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1.  Data Management, Analysis, Standardization and Reproducibility in a ProteoRed Multicentric Quantitative Proteomics Study with the OmicsHub Proteomics Software Tool 
RP-47
The ProteoRed multicentric experiment was designed to test each laboratory abilities to perform quantitative proteomic analysis, compare methodologies and inter-lab reproducibility for relative quantitative analysis of proteomes and to evaluate data reporting and data sharing tools (MIAPE documents, standard formats, public repositories). The experiment consist in analyzing two different samples (A and B), which contain an identical matrix of E. Coli proteins plus four standard proteins (CYC_HORSE, MYG_HORSE, ALDOA_RABIT, BSA_BOVIN), spiked in different amounts. The samples are designed primarily to be analyzed by LC-MS, although DIGE analysis could be also possible. Each lab will have the choice to test their preferred method for quantitative comparison of the two samples. However, to set as much standardization and reproducibility as possible in terms of data analysis, data sharing, protocols information, results and reporting we propose the OmicsHub Proteomics server to be the single platform to integrate the protein identification steps of the MS multicentric experiment and serve as a web repository. After the “In-lab” analysis is performed, with the laboratory's own tools, every lab is able to load its experiment (protocols, parameters, instruments, etc.) and import its spectrum data via web into the OmicsHub Proteomics analysis and managment server. Every experiment in OmicsHub is automatically stored following the PRIDE standard format. The OmicsHub Proteomics software tool performs the workflow tasks of Protein identification (using the search engines Mascot and Phenyx), Protein annotation, Protein grouping, FDR filtering (allowing the use of a local decoy database, designed ad hoc for this experiment) and Reporting of the protein identification results in a systematic and centralized manner. The OmicsHub Proteomics allows the researchers at ProteoRed consortium to perform its multicentric study with full reproducibility, standardization and experiment comparison; reducing time and data management complexity prior to the final quantification analysis.
PMCID: PMC2918095
2.  Multi-Site Assessment of ProteoRed Plasma Reference Sample for Benchmarking LC-MS Platform Performance 
One of the missions of the Spanish Proteomics Network (ProteoRed ISCIII) is to assist its proteomics core facilities in evaluating their capabilities to perform qualitative and quantitative proteomics analysis. In 2010, the ProteoRed's Sample Collection and Handling Group designed a moderately complex plasma standard reference sample primarily to be used for routine quality assurance monitoring of laboratory instrumentation, as well as inter-laboratory performance assessment, and development and validation of novel technologies. The ProteoRed Plasma Reference (PPR) sample is a subset of highly abundant well-characterized human plasma proteins with a number of isoforms, in addition to 4 spiked-in proteins, altogether distributed over 5 orders of magnitude in concentration. The PPR sample was recently stress tested in the latest ProteoRed Multicenter Experiment (PME6) that counted with the participation of 17 proteomics facilities using a wide range of LC-MS platforms. Although each laboratory was allowed to use its own favorite methodology, we requested the sample be analyzed in a single LC-MS run in experimental triplicate (3 different digestions).Evaluation of the results submitted by the study participants revealed moderate discrepancies at the peptide identification level, and poor overlap at the protein identification level. In an attempt to identify the source of such irreproducibility, raw data of 8 laboratories (24 LC-MS runs) were reanalyzed centrally using a standardized data analysis pipeline, which included protein inference using ProteinProphet software. We found that the majority of protein identification discrepancies across submitted reports of these 8 laboratories were due to inconsistencies on how data analysts and computational tools group and/or infer proteins. Immunoglobulin variable chain identifications were particularly conflicting throughout identification lists, even in the centralized analysis. Using a series of LC-MS performance metrics, we benchmarked the performance of 8 LC-MS instruments (Orbitraps) and identified system components that vary the most across laboratories.
PMCID: PMC3186592
3.  A Multi-Laboratory Study Assessing Robustness and Reproducibility of Plasma Reference Sample for Benchmarking LC-MS Platform Performance 
An increasingly common request for proteomics core facilities is determining qualitative and quantitative differences among clinical samples such as plasma, CSF, or urine. One of the missions of the Spanish Network of Proteomics Facilities (ProteoRed-ISCIII) is to assist its proteomics core facilities in evaluating their capabilities to perform qualitative and quantitative proteomics analysis. This year, in an attempt to represent a realistic experiment scenario that might be requested to a proteomics core facility, we provided a moderately complex plasma standard reference sample to be used for routine QC monitoring of laboratory instrumentation. The ProteoRed Plasma Reference (PPR) sample is a subset of highly abundant well-characterized human plasma proteins with a number of isoforms, in addition to 4 spiked-in proteins, altogether distributed over 5 orders of magnitude in concentration. The PPR sample was recently stress tested in the latest ProteoRed Multicenter Experiment (PME6) that counted with the participation of 17 proteomics facilities using a wide range of LC-MS platforms. We requested the sample be analyzed in a single LC-MS run in experimental triplicate (3 different digestions). Evaluation of the results submitted by the study participants revealed moderate discrepancies at the peptide identification level, and poor overlap at the protein identification level. In an attempt to identify the source of such irreproducibility, raw data of 8 laboratories (24 LC-MS runs) were reanalyzed centrally using a standardized data analysis pipeline, which included protein inference using ProteinProphet software. We found that the majority of protein identification discrepancies across submitted reports of these 8 laboratories were due to inconsistencies on how data analysis and computational tools group and/or infer proteins. Immunoglobulin variable chain identifications were particularly conflicting throughout identification lists, even in the centralized analysis. Using a series of LC-MS performance metrics, we benchmarked the performance of 8 LC-MS instruments (Orbitraps) and identified system components that vary the most across laboratories.
