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Join us for the 4th ETC Auditorium - Writing: The Key to Funding Your Research

DATE: Wednesday, April 12, 2023

TIME:   7 am PDT / 9 am CDT / 10 am EDT

Writing a successful grant application is hard work—regardless of your career level. Once you've convinced yourself that you have a compelling research project, you have to find a way to convince the reviewers and then the funding agency to support you. This webinar will cover fundamental essentials of a successful research proposal, including choice of grant category, PI and collaborators/co-investigators in addition to writing style, organization, and documentation. Guidance about shared instrumentation grant applications will also be presented.

SPEAKER: Dr. Susan Weintraub has been been actively engaged in biomedical mass spectrometry since 1971. She is a co-author of more than 180 scientific papers published in peer-reviewed journals in addition to six book chapters. She completed a six-year term on the Board of Directors of the American Society for Mass Spectrometry (ASMS), serving as Vice President for Programs (2010 - 2012), President (2012 - 2014) and Past President (2014 - 2016). She is currently a member of the HUPO Council and chair the HUPO Mass Spectrometry Resource Pillar. She is also an Associate Editor for the Journal of Proteome Research, with a primary assignment of computational mass spectrometry manuscripts. In 2018, she was elected a Fellow of the American Association for the Advancement of Science. Dr Weintraub's publications can be found in her PubMed Bibliography

PANELISTS:

• Giuseppe Palmisano: Professor - Department of Parasitology, University of Sao Paulo, Brazil
• Brian Searle: Assistant Professor - Department of Biomedical Informatics, State Ohio University Medical

REGISTER HERE

After registering, you will receive a confirmation email containing information about joining the webinar.

The goal of the ETC Auditorium "Stylish Academic Writing" professional development webinar series is to help students and trainees improve their scientific writing skills. The 3rd event featured Ruedi Aebersold from ETH Zurich, Switzerland. Prof. Ruedi Aebersold is an emeritus Professor at ETH Zurich who is an international leader in proteomics field and mentored many scientists. Ruedi's lab has pioneered several widely-used techniques and tools that have contributed to today's proteomics research. His publications have been cited 196,000 times with an h-factor of 214, according to Google Scholar.

The talk emphasized a number of key ideas on why and how paper writing contributes to a successful scientific career as a significant factor, including:

• A paper only matters if it describes progress in the field
• Publishing your work in a way that supports your career goals
• The reason why prestigious journals have a high IF is that they manage to include a small number of papers that have >100-1000s citations
• Publications that are more cooperative generally have a higher impact, especially those describing research at the interface of disciplines
• Make the text easier and clear: One paper one message
• Before you start writing: define the science story and tell it to the lab and other audiences who are not scientists
• Use a foolproof structure and track through the main topics e.g., the discussion should be focused on putting the new results in context and point out limitations
• Developing writing skills by practicing writing and structured talks and using short clear sentences
• Before you submit: anticipate what reviewers might object to and make sure every co-author agrees with the paper.
• Grow a "thick skin" towards rejections: never take the rejection personally and improve and address the criticism factually.
• Talk to the editors to adjust expectations for additional data and grievances with reviewers.
• Avoid frequent problems: write one paper at a time- but do it.
• Perfection is an elusive goal: freeze the story at the point of saturation and let reviewers define the path to perfection.
• After publishment: increase the paper's visibility and impact through social media and conferences.

Ruedi also addressed some voted live questions from PollEverywhere, such as his views on ChatGPT and how that would affect scientific writing.

The session was hosted by Yansheng Liu (Yale University School of Medicine), Blandine Chazarin (Cedars-Sinai Heart Institute), and Deepti J Kundu (PRIDE and EBI).

A full video recording of the session including the figure clinic and Q&A session is available on the HUPO YouTube channel. An alternative link for those who don’t have access to YouTube can be viewed here.

The manuscript competition is a great opportunity for early career researchers to showcase their work. Each year three finalists are selected to present their manuscripts in a plenary session during HUPO’s world congress. We reached out to last year’s finalists and asked a few questions to learn about their experience in the competition at HUPO 2022 in Cancun, Mexico. Take a look at what they had to say.

