AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics.

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs for atlas-scale datasets like Human Pancreas Analysis Program (HPAP), we develop AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX shows the higher performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulates known islet pathobiology and shows differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.

Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets.

Type 1 diabetes (T1D) is a chronic condition in which beta cells are destroyed by immune cells. Despite progress in immunotherapies that could delay T1D onset, early detection of autoimmunity remains challenging. Here, we evaluate the utility of machine learning for early prediction of T1D using single-cell analysis of islets. Using gradient-boosting algorithms, we model changes in gene expression of single cells from pancreatic tissues in T1D and non-diabetic organ donors. We assess if mathematical modeling could predict the likelihood of T1D development in non-diabetic autoantibody-positive donors. While most autoantibody-positive donors are predicted to be non-diabetic, select donors with unique gene signatures are classified as T1D. Our strategy also reveals a shared gene signature in distinct T1D-associated models across cell types, suggesting a common effect of the disease on transcriptional outputs of these cells. Our study establishes a precedent for using machine learning in early detection of T1D.

Intrinsically disordered domain of transcription factor TCF-1 is required for T cell developmental fidelity.

In development, pioneer transcription factors access silent chromatin to reveal lineage-specific gene programs. The structured DNA-binding domains of pioneer factors have been well characterized, but whether and how intrinsically disordered regions affect chromatin and control cell fate is unclear. Here, we report that deletion of an intrinsically disordered region of the pioneer factor TCF-1 (termed L1) leads to an early developmental block in T cells. The few T cells that develop from progenitors expressing TCF-1 lacking L1 exhibit lineage infidelity distinct from the lineage diversion of TCF-1-deficient cells. Mechanistically, L1 is required for activation of T cell genes and repression of GATA2-driven genes, normally reserved to the mast cell and dendritic cell lineages. Underlying this lineage diversion, L1 mediates binding of TCF-1 to its earliest target genes, which are subject to repression as T cells develop. These data suggest that the intrinsically disordered N terminus of TCF-1 maintains T cell lineage fidelity.

High-throughput Oligopaint screen identifies druggable 3D genome regulators.

The human genome functions as a three-dimensional chromatin polymer, driven by a complex collection of chromosome interactions1-3. Although the molecular rules governing these interactions are being quickly elucidated, relatively few proteins regulating this process have been identified. Here, to address this gap, we developed high-throughput DNA or RNA labelling with optimized Oligopaints (HiDRO)-an automated imaging pipeline that enables the quantitative measurement of chromatin interactions in single cells across thousands of samples. By screening the human druggable genome, we identified more than 300 factors that influence genome folding during interphase. Among these, 43 genes were validated as either increasing or decreasing interactions between topologically associating domains. Our findings show that genetic or chemical inhibition of the ubiquitous kinase GSK3A leads to increased long-range chromatin looping interactions in a genome-wide and cohesin-dependent manner. These results demonstrate the importance of GSK3A signalling in nuclear architecture and the use of HiDRO for identifying mechanisms of spatial genome organization.

Dynamic enhancer interactome promotes senescence and aging.

Gene expression programs are regulated by enhancers which act in a context-specific manner, and can reside at great distances from their target genes. Extensive three-dimensional (3D) genome reorganization occurs in senescence, but how enhancer interactomes are reconfigured during this process is just beginning to be understood. Here we generated high-resolution contact maps of active enhancers and their target genes, assessed chromatin accessibility, and established one-dimensional maps of various histone modifications and transcription factors to comprehensively understand the regulation of enhancer configuration during senescence. Hyper-connected enhancer communities/cliques formed around genes that are highly expressed and within essential gene pathways in each cell state. In addition, motif analysis indicates the involvement of specific transcription factors in hyper-connected regulatory elements in each condition; importantly, MafK, a bZIP family transcription factor, was upregulated in senescence, and reduced expression of MafK ameliorated the senescence phenotypes. Because the accumulation of senescent cells is a key feature of aging, we further investigated enhancer connectomes in the liver of young and aged mice. Hyper-connected enhancer communities were identified during aging, which regulate essential genes that maintain cell differentiation and homeostasis. These findings reveal that hyper-connected enhancer communities correlate with high gene expression in senescence and aging and provide potential hotspots for therapeutic intervention in aging and age-associated diseases.

Quantitative control of Ets1 dosage by a multi-enhancer hub promotes Th1 cell differentiation and protects from allergic inflammation.

Multi-enhancer hubs are spatial clusters of enhancers present across numerous developmental programs. Here, we studied the functional relevance of these three-dimensional structures in T cell biology. Mathematical modeling identified a highly connected multi-enhancer hub at the Ets1 locus, comprising a noncoding regulatory element that was a hotspot for sequence variation associated with allergic disease in humans. Deletion of this regulatory element in mice revealed that the multi-enhancer connectivity was dispensable for T cell development but required for CD4+ T helper 1 (Th1) differentiation. These mice were protected from Th1-mediated colitis but exhibited overt allergic responses. Mechanistically, the multi-enhancer hub controlled the dosage of Ets1 that was required for CTCF recruitment and assembly of Th1-specific genome topology. Our findings establish a paradigm wherein multi-enhancer hubs control cellular competence to respond to an inductive cue through quantitative control of gene dosage and provide insight into how sequence variation within noncoding elements at the Ets1 locus predisposes individuals to allergic responses.

