Michael J. MacCoss, Ph.D. - US grants

Insulin resistance is associated with an overall decrease in tyrosine phosphorylation and increased serine phosphorylation of IRS-1. To understand the role that the phosphorylation of IRS-1 serine residues may play in insulin resistance and diabetes we need to i) identify the location of serine phosphorylation sites of IRS-1 and ii) measure the site-specific changes in IRS-1 phosphoserine and phosphotyroserine levels between normal and insulin resistant conditions. Because of the complexity and insensitivity of existing methods for measuring serine phosphorylations, a major aim of this project is to develop a sensitive a robust protocol that is specific to peptides from protein enzyme digests containing serine phosphorylations. Phosphoserine residues will be selectively labeled with either an unlabeled or labeled reagent using a recently report4ed methodology. This modification will then permit the isolation of phosphoserine residues with the addition of a biotin tag and affinity purification. This reagent also contains a cleavable linker to facilitate the release of the enriched peptide from the solid support. During this research training fellowship, I will develop and apply this methodology along with muLC-MS/MS to both locate and quantify the serine phosphorylation sites of IRS-1 associated with insulin resistance.

DESCRIPTION (provided by applicant): The enclosed proposal is requesting funds to expand the mass spectrometry and proteomics resources at the University of Washington through the purchase of a ThermoFinnigan LTQ-FT mass spectrometer. This instrument will be invaluable in the successful completion of our existing NIH funded projects involving the qualitative and quantitative analysis of proteins and protein modifications of complex mixtures. Furthermore, a number of our projects are extending quantitative proteomics technology to the measurement of changes in the rate of protein expression and degradation (protein dynamics). Integral to the timely completion of these NIH research projects is the availability of a mass spectrometer capable of i) sub 2 ppm mass accuracy to distinguish between similar mass peptides, ii) a dynamic range of >1000 in a single spectrum, iii) data-dependent acquisition of tandem mass spectra with the sensitivity and speed of a quadrupole ion trap, and iv) the ability to resolve and detect unusual isotope distributions of multiply charged peptides within a complex mixture. No such shared instrument is available to investigators at the University of Washington and several of our Users travel to outside laboratories to complete their NIH funded projects. Although we have managed to work around the lack of availability of a mass spectrometer capable of these measurements we cannot continue in this way if we hope to remain productive and competitive. We propose to address these limitations through the acquisition of a shared hybrid mass spectrometer which combines the robustness and speed of a linear quadrupole ion-trap with the resolution, mass accuracy, and dynamic range of a Fourier transform ion cyclotron mass spectrometer. The performance of the requested instrumentation will allow the faculty to address current technological limitations on a global level and will provide a resource that is not available within the university.

DESCRIPTION (provided by applicant): The insulin signaling pathway is essential for the regulation of glucose homeostasis, contributes to the regulation of energy substrate metabolism, and is intimately linked to aging and longevity. Because of the prevalence of obesity and type-2 diabetes within industrialized societies, understanding the molecular mechanism of this pathway is an increasing biomedical priority. Insulin like molecules alter system-wide protein turnover, yet the effects on individual proteins is unclear. A change in a protein's turnover can alter the stoichiometry of the active protein and ultimately affect the efficiency of a pathway. Because of the potential functional consequence of protein turnover and the importance of insulin signaling, we propose to study both these processes in the nematode Caenorhabditis elegans using quantitative proteomics. Specific Aim 1 is to develop quantitative stable isotope tracer methodology for both the directed and undirected analysis of protein turnover in C. elegans. Specific Aim 2 will measure the turnover of proteins involved in the insulin/insulin growth factor-1 (IGF-1) signaling pathway of C. elegans in response to the inhibition and overexpression of ligands of the insulin receptor (DAF-2). Specific Aim 3 is to measure the effect of insulin like molecules on the tissue-specific intracellular metabolism of the nematode C. elegans using stable isotope labeling and isotopomer distribution analysis. The successful completion of this proposal will produce methodological framework for studying protein turnover in C. elegans and provide foundation for extending these technologies to higher organisms. Furthermore, the proteome-wide measurement of protein turnover in response to insulin-like molecules will produce an experimental dataset for probing the underlying mechanism of insulin signaling.

[unreadable] DESCRIPTION (provided by applicant): The insulin signaling pathway is essential for the regulation of glucose homeostasis, contributes to the regulation of energy substrate metabolism, and is intimately linked to aging and longevity. Because of the prevalence of obesity and type-2 diabetes within industrialized societies, understanding the molecular mechanism of this pathway is an increasing biomedical priority. Insulin like molecules alter system-wide protein turnover, yet the effects on individual proteins is unclear. A change in a protein's turnover can alter the stoichiometry of the active protein and ultimately affect the efficiency of a pathway. Because of the potential functional consequence of protein turnover and the importance of insulin signaling, we propose to study both these processes in the nematode Caenorhabditis elegans using quantitative proteomics. Specific Aim 1 is to develop quantitative stable isotope tracer methodology for both the directed and undirected analysis of protein turnover in C. elegans. Specific Aim 2 will measure the turnover of proteins involved in the insulin/insulin growth factor-1 (IGF-1) signaling pathway of C. elegans in response to the inhibition and overexpression of ligands of the insulin receptor (DAF-2). Specific Aim 3 is to measure the effect of insulin like molecules on the tissue-specific intracellular metabolism of the nematode C. elegans using stable isotope labeling and isotopomer distribution analysis. The successful completion of this proposal will produce methodological framework for studying protein turnover in C. elegans and provide foundation for extending these technologies to higher organisms. Furthermore, the proteome-wide measurement of protein turnover in response to insulin-like molecules will produce an experimental dataset for probing the underlying mechanism of insulin signaling. [unreadable] [unreadable] [unreadable]

mass spectrometry

library

data quality /integrity

mass spectrometry; university

mass spectrometry; university

CRISP; Cells; Charge; Compensation; Complex Mixtures; Computer Programs; Computer Retrieval of Information on Scientific Projects Database; Computer software; Coupled; Data; Data Set; Dataset; Devices; Financial compensation; Funding; Gases; Grant; Housing; Institution; Investigators; Ions; Methods and Techniques; Methods, Other; NIH; National Institutes of Health; National Institutes of Health (U.S.); Peptides; Phase; Process; Proteomics; Range; Research; Research Personnel; Research Resources; Researchers; Resources; Scanning; Software; Source; Spectrometry; Speed; Speed (motion); System; System, LOINC Axis 4; Techniques; Tripcellim; Trypsin; United States National Institutes of Health; V (voltage); Yeasts; base; computer program/software; cost; experiment; experimental research; experimental study; instrument; ion mobility; mass spectrometer; prototype; research study; ultra high resolution; voltage

Area; Biochemistry; Biomedical Engineering; Blood Plasma; CRISP; Chemistry; Chemistry, Biological; Clinical; Complex Mixtures; Computer Retrieval of Information on Scientific Projects Database; Educational workshop; Funding; Future; Genome; Grant; Institution; Investigators; Korea; Korea, Republic of; Mass Spectrum; Mass Spectrum Analysis; Michigan; Monitor; NIH; National Institutes of Health; National Institutes of Health (U.S.); Needles; North Carolina; Pathology; Peptides; Photometry/Spectrum Analysis, Mass; Plasma; Proteins; Proteome; Proteomics; Range; Reaction; Research; Research Personnel; Research Resources; Researchers; Resources; Reticuloendothelial System, Serum, Plasma; Science; Science of Chemistry; Serum, Plasma; Shotguns; Source; South Korea; Spectrometry, Mass; Spectroscopy, Mass; Spectrum Analyses, Mass; Spectrum Analysis, Mass; Technology; United States National Institutes of Health; Universities; Washington; Workshop; bioengineering; bioengineering/biomedical engineering; day; gene product; improved; nano; quantum; tandem mass spectrometry

CRISP; Computer Programs; Computer Retrieval of Information on Scientific Projects Database; Computer software; Funding; Grant; Institution; Investigators; NIH; National Institutes of Health; National Institutes of Health (U.S.); Research; Research Personnel; Research Resources; Researchers; Resources; Software; Source; United States National Institutes of Health; computer program/software

CRISP; Computer Programs; Computer Retrieval of Information on Scientific Projects Database; Computer software; Funding; Grant; Institution; Investigators; NIH; National Institutes of Health; National Institutes of Health (U.S.); Research; Research Personnel; Research Resources; Researchers; Resources; Software; Source; United States National Institutes of Health; computer program/software

American; Blood; CRISP; Chromatography; Chromatography / Separation Science; Colorado; Computer Retrieval of Information on Scientific Projects Database; Data; Educational process of instructing; Educational workshop; Funding; Genome; Grant; Health Sciences; Institution; Investigators; Korea; Label; Maintenance; Maintenances; Mass Spectrum; Mass Spectrum Analysis; Moon; NIH; National Institutes of Health; National Institutes of Health (U.S.); Operation; Operative Procedures; Operative Surgical Procedures; Pharmacology; Photometry/Spectrum Analysis, Mass; Protein Analysis; Proteomics; Research; Research Personnel; Research Resources; Researchers; Resources; Reticuloendothelial System, Blood; Science; Societies; Sound; Sound - physical agent; Source; Spectrometry, Mass; Spectroscopy, Mass; Spectrum Analyses, Mass; Spectrum Analysis, Mass; Surgical; Surgical Interventions; Surgical Procedure; Teaching; Training; United States National Institutes of Health; Universities; Washington; Workshop; day; instrument; sound; surgery

