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2021-10-20
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Skyline UGM Attendee Survey
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Event Information
Speakers
   Michael MacCoss
   Tania Auchynnikava
   Juan Chavez
   Eralp Dogu
   Shadi Eshghi
   Matt Foster
   Brendan MacLean
   Adam Officer
   Matt Rardin
   Michael Schirm
   Simone Sidoli
   Yang Zhang

Thanks!


The six annual Skyline User Group Meeting took us to Indianapolis, ID and our meeting location was on the 48th floor of the Salesforce.com Building.  With perfectly clear weather and 20-miles of visibility, the 360-degree view was simply breathtaking.  The meeting was held Sunday, June 4, before the 2017 ASMS conference and 150 attendees heard about the latest targeted proteomics and "omics" research approaches -- using Skyline and Panorama.  After a brief introduction by host Dr. Mike MacCoss, the event featured 11 speakers on a wide spectrum of ways that researchers were using Skyline to tackle innovative mass spectrometry projects.  Just like last year, the User Group Meeting also solicited presentation topics from the user base -- and the speakers were selected from culling through submitted abstracts.  The meeting featured full length (20 min.) presentations, as well as rapid-fire "lightning talks"  -- in which speakers had the unenviable task of culling down their current key research into a 5 minute speaking window.  Check out the recordings of the sessions below. We've also posted the presentation slides in the links below for your continued reference. 

Lastly, we'd like to give a heart-felt "thank you" to all of our speakers who prepared and gave up their pre-ASMS Sunday make the Skyline User Group Meeting an event not to be missed.  And to those who attended this year, we hope to see you all at a future Skyline User Group Meeting! 

 

Michael J. MacCoss, Ph.D. (University of Washington):
Introduction and event host

Matt Rardin Ph.D.(Amgen):
Improved Quality Control Workflows and Other Panorama Updates

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

Michael Schirm, Ph.D., (Caprion):
Analysis of Large Scale MRM Studies Using Skyline

Simone Sidoli, Ph.D., (University of Pennsylvania):
DIA for Differential Quantification of Isobaric Phosphopeptides and Other Protein Post-translational Modifications

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

Brendan MacLean, (MacCoss Lab, University of Washington):
Status of the Skyline open-source software project 9 years after its inception

Lightning Talks

Shadi Eshghi, Ph.D., (Genentech):
A Workflow for Quality Assessment, Quantitation and Statistical Inference of Targeted Proteomics Data using Skyline and Panorama

Matt Foster,  Ph.D., (Duke University):
A Targeted Proteomic Assay Quantifies the Periodic Expression of Cell-cycle Regulators in Yeast S. Cerevisae.

Tania Auchynnikava,  Ph.D., (University of Edenburgh):
Deciphering Mechanisms of Epigenetic Inheritance with MSX-DIA

Juan Chavez, Ph.D., (Univerity of Washington):
A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry

Yang Zhang,  Ph.D., (Amyris):
High Throughput Small Molecule Detection Using Automated Skyline Targeted Workflow




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Event Information


Welcome

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.  


--Brendan


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)

  • A favorite for weddings, D'Amore has stunning, endless views from the highest building in Indianapolis. The venue is located on the 48th floor of the Salesforce.com Building, about a 10-15 minute walk (.6 mile) northeast of the Indiana Convention Center.
  • From the Convention Center, head north on S. Capital Ave. Turn right on W. Market Street and turn left around the Soldiers and Sailors Monument until you reach Meridian Street. At the end of the block, turn right onto E. Ohio Street.
  • From the lobby of the Chase Building, only the center bank of elevators go all the way to the 48th floor.

[registration closed]
We have closed down our registration process but you can still attend! Please just come to D'Amore for "day of" registration.


Confirmed Speakers

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.
(More info...)

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.
(More info...)

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.
(More info...)

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.
(More info...)

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.
(More info...)

Lightning Talks

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.
(More info...)

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.
(More info...)

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.
(More info...)

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.
(More info...)

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.
(More info...)


Sponsors

Agilent TechnologiesBruker
ShimadzuThermo Scientific
WatersCambridge Isotope Laboratories
LabKey SoftwareSISCAPA Assay Technology



Speakers


Eleven speakers with interesting and different areas of expertise in Skyline use and development are scheduled to speak at the Skyline User Group Meeting at ASMS 2017 in Indianapolis, IN.

Tania Auchynnikava, Ph.D.

Juan Chavez, Ph.D.

Eralp Dogu, Ph.D.

Shadi Eshghi, Ph.D.

Matt Foster, Ph.D.

Brendan MacLean

Adam Officer

Matthew Rardin, Ph.D.

Michael Schirm, Ph.D.

Simone Sidoli, Ph.D.

Yang Zhang, Ph.D.




Michael MacCoss


Mike MacCoss Michael MacCoss Mike became interested in biomedical applications of mass spectrometry while working in Dr. Patrick Griffin’s protein mass spectrometry lab at Merck Research Laboratories. He obtained a Ph.D. with Professor Dwight Matthews and pursued a postdoc with Professor John R. Yates III. In 2004 he started the MacCoss lab at the University of Washington and it became obvious that while mass spectrometry data could be collected quickly and robustly, the lack of computational tools for the visualization and analysis of these data was a stumbling block. In 2008 he hired Brendan MacLean with the goal of developing professional quality software tools for quantitative proteomics. Read More
Mike has worked closely with the Skyline development team and our outstanding group of laboratory scientists and collaborators to ensure that our software uses analytical approaches that have been thoroughly vetted by the mass spectrometry community.


