20241113 Westlake Symposium for the Future of Proteomics

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Tiannan Guo (China)

Welcome Remarks (5 min)

1. Proteomics and biology

1.1. Overview

Ruedi Aebersold (Switzerland)

Multi-PROTeomics is the central method to study biological processes as complex systems (10 min research+5 min future)

Abstract

Biological or clinical phenotypes arise from the biochemical state of a cell or tissue which, in turn, is the result of the composition of biomolecules, their organization and interactions in the cell. The biochemical state is determined, in part, by the genotype and by external conditions the cell senses and adapts to. At present, there is neither a comprehensive theory nor computational models that generally predict the cellular adaptation to changes in the genome or external conditions. There is general consensus that proteins are essential to the understanding of the function and adaptation of biochemical processes.

The golden age of biochemistry in mid-20th century established the principles how proteins are synthesized, how they fold and function and how their activities are regulated. The advent of the OMICS age nurtured the notion that aggregate results from the profiling of all genes (genomics) and proteins (proteomics) would be suitable to explain the molecular basis of the processes of life.

We postulate that this molecule-centred paradigm is fundamentally incapable of explaining the molecular basis of cells and organisms and that it needs to be replaced by a paradigm that considers living systems as complex adaptable systems. We furthermore postulate that multiPROTeomics, the analysis of the proteome at multiple layers – expression profile, functional state, structure, location and interactions- and the integration of the ensuing results is the only technology that can describe cells as complex adaptable systems.

Therefore, the future of proteomics should focus on the development and routine use of an integrated  multi-PROTeomic technology that capture the information of all relevant proteomic layers and on associated computational strategies that translate the aggregated data into a model that predicts the adaptation of the system to genomic or external perturbations.

Bio

Ruedi Aebersold is a Swiss/Canadian scientist trained at the Biocenter, University of Basel, Switzerland. After postdoctoral research at Caltech he was on the faculties of the University of British Columbia, Vancouver and the University of Washington, Seattle WA. In 2000 he co-founded, with Lee Hood and Alan Aderem, the Institute for Systems Biology in Seattle. In 2004 he joined ETH Zürich to establish the Institute of Molecular Systems Biology. He has co-founded several companies and holds multiple public service appointments. The group’s work was recognized with numerous national and international awards including the Biemann medal of ASMS, the Paracelsus prize of the Swiss Chemical Society, the Otto Naegeli Prize, the Thomson medal of IMSF, the HUPO achievement award, the Marcel Benoist Swiss Science Prize, the most prestigious science award in Switzerland, and the Heineken award for Biochemistry and Biophysics in 2024. 

The research focus of the Aebersold group was the proteome. The group pioneered several widely used techniques and generated open access/open-source software and statistical tools that contribute to making proteomic research results more transparent, reproducible and accurate and, when applied, advanced the understanding of molecular processes in basic biology and clinical research.

Ruedi Aebersold entered emeritus status in 2021 and now serves as a member of the board of trustees of several foundations that support life science research.

1.2. Proteome networks

Rong Zeng (China)

Proteome-wide Network and Dynamics (10 min research+5 min future)

Abstract

The cells and tissues in living beings are very fine-tune infrastructure consisting of multiple biological molecules, which form highly-coordinating network to complete biological process. The inner basis of health transformed to disease is the alteration of biological
molecular network. Therefore, the discovery and intervention of network behaviours associated with diseases could be the key to keep health and control disease. Currently, the monitoring on single-node or single-layer could not adequately reflect the complexity of diseases. The effective supporting systems for precision medicine based on dynamic bio-network could be highly demanded.
The future of proteomics may rely on the developing of platform to elucidate of protein network and dynamics.

Bio

Rong Zeng, Professor of ShanghaiTech University, National Facility for Protein Sciences in Shanghai. 
Rong Zeng is one of the pioneers of mass spectrometry-based proteomics in China. The efforts of Zeng group have been focused on both data generating and data analysis, aiming to integrate proteome-centered network and dynamics. The ultimate mission is monitoring systems changes for health and disease. So far, Dr. Zeng has published more than 200 papers, with a total of more than 12,000 citations and H-index 61.

Lihua Zhang (China)

In-vivo crosslinking MS for protein interactome analysis (10 min research+5 min future)

Abstract

In-vivo cross-linking mass spectrometry (CXMS) has shown great promising in deciphering the dynamic changes of protein configuration and interactome in living cells. Herein, I will introduce the recent advance of CXMS techniques we developed, and discuss the future emphasis on improving the coverage, the reaction rate, and the spatial specificity of in-vivo cross-linking, to achieve the in-depth analysis of dynamic structure of proteins, even for Intrinsically disordered proteins, and to capture more transient protein-protein interaction, even during translocation between various sub-organelles. Furthermore, besides protein interactome analysis, more CXMS techniques should be developed to meet the needs of RNA-protein, drug-protein and cell communication study.

Bio

Prof. Zhang obtained her Bachelor degree of Science from Jilin University in 1995, and obtained her Ph.D. degree from DICP, CAS in 2000. During 1999 to 2000, she was selected to join the Ph.D. joint-education program of DAAD, and carried out research in Germany. From 2001 to 2003, she engaged in the postdoctoral research in Japan. In April 2003, she went back to work in DICP, CAS, and was promoted to be a full professor in 2005. Her research interest is focused on the development of new methods for proteome qualitation, quantitation and interaction. She won the second Prize for National Natural Science Award in 2012, and obtained the funding for Outstanding Young Scientists from National Natural Science Committee in 2017. She has published more than 100 papers in journals such as Nature Chemistry, Nature Communication, Angewandte Chemie International Edition, Advanced Science, Molecular and Cellular Proteomics, and Analytical Chemistry.

