Biology subjects

Heigwer, F.

Publications and source records attributed to Heigwer, F..

10 recordsLinked to original sources

bioRxiv2025

Image-based screens identify regulators of endogenous Dvl2 biomolecular condensates

Dishevelled (Dvl) proteins are essential transducers in Wnt signaling pathways, which have been implicated in development, stem cell maintenance, and human diseases such as cancer. Several studies have shown that Dvl proteins form dynamic biomolecular condensates. However, how cellular signals and cell states influence the formation of biomolecular condensates remains poorly understood. Here, we analyzed cells with endogenous Dvl2 condensates using image-based cell sorting in combination with phosphoproteomics and identified protein enrichment for Wnt/PCP signaling and the G2/M cell cycle transition. We then performed an image-based high-throughput screen to identify small molecule kinase inhibitors that affect Dvl2 liquid-liquid phase separation. Strikingly, CK1{delta}/{varepsilon} inhibition blocked Dvl2 condensate formation. Its effect on Wnt signaling was modulated in genetic epistasis experiments with loss-of-function alleles of APC, Axin1, and MCC. Our study highlights the interplay between post-translational modifications and condensate dynamics, opening new avenues for research on their role in cellular signaling and disease intervention.

cell biology↗

bioRxiv2024

Enhanced in vivo gene knockout with undetectable off-targets using multiplexed Cas12a sgRNAs

CRISPR nuclease-mediated gene knock-out is limited by suboptimal sgRNAs, inaccessible target sites, and silent mutations. Here, we present a Cas12a-based system that targets each gene with four sgRNAs to overcome these limitations, using Drosophila as a tractable in vivo model. We show that multiplexed sgRNAs act synergistically to create deletions between target sites, substantially increasing the fraction of loss-of-function mutations. To systematically assess off-target effects, we developed a novel screening assay that visualizes CRISPR-induced chromosomal alterations in living animals. This enabled comprehensive screening of more than 2000 sgRNAs clustered in 525 quadruple arrays across 21 megabases of genomic DNA, revealing remarkably high on-target activity (100%, 82/82) and undetectable off-target cutting (0%, 0/443). Quantitative side-by-side comparisons with a current Cas9-based system targeting over 100 genes demonstrates that multiplexed Cas12a-mediated gene targeting achieves superior performance and reveals phenotypes missed by established methods. This highly efficient and specific system provides a framework for reliable functional genomics studies across diverse organisms.

genetics↗

bioRxiv2021

Epithelial cells of the intestine acquire cell-intrinsic inflammation signatures during ageing

During ageing, cell-intrinsic and extrinsic factors lead to the decline of tissue function and organismal health. Disentangling these factors is important for developing effective strategies to prolong organismal healthspan. Here, we addressed this question in the mouse intestinal epithelium, which forms a dynamic interface with its microenvironment and receives extrinsic signals affecting its homeostasis and tissue ageing. We systematically compared transcriptional profiles of young and aged epithelial cells in vivo and ex vivo in cultured intestinal organoids. We found that all cell types of the aged epithelium exhibit an inflammation phenotype, which is marked by MHC class II upregulation and most pronounced in enterocytes. This was accompanied by elevated levels of the immune tolerance markers PD-1 and PD-L1 in the aged tissue microenvironment, indicating dysregulation of immunological homeostasis. Intestinal organoids from aged mice still showed an inflammation signature after weeks in culture, which was concurrent with increased chromatin accessibility of inflammation-associated loci. Our results reveal a cell-intrinsic, persistent inflammation phenotype in aged epithelial cells, which might contribute to systemic inflammation observed during ageing.

genomics↗

bioRxiv2020

SARS-CoV-2 infection induces a pro-inflammatory cytokine response through cGAS-STING and NF-κB

