon initial contact of MAP with the intestinal Peyer's patch. To test our hypothesis, ligated ileal loops in neonatal calves were infected with MAP. Intestinal tissue RNAs were collected (0.5, 1, 2, 4, 8 and 12 hrs post-infection), processed, and hybridized to bovine gene expression microarrays. By comparing the gene transcription responses of calves infected with the MAP, informative complex patterns of expression were clearly visible. To interpret these complex data, changes in the gene expression were further analyzed by dynamic Bayesian analysis, and genes were grouped into the specific pathways and gene ontology categories to create a holistic model. This model revealed three different phases of responses: i) early (30 min and 1 hr post-infection), ii) intermediate (2, 4 and 8 hrs post-infection), and iii) late (12 hrs post-infection). We describe here the data that include expression profiles for perturbed pathways, as well as, mechanistic genes (genes predicted to have regulatory influence) that are associated with immune tolerance. In the Early Phase of MAP infection, multiple pathways were initiated in response to MAP invasion via receptor mediated endocytosis and changes in intestinal permeability. During the Intermediate Phase, perturbed pathways involved the inflammatory responses, cytokine-cytokine receptor interaction, and cell-cell signaling. During the Late Phase of infection, gene responses associated with immune tolerance were initiated at the level of T-cell signaling. Our study provides evidence that MAP infection resulted in differentially regulated genes, perturbed pathways and specifically modified mechanistic genes contributing to the colonization of Peyer's patch. © 2012 Khare et al.


Adams L.G.,Texas A&M University | Khare S.,Texas A&M University | Lawhon S.D.,Texas A&M University | Rossetti C.A.,Instituto Nacional de Tecnologia Agropecuaria | And 7 more authors.
Vaccine | Year: 2011

The aim of research on infectious diseases is their prevention, and brucellosis and salmonellosis as such are classic examples of worldwide zoonoses for application of a systems biology approach for enhanced rational vaccine development. When used optimally, vaccines prevent disease manifestations, reduce transmission of disease, decrease the need for pharmaceutical intervention, and improve the health and welfare of animals, as well as indirectly protecting against zoonotic diseases of people. Advances in the last decade or so using comprehensive systems biology approaches linking genomics, proteomics, bioinformatics, and biotechnology with immunology, pathogenesis and vaccine formulation and delivery are expected to enable enhanced approaches to vaccine development. The goal of this paper is to evaluate the role of computational systems biology analysis of host:pathogen interactions (the interactome) as a tool for enhanced rational design of vaccines. Systems biology is bringing a new, more robust approach to veterinary vaccine design based upon a deeper understanding of the host-pathogen interactions and its impact on the host's molecular network of the immune system. A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Mycobacterium avium paratuberculosis (MAP), Salmonella enterica Typhimurium (STM), and a Salmonella mutant (isogenic Δ sipA, sopABDE2) and linked to the basis for rational development of vaccines for brucellosis and salmonellosis as reviewed by Adams et al. and Ficht et al. [1,2]. A bovine ligated ileal loop biological model was established to capture the host gene expression response at multiple time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a comparative pathogenicity analysis of 219 signaling and metabolic pathways and 1620 gene ontology (GO) categories that defined the host's biosignatures to each infectious condition. Through this DBN computational approach, the method identified significantly perturbed pathways and GO category groups of genes that define the pathogenicity signatures of the infectious agent. Our preliminary results provide deeper understanding of the overall complexity of host innate immune response as well as the identification of host gene perturbations that defines a unique host temporal biosignature response to each pathogen. The application of advanced computational methods for developing interactome models based on DBNs has proven to be instrumental in elucidating novel host responses and improved functional biological insight into the host defensive mechanisms. Evaluating the unique differences in pathway and GO perturbations across pathogen conditions allowed the identification of plausible host-pathogen interaction mechanisms. Accordingly, a systems biology approach to study molecular pathway gene expression profiles of host cellular responses to microbial pathogens holds great promise as a methodology to identify, model and predict the overall dynamics of the host-pathogen interactome. Thus, we propose that such an approach has immediate application to the rational design of brucellosis and salmonellosis vaccines. © 2011 Elsevier Ltd.