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The SEQUEST program was the first and remains one of the most widely used tools for assigning a peptide sequence within a database to a tandem mass spectrum. The cross correlation score is the primary score function implemented within SEQUEST and it is this score that makes the tool particularly sensitive. Unfortunately, this score is computationally expensive to calculate, and thus, to make the score manageable, SEQUEST uses a less sensitive but fast preliminary score and restricts the cross correlation to just the top 500 peptides returned by the preliminary score. Classically, the cross correlation score has been calculated using Fast Fourier Transforms (FFT) to generate the full correlation function. We describe an alternate method of calculating the cross correlation score that does not require FFTs and can be computed efficiently in a fraction of the time. The fast calculation allows all candidate peptides to be scored by the cross correlation function, potentially mitigating the need for the preliminary score, and enables an E-value significance calculation based on the cross correlation score distribution calculated on all candidate peptide sequences obtained from a sequence database.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The dramatic progress in high throughput proteomics analysis via ESI-LC/MS over the last decade has been fueled to a large degree by continuous improvements in instrumentation. High throughput identification experiments are based on peptide sequencing and are largely accomplished through the use of tandem mass spectrometry, with ion trap and trap-based instruments having become the dominant analytical platforms. To satisfy increasingly demanding requirements for depth of characterization and throughput, we present a newly developed dual-pressure linear ion trap mass spectrometer (LTQ VelosTM) that features increased sensitivity, afforded by a new source design, and demonstrates practical cycle times two times shorter than that of an LTQ XL, while improving or maintaining spectral quality for MS/MS fragmentation spectra. These improvements resulted in a substantial increase in the detection and identification of both proteins and unique peptides from the complex proteome of Caenorhabditis elegans, as compared to existing platforms. Faster cycle times on the new instrument alternatively allow for higher throughput for a given depth of proteome analysis, with more peptides and proteins identified in 60 min using an LTQ Velos than in 180 min using an LTQ XL. The greatly increased ion flux into the mass spectrometer also results in greatly increased detection of low abundance peptides. These improvements cumulatively resulted in a substantially greater penetration into the baker?s yeast (Saccharomyces cerevisiae) proteome compared to LTQ XL. Additionally, mass analysis in the new instrument can be carried out with resolution in excess of 20,000 FWHM, sufficient for isotopic resolution and top down experiments of small intact proteins, such as myoglobin.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Shotgun proteomics techniques typically "undersample" peptides in complex mixtures using data-dependent acquisition (DDA). Multi-dimensional chromatographic separations have been used to decrease the number of co-eluting ions, allowing the DDA process to sample the mixtures adequately. However, the mass spectrometer stills spend a majority of experiment time sampling the most abundant species. In data-independent acquisition (DIA), windows in the m/z domain are fragmented continuously, providing an opportunity to obtain fragmentation spectra at every m/z value of interest, without any m/z bias. This process can be improved by increasing the ion flux, which improves sampling of less abundant molecular species. This project investigates improvements in complex mixture analysis by using DIA on a mass spectrometer equipped with an electrodynamic ion funnel. The ion funnel, built in-house from a design by researchers at Pacific Northwest National Lab, increases ion flux by a factor of 10 or more, leading to increased scan speed, sensitivity, and increased numbers of peptide and protein identifications, in multiple modes of analysis.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In shotgun proteomics, the analysis of tandem mass spectrometry data from peptides can benefit greatly from high mass accuracy measurements. In this study we present a software tool, Bullseye, which determines the monoisotopic mass and charge state of the precursor ion of a tandem mass spectrum. By using information throughout the chromatographic elution profile of the peptide, Bullseye discards MS/MS spectra that are a result of the fragmentation of noise and can offer improvements in the accuracy of monoisotopic mass measurements. We have evaluated two database search strategies which use high mass accuracy measurements of the peptide precursor ion. Our results indicate that peptide identifications are improved when spectra are searched with a wide mass tolerance window and precursor mass is used as a filter to discard incorrect matches. Database searches with a peptide dataset constrained to peptides within a narrow mass window resulted in fewer peptide identifications but a significantly faster database search time.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Selected reaction monitoring (SRM) is a powerful tandem mass spectrometry method that can be used to monitor target peptides within a complex protein digest. The specificity and sensitivity of the approach, as well as its capability to multiplex the measurement of many analytes in parallel, has made it a technology of particular promise for hypothesis driven proteomics. An underappreciated step in the development of an assay to measure many peptides in parallel is the time and effort necessary to establish a usable assay. Here we report the use of shotgun proteomics data to expedite the selection of SRM transitions for target peptides of interest. The use of tandem mass spectrometry data acquired on an LTQ ion trap mass spectrometer can accurately predict which fragment ions will produce the greatest signal in an SRM assay using a triple quadrupole mass spectrometer. Furthermore, we present a scoring routine that can compare the targeted SRM chromatogram data with an MS/MS spectrum acquired by data-dependent acquisition and stored in a library. This scoring routine is invaluable in determining which signal in the chromatogram from a complex mixture best represents the target peptide. These algorithmic developments have been implemented in a software package that is available from the authors upon request.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The identification of peptides by microcapillary liquid chromatography-tandem mass spectrometry (?LC-MS/MS) has become routine because of the development of fast scanning mass spectrometers, data-dependent acquisition, and database searching algorithms. However, many peptides within the detection limit of the mass spectrometer remain unidentified because of limitations in MS/MS sampling speed despite the dynamic range and peak capacity of the instrument. We have developed an automated approach that uses the mass spectra from high resolution ?LC-MS data to define the molecular species present in the mixture and directs the acquisition of MS/MS spectra to precursors that were missed in prior analyses. This approach increases the coverage of the molecular species sampled by MS/MS and consequently the number of peptides and proteins identified during the acquisition of technical or biological replicates using a simple one-dimensional chromatographic separation. The combination of a unique workflow and custom software contribute to the improved identification of molecular features detected in proteomics experiments of complex protein mixtures.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Preparation of the YRC progress report.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The Noble and Maccoss Labs distributed the following software in 2007-2008: BiblioSpec: A suite of programs for creating, filtering, and searching MS/MS spectrum libraries ChargeCzar: uses a support vector machine to discriminate between +2- and +3-charged tandem mass spectra, with the goal of reducing database search time by eliminating the need to search twice with each spectrum. Crux analyzes shotgun proteomics tandem mass spectra, associating peptides with observed spectra. Percolator post-processes the results of a shotgun proteomics database search program, re-ranking peptide-spectrum matches so that the top of the list is enriched for correct matches.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The MacCoss lab distributed the following software in 2008-2009: MakeMS2: A windows program for extracting mass spectrometry data from Thermo Fisher RAW instrument files. Hardklor /Kronik: A pair of programs for the analysis of high resolution mass spectrometry data. Hardklor will return monoisotopic m/z and charge states for single or overlapping peptide/protein isotope distributions. CRAWDAD: A software suite for label-free relative quantitation of high- and low-resolution LC-MS data. Replicate runs are aligned in the retention time dimension prior to feature detection using dynamic time warping. Features of differential intensity are detected using statistical tests, and annotated using MS/MS peptide identifcations. MScout: A software tool for assessing LC-MS data quality. P3 Predictor: A simple windows program to aide in establishing SRM transitions for targeted proteomics. IDCalc: A Microsoft Windows program that implements the method reported by Kubinyi, Analytica Chimica Acta, 247 (1991) 107-119 for the prediction of isotope distributions. Skyline: A Windows client application for building Selected Reaction Monitoring methods and analyzing the resulting mass spectrometry data. PAnDA: PAnDA is an acronym for Post Analysis Data Acquisition. PAnDA uses the Hardklor feature finder to determine the molecular species in an LC-MS analysis and then uses this information to automatically construct new methods to acquire features missed in prior analyses.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Training performed for targeted proteomics Trained Paulovich Lab in using Skyline v0.1 Trip to Vanderbilt to train the Liebler lab on Skyline v0.1 Trained Jeff Whiteaker and ChenWei Lin individually on Skyline v0.2 Trained Ping Yan and ChenWei Lin FHCRC on Skyline v0.2 Trained Matt Fitzgibbon and Damon May FHCRC individually on Skyline v0.2 Trained Parag Mallick (WebEx) at USC individually on Skyline v0.2 Created Skyline v0.2 training video See http://proteome.gs.washington.edu/software/skyline Presented (WebEx) Skyline v0.2 to Carr Lab at Broad Trip to Vanderbilt to train Lisa Zimmerman, Robert Sprung, and Haixia Zhang on v0.2 and early v0.5 Trained Sue Abbatiello (WebEx) at the Broad on the use of Skyline v0.5 Trained Lisa Zimmerman (WebEx) from Vanderbilt on Skyline v0.5 Trained Jeff Whiteaker, Chenwei Lin and Ping Yan FHCRC on Skyline v0.5 Trained Birgit Schilling and Jason Held from the Buck Institute (WebEx) on Skyline v0.5 We have also been helping Baohai Shao in the Heinecke lab in the development of targeted proteomics methods using Skyline Training performed in the analysis of differential MS data Andy Hoofnagle for the analysis of HDL particles in type 1 and type 2 diabetes patients metabolomics analysis using CRAWDAD Training performed in the use of PAnDA Weekly phone calls with Bruce Pascal in Patrick Griffin?s lab at Scripps Florida in the use of our PAnDA software with the Advion Replay Training with the Thermo BRIMS Center in the integration of PAnDA within the Sieve Workflow Training provided in general mass spectrometry Jan Aagaard from the Swanson Lab: training in building MS methods, packing chromatography columns Catherine Eakin from the Klevit Lab: guidance in the acquisition of MS spectra and separations of whole proteins Hitomi Sakano from the Buck Lab: guidance in the analysis of her tandem mass spectrometry data and in understanding the meaning of q-values and posterior error probabilities Tonya Pekar Second at Thermo Fisher: help with calculation of chromatographic peak capacity.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Co-Instructor, American Society for Mass Spectrometry Two Day Short Course on Case Studies in Quantitative Proteomics, Philadelphia, PA 2009 Educational Workshop on Multidimensional Chromatography Tandem Mass Spectrometry at the Human Proteome Organization (HUPO), Amsterdam, Netherlands 2008 Lectured at a Statistical Proteomics Workshop at US Human Proteome Organization Meeting, San Diego, CA 2009. Statistical Proteomics: Challenges and Works in Progress Quantitative Proteomes: Theory, Methodology, and Applications, Chicago Biomedical Consortium Summer Workshop in Proteomics, Chicago, Il, 2008

