Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R

Plasmodium falciparum infection induces T cell tolerance that is associated with decreased disease severity upon re-infection

Immunity to severe malaria is acquired quickly, operates independently of pathogen load, and represents a highly effective form of disease tolerance. The mechanism that underpins tolerance remains unknown. We used a human rechallenge model of falciparum malaria in which healthy adult volunteers were infected three times over a 12 mo period to track the development of disease tolerance in real-time. We found that parasitemia triggered a hardwired innate immune response that led to systemic inflammation, pyrexia, and hallmark symptoms of clinical malaria across the first three infections of life. In contrast, a single infection was sufficient to reprogram T cell activation and reduce the number and diversity of effector cells upon rechallenge. Crucially, this did not silence stem-like memory cells but instead prevented the generation of cytotoxic effectors associated with autoinflammatory disease. Tolerized hosts were thus able to prevent collateral tissue damage in the absence of antiparasite immunity.

Characterisation of the avascular mesenchyme during digit outgrowth

The avascular mesenchyme at the tip of the developing digit contributes to digit outgrowth and patterning, however, it has been poorly characterised. Using newly developed fate mapping approaches, tissue manipulation and single-cell mRNA sequencing data, we explore the transcriptional nature and developmental potential of this tissue. We find that the avascular mesenchyme is essential to normal segmental patterning of the digit and has a distinct transcriptional identity. In addition, we uncover an unexpected relationship between the unspecified tissue of the avascular mesenchyme and the committed phalanx forming region, which controls patterning, but not outgrowth of the digit. This multifaceted approach provides insights into the mechanics and genetic pathways that regulate digit outgrowth and patterning.

BCL2A1‑ and G0S2‑driven neutrophil extracellular traps: A protective mechanism linking preeclampsia to reduced breast cancer risk

Preeclampsia has been associated with a reduced risk of breast cancer (BC), but the mechanisms underlying this relationship remain unclear. It has been suggested that neutrophil extracellular traps (NETs), which are released upon neutrophil activation, play a key role in both preeclampsia and BC. To investigate this link, the single‑cell RNA sequencing dataset GSE173193 was analyzed and upregulated genes BCL2A1 and G0/G1 switch gene 2 (G0S2) were identified in neutrophils from preeclamptic placentas. These findings were validated using reverse transcription‑quantitative PCR and western blotting. Combined analyses of preeclampsia and BC tissues, from Gene Expression Omnibus (GSE24129) and The Cancer Genome Atlas databases respectively, identified 2,040 upregulated differentially expressed genes, including BCL2A1 and G0S2. Furthermore, these genes showed clinical relevance to BC, as demonstrated by Receiver Operating Characteristic curve, survival analyses and weighted gene co‑expression network analysis. Functional experiments revealed that overexpression of BCL2A1 and G0S2 increased NET release and inhibited BC cell proliferation, invasion and migration. The present study provides novel insights into the shared molecular pathways of preeclampsia and BC, emphasizing NETs as a potential protective mechanism as increased NET production in preeclampsia may contribute to a reduced BC risk by influencing tumor progression and offer avenues for further research into therapeutic interventions.

Integrating bulk RNA-seq and scRNA-seq analyses with machine learning to predict platinum response and prognosis in ovarian cancer

Platinum-based therapy is an integral part of the standard treatment for ovarian cancer. However, despite extensive research spanning several decades, the identification of dependable predictive biomarkers for platinum response in clinical practice has proven to be a formidable challenge. Recently, the development of single-cell technology has enabled more precise investigations into the heterogeneity of cancer. In this study, we isolated cancer cells from the single-cell transcriptomic data of platinum-sensitive and platinum-resistant patients with ovarian cancer. Differential gene analysis of platinum-sensitive and platinum-resistant cancer cells revealed that several of the differentially expressed genes had previously been reported in other studies to be associated with platinum resistant. Gene set enrichment analysis revealed the up-regulation of pathways involved in processes such as autophagy, cell cycle regulation, and DNA damage repair, which are known to promote platinum resistance in ovarian cancer. Based on these findings, we hypothesized that these differentially expressed genes could be used to predict the response of ovarian cancer patients to platinum-based chemotherapy. To validate this hypothesis, we explored 7 different machine learning models for predicting platinum chemotherapy response at varying feature gene counts. Ultimately, the random forest model performed the best, with 5 genes (PAX2, TFPI2, APOA1, ADIRF and CRISP3) and achieve an AUC of 0.993 in test cohort and 0.989 in GSE63885 independent validation cohorts. We named this model GPPS (Genes to Predict Platinum response Signature). Furthermore, we discovered that the GPPS model can also predict patient prognosis.

Co-targeting of epigenetic regulators and BCL-XL improves efficacy of immune checkpoint blockade therapy in multiple solid tumors

Epigenetic modulators in combination with proapoptotic drugs have become the standard of care treatment in hematological malignancies. Conversely, these combinations have failed to demonstrate clinical efficacy in solid tumors. To address this discrepancy, we conducted a comprehensive analysis of the anti-tumor activity of epigenetic inhibitors in combination with BH3 mimetics that block anti-apoptotic proteins BCL-XL, BCL2 or MCL1 in a large set of solid tumor cell lines derived from patients and mouse models. Treatment with epigenetic drugs targeting DNA methyltransferase, histone methyltransferase, and histone deacetylase enzymes in combination with a BCL-XL inhibitor resulted in marked synergistic in vitro responses both in human and mouse solid tumor cell lines. This unique BCL-XL dependency was in clear contrast to hematological malignancies, which are largely dependent on BCL2 or MCL1 inhibition under epigenetic drug treatment. Mechanistically, co-targeting of epigenetic regulators and BCL-XL induced expression of endogenous retroelements that led to immunogenic cell death. We thus hypothesized that this response may sensitize tumor cells to immune checkpoint blockade (ICB). Accordingly, treatment with a triple combination of epigenetic and BCL-XL inhibitors with an anti-PD-1 monoclonal antibody in vivo reduced tumor growth and prolonged overall survival in a panel of murine syngeneic and orthotopic models of lung, colorectal and breast carcinomas, melanoma, and glioblastoma, as well as in an immunocompetent human colon cancer model. Using flow cytometry and single-cell RNA sequencing of the tumor microenvironment, we found that the broad activity of the triple therapy relied on the expansion of T and NK cells with cytotoxic potential, an increase in the M1/M2 macrophage ratio, and a reduction of immunosuppressive Treg cells, dendritic cells, and B lymphocytes. In conclusion, we report a novel regimen combining epigenetic and BCL-XL inhibitors with ICB that produces potent anti-tumor responses in multiple preclinical models of solid tumors.

Delineation of the Human Germinal Centre Immune Landscape Using Multiplex Imaging Analysis

Given the role of follicular immune dynamics, especially the germinal centre, for the development of pathogen-specific antibodies, their in situ characterisation is of great importance. We have developed a multiplex immunofluorescence imaging pipeline that allows the analysis of human follicular adaptive and innate immune cell subsets. Our data revealed the in situ phenotypic heterogeneity and differential localisation of follicular helper CD4 T (TFH) cell subsets across follicular areas in tonsils and reactive lymph nodes (LNs). Cell clustering analysis identified specific TFH subsets with differential prevalence between tonsils and LNs. Further, a multiplex RNAscope/protein imaging assay revealed the functional heterogeneity of TFH cells. No significant differences in follicular innate immune cell densities were found between tonsils and LNs. In conclusion, we present a combinatory experimental approach that provides a comprehensive analysis of human follicular and/or germinal centre immune dynamics and could be used to further understand the pathogenesis of diseases such as HIV and lymphomas.

