PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data

Identification of immune feature genes and intercellular profiles in diabetic cardiomyopathy

BACKGROUND

Diabetic cardiomyopathy (DCM) is a multifaceted cardiovascular disorder in which immune dysregulation plays a pivotal role. The immunological molecular mechanisms underlying DCM are poorly understood.

AIM

To examine the immunological molecular mechanisms of DCM and construct diagnostic and prognostic models of DCM based on immune feature genes (IFGs).

METHODS

Weighted gene co-expression network analysis along with machine learning methods were employed to pinpoint IFGs within bulk RNA sequencing (RNA-seq) datasets. Single-sample gene set enrichment analysis (ssGSEA) facilitated the analysis of immune cell infiltration. Diagnostic and prognostic models for these IFGs were developed and assessed in a validation cohort. Gene expression in the DCM cell model was confirmed through real time-quantitative polymerase chain reaction and western blotting techniques. Additionally, single-cell RNA-seq data provided deeper insights into cellular profiles and interactions.

RESULTS

The overlap between 69 differentially expressed genes in the DCM-associated module and 2483 immune genes yielded 7 differentially expressed immune-related genes. Four IFGs showed good diagnostic and prognostic values in the validation cohort: Proenkephalin (Penk) and retinol binding protein 7 (Rbp7), which were highly expressed, and glucagon receptor and inhibin subunit alpha, which were expressed at low levels in DCM patients (all area under the curves > 0.9). SsGSEA revealed that IFG-related immune cell infiltration primarily involved type 2 T helper cells. High expression of Penk (P < 0.0001) and Rbp7 (P = 0.001) was detected in cardiomyocytes and interstitial cells and further confirmed in a DCM cell model in vitro. Intercellular events and communication analysis revealed abnormal cellular phenotype transformation and signaling communication in DCM, especially between mesenchymal cells and macrophages.

CONCLUSION

The present study identified Penk and Rbp7 as potential DCM biomarkers, and aberrant mesenchymal-immune cell phenotype communication may be an important aspect of DCM pathogenesis.

Myeloid-Specific JAK2 Contributes to Inflammation and Salt Sensitivity of Blood Pressure

BACKGROUND

Salt sensitivity of blood pressure (SSBP), characterized by acute changes in blood pressure with changes in dietary sodium intake, is an independent risk factor for cardiovascular disease and mortality in people with and without hypertension. We previously found that elevated sodium concentration activates antigen-presenting cells (APCs), resulting in high blood pressure, but the mechanisms are unknown. Here, we hypothesized that APC-specific JAK2 (Janus kinase 2) through STAT3 (signal transducer and activator of transcription 3) and SMAD3 (small mothers against decapentaplegic homolog 3) contributes to SSBP.

METHODS

We performed bulk or single-cell transcriptomic analyses following in vitro monocytes exposed to high salt and in vivo high sodium treatment in humans using a rigorous salt-loading/depletion protocol to phenotype SSBP. We also used a myeloid cell-specific CD11c+ JAK2 knockout mouse model and measured blood pressure with radiotelemetry after N-omega-nitro-L-arginine-methyl ester and a high salt diet treatment. We used flow cytometry for immunophenotyping and measuring cytokine levels. Fluorescence in situ hybridization and immunohistochemistry were performed to spatially visualize the kidney's immune cells and cytokine levels. Echocardiography was performed to assess cardiac function.

RESULTS

We found that high salt treatment upregulates gene expression of the JAK/STAT/SMAD pathway while downregulating inhibitors of this pathway, such as suppression of cytokine signaling and cytokine-inducible SH2, in human monocytes. Expression of the JAK2 pathway genes mirrored changes in blood pressure after salt loading and depletion in salt-sensitive but not salt-resistant humans. Ablation of JAK2, specifically in CD11c+ APCs, attenuated salt-induced hypertension in mice with SSBP. Mechanistically, we found that SMAD3 acted downstream of JAK2 and STAT3, leading to increased production of highly reactive isolevuglandins and proinflammatory cytokine IL (interleukin)-6 in renal APCs, which activate T cells and increase production of IL-17A, IL-6, and TNF-α (tumor necrosis factor-alpha).

CONCLUSIONS

Our findings reveal the APC JAK2 signaling pathway as a potential target for the diagnosis and treatment of SSBP in humans.

Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data

Assay for Transposase-Accessible Chromatin sequencing (ATAC-Seq) is a widely used technique to explore gene regulatory mechanisms. For most ATAC-Seq data from healthy and diseased tissues such as tumors, chromatin accessibility measurement represents a mixed signal from multiple cell types. In this work, we derive reliable chromatin accessibility marker peaks and reference profiles for most non-malignant cell types frequently observed in the microenvironment of human tumors. We then integrate these data into the EPIC deconvolution framework (Racle et al., 2017) to quantify cell-type heterogeneity in bulk ATAC-Seq data. Our EPIC-ATAC tool accurately predicts non-malignant and malignant cell fractions in tumor samples. When applied to a human breast cancer cohort, EPIC-ATAC accurately infers the immune contexture of the main breast cancer subtypes.

microRNA-324 mediates bone homeostasis and the regulation of osteoblast and osteoclast differentiation and activity

MicroRNAs (miRNAs) modulate the expression of other RNA molecules. One miRNA can target many transcripts, allowing each miRNA to play key roles in many biological pathways. Defects in bone homeostasis result in common age-related diseases including osteoporosis. Serum levels of miR-324-3p positively correlate with several features of bone maintenance. In contrast here, using in vivo micro-computed tomography and histology, global miR-324-null mice demonstrated increased bone mineral density and both trabecular and cortical thickness, with effect magnitudes increasing with age. The bone marrow of miR-324-null mice had reduced lipid content while TRAP staining revealed a decrease in osteoclasts, with histomorphometry demonstrating an increased rate of bone formation. Ex vivo assays showed that the high bone mass phenotype of miR-324-null mice resulted from both increased osteoblast activity and decreased osteoclastogenesis. RNA-seq analysis of osteoblasts, osteoclasts and bone marrow macrophages and target validation assays identified that the osteoclast fusion regulator Pin1 and the master osteogenic regulator Runx2 were targets of miR-324-5p in osteoclast lineage cells and osteoblasts, respectively. Indeed, in vitro Runx2 overexpression recapitulated the increased osteogenesis and decreased adipogenesis phenotype observed in vivo by the loss of miR-324. Overall, these data demonstrate the importance of miR-324 in bone homeostasis by regulating aspects of both bone formation and remodelling. Elucidation of pathways regulated by miR-324 offer promise for the treatment of bone diseases such as osteoporosis.

CXCR4 orchestrates the TOX-programmed exhausted phenotype of CD8+ T cells via JAK2/STAT3 pathway

Evidence from clinical trials suggests that CXCR4 antagonists enhance immunotherapy effectiveness in several cancers. However, the specific mechanisms through which CXCR4 contributes to immune cell phenotypes are not fully understood. Here, we employed single-cell transcriptomic analysis and identified CXCR4 as a marker gene in T cells, with CD8+PD-1high exhausted T (Tex) cells exhibiting high CXCR4 expression. By blocking CXCR4, the Tex phenotype was attenuated in vivo. Mechanistically, CXCR4-blocking T cells mitigated the Tex phenotype by regulating the JAK2-STAT3 pathway. Single-cell RNA/TCR/ATAC-seq confirmed that Cxcr4-deficient CD8+ T cells epigenetically mitigated the transition from functional to exhausted phenotypes. Notably, clinical sample analysis revealed that CXCR4+CD8+ T cells showed higher expression in patients with a non-complete pathological response. Collectively, these findings demonstrate the mechanism by which CXCR4 orchestrates CD8+ Tex cells and provide a rationale for combining CXCR4 antagonists with immunotherapy in clinical trials.

In vivo perturb-seq of cancer and microenvironment cells dissects oncologic drivers and radiotherapy responses in glioblastoma

BACKGROUND

Genetic perturbation screens with single-cell readouts have enabled rich phenotyping of gene function and regulatory networks. These approaches have been challenging in vivo, especially in adult disease models such as cancer, which include mixtures of malignant and microenvironment cells. Glioblastoma (GBM) is a fatal cancer, and methods of systematically interrogating gene function and therapeutic targets in vivo, especially in combination with standard of care treatment such as radiotherapy, are lacking.

RESULTS

Here, we iteratively develop a multiplex in vivo perturb-seq CRISPRi platform for single-cell genetic screens in cancer and tumor microenvironment cells that leverages intracranial convection enhanced delivery of sgRNA libraries into mouse models of GBM. Our platform enables potent silencing of drivers of in vivo growth and tumor maintenance as well as genes that sensitize GBM to radiotherapy. We find radiotherapy rewires transcriptional responses to genetic perturbations in an in vivo-dependent manner, revealing heterogenous patterns of treatment sensitization or resistance in GBM. Furthermore, we demonstrate targeting of genes that function in the tumor microenvironment, enabling alterations of ligand-receptor interactions between immune and stromal cells following in vivo CRISPRi perturbations that can affect tumor cell phagocytosis.

