Context transcription factors establish cooperative environments and mediate enhancer communication.

Many enhancers control gene expression by assembling regulatory factor clusters, also referred to as condensates. This process is vital for facilitating enhancer communication and establishing cellular identity. However, how DNA sequence and transcription factor (TF) binding instruct the formation of high regulatory factor environments remains poorly understood. Here we developed a new approach leveraging enhancer-centric chromatin accessibility quantitative trait loci (caQTLs) to nominate regulatory factor clusters genome-wide. By analyzing TF-binding signatures within the context of caQTLs and comparing episomal versus endogenous enhancer activities, we discovered a class of regulators, 'context-only' TFs, that amplify the activity of cell type-specific caQTL-binding TFs, that is, 'context-initiator' TFs. Similar to super-enhancers, enhancers enriched for context-only TF-binding sites display high coactivator binding and sensitivity to bromodomain-inhibiting molecules. We further show that binding sites for context-only and context-initiator TFs underlie enhancer coordination, providing a mechanistic rationale for how a loose TF syntax confers regulatory specificity.

Predicting standardized uptake value of brown adipose tissue from CT scans using convolutional neural networks.

The standard method for identifying active Brown Adipose Tissue (BAT) is [18F]-Fluorodeoxyglucose ([18F]-FDG) PET/CT imaging, which is costly and exposes patients to radiation, making it impractical for population studies. These issues can be addressed with computational methods that predict [18F]-FDG uptake by BAT from CT; earlier population studies pave the way for developing such methods by showing some correlation between the Hounsfield Unit (HU) of BAT in CT and the corresponding [18F]-FDG uptake in PET. In this study, we propose training convolutional neural networks (CNNs) to predict [18F]-FDG uptake by BAT from unenhanced CT scans in the restricted regions that are likely to contain BAT. Using the Attention U-Net architecture, we perform experiments on datasets from four different cohorts, the largest study to date. We segment BAT regions using predicted [18F]-FDG uptake values, achieving 23% to 40% better accuracy than conventional CT thresholding. Additionally, BAT volumes computed from the segmentations distinguish the subjects with and without active BAT with an AUC of 0.8, compared to 0.6 for CT thresholding. These findings suggest CNNs can facilitate large-scale imaging studies more efficiently and cost-effectively using only CT.

Vestigial like 4 regulates the adipogenesis of classical brown adipose tissue.

Brown adipose tissue (BAT) is mammals' primary non-shivering thermogenesis organ, and the molecular mechanisms regulating BAT growth and adipogenesis are largely unknown. The Hippo-YAP pathway has been well-known for controlling organ size, and Vestigial like 4 (VGLL4) is a transcriptional regulator that modulates the Hippo-YAP pathway by competing against YAP for binding to TEAD proteins. In this study, we dissected the function of VGLL4 in regulating BAT development. We generated a conventional Vgll4 mutant mouse line, in which the two Tondu (TDU) domains of VGLL4 were disrupted. We found that deletion of the TDU domains of VGLL4 resulted in perinatal lethality and paucity of the interscapular BAT. Histological and magnetic resonance imaging studies confirmed that the adipogenesis of BAT was impaired in Vgll4 mutants. Adeno-associated virus (AAV) mediated, brown adipocyte-specific overexpression of VGLL4 increased BAT volume and protected the adult male mice from acute cold stress. Genomic studies suggest that VGLL4/TEAD1 complex directly regulates the myogenic and adipogenic gene expression programs of BAT. In conclusion, our data identify VGLL4 as a previously unrecognized adipogenesis factor that regulates classical BAT development.

Non-coding variants impact cis-regulatory coordination in a cell type-specific manner.

BACKGROUND: Interactions among cis-regulatory elements (CREs) play a crucial role in gene regulation. Various approaches have been developed to map these interactions genome-wide, including those relying on interindividual epigenomic variation to identify groups of covariable regulatory elements, referred to as chromatin modules (CMs). While CM mapping allows to investigate the relationship between chromatin modularity and gene expression, the computational principles used for CM identification vary in their application and outcomes. RESULTS: We comprehensively evaluate and streamline existing CM mapping tools and present guidelines for optimal utilization of epigenome data from a diverse population of individuals to assess regulatory coordination across the human genome. We showcase the effectiveness of our recommended practices by analyzing distinct cell types and demonstrate cell type specificity of CRE interactions in CMs and their relevance for gene expression. Integration of genotype information revealed that many non-coding disease-associated variants affect the activity of CMs in a cell type-specific manner by affecting the binding of cell type-specific transcription factors. We provide example cases that illustrate in detail how CMs can be used to deconstruct GWAS loci, assess variable expression of cell surface receptors in immune cells, and reveal how genetic variation can impact the expression of prognostic markers in chronic lymphocytic leukemia. CONCLUSIONS: Our study presents an optimal strategy for CM mapping and reveals how CMs capture the coordination of CREs and its impact on gene expression. Non-coding genetic variants can disrupt this coordination, and we highlight how this may lead to disease predisposition in a cell type-specific manner.

