Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression

Analysis of Haemonchus embryos at single cell resolution identifies two eukaryotic elongation factors as intervention target candidates

Advances in single cell technologies are allowing investigations of a wide range of biological processes and pathways in animals, such as the multicellular model organism Caenorhabditis elegans - a free-living nematode. However, there has been limited application of such technology to related parasitic nematodes which cause major diseases of humans and animals worldwide. With no vaccines against the vast majority of parasitic nematodes and treatment failures due to drug resistance or inefficacy, new intervention targets are urgently needed, preferably informed by a deep understanding of these nematodes' cellular and molecular biology - which is presently lacking for most worms. Here, we created the first single cell atlas for an early developmental stage of Haemonchus contortus - a highly pathogenic, C. elegans-related parasitic nematode. We obtained and curated RNA sequence (snRNA-seq) data from single nuclei from embryonating eggs of H. contortus (150,000 droplets), and selected high-quality transcriptomic data for > 14,000 single nuclei for analysis, and identified 19 distinct clusters of cells. Guided by comparative analyses with C. elegans, we were able to reproducibly assign seven cell clusters to body wall muscle, hypodermis, neuronal, intestinal or seam cells, and identified eight genes that were transcribed in all cell clusters/types, three of which were inferred to be essential in H. contortus. Two of these genes (i.e. Hc-eef-1A and Hc-eef1G), coding for eukaryotic elongation factors (called Hc-eEF1A and Hc-eEF1G), were also demonstrated to be transcribed and expressed in all key developmental stages of H. contortus. Together with these findings, sequence- and structure-based comparative analyses indicated the potential of Hc-eEF1A and/or Hc-eEF1G as intervention targets within the protein biosynthesis machinery of H. contortus. Future work will focus on single cell studies of all key developmental stages and tissues of H. contortus, and on evaluating the suitability of the two elongation factor proteins as drug targets in H. contortus and related nematodes, with a view to finding new nematocidal drug candidates.

Single-cell 5' RNA sequencing of camelid peripheral B cells provides insights into cellular basis of heavy-chain antibody production

Camelids produce both conventional tetrameric antibodies (Abs) and dimeric heavy-chain antibodies (HCAbs). Although B cells that generate these two types of Abs exhibit distinct B cell receptors (BCRs), whether these two B cell populations differ in their phenotypes and developmental processes remains unclear. Here, we performed single-cell 5' RNA profiling of peripheral blood mononuclear cell samples from Bactrian camels before and after immunization. We characterized the functional subtypes and differentiation trajectories of circulating B cells in camels, and reconstructed single-cell BCR sequences. We found that in contrast to humans, the proportion of T-bet+ B cells was high among camelid peripheral B cells. Several marker genes of human B cell subtypes, including CD27 and IGHD, were expressed at low levels in the corresponding camel B cell subtypes. Camelid B cells expressing variable genes of HACbs (VHH) were widely present in various functional subtypes and showed highly overlapping differentiation trajectories with B cells expressing variable genes of conventional Abs (VH). After immunization, the transcriptional changes in VHH+ and VH+ B cells were largely consistent. Through structure modeling, we identified a variety of scaffold types among the reconstructed VHH sequences. Our study provides insights into the cellular context of HCAb production in camels and lays the foundation for developing single-B cell-based camelid single-domain Ab screening.

High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment

Single-cell analyses can be confounded by assigning unrelated groups of cells to common developmental trajectories. For instance, cancer cells and admixed normal epithelial cells could adopt similar cell states thus complicating analyses of their developmental potential. Here, we develop and benchmark CCISM (for Cancer Cell Identification using Somatic Mutations) to exploit genomic single nucleotide variants for the disambiguation of cancer cells from genomically normal non-cancer cells in single-cell data. We find that our method and others based on gene expression or allelic imbalances identify overlapping sets of colorectal cancer versus normal colon epithelial cells, depending on molecular characteristics of individual cancers. Further, we define consensus cell identities of normal and cancer epithelial cells with higher transcriptome cluster homogeneity than those derived using existing tools. Using the consensus identities, we identify significant shifts of cell state distributions in genomically normal epithelial cells developing in the cancer microenvironment, with immature states increased at the expense of terminal differentiation throughout the colon, and a novel stem-like cell state arising in the left colon. Trajectory analyses show that the new cell state extends the pseudo-time range of normal colon stem-like cells in a cancer context. We identify cancer-associated fibroblasts as sources of WNT and BMP ligands potentially contributing to increased plasticity of stem cells in the cancer microenvironment. Our analyses advocate careful interpretation of cell heterogeneity and plasticity in the cancer context and the consideration of genomic information in addition to gene expression data when possible.

Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

BACKGROUND

The encoding of cell intrinsic drug resistance states in breast cancer reflects the contributions of genomic and non-genomic variations and requires accurate estimation of clonal fitness from co-measurement of transcriptomic and genomic data. Somatic copy number (CN) variation is the dominant mutational mechanism leading to transcriptional variation and notably contributes to platinum chemotherapy resistance cell states. Here, we deploy time series measurements of triple negative breast cancer (TNBC) single-cell transcriptomes, along with co-measured single-cell CN fitness, identifying genomic and transcriptomic mechanisms in drug-associated transcriptional cell states.

RESULTS

We present scRNA-seq data (53,641 filtered cells) from serial passaging TNBC patient-derived xenograft (PDX) experiments spanning 2.5 years, matched with genomic single-cell CN data from the same samples. Our findings reveal distinct clonal responses within TNBC tumors exposed to platinum. Clones with high drug fitness undergo clonal sweeps and show subtle transcriptional reversion, while those with weak fitness exhibit dynamic transcription upon drug withdrawal. Pathway analysis highlights convergence on epithelial-mesenchymal transition and cytokine signaling, associated with resistance. Furthermore, pseudotime analysis demonstrates hysteresis in transcriptional reversion, indicating generation of new intermediate transcriptional states upon platinum exposure.

CONCLUSIONS

Within a polyclonal tumor, clones with strong genotype-associated fitness under platinum remained fixed, minimizing transcriptional reversion upon drug withdrawal. Conversely, clones with weaker fitness display non-genomic transcriptional plasticity. This suggests CN-associated and CN-independent transcriptional states could both contribute to platinum resistance. The dominance of genomic or non-genomic mechanisms within polyclonal tumors has implications for drug sensitivity, restoration, and re-treatment strategies.

A group 3 medulloblastoma stem cell program is maintained by OTX2-mediated alternative splicing

OTX2 is a transcription factor and known driver in medulloblastoma (MB), where it is amplified in a subset of tumours and overexpressed in most cases of group 3 and group 4 MB. Here we demonstrate a noncanonical role for OTX2 in group 3 MB alternative splicing. OTX2 associates with the large assembly of splicing regulators complex through protein-protein interactions and regulates a stem cell splicing program. OTX2 can directly or indirectly bind RNA and this may be partially independent of its DNA regulatory functions. OTX2 controls a pro-tumorigenic splicing program that is mirrored in human cerebellar rhombic lip origins. Among the OTX2-regulated differentially spliced genes, PPHLN1 is expressed in the most primitive rhombic lip stem cells, and targeting PPHLN1 splicing reduces tumour growth and enhances survival in vivo. These findings identify OTX2-mediated alternative splicing as a major determinant of cell fate decisions that drive group 3 MB progression.

Bipotential B-neutrophil progenitors are present in human and mouse bone marrow and emerge in the periphery upon stress hematopoiesis

Hematopoiesis is a tightly regulated process that gets skewed toward myelopoiesis. This restrains lymphopoiesis, but the role of lymphocytes in this process is not well defined. To unravel the intricacies of neutrophil responses in COVID-19, we performed bulk RNAseq on neutrophils from healthy controls and COVID-19 patients. Principal component analysis revealed distinguishing neutrophil gene expression alterations in COVID-19 patients. ICU and ward patients displayed substantial transcriptional changes, with ICU patients exhibiting a more pronounced response. Intriguingly, neutrophils from COVID-19 patients, notably ICU patients, exhibited an enrichment of immunoglobulin (Ig) and B cell lineage-associated genes, suggesting potential lineage plasticity. We validated our RNAseq findings in a larger cohort. Moreover, by reanalyzing single-cell RNA sequencing (scRNAseq) data on human bone marrow (BM) granulocytes, we identified the cluster of granulocyte-monocyte progenitors (GMP) enriched with Ig and B cell lineage-associated genes. These cells with lineage plasticity may serve as a resource depending on the host's needs during severe systemic infection. This distinct B cell subset may play a pivotal role in promoting myelopoiesis in response to infection. The scRNAseq analysis of BM neutrophils in infected mice further supported our observations in humans. Finally, our studies using an animal model of acute infection implicate IL-7/GM-CSF in influencing neutrophil and B cell dynamics. Elevated GM-CSF and reduced IL-7 receptor expression in COVID-19 patients imply altered hematopoiesis favoring myeloid cells over B cells. Our findings provide novel insights into the relationship between the B-neutrophil lineages during severe infection, hinting at potential implications for disease pathogenesis.

