Growth of the yeast Pichia pastoris on methanol induces the expression of genes whose products are required for its metabolism. Three of the methanol pathway enzymes are located in an organelle called the peroxisome. As a result, both methanol pathway enzymes and proteins involved in peroxisome biogenesis (PEX proteins) are induced in response to this substrate. The most highly regulated of these genes is AOX1, which encodes alcohol oxidase, the first enzyme of the methanol pathway, and a peroxisomal enzyme. To elucidate the molecular mechanisms responsible for methanol regulation, we identify genes required for the expression of AOX1. Mutations in one gene, named MXR1 (methanol expression regulator 1), result in strains that are unable to (i) grow on the peroxisomal substrates methanol and oleic acid, (ii) induce the transcription of AOX1 and other methanol pathway and PEX genes, and (iii) form normal-appearing peroxisomes in response to methanol. MXR1 encodes a large protein with a zinc finger DNA-binding domain near its N terminus that has similarity to Saccharomyces cerevisiae Adr1p. In addition, Mxr1p is localized to the nucleus in cells grown on methanol or other gluconeogenic substrates. Finally, Mxr1p specifically binds to sequences upstream of AOX1. We conclude that Mxr1p is a transcription factor that is necessary for the activation of many genes in response to methanol. We propose that MXR1 is the P. pastoris homologue of S. cerevisiae ADR1 but that it has gained new functions and lost others through evolution as a result of changes in the spectrum of genes that it controls.The ability to utilize methanol as a carbon and energy source is limited in eukaryotes to a few yeast species (1,34,57). The metabolic pathway is nearly identical in each species and begins with the oxidation of methanol to formaldehyde, which is catalyzed by the peroxisomal matrix enzyme alcohol oxidase (Aox). A by-product of this reaction is hydrogen peroxide, which is subsequently degraded to water and oxygen by a second peroxisomal enzyme catalase (Cat). The formaldehyde generated by Aox follows one of two paths. A portion leaves the peroxisome and is further oxidized by two cytoplasmic enzymes, formaldehyde dehydrogenase (Fld) and formate dehydrogenase (Fdh), to generate energy for the cell. The remaining formaldehyde is condensed with xylulose-5-phosphate by a third peroxisomal enzyme, dihydroxyacetone synthase (Dhas), to generate two three-carbon molecules that leave the peroxisome and enter a cyclic pathway that regenerates xylulose-5-phosphate and produces one net molecule of glyceraldehyde-3-phosphate for every three turns of this cycle (1, 57).Because three of the methanol pathway enzymes (Aox, Cat, and Dhas) are peroxisomal, the function of this organelle is also essential for methanol growth (21,26,33). This observation has made Pichia pastoris a major model system for the elucidation of peroxisome biogenesis and function (2,40,49). One advantage of P. pastoris for peroxisome studies is that in addition to methanol uti...

Motivation: We present a method for directly inferring transcriptional modules (TMs) by integrating gene expression and transcription factor binding (ChIP-chip) data. Our model extends a hierarchical Dirichlet process mixture model to allow data fusion on a gene-by-gene basis. This encodes the intuition that co-expression and co-regulation are not necessarily equivalent and hence we do not expect all genes to group similarly in both datasets. In particular, it allows us to identify the subset of genes that share the same structure of transcriptional modules in both datasets.Results: We find that by working on a gene-by-gene basis, our model is able to extract clusters with greater functional coherence than existing methods. By combining gene expression and transcription factor binding (ChIP-chip) data in this way, we are better able to determine the groups of genes that are most likely to represent underlying TMs.Availability: If interested in the code for the work presented in this article, please contact the authors.Contact: d.l.wild@warwick.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.

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