The skeletal muscle response to high-intensity training assessed by single-nucleus RNA-sequencing is blunted in individuals with type 2 diabetes

Training can improve insulin sensitivity in individuals with type 2 diabetes, but a clear understanding of the mechanisms remains elusive. To further our knowledge in this area, we aimed to examine the effect of type 2 diabetes and of high-intensity interval training (HIIT) on the nuclear transcriptional response in skeletal muscle. We performed single-nucleus RNA-sequencing (snRNA-seq) and immunofluorescence analysis on muscle biopsies from the trained and the untrained legs of participants with and without type 2 diabetes, after 2 weeks of one-legged HIIT on a cycle ergometer. Surprisingly, the type 2 diabetes condition only seemed to have a minor effect on transcriptional activity in myonuclei related to major metabolic pathways when comparing the untrained legs. However, while in particular the type IIA myonuclei in the control group displayed a considerable metabolic response to HIIT, with increases in genes related to glycogen breakdown and glycolysis primarily in the type IIA myonuclei of the trained leg, this response was blunted in the diabetes group, despite a marked increase in glucose clearance in both groups. Additionally, we observed that fibre type distribution assessed by immunofluorescence significantly correlated with the proportion of myonuclei in the snRNA-seq analysis. In conclusion, the type 2 diabetes condition blunts the metabolic transcriptional response to HIIT in the type IIA myonuclei without affecting the improvement in insulin sensitivity. Additionally, our results indicate that snRNA-seq can be used as a surrogate marker for fibre type distribution in sedentary middle-aged adults. KEY POINTS: The study utilized single-nucleus RNA sequencing (snRNA-seq) to analyse 38 skeletal muscle biopsies, revealing distinct transcriptional profiles in myonuclei from individuals with and without type 2 diabetes (T2D) after 2 weeks of HIIT. snRNA-seq identified significant differences in gene expression, with 14 differentially expressed genes (DEGs) in type IIA myonuclei of the control group, specifically related to glycogen breakdown and glycolysis, which were blunted in the T2D group. In the control group, HIIT induced a substantial transcriptional response in type IIA myonuclei, enhancing metabolic pathways associated with insulin sensitivity, while the T2D group showed minimal transcriptional changes despite improved insulin sensitivity. The T2D group exhibited a blunted response in metabolic gene expression, indicating that the training effect on muscle adaptation was significantly impaired compared to healthy controls. Overall, the findings highlight the differential impact of HIIT on muscle metabolism, emphasizing the need for tailored exercise interventions for individuals with T2D.

Accurate Transcription Factor Activity Inference to Decipher Cell Identity from Single-Cell Transcriptomic Data with MetaTF

Cellular heterogeneity within cancer tissues determines cancer progression and treatment response. Single-cell RNA sequencing (scRNA-seq) has provided a powerful approach for investigating the cellular heterogeneity of both cancer cells and stroma cells in the tumor microenvironment. However, the common practice to characterize cell identity based on the similarity of their gene expression profiles may not really indicate distinct cellular populations with unique roles. Generally, the cell identity and function are orchestrated by the expression of given specific genes tightly regulated by transcription factors (TFs). Therefore, deciphering TF activity is essential for gaining a better understanding of the uniqueness and functionality of each cell type. Herein, metaTF, a computational framework designed to infer TF activity in scRNA-seq data, is introduced and existing methods are outperformed for estimating TF activity. It presents the improved effectiveness in characterizing cell identity during mouse hematopoietic stem cell development. Furthermore, metaTF provides a superior characterization of the functional identity of breast cancer epithelial cells, and identifies a novel subset of neural-regulated T cells within the tumor immune microenvironment, which potentially activates BCL6 in response to neural-related signals. Overall, metaTF enables robust TF activity analysis from scRNA-seq data, significantly enhancing the characterization of cell identity and function.

Navigating single-cell RNA-sequencing: protocols, tools, databases, and applications

Single-cell RNA-sequencing (scRNA-seq) technology brought about a revolutionary change in the transcriptomic world, paving the way for comprehensive analysis of cellular heterogeneity in complex biological systems. It enabled researchers to see how different cells behaved at single-cell levels, providing new insights into the process. However, despite all these advancements, scRNA-seq also experiences challenges related to the complexity of data analysis, interpretation, and multi-omics data integration. In this review, these complications were discussed in detail, directly pointing at the optimization of scRNA-seq approaches and understanding the world of single-cell and its dynamics. Different protocols and currently functional single-cell databases were also covered. This review highlights different tools for the analysis of scRNA-seq and their methodologies, emphasizing innovative techniques that enhance resolution and accuracy at a single-cell level. Various applications were explored across domains including drug discovery, tumor microenvironment (TME), biomarker discovery, and microbial profiling, and case studies were discussed to explain the importance of scRNA-seq by uncovering novel and rare cell types and their identification. This review underlines a crucial aspect of scRNA-seq in the advancement of personalized medicine and highlights its potential to understand the complexity of biological systems.

Divergent DNA methylation dynamics in marsupial and eutherian embryos

Based on seminal work in placental species (eutherians)1-10, a paradigm of mammalian development has emerged wherein the genome-wide erasure of parental DNA methylation is required for embryogenesis. Whether such DNA methylation reprogramming is, in fact, conserved in other mammals is unknown. Here, to resolve this point, we generated base-resolution DNA methylation maps in gametes, embryos and adult tissues of a marsupial, the opossum Monodelphis domestica, revealing variations from the eutherian-derived model. The difference in DNA methylation level between oocytes and sperm is less pronounced than that in eutherians. Furthermore, unlike the genome of eutherians, that of the opossum remains hypermethylated during the cleavage stages. In the blastocyst, DNA demethylation is transient and modest in the epiblast. However, it is sustained in the trophectoderm, suggesting an evolutionarily conserved function for DNA hypomethylation in the mammalian placenta. Furthermore, unlike that in eutherians, the inactive X chromosome becomes globally DNA hypomethylated during embryogenesis. We identify gamete differentially methylated regions that exhibit distinct fates in the embryo, with some transient, and others retained and that represent candidate imprinted loci. We also reveal a possible mechanism for imprinted X inactivation, through maternal DNA methylation of the Xist-like noncoding RNA RSX11. We conclude that the evolutionarily divergent eutherians and marsupials use DNA demethylation differently during embryogenesis.

Acute exposure to high-fat diet impairs ILC3 functions and gut homeostasis

Prolonged exposure to a high-fat diet (HFD) exacerbates intestinal disease pathology, yet the early events preceding the development of gut inflammation remain poorly understood. Here, we show that within 48 h, HFD impairs intestinal group 3 innate lymphoid cells (ILC3s) and their capacity to produce interleukin-22 (IL-22), critical for maintaining gut homeostasis. This loss of function was associated with rapid dysbiosis, increased gut permeability, and reduced production of antimicrobial peptides, mucus, and tight-junction proteins. While saturated fatty acids metabolized through oxidation impaired ILC3 function, unsaturated fatty acids sustained IL-22 secretion by ILC3s through the formation of lipid droplets using diacylglycerol O-acyltransferase (DGAT) enzymes. Upon inflammation, saturated fatty acids impaired IL-22 production by ILC3s and increased the susceptibility of the gut to injury. Our findings reveal the differential acute impact of saturated and unsaturated fatty acids on gut homeostasis through distinct metabolic pathways in ILC3s.

