Summer Research Fellowship Programme of India's Science Academies

Identification of differentially expressed genes in Staphylococcus aureus in response to antibiotic exposure

Johny IJaq

Teaching Assistant, University College for Women, Osmania University, Hyderabad- 500095

Dr. Saroj Kant Mohapatra

Assistant Professor, NIBMG, Kalyani, West Bengal- 741251


Genome-wide expression profiling simultaneously measures expression of the entire genome of an organism, and thus offers the opportunity to detect differentially expressed genes (under different phenotypic conditions) in a single experiment. In this study, we have focused on analysis of genome-wide expression data of a bacterial species of clinical significance. Staphylococcus aureus is a gram-positive bacterium that causes sepsis, a life-threatening condition. Antimicrobial resistance (AMR) is worrisome in staphylococcal infections as it is associated with high morbidity and mortality. Understanding the biological basis of emergence of AMR is an important first step toward development of appropriate treatment strategies. We aim to identify a common set of genes that are differentially expressed in S. aureus under different stress exposures. In order to better elucidate the molecular changes associated with exposure to different stressors, we selected published data sets of the transcriptome of S. aureus exposed to various antibiotics. Normalized data from over 28 samples of bacteria transcriptome (including treated and untreated groups) were downloaded from NCBI GEO. Gene expression data matrix was prepared showing feature annotation, expression levels (log 2 scale) and sample annotation. Various analytical procedures were applied to identify the genes with similar transcription patterns among the five selected studies. Appropriate visualization was performed to demonstrate the functional relevance of the selected genes. The selected genes were annotated for previous known association with bacterial stress response. The analyses were done using R and Bioconductor packages in GNU/Linux environment.

Keywords: Gene Expression Profiling, Microarray Data Analysis, Bacterial Stress Response, Antibiotic Resistance

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