CONCLUSION

In sum, we demonstrate the utility of multiplexed perturb-seq for in vivo single-cell dissection of adult cancer and normal tissue biology across multiple cell types in the context of therapeutic intervention, a platform with potential for broad application.

Inflammation-induced epigenetic imprinting regulates intestinal stem cells

It remains unknown whether and how intestinal stem cells (ISCs) adapt to inflammatory exposure and whether the adaptation leaves scars that will affect their subsequent regeneration. We investigated the consequences of inflammation on Lgr5+ ISCs in well-defined clinically relevant models of acute gastrointestinal graft-versus-host disease (GI GVHD). Utilizing single-cell transcriptomics, as well as organoid, metabolic, epigenomic, and in vivo models, we found that Lgr5+ ISCs undergo metabolic changes that lead to the accumulation of succinate, which reprograms their epigenome. These changes reduced the ability of ISCs to differentiate and regenerate ex vivo in serial organoid cultures and also in vivo following serial transplantation. Furthermore, ISCs demonstrated a reduced capacity for in vivo regeneration despite resolution of the initial inflammatory exposure, demonstrating the persistence of the maladaptive impact induced by the inflammatory encounter. Thus, inflammation imprints the epigenome of ISCs in a manner that persists and affects their sensitivity to adapt to future stress or challenges.

Network modeling links kidney developmental programs and the cancer type-specificity of VHL mutations

Elucidating the molecular dependencies behind the cancer-type specificity of driver mutations may reveal new therapeutic opportunities. We hypothesized that developmental programs would impact the transduction of oncogenic signaling activated by a driver mutation and shape its cancer-type specificity. Therefore, we designed a computational analysis framework by combining single-cell gene expression profiles during fetal organ development, latent factor discovery, and information theory-based differential network analysis to systematically identify transcription factors that selectively respond to driver mutations under the influence of organ-specific developmental programs. After applying this approach to VHL mutations, which are highly specific to clear cell renal cell carcinoma (ccRCC), we revealed important regulators downstream of VHL mutations in ccRCC and used their activities to cluster patients with ccRCC into three subtypes. This classification revealed a more significant difference in prognosis than the previous mRNA profile-based method and was validated in an independent cohort. Moreover, we found that EP300, a key epigenetic factor maintaining the regulatory network of the subtype with the worst prognosis, can be targeted by a small inhibitor, suggesting a potential treatment option for a subset of patients with ccRCC. This work demonstrated an intimate relationship between organ development and oncogenesis from the perspective of systems biology, and the method can be generalized to study the influence of other biological processes on cancer driver mutations.

A scalable approach to topic modelling in single-cell data by approximate pseudobulk projection

Probabilistic topic modelling has become essential in many types of single-cell data analysis. Based on probabilistic topic assignments in each cell, we identify the latent representation of cellular states. A dictionary matrix, consisting of topic-specific gene frequency vectors, provides interpretable bases to be compared with known cell type-specific marker genes and other pathway annotations. However, fitting a topic model on a large number of cells would require heavy computational resources-specialized computing units, computing time and memory. Here, we present a scalable approximation method customized for single-cell RNA-seq data analysis, termed ASAP, short for Annotating a Single-cell data matrix by Approximate Pseudobulk estimation. Our approach is more accurate than existing methods but requires orders of magnitude less computing time, leaving much lower memory consumption. We also show that our approach is widely applicable for atlas-scale data analysis; our method seamlessly integrates single-cell and bulk data in joint analysis, not requiring additional preprocessing or feature selection steps.

Long-term alterations in lung epithelial cells after EL-RSV infection exacerbate allergic responses through IL-1β-induced pathways

Early-life (EL) respiratory infections increase pulmonary disease risk, especially EL-Respiratory Syncytial Virus (EL-RSV) infections linked to asthma. Mechanisms underlying asthma predisposition remain unknown. In this study, we examined the long-term effects on the lung after four weeks post EL-RSV infection. We identified alterations in the lung epithelial cell, with a rise in the percentage of alveolar type 2 epithelial cells (AT2) and a decreased percentage of cells in the AT1 and AT2-AT1 subclusters, as well as upregulation of Bmp2 and Krt8 genes that are associated with AT2-AT1 trans-differentiation, suggesting potential defects in lung repair processes. We identified persistent upregulation of asthma-associated genes, including Il33. EL-RSV-infected mice allergen-challenged exhibited exacerbated allergic response, with significant upregulation of Il33 in the lung and AT2 cells. Similar long-term effects were observed in mice exposed to EL-IL-1β. Notably, treatment with IL-1ra during acute EL-RSV infection mitigated the long-term alveolar alterations and the allergen-exacerbated response. Finally, epigenetic modifications in the promoter of the Il33 gene were detected in AT2 cells harvested from EL-RSV and EL-IL1β groups, suggesting that long-term alteration in the epithelium after RSV infection is dependent on the IL-1β pathway. This study provides insight into the molecular mechanisms of asthma predisposition after RSV infection.

Inducible pluripotent stem cells to study human mast cell trajectories

Mast cells (MCs) are derived from CD34+ hematopoietic progenitors, consist of different subtypes, and are involved in several inflammatory conditions. However, our understanding of human MC developmental trajectories and subtypes has been limited by a scarcity of suitable cellular model systems. Herein, we developed an in vitro model of human MC differentiation from induced pluripotent stem cells (iPSC) to study human MC differentiation trajectories. Flow cytometry characterization of hemopoietic cells derived from the myeloid cells-forming complex (MCFC) revealed an initial increase in Lin- CD34+ hematopoietic progenitors within Weeks 1-3, followed by an increase in CD34- CD45RA- SSClow and SSChigh hematopoietic cells. The Lin- CD34+ hematopoietic progenitors consisted of SSClow CD45RA- CD123± c-Kit+ FcεRI+ populations that were β7-integrinhigh CD203c+ and β7-integrinhigh CD203c- cells consistent with CMPFcεRI+ cells. Flow cytometry and cytologic analyses of the CD34- Lin- (SSClow) population revealed hypogranular cell populations, predominantly characterized by CD45RA- CD123± c-Kit+ FcεRI- β7-integrinlow and CD45RA- CD123± c-Kit- FcεRI+ β7-integrinMid cells. Analyses of hypergranular SSChigh cells identified Lin- CD34- CD45RA- c-Kit+ FcεRI- and Lin- CD34- CD45RA- c-Kit+ FcεRI+ cells. scRNA-seq analysis of the cells harvested at week 4 of the MCFC culture revealed the presence of monocyte and granulocyte progenitors (n = 547 cells, 26.7 %), Erythrocyte / unknown (n = 85, 4.1 %), neutrophils / myelocytes (n = 211 cells, 10.2 %), mast cell progenitor 1 (n = 599, 29.1 %), mast cell progenitor 2 (n = 152, 7.4 %), committed mast cell precursor (n = 113, 5.5 %), and MCs (n = 353, 17.1 %). In silico analyses of the MC precursor and mature MC populations revealed transcriptionally distinct MC precursor subtype and mature MC states (CMA1+ and CMA1- subtypes). Culturing MC precursor populations in MC maturation media (mast cell media II) led to homogenous mature MC populations as evidenced by high expression of high-affinity IgE receptor, metachromatic granules, presence of MC granule proteins (Tryptase and Chymase) and activation following substance P stimulation and FcεRI crosslinking. This human iPSC-based approach generates MC precursors and phenotypically mature and functional MC populations. This system will be a useful model to generate human MC populations and broaden our understanding of MC biology and transcriptional regulation of MC differentiation trajectories.

Single-cell RNA sequencing reveals the MIF/ACKR3 receptor-ligand interaction between neutrophils and nucleus pulposus cells in intervertebral disc degeneration

OBJECTIVES

To unravel the heterogeneity and function of microenvironmental neutrophils during intervertebral disc degeneration (IDD).

METHODS

Single-cell RNA sequencing (scRNA-seq) was utilized to dissect the cellular landscape of neutrophils in intervertebral disc (IVD) tissues and their crosstalk with nucleus pulposus cells (NPCs). The expression levels of macrophage migration inhibitory factor (MIF) and ACKR3 in IVD tissues were detected. The MIF/ACKR3 axis was identified and its effects on IDD were investigated in vitro and in vivo.

