Table of Contents

guest
2024-12-08
Thanks!
Event Information
Speakers
   Michael MacCoss
   Brendan MacLean
   Abigail Burrows
   Ellen Casavant
   Jeroen Demmers
   Gunnar Dittmar
   Tom Lin
   Philip Remes
   Julia Robbins
   Eduard Sabido
   Ariana Shannon
   Gary Siuzdak
   Stoyan Stoychev

Thanks!


Thanks to everyone who joined us in Houston for the Skyline User Group Meeting before ASMS 2023. It was great to meet with all of you passion Skyline users and share the tremendous opportunity to hear terrific and varied presentations about recent work enabled by Skyline software!

Below are links to the speakers' pages with options to view their slides or watch their presentations. At the bottom of this page, you will also find some photos from the event.

Thanks especially to all the wonderful speakers who volunteered their time and effort to share great presentations ranging from Skyline workflows to the lemons-to-lemonade experience of a destroyed science lab, and much more!

We hope these presentations long outlast the event itself, as previous years have.

Thank you! -- Brendan MacLean and Mike MacCoss, Event hosts


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 15 years after its inception [video]
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 15 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...)

Abigail Burrows Franco Ph.D., (University of Kentucky): Efficient generation of highly multiplexed serum biomarker panels using gas phase fractionation and DIA libraries [video]
Data Independent Acquisition (DIA) methods have become an attractive alternative to traditional Data Dependent Acquisition (DDA) methods for quantitative proteomics and biomarker identification. Here, we describe a novel DIA methodology for evaluating the equine proteome. Detectable peptides can serve as biomarkers for equine medicine to diagnose health conditions, monitor disease progression, and detect performance-enhancing drugs in anti-doping efforts. Typically, DDA-based spectrum libraries are required prior to DIA data analysis. (More info...)

Philip Remes Ph.D., (Thermo Fisher Scientific): A Skyline Tool for Creating Robust Large Scale Targeted MS/MS Assays [video]
Targeted MS/MS is the gold standard for quantitative quality in proteomics but is not widely utilized for large assays (1000’s of targets), because of the manual work involved in setting up the experiment, maintaining the retention time schedule, and analyzing the results. We created a Skyline External tool that automates the tedious parts and makes large scale targeted MS/MS a competitive option to Data Independent Acquisition (DIA) for some situations. (More info...)

Julia Robbins, (Talus Bio): How sweet it is: Leveraging the nuclear envelope glycome for the automated extraction of proteins from cell nuclei [video]
Protein localization within the subcellular environment influences their structure and function. One example is the transcription factor (TF) protein class, which commonly reside in the cytosol prior to being activated, typically by post-translational modification, and then translocating to the nucleus where they interact with DNA and other regulatory proteins to initiate transcription of genes. However, studying TFs is difficult because the process of isolating nuclei is a low-throughput, manual process, and existing bead-based approaches are not selective for nuclei. (More info...)

Stoyan Stoychev Ph.D., (Evosep and ReSyn Biosciences): Mag-Net: Bead based capture of membrane particles from plasma enables liquid biopsy measurements for >4,500 proteins [video]
The robust quantitative characterization of proteins from plasma is critical to the diagnosis of disease and therapeutic monitoring. Membrane-bound particles in plasma are composed of extracellular vesicles, exosomes, and apoptotic bodies and represent ~1-2% of the total protein composition. Analysis of this enriched membrane particle fraction by mass spectrometry is effectively a “liquid biopsy,” and significantly improves the dynamic range of the proteins measurable in plasma. (More info...)

Gary Siuzdak Ph.D., (The Scripps Research Institute): METLIN Ion Mobility: How to Analyze a Million Molecular Standards and Stay Sane [video]
The new METLIN Ion Mobility database has now been created having just completed the analysis of 30,000 molecular standards. METLIN Ion Mobility is an ongoing effort of the METLIN Tandem Mass Spectrometry database with over one million molecular standards analyzed, representing a challenging endeavor, especially when it needs to be accomplished at multiple collisional energies and in both positive and negative ionization modes. (More info...)

Lightning Talks

Ellen Casavant, Ph.D., (Genetech): AutoQC enables efficient and reproducible LC-MS/MS chromatography and instrumentation [video]
Mass spectrometry based proteomics is one approach to identifying and quantifying proteins from biological samples. In the Translational Medicine team at Genentech, discovery and targeted proteomics are performed on clinical samples to discover or quantify proteins relevant to therapeutic treatment or disease progression. To acquire high confidence data that can assist in therapeutic pipeline decision making, consistent evaluation of system suitability is imperative. (More info...)

Gunnar Dittmar Ph.D., (Luxembourg Institute of Health): Quantification of 782 Plasma Peptides by Multiplexed Targeted Proteomics [video]
Blood analysis is one of the foundations of clinical diagnostics. In recent years the analysis of proteins in blood samples by mass spectrometry has taken a jump forward in terms of sensitivity and the number of identified proteins. The recent development of parallel reaction monitoring with parallel accumulation and serial fragmentation (prm-PASEF) combines ion mobility as an additional separation dimension. This increases the proteome coverage while allowing the use of shorter chromatographic gradients. (More info...)

Jeroen Demmers Ph.D., (Erasmus MC Proteomics): Targeted mass spectrometry reveals that USP7 regulates the ncPRC1 Polycomb axis [video]
Ubiquitin-specific protease 7 (USP7) is a deubiquitylating enzyme that is involved in the regulation of multiple key cellular processes, including tumor suppression, transcription, epigenetics, the DNA damage response, and DNA replication. Whereas the role of USP7 in the p53 pathway is well established, a full picture of the USP7 regulatory network is lacking. For example, USP7 has been connected to the Polycomb system, but the molecular mechanism through which USP7 regulates Polycomb functions remains unclear. For debiquitinating enzymes, the regulatory mode of action is at the posttranslational level and, thus, proteomics tools are indispensable to study this. Here, we took an unbiased multi-omics approach with a strong targeted quantitative proteomics component to define the core USP7 network. (More info...)