A human omentum-specific mesothelial-like stromal population inhibits adipogenesis through IGFBP2 secretion.

Adipose tissue plasticity is orchestrated by molecularly and functionally diverse cells within the stromal vascular fraction (SVF). Although several mouse and human adipose SVF cellular subpopulations have by now been identified, we still lack an understanding of the cellular and functional variability of adipose stem and progenitor cell (ASPC) populations across human fat depots. To address this, we performed single-cell and bulk RNA sequencing (RNA-seq) analyses of >30 SVF/Lin- samples across four human adipose depots, revealing two ubiquitous human ASPC (hASPC) subpopulations with distinct proliferative and adipogenic properties but also depot- and BMI-dependent proportions. Furthermore, we identified an omental-specific, high IGFBP2-expressing stromal population that transitions between mesothelial and mesenchymal cell states and inhibits hASPC adipogenesis through IGFBP2 secretion. Our analyses highlight the molecular and cellular uniqueness of different adipose niches, while our discovery of an anti-adipogenic IGFBP2+ omental-specific population provides a new rationale for the biomedically relevant, limited adipogenic capacity of omental hASPCs.

Multi-well plate lid for single-step pooling of 96 samples for high-throughput barcode-based sequencing.

High-throughput transcriptomics is of increasing fundamental biological and clinical interest. The generation of molecular data from large collections of samples, such as biobanks and drug libraries, is boosting the development of new biomarkers and treatments. Focusing on gene expression, the transcriptomic market exploits the benefits of next-generation sequencing (NGS), leveraging RNA sequencing (RNA-seq) as standard for measuring genome-wide gene expression in biological samples. The cumbersome sample preparation, including RNA extraction, conversion to cDNA and amplification, prevents high-throughput translation of RNA-seq technologies. Bulk RNA barcoding and sequencing (BRB-seq) addresses this limitation by enabling sample preparation in multi-well plate format. Sample multiplexing combined with early pooling into a single tube reduces reagents consumption and manual steps. Enabling simultaneous pooling of all samples from the multi-well plate into one tube, our technology relies on smart labware: a pooling lid comprising fluidic features and small pins to transport the liquid, adapted to standard 96-well plates. Operated with standard fluidic tubes and pump, the system enables over 90% recovery of liquid in a single step in less than a minute. Large scale manufacturing of the lid is demonstrated with the transition from a milled polycarbonate/steel prototype into an injection molded polystyrene lid. The pooling lid demonstrated its value in supporting high-throughput barcode-based sequencing by pooling 96 different DNA barcodes directly from a standard 96-well plate, followed by processing within the single sample pool. This new pooling technology shows great potential to address medium throughput needs in the BRB-seq workflow, thereby addressing the challenge of large-scale and cost-efficient sample preparation for RNA-seq.

Systematic benchmarking of single-cell ATAC-sequencing protocols.

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols.

Pseudomonas aeruginosa type IV pili actively induce mucus contraction to form biofilms in tissue-engineered human airways.

The opportunistic pathogen Pseudomonas aeruginosa causes antibiotic-recalcitrant pneumonia by forming biofilms in the respiratory tract. Despite extensive in vitro experimentation, how P. aeruginosa forms biofilms at the airway mucosa is unresolved. To investigate the process of biofilm formation in realistic conditions, we developed AirGels: 3D, optically accessible tissue-engineered human lung models that emulate the airway mucosal environment. AirGels recapitulate important factors that mediate host-pathogen interactions including mucus secretion, flow and air-liquid interface (ALI), while accommodating high-resolution live microscopy. With AirGels, we investigated the contributions of mucus to P. aeruginosa biofilm biogenesis in in vivo-like conditions. We found that P. aeruginosa forms mucus-associated biofilms within hours by contracting luminal mucus early during colonization. Mucus contractions facilitate aggregation, thereby nucleating biofilms. We show that P. aeruginosa actively contracts mucus using retractile filaments called type IV pili. Our results therefore suggest that, while protecting epithelia, mucus constitutes a breeding ground for biofilms.

