Biology subjects

van Heeringen, S. J.

Publications and source records attributed to van Heeringen, S. J..

12 recordsLinked to original sources

bioRxiv2024

The Regulatory Logic of Planarian Stem Cell Differentiation

Cell type identity is determined by gene regulatory networks (GRNs), comprising the expression of specific transcription factors (TFs) regulating target genes (TGs) via binding to open chromatin regions (OCRs). The regulatory logic of differentiation includes factors specific to one or multiple cell types, functioning in a combinatorial fashion. Classic approaches of GRN discovery used perturbational data to elucidate TF-TG links, but are laborious and not scalable across the tree of life. Single cell transcriptomics has emerged as a revolutionary approach to study gene expression with cell type resolution, but incorporating perturbational data is challenging. Planarians, with their pluripotent neoblast stem cells continuously giving rise to all cell types, offer an ideal model to attempt this integration. Despite extensive single cell transcriptomic studies, the transcriptional and chromatin regulation at the cell type level remains unexplored. Here, we investigate the regulatory logic of planarian stem cell differentiation by obtaining an organism-level integration of single cell transcriptomics and single cell accessibility data. We identify specific open chromatin profiles for major differentiated cell types and analyse their transcriptomic landscape, revealing distinct gene modules expressed in individual types and combinations of them. Integrated analysis unveils gene networks reflecting known TF interactions in each type and identifies TFs potentially driving differentiation across multiple cell types. To validate our predictions, we combined TF knockdown RNAi experiments with single cell transcriptomics. We focus on hnf4, a TF known to be expressed in gut phagocytes, and confirm its influence on other types, including parenchymal cells. Our results demonstrate high overlap between predicted targets and experimentally-validated differentially-regulated genes. Overall, our study integrates TFs, TGs and OCRs to reveal the regulatory logic of planarian stem cell differentiation, showcasing that the combination of single cell methods and perturbational studies will be key for characterising GRNs widely.

systems biology↗

bioRxiv2023

Integrative omics analysis reveals gene regulatory mechanisms distinguishing organoid-derived hepatocytes from primary human hepatocytes

Background and AimsHepatic organoid cultures are considered a powerful model system to study liver development and diseases in vitro. However, hepatocyte-like cells differentiated from such organoids remain immature compared to primary human hepatocytes. Therefore, a comprehensive understanding of differences in gene regulatory mechanisms between primary human hepatocytes and hepatic organoids is essential to obtain functional hepatocyte-like cells in vitro for fundamental and therapeutic applications. MethodsWe obtained primary human hepatocytes at high purity from all zones of the liver lobule using an optimized two-step perfusion protocol. We captured the single-cell transcriptome and chromatin accessibility landscape using scRNA-seq and ATAC-seq, respectively. We identified key transcription factors and compared the gene regulatory mechanisms in primary human hepatocytes and (un)differentiated intrahepatic cholangiocyte organoids. Using siRNA-mediated perturbations, we showed the functional relevance of an organoid-enriched transcription factor during in vitro differentiation of hepatocyte-like cells. ResultsOur integrative omics analysis revealed that Activator Protein 1 (AP-1) family members cooperate with hepatocyte-specific transcription factors, including HNF4A, in maintaining cellular functionality of mature human hepatocytes. Comparative analysis identified distinct transcription factor sets specifically active in human hepatocytes and organoids. Amongst these ELF3 is unique to intrahepatic cholangiocyte organoids and its expression level negatively correlate with expression of hepatic marker genes. Functional analysis of ELF3 furthermore revealed that ELF3 depletion optimizes the formation of hepatocyte-like cells from intrahepatic cholangiocyte organoids. ConclusionsCollectively, our integrative analysis provides insights into the transcriptional regulatory networks of human hepatocytes and hepatic organoids, thereby informing future strategies for better establishment of urgently-needed hepatic model systems in vitro.

molecular biology↗

bioRxiv2023

The aryl hydrocarbon receptor regulates epidermal differentiation through transient activation of TFAP2A

