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Michael Snyder

Publications and source records attributed to Michael Snyder.

87 records · Page 5Linked to original sources

The alpha-factor receptor C-terminus is important for mating projection formation and orientation in Saccharomyces cerevisiae.

Successful mating of MATa Saccharomyces cerevisiae cells is dependent on Ste2p, the alpha-factor receptor. Besides receiving the pheromone signal and transducing it through the G-protein coupled MAP kinase pathway, Ste2p is active in the establishment and orientation of the mating projection. We investigated the role of the carboxyl terminus of the receptor in mating projection formation and orientation using a spatial gradient assay. Cells carrying the ste2-T326 mutation, truncating 105 of the 135 amino acids in the receptor tail including a motif necessary for its ligand-mediated internalization, display slow onset of projection formation, abnormal shmoo morphology, and reduced ability to orient the mating projection toward a pheromone source. This reduction was due to the increased loss of mating projection orientation in a pheromone gradient. Cells with a mutated endocytosis motif were defective in reorientation in a pheromone gradient. ste2-Delta296 cells, which carry a complete truncation of the Ste2p tail, exhibit a severe defect in projection formation, and those projections that do form are unable to orient in a pheromone gradient. These results suggest a complex role for the Ste2p carboxy-terminal tail in the formation, orientation, and directional adjustment of the mating projection, and that endocytosis of the receptor is important for this process. In addition, mutations in RSR1/BUD1 and SPA2, genes necessary for budding polarity, exhibited little or no defect in formation or orientation of mating projections. We conclude that mating projection orientation depends upon the carboxyl terminus of the pheromone receptor and not the directional machinery used in budding.

Cell Differentiation↗

"Omic" approaches for unraveling signaling networks.

Signaling pathways are crucial for cell differentiation and response to cellular environments. Recently, a large number of approaches for the global analysis of genes and proteins have been described. These have provided important new insights into the components of different pathways and the molecular and cellular responses of these pathways. This review covers genomic and proteomic (collectively referred to as "omic") approaches for the global analysis of cell signaling, including gene expression profiling and analysis, protein-protein interaction methods, protein microarrays, mass spectroscopy and gene-disruption and engineering approaches.

Animals↗

Carbohydrate analysis prepares to enter the "Omics" era.

In this issue, Houseman and Mrksich describe a carbohydrate array preparation method that can be used to analyze protein-carbohydrate interactions and to characterize the substrate specificity of a carbohydrate-modifying enzyme. Carbohydrate chips were prepared by a novel procedure that allows the covalent attachment of carbohydrate-diene conjugates to a specially engineered monolayer surface. The surface presents a precisely controllable ratio of reactive benzoquinone and inert ethylene glycol groups. Nonspecific adsorption of proteins to the surface is extremely low, and the surface is compatible with popular detection techniques. The immobilization technique was demonstrated to be compatible with recently developed automated solid phase carbohydrate synthesis methods, paving the way for the development of highly complex carbohydrate arrays.

Adsorption↗

Bud-site selection and cell polarity in budding yeast.

Polarized growth involves a hierarchy of events such as selection of the growth site, polarization of the cytoskeleton to the selected growth site, and transport of secretory vesicles containing components required for growth. The budding yeast Saccharomyces cerevisiae is an excellent model system for the study of polarized cell growth. A large number of proteins have been found to be involved in these processes, although their mechanisms of action are not yet well-understood. Recent discoveries have helped elucidate many of the processes involved in cell polarity and bud-site selection in yeast and have modified the traditional view of cellular structures involved in these processes. This review focuses on recent advances on the roles of cortical tags, GTPases and the cytoskeleton in the generation and maintenance of cell polarity in yeast.

Actins↗

An integrated approach for finding overlooked genes in yeast.

We report here the discovery of 137 previously unappreciated genes in yeast through a widely applicable and highly scalable approach integrating methods of gene-trapping, microarray-based expression analysis, and genome-wide homology searching. Our approach is a multistep process in which expressed sequences are first trapped using a modified transposon that produces protein fusions to beta-galactosidase (beta-gal); non-annotated open reading frames (ORFs) translated as beta-gal chimeras are selected as a candidate pool of potential genes. To verify expression of these sequences, labeled RNA is hybridized against a microarray of oligonucleotides designed to detect gene transcripts in a strand-specific manner. In complement to this experimental method, novel genes are also identified in silico by homology to previously annotated proteins. As these methods are capable of identifying both short ORFs and antisense ORFs, our approach provides an effective supplement to current gene-finding schemes. In total, the genes discovered using this approach constitute 2% of the yeast genome and represent a wealth of overlooked biology.

Chromosomes↗

Proteomic approaches for the global analysis of proteins.

Improvements in technology that allow miniaturization and high-throughput analyses of thousand of genes and gene products have changed the focus and scope of research and development in both academia and industry. It is now possible to study entire proteomes with the goals of elucidating protein expression, subcellular localization, biochemical activities, and their regulation. Alterations in different cell types and conditions and in normal and disease states can be revealed. This wealth of information not only has facilitated our basic understanding of many biological processes but also has enormous potential for drug discovery and development.