Single-cell biology: what does the future hold?

In this Editorial, our Chief Editor and members of our Advisory Editorial Board discuss recent breakthroughs, current challenges, and emerging opportunities in single-cell biology and share their vision of "where the field is headed."

Direct In Vivo Activation of T Cells with Nanosized Immunofilaments Inhibits Tumor Growth and Metastasis.

Adoptive T cell therapy has successfully been implemented for the treatment of cancer. Nevertheless, ex vivo expansion of T cells by artificial antigen-presenting cells (aAPCs) remains cumbersome and can compromise T cell functionality, thereby limiting their therapeutic potential. We propose a radically different approach aimed at direct expansion of T cells in vivo, thereby omitting the need for large-scale ex vivo T cell production. We engineered nanosized immunofilaments (IFs), with a soluble semiflexible polyisocyanopeptide backbone that presents peptide-loaded major histocompatibility complexes and costimulatory molecules multivalently. IFs readily activated and expanded antigen-specific T cells like natural APCs, as evidenced by transcriptomic analyses of T cells. Upon intravenous injection, IFs reach the spleen and lymph nodes and induce antigen-specific T cell responses in vivo. Moreover, IFs display strong antitumor efficacy resulting in inhibition of the formation of melanoma metastases and reduction of primary tumor growth in synergy with immune checkpoint blockade. In conclusion, nanosized IFs represent a powerful modular platform for direct activation and expansion of antigen-specific T cells in vivo, which can greatly contribute to cancer immunotherapy.

MarrowQuant 2.0: A Digital Pathology Workflow Assisting Bone Marrow Evaluation in Experimental and Clinical Hematology.

Bone marrow (BM) cellularity assessment is a crucial step in the evaluation of BM trephine biopsies for hematologic and nonhematologic disorders. Clinical assessment is based on a semiquantitative visual estimation of the hematopoietic and adipocytic components by hematopathologists, which does not provide quantitative information on other stromal compartments. In this study, we developed and validated MarrowQuant 2.0, an efficient, user-friendly digital hematopathology workflow integrated within QuPath software, which serves as BM quantifier for 5 mutually exclusive compartments (bone, hematopoietic, adipocytic, and interstitial/microvasculature areas and other) and derives the cellularity of human BM trephine biopsies. Instance segmentation of individual adipocytes is realized through the adaptation of the machine-learning-based algorithm StarDist. We calculated BM compartments and adipocyte size distributions of hematoxylin and eosin images obtained from 250 bone specimens, from control subjects and patients with acute myeloid leukemia or myelodysplastic syndrome, at diagnosis and follow-up, and measured the agreement of cellularity estimates by MarrowQuant 2.0 against visual scores from 4 hematopathologists. The algorithm was capable of robust BM compartment segmentation with an average mask accuracy of 86%, maximal for bone (99%), hematopoietic (92%), and adipocyte (98%) areas. MarrowQuant 2.0 cellularity score and hematopathologist estimations were highly correlated (R2 = 0.92-0.98, intraclass correlation coefficient [ICC] = 0.98; interobserver ICC = 0.96). BM compartment segmentation quantitatively confirmed the reciprocity of the hematopoietic and adipocytic compartments. MarrowQuant 2.0 performance was additionally tested for cellularity assessment of specimens prospectively collected from clinical routine diagnosis. After special consideration for the choice of the cellularity equation in specimens with expanded stroma, performance was similar in this setting (R2 = 0.86, n = 42). Thus, we conclude that these validation experiments establish MarrowQuant 2.0 as a reliable tool for BM cellularity assessment. We expect this workflow will serve as a clinical research tool to explore novel biomarkers related to BM stromal components and may contribute to further validation of future digitalized diagnostic hematopathology workstreams.

Chromatin modules and their implication in genomic organization and gene regulation.

Regulation of gene expression is a complex but highly guided process. While genomic technologies and computational approaches have allowed high-throughput mapping of cis-regulatory elements (CREs) and their interactions in 3D, their precise role in regulating gene expression remains obscure. Recent complementary observations revealed that interactions between CREs frequently result in the formation of small-scale functional modules within topologically associating domains. Such chromatin modules likely emerge from a complex interplay between regulatory machineries assembled at CREs, including site-specific binding of transcription factors. Here, we review the methods that allow identifying chromatin modules, summarize possible mechanisms that steer CRE interactions within these modules, and discuss outstanding challenges to uncover how chromatin modules fit in our current understanding of the functional 3D genome.

