Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA-sequencing data quality control

Pronounced early differentiation underlies zebra finch gonadal germ cell development

The diversity of germ cell developmental strategies has been well documented across many vertebrate clades. However, much of our understanding of avian primordial germ cell (PGC) specification and differentiation has derived from only one species, the chicken (Gallus gallus). Of the three major classes of birds, chickens belong to Galloanserae, representing less than 4% of species, while nearly 95% of extant bird species belong to Neoaves. This represents a significant gap in our knowledge of germ cell development across avian species, hampering efforts to adapt genome editing and reproductive technologies developed in chicken to other birds. We therefore applied single-cell RNA sequencing to investigate inter-species differences in germ cell development between chicken and zebra finch (Taeniopygia castanotis), a Neoaves songbird species and a common model of vocal learning. Analysis of early embryonic male and female gonads revealed the presence of two distinct early germ cell types in zebra finch and only one in chicken. Both germ cell types expressed zebra finch Germline Restricted Chromosome (GRC) genes, present only in songbirds among birds. One of the zebra finch germ cell types expressed the canonical PGC markers, as did chicken, but with expression differences in several signaling pathways and biological processes. The second zebra finch germ cell cluster was marked by proliferation and fate determination markers, indicating beginning of differentiation. Notably, these two zebra finch germ cell populations were present in both male and female zebra finch gonads as early as HH25. Using additional chicken developmental stages, similar germ cell heterogeneity was identified in the more developed gonads of females, but not males. Overall, our study demonstrates a substantial heterochrony in zebra finch germ cell development compared to chicken, indicating a richer diversity of avian germ cell developmental strategies than previously known.

Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics

Single-cell transcriptomics has broadened our understanding of cellular diversity and gene expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has emerged as a tool to contextualize single cells in multicellular neighbourhoods and to identify spatially recurrent phenotypes, or ecotypes. These technologies have generated vast datasets with targeted-transcriptome and whole-transcriptome profiles of hundreds to millions of cells. Such data have provided new insights into developmental hierarchies, cellular plasticity and diverse tissue microenvironments, and spurred a burst of innovation in computational methods for single-cell analysis. In this Review, we discuss recent advancements, ongoing challenges and prospects in identifying and characterizing cell states and multicellular neighbourhoods. We discuss recent progress in sample processing, data integration, identification of subtle cell states, trajectory modelling, deconvolution and spatial analysis. Furthermore, we discuss the increasing application of deep learning, including foundation models, in analysing single-cell and spatial transcriptomics data. Finally, we discuss recent applications of these tools in the fields of stem cell biology, immunology, and tumour biology, and the future of single-cell and spatial transcriptomics in biological research and its translation to the clinic.

Resident synovial macrophages in synovial fluid: Implications for immunoregulation

Resident synovial macrophages (RSMs) are anti-inflammatory, self-renewing macrophages that provide physical immune sequestration of the joint space from the peripheral immune system. Increased permeability of this structure is associated with peripheral immune cells in the synovial fluid (SF). Direct measures of synovial barrier integrity are possible with tissue histology, but after barrier breakdown, if these cells perpetuate or initiate chronic inflammation in SF remains unknown. We sought to identify RSM in human SF as an indirect measure of synovial barrier integrity. To validate findings, we created a novel ex vivo explant model using human synovium. scRNA-seq revealed these SF RSMs upregulated pro-fibrotic and pro-osteoclastic pathways in inflammatory arthritis, but not septic arthritis. Increased frequencies of RSMs in SF was associated with increased sRANKL regardless of underlying pathology. These findings suggest the frequency of RSMs in SF may correlate with synovial barrier damage and in turn, potential damage to joint structures.

