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)
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
Opening Session | Sponsored by Covaris
Session chair: Sara Zanivan | Session co-chair: Maike Langini
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
The Covaris R230 Focused-ultrasonicator is one of the newest Focused-ultrasonicators. With its small footprint, it is perfect for use on-bench or integrated on-deck in a liquid handler. This truly versatile instrument can process mid- to ultra high-throughput to meet all of your current and future needs. The compact R230 was designed to help you achieve optimal workflow efficiency, automation capabilities and standardized sample prep for NGS and Proteomics.
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.
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 | Sponsored by Promega
11:30 - 11:31 | Session 2 introduction
11:31 - 11:35 | Promega talk presented by Hillary Pollard
11:35 - 11:50 | Helen Cooper, University of Birmingham
Native ambient mass spectrometry: Mass spectrometry imaging of intact proteins and protein complexes
Mass spectrometry imaging (MSI) provides information on the spatial distribution of molecules within a biological substrate, such as a thin tissue section, without the requirement for labelling. Ambient mass spectrometry, in which biological substrates are sampled at ambient temperature and pressure, and which requires little or no sample preparation, is ideally suited to in situ analysis of biomolecules. A suite of ambient mass spectrometry techniques exist including liquid extraction surface analysis (LESA), desorption electrospray ionisation
(DESI) and nanoelectrospray desorption electrospray ionisation (nano-DESI), all of which have found applications in MSI.
A separate branch of mass spectrometry, native mass spectrometry, provides information relating to protein structure, including stoichiometry of protein assemblies and protein-ligand complexes, through retention of solution-phase interactions in the gas-phase. When native mass spectrometry is combined with ion mobility spectrometry, it is possible to determine rotationally-averaged collision cross sections.
Our goal is to combine native mass spectrometry with ambient mass spectrometry imaging to enable simultaneous acquisition of spatial and structural information on intact proteins directly from their physiological environment. Latest developments with LESA and nano-DESI, and their integration with ion mobility spectrometry, for the identification, structural characterisation, and imaging of monomeric proteins, protein assemblies, and protein-ligand complexes directly from a range of tissue types and pathologies will be presented.
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 | Sponsored by Thermo Fisher Scientific
09:30 - 09:31 | Session 3 introduction
09:31 - 09:35 | Thermo Fisher Scientific talk presented by Aaron Robitaille
09:35 - 09:47 | Diana Canetti, University College London
Clinical ApoA-IV amyloid is associated with fibrillogenic signal sequence
Amyloidosis is an uncommon disease that occurs when normal circulating proteins misfold and accumulate as insoluble fibrillar aggregates. There are over 20 different circulating proteins known to cause amyloidosis. The UK National Amyloidosis Centre (NAC) operates a UKAS-validated proteomics facility to type these amyloid proteins. Apolipoprotein A-IV amyloidosis (AApoA-IV) is a rare form of the disease, mainly characterised by renal and cardiac dysfunction. In addition to its intrinsic amyloidogenicity, ApoA-IV is also deposited along with amyloid of all protein types and is one of the amyloid signature proteins. This can cause difficulties in distinguishing between ApoA-IV as the amyloid protein and an amyloid-associated signature protein. The Mayo clinic have set proteomics criteria for ApoA-IV amyloid which include a high probability identification of ApoA-IV in the absence of other candidate amyloid proteins. We have now established that clinical ApoA-IV amyloid commonly contains signal sequence: following tryptic digestion, signal sequence peptides (p.18-43, p.19-43 and p.20-43) were identified in 17/24 clinical biopsies from ApoA-IV