Talks will be on topics including Clinical Proteomics, Structural Proteomics, Spatial Proteomics, Post-translational Modifications, New Technologies, Computational Proteomics, Single Cell Proteomics, Biomarkers and Artificial Intelligence.

Programme at a glance

All times shown are BST (UTC+01:00)

Detailed programme

This page is being actively reviewed with information being added as we finalise the BSPR Interact 2021 programme. The following programme is intended as a guide only, and is subject to change without notice.

Day 1: 6th July 2021

09:00 - 09:30 | Break, poster viewing and networking

Session 1

09:30 - 09:45 | Welcome address from the BSPR President, Steve Pennington

09:45 - 10:10 | Plenary talk presented by Paola Picotti, ETH Zürich Institute of Molecular Systems Biology

Proteomes in 3D


Biological processes are regulated by molecular events, such as intermolecular interactions, chemical modification and conformational changes, which do not affect protein levels and therefore escape detection in classical proteomic screens. Reasoning that these events affect protein structure, we tested whether a global readout of protein structure could detect various types of functional alterations simultaneously and in situ. We tested this idea using limited proteolysis coupled to mass spectrometry (LiP-MS), which monitors structural changes in thousands of proteins within a complex, native-like environment. In bacteria adapting to different nutrient sources and in yeast responding to acute stress, the structural readout, visualized as structural barcodes, captured enzyme activity changes, allosteric regulation, phosphorylation, protein aggregation and protein complex formation, with the resolution of individual regulated functional sites such as binding and active sites. Comparison with prior knowledge, including flux, phosphoproteomics and metabolomics data, showed that LiP-MS detects many known functional alterations within well-studied pathways. It suggested novel metabolite-protein interactions and enabled identification of a fructose-1,6-bisphosphate-based regulatory mechanism of glucose uptake in E. coli. The structural readout dramatically increases the coverage of classical protein expression profiling, generates mechanistic hypotheses, better links holistic and reductionist approaches, and paves the way for a new in situ structural systems biology.  

10:10 - 10:30 | Plenary 1 question and answer session

10:30 - 10:50 | Covaris sponsored talk by Jeroen Krijgsveld, German Cancer Research Center & University Heidelberg


Covaris Adaptive Focused Acoustics® (AFA®) technology is the most flexible and reproducible sample preparation platform available for mass spectrometry applications. AFA-energetics® has been for long the gold standard for shearing DNA and RNA for Next Generation Sequencing (NGS) and is setting new standards in proteomics (and metabolomics) pre-analytical methods. 

Numerous publications have assessed its efficiency and robustness in various conditions (volume, buffer, sample type) and throughputs (single tubes, 8-strips, 96-well and 384-well plates), assisting protein processing in different steps of the workflow including lysis, homogenization, accelerated enzymatic digestion and peptide resuspension. All those steps can be automated and are particularly well suited for use in combination with SP3 clean up.

Automated sample preparation for reproducible proteomics in biology and the clinic

Proteome analysis is typically performed by direct integration of chromatography and mass spectrometry, allowing unattended and standardized analysis of multiple samples. In contrast, sample preparation prior to LC-MS is still largely a manual process, constituting a major source of variability in sample handling and, ultimately, in proteomic data. Here, we present how we established a generic, automated workflow for proteomic sample preparation by combining AFA-based ultrasonication and single-pot solid-phase-enhanced sample preparation (SP3), enabling routine and standardized proteome analysis with minimal hands-on time. Sonication is used for protein extraction from virtually any sample type, including cells, fresh tissue and FFPE tissues in a 96-well format, followed by protein clean-up and digestion by SP3 performed on a Bravo liquid handling platform. Sensitivity and reproducibility of the approach will be shown from low-input experiments starting from 100-1000 cells, from fresh tissues of various organs, and from FFPE tissue sections of cancer specimens. Furthermore, we used this pipeline to analyze a cohort of 96 ependymoma brain tumor samples, and integrated the obtained proteomic data with other omics layers for disease sub-classification. In conclusion, AFA-based ultrasonication combined with autoSP3 is a robust platform for standardized and parallel processing of a variety of tissue types for low-input proteomics, serving a wide range of clinical and non-clinical proteomic applications.