IMPORTANCE

This study investigates the dynamics of hematopoiesis in COVID-19, focusing on neutrophil responses. Through RNA sequencing of neutrophils from healthy controls and COVID-19 patients, distinct gene expression alterations are identified, particularly in ICU patients. Notably, neutrophils from COVID-19 patients, especially in the ICU, exhibit enrichment of immunoglobulin and B cell lineage-associated genes, suggesting potential lineage plasticity. Validation in a larger patient cohort and single-cell analysis of bone marrow granulocytes support the presence of granulocyte-monocyte progenitors with B cell lineage-associated genes. The findings propose a link between B-neutrophil lineages during severe infection, implicating a potential role for these cells in altered hematopoiesis favoring myeloid cells over B cells. Elevated GM-CSF and reduced IL-7 receptor expression in stress hematopoiesis suggest cytokine involvement in these dynamics, providing novel insights into disease pathogenesis.

Integration of single-cell and bulk RNA sequencing revealed immune heterogeneity and its association with disease activity in rheumatoid arthritis patients

Rheumatoid arthritis (RA) is a chronic, inflammatory, systemic autoimmune disease characterized by cartilage, bone damage, synovial inflammation, hyperplasia, autoantibody production, and systemic features. To obtain an overall profile of the immune environment in RA patients and its association with clinical features, we performed single-cell transcriptome and T-cell receptor sequencing of mononuclear cells from peripheral blood (PBMC) and synovial fluid (SF) from RA patients, integrated with two large cohorts with bulk RNA sequencing for further validation and investigation. Dendritic cells (DCs) exhibited relatively high functional heterogeneity and tissue specificity in relation to both antigen presentation and proinflammatory functions. Peripheral helper T cells (TPHs) are likely to originate from synovial tissue, undergo activation and exhaustion, and are subsequently released into the peripheral blood. Notably, among all immune cell types, TPHs were found to have the most intense associations with disease activity. In addition, CD8 effector T cells could be clustered into two groups with different cytokine expressions and play distinct roles in RA development. By integrating single-cell data with bulk sequencing from two large cohorts, we identified interactions among TPHs, CD8 cells, CD16 monocytes, and DCs that strongly contribute to the proinflammatory local environment in RA joints. Of note, the swollen 28-joint counts exhibited a more pronounced association with this immune environment compared to other disease activity indexes. The immune environment alternated significantly from PBMCs to SF, which indicated that a series of immune cells was involved in proinflammatory responses in the local joints of RA patients. By integrating single-cell data with two large cohorts, we have uncovered associations between specific immune cell populations and clinical features. This integration provides a rapid and precise methodology for assessing local immune activation, offering valuable insights into the pathophysiological mechanisms at play in RA.

Metabolic imaging across scales reveals distinct prostate cancer phenotypes

Hyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer.

A spatiotemporal molecular atlas of mouse spinal cord injury identifies a distinct astrocyte subpopulation and therapeutic potential of IGFBP2

Spinal cord injury (SCI) triggers a cascade of intricate molecular and cellular changes that determine the outcome. In this study, we resolve the spatiotemporal organization of the injured mouse spinal cord and quantitatively assess in situ cell-cell communication following SCI. By analyzing existing single-cell RNA sequencing datasets alongside our spatial data, we delineate a subpopulation of Igfbp2-expressing astrocytes that migrate from the white matter (WM) to gray matter (GM) and become reactive upon SCI, termed Astro-GMii. Further, Igfbp2 upregulation promotes astrocyte migration, proliferation, and reactivity, and the secreted IGFBP2 protein fosters neurite outgrowth. Finally, we show that IGFBP2 significantly reduces neuronal loss and remarkably improves the functional recovery in a mouse model of SCI in vivo. Together, this study not only provides a comprehensive molecular atlas of SCI but also exemplifies how this rich resource can be applied to endow cells and genes with functional insight and therapeutic potential.

A multiomic atlas of the aging hippocampus reveals molecular changes in response to environmental enrichment

Aging involves the deterioration of organismal function, leading to the emergence of multiple pathologies. Environmental stimuli, including lifestyle, can influence the trajectory of this process and may be used as tools in the pursuit of healthy aging. To evaluate the role of epigenetic mechanisms in this context, we have generated bulk tissue and single cell multi-omic maps of the male mouse dorsal hippocampus in young and old animals exposed to environmental stimulation in the form of enriched environments. We present a molecular atlas of the aging process, highlighting two distinct axes, related to inflammation and to the dysregulation of mRNA metabolism, at the functional RNA and protein level. Additionally, we report the alteration of heterochromatin domains, including the loss of bivalent chromatin and the uncovering of a heterochromatin-switch phenomenon whereby constitutive heterochromatin loss is partially mitigated through gains in facultative heterochromatin. Notably, we observed the multi-omic reversal of a great number of aging-associated alterations in the context of environmental enrichment, which was particularly linked to glial and oligodendrocyte pathways. In conclusion, our work describes the epigenomic landscape of environmental stimulation in the context of aging and reveals how lifestyle intervention can lead to the multi-layered reversal of aging-associated decline.

Specification and survival of post-metamorphic branchiomeric neurons in a non-vertebrate chordate

Tunicates are the sister group to the vertebrates, yet most species have a life cycle split between swimming larva and sedentary adult phases. During metamorphosis, larval neurons are replaced by adult-specific ones. The regulatory mechanisms underlying this replacement remain largely unknown. Using tissue-specific CRISPR/Cas9-mediated mutagenesis in the tunicate Ciona, we show that orthologs of conserved hindbrain and branchiomeric neuron regulatory factors Pax2/5/8 and Phox2 are required to specify the 'neck', a cellular compartment set aside in the larva to give rise to cranial motor neuron-like neurons post-metamorphosis. Using bulk and single-cell RNA-sequencing analyses, we characterize the transcriptome of the neck downstream of Pax2/5/8. We present evidence that neck-derived adult ciliomotor neurons begin to differentiate in the larva and persist through metamorphosis, contrary to the assumption that the adult nervous system is formed after settlement and the death of larval neurons during metamorphosis. Finally, we show that FGF signaling during the larval phase alters the patterning of the neck and its derivatives. Suppression of FGF converts neck cells into larval neurons that fail to survive metamorphosis, whereas prolonged FGF signaling promotes an adult neural stem cell-like fate.

Single-cell RNA-sequencing identifies unique cell-specific gene expression profiles in high-grade cardiac allograft vasculopathy

Background

Cardiac allograft vasculopathy (CAV), a diffuse thickening of the intima of the coronary arteries and microvasculature, is the leading cause of late graft failure and mortality after heart transplantation (HT). Diagnosis involves invasive coronary angiography, which carries substantial risk, and minimally-invasive approaches to CAV diagnosis are urgently needed. Using single-cell RNA-sequencing in peripheral blood mononuclear cells (PBMCs), we sought to identify cell-specific gene expression profiles in CAV.

Methods

Whole blood was collected from 22 HT recipients with angiographically-confirmed CAV and 18 HT recipients without CAV. PBMCs were isolated and subjected to single-cell RNA-sequencing using a 10X Genomics microfluidic platform. Downstream analyses focused on differential expression of genes, cell compositional changes, and T cell receptor repertoire analyses.

Results

Across 40 PBMC samples, we isolated 134,984 cells spanning 8 major clusters and 31 subclusters of cell types. Compositional analyses showed subtle, but significant increases in CD4+ T central memory cells, and CD14+ and CD16+ monocytes in high-grade CAV (CAV-2 and CAV-3) as compared to low-grade or absent CAV. After adjusting for age, gender, and prednisone use, 745 genes were differentially expressed in a cell-specific manner in high-grade CAV. Weighted gene co-expression network analyses showed enrichment for putative pathways involved in inflammation and angiogenesis. There were no significant differences in T cell clonality or diversity with increasing CAV severity.

Conclusions

Unbiased whole transcriptomic analyses at single-cell resolution identify unique, cell-specific gene expression patterns in CAV, suggesting the potential utility of peripheral gene expression biomarkers in diagnosing CAV.

