Biology subjects

Willemsen, M.

Publications and source records attributed to Willemsen, M..

5 recordsLinked to original sources

bioRxiv2025

An optimal transport-based low-dimensional visualization framework for high-parameter flow cytometry

Conventional data visualization techniques in single-cell analysis (such as two-dimensional dot plots, SPADE, PCA, t-SNE, or UMAP) often fall short in providing an intuitive understanding of high-parameter flow cytometry data. These methods tend to oversimplify complex biological relationships, lack biologically meaningful interpretations, and offer no principled framework for downstream quantitative analysis. To address these limitations, we present a graph-based visualization framework grounded in optimal transport theory. In this framework, cell populations are defined by their marker-expression profiles, and inter-population similarity is quantified using an efficiently computable optimal transport formulation known as the Sinkhorn distance. Our approach produces biologically consistent two-dimensional graph layouts using a phenotypeaware Hamming distance. Structural differences between sample graphs are characterized through a customized graph-edit distance that captures changes in population size, marker expression, and relationships between populations. We demonstrate our methods on two flow cytometry datasets: one from a clinical trial of dendritic cell-based immunotherapy in malignant peritoneal mesothelioma, involving 14 patients sampled at three time points with 14-color panels, and another from FlowCAP-II, which involved 43 acute myeloid leukemia patient samples analyzed with 7-color panels. Our framework produces robust, quantitative visual summaries of cell populations and supports statistical analysis based on graph edit distances, thereby offering new insights into disease progression and treatment response. Ultimately, our method bridges the gap between flow cytometry data visualization and biological interpretation.

bioinformatics↗

bioRxiv2024

Adults patients with autoinflammation of unknown origin partially phenocopy the immune presentation of Still's disease

Autoinflammation of unknown origin remains amongst the most enigmatic of systemic autoinflammatory disorders (SAIDs), immunological disorders characterized by inappropriate activation of the innate immune response. Recent clinical research has identified multiple distinct disorders, although overlap in clinical characteristics and genetic drivers impede rapid and precise diagnosis, and the immunological underpinning of disease is poorly understood. Here we aimed to understand the immunological process behind patients with autoinflammation of unknown origin. In a multi-center European trial, we collected samples from 36 patients with recent disease activity, and used deep immunophenotyping and plasma proteomics to compare to 58 healthy controls and an additional demographically-similar 92 SAID patients. Key immunological changes were upregulation of CD38 and HLA across T cell subsets and upregulation of acute phase plasma proteins in autoinflammation of unknown origin patients. These previously poorly characterised patients partially phenocopied the Stills disease presentation. Together this study identifies potential biomarkers and disease-mediators in autoinflammation of unknown origin.

immunology↗

bioRxiv2024

Rate variation and recurrent sequence errors in pandemic-scale phylogenetics

Phylogenetic analyses of genome sequences from infectious pathogens reveal essential information regarding their evolution and transmission, as seen during the COVID-19 pandemic. Recently developed pandemic-scale phylogenetic inference methods reduce the computational demand of phylogenetic reconstruction from genomic epidemiological datasets, allowing the analysis of millions of closely related genomes. However, widespread homoplasies, due to recurrent mutations and sequence errors, cause phylogenetic uncertainty and biases. We present new algorithms and models to substantially improve the computational performance and accuracy of pandemic-scale phylogenetics. In particular, we account for, and identify, mutation rate variation and recurrent sequence errors. We reconstruct reliable and public sequence alignment and phylogenetic tree of > 2 million SARS-CoV-2 genomes encapsulating the evolutionary history and global spread of the virus up to February 2023.

bioinformatics↗

bioRxiv2023

Novel emm4 lineage associated with an upsurge in invasive group A streptococcal disease in the Netherlands, 2022

Invasive group A streptococcal (iGAS) disease cases increased in the first half year of 2022 in the Netherlands with a remarkably high proportion of emm4 isolates. Whole-genome sequence analysis of 66 emm4 isolates, 40 isolates from the pre-COVID-19-pandemic period 2009-2019 and 26 contemporary isolates from 2022, identified a novel Streptococcus pyogenes lineage (M4NL22), which accounted for 85% emm4 iGAS cases in 2022. Surprisingly, we detected few isolates of the emm4 hypervirulent clone, which has replaced nearly all other emm4 in the USA and the UK. M4NL22 displayed genetic differences compared to other emm4 strains, although these were of unclear biological significance. In publicly available data, we identified a single Norwegian isolate belonging to M4NL22, which was sampled after the isolates from this study, possibly suggesting export of M4NL22 to Norway. In conclusion, our study identified a novel S. pyogenes emm4 lineage underlying an increase of iGAS disease in early 2022 in the Netherlands and results have been promptly communicated with public health officials. Impact statementGroup A Streptococcus (predominantly comprising Streptococcus pyogenes) has a long history of causing disease in humans. Over the past decades, researchers have described various changes in the S. pyogenes population circulating in humans. In this study, we describe a shift in the S. pyogenes population within type emm4 in the Netherlands in early 2022. A novel lineage, which we termed M4NL22, became the predominant emm4 lineage during this period. This was surprising, as in other countries such as the USA and the UK, another recently emerged lineage became dominant. Our work informed public health officials on the possible causes of increased S. pyogenes cases in the Netherlands and underlines the added value of continued active bacteriological surveillance. Data summaryCode is freely available from https://github.com/boasvdp/GAS_M4. All sequencing data is freely available from BioProject PRJEB58654.

microbiology↗

bioRxiv2017

De novo BK channel mutation causes epilepsy by regulating voltage-dependent, but not calcium-dependent, activation

Epilepsy is one of the most common neurological diseases. Here we report the first de novo mutation in the BK channel (p.N995S) that causes epilepsy in two independent families. The p.N995S mutant channel showed a markedly increased macroscopic potassium current mediated by increases in both channel open probability and channel open dwell time. Mutation p.N995S affects the voltage-activation pathway of BK channel, but does not affect the calcium sensitivity. Paxilline blocks potassium currents from both WT and mutant BK channels. We also identified two variants of unknown significance, p.E656A and p.N1159S in epilepsy patients. However, they do not affect BK channel functions, therefore, are unlikely to be a cause of disease. These results expand the BK channelopathy to a more common disease of epilepsy, suggest that the BK channel is a drug target for treatment of epilepsy, and highlight the importance of functional studies in the era of precision medicine.

biophysics↗