amyloidosis patients either attending the NAC clinics or sent to us for histology review. The normal N-terminal peptide, p.21-43, was present in all cases. ApoA-IV signal was also identified in the original cardiac biopsy from a Swedish patient in which ApoA-IV amyloid was first described, and in plasma from 1/3 cardiac AApoA-IV patients by targeted mass spectrometric analysis; it was not detected in controls suggesting the circulating level of signal-ApoA-IV is low. The identity of these signal-containing N-terminal peptides were confirmed by comparison with authentic standards. ApoA-IV signal was present in only 1/266 clinical biopsies where other amyloidogenic proteins were identified as the amyloid type: signature ApoA-IV does not appear to be associated with the presence of signal. The three signal-containing tryptic peptides together with the normal N-terminal peptide (p.21-43) that were all detected in ApoA-IV amyloid were examined for the capacity to form amyloid fibrils in vitro. The p.20-43 peptide and to a lesser extent, the N-terminal peptide were fibrillogenic at physiological pH generating amyloid-like Congo Red positive fibrils. If this effect translates to the mature circulating protein in vivo, then the presence of signal may result in preferential deposition as amyloid, perhaps acting as seed for the main circulating native form of the protein. In conclusion, ApoA-IV amyloid is associated with signal-containing protein, and this is now used in our facility as a further diagnostic test for ApoA-IV amyloid. The p.20-43 peptide shows enhanced fibril formation in vitro compared with the N-terminal peptide and other signal peptides. The presence of additional signal sequence on circulating ApoA-IV may lead to enhanced amyloid deposition in vivo and could potentially influence other ApoA-IV pathologies
09:47 - 09:59 | Wael Kamel, University of Oxford
Global analysis of protein-RNA interactions in SARS-CoV-2 infected cells
As with all RNA viruses, the viral life cycle of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) relies on host RNA binding protein (RBPs). However, the complement of RBPs involved in SARS-CoV-2 infection of human lung cells remained largely unknown. To answer this question in a global scale, we employed a multi-omics approach to uncover the complement of RBPs that are involved in SARS-CoV-2 infection of Calu-3 cells. Applying the previously-established comparative RNA interactome capture (cRIC) (Garcia-Moreno et al., 2019), we discovered that the cellular RNA-binding proteome (RBPome) is profoundly remodelled upon SARS-CoV-2 infection, affecting translation initiation, splicing and antiviral pathways amongst others. Interestingly, we observed that the alterations in the RBPome are not due to changes in RBP abundance, but correlates with a pervasive alteration of the cellular transcriptome and an increase in post-translation modifications mapping to cellular RBPs. To determine the complement of cellular and viral RBPs that interact with SARS-CoV-2 RNA, we applied a novel method named viral RNA interactome capture (vRIC). This method combines 4-thiouridine labelling of viral RNA in presence of an inhibitor of cellular RNA polymerases, UV crosslinking at 365 nm, oligo (dT) capture and quantitative proteomics. vRIC identified 139 cellular and 6 viral proteins that directly interact with SARS-CoV-2 RNA. Pharmacological inhibition of these RBPs impairs SARS-CoV-2 infection, thus revealing novel potential targets for antiviral therapies against COVID-19. Finally, we identified several members of the tRNA ligase complex (tRNA-LC) that interact directly with SARS-CoV-2 RNA. The tRNA-LC colocalizes with viral replication centres upon SARS-CoV-2 infection of Calu-3 cells. Knock down of the tRNA-LC core component DDX1 hampers the synthesis of positive and negative SARS-CoV-2 strands. Importantly, this effect was also observed in other positive stranded RNA viruses, suggesting a master regulatory role in virus replication. Collectively, our results provide a comprehensive view of protein-RNA interactions in SARS-CoV-2 infected cells, revealing important cellular factors for the virus life cycle with great therapeutic potential.