Tom Lin Ph.D., (Washington University in St. Louis): An Unbiased Proteomics Method to Discover Posttranslational Arginylation Sites from Whole Proteomes [video]
Posttranslational arginylation installed on proteins by arginyltransferase (ATE1) is a critical modification for mammalian cellular homeostasis and development. Absence of this modification in ATE1 knockout mice was embryonically lethal with various signs of cardiovascular defects. Proteomic profiling of arginylation sites is extremely difficult since mass spectrometry cannot distinguish the same mass of translational and posttranslational arginine (+156 Da), and arginylated proteins go through Arg/N-degron pathway for ubiquitin-mediated degradation. Existing methods have proposed plausible arginylation sites on a handful of proteins (More info...)

Eduard Sabido Ph.D., (Center for Genomics Regulation and the University Pompeu Fabra): High-collision energy data-independent acquisition enables targeted and discovery identification of modified ribonucleotides by mass spectrometry [video]
Over 170 post-transcriptional RNA modifications have been described and are common in all kingdoms of life. These modifications range from methylation to complex chemical structures, with methylation being the most abundant. RNA modifications play a key role in RNA folding and function and their dysregulation in humans has been linked to several diseases such as cancer, metabolic diseases or neurological disorder. Nowadays, liquid chromatography-tandem mass spectrometry is considered the gold standard method for the identification and quantification of these modifications due to its sensitivity and accuracy. However, the analysis of modified ribonucleosides by mass spectrometry is complex due to the presence of positional isomers. (More info...)

Ariana Shannon, (Ohio State University): Generating fit-for-purpose targeted assays from a catalog of pre-screened peptides using data-independent acquisition (DIA) based figures of merit [video]
The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) classifies proteomics studies in three tiers, where targeted assays are typically Tier-1 (clinical) or Tier-2 (non-clinical), and global studies are Tier-3. Tier-2 targeted proteomics assays using parallel reaction monitoring (PRM) are developed by assessing figures-of-merit (such as limit of quantification) with stable isotope labeled (SIL) peptides and refining or re-selecting those targets through iterative experiments. This process is expensive and time consuming as SIL peptides must be purchased prior to validation. (More info...)


  Houston UGM
  Houston UGM
  Houston UGM
  Houston UGM



Event Information


Welcome

The Skyline Team is pleased to announce this year's big event, the Twelfth Annual Skyline User Group Meeting, which will be held in Houston, TX on Sunday afternoon before ASMS. We love seeing you all in-person -- so be sure to register and attend! 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 mass spectrometry techniques.  


--Brendan


When: Sunday, June 4, 2023
         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: Crystal Ballroom at the Rice 909 Texas Avenue, Houston, TX 77002 (map)

  • From the Convention Center, head northeast on Avenida De Las Americas toward Mc Kinney
  • Turn left onto Walker St
  • Walk seven blocks and turn right onto Main Street
  • Walk three blocks and turn left onto Texas Street
  • Crystal Ballroom at the Rice (909 Texas Avenue) is on the right in 1/2 block

Here are transportation options in downtown Houston.


[registration closed]

We have closed down our registration process but you can still attend! Please just come to Crystal Ballroom at the Rice 909 Texas Avenue for "day of" registration.

 


Scheduled 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 15 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 15 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...)

Abigail Burrows Franco Ph.D., (University of Kentucky): Efficient generation of highly multiplexed serum biomarker panels using gas phase fractionation and DIA libraries
Data Independent Acquisition (DIA) methods have become an attractive alternative to traditional Data Dependent Acquisition (DDA) methods for quantitative proteomics and biomarker identification. Here, we describe a novel DIA methodology for evaluating the equine proteome. Detectable peptides can serve as biomarkers for equine medicine to diagnose health conditions, monitor disease progression, and detect performance-enhancing drugs in anti-doping efforts. Typically, DDA-based spectrum libraries are required prior to DIA data analysis. (More info...)

Philip Remes Ph.D., (Thermo Fisher Scientific): A Skyline Tool for Creating Robust Large Scale Targeted MS/MS Assays
Targeted MS/MS is the gold standard for quantitative quality in proteomics but is not widely utilized for large assays (1000’s of targets), because of the manual work involved in setting up the experiment, maintaining the retention time schedule, and analyzing the results. We created a Skyline External tool that automates the tedious parts and makes large scale targeted MS/MS a competitive option to Data Independent Acquisition (DIA) for some situations. (More info...)

Julia Robbins, (Talus Bio): How sweet it is: Leveraging the nuclear envelope glycome for the automated extraction of proteins from cell nuclei
Protein localization within the subcellular environment influences their structure and function. One example is the transcription factor (TF) protein class, which commonly reside in the cytosol prior to being activated, typically by post-translational modification, and then translocating to the nucleus where they interact with DNA and other regulatory proteins to initiate transcription of genes. However, studying TFs is difficult because the process of isolating nuclei is a low-throughput, manual process, and existing bead-based approaches are not selective for nuclei. (More info...)

Stoyan Stoychev Ph.D., (Evosep and ReSyn Biosciences): Mag-Net: Bead based capture of membrane particles from plasma enables liquid biopsy measurements for >4,500 proteins
The robust quantitative characterization of proteins from plasma is critical to the diagnosis of disease and therapeutic monitoring. Membrane-bound particles in plasma are composed of extracellular vesicles, exosomes, and apoptotic bodies and represent ~1-2% of the total protein composition. Analysis of this enriched membrane particle fraction by mass spectrometry is effectively a “liquid biopsy,” and significantly improves the dynamic range of the proteins measurable in plasma. (More info...)