PIM kinase control of CD8 T cell protein synthesis and cell trafficking

Integration of kinase signalling networks co-ordinates the transcriptional, translational, and metabolic changes required for T cell activation and differentiation. This study explores the role of the Serine/Threonine kinases PIM1 and PIM2 in controlling mouse CD8 T lymphocyte antigen receptor-mediated activation and differentiation in response to the cytokines Interleukin-2 (IL-2) or IL-15. We show that the PIM kinases are dispensable for antigen-receptor and IL-15 controlled differentiation programs, but that they play a selective role in IL-2 regulated CD8 T cell fate. One key insight was that PIM kinases controlled the migratory capabilities of effector CD8 T cells, with Pim1/Pim2-deficient CD8 T cells unable to fully switch off the naive T cell chemokine and adhesion receptor program during effector differentiation. PIM kinases were also needed for IL-2 to sustain high expression of the glucose transporters SLC2A1 and SLC2A3 and to maintain activity of the nutrient-sensing kinase mTORc1. Strikingly, PIM kinases did not have a dominant impact on IL-2-driven transcriptional programs but rather selectively modulated protein synthesis to shape cytotoxic T cell proteomes. This study reveals a selective role of PIM kinases in IL-2 control of CD8 T cells and highlights how regulated changes in protein synthesis can impact T cell phenotypes.

Monocytes can efficiently replace all brain macrophages and fetal liver monocytes can generate bona fide SALL1+ microglia

Microglia and border-associated macrophages (BAMs) are critical for brain health, and their dysfunction is associated to disease. Replacing brain macrophages holds substantial therapeutic promise but remains challenging. Here, we demonstrate that monocytes can efficiently replace all brain macrophages. Monocytes readily replaced embryonal BAMs upon their depletion and engrafted as monocyte-derived microglia (Mo-Microglia) upon more sustained niche availability. Mo-Microglia expanded comparably to their embryonic counterparts and showed similar longevity. However, monocytes were unable to replicate the distinct identity of embryonically derived BAMs and microglia. Using xenotransplantation, we found that human monocytes exhibited similar behavior, enabling identification of putative Mo-Microglia in Alzheimer's disease individuals. In mice and humans, monocyte ontogeny shaped their identity as brain macrophages. Importantly, mouse fetal liver monocytes exhibited a distinct epigenetic landscape and could develop a bona fide microglial identity. Our results illuminate brain macrophage development and highlight monocytes as an abundant progenitor source for brain macrophage replacement therapies.

MeCP2 and non-CG DNA methylation stabilize the expression of long genes that distinguish closely related neuron types

The diversity of mammalian neurons is delineated by subtle gene expression differences that may require specialized mechanisms to be maintained. Neurons uniquely express the longest genes in the genome and use non-CG DNA methylation (mCA), together with the Rett syndrome protein methyl-CpG-binding protein 2 (MeCP2), to control gene expression. However, whether these distinctive gene structures and molecular machinery regulate neuronal diversity remains unexplored. Here, we use genomic and spatial transcriptomic analyses to show that MeCP2 maintains transcriptomic diversity across closely related neuron types. We uncover differential susceptibility of neuronal populations to MeCP2 loss according to global mCA levels and dissect methylation patterns driving shared and distinct MeCP2 gene regulation. We show that MeCP2 regulates long, mCA-enriched, 'repeatedly tuned' genes, that is, genes differentially expressed between many closely related neuron types, including across spatially distinct, vision-dependent gene programs in the visual cortex. Thus, MeCP2 maintains neuron type-specific gene programs to facilitate cellular diversity in the brain.

Circulating immune cells exhibit distinct traits linked to metastatic burden in breast cancer

BACKGROUND

Circulating immune cells play a crucial role in the anti-tumour immune response, yet the systemic immune system in metastatic breast cancers is not fully characterised. Investigating the cellular and molecular changes in peripheral blood mononuclear cells (PBMCs) from breast cancer patients could elucidate the role of circulating immune cells in metastasis and aid in identifying biomarkers for disease burden and progression.

METHODS

In this study, we characterised the systemic immune landscape associated with varying levels of metastatic burden by analysing the single-cell transcriptomes of PBMCs from breast cancer patients and healthy controls. Our research focused on identifying changes in immune cell composition, transcriptional programs, and immune-cell communication networks linked to metastatic burden. Additionally, we compared these PBMC features onto a single-cell atlas of primary breast tumours to study corresponding traits in tumour-infiltrating immune cells.

RESULTS

In metastatic breast cancer, PBMCs exhibit a significant downregulation of the adaptive immune system and a decreased number and activity of unconventional T cells, such as γδ T cells. Additionally, metastatic burden is associated with impaired cell communication pathways involved in immunomodulatory functions. We also identified a gene signature derived from myeloid cells shared between tumour immune infiltrates and circulating immune cells in breast cancer patients.

CONCLUSIONS

Our study provides a comprehensive single-cell molecular profile of the peripheral immune system in breast cancer, offering a valuable resource for understanding metastatic disease in terms of tumour burden. By identifying immune traits linked to metastasis, we have unveiled potential new biomarkers of metastatic disease.

scMINER: a mutual information-based framework for clustering and hidden driver inference from single-cell transcriptomics data

Single-cell transcriptomics data present challenges due to their inherent stochasticity and sparsity, complicating both cell clustering and cell type-specific network inference. To address these challenges, we introduce scMINER (single-cell Mutual Information-based Network Engineering Ranger), an integrative framework for unsupervised cell clustering, transcription factor and signaling protein network inference, and identification of hidden drivers from single-cell transcriptomic data. scMINER demonstrates superior accuracy in cell clustering, outperforming five state-of-the-art algorithms and excelling in distinguishing closely related cell populations. For network inference, scMINER outperforms three established methods, as validated by ATAC-seq and CROP-seq. In particular, it surpasses SCENIC in revealing key transcription factor drivers involved in T cell exhaustion and Treg tissue specification. Moreover, scMINER enables the inference of signaling protein networks and drivers with high accuracy, which presents an advantage in multimodal single cell data analysis. In addition, we establish scMINER Portal, an interactive visualization tool to facilitate exploration of scMINER results.

Immunotherapy-related cognitive impairment after CAR T cell therapy in mice

Immunotherapies have revolutionized cancer care for many tumor types, but their potential long-term cognitive impacts are incompletely understood. Here, we demonstrated in mouse models that chimeric antigen receptor (CAR) T cell therapy for both central nervous system (CNS) and non-CNS cancers impaired cognitive function and induced a persistent CNS immune response characterized by white matter microglial reactivity, microglial chemokine expression, and elevated cerebrospinal fluid (CSF) cytokines and chemokines. Consequently, oligodendroglial homeostasis and hippocampal neurogenesis were disrupted. Single-nucleus sequencing studies of human frontal lobe from patients with or without previous CAR T cell therapy for brainstem tumors confirmed reactive states of microglia and oligodendrocytes following treatment. In mice, transient microglial depletion or CCR3 chemokine receptor blockade rescued oligodendroglial deficits and cognitive performance in a behavioral test of attention and short-term memory function following CAR T cell therapy. Taken together, these findings illustrate targetable neural-immune mechanisms underlying immunotherapy-related cognitive impairment.

