Biomedical subjects

Marcello Marelli

Publications and source records attributed to Marcello Marelli.

7 recordsLinked to original sources

PubMed2006

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.

Computer Simulation↗

PubMed2006

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.

Fatty Acids↗

PubMed2004

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.

Actins↗

PubMed2003

Pex11-related proteins in peroxisome dynamics: a role for the novel peroxin Pex27p in controlling peroxisome size and number in Saccharomyces cerevisiae.

Transcriptome profiling identified the gene PEX25 encoding Pex25p, a peroxisomal membrane peroxin required for the regulation of peroxisome size and maintenance in Saccharomyces cerevisiae. Pex25p is related to a protein of unknown function encoded by the open reading frame, YOR193w, of the S. cerevisiae genome. Yor193p is a peripheral peroxisomal membrane protein that exhibits high sequence similarity not only to Pex25p but also to the peroxisomal membrane peroxin Pex11p. Unlike Pex25p and Pex11p, Yor193p is constitutively expressed in wild-type cells grown in oleic acid-containing medium, the metabolism of which requires intact peroxisomes. Cells deleted for the YOR193w gene show a few enlarged peroxisomes. Peroxisomes are greatly enlarged in cells harboring double deletions of the YOR193w and PEX25 genes, the YOR193w and PEX11 genes, and the PEX25 and PEX11 genes. Yeast two-hybrid analyses showed that Yor193p interacts with Pex25p and itself, Pex25p interacts with Yor193p and itself, and Pex11p interacts only with itself. Overexpression of YOR193w, PEX25, or PEX11 led to peroxisome proliferation and the formation of small peroxisomes. Our data suggest a role for Yor193p, renamed Pex27p, in controlling peroxisome size and number in S. cerevisiae.

Amino Acid Sequence↗

PubMed2002

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 Kap121p's movement through the NPC.

Binding Sites↗

PubMed2002

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.

Gene Expression Profiling↗

PubMed2002

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 (microLC/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 GPF(m/z) and GPF(RI). Comparison of results of direct nuLC/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 GPF(m/z) from 400-800, 800-1200 and 1200-1800 produced the following results: (i) 1.3 x more proteins were identified by GPF(m/z) for an equal amount of effort (i.e., 3 microLC/ESI-MS/MS) and (ii) proteins identified by GPF(m/z) had a lower average codon bias value. Use of GPF(RI) identified more proteins per m/z unit scanned than GPF(m/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 GPF(m/z), but only 73% using a standard wide m/z range survey scan.

Chromatography, High Pressure Liquid↗