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The kinetochore is a highly conserved complex responsible for making the attachment between microtubules and chromosomes during mitosis. Although the major sub-complexes of the kinetochore have been identified, relatively little is known about the structural organization of these sub-complexes. We would like to determine which proteins/sub-complexes are copurifying when expressed in bacteria to aid in structural analysis.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Our focus of research, the Werner protein, is one of disease-associated RecQ helicases. Its deficiency results in the Werner syndrome (WS), characterized by accelerated rate of mutation and the organism's inability to resolve a variety of genome-damaging events. Mutations in the WRN gene (also referred to as RECQ3 or RECQL2) don't appear to increase a person's susceptibility to DNA damage, and they alone do not cause the development of the disease. Instead they accelerate and exacerbate the disease that could develop even without this sensitizing mutation due to the damaging environmental agents. An important consequence of understanding the mechanism of a pathology is the ability to treat it more effectively, and even to prevent it in some cases. Aging research is extremely important considering the changing demographics worldwide, increased overall longevity and rise in elderly population. Understanding of the mechanisms that underlie aging and development of age-related disease due to genomic aberration can lead us to improved treatment and alleviated burden of age-related disease. Activity of proteins such as WRN suggests that the complex process of ageing is controlled by a conserved number of genes. However, mutations in a series of proteins do not suggest that their normal function is involved in promoting longevity. We are interested in understanding how normal function of this protein stalls senescence. In order to determine these mechanisms we study protein function in normal and diseased states with the use of proteomics. Resources that are currently available to us include modern analytical instrumentation, support from computational sciences, and access to rare biological samples. Our work is aimed at defining consistently associated proteins and post-translational modifications of WRN that are required or are causal for its function in human cells. This knowledge will increase our understanding of WS pathogenesis and provide insight into novel strategies to alter the progression of WS or associated diseases such as ASCVD, cancer, diabetes, and osteoporosis.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Variation in protein expression levels among individuals is thought to be an important source of physiological differences within and between species. However, relatively little is known about the magnitude and genetic basis of variation in protein expression levels. Recently, the Sanger Institute has resequenced the complete genomes of 37 Saccharomyces cerevisiae strains. This data set provides an important, novel, and powerful opportunity to synergistically combine comparative functional genomics data with comparative sequence analyses to delineate the genetic architecture of protein expression levels in yeast. Specifically, the goals of this project are two-fold. First, quantitative protein expression levels will be obtained for all 37 S. cerevisiae strains (or a maximally informative subset based upon their phylogenetic relationships), and protein levels that vary significantly among strains will be identified. Second, the whole genome sequence data will be leveraged to correlate patterns of protein expression levels with genetic variation. These data will provide the first systematic insight into the magnitude and patterns of natural protein expression variation as well as its genetic basis.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Variation in protein expression levels among individuals is thought to be an important source of physiological differences within and between species. However, relatively little is known about the magnitude and genetic basis of variation in protein expression levels. Recently, the Sanger Institute has resequenced the complete genomes of 37 Saccharomyces cerevisiae strains. This data set provides an important, novel, and powerful opportunity to synergistically combine comparative functional genomics data with comparative sequence analyses to delineate the genetic architecture of protein expression levels in yeast. Specifically, the goals of this project are two-fold. First, quantitative protein expression levels will be obtained for all 37 S. cerevisiae strains (or a maximally informative subset based upon their phylogenetic relationships), and protein levels that vary significantly among strains will be identified. Second, the whole genome sequence data will be leveraged to correlate patterns of protein expression levels with genetic variation. These data will provide the first systematic insight into the magnitude and patterns of natural protein expression variation as well as its genetic basis. This experiment represents a pilot experiment to first examine BY and RM strains.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. High field asymmetric waveform ion mobility spectrometry (FAIMS) has been used increasingly in recent years as an additional method of ion separation and selection before mass spectrometry. The FAIMS electrodes are relatively simple to design and fabricate for laboratories wishing to implement their own FAIMS designs. However, construction of the electronics apparatus needed to produce the required high magnitude asymmetric electric field oscillating at a frequency of several hundred kilohertz is not trivial. Here we present an entirely custom-built electronics setup capable of supplying the required waveforms and voltages. The apparatus is relatively simple and inexpensive to implement. We also present data acquired on this system demonstrating the use of FAIMS as a gas-phase ion filter interface to an ion trap mass spectrometer.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In data-independent acquisition (DIA), MS/MS spectra are acquired continuously at predetermined m/z windows independent of peptide precursor detection. Ideally, DIA would cover the entire mass range with small precursor m/z isolation windows and a total cycle time of <5 sec to ensure adequate chromatographic sampling. Unfortunately, current ion trap mass spectrometers are limited to 30-50 MS/MS scans in a 5-second cycle. Thus, we need to perform many runs to cover the mass range, increase isolation window size, or cover an informative subset of the m/z range. We developed methods to deconvolute DIA fragmentation spectra derived from multiple peptides into their individual components. We empirically optimized fragmentation window selection in Saccharomyces cerevisiae and Caenorhabditis elegans maximizing protein identifications in a run.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We compare methods of data-dependent acquisition (DDA) and data-independent acquisition (DIA), implemented both on a traditional LTQ and an LTQ equipped with an electrodynamic ion funnel.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This project seeks to compare the efficacy of data-independent acquisition (DIA) with data-dependent acquisition (DDA) strategies. This study is conducted with Saccharomyces cerevisiae, for which copy numbers of many proteins are known. Thus the protein sampling depth of each method can be examined.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. It is known that cells deficient in the Werner protein (WRN) are specifically sensitive to cisplatinum (cis-Pt), a chemotherapy drug that works by crosslinking DNA and triggering apoptosis. Our profiling analysis of cells exposed to this drug is aimed at understanding the mechanisms cells employ to resolve the resulting damage, and how WRN protein is involved in these mechanisms. In order to understand WRN involvement, we aim to analyze its associated protein complex. By using a genetically encoded TAP tag, we are enriching for the WRN and its partners from whole cell lysates in human embryonic kidney (HEK-293) cells and are proposing to analyze these complexes by profiling mass spectrometry. Our lab has previously established conditions for treating cells with these chemotherapeutic compounds, and initial experiments with cell treatment have been performed. We are currently awaiting first MS results.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. A systematic study of nanoflow LC-MS/MS conditions (column length, gradient length) was conducted to evaluate the relationship between chromatographic performance and peptide/protein identification in a highly complex mixture. A specialized software platform was developed and used to determine fundamental performance metrics including peak capacity in relation to peptide and protein ID from data dependent acquisition. The optimum analytical strategy appears to involve the use of "short gradient-short column" (for throughput) or "long gradient-long column" (for ID quantity) approaches.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We would like to design a protocol for the enrichment of kinases from a complex mixture of proteins. Staurosporine is a tightly binding, non specific inhibitor of kinases. Rob Young's lab at Simon Fraser University has synthesized a number of biotinylated staurosporine analogs. By incubating these analogs with protein samples, we hope to selectively bind kinases, which can then be enriched using avidin beads.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Typical approaches to validating label-free quantitative mass spectrometry use the spiking in of a limited number of proteins against a complex background proteome. However, a low number of spike-in proteins is limited in number, and is less than the expected number of proteins changed in abundance between two or more biological conditions. A convenient source of a large number of known spike-ins is that of a simpler proteome from an organism which has little peptide-level homology with the complex background. We propose to create a dataset with known levels of digested E. coli proteome spiked into a HEK293 human epithelial kidney cell proteome background which will allow us to assess the false discovery rate and quantitative accuracy of relative changes in protein abundance using a label-free approach. Also, we will qualitatively characterize the proteome of the HEK293 due to the large number of MS/MS spectra that will be acquired.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. For an insoluble yeast lysate both methods reported similar numbers in protein IDs and for membrane proteins. However the SDS spin cartridges were considerably faster. This intial finding is currently being reproduced in various complex samples including C elegans, yeast lysate, and HeLa cells.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. C12 Halo beads did provide higher peak capacity with longer gradient runs;however the results were not significant, about 10% higher. With shorter gradients the Halo beads did not provide significant gains compared to the tradition 4 um C12 beads. One pitfall of the HALO beads was the high back pressure which often lead to blown fittings or pressure overloads after only a few runs

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In liquid chromatography a number of parameters, such as the stationary phase, mobile phase, mobile phase gradient and column diameter, can affect separation performance. We are interested in investigating the affect of column temperature on peak capacity, peptide separation and peptide recovery. We will design and construct a custom column heater that integrates into our mass spectrometer source stage, and analyze complex protein samples at a variety of temperatures and column resins.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We are investigating the accuracy of absolute and relative quantification of proteins in simple and complex mixtures using the 3 highest ionizing peptides. The average of the areas under the curve of the three highest ionizing peptides provides a metric for relative and absolute quantification. In addition we are comparing the HI 3 method with spectral counting

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This was a small trial research project to test our capability to identify proteins by doing an affinity pulldown with a small molecule affinity column. The small molecule was chosen that is known to interact with ALDH.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. F-box proteins are tumor suppressor genes that are part of the ubiquitin ligase complex known to mediate protein-protein interactions via their 50 amino acid F-box domain. We hope to identify F-box substrates (proto-oncogenes) by observing the changes of proteins over time between the F-box deletion strains in Saccharomyces cerevisiae versus the wild-type control using stable isotope labeling (D3-Leucine).

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In shotgun proteomics, the analysis of tandem mass spectrometry data from peptides can benefit greatly from high mass accuracy measurements. In this study, we have evaluated two database search strategies which use high mass accuracy measurements of the peptide precursor ion. Our results indicate that peptide identifications are improved when spectra are searched with a wide mass tolerance window and precursor mass is used as a filter to discard incorrect matches. Database searches with a peptide data set constrained to peptides within a narrow mass window resulted in fewer peptide identifications but a significantly faster database search time.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The LTQ-Velos ion trap is currently set to a default state of trapping 2000 ions during the MSn scans. Trapping more ions may improve our identifications since the LTQ-Velos is significantly faster than the original LTQ. We compare the number of peptides identified and spectra acquired between the different ion capacity experiments using C. elegans soluble lysate in both data-dependent acquisition and data-independent acquisition experiments.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Robust genome sequencing technology has resulted in over 180 completed genomes, with sequencing projects for an additional 700+ organisms in progress. The difficult and important problem of experimentally determining the proteins encoded by these genomes lags far behind. We propose to complement existing messenger-RNA based approaches with high throughput mass spectrometry of the entire protein complement of a complex animal, the nematode Caenorhabditis elegans. Our approach combines open reading- frarne (ORF) analysis of the fully sequenced C. elegans genome with high-throughput mass spectrometry, using multidimensional protein identification technology (MudPIT). Our long-term goal is development of these methods to the point that at least 80% of all proteins in a newly sequenced organism can be identified in a few months of concerted effort by a small group of investigators. This goal l requires development of the following tools: 1) efficient evolutionary analysis of genomic ORFs to identify a computationally manageable set of candidate peptides for mass spectrum matching;2) a robust method for biochemical fractionation of intact proteins from whole organisms or tissues;and 3) analytical approaches to assessing the significance of MudPIT matches to specific candidate peptides. Peptide cleavage, fractionation, and 2- dimensional mass spectrometry methods are established in our labs and are currently sufficient achieve our goal with the addition of these tools.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. From discovery to targeted protein analy Integrating the workflow from traps to triples, Thermo Fisher Scientific United Kingdom User Meetings, Leeds and London, UK, 2009 First Impressions of New Ion Trap Technology: Implications and Impact for Proteomics, Thermo Fisher ASMS User Meeting, Philadelphia, PA, 2009 Complementary Proteomics Strategies for Understanding the C. elegan Genome, British Society for Proteome Research, Wellcome Trust Conference Center, Hinxton, Cambridge UK, 2009 Raising the Bar in Proteomics: Developing New Technologies to Keep up with Genomics, Lorne Proteomics Symposium, Lorne, Australia, 2010 Application of FAIMS-MS to Shotgun Proteomics, Pittcon Meeting, Orlando, Fl, 2010 Improving the Throughput, Reproducibility, and Usability of Proteomics Measurements, Fred Hutchinson Cancer Research Center, Seattle, WA, 2010 Facilitating Alternative Proteomics Data Acquisition Strategies by Improving the Data Analysis, CASB, San Diego, CA, 2010 Targeted Analysis of Complex Mixtures: A Computational Workflow from Discovery to Validation, Recomb-CP, San Diego, CA, 2010 Advances in the Analysis of Complex Protein Mixtures: Finding Protein Needles in Cellular Haystacks, Department of Biology, University of New Mexico, Albuquerque, NM, 2010 Improving the Throughput, Reproducibility, and Usability of Proteomics Measurements, Thermo/Pierce, Rockford, Il, 2010 Improving Shotgun Proteomics by Multiplexed MW Separation of Intact Proteins, Protein Discoveries User Meeting, ASMS, Salt Lake City Utah, 2010 Bridging the Gap from Discovery to Validation: Automating the Workflow for Establishing Multiplexed Targeted Mass Spectrometry Methods, Foundation of the National Institutes of Health, Biomarker Consortium, Bethesda, MD, 2010 Integrating new sample prep, instrumentation, and analysis tools to improve the characterization of complex protein mixtures, University of Gent, Belgium, 2010