The aryl hydrocarbon receptor (AHR) is an evolutionary conserved environmental sensor identified as indispensable regulator of epithelial homeostasis and barrier organ function. Molecular signaling cascade and target genes upon AHR activation and their contribution to cell and tissue function are however not fully understood. Multi-omics analyses using human skin keratinocytes revealed that, upon ligand activation, AHR binds open chromatin to induce expression of transcription factors (TFs), e.g., Transcription Factor AP-2 (TFAP2A), as a swift response to environmental stimuli. The terminal differentiation program including upregulation of barrier genes, filaggrin and keratins, was mediated by TFAP2A as a secondary response to AHR activation. The role of AHR-TFAP2A axis in controlling keratinocyte terminal differentiation for proper barrier formation was further confirmed using CRISPR/Cas9 in human epidermal equivalents. Overall, the study provides novel insights into the molecular mechanism behind AHR-mediated barrier function and potential novel targets for the treatment of skin barrier diseases.

cell biology↗

bioRxiv2022

ONECUT2 restricts Microfold cell numbers in the small intestine; a multi-omics study

Microfold (M) cells reside in the intestinal epithelium of Peyers patches. Their unique ability to take up and transport antigens from the intestinal lumen to the underlying lymphoid tissue is key in the regulation of the gut-associated immune response. Here, we applied a (single-cell) multi-omics approach to investigate the molecular mechanisms that drive M cell differentiation in mouse small intestinal organoids. We generated a comprehensive profile of chromatin accessibility changes and transcription factor dynamics during in vitro M cell differentiation, allowing us to uncover numerous cell type-specific regulatory elements and associated transcription factors. Single-cell RNA sequencing resulted in the identification of an M cell precursor population. Our new computational tool SCEPIA determined that these precursor cells were characterized by high expression of and motif activity for the transcription factor ONECUT2. Subsequent perturbation experiments revealed that ONECUT2 acts downstream of the RANK/RANKL signalling to support Enterocyte differentiation and restrict M cell lineage specification in vitro and in vivo, thereby regulating mucosal immunity. This study provides a useful blueprint for future investigations of cell fate switches in the intestinal epithelium.

molecular biology↗

bioRxiv2022

Multi-omics analyses identify transcription factor interplay in corneal epithelial fate determination and disease

The transparent corneal epithelium in the eye is maintained through the homeostasis regulated by limbal stem cells, while the non-transparent epidermis relies on epidermal keratinocytes for renewal. Despite their cellular similarities, the precise cell fates of these two types of epithelial stem cells, which give rise to functionally distinct epithelia, remain unknown. We performed a multi-omics analysis of human limbal stem cells from the cornea and keratinocytes from the epidermis, and characterized their molecular signatures, highlighting their similarities and differences. Through gene regulatory network analyses, we identified shared and cell type-specific transcription factors that define specific cell fates, and established their regulatory hierarchy. Single-cell RNA-seq analyses of the cornea and the epidermis confirmed these shared and cell type-specific transcription factors. Notably, the shared and limbal stem cell-specific transcription factors can cooperatively target genes associated with corneal opacity. Importantly, we discovered that FOSL2, a direct PAX6 target gene, is a novel candidate associated with corneal opacity, and it regulates genes implicated in corneal diseases. By characterizing molecular signatures, our study unveils the regulatory circuitry governing the limbal stem cell fate and its association with corneal opacity.

developmental biology↗

bioRxiv2022

Chromatin regulates genome-wide transcription factor binding affinities

Transcription factor binding across the genome is regulated by DNA sequence and chromatin features. However, it is not yet possible to quantify the impact of chromatin context on genome-wide transcription factor binding affinities. Here we report the establishment of a method to determine genome-wide absolute apparent binding affinities of transcription factors to native, chromatinized DNA. Our experiments revealed that DNA accessibility is the main determinant of transcription factor binding in the genome, which largely restricts nanomolar affinity binding of YY1, SP1 and MYC/MAX to promoters, while FOXA1 also interacts with non-promoter elements with high affinity. Furthermore, whereas consensus DNA binding motifs for transcription factors are important to establish very high-affinity binding sites, these motifs are not always strictly required to generate nanomolar affinity interactions in the genome. Finally, we uncovered transcription factor concentration dependent binding to specific gene classes, suggesting transcription factor concentration dependent effects on gene expression and cell fate. Importantly, our method adds a quantitative dimension to transcription factor biology which enables stratification of genomic targets based on transcription factor concentration and prediction of transcription factor binding sites under non-physiological conditions, such as disease associated overexpression of (onco)genes.

genomics↗

bioRxiv2020

ANANSE: An enhancer network-based computational approach for predicting key transcription factors in cell fate determination

