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Accession Number DE2012-1034753
Title Integrated Genome-Based Studies of Shewanella Ecophysiology.
Publication Date Feb 2012
Media Count 7p
Personal Author D. Segre
Abstract This project was a component of the Shewanella Federation and, as such, contributed to the overall goal of applying the genomic tools to better understand eco-physiology and speciation of respiratory-versatile members of Shewanella genus. Our role at Boston University was to perform bioreactor and high throughput gene expression microarrays, and combine dynamic flux balance modeling with experimentally obtained transcriptional and gene expression datasets from different growth conditions. In the first part of project, we designed the S. oneidensis microarray probes for Affymetrix Inc. (based in California), then we identified the pathways of carbon utilization in the metal-reducing marine bacterium Shewanella oneidensis MR-1, using our newly designed high-density oligonucleotide Affymetrix microarray on Shewanella cells grown with various carbon sources. Next, using a combination of experimental and computational approaches, we built algorithm and methods to integrate the transcriptional and metabolic regulatory networks of S. oneidensis. Specifically, we combined mRNA microarray and metabolite measurements with statistical inference and dynamic flux balance analysis (dFBA) to study the transcriptional response of S. oneidensis MR-1 as it passes through exponential, stationary, and transition phases. By measuring time-dependent mRNA expression levels during batch growth of S. oneidensis MR-1 under two radically different nutrient compositions (minimal lactate and nutritionally rich LB medium), we obtain detailed snapshots of the regulatory strategies used by this bacterium to cope with gradually changing nutrient availability. In addition to traditional clustering, which provides a first indication of major regulatory trends and transcription factors activities, we developed and implemented a new computational approach for Dynamic Detection of Transcriptional Triggers (D2T2). This new method allows us to infer a putative topology of transcriptional dependencies, with special emphasis on the nodes at which external stimuli are expected to affect the internal dynamics.
Keywords Algorithms
Bioreactors
Carbon sources
Detection
Genes
Glycogen
Lactates
Metabolites
Nitrogen
Nutrients
Oligonucleotides
Oxygen
Pipelines
Shwanella ecophysiology
Topology
Transcription factors

 
Source Agency Technical Information Center Oak Ridge Tennessee
NTIS Subject Category 57B - Biochemistry
57F - Cytology, Genetics, & Molecular Biology
Corporate Author Boston Univ., MA.
Document Type Technical report
Title Note N/A
NTIS Issue Number 1303
Contract Number DE-FG02-07ER64388

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