Computational workflow and interactive analysis of single-cell expression profiling of islets generated by the Human Pancreas Analysis Program.

Type 1 and Type 2 diabetes are distinct genetic diseases of the pancreas which are defined by the abnormal level of blood glucose. Understanding the initial molecular perturbations that occur during the pathogenesis of diabetes is of critical importance in understanding these disorders. The inability to biopsy the human pancreas of living donors hampers insights into early detection, as the majority of diabetes studies have been performed on peripheral leukocytes from the blood, which is not the site of pathogenesis. Therefore, efforts have been made by various teams including the Human Pancreas Analysis Program (HPAP) to collect pancreatic tissues from deceased organ donors with different clinical phenotypes. HPAP is designed to define the molecular pathogenesis of islet dysfunction by generating detailed datasets of functional, cellular, and molecular information in pancreatic tissues of clinically well-defined organ donors with Type 1 and Type 2 diabetes. Moreover, data generated by HPAP continously become available through a centralized database, PANC-DB, thus enabling the diabetes research community to access these multi-dimensional data prepublication. Here, we present the computational workflow for single-cell RNA-seq data analysis of 258,379 high-quality cells from the pancreatic islets of 67 human donors generated by HPAP, the largest existing scRNA-seq dataset of human pancreatic tissues. We report various computational steps including preprocessing, doublet removal, clustering and cell type annotation across single-cell RNA-seq data from islets of four distintct classes of organ donors, i.e. non-diabetic control, autoantibody positive but normoglycemic, Type 1 diabetic, and Type 2 diabetic individuals. Moreover, we present an interactive tool, called CellxGene developed by the Chan Zuckerberg initiative, to navigate these high-dimensional datasets. Our data and interactive tools provide a reliable reference for singlecell pancreatic islet biology studies, especially diabetes-related conditions.

AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics.

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs, we developed AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX show the superior performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulated known islet pathobiology and showed differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.

Multiscale 3D genome organization underlies ILC2 ontogenesis and allergic airway inflammation.

Innate lymphoid cells (ILCs) are well-characterized immune cells that play key roles in host defense and tissue homeostasis. Yet, how the three-dimensional (3D) genome organization underlies the development and functions of ILCs is unknown. Herein, we carried out an integrative analysis of the 3D genome structure, chromatin accessibility and gene expression in mature ILCs. Our results revealed that the local 3D configuration of the genome is rewired specifically at loci associated with ILC biology to promote their development and functional differentiation. Importantly, we demonstrated that the ontogenesis of ILC2s and the progression of allergic airway inflammation are determined by a unique local 3D configuration of the region containing the ILC-lineage-defining factor Id2, which is characterized by multiple interactions between the Id2 promoter and distal regulatory elements bound by the transcription factors GATA-3 and RORα, unveiling the mechanism whereby the Id2 expression is specifically controlled in group 2 ILCs.

TCF-1 promotes chromatin interactions across topologically associating domains in T cell progenitors.

The high mobility group (HMG) transcription factor TCF-1 is essential for early T cell development. Although in vitro biochemical assays suggest that HMG proteins can serve as architectural elements in the assembly of higher-order nuclear organization, the contribution of TCF-1 on the control of three-dimensional (3D) genome structures during T cell development remains unknown. Here, we investigated the role of TCF-1 in 3D genome reconfiguration. Using gain- and loss-of-function experiments, we discovered that the co-occupancy of TCF-1 and the architectural protein CTCF altered the structure of topologically associating domains in T cell progenitors, leading to interactions between previously insulated regulatory elements and target genes at late stages of T cell development. The TCF-1-dependent gain in long-range interactions was linked to deposition of active enhancer mark H3K27ac and recruitment of the cohesin-loading factor NIPBL at active enhancers. These data indicate that TCF-1 has a role in controlling global genome organization during T cell development.

α Cell dysfunction in islets from nondiabetic, glutamic acid decarboxylase autoantibody-positive individuals.

BACKGROUNDMultiple islet autoantibodies (AAbs) predict the development of type 1 diabetes (T1D) and hyperglycemia within 10 years. By contrast, T1D develops in only approximately 15% of individuals who are positive for single AAbs (generally against glutamic acid decarboxylase [GADA]); hence, the single GADA+ state may represent an early stage of T1D.METHODSHere, we functionally, histologically, and molecularly phenotyped human islets from nondiabetic GADA+ and T1D donors.RESULTSSimilar to the few remaining ß cells in the T1D islets, GADA+ donor islets demonstrated a preserved insulin secretory response. By contrast, α cell glucagon secretion was dysregulated in both GADA+ and T1D islets, with impaired glucose suppression of glucagon secretion. Single-cell RNA-Seq of GADA+ α cells revealed distinct abnormalities in glycolysis and oxidative phosphorylation pathways and a marked downregulation of cAMP-dependent protein kinase inhibitor ß (PKIB), providing a molecular basis for the loss of glucose suppression and the increased effect of 3-isobutyl-1-methylxanthine (IBMX) observed in GADA+ donor islets.CONCLUSIONWe found that α cell dysfunction was present during the early stages of islet autoimmunity at a time when ß cell mass was still normal, raising important questions about the role of early α cell dysfunction in the progression of T1D.FUNDINGThis work was supported by grants from the NIH (3UC4DK112217-01S1, U01DK123594-02, UC4DK112217, UC4DK112232, U01DK123716, and P30 DK019525) and the Vanderbilt Diabetes Research and Training Center (DK20593).