A comprehensive analysis framework for evaluating commercial single-cell RNA sequencing technologies

This study examined nine prominent commercially available single-cell RNA sequencing (scRNA-seq) kits across four technology groups. Each kit was characterized using peripheral blood mononuclear cells (PBMCs) from a single donor, which enabled consistent assessment of factors such as analytical performance, protocol duration and cost. The Chromium Fixed RNA Profiling kit from 10× Genomics, with its probe-based RNA detection method, demonstrated the best overall performance. The Rhapsody WTA kit from Becton Dickinson exhibited a balance between performance and cost. Importantly, we introduce the read utilization metric, which differentiates scRNA-seq kits based on the efficiency of converting sequencing reads into usable counts. Thus, read utilization is an important feature that substantially impacts sensitivity and cost. With data from 169, 262 cells, our work provides a comprehensive comparison of commercial scRNA-seq technologies to facilitate the effective implementation of single-cell studies.

Multiomic-based immune response profiling in migraine, vestibular migraine and Meniere's disease

Migraine (MI) is the most common neurological disease, affecting with 20% of the world population. A subset of 25% of MI patients showcase concurrent vestibular symptoms, which may classify as vestibular migraine (VM). Meniere's disease (MD) is a complex inner ear disorder defined by episodes of vertigo associated with tinnitus and sensorineural hearing loss with a significant autoimmune/autoinflammatory contribution, which symptoms overlap with VM. Blood samples from 18 patients with MI (5), VM (5) and MD (8) and 6 controls were collected and compared in a case-control study. Droplet-isolated nuclei from mononuclear cells used to generate scRNAseq and scATACseq data sets from MI, VM and MD. MI and VM have no differences in their immune transcriptome; therefore, they were considered as a single cluster for further analyses. Natural Killer (NK) cells transcriptomic data support a polarisation triggered by Type 1 innate immune cells via the release of interleukin (IL)-12, IL-15 and IL-18. According to the monocyte scRNAseq data, there were two MD clusters, one inactive and one driven by monocytes. The unique pathways of the MI + VM cluster were cellular responses to metal ions, whereas MD monocyte-driven cluster pathways showed responses to biotic stimuli. MI and MD have different immune responses. These findings support that MI and VM have a Type 1 immune lymphoid cell response, and that there are two clusters of MD patients, one inactive and one Monocyte-driven.

A cross-disease resource of living human microglia identifies disease-enriched subsets and tool compounds recapitulating microglial states

Human microglia play a pivotal role in neurological diseases, but we still have an incomplete understanding of microglial heterogeneity, which limits the development of targeted therapies directly modulating their state or function. Here, we use single-cell RNA sequencing to profile 215,680 live human microglia from 74 donors across diverse neurological diseases and CNS regions. We observe a central divide between oxidative and heterocyclic metabolism and identify microglial subsets associated with antigen presentation, motility and proliferation. Specific subsets are enriched in susceptibility genes for neurodegenerative diseases or the disease-associated microglial signature. We validate subtypes in situ with an RNAscope-immunofluorescence pipeline and high-dimensional MERFISH. We also leverage our dataset as a classification resource, finding that induced pluripotent stem cell model systems capture substantial in vivo heterogeneity. Finally, we identify and validate compounds that recapitulate certain subtypes in vitro, including camptothecin, which downregulates the signature of disease-enriched subtypes and upregulates a signature previously associated with Alzheimer's disease.

Fibroblast-Mediated Macrophage Recruitment Supports Acute Wound Healing

Epithelial and immune cells have long been appreciated for their contribution to the early immune response after injury; however, much less is known about the role of mesenchymal cells. Using single-nuclei RNA sequencing, we defined changes in gene expression associated with inflammation 1 day after wounding in mouse skin. Compared with those in keratinocytes and myeloid cells, we detected enriched expression of proinflammatory genes in fibroblasts associated with deeper layers of the skin. In particular, SCA1+ fibroblasts were enriched for numerous chemokines, including CCL2, CCL7, and IL-33, compared with SCA1- fibroblasts. Genetic deletion of Ccl2 in fibroblasts resulted in fewer wound-bed macrophages and monocytes during injury-induced inflammation, with reduced revascularization and re-epithelialization during the proliferation phase of healing. These findings highlight the important contribution of fibroblast-derived factors to injury-induced inflammation and the impact of immune cell dysregulation on subsequent tissue repair.