Ling Hao’s Interview:

Dr. Ling Hao was a finalist in the 2022 HUPO ECR manuscript competition, for which she presented her work: Thiol-Cleavable Biotin for Chemical and Enzymatic Biotinylation and its Application to Mitochondrial TurboID Proteomics in a plenary session. We asked a few questions to Dr. Hao about her experience in the competition. Read what she had to say below!

What is your current position and affiliation?

I am an Assistant Professor of Chemistry in the George Washington University in Washington, DC, USA. 

How would you like your work to contribute to the field of proteomics?

I hope that our research work can lead to both proteomics method advancements and a deeper understanding of molecular mechanisms of brain diseases. I also hope to support students and postdocs through classroom teaching and individual mentoring, so that they can enjoy research and pursue their dream careers in the proteomics field. 

How was your experience and what did it mean to you to present your work at the HUPO World Congress?

It was a tremendous honor and encouragement to present our research during the 2022 HUPO ECR manuscript competition and also be selected as the HUPO Rising Star Award. I received a lot of valuable feedback to improve our research work. I felt much empowered to continue our research, pushing our science forward and supporting young researchers in the field. 

What have you found in the HUPO community/congress?

I deeply appreciate and value both the exciting science and supportive environment in the HUPO community. My proteomics journey started when I was a graduate student in Prof. Lingjun Li's group in University of Wisconsin-Madison. Learning how cutting-edge proteomics techniques were developed to advance diverse aspects of human health (both in the Li Lab and during HUPO Congress) were eye-opening experiences. During the 2022 HUPO Congress, I learned about the exciting new pi-hub project as the proteomic navigator of the human body. I was also super impressed by how amazing and supportive the HUPO ECR group is. 

Wout Bittremieux’s Interview:

Dr. Wout Bittremieux was a finalist and first prize winner in the 2022 HUPO ECR manuscript competition. He presented his work on:  A learned embedding for efficient joint analysis of millions of mass spectra.

What is your current position and affiliation?

I recently started as an assistant research professor at the University of Antwerp, Belgium.

How would you like your work to contribute to the field of proteomics?

Building on recent breakthroughs in artificial intelligence that have led to disruptive advances across many scientific domains, my career is oriented towards developing powerful computational solutions to uncover novel biological and biomedical insights from proteomics data.

What have you found in the HUPO community/congress?

HUPO has an extremely vibrant and welcoming community. I was especially impressed by the various dedicated activities for early career researchers, as well as the open and friendly atmosphere throughout the entire conference.

How was your experience/what did it mean to present your work at HUPO? 

The HUPO 2022 World Congress was my first time attending the HUPO meeting and I had a blast. With engaging discussions in the Bioinformatics Hub, an exciting scientific program, participating in the ECR Manuscript Competition, and even a little bit of beach time in between, HUPO 2022 was the year's highlight.

Ready to apply? Click here to learn more about how you can submit your work for the competition.

Use protein and peptide data measurements from Parkinson's Disease patients to predict progression of the disease.

Goal of the Competition:

The goal of this competition is to predict MDS-UPDR scores, which measure progression in patients with Parkinson's disease. The Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is a comprehensive assessment of both motor and non-motor symptoms associated with Parkinson's. You will develop a model trained on data of protein and peptide levels over time in subjects with Parkinson’s disease versus normal age-matched control subjects.

Your work could help provide important breakthrough information about which molecules change as Parkinson’s disease progresses.

Context:

Parkinson’s disease (PD) is a disabling brain disorder that affects movements, cognition, sleep, and other normal functions. Unfortunately, there is no current cure—and the disease worsens over time. It's estimated that by 2037, 1.6 million people in the U.S. will have Parkinson’s disease, at an economic cost approaching $80 billion. Research indicates that protein or peptide abnormalities play a key role in the onset and worsening of this disease. Gaining a better understanding of this—with the help of data science—could provide important clues for the development of new pharmacotherapies to slow the progression or cure Parkinson’s disease.

Current efforts have resulted in complex clinical and neurobiological data on over 10,000 subjects for broad sharing with the research community. A number of important findings have been published using this data, but clear biomarkers or cures are still lacking.

