Biology subjects

Wenzel, A.

Publications and source records attributed to Wenzel, A..

6 recordsLinked to original sources

bioRxiv2026

The Multi-scale Copula Index (MCI): a new information-theoretic measure of association and its applications in functional cancer genomics

Cancer genomic analyses increasingly involve large, complex datasets representing diverse omics variables, such as gene expression, mutations, copy number alterations, genetic perturbations (e.g. CRISPR or iRNA), drug sensitivity, and clinical phenotypes, making it crucial to accurately measure associations among these variables. Traditional correlation-based methods, like the Pearson correlation coefficient, often assume linearity, Gaussian distributions, and independence among variables, leading to oversimplified assumptions, less sensitive readouts and less accurate significance estimation. Information-theoretic measures overcome these limitations by being one step removed from the data and assessing dependencies at the level of probability distributions, thus providing a more data-agnostic, robust measure for identifying associations in common analysis tasks such as feature selection, pattern recognition, and predictive modeling. Building on these foundations, we introduce the Multi-scale Copula Index (MCI), a novel information-theoretic measure of association. The MCI offers significant advantages over existing methods by eliminating the need for density estimation and parameter tuning, thereby ensuring consistent estimation with reduced computational complexity. Furthermore, it enhances statistical power at lower sample sizes, exhibits strong robustness to outliers, and successfully captures both directionality and important symmetries under input-data transformations, such as reflection or complementation. Due to these strengths, the MCI is particularly useful for functional cancer genomic applications involving, e.g., transcriptional and perturbational data, with different statistical properties across a wide range of dataset sizes and complexity. Contextual associations often arise in functional genomics datasets: two genomic variables show little or no correlation in most samples, yet display a strong linkage within the subset that reflects the active biological context. These situations are ideal for quantifying associations with the MCI. We illustrate the performance of the MCI in a variety of benchmarks and cancer genomic examples and applications. We also introduce the Cumulative Entropy Diagram (CED), a graphical display that allows the visualization of the MCI between a reference vector, such as a phenotype, pathway activation or drug response, and a complete set of genomic features.

bioinformatics↗

bioRxiv2025

HDAC3 prevents enhancer hyperactivation to enable developmental transitions

Dynamic gene regulation requires precise cooperation between transcription factors and chromatin modifiers at regulatory elements to achieve not only activation or repression, but also appropriate transcript dosage. However, the molecular mechanisms that ensure developmental genes are transcribed at specific levels remain largely unknown. Here, we discover that the epigenetic repressor histone deacetylase 3 (HDAC3), together with co-activators, binds a subset of the most active putative enhancer elements. Using a tunable mouse embryonic stem cell degron system, we uncover that HDAC3 directly prevents enhancer--and consequently gene--overactivation, effectively establishing a molecular "speed limit" for many naive pluripotency and housekeeping genes. Interestingly, we find that both the catalytic and non-catalytic functions of HDAC3 contribute to establishing this physiological transcript dose. Specifically during early development, HDAC3 rather than functioning as a canonical repressor, constrains the activity of highly transcribed genes of the implanting epiblast and ensures timely exit from naive pluripotency in vitro. Altogether, this indicates that a dynamic equilibrium between activators and repressors coexists at highly active enhancer elements in pluripotent stem cells, establishing appropriate transcriptional dosage and rendering them responsive to signaling cues, thereby enabling timely and coordinated developmental progression.

developmental biology↗

bioRxiv2025

An intergenerational lipid memory of the social environment in C. elegans

Information about the environment can, in some cases, be transmitted to an organisms offspring by epigenetic inheritance. Here, we describe a novel form of epigenetics in C. elegans where information is transmitted between generations not by alterations in DNA, chromatin, or RNA, but by changes in the composition of lipids. Specifically, we delineate an environment-to-neuron-to-intestine-to-oocyte signalling axis that alters progeny thermotolerance by remodelling lipid provisioning to oocytes when animals detect social pheromones. Intergenerational information transmission via lipid memories may represent an underappreciated form of epigenetics.

