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AUSTIN, TX, United States

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. Source


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 939.46K | Year: 2005

DESCRIPTION (provided by applicant): This Phase II proposal continues the development and validation of a bioinformatics and diagnostic platform for rapid detection and pre-symptomatic identification of biological agents on the basis of host gene and proteomic expression response profiles. Our collaborators preliminary host-pathogen studies indicate that exposed individuals display idiosyncratic peripheral blood mononuclear cell (PBMC) mKNA expression and serum protein temporal patterns to pathogenic agents prior to the onset of full illness. New tools are needed to determine the patterns from the volumes of complex, variable, and noisy genomic/proteomic data generated from host-pathogen studies. Our computational tools are based on the probabilistic power of dynamic Bayesian networks (DBNs) which are utilized to learn, model and recognize the dynamic pattern-of-change of mRNA and proteins ("biosignature") of the hostpathogen innate immune response. A unique feature of our approach is the inclusion of "time" combined with prior quantitative and qualitative knowledge that improves the recognition accuracy between different pathogenic agents. Phase I s/w prototype demonstrated proof-of-concept that our computational approach produced correct DBN models from time-course data mimicking the innate immune response to nine different pathogen types. The prototype performed remarkably well in both the representation of the time-course biosignatures as DBN models and for correctly identifying an unknown biosignature to the correct infectious agent with better than 98% accuracy. Phase II main objective is to statistically show that Seralogix's computational framework can extract and model unique host-pathogen biosignature patterns in the face of host heterogeneities using real time-course PBMC mRNA and protein datasets for the pathogens/toxin B. anthracis, cowpow, and staphylococcal enterotoxin B. in animal and non-human primate models. Existing time course data will be provided by our collaborators at the Walter Reed Army Institute of Research and the Biosignature Consortium (comprised of the University of New Mexico, the University of Texas Southwestern Med. Ctr., and Lawrence Livermore Labs). Seralogix believes that our DBN based computational tools will be important for: 1) deciphering the cellular signaling pathways and mechanisms of virulence and toxicity of pathogens/toxins; 2) creating new diagnostics for real-time, pre-symptomatic pathogenic identification, and 3) understanding the progressive stages of a disease to aid in creating new intervening drugs and therapeutic strategies.


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


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 660.74K | Year: 2004

DESCRIPTION (provided by applicant): Seralogix, inc. is proposing to develop and validate new computational tools and methods in conjunction with an intelligent framework for the identification, analysis, and modeling of the mechanisms and pathways ass

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