De novo detection of somatic variants in high-quality long-read single-cell RNA sequencing data

In cancer, genetic and transcriptomic variations generate clonal heterogeneity, leading to treatment resistance. Long-read single-cell RNA sequencing (LR scRNA-seq) has the potential to detect genetic and transcriptomic variations simultaneously. Here, we present LongSom, a computational workflow leveraging high-quality LR scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy-number alterations (CNAs), and gene fusions, to reconstruct the tumor clonal heterogeneity. Before somatic variants calling, LongSom re-annotates marker gene based cell types using cell mutational profiles. LongSom distinguishes somatic SNVs from noise and germline polymorphisms by applying an extensive set of hard filters and statistical tests. Applying LongSom to human ovarian cancer samples, we detected clinically relevant somatic SNVs that were validated against matched DNA samples. Leveraging somatic SNVs and fusions, LongSom found subclones with different predicted treatment outcomes. In summary, LongSom enables de novo variant detection without the need for normal samples, facilitating the study of cancer evolution, clonal heterogeneity, and treatment resistance.

γδ T17 Cells Regulate the Acute Antiviral Response of NK Cells in HSV-1-Infected Corneas

Purpose

To determine whether γδ T cells regulate natural killer (NK) cells in the herpes simplex virus 1 (HSV-1)-infected cornea.

Methods

CD57Bl/6 (wild-type [WT]), TCRδ-/-, and IFN-γ-/- mice were infected intracorneally with HSV-1. TCR-/- mice were treated with IL-17A at 24 hours post-infection (PI), and the WT mice received treatments of fingolimod (FTY720) and anti-IL-17A. At 48 hours PI, corneas were excised, and intracellular staining flow cytometry was performed, as well as multiplex analysis. Additionally, single-cell RNA sequencing (scRNAseq) was done to analyze the transcriptome of NK cells from WT and TCRδ-/- mice.

Results

In mice lacking γδ T cells, there were significantly fewer NK cells following ocular HSV-1 infection. This reduction of NK cells corresponded with lower levels of cytokines and chemokines associated with the antiviral response. Furthermore, NK cells from WT mice had enriched IL-17A signaling compared to those from TCRδ-/- mice. The NK cell response was partially rescued in TCRδ-/- mice by administration of IL-17A. Correspondingly, the NK cell response could be blunted in WT mice by administration of anti-IL-17A. Finally, IFN-γ-/- mice had significantly less IL-17A production compared to WT mice.

Conclusions

γδ T17 cells promote NK cell accumulation in HSV-1-infected corneas. In turn, NK cells secrete IFN-γ, which negatively regulates further IL-17A production by γδ T cells.

Optimized protocol for the multiomics processing of cryopreserved human kidney tissue

Biobanking of tissue from clinically obtained kidney biopsies for later analysis with multiomic approaches, such as single-cell technologies, proteomics, metabolomics, and the different types of imaging, is an inevitable step to overcome the need of disease model systems and toward translational medicine. Hence, collection protocols that ensure integration into daily clinical routines by the usage of preservation media that do not require liquid nitrogen but instantly preserve kidney tissue for both clinical and scientific analyses are necessary. Thus, we modified a robust single-nucleus dissociation protocol for kidney tissue stored snap-frozen or in the preservation media RNAlater and CellCover. Using at first porcine kidney tissue as a surrogate for human kidney tissue, we conducted single-nucleus RNA sequencing with the widely recognized Chromium 10X Genomics platform. The resulting datasets from each storage condition were analyzed to identify any potential variations in transcriptomic profiles. Furthermore, we assessed the suitability of the preservation media for additional analysis techniques such as proteomics, metabolomics, and the preservation of tissue architecture for histopathological examination including immunofluorescence staining. In this study, we show that in daily clinical routines, the preservation medium RNAlater facilitates the collection of highly preserved human kidney biopsies and enables further analysis with cutting-edge techniques like single-nucleus RNA sequencing, proteomics, and histopathological evaluation. Only metabolome analysis is currently restricted to snap-frozen tissue. This work will contribute to build tissue biobanks with well-defined cohorts of the respective kidney disease that can be deeply molecularly characterized, opening up new horizons for the identification of unique cells, pathways and biomarkers for the prevention, early identification, and targeted therapy of kidney diseases.NEW & NOTEWORTHY In this study, we addressed challenges in integrating clinically obtained kidney biopsies into everyday clinical routines. Using porcine kidneys, we evaluated preservation media (RNAlater and CellCover) versus snap freezing for multi-omics processing. Our analyses highlighted RNAlater's suitability for single-nucleus RNA sequencing, proteome analysis and histopathological evaluation. Only metabolomics are currently restricted to snap-frozen biopsies. Our research established a cryopreservation protocol that facilitates tissue biobanking for advancing precision medicine in nephrology.