RESULTS

We sequenced here 71520 single cells from 5 control and 9 degenerated IVD samples using scRNA-seq. We identified a unique cluster of neutrophils abundant in degenerated IVD tissues that highly expressed MIF and was functionally enriched in extracellular matrix organization (ECMO). Cell-to-cell communication analyses showed that this ECMO-neutrophil subpopulation was closely interacted with an effector NPCs subtype, which displayed high expression of ACKR3. Further analyses revealed that MIF was positively correlated with ACKR3 and functioned via directly binding to ACKR3 on effector NPCs. MIF inhibition attenuated degenerative changes of NPCs and extracellular matrix, which could be partially reversed by ACKR3 overexpression. Clinically, a significant correlation of high MIF/ACKR3 expression with advanced IDD grade was observed. Furthermore, we also found a positive association between MIF+ ECMO-neutrophil counts and ACKR3+ effector NPCs density as well as higher expression of the MIF/ACKR3 signaling in areas where these two cell types were neighbors.

CONCLUSIONS

These data suggest that ECMO-neutrophil promotes IDD progression by their communication with NPCs via the MIF/ACKR3 axis, which may shed light on therapeutic strategies.

Obtaining source material for cellular agriculture

Cellular Agriculture (CellAg) is an attractive concept for innovative technology with the intent to provide food and nutrition complementary to existing supply streams. The past decade has seen considerable progress in the field with advancement of cellular technology that delivers the initial building blocks for meaningful implementation. The availability of natural cell-based material that can serve as nutrient-filled source for human consumption at low cost is a critical challenge for the emerging cellular agriculture industry. Therefore, here the isolation of bovine myofibroblasts of the Black Angus breed has been pursued and accomplished together with its characterisation by using RNA sequencing and proteomics through western blotting. To transition CellAg from a concept to a game changing technology for the industry, multiple challenges need to be overcome. The field requires powerful initial material, i.e., dedicated cells that can proliferate and differentiate robustly at scale. The methodology described allows for the production of healthy cells, which have been unequivocally characterized as clonal representatives of a stable myofibroblast cell line using transcriptomics and proteomics validation. Stringent and rigorous live cell monitoring of a nascent cell line derived from healthy muscle tissue allowed for stable cell growth. In this research article, a simple and precise methodology is presented for creating a bovine myofibroblast cell line (Bov.mia). Our work puts forward a low-tech use of materials and expertise that is devoid of transgenic approaches, thus creating a reliable approach for lab-scale research.

Functional gene signature offers a powerful tool for characterizing clinicopathological features and depicting tumor immune microenvironment of colorectal cancer

BACKGROUND

Colorectal cancer, a prevalent malignancy worldwide, poses a significant challenge due to the lack of effective prognostic tools. In this study, we aimed to develop a functional gene signature to stratify colorectal cancer patients into different groups with distinct characteristics, which will greatly facilitate disease prediction.

RESULTS

Patients were stratified into high- and low-risk groups using a prediction model built based on the functional gene signature. This innovative approach not only predicts clinicopathological features but also reveals tumor immune microenvironment types and responses to immunotherapy. The study reveals that patients in the high-risk group exhibit poorer pathological features, including invasion depth, lymph node metastasis, and distant metastasis, as well as unfavorable survival outcomes in terms of overall survival and disease-free survival. The underlying mechanisms for these observations are attributed to upregulated tumor-related signaling pathways, increased infiltration of pro-tumor immune cells, decreased infiltration of anti-tumor immune cells, and a lower tumor mutation burden. Consequently, patients in the high-risk group exhibit a diminished response to immunotherapy. Furthermore, the high-risk group demonstrates enrichment in extracellular matrix-related functions and significant infiltration of cancer-associated fibroblasts (CAFs). Single-cell transcriptional data analysis identifies CAFs as the primary cellular type expressing hub genes, namely ACTA2, TPM2, MYL9, and TAGLN. This finding is further validated through multiple approaches, including multiplex immunohistochemistry (mIHC), polymerase chain reaction (PCR), and western blot analysis. Notably, TPM2 emerges as a potential biomarker for identifying CAFs in colorectal cancer, distinguishing them from both colorectal cancer cell lines and normal colon epithelial cell lines. Co-culture of CAFs and colorectal cancer cells revealed that CAFs could enhance the tumorigenic biofunctions of cancer cells indirectly, which could be partially inhibited by knocking down CAF original TPM2 expression.

CONCLUSIONS

This study introduces a functional gene signature that effectively and reliably predicts clinicopathological features and the tumor immune microenvironment in colorectal cancer. Moreover, the identification of TPM2 as a potential biomarker for CAFs holds promising implications for future research and clinical applications in the field of colorectal cancer.

Single-cell genomics details the maturation block in BCP-ALL and identifies therapeutic vulnerabilities in DUX4-r cases

ABSTRACT

B-cell progenitor acute lymphoblastic leukemia (BCP-ALL) is the most common childhood malignancy and is driven by multiple genetic alterations that cause maturation arrest and accumulation of abnormal progenitor B cells. Current treatment protocols with chemotherapy have led to favorable outcomes but are associated with significant toxicity and risk of side effects, highlighting the necessity for highly effective, less toxic, targeted drugs, even in subtypes with a favorable outcome. Here, we used multimodal single-cell sequencing to delineate the transcriptional, epigenetic, and immunophenotypic characteristics of 23 childhood BCP-ALLs belonging to the BCR::ABL1+, ETV6::RUNX1+, high hyperdiploid, and recently discovered DUX4-rearranged (DUX4-r) subtypes. Projection of the ALL cells along the normal hematopoietic differentiation axis revealed a diversity in the maturation pattern between the different BCP-ALL subtypes. Although the BCR::ABL1+, ETV6::RUNX1+, and high hyperdiploidy cells mainly showed similarities to normal pro-B cells, DUX4-r ALL cells also displayed transcriptional signatures resembling mature B cells. Focusing on the DUX4-r subtype, we found that the blast population displayed not only multilineage priming toward nonhematopoietic cells, myeloid, and T-cell lineages, but also an activation of phosphatidylinositol 3-kinase (PI3K)/AKT signaling that sensitized the cells to PI3K inhibition in vivo. Given the multilineage priming of DUX4-r blasts with aberrant expression of myeloid marker CD371 (CLL-1), we generated chimeric antigen receptor T cells, which effectively eliminated DUX4-r ALL cells in vivo. These results provide a detailed characterization of BCP-ALL at the single-cell level and reveal therapeutic vulnerabilities in the DUX4-r subtype, with implications for the understanding of ALL biology and new therapeutic strategies.

Relevance of the regulation of the brain-placental axis to the nocturnal bottleneck of mammals

INTRODUCTION

Evolutionary theory suggests that the ancestors of all placental animals were nocturnal. Visual perceptive function of mammalian brain has evolved extensively, but nearly 70 % of today's mammals are still nocturnal. While placental influence on brain development is known, if placenta plays a role in the visual perceptive function of mammalian brain remains untested. The present study aims to test this hypothesis.

METHODS

In this study, single-nuclei RNA sequencing was performed to identify genes expressed in the pig placenta and fetal brain, and then compared with the orthologous genes expressed in the placenta and fetal brain cells of mouse. Differential gene expression analysis was performed to identify placental genes regulated differentially between nocturnal and diurnal animals. Phylogenetic modeling was performed to test correlated evolution between placenta type, and the nocturnal or diurnal activity among different mammals.

RESULTS

The results showed that genes differentially regulated in the fetal brain were related to visual perception whereas the placental genes were related to the nocturnal or diurnal activity in placental animals. Phylogenetic modeling of these genes in thirty-four diverse mammalian species showed evidence for evolutionary link between placenta and the nocturnal/diurnal activity in animals.

DISCUSSION

The findings of this study suggest that the placenta plays a role in the evolution of visual perceptive function of brain to shape the nocturnal or diurnal activity of placental animals.

scMMO-atlas: a single cell multimodal omics atlas and portal for exploring fine cell heterogeneity and cell dynamics

Single-cell multimodal sequencing parallelly captures multiple modalities of the same cell, providing unparalleled insights into cell heterogeneity and cell dynamics. For example, joint profiling of chromatin accessibility and transcriptome from the same single cell (scATAC + RNA) identified new cell subsets within the well-defined clusters. However, lack of single-cell multimodal omics (scMMO) database has led to data fragmentation, seriously hindering access, utilization and mining of scMMO data. Here, we constructed a scMMO atlas by collecting and integrating various scMMO data, then constructed scMMO database and portal called scMMO-atlas (https://www.biosino.org/scMMO-atlas/). scMMO-atlas includes scATAC + RNA (ISSAAS-seq, SNARE-seq, paired-seq, sci-CAR, scCARE-seq, 10X Multiome and so on), scRNA + protein, scATAC + protein and scTri-modal omics data, with 3 168 824 cells from 27 cell tissues/organs. scMMO-atlas offered an interactive portal for visualization and featured analysis for each modality and the integrated data. Integrated analysis of scATAC + RNA data of mouse cerebral cortex in scMMO-atlas identified more cell subsets compared with unimodal omics data. Among these new cell subsets, there is an early astrocyte subset highly expressed Grm3, called Astro-Grm3. Furthermore, we identified Ex-L6-Tle4-Nrf1, a progenitor of Ex-L6-Tle4, indicating the statistical power provided by the big data in scMMO-atlas. In summary, scMMO-atlas offers cell atlas, database and portal to facilitate data utilization and biological insight.

