Ben Collins (Queens University Belfast)
With the advent of high throughput data acquisition methods producing increasing complex and high dimensional data in proteomics we now face the challenge of increasing data volume and analysis needs. Many academic labs have access to high performance computing (HPC) capabilities via their university or via national facilities that could increase their data processing potential. However, these facilities generally run Linux operating systems with job scheduling and are therefore less accessible for some analysis pipelines. Recently Linux support has been introduced in Spectronaut enabling the possibility of running on Linux-based HPC environments.
Our lab has recently established a pipeline for the analysis of diaPASEF data at scale with Spectronaut using the Northern Ireland High Performance Computing Centre hosted at Queen’s University Belfast. The workflow leverages Spectronaut’s capability to store results in saved experiment files (.SNE) such that computationally intensive signal processing steps are carried out on the compute cluster, but data visualization and post-processing can be performed on local machines in the Spectronaut GUI environment.
In this talk I aim to first describe our experience with this mode of data analysis and, second, to describe some applications in the space of quantitative interaction proteomics and/or targeted protein degradation.
Yansheng Liu (Yale School of Medicine)
In this presentation, we will discuss the experimental and bioinformatic advancements of a multiplex DIA-MS workflow. This new workflow leverages a false discovery rate (FDR) control algorithm with various options supported by the latest version of Spectronaut, including channel-specific FDR and deep-learning-based selection of heavy and light transitions. We will show the extensive validation of this enhanced multiplex workflow for dynamic or pulse SILAC experiments, designed to determine proteome-wide turnover rates. We will demonstrate how different Spectronaut options influence experimental performance and how this workflow reveals selective protein turnover in response to genome/gene dosage imbalances that are relevant to genetic syndromes and cancer drug resistance.
Short Bio:
Ben is a Full Professor in the School of Biological Sciences at Queen’s University Belfast, UK. His research focuses on broadly on 3 topics: (i) method development and applications in data independent acquisition mass spectrometry; (ii) analysis of protein interaction networks and protein complexes; and (iii) applications of these strategies in drug discovery, innate immunity, host-pathogen biology, and cancer biology. Ben’s PhD was completed at University College Dublin in 2009 where he remained for 1 year as the Agilent Technologies Newman Fellow. Ben moved to the Institute of Molecular Systems Biology at ETH Zurich in Autumn 2010 as postdoctoral researcher in the pioneering group of Prof. Ruedi Aebersold, where his research focused on the application of quantitative interaction proteomics in signaling and the development of DIA mass spectrometry. Following this Ben was a Group Leader and SNF Ambizione Fellow at ETH Zurich before moving to moving to Belfast in 2019 to set up an independent group. In 2020 Ben won the HUPO Discovery in Proteomic Sciences Award for contributions to DIA mass spectrometry. He currently co-directs the NI Centre of Excellence for Chemoproteomics.
Short Bio:
Dr. Yansheng Liu is an Associate Professor in the Department of Pharmacology and the Department of Biomedical Informatics & Data Science at Yale University School of Medicine. Dr. Liu received his Ph.D. in Biomedical Sciences from the Chinese Academy of Sciences in 2011 and completed his post-doctoral training at ETH Zurich Switzerland. Since joining Yale’s faculty in December 2017, Dr. Liu has focused his research on analyzing protein turnover and post-translational modifications to understand cancer aneuploidy, cellular signaling transduction, and biodiversity. His lab is further dedicated to advancing multiplexed data-independent acquisition mass spectrometry (DIA-MS) and recently harnessing MALDI imaging mass spectrometry techniques in clinical applications. Dr. Liu has been recognized with several prestigious awards, including the ASMS Research Award, the HUPO ECR Award, and the US HUPO Robert J. Cotter Award.