The multifaceted role of mitochondria in cardiac function: insights and approaches

Cardiovascular disease (CVD) remains a global economic burden even in the 21st century with 85% of deaths resulting from heart attacks. Despite efforts in reducing the risk factors, and enhancing pharmacotherapeutic strategies, challenges persist in early identification of disease progression and functional recovery of damaged hearts. Targeting mitochondrial dysfunction, a key player in the pathogenesis of CVD has been less successful due to its role in other coexisting diseases. Additionally, it is the only organelle with an agathokakological function that is a remedy and a poison for the cell. In this review, we describe the origins of cardiac mitochondria and the role of heteroplasmy and mitochondrial subpopulations namely the interfibrillar, subsarcolemmal, perinuclear, and intranuclear mitochondria in maintaining cardiac function and in disease-associated remodeling. The cumulative evidence of mitochondrial retrograde communication with the nucleus is addressed, highlighting the need to study the genotype-phenotype relationships of specific organelle functions with CVD by using approaches like genome-wide association study (GWAS). Finally, we discuss the practicality of computational methods combined with single-cell sequencing technologies to address the challenges of genetic screening in the identification of heteroplasmy and contributory genes towards CVD.

Single-Cell RNA Profiling of Ocular Adnexal Sebaceous Carcinoma Reveals a Complex Tumor Microenvironment and Identifies New Biomarkers

PURPOSE

Ocular adnexal sebaceous carcinoma (OaSC) is an aggressive malignancy that often necessitates orbital exenteration. Its tumor composition and transcriptional profile remain largely unknown, which poses a significant barrier to medical advances. Here, we report the first in-depth transcriptomic analysis of OaSC at the single-cell resolution and discern mechanisms underlying cancer progression for the discovery of potential globe-sparing immunotherapies, targeted therapies, and biomarkers to guide clinical management.

DESIGN

Laboratory investigation with a retrospective observational case series.

METHODS

Single-cell RNA sequencing was performed on six patient specimens: three primary tumors, two tumors with pagetoid spread, and a normal tarsus sample. Cellular components were identified via gene signatures. Molecular pathways underlying tumorigenesis and pagetoid spread were discerned via gene ontology analysis of the differentially expressed genes between specimens. CALML5 immunohistochemistry was performed on an archival cohort of OaSC, squamous cell carcinoma, ocular surface squamous neoplasia (OSSN), and basal cell carcinoma cases.

RESULTS

Analysis of 29,219 cells from OaSC specimens revealed tumor, immune, and stromal cells. Tumor-infiltrating immune cells include a diversity of cell types, including exhausted T-cell populations. In primary OaSC tumors, mitotic nuclear division and oxidative phosphorylation pathways are upregulated, while lipid biosynthesis and metabolism pathways are downregulated. Epithelial tissue migration pathways are upregulated in tumor cells undergoing pagetoid spread. Single-cell RNA sequencing analyses also revealed that CALML5 is upregulated in OaSC tumor cells. Diffuse nuclear and cytoplasmic CALML5 staining was present in 28 of 28 (100%) OaSC cases. Diffuse nuclear and membranous CALML5 staining was present in 5 of 25 (20%) squamous cell carcinoma and OSSN cases, while diffuse nuclear staining was present in 1 of 12 (8%) basal cell carcinoma cases.

