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Title: Multi-comparative systems biology analysis reveals time-course biosignatures of in vivo bovine pathway responses to B. melitensis, S. enterica Typhimurium and M. avium paratuberculosis

Journal Article · · BMC Proceedings
 [1];  [2];  [2];  [3];  [4];  [5];  [5];  [6];  [6];  [7]
  1. Texas A & M Univ., College Station, TX (United States). College of Veterinary Medicine and Biomedical Science. Dept. of Veterinary Pathology; DOE/OSTI
  2. Texas A & M Univ., College Station, TX (United States). College of Veterinary Medicine and Biomedical Science. Dept. of Veterinary Pathology
  3. Instituto de Patobiologia, CICVyA-CNIA, INTA, Buenos Aires (Argentina)
  4. Univ. of Illinois at Urbana-Champaign, IL (United States). Dept. of Animal Sciences
  5. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Biological Sciences Division. Macromolecular Structure and Dynamics. Fundamental and Computational Sciences Directorate
  6. Washington State Univ., Pullman, WA (United States). College of Veterinary Medicine. Veterinary Microbiology and Pathology
  7. Seralogix LLC, Austin, TX (United States)
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Background: To decipher the complexity and improve the understanding of host-pathogen interactions, biologists must adopt new system level approaches in which the hierarchy of biological interactions and dynamics can be studied. This paper presents the application of systems biology for the cross-comparative analysis and interactome modeling of three different infectious agents, leading to the identification of novel, unique and common molecular host responses (biosignatures). Methods: A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Salmonella enterica Typhimurium (STM) and Mycobacterium avium paratuberculosis (MAP). A bovine ligated ileal loop biological model was employed to capture the host gene expression response at four time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a systematic comparative analysis of pathway and Gene Ontology category perturbations. Results: A cross-comparative assessment of 219 pathways and 1620 gene ontology (GO) categories was performed on each pathogen-host condition. Both unique and common pathway and GO perturbations indicated remarkable temporal differences in pathogen-host response profiles. Highly discriminatory pathways were selected from each pathogen condition to create a common system level interactome model comprised of 622 genes. This model was trained with data from each pathogen condition to capture unique and common gene expression features and relationships leading to the identification of candidate host-pathogen points of interactions and discriminatory biosignatures. Conclusions: Our results provide deeper understanding of the overall complexity of host defensive and pathogen invasion processes as well as the identification of novel host-pathogen interactions. The application of advanced computational methods for developing interactome models based on DBN has proven to be instrumental in conducting multi-conditional cross-comparative analyses. Further, this approach generates a fully simulateable model with capabilities for predictive analysis as well as for diagnostic pattern recognition. The resulting biosignatures may represent future targets for identification of emerging pathogens as well as for development of antimicrobial drugs, immunotherapeutics, or vaccines for prevention and treatment of diseases caused by known, emerging/re-emerging infectious agents.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
National Institutes of Health (NIH); USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
1629198
Journal Information:
BMC Proceedings, Journal Name: BMC Proceedings Journal Issue: S4 Vol. 5; ISSN 1753-6561
Publisher:
BioMed CentralCopyright Statement
Country of Publication:
United States
Language:
English

References (12)

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Macrophage signalling upon mycobacterial infection: the MAP kinases lead the way journal March 2003
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Simultaneous gene expression profiling in human macrophages infected with Leishmania major parasites using SAGE journal January 2008
Host-pathogen systems biology: logical modelling of hepatocyte growth factor and Helicobacter pylori induced c-Met signal transduction journal January 2008
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Morphologic and Molecular Characterization of Salmonella typhimurium Infection in Neonatal Calves journal March 2002
Genomic-scale Analysis of Bacterial Gene and Protein Expression in the Host journal August 2004

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Related Subjects

59 BASIC BIOLOGICAL SCIENCES
Brucella melitensis
dynamic Bayesian network
gene ontology
ileal loop
pathogen condition