Single Cell RNAseq Analysis of Cytokine-Treated Human Islets: Association of Cellular Stress with Impaired Cytokine Responsiveness

Pancreatic β-cells are essential for survival, being the only cell type capable of insulin secretion. While they are believed to be vulnerable to damage by inflammatory cytokines such as interleukin-1 beta (IL-1β) and interferon-gamma, we have recently identified physiological roles for cytokine signaling in rodent β-cells that include the stimulation of antiviral and antimicrobial gene expression and the inhibition of viral replication. In this study, we examine cytokine-stimulated changes in gene expression in human islets using single-cell RNA sequencing. Surprisingly, the global responses of human islets to cytokine exposure were remarkably blunted compared to our previous observations in the mouse. The small population of human islet cells that were cytokine responsive exhibited increased expression of IL-1β-stimulated antiviral guanylate-binding proteins, just like in the mouse. Most human islet cells were not responsive to cytokines, and this lack of responsiveness was associated with high expression of genes encoding ribosomal proteins. We further correlated the expression levels of RPL5 with stress response genes, and when expressed at high levels, RPL5 is predictive of failure to respond to cytokines in all endocrine cells. We postulate that donor causes of death and isolation methodologies may contribute to stress of the islet preparation. Our findings indicate that activation of stress responses in human islets limits cytokine-stimulated gene expression, and we urge caution in the evaluation of studies that have examined cytokine-stimulated gene expression in human islets without evaluation of stress-related gene expression.

Cell atlas of the regenerating human liver after portal vein embolization

The liver has the remarkable capacity to regenerate. In the clinic, regeneration is induced by portal vein embolization, which redirects portal blood flow, resulting in liver hypertrophy in locations with increased blood supply, and atrophy of embolized segments. Here, we apply single-cell and single-nucleus transcriptomics on healthy, hypertrophied, and atrophied patient-derived liver samples to explore cell states in the regenerating liver. Our data unveils pervasive upregulation of genes associated with developmental processes, cellular adhesion, and inflammation in post-portal vein embolization liver, disrupted portal-central hepatocyte zonation, and altered cell subtype composition of endothelial and immune cells. Interlineage crosstalk analysis reveals mesenchymal cells as an interaction hub between immune and endothelial cells, and highlights the importance of extracellular matrix proteins in liver regeneration. Moreover, we establish tissue-scale iterative indirect immunofluorescence imaging for high-dimensional spatial analysis of perivascular microenvironments, uncovering changes to tissue architecture in regenerating liver lobules. Altogether, our data is a rich resource revealing cellular and histological changes in human liver regeneration.

Hypoxia drives HIF2-dependent reversible macrophage cell cycle entry

Low-oxygen conditions (hypoxia) have been associated primarily with cell-cycle arrest in dividing cells. Macrophages are typically quiescent in G0 but can proliferate in response to tissue signals. Here we show that hypoxia (1% oxygen tension) results in reversible entry into the cell cycle in macrophages. Cell cycle progression is largely limited to G0-G1/S phase transition with little progression to G2/M. This cell cycle transitioning is triggered by an HIF2α-directed transcriptional program. The response is accompanied by increased expression of cell-cycle-associated proteins, including CDK1, which is known to phosphorylate SAMHD1 at T592 and thereby regulate antiviral activity. Prolyl hydroxylase (PHD) inhibitors are able to recapitulate HIF2α-dependent cell cycle entry in macrophages. Finally, tumor-associated macrophages (TAMs) in lung cancers exhibit transcriptomic profiles representing responses to low oxygen and cell cycle progression at the single-cell level. These findings have implications for inflammation and tumor progression/metastasis where low-oxygen environments are common.

Single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of single nucleus RNA sequencing (snRNA-seq) offers to revolutionize the study of Alzheimer's disease (AD). Integration with complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link cell subpopulations and molecular networks with a broader disease-relevant context. We report snRNA-seq profiles from superior frontal gyrus samples from 101 well characterized subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in hematological parameters. We observed an AD-associated CD83(+) microglial subtype with unique molecular networks and which is associated with immunoglobulin IgG4 production in the transverse colon. Our major observations were replicated in two additional, independent snRNA-seq data sets. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal disease biology.

Progenitors of distinct lineages shape the diversity of mature type 2 conventional dendritic cells

Conventional dendritic cells (cDC) are antigen-presenting cells comprising cDC1 and cDC2, responsible for priming naive CD8+ and CD4+ T cells, respectively. Recent studies have unveiled cDC2 heterogeneity and identified various cDC2 progenitors beyond the common DC progenitor (CDP), hinting at distinct cDC2 lineages. By generating Cd300ciCre-hCD2R26tdTomato reporter mice, we identified a bone marrow pro-cDC2 progenitor exclusively generating cDC2 in vitro and in vivo. Single-cell analyses and multiparametric flow cytometry demonstrated that pro-cDC2 encompasses myeloid-derived pre-cDC2 and lymphoid-derived plasmacytoid DC (pDC)-like precursors differentiating into a transcriptionally convergent cDC2 phenotype. Cd300c-traced cDC2 had distinct transcriptomic profiles, phenotypes, and tissue distributions compared with Ms4a3CreR26tdTomato lineage-traced DC3, a monocyte-DC progenitor (MDP)-derived subset that bypasses CDP. Mice with reduced Cd300c-traced cDC2 showed impaired humoral responses to T cell-dependent antigens. We conclude that progenitors of distinct lineages shape the diversity of mature cDC2 across tissues. Thus, ontogenesis may impact tissue immune responses.

Differential regulation by CD47 and thrombospondin-1 of extramedullary erythropoiesis in mouse spleen

Extramedullary erythropoiesis is not expected in healthy adult mice, but erythropoietic gene expression was elevated in lineage-depleted spleen cells from Cd47-/- mice. Expression of several genes associated with early stages of erythropoiesis was elevated in mice lacking CD47 or its signaling ligand thrombospondin-1, consistent with previous evidence that this signaling pathway inhibits expression of multipotent stem cell transcription factors in spleen. In contrast, cells expressing markers of committed erythroid progenitors were more abundant in Cd47-/- spleens but significantly depleted in Thbs1-/- spleens. Single-cell transcriptome and flow cytometry analyses indicated that loss of CD47 is associated with accumulation and increased proliferation in spleen of Ter119-CD34+ progenitors and Ter119+CD34- committed erythroid progenitors with elevated mRNA expression of Kit, Ermap, and Tfrc. Induction of committed erythroid precursors is consistent with the known function of CD47 to limit the phagocytic removal of aged erythrocytes. Conversely, loss of thrombospondin-1 delays the turnover of aged red blood cells, which may account for the suppression of committed erythroid precursors in Thbs1-/- spleens relative to basal levels in wild-type mice. In addition to defining a role for CD47 to limit extramedullary erythropoiesis, these studies reveal a thrombospondin-1-dependent basal level of extramedullary erythropoiesis in adult mouse spleen.

Using a pan-cancer atlas to investigate tumour associated macrophages as regulators of immunotherapy response

The paradigm for macrophage characterization has evolved from the simple M1/M2 dichotomy to a more complex model that encompasses the broad spectrum of macrophage phenotypic diversity, due to differences in ontogeny and/or local stimuli. We currently lack an in-depth pan-cancer single cell RNA-seq (scRNAseq) atlas of tumour-associated macrophages (TAMs) that fully captures this complexity. In addition, an increased understanding of macrophage diversity could help to explain the variable responses of cancer patients to immunotherapy. Our atlas includes well established macrophage subsets as well as a number of additional ones. We associate macrophage composition with tumour phenotype and show macrophage subsets can vary between primary and metastatic tumours growing in sites like the liver. We also examine macrophage-T cell functional cross talk and identify two subsets of TAMs associated with T cell activation. Analysis of TAM signatures in a large cohort of immune checkpoint inhibitor-treated patients (CPI1000 + ) identify multiple TAM subsets associated with response, including the presence of a subset of TAMs that upregulate collagen-related genes. Finally, we demonstrate the utility of our data as a resource and reference atlas for mapping of novel macrophage datasets using projection. Overall, these advances represent an important step in both macrophage classification and overcoming resistance to immunotherapies in cancer.

