Mark A. Shifman

Revealing the amino acid composition of proteins within an expanded genetic code

The genetic code can be manipulated to reassign codons for the incorporation of non-standard amino acids (NSAA). Deletion of release factor 1 in Escherichia coli enhances translation of UAG (Stop) codons, yet may also extended protein synthesis at natural UAG terminated messenger RNAs. The fidelity of protein synthesis at reassigned UAG codons and the purity of the NSAA containing proteins produced require careful examination. Proteomics would be an ideal tool for these tasks, but conventional proteomic analyses cannot readily identify the extended proteins and accurately discover multiple amino acid (AA) insertions at a single UAG. To address these challenges, we created a new proteomic workflow that enabled the detection of UAG readthrough in native proteins in E. coli strains in which UAG was reassigned to encode phosphoserine. The method also enabled quantitation of NSAA and natural AA incorporation at UAG in a recombinant reporter protein. As a proof-of-principle, we measured the fidelity and purity of the phosphoserine orthogonal translation system (OTS) and used this information to improve its performance. Our results show a surprising diversity of natural AAs at reassigned stop codons. Our method can be used to improve OTSs and to quantify amino acid purity at reassigned codons in organisms with expanded genetic codes.

Portability issues for a structured clinical vocabulary: mapping from Yale to the Columbia medical entities dictionary.

OBJECTIVE To examine the issues involved in mapping an existing structured controlled vocabulary, the Medical Entities Dictionary (MED) developed at Columbia University, to an institutional vocabulary, the laboratory and pharmacy vocabularies of the Yale New Haven Medical Center. DESIGN 200 Yale pharmacy terms and 200 Yale laboratory terms were randomly selected from database files containing all of the Yale laboratory and pharmacy terms. These 400 terms were then mapped to the MED in three phases: mapping terms, mapping relationships between terms, and mapping attributes that modify terms. RESULTS 73% of the Yale pharmacy terms mapped to MED terms. 49% of the Yale laboratory terms mapped to MED terms. After certain obsolete and otherwise inappropriate laboratory terms were eliminated, the latter rate improved to 59%. 23% of the unmatched Yale laboratory terms failed to match because of differences in granularity with MED terms. The Yale and MED pharmacy terms share 12 of 30 distinct attributes. The Yale and MED laboratory terms share 14 of 23 distinct attributes. CONCLUSION The mapping of an institutional vocabulary to a structured controlled vocabulary requires that the mapping be performed at the level of terms, relationships, and attributes. The mapping process revealed the importance of standardization of local vocabulary subsets, standardization of attribute representation, and term granularity.

YPED: an integrated bioinformatics suite and database for mass spectrometry-based proteomics research.

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography-tandem mass spectrometry (LC-MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPEDs database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results.

Development of a highly automated and multiplexed targeted proteome pipeline and assay for 112 rat brain synaptic proteins

We present a comprehensive workflow for large scale (>1000 transitions/run) label‐free LC‐MRM proteome assays. Innovations include automated MRM transition selection, intelligent retention time scheduling that improves S/N by twofold, and automatic peak modeling. Improvements to data analysis include a novel Q/C metric, normalized group area ratio, MLR normalization, weighted regression analysis, and data dissemination through the Yale protein expression database. As a proof of principle we developed a robust 90 min LC‐MRM assay for mouse/rat postsynaptic density fractions which resulted in the routine quantification of 337 peptides from 112 proteins based on 15 observations per protein. Parallel analyses with stable isotope dilution peptide standards (SIS), demonstrate very high correlation in retention time (1.0) and protein fold change (0.94) between the label‐free and SIS analyses. Overall, our method achieved a technical CV of 11.4% with >97.5% of the 1697 transitions being quantified without user intervention, resulting in a highly efficient, robust, and single injection LC‐MRM assay.

Molecular dynamics simulation on a network of workstations using a machine-independent parallel programming language

Molecular dynamics simulations investigate local and global motion in molecules. Several parallel computing approaches have been taken to attack the most computationally expensive phase of molecular simulations, the evaluation of long range interactions. This paper develops a straightforward but effective algorithm for molecular dynamics simulations using the machine-independent parallel programming language, Linda. The algorithm was run both on a shared memory parallel computer and on a network of high performance Unix workstations. Performance benchmarks were performed on both systems using two proteins. This algorithm offers a portable cost-effective alternative for molecular dynamics simulations. In view of the increasing numbers of networked workstations, this approach could help make molecular dynamics simulations more easily accessible to the research community.

Parallel Computation for Medicine and Biology: Applications of Linda At Yale University

This article describes research in progress at the Yale University School of Medicine on the use of parallel computation in medicine and biology. We have experi mented with the parallelization of programs from sev eral different biomedical fields, using the machine-in dependent parallel programming language Linda. This research has helped us identify several general prob lem areas in which parallel computation can play a major role: namely, real-time computation, database searching, and computationally intensive algorithms. Methods for designing, debugging, and evaluating programs from each of these three problem areas are discussed. Results and evaluations of example pro grams implemented in each of these areas are pre sented. Finally, certain lessons learned are discussed.

PFGE MAPPER: a tool to aid in the analysis of pulse field gel electrophoresis maps.

Pulse field gel electrophoresis mapping is an important technique for characterizing large segments of DNA and constructing long-range restriction maps. We have developed a tool, PFGE MAPPER, to aid in the construction of pulse field electrophoresis gel maps. This tool helps construct pulse field gel maps from single and double digest experiments visualized by hybridization with single copy probes. The program is written in Think C and runs on Macintosh computers. An intuitive interface allows the user to interactively modify fragment sizes or errors, select fragments for analysis and recalculate the maps. Maps can be printed or saved for later viewing. After constructing and saving several maps in a region, PFGE MAPPER can be used to refine and extend the overall map by merging individual maps. This tool should be useful for constructing long-range restriction maps of genomic DNA and yeast artificial chromosomes.

Application of Linda to molecular modeling

Presents a sampling of work applying parallel computation to computational chemistry using the Linda machine-independent parallel programming language. The authors focus on two projects in particular. The first project parallelized the well-known distance geometry program, DGEOM, while the second project looked at a molecular dynamic code. In both cases, the Linda programs were relatively easy to develop and delivered good performance on a variety of MIMD architectures.<<ETX>>