nsDCC: dual-level contrastive clustering with nonuniform sampling for scRNA-seq data analysis

Dimensionality reduction and clustering are crucial tasks in single-cell RNA sequencing (scRNA-seq) data analysis, treated independently in the current process, hindering their mutual benefits. The latest methods jointly optimize these tasks through deep clustering. However, contrastive learning, with powerful representation capability, can bridge the gap that common deep clustering methods face, which requires pre-defined cluster centers. Therefore, a dual-level contrastive clustering method with nonuniform sampling (nsDCC) is proposed for scRNA-seq data analysis. Dual-level contrastive clustering, which combines instance-level contrast and cluster-level contrast, jointly optimizes dimensionality reduction and clustering. Multi-positive contrastive learning and unit matrix constraint are introduced in instance- and cluster-level contrast, respectively. Furthermore, the attention mechanism is introduced to capture inter-cellular information, which is beneficial for clustering. The nsDCC focuses on important samples at category boundaries and in minority categories by the proposed nearest boundary sparsest density weight assignment algorithm, making it capable of capturing comprehensive characteristics against imbalanced datasets. Experimental results show that nsDCC outperforms the six other state-of-the-art methods on both real and simulated scRNA-seq data, validating its performance on dimensionality reduction and clustering of scRNA-seq data, especially for imbalanced data. Simulation experiments demonstrate that nsDCC is insensitive to "dropout events" in scRNA-seq. Finally, cluster differential expressed gene analysis confirms the meaningfulness of results from nsDCC. In summary, nsDCC is a new way of analyzing and understanding scRNA-seq data.

Single-cell multi-omics identify novel regulators required for osteoclastogenesis during aging

Age-related osteoporosis manifests as a complex pathology that disrupts bone homeostasis and elevates fracture risk, yet the mechanisms facilitating age-related shifts in bone marrow macrophages/osteoclasts (BMMs/OCs) lineage are not fully understood. To decipher these mechanisms, we conducted an investigation into the determinants controlling BMMs/OCs differentiation. We performed single-cell multi-omics profiling on bone marrow samples from mice of different ages (1, 6, and 20 months) to gain a holistic understanding of cellular changes across time. Our analysis revealed that aging significantly instigates OC differentiation. Importantly, we identified Cebpd as a vital gene for osteoclastogenesis and bone resorption during the aging process. Counterbalancing the effects of Cebpd, we found Irf8, Sox4, and Klf4 to play crucial roles. By thoroughly examining the cellular dynamics underpinning bone aging, our study unveils novel insights into the mechanisms of age-related osteoporosis and presents potential therapeutic targets for future exploration.

Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points

Alzheimer's disease (AD) is the most common form of dementia and is characterized by progressive memory loss and cognitive decline, affecting behavior, speech, and motor abilities. The neuropathology of AD includes the formation of extracellular amyloid-β plaque and intracellular neurofibrillary tangles of phosphorylated tau, along with neuronal loss. While neuronal loss is an AD hallmark, cell-cell communication between neuronal and non-neuronal cell populations maintains neuronal health and brain homeostasis. To study changes in cellcell communication during disease progression, we performed snRNA-sequencing of the hippocampus from female 3xTg-AD and wild-type littermates at 6 and 12 months. We inferred differential cell-cell communication between 3xTg-AD and wild-type mice across time points and between senders (astrocytes, microglia, oligodendrocytes, and OPCs) and receivers (excitatory and inhibitory neurons) of interest. We also assessed the downstream effects of altered glia-neuron communication using pseudobulk differential gene expression, functional enrichment, and gene regulatory analyses. We found that glia-neuron communication is increasingly dysregulated in 12-month 3xTg-AD mice. We also identified 23 AD-associated ligand-receptor pairs that are upregulated in the 12-month-old 3xTg-AD hippocampus. Our results suggest increased AD association of interactions originating from microglia. Signaling mediators were not significantly differentially expressed but showed altered gene regulation and TF activity. Our findings indicate that altered glia-neuron communication is increasingly dysregulated and affects the gene regulatory mechanisms in neurons of 12-month-old 3xTg-AD mice.

Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era

As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.

BCAA-producing Clostridium symbiosum promotes colorectal tumorigenesis through the modulation of host cholesterol metabolism

Identification of potential bacterial players in colorectal tumorigenesis has been a focus of intense research. Herein, we find that Clostridium symbiosum (C. symbiosum) is selectively enriched in tumor tissues of patients with colorectal cancer (CRC) and associated with higher colorectal adenoma recurrence after endoscopic polypectomy. The tumorigenic effect of C. symbiosum is observed in multiple murine models. Single-cell transcriptome profiling along with functional assays demonstrates that C. symbiosum promotes the proliferation of colonic stem cells and enhances cancer stemness. Mechanistically, C. symbiosum intensifies cellular cholesterol synthesis by producing branched-chain amino acids (BCAAs), which sequentially activates Sonic hedgehog signaling. Low dietary BCAA intake or blockade of cholesterol synthesis by statins could partially abrogate the C. symbiosum-induced cell proliferation in vivo and in vitro. Collectively, we reveal C. symbiosum as a bacterial driver of colorectal tumorigenesis, thus identifying a potential target in CRC prediction, prevention, and treatment.

A natural language processing system for the efficient extraction of cell markers

Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal tool for exploring cellular landscapes across diverse species and tissues. Precise annotation of cell types is essential for understanding these landscapes, relying heavily on empirical knowledge and curated cell marker databases. In this study, we introduce MarkerGeneBERT, a natural language processing (NLP) system designed to extract critical information from the literature regarding species, tissues, cell types, and cell marker genes in the context of single-cell sequencing studies. Leveraging MarkerGeneBERT, we systematically parsed full-text articles from 3702 single-cell sequencing-related studies, yielding a comprehensive collection of 7901 cell markers representing 1606 cell types across 425 human tissues/subtissues, and 8223 cell markers representing 1674 cell types across 482 mouse tissues/subtissues. Comparative analysis against manually curated databases demonstrated that our approach achieved 76% completeness and 75% accuracy, while also unveiling 89 cell types and 183 marker genes absent from existing databases. Furthermore, we successfully applied the compiled brain tissue marker gene list from MarkerGeneBERT to annotate scRNA-seq data, yielding results consistent with original studies. Conclusions: Our findings underscore the efficacy of NLP-based methods in expediting and augmenting the annotation and interpretation of scRNA-seq data, providing a systematic demonstration of the transformative potential of this approach. The 27323 manual reviewed sentences for training MarkerGeneBERT and the source code are hosted at https://github.com/chengpeng1116/MarkerGeneBERT .

Causal effects of systemic inflammatory proteins on Guillain-Barre Syndrome: insights from genome-wide Mendelian randomization, single-cell RNA sequencing analysis, and network pharmacology

Background

Evidence from observational studies indicates that inflammatory proteins play a vital role in Guillain-Barre Syndrome (GBS). Nevertheless, it is unclear how circulating inflammatory proteins are causally associated with GBS. Herein, we conducted a two-sample Mendelian randomization (MR) analysis to systematically explore the causal links of genetically determined systemic inflammatory proteins on GBS.

Methods

A total of 8,293 participants of European ancestry were included in a genome-wide association study of 41 inflammatory proteins as instrumental variables. Five MR approaches, encompassing inverse-variance weighted, weighted median, MR-Egger, simple model, and weighted model were employed to explore the causal links between inflammatory proteins and GBS. MR-Egger regression was utilized to explore the pleiotropy. Cochran's Q statistic was implemented to quantify the heterogeneity. Furthermore, we performed single-cell RNA sequencing analysis and predicted potential drug targets through molecular docking technology.

Results

By applying MR analysis, four inflammatory proteins causally associated with GBS were identified, encompassing IFN-γ (OR:1.96, 95%CI: 1.02-3.78, PIVW=0.045), IL-7 (OR:1.86, 95%CI: 1.07-3.23, PIVW=0.029), SCGF-β (OR:1.56, 95%CI: 1.11-2.19, PIVW=0.011), and Eotaxin (OR:1.99, 95%CI: 1.01-3.90, PIVW=0.046). The sensitivity analysis revealed no evidence of pleiotropy or heterogeneity. Additionally, significant genes were found through single-cell RNA sequencing analysis and several anti-inflammatory or neuroprotective small molecular compounds were identified by utilizing molecular docking technology.

Conclusions

Our MR analysis suggested that IFN-γ, IL-7, SCGF-β, and Eotaxin were causally linked to the occurrence and development of GBS. These findings elucidated potential causal associations and highlighted the significance of these inflammatory proteins in the pathogenesis and prospective therapeutic targets for GBS.