A point cloud segmentation framework for image-based spatial transcriptomics

Recent progress in image-based spatial RNA profiling enables to spatially resolve tens to hundreds of distinct RNA species with high spatial resolution. It presents new avenues for comprehending tissue organization. In this context, the ability to assign detected RNA transcripts to individual cells is crucial for downstream analyses, such as in-situ cell type calling. Yet, accurate cell segmentation can be challenging in tissue data, in particular in the absence of a high-quality membrane marker. To address this issue, we introduce ComSeg, a segmentation algorithm that operates directly on single RNA positions and that does not come with implicit or explicit priors on cell shape. ComSeg is applicable in complex tissues with arbitrary cell shapes. Through comprehensive evaluations on simulated and experimental datasets, we show that ComSeg outperforms existing state-of-the-art methods for in-situ single-cell RNA profiling and in-situ cell type calling. ComSeg is available as a documented and open source pip package at https://github.com/fish-quant/ComSeg .

CD163+ Macrophages Induce Endothelial-to-Mesenchymal Transition in Atheroma

BACKGROUND

Cell phenotype switching is increasingly being recognized in atherosclerosis. However, our understanding of the exact stimuli for such cellular transformations and their significance for human atherosclerosis is still evolving. Intraplaque hemorrhage is thought to be a major contributor to plaque progression in part by stimulating the influx of CD163+ macrophages. Here, we explored the hypothesis that CD163+ macrophages cause plaque progression through the induction of proapoptotic endothelial-to-mesenchymal transition (EndMT) within the fibrous cap.

METHODS

Human coronary artery sections from CVPath's autopsy registry were selected for pathological analysis. Athero-prone ApoE-/- and ApoE-/-/CD163-/- mice were used for in vivo studies. Human peripheral blood mononuclear cell-induced macrophages and human aortic endothelial cells were used for in vitro experiments.

RESULTS

In 107 lesions with acute coronary plaque rupture, 55% had pathological evidence of intraplaque hemorrhage in nonculprit vessels/lesions. Thinner fibrous cap, greater CD163+ macrophage accumulation, and a larger number of CD31/FSP-1 (fibroblast specific protein-1) double-positive cells and TUNEL (terminal deoxynucleotidyl transferase-dUTP nick end labeling) positive cells in the fibrous cap were observed in nonculprit intraplaque hemorrhage lesions, as well as in culprit rupture sections versus nonculprit fibroatheroma sections. Human aortic endothelial cells cultured with supernatants from hemoglobin/haptoglobin-exposed macrophages showed that increased mesenchymal marker proteins (transgelin and FSP-1) while endothelial markers (VE-cadherin and CD31) were reduced, suggesting EndMT induction. Activation of NF-κB (nuclear factor kappa β) signaling by proinflammatory cytokines released from CD163+ macrophages directly regulated the expression of Snail, a critical transcription factor during EndMT induction. Western blot analysis for cleaved caspase-3 and microarray analysis of human aortic endothelial cells indicated that apoptosis was stimulated during CD163+ macrophage-induced EndMT. Additionally, CD163 deletion in athero-prone mice suggested that CD163 is required for EndMT and plaque progression. Using single-cell RNA sequencing from human carotid endarterectomy lesions, a population of EndMT was detected, which demonstrated significant upregulation of apoptosis-related genes.

CONCLUSIONS

CD163+ macrophages provoke EndMT, which may promote plaque progression through fibrous cap thinning.

Pathophysiology of hypereosinophilia-associated heart disease

Background

Cardiac complications in patients with hypereosinophilia cause significant morbidity and mortality. However, mechanisms of how eosinophilic inflammation causes heart damage are poorly understood.

Methods

We developed a model of hypereosinophilia-associated heart disease by challenging hypereosinophilic mice with peptide from the cardiac myosin heavy chain. Disease outcomes were measured by histology, immunohistochemistry, flow cytometry, and measurement of cells and biomarkers in peripheral blood. Eosinophil dependence was determined by using eosinophil-deficient mice (ΔdblGATA). Single cells from heart were subjected to single cell RNA sequencing to assess cell composition, subtypes and expression profiles.

Results

Mice challenged with myocarditic and control peptide had peripheral blood leukocytosis, but only those challenged with myocarditic peptide had heart inflammation. Heart tissue was infiltrated by eosinophil-rich inflammatory infiltrates associated with cardiomyocyte damage. Disease penetrance and severity were dependent on the presence of eosinophils. Single cell RNA sequencing showed enrichment of myeloid cells, T-cells and granulocytes (neutrophils and eosinophils) in the myocarditic mice. Macrophages were M2 skewed, and eosinophils had an activated phenotype. Gene enrichment analysis identified several pathways potentially involved in pathophysiology of disease.

Conclusion

Eosinophils are required for heart damage in hypereosinophilia-associated heart disease. Additionally, myeloid cells, granulocytes and T-cell cooperatively or independently participate in the pathogenesis of hypereosinophilia-associated heart disease.

Stage-specific GATA3 induction promotes ILC2 development after lineage commitment

Group 2 innate lymphoid cells (ILC2s) are a subset of innate lymphocytes that produce type 2 cytokines, including IL-4, IL-5, and IL-13. GATA3 is a critical transcription factor for ILC2 development at multiple stages. However, when and how GATA3 is induced to the levels required for ILC2 development remains unclear. Herein, we identify ILC2-specific GATA3-related tandem super-enhancers (G3SE) that induce high GATA3 in ILC2-committed precursors. G3SE-deficient mice exhibit ILC2 deficiency in the bone marrow, lung, liver, and small intestine with minimal impact on other ILC lineages or Th2 cells. Single-cell RNA-sequencing and subsequent flow cytometry analysis show that GATA3 induction mechanism, which is required for entering the ILC2 stage, is lost in IL-17RB+PD-1- late ILC2-committed precursor stage in G3SE-deficient mice. Cnot6l, part of the CCR4-NOT deadenylase complex, is a possible GATA3 target during ILC2 development. Our findings implicate a stage-specific regulatory mechanism for GATA3 expression during ILC2 development.

Control of innate olfactory valence by segregated cortical amygdala circuits

Animals perform innate behaviors that are stereotyped responses to specific evolutionarily relevant stimuli in the absence of prior learning or experience. These behaviors can be reduced to an axis of valence, whereby specific odors evoke approach or avoidance. The cortical amygdala (plCoA) mediates innate attraction and aversion to odor. However, little is known about how this brain area gives rise to behaviors of opposing motivational valence. Here, we sought to define the circuit features of plCoA that give rise to innate olfactory behaviors of valence. We characterized the physiology, gene expression, and projections of this structure, identifying a divergent, topographic organization that selectively controls innate attraction and avoidance to odor. First, we examined odor-evoked responses in these areas and found sparse encoding of odor identity, but not valence. We next considered a topographic organization and found that optogenetic stimulation of the anterior and posterior domains of plCoA elicits attraction and avoidance, respectively, suggesting a functional axis for valence. Using single cell and spatial RNA sequencing, we identified the molecular cell types in plCoA, revealing an anteroposterior gradient in cell types, whereby anterior glutamatergic neurons preferentially express Slc17a6 and posterior neurons express Slc17a7. Activation of these respective cell types recapitulates appetitive and aversive valence behaviors, and chemogenetic inhibition reveals partial necessity for valence responses to innate appetitive or aversive odors. Finally, we identified topographically organized circuits defined by projections, whereby anterior neurons preferentially project to medial amygdala, and posterior neurons preferentially project to nucleus accumbens, which are respectively sufficient and necessary for innate negative and positive olfactory valence. Together, these data advance our understanding of how the olfactory system generates stereotypic, hardwired attraction and avoidance, and supports a model whereby distinct, topographically distributed plCoA populations direct innate olfactory valence responses by signaling to divergent valence-specific targets, linking upstream olfactory identity to downstream valence behaviors, through a population code. This represents a novel circuit motif in which valence encoding is represented not by the firing properties of individual neurons, but by population level identity encoding that is routed through divergent targets to mediate distinct valence.

Single Nucleus Total RNA Sequencing of Formalin-Fixed Paraffin-Embedded Gliomas

Gliomas, the predominant form of brain cancer, comprise diverse malignant subtypes with limited curative therapies available. The insufficient understanding of their molecular diversity and evolutionary processes hinders the advancement of new treatments. Technical complexities associated with formalin-fixed paraffin-embedded (FFPE) clinical samples hinder molecular-level analyses of gliomas. Current single-cell RNA sequencing (scRNA-seq) platforms are inadequate for large-scale clinical applications. In this study, automated snRandom-seq is developed, a high-throughput single-nucleus total RNA sequencing platform optimized for archival FFPE samples. This platform integrates automated single-nucleus isolation and droplet barcoding systems with the random primer-based scRNA-seq chemistry, accommodating a broad spectrum of sample types. The automated snRandom-seq is applied to analyze 116 492 single nuclei from 17 FFPE samples of various glioma subtypes, including rare clinical samples and matched primary-recurrent glioblastomas (GBMs). The study provides comprehensive insights into the molecular characteristics of gliomas at the single-cell level. Abundant non-coding RNAs (ncRNAs) with distinct expression profiles across different glioma clusters and uncovered promising recurrence-related targets and pathways in primary-recurrent GBMs are identified. These findings establish automated snRandom-seq as a robust tool for scRNA-seq of FFPE samples, enabling exploration of molecular diversities and tumor evolution. This platform holds significant implications for large-scale integrative and retrospective clinical research.