09:59 - 10:11 | Martin Rusilowicz, University of Manchester
AlacatDesigner, software for the selection of appropriate peptides for protein quantitation
Protein quantitation by MS is conducted via analysis of its constituent peptides, with one or more peptide quantitations acting as a proxy for the protein quantitation. However due to the lack of a 1:1 mapping between quantitation and MS signal intensity, absolute quantitation of the peptides is not possible without the injection of a standard whose concentration is known in advance. // In Qconcat approaches, synthetic "proteins" are introduced. These Qconcats possess arrays of Qbricks. In turn, each Qbrick targets a protein of interest and possesses two peptides encoded in a nucleotide construct that can be combined with others in a synthetic biology approach. In this manner, designer-Qconcats can be "dialled up", allowing multiple proteins to be quantified at the same time and requiring only a single injection. The Qbricks can be produced in advance and assembled to order, with this "a la carte" approach giving rise to the ALACAT philosophy. // However, all Qconcat-like studies can be marred by poor selection of the Qbrick peptides. A number of factors result in divergence of the peptide and protein quantifications, ranging from post-transcriptional-modifications in vivo, different degrees of mis-cleavage during workbench digestion, and varying ionisation potentials and "flyabilities" within the mass spectrometer itself. // Our project, "AlacatDesigner", aims to locate suitable peptides for quantification of the user's target protein, and subsequently determine an appropriate Qbrick (or Qconcat) design. // To this end, the candidate peptides are subject to a barrage of tests ranging from simulations of digestion (e.g. McPred), flyability (e.g. Consequence) and whole-workflow suitability (e.g. DeepMsPeptide), as well as being queried against existing databases (e.g. PrideClusters) and literature (e.g. Google Scholar) for evidence of past performance. An internal database and deep-learning predictor are additionally queried, in order that performance from previous analyses can be fed back into the system, once the Qbricks have been tested empirically and concrete information is available. // An empircal dataset comprising proteins from yeast grown at 6 growth rates is used here to showcase AlacatDesigner. Validation shows that Qconcat peptide selections are enriched for peptides that are good quantotypic and proteotypic candidates. Additionally, the guided interface of AlacatDesigner allows human intervention at all points throughout its processing pipeline, allowing a human mediator to reflect upon test scores and focus the peptide/qbrick selections according to individual project requirements. // The software is freely available to use online via the web interface, or it can be downloaded as a Desktop application for use offline. AlacatDesigner can also be imported as a Python package, to run from the command line interface, or to integrate into custom scripts and programs.
10:11 - 10:23 | Xiaobo Tian, University of Groningen
Isotopic Ac-IP tag enables multiplexed proteome quantification in data-independent acquisition mode
Data-independent acquisition (DIA) is an increasingly used approach for quantitative proteomics. However, most current isotope labeling strategies are not suitable for DIA, as they lead to more complex MS2 spectra or severe ratio distortion. As a result, DIA suffers from a lower throughput than data-dependent acquisition (DDA) due to a lower level of multiplexing. Herein, we synthesized an isotopically labeled acetyl-isoleucine-proline (Ac-IP) tag for multiplexed quantification in DIA. Differentially labeled peptides have distinct precursor ions carrying the quantitative information but identical MS2 spectra, since the isotopically labeled Ac-Ile part leaves as a neutral loss upon collision-induced dissociation, while fragmentation of the peptide backbone generates regular fragment ions for identification. The Ac-IP labeled samples can be analyzed using general DIA LC-MS settings and the data obtained can be processed with established approaches. Relative quantification requires deconvolution of the isotope envelope of the respective precursor ions. Suitability of the Ac-IP tag is demonstrated with a triplex-labeled yeast proteome spiked with bovine serum albumin (BSA) that was mixed at 10 : 5 : 1 ratios resulting in measured ratios of 9.7 : 5.3 : 1.1.
10:23 - 11:00 | Discussion
11:00 - 11:30 | Break, poster viewing and networking
Session 4 - Computational Proteomics | Sponsored by Sciex
11:30 - 11:31 | Session 4 introduction
11:31 - 11:35 | Sciex talk presented by Nick Morrice
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 | Sponsored by Bruker
09:30 - 09:31 | Session 5 introduction
09:31 - 09:35 | Bruker talk presented by Bram Snijders
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 ; 3) the DIA-NN software package that uses deep neural networks and was specifically developed for the spectral complexity of short gradient runs , and 4) Scanning SWATH, a scanning quadrupole data-independent acquisition (DIA) method . 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.
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.
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).
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
Closing Session | Sponsored by PreOmics
11:30 - 11:31 | Closing session introduction
11:31 - 11:35 | PreOmics talk presented by Sarah Lupton
What’s your key concern, sample prep or the MS analysis? Time to look for a streamlined process
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.