Glioblastoma cells increase expression of notch signaling and synaptic genes within infiltrated brain tissue

Glioblastoma remains one of the deadliest brain malignancies. First-line therapy consists of maximal surgical tumor resection, accompanied by chemotherapy and radiotherapy. Malignant cells escape surgical resection by migrating into the surrounding healthy brain tissue, where they give rise to the recurrent tumor. Based on gene expression, tumor cores can be subtyped into mesenchymal, proneural, and classical tumors, each being associated with differences in genetic alterations and cellular composition. In contrast, the adjacent brain parenchyma where infiltrating malignant cells escape surgical resection is less characterized in patients. Using spatial transcriptomics (n = 11), we show that malignant cells within proneural or mesenchymal tumor cores display spatially organized differences in gene expression, although such differences decrease within the infiltrated brain tissue. Malignant cells residing in infiltrated brain tissue have increased expression of genes related to neurodevelopmental pathways and glial cell differentiation. Our findings provide an updated view of the spatial landscape of glioblastomas and further our understanding of the malignant cells that infiltrate the healthy brain, providing new avenues for the targeted therapy of these cells after surgical resection.

Progress in toxicogenomics to protect human health

Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose-response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment.

scRNA-Explorer: An End-user Online Tool for Single Cell RNA-seq Data Analysis Featuring Gene Correlation and Data Filtering

In the majority of downstream analysis pipelines for single-cell RNA sequencing (scRNA-seq), techniques like dimensionality reduction and feature selection are employed to address the problem of high-dimensional nature of the data. These approaches involve mapping the data onto a lower-dimensional space, eliminating less informative genes, and pinpointing the most pertinent features. This process ultimately leads to a reduction in the number of dimensions used for downstream analysis, which in turn speeds up the computation of large-scale scRNA-seq data. Most approaches are directed to isolate from biological background the genes characterizing different cells and or the condition under study by establishing lists of differentially expressed or coexpressed genes. Herein, we present scRNA-Explorer an open-source online tool for simplified and rapid scRNA-seq analysis designed with the end user in mind. scRNA-Explorer utilizes: (i) Filtering out uninformative cells in an interactive manner via a web interface, (ii) Gene correlation analysis coupled with an extra step of evaluating the biological importance of these correlations, and (iii) Gene enrichment analysis of correlated genes in order to find gene implication in specific functions. We developed a pipeline to address the above problem. The scRNA-Explorer pipeline allows users to interrogate in an interactive manner scRNA-sequencing data sets to explore via gene expression correlations possible function(s) of a gene of interest. scRNA-Explorer can be accessed at https://bioinformatics.med.uoc.gr/shinyapps/app/scrnaexplorer.

Dysregulation of cholesterol homeostasis is an early signal of β-cell proteotoxicity characteristic of type 2 diabetes

Type 2 diabetes (T2D) is a common metabolic disease due to insufficient insulin secretion by pancreatic β-cells in the context of insulin resistance. Islet molecular pathology reveals a role for protein misfolding in β-cell dysfunction and loss with islet amyloid derived from islet amyloid polypeptide (IAPP), a protein coexpressed and cosecreted with insulin. The most toxic form of misfolded IAPP is intracellular membrane disruptive toxic oligomers present in β-cells in T2D and in β-cells of mice transgenic for human IAPP (hIAPP). Prior work revealed a high degree of overlap of transcriptional changes in islets from T2D and prediabetic 9- to 10-wk-old mice transgenic for hIAPP with most changes being pro-survival adaptations and therefore of limited therapeutic guidance. Here, we investigated islets from hIAPP transgenic mice at an earlier age (6 wk) to screen for potential mediators of hIAPP toxicity that precede predominance of pro-survival signaling. We identified early suppression of cholesterol synthesis and trafficking along with aberrant intra-β-cell cholesterol and lipid deposits and impaired cholesterol trafficking to cell membranes. These findings align with comparable lipid deposits present in β-cells in T2D and increased vulnerability to develop T2D in individuals taking medications that suppress cholesterol synthesis.NEW & NOTEWORTHY β-Cell failure in type 2 diabetes (T2D) is characterized by β-cell misfolded protein stress due to the formation of toxic oligomers of islet amyloid polypeptide (IAPP). Most transcriptional changes in islets in T2D are pro-survival adaptations consistent with the slow progression of β-cell loss. In the present study, investigation of the islet transcriptional signatures in a mouse model of T2D expressing human IAPP revealed decreased cholesterol synthesis and trafficking as a plausible early mediator of IAPP toxicity.

Proteome-Wide Multicenter Mendelian Randomization Analysis to Identify Novel Therapeutic Targets for Lung Cancer

INTRODUCTION

Lung cancer (LC) remains a leading cause of cancer mortality worldwide, underscoring the urgent need for novel therapeutic targets. The integration of Mendelian randomization (MR) with proteomic data presents a novel approach to identifying potential targets for LC treatment.

METHODS

This study utilized a proteome-wide MR analysis, leveraging publicly available data from genome-wide association studies (GWAS) and protein quantitative trait loci (pQTL) studies. We analyzed genetic association data for LC from the TRICL-ILCCO Consortium and proteomic data from the Decode cohort. The MR framework was employed to estimate the causal effects of specific proteins on LC risk, supplemented by external validation, co-localization analyses, and exploration of protein-protein interaction (PPI) networks.

RESULTS

Our analysis identified five proteins (TFPI, ICAM5, SFTPB, COL6A3, EPHB1) with significant associations to LC risk. External validation confirmed the potential therapeutic relevance of ICAM5 and SFTPB. Co-localization analyses and PPI network exploration provided further insights into the biological pathways involved and their potential mechanistic roles in LC pathogenesis.

CONCLUSION

The study highlights the power of integrating genomic and proteomic data through MR analysis to uncover novel therapeutic targets for lung cancer. The identified proteins, particularly ICAM5 and SFTPB, offer promising directions for future research and development of targeted therapies, demonstrating the potential to advance personalized medicine in lung cancer treatment.

Association Between COVID-19 and Neurological Diseases: Evidence from Large-Scale Mendelian Randomization Analysis and Single-Cell RNA Sequencing Analysis

Observational studies have suggested that SARS-CoV-2 infection increases the risk of neurological diseases, but it remains unclear whether the association is causal. The present study aims to evaluate the causal relationships between SARS-CoV-2 infections and neurological diseases and analyzes the potential routes of SARS-CoV-2 entry at the cellular level. We performed Mendelian randomization (MR) analysis with CAUSE method to investigate causal relationship of SARS-CoV-2 infections with neurological diseases. Then, we conducted single-cell RNA sequencing (scRNA-seq) analysis to obtain evidence of potential neuroinvasion routes by measuring SARS-CoV-2 receptor expression in specific cell subtypes. Fast gene set enrichment analysis (fGSEA) was further performed to assess the pathogenesis of related diseases. The results showed that the COVID-19 is causally associated with manic (delta_elpd, - 0.1300, Z-score: - 2.4; P = 0.0082) and epilepsy (delta_elpd: - 2.20, Z-score: - 1.80; P = 0.038). However, no significant effects were observed for COVID-19 on other traits. Moreover, there are 23 cell subtypes identified through the scRNA-seq transcriptomics data of epilepsy, and SARS-CoV-2 receptor TTYH2 was found to be specifically expressed in oligodendrocyte and astrocyte cell subtypes. Furthermore, fGSEA analysis showed that the cell subtypes with receptor-specific expression was related to methylation of lysine 27 on histone H3 (H3K27ME3), neuronal system, aging brain, neurogenesis, and neuron projection. In summary, this study shows causal links between SARS-CoV-2 infections and neurological disorders such as epilepsy and manic, supported by MR and scRNA-seq analysis. These results should be considered in further studies and public health measures on COVID-19 and neurological diseases.

Altered hepatic metabolic landscape and insulin sensitivity in response to pulmonary tuberculosis

Chronic inflammation triggers development of metabolic disease, and pulmonary tuberculosis (TB) generates chronic systemic inflammation. Whether TB induced-inflammation impacts metabolic organs and leads to metabolic disorder is ill defined. The liver is the master regulator of metabolism and to determine the impact of pulmonary TB on this organ we undertook an unbiased mRNA and protein analyses of the liver in mice with TB and reanalysed published data on human disease. Pulmonary TB led to upregulation of genes in the liver related to immune signalling and downregulation of genes encoding metabolic processes. In liver, IFN signalling pathway genes were upregulated and this was reflected in increased biochemical evidence of IFN signalling, including nuclear location of phosphorylated Stat-1 in hepatocytes. The liver also exhibited reduced expression of genes encoding the gluconeogenesis rate-limiting enzymes Pck1 and G6pc. Phosphorylation of CREB, a transcription factor controlling gluconeogenesis was drastically reduced in the livers of mice with pulmonary TB as was phosphorylation of other glucose metabolism-related kinases, including GSK3a, AMPK, and p42. In support of the upregulated IFN signalling being linked to the downregulated metabolic functions in the liver, we found suppression of gluconeogenic gene expression and reduced CREB phosphorylation in hepatocyte cell lines treated with interferons. The impact of reduced gluconeogenic gene expression in the liver was seen when infected mice were less able to convert pyruvate, a gluconeogenesis substrate, to the same extent as uninfected mice. Infected mice also showed evidence of reduced systemic and hepatic insulin sensitivity. Similarly, in humans with TB, we found that changes in a metabolite-based signature of insulin resistance correlates temporally with successful treatment of active TB and with progression to active TB following exposure. These data support the hypothesis that TB drives interferon-mediated alteration of hepatic metabolism resulting in reduced gluconeogenesis and drives systemic reduction of insulin sensitivity.

