The SPOC proteins DIDO3 and PHF3 co-regulate gene expression and neuronal differentiation.

Transcription is regulated by a multitude of activators and repressors, which bind to the RNA polymerase II (Pol II) machinery and modulate its progression. Death-inducer obliterator 3 (DIDO3) and PHD finger protein 3 (PHF3) are paralogue proteins that regulate transcription elongation by docking onto phosphorylated serine-2 in the C-terminal domain (CTD) of Pol II through their SPOC domains. Here, we show that DIDO3 and PHF3 form a complex that bridges the Pol II elongation machinery with chromatin and RNA processing factors and tethers Pol II in a phase-separated microenvironment. Their SPOC domains and C-terminal intrinsically disordered regions are critical for transcription regulation. PHF3 and DIDO exert cooperative and antagonistic effects on the expression of neuronal genes and are both essential for neuronal differentiation. In the absence of PHF3, DIDO3 is upregulated as a compensatory mechanism. In addition to shared gene targets, DIDO specifically regulates genes required for lipid metabolism. Collectively, our work reveals multiple layers of gene expression regulation by the DIDO3 and PHF3 paralogues, which have specific, co-regulatory and redundant functions in transcription.

Transcriptional reprogramming by mutated IRF4 in lymphoma.

Disease-causing mutations in genes encoding transcription factors (TFs) can affect TF interactions with their cognate DNA-binding motifs. Whether and how TF mutations impact upon the binding to TF composite elements (CE) and the interaction with other TFs is unclear. Here, we report a distinct mechanism of TF alteration in human lymphomas with perturbed B cell identity, in particular classic Hodgkin lymphoma. It is caused by a recurrent somatic missense mutation c.295 T > C (p.Cys99Arg; p.C99R) targeting the center of the DNA-binding domain of Interferon Regulatory Factor 4 (IRF4), a key TF in immune cells. IRF4-C99R fundamentally alters IRF4 DNA-binding, with loss-of-binding to canonical IRF motifs and neomorphic gain-of-binding to canonical and non-canonical IRF CEs. IRF4-C99R thoroughly modifies IRF4 function by blocking IRF4-dependent plasma cell induction, and up-regulates disease-specific genes in a non-canonical Activator Protein-1 (AP-1)-IRF-CE (AICE)-dependent manner. Our data explain how a single mutation causes a complex switch of TF specificity and gene regulation and open the perspective to specifically block the neomorphic DNA-binding activities of a mutant TF.

The SPOC domain is a phosphoserine binding module that bridges transcription machinery with co- and post-transcriptional regulators.

The heptad repeats of the C-terminal domain (CTD) of RNA polymerase II (Pol II) are extensively modified throughout the transcription cycle. The CTD coordinates RNA synthesis and processing by recruiting transcription regulators as well as RNA capping, splicing and 3'end processing factors. The SPOC domain of PHF3 was recently identified as a CTD reader domain specifically binding to phosphorylated serine-2 residues in adjacent CTD repeats. Here, we establish the SPOC domains of the human proteins DIDO, SHARP (also known as SPEN) and RBM15 as phosphoserine binding modules that can act as CTD readers but also recognize other phosphorylated binding partners. We report the crystal structure of SHARP SPOC in complex with CTD and identify the molecular determinants for its specific binding to phosphorylated serine-5. PHF3 and DIDO SPOC domains preferentially interact with the Pol II elongation complex, while RBM15 and SHARP SPOC domains engage with writers and readers of m6A, the most abundant RNA modification. RBM15 positively regulates m6A levels and mRNA stability in a SPOC-dependent manner, while SHARP SPOC is essential for its localization to inactive X-chromosomes. Our findings suggest that the SPOC domain is a major interface between the transcription machinery and regulators of transcription and co-transcriptional processes.

Herpesviruses mimic zygotic genome activation to promote viral replication.