Transient inhibition of type I interferon enhances CD8+ T cell stemness and vaccine protection

Developing vaccines that promote CD8+ T cell memory is a challenge for infectious disease and cancer immunotherapy. TCF-1+ stem cell-like memory CD8+ T (TSCM) cells are important determinants of long-lived memory. Yet, the developmental requirements for TSCM cell formation are unclear. Here, we identify the temporal window for type I interferon receptor (IFNAR) blockade to drive TSCM cell generation following viral infection and mRNA-lipid nanoparticle vaccination. We reveal a reversible developmental trajectory where transcriptionally distinct TSCM cells emerged from a transitional precursor of exhausted T cellular state concomitant with viral clearance. TSCM cell differentiation correlated with T cell retention within the lymph node paracortex due to disrupted CXCR3 chemokine gradient formation. These effects were linked to increased antigen load and a counterintuitive increase in IFNγ, which controlled cell location. Vaccination with the IFNAR blockade promoted TSCM cell differentiation and enhanced protection against chronic infection. These findings propose an approach to vaccine design whereby modulation of inflammation promotes memory formation and function.

Understanding and reversing mammary tumor-driven reprogramming of myelopoiesis to reduce metastatic spread

Tumor-induced systemic accumulation and polarization of neutrophils to an immunosuppressive phenotype is a potent driver of metastasis formation. Yet, how mammary tumors reprogram granulopoiesis at the molecular level and when tumor imprinting occurs during neutrophil development remains underexplored. Here, we combined single-cell, chromatin and functional analyses to unravel the tumor-driven reprogramming of granulopoiesis in the bone marrow, along with intervention studies aimed at reversing this process. We observe that mammary tumors accelerate commitment to the neutrophil lineage at the expense of lymphopoiesis and erythropoiesis without stimulating the development of a novel myeloid lineage. Moreover, tumor-directed immunosuppressive imprinting of neutrophils starts early in hematopoiesis. Treatment with anti-IL-1β normalizes tumor-induced granulopoiesis, reducing neutrophil immunosuppressive phenotype and mitigating metastatic spread. Together, these data provide molecular insights into the aberrant, tumor-driven neutrophil differentiation pathway leading to metastasis-promoting chronic inflammation and how it can be reversed to reduce metastatic spread.

Fibroblastic reticular cells form reactive myeloid cell niches in human lymph nodes

Lymph nodes play a key role in maintaining fluid balance in homeostatic and inflamed tissues and provide fibroblastic niche environments for optimal immune cell positioning and interaction. Here, we used single-cell and spatial transcriptomic analyses in combination with high-resolution imaging to molecularly define and functionally characterize niche-forming cells that control inflammation-driven remodeling in human lymph nodes. Fibroblastic reticular cells responded to inflammatory perturbation with activation and expansion of poised niche environments. Inflammation-induced adaptation of lymph node infrastructure and topography included the expansion of peptidase inhibitor 16 (PI16)-expressing reticular cell (PI16+ RC) networks that enwrap the perivenular conduit system. Interactome analyses indicated that macrophage-derived oncostatin M directs PI16+ RC activation in inflamed lymph nodes and thereby promotes immune cell aggregation in the perivenular space. In conclusion, these data demonstrate that the inflammatory remodeling of human lymph nodes results in the formation of reactive myeloid cell niches by PI16+ RCs.

Presence of Tertiary Lymphoid Structures and Exhausted Tissue-Resident T Cells Determines Clinical Response to PD-1 Blockade in Renal Cell Carcinoma

SIGNIFICANCE

We describe a paradigm wherein combined high TLS and low tissue-resident exhausted CD8+ T cells are required for optimal response to PD-1 blockade in RCC. This analysis identifies key determinants of response to PD-1 blockade in advanced RCC and suggests avenues for future immune modulation through rational combination therapy strategies.

Spinal lumbar Urocortin 3-expressing neurons are associated with both scratching and Compound 48/80-induced sensations

ABSTRACT

Urocortin 3 is a neuropeptide that belongs to the corticotropin-releasing hormone family and is involved in mechanosensation and stress regulation. In this study, we show that Urocortin 3 marks a population of excitatory neurons in the mouse spinal cord, divided into 2 nonoverlapping subpopulations expressing protein kinase C gamma or calretinin/calbindin 2, populations previously associated with mechanosensation. Electrophysiological experiments demonstrated that lumbar spinal Urocortin 3 neurons receive both glycinergic and GABAergic local tonic inhibition, and monosynaptic inputs from both Aβ and C fibers, which could be confirmed by retrograde trans-synaptic rabies tracing. Furthermore, fos analyses showed that subpopulations of lumbar Urocortin 3 neurons are activated by artificial scratching or Compound 48/80-induced sensations. Chemogenetic activation of lumbar Urocortin 3-Cre neurons evoked a targeted biting/licking behavior towards the corresponding dermatome and chemogenetic inhibition decreased Compound 48/80-induced behavior. Hence, spinal lumbar Urocortin 3 neurons represent a mechanically associated population with roles in both scratching and Compound 48/80-induced sensations.

CHOIR improves significance-based detection of cell types and states from single-cell data

Clustering is a critical step in the analysis of single-cell data, enabling the discovery and characterization of cell types and states. However, most popular clustering tools do not subject results to statistical inference testing, leading to risks of overclustering or underclustering data and often resulting in ineffective identification of cell types with widely differing prevalence. To address these challenges, we present CHOIR (cluster hierarchy optimization by iterative random forests), which applies a framework of random forest classifiers and permutation tests across a hierarchical clustering tree to statistically determine clusters representing distinct populations. We demonstrate the performance of CHOIR through extensive benchmarking against 15 existing clustering methods across 230 simulated and five real single-cell RNA sequencing, assay for transposase-accessible chromatin sequencing, spatial transcriptomic and multi-omic datasets. CHOIR can be applied to any single-cell data type and provides a flexible, scalable and robust solution to the challenge of identifying biologically relevant cell groupings within heterogeneous single-cell data.

Integrating Spatially-Resolved Transcriptomics Data Across Tissues and Individuals: Challenges and Opportunities

Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. The lowering cost of SRT data generation presents an unprecedented opportunity to create large-scale spatial atlases and enable population-level investigation, integrating SRT data across multiple tissues, individuals, species, or phenotypes. Here, unique challenges are described in the SRT data integration, where the analytic impact of varying spatial and biological resolutions is characterized and explored. A succinct review of spatially-aware integration methods and computational strategies is provided. Exciting opportunities to advance computational algorithms amenable to atlas-scale datasets along with standardized preprocessing methods, leading to improved sensitivity and reproducibility in the future are further highlighted.

An overview of computational methods in single-cell transcriptomic cell type annotation

The rapid accumulation of single-cell RNA sequencing data has provided unprecedented computational resources for cell type annotation, significantly advancing our understanding of cellular heterogeneity. Leveraging gene expression profiles derived from transcriptomic data, researchers can accurately infer cell types, sparking the development of numerous innovative annotation methods. These methods utilize a range of strategies, including marker genes, correlation-based matching, and supervised learning, to classify cell types. In this review, we systematically examine these annotation approaches based on transcriptomics-specific gene expression profiles and provide a comprehensive comparison and categorization of these methods. Furthermore, we focus on the main challenges in the annotation process, especially the long-tail distribution problem arising from data imbalance in rare cell types. We discuss the potential of deep learning techniques to address these issues and enhance model capability in recognizing novel cell types within an open-world framework.

lute: estimating the cell composition of heterogeneous tissue with varying cell sizes using gene expression

BACKGROUND

Relative cell type fraction estimates in bulk RNA-sequencing data are important to control for cell composition differences across heterogenous tissue samples. While there exist algorithms to estimate the cell type proportions in tissues, a major challenge is the algorithms can show reduced performance if using tissues that have varying cell sizes, such as in brain tissue. In this way, without adjusting for differences in cell sizes, computational algorithms estimate the relative fraction of RNA attributable to each cell type, rather than the relative fraction of cell types, leading to potentially biased estimates in cellular composition. Furthermore, these tools were built on different frameworks with non-uniform input data formats while addressing different types of systematic errors or unwanted bias.