PMCID: PMC3186614
4.  ProteoRed Multicenter Experiment for Long-term Quality Control Evaluation of Proteomics Core Facilities 
Quality control (QC) is becoming increasingly important in proteomic experiments in order to guarantee the quality of research results. Deployment of QC metrics helps in monitoring stability, overall performance and reproducibility of analytical techniques. In an attempt to dispel some of the notions that LC-MS-based proteomics is poorly reproducible, the proteomics community has demonstrated increasingly concerns about the quality of proteomics data made publicly available. Here we describe the ProteoRed Multicenter Experiment for Quality Control (PMEQC), a longitudinal QC multicenter study involving 12 institutions, to assess the repeatability of LC-MS/MS proteomics data within a specific site, the reproducibility across multiple sites and across multiple platforms. Our experimental design also provided a unique opportunity to assess the repeatability of protein sample preparation within a specific site.
The main study was divided into 2 sub studies (Study A and B) that evaluate separately inter- and intra-laboratory variability. Each participant received two sample vials of trypsin-digested yeast proteins (Study A) and the same undigested protein sample (Study B). All participants were requested to follow a strict LC-MS/MS guideline for sample injection amounts and LC gradient. To enable inter-laboratory comparisons, data analysis was centralized and performed under standard procedures using a common workflow that includes well-known software tools for proteomics analysis such as msconvert.exe, X!Tandem, PeptideProphet, OpenMS and R programming language.
Here, we summarize the key findings of the PMEQC project and provide technical insights to better understand and pinpoint the main sources of variability and other issues faced by proteomics core facilities. Our study reveals that the overall performance regarding reproducibility, sensitivity, dynamic range, among other metrics, is directly related to laboratory staff expertise, and less dependent on instrumentation. Furthermore, the present study provides a rich data set of metrics against which other laboratories can benchmark their performance.
PMCID: PMC3630681
5.  A DIGE study on the effects of salbutamol on the rat muscle proteome - an exemplar of best practice for data sharing in proteomics 
BMC Research Notes  2011;4:86.
Background
Proteomic techniques allow researchers to perform detailed analyses of cellular states and many studies are published each year, which highlight large numbers of proteins quantified in different samples. However, currently few data sets make it into public databases with sufficient metadata to allow other groups to verify findings, perform data mining or integrate different data sets. The Proteomics Standards Initiative has released a series of "Minimum Information About a Proteomics Experiment" guideline documents (MIAPE modules) and accompanying data exchange formats. This article focuses on proteomic studies based on gel electrophoresis and demonstrates how the corresponding MIAPE modules can be fulfilled and data deposited in public databases, using a new experimental data set as an example.
Findings
We have performed a study of the effects of an anabolic agent (salbutamol) at two different time points on the protein complement of rat skeletal muscle cells, quantified by difference gel electrophoresis. In the DIGE study, a total of 31 non-redundant proteins were identified as being potentially modulated at 24 h post treatment and 110 non redundant proteins at 96 h post-treatment. Several categories of function have been highlighted as strongly enriched, providing candidate proteins for further study. We also use the study as an example of best practice for data deposition.
Conclusions
We have deposited all data sets from this study in public databases for further analysis by the community. We also describe more generally how gel-based protein identification data sets can now be deposited in the PRoteomics IDEntifications database (PRIDE), using a new software tool, the PRIDESpotMapper, which we developed to work in conjunction with the PRIDE Converter application. We also demonstrate how the ProteoRed MIAPE generator tool can be used to create and share a complete and compliant set of MIAPE reports for this experiment and others.
doi:10.1186/1756-0500-4-86
PMCID: PMC3080311  PMID: 21443781
6.  ABRF Affiliates and Chapters 
The mission of the ABRF is to advance life sciences core facilities and biotechnology laboratories through research, communication, and education. To facilitate this mission, the ABRF has implemented ABRF Affiliates and Chapters and the ABRF Affiliates and Chapters Committee for the following purposes: a) To encourage the establishment, support the operations, and facilitate the coordination of new regional and special interest groups that have goals related to those of the ABRF in support of life sciences shared resources; b) To establish partnerships and collaborate with other existing organizations that have goals related to those of the ABRF in support of life sciences shared resources; c) To promote the technologies, research support and administration of biomolecular resource facilities; d) To promote the development and applications of biotechnologies as shared research resources and to facilitate the advancement of life sciences research; e) To play a leadership role in networking core laboratories, researchers, and students, matching those with similar and complementary interests and skills; e) To enhance communication on the regional, national and international level regarding ABRF activities; to enhance the visibility of the ABRF in the scientific community; to educate the scientific community about the value of the ABRF; and to broaden the number and diversity of core laboratories and biotechnology laboratories that take advantage of the ABRF research group studies and ABRF membership networking opportunities; and f) To enhance the visibility of the ABRF with funding agencies that support the development, acquisition and application of core facility shared research resources. ABRF Chapters are special interest groups which may be formed based on common interests and/or geographical boundaries and support grassroots networks of individuals who wish to help advance ABRF goals and promote the mission of shared resource facilities and biomolecular resources. ABRF Affiliates are special interest organizations that are autonomous from the ABRF, have common and complementary interests with the ABRF, and have the goal of developing a collaborative relationship with the ABRF. Please join us for the ABRF Affiliates and Chapters Open Mic Session from 6:00 pm to 6:45 pm on Sunday.