DUX4 is a germline transcription factor and a master regulator of zygotic genome activation. During early embryogenesis, DUX4 is crucial for maternal to zygotic transition at the 2-8-cell stage in order to overcome silencing of genes and enable transcription from the zygotic genome. In adult somatic cells, DUX4 expression is silenced and its activation in adult muscle cells causes the genetic disorder Facioscapulohumeral Muscular Dystrophy (FSHD). Here we show that herpesviruses from alpha-, beta- and gamma-herpesvirus subfamilies as well as papillomaviruses actively induce DUX4 expression to promote viral transcription and replication. We demonstrate that HSV-1 immediate early proteins directly induce expression of DUX4 and its target genes including endogenous retroelements, which mimics zygotic genome activation. We further show that DUX4 directly binds to the viral genome and promotes viral transcription. DUX4 is functionally required for herpesvirus infection, since genetic depletion of DUX4 by CRISPR/Cas9 abrogates viral replication. Our results show that herpesviruses induce DUX4 expression and its downstream germline-specific genes and retroelements, thus mimicking an early embryonic-like transcriptional program that prevents epigenetic silencing of the viral genome and facilitates herpesviral gene expression.

Multi-Omics Alleviates the Limitations of Panel Sequencing for Cancer Drug Response Prediction.

Comprehensive genomic profiling using cancer gene panels has been shown to improve treatment options for a variety of cancer types. However, genomic aberrations detected via such gene panels do not necessarily serve as strong predictors of drug sensitivity. In this study, using pharmacogenomics datasets of cell lines, patient-derived xenografts, and ex vivo treated fresh tumor specimens, we demonstrate that utilizing the transcriptome on top of gene panel features substantially improves drug response prediction performance in cancer.

SARS-CoV-2 infection dynamics revealed by wastewater sequencing analysis and deconvolution.

The use of RNA sequencing from wastewater samples is a valuable way for estimating infection dynamics and circulating lineages of SARS-CoV-2. This approach is independent from testing individuals and can therefore become the key tool to monitor this and potentially other viruses. However, it is equally important to develop easily accessible and scalable tools which can highlight critical changes in infection rates and dynamics over time across different locations given sequencing data from wastewater. Here, we provide an analysis of lineage dynamics in Berlin and New York City using wastewater sequencing and present PiGx SARS-CoV-2, a highly reproducible computational analysis pipeline with comprehensive reports. This end-to-end pipeline includes all steps from raw data to shareable reports, additional taxonomic analysis, deconvolution and geospatial time series analyses. Using simulated datasets (in silico generated and spiked-in samples) we could demonstrate the accuracy of our pipeline calculating proportions of Variants of Concern (VOC) from environmental as well as pre-mixed samples (spiked-in). By applying our pipeline on a dataset of wastewater samples from Berlin between February 2021 and January 2022, we could reconstruct the emergence of B.1.1.7(alpha) in February/March 2021 and the replacement dynamics from B.1.617.2 (delta) to BA.1 and BA.2 (omicron) during the winter of 2021/2022. Using data from very-short-reads generated in an industrial scale setting, we could see even higher accuracy in our deconvolution. Lastly, using a targeted sequencing dataset from New York City (receptor-binding-domain (RBD) only), we could reproduce the results recovering the proportions of the so-called cryptic lineages shown in the original study. Overall our study provides an in-depth analysis reconstructing virus lineage dynamics from wastewater. While applying our tool on a wide range of different datasets (from different types of wastewater sample locations and sequenced with different methods), we show that PiGx SARS-CoV-2 can be used to identify new mutations and detect any emerging new lineages in a highly automated and scalable way. Our approach can support efforts to establish continuous monitoring and early-warning projects for detecting SARS-CoV-2 or any other pathogen.

Rapid Inflammasome Activation Is Attenuated in Post-Myocardial Infarction Monocytes.