RESULTS

We present lute, a software tool to accurately deconvolute cell types with varying sizes. Our package lute wraps existing deconvolution algorithms in a flexible and extensible framework to enable easy benchmarking and comparison of existing deconvolution algorithms. Using simulated and real datasets, we demonstrate how lute adjusts for differences in cell sizes to improve the accuracy of cell composition.

CONCLUSIONS

Our software ( https://bioconductor.org/packages/lute ) can be used to enhance and improve existing deconvolution algorithms and can be used broadly for any type of tissue containing cell types with varying cell sizes.

Single cell RNA sequencing of haematopoietic cells in fresh and frozen human atheroma tissue

AIMS

Single-cell RNA sequencing (scRNA-seq) is a powerful method for exploring the cellular heterogeneity within human atheroma but typically requires fresh tissue to preserve cell membrane integrity, limiting the feasibility of large-scale biobanking for later analysis. The aim of this study was to determine whether cryopreservation of fragile and necrotic atheroma tissue affects the viability and transcriptomic profiles of haematopoietic cells in subsequent scRNA-seq analysis, enabling the use of cryopreserved atheroma samples for future research.

METHODS AND RESULTS

We performed scRNA-seq on five paired fresh and cryopreserved atheroma samples-three from coronary arteries and two from carotid arteries. Each sample was enzymatically digested, sorted for CD45+ haematopoietic cells, and processed using the 10× Genomics scRNA-seq workflow. Half of each sample was processed immediately, while the other half was cryopreserved in liquid nitrogen for an average of 5 weeks before thawing and processing. In carotid artery samples, we noted the absence of LYVE1+ macrophages, likely due to the loss of the adventitial layer during endarterectomy procedures. Our results indicated that cryopreservation modestly affected cellular integrity, leading to an increase in the relative abundance of mitochondrial RNA in frozen samples. Minimal differences were observed between fresh and cryopreserved samples in uniquely detected transcripts, cell clustering, or transcriptional profiles within haematopoietic populations.

CONCLUSIONS

Our study demonstrates that cryopreserved human atheroma samples can be successfully profiled using scRNA-seq, with comparable transcriptomic data to that obtained from fresh samples. These findings suggest that cryopreservation is a viable method for biobanking atheroma tissues, facilitating large-scale studies without the need for immediate sample processing.

Autophagy disruption and mitochondrial stress precede photoreceptor necroptosis in multiple mouse models of inherited retinal disorders

Inherited retinal diseases (IRDs) are a leading cause of blindness worldwide. One of the greatest barriers to developing treatments for IRDs is the heterogeneity of these disorders, with causative mutations identified in over 280 genes. It is therefore a priority to find therapies applicable to a broad range of genetic causes. To do so requires a greater understanding of the common or overlapping molecular pathways that lead to photoreceptor death in IRDs and the molecular processes through which they converge. Here, we characterise the contribution of different cell death mechanisms to photoreceptor degeneration and loss throughout disease progression in humanised mouse models of IRDs. Using single-cell transcriptomics, we identify common transcriptional signatures in degenerating photoreceptors. Further, we show that in genetically and functionally distinct IRD models, common early defects in autophagy and mitochondrial damage exist, triggering photoreceptor cell death by necroptosis in later disease stages. These results suggest that, regardless of the underlying genetic cause, these pathways likely contribute to cell death in IRDs. These insights provide potential therapeutic targets for novel, gene-agnostic treatments for IRDs applicable to the majority of patients.

Macrophages direct location-dependent recall of B cell memory to vaccination

Vaccines generate long-lived plasma cells and memory B cells (Bmems) that may re-enter secondary germinal centers (GCs) to further mutate their B cell receptor upon boosting and re-exposure to antigen. We show in mouse models that lymph nodes draining the site of primary vaccination harbor a subset of Bmems that reside in the subcapsular niche, generate larger recall responses, and are more likely to re-enter GCs compared with circulating Bmems in non-draining lymph nodes. This location-dependent recall of Bmems into the GC in the draining lymph node was dependent on CD169+ subcapsular sinus macrophages (SSMs) in the subcapsular niche. In human participants, boosting of the BNT162b2 vaccine in the same arm generated more rapid secretion of broadly neutralizing antibodies, GC participation, and clonal expansion of SARS-CoV-2-specific B cells than boosting of the opposite arm. These data reveal an unappreciated role for primed draining lymph node SSMs in Bmem cell fate determination.

Single-cell and multi-omics integration reveals cholesterol biosynthesis as a synergistic target with HER2 in aggressive breast cancer

Breast cancer stands as one of the most prevalent malignancies affecting women. Alterations in molecular pathways in cancer cells represent key regulatory disruptions that drive malignancy, influencing cancer cell survival, proliferation, and potentially modulating therapeutic responsiveness. Therefore, decoding the intricate molecular mechanisms and identifying novel therapeutic targets through systematic computational approaches are essential steps toward advancing effective breast cancer treatments. In this study, we developed an integrative computational framework that combines single-cell RNA sequencing (scRNA-seq) and multi-omics analyses to delineate the functional characteristics of malignant cell subsets in breast cancer patients. Our analyses revealed a significant correlation between cholesterol biosynthesis and HER2 expression in malignant breast cancer cells, supported by proteomics data, gene expression profiles, drug treatment scores, and cell-surface HER2 intensity measurements. Given previous evidence linking cholesterol biosynthesis to HER2 membrane dynamics, we proposed a combinatorial strategy targeting both pathways. Experimental validation through clonogenic and viability assays demonstrated that simultaneous inhibition of cholesterol biosynthesis (via statins) and HER2 (via Neratinib) synergistically reduced malignant breast cancer cells, even in HER2-negative contexts. Through systematic analysis of scRNA-seq and multi-omics data, our study computationally identified and experimentally validated cholesterol biosynthesis and HER2 as novel combinatorial therapeutic targets in breast cancer. This data-driven approach highlights the potential of leveraging multiple molecular profiling techniques to uncover previously unexplored treatment strategies.

Single-cell transcriptomic data reveal the cellular heterogeneity of glutamine metabolism in gastric premalignant lesions and early gastric cancer

Glutamine metabolism is a hallmark of cancer metabolism. This study aims to perform a comprehensive and systematic single-cell profile of glutamine metabolism in premalignant and malignant gastric lesions. We use single-cell transcriptomics data from chronic atrophic gastritis (CAG) and early gastric cancer (EGC) lesions and investigate glutamine metabolism features at the single-cell level. Experiments are implemented to validate the expression and biological role of ERO1LB in gastric cancer (GC). A single-cell atlas based on 22511 cells from premalignant and early-malignant gastric lesions is established. Among these cells, epithelial cells constitute the dominant cell population in both CAG and EGC lesions. The activity of glutamine metabolism is higher in epithelial cells from EGC lesions than in those from CAG lesions. Among the epithelial cell subpopulations, glutamine metabolism is more active in the epithelial cell subpopulation cluster_4 in EGCs than in CAG lesions. As a key marker gene of this subpopulation, ERO1LB is experimentally proven to be overexpressed in human GC tissue lesions. In both in vitro and in vivo experiments, overexpression of ERO1LB in GC cells increases glutamine metabolism, facilitates cell growth and migration and prevents cell apoptosis, and vice versa. This study provides insight into the cellular heterogeneityof glutamine metabolism within the gastric mucosa in premalignant and malignant gastric lesions and identifies ERO1LB as a key orchestrator of glutamine metabolism, which may help to identify markers for GC prevention and contribute to our understanding of GC pathogenesis.

