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United States Department of Agriculture

Agricultural Research Service

Title: Computational Methods and Evaluation of Rna Stabilization Reagents for Genome-Wide Expression Studies

Authors
item Bhagwat, Arvind
item Phadke, Ravindra - RUIA COLLGE, INDIA
item Wheeler, David - NCBI, NIH, MD
item Kalantre, Sagar - RUIA COLLEGE, INDIA
item Ram, Mohan - RUIA COLLEGE, INDIA
item Bhagwat, Medha - NCBI, NIH, MD

Submitted to: Journal of Microbiological Methods
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 5, 2003
Publication Date: December 1, 2003
Citation: Bhagwat, A.A., Phadke, R.P., Wheeler, D., Kalantre, S., Ram, M., Bhagwat, M. 2003. Computational methods and evaluation of rna stabilization reagents for genome-wide expression studies. Journal of Microbiological Methods 55 (2003) 399-409

Interpretive Summary: Controlling or limiting outbreaks of human pathogenic bacteria on fresh fruits and vegetables has become a major priority. One of our approaches to this problem is to understand the genes involved in the ability of bacteria to attach, survive and grow on produce. However, to predict gene function(s) accurately from the genome sequence data of foodborne pathogens remains a formidable task. For example, about 30% of Escherichia coli genes are still classified as unknowns, with little idea about their function. Gene functions and their expression profiles of food-borne pathogens are required to identify "new targets" to better address the problem of ever increasing antibiotic resistance. One of the powerful methods for whole-genome analysis is array-based gene expression monitoring. This manuscript proposes new experimental and computational protocols for genome-wide gene expression studies. Our data indicate that certain RNA-stabilization reagents can induce stress responses, and proper caution must be exercised during their use. To assist in the analysis of gene-expression data, we wrote a number of software programs that use the most recent gene data in accordance with gene function. Analyzing relationships among messenger RNA expression data is a significant step towards establishing functional links between the proteins encoded by the corresponding genes. This research will provide necessary insights for some of the critical emerging issues of food safety, such as survival tactics used by human pathogens.

Technical Abstract: Gene expression studies require high quality messenger RNA in addition to other factors such as efficient primers and labeling reagents. In order to prevent RNA degradation and to improve the quality of gene array expression data, several commercial reagents have become available. We examined conventional hot-phenol-lysis method and RNA-stabilization reagents, and generated comparative gene-expression profiles from Escherichia coli cells grown on minimal medium. Our data indicate that certain RNA-stabilization reagents could induce stress responses and proper caution must be exercised during their use. We found that the laboratory reagent (5% phenol-95% ethanol) worked efficiently in isolating high quality mRNA and reproducibility was such that reliable gene expression profiles were generated. To assist in the analysis of gene-expression data, we have written a number of macros that use the most recent gene annotation and process data in accordance with gene function. Scripts were also written to examine the occurrence of any artifacts, based on GC content, length of the individual open reading frame, it's distribution on plus and minus DNA strands, and the distance from the replication origin.

Last Modified: 4/19/2014
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