Rob Moritz (USA)

Protein Discovery: Assessing Translation of Novel ORFs and Discovering Function (10 min research+5 min future)

Abstract

With new technological advances, novel discoveries are made in our genome and proteome. Gene and protein databases such as Ensembl-GENCODE and UniProtKB have been the backbone of biochemical analyses and are crucial for biomedical research. Recent advancements in ribosome profiling (Ribo-Seq) have unveiled over 7000 short open reading frames (sORFs) in the human genome, some of which encode detectable polypeptides and small proteins not previously recognized.
However, assessing the protein-level evidence for these sORFs remains a challenge. Immunopeptidomics, offers new avenues for identifying such proteins given the presentation of defined peptide lengths. I will discuss the annotation of sORF’s to advance our understanding of gene expression, protein synthesis, and functional consequence of these expressed sORF proteins, and discuss the impact of tools to access these understudied proteomes.

Bio

Dr. Robert Moritz is Professor and Head of Proteomics Research at the Institute for Systems Biology (ISB) in Seattle, Washington, USA. He received his PhD from the University of Melbourne in Biochemistry whilst beginning his full-time career at the Ludwig Institute for Cancer Research, Melbourne, Australia from 1983 to 2008. In 2008, he moved to the US to ISB as faculty member.
The Moritz group develops and applies cutting edge proteomics technologies to biomarker analysis of wellness and aging, disease biomarkers for early detection of cancer, biomarkers and mechanistic interfaces for a number of infectious disease pathogens. The Moritz group is the developer of the world renowned Trans-Proteomic Pipeline proteomics software tools for statistical validation of proteome identifications, protein crosslinking analysis with Kojak and many online resources for quantitative proteomics. His group developed the complete Human PeptideAtlas, SRMAtlas, SWATHAtlas and related software routines to provide quantitative resources and repositories of mass spectrometric assays to all proteins. Using these technologies, his group has discovered the translation of thousands of novel proteins expanding the knowledge of the Human genome and proteome. Dr. Moritz has published more than 300 research articles, a number of book chapters, and holds multiple patents in proteomics technologies.
Dr. Moritz was recently the Chair of the Human Proteome Project (HPP) and previously Vice-President of the Human Proteome Organization (HUPO) where he plays a large role in growing the society and guiding the HPP Grand Challenge of defining “A function for every protein”. He works with several scientific journals as Journal Scientific Chair, Journals boards, and is a member of a number of scientific advisory boards to life-science companies. Dr. Moritz is an entrepreneur with the establishment of several life science companies, is active in teaching and dissemination of proteomics technologies, fosters education exchanges and create forums for collaborative relationships centered on the proteome.

Chris Overall (Canada)

Termini are not just the ends of proteins (10 min research+5 min future) 

Abstract

Whereas proteomics identifies protein levels, these do not necessarily reflect biological activity. Protein N and C terminal peptides provide critical information on protein function and stability. Our terminomics methods (TAILS, PICS) enrich and annotate terminomes, and our N and C-termini database TopFIND (https://topfind.clip.msl.ubc.ca) reveal widespread truncation and generationof termini in normal and diseased tissue. In analyzing the N-terminome of normal human cells and tissues, we find that the N-termini of protein chainsin vivocan commence at many points Cterminal to the predicted start site and result from proteolytic processing to generate stable protein chains: Proteolytic processing generates new protein species with characteristic neo-N termini that are frequently accompanied by altered half-lives, function, interactions and location. Selected examples will be presented to highlight the need to consider N and C termini annotation to more completely understand protein function regulation and identify mechanistically informative biomarkers.

Bio

Professor Chris Overall is a Distinguished University Scholar of the University of British Columbia, a fellow of the Royal Society of Canada, a Canada Research Chair Laureate in Protease Proteomics and Systems Biology, a Yonsei Distinguished Scholar of Yonsei University, Korea, and a Senior Fellow of the Freiburg Institute of Advanced Studies, Albert Ludwigs Universität Freiburg, Germany, where he is an Honorary Professor. His 314 papers are influential, with an h-index of 108. He is best known for his development of terminomic methodology for the identification of protein N and C-termini for the identification of mature and neo-protein substrate termini in vivo. He Chairs the HUPO Chromosome-centric Human Proteome Project (C-HPP), sits on the 1st Council of the pi-Hub Global Proteomics Project, and is the recipient of numerous awards, e.g., CNPN Tony Pawson Award, the Proteomass Scientific Society Award; 2018 HUPO Discovery
Award in Proteomics Sciences; and 2022 Helmut Holzer Award.

Teck Yew Low (Malaysia)

Non-canonical proteins in cancer (10 min research+5 min future)

Abstract

 Short open reading frames (ORFs, ≤300 bases) encode microproteins that are often missed in proteomic studies, such as the CPTAC cancer proteogenomic project, which centers exclusively on annotated, canonical proteins. This study investigates the expression patterns of microproteins across six colorectal cancer (CRC) cell lines representing various Dukes' stages. We employed 0.25% acetic acid precipitation followed by a bottom-up proteomics workflow to enrich microproteins from these cell lines. Mass spectrometry (MS) data were analyzed using FragPipe against a customized FASTA database integrating sequences from SwissProt, OpenProt, and RIBO-Seq data. Additionally, we retrieved and reanalyzed MS data from CRC tumor tissues at different stages from the CPTAC server, applying the exact computational pipeline. This study identified 207 microproteins in cell lines and 665 in CPTAC data, with 167 and 66 differentially expressed, respectively. Notably, the newly annotated microproteins PIGBOS and NoBody, both hypothesized to play roles in cancer, were downregulated across all CRC cell lines. Among annotated microproteins, S100P and UQCR11 were upregulated, while ADIRF, PCP4, and NMES1 showed downregulation in specific cell lines and consistently across all CPTAC stages. We employed a "guilt-by-association" approach to predict biological functions, reanalyzing BioPlex interactome MS data for novel, unannotated microproteins. Bait proteins interacting with the same microprotein prey were counted and subjected to enrichment analysis, resulting in the assignment of (i) IP_662645 (89 baits) to NOD-like receptor signaling, (ii) IP_624439 (21 baits) to SCF-dependent proteasomal catabolism, and (iii) IP_671454 (26 baits) to actin-binding functions. This work reveals differentially expressed microproteins across CRC samples, emphasizing the importance of short ORFs and microproteins in cancer progression.