Gary Siuzdak Ph.D., (The Scripps Research Institute): METLIN Ion Mobility: How to Analyze a Million Molecular Standards and Stay Sane
The new METLIN Ion Mobility database has now been created having just completed the analysis of 30,000 molecular standards. METLIN Ion Mobility is an ongoing effort of the METLIN Tandem Mass Spectrometry database with over one million molecular standards analyzed, representing a challenging endeavor, especially when it needs to be accomplished at multiple collisional energies and in both positive and negative ionization modes. (More info...)

Lightning Talks

Ellen Casavant, Ph.D., (Genetech): AutoQC enables efficient and reproducible LC-MS/MS chromatography and instrumentation
Mass spectrometry based proteomics is one approach to identifying and quantifying proteins from biological samples. In the Translational Medicine team at Genentech, discovery and targeted proteomics are performed on clinical samples to discover or quantify proteins relevant to therapeutic treatment or disease progression. To acquire high confidence data that can assist in therapeutic pipeline decision making, consistent evaluation of system suitability is imperative. (More info...)

Gunnar Dittmar Ph.D., (Luxembourg Institute of Health): Quantification of 782 Plasma Peptides by Multiplexed Targeted Proteomics
Blood analysis is one of the foundations of clinical diagnostics. In recent years the analysis of proteins in blood samples by mass spectrometry has taken a jump forward in terms of sensitivity and the number of identified proteins. The recent development of parallel reaction monitoring with parallel accumulation and serial fragmentation (prm-PASEF) combines ion mobility as an additional separation dimension. This increases the proteome coverage while allowing the use of shorter chromatographic gradients. (More info...)

Jeroen Demmers Ph.D., (Erasmus MC Proteomics): Targeted mass spectrometry reveals that USP7 regulates the ncPRC1 Polycomb axis
Ubiquitin-specific protease 7 (USP7) is a deubiquitylating enzyme that is involved in the regulation of multiple key cellular processes, including tumor suppression, transcription, epigenetics, the DNA damage response, and DNA replication. Whereas the role of USP7 in the p53 pathway is well established, a full picture of the USP7 regulatory network is lacking. For example, USP7 has been connected to the Polycomb system, but the molecular mechanism through which USP7 regulates Polycomb functions remains unclear. For debiquitinating enzymes, the regulatory mode of action is at the posttranslational level and, thus, proteomics tools are indispensable to study this. Here, we took an unbiased multi-omics approach with a strong targeted quantitative proteomics component to define the core USP7 network. (More info...)

Tom Lin Ph.D., (Washington University in St. Louis): An Unbiased Proteomics Method to Discover Posttranslational Arginylation Sites from Whole Proteomes
Posttranslational arginylation installed on proteins by arginyltransferase (ATE1) is a critical modification for mammalian cellular homeostasis and development. Absence of this modification in ATE1 knockout mice was embryonically lethal with various signs of cardiovascular defects. Proteomic profiling of arginylation sites is extremely difficult since mass spectrometry cannot distinguish the same mass of translational and posttranslational arginine (+156 Da), and arginylated proteins go through Arg/N-degron pathway for ubiquitin-mediated degradation. Existing methods have proposed plausible arginylation sites on a handful of proteins (<20), most of which have not been further validated or functionally investigated. Therefore, protein arginylation remains an understudied field. (More info...)

Eduard Sabido Ph.D., (Center for Genomics Regulation and the University Pompeu Fabra): High-collision energy data-independent acquisition enables targeted and discovery identification of modified ribonucleotides by mass spectrometry
Over 170 post-transcriptional RNA modifications have been described and are common in all kingdoms of life. These modifications range from methylation to complex chemical structures, with methylation being the most abundant. RNA modifications play a key role in RNA folding and function and their dysregulation in humans has been linked to several diseases such as cancer, metabolic diseases or neurological disorder. Nowadays, liquid chromatography-tandem mass spectrometry is considered the gold standard method for the identification and quantification of these modifications due to its sensitivity and accuracy. However, the analysis of modified ribonucleosides by mass spectrometry is complex due to the presence of positional isomers. (More info...)

Ariana Shannon, (Ohio State University): Generating fit-for-purpose targeted assays from a catalog of pre-screened peptides using data-independent acquisition (DIA) based figures of merit
The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) classifies proteomics studies in three tiers, where targeted assays are typically Tier-1 (clinical) or Tier-2 (non-clinical), and global studies are Tier-3. Tier-2 targeted proteomics assays using parallel reaction monitoring (PRM) are developed by assessing figures-of-merit (such as limit of quantification) with stable isotope labeled (SIL) peptides and refining or re-selecting those targets through iterative experiments. This process is expensive and time consuming as SIL peptides must be purchased prior to validation. (More info...)


Sponsors


Agilent Bruker
SCIEX Shimadzu
Thermo Scientific Waters
  LabKey Software



Speakers


Here are biographies and abstracts for this year's speakers -- each users of Skyline -- scheduled to speak at the Skyline User Group Meeting at ASMS 2023 in Houston, TX.

Abigail Burrows

Ellen Casavant

Jeroen Demmers

Gunnar Dittmar

Tom Lin

Brendan MacLean

Philip Remes

Julia Robbins

Eduard Sabido

Ariana Shannon

Gary Siuzdak

Stoyan Stoychev




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. 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.



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. Since that time, he has worked as a Sr. Software Engineer within the MacCoss lab and led all aspects of design, development and support in creating the Skyline Targeted Mass Spectrometry Environment and its growing worldwide user community.