CONCLUSIONS

This study reveals a complex OaSC tumor microenvironment and confirms that the CALML5 immunohistochemical stain is a sensitive diagnostic marker.

Visualizing scRNA-Seq data at population scale with GloScope

Increasingly, scRNA-Seq studies explore cell populations across different samples and the effect of sample heterogeneity on organism's phenotype. However, relatively few bioinformatic methods have been developed which adequately address the variation between samples for such population-level analyses. We propose a framework for representing the entire single-cell profile of a sample, which we call a GloScope representation. We implement GloScope on scRNA-Seq datasets from study designs ranging from 12 to over 300 samples and demonstrate how GloScope allows researchers to perform essential bioinformatic tasks at the sample-level, in particular visualization and quality control assessment.

Multiomic single-cell sequencing defines tissue-specific responses in Stevens-Johnson syndrome and toxic epidermal necrolysis

Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS/TEN) is a rare but life-threatening cutaneous drug reaction mediated by human leukocyte antigen (HLA) class I-restricted CD8+ T cells. For unbiased assessment of cellular immunopathogenesis, here we perform single-cell (sc) transcriptome, surface proteome, and T cell receptor (TCR) sequencing on unaffected skin, affected skin, and blister fluid from 15 SJS/TEN patients. From 109,888 cells, we identify 15 scRNA-defined subsets. Keratinocytes express markers indicating HLA class I-restricted antigen presentation and appear to trigger the proliferation of and killing by cytotoxic CD8+ tissue-resident T cells that express granulysin, granzyme B, perforin, LAG3, CD27, and LINC01871, and signal through the PKM, MIF, TGFβ, and JAK-STAT pathways. In affected tissue, cytotoxic CD8+ T cells express private expanded and unexpanded TCRαβ that are absent or unexpanded in unaffected skin, and mixed populations of macrophages and fibroblasts express pro-inflammatory markers or those favoring repair. This data identifies putative cytotoxic TCRs and therapeutic targets.

Epstein-Barr virus reactivation induces divergent abortive, reprogrammed, and host shutoff states by lytic progression

Viral infection leads to heterogeneous cellular outcomes ranging from refractory to abortive and fully productive states. Single cell transcriptomics enables a high resolution view of these distinct post-infection states. Here, we have interrogated the host-pathogen dynamics following reactivation of Epstein-Barr virus (EBV). While benign in most people, EBV is responsible for infectious mononucleosis, up to 2% of human cancers, and is a trigger for the development of multiple sclerosis. Following latency establishment in B cells, EBV reactivates and is shed in saliva to enable infection of new hosts. Beyond its importance for transmission, the lytic cycle is also implicated in EBV-associated oncogenesis. Conversely, induction of lytic reactivation in latent EBV-positive tumors presents a novel therapeutic opportunity. Therefore, defining the dynamics and heterogeneity of EBV lytic reactivation is a high priority to better understand pathogenesis and therapeutic potential. In this study, we applied single-cell techniques to analyze diverse fate trajectories during lytic reactivation in three B cell models. Consistent with prior work, we find that cell cycle and MYC expression correlate with cells refractory to lytic reactivation. We further found that lytic induction yields a continuum from abortive to complete reactivation. Abortive lytic cells upregulate NFκB and IRF3 pathway target genes, while cells that proceed through the full lytic cycle exhibit unexpected expression of genes associated with cellular reprogramming. Distinct subpopulations of lytic cells further displayed variable profiles for transcripts known to escape virus-mediated host shutoff. These data reveal previously unknown and promiscuous outcomes of lytic reactivation with broad implications for viral replication and EBV-associated oncogenesis.