Competition host, the Accelerating Medicines Partnership® Parkinson’s Disease (AMP®PD), is a public-private partnership between government, industry, and nonprofits that is managed through the Foundation of the National Institutes of Health (FNIH). The Partnership created the AMP PD Knowledge Platform, which includes a deep molecular characterization and longitudinal clinical profiling of Parkinson’s disease patients, with the goal of identifying and validating diagnostic, prognostic, and/or disease progression biomarkers for Parkinson’s disease.

Your work could help in the search for a cure for Parkinson’s disease, which would alleviate the substantial suffering and medical care costs of patients with this disease.

Visit Kaggle.com to Join the Competition and for details on the competition's:

• Description
• Evaluation
• Timeline
• Prizes
• Code Requirements

Written by: Fengchao Yu and Daniel A. Polasky, University of Michigan, USA

Mass spectrometry-based proteomics is a widely used technique to study peptides and proteins quantitatively. This approach has several advantages over other techniques, such as high throughput and sensitivity. However, the data analysis process is challenging, due to the complexity of tandem MS data and wide variety of experiments and workflows under the umbrella of proteomics. To overcome these challenges, various tools have been developed to process mass spectrometry data. Unfortunately, these tools typically focus on specific aspects of data analysis, such as peptide identification, protein identification, or quantification, requiring researchers to learn and “link” multiple tools to complete the analysis. Such a process can be time-consuming and often requires specialized knowledge, limiting the growth of proteomics in the broader research community. Complete, user-friendly software suites for proteomics have been developed commercially, but are expensive and may have limited capability to be adapted to new methods and applications. Aiming to strike a balance in this space, FragPipe is an open-source and freely available graphical user interface (GUI)-based software suite that provides a one-stop solution to streamline the processing of proteomics data from raw data to result tables.

FragPipe combines state-of-the-art tools in many areas of proteome informatics to process mass spectrometry data from identification to quantification. It leverages MSFragger1-3, a fast database search engine, to perform database searching. It also couples MSBooster and Percolator4 to re-score peptide-spectrum matches (PSMs) using deep-learning predicted features, and Philosopher5 for false discovery rate (FDR) estimation. In addition, FragPipe contains several results processing tools, such as PTM-Shepherd6, which is used to discover post-translational modifications and characterize their fragmentation. IonQuant7 is used for label-free and isotopic-labeling quantifications, while TMT-Integrator is used for isobaric-labeling quantification. Finally, recent additions of a spectrum viewer, FP-PDV8, for summarizing results and viewing annotated spectra, and FragPipe-Analyst for downstream results processing and comparison of different experimental conditions have expanded FragPipe into a complete pipeline for proteomics data.  

Most of the individual tools within FragPipe are being continuously developed and improved, offering cutting-edge capabilities with the convenience of a stable and user-friendly pipeline. For example, FragPipe hosts a set of advanced tools for glycoproteomics data analysis, including MSFragger Glyco search9, glycan composition assignment and FDR in PTM-Shepherd10, and O-Pair for O-glycan localization11. Analyzing glycoproteomics data is a challenging process, requiring characterization of both peptide and glycan components from glycopeptide mass spectra. MSFragger Glyco search excels at rapidly identifying glycopeptides, building on the open search methods developed in MSFragger. FragPipe allows this capability to be connected to the advanced methods for FDR control and quantitation available from other tools in FragPipe, enabling a complete platform for glycoproteomics. It also provides an easy way to integrate additional tools, such as the recently added O-Pair localization method that was originally implemented in MetaMorpheus.

Unlike other tools that are typically designed for either data-dependent acquisition (DDA) or data-independent acquisition (DIA) data, FragPipe can analyze both DDA and DIA data. To handle the complexity of DIA data, specific modules have been developed, including DIA-Umpire12, which demultiplexes spectra to pseudo-DDA spectra, and MSFragger-DIA, which directly searches multiplexed spectra. The search results are carefully curated to construct a spectral library, employing deep learning-based scoring and false discovery rate (FDR) filtering. This spectral library can be used to extract quantitative information from the DIA spectra. One of FragPipe’s key advantages is its ability to analyze DDA and DIA data together, which allows it to build a hybrid spectral library. Such a hybrid spectral library fully utilizes the information in both data types and contains more peptides, which results in more quantified peptides and proteins when used in library-based quantification.