Status of the Skyline open-source software project 15 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 15 years later, the Skyline project is a thriving mass spectrometry community open-source collaboration supporting 6 mass spec instrument vendors, integrated with a wide variety of external software, with many thousands of users worldwide and over ten thousand instances started each week. Read More
In this presentation, the Skyline principal developer will present recent developments and a glimpse of the project's future. Topics covered will include:
  • Supporting new upstream processing pipelines
  • Supporting new instrument acquisition methods
  • Enhanced visualizations to better understand input data
  • Growth in the Skyline software ecosystem for targeted MS (Skyline, Skyline Batch, AutoQC, Panorama, and External Tools)
  • Strong industry support from instrument vendors
  • Courses, workshops, webinars and other efforts to create instructional resources for the Skyline community


[PDF




Abigail Burrows


Abigail Burrows   Abigail Burrows Franco, Ph.D., obtained her PhD from the University of Nebraska – Lincoln in 2020 and completed her post-doctoral studies at the University of Kentucky under the guidance of Dr. Scott Stanley. During her post-doctoral training, Dr. Burrows Franco was tasked with identifying peptide and protein biomarkers in equine athletes in response to drug administration. This work was in support of the Equine Biological Passport research program. Currently, she is a staff scientist continuing to develop the Equine Biological Passport within Dr. Stanley’s research lab and also serves as the services director of the Research Mass Spec core facility at the University of Kentucky.

Efficient generation of highly multiplexed serum biomarker panels using gas phase fractionation and DIA libraries

Data Independent Acquisition (DIA) methods have become an attractive alternative to traditional Data Dependent Acquisition (DDA) methods for quantitative proteomics and biomarker identification. Here, we describe a novel DIA methodology for evaluating the equine proteome. Detectable peptides can serve as biomarkers for equine medicine to diagnose health conditions, monitor disease progression, and detect performance-enhancing drugs in anti-doping efforts. Typically, DDA-based spectrum libraries are required prior to DIA data analysis. However, we generated a chromatogram library using narrow-window gas phase fractionation (GPF) DIA without previously generating a spectral library. Our primary aim was to develop a routine DIA method for identification of peptide biomarkers in healthy horses. Ultimately, this method will be implemented to establish baseline measurements of equine biomarker peptides. Serum (n=20) were collected from a population of healthy horses. Sera were pooled and tryptically digested using the Thermo Scientific EasyPep Maxi MS Sample Prep Kit. Prepared digests were analyzed on a high-resolution accurate mass coupled to a nano-liquid chromatography system. Six narrow-window GPFs with staggered windows were analyzed from 400-1000 m/z by 100 Da windows and 4 Da scan ranges (Pino et al., 2020). Digested peptides (500 ng) were separated over a 65-minute gradient. Collected DIA data were analyzed against a predicted peptide library (Prosit DB, EncyclopeDIA). Data were analyzed in Skyline (22.2.0.351) and peptides were filtered for suitability as routine biomarker peptides. Peptides were confirmed in a wide-window DIA method (400-1000 m/z; 12 Da). Read More
Each pooled serum sample was injected six times in order to cover the entire mass range of the narrow-window isolation scheme. The use of pooled serum reduces the time for sample preparation, and preserves the integrity of the sample matrix. Soy lectin protein was added prior to digestion to monitor digestion efficiency, while PRTC was added following digestion prior to injection to evaluate instrument performance. Narrow-window data were analyzed using Skyline against the predicted chromatogram library (Prosit DB, EncyclopeDIA). In this work, an ELIB (DIA-based chromatogram library) was used to select biomarker peptides for routine monitoring. Peptides were detected across 51 overlapping windows at 4 m/z width. Detected peptides represent all the potential peptide detections within the wide-window DIA methods. Data and peptides were filtered in Skyline to remove any non-detectable peptides. Following peptide filtering we identified ~2000 unique peptides, representing approximately 300 proteins from the narrow-window acquisitions. The relative abundances of detected peptides were determined. Peptides detectable in the wide-window acquisitions were filtered for suitability as candidate biomarkers for screening methods. Due to the size of the equine database (Uniprot, Reviewed) selected, these observations are expected for a non-depleted serum. By using HRAM mass spectrometry to generate an equine chromatogram library, we can monitor thousands of peptides in the wide-window DIA method. Additionally, this workflow will be transferred to a targeted peptide method using SRM transitions. A major advantage of performing DIA-GPF is the depth of proteome coverage achieved in a non-depleted serum digest. Furthermore, this work has been a collaboration between Thermo Fisher Scientific, Mike MacCoss of the University of Washington, and the University of Kentucky. Panorama was additionally utilized between collaborators to facilitate data and information sharing.


[PDF




Ellen Casavant


Ellen Casavant   Ellen Casavant, Ph.D., is a Senior Scientist in the Biomarker Mass Spectrometry team within the department of Translational Medicine (TM) at Genentech. The biomarker mass spectrometry team aims to develop mass spectrometry data acquisition methods and analytical techniques to support measurement of clinically relevant candidate biomarkers from large clinical cohorts to help inform drug development decision making. As a part of this group, she leads a computational team that is developing a semi-qualified data-independent acquisition mass spectrometry pipeline that can enable efficient processing and QC of DIA-MS datasets. Dr. Casavant has developed a DIA-MS serial dilution method to help understand and establish a quantitative range within a set matrix (Casavant et al, 2023). She is particularly interested in developing a fecal proteomics technique to help to identify non-invasive biomarkers to evaluate mechanism of action for candidate IBD therapeutics and to ease endoscopy burden on patients suffering from this disease.

AutoQC enables efficient and reproducible LC-MS/MS chromatography and instrumentation

Mass spectrometry based proteomics is one approach to identifying and quantifying proteins from biological samples. In the Translational Medicine team at Genentech, discovery and targeted proteomics are performed on clinical samples to discover or quantify proteins relevant to therapeutic treatment or disease progression. To acquire high confidence data that can assist in therapeutic pipeline decision making, consistent evaluation of system suitability is imperative. AutoQC, which leverages both panorama and skyline, enables users to monitor the performance of both triple quadrupole and orbitrap instruments through visual assessment of retention drift, mass error shift, peak shape, and many other attributes. From this ongoing monitoring and collection of data, troubleshooting is faster and quantitation is more reproducible over time. More features from AutoQC are currently being implemented to further assist with instrument troubleshooting and performance, including the ability to monitor every sample run on the instrument in order to assess instrument performance during sample collection. AutoQC has now been implemented on all instruments in our laboratory and has helped to quantify and visualize instrument performance in an automated way that improves efficiency of our workflows.