Sodium chloride in the tumor microenvironment enhances T cell metabolic fitness and cytotoxicity

The efficacy of antitumor immunity is associated with the metabolic state of cytotoxic T cells, which is sensitive to the tumor microenvironment. Whether ionic signals affect adaptive antitumor immune responses is unclear. In the present study, we show that there is an enrichment of sodium in solid tumors from patients with breast cancer. Sodium chloride (NaCl) enhances the activation state and effector functions of human CD8+ T cells, which is associated with enhanced metabolic fitness. These NaCl-induced effects translate into increased tumor cell killing in vitro and in vivo. Mechanistically, NaCl-induced changes in CD8+ T cells are linked to sodium-induced upregulation of Na+/K+-ATPase activity, followed by membrane hyperpolarization, which magnifies the electromotive force for T cell receptor (TCR)-induced calcium influx and downstream TCR signaling. We therefore propose that NaCl is a positive regulator of acute antitumor immunity that might be modulated for ex vivo conditioning of therapeutic T cells, such as CAR T cells.

A sexually dimorphic hepatic cycle of periportal VLDL generation and subsequent pericentral VLDLR-mediated re-uptake

Recent single-cell transcriptomes revealed spatiotemporal programmes of liver function on the sublobular scale. However, how sexual dimorphism affected this space-time logic remained poorly understood. We addressed this by performing scRNA-seq in the mouse liver, which revealed that sex, space and time together markedly influence xenobiotic detoxification and lipoprotein metabolism. The very low density lipoprotein receptor (VLDLR) exhibits a pericentral expression pattern, with significantly higher mRNA and protein levels in female mice. Conversely, VLDL assembly is periportally biased, suggesting a sexually dimorphic hepatic cycle of periportal formation and pericentral uptake of VLDL. In humans, VLDLR expression is also pericentral, with higher mRNA and protein levels in premenopausal women compared to similarly aged men. Individuals with low hepatic VLDLR expression show a high prevalence of atherosis in the coronary artery already at an early age and an increased incidence of heart attack.

Spatial Transcriptomic Profiling of Human Saphenous Vein Exposed to Ex Vivo Arterial Haemodynamics-Implications for Coronary Artery Bypass Graft Patency and Vein Graft Disease

Vein graft disease is the process by which saphenous vein grafts, utilised for revascularisation during coronary artery bypass graft surgery, undergo an inflammation-driven intimal hyperplasia and accelerated atherosclerosis process in subsequent years after implantation. The role of the arterial circulation, particularly the haemodynamic properties' impact on graft patency, have been investigated but have not to date been explored in depth at the transcriptomic level. We have undertaken the first-in-man spatial transcriptomic analysis of the long saphenous vein in response to ex vivo acute arterial haemodynamic stimulation, utilising a combination of a custom 3D-printed perfusion bioreactor and the 10X Genomics Visium Spatial Gene Expression technology. We identify a total of 413 significant genes (372 upregulated and 41 downregulated) differentially expressed in response to arterial haemodynamic conditions. These genes were associated with pathways including NFkB, TNF, MAPK, and PI3K/Akt, among others. These are established pathways involved in the initiation of an early pro-inflammatory response, leukocyte activation and adhesion signalling, tissue remodelling, and cellular differentiation. Utilising unsupervised clustering analysis, we have been able to classify subsets of the expression based on cell type and with spatial resolution. These findings allow for further characterisation of the early saphenous vein graft transcriptional landscape during the earliest stage of implantation that contributes to vein graft disease, in particular validation of pathways and druggable targets that could contribute towards the therapeutic inhibition of processes underpinning vein graft disease.

Protocol to achieve high-resolution single-cell transcriptomics of cardiomyocytes in multiple species

Single-cell RNA sequencing (scRNA-seq) remains state-of-the-art for transcriptomic cell-mapping. Here, we provide a protocol to generate high-resolution scRNA-seq of rare cardiomyocyte populations (e.g., regenerating/dividing, etc.) from mouse and zebrafish hearts as well as induced pluripotent stem cells, collected in time to achieve detailed transcriptomic insight. We describe the serial steps of viability staining, methanol fixation, storage, and cell sorting to preserve RNA integrity suited for scRNA-seq as well as the quality assessment of the data as shown by examples. For complete details on the use and execution of this protocol, please refer to Bak et al.1.

