from Schizosaccharomyces pombe and MSX-DIA-based workflow for histone PTMs analysis with Skyline. Such workflow expands repertoire of quantified histone PTMs including rare co-occurring modifications which cannot be quantified using conventional antibody-based methodologies. We demonstrate that our heterochromatin preparations were enriched in repressive H3K9me2/3 as expected. Additionally we observe H3K9me2/3K14ac and H3K9me2/3S10ph suggesting that fraction of H3K9me2/3 co-exists with marks associated with open chromatin structures. We quantified histone PTMs associated with chromatin regions isolated mutant backgrounds derived by different routes, and demonstrate quantitative differences on histone PTMs level which are dependent on prior exposure to H3K9me2/3 suggesting epigenetic memory mechanism. Further results are going to be discussed.

A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry

Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs utilizing parallel reaction monitoring (PRM) methods. Skyline was adapted for the analysis of quantitative XL-MS data and as a means for sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study. A PRM transition calculator for cross-linked peptides has been integrated into XLinkDB (http://xlinkdb.gs.washington.edu/xlinkdb/), an online database for the storage and analysis of XL-MS data, to easily generate transition lists for import into Skyline. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions.

In 2014, he joined the Healthcare Systems Engineering (HSyE) Institute at Northeastern University as a postdoctoral fellow. In 2015, Eralp joined the Olga Vitek lab for Statistical Methods for Studies of Biomolecular Systems at Northeastern University, where he developed MSstatsQC, an R based software to analyze system suitability for proteomic experiments, as a postdoctoral fellow.

MSstatsQC: An R-based Tool to Monitor System Suitability and Quality Control Results for Targeted Proteomic Experiments

MSstatsQC is an open-source R-based software package and a web-based graphical user interface for monitoring data quality of targeted experiments. It helps user to monitor (i) longitudinal system suitability testing (SST) results which verify that mass spectrometric instrumentation performs as specified and (ii) quality control (QC) results which provides in-process quality assurance of the sample profile. MSstatsQC is available as a stand-alone tool from www.msstats.org/msstatsqc. It is compatible with Skyline custom reports and additionally, its functionalities are available to the users as part of Panorama AutoQC. MSstatsQC translates modern methods of longitudinal statistical monitoring, such as simultaneous and time weighted control charts and change point analysis, to the context of LC-MS experiments, discusses their advantages, and provides practical guidelines for overall decision making. In this presentation the functionalities of MSstatsQC, how it can be used to monitor data quality in targeted proteomic experiments, and its implementation into Panorama AutoQC are discussed.

Her research led to development of GPQuest, a spectral library matching algorithm and accompanying application for identification of intact glycopeptides in complex biological matrices using LC-MS/MS. Shadi obtained a Ph.D. in biomedical engineering from Johns Hopkins University and a B.Sc. in electrical engineering.

A Workflow for Quality Assessment, Quantitation and Statistical Inference of Targeted Proteomics Data using Skyline and Panorama

Skyline and Panorama are integral parts of our data analysis and management system for targeted mass spectrometry experiments. Implemented as a module on the Labkey Server bioinformatics platform, Panorama enables integration of a diverse set of tools such as R programming to create customized workflows. Taking advantage of this feature, we are developing a workflow for post-processing of targeted mass spectrometry Skyline files on the Panorama server. This workflow combines built-in Panorama features with custom R packages (e.g. TargetedMSQC and MSstats) to perform quality control, quantitation and statistical inference. These tests can be performed on Skyline files within Panorama to create a comprehensive and sharable report. This workflow will provide an efficient means for high-throughput analysis of targeted mass spectrometry data, and enable sharing of not only files and final results, but also the processing steps required to generate reports, thus bringing more transparency to the data processing pipeline.

He has a keen interest in the application of discovery-based and targeted proteomics to both clinical and basic science research problems. 

A Targeted Proteomic Assay Quantifies the Periodic Expression of Cell-cycle Regulators in Yeast S. Cerevisae.