PMCID: PMC3186469
7.  Mass Spectrometry Data Collection in Parallel at Multiple Core Facilities Operating TripleTOF 5600 and Orbitrap Elite/Velos Pro/Q Exactive Mass Spectrometers 
Proteomic research can benefit from simultaneous access to multiple cutting-edge mass spectrometers. 18 core facilities responded to our investigators seeking service through the ABRF Discussion Forum. Five of the facilities selected completed four plasma proteomics experiments as routine fee-for-service. Each biological experiment entailed an iTRAQ 4-plex proteome comparison of immunodepleted plasma provided as 30 labeled-peptide fractions. Identical samples were analyzed by two AB SCIEX TripleTOF 5600 and three Thermo Orbitrap (Elite/Velos Pro/Q Exactive) instruments. 480 LC-MS/MS runs delivered >250 GB of data over two months.
We compare herein routine service analyses of three peptide fractions of different peptide abundance. Data files from each instrument were studied to develop optimal analysis parameters to compare with default parameters in Mascot Distiller 2.4, ProteinPilot 4.5 beta, AB Sciex MS Data Converter 1.3 beta, and Proteome Discover 1.3. Peak-picking for TripleTOFs was best by ProteinPilot 4.5 beta while Mascot Distiller and Proteome Discoverer were comparable for the Orbitraps.
We compared protein identification and quantitation in SwissProt 2012_07 database by Mascot Server 2.4.01 versus ProteinPilot. By all search methods, more proteins, up to two fold, were identified using the Q Exactive than others. Q Exactive excelled also at the number of unique significant peptide ion sequences. However, software-dependent impact on subsequent interpretation, due to peptide modifications, can be critical. These findings may have special implications for iTRAQ plasma proteomics. For the low abundance peptide ions, the slope of the dynamic range drop-off in the plasma proteome is uniquely sharp compared with cell lysates. Our study provides data for testable improvements in the operation of these mass spectrometers. More importantly, we have demonstrated a new affordable expedient workflow for investigators to perform proteomic experiments through the ABRF infrastructure. (We acknowledge John Cottrell for optimizing the peak-picking parameters for Mascot Distiller).
PMCID: PMC3635246
8.  ABRF-sPRG 2013 Study: Development and Characterization of a Proteomics Normalization Standard Consisting of 1000 Stable Isotope Labeled Peptides and a Qualitative Stability Study of Peptides from the ABRF-sPRG 2012 Study 
The Proteomics Standards Research Group (sPRG) is reporting the first year progress in a two-year sPRG 2012-2013 study which focuses on the generation of a standard that can be used for interassay, interspecies, and interlaboratory normalization in both label-free and stable isotope label-based quantitative proteomics analysis. The standard has been formulated as two mixtures: 1000 stable isotope 13C/15N-labeled synthetic tryptic peptides alone, and peptides mixed with a tryptic digest from a HEK 293 cell lysate. The sequences of the synthetic peptides were derived from approximately 400 proteins and were conserved across proteomes of the most commonly analyzed species: Homo sapiens, Mus musculus and Rattus norvegicus. The selected peptides represent the full range of hydrophobicities and isoelectric points typical to tryptic peptides from complex proteomic samples. The standard was designed to represent proteins of various concentrations, spanning three orders of magnitude. This year we focused our efforts on selection of appropriate protein and peptide candidates, peptide synthesis, quality assessment and LC-MS evaluation by several sPRG member laboratories. The sPRG study design and initial results of a thorough characterization of the standard using a variety of instrumental configurations and bioinformatics approaches will be presented in this talk.
The sPRG is hopeful that the designed formulation will become a valuable resource in various mass spectrometry-based proteomic applications, including quantitative and differential profiling, as well as general benchmarking (e.g. chromatographic retention time). The sPRG plans to start recruiting study participants in April 2013, complete the study by the end of the year 2013, and present the results at the ABRF 2014 meeting. The sPRG encourages proteomics laboratories to participate in the study and sign in at www.abrf.org/sprg.
The second half of the session will discuss the qualitative stability study performed using purified synthetic peptides containing a variety of modifications selected from the 2012 sPRG ABRF sample. The stability of the selected synthetic peptides was evaluated by the sPRG using different storage conditions over a three-month period. After storage at either at room temperature, +4°C or −80°C for one week, one month, or three months. Quantitative LC-MS/MS analysis was used to monitor the stability and degradation of the peptides, and to determine the effect of modifications and storage conditions on peptide degradation rates. The data presented have been built on the quantitative study that was presented at both the 2012 ABRF and ASMS conferences. All forms of degraded peptides were separated and identified using nano-LC tandem mass spectrometry on a Thermo Scientific Q-Exactive hybrid mass spectrometer. Integrated extracted ion chromatograms were used to measure relative amounts of degradation to identify which pathways are most prevalent during storage.
PMCID: PMC3635292
9.  [No title available] 
The Proteomics Standards Research Group (sPRG) is reporting the first year progress in a two-year sPRG 2012–2013 study which focuses on the generation of a standard that can be used for interassay, interspecies, and interlaboratory normalization in both label-free and stable isotope label-based quantitative proteomics analysis. The standard has been formulated as two mixtures: 1000 stable isotope 13C/15N-labeled synthetic tryptic peptides alone, and peptides mixed with a tryptic digest from a HEK 293 cell lysate. The sequences of the synthetic peptides were derived from approximately 400 proteins and were conserved across proteomes of the most commonly analyzed species: Homo sapiens, Mus musculus and Rattus norvegicus. The selected peptides represent the full range of hydrophobicities and isoelectric points typical to tryptic peptides from complex proteomic samples. The standard was designed to represent proteins of various concentrations, spanning three orders of magnitude. This year we focused our efforts on selection of appropriate protein and peptide candidates, peptide synthesis, quality assessment and LC-MS evaluation by several sPRG member laboratories. The sPRG study design and initial results of a thorough characterization of the standard using a variety of instrumental configurations and bioinformatics approaches will be presented in this talk.
