The Skyline Team is pleased to announce the Sixth Annual Skyline User Group Meeting, which will be held in Indianapolis, IN on Sunday afternoon before ASMS. We would like to thank the event sponsors (see below) for their generosity and interest in collaborating with the Skyline project on exciting new targeted and quantitative proteomics techniques.
When: Sunday, June 4, 2017
12:00 - 1:00 pm : Lunch served
1:00 - 2:30 pm : Presentations
2:30 - 3:00 pm : Snacks and break-out discussions
3:00 - 4:30 pm : Presentations
Where: D'Amore (http://www.damoreindy.com), 1 East Ohio Street, Suite 4800 (Chase Building), Indianapolis, IN 46204 (map)
We have closed down our registration process but you can still attend! Please just come to D'Amore for "day of" registration.
Michael J. MacCoss, Ph.D. (University of Washington): Introduction and event host
Brendan MacLean, (MacCoss Lab, University of Washington): 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. (More info...)
Eralp Dogu, Ph.D., (Mugla Sitki Kocman University): 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. This presentation will cover the functionalities of MSstatsQC, how it can be used to monitor data quality in targeted proteomic experiments, and its implementation into Panorama AutoQC.
Adam Officer, (Broad Institute): 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. We have developed a workflow that utilizes Skyline, Panorama, and online visualization tools to address these issues.
Matthew Rardin, Ph.D., (Amgen): 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.
Michael Schirm, Ph.D., (Caprion): Analysis of Large Scale MRM Studies Using Skyline
This presentation will focus on the development of a high-throughput peak integration MRM 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.
Simone Sidoli, Ph.D., (University of Pennsylvania): 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 and histone peptide analysis many modified peptides are erroneously quantified using both approaches, because they have isobaric forms that cannot be discriminated when co-eluting by liquid chromatography.
Tania Auchynnikava, Ph.D., (University of Edenburgh): Deciphering Mechanisms of Epigenetic Inheritance with MSX-DIA
Deciphering mechanisms of epigenetic inheritance of repressed loci and cross-talk between epigenetic factors (histone PTMs, RNAi) is important for understanding of mechanisms of stable heterochromatin propagation through generations. HIn our study we utilized affinity purification of minichromosome-associated heterochromatin regions from Schizosaccharomyces pombe and MSX-DIA-based workflow for histone PTMs analysis.
Juan Chavez, Ph.D., (Univerity of Washington): A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry
This talk describes 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.
Shadi Eshghi, Ph.D., (Genentech):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. Using a diverse set of tools such as R programming, we are developing a customized 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.
Matt Foster, Ph.D., (Duke University): A Targeted Proteomic Assay Quantifies the Periodic Expression of Cell-cycle Regulators in Yeast S. Cerevisae.
We use 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.
Yang Zhang, Ph.D., (Amyris): 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. Based on Skyline Runner, 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.