10:50 - 11:00 | Covaris sponsored talk question and answer session

11:00 - 11:30 | Break, poster viewing and networking

Session 2 - Cell signalling and Emerging Technologies

11:30 - 11:31 | Session 2 introduction

11:31 - 11:35 | Vendor talk 

11:35 - 11:50 | Helen Cooper, University of Birmingham

Native ambient mass spectrometry: Mass spectrometry imaging of intact proteins and protein complexes

11:50 - 12:05 | Maria Robles, Ludwig Maximilian University of Munich

Daily cycles of protein and phosphorylation abundance regulating rhythmic physiology

Circadian clocks are cell endogenous and self-sustainable oscillators found in virtually every cell in the body that play a fundamental role in cellular and tissue physiology. This internal time-keeping system anticipates daily environmental changes to thus prepare organismal metabolism for those recurrent changes. We use MS-based label free quantitative proteomics to study organismal daily dynamics of protein and phosphorylation. In my talk I will present some of our proteomics work aiming to elucidate circadian clock mechanisms from molecular to system levels in health and diseases. 

12:05 - 12:20 | Joshua Coon, University of Wisconsin-Madison

New mass spectrometry technology for proteome analysis


In this presentation I will describe a variety of new mass spectrometry technologies for the analysis of proteins and proteomes. Through development of a multi-protease digestion strategy and the use of collisional and electron transfer dissociation we have achieved the deepest proteome analysis reported to date. This approach has led to the detection of over 17,000 gene products and the first ever global assessment of how mutations and splicing events are incorporated into the proteome. In another method we describe the use of ion mobility coupled with tandem mass spectrometry to directly analyze complex proteome mixtures at very high speeds. Finally, we describe a novel approach to prepare samples for transmission electron microscopy using native mass spectrometry to purify and collect protein complexes.  

12:20 - 13:00 | Discussion

13:00 - 14:00 | Poster session 

14:00 | Day 1 END



Day 2: 7th July 2021

09:00 - 09:30 | Break, poster viewing and networking

Session 3 - Early Career Researcher (ECR) Session

09:30 - 09:31 | Session 3 introduction

09:31 - 09:35 | Vendor talk

09:35 - 09:47 | ECR talk 1

09:47 - 09:59 | ECR talk 2

09:59 - 10:11 | ECR talk 3

10:11 - 10:23 | ECR talk 4

10:23 - 11:00 | Discussion

11:00 - 11:30 | Break, poster viewing and networking

Session 4 - Computational Proteomics

11:30 - 11:31 | Session 4 introduction

11:31 - 11:35 | Vendor talk

11:35 - 11:50 | Mischa Savitski, EMBL Heidelberg

Understanding post-translational regulation using biophysical proteomics

Mapping gene function and interactions has been revolutionized by the advent of high-throughput reverse genetic approaches. However, due to the large number of perturbations needed to empower the functional association of genes, these approaches are limited to growth or morphological readouts. We have recently developed thermal proteome profiling (TPP) to assess protein state and interactions in vivo. TPP is based on the principle that heat-induced protein aggregation depends on its binding to ligands (metabolites, nucleic acids or other proteins) or post-translational modifications.

Here, we combine thermal proteome profiling (TPP) with a reverse genetics approach to measure abundance and thermal stability of over 1,700 proteins upon 121 genetic perturbations in Escherichia coli. This revealed that essential proteins are rarely regulated in their abundance, but commonly change in their thermal stability—with this being related to changes in their activity. We found that functionally associated proteins have coordinated abundance and thermal stability changes across mutants, which are a result of their co-regulation and physical interactions (with metabolites, co-factors or other proteins). This allows us to suggest the function of uncharacterized proteins in a guilt-by-association manner. Further, we observed that deletion mutants with a larger proportion of their proteome affected were more sensitive to chemical and environmental perturbations. We were also able to pinpoint molecular changes that explain previously determined growth phenotypes and that go beyond the deleted gene.

In conclusion, TPP provides a novel way of systematically phenotyping the cell. This platform can be used to improve our understanding of basic bacterial biology by gaining insights into gene regulation, protein complex architecture, and metabolic activity.