Bio

Dr. Teck Yew Low is an Associate Professor and Senior Research Fellow at the UKM Medical Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM). He completed his Ph.D. at the National University of Singapore, where his work on proteomic studies in chemically induced cirrhosis laid the groundwork for his continuing research in proteomics. Dr. Low’s research interests include proteomics, proteogenomics, and the analysis of non-canonical proteins, with application in cancer biology and biomarker discovery. His work focuses on the understanding of proteogenomic signatures of cancers to explore disease mechanisms and identify possible therapeutic pathways. In addition to his research, Dr. Low serves as the Secretary-General of the Asia Oceania Human Organization (AOHUPO) and holds Council Member positions at AOHUPO and the Human Proteome Organization (HUPO). He supports collaborations in proteomics research across the Asia-Pacific region and globally. He also contributes to the field as Editor-in-Chief of Proteome Science. He serves on the Editorial Board of Molecular and Cellular Proteomics, where he helps facilitate proteomics research and publications. Dr. Low has published his work in various peer-reviewed journals and has been invited to speak at several international conferences, sharing his insights on the applications of proteomics in biomedical research.

2. Proteomics-driven precision medicine

2.1. Selected technologies

Anthony Purcell (Australia)

Immunopeptidomics - from basic cell biology to next generation vaccine design  (10 min research+5 min future)

Abstract

Immunopeptidomics has matured as a field that bridges basic cell biology with applied immunology and vaccine design. It focuses on the study of peptide fragments presented by major histocompatibility complex (MHC) molecules on the surface of cells, which play a crucial role in the immune response. These valuable insights into immune system functionality will inform the development of next-generation vaccines in cancer and infectious disease as well as provide opportunities for antigen specific therapies in autoimmunity. I will introduce the current state of the art immunopeptidomic technology and highlight recent examples from my group in cancer and infectious disease research.

Bio

Tony is currently a National Health and Medical Research Council Investigator Fellow and Laboratory Head in the Department of Biochemistry at Monash University Melbourne, Australia. He is also Vice President of the Australasian Proteomics Society and a HuPO council member.
With a background in immunology and biochemistry, his laboratory focusses on how the peptide antigens presented to the immune system, coined the immunopeptidome, is influenced by infection, inflammation and the environment. He has made important contributions to understanding the role of antigen in autoimmune diseases, drug hypersensitivity, cancer and infectious diseases. He is well known for work that has highlighted a role for post-translationally modified antigens in immunity. He has been instrumental in bringing new quantitative tools to immunological studies, in particular the quantitation of the cell surface expression levels of specific HLA-peptide complexes. He is a leader in the field of immunopeptidomics with over 330 related publications.

Hui Zhang (USA)

Glycoproteomics: method and clinical applications (10 min research+5 min future)

Abstract

Glycoproteomics, a specialized field within proteomics, focuses on the comprehensive characterization of glycoproteins. One of the main challenges in glycoproteomics lies in the heterogeneity of glycosylation, including variations in glycan types, sites of glycosylation, and the specific glycans attached to each glycosylation site. In recent years, mass spectrometry-based technologies have emerged as the cornerstone of advancements in glycoproteomics.

By developing and employing the advanced glycoproteomic technologies to investigate tumors, we have investigated the interplay between genomics and functions. The integration of glycoproteomic approaches into biomedical research has significantly advanced our understanding of cancer for more personalized and effective clinical interventions.

Bio

Hui Zhang graduated from Peking University with a B.S and MS, and University of Pennsylvania with a Ph.D. degree, worked at New England Biolabs, Cell Singling Technologies, Institute for Systems Biology, and started her lab at Johns Hopkins University in 2006. Currently, Dr. Hui Zhang is a professor of Pathology, Oncology, Chemical and Biomolecular Engineering, and Urology at Johns Hopkins University. She is the director of the Mass Spectrometry Core Facility and Proteomic Research in the Center for Biomarker Discovery and Translation. The research in her group focuses on understanding the functions of proteins and protein modifications, especially protein glycosylation in biology and human diseases.

Please visit her Publications page. https://scholar.google.com/citations?user=ununaGsAAAAJ&hl=en

2.2. Diseases at focus

Connie Jimenez (Netherlands)

Multi-dimensional clinical proteomics of colorectal cancer (10 min research+5 min future)

Abstract

In the past (almost) two decades, we have applied clinical proteomics to multiple types of clinically relevant materials of colorectal cancer. Our pioneering large-scale study of over 300 stool samples identified and validated novel protein biomarkers for colorectal cancer screening that are currently in prospective clinical testing phase. More recently, we analyzed the microbiome in these samples to explore the added value of the microbiome for colorectal cancer detection. Large-scale analysis of tumor tissues identified colorectal cancer subtype biology and immune subsets with prognostic implications, and kinase targets for low dose combination treatments in drug resistant forms. Multi-compartment proteomics of colorectal cancer and adjacent normal tissue secretomes and exosomes revealed dysregulated pathways, TFs, and secretion mechanisms as well as promising potential biofluid biomarkers. Finally, recently we established plasma proteomics in our laboratory and performed a pilot study in colorectal cancer, revealing an EV plasma signature of CRC.

