Diverse digital and fuzzy composite transcriptional elements are prevalent features of mammalian cis-regulomes

Mammalian transcriptional regulatory sequences are comprised of complex combinations of simple transcription factor (TF) motifs. Stereospecific juxta-positioning of simple TF motifs generates composite elements (CEs), that increase combinatorial and regulatory specificity of TF-DNA interactions. Although a small number of CEs and their cooperative or anti-cooperative modes of TF binding have been thoroughly characterized, a systematic analysis of CE diversity, prevalence and properties in cis-regulomes has not been undertaken. We developed a computational pipeline termed CEseek to discover >20,000 CEs in open chromatin regions of diverse immune cells and validated many using CAP-SELEX, ChIP-Seq and STARR-seq datasets. Strikingly, the CEs manifested a bimodal distribution of configurations, termed digital and fuzzy, based on their stringent or relaxed stereospecific constraints, respectively. Digital CEs mediate cooperative as well as anti-cooperative binding of structurally diverse TFs that likely reflect AND/OR genomic logic gates. In contrast, fuzzy CEs encompass a less diverse set of TF motif pairs that are selectively enriched in p300 associated, multi-genic enhancers. The annotated CEs greatly expand the regulatory DNA motif lexicon and the universe of TF-TF interactions that underlie combinatorial logic of gene regulation.

Chromatin-accessibility estimation from single-cell ATAC-seq data with scOpen

A major drawback of single-cell ATAC-seq (scATAC-seq) is its sparsity, i.e., open chromatin regions with no reads due to loss of DNA material during the scATAC-seq protocol. Here, we propose scOpen, a computational method based on regularized non-negative matrix factorization for imputing and quantifying the open chromatin status of regulatory regions from sparse scATAC-seq experiments. We show that scOpen improves crucial downstream analysis steps of scATAC-seq data as clustering, visualization, cis-regulatory DNA interactions, and delineation of regulatory features. We demonstrate the power of scOpen to dissect regulatory changes in the development of fibrosis in the kidney. This identifies a role of Runx1 and target genes by promoting fibroblast to myofibroblast differentiation driving kidney fibrosis.

PLCG1 is required for AML1-ETO leukemia stem cell self-renewal

In an effort to identify novel drugs targeting fusion-oncogene induced acute myeloid leukemia (AML), we performed high-resolution proteomic analysis. In AML1-ETO (AE) driven AML we uncovered a de-regulation of phospholipase C (PLC) signaling. We identified PLCgamma 1 (PLCG1) as a specific target of the AE fusion protein which is induced after AE binding to intergenic regulatory DNA elements. Genetic inactivation of PLCG1 in murine and human AML inhibited AML1-ETO dependent self-renewal programs, leukemic proliferation, and leukemia maintenance in vivo. In contrast, PLCG1 was dispensable for normal hematopoietic stem- and progenitor cell function. These findings are extended to and confirmed by pharmacologic perturbation of Ca++-signaling in AML1-ETO AML cells, indicating that the PLCG1 pathway poses an important therapeutic target for AML1-ETO positive leukemic stem cells.

The HMGB Protein KlIxr1, a DNA Binding Regulator of Kluyveromyces lactis Gene Expression Involved in Oxidative Metabolism, Growth, and dNTP Synthesis

In the traditional fermentative model yeast Saccharomyces cerevisiae, ScIxr1 is an HMGB (High Mobility Group box B) protein that has been considered as an important regulator of gene transcription in response to external changes like oxygen, carbon source, or nutrient availability. Kluyveromyces lactis is also a useful eukaryotic model, more similar to many human cells due to its respiratory metabolism. We cloned and functionally characterized by different methodologies KlIXR1, which encodes a protein with only 34.4% amino acid sequence similarity to ScIxr1. Our data indicate that both proteins share common functions, including their involvement in the response to hypoxia or oxidative stress induced by hydrogen peroxide or metal treatments, as well as in the control of key regulators for maintenance of the dNTP (deoxyribonucleotide triphosphate) pool and ribosome synthesis. KlIxr1 is able to bind specific regulatory DNA sequences in the promoter of its target genes, which are well conserved between S. cerevisiae and K. lactis. Oppositely, we found important differences between ScIrx1 and KlIxr1 affecting cellular responses to cisplatin or cycloheximide in these yeasts, which could be dependent on specific and non-conserved domains present in these two proteins.