SARS-CoV-2 is a novel virus that has rapidly spread, causing a global pandemic. In the majority of infected patients, SARS-CoV-2 leads to mild disease; however, in a significant proportion of infections, individuals develop severe symptoms that can lead to permanent lung damage or death. These severe cases are often associated with high levels of pro-inflammatory cytokines and low antiviral responses which can lead to systemic complications. We have evaluated transcriptional and cytokine secretion profiles from infected cell cultures and detected a distinct upregulation of inflammatory cytokines that parallels samples taken from infected patients. Building on these observations, we found a specific activation of NF-{kappa}B and a block of IRF3 nuclear translocation in SARS-CoV-2 infected cells. This NF-{kappa}B response is mediated by cGAS-STING activation and could be attenuated through STING targeting drugs. Our results show that SARS-CoV-2 curates a cGAS-STING mediated NF-{kappa}B driven inflammatory immune response in epithelial cells that likely contributes to inflammatory responses seen in patients and might be a target to suppress severe disease symptoms.

microbiology↗

bioRxiv2019

A large-scale resource for tissue-specific CRISPR mutagenesis in Drosophila

Genetic screens are powerful tools for the functional annotation of genomes. In the context of multicellular organisms, interrogation of gene function is greatly facilitated by methods that allow spatial and temporal control of gene abrogation. Here, we describe a large-scale transgenic short guide (sg) RNA library for efficient CRISPR-based disruption of specific target genes in a constitutive or conditional manner. The library consists currently of more than 2600 plasmids and 1600 fly lines with a focus on targeting kinases, phosphatases and transcription factors, each expressing two sgRNAs under control of the Gal4/UAS system. We show that conditional CRISPR mutagenesis is robust across many target genes and can be efficiently employed in various somatic tissues, as well as the germline. In order to prevent artefacts commonly associated with excessive amounts of Cas9 protein, we have developed a series of novel UAS-Cas9 transgenes, which allow fine tuning of Cas9 expression to achieve high gene editing activity without detectable toxicity. Functional assays, as well as direct sequencing of genomic sgRNA target sites, indicates that the vast majority of transgenic sgRNA lines mediate efficient gene disruption. Furthermore, we conducted the so far largest fully transgenic CRISPR screen in any metazoan organism, which further supported the high efficiency and accuracy of our library and revealed many so far uncharacterized genes essential for development.

genetics↗

bioRxiv2019

Lineage specific core-regulatory circuits determine gene essentiality in cancer cells

Cancer cells rely on dysregulated gene expression programs to maintain their malignant phenotype. A cells transcriptional state is controlled by a small set of interconnected transcription factors that form its core-regulatory circuit (CRC). Previous work in pediatric cancers has shown, that disruption of the CRC by genetic alterations causes tumor cells to become highly dependent on its components creating new opportunities for therapeutic intervention. However, the role of CRCs and the mechanisms by which they are controlled remain largely unknown for most tumor types. Here, we developed a method that infers lineage dependency scores to systematically predict functional CRCs and associated biological processes from context-dependent essentiality data sets. Analysis of genome-scale CRISPR-Cas9 screens in 558 cancer cell lines showed that most tumor types specifically depend on a small number of transcription factors for proliferation. We found that these transcription factors compose the CRCs in these tumor types. Moreover, they are frequently altered in patient tumor samples indicating their oncogenic potential. Finally, we show that biological processes associated with each CRC are revealed by analyzing codependency between lineage-specific essential genes. Our results demonstrate that genetic addiction to lineage-specific core transcriptional mechanisms occurs across a broad range of tumor types. We exploit this phenomenon to systematically infer CRCs from lineage specific gene essentiality. Furthermore, our findings shed light on the selective genetic vulnerabilities that arise as the consequence of transcriptional dysregulation in different tumor types and show how the plasticity of regulatory circuits might influence drug resistance and metastatic potential.

systems biology↗

bioRxiv2018

Time-resolved mapping of genetic interactions to model rewiring of signaling pathways

Context-dependent changes in genetic vulnerabilities are important to understand the wiring of cellular pathways and variations in different environmental conditions. However, methodological frameworks to investigate the plasticity of genetic networks over time or in response to external stresses are lacking. To analyze the plasticity of genetic interactions, we performed an arrayed combinatorial RNAi screen in Drosophila cells at multiple time points and after pharmacological inhibition of Ras signaling activity. Using an image-based morphology assay to capture a broad range of phenotypes, we assessed the effect of 12768 pairwise RNAi perturbations in six different conditions. We found that genetic interactions form in different trajectories and developed an algorithm, termed MODIFI, to analyze how genetic interactions rewire over time. Using this framework, we identified more statistically significant interactions compared to endpoints assays and further observed several examples of context-dependent crosstalk between signaling pathways such as an interaction between Ras and Rel which is dependent on MEK activity.