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Skyline is a Windows client application for targeted pro-teomics 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 Biosys-tems, 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 is 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.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The MacCoss lab distributed the following software in 2009-2010: MakeMS2: A windows program for extracting mass spectrometry data from Thermo Fisher RAW instrument files. Hardklor /Kronik: A pair of programs for the analysis of high resolution mass spectrometry data. Hardklor will return monoisotopic m/z and charge states for single or overlapping peptide/protein isotope distributions. CRAWDAD: A software suite for label-free relative quantitation of high- and low-resolution LC-MS data. Replicate runs are aligned in the retention time dimension prior to feature detection using dynamic time warping. Features of differential intensity are detected using statistical tests, and annotated using MS/MS peptide identifications. MScout: A software tool for assessing LC-MS data quality. P3 Predictor: A simple windows program to aide in establishing SRM transitions for targeted proteomics. IDCalc: A Microsoft Windows program that implements the method reported by Kubinyi, Analytica Chimica Acta, 247 (1991) 107-119 for the prediction of isotope distributions. Skyline: A Windows client application for building Selected Reaction Monitoring methods and analyzing the resulting mass spectrometry data. PAnDA: PAnDA is an acronym for Post Analysis Data Acquisition. PAnDA uses the Hardklor feature finder to determine the molecular species in an LC-MS analysis and then uses this information to automatically construct new methods to acquire features missed in prior analyses. Topograph: A Microsoft Windows application for the analysis of mass spectrometry data from biological samples that have been labeled with stable isotope labeled amino acid(s) BullsEye: A program for correcting the monoisotopic m/z for MS/MS spectra from hybrid LTQ-FT and LTQ-Orbitrap mass spectrometers. PepLynx: A program for the interpretation of high resolution MS/MS spectra of cross-linked peptides. The MacCoss lab distributed the following software in 2009-2010: MakeMS2: A windows program for extracting mass spectrometry data from Thermo Fisher RAW instrument files. Hardklor /Kronik: A pair of programs for the analysis of high resolution mass spectrometry data. Hardklor will return monoisotopic m/z and charge states for single or overlapping peptide/protein isotope distributions. CRAWDAD: A software suite for label-free relative quantitation of high- and low-resolution LC-MS data. Replicate runs are aligned in the retention time dimension prior to feature detection using dynamic time warping. Features of differential intensity are detected using statistical tests, and annotated using MS/MS peptide identifications. MScout: A software tool for assessing LC-MS data quality. P3 Predictor: A simple windows program to aide in establishing SRM transitions for targeted proteomics. IDCalc: A Microsoft Windows program that implements the method reported by Kubinyi, Analytica Chimica Acta, 247 (1991) 107-119 for the prediction of isotope distributions. Skyline: A Windows client application for building Selected Reaction Monitoring methods and analyzing the resulting mass spectrometry data. PAnDA: PAnDA is an acronym for Post Analysis Data Acquisition. PAnDA uses the Hardklor feature finder to determine the molecular species in an LC-MS analysis and then uses this information to automatically construct new methods to acquire features missed in prior analyses. Topograph: A Microsoft Windows application for the analysis of mass spectrometry data from biological samples that have been labeled with stable isotope labeled amino acid(s) BullsEye: A program for correcting the monoisotopic m/z for MS/MS spectra from hybrid LTQ-FT and LTQ-Orbitrap mass spectrometers. PepLynx: A program for the interpretation of high resolution MS/MS spectra of cross-linked peptides.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This project is almost entirely based upon the work of Josh McElwee. The Insulin/IGF-1-like (IIS) pathway has been a pathway of great interest in the field of aging since modulation of components of the pathway extend lifespan significantly in taxonomically diverse model organisms. This study seeks to identify the key interacting partners of factors in this pathway in human cells as well as changes in interacting partners under serum-starved conditions. We hope to uncover new candidates for future study of this pathway in regards to aging. The response of this pathway to serum-starved conditions may provide insight into the relationship of this pathway and caloric restriction, another conserved mediator of longevity.

DESCRIPTION (provided by applicant): The enclosed proposal is requesting funds to expand the mass spectrometry and proteomics resources at the University of Washington through the purchase of a Thermo Fisher LTQ-Orbitrap mass spectrometer. This instrument will be invaluable in the successful completion of our existing NIH funded projects involving the qualitative and quantitative analysis of proteins and protein modifications of complex mixtures. Furthermore, a number of our projects are extending quantitative proteomics technology to the measurement of changes in the rate of turnover. Integral to the timely completion of these NIH research projects is the availability of a mass spectrometer capable of i) sub 5 ppm mass accuracy to distinguish between similar mass peptides, ii) a dynamic range of >1000 in a single spectrum, iii) data-dependent acquisition of tandem mass spectra with the sensitivity and speed of a quadrupole ion trap, and iv) the ability to resolve and detect unusual isotope distributions of multiply charged peptides within a complex mixture. Current mass spectrometers capable of these measurements are oversubscribed and, thus, can provide little to no access to our grants user groups. We propose to address these limitations through the acquisition of a shared hybrid mass spectrometer which combines the robustness and speed of a linear quadrupole ion-trap with the resolution, mass accuracy, and dynamic range of a Fourier transform mass spectrometer. The requested instrumentation will allow the faculty to address current technological limitations on a global level and improve the sample analysis bottleneck that will improve the capabilities of existing and future NIH funded projects within the University of Washington, College of Medicine. PUBLIC HEALTH RELEVANCE: We are requesting support to purchase a mass spectrometer for the qualitative and quantitative analysis of complex protein mixtures. These analyses will be used to improve our understanding of how a genome sequence encodes a functional living organism, to identify novel reproductive proteins, identify biomarkers of exposure to environmental toxins, understanding the molecular machinery responsible for double stranded DNA breaks, the basic molecular processes involved in aging, and more. All of these areas improve our understanding, prevention, or treatment of human disease.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Training Provided by Brendan MacLean on the Use of Skyline 1. Taught 3 hours of hands-on tutorials for CPTAC Verification Working Group Operators meeting at Broad Institute 2. Created 2 x 25 minute training videos for Skyline v0.5 3. Regular bimonthly instructional updates over WebEx for Verification Working Group 4. Regular WebEx sessions with Susan Abbatiello and Birgit Schilling, leaders of Verification Working Group 5. Multi-day site visit at Vanderbilt University, Liebler and Tabb labs 6. Presentation to Aebersold Lab in Zurich 7. Presentation at U. Zurich mini-symposium 8. Multi-day site visit at Broad Institute, Carr lab 9. Co-taught 1.5 hours of US HUPO quantitative proteomics course 10. Created 3 x 10-20 page tutorials in using Skyline v0.6 11. Answered 110 support requests on Skyline support board (many others through direct email) 12. WebEx sessions with Christina Ludwig of Aebersold Lab 13. Taught undergraduate Alana Killeen professional software development for independent study Training Provided by Jesse Canterbury on General Mass Spectrometry Analysis 1. Rob Moritz, Jeff Stevens (ISB): FAIMS, triple quad operation &data 2. interpretation 3. Matt Chambers (Vanderbilt): generating data files for unit tests of file reader code 4. Shawna Hengel (Med Chem, Goodlett): ECD experiments 5. Scott Shaffer (Med Chem, Goodlett): ion funnel &Velos troubleshooting 6. Jason Wooden (Puget Sound Blood Center): mass spec &HPLC operation 7. Katrina Claw (Swanson lab): mass spec operation 8. Jan Aagaard (Swanson lab): mass spec operation 9. Andrew Stergachis (Stamatoyannopoulos lab): mass spec operation 10. Sean McIlwain (Noble): DIA data interpretation 11. Mirela Andronescu (Noble): data conversion/interpretation Training Provided by Daniela Tomazela on General Mass Spectrometry Analysis 1. Michael Paulsen: (BChE) Skyline, Column Packing, Data Acquisition 2. Francisco Nociti Jr. (Cementum project) Sample Preparation: Tryptic Digestion, Data Acquisition, MSDaPl 3. Ling Wang (Baker Lab): Data Acquisition 4. Judit Marsillach (Furlong lab / OP Project): Tryptic Digestion, MCX Peptide Sample Cleanup, Column Packing 5. Andrew Stergachis (Stamatoyannopoulos lab): Skyline, MS Method setup, SRM data Analysis 6. Jason Wooden (Puget Sound Blood Center): Skyline, LTQ SRM data acquisition, SRM data analysis 7. Tomas Vaisar (Heinecke Lab): Scheduled SRM using Skyline Training Provided by Ed Hsieh on General Mass Spectrometry Analysis 1. Katrina Claw (Swanson Lab): packing capillary columns and use of Agilent 1100 HPLCs 2. Dao-Fu Dao (Rabinovitch Lab): packing capillary columns, with sample analysis on Waters nanoAcquity and Thermo LTQ-FT instruments and with data analysis. 3. Peter Straub (Vanderbilt): in data analysis with Bullseye. 4. Lea Starita (Fields Lab): in data analysis with Bullseye and capillary column packing. Training Provided by Gennifer Merrihew 1. MSDaPl / MacCoss lab pipeline help - Evvie Vincow, Lea Starita, Jan Aagard, Melody Rynerson, Katrina Claw, Renee George, Angela Poole 2. Orbitrap runs, sample prep discussions - Evvie Vincow, Lea Starita 3. GelFree - Lea Starita, Andrew Stergachis, Chuck Witkowski, Jeremy Norris 4. LTQ analysis help, column making help - Melody Rynerson, Katrina Claw, Renee George, Jan Aagard, Angela Poole, Lea Starita 5. Ancient Protein Sample Prep - Ben Novak, Tom Kaye, Matthew Fitzgibbon, Pavel Pezner, Martin McIntosh 6. Isotope labeling discussions - Soledad Undurraga 7. TAP-tagged FOXO cell lines - Matt Kaeberlein, Lara Shamieh