PHF6 suppresses self-renewal of leukemic stem cells in AML

Acute myeloid leukemia is characterized by uncontrolled proliferation of self-renewing myeloid progenitors accompanied by a differentiation arrest. PHF6 is a chromatin-binding protein mutated in myeloid leukemias, and its isolated loss increases mouse HSC self-renewal without malignant transformation. We report here that Phf6 knockout increases the aggressiveness of Hoxa9-driven AML over serial transplantation, and increases the frequency of leukemia initiating cells. We define the in vivo hierarchy of Hoxa9-driven AML and identify a population that we term the "LIC-e" (leukemia initiating cells enriched) population. We find that Phf6 loss expands the LIC-e population and skews its transcriptome to a more stem-like state; concordant transcriptome shifts are also observed on PHF6 knockout in a human AML cell line and in PHF6 mutant patient samples from the BEAT AML dataset. We demonstrate that LIC-e accumulation in Phf6 knockout AML occurs not due to effects on cell cycle or apoptosis, but due to an increase in the fraction of its progeny that retain LIC-e identity. Our work indicates that Phf6 loss increases AML self-renewal through context-specific effects on leukemia stem cells.

Small data methods in omics: the power of one

Over the last decade, biology has begun utilizing 'big data' approaches, resulting in large, comprehensive atlases in modalities ranging from transcriptomics to neural connectomics. However, these approaches must be complemented and integrated with 'small data' approaches to efficiently utilize data from individual labs. Integration of smaller datasets with major reference atlases is critical to provide context to individual experiments, and approaches toward integration of large and small data have been a major focus in many fields in recent years. Here we discuss progress in integration of small data with consortium-sized atlases across multiple modalities, and its potential applications. We then examine promising future directions for utilizing the power of small data to maximize the information garnered from small-scale experiments. We envision that, in the near future, international consortia comprising many laboratories will work together to collaboratively build reference atlases and foundation models using small data methods.

scCAD: Cluster decomposition-based anomaly detection for rare cell identification in single-cell expression data

Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for characterizing cellular landscapes within complex tissues. Large-scale single-cell transcriptomics holds great potential for identifying rare cell types critical to the pathogenesis of diseases and biological processes. Existing methods for identifying rare cell types often rely on one-time clustering using partial or global gene expression. However, these rare cell types may be overlooked during the clustering phase, posing challenges for their accurate identification. In this paper, we propose a Cluster decomposition-based Anomaly Detection method (scCAD), which iteratively decomposes clusters based on the most differential signals in each cluster to effectively separate rare cell types and achieve accurate identification. We benchmark scCAD on 25 real-world scRNA-seq datasets, demonstrating its superior performance compared to 10 state-of-the-art methods. In-depth case studies across diverse datasets, including mouse airway, brain, intestine, human pancreas, immunology data, and clear cell renal cell carcinoma, showcase scCAD's efficiency in identifying rare cell types in complex biological scenarios. Furthermore, scCAD can correct the annotation of rare cell types and identify immune cell subtypes associated with disease, thereby offering valuable insights into disease progression.

Canine mesenteric lymph nodes (MLNs) characterization by sc-RNAseq: insights compared to human and mouse MLNs

In the human and veterinary fields, oral vaccines generate considerable interest. In dogs, these vaccines are newly developed, and understanding their mechanisms is crucial. Mesenteric lymph nodes (MLNs) and Peyer's patches (PPs) are important sites for gastrointestinal mucosal induction, yet canine MLNs lack sufficient information. To address this, we collected MLN samples from healthy dogs, performed flow cytometry to characterize immune cells, and conducted single-cell RNA sequencing (scRNA-seq) to explore subpopulations, particularly B and T lymphocytes. This effort enabled the characterization of canine MLN's main cell populations and the construction of a predictive atlas, as well as the identification of particularities of this area.

Epigenetic control of commensal induced Th2 Responses and Intestinal immunopathology

Understanding the initiation of T-helper (Th)-2 immunity is crucial for addressing allergic diseases that have been linked to the commensal microbiota. However, Th2 responses are notably absent from known host-microbiota intestinal immune circuits. Notably, the commensal protist Tritrichomonas induces a transient innate ILC2 circuit rather than a chronic Th2 circuit. Canonical Th2 responses rely on the induction of IL-4 production by innate cells. This study shows that the absence of Tet2 , a DNA demethylase, reprograms naïve T cells to autonomously produce IL-4 upon T cell receptor stimulation, bypassing the need for IL-4 from innate cells for Th2 differentiation. Loss of this checkpoint induces chronic Th2 responses to Tritrichomonas , associated with IL-25-dependent barrier dysfunction and increased susceptibility to allergic pathology in response to dietary antigens.

Sentence Summary

Regulation of cell autonomous IL-4 in T cells is critical to prevent dysregulated Th2 immunity to commensals and predisposition to allergy.

Convergent alterations in the tumor microenvironment of MYC-driven human and murine prostate cancer

How prostate cancer cells and their precursors mediate changes in the tumor microenvironment (TME) to drive prostate cancer progression is unclear, in part due to the inability to longitudinally study the disease evolution in human tissues. To overcome this limitation, we perform extensive single-cell RNA-sequencing (scRNA-seq) and molecular pathology of the comparative biology between human prostate cancer and key stages in the disease evolution of a genetically engineered mouse model (GEMM) of prostate cancer. Our studies of human tissues reveal that cancer cell-intrinsic activation of MYC signaling is a common denominator across the well-known molecular and pathological heterogeneity of human prostate cancer. Cell communication network and pathway analyses in GEMMs show that MYC oncogene-expressing neoplastic cells, directly and indirectly, reprogram the TME during carcinogenesis, leading to a convergence of cell state alterations in neighboring epithelial, immune, and fibroblast cell types that parallel key findings in human prostate cancer.

Targeting Liver Epsins Ameliorates Dyslipidemia in Atherosclerosis

Rationale

Low density cholesterol receptor (LDLR) in the liver is critical for the clearance of low-density lipoprotein cholesterol (LDL-C) in the blood. In atherogenic conditions, proprotein convertase subtilisin/kexin 9 (PCSK9) secreted by the liver, in a nonenzymatic fashion, binds to LDLR on the surface of hepatocytes, preventing its recycling and enhancing its degradation in lysosomes, resulting in reduced LDL-C clearance. Our recent studies demonstrate that epsins, a family of ubiquitin-binding endocytic adaptors, are critical regulators of atherogenicity. Given the fundamental contribution of circulating LDL-C to atherosclerosis, we hypothesize that liver epsins promote atherosclerosis by controlling LDLR endocytosis and degradation.

Objective

We will determine the role of liver epsins in promoting PCSK9-mediated LDLR degradation and hindering LDL-C clearance to propel atherosclerosis.

Methods and Results

We generated double knockout mice in which both paralogs of epsins, namely, epsin-1 and epsin-2, are specifically deleted in the liver (Liver-DKO) on an ApoE -/- background. We discovered that western diet (WD)-induced atherogenesis was greatly inhibited, along with diminished blood cholesterol and triglyceride levels. Mechanistically, using scRNA-seq analysis on cells isolated from the livers of ApoE-/- and ApoE-/- /Liver-DKO mice on WD, we found lipogenic Alb hi hepatocytes to glycogenic HNF4α hi hepatocytes transition in ApoE-/- /Liver-DKO. Subsequently, gene ontology analysis of hepatocyte-derived data revealed elevated pathways involved in LDL particle clearance and very-low-density lipoprotein (VLDL) particle clearance under WD treatment in ApoE-/- /Liver-DKO, which was coupled with diminished plasma LDL-C levels. Further analysis using the MEBOCOST algorithm revealed enhanced communication score between LDLR and cholesterol, suggesting elevated LDL-C clearance in the ApoE-/- Liver-DKO mice. In addition, we showed that loss of epsins in the liver upregulates of LDLR protein level. We further showed that epsins bind LDLR via the ubiquitin-interacting motif (UIM), and PCSK9-triggered LDLR degradation was abolished by depletion of epsins, preventing atheroma progression. Finally, our therapeutic strategy, which involved targeting liver epsins with nanoparticle-encapsulated siRNAs, was highly efficacious at inhibiting dyslipidemia and impeding atherosclerosis.