PubMed | University of Illinois at Urbana - Champaign, Seralogix and Texas A&M University
Type: Journal Article | Journal: PloS one | Year: 2016

It has long been a quest in ruminants to understand how two very similar mycobacterial species, Mycobacterium avium ssp. paratuberculosis (MAP) and Mycobacterium avium ssp. avium (MAA) lead to either a chronic persistent infection or a rapid-transient infection, respectively. Here, we hypothesized that when the host immune response is activated by MAP or MAA, the outcome of the infection depends on the early activation of signaling molecules and host temporal gene expression. To test our hypothesis, ligated jejuno-ileal loops including Peyers patches in neonatal calves were inoculated with PBS, MAP, or MAA. A temporal analysis of the host transcriptome profile was conducted at several times post-infection (0.5, 1, 2, 4, 8 and 12 hours). When comparing the transcriptional responses of calves infected with the MAA versus MAP, discordant patterns of mucosal expression were clearly evident, and the numbers of unique transcripts altered were moderately less for MAA-infected tissue than were mucosal tissues infected with the MAP. To interpret these complex data, changes in the gene expression were further analyzed by dynamic Bayesian analysis. Bayesian network modeling identified mechanistic genes, gene-to-gene relationships, pathways and Gene Ontologies (GO) biological processes that are involved in specific cell activation during infection. MAP and MAA had significant different pathway perturbation at 0.5 and 12 hours post inoculation. Inverse processes were observed between MAP and MAA response for epithelial cell proliferation, negative regulation of chemotaxis, cell-cell adhesion mediated by integrin and regulation of cytokine-mediated signaling. MAP inoculated tissue had significantly lower expression of phagocytosis receptors such as mannose receptor and complement receptors. This study reveals that perturbation of genes and cellular pathways during MAP infection resulted in host evasion by mucosal membrane barrier weakening to access entry in the ileum, inhibition of Ca signaling associated with decreased phagosome-lysosome fusion as well as phagocytosis inhibition, bias toward Th2 cell immune response accompanied by cell recruitment, cell proliferation and cell differentiation; leading to persistent infection. Contrarily, MAA infection was related to cellular responses associated with activation of molecular pathways that release chemicals and cytokines involved with containment of infection and a strong bias toward Th1 immune response, resulting in a transient infection.


Weeks J.N.,Texas A&M University | Weeks J.N.,St Jude Childrens Research Hospital | Galindo C.L.,University of Virginia | Drake K.L.,Seralogix | And 3 more authors.
BMC Microbiology | Year: 2010

Background. Quorum sensing is a communication system that regulates gene expression in response to population density and often regulates virulence determinants. Deletion of the luxR homologue vjbR highly attenuates intracellular survival of Brucella melitensis and has been interpreted to be an indication of a role for QS in Brucella infection. Confirmation for such a role was suggested, but not confirmed, by the demonstrated in vitro synthesis of an auto-inducer (AI) by Brucella cultures. In an effort to further delineate the role of VjbR to virulence and survival, gene expression under the control of VjbR and AI was characterized using microarray analysis. Results. Analyses of wildtype B. melitensis and isogenic ΔvjbR transciptomes, grown in the presence and absence of exogenous N-dodecanoyl homoserine lactone (C 12-HSL), revealed a temporal pattern of gene regulation with variances detected at exponential and stationary growth phases. Comparison of VjbR and C12-HSL transcriptomes indicated the shared regulation of 127 genes with all but 3 genes inversely regulated, suggesting that C 12-HSL functions via VjbR in this case to reverse gene expression at these loci. Additional analysis using a vjbR mutant revealed that AHL also altered gene expression in the absence of VjbR, up-regulating expression of 48 genes and a luxR homologue blxR 93-fold at stationary growth phase. Gene expression alterations include previously un-described adhesins, proteases, antibiotic and toxin resistance genes, stress survival aids, transporters, membrane biogenesis genes, amino acid metabolism and transport, transcriptional regulators, energy production genes, and the previously reported fliF and virB operons. Conclusions. VjbR and C12-HSL regulate expression of a large and diverse number of genes. Many genes identified as virulence factors in other bacterial pathogens were found to be differently expressed, suggesting an important contribution to intracellular survival of Brucella. From these data, we conclude that VjbR and C12-HSL contribute to virulence and survival by regulating expression of virulence mechanisms and thus controlling the ability of the bacteria to survive within the host cell. A likely scenario occurs via QS, however, operation of such a mechanism remains to be demonstrated. © 2010 Weeks et al; licensee BioMed Central Ltd.