LMNA-Related Dilated Cardiomyopathy: Single-Cell Transcriptomics during Patient-Derived iPSC Differentiation Support Cell Type and Lineage-Specific Dysregulation of Gene Expression and Development for Cardiomyocytes and Epicardium-Derived Cells with Lamin A/C Haploinsufficiency

LMNA-related dilated cardiomyopathy (DCM) is an autosomal-dominant genetic condition with cardiomyocyte and conduction system dysfunction often resulting in heart failure or sudden death. The condition is caused by mutation in the Lamin A/C (LMNA) gene encoding Type-A nuclear lamin proteins involved in nuclear integrity, epigenetic regulation of gene expression, and differentiation. The molecular mechanisms of the disease are not completely understood, and there are no definitive treatments to reverse progression or prevent mortality. We investigated possible mechanisms of LMNA-related DCM using induced pluripotent stem cells derived from a family with a heterozygous LMNA c.357-2A>G splice-site mutation. We differentiated one LMNA-mutant iPSC line derived from an affected female (Patient) and two non-mutant iPSC lines derived from her unaffected sister (Control) and conducted single-cell RNA sequencing for 12 samples (four from Patients and eight from Controls) across seven time points: Day 0, 2, 4, 9, 16, 19, and 30. Our bioinformatics workflow identified 125,554 cells in raw data and 110,521 (88%) high-quality cells in sequentially processed data. Unsupervised clustering, cell annotation, and trajectory inference found complex heterogeneity: ten main cell types; many possible subtypes; and lineage bifurcation for cardiac progenitors to cardiomyocytes (CMs) and epicardium-derived cells (EPDCs). Data integration and comparative analyses of Patient and Control cells found cell type and lineage-specific differentially expressed genes (DEGs) with enrichment, supporting pathway dysregulation. Top DEGs and enriched pathways included 10 ZNF genes and RNA polymerase II transcription in pluripotent cells (PP); BMP4 and TGF Beta/BMP signaling, sarcomere gene subsets and cardiogenesis, CDH2 and EMT in CMs; LMNA and epigenetic regulation, as well as DDIT4 and mTORC1 signaling in EPDCs. Top DEGs also included XIST and other X-linked genes, six imprinted genes (SNRPN, PWAR6, NDN, PEG10, MEG3, MEG8), and enriched gene sets related to metabolism, proliferation, and homeostasis. We confirmed Lamin A/C haploinsufficiency by allelic expression and Western blot. Our complex Patient-derived iPSC model for Lamin A/C haploinsufficiency in PP, CM, and EPDC provided support for dysregulation of genes and pathways, many previously associated with Lamin A/C defects, such as epigenetic gene expression, signaling, and differentiation. Our findings support disruption of epigenomic developmental programs, as proposed in other LMNA disease models. We recognized other factors influencing epigenetics and differentiation; thus, our approach needs improvement to further investigate this mechanism in an iPSC-derived model.

A practical handbook on single-cell RNA sequencing data quality control and downstream analysis

Advancements in single-cell analysis have facilitated high-resolution observation of the transcriptome in individual cells. However, standards for obtaining high-quality cells and data analysis pipelines remain variable. Here, we provide the groundwork for improving the quality of single-cell analysis by delineating guidelines for selecting high-quality cells and considerations throughout the analysis. This review will streamline researchers' access to single-cell analysis and serve as a valuable guide for analysis.

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.

Fasting induces metabolic switches and spatial redistributions of lipid processing and neuronal interactions in tanycytes

The ependyma lining the third ventricle (3V) in the mediobasal hypothalamus plays a crucial role in energy balance and glucose homeostasis. It is characterized by a high functional heterogeneity and plasticity, but the underlying molecular mechanisms governing its features are not fully understood. Here, 5481 hypothalamic ependymocytes were cataloged using FACS-assisted scRNAseq from fed, 12h-fasted, and 24h-fasted adult male mice. With standard clustering analysis, typical ependymal cells and β2-tanycytes appear sharply defined, but other subpopulations, β1- and α-tanycytes, display fuzzy boundaries with few or no specific markers. Pseudospatial approaches, based on the 3V neuroanatomical distribution, enable the identification of specific versus shared tanycyte markers and subgroup-specific versus general tanycyte functions. We show that fasting dynamically shifts gene expression patterns along the 3V, leading to a spatial redistribution of cell type-specific responses. Altogether, we show that changes in energy status induce metabolic and functional switches in tanycyte subpopulations, providing insights into molecular and functional diversity and plasticity within the tanycyte population.

