COVID-19 in health-care workers in three hospitals in the south of the Netherlands:A cross-sectional study

Background: 10 days after the first reported case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the Netherlands (on Feb 27, 2020), 55 (4%) of 1497 health-care workers in nine hospitals located in the south of the Netherlands had tested positive for SARS-CoV-2 RNA. We aimed to gain insight in possible sources of infection in health-care workers. Methods: We did a cross-sectional study at three of the nine hospitals located in the south of the Netherlands. We screened health-care workers at the participating hospitals for SARS-CoV-2 infection, based on clinical symptoms (fever or mild respiratory symptoms) in the 10 days before screening. We obtained epidemiological data through structured interviews with health-care workers and combined this information with data from whole-genome sequencing of SARS-CoV-2 in clinical samples taken from health-care workers and patients. We did an in-depth analysis of sources and modes of transmission of SARS-CoV-2 in health-care workers and patients. Findings: Between March 2 and March 12, 2020, 1796 (15%) of 12 022 health-care workers were screened, of whom 96 (5%) tested positive for SARS-CoV-2. We obtained complete and near-complete genome sequences from 50 health-care workers and ten patients. Most sequences were grouped in three clusters, with two clusters showing local circulation within the region. The noted patterns were consistent with multiple introductions into the hospitals through community-acquired infections and local amplification in the community. Interpretation: Although direct transmission in the hospitals cannot be ruled out, our data do not support widespread nosocomial transmission as the source of infection in patients or health-care workers. Funding: EU Horizon 2020 (RECoVer, VEO, and the European Joint Programme One Health METASTAVA), and the National Institute of Allergy and Infectious Diseases, National Institutes of Health

COVID-19 in health-care workers in three hospitals in the south of the Netherlands: a cross-sectional study

Background: 10 days after the first reported case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the Netherlands (on Feb 27, 2020), 55 (4%) of 1497 health-care workers in nine hospitals located in the south of the Netherlands had tested positive for SARS-CoV-2 RNA. We aimed to gain insight in possible sources of infection in health-care workers. Methods: We did a cross-sectional study at three of the nine hospitals located in the south of the Netherlands. We screened health-care workers at the participating hospitals for SARS-CoV-2 infection, based on clinical symptoms (fever or mild respiratory symptoms) in the 10 days before screening. We obtained epidemiological data through structured interviews with health-care workers and combined this information with data from whole-genome sequencing of SARS-CoV-2 in clinical samples taken from health-care workers and patients. We did an in-depth analysis of sources and modes of transmission of SARS-CoV-2 in health-care workers and patients. Findings: Between March 2 and March 12, 2020, 1796 (15%) of 12 022 health-care workers were screened, of whom 96 (5%) tested positive for SARS-CoV-2. We obtained complete and near-complete genome sequences from 50 health-care workers and ten patients. Most sequences were grouped in three clusters, with two clusters showing local circulation within the region. The noted patterns were consistent with multiple introductions into the hospitals through community-acquired infections and local amplification in the community. Interpretation: Although direct transmission in the hospitals cannot be ruled out, our data do not support widespread nosocomial transmission as the source of infection in patients or health-care workers. Funding: EU Horizon 2020 (RECoVer, VEO, and the European Joint Programme One Health METASTAVA), and the National Institute of Allergy and Infectious Diseases, National Institutes of Health

Assessing the Capability of Multimodal Variational Auto-Encoders in Combining Information From Biological Layers in Cancer Cells

Personalized treatment methods for a complex disease such as cancer benefit from using multiple data modalities from a patient's cancer cells. Multiple modalities allow for analysis of dependencies between complex biological processes and downstream tasks, such as drug response and/or expected survival rate. To this end, it is important to gain an understanding of the relationships between modalities in tumor cells. Multimodal Variational Auto-Encoders (MVAEs) are a combination of generative models trained on different sets of data modalities. In this research, the ability of MVAEs to capture common information between different data views from the same tumor cells is assessed. MVAE models discussed here are a Mixture-of-Experts (MoE) and a Product-of-Experts (PoE) approach to combining the generative model posterior distributions into a single common latent space. The performance assessment is done by: i) comparing the loss of information when reconstructing the training data to MOFA+, a linear method for combining multimodal data, and ii) measuring if one modality of a tumor cell can generate another modality, based on characteristics of the latent space learned by the MVAE. Biological data modalities considered are RNA-seq, gene-level copy number and DNA methylation (DNAme), gathered by The Cancer Genome Atlas. It is found that PoE reconstructs data from all data types with a higher accuracy compared to MoE and MOFA+. The mean squared error of PoE's average reconstruction loss is about a quarter of MOFA+'s, and less than a seventh of the MoE's average reconstruction loss. In terms of predicting modalities from other modalities, the PoE again outperforms MoE on all cross-modal predictions. Additionally, it can be concluded that both models have higher losses in their prediction of DNAme from other modalities, indicating a lesser correlation between this data type and the others.CSE3000 Research ProjectComputer Science and Engineerin