Laughlin R.C.,Texas A&M University | Laughlin R.C.,Texas A&M University-Kingsville | Drake K.L.,Seralogix | Morrill J.C.,University of Texas Medical Branch | Adams L.G.,Texas A&M University
PLoS ONE | Year: 2016

Rift Valley fever Virus (RVFV), a negative-stranded RNA virus, is the etiological agent of the vector-borne zoonotic disease, Rift Valley fever (RVF). In both humans and livestock, protective immunity can be achieved through vaccination. Earlier and more recent vaccine trials in cattle and sheep demonstrated a strong neutralizing antibody and total IgG response induced by the RVF vaccine, authentic recombinant MP-12 (arMP-12). From previous work, protective immunity in sheep and cattle vaccinates normally occurs from 7 to 21 days after inoculation with arMP-12. While the serology and protective response induced by arMP-12 has been studied, little attention has been paid to the underlying molecular and genetic events occurring prior to the serologic immune response. To address this, we isolated RNA from whole blood of vaccinated calves over a time course of 21 days before and after vaccination with arMP-12. The time course RNAs were sequenced by RNASeq and bioinformatically analyzed. Our results revealed time-dependent activation or repression of numerous gene ontologies and pathways related to the vaccine induced immune response and its regulation. Additional bioinformatic analyses identified a correlative relationship between specific host immune response genes and protective immunity prior to the detection of protective serum neutralizing antibody responses. These results contribute an important proof of concept for identifying molecular and genetic components underlying the immune response to RVF vaccination and protection prior to serologic detection. © 2016 Laughlin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Hanna N.,Montpellier University | Hanna N.,French National Center for Scientific Research | Ouahrani-Bettache S.,Montpellier University | Ouahrani-Bettache S.,French National Center for Scientific Research | And 6 more authors.
BMC Genomics | Year: 2013

Background: In the intracellular pathogen Brucella spp., the activation of the stringent response, a global regulatory network providing rapid adaptation to growth-affecting stress conditions such as nutrient deficiency, is essential for replication in the host. A single, bi-functional enzyme Rsh catalyzes synthesis and hydrolysis of the alarmone (p)ppGpp, responsible for differential gene expression under stringent conditions.Results: cDNA microarray analysis allowed characterization of the transcriptional profiles of the B. suis 1330 wild-type and Δrsh mutant in a minimal medium, partially mimicking the nutrient-poor intramacrophagic environment. A total of 379 genes (11.6% of the genome) were differentially expressed in a rsh-dependent manner, of which 198 were up-, and 181 were down-regulated. The pleiotropic character of the response was confirmed, as the genes encoded an important number of transcriptional regulators, cell envelope proteins, stress factors, transport systems, and energy metabolism proteins. Virulence genes such as narG and sodC, respectively encoding respiratory nitrate reductase and superoxide dismutase, were under the positive control of (p)ppGpp, as well as expression of the cbb3-type cytochrome c oxidase, essential for chronic murine infection. Methionine was the only amino acid whose biosynthesis was absolutely dependent on stringent response in B. suis.Conclusions: The study illustrated the complexity of the processes involved in adaptation to nutrient starvation, and contributed to a better understanding of the correlation between stringent response and Brucella virulence. Most interestingly, it clearly indicated (p)ppGpp-dependent cross-talk between at least three stress responses playing a central role in Brucella adaptation to the host: nutrient, oxidative, and low-oxygen stress. © 2013 Hanna et al.; licensee BioMed Central Ltd.