PFHpA alters lipid metabolism and increases the risk of metabolic dysfunction-associated steatotic liver disease in youth-a translational research framework

To address the growing epidemic of liver disease, particularly in pediatric populations, it is crucial to identify modifiable risk factors for the development and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). Per- and polyfluoroalkyl substances (PFAS) are persistent ubiquitous chemicals and have emerged as potential risk factors for liver damage. However, their impact on the etiology and severity of MASLD remains largely unexplored in humans. This study aims to bridge the gap between human and in vitro studies to understand how exposure to perfluoroheptanoic acid (PFHpA), one of the emerging PFAS replacements which accumulates in high concentrations in the liver, contributes to MASLD risk and progression. First, we showed that PFHpA plasma concentrations were significantly associated with increased risk of MASLD in obese adolescents. Further, we examined the impact of PFHpA on hepatic metabolism using 3D human liver spheroids and single-cell transcriptomics to identify major hepatic pathways affected by PFHpA. Next, we integrated the in vivo and in vitro multi-omics datasets with a novel statistical approach which identified signatures of proteins and metabolites associated with MASLD development triggered by PFHpA exposure. In addition to characterizing the contribution of PFHpA to MASLD progression, our study provides a novel strategy to identify individuals at high risk of PFHpA-induced MASLD and develop early intervention strategies. Notably, our analysis revealed that the proteomic signature exhibited a stronger correlation between both PFHpA exposure and MASLD risk compared to the metabolomic signature. While establishing a clear connection between PFHpA exposure and MASLD progression in humans, our study delved into the molecular mechanisms through which PFHpA disrupts liver metabolism. Our in vitro findings revealed that PFHpA primarily impacts lipid metabolism, leading to a notable increase of lipid accumulation in human hepatocytes after PFHpA exposure. Among the pathways involved in lipid metabolism in hepatocytes, regulation of lipid metabolism by PPAR-a showed a remarkable activation. Moreover, the translational research framework we developed by integrating human and in vitro data provided us biomarkers to identify individuals at a high risk of MASLD due to PFHpA exposure. Our framework can inform policies on PFAS-induced liver disease and identify potential targets for prevention and treatment strategies.

The Human Developing Cerebral Cortex Is Characterized by an Elevated De Novo Expression of Long Noncoding RNAs in Excitatory Neurons

The outstanding human cognitive capacities are computed in the cerebral cortex, a mammalian-specific brain region and the place of massive biological innovation. Long noncoding RNAs have emerged as gene regulatory elements with higher evolutionary turnover than mRNAs. The many long noncoding RNAs identified in neural tissues make them candidates for molecular sources of cerebral cortex evolution and disease. Here, we characterized the genomic and cellular shifts that occurred during the evolution of the long noncoding RNA repertoire expressed in the developing cerebral cortex and explored putative roles for these long noncoding RNAs in the evolution of the human brain. Using transcriptomics and comparative genomics, we comprehensively annotated the cortical transcriptomes of humans, rhesus macaques, mice, and chickens and classified human cortical long noncoding RNAs into evolutionary groups as a function of their predicted minimal ages. Long noncoding RNA evolutionary groups showed differences in expression levels, splicing efficiencies, transposable element contents, genomic distributions, and transcription factor binding to their promoters. Furthermore, older long noncoding RNAs showed preferential expression in germinative zones, outer radial glial cells, and cortical inhibitory (GABAergic) neurons. In comparison, younger long noncoding RNAs showed preferential expression in cortical excitatory (glutamatergic) neurons, were enriched in primate and human-specific gene co-expression modules, and were dysregulated in neurodevelopmental disorders. These results suggest different evolutionary routes for older and younger cortical long noncoding RNAs, highlighting old long noncoding RNAs as a possible source of molecular evolution of conserved developmental programs; conversely, we propose that the de novo expression of primate- and human-specific young long noncoding RNAs is a putative source of molecular evolution and dysfunction of cortical excitatory neurons, warranting further investigation.

ezSingleCell: an integrated one-stop single-cell and spatial omics analysis platform for bench scientists

ezSingleCell is an interactive and easy-to-use application for analysing various single-cell and spatial omics data types without requiring prior programing knowledge. It combines the best-performing publicly available methods for in-depth data analysis, integration, and interactive data visualization. ezSingleCell consists of five modules, each designed to be a comprehensive workflow for one data type or task. In addition, ezSingleCell allows crosstalk between different modules within a unified interface. Acceptable input data can be in a variety of formats while the output consists of publication ready figures and tables. In-depth manuals and video tutorials are available to guide users on the analysis workflows and parameter adjustments to suit their study aims. ezSingleCell's streamlined interface can analyse a standard scRNA-seq dataset of 3000 cells in less than five minutes. ezSingleCell is available in two forms: an installation-free web application ( https://immunesinglecell.org/ezsc/ ) or a software package with a shinyApp interface ( https://github.com/JinmiaoChenLab/ezSingleCell2 ) for offline analysis.

Single-nucleus multi-omics of Parkinson's disease reveals a glutamatergic neuronal subtype susceptible to gene dysregulation via alteration of transcriptional networks

The genetic architecture of Parkinson's disease (PD) is complex and multiple brain cell subtypes are involved in the neuropathological progression of the disease. Here we aimed to advance our understanding of PD genetic complexity at a cell subtype precision level. Using parallel single-nucleus (sn)RNA-seq and snATAC-seq analyses we simultaneously profiled the transcriptomic and chromatin accessibility landscapes in temporal cortex tissues from 12 PD compared to 12 control subjects at a granular single cell resolution. An integrative bioinformatic pipeline was developed and applied for the analyses of these snMulti-omics datasets. The results identified a subpopulation of cortical glutamatergic excitatory neurons with remarkably altered gene expression in PD, including differentially-expressed genes within PD risk loci identified in genome-wide association studies (GWAS). This was the only neuronal subtype showing significant and robust overexpression of SNCA. Further characterization of this neuronal-subpopulation showed upregulation of specific pathways related to axon guidance, neurite outgrowth and post-synaptic structure, and downregulated pathways involved in presynaptic organization and calcium response. Additionally, we characterized the roles of three molecular mechanisms in governing PD-associated cell subtype-specific dysregulation of gene expression: (1) changes in cis-regulatory element accessibility to transcriptional machinery; (2) changes in the abundance of master transcriptional regulators, including YY1, SP3, and KLF16; (3) candidate regulatory variants in high linkage disequilibrium with PD-GWAS genomic variants impacting transcription factor binding affinities. To our knowledge, this study is the first and the most comprehensive interrogation of the multi-omics landscape of PD at a cell-subtype resolution. Our findings provide new insights into a precise glutamatergic neuronal cell subtype, causal genes, and non-coding regulatory variants underlying the neuropathological progression of PD, paving the way for the development of cell- and gene-targeted therapeutics to halt disease progression as well as genetic biomarkers for early preclinical diagnosis.

