Marcello Marelli

Transcriptome profiling to identify genes involved in peroxisome assembly and function.

Yeast cells were induced to proliferate peroxisomes, and microarray transcriptional profiling was used to identify PEX genes encoding peroxins involved in peroxisome assembly and genes involved in peroxisome function. Clustering algorithms identified 224 genes with expression profiles similar to those of genes encoding peroxisomal proteins and genes involved in peroxisome biogenesis. Several previously uncharacterized genes were identified, two of which, YPL112c and YOR084w, encode proteins of the peroxisomal membrane and matrix, respectively. Ypl112p, renamed Pex25p, is a novel peroxin required for the regulation of peroxisome size and maintenance. These studies demonstrate the utility of comparative gene profiling as an alternative to functional assays to identify genes with roles in peroxisome biogenesis.

Approaching complete peroxisome characterization by gas-phase fractionation.

We examined the utility of gas‐phase fractionation (GPF) in the m/z dimension to increase proteome coverage and reproducibility of peptide ion selection by direct microliquid chromatography/electrospray ionization‐tandem mass spectrometry (νLC/ESI‐MS/MS) analysis of the peptides produced by proteolytic digestion of unfractionated proteins from a yeast whole‐cell lysate and in a peroxisomal membrane protein fraction derived from isolated yeast peroxisomes. We also investigated GPF in the relative ion intensity dimension and propose denoting the two types of GPF as GPFm/z and GPFRI. Comparison of results of direct νLC/ESI‐MS/MS analysis of the unfractionated mixture of peptides from proteolysis of a yeast whole cell lysate by DD ion selection from 400–1800 m/z in triplicate and GPFm/z from 400–800, 800–1200 and 1200–1800 produced the following results: (i) 1.3× more proteins were identified by GPFm/z for an equal amount of effort (i.e., 3 νLC/ESI‐MS/MS) and (ii) proteins identified by GPFm/z had a lower average codon bias value. Use of GPFRI identified more proteins per m/z unit scanned than GPFm/z or triplicate analysis over a wide m/z range. After tryptic digestion of all the proteins from a discontinuous Nycodenz gradient fraction known to be enriched with yeast peroxisomal membrane proteins we detected 93% (38/41) of known peroxisomal proteins using GPFm/z, but only 73% using a standard wide m/z range survey scan.

Quantitative mass spectrometry reveals a role for the GTPase Rho1p in actin organization on the peroxisome membrane

We have combined classical subcellular fractionation with large-scale quantitative mass spectrometry to identify proteins that enrich specifically with peroxisomes of Saccharomyces cerevisiae. In two complementary experiments, isotope-coded affinity tags and tandem mass spectrometry were used to quantify the relative enrichment of proteins during the purification of peroxisomes. Mathematical modeling of the data from 306 quantified proteins led to a prioritized list of 70 candidates whose enrichment scores indicated a high likelihood of them being peroxisomal. Among these proteins, eight novel peroxisome-associated proteins were identified. The top novel peroxisomal candidate was the small GTPase Rho1p. Although Rho1p has been shown to be tethered to membranes of the secretory pathway, we show that it is specifically recruited to peroxisomes upon their induction in a process dependent on its interaction with the peroxisome membrane protein Pex25p. Rho1p regulates the assembly state of actin on the peroxisome membrane, thereby controlling peroxisome membrane dynamics and biogenesis.

Dual feedback loops in the GAL regulon suppress cellular heterogeneity in yeast.

Transcriptional noise is known to be an important cause of cellular heterogeneity and phenotypic variation. The extent to which molecular interaction networks may have evolved to either filter or exploit transcriptional noise is a much debated question. The yeast genetic network regulating galactose metabolism involves two proteins, Gal3p and Gal80p, that feed back positively and negatively, respectively, on GAL gene expression. Using kinetic modeling and experimental validation, we demonstrate that these feedback interactions together are important for (i) controlling the cell-to-cell variability of GAL gene expression and (ii) ensuring that cells rapidly switch to an induced state for galactose uptake.

Karyopherins in nuclear pore biogenesis: a role for Kap121p in the assembly of Nup53p into nuclear pore complexes

The mechanisms that govern the assembly of nuclear pore complexes (NPCs) remain largely unknown. Here, we have established a role for karyopherins in this process. We show that the yeast karyopherin Kap121p functions in the targeting and assembly of the nucleoporin Nup53p into NPCs by recognizing a nuclear localization signal (NLS) in Nup53p. This karyopherin-mediated function can also be performed by the Kap95p–Kap60p complex if the Kap121p-binding domain of Nup53p is replaced by a classical NLS, suggesting a more general role for karyopherins in NPC assembly. At the NPC, neighboring nucleoporins bind to two regions in Nup53p. One nucleoporin, Nup170p, associates with a region of Nup53p that overlaps with the Kap121p binding site and we show that they compete for binding to Nup53p. We propose that once targeted to the NPC, dissociation of the Kap121p–Nup53p complex is driven by the interaction of Nup53p with Nup170p. At the NPC, Nup53p exists in two separate complexes, one of which is capable of interacting with Kap121p and another that is bound to Nup170p. We propose that fluctuations between these two states drive the binding and release of Kap121p from Nup53p, thus facilitating Kap121ps movement through the NPC.

Dynamic changes in the subcellular distribution of Gpd1p in response to cell stress.

