Nutrilyzer: A Tool for Deciphering Atomic Stoichiometry of Differentially Expressed Paralogous Proteins

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doi doi:10.2390/biecoll-jib-2012-196
submission May 16, 2012
published July 16, 2012
NCBI PubMed PubMed ID 22796635

Katrin Lotz, Falk Schreiber and Röbbe Wünschiers

Correspondence should be addressed to:
Röbbe Wünschiers
University of Applied Sciences Mittweida, Technikumplatz 17, 09648 Mittweida, Germany


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 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.


Katrin Lotz, Falk Schreiber and Röbbe Wünschiers. Nutrilyzer: A Tool for Deciphering Atomic Stoichiometry of Differentially Expressed Paralogous Proteins. Journal of Integrative Bioinformatics, 9(2):196, 2012. Online Journal:
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