SLAM/SAP signaling regulates discrete γδ T cell developmental checkpoints and shapes the innate-like γδ TCR repertoire

During thymic development, most γδ T cells acquire innate-like characteristics that are critical for their function in tumor surveillance, infectious disease, and tissue repair. The mechanisms, however, that regulate γδ T cell developmental programming remain unclear. Recently, we demonstrated that the SLAM-SAP signaling pathway regulates the development and function of multiple innate-like γδ T cell subsets. Here, we used a single-cell proteogenomics approach to identify SAP-dependent developmental checkpoints and to define the SAP-dependent γδ TCR repertoire. SAP deficiency resulted in both a significant loss of an immature Gzma + Blk + Etv5 + Tox2 + γδT17 precursor population, and a significant increase in Cd4 + Cd8+ Rorc + Ptcra + Rag1 + thymic γδ T cells. SAP-dependent diversion of embryonic day 17 thymic γδ T cell clonotypes into the αβ T cell developmental pathway was associated with a decreased frequency of mature clonotypes in neonatal thymus, and an altered γδ TCR repertoire in the periphery. Finally, we identify TRGV4/TRAV13-4(DV7)-expressing T cells as a novel, SAP-dependent Vγ4 γδT1 subset. Together, the data suggest that SAP-dependent γδ/αβ T cell lineage commitment regulates γδ T cell developmental programming and shapes the γδ TCR repertoire.

spatialGE: A user-friendly web application to democratize spatial transcriptomics analysis

Spatial transcriptomics (ST) is a powerful tool for understanding tissue biology and disease mechanisms. However, its potential is often underutilized due to the advanced data analysis and programming skills required. To address this, we present spatialGE, a web application that simplifies the analysis of ST data. The application spatialGE provides a user-friendly interface that guides users without programming expertise through various analysis pipelines, including quality control, normalization, domain detection, phenotyping, and multiple spatial analyses. It also enables comparative analysis among samples and supports various ST technologies. We demonstrate the utility of spatialGE through its application in studying the tumor microenvironment of melanoma brain metastasis and Merkel cell carcinoma. Our results highlight the ability of spatialGE to identify spatial gene expression patterns and enrichments, providing valuable insights into the tumor microenvironment and its utility in democratizing ST data analysis for the wider scientific community.

Characterization of pathological stages in a mouse model of progressive multiple sclerosis

The purpose of this study was to analyze and elucidate the mechanisms of non-obese diabetes-experimental autoimmune encephalomyelitis (NOD-EAE), an animal model of progressive multiple sclerosis (MS), and to compare the pathological features with those observed in human progressive MS. Pathological analysis, flow cytometry analysis, immunohistochemical staining, and transcriptome analysis were performed at each pathological stage of the NOD-EAE mice to characterize each pathological stage in the lesion. The NOD-EAE mice showed a biphasic pattern of disease progression once in remission. The longitudinal profile of demyelination and inflammatory cell infiltration in the spinal cord was consistent with the pathological score. In the chronic phase of the disease, fibrosis and lymph follicle formation, characteristic of progressive human MS, were observed. Here we describe the pathological profile and transcriptome analysis of the NOD-EAE mice and verify that this model has similar features to those of human progressive MS. Our findings suggest that this model recapitulates lymph follicle formation, a disease hallmark of progressive MS, and fibrosis, a feature complicating the pathogenesis of MS in the chronic phase. This model may be useful for evaluating the efficacy of therapeutic agents and for mechanistic analysis.

GHCU, a Molecular Chaperone, Regulates Leaf Curling by Modulating the Distribution of KNGH1 in Cotton

Leaf shape is considered to be one of the most significant agronomic traits in crop breeding. However, the molecular basis underlying leaf morphogenesis in cotton is still largely unknown. In this study, through genetic mapping and molecular investigation using a natural cotton mutant cu with leaves curling upward, the causal gene GHCU is successfully identified as the key regulator of leaf flattening. Knockout of GHCU or its homolog in cotton and tobacco using CRISPR results in abnormal leaf shape. It is further discovered that GHCU facilitates the transport of the HD protein KNOTTED1-like (KNGH1) from the adaxial to the abaxial domain. Loss of GHCU function restricts KNGH1 to the adaxial epidermal region, leading to lower auxin response levels in the adaxial boundary compared to the abaxial. This spatial asymmetry in auxin distribution produces the upward-curled leaf phenotype of the cu mutant. By analysis of single-cell RNA sequencing and spatiotemporal transcriptomic data, auxin biosynthesis genes are confirmed to be expressed asymmetrically in the adaxial-abaxial epidermal cells. Overall, these findings suggest that GHCU plays a crucial role in the regulation of leaf flattening through facilitating cell-to-cell trafficking of KNGH1 and hence influencing the auxin response level.

Distinct origin and region-dependent contribution of stromal fibroblasts to fibrosis following traumatic injury in mice

Fibrotic scar tissue formation occurs in humans and mice. The fibrotic scar impairs tissue regeneration and functional recovery. However, the origin of scar-forming fibroblasts is unclear. Here, we show that stromal fibroblasts forming the fibrotic scar derive from two populations of perivascular cells after spinal cord injury (SCI) in adult mice of both sexes. We anatomically and transcriptionally identify the two cell populations as pericytes and perivascular fibroblasts. Fibroblasts and pericytes are enriched in the white and gray matter regions of the spinal cord, respectively. Both cell populations are recruited in response to SCI and inflammation. However, their contribution to fibrotic scar tissue depends on the location of the lesion. Upon injury, pericytes and perivascular fibroblasts become activated and transcriptionally converge on the generation of stromal myofibroblasts. Our results show that pericytes and perivascular fibroblasts contribute to the fibrotic scar in a region-dependent manner.

The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation

Dexamethasone is a life-saving treatment for severe COVID-19, yet its mechanism of action is unknown, and many patients deteriorate or die despite timely treatment initiation. Here, we identify dexamethasone treatment-induced cellular and molecular changes associated with improved survival in COVID-19 patients. We observed a reversal of transcriptional hallmark signatures in monocytes associated with severe COVID-19 and the induction of a monocyte substate characterized by the expression of glucocorticoid-response genes. These molecular responses to dexamethasone were detected in circulating and pulmonary monocytes, and they were directly linked to survival. Monocyte single-cell RNA sequencing (scRNA-seq)-derived signatures were enriched in whole blood transcriptomes of patients with fatal outcome in two independent cohorts, highlighting the potential for identifying non-responders refractory to dexamethasone. Our findings link the effects of dexamethasone to specific immunomodulation and reversal of monocyte dysregulation, and they highlight the potential of single-cell omics for monitoring in vivo target engagement of immunomodulatory drugs and for patient stratification for precision medicine approaches.

Opening the Black Box: Spatial Transcriptomics and the Relevance of Artificial Intelligence-Detected Prognostic Regions in High-Grade Serous Carcinoma

Image-based deep learning models are used to extract new information from standard hematoxylin and eosin pathology slides; however, biological interpretation of the features detected by artificial intelligence (AI) remains a challenge. High-grade serous carcinoma of the ovary (HGSC) is characterized by aggressive behavior and chemotherapy resistance, but also exhibits striking variability in outcome. Our understanding of this disease is limited, partly due to considerable tumor heterogeneity. We previously trained an AI model to identify HGSC tumor regions that are highly associated with outcome status but are indistinguishable by conventional morphologic methods. Here, we applied spatially resolved transcriptomics to further profile the AI-identified tumor regions in 16 patients (8 per outcome group) and identify molecular features related to disease outcome in patients who underwent primary debulking surgery and platinum-based chemotherapy. We examined formalin-fixed paraffin-embedded tissue from (1) regions identified by the AI model as highly associated with short or extended chemotherapy response, and (2) background tumor regions (not identified by the AI model as highly associated with outcome status) from the same tumors. We show that the transcriptomic profiles of AI-identified regions are more distinct than background regions from the same tumors, are superior in predicting outcome, and differ in several pathways including those associated with chemoresistance in HGSC. Further, we find that poor outcome and good outcome regions are enriched by different tumor subpopulations, suggesting distinctive interaction patterns. In summary, our work presents proof of concept that AI-guided spatial transcriptomic analysis improves recognition of biologic features relevant to patient outcomes.

Microglial function interacts with the environment to affect sex-specific depression risk

There is a two-fold higher incidence of depression in females compared to men with recent studies suggesting a role for microglia in conferring this sex-dependent depression risk. In this study we investigated the nature of this relation. Using GWAS enrichment, gene-set enrichment analysis and Mendelian randomization, we found minimal evidence for a direct relation between genes functionally related to microglia and sex-dependent genetic risk for depression. We then used expression quantitative trait loci and single nucleus RNA-sequencing resources to generate polygenic scores (PGS) representative of individual variation in microglial function in the adult (UK Biobank; N = 54753-72682) and fetal (ALSPAC; N = 1452) periods. The adult microglial PGS moderated the association between BMI (UK Biobank; beta = 0.001, 95 %CI 0.0009 to 0.003, P = 7.74E-6) and financial insecurity (UK Biobank; beta = 0.001, 95 %CI 0.005 to 0.015, P = 2E-4) with depressive symptoms in females. The fetal microglia PGS moderated the association between maternal prenatal depressive symptoms and offspring depressive symptoms at 24 years in females (ALSPAC; beta = 0.04, 95 %CI 0.004 to 0.07, P = 0.03). We found no evidence for an interaction between the microglial PGS and depression risk factors in males. Our results illustrate a role for microglial function in the conferral of sex-dependent depression risk following exposure to a depression risk factor.

