Biology subjects

Steinhauser, S.

Publications and source records attributed to Steinhauser, S..

7 recordsLinked to original sources

bioRxiv2024

Benchmarking tools for transcription factor prioritization

Spatiotemporal regulation of gene expression is controlled by transcription factor (TF) binding to regulatory elements, resulting in a plethora of cell types and cell states from the same genetic information. Due to the importance of regulatory elements, various sequencing methods have been developed to localise them in genomes, for example using ChIP-seq profiling of the histone mark H3K27ac that marks active regulatory regions. Moreover, multiple tools have been developed to predict TF binding to these regulatory elements based on DNA sequence. As altered gene expression is a hallmark of disease phenotypes, identifying TFs driving such gene expression programs is critical for the identification of novel drug targets. In this study, we curated 84 chromatin profiling experiments (H3K27ac ChIP-seq) where TFs were perturbed through e.g., genetic knockout or overexpression. We ran nine published tools to prioritize TFs using these real-world data sets and evaluated the performance of the methods in identifying the perturbed TFs. This allowed the nomination of three frontrunner tools, namely RcisTarget, MEIRLOP and monaLisa. Our analyses revealed opportunities and commonalities of tools that will help to guide further improvements and developments in the field.

bioinformatics↗

bioRxiv2024

The transcription factor ZNF469 regulates collagen production in liver fibrosis

Non-alcoholic fatty liver disease (NAFLD) - characterized by excess accumulation of fat in the liver - now affects one third of the worlds population. As NAFLD progresses, extracellular matrix components including collagen accumulate in the liver causing tissue fibrosis, a major determinant of disease severity and mortality. To identify transcriptional regulators of fibrosis, we computationally inferred the activity of transcription factors (TFs) relevant to fibrosis by profiling the matched transcriptomes and epigenomes of 108 human liver biopsies from a deeply-characterized cohort of patients spanning the full histopathologic spectrum of NAFLD. CRISPR-based genetic knockout of the top 100 TFs identified ZNF469 as a regulator of collagen expression in primary human hepatic stellate cells (HSCs). Gain- and loss-of-function studies established that ZNF469 regulates collagen genes and genes involved in matrix homeostasis through direct binding to gene bodies and regulatory elements. By integrating multiomic large-scale profiling of human biopsies with extensive experimental validation we demonstrate that ZNF469 is a transcriptional regulator of collagen in HSCs. Overall, these data nominate ZNF469 as a previously unrecognized determinant of NAFLD-associated liver fibrosis.

molecular biology↗

bioRxiv2021

MYCN mediates cysteine addiction and sensitizes to ferroptosis

Aberrant expression of MYC family members predicts poor clinical outcome in many human cancers. Oncogenic MYC profoundly alters metabolism and mediates an antioxidant response to maintain redox balance. Here we show that MYC induces massive lipid peroxidation upon depletion of cysteine, the rate-limiting amino acid for glutathione biosynthesis and sensitizes cells to ferroptosis, an oxidative, non-apoptotic and irondependent type of cell death. In MYCN-amplified childhood neuroblastoma, MYCN mediates resistance to ferroptosis by activating transsulfuration of methionine to cysteine. MYCN may contribute to spontaneous tumor regression in low-risk neuroblastomas by promoting ferroptosis in cells with epigenetically silenced cystathionine-beta-synthase, the rate-limiting enzyme for transsulfuration. We identified enzymes and antiporter proteins crucial to ferroptotic escape, providing multiple previously unknown sites that may be acted on therapeutically.

cancer biology↗

bioRxiv2021

ChromWave: Deciphering the DNA-encoded competition between transcription factors and nucleosomes with deep neural networks