Activated polyreactive B cells are clonally expanded in autoantibody positive and patients with recent-onset type 1 diabetes

Autoreactive B cells play an important but ill-defined role in autoimmune type 1 diabetes (T1D). We isolated pancreatic islet antigen-reactive B cells from the peripheral blood of non-diabetic autoantibody-negative first-degree relatives, autoantibody-positive, and recent-onset T1D donors. Single-cell RNA sequencing analysis revealed that islet antigen-reactive B cells from autoantibody-positive and T1D donors had altered gene expression in pathways associated with B cell signaling and inflammation. Additionally, BCR sequencing uncovered a similar shift in islet antigen-reactive B cell repertoires among autoantibody-positive and T1D donors where greater clonal expansion was also observed. Notably, a substantial fraction of islet antigen-reactive B cells in autoantibody-positive and T1D donors appeared to be polyreactive, which was corroborated by analysis of recombinant monoclonal antibodies. These results expand our understanding of autoreactive B cell phenotypes during T1D and identify unique BCR repertoire changes that may serve as biomarkers for increased disease risk.

STAT3 signaling enhances tissue expansion during postimplantation mouse development

Signal transducer and activator of transcription (STAT)3 signaling has been studied extensively using mouse embryonic stem cells. Zygotic deletion of Stat3 enables embryo implantation, but thereafter, mutants resemble non-affected littermates from the previous day until around mid-gestation. This probably results from the loss of serine-phosphorylated STAT3, the predominant form in early postimplantation embryonic tissues associated with mitochondrial activity. Bulk RNA sequencing of isolated mouse epiblasts confirmed developmental delay transcriptionally. Single-cell RNA sequencing revealed the exclusion of derivatives of Stat3 null embryonic stem cells exclusively from the erythroid lineage of mid-gestation chimeras. We show that Stat3 null embryonic stem cells can differentiate into erythroid and hematopoietic lineages in vitro but become outcompeted when mixed with wild-type cells. Our results implicate a role for STAT3 in the temporal control of embryonic progression, particularly in tissues requiring rapid cell division, such as postimplantation epiblast and hematopoietic lineages. Interestingly, mutations in STAT3 are associated with short stature in humans.

Single-cell Rapid Capture Hybridization sequencing reliably detects isoform usage and coding mutations in targeted genes

Single-cell long-read sequencing has transformed our understanding of isoform usage and the mutation heterogeneity between cells. Despite unbiased in-depth analysis, the low sequencing throughput often results in insufficient read coverage, thereby limiting our ability to perform mutation calling for specific genes. Here, we developed a single-cell Rapid Capture Hybridization sequencing (scRaCH-seq) method that demonstrates high specificity and efficiency in capturing targeted transcripts using long-read sequencing, allowing an in-depth analysis of mutation status and transcript usage for genes of interest. The method includes creating a probe panel for transcript capture, using barcoded primers for pooling and efficient sequencing via Oxford Nanopore Technologies platforms. scRaCH-seq is applicable to stored and indexed single-cell cDNA, which allows analysis to be combined with existing short-read RNA-seq data sets. In our investigation of BTK and SF3B1 genes in samples from patients with chronic lymphocytic leukemia (CLL), we detect SF3B1 isoforms and mutations with high sensitivity. Integration with short-read single-cell RNA sequencing (scRNA-seq) data reveals significant gene expression differences in SF3B1-mutated CLL cells, although it does not impact the sensitivity of the anticancer drug venetoclax. scRaCH-seq's capability to study long-read transcripts of multiple genes makes it a powerful tool for single-cell genomics.

A simplified preparation method for single-nucleus RNA-sequencing using long-term frozen brain tumor tissues

Single-cell RNA-sequencing has provided intriguing new insights into research areas such as developmental processes and tumor heterogeneity. Most approaches, however, rely on the availability of fresh surgical specimens, thereby dramatically reducing the ability to profile particularly rare tissue types. Here, we optimized a method to isolate intact nuclei from long-term frozen pediatric glioma tissues. We performed a technical comparison between different single-nucleus RNA-sequencing (snRNA-seq) systems and applied the established nucleus isolation method to analyze frozen primary glioma tissues. The results show that our fast, simple and low-cost nuclear isolation protocol provides intact nuclei, which can be used in both droplet- and plate-based single-cell sequencing platforms - allowing the identification of distinct tumor cell populations and infiltrating microglia. Additional optimization to include shorter RNA fragments in the 3' sequencing library improved gene detection and cell type annotation. Taken together, the method dramatically increases the potential of studying rare tumor entities and is specifically tailored for using frozen brain tumor tissue.

Myeloid lineage C3 induces reactive gliosis and neuronal stress during CNS inflammation

Complement component C3 mediates pathology in CNS neurodegenerative diseases. Here we use scRNAseq of sorted C3-reporter positive cells from mouse brain and optic nerve to characterize C3 producing glia in experimental autoimmune encephalomyelitis (EAE), a model in which peripheral immune cells infiltrate the CNS, causing reactive gliosis and neuro-axonal pathology. We find that C3 expression in the early inflammatory stage of EAE defines disease-associated glial subtypes characterized by increased expression of genes associated with mTOR activation and cell metabolism. This pro-inflammatory subtype is abrogated with genetic C3 depletion, a finding confirmed with proteomic analyses. In addition, early optic nerve axonal injury and retinal ganglion cell oxidative stress, but not loss of post-synaptic density protein 95, are ameliorated by selective deletion of C3 in myeloid cells. These data suggest that in addition to C3b opsonization of post synaptic proteins leading to neuronal demise, C3 activation is a contributor to reactive glia in the optic nerve.

MetaDAVis: An R shiny application for metagenomic data analysis and visualization

The human microbiome exerts tremendous influence on maintaining a balance between human health and disease. High-throughput sequencing has enabled the study of microbial communities at an unprecedented resolution. Generation of massive amounts of sequencing data has also presented novel challenges to analyzing and visualizing data to make biologically relevant interpretations. We have developed an interactive Metagenome Data Analysis and Visualization (MetaDAVis) tool for 16S rRNA as well as the whole genome sequencing data analysis and visualization to address these challenges using an R Shiny application. MetaDAVis can perform six different types of analyses that include: i) Taxonomic abundance distribution; ii) Alpha and beta diversity analyses; iii) Dimension reduction tasks using PCA, t-SNE, and UMAP; iv) Correlation analysis using taxa- or sample-based data; v) Heatmap generation; and vi) Differential abundance analysis. MetaDAVis creates interactive and dynamic figures and tables from multiple methods enabling users to easily understand their data using different variables. Our program is user-friendly and easily customizable allowing those without any programming background to perform comprehensive data analyses using a standalone or web-based interface.

