HUPO 2025

An Integrated Workflow for High-throughput Analyses of Protein and Protein Post-Translational Modification Landscapes

Hui Zhang, Ph.D., Professor of Pathology, Oncology, Urology, and Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA

Abstract:

The integration of proteomic technologies into clinical practice indeed holds significant promise for revolutionizing disease diagnosis, prognosis, and treatment. By delving into the intricate world of proteins and their modifications in high-throughput workflow, researchers aim to unravel the complexities underlying various diseases.

The advanced mass spectrometry-based proteomic technologies also offer unprecedented opportunities to investigate the interplay between genomic, transcriptomic, and proteomic alterations. By employing these technologies to investigate tumors and precancerous lesions, we have gained invaluable insights into cancer biology, particularly pertaining to protein modifications such as glycosylation, phosphorylation, acetylation, and ubiquitination. 

Exploring non-canonical interactions of G protein-coupled receptors using unbiased proteomics

Ruth Huttenhain, Ph.D., Assistant Professor, Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA

Abstract:

G protein-coupled receptors (GPCRs) are essential mediators of cellular signaling, detecting a wide range of external stimuli and translating them into specific cellular responses. According to the prevailing signaling paradigm, the ~1,000 human GPCRs exert their biological effects primarily by engaging two canonical effectors: heterotrimeric G proteins and β-Arrestins (ARRBs). Yet this model does not fully account for the remarkable diversity of GPCR-mediated physiological outcomes.

Emerging evidence indicates that GPCRs also engage additional, non-canonical signaling pathways via interactions with proteins beyond G proteins or ARRBs, often through intrinsically disordered regions (IDRs) in GPCR cytoplasmic domains. These non-canonical interactions can be initiated by selective phosphorylation of the receptors’ active conformations by GPCR kinases (GRKs), ensuring that the resulting signaling events are dependent on receptor activation.

To understand the prevalence of non-canonical GPCR signaling, we developed a high-throughput proximity labeling (PL) proteomics platform creating time-resolved maps of GPCR interactions. By profiling interaction networks of biologically diverse GPCRs after activation in HEK293A wildtype, GRK-, and ARRB-knockout cells, we identify both known and novel interactions of the activated receptors and their dependence on GRKs and/or ARRBs. For example, we discovered a novel GRK-dependent but ARRB-independent interaction between the RF-amide receptor NPFFR1 and the CUL1-FBXW11 E3 ligase.

Integrating proximity-labeling proteomics data with AlphaFold-based structural prediction and biochemistry, our study promises to reveal previously unrecognized, non-canonical signaling mechanisms across GPCR families, providing new insights into GPCR function and extending the current signaling paradigm.

Tackling a next frontier in proteomics: template free de novo sequencing of endogenous antibodies enabled by the timsOmni™

Albert Heck, Ph.D., Distinguished Faculty Professor of Chemistry and Pharmaceutical Sciences, Utrecht University and Scientific Director, Netherlands Proteomics Center, Utrecht, Netherlands

Abstract:

Immunoglobulins are among the most abundant proteins in our body, and in our blood. They play a key role in our humoral immune system, protecting us against microbial infections. Antibody diversity in humans is enormous and arises primarily through V(D)J recombination, a process that combines variable (V), diversity (D), and joining (J) gene segments in developing B cells that are responsible for antibody production. This mechanism, along with junctional diversification, generates an immense repertoire of antibodies, often estimated to range between 1015 to 1020 unique sequences, enabling our body to make antibodies against almost any pathogen. This vast pool of sequence diversity does not allow genome-template guided proteomics to identify the sequences of endogenous antibodies but makes protein-centric based de novo sequencing essential. In our laboratory we aim to advance antibody de novo sequencing, developing both new peptide-centric and protein-centric approaches.

I will describe how we advance protein-centric approaches, using the new timsOmni™ instrument, to obtain information on the complexity of the human antibody repertoire. The by Bruker/Fasmatech developed prototype timsOmni platform combines the capabilities of a timsTOF with the multiplexed and hybrid fragmentation techniques and flexibility of an Omnitrap®. We use the instrument to sequence in a protein-centric manner antibodies (or Fab fragment thereof) using combinations of CID and electron capture dissociation (ECD). The acquired data provide unambiguous sequence information especially about the relevant hypervariable CDR regions of the antibodies, which are essential for target recognition.

Scaling up and democratizing spatial tissue proteomics

Fabian Coscia, Ph.D., Group Leader, Spatial Proteomics Group, Max Delbrück Center, Berlin, Germany

Abstract:

Spatial proteomics (SP) is transforming our ability to understand the location, abundance, and interactions of proteins within cells and tissues, thereby allowing us to map protein networks precisely in space. SP technologies are currently revolutionizing our understanding of cellular structure and function (Method of the Year 2024, Nature Methods), offering profound insights into how protein distribution and dynamics influence both normal and disease processes. Our team has co-developed deep visual proteomics (DVP), which leverages high-resolution microscopy, AI-driven image analysis, and laser microdissection-enabled deep proteomic profiling. This approach enables the visualization, measurement, and linking of protein levels, subcellular locations, and post-translational modifications within a single preserved tissue section. In my talk, I will present an overview of our spatial tissue proteomics pipelines and discuss our current efforts to significantly improve their throughput, sensitivity, and accessibiopenDVP).

Antigen Discovery with High-Sensitivity Immunopeptidomics: From Biologics to (Immuno)Therapy Development

Elise Pepermans, Ph.D., CEO and Co-founder, ImmuneSpec, Antwerp, Belgium

Abstract:

The identification of tumor-specific antigens (TSAs) and tumor-associated antigens (TAAs) remains a central challenge in the development of (personalized) cancer immunotherapies. NeoEpitopipe integrates next-generation sequencing data with our optimized high-sensitivity immunopeptidomics platform. This combined approach enables the identification of an expanded repertoire of validated HLA peptides, including non-canonical, patient- and disease-specific variants and mutations such as somatic alterations, indels, and cryptic peptides. Our optimized immunopeptidomics workflow requires minimal sample input (as little as 5 mg of tissue) while delivering high-resolution peptide identification. This strategy significantly broadens the landscape of validated non-canonical antigens for immunotherapy, providing a robust framework for accurate neoantigen discovery.

From regulome maps to first-in-class targets through functional proteomics at scale

Lindsay Pino, Ph.D., Co-Founder and CTO, Talus Bio, Seattle, WA, USA

Abstract:

Transcription factors, cofactors, and chromatin regulators control gene expression yet remain poorly measured in their native context and historically hard to drug. We present “regulome profiling”, a functional proteomics approach that measures protein-DNA binding activity in live cells using a high-throughput DIA-MS readout. We discuss how the application of fundamental quantitative proteomics assay principles allow us to make comparisons of protein:DNA binding across cell types and perturbations, how we’ve scaled subcellular proteomics sample preparation, and why we support open-source data pipelines that convert proteomic signals into actionable, translational biological insights. We will highlight case studies from recent internal work to illustrate how these comprehensive maps of regulator activity reveal tractable intervention points across disease, support basic gene regulation biology, investigate mechanisms of toxicity and safety assessment, and our goals for AI foundation models.