Conclusions

Liver epsins promote atherogenesis by mediating PCSK9-triggered degradation of LDLR, thus raising the circulating LDL-C levels. Targeting epsins in the liver may serve as a novel therapeutic strategy to treat atherosclerosis by suppression of PCSK9-mediated LDLR degradation.

A novel iPSC model of Bryant-Li-Bhoj neurodevelopmental syndrome demonstrates the role of histone H3.3 in neuronal differentiation and maturation

Background

Bryant-Li-Bhoj neurodevelopmental syndrome (BLBS) is neurogenetic disorder caused by variants in H3-3A and H3-3B, the two genes that encode the histone H3.3 protein. Ninety-nine percent of individuals with BLBS show developmental delay/intellectual disability, but the mechanism by which variants in H3.3 result in these phenotypes is not yet understood. As a result, only palliative interventions are available to individuals living with BLBS.

Methods

Here, we investigate how one BLBS-causative variant, H3-3B p.Leu48Arg (L48R), affects neurodevelopment using an induced pluripotent stem cell (iPSC) model differentiated to 2D neural progenitor cells (NPCs), 2D forebrain neurons (FBNs), and 3D dorsal forebrain organoids (DFBOs). We employ a multi-omic approach in the 2D models to quantify the resulting changes in gene expression and chromatin accessibility. We used immunofluorescence (IF) staining to define the identities of cells in the 3D DFBOs.

Results

In the 2D systems, we found dysregulation of both gene expression and chromatin accessibility of genes important for neuronal fate, maturation, and function in H3.3 L48R compared to control. Our work in 3D organoids corroborates these findings, demonstrating altered proportions of radial glia and mature neuronal cells.

Conclusions

These data provide the first mechanistic insights into the pathogenesis of BLBS from a human-derived model of neurodevelopment, which suggest that the L48R increases H3-3B expression, resulting in the hyper-deposition of H3.3 into the nucleosome which underlies changes in gene expression and chromatin accessibility. Functionally, this causes dysregulation of cell adhesion, neurotransmission, and the balance between excitatory and inhibitory signaling. These results are a crucial step towards preclinical development and testing of targeted therapies for this and related disorders.

Endometriotic lesions exhibit distinct metabolic signature compared to paired eutopic endometrium at the single-cell level

Current therapeutics of endometriosis focus on hormonal disruption of endometriotic lesions (ectopic endometrium, EcE). Recent findings show higher glycolysis utilization in EcE, suggesting non-hormonal strategy for disease treatment that addresses cellular metabolism. Identifying metabolically altered cell types in EcE is important for targeted metabolic drug therapy without affecting eutopic endometrium (EuE). Here, using single-cell RNA-sequencing, we examine twelve metabolic pathways in paired samples of EuE and EcE from women with confirmed endometriosis. We detect nine major cell types in both EuE and EcE. Metabolic pathways are most differentially regulated in perivascular, stromal, and endothelial cells, with the highest changes in AMPK signaling, HIF-1 signaling, glutathione metabolism, oxidative phosphorylation, and glycolysis. We identify transcriptomic co-activation of glycolytic and oxidative metabolism in perivascular and stromal cells of EcE, indicating a critical role of metabolic reprogramming in maintaining endometriotic lesion growth. Perivascular cells, involved in endometrial stroma repair and angiogenesis, may be potential targets for non-hormonal treatment of endometriosis.

Regulation of Bacteroides acidifaciens by the aryl hydrocarbon receptor in IL-22-producing immune cells has sex-dependent consequential impact on colitis

Introduction

Colitis is an inflammatory bowel disease (IBD) characterized by immune cell dysregulation and alterations in the gut microbiome. In our previous report, we showed a natural product in cruciferous vegetables and ligand of the aryl hydrocarbon receptor (AhR), indole-3-carbinol (I3C), was able to reduce colitis-induced disease severity and microbial dysbiosis in an interleukin-22 (IL-22) dependent manner.

Methods

In the current study, we performed single-cell RNA sequencing (scRNAseq) from colonocytes during colitis induction and supplementation with I3C and show how this treatment alters expression of genes involved in IL-22 signaling. To further define the role of IL-22 signaling in I3C-mediated protection during colitis and disease-associated microbial dysbiosis, we generated mice with AhR deficiency in RAR-related orphan receptor c (Rorc)-expressing cells (AhR ΔRorc ) which depletes this receptor in immune cells involved in production of IL-22. Colitis was induced in wildtype (WT), AhR ΔRorc , and littermate (LM) mice with or without I3C treatment.

Results

Results showed AhR ΔRorc mice lost the efficacy effects of I3C treatment which correlated with a loss of ability to increase IL-22 by innate lymphoid type 3 (ILC3s), not T helper 22 (Th22) cells. 16S rRNA microbiome profiling studies showed AhR ΔRorc mice were unable to regulate disease-associated increases in Bacteroides, which differed between males and females. Lastly, inoculation with a specific disease-associated Bacteroides species, Bacteroides acidifaciens (B. acidifaciens), was shown to exacerbate colitis in females, but not males.

Discussion

Collectively, this report highlights the cell and sex-specific role of AhR in regulating microbes that can impact colitis disease.

Functional mapping of epigenetic regulators uncovers coordinated tumor suppression by the HBO1 and MLL1 complexes

Epigenetic dysregulation is widespread in cancer. However, the specific epigenetic regulators and the processes they control to drive cancer phenotypes are poorly understood. Here, we employed a novel, scalable and high-throughput in vivo method to perform iterative functional screens of over 250 epigenetic regulatory genes within autochthonous oncogenic KRAS-driven lung tumors. We identified multiple novel epigenetic tumor suppressor and tumor dependency genes. We show that a specific HBO1 complex and the MLL1 complex are among the most impactful tumor suppressive epigenetic regulators in lung. The histone modifications generated by the HBO1 complex are frequently absent or reduced in human lung adenocarcinomas. The HBO1 and MLL1 complexes regulate chromatin accessibility of shared genomic regions, lineage fidelity and the expression of canonical tumor suppressor genes. The HBO1 and MLL1 complexes are epistatic during lung tumorigenesis, and their functional correlation is conserved in human cancer cell lines. Together, these results demonstrate the value of quantitative methods to generate a phenotypic roadmap of epigenetic regulatory genes in tumorigenesis in vivo .

Quantized multi-task learning for context-specific representations of gene network dynamics

While often represented as static entities, gene networks are highly context-dependent. Here, we developed a multi-task learning strategy to yield context-specific representations of gene network dynamics. We assembled a corpus comprising ~103 million human single-cell transcriptomes from a broad range of tissues and diseases and performed a two stage pretraining, first with non-malignant cells to generate a foundational model and then with continual learning on cancer cells to tune the model to the cancer domain. We performed multi-task learning with the foundational model to learn context-specific representations of a broad range of cell types, tissues, developmental stages, and diseases. We then leveraged the cancer-tuned model to jointly learn cell states and predict tumor-restricting factors within the colorectal tumor microenvironment. Model quantization allowed resource-efficient fine-tuning and inference while preserving biological knowledge. Overall, multi-task learning enables context-specific disease modeling that can yield contextual predictions of candidate therapeutic targets for human disease.

The mRNA content of plasma extracellular vesicles provides a window into molecular processes in the brain during cerebral malaria

The impact of cerebral malaria on the transcriptional profiles of cerebral tissues is difficult to study using noninvasive approaches. We isolated plasma extracellular vesicles (EVs) from patients with cerebral malaria and community controls and sequenced their mRNA content. Deconvolution analysis revealed that EVs from cerebral malaria are enriched in transcripts of brain origin. We ordered the patients with cerebral malaria based on their EV-transcriptional profiles from cross-sectionally collected samples and inferred disease trajectory while using healthy community controls as a starting point. We found that neuronal transcripts in plasma EVs decreased with disease trajectory, whereas transcripts from glial, endothelial, and immune cells increased. Disease trajectory correlated positively with severity indicators like death and was associated with increased VEGFA-VEGFR and glutamatergic signaling, as well as platelet and neutrophil activation. These data suggest that brain tissue responses in cerebral malaria can be studied noninvasively using EVs circulating in peripheral blood.

The zinc-finger transcription factor KLF6 regulates cardiac fibrosis

AIMS

Heart failure (HF) is one of the most devastating consequences of cardiovascular diseases. Regardless of etiology, cardiac fibrosis is present and promotes the loss of heart function in HF patients. Cardiac resident fibroblasts, in response to a host of pro-fibrogenic stimuli, trans-differentiate into myofibroblasts to mediate cardiac fibrosis, the underlying mechanism of which remains incompletely understood.