Outlook: Tissue biopsy (phospho)proteomics in a multi-omics context is entering the precision medicine space. Liquid biopsy (phospho)proteomics for diagnosis and therapy selection may become a reality in the future.

References
Bosch LJW, de Wit M, Jimenez CR*, Meijer GA* et al. Novel Stool-Based Protein Biomarkers for Improved Colorectal Cancer Screening: A Case-Control Study. Ann Intern Med. 2017 Dec 19;167(12):855-866.
de Klaver W, Jimenez CR, de Wit M, Meijer GA et al. Clinical Validation of a Multitarget Fecal Immunochemical Test for Colorectal Cancer Screening : A Diagnostic Test Accuracy Study. Ann Intern Med. 2021 Sep;174(9):1224-1231.
Jaco C. Knol, Mengge Lyu, Franziska Böttger, Guo, Jimenez et al., The Pan-Cancer Proteome Atlas, a mass spectrometry-based landscape for discovering tumor biology, biomarkers and therapeutic targets. Submitted.
Monteiro MN*, Almeida-Marques C*, Jimenez CR et al., Proteomics of tissue-derived extracellular vesicles and soluble secretome reveals cancer hallmarks in colorectal cancer progression and MCM3 as plasma marker. Submitted.

Ka Wan Li (Netherlands)

Proteomics of postmortem brains Alzheimer's disease   (10 min research+5 min future)

Abstract

Alzheimer’s disease (AD) is the most common cause of dementia. The pathological hallmarks are the deposition of amyloid beta (Aβ) in the brain parenchyma as plaques, and the accumulates of hyperphosphorylated Mapt (tau) intraneuronally as neurofibrillary tangles. Proteomics analysis of AD brains have been reported. However the AD-specific peptides derived from posttranslational modified tau and the semi-tryptic fragments of Aβ are seldom detected in the global analysis of the tissue proteomics. Furthermore, the spatio-temporal proteome patterns in AD are poorly described.
Tissue proteomics analysis of early and late onset AD samples; the inclusion of tau peptides with PTMs and the semi-tryptic Aβ peptides
In the present study, we built a spectral library with 128,000 peptides and 9,000 protein groups including tau tryptic peptides that have post-translational modifications and the semi-tryptic peptides derived from Aβ, and used it for DIA search. We performed proteomics analyses of temporal lobe extracts from 115 AD and non-demented post-mortem brains covering age groups of 56-70 (EOAD) and 85-96 (LOAD), and revealed EOAD as a more aggressive form of neurodegeneration. We further detected a number of phosphorylated and/or ubiquitinated tau tryptic peptides, and the truncated Aβ isoforms. The use of two tau peptides derived from the microtubule-binding domain repeat, and two phosphorylated peptides corresponding to the p-tau180 and p-tau231, yielded a near prefect classification of AD from healthy controls. Interestingly, a number of healthy controls also contained Aβ, but the AD-specific posttranslational modifications of tau were absent. Gene Set Enrichment Analysis of the healthy control with or without Aβ revealed alteration of biological processes of aerobic respiration, small molecule metabolism and detoxification in the Aβ-containing group. This implies that the presence of Aβ alone induces subtle proteome changes that may represent an early stage of neurodegeneration before any AD symptoms occur or an AD-resilient state.
Future direction, spatial proteomics and interactome analysis of AD samples
AD brain is characterized by the depletion of synapses and neurons, astrogliosis, and the activation of microglial cells, but their specific cellular changes cannot be differentiated from the tissue proteomics alone. Previously, we have applied a combination of immunohistochemistry, cellular-resolution laser microdissection, and proteomics, to reveal the distinct protein changes in a specific neuronal type in AD patients with Granulovacuolar degeneration. This proof-of-principle study used 3000 pooled cells per sample. With the advancement of mass spectrometer in both sensitivity and speed, we are now investigating the possibility of performing large scale proteomics on different cell types in multiple brain regions from FFPE slices.
Cellular physiology is driven by processes involving protein-protein interaction and in the form of protein complexes. We have performed large scale immunoprecipitation experiments using supernatant obtained from the mild-detergent extracted post-mortem brain as input. Disregards the vast proteome differences between healthy and AD brains, their protein interactomes were similar. Proteomics analyses of the extracts revealed the pellet as the source of differences between AD and controls, which unfortunately is not amendable for immunoprecipitation experiment. We will explore the possibility of crosslink protocol to define and quantify protein complexes from the pellet, in ways similar to our previous large scale cross-link study on isolated synapse.

Bio

Ka Wan Li does research in Neuroscience since 1990 in the Vrije Universiteit Amsterdam, the Netherland. His current research focus on the characterization of protein nano-machineries that underlies synapse function and plasticity, and study synapse/tissue proteome changes in neurodegenerative and neuropsychiatric disorders. State-of-the-art quantitative proteomics techniques are employed, using both human post-mortem brain tissues from patients and healthy controls, and the diverse mouse models of brain disorders.