The sPRG is hopeful that the designed formulation will become a valuable resource in various mass spectrometry-based proteomic applications, including quantitative and differential profiling, as well as general benchmarking (e.g. chromatographic retention time). The sPRG plans to start recruiting study participants in April 2013, complete the study by the end of the year 2013, and present the results at the ABRF 2014 meeting. The sPRG encourages proteomics laboratories to participate in the study and sign in at www.abrf.org/sprg.
The second half of the session will discuss the qualitative stability study performed using purified synthetic peptides containing a variety of modifications selected from the 2012 sPRG ABRF sample. The stability of the selected synthetic peptides was evaluated by the sPRG using different storage conditions over a three-month period. After storage at either at room temperature, +4°C or -80°C for one week, one month, or three months. Quantitative LC-MS/MS analysis was used to monitor the stability and degradation of the peptides, and to determine the effect of modifications and storage conditions on peptide degradation rates. The data presented have been built on the quantitative study that was presented at both the 2012 ABRF and ASMS conferences. All forms of degraded peptides were separated and identified using nano-LC tandem mass spectrometry on a Thermo Scientific Q-Exactive hybrid mass spectrometer. Integrated extracted ion chromatograms were used to measure relative amounts of degradation to identify which pathways are most prevalent during storage.
PMCID: PMC3635369
10.  Label-free Differential Proteomics Using a Combination of MS Profiling and Targeted MS/MS 
RP-105
Differential proteomic analysis is an essential tool in the effort to elucidate the biochemical mechanisms that underlie phenotypes in mouse models of human diseases. There are many methods for differential proteomic analysis of complex samples, such as mouse tissue lysates, including two dimensional gel electrophoresis, iTRAQ and label-free methods. The Association for Biomolecular Resource Facilities proteomic research group study from 2007 (ABRF PRG07) evaluated multiple laboratories and methodologies for performing differential proteomics. Overall, label-free mass spectrometry (MS)-based methodologies were the most sensitive and most accurate for identifying and quantifying differentially expressed/spiked proteins. In an effort to evaluate a label-free method for (MS) based differential proteomic analysis, a combination of MS profiling and targeted MS/MS experiments have been used to identify tryptic peptides derived three proteins that were differentially spiked into the Sigma Proteomics Dynamic Range Standard Set (UPS2). LC/MS analyses were done on a microfluidic-based nanoflow LC coupled to a quadrupole time-of-flight (Q-TOF) mass spectrometer. The MS profiling data was processed using differential analysis software. Features that were differentially-spiked were subjected to targeted MS/MS and the peptides were identified using database search software. Our results illustrate the effectiveness of this approach, as all three unknown differentially-spiked proteins were successfully identified and quantitated. Beyond the QTOF itself, this study demonstrates the importance of both reproducible high resolution HPLC and appropriate software as being critical components of the described label-free method.
PMCID: PMC2918089
11.  [No title available] 
The goals of the ABRF Next Generation Sequencing (ABRF-NGS) study are to evaluate the performance of all available NGS platforms and to identify optimal methods and best practices across sites. The study is a coordinated effort of five ABRF Research Groups, involving over 20 core facility laboratories. The ABRF-NGS study currently includes the Illumina HiSeq, Roche 454, Life Technologies Ion Torrent PGM and Pacific Biosciences PacBio RS platforms. The first phase of the study is focused on transcriptome analysis using RNA reference samples from the Microarray Quality Control (MAQC) study together with spike-in controls developed by the External RNA Controls Consortium (ERCC). The aim of this first phase is to assess sequencing accuracy, absolute and relative expression levels, and differential expression detection. The ABRF-NGS study is not intended to be a “bake-off” but rather is an effort to establish a reference data set for each platform to help sites improve their methods. Future phases of the study will include evaluation of results with degraded RNA and DNA, microRNA profiling, DNA and RNA sequencing of a HapMap trio, and DNA sequencing of reference sets of samples with well defined “difficult-to-sequence” regions. The long-term goals of the ABRF-NGS study are to optimize the detection of genetic variation with the latest sequencing tools and to establish a community resource for self-evaluation and self-improvement that will allow users of next generation sequencing technologies to readily compare their own performance data as instruments and protocols change. This is a key feature of an evaluation resource given the rapid pace of development of NGS technologies. This session will present the ABRF-NGS project design and participants and the current status of data collection and analysis.
PMCID: PMC3630658
12.  A Multi-Centric Study To Assess Reproducibility of Protein Quantification By SRM LC-MS Proteomic Analysis 
In order to evaluate the robustness and reproducibility, within and across laboratories, of the SRM quantification methodology, we set up a multi-centric study (PME7) carried out at 9 laboratories, most of them members of the ProteoRed-ISCIII network of proteomics facilities in Spain.
Each participant laboratory received identical samples of a “Quantitative Proteomics Sample Set” prepared by Sigma-Aldrich. The sample set consisted of 5 different samples A-E, containing tryptic digests of 9 human proteins, spiked in different amounts to a yeast lysate digest. The amounts of these proteins are distributed in three different concentration “Tiers”: Tier 1: 3 protein digests in the range 25-2500 fmol / microgram of yeast lysate; Tier 2: 3 protein digests in the range 2.5- 1250 fmol / microgram of yeast lysate; Tier 3: 3 protein digests in the range 0.25-25 fmol / microgram of yeast lysate. In addition, each sample contains identical amount (250 fmol) of a tenth protein digest, for normalization purposes. Finally, two different labeled AQUA peptides per protein were added to each sample in defined amounts.