Current challenges in understanding the role of enhancers in disease.

Enhancers play a central role in the spatiotemporal control of gene expression and tend to work in a cell-type-specific manner. In addition, they are suggested to be major contributors to phenotypic variation, evolution and disease. There is growing evidence that enhancer dysfunction due to genetic, structural or epigenetic mechanisms contributes to a broad range of human diseases referred to as enhanceropathies. Such mechanisms often underlie the susceptibility to common diseases, but can also play a direct causal role in cancer or Mendelian diseases. Despite the recent gain of insights into enhancer biology and function, we still have a limited ability to predict how enhancer dysfunction impacts gene expression. Here we discuss the major challenges that need to be overcome when studying the role of enhancers in disease etiology and highlight opportunities and directions for future studies, aiming to disentangle the molecular basis of enhanceropathies.

Postnatal expansion of mesenteric lymph node stromal cells towards reticular and CD34+ stromal cell subsets.

Gut-draining mesenteric lymph nodes (LN) provide the framework to shape intestinal adaptive immune responses. Based on the transcriptional signatures established by our previous work, the composition and immunomodulatory function of LN stromal cells (SC) vary according to location. Here, we describe the single-cell composition and development of the SC compartment within mesenteric LNs derived from postnatal to aged mice. We identify CD34+ SC and fibroblastic reticular stromal cell (FRC) progenitors as putative progenitors, both supplying the typical rapid postnatal mesenteric LN expansion. We further establish the location-specific chromatin accessibility and DNA methylation landscape of non-endothelial SCs and identify a microbiota-independent core epigenomic signature, showing characteristic differences between SCs from mesenteric and skin-draining peripheral LNs. The epigenomic landscape of SCs points to dynamic expression of Irf3 along the differentiation trajectories of FRCs. Accordingly, a mesenchymal stem cell line acquires a Cxcl9+ FRC molecular phenotype upon lentiviral overexpression of Irf3, and the relevance of Irf3 for SC biology is further underscored by the diminished proportion of Ccl19+ and Cxcl9+ FRCs in LNs of Irf3-/- mice. Together, our data constitute a comprehensive transcriptional and epigenomic map of mesenteric LNSC development in early life and dissect location-specific, microbiota-independent properties of non-endothelial SCs.

Diverse cell-specific patterns of alternative polyadenylation in Drosophila.

Most genes in higher eukaryotes express isoforms with distinct 3' untranslated regions (3' UTRs), generated by alternative polyadenylation (APA). Since 3' UTRs are predominant locations of post-transcriptional regulation, APA can render such programs conditional, and can also alter protein sequences via alternative last exon (ALE) isoforms. We previously used 3'-sequencing from diverse Drosophila samples to define multiple tissue-specific APA landscapes. Here, we exploit comprehensive single nucleus RNA-sequencing data (Fly Cell Atlas) to elucidate cell-type expression of 3' UTRs across >250 adult Drosophila cell types. We reveal the cellular bases of multiple tissue-specific APA/ALE programs, such as 3' UTR lengthening in differentiated neurons and 3' UTR shortening in spermatocytes and spermatids. We trace dynamic 3' UTR patterns across cell lineages, including in the male germline, and discover new APA patterns in the intestinal stem cell lineage. Finally, we correlate expression of RNA binding proteins (RBPs), miRNAs and global levels of cleavage and polyadenylation (CPA) factors in several cell types that exhibit characteristic APA landscapes, yielding candidate regulators of transcriptome complexity. These analyses provide a comprehensive foundation for future investigations of mechanisms and biological impacts of alternative 3' isoforms across the major cell types of this widely-studied model organism.

Mammalian adipogenesis regulator (Areg) cells use retinoic acid signalling to be non- and anti-adipogenic in age-dependent manner.