11:50 - 12:05 | Oliver Crook, University of Oxford

Uncertainty and choices in mass spectrometry data science

Uncertainties arise in mass spectrometry because of the technical variability inherent in the instruments we use, the biologically variability in the samples, as well as the choices made by filtering and preprocessing. These choices are often employed to control an error rate or prioritise “hits”. This process can lead us to being overconfident in our results but, perhaps worse, overlook interesting biological results. Time permitting, I will introduce several examples from diverse areas of mass spectrometry including spatial proteomics, thermal proteome profiling and hydrogen-deuterium exchange mass spectrometry and show what tools we have to deal with errors and uncertainty in mass spectrometry data science

12:05 - 12:20 | Mike MacCoss, University of Washington

Can we put Humpty Dumpty back together again? What does protein quantification mean in bottom-up proteomics?

Bottom-up proteomics provides peptide measurements and has been invaluable for moving proteomics into large-scale analyses. In bottom-up proteomics, protein parsimony and protein inference derived from these measured peptides are important for determining which protein coding genes are present. However, given the complexity of RNA splicing processes, and how proteins can be modified post-translationally, it is overly simplistic to assume that all peptides that map to a singular protein coding gene will demonstrate the same quantitative response. Accordingly, by assuming all peptides from a protein coding sequence are representative of the same protein we may be missing out on detecting important biological differences. To better account for the complexity of the proteome we need to think of new or better ways of handling peptide data.

12:20 - 13:00 | Discussion

13:00 - 14:00 | Poster session

14:15 - 15:30 | BSPR Annual General Meeting

15:30 | Day 2 END



Day 3: 8th July 2021

09:00 - 09:30 | Break, poster viewing and networking

Session 5 - Single Cell and Clinical Proteomics

09:30 - 09:31 | Session 5 introduction

09:31 - 09:35 | Vendor talk

09:35 - 09:50 | Erwin Schoof, Technical University of Denmark

Characterizing heterogeneity within hematopoietic cell hierarchies using quantitative Single-Cell Proteomics approaches

In recent years, life science research has experienced a significant shift, moving away from conducting bulk cell interrogation towards single-cell analysis. It is only through single-cell analysis that a complete understanding of cellular heterogeneity, and the interplay between various cell types that are fundamental to specific biological phenotypes, can be achieved. The hematopoietic system is a prime example of such a complex hierarchy, where Hematopoietic stem cells (HSC) are the origin of all cell lineages contained therein. Acute myeloid leukemia (AML), a perturbed state of hematopoiesis, is also hierarchically organized, with leukemia stem cells (LSC) at the apex. Successful eradication of AML will likely depend on specific targeting of these tumour-initiating cells, in turn requiring their molecular characterization. 

Here, we have taken both healthy and malignant hematopoietic cells, and subjected them to fluorescence-activated cell sorting combined with novel single-cell proteomics (scMS) strategies to identify the protein landscapes of individual cells. We demonstrate both through pre-enrichment of cell populations and through a non-enriched unbiased approach that our workflow enables the exploration of cellular heterogeneity within developmental hierarchies. By using the latest state-of-the-art LC-MS instrumentation with intelligent data acquisition, this has resulted in unprecedented maps of protein expression in individual cells.  Furthermore, we developed a computational workflow (SCeptre) that effectively normalizes the data, clusters the cells, integrates available FACS data (i.e immunophenotype) and permits the extraction of cell-specific proteins. We found a strong enrichment of cell-type specific proteins in various compartments, and the resulting protein signatures clearly distinguish the differentiation stages that exist within their respective hierarchies. The results presented here support the power of implementing global single-cell proteomics studies in proteomics labs across the world.

09:50 - 10:05 | Tami Geiger, Tel Aviv University

Proteomic analysis of cancer internal heterogeneity

Cancer heterogeneity is one of the major challenges that hampers the ability to cure the disease. Tumors differ in their genetic profiles and the cellular interactions in the microenvironment, and each tumor may have multiple different clones with distinct molecular characteristics. Therefore understanding cancer heterogeneity has major translational implications. In breast cancer, different regions within single tumors may vary in the levels of key molecular markers, such as the estrogen receptor, progesterone receptor and HER2, and this heterogeneity affects metastasis and treatment response. Global analyses of internal heterogeneity have mainly concentrated on the genomic layer, revealing evolutionary trajectories, and their association with immune selection. However, focusing only on the genomic level ignores the functional proteomic layer of tumor subpopulations, and their interactions with the tumor microenvironment. Using mass spectrometry-based proteomics, we aim to understand the functional proteomic layer of cancer heterogeneity in breast cancer. We combined analysis of clinical samples with histopathological analysis and functional validations, to unravel novel regulators of cancer progression. To tackle the challenge of the very small sample amounts from tumor regions, we implemented an automated high-throughput pipeline, which combines the Single Pot Solid Phase Sample Preparation (SP3) technique with multiplexed TMT labeling. These methods enable highly sensitive sample preparation from small formalin-fixed tissue samples and from single cells in culture. Analysis of hundreds of breast cancer tumor regions unraveled the association between clinical parameters and the protein networks, and showed their heterogeneity within single tumors. Our research showed the importance of each clinical feature and the significance of the immune system in affecting tumor heterogeneity. Finally, the proteomic layer added the functional attributes that cannot be seen by any clinical measurement, thereby showing the importance of the protein complement in clinical cancer research.

