Biomedical subjects

Lorrie Boucher

Publications and source records attributed to Lorrie Boucher.

7 recordsLinked to original sources

PubMed2006

Structural and functional analysis of Saccharomyces cerevisiae Mob1.

The Mob proteins function as activator subunits for the Dbf2/Dbf20 family of protein kinases. Human and Xenopus Mob1 protein structures corresponding to the most conserved C-terminal core, but lacking the variable N-terminal region, have been reported and provide a framework for understanding the mechanism of Dbf2/Dbf20 regulation. Here, we report the 2.0 A X-ray crystal structure of Saccharomyces cerevisiae Mob1 containing both the conserved C-terminal core and the variable N-terminal region. Within the N-terminal region, three novel structural elements are observed; namely, an alpha-helix denoted H0, a strand-like element denoted S0 and a short beta strand denoted S-1. Helix H0 associates in an intermolecular manner with a second Mob1 molecule to form a Mob1 homodimer. Strand S0 binds to the core domain in an intramolecular manner across a putative Dbf2 binding site mapped by Mob1 temperature-sensitive alleles and NMR binding experiments. In vivo functional analysis demonstrates that Mob1 mutants that target helix H0 or its reciprocal binding site are biologically compromised. The N-terminal region of Mob1 thus contains structural elements that are functionally important.

Amino Acid Sequence↗

PubMed2006

Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae.

BACKGROUND: The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. RESULTS: We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID (http://www.thebiogrid.org) and SGD (http://www.yeastgenome.org/) databases. CONCLUSION: Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks.

Computational Biology↗

PubMed2006

BioGRID: a general repository for interaction datasets.

Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at http://www.thebiogrid.org. BioGRID release version 2.0 includes >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. Over 30 000 interactions have recently been added from 5778 sources through exhaustive curation of the Saccharomyces cerevisiae primary literature. An internally hyper-linked web interface allows for rapid search and retrieval of interaction data. Full or user-defined datasets are freely downloadable as tab-delimited text files and PSI-MI XML. Pre-computed graphical layouts of interactions are available in a variety of file formats. User-customized graphs with embedded protein, gene and interaction attributes can be constructed with a visualization system called Osprey that is dynamically linked to the BioGRID.

Animals↗

PubMed2006

Stratus not altocumulus: a new view of the yeast protein interaction network.

Systems biology approaches can reveal intermediary levels of organization between genotype and phenotype that often underlie biological phenomena such as polygenic effects and protein dispensability. An important conceptualization is the module, which is loosely defined as a cohort of proteins that perform a dedicated cellular task. Based on a computational analysis of limited interaction datasets in the budding yeast Saccharomyces cerevisiae, it has been suggested that the global protein interaction network is segregated such that highly connected proteins, called hubs, tend not to link to each other. Moreover, it has been suggested that hubs fall into two distinct classes: "party" hubs are co-expressed and co-localized with their partners, whereas "date" hubs interact with incoherently expressed and diversely localized partners, and thereby cohere disparate parts of the global network. This structure may be compared with altocumulus clouds, i.e., cotton ball-like structures sparsely connected by thin wisps. However, this organization might reflect a small and/or biased sample set of interactions. In a multi-validated high-confidence (HC) interaction network, assembled from all extant S. cerevisiae interaction data, including recently available proteome-wide interaction data and a large set of reliable literature-derived interactions, we find that hub-hub interactions are not suppressed. In fact, the number of interactions a hub has with other hubs is a good predictor of whether a hub protein is essential or not. We find that date hubs are neither required for network tolerance to node deletion, nor do date hubs have distinct biological attributes compared to other hubs. Date and party hubs do not, for example, evolve at different rates. Our analysis suggests that the organization of global protein interaction network is highly interconnected and hence interdependent, more like the continuous dense aggregations of stratus clouds than the segregated configuration of altocumulus clouds. If the network is configured in a stratus format, cross-talk between proteins is potentially a major source of noise. In turn, control of the activity of the most highly connected proteins may be vital. Indeed, we find that a fluctuation in steady-state levels of the most connected proteins is minimized.

Computational Biology↗

PubMed2004

Uncovering novel cell cycle players through the inactivation of securin in budding yeast.

Budding yeast securin/Pds1p, an inhibitor of the anaphase activator separase/Esp1p, is involved in several checkpoint pathways and in promoting Esp1p's nuclear localization. Using a modified synthetic genetic array (SGA) screen for genes that become essential in the absence of Pds1p, we uncovered roles for uncharacterized genes in cell cycle processes, including Esp1p activation.

Cell Cycle↗

PubMed2003

CHD1 associates with NCoR and histone deacetylase as well as with RNA splicing proteins.

CHD1 is one of a family of nuclear proteins containing two chromodomains, a SWI/SNF-like helicase/ATPase domain and a DNA binding domain. We found that CHD1 co-immunoprecipitates with histone deacetylase (HDAC) activity and that CHD1 also associates with NCoR, a transcriptional corepressor, in yeast two-hybrid and in vitro pull-down assays. NCoR is known to associate with HDACs to effect its repressive activity, suggesting that the predicted chromatin remodeling activity of CHD1 plays a role in this repression. Yeast two-hybrid assays also showed that CHD1 interacts with splicing proteins mKIAA0164, Srp20, and SAF-B. Splicing assays show that CHD1 overexpression can affect alternative splicing. These results suggest that CHD1 may function in both chromatin mediated transcriptional repression and RNA splicing.

Base Sequence↗

PubMed2003

Phenotypic and transcriptional plasticity directed by a yeast mitogen-activated protein kinase network.

The yeast pheromone/filamentous growth MAPK pathway mediates both mating and invasive-growth responses. The interface between this MAPK module and the transcriptional machinery consists of a network of two MAPKs, Fus3 and Kss1; two regulators, Rst1 and Rst2 (a.k.a. Dig1 and Dig2); and two transcription factors, Ste12 and Tec1. Of 16 possible combinations of gene deletions in FUS3, KSS1, RST1, and RST2 in the sigma1278 background, 10 display constitutive invasive growth. Rst1 was the primary negative regulator of invasive growth, while other components either attenuated or enhanced invasive growth, depending on the genetic context. Despite activation of the invasive response by lesions at the same level in the MAPK pathway, transcriptional profiles of different invasive mutant combinations did not exhibit a unified program of gene expression. The distal MAPK regulatory network is thus capable of generating phenotypically similar invasive-growth states (an attractor) from different molecular architectures (trajectories) that can functionally compensate for one another. This systems-level robustness may also account for the observed diversity of signals that trigger invasive growth.

Haploidy↗