Last but not least, FragPipe also has a command line interface that can be run on Linux servers, clusters, high-performance computers, etc. The GUI and the command line interface use the same codebase, which makes the result identical. The workflow files used to run the command line interface, and for saving settings in the GUI mode, are saved automatically whenever FragPipe is run and can be loaded to exactly reproduce a previous analysis. They can also be shared among users to provide easy access to developed methods and deposited with data uploaded to public repositories for reproducibility.

In summary, FragPipe is an all-in-one software tool that streamlines the entire process of mass spectrometry-based proteomics data analysis, from identification to quantification. Its ability to handle both DDA and DIA data types, support for glycopeptide identification and a wide variety of proteomics-associated workflows, and its ability to perform MS1-based and MS2-based quantification make it a versatile tool for researchers. FragPipe combines the user-friendliness of a commercial software program with the cutting-edge methods of research software to help improve data processing across bottom-up proteomics.

Figure 1. Graphical summarization of the modules and functionalities in FragPipe, which contains identification, quantification, PTM analysis, visualization, and downstream analysis.

Bios:

Fengchao Yu:

Fengchao is a research investigator from the Alexey Nesvizhskii Lab at the University of Michigan. His research interests include peptide identification, PTM discovery, label-free quantification, isotopic-labeling quantification, isobaric-labeling quantification, and DIA data analysis. Currently, Fengchao is the leading developer of FragPipe, MSFragger, and IonQuant. These tools have been used by research laboratories and companies in the United States and worldwide. He has also published papers in journals such as Nature Methods, Nature Biotechnology, Nature Communications, Molecular & Cellular Proteomics, and Journal of Proteome Research.

Daniel Polasky:

Daniel A. Polasky is a research investigator in the lab of Prof. Alexey Nesvizhskii in the department of Pathology at the University of Michigan. His research focuses on developing computational tools and methods for proteomics, with a particular focus on glycosylation and other post-translational modifications. He is a member of the MSFragger and FragPipe development teams, including leading work on MSFragger Glyco and associated tools for glycoproteomics data analysis. Before moving into computational proteomics, his PhD work in the lab of Prof. Brandon Ruotolo focused on developing mass spectrometry and ion mobility-mass spectrometry methods for analysis of intact proteins and protein complexes.

References:

1. Kong, A. T., Leprevost, F. V., Avtonomov, D. M., Mellacheruvu, D. & Nesvizhskii, A. I. MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics. Nat Methods 14, 513-520, doi:10.1038/nmeth.4256 (2017).
2. Yu, F. et al. Identification of modified peptides using localization-aware open search. Nat Commun 11, 4065 (2020).
3. Yu, F. et al. Fast Quantitative Analysis of timsTOF PASEF Data with MSFragger and IonQuant. Mol Cell Proteomics 19, 1575-1585 (2020).
4. Käll, L., Canterbury, J. D., Weston, J., Noble, W. S. & MacCoss, M. J. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nature Methods 4, 923-925, doi:10.1038/nmeth1113 (2007).
5. da Veiga Leprevost, F. et al. Philosopher: a versatile toolkit for shotgun proteomics data analysis. Nature Methods 17, 869-870, doi:10.1038/s41592-020-0912-y (2020).
6. Geiszler, D. J. et al. PTM-shepherd: Analysis and summarization of post-translational and chemical modifications from open search results. Molecular and Cellular Proteomics 20, 100018-100018, doi:10.1074/MCP.TIR120.002216 (2021).
7. Yu, F., Haynes, S. E. & Nesvizhskii, A. I. IonQuant enables accurate and sensitive label-free quantification with FDR-controlled match-between-runs. Molecular and Cellular Proteomics 20, 100077-100077, doi:10.1016/J.MCPRO.2021.100077 (2021).
8. Li, K., Vaudel, M., Zhang, B., Ren, Y. & Wen, B. PDV: An integrative proteomics data viewer. Bioinformatics 35, 1249-1251, doi:10.1093/bioinformatics/bty770 (2019).
9. Polasky, D. A., Yu, F., Teo, G. C. & Nesvizhskii, A. I. Fast and comprehensive N- and O-glycoproteomics analysis with MSFragger-Glyco. Nat Methods 17, 1125-1132, doi:10.1038/s41592-020-0967-9 (2020).
10. Polasky, D. A., Geiszler, D. J., Yu, F. & Nesvizhskii, A. I. Multi-attribute Glycan Identification and FDR Control for Glycoproteomics. Molecular & Cellular Proteomics, doi:10.1016/j.mcpro.2022.100205 (2022).
11. Lu, L., Riley, N. M., Shortreed, M. R., Bertozzi, C. R. & Smith, L. M. O-Pair Search with MetaMorpheus for O-glycopeptide characterization. Nat Methods 17, 1133-1138, doi:10.1038/s41592-020-00985-5 (2020).
12. Tsou, C. C. et al. DIA-Umpire: Comprehensive computational framework for data-independent acquisition proteomics. Nature Methods 12, 258-264, doi:10.1038/nmeth.3255 (2015).