The five samples were analyzed in triplicate by SRM at the different laboratories, using similar, but not strictly identical, chromatographic and spectrometric conditions, and with different instruments. Each laboratory reported results on relative quantification (fold changes between A-E samples) and absolute quantification based on the AQUA peptide standards.
The results demonstrate a good degree of reproducibility of targeted quantification measurements by SRM at different laboratories, irrespective of the method of analysis and the spectrometer used. The average %CV of the measured absolute protein amounts ranges from less than 10% for Tier 1 proteins, to 40-60% for the proteins at the lowest concentrations.
The results obtained at each laboratory allow the assessment of the limitations in sensitivity and limits of quantification under the diverse analytical conditions used.
PMCID: PMC3630565
13.  PRG-2011: Defining the Interaction between Users and Suppliers of Proteomics Services 
Over the last ten years the Proteomics Research Group (PRG) has undertaken technical studies that have covered a wide range of issues unique to the rapidly developing field of proteomics and have included a range of qualitative and quantitative experiments. The PRG studies have resulted in a great deal of attention not only within the ABRF community but also outside as is evident from numerous articles dealing with proteomics methods, procedures and standardization. As the field continues to develop, the diversity of instrumentation and laboratory workflows have grown in tandem. Therefore, in the PRG2011 study it seemed especially useful to perform a survey to help the PRG define future studies based on the current blend of sample types and technologies and obtain a view of emerging trends. A survey was created to ascertain three main insights into core facility function: 1) How labs interact with their clients, 2) The capacity of labs to meet the demands of their clients, and 3) The blend of experimental techniques offered to and requested by clients. Survey questions were designed to obtain information from both users of core facilities and the directors and personnel of core facilities. Questions covered such topics as the type and age of instruments in use, how data is analyzed and presented to client, sources of funding, and emerging proteomics trends. Results are compiled en masse and presented without regard to institution. Early results reveal that about 2/3 of the responders are not ABRF members, and at least one lab still has an operational mass spectrometer that was acquired in 1990!
PMCID: PMC3186496
14.  Help Us Help You! The Cytometry Interest Research Group Bridging the Gap Between Sample Purification and Downstream Applications 
Cytometry is a critical tool applied throughout life sciences research. For example, the ability to identify and isolate cells with desired characteristics is required for subsequent analysis using downstream applications such as proteomics and DNA sequencing. Most research institutions have a shared cytometry resource facility within their organization. Recently, a group of cytometrists affiliated with the Association of Biomolecular Research Facilities (ABRF) have come together to discuss the formation of a new research group (RG) within ABRF. Unlike other organizations, such as the International Society for the Advancement of Cytometry (ISAC) which focuces on technology issues related to flow cytometry, our goal is to create a group that serves as a bridge between cytometry and other RG's such as proteomics, nucleic acids, and light microscopy. Some examples of important areas to be explored include: filling in the gaps between the transfer of samples from cytometry to other cores, creating synergistic relationships between cores and enhancing overall data output. This can be accomplished by creating a deeper relationship with other RGs to determine specific areas that need improvement within the sample processing pipeline. Pilot/validation studies can be created to pinpoint and resolve these issues. As institutional research core facilities become more centralized, there is an added value when cores cooperate with each other to streamline the processing pipeline, and optimize results with the least amount of material. The Cytometry RG organizing committee is interested in your input and would like other RG group members to share their ideas with us to help shape this group. Preparative cytometry is a hub from which many other cores acquire their samples and our ultimate goal is to create better service, samples and data for end users.
PMCID: PMC3630556
15.  Absolute quantification of microbial proteomes at different states by directed mass spectrometry 
The developed, directed mass spectrometry workflow allows to generate consistent and system-wide quantitative maps of microbial proteomes in a single analysis. Application to the human pathogen L. interrogans revealed mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense, and new insights about the regulation of absolute protein abundances within operons.
The developed, directed proteomic approach allowed consistent detection and absolute quantification of 1680 proteins of the human pathogen L. interrogans in a single LC–MS/MS experiment.The comparison of 25 extensive, consistent and quantitative proteome maps revealed new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans, and about the regulation of protein abundances within operons.The generated time-resolved data sets are compatible with pattern analysis algorithms developed for transcriptomics, including hierarchical clustering and functional enrichment analysis of the detected profile clusters.This is the first study that describes the absolute quantitative behavior of any proteome over multiple states and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
Over the last decade, mass spectrometry (MS)-based proteomics has evolved as the method of choice for system-wide proteome studies and now allows for the characterization of several thousands of proteins in a single sample. Despite these great advances, redundant monitoring of protein levels over large sample numbers in a high-throughput manner remains a challenging task. New directed MS strategies have shown to overcome some of the current limitations, thereby enabling the acquisition of consistent and system-wide data sets of proteomes with low-to-moderate complexity at high throughput.
In this study, we applied this integrated, two-stage MS strategy to investigate global proteome changes in the human pathogen L. interrogans. In the initial discovery phase, 1680 proteins (out of around 3600 gene products) could be identified (Schmidt et al, 2008) and, by focusing precious MS-sequencing time on the most dominant, specific peptides per protein, all proteins could be accurately and consistently monitored over 25 different samples within a few days of instrument time in the following scoring phase (Figure 1). Additionally, the co-analysis of heavy reference peptides enabled us to obtain absolute protein concentration estimates for all identified proteins in each perturbation (Malmström et al, 2009). The detected proteins did not show any biases against functional groups or protein classes, including membrane proteins, and span an abundance range of more than three orders of magnitude, a range that is expected to cover most of the L. interrogans proteome (Malmström et al, 2009).