Mapping spatially resolved transcriptomes in human and mouse pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with poor prognosis and limited treatment options. Efforts to identify effective treatments are thwarted by limited understanding of IPF pathogenesis and poor translatability of available preclinical models. Here we generated spatially resolved transcriptome maps of human IPF (n = 4) and bleomycin-induced mouse pulmonary fibrosis (n = 6) to address these limitations. We uncovered distinct fibrotic niches in the IPF lung, characterized by aberrant alveolar epithelial cells in a microenvironment dominated by transforming growth factor beta signaling alongside predicted regulators, such as TP53 and APOE. We also identified a clear divergence between the arrested alveolar regeneration in the IPF fibrotic niches and the active tissue repair in the acutely fibrotic mouse lung. Our study offers in-depth insights into the IPF transcriptional landscape and proposes alveolar regeneration as a promising therapeutic strategy for IPF.

Combined analysis of single-cell sequencing and bulk transcriptome sequencing reveals new mechanisms for non-healing diabetic foot ulcers

Diabetic foot ulcers (DFUs) pose a significant challenge in diabetes care. Yet, a comprehensive understanding of the underlying biological disparities between healing and non-healing DFUs remains elusive. We conducted bioinformatics analysis of publicly available transcriptome sequencing data in an attempt to elucidate these differences. Our analysis encompassed differential analysis to unveil shifts in cell composition and gene expression profiles between non-healing and healing DFUs. Cell communication alterations were explored employing the Cellchat R package. Pseudotime analysis and cytoTRACE allowed us to dissect the heterogeneity within fibroblast subpopulations. Our findings unveiled disruptions in various cell types, localized low-grade inflammation, compromised systemic antigen processing and presentation, and extensive extracellular matrix signaling disarray in non-healing DFU patients. Some of these anomalies partially reverted in healing DFUs, particularly within the abnormal ECM-receptor signaling pathway. Furthermore, we distinguished distinct fibroblast subpopulations in non-healing and healing DFUs, each with unique biological functions. Healing-associated fibroblasts exhibited heightened extracellular matrix (ECM) remodeling and a robust wound healing response, while non-healing-associated fibroblasts showed signs of cellular senescence and complement activation, among other characteristics. This analysis offers profound insights into the wound healing microenvironment, identifies pivotal cell types for DFU healing promotion, and reveals potential therapeutic targets for DFU management.

Senescent CAFs Mediate Immunosuppression and Drive Breast Cancer Progression

The tumor microenvironment (TME) profoundly influences tumorigenesis, with gene expression in the breast TME capable of predicting clinical outcomes. The TME is complex and includes distinct cancer-associated fibroblast (CAF) subtypes whose contribution to tumorigenesis remains unclear. Here, we identify a subset of myofibroblast CAFs (myCAF) that are senescent (senCAF) in mouse and human breast tumors. Utilizing the MMTV-PyMT;INK-ATTAC (INK) mouse model, we found that senCAF-secreted extracellular matrix specifically limits natural killer (NK) cell cytotoxicity to promote tumor growth. Genetic or pharmacologic senCAF elimination unleashes NK cell killing, restricting tumor growth. Finally, we show that senCAFs are present in HER2+, ER+, and triple-negative breast cancer and in ductal carcinoma in situ (DCIS) where they predict tumor recurrence. Together, these findings demonstrate that senCAFs are potently tumor promoting and raise the possibility that targeting them by senolytic therapy could restrain breast cancer development. Significance: senCAFs limit NK cell-mediated killing, thereby contributing to breast cancer progression. Thus, targeting senCAFs could be a clinically viable approach to limit tumor progression. See related article by Belle et al., p. 1324.

Quantification and statistical modeling of droplet-based single-nucleus RNA-sequencing data

In complex tissues containing cells that are difficult to dissociate, single-nucleus RNA-sequencing (snRNA-seq) has become the preferred experimental technology over single-cell RNA-sequencing (scRNA-seq) to measure gene expression. To accurately model these data in downstream analyses, previous work has shown that droplet-based scRNA-seq data are not zero-inflated, but whether droplet-based snRNA-seq data follow the same probability distributions has not been systematically evaluated. Using pseudonegative control data from nuclei in mouse cortex sequenced with the 10x Genomics Chromium system and mouse kidney sequenced with the DropSeq system, we found that droplet-based snRNA-seq data follow a negative binomial distribution, suggesting that parametric statistical models applied to scRNA-seq are transferable to snRNA-seq. Furthermore, we found that the quantification choices in adapting quantification mapping strategies from scRNA-seq to snRNA-seq can play a significant role in downstream analyses and biological interpretation. In particular, reference transcriptomes that do not include intronic regions result in significantly smaller library sizes and incongruous cell type classifications. We also confirmed the presence of a gene length bias in snRNA-seq data, which we show is present in both exonic and intronic reads, and investigate potential causes for the bias.

Revealing gene expression heterogeneity in a clonal population of Tetrahymena thermophila through single-cell RNA sequencing

We performed single-cell RNA sequencing (scRNA-seq) on a population of 5,000 Tetrahymena thermophila, using the 10x Genomics 3' gene expression analysis, to investigate gene expression variability within this clonal population. Initially, we estimated the 3'-untranslated regions (3' UTRs), which were absent in existing annotation files but are crucial for the 10x Genomics 3' gene expression analysis, using the peaks2utr method. This allowed us to create a modified annotation file, which was then utilized in our scRNA-seq analysis. Our analysis revealed significant gene expression variability within the population, even after removing the effect of cell phase-related features. This variability predominantly appeared in six distinct clusters. Through gene ontology and KEGG pathway enrichment analyses, we identified that these were primarily associated with ribosomal proteins, proteins specific to mitochondria, proteins involved in peroxisome-specific carbon metabolism, cytoskeletal proteins, motor proteins, and immobilized antigens.

Optimizing single-cell RNA sequencing methods for human colon biopsies: droplet-based vs. picowell-based platforms

Background & Aims

Single-cell RNA sequencing (scRNA) has empowered many insights into gastrointestinal microenvironments. However, profiling human biopsies using droplet-based scRNA (D-scRNA) is challenging since it requires immediate processing to minimize epithelial cell damage. In contrast, picowell-based (P-scRNA) platforms permit short-term frozen storage before sequencing. We compared P- and D-scRNA platforms on cells derived from human colon biopsies.

Methods

Endoscopic rectosigmoid mucosal biopsies were obtained from two adults and conducted D-scRNA (10X Chromium) and P-scRNA (Honeycomb HIVE) in parallel using an individual's pool of single cells (> 10,000 cells/participant). Three experiments were performed to evaluate 1) P-scRNA with cells under specific storage conditions (immediately processed [fresh], vs. frozen at -20C vs. -80C [2 weeks]); 2) fresh P-scRNA versus fresh D-scRNA; and 3) P-scRNA stored at -80C with fresh D-scRNA.

Results

Significant recovery of loaded cells was achieved for fresh (80.9%) and -80C (48.5%) P-scRNA and D-scRNA (76.6%), but not -20C P-scRNA (3.7%). However, D-scRNA captures more typeable cells among recovered cells (71.5% vs. 15.8% Fresh and 18.4% -80C P-scRNA), and these cells exhibit higher gene coverage at the expense of higher mitochondrial read fractions across most cell types. Cells profiled using D-scRNA demonstrated more consistent gene expression profiles among the same cell type than those profiled using P-scRNA. Significant intra-cell-type differences were observed in profiled gene classes across platforms.

Conclusions

Our results highlight non-overlapping advantages of P-scRNA and D-scRNA and underscore the need for innovation to enable high-fidelity capture of colonic epithelial cells. The platform-specific variation highlights the challenges of maintaining rigor and reproducibility across studies that use different platforms.

Glycolysis in hepatic stellate cells coordinates fibrogenic extracellular vesicle release spatially to amplify liver fibrosis

Liver fibrosis is characterized by the activation of perivascular hepatic stellate cells (HSCs), the release of fibrogenic nanosized extracellular vesicles (EVs), and increased HSC glycolysis. Nevertheless, how glycolysis in HSCs coordinates fibrosis amplification through tissue zone-specific pathways remains elusive. Here, we demonstrate that HSC-specific genetic inhibition of glycolysis reduced liver fibrosis. Moreover, spatial transcriptomics revealed a fibrosis-mediated up-regulation of EV-related pathways in the liver pericentral zone, which was abrogated by glycolysis genetic inhibition. Mechanistically, glycolysis in HSCs up-regulated the expression of EV-related genes such as Ras-related protein Rab-31 (RAB31) by enhancing histone 3 lysine 9 acetylation on the promoter region, which increased EV release. Functionally, these glycolysis-dependent EVs increased fibrotic gene expression in recipient HSC. Furthermore, EVs derived from glycolysis-deficient mice abrogated liver fibrosis amplification in contrast to glycolysis-competent mouse EVs. In summary, glycolysis in HSCs amplifies liver fibrosis by promoting fibrogenic EV release in the hepatic pericentral zone, which represents a potential therapeutic target.