Topologically associating domains are disrupted by evolutionary genome rearrangements forming species-specific enhancer connections in mice and humans.

Distinguishing between conserved and divergent regulatory mechanisms is essential for translating preclinical research from mice to humans, yet there is a lack of information about how evolutionary genome rearrangements affect the regulation of the immune response, a rapidly evolving system. The current model is topologically associating domains (TADs) are conserved between species, buffering evolutionary rearrangements and conserving long-range interactions within a TAD. However, we find that TADs frequently span evolutionary translocation and inversion breakpoints near genes with species-specific expression in immune cells, creating unique enhancer-promoter interactions exclusive to the mouse or human genomes. This includes TADs encompassing immune-related transcription factors, cytokines, and receptors. For example, we uncover an evolutionary rearrangement that created a shared LPS-inducible regulatory module between OASL and P2RX7 in human macrophages that is absent in mice. Therefore, evolutionary genome rearrangements disrupt TAD boundaries, enabling sequence-conserved enhancer elements from divergent genomic locations between species to create unique regulatory modules.

Stripenn detects architectural stripes from chromatin conformation data using computer vision.

Architectural stripes tend to form at genomic regions harboring genes with salient roles in cell identity and function. Therefore, the accurate identification and quantification of these features are essential for understanding lineage-specific gene regulation. Here, we present Stripenn, an algorithm rooted in computer vision to systematically detect and quantitate architectural stripes from chromatin conformation measurements using various technologies. We demonstrate that Stripenn outperforms existing methods and highlight its biological applications in the context of B and T lymphocytes. By comparing stripes across distinct cell types and different species, we find that these chromatin features are highly conserved and form at genes with prominent roles in cell-type-specific processes. In summary, Stripenn is a computational method that borrows concepts from widely used image processing techniques to demarcate and quantify architectural stripes.

Single-cell multi-omics analysis of human pancreatic islets reveals novel cellular states in type 1 diabetes.

Type 1 diabetes (T1D) is an autoimmune disease in which immune cells destroy insulin-producing beta cells. The aetiology of this complex disease is dependent on the interplay of multiple heterogeneous cell types in the pancreatic environment. Here, we provide a single-cell atlas of pancreatic islets of 24 T1D, autoantibody-positive and nondiabetic organ donors across multiple quantitative modalities including ~80,000 cells using single-cell transcriptomics, ~7,000,000 cells using cytometry by time of flight and ~1,000,000 cells using in situ imaging mass cytometry. We develop an advanced integrative analytical strategy to assess pancreatic islets and identify canonical cell types. We show that a subset of exocrine ductal cells acquires a signature of tolerogenic dendritic cells in an apparent attempt at immune suppression in T1D donors. Our multimodal analyses delineate cell types and processes that may contribute to T1D immunopathogenesis and provide an integrative procedure for exploration and discovery of human pancreatic function.

Transcription factors combine to paint the methylation landscape.

There is paucity of information about DNA methylation dynamics in immune cells. Roy et al. mapped the DNA methylation status of several thousand differentially methylated CpGs in human immune cells. They reported that the extent of cell type-specific hypermethylation is intriguingly most prevalent in adaptive immune cells rather than innate cells.

BRD4 orchestrates genome folding to promote neural crest differentiation.

Higher-order chromatin structure regulates gene expression, and mutations in proteins mediating genome folding underlie developmental disorders known as cohesinopathies. However, the relationship between three-dimensional genome organization and embryonic development remains unclear. Here we define a role for bromodomain-containing protein 4 (BRD4) in genome folding, and leverage it to understand the importance of genome folding in neural crest progenitor differentiation. Brd4 deletion in neural crest results in cohesinopathy-like phenotypes. BRD4 interacts with NIPBL, a cohesin agonist, and BRD4 depletion or loss of the BRD4-NIPBL interaction reduces NIPBL occupancy, suggesting that BRD4 stabilizes NIPBL on chromatin. Chromatin interaction mapping and imaging experiments demonstrate that BRD4 depletion results in compromised genome folding and loop extrusion. Finally, mutation of individual BRD4 amino acids that mediate an interaction with NIPBL impedes neural crest differentiation into smooth muscle. Remarkably, loss of WAPL, a cohesin antagonist, rescues attenuated smooth muscle differentiation resulting from BRD4 loss. Collectively, our data reveal that BRD4 choreographs genome folding and illustrates the relevance of balancing cohesin activity for progenitor differentiation.