Proper cell fate determination is largely orchestrated by complex gene regulatory networks centered around transcription factors. However, experimental elucidation of key transcription factors that drive cellular identity is currently often intractable. Here, we present ANANSE (ANalysis Algorithm for Networks Specified by Enhancers), a network-based method that exploits enhancer-encoded regulatory information to identify the key transcription factors in cell fate determination. As cell type-specific transcription factors predominantly bind to enhancers, we use regulatory networks based on enhancer properties to prioritize transcription factors. First, we predict genome-wide binding profiles of transcription factors in various cell types using enhancer activity and transcription factor binding motifs. Subsequently, applying these inferred binding profiles, we construct cell type-specific gene regulatory networks, and then predict key transcription factors controlling cell fate transitions using differential networks between cell types. This method outperforms existing approaches in correctly predicting major transcription factors previously identified to be sufficient for trans-differentiation. Finally, we apply ANANSE to define an atlas of key transcription factors in 18 normal human tissues. In conclusion, we present a ready-to-implement computational tool for efficient prediction of transcription factors in cell fate determination and to study transcription factor-mediated regulatory mechanisms. ANANSE is freely available at https://github.com/vanheeringen-lab/ANANSE.

systems biology↗

bioRxiv2020

Combinatorial action of transcription factors in open chromatin contributes to early cellular heterogeneity and organizer mesendoderm specification.

During gastrulation, mesoderm is induced in pluripotent cells, concomitant with dorsal-ventral patterning and establishing of the dorsal axis. How transcription factors operate within the constraints of chromatin accessibility to mediate these processes is not well-understood. We applied chromatin accessibility and single cell transcriptome analyses to explore the emergence of heterogeneity and underlying gene-regulatory mechanisms during early gastrulation in Xenopus. ATAC-sequencing of pluripotent animal cap cells revealed a state of open chromatin of transcriptionally inactive lineage-restricted genes, whereas chromatin accessibility in dorsal marginal zone cells more closely reflected the transcriptional activity of genes. We characterized single cell trajectories in animal cap and dorsal marginal zone in early gastrula embryos, and inferred the activity of transcription factors in single cell clusters by integrating chromatin accessibility and single cell RNA-sequencing. We tested the activity of organizer-expressed transcription factors in mesoderm-competent animal cap cells and found combinatorial effects of these factors on organizer gene expression. In particular the combination of Foxb1 and Eomes induced a gene expression profile that mimicked those observed in head and trunk organizer single cell clusters. In addition, genes induced by Eomes, Otx2 or the Irx3-Otx2 combination, were enriched for promoters with maternally regulated H3K4me3 modifications, whereas promoters selectively induced by Lhx8 were marked more frequently by zygotically controlled H3K4me3. Our results show that combinatorial activity of zygotically expressed transcription factors acts on maternally-regulated accessible chromatin to induce organizer gene expression.

developmental biology↗

bioRxiv2019

Bayesian Linear Mixed Models for Motif Activity Analysis

MotivationCellular identity and behavior is controlled by complex gene regulatory networks. Transcription factors (TFs) bind to specific DNA sequences to regulate the transcription of their target genes. On the basis of these TF motifs in cis-regulatory elements we can model the influence of TFs on gene expression. In such models of TF motif activity the data is usually modeled assuming a linear relationship between the motif activity and the gene expression level. A commonly used method to model motif influence is based on Ridge Regression. One important assumption of linear regression is the independence between samples. However, if samples are generated from the same cell line, tissue, or other biological source, this assumption may be invalid. This same assumption of independence is also applied to different, yet similar, experimental conditions, which may also be inappropriate. In theory, the independence assumption between samples could lead to loss in signal detection. Here we investigate whether a Bayesian model that allows for correlations results in more accurate inference of motif activities.\n\nResultsWe extend the Ridge Regression to a Bayesian Linear Mixed Model, which allows us to model dependence between different samples. In a simulation study, we in-vestigate the differences between the two model assumptions. We show that our Bayesian Linear Mixed Model implementation outperforms Ridge Regression in a simulation scenario where the noise, the signal that can not be explained by TF motifs, is uncorrelated. However, we demonstrate that there is no such gain in performance if the noise has a similar covariance structure over samples as the signal that can be explained by motifs. We give a mathematical explanation to why this is the case. Using two representative real data sets we show that at most[~] 40% of the signal is explained by motifs using the linear model. With these data there is no advantage to using the Bayesian Linear Mixed Model, due to the similarity of the covariance structure.\n\nAvailability & ImplementationThe project implementation is available at https://github.com/Sim19/SimGEXPwMotifs.