Inflammasomes are crucial gatekeepers of the immune response, but their maladaptive activation associates with inflammatory pathologies. Besides canonical activation, monocytes can trigger non-transcriptional or rapid inflammasome activation that has not been well defined in the context of acute myocardial infarction (AMI). Rapid transcription-independent inflammasome activation induced by simultaneous TLR priming and triggering stimulus was measured by caspase-1 (CASP1) activity and interleukin release. Both classical and intermediate monocytes from healthy donors exhibited robust CASP1 activation, but only classical monocytes produced high mature interleukin-18 (IL18) release. We also recruited a limited number of coronary artery disease (CAD, n=31) and AMI (n=29) patients to evaluate their inflammasome function and expression profiles. Surprisingly, monocyte subpopulations isolated from blood collected during percutaneous coronary intervention (PCI) from AMI patients presented diminished CASP1 activity and abrogated IL18 release despite increased NLRP3 gene expression. This unexpected attenuated rapid inflammasome activation was accompanied by a significant increase of TNFAIP3 and IRAKM expression. Moreover, TNFAIP3 protein levels of circulating monocytes showed positive correlation with high sensitive troponin T (hsTnT), implying an association between TNFAIP3 upregulation and the severity of tissue injury. We suggest this monocyte attenuation to be a protective phenotype aftermath following a very early inflammatory wave in the ischemic area. Damage-associated molecular patterns (DAMPs) or other signals trigger a transitory negative feedback loop within newly recruited circulating monocytes as a mechanism to reduce post-injury tissue damage.

Identifying tumor cells at the single-cell level using machine learning.

Tumors are complex tissues of cancerous cells surrounded by a heterogeneous cellular microenvironment with which they interact. Single-cell sequencing enables molecular characterization of single cells within the tumor. However, cell annotation-the assignment of cell type or cell state to each sequenced cell-is a challenge, especially identifying tumor cells within single-cell or spatial sequencing experiments. Here, we propose ikarus, a machine learning pipeline aimed at distinguishing tumor cells from normal cells at the single-cell level. We test ikarus on multiple single-cell datasets, showing that it achieves high sensitivity and specificity in multiple experimental contexts.

The SEQC2 epigenomics quality control (EpiQC) study.

BACKGROUND: Cytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA's Epigenomics Quality Control Group. RESULTS: Each sample is processed in multiple replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), enzymatic deamination method (EMSeq), targeted methylation sequencing (Illumina Methyl Capture EPIC), single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies, and 850k Illumina methylation arrays. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, bwa-meth, and BitMapperBS), we find overall high concordance between assays, but also differences in efficiency of read mapping, CpG capture, coverage, and platform performance, and variable performance across 26 microarray normalization algorithms. CONCLUSIONS: The data provided herein can guide the use of these DNA reference materials in epigenomics research, as well as provide best practices for experimental design in future studies. By leveraging seven human cell lines that are designated as publicly available reference materials, these data can be used as a baseline to advance epigenomics research.

Cell-type specialization is encoded by specific chromatin topologies.

The three-dimensional (3D) structure of chromatin is intrinsically associated with gene regulation and cell function1-3. Methods based on chromatin conformation capture have mapped chromatin structures in neuronal systems such as in vitro differentiated neurons, neurons isolated through fluorescence-activated cell sorting from cortical tissues pooled from different animals and from dissociated whole hippocampi4-6. However, changes in chromatin organization captured by imaging, such as the relocation of Bdnf away from the nuclear periphery after activation7, are invisible with such approaches8. Here we developed immunoGAM, an extension of genome architecture mapping (GAM)2,9, to map 3D chromatin topology genome-wide in specific brain cell types, without tissue disruption, from single animals. GAM is a ligation-free technology that maps genome topology by sequencing the DNA content from thin (about 220 nm) nuclear cryosections. Chromatin interactions are identified from the increased probability of co-segregation of contacting loci across a collection of nuclear slices. ImmunoGAM expands the scope of GAM to enable the selection of specific cell types using low cell numbers (approximately 1,000 cells) within a complex tissue and avoids tissue dissociation2,10. We report cell-type specialized 3D chromatin structures at multiple genomic scales that relate to patterns of gene expression. We discover extensive 'melting' of long genes when they are highly expressed and/or have high chromatin accessibility. The contacts most specific of neuron subtypes contain genes associated with specialized processes, such as addiction and synaptic plasticity, which harbour putative binding sites for neuronal transcription factors within accessible chromatin regions. Moreover, sensory receptor genes are preferentially found in heterochromatic compartments in brain cells, which establish strong contacts across tens of megabases. Our results demonstrate that highly specific chromatin conformations in brain cells are tightly related to gene regulation mechanisms and specialized functions.

