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Biomedical subjects

Daniel M Janse

Publications and source records attributed to Daniel M Janse.

2 recordsLinked to original sources

Localization to the proteasome is sufficient for degradation.

The majority of unstable proteins in eukaryotic cells are targeted for degradation through the ubiquitin-proteasome pathway. Substrates for degradation are recognized by the E1, E2, and E3 ubiquitin conjugation machinery and tagged with polyubiquitin chains, which are thought to promote the proteolytic process through their binding with the proteasome. We describe a method to bypass the ubiquitination step artificially both in vivo and in a purified in vitro system. Seven proteasome subunits were tagged with Fpr1, and fusion reporter constructs were created with the Fpr1-rapamycin binding domain of Tor1. Reporter proteins were localized to the proteasome by the addition of rapamycin, a drug that heterodimerizes Fpr1 and Tor1. Degradation of reporter proteins was observed with proteasomes that had either Rpn10 or Pre10 subunits tagged with Fpr1. Our experiments resolved a simple but central problem concerning the design of the ubiquitin-proteasome pathway. We conclude that localization to the proteasome is sufficient for degradation and, therefore, any added functions polyubiquitin chains possess beyond tethering substrates to the proteasome are not strictly necessary for proteolysis.

Cloning, Molecular↗

Predicting phenotype from patterns of annotation.

MOTIVATION: Predicting the outcome of specific experiments (such as the growth of a particular mutant strain in a particular medium) has the potential to allow researchers to devote resources to experiments with higher expected numbers of 'hits'. RESULTS: We use decision trees to predict phenotypes associated with Saccharomyces cerevisiae genes on the basis of Gene Ontology (GO) functional annotations from the Saccharomyces Genome Database (SGD) and other phenotypic annotations from the Yeast Phenotype Catalog at the Munich Information Center for Protein Sequences (MIPS). We assess the methodology in three ways: (1) we use cross-validation on the phenotypic annotations listed in MIPS, and show ROC curves indicating the tradeoff between true-positive rate and false-positive rate; (2) we do a literature-search for 100 of the predicted gene-phenotype associations that are not listed in MIPS, and find evidence for 43 of them; (3) we use deletion strains to experimentally assess 61 predicted gene-phenotype associations not listed in MIPS; significantly more of these deletion strains show abnormal growth than would be expected by chance.

Algorithms↗