[PDF




Jeroen Demmers


Jeroen Demmers   Jeroen Demmers, Ph.D. studied Chemistry at Utrecht University (the Netherlands). He earned his PhD degree from the same university in 2002, working on the development of tools to study transmembrane peptide and proteins interactions with phospholipid bilayers using hydrogen-deuterium exchange and electrospray ionization mass spectrometry in the groups of Albert Heck and Antoinette Killian. As a postdoctoral fellow in the lab of Brian Chait at The Rockefeller University (New York) he worked on a project involving the proteomic identification of plasmid DNA binding proteins in yeast. In 2005, Jeroen moved to Erasmus University Medical Center to set up a proteomics lab and core facility and to initiate a research program in the field of protein mass spectrometry. Currently, he is an associate professor and director of the Erasmus MC proteomics core facility (www.proteomicscenter.nl). Research in his lab focuses on the molecular mechanisms of the ubiquitin–proteasome system and the lab develops quantitative proteomics technologies for the analysis of protein posttranslational modifications. The Demmers lab collaborates with many research groups within the institute and abroad on various topics, such as protein-protein interactions, immunopeptidomics, targeted proteomics, etc. Jeroen’s mission is to advocate the superiority of targeted proteomics in terms of specificity, quantitative accuracy, and – arguably – sensitivity over immunoblotting for the quantitative analysis of target proteins in complex biological mixtures. Although one currently still needs a dedicated mass spectrometry facility with skilled personnel and therefore higher initial costs, with the pace of technology development it is likely that small, user-friendly bench-top mass spectrometry equipment will democratize targeted proteomics assays soon. In addition, to push this transformation, the proteomics community should actively show the life science community what advantages it can bring.

Targeted mass spectrometry reveals that USP7 regulates the ncPRC1 Polycomb axis

INTRODUCTION: Ubiquitin-specific protease 7 (USP7) is a deubiquitylating enzyme that is involved in the regulation of multiple key cellular processes, including tumor suppression, transcription, epigenetics, the DNA damage response, and DNA replication. Whereas the role of USP7 in the p53 pathway is well established, a full picture of the USP7 regulatory network is lacking. For example, USP7 has been connected to the Polycomb system, but the molecular mechanism through which USP7 regulates Polycomb functions remains unclear. For debiquitinating enzymes, the regulatory mode of action is at the posttranslational level and, thus, proteomics tools are indispensable to study this. Here, we took an unbiased multi-omics approach with a strong targeted quantitative proteomics component to define the core USP7 network. METHODS: Relevant knock-outs, including Dox inducible USP7, were generated in HAP-1, DLD1 and U2OS cell lines. We performed interactomics and in-depth global proteomics to identify the USP7 interaction network. Targeted proteomics using parallel reaction monitoring (PRM) was done to accurately quantify all relevant players of the Polycomb system in a label free manner. For targeted proteomics a PRM regime on an Orbitrap Eclipse Tribrid was used to select for sets of previously selected peptides. Targeted proteomics data were analyzed with the Skyline software suite. Read More
RESULTS: Using a targeted mass spectrometry assay focused on a subset of potential USP7 target proteins and defined PTMs, we found that USP7 modulates the ncPRC1 axis at the posttranslational level through stabilization of the non-canonical Polycomb-repressive complexes ncPRC1.6 and ncPRC1.1. At the transcriptional level, USP7 silences AUTS2, the subunit that suppresses H2A ubiquitylation by ncPRC1.3/5. Collectively, these USP7 activities increase the genomic deposition of H2AK119ub1. Contradicting prevalent paradigms of Polycomb function, our findings reveal that changes in H2AK119ub1 are generally uncoupled from H3K27me3 and thus argue against a hierarchical relationship between these two repressive histone marks. Importantly, the connection of USP7 to the Polycomb system suggests that its role in cancer extends beyond regulation of p53. Furthermore, our interactomics assay shows that USP7 has a remarkable range of interaction partners, of which only a portion appears to be stabilized by USP7. Current studies address the relevance of these other USP7 partners. CONCLUSION: This multi-angle analysis establishes USP7 as a regulatory hub in a multinodal network involved in tumor biology, protein (de)ubiquitylation, and genome regulation. Combined, our multi-omics results provide a resource for future studies on the role of USP7 in (neuro)development and cancer.


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Gunnar Dittmar


Gunnar Dittmar   Gunnar Dittmar, Ph.D. is the group leader of the proteomics of cellular signalling research group at the Luxembourg Institute of Health. After finishing his PhD at the University of Heidelberg, he joined the Lab of Dan Finley at Harvard Medical school as a post-doc. After finishing my Post-Doc, he joined the Max-Delbrück Center for molecular medicine in Berlin as a group leader, starting my own group. At the Delbrück Center, he set up the mass spectrometry core facility, and later he also set up the proteomics core facility at the newly founded Berlin Institute of Health. In 2016 he joined the Luxembourg Institute of Health, where he is still leading the proteomics of cellular signalling group. In parallel, he created the genomic sequencing centre, LuxGen, a joined high throughput sequencing facility and the quantitative biology unit, a technology focused department covering FACS, MRI, Bioinformatics, a reverse protein array and a proteomics platform besides several research groups.

