The goal of this proposal is to translate genomic sequence data into high-quality biological knowledge on microbial signal transduction. Signal transduction pathways control important cellular activities ranging from virulence and antibiotic resistance in bacterial pathogens to intracellular communication and coordination of complex cellular functions in humans. Signal transduction is one of the most problematic areas for current genome annotation protocols because of the high sequence variability of input and output domains and mosaic architecture of signal transduction proteins. We will achieve the goal of this proposal via high-throughput genome processing, sophisticated computational protein sequence analysis, and collaborations with leading experimental scientists. The central questions in the biology of signal transduction are: (1) What proteins comprise signal transduction pathways and (2) How the proteins transduce signals. To address these questions, we will first develop a high-throughput computational approach to improve function prediction for signal transduction proteins in microbial genomes combined with experimental validation of selected targets by our collaborators (SPECIFIC AIM 1). Second, we will develop an innovative computational approach to predict contact sites in interacting proteins within the best-studied signal transduction pathway (SPECIFIC AIM 2). These predictions will also be validated by our collaborators. A Knowledge Environment developed under SPECIFIC AIM 3 will integrate results obtained under this proposal and provide free access to the data and computational resources. In the long term, this research will allow us to generalize the computational approaches to signal transduction developed in simple microbial systems and extend them to complex eukaryotic systems, including those in humans. This research will also have an immediate impact on understanding the biology of human pathogens and antimicrobial drug design, and contribute to improvement of automated annotation in primary sequence databases.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
7R01GM072285-02
Application #
6946930
Study Section
Special Emphasis Panel (ZRG1-BST-D (50))
Program Officer
Anderson, James J
Project Start
2004-09-06
Project End
2009-08-31
Budget Start
2005-09-01
Budget End
2006-08-31
Support Year
2
Fiscal Year
2005
Total Cost
$187,369
Indirect Cost
Name
University of Tennessee Knoxville
Department
Microbiology/Immun/Virology
Type
Schools of Arts and Sciences
DUNS #
003387891
City
Knoxville
State
TN
Country
United States
Zip Code
37996
Ortega, Davi R; Zhulin, Igor B (2018) Phylogenetic and Protein Sequence Analysis of Bacterial Chemoreceptors. Methods Mol Biol 1729:373-385
Petukh, Marharyta; Zhulin, Igor B (2018) Comparative study of the effect of disease causing and benign mutations in position Q92 on cholesterol binding by the NPC1 n-terminal domain. Proteins 86:1165-1175
Liu, Jinpeng; Murali, Thilakam; Yu, Tianxin et al. (2018) Characterization of Squamous Cell Lung Cancers from Appalachian Kentucky. Cancer Epidemiol Biomarkers Prev :
Lu, Jacqueline G; Bishop, Juliet; Cheyette, Sarah et al. (2018) A novel PRRT2 pathogenic variant in a family with paroxysmal kinesigenic dyskinesia and benign familial infantile seizures. Cold Spring Harb Mol Case Stud 4:
Zhulin, Igor B (2017) By Staying Together, Two Genes Keep the Motor Running. Structure 25:214-215
Stock, Ann M; Zhulin, Igor B (2017) Two-Component Signal Transduction: a Special Issue in the Journal of Bacteriology. J Bacteriol 199:
Adebali, Ogun; Petukh, Marharyta G; Reznik, Alexander O et al. (2017) Class III Histidine Kinases: a Recently Accessorized Kinase Domain in Putative Modulators of Type IV Pilus-Based Motility. J Bacteriol 199:
Adebali, Ogun; Zhulin, Igor B (2017) Aquerium: A web application for comparative exploration of domain-based protein occurrences on the taxonomically clustered genome tree. Proteins 85:72-77
Ortega, Álvaro; Zhulin, Igor B; Krell, Tino (2017) Sensory Repertoire of Bacterial Chemoreceptors. Microbiol Mol Biol Rev 81:
Ortega, Davi R; Fleetwood, Aaron D; Krell, Tino et al. (2017) Assigning chemoreceptors to chemosensory pathways in Pseudomonas aeruginosa. Proc Natl Acad Sci U S A 114:12809-12814

Showing the most recent 10 out of 44 publications