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We are interested in testing the reproducibility and detection of hydrophillic peptides by LC-MS/MS using an HPLC system with and without a trapping column. Trapping columns are typically used in nanoLC systems because they allow for more rapid sample loading. However, during loading, the more hydrophillic peptides may be washed off the trapping column. We are interested in determining the degree of peptides that are lost when using a trapping column versus without.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Educational Workshop on Multidimensional Chromatography Tandem Mass Spectrometry at the Human Proteome Organization (HUPO;2009), Toronto, ON American Society for Mass Spectrometry Workshop (2009), Baltimore, MD Lectured on Statistics and Validation: Challenges and Work in Progress Instructor and Organizer: US Human Proteome Organization (2010), Denver, CO One Day Short Course on Quantitative Mass Spectrometry Co-Instructor: American Society for Mass Spectrometry Two Day Short Course on Case Studies in Quantitative Proteomics (2010), Salt Lake City, UT

DESCRIPTION (provided by applicant): The LINCS program seeks to derive molecular signatures resultant from cellular perturbation. Cellular signaling through modulation of protein phosphorylation is an important component of the cellular response to stimuli, and is complementary to transcriptional profiling. This proposal details the development of a high information content multiplex mass spectrometry-based assay to query serine and threonine signaling pathways. A reductionist approach, whereby the natural correlations of multiple phosphorylation sites under disparate cellular conditions are elucidated, will be used to create efficiencies in representing the cellular state. To achieve this, a modest number of quantitative global phosphoproteomic profiles under varying conditions will be obtained using mass spectrometry (MS). From these data, a limited number of representative phosphopeptides will be extracted - the reduced representation set - whose levels and stoichiometries will serve to capture signatures in response to perturbation. Subsequently, the necessary reagents will be procured to allow the design of targeted mass spectrometry assays (multiple reaction monitoring, or MRM-MS) to quantify the peptides in the reduced representation set in a multiplex (~100-plex) fashion. Variability, reproducibility, limits of detection and quantification, and final assay cost will be measured. Multi-laboratory implementation of the assay will also be demonstrated. In parallel to these efforts, the established open access proteomics software Skyline will be extended to provide a standard means of housing important assay parameters, processing data acquired from reduced representation set MRM-MS assays, and integrating QA/QC metrics to determine assay performance. Skyline will also be adapted to allow for inter-laboratory exchange of MRM-MS methods and data, and we will develop a public database that will integrate assay results from multiple LINCS laboratories. The final product will be a high information content multiplex MS assay called the "Accelerated Protein Signaling Signature" and the informatics infrastructure to support a community resource that contains all of the necessary information and tools for its practical implementation across multiple proteomics laboratories in a collaborative manner. PUBLIC HEALTH RELEVANCE: Development of these experiments will allow us to determine how human cells respond to drug treatment for a fraction of the time and cost of comparable methods. The information provided from these experiments will give us early indicators of potential new therapies and help us differentiate drugs that have desired effects from those that might have undesirable side effects.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. We were approached by Dirk Valkenborg in Belgium to help them benchmark their new instrument using our analysis pipeline. They have been trying to reproduce the work we reported in the Second et al, Anal Chem 2010 paper and without our tools it is hard to differentiate the cause of the differences. We are going to put the data through, BullsEye, SEQUEST, Percolator, and MSDaPL Protein Inference for them.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Comparison of 1D CE and LC of 5 std protein digest (containing phosphopeptides) and SCX fractions enriched for phosphopeptides. CE-microreactor-CE for analysis in application to phosphoproteomics

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. We are interested in determining if the extra computational overhead is worth the increase in peptide and protein identifications to do searches without trypsin specificity.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Virtually all mass spectrometry-based proteomics methods employ some sort of chromatographic separation prior to mass analysis. While the added peak capacity of liquid chromatography is of great benefit, it is inherently slow. In this work, we attempt to perform proteomics experiments on simpler samples (i.e., protein complexes and other samples containing digests of 10 or less proteins) without using chromatography. Instead we use the Advion Nanomate nanospray infusion system coupled with a variety of data acquisition strategies, most notably data-independent acquisition (DIA).

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The objective of this work is to develop a SRM method that could easily help to check the integrity of data analysis during DDA experiments.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool ( http://proteome.gs.washington.edu/software/skyline ).

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. We are looking at HCD vs. CID for the analysis of peptides that have a N-acetyl glucosamine modification. This is a labile modification and often pops off in CID with limited sequence information

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. This project is focused on the analysis/sequencing of the FAB portion of a mouse antibody.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The LTQ-Velos ion trap mass spectrometer has recently been modified to allow performing higher-energy collision-induced dissociation (HCD) within the first quadrupole (Q00) in the intermediate vacuum region of the instrument. The new instrument is called the LTQ-Velos-Pro. HCD is a collision-based fragmentation technique which uses electric potentials to drive ions through a collision gas, in this case air. This beam-like fragmentation technique produces fragmentation spectra that are qualitatively similar to fragmentation patterns observed in triple-quadrupole instruments. We investigate the utility of performing HCD on the LTQ-Velos Pro for proteomics. In particular, we compare HCD and resonant CID, using several different experimental configurations, comparing the methods in the same LC/MS run and between different runs. We also evaluate the utility of HCD in producing library spectra that are well-matched to triple-quadrupole data and are thus well-suited to providing a transition from discovery-based proteomics to a more targeted approach.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Butyrylcholinesterase (BCHE), or serum cholinesterase, is a non-specific cholinesterase found in blood plasma that hydrolyses choline esters. This project entails the search for modifications of BCHE by organophosphorous compounds such as phenyl saligenin phosphate (PSP) and 2-(o-cresyl)-4H-1:3:2-benzodioxaphosphorin-2-oxide (CBDP).

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. In shotgun proteomics, reverse phase nanoflow HPLC is widely used as a method of separating peptides prior to analysis by mass spectrometry. The chromatographic separation of peptides enables the analysis of complex peptide samples that would otherwise not be possible. We are interested in the effect of altering nanoLC parameters, such as column length and gradient length, on peak capacity and peptide identifications. We are also interested in whether obtaining optimal chromatographic peak capacity results in optimal peptide identifications.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Tubulogenesis, the morphogenesis of biological tubes, is required for the development and function of the gut, neural tube, and other organs and is evolutionarily conserved. A useful model for the study of tubulogenesis is dorsal appendage (DA) formation in the Drosophila egg chamber during oogenesis. The DAs are specialized eggshell structures that facilitate embryonic gas exchange. They are made by two patches of ~75 follicle cells, each composed of roof and floor cells that reorganize from a flat epithelium into tubes, extend anteriorly, form paddle-shaped structures at the anterior tips of the tubes, and secrete chorion into the tube lumens. During anterior extension of the DA tubes, roof and floor cells extend filopodia-like extensions towards their substrate;the squamous stretch follicle cells (SCs). Likewise, the SCs project cellular extensions toward the migrating DA-forming cells. In bullwinkle (bwk) mutants, patterning of the DA primordium occurs normally but the egg chamber forms moose-antler shaped DAs. A modifier screen identified shark, a tyrosine kinase, as a strong enhancer of the bwk phenotype. shark is required in the SCs for proper DA morphogenesis. The nature of the signal from the SCs to the DA forming cells is unknown. Knowledge of the genetic and signaling interactions and how they affect the behavior of the cells that form DA tubes will potentially shed light on human developmental processes such as neural tube defects and add to a growing body of knowledge that will lead to the prevention of birth defects in humans.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Mouse olfaction is mediated by ~1000 odorant receptors (ORs) expressed in the cilia of olfactory sensory neurons (OSNs). It is known that ORs are also expressed in the axons of OSNs and that ORs help mediate axon pathfinding during development. To understand the role of ORs in axon pathfinding, antibodies to an OR was used to immunoprecipitate OR protein complexes from various olfactory tissues. These tissues include olfactory epithelium (OSN cilia/cell body) and olfactory bulb (OSN axons) from adult and neonatal animals. By comparing samples from OB to those from the OE, we hope to gain insight into the mechanism of OR-directed axonal targeting.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Earlier in the decade, the limiting factor in CE-MS proteomic experiments were slow scanning instruments not catching up with fast and efficient CE separation. We revisited the concept of a proof-of principle MUDPIT experiment, performed by Tong and Yates at the turn of the century (Anal. Chem. 1999, 71, 2270-2278). We performed experiments on LTQ and simplified nanospray sheath flow CE-MS interface to see if it is possible to take advantage of fast CE separations as a competitive tool for proteomic experiments by coupling them with modern, fast scanning MS instrumentation.