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Tania Auchynnikava


Tania Auchynnikava Tania Auchynnikava Ph.D. received her PhD in Edinburgh in RNA processing field. For post-doc work, she joined the lab of renowned epigenetic expert R.Allshire (Edinburgh) to perform large scale MS-based screens in collaboration with J. Rappsilber.; 

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. Here we utilized affinity purification of minichromosome-associated heterochromatin regions Read More
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.



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Juan Chavez


Juan Chavez Juan Chavez Ph.D.  is currently a Research Scientist in Jim Bruce’s laboratory at the University of Washington. His research is focused on the development and application of in vivo chemical cross-linking and mass spectrometry technology to study protein structures and interactions in cells. He obtained a Ph.D. in Analytical Chemistry from Oregon State University and a B.S. in Chemistry from the University of New Mexico. Read More

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.



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Eralp Dogu


Eralp Dogu Eralp Dogu Ph.D. is an assistant professor of statistics in the College of Science at Mugla Sitki Kocman University (Turkey). He holds a B.S. degree in Statistics, a M.S. degree in Statistics, and a Ph.D. in Statistics from Dokuz Eylul University (Turkey). He joined Marcus Department of Industrial and Manufacturing Engineering at Penn State as a visiting scientist in 2009. He also conducted research at the Center for Integrated Healthcare Delivery Systems (CHIDS) as a CHIDS scholar during 2009-2010.  Read More

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.



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Shadi Eshghi


Shadi Eshghi Shadi Eshghi Ph.D. is an associate scientist in the biomarker development department at Genentech. Her work currently focuses on development of bioinformatics tools and techniques to facilitate analysis and interpretation of targeted mass spectrometry data. Prior to joining Genentech, Shadi worked in Dr. Hui Zhang’s group at Johns Hopkins University on development of novel computational and experimental methods for exploring the glycome and glycoproteome using mass spectrometry.   Read More
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.



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Matt Foster


Matt Foster Matt Foster Ph.D. is an Assistant Professor in the Division of Pulmonary, Allergy and Critical Care Medicine at Duke University and is also on the staff of the Duke Proteomics and Metabolomics Shared Resource. His formal training is in the areas of bioinorganic chemistry and nitric oxide biology. Read More
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.



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Brendan MacLean


Brendan MacLean Brendan MacLean worked at Microsoft for 8 years in the 1990s where he was a lead developer and development manager for the Visual C++/Developer Studio Project.  Since leaving Microsoft, Brendan has been the Vice President of Engineering for Westside Corporation, Director of Engineering for BEA Systems, Inc., Sr. Software Engineer at the Fred Hutchinson Cancer Research Center, and a founding partner of LabKey Software.  In this last position he was one of the key programmers responsible for the Computational Proteomics Analysis System (CPAS), made significant contributions to the development of X!Tandem and the Trans Proteomic Pipeline, and created the LabKey Enterprise Pipeline.   Read More
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


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Adam Officer


Adam Officer Adam Officer is currently a Research Associate at the Broad Institute of MIT and Harvard in the Proteomics Platform working under Dr. Jacob Jaffe. His research is based around the Library of Integrated Network-Based Cellular Signatures Program and aims to apply high-throughput proteomics to create a database of targeted proteomics signatures to ask questions that deepen our understanding of disease biology and inform clinical treatments. Read More
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.



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Matt Rardin


Matthew Rardin Matthew Rardin Ph.D., is currently a scientist in the Discovery Attribute Sciences group at Amgen where he develops discovery and quantitative proteomic workflows to understand mechanism of action, pre-clinical biomarker discovery, and target engagement. Originally from Colorado, he received a B.S. in Microbiology at Colorado State University followed by graduate studies in Jack Dixon’s group at UCSD on the role of reversible phosphorylation signaling in mitochondria. Read More
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.



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Michael Schirm


Michael Schirm Michael Schirm Ph.D., is the Associate Director of the Mass Spectrometry group at Caprion Biosciences. Michael received his Ph.D. in Chemistry at the University of Montreal under the supervision of Prof. Pierre Thibault. His research focused on the detection and characterization of protein glycosylation in bacterial systems.   Read More
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.



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Simone Sidoli


Simone Sidoli Simone Sidoli  Ph.D. works in the laboratory directed by Prof. Garcia (University of Pennsylvania), where we focus on the analysis of histone PTMs using mass spectrometry. Since several histone peptides have isobaric forms, a central part of our work consists in accurately discriminating their abundance using the profiles of selected fragment ions. Read More
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.



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Yang Zhang


Yang Zhang Yang Zhang, Ph.D. is a Bioinformatics scientist in the Scientific Computing group at Amyris, a synthetic biology and renewable chemicals company based in the San Francisco Bay Area. He obtained a Ph.D. in Bioinformatics from New Mexico State University with a minor in statistics. Read More
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.



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