Transcription factors (TFs) regulate gene expression by recognising and binding specific DNA sequences. At times, these regulatory elements may be occluded by nucleosomes, making them inaccessible for TF-binding. The competition for DNA occupancy between TFs and nucleosomes, and associated gene regulatory outputs, are important consequences of the cis-regulatory information encoded in the genome. However, these sequence patterns are subtle and remain difficult to interpret. Here, we introduce ChromWave, a deep-learning model that, for the first time, predicts the competing profiles for TF and nucleosomes occupancies with remarkable accuracy. Models trained using short- and long-fragment MNase-Seq data successfully learn the sequence preferences underlying TF and nucleosome occupancies across the entire yeast genome. They recapitulate nucleosome evictions from regions containing "strong" TF binding sites and knock-out simulations show nucleosomes gaining occupancy in the absence of these TFs, accompanied by lateral rearrangement of adjacent nucleosomes. At a local level, models anticipate with high accuracy the outcomes of detailed experimental analysis of partially unwrapped nucleosomes at the GAL4 UAS locus. Finally, we trained a ChromWave model that successfully predicts nucleosome positions at promoters in the human genome. We find that human promoters generally contain few sites at which simple sequence changes can alter nucleosome occupancies and that these positions align well with causal variants linked to DNase hypersensitivity.

genomics↗

bioRxiv2021

Epiblast morphogenesis is controlled by selective mRNA decay triggered by LIN28A relocation

The embryonic progression from naive to primed pluripotency is accompanied by the rapid decay of pluripotency-associated mRNAs and a concomitant radical morphogenetic sequence of epiblast polarization, rosette formation and lumenogenesis. The mechanisms triggering and linking these events remain poorly understood. Guided by machine learning and metabolic RNA sequencing, we identified RNA binding proteins (RBPs), especially LIN28A, as primary mRNA decay factors. Using mRNA-RBP interactome capture, we revealed a dramatic increase in LIN28A mRNA binding during the naive-rosette-primed pluripotency transition, driven by its nucleolar-to-cytoplasmic translocation. Cytoplasmic LIN28A binds to 3UTRs of pluripotency-associated mRNAs to directly stimulate their decay and drive lumenogenesis. Accordingly, forced nuclear retention of LIN28A impeded lumenogenesis, impaired gastrulation, and caused an unforeseen embryonic multiplication. Selective mRNA decay, driven by nucleo-cytoplasmic RBP translocation, therefore acts as an intrinsic mechanism linking cell identity switches to the control of embryonic growth and morphogenesis.

developmental biology↗

bioRxiv2017

Regionalization of the nervous system requires axial allocation prior to neural lineage commitment

SummaryNeural induction in vertebrates generates a central nervous system that extends the rostral-caudal length of the body. The prevailing view is that neural cells are initially induced with anterior (forebrain) identity, with caudalising signals then converting a proportion to posterior fates (spinal cord). To test this model, we used chromatin accessibility assays to define how cells adopt region-specific neural fates. Together with genetic and biochemical perturbations this identified a developmental time window in which genome-wide chromatin remodeling events preconfigure epiblast cells for neural induction. Contrary to the established model, this revealed that cells commit to a regional identity before acquiring neural identity. This \"primary regionalization\" allocates cells to anterior or posterior regions of the nervous system, explaining how cranial and spinal neurons are generated at appropriate axial positions. These findings prompt a revision to models of neural induction and support the proposed dual evolutionary origin of the vertebrate central nervous system.

developmental biology↗

bioRxiv2017

Deciphering programs of transcriptional regulation by combined deconvolution of multiple omics layers

Metazoans are crucially dependent on multiple layers of gene regulatory mechanisms which allow them to control gene expression across developmental stages, tissues and cell types. Multiple recent research consortia have aimed to generate comprehensive datasets to profile the activity of these cell type- and condition-specific regulatory landscapes across many different cell lines and primary cells. However, extraction of genes or regulatory elements specific to certain entities from these datasets remains challenging. We here propose a novel method based on non-negative matrix factorization for disentangling and associating huge multi-assay datasets including chromatin accessibility and gene expression data. Taking advantage of implementations of NMF algorithms in the GPU CUDA environment full datasets composed of tens of thousands of genes as well as hundreds of samples can be processed without the need for prior feature selection to reduce the input size. Applying this framework to multiple layers of genomic data derived from human blood cells we unravel mechanisms of regulation of cell type-specific expression in T-cells and monocytes.

genomics↗