Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris

A new atlas to study embryonic cell types in Xenopus

This paper introduces a single-cell atlas for pivotal developmental stages in Xenopus, encompassing gastrulation, neurulation, and early tailbud. Notably surpassing its predecessors, the new atlas enhances gene mapping, read counts, and gene/cell type nomenclature. Leveraging the latest Xenopus tropicalis genome version, alongside advanced alignment pipelines and machine learning for cell type assignment, this release maintains consistency with previous cell type annotations while rectifying nomenclature issues. Employing an unbiased approach for cell type assignment proves especially apt for embryonic contexts, given the considerable number of non-terminally differentiated cell types. An alternative cell type attribution here adopts a fuzzy, non-deterministic stance, capturing the transient nature of early embryo progenitor cells by presenting an ensemble of types in superposition. The value of the new resource is emphasized through numerous examples, with a focus on previously unexplored germ cell populations where we uncover novel transcription onset features. Offering interactive exploration via a user-friendly web portal and facilitating complete data downloads, this atlas serves as a comprehensive and accessible reference.

Brd4::Nutm1 fusion gene initiates NUT carcinoma in vivo

NUT carcinoma (NC) is an aggressive cancer with no effective treatment. About 70% of NUT carcinoma is associated with chromosome translocation events that lead to the formation of a BRD4::NUTM1 fusion gene. Because the BRD4::NUTM1 gene is unequivocally cytotoxic when ectopically expressed in cell lines, questions remain on whether the fusion gene can initiate NC. Here, we report the first genetically engineered mouse model for NUT carcinoma that recapitulates the human t(15;19) chromosome translocation in mice. We demonstrated that the mouse t(2;17) syntenic chromosome translocation, forming the Brd4::Nutm1 fusion gene, could induce aggressive carcinomas in mice. The tumors present histopathological and molecular features similar to human NC, with enrichment of undifferentiated cells. Similar to the reports of human NC incidence, Brd4::Nutm1 can induce NC from a broad range of tissues with a strong phenotypical variability. The consistent induction of poorly differentiated carcinoma demonstrated a strong reprogramming activity of BRD4::NUTM1. The new mouse model provided a critical preclinical model for NC that will lead to better understanding and therapy development for NC.

Coronary Artery Disease Risk Variant Dampens the Expression of CALCRL by Reducing HSF Binding to Shear Stress Responsive Enhancer in Endothelial Cells In Vitro

BACKGROUND

CALCRL (calcitonin receptor-like) protein is an important mediator of the endothelial fluid shear stress response, which is associated with the genetic risk of coronary artery disease. In this study, we functionally characterized the noncoding regulatory elements carrying coronary artery disease that risks single-nucleotide polymorphisms and studied their role in the regulation of CALCRL expression in endothelial cells.

METHODS

To functionally characterize the coronary artery disease single-nucleotide polymorphisms harbored around the gene CALCRL, we applied an integrative approach encompassing statistical, transcriptional (RNA-seq), and epigenetic (ATAC-seq [transposase-accessible chromatin with sequencing], chromatin immunoprecipitation assay-quantitative polymerase chain reaction, and electromobility shift assay) analyses, alongside luciferase reporter assays, and targeted gene and enhancer perturbations (siRNA and clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat-associated 9) in human aortic endothelial cells.

RESULTS

We demonstrate that the regulatory element harboring rs880890 exhibits high enhancer activity and shows significant allelic bias. The A allele was favored over the G allele, particularly under shear stress conditions, mediated through alterations in the HSF1 (heat shock factor 1) motif and binding. CRISPR deletion of rs880890 enhancer resulted in downregulation of CALCRL expression, whereas HSF1 knockdown resulted in a significant decrease in rs880890-enhancer activity and CALCRL expression. A significant decrease in HSF1 binding to the enhancer region in endothelial cells was observed under disturbed flow compared with unidirectional flow. CALCRL knockdown and variant perturbation experiments indicated the role of CALCRL in mediating eNOS (endothelial nitric oxide synthase), APLN (apelin), angiopoietin, prostaglandins, and EDN1 (endothelin-1) signaling pathways leading to a decrease in cell proliferation, tube formation, and NO production.

CONCLUSIONS

Overall, our results demonstrate the existence of an endothelial-specific HSF (heat shock factor)-regulated transcriptional enhancer that mediates CALCRL expression. A better understanding of CALCRL gene regulation and the role of single-nucleotide polymorphisms in the modulation of CALCRL expression could provide important steps toward understanding the genetic regulation of shear stress signaling responses.

Identification of ANKRD13D as a potential target in renal cell carcinomas

BACKGROUND

The correlation of the expression of ankyrin repeat domain (ANKRD) family members with renal cell carcinoma prognosis was investigated.

METHODS

The GEPIA2, GEO2R, UALCAN, GDC, OncoLnc, TIMER, PanglaoDB, CancerSEA, and Tabula Muris databases were used. Twelve ANKRD family members were identified as having overexpressed renal cell carcinoma samples. The ANKRD13D was identified as a renal cell carcinoma-specific target by cross-referencing the multiple survival databases. To clarify the role of ANKRD13D, the expression of NAKRD13D was analyzed at the single-cell level.

RESULTS

ANKRD13D was mainly expressed in immune cells and positively correlated with Treg cell infiltration. The expression of ANKRD13D was also positively correlated with PDCD1, CTLA4, LAG3, TNFSF14, and ISG20. The overexpression of ANKRD13D in Treg was confirmed using reverse transcription-quantitative polymerase chain reaction. The structure of ANKRD13D was predicted using AlphaFold.

CONCLUSION

In conclusion, we identified ANKRD13D as a key immune regulator, and targeting ANKRD13D with immune checkpoints blockade may be a promoting strategy for renal cell carcinoma immunotherapy.

SpatialPrompt: spatially aware scalable and accurate tool for spot deconvolution and domain identification in spatial transcriptomics

Efficiently mapping of cell types in situ remains a major challenge in spatial transcriptomics. Most spot deconvolution tools ignore spatial coordinate information and perform extremely slow on large datasets. Here, we introduce SpatialPrompt, a spatially aware and scalable tool for spot deconvolution and domain identification. SpatialPrompt integrates gene expression, spatial location, and single-cell RNA sequencing (scRNA-seq) dataset as reference to accurately infer cell-type proportions of spatial spots. SpatialPrompt uses non-negative ridge regression and graph neural network to efficiently capture local microenvironment information. Our extensive benchmarking analysis on Visium, Slide-seq, and MERFISH datasets demonstrated superior performance of SpatialPrompt over 15 existing tools. On mouse hippocampus dataset, SpatialPrompt achieves spot deconvolution and domain identification within 2 minutes for 50,000 spots. Overall, domain identification using SpatialPrompt was 44 to 150 times faster than existing methods. We build a database housing 40 plus curated scRNA-seq datasets for seamless integration with SpatialPrompt for spot deconvolution.

Contribution of VEGF-B-Induced Endocardial Endothelial Cell Lineage in Physiological Versus Pathological Cardiac Hypertrophy

BACKGROUND

Preclinical studies have shown the therapeutic potential of VEGF-B (vascular endothelial growth factor B) in revascularization of the ischemic myocardium, but the associated cardiac hypertrophy and adverse side effects remain a concern. To understand the importance of endothelial proliferation and migration for the beneficial versus adverse effects of VEGF-B in the heart, we explored the cardiac effects of autocrine versus paracrine VEGF-B expression in transgenic and gene-transduced mice.

METHODS

We used single-cell RNA sequencing to compare cardiac endothelial gene expression in VEGF-B transgenic mouse models. Lineage tracing was used to identify the origin of a VEGF-B-induced novel endothelial cell population and adeno-associated virus-mediated gene delivery to compare the effects of VEGF-B isoforms. Cardiac function was investigated using echocardiography, magnetic resonance imaging, and micro-computed tomography.