Rossetti C.A.,Texas A&M University | Rossetti C.A.,Instituto Nacional de Tecnologia Agropecuaria | Drake K.L.,Seralogix | Adams L.G.,Texas A&M University
Microbes and Infection | Year: 2012

Brucella spp. infect hosts primarily by adhering and penetrating mucosal surfaces, however the initial molecular phenomena of this host:pathogen interaction remain poorly understood. We hypothesized that characterizing the epithelial-like human HeLa cell line molecular response to wild type Brucella melitensis infection would help to understand the role of the mucosal epithelium at the onset of the Brucella pathogenesis. RNA samples from B. melitensis-infected HeLa cells were taken at 4 and 12 h of infection and hybridized in a cDNA microarray. The analysis using a dynamic Bayesian network modeling approach (DBN) identified several pathways, biological processes, cellular components and molecular functions altered due to infection at 4 h p.i., but almost none at 12 h p.i. The in silico modeling results were experimentally tested by knocking down the expression of MAPK1 by siRNA technology. MAPK1-siRNA transfected cell cultures decreased the internalization and impaired the intracellular replication of the pathogen in HeLa cells after 4 h p.i. DBN analysis provides important insights into the role of the epithelial cells response to Brucella infection and guide research to novel mechanisms identification. © 2012 Institut Pasteur.


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 1.13M | Year: 2010

DESCRIPTION (provided by applicant): The overall Phase II objective is to continue the development/validation of new system biology computational tools for inferencing gene regulatory relationships from gene expression data obtained from multi-perturbation gene knockout experiments. NIH's Knockout Mouse Project (KOMP) is an initiative to generate a public resource of mouse embryonic stem (ES) cells containing a null mutation in every gene in the mouse genome - important for deciphering the complexity of biological systems of mice and ultimately man. It is anticipated that a new generation of multi-perturbation/KO studies with a biological system perspective will emerge in all areas of biomedical research. New computational tools for deciphering genetically regulated responses (genotype-to- phenotype signaling cascades) will significantly aid in advancing our understanding of the molecular targets and mechanisms of many diseases. Today, researchers need new tools to deal with and decipher the tremendous volumes of gene/protein expression data generated from multi-perturbation investigations. Seralogix's Phase II efforts focus on improving and creating new functionality for learning larger scale (biological system level) gene regulatory networks and integrating this network learning functionality into our existing Biosystem Analysis Framework (BAF). Our BAF is comprised of a suite of integrated mathematical analysis and modeling tools and databases. The BAF core tools are based on Dynamic Bayesian Networks (DBNs). DBNs allow us to systematically integrate prior knowledge with empirical time-course expression data for modeling, pattern recognition and eventually biological system genetic network learning as proposed herein. Our algorithmic innovation, proven feasible in Phase I, is the incorporation of biological prior knowledge and multi-perturbation data with our DBNs for enabling a genetic network learning approach. This approach is based on well established Bayesian statistical methods that we adopt in a sampling scheme enhanced with biological prior knowledge to overcome the intrinsic difficulty of structure learning from sparse and noisy gene expression data. We show in Phase I that prior-knowledge, coupled with Bayesian network learning methods and multi-perturbation/KO experimental data, resulted in reliable gene regulatory relationship identification. We believe this approach can be scaled up, leading to a more robust mathematical/functional system level model. Further, we believe that integrating genetic network learning into Seralogix's BAF will provide an important new tool for identifying novel gene regulatory relations and insights into disease processes and have significant commercial potential for Seralogix. We will be collaborating with the Texas Institute of Genomic Medicine as a provider of mouse gene expression KO data who are studying the genomic causes of birth defects. Our Phase II aims include: 1) scaling our approach to support biological system level network learning; 2) statistical assessment and biological validation of our learned networks; 3) developing new tools/techniques to interrogate the resulting system network models so biologist can extract important knowledge. PUBLIC HEALTH RELEVANCE: It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that control health and disease, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. Having new computational methods (software tools) for identifying and deciphering genetically regulated response (e.g. signaling cascades) will significantly aid in advancing our understanding of the molecular targets and mechanisms of many diseases of high public health concern. The discovery of underlying genetic function and relationships will be extremely important for making medical breakthroughs, especially for the safe and effective development of drugs and diagnostics. Today, researchers are hindered by the tremendous volumes of gene/protein expression data generated from knockout investigations. Computational tools that transform these volumes of raw genomic/proteomic data to actionable knowledge via mathematical modeling will help guide and accelerate researchers' investigations of genetic disorder and identifying targets of intervention and treatment.