Approaches for Mapping Unique Phenotype Screens To a Genetic Interaction Network

Targeted and successful cellular therapies for disease treatment require an extensive mapping of the complex structure and dynamics of molecular mechanisms which determine the behaviour and function of cell. CELL-seq is a genome-wide screening procedure measuring specific and targeted protein quantities as phenotypic readouts and is employed by the Netherlands Cancer Institute to analyze which genes regulate the protein state of interest. This research aims to explore the current compendium of CELL-seq screens that investigate a range of phenotypes, to create a mapping of gene-gene associations that share similar phenotypic profiles and elucidate biology that is hard to uncover with more conventional screening techniques.We perform exploratory research to investigate the ability of the screen compendium to show network structures that reflect known biological processes. We find that with stringent requirements on interactions the screen compendium shows enrichment for a wide range of biological processes and known protein-protein interactions. We further conclude that the experimental design biases network behaviour and needs to be accounted for when constructing networks. We recommended a mutual k-nearest neighbor network construction approach, which yielded networks with the most biological relevance.We compare the CELL-seq screens using findings from the approaches to the DepMap dataset, a well-known collection of synthetic lethality CRISPR screens, and find that the behaviour of these datasets is in many ways mirrored. We conclude that this is both due to the biology they represent and the differences in the number of screens in each dataset. Finally, we compare the coverage of biological processes between the HAP1 compendium and DepMap, and show large overlap in their coverage. Nonetheless, the differences they do show leads us to bring forward two hypotheses for gene-gene interactions that score strongly uniquely in the CELL-seq networks which are biologically plausible but are not found in DepMap or curated literature, warranting future investigations.All code pertaining to the methods and figures in this work are hosted on GitLab by the High Performance Computing Facility of the Netherlands Cancer Institute. As such the code can be viewed by supervisors, but further details could be shared upon request.Computer Scienc

An in-depth comparison of linear and non-linear joint embedding methods for bulk and single-cell multi-omics

Multi-omic analyses are necessary to understand the complex biological processes taking place at the tissue and cell level, but also to make reliable predictions about, for example, disease outcome. Several linear methods exist that create a joint embedding using paired information per sample, but recently there has been a rise in the popularity of neural architectures that embed paired -omics into the same non-linear manifold. This work describes a head-to-head comparison of linear and non-linear joint embedding methods using both bulk and single-cell multi-modal datasets. We found that non-linear methods have a clear advantage with respect to linear ones for missing modality imputation. Performance comparisons in the downstream tasks of survival analysis for bulk tumor data and cell type classification for single-cell data lead to the following insights: First, concatenating the principal components of each modality is a competitive baseline and hard to beat if all modalities are available at test time. However, if we only have one modality available at test time, training a predictive model on the joint space of that modality can lead to performance improvements with respect to just using the unimodal principal components. Second, -omic profiles imputed by neural joint embedding methods are realistic enough to be used by a classifier trained on real data with limited performance drops. Taken together, our comparisons give hints to which joint embedding to use for which downstream task. Overall, product-of-experts performed well in most tasks and was reasonably fast, while early integration (concatenation) of modalities did quite poorly.</p

Changes in DNA methylation induced by multi-walled carbon nanotube exposure in the workplace