RESULTS

Unlike in physiological cardiac hypertrophy driven by a cardiomyocyte-specific VEGF-B transgene (myosin heavy chain alpha-VEGF-B), autocrine VEGF-B expression in cardiac endothelium (aP2 [adipocyte protein 2]-VEGF-B) was associated with septal defects and failure to increase perfused subendocardial capillaries postnatally. Paracrine VEGF-B led to robust proliferation and myocardial migration of a novel cardiac endothelial cell lineage (VEGF-B-induced endothelial cells) of endocardial origin, whereas autocrine VEGF-B increased proliferation of VEGF-B-induced endothelial cells but failed to promote their migration and efficient contribution to myocardial capillaries. The surviving aP2-VEGF-B offspring showed an altered ratio of secreted VEGF-B isoforms and developed massive pathological cardiac hypertrophy with a distinct cardiac vessel pattern. In the normal heart, we found a small VEGF-B-induced endothelial cell population that was only minimally expanded during myocardial infarction but not during physiological cardiac hypertrophy associated with mouse pregnancy.

CONCLUSIONS

Paracrine and autocrine secretions of VEGF-B induce expansion of a specific endocardium-derived endothelial cell population with distinct angiogenic markers. However, autocrine VEGF-B signaling fails to promote VEGF-B-induced endothelial cell migration and contribution to myocardial capillaries, predisposing to septal defects and inducing a mismatch between angiogenesis and myocardial growth, which results in pathological cardiac hypertrophy.

Biochemical-free enrichment or depletion of RNA classes in real-time during direct RNA sequencing with RISER

The heterogeneous composition of cellular transcriptomes poses a major challenge for detecting weakly expressed RNA classes, as they can be obscured by abundant RNAs. Although biochemical protocols can enrich or deplete specified RNAs, they are time-consuming, expensive and can compromise RNA integrity. Here we introduce RISER, a biochemical-free technology for the real-time enrichment or depletion of RNA classes. RISER performs selective rejection of molecules during direct RNA sequencing by identifying RNA classes directly from nanopore signals with deep learning and communicating with the sequencing hardware in real time. By targeting the dominant messenger and mitochondrial RNA classes for depletion, RISER reduces their respective read counts by more than 85%, resulting in an increase in sequencing depth of 47% on average for long non-coding RNAs. We also apply RISER for the depletion of globin mRNA in whole blood, achieving a decrease in globin reads by more than 90% as well as an increase in non-globin reads by 16% on average. Furthermore, using a GPU or a CPU, RISER is faster than GPU-accelerated basecalling and mapping. RISER's modular and retrainable software and intuitive command-line interface allow easy adaptation to other RNA classes. RISER is available at https://github.com/comprna/riser .

Establishing a conceptual framework for holistic cell states and state transitions

Cell states were traditionally defined by how they looked, where they were located, and what functions they performed. In this post-genomic era, the field is largely focused on a molecular view of cell state. Moving forward, we anticipate that the observables used to define cell states will evolve again as single-cell imaging and analytics are advancing at a breakneck pace via the collection of large-scale, systematic cell image datasets and the application of quantitative image-based data science methods. This is, therefore, a key moment in the arc of cell biological research to develop approaches that integrate the spatiotemporal observables of the physical structure and organization of the cell with molecular observables toward the concept of a holistic cell state. In this perspective, we propose a conceptual framework for holistic cell states and state transitions that is data-driven, practical, and useful to enable integrative analyses and modeling across many data types.

Protocol for quantifying stem-cell-derived cardiomyocyte maturity using transcriptomic entropy score

The inability to quantify cardiomyocyte (CM) maturation remains a significant barrier to evaluating the effects of ongoing efforts to produce adult-like CMs from pluripotent stem cells (PSCs). Here, we present a protocol to quantify stem-cell-derived CM maturity using a single-cell RNA sequencing-based metric "entropy score." We describe steps for generating an entropy score using customized R code. This tool can be used to quantify maturation levels of PSC-CMs and potentially other cell types. For complete details on the use and execution of this protocol, please refer to Kannan et al.1.

Gain-of-function mutations of TRPV4 acting in endothelial cells drive blood-CNS barrier breakdown and motor neuron degeneration in mice

Blood-CNS barrier disruption is a hallmark of numerous neurological disorders, yet whether barrier breakdown is sufficient to trigger neurodegenerative disease remains unresolved. Therapeutic strategies to mitigate barrier hyperpermeability are also limited. Dominant missense mutations of the cation channel transient receptor potential vanilloid 4 (TRPV4) cause forms of hereditary motor neuron disease. To gain insights into the cellular basis of these disorders, we generated knock-in mouse models of TRPV4 channelopathy by introducing two disease-causing mutations (R269C and R232C) into the endogenous mouse Trpv4 gene. TRPV4 mutant mice exhibited weakness, early lethality, and regional motor neuron loss. Genetic deletion of the mutant Trpv4 allele from endothelial cells (but not neurons, glia, or muscle) rescued these phenotypes. Symptomatic mutant mice exhibited focal disruptions of blood-spinal cord barrier (BSCB) integrity, associated with a gain of function of mutant TRPV4 channel activity in neural vascular endothelial cells (NVECs) and alterations of NVEC tight junction structure. Systemic administration of a TRPV4-specific antagonist abrogated channel-mediated BSCB impairments and provided a marked phenotypic rescue of symptomatic mutant mice. Together, our findings show that mutant TRPV4 channels can drive motor neuron degeneration in a non-cell autonomous manner by precipitating focal breakdown of the BSCB. Further, these data highlight the reversibility of TRPV4-mediated BSCB impairments and identify a potential therapeutic strategy for patients with TRPV4 mutations.

TSG-6-Mediated Extracellular Matrix Modifications Regulate Hypoxic-Ischemic Brain Injury

Proteoglycans containing link domains modify the extracellular matrix (ECM) to regulate cellular homeostasis and can also sensitize tissues/organs to injury and stress. Hypoxic-ischemic (H-I) injury disrupts cellular homeostasis by activating inflammation and attenuating regeneration and repair pathways. In the brain, the main component of the ECM is the glycosaminoglycan hyaluronic acid (HA), but whether HA modifications of the ECM regulate cellular homeostasis and response to H-I injury is not known. In this report, employing both male and female mice, we demonstrate that link-domain-containing proteoglycan, TNFα-stimulated gene-6 (TSG-6), is active in the brain from birth onward and differentially modifies ECM HA during discrete neurodevelopmental windows. ECM HA modification by TSG-6 enables it to serve as a developmental switch to regulate the activity of the Hippo pathway effector protein, yes-associated protein 1 (YAP1), in the maturing brain and in response to H-I injury. Mice that lack TSG-6 expression display dysregulated expression of YAP1 targets, excitatory amino acid transporter 1 (EAAT1; glutamate-aspartate transporter) and 2 (EAAT2; glutamate transporter-1). Dysregulation of YAP1 activation in TSG-6-/- mice coincides with age- and sex-dependent sensitization of the brain to H-I injury such that 1-week-old neonates display an anti-inflammatory response in contrast to an enhanced proinflammatory injury reaction in 3-month-old adult males but not females. Our findings thus support that a key regulator of age- and sex-dependent H-I injury response in the mouse brain is modulation of the Hippo-YAP1 pathway by TSG-6-dependent ECM modifications.

