High-throughput profiling of amino acids in strains of the Saccharomyces cerevisiae deletion collection.

The measurement of small molecule metabolites on a large scale offers the opportunity for a more complete understanding of cellular metabolism. We developed a high-throughput method to quantify primary amine-containing metabolites in the yeast Saccharomyces cerevisiae by the use of capillary electrophoresis in combination with fluorescent derivatization of cell extracts. We measured amino acid levels in the yeast deletion collection, a set of approximately 5000 strains each lacking a single gene, and developed a computational pipeline for data analysis. Amino acid peak assignments were validated by mass spectrometry, and the overall approach was validated by the result that expected pathway intermediates accumulate in mutants of the arginine biosynthetic pathway. Global analysis of the deletion collection was carried out using clustering methods. We grouped strains based on their metabolite profiles, revealing clusters of mutants enriched for genes encoding mitochondrial proteins, urea cycle enzymes, and vacuolar ATPase functions. One of the most striking profiles, common among several strains lacking ribosomal protein genes, accumulated lysine and a lysine-related metabolite. Mutations in the homologous ribosomal protein genes in the human result in Diamond-Blackfan anemia, demonstrating that metabolite data may have potential value in understanding disease pathology. This approach establishes metabolite profiling as capable of characterizing genes in a large collection of genetic variants.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

SUMMARY: Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. AVAILABILITY: Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.

Label-free comparative analysis of proteomics mixtures using chromatographic alignment of high-resolution muLC-MS data.

Label-free relative quantitative proteomics is a powerful tool for the survey of protein level changes between two biological samples. We have developed and applied an algorithm using chromatographic alignment of microLC-MS runs to improve the detection of differences between complex protein mixtures. We demonstrate the performance of our software by finding differences in E. coli protein abundance upon induction of the lac operon genes using isopropyl beta-D-thiogalactopyranoside. The use of our alignment gave a 4-fold decrease in mean relative retention time error and a 6-fold increase in the number of statistically significant differences between samples. Using a conservative threshold, we have identified 5290 total microLC-MS regions that have a different abundance between these samples. Of the detected difference regions, only 23% were mapped to MS/MS peptide identifications. We detected 74 proteins that had a greater relative abundance in the induced sample and 21 with a greater abundance in the uninduced sample. We have developed an effective tool for the label-free detection of differences between samples and demonstrate an increased sensitivity following chromatographic alignment.

High-speed data reduction, feature detection, and MS/MS spectrum quality assessment of shotgun proteomics data sets using high-resolution mass spectrometry.

Advances in Fourier transform mass spectrometry have made the acquisition of high-resolution and accurate mass measurements routine on a chromatographic time scale. Here we report an algorithm, Hardklör, for the rapid and robust analysis of high-resolution mass spectra acquired in shotgun proteomics experiments. Our algorithm is demonstrated in the analysis of an Escherichia coli enriched membrane fraction. The mass spectrometry data of the respective peptides are acquired by microcapillary HPLC on an LTQ-orbitrap mass spectrometer with data-dependent acquisition of MS/MS spectra. Hardklör detects 211,272 total peptide isotope distributions over a 2-h analysis (75-min gradient) in only a small fraction of the time required to acquire the data. From these data there are 13,665 distinct, chromatographically persistent peptide isotope distributions. Hardklör is also used to assess the quality of the product ion spectra and finds that more than 11.2% of the MS/MS spectra are composed of fragment ions from multiple different molecular species. Additionally, a method is reported that enzymatically labels N-linked glycosylation sites on proteins, creating a unique isotope signature that can be detected with Hardklör. Using the protein invertase, Hardklör identifies 18O-labeled peptide isotope distributions of four glycosylation sites. The speed and robustness of the algorithm create a versatile tool that can be used in many different areas of mass spectrometry data analysis.

Estrogen receptor alpha is a putative substrate for the BRCA1 ubiquitin ligase.

The breast cancer suppressor protein, BRCA1, is a ubiquitin ligase expressed in a wide range of tissues. However, inheritance of a single BRCA1 mutation significantly increases a woman's lifetime chance of developing tissue-specific cancers in the breast and ovaries. Recently, studies have suggested this tissue specificity may be linked to inhibition of estrogen receptor alpha (ERalpha) transcriptional activation by BRCA1. Here, we show that ERalpha is a putative substrate for the BRCA1/BARD1 ubiquitin ligase, suggesting a possible mechanism for regulation of ERalpha activity by BRCA1. Our results show ERalpha is predominantly monoubiquitinated in a reaction that involves interactions with both BRCA1 and BARD1. The regions of BRCA1/BARD1 necessary for ERalpha ubiquitination include the RING domains and at least 241 and 170 residues of BRCA1 and BARD1, respectively. Cancer-predisposing mutations in BRCA1 are observed to abrogate ERalpha ubiquitination. The identification of ERalpha as a putative BRCA1/BARD1 ubiquitination substrate reveals a potential link between the loss of BRCA1/BARD1 ligase activity and tissue-specific carcinoma.