2.3. Clinical cohorts

Ed Nice (Australia)

Pathology, Proteomics and Precision Medicine (10 min research+5 min future) 

Abstract

The last 20 years has seen rapid advances in genomics, proteomics, and other omics technologies with both the human genome and proteome now being at >90% completion at high stringency [1]. Attention is now turning to understanding the function of each protein and it’s role  both in wellness and disease as we undergo a paradigm shift in medical treatment from the traditional “one size fits all” approach, where all patients receive the same standardised treatment for a particular disease, many drugs proving to be ineffective for much of the population, to a personalised/precision medicine (PM) approach in which treatment is tailored for a specific individual based on an understanding of their individual systems biology (comprehensive in-depth monitoring of genes, proteins), disease related pathways, lifestyle and environmental factors [2,3]. Aided by the comprehensive toolbox that has been developed, the omics pipeline (genomics, transcriptomics, proteomics, metabolomics, interactomics and microbiomics) can provide an overall systems biology perspective of health and disease, leading to the identification of potential biomarkers for disease detection and surveillance, the unravelling of key disease-related biological pathways and the identification of novel drug targets. Close interactions with pathologists and clinicians will be essential for the successful development of these initiatives. To this end the HUPO Pathology Pillar was established in 2018.

In this presentation, I will introduce precision medicine, discuss the role of pathology in supporting it’s role out and future directions, introduce some of the emerging technologies which will assist that, and, using colorectal cancer as a model system, suggest how precision medicine could help eliminate this major health problem.

1. Adhikari et al. A high-stringency blueprint of the human proteome. Nat Commun, 2020,11(1):5301.
2. Su et al. Proteomics, Personalized Medicine and Cancer. Cancers (Basel). 2021, 13(11):2512.
3. Yurkovichet al. The transition from genomics to phenomics in personalized population
health. Nat Rev Genet 2024, 25 (4), 286-302.

Bio

Ed Nice is currently a Professor at Monash University where he is Head of Clinical Biomarker Discovery and Validation (Department of Biochemistry and Molecular Biology) and a scientific advisor to the Monash Antibody Technologies Facility (MATF. He is also a Visiting Professorship at Sichuan University/West China Hospital. His long-term research interests have been in protein and peptide micropurification, biomarker discovery and validation, SPR analysis, high throughput monoclonal antibody production and validation, clinical biomarker assay development and personalised/precision medicine, with a strong translational focus on colorectal cancer. He has an active involvement in the Human Proteome Organization (HUPO and is currently co-chair of the Pathology Pillar, co-chair of the Human Cancer Proteome Project, a member of the B/D HPP executive committee and leader of the HUPO Chromosome 7 initiative.

Uwe Völker (Germany)

Population proteomics (10 min research+5 min future)

Abstract

TBC

Bio

Prof. Uwe Völker leads the Department of Functional Genomics at the University of Greifswald, where his research focuses on the physiology of microorganisms, transcriptome and proteome analyses, and in-vivo proteomics in host-pathogen interactions. His interdisciplinary work advances our understanding of microbial behavior and the mechanisms of infectious disease. Prof. Völker has an extensive publication record and is an active member of the scientific community, contributing valuable insights to the field of functional genomics.

Paola Roncada (Italy)

One Health Proteomics (10 min research+5 min future)

Abstract

The One Health framework, which emphasizes the interconnectedness of human, animal, and environmental health, has gained recognition as a holistic approach to addressing complex global health issues. Proteomics, the large-scale study of proteins, offers a powerful tool to explore the molecular underpinnings of health and disease across species and ecosystems. Recent advancements in applying proteomic technologies within the One Health paradigm, were done, highlighting how these methods can enhance our understanding of zoonotic diseases, antimicrobial resistance (AMR), and environmental contaminants affecting public health. Proteomics allows for the identification of biomarkers for early disease detection, monitoring of pathogen spillovers, and assessment of antimicrobial resistance mechanisms in both clinical and agricultural settings. Additionally, environmental proteomics reveals the impacts of pollutants and climate change on biodiversity, which in turn influences disease dynamics. Integrating proteomic data with genomics, metabolomics, and epidemiological findings across human, veterinary, and environmental sectors could lead to robust surveillance systems and more targeted interventions. This interdisciplinary approach supports the development of predictive models and precision health strategies, with the potential to transform public health responses globally. Further research should focus on standardizing methodologies, expanding cross-sectoral data sharing, and fostering collaborations to translate proteomic discoveries into practical One Health solutions. As global health challenges become more complex, integrating proteomics into the One Health initiative offers unparalleled opportunities to understand and address these interconnected issues.

References:
1: Roncada P, Modesti A, Timperio AM, Bini L, Castagnola M, Fasano M, Urbani A. One medicine--one health--one biology and many proteins: proteomics on the verge of the One Health approach. Mol Biosyst. 2014 Jun;10(6):1226-7. doi: 10.1039/c4mb90011a. Epub 2014 Apr 29. PMID: 24777557.

2: Tilocca B, Soggiu A, Iavarone F, Greco V, Putignani L, Ristori MV, Macari G, Spina AA, Morittu VM, Ceniti C, Piras C, Bonizzi L, Britti D, Urbani A, Figeys
D, Roncada P. The Functional Characteristics of Goat Cheese Microbiota from a One-Health Perspective. Int J Mol Sci. 2022 Nov 16;23(22):14131. doi: 10.3390/ijms232214131. PMID: 36430609; PMCID: PMC9698706.

3: Tilocca B, Greco V, Piras C, Ceniti C, Paonessa M, Musella V, Bava R, Palma E, Morittu VM, Spina AA, Castagna F, Urbani A, Britti D, Roncada P. The Bee Gut Microbiota: Bridging Infective Agents Potential in the One Health Context. Int J Mol Sci. 2024 Mar 27;25(7):3739. doi: 10.3390/ijms25073739. PMID: 38612550; PMCID: PMC11012054.

4: Tilocca B, Soggiu A, Musella V, Britti D, Sanguinetti M, Urbani A, Roncada P. Molecular basis of COVID-19 relationships in different species: a one health perspective. Microbes Infect. 2020 May-Jun;22(4-5):218-220. doi: 10.1016/j.micinf.2020.03.002. Epub 2020 Mar 17. PMID: 32194253; PMCID: PMC7102648.