Analysis of yeast mRNA has identified a cell cycle-regulated network of transcription factors (TFs) that control periodic gene expression. However, it has not been possible to readily quantify the protein expression of these TFs. Here, we used Skyline to develop, optimize and deploy a parallel reaction monitoring (PRM) assay for over 40 low abundance TFs, including several that have not previously been identified by mass spectrometry. Analysis of synchronized wild-type yeast S. cerevisiae, sampled over ~2 cell cycles (20 time points per replicate), confirmed the periodic protein expression of numerous TFs that was highly correlated with mRNA expression. In cyclin-deficient yeast, the cell cycle-dependent proteasomal degradation of many, but not all, TFs was abrogated. These data help to establish a model of (post)-transcriptional regulation of cell cycle-regulated yeast TFs and more generally highlight the utility of targeted proteomic assays for high resolution temporal profiling of protein expression. Skyline addition: In my research (and the work that I do with the Duke Proteomics and Metabolomics Shared Resource), Skyline is an essential tool for targeted proteomics, for assessing longitudinal system suitability, and for tracking system performance during acquisition of large unbiased proteomics datasets. I also use Skyline, to a lesser extent, for label-free MS1 and MS2/DIA quantitation and metabolomics. I will highlight how Skyline was used for assay development in order to insure that we achieved maximum sensitivity for detection of a large set of very low abundance peptides while still maintaining sufficient points across the peak for quantitation. I will discuss our experience with manual peak/transition picking versus automation of these steps in Skyline. Finally, I will use Skyline to highlight a few aspects of this work that could be improved upon for future large-scale studies.

For the last 8 and a half years he has worked as a Sr. Software Engineer within the MacCoss lab and lead all aspects of design, development and support in creating the Skyline Targeted Proteomics Environment and its growing worldwide user community.

Status of the Skyline open-source software project 9 years after its inception

The Skyline project started just after ASMS 2008 as a 2-year effort to bring better SRM/MRM software tools to the NCI-CPTAC Verification Working Group that could support the variety of mass spectrometers in use in participating laboratories. Nearly 9 years later, the Skyline project is a thriving proteomics community open-source collaboration supporting 6 mass spec instrument vendors, integrated with a wide variety of external software, with thousands of users worldwide and many thousands of instances started each week. In this presentation, the Skyline principal developer will present recent developments and a roadmap for the project's future. Topics covered will include:

• Advances in DIA workflow support
• Growing support for targeting small molecules in Skyline
• Calibrated (a.k.a. Absolute) quantification with Skyline
• Growth in the Skyline software ecosystem for targeted MS (Skyline, Panorama, Chorus and External Tools)
• Strong industry support from instrument vendors
• Courses, workshops, webinars and other efforts to create instructional resources for the Skyline community

He completed his BS in Chemistry and Biochemistry at the University of Washington while performing research on protein engineering for synthetic biology applications at Arzeda Corporation. 

Skyline Metadata Annotation and Automation of Robust Data Processing via Panorama Allows for Facile Analysis of High Throughput Targeted Proteomics Data

Dissemination of targeted proteomics data via Skyline has recently been bolstered by the introduction of Panorama as a ready to use web sharing portal. However, there are still several challenges faced by end-users: discovery and reusability of these data is hampered by inconsistent or incomplete metadata annotation, a lack of reproducible data processing pipelines lead to errant findings, and a dearth of visualization tools further raises the barrier to consuming data. Under the auspices of the Library of Integrated Network-Based Cellular Signatures (LINCS) Program we have developed a workflow that utilizes Skyline, Panorama, and online visualization tools to address these three issues. Firstly, we attach standards-based, human-readable Skyline metadata annotations that fully describe our diverse biological samples. Upon publication to Panorama our scripts hosted on the LabKey server read embedded metadata processing parameters from each file and execute our pipeline resulting in reproducibly analyzed data in a standardized format. Deeper analysis and interactivity occurs through a direct data transfer from the Panorama portal into the web-based visualization software Morpheus. Currently our LINCS repository contains over 4000 samples and has a user community of >1500 unique visitors from all over the world.