Single-cell sequencing exposes mast cell-derived CD52's anti-tumor action in breast cancer through the IL-6/JAK/STAT3 axis

The aggressive nature and rapid progression of triple-negative breast cancer (TNBC), coupled with a high likelihood of recurrence and mortality, underscore the critical need for effective treatments. While immunotherapy presents promising advantages for those with triple-negative breast cancer (TNBC), its efficacy is not universal. This disparity highlights the importance of investigating survival outcomes and prognostic factors for those TNBC patients who don't respond well to immunotherapy. Our study leverages both bulk and single-cell RNA sequencing data to conduct an in-depth analysis, revealing that genes associated with mast cells (PCMT1, VDAC1, YWHAB, BRD4, BTG1, and CD52) are pivotal in prognostication for TNBC patients. Laboratory experiments have further substantiated our findings, demonstrating that the overexpression of CD52 in mast cells impedes the proliferation, invasion, and metastasis of breast cancer cells. Further anti-CD52 treatment inhibiting breast tumor growth in vivo. Additionally, we have discovered that CD52 elicits its antitumor effects by meditating the IL-6/JAK/STAT3 signaling pathway. These insights not only enhance the prognostic significance of mast cells in TNBC but also pave the way for the development of novel targeted immunotherapy strategies.

A comprehensive Schizosaccharomyces pombe atlas of physical transcription factor interactions with proteins and chromatin

Transcription factors (TFs) are key regulators of gene expression, yet many of their targets and modes of action remain unknown. In Schizosaccharomyces pombe, one-third of TFs are solely homology predicted, with few experimentally validated. We created a comprehensive library of 89 endogenously tagged S. pombe TFs, mapping their protein and chromatin interactions using immunoprecipitation-mass spectrometry and chromatin immunoprecipitation sequencing. Our study identified protein interactors for half the TFs, with over a quarter potentially forming stable complexes. We discovered DNA-binding sites for most TFs across 2,027 unique genomic regions, revealing motifs for 38 TFs and uncovering a complex network of extensive TF cross- and autoregulation. Characterization of the largest TF family revealed conserved DNA sequence preferences but diverse binding patterns and identified a repressive heterodimer, Ntu1/Ntu2, linked to perinuclear gene localization. Our TFexplorer webtool makes all data interactively accessible, offering insights into TF interactions and regulatory mechanisms with broad biological relevance.

The dynamic and diverse nature of parenchyma cells in the Arabidopsis root during secondary growth

During secondary growth, the vascular cambium produces conductive xylem and phloem cells, while the phellogen (cork cambium) deposits phellem (cork) as the outermost protective barrier. Although most of the secondary tissues are made up of parenchyma cells, which are also produced by both cambia, their diversity and function are poorly understood. Here we combined single-cell RNA sequencing analysis with lineage tracing to recreate developmental trajectories of the cell types in the Arabidopsis root undergoing secondary growth. By analysing 93 reporter lines, we were able to identify 20 different cell types or cell states, many of which have not been described before. We additionally observed distinct transcriptome signatures of parenchyma cells depending on their maturation state and proximity to the conductive cell types. Our data show that both xylem and phloem parenchyma tissues are required for normal formation of conductive tissue cell types. Furthermore, we show that mature phloem parenchyma gradually obtains periderm identity, and this transformation can be accelerated by jasmonate treatment or wounding. Our study thus reveals the diversity of parenchyma cells and their capacity to undergo considerable identity changes during secondary growth.

The guinea pig serves as an alternative model to study human preimplantation development

Preimplantation development is an important window of human embryogenesis. However, ethical constraints and the limitations involved in studying human embryos often necessitate the use of alternative model systems. Here we identify the guinea pig as a promising small animal model to study human preimplantation development. Using single-cell RNA-sequencing, we generated an atlas of guinea pig preimplantation development, revealing its close resemblance to early human embryogenesis in terms of the timing of compaction, early-, mid- and late-blastocyst formation, and implantation, and the spatio-temporal expression of key lineage markers. We also show conserved roles of Hippo, MEK-ERK and JAK-STAT signalling. Furthermore, multi-species analysis highlights the spatio-temporal expression of conserved and divergent genes during preimplantation development and pluripotency. The guinea pig serves as a valuable animal model for advancing preimplantation development and stem cell research, and can be leveraged to better understand the longer-term impact of early exposures on offspring outcomes.

Characterization of single neurons reprogrammed by pancreatic cancer

The peripheral nervous system (PNS) orchestrates organ function in health and disease. Most cancers, including pancreatic ductal adenocarcinoma (PDAC), are infiltrated by PNS neurons, and this contributes to the complex tumour microenvironment (TME)1,2. However, neuronal cell bodies reside in various PNS ganglia, far from the tumour mass. Thus, cancer-innervating or healthy-organ-innervating neurons are lacking in current tissue-sequencing datasets. To molecularly characterize pancreas- and PDAC-innervating neurons at single-cell resolution, we developed Trace-n-Seq. This method uses retrograde tracing of axons from tissues to their respective ganglia, followed by single-cell isolation and transcriptomic analysis. By characterizing more than 5,000 individual sympathetic and sensory neurons, with about 4,000 innervating PDAC or healthy pancreas, we reveal novel neuronal cell types and molecular networks that are distinct to the pancreas, pancreatitis, PDAC or melanoma metastasis. We integrate single-cell datasets of innervating neurons and the TME to establish a neuron-cancer-microenvironment interactome, delineate cancer-driven neuronal reprogramming and generate a pancreatic-cancer nerve signature. Pharmacological denervation induces a pro-inflammatory TME and increases the effectiveness of immune-checkpoint inhibitors. The taxane nab-paclitaxel causes intratumoral neuropathy, which attenuates PDAC growth and, in combination with sympathetic denervation, results in synergistic tumour regression. Our multi-dimensional data provide insights into the networks and functions of PDAC-innervating neurons, and support the inclusion of denervation in future therapies.

Single-cell transcriptomic atlas of the human testis across the reproductive lifespan

Testicular aging is associated with declining reproductive health, but the molecular mechanisms are unclear. Here we generate a dataset of 214,369 single-cell transcriptomes from testicular cells of 35 individuals aged 21-69, offering a resource for studying testicular aging and physiology. Machine learning analysis reveals a stronger aging response in somatic cells compared to germ cells. Two waves of aging-related changes are identified: the first in peritubular cells of donors in their 30s, marked by increased basement membrane thickness, indicating a priming state for aging. In their 50s, testicular cells exhibit functional changes, including altered steroid metabolism in Leydig cells and immune responses in macrophages. Further analyses reveal the impact of body mass index on spermatogenic capacity as age progresses, particularly after age 45. Altogether, our findings illuminate molecular alterations during testis aging and their relationship with body mass index, providing a foundation for future research and offering potential diagnostic markers and therapeutic targets.

No Evidence for Distinct Transcriptomic Subgroups of Devil Facial Tumor Disease (DFTD)

Contagious cancers represent one of the least understood types of infections in wildlife. Devil Facial Tumor Disease (comprised of two different contagious cancers, DFT1 and DFT2) has led to an 80% decline in the Tasmanian devil (Sarcophilus harrisii ) population at the regional level since it was first observed in 1996. There are currently no treatment options for the disease, and research efforts are focused on vaccine development. Although DFT1 is clonal, phylogenomic studies have identified different genetic variants of the pathogen. We postulated that different genetic strains may have different gene expression profiles and would therefore require different vaccine components. Here, we aimed to test this hypothesis by applying two types of unsupervised clustering (hierarchical and k-means) to 35 DFT1 transcriptomes selected from the disease's four major phylogenetic clades. The two algorithms produced conflicting results, and there was low support for either method individually. Validation metrics, such as the Gap statistic method, the Elbow method, and the Silhouette method, were ambiguous, contradictory, or indicated that our dataset only consisted of a single cluster. Collectively, our results show that the different phylogenetic clades of DFT1 all have similar gene expression profiles. Previous studies have suggested that transcriptomic differences exist between tumours from different locations. However, our study differs in that it considers both tumor purity and genotypic clade when analysing differences between DFTD biopsies. These results have important implications for therapeutic development, as they indicate that a single vaccine or treatment approach has the potential to be effective for a large cross-section of DFT1 tumors. As one of the largest studies to use transcriptomics to investigate phenotypic variation within a single contagious cancer, it also provides novel insight into this unique group of diseases.