Direct conversion of cardiac fibroblasts into endothelial-like cells using Sox17 and Erg

Endothelial cells are a heterogeneous population with various organ-specific and conserved functions that are critical to organ development, function, and regeneration. Here we report a Sox17-Erg direct reprogramming approach that uses cardiac fibroblasts to create differentiated endothelial cells that demonstrate endothelial-like molecular and physiological functions in vitro and in vivo. Injection of these induced endothelial cells into myocardial infarct sites after injury results in improved vascular perfusion of the scar region. Furthermore, we use genomic analyses to illustrate that Sox17-Erg reprogramming instructs cardiac fibroblasts toward an arterial-like identity. This results in a more efficient direct conversion of fibroblasts into endothelial-like cells when compared to traditional Etv2-based reprogramming. Overall, this Sox17-Erg direct reprogramming strategy offers a robust tool to generate endothelial cells both in vitro and in vivo, and has the potential to be used in repairing injured tissue.

The main duct of von Ebner's glands is a source of Sox10 + taste bud progenitors and susceptible to pathogen infections

We have recently demonstrated that Sox10 -expressing ( Sox10 + ) cells give rise to mainly type-III neuronal taste bud cells that are responsible for sour and salt taste. The two tissue compartments containing Sox10 + cells in the surrounding of taste buds include the connective tissue core of taste papillae and von Ebner's glands (vEGs) that are connected to the trench of circumvallate and foliate papillae. In this study, we used inducible Cre mouse models to map the cell lineages of connective tissue (including stromal and Schwann cells) and vEGs and performed single cell RNA-sequencing of the epithelium of Sox10-Cre/tdT mouse circumvallate/vEG complex. In vivo lineage mapping showed that the distribution of traced cells in circumvallate taste buds was closely linked with that in the vEGs, but not in the connective tissue. Sox10 , but not the known stem cells marker Lgr5 , expression was enriched in the cell clusters of main ducts of vEGs that contained abundant proliferating cells, while Sox10-Cre/tdT expression was enriched in type-III taste bud cells and excretory ductal cells. Moreover, multiple genes encoding pathogen receptors are enriched in the vEG main ducts. Our data indicate that the main duct of vEGs is a source of Sox10 + taste bud progenitors and susceptible to pathogen infections.

Quantifying 3'UTR length from scRNA-seq data reveals changes independent of gene expression

Although more than half of all genes generate transcripts that differ in 3'UTR length, current analysis pipelines only quantify the amount but not the length of mRNA transcripts. 3'UTR length is determined by 3' end cleavage sites (CS). We map CS in more than 200 primary human and mouse cell types and increase CS annotations relative to the GENCODE database by 40%. Approximately half of all CS are used in few cell types, revealing that most genes only have one or two major 3' ends. We incorporate the CS annotations into a computational pipeline, called scUTRquant, for rapid, accurate, and simultaneous quantification of gene and 3'UTR isoform expression from single-cell RNA sequencing (scRNA-seq) data. When applying scUTRquant to data from 474 cell types and 2134 perturbations, we discover extensive 3'UTR length changes across cell types that are as widespread and coordinately regulated as gene expression changes but affect mostly different genes. Our data indicate that mRNA abundance and mRNA length are two largely independent axes of gene regulation that together determine the amount and spatial organization of protein synthesis.

LGR4 is essential for maintaining β-cell homeostasis through suppression of RANK

Pancreatic β-cell stress contributes to diabetes progression. This study demonstrates that Leucine-rich repeat-containing G-protein-coupled-receptor-4 (LGR4) is critical for maintaining β-cell health and is modulated by stressors. In vitro , Lgr4 knockdown decreases proliferation and survival in rodent β-cells, while overexpression protects against cytokine-induced cell death in rodent and human β-cells. Mechanistically, LGR4 suppresses Receptor Activator of Nuclear Factor Kappa B (NFκB) (RANK) and its subsequent activation of NFκB to protect β-cells. β-cell-specific Lgr4 -conditional knockout (cko) mice exhibit normal glucose homeostasis but increased β-cell death in both sexes and decreased proliferation only in females. Male Lgr4 cko mice under stress display reduced β-cell proliferation and a further increase in β-cell death. Upon aging, both male and female Lgr4 cko mice display impaired β-cell homeostasis, however, only female mice are glucose intolerant with decreased plasma insulin. We show that LGR4 is required for maintaining β-cell health under basal and stress-induced conditions, through suppression of RANK.

Teaser

LGR4 receptor is critical for maintaining β-cell health under basal and stressed conditions, through suppression of RANK.

Mutant IDH inhibitors induce lineage differentiation in IDH-mutant oligodendroglioma

A subset of patients with IDH-mutant glioma respond to inhibitors of mutant IDH (IDHi), yet the molecular underpinnings of such responses are not understood. Here, we profiled by single-cell or single-nucleus RNA-sequencing three IDH-mutant oligodendrogliomas from patients who derived clinical benefit from IDHi. Importantly, the tissues were sampled on-drug, four weeks from treatment initiation. We further integrate our findings with analysis of single-cell and bulk transcriptomes from independent cohorts and experimental models. We find that IDHi treatment induces a robust differentiation toward the astrocytic lineage, accompanied by a depletion of stem-like cells and a reduction of cell proliferation. Furthermore, mutations in NOTCH1 are associated with decreased astrocytic differentiation and may limit the response to IDHi. Our study highlights the differentiating potential of IDHi on the cellular hierarchies that drive oligodendrogliomas and suggests a genetic modifier that may improve patient stratification.

The future of rapid and automated single-cell data analysis using reference mapping

As the number of single-cell datasets continues to grow rapidly, workflows that map new data to well-curated reference atlases offer enormous promise for the biological community. In this perspective, we discuss key computational challenges and opportunities for single-cell reference-mapping algorithms. We discuss how mapping algorithms will enable the integration of diverse datasets across disease states, molecular modalities, genetic perturbations, and diverse species and will eventually replace manual and laborious unsupervised clustering pipelines.

Integrative spatial analysis reveals a multi-layered organization of glioblastoma

Glioma contains malignant cells in diverse states. Here, we combine spatial transcriptomics, spatial proteomics, and computational approaches to define glioma cellular states and uncover their organization. We find three prominent modes of organization. First, gliomas are composed of small local environments, each typically enriched with one major cellular state. Second, specific pairs of states preferentially reside in proximity across multiple scales. This pairing of states is consistent across tumors. Third, these pairwise interactions collectively define a global architecture composed of five layers. Hypoxia appears to drive the layers, as it is associated with a long-range organization that includes all cancer cell states. Accordingly, tumor regions distant from any hypoxic/necrotic foci and tumors that lack hypoxia such as low-grade IDH-mutant glioma are less organized. In summary, we provide a conceptual framework for the organization of cellular states in glioma, highlighting hypoxia as a long-range tissue organizer.

Native N-glycome profiling of single cells and ng-level blood isolates using label-free capillary electrophoresis-mass spectrometry

The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we present an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased quantitative characterization of single-cell surface N-glycomes are demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations are unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow is also applied to the profiling of ng-level amounts (5-500 ng) of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.

Disentangling associations between complex traits and cell types with seismic

Integrating single-cell RNA sequencing (scRNA-seq) with Genome-Wide Association Studies (GWAS) can help reveal GWAS-associated cell types, furthering our understanding of the cell-type-specific biological processes underlying complex traits and disease. However, current methods have technical limitations that hinder them from making systematic, scalable, interpretable disease-cell-type associations. In order to rapidly and accurately pinpoint associations, we develop a novel framework, seismic , which characterizes cell types using a new specificity score. We compare seismic with alternative methods across over 1,000 cell type characterizations at different granularities and 28 traits, demonstrating that seismic both corroborates findings and identifies trait-relevant cell groups which are not apparent through other methodologies. Furthermore, as part of the seismic framework, the specific genes driving cell type-trait associations can easily be accessed and analyzed, enabling further biological insights. The advantages of seismic are particularly salient in neurodegenerative diseases such as Parkinson's and Alzheimer's, where disease pathology has not only cell-specific manifestations, but also brain region-specific differences. Interestingly, a case study of Alzheimer's disease reveals the importance of considering GWAS endpoints, as studies relying on clinical diagnoses consistently identify microglial associations, while GWAS with a tau biomarker endpoint reveals neuronal associations. In general, seismic is a computationally efficient, powerful, and interpretable approach for identifying associations between complex traits and cell type-specific expression.