PROJECT SUMMARY With the maturation of proteomics technologies, these tools are being used to improve our understanding of many basic and clinical questions in human and model organism biology. To handle this, laboratories have shown that targeted mass spectrometry measurements offer a promising alternative to immunological based assays. Critical to these experiments is software to handle the generation of instrument methods and the consequent analysis of the resulting data. Our laboratory has developed a client software tool to handle these analyses called Skyline. In the last 8 years, Skyline has become one of the most widely software tools in proteomics and mass spectrometry. In this grant, we propose to continue the development and maintenance of Skyline and its associated software ecosystem, which currently supports 1000s of investigators in their basic science, pre-clinical, and translational research. Specifically, our proposal has five aims. 1) Expand our test infrastructure to improve the robustness, stress test the software, confirm compatibility across computer systems, and track performance over time. 2) Improve support for non-proteomics workflows. 3) Improve the collection, sharing, and dissemination of quantitative mass spectrometry data. 4) Modify Skyline to work in a cloud computing environment. 5) Provide continued support and training for the Skyline ecosystem.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The MacCoss lab distributed the following software in 2010-2011: MakeMS2: A windows program for extracting mass spectrometry data from Thermo Fisher RAW instrument files. Hardklor /Kronik: A pair of programs for the analysis of high resolution mass spectrometry data. Hardklor will return monoisotopic m/z and charge states for single or overlapping peptide/protein isotope distributions. CRAWDAD: A software suite for label-free relative quantitation of high- and low-resolution LC-MS data. Replicate runs are aligned in the retention time dimension prior to feature detection using dynamic time warping. Features of differential intensity are detected using statistical tests, and annotated using MS/MS peptide identifications. MScout: A software tool for assessing LC-MS data quality. P3 Predictor: A simple windows program to aide in establishing SRM transitions for targeted proteomics. IDCalc: A Microsoft Windows program that implements the method reported by Kubinyi, Analytica Chimica Acta, 247 (1991) 107-119 for the prediction of isotope distributions. Skyline: A Windows client application for building Selected Reaction Monitoring methods and analyzing the resulting mass spectrometry data. PAnDA: PAnDA is an acronym for Post Analysis Data Acquisition. PAnDA uses the Hardklor feature finder to determine the molecular species in an LC-MS analysis and then uses this information to automatically construct new methods to acquire features missed in prior analyses. Topograph: A Microsoft Windows application for the analysis of mass spectrometry data from biological samples that have been labeled with stable isotope labeled amino acid(s) BullsEye: A program for correcting the monoisotopic m/z for MS/MS spectra from hybrid LTQ-FT and LTQ-Orbitrap mass spectrometers. PepLynx: A program for the interpretation of high resolution MS/MS spectra of cross-linked peptides. P3 Predictor: A simple windows program to aide in establishing SRM transitions for targeted proteomics.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Provided by Brendan MacLean on proteomics software engineering 1. Wrote 3 new 20-40 page tutorials on using Skyline 2. 1 week site visit to Aebersold lab at ETH Zurich with presentation and training in use of Skyline 3. Multi-day site visit at Vanderbilt University, Liebler and Tabb labs with presentation and training in use of Skyline 4. Two presentations at CPTC annual conference in D.C. (one in main hall, one break-out tutorial session) 5. Wrote TechTalk article for US HUPO newsletter on targeted proteomics and Skyline 6. Multi-day site visit at Broad Institute, Carr lab with presentation and training in use of Skyline 7. Answered 140 support requests on Skyline support board (many others through direct email) 8. Regular bimonthly instructional updates over WebEx for Verification Working Group 9. Frequent WebEx sessions with Skyline users to help work through issues 10. Taught undergraduates Alana Killeen and Mimi Fung professional software development for independent study and as interns Provided by Gennifer Merrihew on General Mass Spectrometry Analysis 1. Evvie Vincow (UW Genome Sciences, Pallanck lab) Orbi mass spectrometry, sample prep assistance, data analysis 2. Melody Rynerson (Uw Genome Sciences, Swanson lab) LTQ1 mass spectrometry, sample prep assistance, data analysis 3. Renee George (Uw Genome Sciences, Swanson lab) sample prep assistance 4. Sandra Zimmerman (UW Genome Sciences, Berg lab) LTQ1 mass spectrometry, sample prep assistance, data analysis 5. Jan Aagard (UW Genome Sciences, Swanson lab) data analysis 6. Jennifer Anderson (University of Oregon) LTQ1 and LTQ-FT mass spectrometry, sample prep assistance, data analysis 7. Dana Miller (UW Biochemistry) sample prep assistance 8. Alex Zelter (UW Biochemistry, Davis lab) sample prep assistance, data analysis 9. Marnie Johansson (UW Genome Sciences, Akey lab) sample prep assistance 10. Nicole Liachko (VA Puget Sound Health Care System, Kraemer lab) sample prep assistance 11. Max Boeck (UW Genome Sciences, Waterston lab) sample prep assistance Provided by Jesse Canterbury on General Mass Spectrometry Analysis 1. Scott Shaffer (Med Chem, Goodlett): ion funnel &Velos troubleshooting 2. Young-Ah Goo (Med Chem, Goodlett): triple quad operation/method development 3. Christophe Masselson (Med Chem, Goodlett): SAWN-FAIMS experiments 4. J. Scott Edgar (Med Chem, Goodlett): ion funnel operation 5. Katrina Claw (Swanson lab): mass spec operation 6. Andrew Stergachis (Stamatoyannopoulos lab): mass spec operation 7. Sean McIlwain (Noble): DIA data interpretation 8. Marina Spivak (Noble): HCD data interpretation 9. Alex Zelter (Biochem, Davis): instrument operation, method development Provided by Ed Hsieh on General Mass Spectrometry Analysis 1. Judit Marsillach (UW, Medicinal Chemistry, Furlong lab): Mass spec and HPLC operation, Column preparation, DDA and SRM data analysis. 2. Katrina Claw (UW, Genome Sciences, Swanson lab): Mass spec operation. Experimental design. Data analysis and interpretation. 3. Simon Johnson (UW, Pathology, Rabinovitch and Kaeberlein labs): Mass spec operation. Data analysis and interpretation. 4. Andreas Quandt (Institute of Molecular Systems Biology, Malmstrom lab): Bullseye software setup and analysis. 5. Dao-Fu Dai (UW, Pathology, Rabinovitch lab): Sample preparation, data analysis. 6. Tony Chen (UW, Pathology, Rabinovitch lab): Sample cleanup and preparation. 7. Megan Wargacki (UW, Biochemistry, Davis lab): Sample prepration, DDA data analysis. Provided by Jarrett Egertson on General Mass Spectrometry Analysis 1. Nathan Basisty (UW Pathology): Ion trap operation, QC analysis, Data Independent Acquisition and Data Dependent Acquisition-based method development, data interpretation, Linux 2. Jim Hibbard (UW): Data Independent Acquisition method development, Linux, data interpretation, development of new methods for data post-processing 3. Danielle Swaney (UW Genome Sciences): Database searching for dynamic modification analysis Provided by Michael Bereman on General Mass Spectrometry Analysis 1. Michelle Cilia (USDA): Skyline and cleaning of Vantage, nanoLC operation. 2. Andrew Stergachis (Stamatoyannopulos lab) nanoLC troubleshooting 3. Katrina Claw (Swanson lab): Topograph, Relative quantification 4. Alex Zelter (Davis Lab): Use of Skyline

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. 1. Cold Spring Harbor Course on Proteomics (2010): Course organized by Andy Link, Jim Bruce, and Darryl Pappin. Michael MacCoss gave a set of lectures on targeted proteomics, validation of quantitative assays, and teach a software lab on the use of Skyline on the development of targeted methods and the analysis of the resulting data. 2. Co-taught a full-day workshop on quantitative proteomics with Gary Valaskvic in Cambridge, MA (2010) 3. Organized and co-instructed a workshop on the quantitative analysis of proteins to the US Anti-Doping Association (2010) 4. Co-organized and instructed a full-day workshop on quantitative proteomics for the Mass Spectrometry Applications to the Clinical Laboratory Meeting (2011), San Diego, CA. 5. Co-organized and co-instructing a two day workshop on case studies in quantitative proteomics for the American Society for Mass Spectrometry in Denver, CO (2011) 6. Giving a lecture at the educational workshop on the promise and limitations of shotgun proteomics at the Human Proteome Organization meeting Geneva, (2011)

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. C. elegans has two sexes hermaphrodite(XX)and male(XO). Males only arise in the wild population at about 0.2% but hermaphrodites will use male sperm preferentially over their own sperm and some wild isolates use copulatory plugs to block sperm from other males.

DESCRIPTION (provided by applicant): The overall goal of this proposal is to improve the quality, reliability, and interlaboratory comparability of peptide mass spectrometry data. Mass spectrometry (MS) has become a fundamental technology for the identification and quantitative analysis of proteins, protein interactions, and protein post-translational modifications. These analyses are an important part of solving biological problems that involve changes in protein abundance in response to disease, drug treatment, and genetic or environmental perturbations. Unfortunately, the application of protein mass spectrometry measurements in the clinical laboratory has been limited. Unlike most clinical assays by mass spectrometry, which use microflow liquid chromatography, peptide measurements are commonly performed using a nanoflow liquid chromatograph interface to the mass spectrometer (nanoflow LC-MS). Despite their analytical power, these nanoflow LC-MS methods have been difficult to apply robustly in quantitative assays involving large numbers of samples from a challenging sample matrix. The successful completion of our project will result in a peptide analysis platform that can automatically assess problems with the nanoflow LC-MS system and correct the problem during an analytical run and will significantly improve the robustness and reproducibility of peptide mass spectrometry measurements.

Since its inception the Yeast Resource Center has specialized in extracting information about protein function from genome sequence. We began when the first eukaryotic genome was completed (budding yeast) and developed an array of technologies to decipher protein function from genome sequence. In this application, we make the natural progression towards understanding how protein variation affects protein levels, modification, function and structure. We propose to develop technologies in four areas: 1) To identify different protein variants or isoforms. 2) To quantify proteins by mass spectrometry with a focus on determining absolute levels of a protein. 3) To study how protein variation affects protein function. 4) To determine the structures of protein complexes not amenable to high-resolution methods such as x-ray crystallography and NMR.

CORE A: PROTEIN PHENOTYPES OF AGING - PROJECT SUMMARY/ABSTRACT It is now clear that genetics alone cannot explain the majority of the observed phenotypic traits and cellular response to perturbation. One of the fundamental questions in aging biology is to understand the complexity with which cellular systems respond to stimuli and stress. Proteins perform nearly all the work of the cell. It is therefore important to measure directly the effects of aging on the proteome itself, as opposed to an indirect molecular phenotype like the transcriptome. The direct analysis of proteins, their modifications, and their flux has the potential to greatly enhance our ability to identify and understand the functional pathways that underlie the biology of aging. A challenge to this task has been that the field of MS-based proteomics has long suffered from a reputation of difficulty in reproducing experimental measurements. This irreproducibility has been primarily due to the semi-stochastic way in which shotgun proteomics measurements have been made. To address these issues, the MacCoss lab has been at the forefront of developing technologies to perform large- scale targeted proteomics assays that generate near complete data matrices, accurate quantitation, and high reproducibility ? even across multiple laboratories. The primary goal of Core A is to apply these improved methods to studies of aging, to obtain accurate quantitative measurements of peptides from samples provided by its users, and to aid geroscience researchers in linking these high-dimensional data to biologically meaningful outcomes. In addition, the Core will develop and apply new assays especially suited to aging. This Core will work closely with Core B (Metabolite Phenotypes of Aging), which will share some of the same facilities, and with Core C (Invertebrate Longevity and Healthspan). The resources offered here include methods that can be applied to a wide range of non-model species, including humans. Core A will also play a key role in collaborative efforts between the University of Washington Nathan Shock Center (NSC) and other NSCs throughout the country. Core A will devote considerable resources to technology and software development, ensuring that we are constantly pushing the scientific boundaries in this field. The core will also serve as a central repository for aging-related mass spectrometry data using our cloud-based platform http://chorusproject.org. In the long term, Core A will help to make comprehensive, age-specific protein phenotypes an essential and invaluable component of any study of aging phenotypes. The core will impact on biogerontology at the broadest level, enabling our collaborators to identify new mechanistic pathways linking genes with aging, including pathways that have the potential to reveal new drugs to target aging. Moreover, these capabilities will lead to resources of value not just to collaborating Nathan Shock Centers but to others in the biogerontology community, and ultimately, to all researchers interested in the proteomic foundations of biomedically relevant problems.