5: Tilocca B, Soggiu A, Greco V, Sacchini F, Garofolo G, Paci V, Bonizzi L, Urbani A, Tittarelli M, Roncada P. Comparative proteomics of <i>Brucella melitensis</i> is a useful toolbox for developing prophylactic interventions in a One-Health context. One Health. 2021 Apr 23;13:100253. doi: 10.1016/j.onehlt.2021.100253. PMID: 33997237; PMCID: PMC8100217.

Bio

Paola Roncada is full professor of Microbiology and Animal Infectious disease at University Magna Græcia of Catanzaro, Italy. She obtained her Master Degree in Medicinal Chemistry at University of Milano in 1995 and the PhD in biochemistry at University of Sassari in 2001.
The results of Professor Roncada's research activity is reported in more than 118 publications in international journals with anonymous review (peer review), H index is 34 (Scopus 07.11.24) She is therefore the author or co-author of more than three hundred works, including communications to national and international congresses. Over the years, Professor Roncada has been particularly dedicated to studies of proteomics, a discipline that she has applied to the study of One Health approach, on microorganisms in the veterinary public health sector, applying advanced molecular methodologies to the etiopathogenetic and diagnostic study of diseases of medical-veterinary interest, even in animal models. He also applied proteomics by investigating phenotypic adaptations of microbiota and more in general microbial consortia in complex matrices, both animal and food of animal origin. It has also applied these methodologies in the field of veterinary reproduction and animal production, in the field of allergens and on animal models of diseases. She is involved in different international and national projects, as ERA NET, COST ACTIONS, AND EU KBBE, as listed. She was invited and keynote speakers in several international and national congress.

3. Proteomics-driven drug discovery

Ben Collins (UK)

Proteomics can drive drug discovery (10 min research+5 min future)

Abstract

As proteomics technologies have matured there is increasing focus on their utility in applied settings. Much energy is now (rightly) spent pursuing goals related to personalized medicine via proteomic analysis of clinical materials. However, there is a second applied space that, to date, has received less attention in the academic proteomics world. The pharmaceutical and biotech industry increasingly rely on proteomics tools to generate actionable information at many stages along the drug discovery and development pipeline. This includes a big pharma, but also a rich ecosystem of startup companies that have proteomics at the core of their platform approaches, and CROs that provide such services to drug discovery companies. The strong interest from drug discovery is driven by (i) the understanding that proteomics can provide robust and rich information (i.e. proteomics works in a way and at a scale it did not ~10 years ago!), and (ii) the emergence of alternative therapeutic modalities for which proteomics technologies are particularly well suited to provide actionable information (targeted protein degradation, chemically induced proximity, covalent inhibitors, antibody drug conjugates, …). However, the level of investment in this space is not outwardly apparent as much of the research goes on behind closed doors in companies and only a fraction reaches the literature. In this talk I will present some perspectives on this field with some focus on the idea that academic researchers with expertise in proteomics can have substantial value to add and should engage.

Bio

Ben is Professor of Proteomics and Chemical Biology 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.

Bernd Wollscheid (Switzerland)

From surface proteomics to drug discovery (10 min research+5 min future)

Abstract

The molecular nanoscale organization of the surfaceome is a fundamental regulator of cellular signaling in health and disease. Technologies for mapping the spatial relationships of cell surface receptors and their extracellular signaling synapses would unlock theranostic opportunities to target protein communities and the possibility of engineering extracellular signaling. At the Westlake Symposium for the Future of Proteomics, I will describe the development and application of an optoproteomic technology termed LUX-MS that enables the targeted elucidation of acute protein interactions on and in between living cells using light-controlled singlet oxygen generators (SOGs). By using SOG-coupled antibodies, small molecule drugs, biologics, and intact viral particles, I will demonstrate the ability of LUX-MS to decode ligand-receptor interactions across organisms and to discover surfaceome receptor nanoscale organization with direct implications for drug action. LUX-MS-based decoding of surfaceome signaling architectures provides a molecular framework for rationally developing theranostic strategies. In the context of the TumorProfiler project under development, I will further highlight new Swiss/ETH projects integrating proteotyping with other technologies for digitizing patient samples, such as pharmacoscopy,  geared towards supporting clinical decision-making.

Bio

Bernd Wollscheid, Ph.D., is founder of DISCO Pharmaceuticals. He is a Professor of Molecular Health and Head of the Institute of Translational Medicine at the Department of Health Sciences and Technology at ETH Zürich, Switzerland. As the chairman of EC of the ETH domain Strategic Focus Area, “Personalized Health and Related Technology (PHRT),” he aims to bridge the gap between scientific discoveries and their practical applications in healthcare. Bernd’s research team pioneers developing and applying next-generation technologies at the intersection of biology, chemistry, medicine, and bioinformatics. This research contributes to understanding how molecular nanoscale organization influences cellular function and opens up new opportunities for theranostics.

Bernd studied Chemistry and holds a Ph.D. in Molecular Immunology from the Max Planck Institute of Immunobiology in Freiburg, Germany. He performed post-doctoral research at the Institute of Systems Biology, Seattle, USA.

4. Proteomics for Agriculture

Qingsong Lin (Singapore)

Proteomics Revolution: Transforming Food, Agriculture, and Aquaculture Research (10 min research+5 min future)

Abstract

In the past three decades, proteomics has experienced tremendous growth, primarily advancing human biological and biomedical research. Significant developments have been made in a range of technologies, from protein isolation and separation to various approaches for protein identification and quantification, including both mass spectrometry (MS)-based and alternative, non-MS techniques. These advancements are supported by sophisticated bioinformatics tools, data handling systems, and high-capacity storage solutions, all of which have propelled proteomics to new heights.
However, the application of proteomics in other essential fields—such as food science, agriculture, and aquaculture—has not kept pace, leaving many opportunities for exploration. This presentation will provide an overview of some of our recent efforts to bridge this gap, applying proteomics to address challenges and unlock insights within these industries. I will also discuss future perspectives, focusing on how expanding proteomics in these areas could drive innovation and address critical global needs.