Modeling blood-brain barrier formation and cerebral cavernous malformations in human PSC-derived organoids

The human blood-brain barrier (hBBB) is a highly specialized structure that regulates passage across blood and central nervous system (CNS) compartments. Despite its critical physiological role, there are no reliable in vitro models that can mimic hBBB development and function. Here, we constructed hBBB assembloids from brain and blood vessel organoids derived from human pluripotent stem cells. We validated the acquisition of blood-brain barrier (BBB)-specific molecular, cellular, transcriptomic, and functional characteristics and uncovered an extensive neuro-vascular crosstalk with a spatial pattern within hBBB assembloids. When we used patient-derived hBBB assembloids to model cerebral cavernous malformations (CCMs), we found that these assembloids recapitulated the cavernoma anatomy and BBB breakdown observed in patients. Upon comparison of phenotypes and transcriptome between patient-derived hBBB assembloids and primary human cavernoma tissues, we uncovered CCM-related molecular and cellular alterations. Taken together, we report hBBB assembloids that mimic the core properties of the hBBB and identify a potentially underlying cause of CCMs.

Beaconet: A Reference-Free Method for Integrating Multiple Batches of Single-Cell Transcriptomic Data in Original Molecular Space

Integrating multiple single-cell datasets is essential for the comprehensive understanding of cell heterogeneity. Batch effect is the undesired systematic variations among technologies or experimental laboratories that distort biological signals and hinder the integration of single-cell datasets. However, existing methods typically rely on a selected dataset as a reference, leading to inconsistent integration performance using different references, or embed cells into uninterpretable low-dimensional feature space. To overcome these limitations, a reference-free method, Beaconet, for integrating multiple single-cell transcriptomic datasets in original molecular space by aligning the global distribution of each batch using an adversarial correction network is presented. Through extensive comparisons with 13 state-of-the-art methods, it is demonstrated that Beaconet can effectively remove batch effect while preserving biological variations and is superior to existing unsupervised methods using all possible references in overall performance. Furthermore, Beaconet performs integration in the original molecular feature space, enabling the characterization of cell types and downstream differential expression analysis directly using integrated data with gene-expression features. Additionally, when applying to large-scale atlas data integration, Beaconet shows notable advantages in both time- and space-efficiencies. In summary, Beaconet serves as an effective and efficient batch effect removal tool that can facilitate the integration of single-cell datasets in a reference-free and molecular feature-preserved mode.

A metabolic atlas of mouse aging

Humans are living longer, but this is accompanied by an increased incidence of age-related chronic diseases. Many of these diseases are influenced by age-associated metabolic dysregulation, but how metabolism changes in multiple organs during aging in males and females is not known. Answering this could reveal new mechanisms of aging and age-targeted therapeutics. In this study, we describe how metabolism changes in 12 organs in male and female mice at 5 different ages. Organs show distinct patterns of metabolic aging that are affected by sex differently. Hydroxyproline shows the most consistent change across the dataset, decreasing with age in 11 out of 12 organs investigated. We also developed a metabolic aging clock that predicts biological age and identified alpha-ketoglutarate, previously shown to extend lifespan in mice, as a key predictor of age. Our results reveal fundamental insights into the aging process and identify new therapeutic targets to maintain organ health.

scTPC: a novel semisupervised deep clustering model for scRNA-seq data

MOTIVATION

Continuous advancements in single-cell RNA sequencing (scRNA-seq) technology have enabled researchers to further explore the study of cell heterogeneity, trajectory inference, identification of rare cell types, and neurology. Accurate scRNA-seq data clustering is crucial in single-cell sequencing data analysis. However, the high dimensionality, sparsity, and presence of "false" zero values in the data can pose challenges to clustering. Furthermore, current unsupervised clustering algorithms have not effectively leveraged prior biological knowledge, making cell clustering even more challenging.

RESULTS

This study investigates a semisupervised clustering model called scTPC, which integrates the triplet constraint, pairwise constraint, and cross-entropy constraint based on deep learning. Specifically, the model begins by pretraining a denoising autoencoder based on a zero-inflated negative binomial distribution. Deep clustering is then performed in the learned latent feature space using triplet constraints and pairwise constraints generated from partial labeled cells. Finally, to address imbalanced cell-type datasets, a weighted cross-entropy loss is introduced to optimize the model. A series of experimental results on 10 real scRNA-seq datasets and five simulated datasets demonstrate that scTPC achieves accurate clustering with a well-designed framework.

AVAILABILITY AND IMPLEMENTATION

scTPC is a Python-based algorithm, and the code is available from https://github.com/LF-Yang/Code or https://zenodo.org/records/10951780.

Global IL4Rα blockade exacerbates heart failure after an ischemic event in mice and humans

Ischemic heart failure continues to be a highly prevalent disease among westernized countries and there is great interest in understanding the mechanisms preventing or exacerbating disease progression. The literature suggests an important role for the activation of interleukin-13 or interleukin-4 signaling in improving ischemic heart failure outcomes after myocardial infarction in mice. Dupilumab, a neutralizing antibody that inhibits the shared IL13/IL4 receptor subunit IL4Rα, is widely used for conditions such as ectopic dermatitis in humans. If global depletion of IL4Rα influences ischemic heart failure, either in mice or in humans taking dupilumab, is unknown. Here, we investigated the pathophysiological effects of global IL4Rα genetic deletion in adult mice after surgically induced myocardial infarction (MI). We also determined heart failure risk in patients with ischemic heart disease and concomitant usage of dupilumab using the collaborative patient data network TriNetX. Global deletion of IL4Rα results in exacerbated cardiac dysfunction associated with reduced capillary size after myocardial infarction in mice. In agreement with our findings in mice, dupilumab treatment significantly increased the risk of heart failure development in patients with preexisting diagnosis of ischemic heart disease. Our results indicate that systemic IL4Rα signaling is protective against heart failure development in adult mice and human patients specifically following an ischemic event. Thus, the compelling evidence presented hereby advocates for the development of a randomized clinical trial specifically investigating heart failure development after myocardial ischemia in patients taking dupilumab for another underlying condition.NEW & NOTEWORTHY A body of literature suggests a protective role for IL4Rα signaling postmyocardial infarction in mice. Here, our observational study demonstrates that humans taking the IL4Rα neutralizing antibody, dupilumab, have increased incidence of heart failure following an ischemic event. Similarly, global IL4Rα deletion in mice exacerbates heart failure postinfarct. To our knowledge, this is the first study reporting an adverse association in humans of dupilumab use with heart failure following a cardiac ischemic event.

Identification of a myofibroblast differentiation program during neonatal lung development

Alveologenesis is the final stage of lung development in which the internal surface area of the lung is increased to facilitate efficient gas exchange in the mature organism. The first phase of alveologenesis involves the formation of septal ridges (secondary septae) and the second phase involves thinning of the alveolar septa. Within secondary septa, mesenchymal cells include a transient population of alveolar myofibroblasts (MyoFBs) and a stable but poorly described population of lipid-rich cells that have been referred to as lipofibroblasts or matrix fibroblasts (MatFBs). Using a unique Fgf18CreER lineage trace mouse line, cell sorting, single-cell RNA sequencing and primary cell culture, we have identified multiple subtypes of mesenchymal cells in the neonatal lung, including an immature progenitor cell that gives rise to mature MyoFB. We also show that the endogenous and targeted ROSA26 locus serves as a sensitive reporter for MyoFB maturation. These studies identify a MyoFB differentiation program that is distinct from other mesenchymal cell types and increases the known repertoire of mesenchymal cell types in the neonatal lung.

