Summary
The keynote speaker Tim Hubbard (King’s College London & Genomics England) introduced the UK's 100,000 genomes project which set out to mainstream whole genome sequencing for treatment into the UK National Health Service (NHS). Genomics England, set up in 2013 to deliver the project, established sequencing and interpretation pipelines to enable whole genome sequences (WGS) to be analyzed for rare diseases and cancer patients with individual reports returned to clinicians. Following the successful completion of the project, the UK is establishing the NHS Genome Medicine Service which will sequence another 500,000 whole genomes for clinical care over the next 5 years, alongside a commitment to sequence the whole of the research cohort UK Biobank (another 500,000 whole genomes). Tim talked about how data from the project had been made accessible to more than 3,000 researchers through the creation of a ’Trusted Research Environment’ and how this model is being more widely adopted to enable research access to health service data in UK.

Recorded Part 1 (@ 00:09:02)   Presentation

Key take home messages 

• Analysis of gut hormone secretion and extracellular peptide hormone processing requires a proteomics approach.
• Combined analysis of human enteroendocrine cells (EECs) by transcriptomics, proteomics, secretomics and bioactive peptidomics provides a high resolution mRNA and secretome atlas resource.

Recorded Part 2 (@ start)   Presentation

Summary
Whether you are a discovery or translational researcher, the GeoMx DSP is the most flexible spatial solution designed to conform to your ever-changing research needs.  It allows you to explore biology with more targets (>20,000) and more analytes (RNA & Protein) to get to your publishable discovery data faster.  Plus, expand your research scope and/or collaborations to access more sample types. From FFPE and Fresh Frozen to the most challenging sample types, your research is not limited by type of sample leading to broader discovery and faster data.

Recorded Part 2 (@ 00:14:58)   Presentation

Summary 
Bert Wouters (Leiden University) talked about “Novel analytical technologies for metabolomics: more for less". More specifically, he discussed a novel sample-handling platform for high-throughput flow-NMR aiming to triple the sample throughput compared to conventional NMR screening platforms. He shared insights into the design process of the new platform, including the use of segmented-slug flow for sample transfer, the development of a non-intrusive laser sensor to characterize sample transfer, the development of a novel fluoropolymer-based NMR flow cell, and finally, the application of the NMR platform for high-throughput screening of wine samples.

Key take home messages

• Nuclear magnetic resonance (NMR) spectroscopy has proven itself as a powerful analytical technique capable of providing quantitative molecular information of complex samples in a cost- and time-efficient manner. For rapid screening of samples, fast and robust sample transfer is crucial to increase the sample throughput. 
• Segmented-flow analysis NMR (SFA-NMR) with fluorinated oil was recently introduced for sample transfer, employing a biphasic flow consisting of samples isolated by oil segments. It has numerous benefits over existing flow-NMR methods (direct-injection, DI-NMR, flow-injection analysis, FIA-NMR, and segmented-flow analysis with air bubbles to separate samples), most importantly lower sample consumption, zero sample dispersion, and low carryover. 
• A laser-based sensor for the characterization and differentiation of segmented flow through optically-transparent fluoropolymer tubing was developed. The sensor was successfully applied for the detection of liquid-liquid and air-liquid flows and was able to identify ten common solvents in segmented flow. The high temporal resolution allowed to assess the slug quality and identify break-up mechanisms such as frothing and fragmentation.
• We have developed a novel polychlorotrifluoroethylene (PCTFE) fluoropolymer flow cell combined with segmented-flow analysis for an automated flow-NMR screening platform based on a conventional 5.0-mm NMR probe.
• Compared to the material properties of conventional glass flow cells, the proposed PCTFE flow cells are less fragile, cheaper in terms of manufacturing costs, and offer improved wetting by the fluorinated oil for SFA-NMR as their surface is permanently fluorinated.
• We demonstrated a very low sample-to-sample carryover for sucrose, maleic acid, and citrate samples as well as multi-component samples such as wine (0.4-1.1% range).

Recorded Part 2 (@ 00:20:25)   Presentation

Summary
Bruker’s innovative timsTOF Flex mass spectrometer includes the ability to do MALDI-MS imaging on tissue slices as well as protein and metabolite identification and quantitation on proteins and metabolites extracted from the same tissue slice. In all modes of analysis the timsTOF Pro provides accurate measurements of the collision cross sections of the measured metabolites and proteins, providing an additional dimension of information to correlate spatially resolved information from imaging with detailed identification and quantitation results from LC-MS workflows in an approach we call 4D-SpatialOmx.

Key take home messages

• Disease tissue such as cancer is not homogeneous, but includes cancerous, pre-cancerous and healthy regions
• MALDI-MS imaging allows non-targeted discovery of metabolites and protein markers that distinguish these tissue types
• LC-MS workflows allow in-depth quantitation and identification of those markers in a 4D-SpatialOmx

Due to the use of privacy sensitive information, Gary's online presentation can’t be shown.

Summary
During the X-Omics 2020 festival dr. Hans Wessels presented on application of clinical glycoproteomics in research and diagnostics. He shared insights into the technology driving N-glycopeptide profiling in plasma and how acquired site-specific protein glycosylation data is key to understand and detect disease processes. First examples for implementation of glycopeptide-based diagnostics at the Translational Metabolic Laboratory of the Radboudumc were shown to illustrate the translation from research technology into applied patient care.