10:05 - 10:20 | Christoph Messner, Francis Crick Institute

Ultra-high-throughput proteomics and its clinical applications

Biomarker discovery studies or precision medicine require the measurement of large sample series. However, conventional MS-based proteomics technologies are limited in throughput and robustness. To overcome these limitations we have developed a platform that consists of 1) a semi-automated and highly standardised sample preparation workflow that can process four 96-well plates in parallel; 2) a high flow-rate chromatographic setup (800 µl/min) for reduced overheads and increased robustness [1]; 3) the DIA-NN software package that uses deep neural networks and was specifically developed for the spectral complexity of short gradient runs [2], and 4) Scanning SWATH, a scanning quadrupole data-independent acquisition (DIA) method [3]. The latter accelerates the mass spectrometric duty cycles and exploits a continuous movement of the precursor isolation window to assign precursor masses to the MS2 fragment traces. This increases the precursor identifications of up to 70% compared to conventional DIA methods on 0.5-5 minute chromatographic gradients. We demonstrate the application of ultra-fast proteomics in COVID-19 patient classification and biomarker discovery. With gradients as fast as 1 minute, we identified a panel of plasma proteins that change depending on the severity of the disease. In conclusion, our results demonstrate a significant acceleration of proteomic experiments, facilitating large-scale clinical and epidemiological studies.

  1. Messner, C. B. et al. Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection. Cell Systems (2020) doi:10.1016/j.cels.2020.05.012.

  2. Demichev, V., Messner, C. B., Vernardis, S. I., Lilley, K. S. & Ralser, M. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nat. Methods 17, 41–44 (2020).

  3. Messner, C. B. et al. Ultra-fast proteomics with Scanning SWATH. Nat. Biotechnol. (2021) doi:10.1038/s41587-021-00860-4

10:20 - 11:00 | Discussion

11:00 - 11:30 | Break, poster viewing and networking

Session 6

11:30 - 11:31 | Session 6 introduction

11:31 - 11:35 | Vendor Talk 5

11:35 - 11:40 | ECR Prizes

11:40 - 11:45 | Poster winner

11:45 - 12:20 | Plenary talk presented by Bernhard Küster, Technical University of Munich

Watching drug action in cancer cells through the proteomic burning glass

Most drugs act directly on proteins, are proteins themselves or engage cellular pathways controlled by proteins. It, therefore, comes as no surprise that proteomics has become an integral part of modern drug discovery research, particularly when screening compounds in phenotypic assays. Here, success stories from the past include target deconvolution using immobilized drugs as affinity tools, thermal proteome profiling or exploiting other biophysical properties on a protein-drug interactions. 

More recently, the field of chemical biology has become to rely a great deal on proteomics to find out if and how chemical probes engage their targets in cells. Prominent examples are Cys- or Lys-reactive molecules or protein degraders such as PROTACs. This talk will touch on some of these aspects but will mostly deal with the impact of drugs on post-translational modifications such as phosphorylation, acetylation or ubiquitinylation because many cancer drugs directly or indirectly impinge on signaling pathways regulated by PTMs. Examples that will be covered are classic chemotherapeutics, kinase, phosphatase, HDAC and protease inhibitors as well as antibodies. I will discuss what can be learned from monitoring PTMs in response to drugs and show that the proteomic burning glass uncovers an entire new micro cosmos of proteins and PTMs with implications for drug discovery and patient stratification and monitoring.

12:20 - 12:45 | Question and answer session

12:45 - 13:00 | Close 


13:15 - 14:30 | The Kathryn Lilley Quiz!


14:30 | Day 3 END

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