Bio

Qingsong LIN is a Principal Research Fellow (Research Associate Professor) of the Department of Biological Sciences, National University of Singapore (NUS).  He obtained B. Sc in Biochemistry (1991) and M. Sc. In Enzymology (1994) from Xiamen University, China, and Ph. D. in Clinical Biochemistry (2002) from University of Toronto, Canada. He is currently the Director of the Protein and Proteomics Centre (PPC), NUS, and the Corresponding Principal Investigator of SingMass (Singapore National Laboratory for Mass Spectrometry). 
Besides, he has been the President of the Singapore Mass Spectrometry Society during 2017-24, and a council member of the Human Proteome Organization (HUPO) during 2021-24.  His expertise lies in applications of mass spectrometry in proteins and proteomics, extended to other biomolecules.  His research interests are mainly in disease biomarker discovery and disease mechanism, drug target identification and mechanism of action studies, as well as the application of mass spectrometry and quantitative proteomics technologies to address various biological questions. He has published over 150 peer-reviewed papers to date.

5. AI proteomics

5.1. MS and AI

Paulo Costa Carvalho (Brasil)

Mass Spectrometry Beyond Boundaries: AI Solutions for Unsolved Challenges in Proteomics  (10 min research+5 min future)

Abstract

AI Solutions for Unsolved Challenges in Proteomics.
In this talk, I will introduce three transformative applications of AI within proteomics, each addressing challenges that remain unsolved by current methodologies. The first focus is Scout, a search engine specifically designed to process cross-linking mass spectrometry data on a proteome-wide scale. Validated against a dataset from recombinant proteins, Scout outperformed existing tools, delivering unmatched speed and the most reliable False Discovery Rate (FDR) for precise protein-protein interaction mapping. The second application showcases AI-driven diagnostics for cerebral pathologies. Our novel approach achieves differential diagnoses for conditions indistinguishable by MRI alone, which currently necessitate invasive brain biopsies. By leveraging blood-based tandem MS patterns, our AI model enables non-invasive diagnostics with accuracy comparable to biopsy-based methods. Lastly, I present an unbiased, AI-integrated mass spectrometry framework for evaluating the efficacy of bioactive compounds in skin treatments. This approach reliably assesses the “rejuvenating effects” of skin bioactives without the biases inherent in traditional evaluations, utilizing a model trained on the skin profiles of varying ages.

Bio

Dr. Paulo Costa Carvalho, holds a BSc in engineering, an MSc inMolecular Biology from Fiocruz, and a PhD in Systems Engineering and Computer Science from the Federal University of Rio de Janeiro with major in Artifitial Inteligence. He is an alum of the Laboratory for Biological Mass Spectrometry, directed by Prof. John R. Yates (h-index 210) at the Scripps Research Institute in California, USA. Throughout his career, Paulo has made several contributions to the field of computational mass spectrometry which culminated in several notable awards, including the Google Award for Academic Excellence and the CAPES Award for being among the top-3 PhD thesis in Brazil on three ocasions (once as a student and twice as mentor), and the Vichy Exposome Award (2022). Moreover, he made history in 2019 as the first and only Brazilian to receive the esteemed Institute Pasteur Talent Award; this honor recognizes his outstanding scientific career, placing him among the top researchers from 33 countries within the International Pasteur network. Presently, as a full researcher at Fiocruz Paraná, Paulo heads the Laboratory for Structural and Computational Proteomics. He also serves as a full professor at the graduate level, where he mentors MSc and Ph.D. students. With over 150 papers to his name, he was admitted into Brazil’s research Council’s exclusive group of sponsored researchers, a testament to the recognized quality of his research. As founding member of the Brazilian Society for Proteomics, Paulo contributes to its scientific committee and has served as an executive editor for the Journal of Proteomics, the official journal of the European Proteomics Association, since October 2014. Further demonstrating his commitment to scientific advancement, Dr. Carvalho has secured several prestigious national and international grants, including CNPq Universal, Papes Jovem Cientista, Fiocruz Inova, and Microsoft Research. He is also highly regarded for his collaborations with industry partners, including Nitto Aveccia (USA), Nova Analítica (Brazil), and O Boticario (Brazil), and continues to coordinate projects with these and other organizations.

Tiannan Guo (China)  

Two action plans for AI proteomics: MassNet and iYeast (10 min research+5 min future)

Abstract

Here I will introduce the AI proteomics initiative, and propose two research projects. One is to build an imageNet like curated data resource for proteomics data analysis. The 2nd one is a proposal of building a digital yeast cell.

Bio

Tiannan Guo – Laboratory for Proteome Complexity Science

Qing Zhong (Australia)

Federated deep learning enables cancer subtyping by proteomics (10 min research+5 min future)

Artificial intelligence applications in biomedicine face major challenges from data privacy requirements. To address this issue for clinically annotated tissue proteomic data, we developed a Federated Deep Learning (FDL) approach (ProCanFDL), training local models on simulated sites containing data from a pan-cancer cohort (n=1,260) and 29 cohorts held behind private firewalls (n=6,265), representing 19,930 replicate data-independent acquisition mass spectrometry (DIA-MS) runs. Local parameter updates were aggregated to build the global model, achieving a 43% performance gain on the hold-out test set (n=625) in 14 cancer subtyping tasks compared to local models, and matching centralized model performance. The approach's generalizability was demonstrated by retraining the global model with data from two external DIA-MS cohorts (n=55) and eight acquired by tandem mass tag (TMT) proteomics (n=832). ProCanFDL presents a solution for internationally collaborative machine learning initiatives using proteomic data, e.g., for discovering predictive biomarkers or treatment targets, while maintaining data privacy.