bioinformatics↗

bioRxiv2018

GimmeMotifs: an analysis framework for transcription factor motif analysis

BackgroundTranscription factors (TFs) bind to specific DNA sequences, TF motifs, in cis-regulatory sequences and control the expression of the diverse transcriptional programs encoded in the genome. The concerted action of TFs within the chromatin context enables precise temporal and spatial expression patterns. To understand how TFs control gene expression it is essential to model TF binding. TF motif information can help to interpret the exact role of individual regulatory elements, for instance to predict the functional impact of non-coding variants.\n\nFindingsHere we present GimmeMotifs, a comprehensive computational framework for TF motif analysis. Compared to the previously published version, this release adds a whole range of new functionality and analysis methods. It now includes tools for de novo motif discovery, motif scanning and sequence analysis, motif clustering, calculation of performance metrics and visualization. Included with GimmeMotifs is a non-redundant database of clustered motifs. Compared to other motif databases, this collection of motifs shows competitive performance in discriminating bound from unbound sequences. Using our de novo motif discovery pipeline we find large differences in performance between de novo motif finders on ChIP-seq data. Using an ensemble method such as implemented in GimmeMotifs will generally result in improved motif identification compared to a single motif finder. Finally, we demonstrate maelstrom, a new ensemble method that enables comparative analysis of TF motifs between multiple high-throughput sequencing experiments, such as ChIP-seq or ATAC-seq. Using a collection of ~200 H3K27ac ChIP-seq data sets we identify TFs that play a role in hematopoietic differentiation and lineage commitment.\n\nConclusionGimmeMotifs is a fully-featured and flexible framework for TF motif analysis. It contains both command-line tools as well as a Python API and is freely available at: https://github.com/vanheeringen-lab/gimmemotifs.

bioinformatics↗

bioRxiv2018

Wdr5, Brca1 and Bard1 link the DNA damage response to the mesenchymal-to-epithelial transition during early reprogramming.

Differentiated cells are epigenetically stable, but can be reprogrammed to pluripotency by expression of the OSKM transcription factors. Despite significant effort, relatively little is known about the cellular requirements for reprogramming and how they affect the properties of induced pluripotent stem cells (iPSC). We have performed high-content screening with siRNAs targeting 300 chromatin-associated factors. We used colony features, such as size and shape, as well as strength and homogeneity of marker gene expression to define five colony phenotypes in early reprogramming. We identified transcriptional signatures associated with these phenotypes in a secondary RNA sequencing screen. One of these phenotypes involves large colonies and an early block of reprogramming. Double knockdown epistasis experiments of the genes involved, revealed that Brca1, Bard1 and Wdr5 functionally interact and are required for both the DNA damage response and the mesenchymal-to-epithelial transition (MET), linking these processes. Moreover, the data provide a resource on the role of chromatin-associated factors in reprogramming and underline colony morphology as an important high dimensional readout for reprogramming quality.

developmental biology↗

bioRxiv2017

Regulatory remodeling in the allo-tetraploid frog Xenopus laevis

BackgroundGenome duplication has played a pivotal role in the evolution of many eukaryotic lineages, including the vertebrates. The most recent vertebrate genome duplication is that in Xenopus laevis, resulting from the hybridization of two closely related species about 17 million years ago [1]. However, little is known about the consequences of this duplication at the level of the genome, the epigenome and gene expression.\n\nResultsOf the parental subgenomes, S chromosomes have degraded faster than L chromosomes ever since the genome duplication and until the present day. Deletions appear to have the largest effect on pseudogene formation and loss of regulatory regions. Deleted regions are enriched for long DNA repeats and the flanking regions have high alignment scores, suggesting that non-allelic homologous recombination (NAHR) has played a significant role in the loss of DNA. To assess innovations in the X. laevis subgenomes we examined p300 (Ep300)-bound enhancer peaks that are unique to one subgenome and absent from X. tropicalis. A large majority of new enhancers are comprised of transposable elements. Finally, to dissect early and late events following interspecific hybridization, we examined the epigenome and the enhancer landscape in X. tropicalis x X. laevis hybrid embryos. Strikingly, young X. tropicalis DNA transposons are derepressed and recruit p300 in hybrid embryos.\n\nConclusionsThe results show that erosion of X. laevis genes and functional regulatory elements is associated with repeats and NAHR, and furthermore that young repeats have also contributed to the p300-bound regulatory landscape following hybridization and whole genome duplication.

evolutionary biology↗