Profiling Transcription Initiation in Peripheral Leukocytes Reveals Severity-Associated Cis-Regulatory Elements in Critical COVID-19

The contribution of transcription factors (TFs) and gene regulatory programs in the immune response to COVID-19 and their relationship to disease outcome is not fully understood. Analysis of genome-wide changes in transcription at both promoter-proximal and distal cis-regulatory DNA elements, collectively termed the 'active cistrome,' offers an unbiased assessment of TF activity identifying key pathways regulated in homeostasis or disease. Here, we profiled the active cistrome from peripheral leukocytes of critically ill COVID-19 patients to identify major regulatory programs and their dynamics during SARS-CoV-2 associated acute respiratory distress syndrome (ARDS). We identified TF motifs that track the severity of COVID-19 lung injury, disease resolution, and outcome. We used unbiased clustering to reveal distinct cistrome subsets delineating the regulation of pathways, cell types, and the combinatorial activity of TFs. We found critical roles for regulatory networks driven by stimulus and lineage determining TFs, showing that STAT and E2F/MYB regulatory programs targeting myeloid cells are activated in patients with poor disease outcomes and associated with single nucleotide genetic variants implicated in COVID-19 susceptibility. Integration with single-cell RNA-seq found that STAT and E2F/MYB activation converged in specific neutrophils subset found in patients with severe disease. Collectively we demonstrate that cistrome analysis facilitates insight into disease mechanisms and provides an unbiased approach to evaluate global changes in transcription factor activity and stratify patient disease severity.

Feedback regulation of Notch signaling and myogenesis connected by MyoD–Dll1 axis

Muscle precursor cells known as myoblasts are essential for muscle development and regeneration. Notch signaling is an ancient intercellular communication mechanism that plays prominent roles in controlling the myogenic program of myoblasts. Currently whether and how the myogenic cues feedback to refine Notch activities in these cells are largely unknown. Here, by mouse and human gene gain/loss-of-function studies, we report that MyoD directly turns on the expression of Notch-ligand gene Dll1 which activates Notch pathway to prevent precautious differentiation in neighboring myoblasts, while autonomously inhibits Notch to facilitate a myogenic program in Dll1 expressing cells. Mechanistically, we studied cis-regulatory DNA motifs underlying the MyoD–Dll1–Notch axis in vivo by characterizing myogenesis of a novel E-box deficient mouse model, as well as in human cells through CRISPR-mediated interference. These results uncovered the crucial transcriptional mechanism that mediates the reciprocal controls of Notch and myogenesis.

Chromatin Alterations in Neurological Disorders and Strategies of (Epi)Genome Rescue

Neurological disorders (NDs) comprise a heterogeneous group of conditions that affect the function of the nervous system. Often incurable, NDs have profound and detrimental consequences on the affected individuals’ lives. NDs have complex etiologies but commonly feature altered gene expression and dysfunctions of the essential chromatin-modifying factors. Hence, compounds that target DNA and histone modification pathways, the so-called epidrugs, constitute promising tools to treat NDs. Yet, targeting the entire epigenome might reveal insufficient to modify a chosen gene expression or even unnecessary and detrimental to the patients’ health. New technologies hold a promise to expand the clinical toolkit in the fight against NDs. (Epi)genome engineering using designer nucleases, including CRISPR-Cas9 and TALENs, can potentially help restore the correct gene expression patterns by targeting a defined gene or pathway, both genetically and epigenetically, with minimal off-target activity. Here, we review the implication of epigenetic machinery in NDs. We outline syndromes caused by mutations in chromatin-modifying enzymes and discuss the functional consequences of mutations in regulatory DNA in NDs. We review the approaches that allow modifying the (epi)genome, including tools based on TALENs and CRISPR-Cas9 technologies, and we highlight how these new strategies could potentially change clinical practices in the treatment of NDs.

Predictive modeling reveals that higher-order cooperativity drives transcriptional repression in a synthetic developmental enhancer

A challenge in quantitative biology is to predict output patterns of gene expression from knowledge of input transcription factor patterns and from the arrangement of binding sites for these transcription factors on regulatory DNA. We tested whether widespread thermodynamic models could be used to infer parameters describing simple regulatory architectures that inform parameter-free predictions of more complex enhancers in the context of transcriptional repression by Runt in the early fruit fly embryo. By modulating the number and placement of Runt binding sites within an enhancer, and quantifying the resulting transcriptional activity using live imaging, we discovered that thermodynamic models call for higher-order cooperativity between multiple molecular players. This higher-order cooperativity capture the combinatorial complexity underlying eukaryotic transcriptional regulation and cannot be determined from simpler regulatory architectures, highlighting the challenges in reaching a predictive understanding of transcriptional regulation in eukaryotes and calling for approaches that quantitatively dissect their molecular nature.