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Nutrilyzer: A Tool for Deciphering Atomic Stoichiometry of Differentially Expressed Paralogous Proteins
Lotz, Katrin ; Schreiber, Falk ; Wunschiers, Robbe
Journal of Integrative Bioinformatics - JIB (ISSN 1613-4516)
Organisms try to maintain homeostasis by balanced uptake of nutrients from their environment. From an atomic perspective this means that, for example, carbon:nitrogen:sulfur ratios are kept within given limits. Upon limitation of, for example, sulfur, its acquisition is triggered. For yeast it was shown that transporters and enzymes involved in sulfur uptake are encoded as paralogous genes that express different isoforms. Sulfur deprivation leads to up-regulation of isoforms that are poor in sulfur-containing amino acids, that is, methinone and cysteine. Accordingly, sulfur-rich isoforms are down-regulated. We developed a web-based software, doped Nutrilyzer, that extracts paralogous protein coding sequences from an annotated genome sequence and evaluates their atomic composition. When fed with gene-expression data for nutrient limited and normal conditions, Nutrilyzer provides a list of genes that are significantly differently expressed and simultaneously contain significantly different amounts of the limited nutrient in their atomic composition. Its intended use is in the field of ecological stoichiometry. Nutrilyzer is available at http://nutrilyzer.hs-mittweida.de. Here we describe the work flow and results with an example from a whole-genome Arabidopsis thaliana gene-expression analysis upon oxygen deprivation. 43 paralogs distributed over 37 homology clusters were found to be significantly differently expressed while containing significantly different amounts of oxygen.
||Faculty of Technology, Research Groups in Informatics
||Data processing, computer science, computer systems
Nutrilyzer: A Tool for Deciphering Atomic Stoichiometry of Differentially Expressed Paralogous Proteins.
Journal of Integrative Bioinformatics - JIB (ISSN 1613-4516), 9(2): Special Issue: 7th International Symposium on Integrative Bioinformatics, Hangzhou, China, 2012