Lymphocyte access to lymphoma is impaired by high endothelial venule regression.

Blood endothelial cells display remarkable plasticity depending on the demands of a malignant microenvironment. While studies in solid tumors focus on their role in metabolic adaptations, formation of high endothelial venules (HEVs) in lymph nodes extends their role to the organization of immune cell interactions. As a response to lymphoma growth, blood vessel density increases; however, the fate of HEVs remains elusive. Here, we report that lymphoma causes severe HEV regression in mouse models that phenocopies aggressive human B cell lymphomas. HEV dedifferentiation occurrs as a consequence of a disrupted lymph-carrying conduit system. Mechanosensitive fibroblastic reticular cells then deregulate CCL21 migration paths, followed by deterioration of dendritic cell proximity to HEVs. Loss of this crosstalk deprives HEVs of lymphotoxin-ß-receptor (LTßR) signaling, which is indispensable for their differentiation and lymphocyte transmigration. Collectively, this study reveals a remodeling cascade of the lymph node microenvironment that is detrimental for immune cell trafficking in lymphoma.

PHF3 regulates neuronal gene expression through the Pol II CTD reader domain SPOC.

The C-terminal domain (CTD) of the largest subunit of RNA polymerase II (Pol II) is a regulatory hub for transcription and RNA processing. Here, we identify PHD-finger protein 3 (PHF3) as a regulator of transcription and mRNA stability that docks onto Pol II CTD through its SPOC domain. We characterize SPOC as a CTD reader domain that preferentially binds two phosphorylated Serine-2 marks in adjacent CTD repeats. PHF3 drives liquid-liquid phase separation of phosphorylated Pol II, colocalizes with Pol II clusters and tracks with Pol II across the length of genes. PHF3 knock-out or SPOC deletion in human cells results in increased Pol II stalling, reduced elongation rate and an increase in mRNA stability, with marked derepression of neuronal genes. Key neuronal genes are aberrantly expressed in Phf3 knock-out mouse embryonic stem cells, resulting in impaired neuronal differentiation. Our data suggest that PHF3 acts as a prominent effector of neuronal gene regulation by bridging transcription with mRNA decay.

Transcriptomic profiling of SARS-CoV-2 infected human cell lines identifies HSP90 as target for COVID-19 therapy.

Detailed knowledge of the molecular biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is crucial for understanding of viral replication, host responses, and disease progression. Here, we report gene expression profiles of three SARS-CoV- and SARS-CoV-2-infected human cell lines. SARS-CoV-2 elicited an approximately two-fold higher stimulation of the innate immune response compared to SARS-CoV in the human epithelial cell line Calu-3, including induction of miRNA-155. Single-cell RNA sequencing of infected cells showed that genes induced by virus infections were broadly upregulated, whereas interferon beta/lambda genes, a pro-inflammatory cytokines such as IL-6, were expressed only in small subsets of infected cells. Temporal analysis suggested that transcriptional activities of interferon regulatory factors precede those of nuclear factor κB. Lastly, we identified heat shock protein 90 (HSP90) as a protein relevant for the infection. Inhibition of the HSP90 activity resulted in a reduction of viral replication and pro-inflammatory cytokine expression in primary human airway epithelial cells.