Bio

Dr. Qing Zhong is an Associate Professor at the University of Sydney. He completed both his undergraduate and doctoral studies in computer science at ETH Zurich (Swiss Federal Institute of Technology). After earning his PhD, he conducted postdoctoral research at the University of Zurich and later served as a Senior Data Scientist at University Hospital Zurich. Since 2017, Dr. Zhong has led the Cancer Data Science Group at ProCan in Children's Medical Research Institute, with his research focusing on large-scale cancer data analysis, machine learning, and computational biology.

5.3. AI-empowered Perturbation biology

Chris Sander (USA)

Challenges for perturbation biology: AI methods and focus on human health (10 min research+5 min future)

Abstract

Challenges for perturbation biology in the pi-Hub project: AI methods and focus on human health.

Bio

Chris Sander was trained as a theoretical physicist and as postdoc switched to theoretical biology. He founded two computational biology departments—at the European Molecular Biology Laboratory and Memorial Sloan Kettering Cancer Center -- co-founded the research branch of the European Bioinformatics Institute and built a center for computational biology at Dana-Farber Cancer Institute.

Now at Harvard Medical School his group and collaborators focus on solving hard biological problems using AI and statistical learning at the level of molecules, cells and humans. (1) EVcouplings: Protein structure and function from natural and experimental evolution – building on the concept of co-evolution developed by him for the first successful protein folding twelve years ago and now a key ingredient in the latest methods for protein structure prediction. (2) CancerRiskNet: Identifying high risk of cancer from real-world clinical records using machine learning. They analyze real-world clinical records to define patient groups at high risk for aggressive cancers and collaborate with clinicians to design screening programs aimed at catching cancer early. (3) Perturbation Biology & CellBox: after laying the foundational concept of perturbation biology, they derive computational models of cell biological processes from large-scale and single cell perturbation-response experiments, especially using mass spec protein profiling, and the design of anti-resistance cancer combination therapy.

As a service to the research community, they build tools for the research and clinical communities, such as the evolutionary couplings server for highlighting co-evoluation patterns in protein sequences and 3D structures and mutation effects of genetic variation, with focus on human genomes; the Pathway Commons knowledge resource; and the cBioPortal for Cancer Genomics in collaboration with the Knowledge Systems Groups at MSKCC and DFCI.

Publications:
by publication date http://bit.ly/ACCayl & by citation count http://bit.ly/yAdPhU

5.4. Multi-modal integration

Kang Zhang (China)

Enhanced AI model performance and clinical applications by multi-modal integration and diverse data sources (10 min research+5 min future)

Abstract

Integrating multi-modal data—including imaging, multi-omics , and electronic health records—enables a more comprehensive assessment of a patient health and disease status, which is beneficial in complex disease management.

Merging diverse data sources including synthetic medical data enhance AI model accuracy and generalization by incorporating a large amount of synthetic complementary information and mitigating data biases, especially in cases of incomplete, inconsistent data, or rare diseases. This multi-source integration strengthens diagnostic support and enables more precise disease progression predictions, allowing clinicians to develop personalized treatment plans. Using synthetic medical data also help overcoming a major challenge of data scarcity and privacy issues in healthcare and medicine.

Recent technological innovations, such as cross-modal learning with Transformer models and multi-modal pre-training, and digital twin technology support improved feature integration and model adaptability to clinical tasks. These advancements enhance AI’s capacity to process and interpret complex, multi-dimensional data, increasing its utility in clinical applications.

Looking forward, multi-modal AI integration holds transformative potential across medical fields, enabling clinicians to make data-driven, informed decisions. Enhanced integration and AI advancements are paving the way for improved patient outcomes, fostering significant progress in personalized and precision medicine and biomedical research.

Bio

Professor Kang Zhang, MD,PHD is President of the World Association of Chinese Eye Doctors, the chief scientist of the National Clinical Medical Research Center for Eye Diseases, Director of the Advanced Research Institute of Eye Health and Diseases of Wenzhou Medical University, Director of Clinical Big Data Research Institute of Wenzhou Medical University.Pro. Zhang obtained his M.D. with Magna Cum Laude honors from Harvard Medical School and MIT joint MD program and his PhD in genetics from Harvard University. He did his postdoctoral training also at Harvard. He completed his residency in ophthalmology at Johns Hopkins University and his retina surgery fellowship at University of Utah. Prior coming to Wenzhou, he was the founding director of Institute for Genomic Medicine, Professor of Ophthalmology, Nanoengineering, and Genetics at University of California San Diego. Among his honors include an elected fellow of AAAS, AIBME, Association of American Physicians, American Society of Clinical Investigation, Royal Society of Medicine, Royal Society of Chemistry; Burroughs Wellcome Clinical Scientist Award in Translational Research; Steinbach Award, the Ophthalmologist 100 World Power list, American’s Top Ophthalmologists, Clarivate Highly Cited Researchers in Cross-Field from 2019 to 2023. Dr. Zhang has published over 300 peer reviewed manuscripts in top peer-reviewed journals- covering a wide range of topics including artificial intelligence and clinical trials.  He has more than 75,000 citations and an H-index of 114. His research has been extensively covered by prominent news media including New York Times, Wall Street Journal, The Guardian, LA Times, Xinhua News Agency, People’s Daily, NBC, CBS 60 Minutes, ABC, BBC, and CCTV.

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