Michael C. Giddings

Computational identification of putative programmed translational frameshift sites.

MOTIVATION In an effort to identify potential programmed frameshift sites by statistical analysis, we explore the hypothesis that selective pressure would have rendered such sites underabundant and underrepresented in protein-coding sequences. We developed a computer program to compare the frequencies of k-length subsequences of nucleotides with the frequencies predicted by a zero order Markov chain determined by the codon bias of the same set of sequences. The program was used to calculate and evaluate the distribution of 7-base oligonucleotides in the 6000+ putative protein-coding sequences of S. cerevisiae preliminary to the laboratory testing of the most highly underrepresented oligos for frameshifting efficiency. RESULTS Among the most significant results is the finding that the heptanucleotides CUU-AGG-C and CUU-AGU-U, sites of the programmed +1 translational frameshifts required for the production in yeast of actin filament-binding protein ABP140 and telomerase subunit EST3, respectively, rank among the least represented of phase I heptanucleotides in the coding sequences of S. cerevisiae. Laboratory experiments demonstrated that other underrepresented heptanucleotides identified by the program, for example GGU-CAG-A, are also prone to significant translational frameshifting, suggesting the possibility that genes containing other underrepresented heptamers may also encode transframe products. AVAILABILITY The program is available for download from http://www.gesteland.genetics.utah.edu/freqAnalysis SUPPLEMENTARY INFORMATION Complete results from the analysis of S. cerevisiae are available on http://www.gesteland.genetics.utah.edu/freqAnalysis

Genome-based peptide fingerprint scanning

We have implemented a method that identifies the genomic origins of sample proteins by scanning their peptide-mass fingerprint against the theoretical translation and proteolytic digest of an entire genome. Unlike previously reported techniques, this method requires no predefined ORF or protein annotations. Fixed-size windows along the genome sequence are scored by an equation accounting for the number of matching peptides, the number of missed enzymatic cleavages in each peptide, the number of in-frame stop codons within a window, the adjacency between peptides, and duplicate peptide matches. Statistical significance of matching regions is assessed by comparing their scores to scores from windows matching randomly generated mass data. Tests with samples from Saccharomyces cerevisiae mitochondria and Escherichia coli have demonstrated the ability to produce statistically significant identifications, agreeing with two commonly used programs, peptident and mascot, in 86% of samples analyzed. This genome fingerprint scanning method has the potential to aid in genome annotation, identify proteins for which annotation is incorrect or missing, and handle cases where sequencing errors have caused framing mistakes in the databases. It might also aid in the identification of proteins in which recoding events such as frameshifting or stop-codon read-through have occurred, elucidating alternative translation mechanisms. The prototype is implemented as a client/server pair, allowing the distribution, among a set of cluster nodes, of a single or multiple genomes for concurrent analysis.

Genomes to life "Center for Molecular and Cellular Systems": A research program for identification and characterization of protein complexes

Goal 1 of Department of Energys Genomes to Life (GTL) program seeks to identify and characterize the complete set of protein complexes within a cell. Goal 1 forms the foundation necessary to accomplish the other objectives of the GTL program, which focus on gene regulatory networks and molecular level characterization of interactions in microbial communities. Together this information would allow cells and their components to be understood in sufficient detail to predict, test and understand the responses of a biological system to its environment. The Center for Molecular and Cellular Systems has been established to identify and characterize protein complexes using high through-put analytical technologies.A dynamic research program is being developed that supports the goals of the Center by focusing on the development new capabilities for sample preparation and complex separations, molecular level identification of the protein complexes by mass spectrometry, characterization of the complexes in living cells by imaging techniques, and bioinformatics and computational tools for the collection and interpretation of data and formation of databases and tools to allow the data to be shared by the biological community.

Genome fingerprint scanning for protein identification and gene finding

Abstract The genome fingerprint scanning (GFS) system was developed to link proteomic data, consisting of peptide mass fingerprints and tandem mass spectrometry (MS/MS) data, to the genome sequence of an organism. It maps MS data directly to the genomic locus responsible for expression of a protein, without relying on prior genome annotation. The GFS approach provides the intriguing possibility of identifying novel genes straight from protein data, thereby potentially enhancing ongoing efforts to annotate the genomes.