For his postdoctoral studies, Matt joined Brad Gibson’s group where he focused on developing quantitative proteomic techniques to understand the regulation of lysine acylation by sirtuins and their role in metabolic function.

Rapid Identification of Contaminants and Interferences Using Skyline

Proper sample preparation in proteomic workflows is essential to the success of modern mass spectrometry experiments. Complex workflows often require reagents which are incompatible with MS analysis (e.g. detergents) necessitating a variety of sample cleanup methods. Efforts to understand and mitigate sample contamination are a continual source of distraction with respect to both time and resources. To improve the ability to rapidly assess sample contamination from a diverse array of sources, we developed a molecular library in Skyline for rapid extraction of contaminant precursor signals using MS1 Filtering. This contaminant template library is easily managed and can be modified for a diverse array of mass spectrometry sample preparation workflows. Utilization of this template allows the assessment of sample integrity and indicates potential sources of contamination.

In 2005, Michael joined the MS group at Caprion where Michaels’ research interests include the development of robust and reproducible workflows for the quantification of peptides and proteins in various matrices, and the development of novel proteomics methods to solve challenging analytical problems for clients.

Analysis of Large Scale MRM Studies Using Skyline

Multiple Reaction Monitoring (MRM) is routinely used for protein biomarker qualification, verification and validation in large clinical cohorts. A typical study may include the monitoring of several hundreds of peptides across hundreds or thousands of plasma/serum samples. Peak integration of these large scale data sets is both very challenging and time consuming, due to the need for manual inspection and correction of incorrectly integrated peaks. This presentation will focus on the development of a high-throughput peak integration workflow for the analysis of large-scale proteomics datasets using Skyline and in-house developed tools. Datasets containing several hundreds of thousands of peaks can be integrated and QC’d within 2 days with a minimal amount of manual inspection. This same workflow is also used for the automatic monitoring of instrument performance (sensitivity, RT reproducibility and peak width of target peptides) during the analysis of the study samples.

We frequently use Skyline to retrieve fragment ion profiles, and now we developed templates to analyze more than 200 known histone modifications and protein phosphorylation in general. We believe we are taking advantage of a feature of Skyline that is currently unexploited by proteomics labs in general. We would like to show that critical insights are missed when isobaric forms are not considered. 

DIA for Differential Quantification of Isobaric Phosphopeptides and Other Protein Post-translational Modifications

State-of-the-art quantification in proteomics is performed by extracting the precursor ion chromatogram of identified peptides. When using data independent acquisition (DIA) the profiles of the fragment ions can also be used to increase quantification confidence, or sometimes in alternative to the precursor ion signal. We recently demonstrated that in both phosphoproteomics (PubMedID: 27301801) and histone peptide analysis (PubMedID: 26505526) many modified peptides are erroneously quantified using both approaches, because they have isobaric forms that cannot be discriminated when co-eluting by liquid chromatography. These peptides have the same mass, but modifications on different residues. We thus developed templates that use DIA data and the Skyline (v3.6) output to assign the correct intensity on co-eluting isobaric modified peptides. These templates select unique fragment ions to determine the relative ratio of such peptides. This approach is imperative for samples where isobaric forms are common, i.e. histone peptides, for proper biological interpretation.

His current work is focused on supporting metabolomics and proteomics data storage and analysis. 

High Throughput Small Molecule Detection Using Automated Skyline Targeted Workflow

The DARPA-funded milligrams-to-kilograms (M2K) program at Amyris aims to biosynthetically produce 450 molecules starting at mg scale, and eventually produce 10 molecules at kg scale within a 4 year time frame, in a number of microbial hosts. This mission will be impossible without the aid of high throughput metabolomics and proteomics measurements on microbial strains. Previously, manual LC/MS data processing required multiple manual operations. Based on skylinerunner, the command line version of Skyline, we created customized scripts that reduced the processing time by at least a 100-fold, enabling the processing of thousands of samples per day with minimal human intervention. With no compromise in accuracy, the optimized workflow improves efficiency, freeing lab personnel to focus on experiment design or robust data acquisition.