Transcription factor PBX4 regulates limb development and haematopoiesis in mice

The mammalian Pre-B cell leukaemia transcription factors 1-4 (PBX1-4) constitutes the PBC class of the homeodomain (HD)-containing proteins, which play important roles in diverse developmental processes. The functions and the underlying molecular mechanisms of PBX1-3 but not PBX4 have been extensively studied, and they have been reported to direct essential morphogenetic processes and organogenesis. In the present study, we generated knockin mice of FLAG-tagged PBX4 and the Pbx4 knockout (KO) mice and carried out in-depth characterisation of PBX4 expression and function. PBX4 was initially detected only in the testis among several organs of the adult mice and was expressed in spermatocytes and spermatids. However, no abnormality in spermatogenesis, but growth retardation and premature death after birth were observed in most adult Pbx4 KO mice. These animals were inactive and had shorter hindlimbs and lower numbers of reticulocytes and lymphocytes, probably caused by abnormalities at earlier developmental stages. Pbx4 mRNAs were indeed detected in several embryonic cell types related to limb development by in situ hybridisation and single-cell RNA-sequencing analysis. Pbx4 protein was also detected in the bone marrow of adult mice with a lower level compared with that in the testis. PBX4 preferentially binds to the promoters of a large number of genes including those for other HD-containing proteins and ribosomal proteins whose mutations are related to anaemia. PBX4-binding sites are enriched in motifs similar to those of other HD-containing proteins such as PKNOX1 indicating that PBX4 may also act as a co-transcription factor like other PBC proteins. Together, these results show that PBX4 participates in limb development and haematopoiesis while its function in spermatogenesis has not been revealed by gene KO probably due to the complementary effects of other genes.

PPPCT: Privacy-Preserving framework for Parallel Clustering Transcriptomics data

Single-cell transcriptomics data provides crucial insights into patients' health, yet poses significant privacy concerns. Genomic data privacy attacks can have deep implications, encompassing not only the patients' health information but also extending widely to compromise their families'. Moreover, the permanence of leaked data exacerbates the challenges, making retraction an impossibility. While extensive efforts have been directed towards clustering single-cell transcriptomics data, addressing critical challenges, especially in the realm of privacy, remains pivotal. This paper introduces an efficient, fast, privacy-preserving approach for clustering single-cell RNA-sequencing (scRNA-seq) datasets. The key contributions include ensuring data privacy, achieving high-quality clustering, accommodating the high dimensionality inherent in the datasets, and maintaining reasonable computation time for big-scale datasets. Our proposed approach utilizes the map-reduce scheme to parallelize clustering, addressing intensive calculation challenges. Intel Software Guard eXtension (SGX) processors are used to ensure the security of sensitive code and data during processing. Additionally, the approach incorporates a logarithm transformation as a preprocessing step, employs non-negative matrix factorization for dimensionality reduction, and utilizes parallel k-means for clustering. The approach fully leverages the computing capabilities of all processing resources within a secure private cloud environment. Experimental results demonstrate the efficacy of our approach in preserving patient privacy while surpassing state-of-the-art methods in both clustering quality and computation time. Our method consistently achieves a minimum of 7% higher Adjusted Rand Index (ARI) than existing approaches, contingent on dataset size. Additionally, due to parallel computations and dimensionality reduction, our approach exhibits efficiency, converging to very good results in less than 10 seconds for a scRNA-seq dataset with 5000 genes and 6000 cells when prioritizing privacy and under two seconds without privacy considerations. Availability and implementation Code and datasets availability: https://github.com/University-of-Windsor/PPPCT.

JAK-STAT signaling maintains homeostasis in T cells and macrophages

Immune cells need to sustain a state of constant alertness over a lifetime. Yet, little is known about the regulatory processes that control the fluent and fragile balance that is called homeostasis. Here we demonstrate that JAK-STAT signaling, beyond its role in immune responses, is a major regulator of immune cell homeostasis. We investigated JAK-STAT-mediated transcription and chromatin accessibility across 12 mouse models, including knockouts of all STAT transcription factors and of the TYK2 kinase. Baseline JAK-STAT signaling was detected in CD8+ T cells and macrophages of unperturbed mice-but abrogated in the knockouts and in unstimulated immune cells deprived of their normal tissue context. We observed diverse gene-regulatory programs, including effects of STAT2 and IRF9 that were independent of STAT1. In summary, our large-scale dataset and integrative analysis of JAK-STAT mutant and wild-type mice uncovered a crucial role of JAK-STAT signaling in unstimulated immune cells, where it contributes to a poised epigenetic and transcriptional state and helps prepare these cells for rapid response to immune stimuli.

Keeping pace: the primary cilium as the conducting baton of the islet

Primary cilia are rod-like sensory organelles that protrude from the surface of most mammalian cells, including the cells of the islet, and mounting evidence supports important roles of these structures in the regulation of beta cell function and insulin secretion. The sensory abilities of the cilium arise from local receptor activation that is coupled to intrinsic signal transduction, and ciliary signals can propagate into the cell and influence cell function. Here, we review recent advances and studies that provide insights into intra-islet cues that trigger primary cilia signalling; how second messenger signals are generated and propagated within cilia; and how ciliary signalling affects beta cell function. We also discuss the potential involvement of primary cilia and ciliary signalling in the development and progression of type 2 diabetes, identify gaps in our current understanding of islet cell cilia function and provide suggestions on how to further our understanding of this intriguing structure.

The effect of data transformation on low-dimensional integration of single-cell RNA-seq

BACKGROUND

Recent developments in single-cell RNA sequencing have opened up a multitude of possibilities to study tissues at the level of cellular populations. However, the heterogeneity in single-cell sequencing data necessitates appropriate procedures to adjust for technological limitations and various sources of noise when integrating datasets from different studies. While many analysis procedures employ various preprocessing steps, they often overlook the importance of selecting and optimizing the employed data transformation methods.

RESULTS

This work investigates data transformation approaches used in single-cell clustering analysis tools and their effects on batch integration analysis. In particular, we compare 16 transformations and their impact on the low-dimensional representations, aiming to reduce the batch effect and integrate multiple single-cell sequencing data. Our results show that data transformations strongly influence the results of single-cell clustering on low-dimensional data space, such as those generated by UMAP or PCA. Moreover, these changes in low-dimensional space significantly affect trajectory analysis using multiple datasets, as well. However, the performance of the data transformations greatly varies across datasets, and the optimal method was different for each dataset. Additionally, we explored how data transformation impacts the analysis of deep feature encodings using deep neural network-based models, including autoencoder-based models and proto-typical networks. Data transformation also strongly affects the outcome of deep neural network models.

CONCLUSIONS

Our findings suggest that the batch effect and noise in integrative analysis are highly influenced by data transformation. Low-dimensional features can integrate different batches well when proper data transformation is applied. Furthermore, we found that the batch mixing score on low-dimensional space can guide the selection of the optimal data transformation. In conclusion, data preprocessing is one of the most crucial analysis steps and needs to be cautiously considered in the integrative analysis of multiple scRNA-seq datasets.