genomics↗

bioRxiv2017

A Map Of Genetic Interactions In Cancer Cells

Cancer genomes often harbor hundreds of molecular aberrations. Such genetic variants can be drivers or passengers of tumorigenesis and, as a side effect, create new vulnerabilities for potential therapeutic exploitation. To systematically identify genotype-dependent vulnerabilities and synthetic lethal interactions, forward genetic screens in different genetic backgrounds have been conducted. We devised MINGLE, a computational framework that integrates CRISPR/Cas9 screens originating from many different libraries and laboratories to build genetic interaction maps. It builds on analytical approaches that were established for genetic network discovery in model organisms. We applied this method to integrate and analyze data from 85 CRISPR/Cas9 screens in human cancer cell lines combining functional data with information on genetic variants to explore the relationships of more than 2.1 million gene-background relationships. In addition to known dependencies, our analysis identified new genotype-specific vulnerabilities of cancer cells. Experimental validation of predicted vulnerabilities associated with aberrant Wnt/{beta}-catenin signaling identified GANAB and PRKCSH as new positive regulators of Wnt/{beta}-catenin signaling. By clustering genes with similar genetic interaction profiles, we drew the largest genetic network in cancer cells to date. Our scalable approach highlights how diverse genetic screens can be integrated to systematically build informative maps of genetic interactions in cancer, which can grow dynamically as more data is included.

systems biology↗

bioRxiv2017

CRISPRAnalyzeR: Interactive analysis, annotation and documentation of pooled CRISPR screens

Pooled CRISPR/Cas9 screens are a powerful and versatile tool for the systematic investigation of cellular processes in a variety of organisms. Such screens generate large amounts of data that present a new challenge to analyze and interpret. Here, we developed a web application to analyze, document and explore pooled CRISR/Cas9 screens using a unified single workflow. The end-to-end analysis pipeline features eight different hit calling strategies based on state-of-the-art methods, including DESeq2, MAGeCK, edgeR, sgRSEA, Z-Ratio, Mann-Whitney test, ScreenBEAM and BAGEL. Results can be compared with interactive visualizations and data tables. CRISPRAnalyzeR integrates meta-information from 26 external data resources, providing a wide array of options for the annotation and documentation of screens. The application was developed with user experience in mind, requiring no previous knowledge in bioinformatics. All modern operating systems are supported.\n\nAvailability and online documentation: The source code, a pre-configured docker application, sample data and a documentation can be found on our GitHub page (http://www.github.com/boutroslab/CRISPRAnalyzeR). A tutorial video can be found at http://www.crispr-analyzer.org.

bioinformatics↗

bioRxiv2017

HTSvis: A web app for exploratory data analysis and visualization of arrayed high-throughput screens

The analysis and visualization of arrayed high-throughput screens (HTS), such as cell-based RNAi or small-molecule HTS experiments, requires specialized computational methods. Software packages such as the R/Bioconductor package cellHTS have been developed to support the analysis and are broadly used by the high-throughput screening community. However, exploratory data analysis and integration of screening results remains challenging due to the size of produced data tables in multi-channel experiments and the lack of user-friendly tools to integrate and visualize screening results. Here we present HTSvis, an R/Shiny open-source web application for interactive visualization and exploratory analysis of arrayed high-throughput data. Using a light-weight infrastructure suitable for desktop computers, HTSvis can be used to visualize raw data, perform quality control and interactively visualize screening results from single- to multi-channel measurements, such as image-based, screens. Input data can either be a result file obtained upon analysis with cellHTS or a generic table with raw or analyzed data from, e.g. a high-content microscopy screen. HTSvis can be downloaded from http://github.com/boutroslab/HTSvis.

bioinformatics↗