Gpd1p is a cytosolic NAD+-dependent glycerol 3-phosphate dehydrogenase that also localizes to peroxisomes and plays an essential role in the cellular response to osmotic stress and a role in redox balance. Here, we show that Gpd1p is directed to peroxisomes by virtue of an N-terminal type 2 peroxisomal targeting signal (PTS2) in a Pex7p-dependent manner. Significantly, localization of Gpd1p to peroxisomes is dependent on the metabolic status of cells and the phosphorylation of aminoacyl residues adjacent to the targeting signal. Exposure of cells to osmotic stress induces changes in the subcellular distribution of Gpd1p to the cytosol and nucleus. This behavior is similar to Pnc1p, which is coordinately expressed with Gpd1p, and under conditions of cell stress changes its subcellular distribution from peroxisomes to the nucleus where it mediates chromatin silencing. Although peroxisomes are necessary for the β-oxidation of fatty acids in yeast, the localization of Gpd1p to peroxisomes is not. Rather, shifts in the distribution of Gpd1p to different cellular compartments in response to changing cellular status suggests a role for Gpd1p in the spatial regulation of redox potential, a process critical to cell survival, especially under the complex stress conditions expected to occur in the wild.

Transcriptional responses to fatty acid are coordinated by combinatorial control

In transcriptional regulatory networks, the coincident binding of a combination of factors to regulate a gene implies the existence of complex mechanisms to control both the gene expression profile and specificity of the response. Unraveling this complexity is a major challenge to biologists. Here, a novel network topology‐based clustering approach was applied to condition‐specific genome‐wide chromatin localization and expression data to characterize a dynamic transcriptional regulatory network responsive to the fatty acid oleate. A network of four (predicted) regulators of the response (Oaf1p, Pip2p, Adr1p and Oaf3p) was investigated. By analyzing trends in the network structure, we found that two groups of multi‐input motifs form in response to oleate, each controlling distinct functional classes of genes. This functionality is contributed in part by Oaf1p, which is a component of both types of multi‐input motifs and has two different regulatory activities depending on its binding context. The dynamic cooperation between Oaf1p and Pip2p appears to temporally synchronize the two different responses. Together, these data suggest a network mechanism involving dynamic combinatorial control for coordinating transcriptional responses.

Expression and functional profiling reveal distinct gene classes involved in fatty acid metabolism

Cells respond to fatty acid exposure by metabolic reorganization and proliferation of peroxisomes. Described here is the development and application of a genome‐wide screen to identify nonessential yeast genes necessary for efficient metabolism of myristic and oleic acids. Comparison of the resultant fitness data set with an integrated data set of genes transcriptionally responsive to fatty acids revealed very little overlap between the data sets. Furthermore, the fitness data set enriched for genes involved in peroxisome biogenesis and other processes related to cell morphology, whereas the expression data set enriched for genes related to metabolism. These data suggest that in response to fatty acid exposure, transcriptional control is biased towards metabolic reorganization, and structural changes tend to be controlled post‐transcriptionally. They also suggest that fatty acid responsive metabolic networks are more robust than those related to cell structure. Statistical analyses of these and other global data sets suggest that the utilization of distinct control mechanisms for the execution of morphological versus metabolic responses is widespread.

The peroxin Pex17p of the yeast Yarrowia lipolytica is associated peripherally with the peroxisomal membrane and is required for the import of a subset of matrix proteins.

PEX genes encode peroxins, which are required for the biogenesis of peroxisomes. The Yarrowia lipolytica PEX17 gene encodes the peroxin Pex17p, which is 671 amino acids in length and has a predicted molecular mass of 75,588 Da. Pex17p is peripherally associated with the peroxisomal membrane. The carboxyl-terminal tripeptide, Gly-Thr-Leu, of Pex17p is not necessary for its targeting to peroxisomes. Synthesis of Pex17p is low in cells grown in glucose-containing medium and increases after the cells are shifted to oleic acid-containing medium. Cells of the pex17-1 mutant, the original mutant strain, and the pex17-KA mutant, a strain in which most of the PEX17 gene is deleted, fail to form normal peroxisomes but instead contain numerous large, multimembraned structures. The import of peroxisomal matrix proteins in these mutants is selectively impaired. This selective import is not a function of the nature of the peroxisomal targeting signal. We suggest a regulatory role for Pex17p in the import of a subset of matrix proteins into peroxisomes.

Identifying bona fide components of an organelle by isotope-coded labeling of subcellular fractions : an example in peroxisomes.

Organelles are biochemically distinct subcellular compartments that perform specific functions within a cell. These roles are regulated by the complement of proteins associated with each organelle. Thus, a comprehensive understanding of an organelles proteome is necessary to elucidate the diverse roles of each organelle. Mass spectrometry combined with biochemical fractionation methods has enabled the proteomic characterization of several organelles. However, due to the poorly quantitative nature of mass spectrometry and the inability to generate pure fractions of an organelle, distinguishing bona fide components of the organelle from contaminants of the fraction is a significant challenge. We have addressed this limitation by adopting quantitative mass spectrometric approaches to identify proteins that enrich in a purified fraction of organelles relative to a crude or contaminating fraction. The methods for the analyses of the yeast peroxisome are described in detail; however, these concepts are generally applicable to the study of other organelles.