genetics↗

bioRxiv2025

Feeder-free culture of naive human pluripotent stem cells retaining embryonic, extraembryonic and blastoid generation potential

Conventional human pluripotent stem cells (hPSCs) are widely used to study early embryonic development, generate somatic cells, and model diseases, with differentiation potential aligned to a post-implantation epiblast identity. In the past decade, naive hPSCs, representing a pre-implantation stage, have been derived. Naive hPSCs efficiently differentiate towards embryonic and extraembryonic lineages such as trophectoderm, primitive endoderm, and extraembryonic mesoderm, and also self-organize into blastocyst-like structures called blastoids. However, their culture typically relies on mouse embryonic fibroblasts (MEFs), which are variable, resource-intensive, and can confound analyses. We report the long-term maintenance of naive hPSCs in a feeder-free, serum-coated system. We successfully expanded for up to 25 passages 8 different naive hPSCs lines across 5 laboratories. Growth rate, clonogenicity, and gene expression profiles on serum coating were comparable to MEF-based cultures, but serum coating eliminated fibroblast contamination. Naive hPSCs cultured on serum exhibited more efficient germ layer specification, retained trophectoderm potential and high blastoid formation efficiency. Exome sequencing revealed fewer mutations in serum-cultured cells, and mass spectrometry identified extracellular matrix proteins such as vitronectin, fibronectin, and collagens in the serum coating. Overall, serum coating offers a scalable, cost-effective and therefore widely applicable alternative for naive hPSC culture, maintaining developmental potential, reducing DNA mutations, and eliminating MEF-related confounding factors. We believe serum coating will expand the use of naive hPSCs to large-scale studies and facilitate the investigation of mechanistic insights into developmental and disease modelling.

cell biology↗

bioRxiv2024

Mapping the human hematopoietic stem and progenitor cell hierarchy through integrated single-cell proteomics and transcriptomics

Single-cell transcriptomics (scRNA-seq) has enabled the characterization of cell state heterogeneity and recapitulation of differentiation trajectories. However, since proteins are the main functional entities in cells, the exclusive use of mRNA measurements comes at the risk of missing important biological information. Here we leverage recent technological advances in single-cell proteomics by Mass Spectrometry (scp-MS) to generate the first scp-MS dataset of an in vivo differentiation hierarchy encompassing over 2,500 human CD34+ hematopoietic stem and progenitor cells. Through integration with scRNA-seq, we identify proteins that are important for stem cell quiescence, which were not indicated by their mRNA transcripts, and demonstrate functional expression covariance during differentiation that is only detectable on protein level. Finally, we show that modeling translation dynamics can infer cell progression during differentiation and explain 45% more protein variation from mRNA than linear correlation. Our work serves as a framework for future single-cell multi-omics studies across biological systems.

cell biology↗

bioRxiv2023

TET2 lesions enhance the aggressiveness of CEBPA-mutant AML by rebalancing GATA2 expression

The myeloid transcription factor CEBPA is recurrently biallelically mutated (i.e., double mutated; CEBPADM) in acute myeloid leukemia (AML) with a combination of hypermorphic N-terminal mutations (CEBPANT), promoting expression of the leukemia-associated p30 isoform, and amorphic C-terminal mutations. The most frequently co-mutated genes in CEBPADM AML are GATA2 and TET2, however the molecular mechanisms underlying this co-mutational spectrum are incomplete. By combining transcriptomic and epigenomic analyses of CEBPA-TET2 co-mutated patients with models thereof, we identify GATA2 as a conserved target of the CEBPA-TET2 mutational axis, providing a rationale for the mutational spectra in CEBPADM AML. Elevated CEBPA levels, driven by CEBPANT, mediate recruitment of TET2 to the Gata2 distal hematopoietic enhancer thereby increasing Gata2 expression. Concurrent loss of TET2 in CEBPADM AML induces a competitive advantage by increasing Gata2 promoter methylation, thereby rebalancing GATA2 levels. Of clinical relevance, demethylating treatment of Cebpa-Tet2 co-mutated AML restores Gata2 levels and prolongs disease latency.

cancer biology↗