This study was designed to assess the epigenetic alterations in blood cells, induced by occupational exposure to multi-wall carbon nanotubes (MWCNT). The study population comprised of MWCNT-exposed workers (n=24) and unexposed controls (n=43) from the same workplace. We measured global DNA methylation/hydroxymethylation levels on the 5th cytosine residues using a validated liquid chromatography tandem-mass spectrometry (LC-MS/MS) method. Sequence-specific methylation of LINE1 retrotransposable element 1 (L1RE1) elements, and promoter regions of functionally important genes associated with epigenetic regulation [DNA methyltransferase-1 (DNMT1) and histone deacetylase 4 (HDAC4)], DNA damage/repair and cell cycle pathways [nuclear protein, coactivator of histone transcription/ATM serine/threonine kinase (NPAT/ATM)], and a potential transforming growth factor beta (TGF-β) repressor [SKI proto-oncogene (SKI)] were studied using bisulfite pyrosequencing. Analysis of global DNA methylation levels and hydroxymethylation did not reveal significant difference between the MWCNT-exposed and control groups. No significant changes in Cytosine-phosphate-Guanine (CpG) site methylation were observed for the LINE1 (L1RE1) elements. Further analysis of gene-specific DNA methylation showed a significant change in methylation for DNMT1, ATM, SKI, and HDAC4 promoter CpGs in MWCNT-exposed workers. Since DNA methylation plays an important role in silencing/regulation of the genes, and many of these genes have been associated with occupational and smoking-induced diseases and cancer (risk), aberrant methylation of these genes might have a potential effect in MWCNT-exposed workers.status: publishe

Changes in DNA methylation induced by multi-walled carbon nanotube exposure in the workplace

This study was designed to assess the epigenetic alterations in blood cells, induced by occupational exposure to multi-wall carbon nanotubes (MWCNT). The study population comprised of MWCNT-exposed workers (n=24) and unexposed controls (n=43) from the same workplace. We measured global DNA methylation/hydroxymethylation levels on the 5th cytosine residues using a validated liquid chromatography tandem-mass spectrometry (LC-MS/MS) method. Sequence-specific methylation of LINE1 retrotransposable element 1 (L1RE1) elements, and promoter regions of functionally important genes associated with epigenetic regulation [DNA methyltransferase-1 (DNMT1) and histone deacetylase 4 (HDAC4)], DNA damage/repair and cell cycle pathways [nuclear protein, coactivator of histone transcription/ATM serine/threonine kinase (NPAT/ATM)], and a potential transforming growth factor beta (TGF-β) repressor [SKI proto-oncogene (SKI)] were studied using bisulfite pyrosequencing. Analysis of global DNA methylation levels and hydroxymethylation did not reveal significant difference between the MWCNT-exposed and control groups. No significant changes in Cytosine-phosphate-Guanine (CpG) site methylation were observed for the LINE1 (L1RE1) elements. Further analysis of gene-specific DNA methylation showed a significant change in methylation for DNMT1, ATM, SKI, and HDAC4 promoter CpGs in MWCNT-exposed workers. Since DNA methylation plays an important role in silencing/regulation of the genes, and many of these genes have been associated with occupational and smoking-induced diseases and cancer (risk), aberrant methylation of these genes might have a potential effect in MWCNT-exposed workers

Mild Exercise Does Not Prevent Atherosclerosis in APOE*3-Leiden.CETP Mice or Improve Lipoprotein Profile of Men with Obesity

Objective Exercise has been shown to improve cardiometabolic health, yet neither the molecular connection nor the effects of exercise timing have been elucidated. The aim of this study was to investigate whether ad libitum or time-restricted mild exercise reduces atherosclerosis development in atherosclerosis-prone dyslipidemic APOE*3-Leiden.CETP mice and whether mild exercise training in men with obesity affects lipoprotein levels. Methods Mice were group-housed and subjected to ad libitum or time-restricted (first or last 6 hours of the active phase) voluntary wheel running for 16 weeks while on a cholesterol-rich diet, after which atherosclerosis development was assessed in the aortic root. Furthermore, nine men with obesity followed a 12-week mild exercise training program. Lipoprotein levels were measured by nuclear magnetic resonance spectroscopy in plasma collected pre and post exercise training. Results Wheel running did not affect plasma lipid levels, uptake of triglyceride-derived fatty acids by tissues, and aortic atherosclerotic lesion size or severity. Markers of training status were unaltered. Exercise training in men with obesity did not alter lipoprotein levels. Conclusions Mild exercise training does not reduce dyslipidemia or atherosclerosis development in APOE*3-Leiden.CETP mice or affect lipoprotein levels in humans. Future research on the effects of (time-restricted) exercise on atherosclerosis or lipid metabolism should consider more vigorous exercise protocols