To elucidate mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense of L. interrogans, we generated time-resolved proteome maps of cells perturbed with serum and three different antibiotics at sublethal concentrations that are currently used to treat Leptospirosis. This yielded an information-rich proteomic data set that describes, for the first time, the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date. Using this unique property of the data set, we could quantify protein components of entire pathways across several time points and subject the data sets to cluster analysis, a tool that was previously limited to the transcript level due to incomplete sampling on protein level (Figure 4). Based on these analyses, we could demonstrate that Leptospira cells adjust the cellular abundance of a certain subset of proteins and pathways as a general response to stress while other parts of the proteome respond highly specific. The cells furthermore react to individual treatments by ‘fine tuning' the abundance of certain proteins and pathways in order to cope with the specific cause of stress. Intriguingly, the most specific and significant expression changes were observed for proteins involved in motility, tissue penetration and virulence after serum treatment where we tried to simulate the host environment. While many of the detected protein changes demonstrate good agreement with available transcriptomics data, most proteins showed a poor correlation. This includes potential virulence factors, like Loa22 or OmpL1, with confirmed expression in vivo that were significantly up-regulated on the protein level, but not on the mRNA level, strengthening the importance of proteomic studies. The high resolution and coverage of the proteome data set enabled us to further investigate protein abundance changes of co-regulated genes within operons. This suggests that although most proteins within an operon respond to regulation synchronously, bacterial cells seem to have subtle means to adjust the levels of individual proteins or protein groups outside of the general trend, a phenomena that was recently also observed on the transcript level of other bacteria (Güell et al, 2009).
The method can be implemented with standard high-resolution mass spectrometers and software tools that are readily available in the majority of proteomics laboratories. It is scalable to any proteome of low-to-medium complexity and can be extended to post-translational modifications or peptide-labeling strategies for quantification. We therefore expect the approach outlined here to become a cornerstone for microbial systems biology.
Over the past decade, liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) has evolved into the main proteome discovery technology. Up to several thousand proteins can now be reliably identified from a sample and the relative abundance of the identified proteins can be determined across samples. However, the remeasurement of substantially similar proteomes, for example those generated by perturbation experiments in systems biology, at high reproducibility and throughput remains challenging. Here, we apply a directed MS strategy to detect and quantify sets of pre-determined peptides in tryptic digests of cells of the human pathogen Leptospira interrogans at 25 different states. We show that in a single LC–MS/MS experiment around 5000 peptides, covering 1680 L. interrogans proteins, can be consistently detected and their absolute expression levels estimated, revealing new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans. This is the first study that describes the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
doi:10.1038/msb.2011.37
PMCID: PMC3159967  PMID: 21772258
absolute quantification; directed mass spectrometry; Leptospira interrogans; microbiology; proteomics
16.  P5-M Proteinscape—Software Platform for Managing Proteomics Data 
Proteomics inherently deals with huge amounts of data. Current mass spectrometers acquire hundreds of thousands of spectra within a single project. Thus, data management and data analysis are a challenge. We have developed a software platform (Proteinscape) that stores all relevant proteomics data efficiently and allows fast access and correlation analysis within proteomics projects.
The software is based on a relational database system using Web-based server-client architecture with intra- and Internet access.
Proteinscape stores relevant data from all steps of proteomics projects—study design, sample treatment, separation techniques (e.g., gel electrophoresis or liquid chromatography), protein digestion, mass spectrometry, and protein database search results. Gel spot data can be imported directly from several 2DE-gel image analysis software packages as well as spot-picking robots. Spectra (MS and MS/MS) are imported automatically during acquisition from MALDI and ESI mass spectrometers.
Many algorithms for automated spectra and search result processing are integrated. PMF spectra are calibrated and filtered for contaminant and polymer peaks (Score-booster). A single non-redundant protein list—containing only proteins that can be distinguished by the MS/MS data—can be generated from MS/MS search results (ProteinExtractor). This algorithm can combine data from different search algorithms or different experiments (MALDI/ESI, or acquisition repetitions) into a single protein list.
Navigation within the database is possible either by using the hierarchy of project, sample, protein/peptide separation, spectrum, and identification results, or by using a gel viewer plug-in. Available features include zooming, annotations (protein, spot name, etc.), export of the annotated image, and links to spot, spectrum, and protein data.
Proteinscape includes sophisticated query tools that allow data retrieval for typical questions in proteome projects. Here we present the benefit and power of usage of 6 years of continuous use of the software in over 70 proteome projects managed in house.
PMCID: PMC2291826
17.  PRODIS: a proteomics data management system with support to experiment tracking 
BMC Genomics  2011;12(Suppl 4):S15.
Background
A research area that has greatly benefited from the development of new and improved analysis technologies is Proteomics and large amounts of data have been generated by proteomic analysis as a consequence. Previously, the storage, management and analysis of these data have been done manually. This is, however, incompatible with the volume of data generated by modern proteomic analysis. Several attempts have been made to automate the tasks of data analysis and management. In this work we propose PRODIS (Proteomics Database Integrated System), a system for proteomic experimental data management. The proposed system enables an efficient management of the proteomic experimentation workflow, simplifies controlling experiments and associated data and establishes links between similar experiments through the experiment tracking function.