Grant
Agency: Department of Health and Human Services | Branch: National Institutes of Health | Program: SBIR | Phase: Phase II | Award Amount: 190.03K | Year: 2016

DESCRIPTION The primary goal of this fast track project is to commercialize a cloud based software suite complemented with on call expert services to guide life science researchers that may have minimal statistical and experimental design ED knowledge to rigorously plan optimize justify manage and report results for complex animal studies Inadequately planned experiments e g lack of randomization blinding and diversity low sample size high test variabilities etc can introduce bias and limit statistical power both of which may lead to possible misinterpretations of results and ineffective use of resources Such deficiencies and poor quality reporting can lead to irreproducible results and may mislead the scientific community Compounding the problem is the complex nature of the studies themselves such as species diversity strain sex groupings litters randomization sample size power sampling times analysis and treatment plans outcome variability and cost tradeoffs that all must be considered when optimizing EDs Some of these issues may be caused by a lack of access to statisticians test method knowledge i e variabilities and planning tools or a lack of rigorous training in ED methods A collaborative initiative was created by Seralogix to include experts from the University of Texas FDA University of Utah University of Edinburgh and the Broad Institute Addressing these issues Seralogix and our collaborators will implement an intelligent knowledge driven cloud application and service portal for ED planning and optimization called the Statistically Rigorous Experimental Animal Study Designer i e SHREWD We believe that SHREWD will lead to a reduction in animal use savings in financial and scientific resources and will improve the scientific validity of the study results through the rigorous collection of daa following well planned and executed experimental designs PUBLIC HEALTH RELEVANCE This project will commercialize a cloud based software suite complemented with on call expert services to guide life science researchers that may have minimal statistical and experimental design ED knowledge to rigorously plan optimize justify manage and report results for complex animal studies The software may lead to a reduction in animal use savings in financial and scientific resources and will improve the scientific validityof the study results through the rigorous collection of data following well planned and executed experimental designs


Grant
Agency: Department of Health and Human Services | Branch: National Institutes of Health | Program: SBIR | Phase: Phase I | Award Amount: 150.03K | Year: 2016

DESCRIPTION The primary goal of this fast track project is to commercialize a cloud based software suite complemented with on call expert services to guide life science researchers that may have minimal statistical and experimental design ED knowledge to rigorously plan optimize justify manage and report results for complex animal studies Inadequately planned experiments e g lack of randomization blinding and diversity low sample size high test variabilities etc can introduce bias and limit statistical power both of which may lead to possible misinterpretations of results and ineffective use of resources Such deficiencies and poor quality reporting can lead to irreproducible results and may mislead the scientific community Compounding the problem is the complex nature of the studies themselves such as species diversity strain sex groupings litters randomization sample size power sampling times analysis and treatment plans outcome variability and cost tradeoffs that all must be considered when optimizing EDs Some of these issues may be caused by a lack of access to statisticians test method knowledge i e variabilities and planning tools or a lack of rigorous training in ED methods A collaborative initiative was created by Seralogix to include experts from the University of Texas FDA University of Utah University of Edinburgh and the Broad Institute Addressing these issues Seralogix and our collaborators will implement an intelligent knowledge driven cloud application and service portal for ED planning and optimization called the Statistically Rigorous Experimental Animal Study Designer i e SHREWD We believe that SHREWD will lead to a reduction in animal use savings in financial and scientific resources and will improve the scientific validity of the study results through the rigorous collection of daa following well planned and executed experimental designs PUBLIC HEALTH RELEVANCE This project will commercialize a cloud based software suite complemented with on call expert services to guide life science researchers that may have minimal statistical and experimental design ED knowledge to rigorously plan optimize justify manage and report results for complex animal studies The software may lead to a reduction in animal use savings in financial and scientific resources and will improve the scientific validityof the study results through the rigorous collection of data following well planned and executed experimental designs

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