METHODS

Fibroblast-myofibroblast transition was induced in vitro by exposure to transforming growth factor (TGF-β). Cardiac fibrosis was induced in mice by either transverse aortic constriction (TAC) or by chronic infusion with angiotensin II (Ang II).

RESULTS

Through bioinformatic screening, we identified Kruppel-like factor 6 (KLF6) as a transcription factor preferentially up-regulated in cardiac fibroblasts from individuals with non-ischemic cardiomyopathy (NICM) compared to the healthy donors. Further analysis showed that nuclear factor kappa B (NF-κB) bound to the KLF6 promoter and mediated KLF6 trans-activation by pro-fibrogenic stimuli. KLF6 knockdown attenuated whereas KLF6 over-expression enhanced TGF-β induced fibroblast-myofibroblast transition in vitro. More importantly, myofibroblast-specific KLF6 depletion ameliorated cardiac fibrosis and rescued heart function in mice subjected to the TAC procedure or chronic Ang II infusion.

SIGNIFICANCE

In conclusion, our data support a role for KLF6 in cardiac fibrosis.

Biomarker Selection for Adaptive Systems

Biomarkers enable objective monitoring of a given cell or state in a biological system and are widely used in research, biomanufacturing, and clinical practice. However, identifying appropriate biomarkers that are both robustly measurable and capture a state accurately remains challenging. We present a framework for biomarker identification based upon observability guided sensor selection. Our methods, Dynamic Sensor Selection (DSS) and Structure-Guided Sensor Selection (SGSS), utilize temporal models and experimental data, offering a template for applying observability theory to data from biological systems. Unlike conventional methods that assume well-known, fixed dynamics, DSS adaptively select biomarkers or sensors that maximize observability while accounting for the time-varying nature of biological systems. Additionally, SGSS incorporates structural information and diverse data to identify sensors which are resilient against inaccuracies in our model of the underlying system. We validate our approaches by performing estimation on high dimensional systems derived from temporal gene expression data from partial observations. Our algorithms reliably identify known biomarkers and uncover new ones within our datasets. Additionally, integrating chromosome conformation and gene expression data addresses noise and uncertainty, enhancing the reliability of our biomarker selection approach for the genome.

FBLN2 is associated with basal cell markers Krt14 and ITGB1 in mouse mammary epithelial cells and has a preferential expression in molecular subtypes of human breast cancer

BACKGROUND

Fibulin-2 (FBLN2) is a secreted extracellular matrix (ECM) glycoprotein and has been identified in the mouse mammary gland, in cap cells of terminal end buds (TEBs) during puberty, and around myoepithelial cells during early pregnancy. It is required for basement membrane (BM) integrity in mammary epithelium, and its loss has been associated with human breast cancer invasion. Herein, we attempted to confirm the relevance of FBLN2 to myoepithelial phenotype in mammary epithelium and to assess its expression in molecular subtypes of human breast cancer.

METHODS

The relationship between FBLN2 expression and epithelial markers was investigated in pubertal mouse mammary glands and the EpH4 mouse mammary epithelial cell line using immunohistochemistry, immunocytochemistry, and immunoblotting. Human breast cancer mRNA data from the METABRIC and TCGA datasets from Bioportal were analyzed to assess the association of Fbln2 expression with epithelial markers, and with molecular subtypes. Survival curves were generated using data from the METABRIC dataset and the KM databases.

RESULTS

FBLN2 knockdown in mouse mammary epithelial cells was associated with a reduction in KRT14 and an increase in KRT18. Further, TGFβ3 treatment resulted in the upregulation of FBLN2 in vitro. Meta-analyses of human breast cancer datasets from Bioportal showed a higher expression of Fbln2 mRNA in claudin-low, LumA, and normal-like breast cancers compared to LumB, Her2 +, and Basal-like subgroups. Fbln2 mRNA levels were positively associated with mesenchymal markers, myoepithelial markers, and markers of epithelial-mesenchymal transition. Higher expression of Fbln2 mRNA was associated with better prognosis in less advanced breast cancer and this pattern was reversed in more advanced lesions.

CONCLUSION

With further validation, these observations may offer a molecular prognostic tool for human breast cancer for more personalized therapeutic approaches.

Integrative transcriptome analysis reveals the molecular events underlying impaired T-cell responses in EGFR-mutant lung cancer

EGFR mutations are critical oncogenic drivers in lung adenocarcinoma (LUAD). However, the mechanisms by which they impact the tumor microenvironment (TME) and tumor immunity are unclear. Furthermore, the reasons underlying the poor response of EGFR-mutant (EGFR-MU) LUADs to immunotherapy with PD-1/PD-L1 inhibitors are unknown. Utilizing single-cell RNA (sc-RNA) and bulk RNA sequencing datasets, we conducted high-dimensional weighted gene coexpression network analysis to identify key genes and immune-related pathways contributing to the immunosuppressive TME. EGFR-MU cancer cells downregulated MHC class I genes to evade CD8+ cytotoxic T cells, expressed substantial levels of MHC class II molecules, and engaged with CD4+ regulatory T cells (Tregs). EGFR-MU tumors may recruit Tregs primarily through the CCL17/CCL22/CCR4 axis, leading to a Treg-enriched TME. High levels of MHC class II-positive cancer-associated fibroblasts and tumor endothelial cells were found within EGFR-MU tumors. Owing to the absence of costimulatory factors, they may inhibit rather than activate the tumor antigen-specific CD4+ T-cell response, contributing further to immune suppression. Multiplex immunohistochemistry analyses in a LUAD cohort confirmed increased expression of MHC class II molecules in cancer cells and fibroblasts in EGFR-MU tumors. Our research elucidates the highly immunosuppressive TME in EGFR-MU LUAD and suggests potential targets for effective immunotherapy.

Intestinal Epithelia and Myeloid Immune Cells Shape Colitis Severity and Colorectal Carcinogenesis via High-mobility Group Box Protein 1

BACKGROUND

High-mobility group box protein 1 [HMGB1] is a ubiquitous nucleoprotein with immune-regulatory properties following cellular secretion or release in sterile and in infectious inflammation. Stool and serum HMGB1 levels correlate with colitis severity and colorectal cancer [CRC] progression, yet recent reports indicate that HMGB1 mainly operates as an intracellular determinant of enterocyte fate during colitis, and investigations into the roles of HMGB1 in CRC are lacking.

METHODS

Using mice with conditional HMGB1-knockout in enterocytes [Hmgb1ΔIEC] and myeloid cells [Hmgb1ΔLysM], respectively, we explored functions of HMGB1 in pathogenetically diverse contexts of colitis and colitis-associated CRC.

RESULTS

HMGB1 is overexpressed in human inflammatory bowel disease and gastrointestinal cancers, and HMGB1 protein localises in enterocytes and stromal cells in colitis and CRC specimens from humans and rodents. As previously described, enterocyte HMGB1 deficiency aggravates severe chemical-induced intestinal injury, but not Citrobacter rodentium or T cell transfer colitis in mice. HMGB1-deficient enterocytes and organoids do not exhibit deviant apoptotic or autophagic activity, altered proliferative or migratory capacity, abnormal intestinal permeability, or aberrant DSS-induced organoid inflammation in vitro. Instead, we observed altered in vivo reprogramming of both intestinal epithelia and infiltrating myeloid cells in Hmgb1ΔIEC early during colitis, suggesting HMGB1-mediated paracrine injury signalling. Hmgb1ΔIEC had higher CRC burden than wild types in the Apc+/min model, whereas inflammatory CRC was attenuated in Hmgb1ΔLysM. Cellular and molecular phenotyping of Hmgb1ΔIEC and Hmgb1ΔLysM cancers indicates context-dependent transcriptional modulation of immune signalling and extracellular matrix remodelling via HMGB1.

CONCLUSION

Enterocytes and myeloid cells context-dependently regulate host responses to severe colitis and maladaptive intestinal wound healing via HMGB1.

Single-cell RNA sequencing reveals placental response under environmental stress

The placenta is crucial for fetal development, yet the impact of environmental stressors such as arsenic exposure remains poorly understood. We apply single-cell RNA sequencing to analyze the response of the mouse placenta to arsenic, revealing cell-type-specific gene expression, function, and pathological changes. Notably, the Prap1 gene, which encodes proline-rich acidic protein 1 (PRAP1), is significantly upregulated in 26 placental cell types including various trophoblast cells. Our study shows a female-biased increase in PRAP1 in response to arsenic and localizes it in the placenta. In vitro and ex vivo experiments confirm PRAP1 upregulation following arsenic treatment and demonstrate that recombinant PRAP1 protein reduces arsenic-induced cytotoxicity and downregulates cell cycle pathways in human trophoblast cells. Moreover, PRAP1 knockdown differentially affects cell cycle processes, proliferation, and cell death depending on the presence of arsenic. Our findings provide insights into the placental response to environmental stress, offering potential preventative and therapeutic approaches for environment-related adverse outcomes in mothers and children.