Quantification of 782 Plasma Peptides by Multiplexed Targeted Proteomics

Blood analysis is one of the foundations of clinical diagnostics. In recent years the analysis of proteins in blood samples by mass spectrometry has taken a jump forward in terms of sensitivity and the number of identified proteins. The recent development of parallel reaction monitoring with parallel accumulation and serial fragmentation (prm-PASEF) combines ion mobility as an additional separation dimension. This increases the proteome coverage while allowing the use of shorter chromatographic gradients. Read More
To demonstrate the method's full potential, we used an isotope-labeled synthetic peptide mix of 782 peptides, derived from 579 plasma proteins, spiked into blood plasma samples with a prm-PASEF measurement allowing the quantification of 565 plasma proteins by targeted proteomics. All data were analysed using Skyline. As a less time-consuming alternative to the prm-PASEF method, we describe guided dia-PASEF (g-dia-PASEF) and compare its application to prm-PASEF for measuring blood plasma. To demonstrate both methods’ performance in clinical samples, 20 patient plasma samples from a colorectal cancer (CRC) cohort were analyzed. The analysis identified 14 differentially regulated proteins between the CRC patient and control individual plasma samples.


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Tom Lin


Tom Lin   Tom Lin, Ph.D., got his B.S. in Pharmacy in 2009 from Zhengzhou University, M.S. in Bioanalytical Technology in 2012 from Peking University, and Ph.D. in Medicinal Chemistry in 2017 from University of Tennessee HSC. He has been a postdoc for 4 years in Megan Matthews group at University of Pennsylvania working on protein-hydrazine covalent chemistry using Activity-based Protein Profiling (ABPP). Since 2021, he has been a Staff Scientist in Benjamin Garcia lab at Washington University in St. Louis working on discovery and biological functions of posttranslational arginylation.

An Unbiased Proteomics Method to Discover Posttranslational Arginylation Sites from Whole Proteomes

Posttranslational arginylation installed on proteins by arginyltransferase (ATE1) is a critical modification for mammalian cellular homeostasis and development. Absence of this modification in ATE1 knockout mice was embryonically lethal with various signs of cardiovascular defects. Proteomic profiling of arginylation sites is extremely difficult since mass spectrometry cannot distinguish the same mass of translational and posttranslational arginine (+156 Da), and arginylated proteins go through Arg/N-degron pathway for ubiquitin-mediated degradation. Existing methods have proposed plausible arginylation sites on a handful of proteins (<20), most of which have not been further validated or functionally investigated. Therefore, protein arginylation remains an understudied field. Read More
In this work, we have developed a deep proteomic profiling approach using high-pH fractionation and proteomics for unbiased identification of arginylation sites from complex whole proteomes. By performing the ATE1 enzyme reaction ex vivo, we incorporated isotopic Arg (Arg10 and Arg0) to proteome-wide arginylation sites under ribosome-free condition. Labeled proteomes were mixed 1:1, prepared, and fractionated for proteomics analysis. Raw data were searched to give peptide IDs. Using Skyline, we were able to determine the co-eluting behaviors and heavy/light ratios (~1.0) of peptides containing both Arg10 and Arg0 modifications. In addition, a customized R script “ArginylomePlot” was written (publicly available at GitHub) to 1) identify co-eluting peptides modified by isotopic Arg, 2) extract their MS1 pairs in sextets (3 heavy and 3 light peaks), 3) calculate H/L ratios and statistics, 4) export all scans/results in PDF. To increase the throughput of the discovery rate by avoiding peptide fractionation, we have developed a data-independent acquisition (DIA) method for analyzing the same samples. A wide m/z window was used to send isotopic MS1 pairs to MS2 for fragmentation to generate b/y ions including those containing Arg10/Arg0 pairs. The DIA data was searched for peptide IDs, among which paired b/y ions with Arg10/Arg0 were analyzed by Skyline to generate H/L ratios at MS2 level first. Peptides with a series of paired b/y ions will be further quantified by Skyline for their H/L ratio at MS1 level. Using Skyline and DIA, we were able to detect all arginylation sites in a high-throughput manner (1 raw/sample). The established approach allows to discover a set of 64 high-confidence targets containing 86 arginylation sites from four cell lines. We have validated 7 of the newly discovered sites using synthetic peptides. As external validation, our identified sites of CALR and PDIA1 are consistent with literature reporting their arginylation sites at E18 and D18, respectively. The developed platform is applicable to any biological lysates and paves the way for functional studies of posttranslational arginylation.


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Philip Remes


Philip Remes   Philip Remes, Ph.D., is a senior research scientist in the R&D department of Thermo Fisher Scientific in San Jose, California. He received his Ph.D. in Gary Glish’s lab at the University of Chapel Hill, North Carolina, where he worked on quadrupole ion trap and mass filter instrumentation. At Thermo, he worked with Jae Schwartz on instrument control software, ion trap analyzers, detectors and simulations for the LTQ Velos platform. Later he did similar work as a part of Mike Senko’s Tribrid development team on the Fusion, Lumos, and Eclipse projects. In recent years, Philip has continued working on ion trap technology, branching out to learn about applications and get first-hand experience in how they can benefit from improvements in hardware, instrument control, signal processing, and informatics.

A Skyline Tool for Creating Robust Large Scale Targeted MS/MS Assays

Targeted MS/MS is the gold standard for quantitative quality in proteomics but is not widely utilized for large assays (1000’s of targets), because of the manual work involved in setting up the experiment, maintaining the retention time schedule, and analyzing the results. We created a Skyline External tool that automates the tedious parts and makes large scale targeted MS/MS a competitive option to Data Independent Acquisition (DIA) for some situations. Read More
The tool starts from imported peptide DIA search results, refines the transitions, and creates an instrument targeted MS/MS method file that accounts for the details of the LC peak width and the instrument acquisition speed, be it for Orbitrap, Ion trap, or Triple quad analysis. We also show how the tool interfaces with our new real-time chromatogram alignment technology, which eliminates the problem of maintaining the assay schedule over time and provides a significant boost to the number of feasible targets by narrowing the scheduling windows. The automated peak-picking in Skyline is aided by the transition refinement, the peptide search library, and the narrow scheduling windows, making it extremely reliable. With Skyline, our tool, and real-time chromatogram alignment, we demonstrate the creation and use of a targeted MS/MS assay for > 2000 targets in a 30 minute gradient.