Conservation of a Chromosome 8 Inversion and Exon Mutations Confirm Common Gulonolactone Oxidase Gene Evolution Among Primates, Including H. Neanderthalensis

Ascorbic acid functions as an antioxidant and facilitates other biochemical processes such as collagen triple helix formation, and iron uptake by cells. Animals which endogenously produce ascorbic acid have a functional gulonolactone oxidase gene (GULO); however, humans have a GULO pseudogene (GULOP) and depend on dietary ascorbic acid. In this study, the conservation of GULOP sequences in the primate haplorhini suborder were investigated and compared to the GULO sequences belonging to the primates strepsirrhini suborder. Phylogenetic analysis suggested that the conserved GULOP exons in the haplorhini primates experienced a high rate of mutations following the haplorhini/strepsirrhini divergence. This high mutation rate has decreased during the evolution of the haplorhini primates. Additionally, indels of the haplorhini GULOP sequences were conserved across the suborder. A separate analysis for GULO sequences and well-conserved GULOP sequences focusing on placental mammals identified an in-frame GULO sequence in the Brazilian guinea pig, and a potential GULOP sequence in the pika. Similar to haplorhini primates, the guinea pig and lagomorph species have experienced a high substitution rate when compared to the mammals used in this study. A shared synteny to examine the conservation of local genes near GULO/GULOP identified a conserved inversion around the GULO/GULOP locus between the haplorhini and strepsirrhini primates. Fischer's exact test did not support an association between GULOP and the chromosomal inversion. Mauve alignment showed that the inversion of the length of the syntenic block that the GULO/GULOP genes belonged to was variable. However, there were frequent rearrangements around ~ 2 million base pairs adjacent to GULOP involving the KIF13B and MSRA genes. These data may suggest that genes acquiring deleterious mutations in the coding sequence may respond to these deleterious mutations with rapid substitution rates.

scLENS: data-driven signal detection for unbiased scRNA-seq data analysis

High dimensionality and noise have limited the new biological insights that can be discovered in scRNA-seq data. While dimensionality reduction tools have been developed to extract biological signals from the data, they often require manual determination of signal dimension, introducing user bias. Furthermore, a common data preprocessing method, log normalization, can unintentionally distort signals in the data. Here, we develop scLENS, a dimensionality reduction tool that circumvents the long-standing issues of signal distortion and manual input. Specifically, we identify the primary cause of signal distortion during log normalization and effectively address it by uniformizing cell vector lengths with L2 normalization. Furthermore, we utilize random matrix theory-based noise filtering and a signal robustness test to enable data-driven determination of the threshold for signal dimensions. Our method outperforms 11 widely used dimensionality reduction tools and performs particularly well for challenging scRNA-seq datasets with high sparsity and variability. To facilitate the use of scLENS, we provide a user-friendly package that automates accurate signal detection of scRNA-seq data without manual time-consuming tuning.

Mis-expression of GATA6 re-programs cell fate during early hematopoiesis

The traditional view of hematopoiesis is that myeloid cells derive from a common myeloid progenitor (CMP), whereas all lymphoid cell populations, including B, T, and natural killer (NK) cells and possibly plasmacytoid dendritic cells (pDCs), arise from a common lymphoid progenitor (CLP). In Max41 transgenic mice, nearly all B cells seem to be diverted into the granulocyte lineage. Here, we show that these mice have an excess of myeloid progenitors, but their CLP compartment is ablated, and they have few pDCs. Nevertheless, T cell and NK cell development proceeds relatively normally. These hematopoietic abnormalities result from aberrant expression of Gata6 due to serendipitous insertion of the transgene enhancer (Eμ) in its proximity. Gata6 mis-expression in Max41 transgenic progenitors promoted the gene-regulatory networks that drive myelopoiesis through increasing expression of key transcription factors, including PU.1 and C/EBPa. Thus, mis-expression of a single key regulator like GATA6 can dramatically re-program multiple aspects of hematopoiesis.

Generation of Slco1a4-CreERT2-tdTomato Knock-in Mice for Specific Cerebrovascular Endothelial Cell Targeting

The cerebrovascular endothelial cells with distinct characteristics line cerebrovascular blood vessels and are the fundamental structure of the blood-brain barrier, which is important for the development and homeostatic maintenance of the central nervous system. Cre-LoxP system-based spatial gene manipulation in mice is critical for investigating the physiological functions of key factors or signaling pathways in cerebrovascular endothelial cells. However, there is a lack of Cre recombinase mouse lines that specifically target cerebrovascular endothelial cells. Here, using a publicly available single-cell RNAseq database, we screened the solute carrier organic anion transporter family member 1a4 (Slco1a4) as a candidate marker of cerebrovascular endothelial cells. Then, we generated an inducible Cre mouse line in which a CreERT2-T2A-tdTomato cassette was placed after the initiation codon ATG of the Slco1a4 locus. We found that tdTomato, which can indicate the endogenous Slco1a4 expression, was expressed in almost all cerebrovascular endothelial cells but not in any other non-endothelial cell types in the brain, including neurons, astrocytes, oligodendrocytes, pericytes, smooth muscle cells, and microglial cells, as well as in other organs. Consistently, when crossing the ROSA26LSL-EYFP Cre reporter mouse, EYFP also specifically labeled almost all cerebrovascular endothelial cells upon tamoxifen induction. Overall, we generated a new inducible Cre line that specifically targets cerebrovascular endothelial cells.

Single-cell multiomics guided mechanistic understanding of Fontan-associated liver disease

The Fontan operation is the current standard of care for single-ventricle congenital heart disease. Individuals with a Fontan circulation (FC) exhibit central venous hypertension and face life-threatening complications of hepatic fibrosis, known as Fontan-associated liver disease (FALD). The fundamental biology and mechanisms of FALD are little understood. Here, we generated a transcriptomic and epigenomic atlas of human FALD at single-cell resolution using multiomic snRNA-ATAC-seq. We found profound cell type-specific transcriptomic and epigenomic changes in FC livers. Central hepatocytes (cHep) exhibited the most substantial changes, featuring profound metabolic reprogramming. These cHep changes preceded substantial activation of hepatic stellate cells and liver fibrosis, suggesting cHep as a potential first "responder" in the pathogenesis of FALD. We also identified a network of ligand-receptor pairs that transmit signals from cHep to hepatic stellate cells, which may promote their activation and liver fibrosis. We further experimentally demonstrated that activins A and B promote fibrotic activation in vitro and identified mechanisms of activin A's transcriptional activation in FALD. Together, our single-cell transcriptomic and epigenomic atlas revealed mechanistic insights into the pathogenesis of FALD and may aid identification of potential therapeutic targets.

Patterns of Unwanted Biological and Technical Expression Variation Among 49 Human Tissues

Tissue gene expression studies are impacted by biological and technical sources of variation, which can be broadly classified into wanted and unwanted variation. The latter, if not addressed, results in misleading biological conclusions. Methods have been proposed to reduce unwanted variation, such as normalization and batch correction. A more accurate understanding of all causes of variation could significantly improve the ability of these methods to remove unwanted variation while retaining variation corresponding to the biological question of interest. We used 17,282 samples from 49 human tissues in the Genotype-Tissue Expression data set (v8) to investigate patterns and causes of expression variation. Transcript expression was transformed to z-scores, and only the most variable 2% of transcripts were evaluated and clustered based on coexpression patterns. Clustered gene sets were assigned to different biological or technical causes based on histologic appearances and metadata elements. We identified 522 variable transcript clusters (median: 11 per tissue) among the samples. Of these, 63% were confidently explained, 16% were likely explained, 7% were low confidence explanations, and 14% had no clear cause. Histologic analysis annotated 46 clusters. Other common causes of variability included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), disease status, and age. Technical causes included blood draw timing and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens data set of single-cell expression. This is among the largest explorations of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression and demonstrated the utility of matched histologic specimens. It further demonstrated the value of acquiring meaningful tissue harvesting metadata elements to use for improved normalization, batch correction, and analysis of both bulk and single-cell RNA-seq data.