Data Collection↗

YMD: a microarray database for large-scale gene expression analysis.

The use of microarray technology to perform parallel analysis of the expression pattern of a large number of genes in a single experiment has created a new frontier of medical research. The vast amount of gene expression data generated from multiple microarray experiments requires a robust database system that allows efficient data storage, retrieval, secure access, data dissemination, and integrated data analyses. To address the growing needs of microarray researchers at Yale and their collaborators, we have built the Yale Microarray Database (YMD). YMD is Web-accessible with the following features: (i) a Web program that tracks DNA samples between source plates and arrays, (ii) the capability of finding common genes/clones across different array platforms, (iii) an image file server, (iv) laboratory-based user management and access privileges, (v) project management, (vi) template data entry, (vii) linking gene expression data to annotation databases for functional analysis. YMD is currently being used on a pilot basis by several laboratories for different organisms and array platforms.

Databases, Nucleic Acid↗

Large-scale identification of genes important for apical growth in Saccharomyces cerevisiae by directed allele replacement technology (DART) screening.

In Saccharomyces cerevisiae, apical bud growth occurs for a brief period in G1 when the deposition of membrane and cell wall is restricted to the tip of the growing bud. To identify genes important for apical bud growth, we have utilized a novel transposon-based mutagenesis system termed DART (Directed Allele Replacement Technology) that allows the rapid transfer of defined insertion alleles into any strain background. A total of 4,810 insertion alleles affecting 1,392 different yeast genes were transferred into a cdc34-2 mutant strain that arrests in the apical growth phase when grown at the restrictive temperature of 37 degrees C. We identified 29 insertion alleles, containing mutations in 17 different genes ( SMY1, SPA2, PAN1, SLA1, SLA2, CBK1, SEC22, FAB1, VPS36, VID22, RAS2, ECM33, OPI3, API1/YDR372c, API2/YDR525w, API3/YKR020w, and API4/YNL051w), which alter the elongated bud morphology of cdc34-2 cells arrested in the apical growth phase. Upon treatment with mating pheromone at 25 degrees C, cells containing insertion alleles affecting ten of these genes ( SMY1, SPA2, PAN1, SLA1, SLA2, CBK1, FAB1, VPS36, VID22, and API2/YDR525w) form abnormal mating projections. Additionally, cells containing insertion alleles affecting SEC22, RAS2, API1/YDR372c, API3/YKR020w,and API4/YNL051display severe mating projection formation defects at the elevated temperature of 37 degrees C. DART mutagenesis has many advantages over traditional mutagenesis methods and will be a useful tool for dissecting gene networks important for biological processes.

Alleles↗

A dynamic approach to mapping coordinates between microplates and microarrays.

The retrieval of useful data from spotted microarray slides requires keeping track of which microplate wells and DNA sample corresponds to each spot on each array slide. Existing approaches are closely coupled with the type of arrayer in use and are computer operating-system-specific. To support the microarray researcher community at large who use different arrayers and computer platforms, increased flexibility, generality, and portability of these approaches are required. In this paper, we describe a general algorithm that correlates the well positions of DNA samples in each microplate to the positions of the spots on each array slide. Based on this algorithm, we have implemented a flexible and platform-independent program named MicroArray Convolutor (MAC) that provides a Web solution allowing the user to: (a) import a text file that identifies the DNA samples and their well locations, (b) select a transformation method that converts data in 96-well plate format into 384-well plate format, and (c) specify the output format of the array lists dependant on the configuration of the array platform as well as the downstream analysis software chosen for the array. MAC and its source code can be accessed via the following Web address: http://ymd.med.yale.edu/kei-cgi/kc_mac_dev8.pl.

Algorithms↗

Long-term air medical services system performance using APACHE-II and mortality benchmarking.

OBJECTIVE: Air medical transport programs have been in existence for two decades. During this time, no outcome measures have been developed for these services. The authors examined severity scoring and mortality data from their air medical service to characterize its performance and to identify trends in acuity and mortality over a 15-year period. METHODS: APACHE-II scores derived at the time of transport and hospital mortality data have been concurrently recorded in the flight database for adult transports since 1986. The authors analyzed these data and examined the correlation between APACHE-II score at the time of transport and hospital mortality for the 15-year period 1986-2001. RESULTS: 13,808 adult transports were identified. APACHE data were available for 8,204 patients (59%) and mortality for 10,845 (79%), respectively. The number of transports increased from 935 to 1,231 per year. Mean APACHE-II for all patients was 11.6 +/- 8.4. Overall mortality was 22%. Both patient acuity and mortality were trending upward over time. The correlation between APACHE-II and mortality was close and linear (mortality = 0.018 x APACHE-II -0.0243, R2 = 0.97). CONCLUSIONS: Both severity of illness and mortality of air-transported patients appear to be increasing slowly over time in response to changes in the health care system. The strong correlation between APACHE-II performed at the time of transport and mortality validates this technique for benchmarking. The slope of this correlation is an outcome-based characteristic of system performance that may allow monitoring of a system over time and comparisons between systems.

APACHE↗