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Julia Robbins


Julia Robbins   Julia Robbins is a senior research associate at Talus Bio with five years of experience in mass spectrometry proteomics. Her research focuses on methods development for high-throughput proteomics sample preparation, and she has particular interest in bead-based automation. When she’s not orchestrating multiple robots and instruments in the lab, she’s a doting plant mom and dabbles in scientific illustration.

How sweet it is: Leveraging the nuclear envelope glycome for the automated extraction of proteins from cell nuclei

Protein localization within the subcellular environment influences their structure and function. One example is the transcription factor (TF) protein class, which commonly reside in the cytosol prior to being activated, typically by post-translational modification, and then translocating to the nucleus where they interact with DNA and other regulatory proteins to initiate transcription of genes. However, studying TFs is difficult because the process of isolating nuclei is a low-throughput, manual process, and existing bead-based approaches are not selective for nuclei. Read More
We developed a novel lectin-based magnetic bead approach to manipulate nuclei that is more selective and higher-throughput than other methods, using Skyline for glycan and proteomics analyses throughout the method development process. We used SUGA to prepare glycans from the nucleus and from the cytosol, and Skyline to determine which of those glycans was differentially localized to the nucleus. We prepared magnetic beads with lectins specific to those glycans, and used a targeted Skyline document with proteins from different cellular compartments to quantify the enrichment of nuclei using those lectin beads. Finally, we set up AutoQC and Panorama with the Skyline document for subcellular fractionation in order to monitor for nuclear enrichment across a 96-well plate based method using the magnetic beads.


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Eduard Sabido


Eduard Sabido   Eduard Sabido, Ph.D., is the head of the Proteomics Unit of the Center for Genomics Regulation and the University Pompeu Fabra. His group is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and his research interests are focused on the development of innovative mass spectrometry methods for targeted protein quantification and data analysis, and recently, on the characterization of nucleoside modifications in biological samples.

High-collision energy data-independent acquisition enables targeted and discovery identification of modified ribonucleotides by mass spectrometry

Over 170 post-transcriptional RNA modifications have been described and are common in all kingdoms of life. These modifications range from methylation to complex chemical structures, with methylation being the most abundant. RNA modifications play a key role in RNA folding and function and their dysregulation in humans has been linked to several diseases such as cancer, metabolic diseases or neurological disorder. Nowadays, liquid chromatography-tandem mass spectrometry is considered the gold standard method for the identification and quantification of these modifications due to its sensitivity and accuracy. However, the analysis of modified ribonucleosides by mass spectrometry is complex due to the presence of positional isomers. Read More
In this scenario, optimal separation of these compounds by highly sensitive liquid chromatography combined with the generation of high-information spectra is critical to unequivocally identify them, especially in high-complex mixtures. Here we present an analytical method that comprises a new type of mixed-mode nano-flow liquid chromatography column combined with high- and low-collision energy data-independent mass spectrometric acquisition for the identification and quantitation of modified ribonucleosides. The method produces content-rich spectra and combines targeted and screening capabilities thus enabling the identification of a variety of modified nucleosides in biological matrices by single-shot liquid chromatographic analysis coupled to mass spectrometry.


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Ariana Shannon


Ariana Shannon   Ariana Shannon is a fourth-year pre-doctoral graduate student within the Ohio State Biochemistry Program. In 2019 she joined the lab of Dr. Amanda Hummon, while using DIA to study tumor-stromal interactions within 3D cell-based tumor cocultures models. In 2022, she began to additionally work with Dr. Brian Searle developing methods to characterize immunological assays with targeted and global mass-spectrometry based proteomics.

Generating fit-for-purpose targeted assays from a catalog of pre-screened peptides using data-independent acquisition (DIA) based figures of merit