Proteins carry out a vast range of critical activities including signaling, DNA replication, gene regulation, immune response, etc. Tandem mass spectrometry is the only high-throughput way to characterize these proteins in complex biological mixtures. This project will produce algorithms with the potential to dramatically improve the ability of proteomics scientists around the world to interpret their tandem mass spectrometry data, thereby providing critical insights into these fundamental biological processes. Because proteins are the primary functional molecules in the cell, such insights are foundational to our scientific understanding of life.

The key intellectual contributions in this proposal lie in the development of novel machine learning methods for proteomics. Specifically, the project will develop novel methods for spectrum feature extraction, including deep neural network autoencoding and low-dimensional representation learning, learning deep similarity metrics that allow efficient spatial data access methods, applications of autoencoding for spectrum and experiment compression, submodular summarization methods on proteomic data, and classification and ranking methodologies that take advantage of network effects via a data embedding. These tools will then be used for proteomic metadata inference, cloud-based peptide and protein identification, and retrieval and ranking of similar proteomic experiments. The research will hence yield a profoundly more powerful, data-driven approach to jointly interpreting massive mass spectrometry data sets, thereby giving scientists valuable new tools to glean insights into protein function.

? DESCRIPTION (provided by applicant): The last decade has seen an increase in the development and application of new proteomics technologies. These technologies are beginning to make a significant impact on our understanding of basic and clinical questions in cancer biology. However, in the 20 years that we have been able to take tandem mass spectrometry data of peptides and search it against a sequence database, the general strategy has remained largely the same. Basically, protein mixtures are digested to peptide mixtures, the mixture is analyzed by liquid chromatography-tandem mass spectrometry using data dependent acquisition (DDA), and these spectra are interpreted using database searching. Overtime, our field has refined our methods using this same general approach and when combined with improvements in mass spectrometry instrument hardware, the comprehensiveness and throughput of proteomics experiments has improved greatly. To continue to make an impact, we need to further improve the depth and throughput of our experiments. The ultimate and lofty goal being the detection and quantification of all peptides above the limit of detection across many samples. Peptide intensity measurements are currently not comparable between laboratories and platforms without calibration making each experiment an isolated event with little opportunity for labs to build on existing data. While we have made a lot of progress as a field, we need to continue to improve our methods and we need to alter our strategy now so that we can move further forward in the future. We are proposing the development of new data acquisition and analysis strategies that will improve the systematic analysis of large numbers of samples for large-scale molecular phenotyping. Specifically we plan to 1) improve the selectivity of data independent acquisition (DIA), 2) improve the reproducibility and sampling depth of DDA, and 3) change the analysis of the tandem mass spectrometry data from spectrum-centric to peptide-centric. It is necessary to continue to develop both DDA and DIA data acquisition strategies parallel and that with another few cycles of hardware improvements the two methods may ultimately converge. We will then demonstrate the use of these technologies to show that we can rapidly phenotype the cellular state in response to cancer therapeutics.

Since its inception the Yeast Resource Center has specialized in extracting information about protein function from genome sequence. We began when the first eukaryotic genome was completed (budding yeast) and developed an array of technologies to decipher protein function from genome sequence. In this application, we make the natural progression towards understanding how protein variation affects protein levels, modification, function and structure. We propose to develop technologies in four areas: 1) To identify different protein variants or isoforms. 2) To quantify proteins by mass spectrometry with a focus on determining absolute levels of a protein. 3) To study how protein variation affects protein function. 4) To determine the structures of protein complexes not amenable to high-resolution methods such as x-ray crystallography and NMR.

Since its inception the Yeast Resource Center has specialized in extracting information about protein function from genome sequence. We began when the first eukaryotic genome was completed (budding yeast) and developed an array of technologies to decipher protein function from genome sequence. In this application, we make the natural progression towards understanding how protein variation affects protein levels, modification, function and structure. We propose to develop technologies in four areas: 1) To identify different protein variants or isoforms. 2) To quantify proteins by mass spectrometry with a focus on determining absolute levels of a protein. 3) To study how protein variation affects protein function. 4) To determine the structures of protein complexes not amenable to high-resolution methods such as x-ray crystallography and NMR.

Since its inception the Yeast Resource Center has specialized in extracting information about protein function from genome sequence. We began when the first eukaryotic genome was completed (budding yeast) and developed an array of technologies to decipher protein function from genome sequence. In this application, we make the natural progression towards understanding how protein variation affects protein levels, modification, function and structure. We propose to develop technologies in four areas: 1) To identify different protein variants or isoforms. 2) To quantify proteins by mass spectrometry with a focus on determining absolute levels of a protein. 3) To study how protein variation affects protein function. 4) To determine the structures of protein complexes not amenable to high-resolution methods such as x-ray crystallography and NMR.

Since its inception the Yeast Resource Center has specialized in extracting information about protein function from genome sequence. We began when the first eukaryotic genome was completed (budding yeast) and developed an array of technologies to decipher protein function from genome sequence. In this application, we make the natural progression towards understanding how protein variation affects protein levels, modification, function and structure. We propose to develop technologies in four areas: 1) To identify different protein variants or isoforms. 2) To quantify proteins by mass spectrometry with a focus on determining absolute levels of a protein. 3) To study how protein variation affects protein function. 4) To determine the structures of protein complexes not amenable to high-resolution methods such as x-ray crystallography and NMR.

Since its inception the Yeast Resource Center has specialized in extracting information about protein function from genome sequence. We began when the first eukaryotic genome was completed (budding yeast) and developed an array of technologies to decipher protein function from genome sequence. In this application, we make the natural progression towards understanding how protein variation affects protein levels, modification, function and structure. We propose to develop technologies in four areas: 1) To identify different protein variants or isoforms. 2) To quantify proteins by mass spectrometry with a focus on determining absolute levels of a protein. 3) To study how protein variation affects protein function. 4) To determine the structures of protein complexes not amenable to high-resolution methods such as x-ray crystallography and NMR.

Since its inception the Yeast Resource Center has specialized in extracting information about protein function from genome sequence. We began when the first eukaryotic genome was completed (budding yeast) and developed an array of technologies to decipher protein function from genome sequence. In this application, we make the natural progression towards understanding how protein variation affects protein levels, modification, function and structure. We propose to develop technologies in four areas: 1) To identify different protein variants or isoforms. 2) To quantify proteins by mass spectrometry with a focus on determining absolute levels of a protein. 3) To study how protein variation affects protein function. 4) To determine the structures of protein complexes not amenable to high-resolution methods such as x-ray crystallography and NMR.

Project Summary The Administration of the Yeast Resource Center will build on strategies learned and used by the center over the last 20 years of funding in the successful management of a Biomedical Technology Research Resource. The greatest strength of our center is a highly experienced and diverse team of investigators that have worked together for a very long time. Our close and effective working relationship is evident by our long and productive resource. Our center is unique amongst the NIGMS Biotechnology Research Resources in that, unlike many other centers that focus on a single technology, our resource leverages an experimental system using many technologies to drive biomedical research. We will continue to use the administrative capabilities we have put in place over the last two decades to ensure an effective and functioning resource for the scientific community.

Project Summary The overall goal of the collaboration efforts of the Yeast Resource Center is to continue refining technologies developed within the center while simultaneously providing access to expertise and resources to the scientific community. Our resource has been an invaluable collaborative resource for the scientific community by making available advanced technologies developed by the center. In the last 5 years our Biomedical Technology Research Resource (BTRR) has had a total of 347 collaborations that are widely distributed throughout the United States. Collaborations differ from our Driving Biomedical Projects in that they don't require the development of new technologies but instead directly apply more established methods that make use of the expertise, instrumentation, software, and protocols facilitated by our resource. We have a history of openly supporting the scientific community by accepting collaborations that align with our expertise. A strength of a ?Yeast? resource center is that we have been a valuable resource and source of collaboration for the yeast scientific community. These collaborations have become an excellent opportunity in refining our established technologies. Once refined, methods often get extended to collaborations in experimental systems beyond yeast as the technology matures.

CORE C: MASS SPECTROMETRY ? PROJECT SUMMARY/ABSTRACT This Core will provide state of the art proteomics technologies and expertise to improve the understanding of the molecular changes in the mitochondria associated with aging and reversal of aging by SS peptides. The three research projects seek to understand the role of mitochondrial protective interventions on health and lifespan in mouse and rat models. Integral to the success of the program project grant is the measurement of changes in relative mitochondrial protein abundance and half-life in health, disease, and aging. To support the needs of the individual research projects, the Proteomics Core has three aims, each of which provides services in am important MS based technology: 1) The unbiased detection of differences in peptide/protein abundance between complex mixtures; 2) The targeted analysis of protein abundance for mitochondrial proteins of interest; 3) The global measurement of individual mitochondrial protein half-life; 4) Shotgun lipidomics of cardiolipin molecular species. These approaches span a range of broad and specific services that are tailored to optimal application by the Program Project investigators.  

Project Summary We have partnered with 10 outside laboratories from across the United States to form driving biomedical projects (DBPs) for our technology development efforts. These projects represent important and cutting edge research problems that cannot presently be solved with current technologies. The DBPs provide a quantifiable measure of our progress in our Technology Research and Development cores. These DBPs will provide an opportunity to demonstrate and refine our resource technologies. The DBPs are test-bed projects and require significant iterative back and forth between the TR&D personnel and the collaborating lab. Thus, each DBP was carefully selected based on a combination of the biological importance of the project, it providing a challenge to drive a specific TR&D, a working relationship of the collaborating laboratory with a co-investigator in the Yeast Resource Center, and willingness to work through failures of emerging technologies.

