Biology subjects

Holze, H.

Publications and source records attributed to Holze, H..

5 recordsLinked to original sources

bioRxiv2024

Catalytic inhibition of KAT6/KAT7 enhances the efficacy and overcomes primary and acquired resistance to Menin inhibitors in MLL leukaemia

Understanding the molecular pathogenesis of MLL fusion oncoprotein (MLL-FP) leukaemia has spawned epigenetic therapies that have improved clinical outcomes in this often-incurable disease. Using genetic and pharmacological approaches, we define the individual and combined contribution of KAT6A, KAT6B and KAT7, in MLL-FP leukaemia. Whilst inhibition of KAT6A/B is efficacious in some pre-clinical models, simultaneous targeting of KAT7, with the novel inhibitor PF-9363, increases the therapeutic efficacy. KAT7 interacts with Menin and the MLL complex and is co-localised at chromatin to co-regulate the MLL-FP transcriptional program. Inhibition of KAT6/KAT7 provides an orthogonal route to targeting Menin to disable the transcriptional activity of MLL-FP. Consequently, combined inhibition rapidly evicts the MLL-FP from chromatin, potently represses oncogenic transcription and overcomes primary resistance to Menin inhibitors. Moreover, PF-9363 or genetic depletion of KAT7 can also overcome acquired genetic/non-genetic resistance to Menin inhibition. These data provide the molecular rationale for rapid clinical translation of combination therapy in MLL-FP leukaemia.

cancer biology↗

bioRxiv2024

Mult-scale and multi-context mapping of cell states across heterogenous spatial samples.

In clinical applications, spatial data collected under varying conditions, time points, or patients often lack discernible structural alignment. Computational tools designed to align adjacent tissue sections are unsuited for dealing with this structural heterogeneity. There is a growing demand for methods that can effectively align and compare spatial data in the absence of obvious visual correspondence. To address this challenge, we developed an interpretable cell mapping strategy by considering spatial context at various scales. Our approach outperforms existing mapping tools in dealing with heterogeneous samples and is flexible enough to map cells across samples, technologies, resolutions, developmental and regenerative time. Using our approach, we showed spatiotemporal decoupling of cells during development. We even performed alignment for a population of spatial data from cancer patients to identify sub- populations. Our interpretable mapping approach facilitates systemic comparison and analysis of heterogeneous spatial data.

bioinformatics↗

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

BARtab & bartools: an integrated Nextflow pipeline and R package for the analysis of synthetic cellular barcodes in the genome and transcriptome

Cellular barcoding using heritable synthetic barcodes coupled to high throughput sequencing is a powerful technique for the accurate tracing of clonal lineages in a wide variety of biological contexts. Recent studies have integrated cellular barcoding with a single-cell transcriptomics readout, extending the capabilities of these lineage tracing methods to the single-cell level. However there remains a lack of scalable and standardised open-source tools to pre-process and visualise both population-level and single-cell level cellular barcoding datasets. To address these limitations, we developed BARtab, a portable and scalable Nextflow pipeline that automates upstream barcode extraction, quality control, filtering and enumeration from high throughput sequencing data; and bartools, an open-source R package that streamlines the analysis and visualisation of population and single-cell level cellular barcoding datasets. BARtab contains additional methods for the extraction and annotation of transcribed barcodes from single-cell RNA-seq and spatial transcriptomics experiments, thus extending this analytical toolbox to also support novel expressed cellular barcoding methodologies. We showcase the integrated BARtab and bartools workflow through comparison with previously published toolsets and via the analysis of exemplar bulk, single-cell, and spatial transcriptomics cellular barcoding datasets.

bioinformatics↗

bioRxiv2021

Genetic and genomic architecture of species-specific cuticular hydrocarbon variation in parasitoid wasps

Cuticular hydrocarbons (CHCs) serve two fundamental functions in insects: protection against desiccation and chemical signaling. CHC profiles can consist of dozens of different compounds and are considered a prime example for a complex trait. How the interaction of genes shapes CHC profiles, which are essential for insect survival, adaptation, and reproductive success, is still poorly understood. Here we investigate the genetic and genomic basis of CHC biosynthesis and variation in parasitoid wasps of the genus Nasonia. Taking advantage of the wasps haplo-diploid sex determination and cross-species fertility, we mapped 91 quantitative trait loci (QTL) explaining variation of a total of 43 CHCs in F2 hybrid males from interspecific crosses between three Nasonia species. To identify candidate genes, we localized orthologs of CHC biosynthesis-related genes in the Nasonia genomes. By doing so, we discovered multiple genomic regions where the location of QTL coincides with the location of CHC biosynthesis-related candidate genes. Most conspicuously, on a region on chromosome 1 close to the centromere, multiple CHC biosynthesis-related candidate genes co-localize with several QTL explaining variation in methyl-branched alkanes. The genetic underpinnings behind this compound class are not well understood so far, despite their high potential for encoding chemical information as well as their prevalence in both Nasonia CHC profiles and many other Hymenoptera. Our study considerably extends our knowledge on the so far little-known genetic and genomic architecture governing biosynthesis and variation of this fundamental compound class, establishing a model for methyl-branched alkane genetics in the Hymenoptera in general.

genetics↗