Integration of genomics and transcriptomics; Analysis of Streptococcus pneumoniae wild-type and ΔccpA strains

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School of Science | Master's thesis
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In many Gram-positive bacteria, the transcription regulator catabolite control protein A (CcpA) has a global regulatory effect in response to carbohydrate availability, lying at the core of catabolite control mechanisms. In a previous study, whole-genome microarray analysis comparing the human pathogen Streptococcus pneumoniae D39 with its isogenic ccpA mutant, grown in chemically defined medium (CDM) containing two different carbon sources, glucose and galactose, was obtained at mid-exponential and transition to stationary phases of growth. In this work, we resorted to this previous analysis to perform in silico differential expression, clustering, Biclustering and functional analysis of the data in order to narrow down the genome-wide analysis to study specific cellular processes. Besides, an integrative approach was adopted to analyse genomics and transcriptomics data. Our data showed that CcpA regulates the expression of genes involved in many cellular processes as determined by comparing gene ontology associated biological processes and Clusters of Orthologous Groups (COGs) of proteins databases. Carbohydrate transport and metabolism were the most affected functions and, accordingly, defence mechanisms based on carbohydrate availability. In order to predict catabolite responsive element (cre) sites in S. pneumoniae D39, a probabilistic motif inference analysis was performed using the known consensus cre sequences of other Gram-positive bacteria, namely Bacillus subtilis, Bacillus megaterium and Lactobacillus lactis. Remarkably, this analysis revealed the presence of 211 putative targets of CcpA. These motifs, over-represented in differentially expressed genes (Fisher's Exact Test), were further analysed in terms of the distribution of their position related to the promoter region. Integration of genomic information with transcriptomic analyses revealed that a high number of genes from different functional categories were directly affected, thus providing a promising strategy to infer gene regulatory networks.
Lähdesmäki, Harri|Vinga, Susana
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Madeira, Sara C.
comparative transcriptomic analysis, biclustering, carbon catabolite repression, motif inference, pathogen systems, functional analysis