A systematic review of single-cell RNA sequencing applications and innovations

Bulk RNA sequencing is one type of RNA sequencing technique, as well as targeted RNA sequencing and whole transcriptome sequencing. It provides valuable insights into gene expression in specific cell populations or regions. However, these methods often miss the diversity of cells within complex tissues. This restriction is overcome by single-cell RNA sequencing, which records gene expression at the single-cell level. It offers a detailed picture of the diversity of cells. It is essential to study glucose homeostasis. It offers thorough explanations of cellular variation. Networks and Governance Dynamics The use of scRNA-seq in islet cells is reviewed in this study, along with sample preparation, sequencing, and computational analysis. It highlights advances in understanding cell types. Gene activity and cell interactions. Along with the challenges and limitations of scRNA-seq, this review highlights the importance of scRNA-seq in understanding complex biological processes and diseases. It is an essential resource for future research and method development in this field, which will help to build personalized treatment.

C-FOS promotes the formation of neutrophil extracellular traps and the recruitment of neutrophils in lung metastasis of triple-negative breast cancer

BACKGROUND

Neutrophil extracellular traps (NETs) are composed of DNA chains from neutrophils and associated proteolytic enzymes, which play an important role in cancer metastasis. However, the molecular mechanism of NET-mediated lung metastasis in triple-negative breast cancer (TNBC) remains unclear.

METHODS

The expression levels of NETs in breast cancer specimens and serum were analyzed and compared with normal samples. Single-cell sequencing bioinformatics analysis was conducted to identify differentially expressed genes and functional enrichment related to NET formation in patients with breast cancer. The effects of c-FOS on neutrophil recruitment and NET formation in TNBC were investigated. The upstream and downstream regulatory mechanisms mediated by c-FOS were explored through in vitro and in vivo experiments. Therapeutic approaches targeting c-FOS for treating TNBC were further studied.

RESULTS

Inhibition of c-FOS can suppress tumor growth and lung metastasis in TNBC. Mechanistically, c-FOS promotes transcription by binding to the PAD4 promoter region, facilitating the formation of NETs. Additionally, the activation of the ROS-p38 pathway further enhances c-FOS expression. High expression of c-FOS also promotes the expression of inflammatory factors, facilitating neutrophil recruitment. Both in vitro and in vivo experiments demonstrated that the application of T5224 effectively inhibits the formation of NETs, suppressing lung metastasis and tumor growth.

CONCLUSION

In summary, this study demonstrates that the ROS-p38-cFOS-PAD4 axis can increase NET formation in TNBC and promote the expression of inflammatory factors, facilitating neutrophil recruitment. Therefore, targeting this pathway may help inform new therapeutic strategies and provide new insights for immunotherapy in TNBC.

Benchmarking spatial transcriptomics technologies with the multi-sample SpatialBenchVisium dataset

BACKGROUND

Spatial transcriptomics allows gene expression to be measured within complex tissue contexts. Among the array of spatial capture technologies available is 10x Genomics' Visium platform, a popular method which enables transcriptome-wide profiling of tissue sections. Visium offers a range of sample handling and library construction methods which introduces a need for benchmarking to compare data quality and assess how well the technology can recover expected tissue features and biological signatures.

RESULTS

Here we present SpatialBenchVisium, a unique reference dataset generated from spleen tissue of mice responding to malaria infection spanning several tissue preparation protocols (both fresh frozen and FFPE, with either manual or CytAssist tissue placement). We note better quality control metrics in reference samples prepared using probe-based capture methods, particularly those processed with CytAssist, validating the improvement in data quality produced with the platform. Our analysis of replicate samples extends to explore spatially variable gene detection, the outcomes of clustering and cell deconvolution using matched single-cell RNA-sequencing data and publicly available reference data to identify cell types and tissue regions expected in the spleen. Multi-sample differential expression analysis recovered known gene signatures related to biological sex or gene knockout.

Developmental molecular signatures define de novo cortico-brainstem circuit for skilled forelimb movement

Skilled movement relies on descending cortical projections to the brainstem and spinal cord. While corticospinal neurons (CSN) have long been recognized for their role in fine motor control, the contribution of cortical projections to the brainstem remains poorly understood. Here, we identify a previously unrecognized direct cortico-brainstem circuit that emerges early in development and persists into adulthood. A subset of subcerebral projection neurons (SCPN) limit their projections to the brainstem from the earliest stages of axon extension without ever extending to the spinal cord. Using FACS purification and single-cell RNA sequencing, we show that these cortico-brainstem neurons (CBN) can be prospectively identified by the expression of Neuropeptide Y (Npy) in development. Functional silencing of Npy+ CBN in adulthood leads to impaired skilled forelimb reaching, demonstrating their essential role in adult motor control. Npy+ CBN project preferentially to rostral brainstem regions, including the midbrain reticular formation. These findings reveal developmental molecular signatures that define cortico-brainstem pathways for adult skilled movement. Our work provides new insights into the developmental logic that establishes descending cortical circuits and opens avenues for targeted investigation of their roles in motor function and recovery after injury.

Secreted neurofilament light chain after neuronal damage induces myeloid cell activation and neuroinflammation

Neurofilament light chain (NfL) is a neuron-specific cytoskeletal protein that provides structural support for axons and is released into the extracellular space following neuronal injury. While NfL has been extensively studied as a disease biomarker, the underlying release mechanisms and role in neurodegeneration remain poorly understood. Here, we find that neurons secrete low baseline levels of NfL, while neuronal damage triggers calpain-driven proteolysis and release of fragmented NfL. Secreted NfL activates microglial cells, which can be blocked with anti-NfL antibodies. We utilize in vivo single-cell RNA sequencing to profile brain cells after injection of recombinant NfL into the mouse hippocampus and find robust macrophage and microglial responses. Consistently, NfL knockout mice ameliorate microgliosis and delay symptom onset in the SOD1 mouse model of amyotrophic lateral sclerosis (ALS). Our results show that released NfL can activate myeloid cells in the brain and is, thus, a potential therapeutic target for neurodegenerative diseases.

Single-cell genome and transcriptome sequencing without upfront whole-genome amplification reveals cell state plasticity of melanoma subclones

Single-cell multi-omics methods enable the study of cell state diversity, which is largely determined by the interplay of the genome, epigenome, and transcriptome. Here, we describe Gtag&T-seq, a genome-and-transcriptome sequencing (G&T-seq) protocol of the same single cells that omits whole-genome amplification (WGA) by using direct genomic tagmentation (Gtag). Gtag drastically decreases the cost and improves coverage uniformity at single-cell and pseudo-bulk levels compared to WGA-based G&T-seq. We also show that transcriptome-based DNA copy number inference has limited resolution and accuracy, underlining the importance of affordable multi-omic approaches. Applying Gtag&T-seq to a melanoma xenograft model before treatment and at minimal residual disease revealed differential cell state plasticity and treatment response between cancer subclones. In summary, Gtag&T-seq is a low-cost and accurate single-cell multi-omics method that explores genetic alterations and their functional consequences in single cells at scale.