Sponsored By:  Expert Review of Proteomics by Taylor and Francis

Have you recently worked on an original manuscript in the field of proteomics? This is an excellent chance to participate in the 9th edition of the HUPO Early Career Researcher (ECR) Manuscript Competition at HUPO 2023 in Busan, South Korea. This is a unique opportunity for early career researchers to gain visibility in the proteomics community, as it highlights the important contributions that postdoctoral fellows, young clinicians and junior faculty members make to the proteomics field. Three finalists will be selected to present their manuscripts published during the 2022 and 2023 calendar years in a dedicated plenary session at HUPO 2023. An expert committee will evaluate the oral presentations to determine the “Proteomics Highlight of the Year”. The first-place winner will receive a cash prize of $1,000 USD and two runner-ups will each take home $500 USD, thanks to our sponsor, Expert Review of Proteomics by Taylor and Francis.

Application Deadline:  April 15, 2023

More information and details can be found here.

Date: May 21 - 23, 2023

Location: Sao Paolo, Brazil

The Human Brain Proteome Project (HBPP) launched in 2003 and was redesigned in 2015 to promote the connection of neuroproteomics scientists and actively encourage the inclusion of young investigators. 

Our well-established annual HBPP workshop has been travelling around the world to capture, congregate, and connect the international neuroproteomics community. 

This workshop will provide a forum for researchers to meet and discuss the latest developments in neuroproteomic research to better understand brain function and dysfunction.

Visit hbpp2023 for more information, program, speaker and registration details.

Join the Early Career Researcher (ECR) Committee for this exciting webinar!

DATE:  Wednesday April 5, 2023 

TIME:  10 am PDT / 12 noon CDT / 1 pm EDT

Are you interested in proteomics? Considering a non-academic career? Join the HUPO ECR Committee for their online panel discussion “Exploring Non-Academic Pathways in Proteomics”. The panel will have the following speakers: 

• Chris Rose (Scientist and Postdoc Mentor, Genentech)
• Lindsay Pino (Co-founder and CTO, Talus Bio)
• Maria Polychronidou (Senior Scientific Editor, Molecular Systems Biology, EMBO Press).

REGISTER HERE!

After registering, you will receive a confirmation email containing information about joining the webinar.

This EMBO practical course aims to provide a theoretical and practical overview of state-of-the-art techniques for the characterization of various PTMs, such as phosphorylation, acetylation, cysteine PTMs and glycosylation, and their cross-talking in controlling dynamic cellular mechanisms. The laboratory part will focus on a case study of EGF stimulated SILAC labeled HeLa cells. You will be introduced to enrichment, identification and quantitation of the PTM peptides and to mass spectrometry analysis as well as data interpretation and bioinformatics. This will provide you with knowledge needed to perform quantitative large-scale PTMomics from small amounts of sample material yourself. You will be taught in methods developed in the laboratories of the speakers and they will provide you with their own tips and tricks.

Course Location: University of Southern Denmark - Odense, Denmark

Course Date: June 15 June 22, 2023

Visit EMBO Practical Course website for more information.