Results
PRODIS is fully web based which simplifies data upload and gives the system the flexibility necessary for use in complex projects. Data from Liquid Chromatography, 2D-PAGE and Mass Spectrometry experiments can be stored in the system. Moreover, it is simple to use, researchers can insert experimental data directly as experiments are performed, without the need to configure the system or change their experiment routine. PRODIS has a number of important features, including a password protected system in which each screen for data upload and retrieval is validated; users have different levels of clearance, which allow the execution of tasks according to the user clearance level. The system allows the upload, parsing of files, storage and display of experiment results and images in the main formats used in proteomics laboratories: for chromatographies the chromatograms and lists of peaks resulting from separation are stored; For 2D-PAGE images of gels and the files resulting from the analysis are stored, containing information on positions of spots as well as its values of intensity, volume, etc; For Mass Spectrometry, PRODIS presents a function for completion of the mapping plate that allows the user to correlate the positions in plates to the samples separated by 2D-PAGE. Furthermore PRODIS allows the tracking of experiments from the first stage until the final step of identification, enabling an efficient management of the complete experimental process.
Conclusions
The construction of data management systems for Proteomics data importing and storing is a relevant subject. PRODIS is a system complementary to other proteomics tools that combines a powerful storage engine (the relational database) and a friendly access interface, aiming to assist Proteomics research directly at data handling and storage.
doi:10.1186/1471-2164-12-S4-S15
PMCID: PMC3287584  PMID: 22369043
18.  The Establishment and Growth of the Vermont Genetics Network Proteomics Facility 
CF-18
The Vermont Genetics Network (VGN) Proteomics Facility supports biological and biomedical research primarily throughout Vermont, but also welcomes sample submission from investigators outside of Vermont. The facility uses state-of-the-art mass spectrometry for analyzing proteins and peptides. Facility personnel acquire and analyze proteomic data and conduct training in proteomic methods and experimental design. Pre-submission and post-data acquisition consultations are arranged with facility directors. Details can be found at www.uvm.edu/∼vgn/proteomics. The facility is led by Co-Directors Dr. Bryan Ballif and Dr. Dwight Matthews. Facility manager, Dr. Bin Deng interacts with investigators and runs proteomics analyses. Dr. Jim Vincent, VGN Bioinformatics Core director, provides bioinformatics support and Dr. Janet Murray coordinates the outreach to Vermont Baccalaureate Partner Institutions. The Proteomics Facility has three mass spectrometers each coupled to nanoflow high performance liquid chromatography (nano-HPLC). The mass spectrometers are two Thermo-Finnigan LTQ linear quadrupole ion trap mass spectrometers and one Thermo-Finnigan LTQ-Orbitrap hybrid mass spectrometer. Since last year over 2000 samples have been analyzed, twelve peer-reviewed papers have been published and 17 grant proposals have been supported by the proteomics facility. The user base for the proteomics facility is growing and includes over 34 faculty/post doctorate/staff, 28 graduate students and 7 undergraduates. At least 11 seminars and 11 poster presentations have been presented by users/staff that have presented VGN proteomic data. It is an exciting time for proteomics in Vermont. The facility is funded by the VGN through NIH grant P20 RR16462 from the INBRE Program of the National Center for Research Resources.
PMCID: PMC2918110
19.  ABRF Research Group Development and Characterization of a Proteomics Normalization Standard Consisting of 1,000 Stable Isotope Labeled Peptides 
The ABRF Proteomics Standards Research Group (sPRG) is reporting the progress of a two-year study (2012–2014) which focuses on the generation of interassay, interspecies, and interlaboratory peptide standard that can be used for normalization of protein abundance measurements in mass spectrometry based quantitative proteomics analyses. The standard has been formulated as two mixtures: 1,000 stable isotope 13C/15N-labeled (SIL) synthetic peptides alone, and peptides mixed with a tryptic digest of a HEK 293 cell lysate. The sequences of the synthetic peptides were derived from 552 proteins conserved across proteomes of commonly analyzed species: Homo sapiens, Mus musculus and Rattus norvegicus. The selected peptides represent a full range of hydrophobicities and isoelectric points, typical of tryptic peptides derived from complex proteomic samples. The standard was designed to represent proteins of various concentrations, spanning three orders of magnitude. First year efforts were focused on selection of appropriate protein and peptide candidates, peptide synthesis, quality assessment and LC-MS/MS evaluation conducted in laboratories of sPRG members. Using a variety of instrumental configurations and bioinformatics approaches, a thorough characterization of all 1,000 peptides was established. In the second year, the group launched the study to the entire proteomics community. A lyophilized mixture of HEK 293 tryptic digest cell lysate spiked with the 1,000 SIL peptide standards was provided to each participant. Also provided were a Skyline tutorial, tutorial datasets, three MS/MS spectral libraries generated from linear ion-trap (CID), Q-TOF/QQQ (CID), or Orbitrap (HCD) instrumentation, and a Panorama data repository. Participants were asked to analyze the sample in triplicate and calculate ratios of the spiked SIL to endogenous peptides and coefficients of variance for each peptide. Over 40 datasets were returned, and results following thorough characterization of the standard using various instrumental configurations will be reported.
PMCID: PMC4162257
20.  PRG-2011: Defining the Interaction Between Users and Suppliers of Proteomics Services/Facilities 
Over the last ten years the Proteomics Research Group (PRG) has undertaken technical studies that have covered a wide range of issues unique to the rapidly developing field of proteomics. These studies have included a range of qualitative and quantitative experiments. The PRG studies have resulted in a great deal of attention not only within the ABRF community but also outside as is evident from numerous articles dealing with proteomics methods, procedures and standardization. As the field continues to develop, the diversity of instrumentation and laboratory workflows have grown in tandem. Therefore, for the PRG2011 study it seemed especially useful to perform a survey to help define future studies based on the current blend of sample types and technologies and obtain a view of emerging trends. A survey was created to ascertain three main insights into core facility function: 1) How labs interact with their clients, 2) The capacity of labs to meet the demands of their clients, and 3) The blend of experimental techniques offered to and requested by clients. Survey questions were designed to obtain information from both users of core facilities and the directors and personnel of core facilities. Questions covered such topics as the type and age of instruments in use, how data is analyzed and presented to client, sources of funding, and emerging proteomics trends. Results are compiled en masse and presented without regard to institution.