Single-nucleus transcriptomics reveals functional compartmentalization in syncytial skeletal muscle cells.

Syncytial skeletal muscle cells contain hundreds of nuclei in a shared cytoplasm. We investigated nuclear heterogeneity and transcriptional dynamics in the uninjured and regenerating muscle using single-nucleus RNA-sequencing (snRNAseq) of isolated nuclei from muscle fibers. This revealed distinct nuclear subtypes unrelated to fiber type diversity, previously unknown subtypes as well as the expected ones at the neuromuscular and myotendinous junctions. In fibers of the Mdx dystrophy mouse model, distinct subtypes emerged, among them nuclei expressing a repair signature that were also abundant in the muscle of dystrophy patients, and a nuclear population associated with necrotic fibers. Finally, modifications of our approach revealed the compartmentalization in the rare and specialized muscle spindle. Our data identifies nuclear compartments of the myofiber and defines a molecular roadmap for their functional analyses; the data can be freely explored on the MyoExplorer server ( https://shiny.mdc-berlin.de/MyoExplorer/ ).

Single-cell RNA-sequencing of herpes simplex virus 1-infected cells connects NRF2 activation to an antiviral program.

Herpesvirus infection initiates a range of perturbations in the host cell, which remain poorly understood at the level of individual cells. Here, we quantify the transcriptome of single human primary fibroblasts during the first hours of lytic infection with HSV-1. By applying a generalizable analysis scheme, we define a precise temporal order of early viral gene expression and propose a set-wise emergence of viral genes. We identify host cell genes and pathways relevant for infection by combining three different computational approaches: gene and pathway overdispersion analysis, prediction of cell-state transition probabilities, as well as future cell states. One transcriptional program, which correlates with increased resistance to infection, implicates the transcription factor NRF2. Consequently, Bardoxolone methyl and Sulforaphane, two known NRF2 agonists, impair virus production, suggesting that NRF2 activation restricts viral infection. Our study provides insights into early stages of HSV-1 infection and serves as a general blueprint for the investigation of heterogeneous cell states in virus infection.

HOT or not: examining the basis of high-occupancy target regions.

High-occupancy target (HOT) regions are segments of the genome with unusually high number of transcription factor binding sites. These regions are observed in multiple species and thought to have biological importance due to high transcription factor occupancy. Furthermore, they coincide with house-keeping gene promoters and consequently associated genes are stably expressed across multiple cell types. Despite these features, HOT regions are solely defined using ChIP-seq experiments and shown to lack canonical motifs for transcription factors that are thought to be bound there. Although, ChIP-seq experiments are the golden standard for finding genome-wide binding sites of a protein, they are not noise free. Here, we show that HOT regions are likely to be ChIP-seq artifacts and they are similar to previously proposed 'hyper-ChIPable' regions. Using ChIP-seq data sets for knocked-out transcription factors, we demonstrate presence of false positive signals on HOT regions. We observe sequence characteristics and genomic features that are discriminatory of HOT regions, such as GC/CpG-rich k-mers, enrichment of RNA-DNA hybrids (R-loops) and DNA tertiary structures (G-quadruplex DNA). The artificial ChIP-seq enrichment on HOT regions could be associated to these discriminatory features. Furthermore, we propose strategies to deal with such artifacts for the future ChIP-seq studies.

Autocrine LTA signaling drives NF-κB and JAK-STAT activity and myeloid gene expression in Hodgkin lymphoma.