Key take home messages

• Plasma glycoproteomics is analytically robust technology
• Differential glycoforms are clinically relevant and help to understand glycobiology in disease
• Glycopeptide analysis has high potential to advance diagnostics for genetic and acquired human diseases
• Baseline glycosylation of proteins in healthy conditions determines if the protein can be used to monitor specific glycosylation changes for clinical applications
• Glycosylation changes can occur in a protein-, tissue- and site-specific manner

Recorded Part 2 (@ 00:35:25)     Presentation Presentation

Summary 
Many of the technical challenges that the fields of genomics, proteomics and metabolomics evoke can be addressed by using cloud technology. On demand scalable storage and compute enable cost efficient data handling and analysis. The ability to try new tools in a self-service model helps in staying agile and up to speed with the latest developments in your field. 

The challenges mentioned above are even more pronounced in the field of X-omics, where workloads from a heterogeneous field of research domains need to be combined into a manageable data platform. The compute and analytics demands that arise from this combination are heavy and unpredictable. 

Microsoft Azure delivers the platform tools to develop and manage a X-omics environment to tackle these problems. From automated data ingestion, data lake, MPP, and catalog options, to specialized sequencing services  and an open data science platform, Azure offers tools to enable the X-omics pipeline from data ingestion to model deployment. Since Microsoft Azure has a large third party and open source ecosystem, you can use many of the tools you are used to within the context of this platform

Key take home message

• Consider if cloud technology would address your challenges. Experiment and play around with Microsoft Azure. Contact us if you could use some help.

Recorded Part 2 (@ 00:52:48)   Presentation

Summary
Jenny van Dongen presented an Epigenome-wide Association Study meta-analysis of educational attainment performed within the BBMRI-NL Biobank-based Integrative Omics Study Consortium. The study included >4,000 participants from four Dutch cohorts, and focused on genome-wide DNA methylation (Illumina 450k array) measured in whole bood samples. In addition, transcriptomic (RNA-seq), genomic, and metabolomic data are available within these cohorts. Educational attainment is a key behavioural measure in studies of cognitive and physical health, and socioeconomic status. The study identified 58 CpGs associated with educational attainment at loci characterized by pleiotropic functions shared with neuronal, immune and developmental processes. Associations overlapped with those for smoking behaviour, but remained after accounting for smoking at many CpGs: Effect sizes were on average 28% smaller and genome-wide significant at 11 CpGs after adjusting for smoking and were 62% smaller in never smokers. Sources and biological implications of education-related methylation differences were examined, including correlations with maternal prenatal folate, smoking and air pollution signatures, and associations with gene expression in cis, dynamic methylation in foetal brain, and correlations between blood and brain.  

Key take home messages:

• Education is closely related to health, Alzheimer’s disease, societal inequality
• Cognition = brain / DNA methylation = blood
  
• Methylome can provide a read-out of environmental and lifestyle differences

Links

• Results of the study are available here: http://bbmri.researchlumc.nl/atlas/
• Pipeline for DNA methylation array analysis and QC: https://molepi.github.io/DNAmArray_workflow/index.html
• Information on (how to access) BIOS Consortium data: https://www.bbmri.nl/acquisition-use-analyze/bios
• Available omics data within BBMRI-NL: https://omics-explorer.bbmri.nl
• Manuscript: van Dongen, Jenny, et al. "DNA methylation signatures of educational attainment." npj Science of Learning 3.1 (2018): 1-14.

Recorded Part 2 (@ 00:59:48)   Presentation

Recorded Part 3 (@ start)   Presentation

Due to the use of privacy sensitive information, Clara's presentation can’t be shown.

Summary
In the closing talk of the day, Ahmed Mahfouz (Leiden University Medical Center) presented the work of his group on using transcriptomic data to better understand the role of genetic variation in brain function and disease. He first presented their work on Parkinson’s disease linking findings from genetic studies to spatial expression data from the Allen Human Brain Atlas to key pathways and mechanisms that likely underly the vulnerability of brain regions to pathologies. 

Next, Ahmed showed how his group is tackling the limitation in the number of genes measured simultaneously with single-cell spatial transcriptomics techniques. They recently developed SpaGE, a method which integrates spatial and single-cell RNA-sequencing data to predict genome-wide expression patterns in their spatial context.

Link 1: Keo, A., Mahfouz, A., Ingrassia, A.M.T. et al. Transcriptomic signatures of brain regional vulnerability to Parkinson’s disease. Commun Biol 3, 101 (2020).
Link 2: Tamim Abdelaal, Soufiane Mourragui, Ahmed Mahfouz, Marcel J T Reinders, SpaGE: Spatial Gene Enhancement using scRNA-seq, Nucleic Acids Research, gkaa740

Key take-home messages

• Spatially-mapped expression data, such as the Allen Human Brain Atlas, are instrumental in understanding neurobiological mechanisms.
• Integrating spatially-mapped expression data with patterns of pathology progression in Parkinson’s disease reveals key pathways underlying brain vulnerability.
• Understanding spatial expression patterns across brain regions is confounded by differences in cellular composition.
• While computational models can be used to infer cellular composition of bulk gene expression data, single-cell data offer new opportunities in understanding disease mechanisms at a cellular resolution.
• Valuable single-cell spatial transcriptomic data is often limited to measurements across tens or hundreds of genes.
• Integrating spatial transcriptomic data with single-cell RNA-sequencing data allows the prediction of genome-wide expression patterns in their spatial context.
• SpaGE outperforms state-of-the-art methods using is simpler, scalable and more flexible approach to predict unmeasured genes in spatial transcriptomic data at the single-cell level.

Recorded Part 3 (@ 00:27:31)   Presentation