Adipose stem and precursor cells (ASPCs) give rise to adipocytes and determine the composition and plasticity of adipose tissue. Recently, several studies have demonstrated that ASPCs partition into at least three distinct cell subpopulations, including the enigmatic CD142+ cells. An outstanding challenge is to functionally characterise this population, as discrepant properties, from adipogenic to non- and anti-adipogenic, have been reported for these cells. To resolve these phenotypic ambiguities, we characterised mammalian subcutaneous CD142+ ASPCs across various experimental conditions, demonstrating that CD142+ ASPCs exhibit high molecular and phenotypic robustness. Specifically, we find these cells to be firmly non- and anti-adipogenic both in vitro and in vivo, with their inhibitory signals also impacting adipogenic human cells. However, these CD142+ ASPC-specific properties exhibit surprising temporal phenotypic alterations, and emerge only in an age-dependent manner. Finally, using multi-omic and functional assays, we show that the inhibitory nature of these adipogenesis-regulatory CD142+ ASPCs (Aregs) is driven by specifically expressed secretory factors that cooperate with the retinoic acid signalling pathway to transform the adipogenic state of CD142- ASPCs into a non-adipogenic, Areg-like state.

Live-seq enables temporal transcriptomic recording of single cells.

Single-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize cellular heterogeneity1. However, scRNA-seq requires lysing cells, which impedes further molecular or functional analyses on the same cells. Here, we established Live-seq, a single-cell transcriptome profiling approach that preserves cell viability during RNA extraction using fluidic force microscopy2,3, thus allowing to couple a cell's ground-state transcriptome to its downstream molecular or phenotypic behaviour. To benchmark Live-seq, we used cell growth, functional responses and whole-cell transcriptome read-outs to demonstrate that Live-seq can accurately stratify diverse cell types and states without inducing major cellular perturbations. As a proof of concept, we show that Live-seq can be used to directly map a cell's trajectory by sequentially profiling the transcriptomes of individual macrophages before and after lipopolysaccharide (LPS) stimulation, and of adipose stromal cells pre- and post-differentiation. In addition, we demonstrate that Live-seq can function as a transcriptomic recorder by preregistering the transcriptomes of individual macrophages that were subsequently monitored by time-lapse imaging after LPS exposure. This enabled the unsupervised, genome-wide ranking of genes on the basis of their ability to affect macrophage LPS response heterogeneity, revealing basal Nfkbia expression level and cell cycle state as important phenotypic determinants, which we experimentally validated. Thus, Live-seq can address a broad range of biological questions by transforming scRNA-seq from an end-point to a temporal analysis approach.

A Tead1-Apelin axis directs paracrine communication from myogenic to endothelial cells in skeletal muscle.

Apelin (Apln) is a myokine that regulates skeletal muscle plasticity and metabolism and declines during aging. Through a yeast one-hybrid transcription factor binding screen, we identified the TEA domain transcription factor 1 (Tead1) as a novel regulator of the Apln promoter. Single-cell analysis of regenerating muscle revealed that the apelin receptor (Aplnr) is enriched in endothelial cells, whereas Tead1 is enriched in myogenic cells. Knock-down of Tead1 stimulates Apln secretion from muscle cells in vitro and myofiber-specific overexpression of Tead1 suppresses Apln secretion in vivo. Apln secretion via Tead1 knock-down in muscle cells stimulates endothelial cell expansion via endothelial Aplnr. In vivo, Apln peptide supplementation enhances endothelial cell expansion while Tead1 muscle overexpression delays endothelial remodeling following muscle injury. Our work describes a novel paracrine crosstalk in which Apln secretion is controlled by Tead1 in myogenic cells and influences endothelial remodeling during muscle repair.

Shared acute phase traits in effector and memory human CD8 T cells.

CD8 T cells have multiple functional properties that mediate acute phase and long-term immune protection. Several effector and memory CD8 T cell subsets have been described with diverse functionalities and marker profiles. In contrast to the many comprehensive mouse studies, most human studies lack samples from the acute infection phase, a major reason why current knowledge of human T cell subsets and differentiation remains incomplete, particularly with regard to the T cell heterogeneity early during the immune response. Here we analysed the human CD8 T cell response to yellow fever vaccination as the best-known model to study the human immune response to acute viral infection. We performed flow cytometry on 21 markers conventionally used in mice and in humans to describe differentiation, activation, cycling, and so-called effector functions. We found clearly distinct 'acute traits' at the peak of the response that are shared amongst all non-naïve antigen-specific subsets, including memory-differentiated cells. These acute traits were low BCL-2 and high KI67, CD38, HLA-DR, as well as increased Granzyme B and Perforin, previously attributed only to effector cells at the peak of the response. Furthermore, analysis of chromatin accessibility at the single cell level revealed that memory- and effector-differentiated cells clustered together specifically in the acute phase. Altogether, we demonstrate 'acute traits' across differentiation subsets, and point out the need to discriminate the differentiation states when studying human CD8 T cells that undergo an acute response.