PROJECT SUMMARY/ABSTRACT The overarching goal of the Chorus project (http://chorusproject.org) is to advance biomedical research by extending our capabilities for the storage, dissemination, sharing, and analysis of the world's mass spectrometry data. To date, the mass spectrometry community has been storing their files in local ?silos? within the respective research laboratory. Each lab currently builds their own computational infrastructure for the analysis of their data. This process is inefficient and redundant. Mechanisms for labs to share and analyze data in a collaborative manner are almost non-existent. Furthermore, neither the vendor data formats, nor the established repositories make it feasible or efficiently to perform analyses between experiments and laboratories. We have developed a cloud infrastructure that facilitates the efficient storage, sharing, and visualization of mass spectrometry data across vendor platforms. We intend to build on this foundation for enabling the community to build tools to access and analyze individual datasets or the collective data as a whole. By bringing data into a shared cloud infrastructure, we improve the analyses that are possible, minimize the challenges with sharing large datasets, and reduce the overall costs. We will improve the value of all mass spectrometry data through standardization of tools, improved data accessibility, increased sharing, more efficient data access, and better communication. 1

Project Summary Training activities will be incorporated into the Yeast Resource Center at multiple levels. Many of these training components and resources are already in place within our resource. We intend to use this pre-existing and established infrastructure of training activities such as on-site short courses, workshops and short courses at scientific meetings, providing opportunities for visiting scientists to learn our methods with center personnel, on-line tutorials, use of the Center's web site for resource sharing and training in the use of the technology and tools developed. We will build on this infrastructure and a track record of offering comprehensive training opportunities to the scientific community.

Project Summary Biofilm formation has been linked to many chronic bacterial infections. Thus, significant research has been directed towards understanding the basic biology behind biofilm formation. Biofilms produce an extracellular matrix that functions, in part, to hold the community together. Pseudomonas aeruginosa represents a paradigm species for the study of biofilms in the laboratory. The regulation of matrix production and the carbohydrate component of the matrix have both been examined. However, the protein component of the biofilm matrix has been relatively understudied. Our groups identified a biofilm matrix protein for P. aeruginosa, CdrA. CdrA provides structural integrity through extracellular interactions with the matrix polysaccharide Psl. Outside of matrix proteins that provide structural functions, we predict that matrix associated proteins can play both nutritional and protective roles for the community. This project will initially focus on CdrA and its role in the matrix. We will then characterize ecotin a matrix bound protease inhibitor and three matrix-associated proteases. Finally, we will identify new matrix proteins that associate with eps component of the biofilm matrix.

Abstract The Administration of the U19 will build on strategies learned and used over the last 15 years of management of numerous interdisciplinary centers, program projects, consortia, and public/private research collaborations. The greatest strength of our interdisciplinary resource program is a highly experienced and diverse team of investigators who have worked together productively for a very long time. Our program is highly focused on the development and application of state-of-the-art technology. Our resource leverages a unique group of individuals who are in a strong position to bring these technologies forward into a series of deliverables to make a translational impact to monitor Alzheimer's disease progression and/or response to treatment. We will continue to use the administrative capabilities we have learned and put in place over the last 15 years to ensure an effective and functioning resource for the scientific community.

CORE C: PROTEIN PHENOTYPES OF AGING - PROJECT SUMMARY/ABSTRACT It is now clear that genetics alone cannot explain the majority of the observed phenotypic traits and cellular response to perturbation. One of the fundamental questions in aging biology is to understand the complexity with which cellular systems respond to stimuli and stress. Proteins perform nearly all the work of the cell. It is therefore important to measure directly the effects of aging on the proteome itself, as opposed to an indirect molecular phenotype like the transcriptome. The direct analysis of proteins, their modifications, and their flux has the potential to greatly enhance our ability to identify and understand the functional pathways that underlie the biology of aging. A challenge to this task has been that the field of MS-based proteomics has long suffered from a reputation of difficulty in reproducing experimental measurements. This irreproducibility has been primarily due to the semi-stochastic way in which shotgun proteomics measurements have been made. To address these issues, the MacCoss and Villen labs has been at the forefront of developing technologies to perform large-scale targeted proteomics assays that generate near complete data matrices, accurate quantitation, and high reproducibility ? even across multiple laboratories. The primary goal of Core C is to apply these improved methods to studies of aging, to obtain accurate quantitative measurements of peptides from samples provided by its users, and to aid geroscience researchers in linking these high-dimensional data to biologically meaningful outcomes. In addition, the Core will develop and apply new assays especially suited to aging. This Core will work closely with Core D (Metabolite Phenotypes of Aging), which will share some of the same facilities, and with Core E (Invertebrate Longevity and Healthspan) and Core F (Artificial Intelligence and Bioinformatics). The resources offered here include methods that can be applied to a wide range of species, including humans. Core C will also play a key role in collaborative efforts between the University of Washington Nathan Shock Center (NSC) and other NSCs throughout the country. Core C will devote considerable resources to technology and software development, ensuring that we are constantly pushing the scientific boundaries in this field. In the long term, Core C will help to make comprehensive, age-specific protein phenotypes an essential and invaluable component of any study of aging phenotypes. The core will impact on biogerontology at the broadest level, enabling our collaborators to identify new mechanistic pathways linking genes with aging, including pathways that have the potential to reveal new drugs to target aging. Moreover, these capabilities will lead to resources of value not just to collaborating Nathan Shock Centers but to others in the biogerontology community, and ultimately, to all researchers interested in the proteomic foundations of biomedically relevant problems.

Abstract Alzheimer's disease (AD) is a major, growing global public health problem. This is a daunting scientific challenge and solutions will come only from innovative research. We have brought together a unique interdisciplinary team of investigators with the goal of bridging the divide between state-of-the-art technologies and translational applications. To monitor AD disease progression or response to treatment, cerebrospinal fluid (CSF) represents the preferred fluid to reflect brain pathophysiology. The brain interstitial fluid is in direct contact with the CSF by unrestricted bidirectional flow of proteins and the CSF is protected from the peripheral system because of the ? restricted transportation of molecules and proteins by the blood-brain barrier. Known CSF biomarkers have been demonstrated to reflect the three main pathological changes that occur in the AD brain -- amyloid- deposition, neurofibrillary degeneration, and neuronal injury. Therefore, analysis of molecules and particles in CSF holds the greatest potential to improve our diagnosis and characterization of neurodegenerative diseases in vivo. We propose to enable precision medicine for AD by developing a cooperative research program that will unite a unique research team with the specific goal of vastly improving the molecular characterization of CSF as predictors of cognitive decline and AD pathophysiology. The efforts of this program will complement existing efforts to accelerate the identification and validation of clinically relevant therapeutic targets. We will work in parallel with programs like Accelerating Medicines Partnership (AMP) and the AD Centers Program, to provide unique diagnostic capabilities in support of the process of bringing new medicines to patients. Our U19 research program will consist of four projects and four cores that are synergistic to our mission. Moreover, our research team is uniquely suited to the development, validation and translational application of new biomolecular assays to reflect AD pathophysiology. This U19 will harness the collective expertise of multiple fields, combined with the financial resources sufficient to extend and apply next generation proteomics technologies to clinical specimens that have been extensively annotated with longitudinal, consensus clinical diagnostic and neuropsychological test data. We will create new assays with the goal of deployment to the clinical lab. We will create unique and sustainable reagents that will facilitate dissemination and deployment of these methods worldwide. Our program will expand existing infrastructure, developed by our labs, for sharing and disseminating these data and protocols. The application of new technologies, development of novel reagents, creation of new clinical assays, and dissemination of data and protocols will accelerate neuroscience in a way not feasible under traditional NIH mechanisms.

Abstract Despite the association between the levels of CSF A?42, tau, phosphorylated tau and underlying AD pathology, measures of biomarker accuracy for clinical diagnosis vary widely between studies. Given that other neurodegenerative conditions can present with AD-like clinical symptoms, and individuals with AD frequently have comorbid pathologies, additional markers are needed that can aid in differential diagnosis and identify mixed pathologies. Over the last decade, many candidate biomarkers have been identified, reflecting a range of pathophysiological processes including cholesterol metabolism, neuroinflammation and amyloid processing. However, few, have been adopted in clinical practice or been validated in large independent cohorts1. The MacCoss lab and others have been pioneering the development of next generation proteomics methods as an alternative to the classic stochastic mass spectrometry-based methods. These new methods offer a hybrid between a targeted and global proteomics strategy. While mass spectrometry data is collected in an unbiased way, the data is analyzed in a targeted strategy where specific peptides, albeit 1000s are analyzed using prior information. Thus, the reproducible targeting, throughput, and confident MS/MS-based quantification of parallel reaction monitoring (PRM) can be combined with classical discovery methods' ability to qualitatively detect thousands of proteins. These new methods based on systematically collected mass spectrometry data can offer similar quantitative figures of merit and can be validated in analogous fashion to clinical assays. Despite advances in proteomics technologies, most attempts at discovering new CSF markers have either used 1) stochastic sampling methods (e.g. data dependent acquisition) with poorly characterized quantitative performance, 2) small sample cohorts, 3) focused entirely on total CSF, 4) ignored protein processing, and 5) did not consider protein misfolding or stability. The purpose of this project within the cooperative research program is to take our methods to another level ? apply true quantitative methods to large well characterized cohorts and extend them to functionally relevant subpopulations. We have a CSF assay that can measure >1050 proteins from completely unfractionated material with figures of merit of within/between day precision, linearity, LOD/LOQ, etc... Furthermore, we can use this assay on subsets of the CSF proteome to assess functionally relevant aspects of the neurobiology including quantity as part of solution or CSF particles, intact protein MW, and protein stability. Finally, we have enough throughput to apply these analyses on a scale sufficient to eliminate the chance that an observation is due to an aberrant subpopulation.

Development on Skyline started in 2008 to fill a critical need for a software tool to enable targeted proteomics experiments. The development of Skyline grew into an entire ecosystem of tools and has since expanded beyond targeted proteomics. The Skyline software ecosystem is one of the most widely used software platforms in all of mass spectrometry. The current software and its thriving community create exciting new opportunities for quantitative mass spectrometry. As of June 2020, Skyline has been installed >110,000 times, has over 14,000 registered users on its website (http://skyline.ms) and is booted up >9,000 times per week (exceeding 17,500 bootups in a single week). The Skyline project has grown beyond the bounds of a single tool. There are now 16 Skyline external tools that rely on a formalized framework in Skyline, with more in development. Some of these tools have been installed >10,000 times. We have also created the Panorama Knowledgebase (http://panoramaweb.org) and Panorama Public, a platform where Skyline users can organize, share, and disseminate processed quantitative proteomics data. Furthermore, our lab is now the primary contributor to Chorus (http://chorusproject.org), a unique mass spectrometry file sharing resource. In this grant, we propose creating a resource that will enable the continued development and maintenance of these community tools and their dissemination within the community. These tools support >14,000 registered users in their basic science, pre-clinical, and translational research. Specifically, our proposal has four aims. 1) Expand our test infrastructure to improve the robustness, stress test the software, confirm compatibility across computer systems, and track performance over time. 2) Improve support for both proteomics and non- proteomics workflows. 3) Improve the collection, sharing, annotation and dissemination of mass spectrometry data and Skyline documents. 4) Provide continued support and training for the Skyline ecosystem.