A count-based model for delineating cell-cell interactions in spatial transcriptomics data

MOTIVATION

Cell-cell interactions (CCIs) consist of cells exchanging signals with themselves and neighboring cells by expressing ligand and receptor molecules and play a key role in cellular development, tissue homeostasis, and other critical biological functions. Since direct measurement of CCIs is challenging, multiple methods have been developed to infer CCIs by quantifying correlations between the gene expression of the ligands and receptors that mediate CCIs, originally from bulk RNA-sequencing data and more recently from single-cell or spatially resolved transcriptomics (SRT) data. SRT has a particular advantage over single-cell approaches, since ligand-receptor correlations can be computed between cells or spots that are physically close in the tissue. However, the transcript counts of individual ligands and receptors in SRT data are generally low, complicating the inference of CCIs from expression correlations.

RESULTS

We introduce Copulacci, a count-based model for inferring CCIs from SRT data. Copulacci uses a Gaussian copula to model dependencies between the expression of ligands and receptors from nearby spatial locations even when the transcript counts are low. On simulated data, Copulacci outperforms existing CCI inference methods based on the standard Spearman and Pearson correlation coefficients. Using several real SRT datasets, we show that Copulacci discovers biologically meaningful ligand-receptor interactions that are lowly expressed and undiscoverable by existing CCI inference methods.

AVAILABILITY AND IMPLEMENTATION

Copulacci is implemented in Python and available at https://github.com/raphael-group/copulacci.

Fokker-Planck diffusion maps of multiple single cell microglial transcriptomes reveals radial differentiation into substates associated with Alzheimer's pathology

The identification of microglia subtypes is important for understanding the role of innate immunity in neurodegenerative diseases. Current methods of unsupervised cell type identification assume a small noise-to-signal ratio of transcriptome measurements that would produce well-separated cell clusters. However, identification of subtypes is obscured by gene expression noise, diminishing the distances in transcriptome space between distinct cell types and blurring boundaries. Here we use Fokker-Planck (FP) diffusion maps to model cellular differentiation as a stochastic process whereby cells settle into local minima, corresponding to cell subtypes, in a potential landscape constructed from transcriptome data using a nearest neighbor graph approach. By applying critical transition fields, we identify individual cells on the verge of transitioning between subtypes, revealing microglial cells in inactivated, homeostatic state before radially transitioning into various specialized subtypes. Specifically, we show that cells from Alzheimer's disease patients are enriched in a microglia subtype associated to antigen presentation and T-cell recruitment.

Cellular and transcriptional profiles of peripheral blood mononuclear cells pre-vaccination predict immune response to preventative MUC1 vaccine

A single arm trial (NCT007773097) and a double-blind, placebo controlled randomized trial ( NCT02134925 ) were conducted in individuals with a history of advanced colonic adenoma to test the safety and immunogenicity of the MUC1 tumor antigen vaccine and its potential to prevent new adenomas. These were the first two trials of a non-viral cancer vaccine administered in the absence of cancer. The vaccine was safe and strongly immunogenic in 43% (NCT007773097) and 25% ( NCT02134925 ) of participants. The lack of response in a significant number of participants suggested, for the first time, that even in a premalignant setting, the immune system may have already been exposed to some level of suppression previously reported only in cancer. Single-cell RNA-sequencing (scRNA-seq) on banked pre-vaccination peripheral blood mononuclear cells (PBMCs) from 16 immune responders and 16 non-responders identified specific cell types, genes, and pathways of a productive vaccine response. Responders had a significantly higher percentage of CD4+ naive T cells pre-vaccination, but a significantly lower percentage of CD8+ T effector memory (TEM) cells and CD16+ monocytes. Differential gene expression (DGE) and transcription factor inference analysis showed a higher level of expression of T cell activation genes, such as Fos and Jun, in CD4+ naive T cells, and pathway analysis showed enriched signaling activity in responders. Furthermore, Bayesian network analysis suggested that these genes were mechanistically connected to response. Our analyses identified several immune mechanisms and candidate biomarkers to be further validated as predictors of immune responses to a preventative cancer vaccine that could facilitate selection of individuals likely to benefit from a vaccine or be used to improve vaccine responses.

Single Cell Analysis of Peripheral TB-Associated Granulomatous Lymphadenitis

We successfully employed a single cell RNA sequencing (scRNA-seq) approach to describe the cells and the communication networks characterizing granulomatous lymph nodes of TB patients. When mapping cells from individual patient samples, clustered based on their transcriptome similarities, we uniformly identify several cell types that known to characterize human and non-human primate granulomas. Whether high or low Mtb burden, we find the T cell cluster to be one of the most abundant. Many cells expressing T cell markers are clearly quantifiable within this CD3 expressing cluster. Other cell clusters that are uniformly detected, but that vary dramatically in abundance amongst the individual patient samples, are the B cell, plasma cell and macrophage/dendrocyte and NK cell clusters. When we combine all our scRNA-seq data from our current 23 patients (in order to add power to cell cluster identification in patient samples with fewer cells), we distinguish T, macrophage, dendrocyte and plasma cell subclusters, each with distinct signaling activities. The sizes of these subclusters also varies dramatically amongst the individual patients. In comparing FNA composition we noted trends in which T cell populations and macrophage/dendrocyte populations were negatively correlated with NK cell populations. In addition, we also discovered that the scRNA-seq pipeline, designed for quantification of human cell mRNA, also detects Mtb RNA transcripts and associates them with their host cell's transcriptome, thus identifying individual infected cells. We hypothesize that the number of detected bacterial transcript reads provides a measure of Mtb burden, as does the number of Mtb-infected cells. The number of infected cells also varies dramatically in abundance amongst the patient samples. CellChat analysis identified predominating signaling pathways amongst the cells comprising the various granulomas, including many interactions between stromal or endothelial cells and the other component cells, such as Collagen, FN1 and Laminin,. In addition, other more selective communications pathways, including MIF, MHC-1, MHC-2, APP, CD 22, CD45, and others, are identified as originating or being received by individual immune cell components.

Molecular cascade reveals sequential milestones underlying hippocampal neural stem cell development into an adult state

Quiescent adult neural stem cells (NSCs) in the mammalian brain arise from proliferating NSCs during development. Beyond acquisition of quiescence, an adult NSC hallmark, little is known about the process, milestones, and mechanisms underlying the transition of developmental NSCs to an adult NSC state. Here, we performed targeted single-cell RNA-seq analysis to reveal the molecular cascade underlying NSC development in the early postnatal mouse dentate gyrus. We identified two sequential steps, first a transition to quiescence followed by further maturation, each of which involved distinct changes in metabolic gene expression. Direct metabolic analysis uncovered distinct milestones, including an autophagy burst before NSC quiescence acquisition and cellular reactive oxygen species level elevation along NSC maturation. Functionally, autophagy is important for the NSC transition to quiescence during early postnatal development. Together, our study reveals a multi-step process with defined milestones underlying establishment of the adult NSC pool in the mammalian brain.

Hofbauer cells and fetal brain microglia share transcriptional profiles and responses to maternal diet-induced obesity

Maternal immune activation is associated with adverse offspring neurodevelopmental outcomes, many mediated by in utero microglial programming. As microglia remain inaccessible throughout development, identification of noninvasive biomarkers reflecting fetal brain microglial programming could permit screening and intervention. We used lineage tracing to demonstrate the shared ontogeny between fetal brain macrophages (microglia) and fetal placental macrophages (Hofbauer cells) in a mouse model of maternal diet-induced obesity, and single-cell RNA-seq to demonstrate shared transcriptional programs. Comparison with human datasets demonstrated conservation of placental resident macrophage signatures between mice and humans. Single-cell RNA-seq identified common alterations in fetal microglial and Hofbauer cell gene expression induced by maternal obesity, as well as sex differences in these alterations. We propose that Hofbauer cells, which are easily accessible at birth, provide insights into fetal brain microglial programs and may facilitate the early identification of offspring vulnerable to neurodevelopmental disorders.