How Mycobacterium tuberculosis builds a home: Single-cell analysis reveals M. tuberculosis ESX-1-mediated accumulation of anti-inflammatory macrophages in infected mouse lungs

Mycobacterium tuberculosis (MTB) infects and replicates in lung mononuclear phagocytes (MNPs) with astounding ability to evade elimination. ESX-1, a type VII secretion system, acts as a virulence determinant that contributes to MTB's ability to survive within MNPs, but its effect on MNP recruitment and/or differentiation remains unknown. Here, using single-cell RNA sequencing, we studied the role of ESX-1 in MNP heterogeneity and response in mice and murine bone marrow-derived macrophages (BMDM). We found that ESX-1 is required for MTB to recruit diverse MNP subsets with high MTB burden. Further, MTB induces an anti-inflammatory signature in MNPs and BMDM in an ESX-1 dependent manner. Similarly, spatial transcriptomics revealed an upregulation of anti-inflammatory signals in MTB lesions, where monocyte-derived macrophages concentrate near MTB-infected cells. Together, our findings suggest that MTB ESX-1 mediates the recruitment and differentiation of anti-inflammatory MNPs, which MTB can infect and manipulate for survival.

Brief guide to RNA sequencing analysis for nonexperts in bioinformatics

Transcriptome analysis is widely used for current biological research but remains challenging for many experimental scientists. Here, we present a brief but broad guideline for transcriptome analysis, focusing on RNA sequencing, by providing the list of publicly available datasets, tools, and R packages for practical transcriptome analysis. This work will be useful for biologists to perform key transcriptomic analysis with minimum expertise in bioinformatics.

The host transcriptional response to superinfection by influenza A virus and Streptococcus pneumoniae

Secondary bacterial challenges during influenza virus infection "superinfection") cause excessive mortality and hospitalization. Here, we present a longitudinal study of bulk gene expression changes in murine lungs during superinfection, with an initial influenza A virus infection and a subsequent Streptococcus pneumoniae infection. In addition to the well-characterized impairment of the host response, we identified superinfection-specific alterations in the global transcriptional program that are linked to the host's ability to resist the pathogens. Particularly, whereas superinfected mice manifested an excessive rapid induction of the resistance-to-infection program, there was a substantial tissue-level rewiring of this program: upon superinfection, interferon-regulated genes were switched from positive to negative correlations with the host's resistance state, whereas genes of fatty acid metabolism switched from negative to positive correlations with resistance states. Thus, the transcriptional resistance state in superinfection is reprogrammed toward repressed interferon signaling and induced fatty acid metabolism. Our findings suggest new insights into a tissue-level remodeling of the host defense upon superinfection, providing promising targets for future therapeutic interventions.

IMPORTANCE

Secondary bacterial infections are the most frequent complications during influenza A virus (IAV) pandemic outbreaks, contributing to excessive morbidity and mortality in the human population. Most IAV-related deaths are attributed to Streptococcus pneumoniae (SP) infections, which usually begin within the first week of IAV infection in the respiratory tracts. Here, we focused on longitudinal transcriptional responses during a superinfection model consisting of an SP infection that follows an initial IAV infection, comparing superinfection to an IAV-only infection, an SP-only infection, and control treatments. Our longitudinal data allowed a fine analysis of gene expression changes during superinfection. For instance, we found that superinfected mice exhibited rapid gene expression induction or reduction within the first 12 h after encountering the second pathogen. Cell proliferation and immune response activation processes were upregulated, while endothelial processes, vasculogenesis, and angiogenesis were downregulated, providing promising targets for future therapeutic interventions. We further analyzed the longitudinal transcriptional responses in the context of a previously defined spectrum of the host's resistance state, revealing superinfection-specific reprogramming of resistance states, such as reprogramming of fatty acid metabolism and interferon signaling. The reprogrammed functions are compelling new targets for switching the pathogenic superinfection state into a single-infection state.

CD4-mediated immunity shapes neutrophil-driven tuberculous pathology

Pulmonary Mycobacterium tuberculosis (Mtb) infection results in highly heterogeneous lesions ranging from granulomas with central necrosis to those primarily comprised of alveolitis. While alveolitis has been associated with prior immunity in human post-mortem studies, the drivers of these distinct pathologic outcomes are poorly understood. Here, we show that these divergent lesion structures can be modeled in C3HeB/FeJ mice and are regulated by prior immunity. Using quantitative imaging, scRNAseq, and flow cytometry, we demonstrate that Mtb infection in the absence of prior immunity elicits dysregulated neutrophil recruitment and necrotic granulomas. In contrast, prior immunity induces rapid recruitment and activation of T cells, local macrophage activation, and diminished late neutrophil responses. Depletion studies at distinct infection stages demonstrated that neutrophils are required for early necrosis initiation and necrosis propagation at chronic stages, whereas early CD4 T cell responses prevent neutrophil feedforward circuits and necrosis. Together, these studies reveal fundamental determinants of tuberculosis lesion structure and pathogenesis, which have important implications for new strategies to prevent or treat tuberculosis.

Zmiz1 is a novel regulator of brain development associated with autism and intellectual disability

Neurodevelopmental disorders (NDDs) are a class of pathologies arising from perturbations in brain circuit formation and maturation with complex etiological triggers often classified as environmental and genetic. Neuropsychiatric conditions such as autism spectrum disorders (ASD), intellectual disability (ID), and attention deficit hyperactivity disorders (ADHD) are common NDDs characterized by their hereditary underpinnings and inherent heterogeneity. Genetic risk factors for NDDs are increasingly being identified in non-coding regions and proteins bound to them, including transcriptional regulators and chromatin remodelers. Importantly, de novo mutations are emerging as important contributors to NDDs and neuropsychiatric disorders. Recently, de novo mutations in transcriptional co-factor Zmiz1 or its regulatory regions have been identified in unrelated patients with syndromic ID and ASD. However, the role of Zmiz1 in brain development is unknown. Here, using publicly available databases and a Zmiz1 mutant mouse model, we reveal that Zmiz1 is highly expressed during embryonic brain development in mice and humans, and though broadly expressed across the brain, Zmiz1 is enriched in areas prominently impacted in ID and ASD such as cortex, hippocampus, and cerebellum. We investigated the relationship between Zmiz1 structure and pathogenicity of protein variants, the epigenetic marks associated with Zmiz1 regulation, and protein interactions and signaling pathways regulated by Zmiz1. Our analysis reveals that Zmiz1 regulates multiple developmental processes, including neurogenesis, neuron connectivity, and synaptic signaling. This work paves the way for future studies on the functions of Zmiz1 and highlights the importance of combining analysis of mouse models and human data.

Genetic variation is a key determinant of chromatin accessibility and drives differences in the regulatory landscape of C57BL/6J and 129S1/SvImJ mice

Most common genetic variants associated with disease are located in non-coding regions of the genome. One mechanism by which they function is through altering transcription factor (TF) binding. In this study, we explore how genetic variation is connected to differences in the regulatory landscape of livers from C57BL/6J and 129S1/SvImJ mice fed either chow or a high-fat diet. To identify sites where regulatory variation affects TF binding and nearby gene expression, we employed an integrative analysis of H3K27ac ChIP-seq (active enhancers), ATAC-seq (chromatin accessibility) and RNA-seq (gene expression). We show that, across all these assays, the genetically driven (i.e. strain-specific) differences in the regulatory landscape are more pronounced than those modified by diet. Most notably, our analysis revealed that differentially accessible regions (DARs, N = 29635, FDR < 0.01 and fold change > 50%) are almost always strain-specific and enriched with genetic variation. Moreover, proximal DARs are highly correlated with differentially expressed genes. We also show that TF binding is affected by genetic variation, which we validate experimentally using ChIP-seq for TCF7L2 and CTCF. This study provides detailed insights into how non-coding genetic variation alters the gene regulatory landscape, and demonstrates how this can be used to study the regulatory variation influencing TF binding.

