HUPO Awards - 2023 recipients

DISTINGUISHED ACHIEVEMENT IN PROTEOMIC SCIENCES AWARD

The Distinguished Achievement in Proteomic Sciences Award recognizes a scientist for distinguished scientific achievements in the field of proteomic science.

Bernhard Küster, Technical University of Munich, Germany

The Discovery in Proteomic Sciences Award recognizes a scientist for a single discovery in the field of proteomics.

Hannes Röst, University of Toronto, Canada 

Hannes is a world-wide leader who has developed the field’s main analysis strategies and statistical algorithms: During his PhD thesis, he co-developed the SWATH-MS method through simulations that were crucial to demonstrate feasibility of the approach and then invented the OpenSWATH algorithm (Nature Biotechnology 2014), the pioneering software for targeted analysis of DIA data. It matched the quantitative performance of previous targeted proteomics methods), while increasing their throughput by orders of magnitude. As a postdoc with Mike Snyder, Stanford, he developed the TRIC algorithm (Nature Methods 2016), the first crossrun alignment algorithm (“match between runs”) for targeted proteomics data. It solved the problem of chromatographic retention time shifts in targeted proteomics, allowing to scale proteomics experiments to over 1000 samples to study longitudinal variation in human blood plasma (Cell Systems 2018, Nature 2019). Recently he developed the theoretical and computational basis for the completely novel DIA method diaPASEF, combining trapped ion mobility with DIA by synchronizing the quadrupole position for DIA isolation to the ion mobility elution. The method achieves unprecedented number of peptide and protein identifications on a TOF instrument (Nature Methods 2020).

CLINICAL AND TRANSLATIONAL PROTEOMICS AWARD

The Clinical and Translational Proteomics Award recognizes a scientist in the field of clinical and translational proteomics.

Rebekah Gundry, University of Nebraska Medical Center, USA

Rebekah’s technological developments include methodologies and bioinformatic tools to advance our analysis of glycoproteins and glycan structures in clinical samples. CellSurfer (Nature Cardiovascular Research, 2023) is a new automated cell surface glycoproteomics profiling platform. CellSurfer enables highly specific and rapid analysis of human primary cell surfaceomes. Accompanying novel bioinformatic tools include SurfaceGene, CIRFESS, and Veneer, which altogether expedite the discovery, analysis, annotation, and candidate prioritization for downstream validation. These bioinformatic tools are freely available as easy to use web applications, which promote adoption by other investigators. Veneer is the first tool to provide standardized processing and reporting of mammalian cell surface glycoproteome data, which is urgently needed in the proteomics field. glyPAQ is a new high throughput sample preparation approach for structural glycomics. glyPAQ enables, for the first time, automated, high throughput sample preparation of clinical samples for structural isomer quantification. glyPAQ is easy to use, which will encourage future implementation by investigators without previous expertise in glycomics. glyPAQ is poised to impact the proteomics field by providing a way for more investigators to include glycan structures in their analyses, which is becoming recognized as the next ‘omics wave for clinical biomarker development. 

SCIENCE AND TECHNOLOGY AWARD

Recognizes an individual or a team in private industry for the commercialization or (not necessarily) the invention of products, technologies or procedures which had the demonstrated effect in enabling proteome researchers to advance their science.

Sponsored By:  HUPO Industrial Advisory Board (IAB)

Alexey Chernobrovkin and Tomas Friman, Pelago Bioscience

The team developed methodology and implemented a framework for analysis of global cellular thermal shift assay (CETSA®) data. The protocol entails processing of search engine output files (data filtering and normalization), statistical analysis & visualization as well as results sharing and browsing in an on-line data portal format. This has been instrumental in the communication of project output data to external customers, collaborators and colleagues.  Furthermore, at Pelago they have been instrumental in designing and carrying out large scale, inhouse studies applying CETSA® MS to profile large compound sets in live cells. To date, this collection of CETSA fingerprints is made up from >400 test compounds across 3 cell lines (K562, HepG2 & U87MG) covering a wide range of different compound classes & disease areas and in different cellular matrices.  The data analysis methodology and platform allows efficient processing and in-depth analysis of large scale LC-MS based CETSA® MS proteome profiling data. In addition, the large scale in-house studies analysed add significantly to our understanding of general and specific cellular responses, typical reaction patterns and phenomena observed in CETSA® experiments. The team has recognised that there is a heavy responsibility to control a patent, in that you should then also lead the field towards the the best applications and use.  

RISING STAR AWARD 

This career achievement award is designed to recognize early career researchers who have had an exceptional impact on the proteomics field and community. This impact can take the shape of publications, patents obtained, development of a commercial product, establishment of a course, training program, workshop or any other contributions or service to the field of proteomics. 

Sponsored By: HUPO Early Career Researcher (ECR) Committee

Nicholas M. Riley, University of Washington, USA

Nick’s impact is apparent across all levels. His research has been at the leading edge of significant advances in glycoproteomics in the past 5 years. His contributions have made a huge impact on our group and at Stanford, too. Nick’s expertise in mass spectrometry and proteomics has truly opened new avenues to research directions and collaborations that leverage proteomics, phosphoproteomics, and glycoproteomics. In fact, 3 new proteomics-oriented postdocs were hired to maintain the momentum Nick has established. Importantly his outreach efforts also make sure others across our communities get access to great science.  Nick’s work with AI-ETD helped set the stage for an exciting era of electron-based dissociation. Multiple new electron-based technologies look to capitalize on principles described in Nick’s work with AI-ETD, even if they use different implementations. His impact is not just AI-ETD, though. His work with glycoproteomics data analysis and visualization has also generated a lot of excitement that has been used by many other labs. Perhaps his most important impact has been on people. His mentoring and inclusion of many people have made sure proteomics is growing in positive directions as a community.  Nick excels at recognizing the gaps in technology that will enable interesting biological questions, which is what makes his work impactful. Both the O-Pair Search algorithm and the invivo secretome labeling strategies required creativity that draws from deep understanding of diverse fields, e.g., MS, chemical biology, data analysis. These tools now democratize previously inaccessible O-glycopeptide analysis – a true gap in the field – and his secretome work can be broadly useful across many fields. It is this combination of originality, productivity, and leadership that will make Nick’s independent research group so exciting to watch!  Nick's contributions include 14 first author papers speak to the breadth and impact his work with AI-ETD has across multiple applications. Nick’s training in MS-based proteomics is clearly being put to good use; his recent publications underscore how he is combining his technical skill set with his new expertise in glycobiology to develop inventive methods. The reputation Nick has already built across our field shows that his work has been broadly used.