Persistent NF-κB activation is a hallmark of the malignant Hodgkin/Reed-Sternberg (HRS) cells in classical Hodgkin lymphoma (cHL). Genomic lesions, Epstein-Barr virus infection, soluble factors, and tumor-microenvironment interactions contribute to this activation. Here, in an unbiased approach to identify the cHL cell-secreted key factors for NF-κB activation, we have dissected the secretome of cultured cHL cells by chromatography and subsequent mass spectrometry. We identified lymphotoxin-α (LTA) as the causative factor for autocrine and paracrine activation of canonical and noncanonical NF-κB in cHL cell lines. In addition to inducing NF-κB, LTA promotes JAK2/STAT6 signaling. LTA and its receptor TNFRSF14 are transcriptionally activated by noncanonical NF-κB, creating a continuous feedback loop. Furthermore, LTA shapes the expression of cytokines, receptors, immune checkpoint ligands and adhesion molecules, including CSF2, CD40, PD-L1/PD-L2, and VCAM1. Comparison with single-cell gene-activity profiles of human hematopoietic cells showed that LTA induces genes restricted to the lymphoid lineage, as well as those largely restricted to the myeloid lineage. Thus, LTA sustains autocrine NF-κB activation, impacts activation of several signaling pathways, and drives expression of genes essential for microenvironmental interactions and lineage ambiguity. These data provide a robust rationale for targeting LTA as a treatment strategy for cHL patients.

Alternative 3' UTRs direct localization of functionally diverse protein isoforms in neuronal compartments.

The proper subcellular localization of RNAs and local translational regulation is crucial in highly compartmentalized cells, such as neurons. RNA localization is mediated by specific cis-regulatory elements usually found in mRNA 3'UTRs. Therefore, processes that generate alternative 3'UTRs-alternative splicing and polyadenylation-have the potential to diversify mRNA localization patterns in neurons. Here, we performed mapping of alternative 3'UTRs in neurites and soma isolated from mESC-derived neurons. Our analysis identified 593 genes with differentially localized 3'UTR isoforms. In particular, we have shown that two isoforms of Cdc42 gene with distinct functions in neuronal polarity are differentially localized between neurites and soma of mESC-derived and mouse primary cortical neurons, at both mRNA and protein level. Using reporter assays and 3'UTR swapping experiments, we have identified the role of alternative 3'UTRs and mRNA transport in differential localization of alternative CDC42 protein isoforms. Moreover, we used SILAC to identify isoform-specific Cdc42 3'UTR-bound proteome with potential role in Cdc42 localization and translation. Our analysis points to usage of alternative 3'UTR isoforms as a novel mechanism to provide for differential localization of functionally diverse alternative protein isoforms.

PiGx: reproducible genomics analysis pipelines with GNU Guix.

In bioinformatics, as well as other computationally intensive research fields, there is a need for workflows that can reliably produce consistent output, from known sources, independent of the software environment or configuration settings of the machine on which they are executed. Indeed, this is essential for controlled comparison between different observations and for the wider dissemination of workflows. However, providing this type of reproducibility and traceability is often complicated by the need to accommodate the myriad dependencies included in a larger body of software, each of which generally comes in various versions. Moreover, in many fields (bioinformatics being a prime example), these versions are subject to continual change due to rapidly evolving technologies, further complicating problems related to reproducibility. Here, we propose a principled approach for building analysis pipelines and managing their dependencies with GNU Guix. As a case study to demonstrate the utility of our approach, we present a set of highly reproducible pipelines called PiGx for the analysis of RNA sequencing, chromatin immunoprecipitation sequencing, bisulfite-treated DNA sequencing, and single-cell resolution RNA sequencing. All pipelines process raw experimental data and generate reports containing publication-ready plots and figures, with interactive report elements and standard observables. Users may install these highly reproducible packages and apply them to their own datasets without any special computational expertise beyond the use of the command line. We hope such a toolkit will provide immediate benefit to laboratory workers wishing to process their own datasets or bioinformaticians seeking to automate all, or parts of, their analyses. In the long term, we hope our approach to reproducibility will serve as a blueprint for reproducible workflows in other areas. Our pipelines, along with their corresponding documentation and sample reports, are available at http://bioinformatics.mdc-berlin.de/pigx.