A single cell atlas of the mouse seminal vesicle

During mammalian reproduction, sperm are delivered to the female reproductive tract bathed in a complex medium known as seminal fluid, which plays key roles in signaling to the female reproductive tract and in nourishing sperm for their onwards journey. Along with minor contributions from the prostate and the epididymis, the majority of seminal fluid is produced by a somewhat understudied organ known as the seminal vesicle. Here, we report the first single-cell RNA-seq atlas of the mouse seminal vesicle, generated using tissues obtained from 23 mice of varying ages, exposed to a range of dietary challenges. We define the transcriptome of the secretory cells in this tissue, identifying a relatively homogeneous population of the epithelial cells which are responsible for producing the majority of seminal fluid. We also define the immune cell populations - including large populations of macrophages, dendritic cells, T cells, and NKT cells - which have the potential to play roles in producing various immune mediators present in seminal plasma. Together, our data provide a resource for understanding the composition of an understudied reproductive tissue with potential implications for paternal control of offspring development and metabolism.

Single-cell transcriptomics dissecting the development and evolution of nervous system in insects

Insects can display a vast repertoire of complex and adaptive behaviors crucial for survival and reproduction. Yet, how the neural circuits underlying insect behaviors are assembled throughout development and remodeled during evolution remains largely obscure. The advent of single-cell transcriptomics has opened new paths to illuminate these historically intractable questions. Insect behavior is governed by its brain, whose functional complexity is realized through operations across multiple levels, from the molecular and cellular to the circuit and organ. Single-cell transcriptomics enables dissecting brain functions across all these levels and allows tracking regulatory dynamics throughout development and under perturbation. In this review, we mainly focus on the achievements of single-cell transcriptomics in dissecting the molecular and cellular architectures of nervous systems in representative insects, then discuss its applications in tracking the developmental trajectory and functional evolution of insect brains.

Nonlinear DNA methylation trajectories in aging male mice

Although DNA methylation data yields highly accurate age predictors, little is known about the dynamics of this quintessential epigenomic biomarker during lifespan. To narrow the gap, we investigate the methylation trajectories of male mouse colon at five different time points of aging. Our study indicates the existence of sudden hypermethylation events at specific stages of life. Precisely, we identify two epigenomic switches during early-to-midlife (3-9 months) and mid-to-late-life (15-24 months) transitions, separating the rodents' life into three stages. These nonlinear methylation dynamics predominantly affect genes associated with the nervous system and enrich in bivalently marked chromatin regions. Based on groups of nonlinearly modified loci, we construct a clock-like classifier STageR (STage of aging estimatoR) that accurately predicts murine epigenetic stage. We demonstrate the universality of our clock in an independent mouse cohort and with publicly available datasets.

A Multimodal Omics Framework to Empower Target Discovery for Cardiovascular Regeneration

Ischaemic heart disease is a global healthcare challenge with high morbidity and mortality. Early revascularisation in acute myocardial infarction has improved survival; however, limited regenerative capacity and microvascular dysfunction often lead to impaired function and the development of heart failure. New mechanistic insights are required to identify robust targets for the development of novel strategies to promote regeneration. Single-cell RNA sequencing (scRNA-seq) has enabled profiling and analysis of the transcriptomes of individual cells at high resolution. Applications of scRNA-seq have generated single-cell atlases for multiple species, revealed distinct cellular compositions for different regions of the heart, and defined multiple mechanisms involved in myocardial injury-induced regeneration. In this review, we summarise findings from studies of healthy and injured hearts in multiple species and spanning different developmental stages. Based on this transformative technology, we propose a multi-species, multi-omics, meta-analysis framework to drive the discovery of new targets to promote cardiovascular regeneration.

Distribution-Agnostic Deep Learning Enables Accurate Single-Cell Data Recovery and Transcriptional Regulation Interpretation

Single-cell RNA sequencing (scRNA-seq) is a robust method for studying gene expression at the single-cell level, but accurately quantifying genetic material is often hindered by limited mRNA capture, resulting in many missing expression values. Existing imputation methods rely on strict data assumptions, limiting their broader application, and lack reliable supervision, leading to biased signal recovery. To address these challenges, authors developed Bis, a distribution-agnostic deep learning model for accurately recovering missing sing-cell gene expression from multiple platforms. Bis is an optimal transport-based autoencoder model that can capture the intricate distribution of scRNA-seq data while addressing the characteristic sparsity by regularizing the cellular embedding space. Additionally, they propose a module using bulk RNA-seq data to guide reconstruction and ensure expression consistency. Experimental results show Bis outperforms other models across simulated and real datasets, showcasing superiority in various downstream analyses including batch effect removal, clustering, differential expression analysis, and trajectory inference. Moreover, Bis successfully restores gene expression levels in rare cell subsets in a tumor-matched peripheral blood dataset, revealing developmental characteristics of cytokine-induced natural killer cells within a head and neck squamous cell carcinoma microenvironment.

Spontaneous expression of the CIC::DUX4 fusion oncoprotein from a conditional allele potently drives sarcoma formation in genetically engineered mice

CIC::DUX4 sarcoma (CDS) is a rare but highly aggressive undifferentiated small round cell sarcoma driven by a fusion between the tumor suppressor Capicua (CIC) and DUX4. Currently, there are no effective treatments and efforts to identify and translate better therapies are limited by the scarcity of patient tumor samples and cell lines. To address this limitation, we generated three genetically engineered mouse models of CDS (Ch7CDS, Ai9CDS, and TOPCDS). Remarkably, chimeric mice from all three conditional models developed spontaneous soft tissue tumors and disseminated disease in the absence of Cre-recombinase. The penetrance of spontaneous (Cre-independent) tumor formation was complete irrespective of bi-allelic Cic function and the distance between adjacent loxP sites. Characterization of soft tissue and presumed metastatic tumors showed that they consistently expressed the CIC::DUX4 fusion protein and many downstream markers of the disease credentialing the models as CDS. In addition, tumor-derived cell lines were generated and ChIP-seq was preformed to map fusion-gene specific binding using an N-terminal HA epitope tag. These datasets, along with paired H3K27ac ChIP-sequencing maps, validate CIC::DUX4 as a neomorphic transcriptional activator. Moreover, they are consistent with a model where ETS family transcription factors are cooperative and redundant drivers of the core regulatory circuitry in CDS.

Depleting myeloid-biased haematopoietic stem cells rejuvenates aged immunity

Ageing of the immune system is characterized by decreased lymphopoiesis and adaptive immunity, and increased inflammation and myeloid pathologies1,2. Age-related changes in populations of self-renewing haematopoietic stem cells (HSCs) are thought to underlie these phenomena3. During youth, HSCs with balanced output of lymphoid and myeloid cells (bal-HSCs) predominate over HSCs with myeloid-biased output (my-HSCs), thereby promoting the lymphopoiesis required for initiating adaptive immune responses, while limiting the production of myeloid cells, which can be pro-inflammatory4. Ageing is associated with increased proportions of my-HSCs, resulting in decreased lymphopoiesis and increased myelopoiesis3,5,6. Transfer of bal-HSCs results in abundant lymphoid and myeloid cells, a stable phenotype that is retained after secondary transfer; my-HSCs also retain their patterns of production after secondary transfer5. The origin and potential interconversion of these two subsets is still unclear. If they are separate subsets postnatally, it might be possible to reverse the ageing phenotype by eliminating my-HSCs in aged mice. Here we demonstrate that antibody-mediated depletion of my-HSCs in aged mice restores characteristic features of a more youthful immune system, including increasing common lymphocyte progenitors, naive T cells and B cells, while decreasing age-related markers of immune decline. Depletion of my-HSCs in aged mice improves primary and secondary adaptive immune responses to viral infection. These findings may have relevance to the understanding and intervention of diseases exacerbated or caused by dominance of the haematopoietic system by my-HSCs.