PMCID: PMC3186500
21.  Combining Search Engines for Comparative Proteomics 
Many proteomics laboratories have found spectral counting to be an ideal way to recognize biomarkers that differentiate cohorts of samples. This approach assumes that proteins that differ in quantity between samples will generate different numbers of identifiable tandem mass spectra. Increasingly, researchers are employing multiple search engines to maximize the identifications generated from data collections. This talk evaluates four strategies to combine information from multiple search engines in comparative proteomics. The “Count Sum” model pools the spectra across search engines. The “Vote Counting” model combines the judgments from each search engine by protein. Two other models employ parametric and non-parametric analyses of protein-specific p-values from different search engines. We evaluated the four strategies in two different data sets. The ABRF iPRG 2009 study generated five LC-MS/MS analyses of “red” E. coli and five analyses of “yellow” E. coli. NCI CPTAC Study 6 generated five concentrations of Sigma UPS1 spiked into a yeast background. All data were identified with X!Tandem, Sequest, MyriMatch, and TagRecon. For both sample types, “Vote Counting” appeared to manage the diverse identification sets most effectively, yielding heightened discrimination as more search engines were added.
PMCID: PMC3630557
22.  (s9) Proteomics Standardization 
The needs and issues related to establishing inter-laboratory standardization in quantitative proteomics will be highlighted by presentations from three international initiatives. By establishing the need for standardization, each group will also highlight the tremendous amount of instrument and experimental variation that is also measured when trying to determine real biological changes. The Spanish-based ProteoRed consortium addresses multiple proteomics platforms, ranging from MS-based to gel-based. The NIH CPTAC network is focused on MS-based studies, and the UK-based FixingProteomics initiative covers mostly gel-based methods. Results from these studies will demonstrate complement and overlap in technology and approaches used between these groups, all motivated by the universal goal of standardizing these complex technologies across laboratories.
PMCID: PMC3186634
23.  ABRF-PRG03: Phosphorylation Site Determination 
A fundamental aspect of proteomics is the analysis of post-translational modifications, of which phosphorylation is an important class. Numerous nonradioactivity-based methods have been described for high-sensitivity phosphorylation site mapping. The ABRF Proteomics Research Group has conducted a study to help determine how many laboratories are equipped to take on such projects, which methods they choose to apply, and how successful the laboratories are in implementing particular methodologies. The ABRF-PRG03 sample was distributed as a tryptic digest of a mixture of two proteins with two synthetic phosphopeptides added. Each sample contained 5 pmol of unphosphorylated protein digest, 1 pmol of each phosphopeptide from the same protein, and 200 fmol of a minor protein component. Study participants were challenged to identify the two proteins and the two phosphorylated peptides, and determine the site of phosphorylation in each peptide. Almost all respondents successfully identified the major protein component, whereas only 10% identified the minor protein component. Phosphorylation site analysis proved surprisingly difficult, with only 3 of the 54 laboratories correctly determining both sites of phosphorylation. Various strategies and instruments were applied to this task with mixed success; chromatographic separation of the peptides was clearly helpful, whereas enrichment by metal affinity chromatography met with surprisingly little success. We conclude that locating sites of phosphorylation remains a significant challenge at this level of sample abundance.
PMCID: PMC2279948  PMID: 13678151
proteomics; phosphorylation; mass spectrometry; IMAC; post-translational modification
24.  ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining 
BMC Bioinformatics  2008;9(Suppl 9):S5.
Background
New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed.
Results
We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges according to associated data values. We demonstrated the advantages of these new capabilities through three biological network visualization case studies: human disease association network, drug-target interaction network and protein-peptide mapping network.
Conclusion
The architectural design of ProteoLens makes it suitable for bioinformatics expert data analysts who are experienced with relational database management to perform large-scale integrated network visual explorations. ProteoLens is a promising visual analytic platform that will facilitate knowledge discoveries in future network and systems biology studies.
doi:10.1186/1471-2105-9-S9-S5
PMCID: PMC2537576  PMID: 18793469
25.  The Drosophila melanogaster PeptideAtlas facilitates the use of peptide data for improved fly proteomics and genome annotation 
BMC Bioinformatics  2009;10:59.
Background
Crucial foundations of any quantitative systems biology experiment are correct genome and proteome annotations. Protein databases compiled from high quality empirical protein identifications that are in turn based on correct gene models increase the correctness, sensitivity, and quantitative accuracy of systems biology genome-scale experiments.
Results
In this manuscript, we present the Drosophila melanogaster PeptideAtlas, a fly proteomics and genomics resource of unsurpassed depth. Based on peptide mass spectrometry data collected in our laboratory the portal allows querying fly protein data observed with respect to gene model confirmation and splice site verification as well as for the identification of proteotypic peptides suited for targeted proteomics studies. Additionally, the database provides consensus mass spectra for observed peptides along with qualitative and quantitative information about the number of observations of a particular peptide and the sample(s) in which it was observed.
Conclusion
PeptideAtlas is an open access database for the Drosophila community that has several features and applications that support (1) reduction of the complexity inherently associated with performing targeted proteomic studies, (2) designing and accelerating shotgun proteomics experiments, (3) confirming or questioning gene models, and (4) adjusting gene models such that they are in line with observed Drosophila peptides. While the database consists of proteomic data it is not required that the user is a proteomics expert.
doi:10.1186/1471-2105-10-59
PMCID: PMC2648944  PMID: 19210778

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