Introduction: The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) classifies proteomics studies in three tiers, where targeted assays are typically Tier-1 (clinical) or Tier-2 (non-clinical), and global studies are Tier-3. Tier-2 targeted proteomics assays using parallel reaction monitoring (PRM) are developed by assessing figures-of-merit (such as limit of quantification) with stable isotope labeled (SIL) peptides and refining or re-selecting those targets through iterative experiments. This process is expensive and time consuming as SIL peptides must be purchased prior to validation. Read More
We propose a method of developing Tier-2 PRM assays using global DIA measurements to simultaneously estimate figures-of-merit for thousands of peptides before SIL peptides are introduced, letting us rapidly build “du jour” assays from a catalog of pre-screened peptides. The Skyline software provides the necessary infrastructure for us to visualize, and refine the results of both DIA and PRM data. We intend to pre-process data using EncyclopeDIA and Skyline batch in tandem with a customized output report to calculate figures-of-merit using a streamlined, reproducible process. Methods: Global data was acquired for CD8+ T cells isolated from in vitro expanded PMEL-transgenic mice using gas-phase fractionation (GPF) DIA on an Exploris 480 mass spectrometer. A .sky template document was generated for Skyline batch to import EncyclopeDIA searched wide-window DIA data. Using a custom analysis and report script, we determined figures-of-merit for all peptides, including limits of detection (LoD) and quantification (LoQ) using the matrix-matched approach. For response curves, dimethyl-labeled human Jurkat T cells are used as a suitable background matrix. Humans and mice share 85% homology within protein-coding exons; labeling Jurkat peptides mitigates this issue by shifting precursor and y-type ions out of DIA windows. Peptide stability was assessed through storage in 7℃ for up to 7 days with up to 5 freeze-thaw cycles. Digestion repeatability will be determined with a 5 digestion by 5 replicate experiment. Preliminary data: We demonstrate this rapid PRM development approach by monitoring CD8+ T cell exhaustion in mice. First we determined the components of CD8+ T cell proteome using five GPF-DIA datasets with 2 m/z isolation windows derived from multiple mouse in vivo tumor and in vitro exhaustion models. We flow-activated cell sorted the T cells into 3 exhaustion states; progenitor, or stem-like, acutely and chronically-exhausted cells. Cumulatively, 6,801 proteins were identified, of which Reactome mapped 38.2% proteins to immune-related functions. Of these, we observed 283 immune-related proteins, 130 homeostasis proteins, 357 proteins involved in signal transduction, and 47 involved in autophagy. In particular, we observed 151 established exhaustion-related protein markers (over 500 total peptides). T cell exhaustion in cancer is difficult to study because they are both small (approximately 1/10th of a HeLa cell) and are rare in the tumor microenvironment. Transcriptomic data, which requires lower sample amount compared to proteomics, is typically used to study exhaustion due to the low numbers of naïve or differentiated cells present in mouse models. To determine the minimum number of cells required for proteomics sample preparation and measurement, effector T cell peptides were prepared in decreasing numbers (100k, 50k, 10k, 1k, 500). We detected several well-characterized peptides such as DAALMVTNDGATLIK from Cct2, which was regularly measured in 500 cell samples, and had an LoQ of approximately 1500 cells. However, the majority of exhaustion-related peptides have LoQs between 10k and 50k cells. We will discuss estimations of additional figures-of-merit using DIA data and a new computational tool to construct PRM assays from selected proteins of interest. We will demonstrate a computer scheduled exhaustion-specific assay to quantify protein fingerprints in progenitor, acute and chronically exhausted T cells, and contrast those results with single-cell flow cytometry data. Novel aspect: The DIA-to-PRM method will enable streamlined analysis of on-the-fly or new peptide targets routinely used model systems.


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Gary Siuzdak


Gary Siuzdak   Gary Siuzdak, Ph.D., is Professor and Director of the Scripps Center for Metabolomics at The Scripps Research Institute. He is an affiliate scientist at the Lawrence Berkeley National Lab and has served as Vice President of the American Society for Mass Spectrometry. His research includes developing novel technologies for metabolomics, metabolite imaging and systems biology. He has over 300 peer-reviewed publications and two books including the "The Expanding Role of Mass Spectrometry in Biotechnology”. Other information can be found at https://en.wikipedia.org/wiki/Gary_Siuzdak

METLIN Ion Mobility (downloadable): How to Analyze a Million Molecular Standards and Stay Sane

The new METLIN Ion Mobility database has now been created having just completed the analysis of 30,000 molecular standards. METLIN Ion Mobility is an ongoing effort of the METLIN Tandem Mass Spectrometry database with over one million molecular standards analyzed, representing a challenging endeavor, especially when it needs to be accomplished at multiple collisional energies and in both positive and negative ionization modes. Read More
I will describe some of the details of how the ion mobility measurements were performed on the Bruker TimsTOF and the Waters Synapt 2 and why we have pursued not only tandem mass spectrometry (MS2) and neutral loss data acquisition but also this newly created ion mobility database. The primary reason behind this effort is to create high confidence molecular identification of known molecules, and preliminary characterization of novel, unknown molecules (unknowns). METLIN is moving to become a truly comprehensive database with data on ~1% of PubChem’s 93 million compounds, essentially a number that can be characterized as all the currently known chemical space.


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Stoyan Stoychev


Stoyan Stoychev   Stoyan Stoychev, Ph.D., Stoyan has a background in Structural Biology and experience in the field of biological mass spectrometry having worked at a core facility for over 15 years. He currently holds a joint position at Evosep and ReSyn Biosciences with main focus on developing end-to-end (sample to to mass spectrometer) solutions for routine proteome profiling.

Mag-Net: Bead based capture of membrane particles from plasma enables liquid biopsy measurements for >4,500 proteins

The robust quantitative characterization of proteins from plasma is critical to the diagnosis of disease and therapeutic monitoring. Membrane-bound particles in plasma are composed of extracellular vesicles, exosomes, and apoptotic bodies and represent ~1-2% of the total protein composition. Analysis of this enriched membrane particle fraction by mass spectrometry is effectively a “liquid biopsy,” and significantly improves the dynamic range of the proteins measurable in plasma. We have developed a one-step enrichment strategy (Mag-Net) using strong-anion exchange magnetic microparticles (ReSyn Biosciences) to capture membrane-bound particles from plasma. The Mag-Net method is robust, reproducible, hemolysis compatible, inexpensive, and requires <100 μL plasma input. Coupled to a quantitative liquid chromatography mass spectrometry strategy using data independent acquisition, we demonstrate that we can routinely collect results for >42,000 peptides from >4,500 plasma proteins with high precision. Read More
In this presentation, we will illustrate how we used Skyline’s visualization capabilities to evaluate the data quality. This includes assessing the enrichment of known protein markers of exosomes and microvesicles, including CD9, CD61, ALIX, NCAM1, and flotillin-1. Importantly, >400 proteins were depleted relative to unfractionated plasma (e.g. albumin, transferrin, alpha-2-macroglobulin, alpha-1-antitrypsin, ApoA1, and ApoB). Using the Skyline external tool, Protter, we could rapidly evaluate whether proteins were transmembrane, lipid anchored, or peripheral membrane proteins – which totaled ~40% of the proteins measured. Skyline was used to also assess the quantitative precision of the sample preparation and the linearity and lower limit of quantitation (LLOQ) using a matrix matched calibration curve. Finally, Skyline and a shared folder on https://panoramaweb.org were used to share data and to evaluate assay performance between laboratories and instrument platforms.


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