Single-Cell RNA Sequencing and Its Applications in Pituitary Research

BACKGROUND

Mounting evidence underscores the significance of cellular diversity within the endocrine system and the intricate interplay between different cell types and tissues, essential for preserving physiological balance and influencing disease trajectories. The pituitary gland, a central player in the endocrine orchestra, exemplifies this complexity with its assortment of hormone-secreting and nonsecreting cells.

SUMMARY

The pituitary gland houses several types of cells responsible for hormone production, alongside nonsecretory cells like fibroblasts and endothelial cells, each playing a crucial role in the gland's function and regulatory mechanisms. Despite the acknowledged importance of these cellular interactions, the detailed mechanisms by which they contribute to pituitary gland physiology and pathology remain largely uncharted. The last decade has seen the emergence of groundbreaking technologies such as single-cell RNA sequencing, offering unprecedented insights into cellular heterogeneity and interactions. However, the application of this advanced tool in exploring the pituitary gland's complexities has been scant. This review provides an overview of this methodology, highlighting its strengths and limitations, and discusses future possibilities for employing it to deepen our understanding of the pituitary gland and its dysfunction in disease states.

KEY MESSAGE

Single-cell RNA sequencing technology offers an unprecedented means to study the heterogeneity and interactions of pituitary cells, though its application has been limited thus far. Further utilization of this tool will help uncover the complex physiological and pathological mechanisms of the pituitary, advancing research and treatment of pituitary diseases.

CNS-wide repopulation by hematopoietic-derived microglia-like cells corrects progranulin deficiency in mice

Hematopoietic stem cell transplantation can deliver therapeutic proteins to the central nervous system (CNS) through transplant-derived microglia-like cells. However, current conditioning approaches result in low and slow engraftment of transplanted cells in the CNS. Here we optimized a brain conditioning regimen that leads to rapid, robust, and persistent microglia replacement without adverse effects on neurobehavior or hematopoiesis. This regimen combines busulfan myeloablation and six days of Colony-stimulating factor 1 receptor inhibitor PLX3397. Single-cell analyses revealed unappreciated heterogeneity of microglia-like cells with most cells expressing genes characteristic of homeostatic microglia, brain-border-associated macrophages, and unique markers. Cytokine analysis in the CNS showed transient inductions of myeloproliferative and chemoattractant cytokines that help repopulate the microglia niche. Bone marrow transplant of progranulin-deficient mice conditioned with busulfan and PLX3397 restored progranulin in the brain and eyes and normalized brain lipofuscin storage, proteostasis, and lipid metabolism. This study advances our understanding of CNS repopulation by hematopoietic-derived cells and demonstrates its therapeutic potential for treating progranulin-dependent neurodegeneration.

scRNA-seq reveals the diversity of the developing cardiac cell lineage and molecular players in heart rhythm regulation

We utilized scRNA-seq to delineate the diversity of cell types in the zebrafish heart. Transcriptome profiling of over 50,000 cells at 48 and 72 hpf defined at least 18 discrete cell lineages of the developing heart. Utilizing well-established gene signatures, we identified a population of cells likely to be the primary pacemaker and characterized the transcriptome profile defining this critical cell type. Two previously uncharacterized genes, atp1b3b and colec10, were found to be enriched in the sinoatrial cardiomyocytes. CRISPR/Cas9-mediated knockout of these two genes significantly reduced heart rate, implicating their role in cardiac development and conduction. Additionally, we describe other cardiac cell lineages, including the endothelial and neural cells, providing their expression profiles as a resource. Our results established a detailed atlas of the developing heart, providing valuable insights into cellular and molecular mechanisms, and pinpointed potential new players in heart rhythm regulation.

CHIT1 at diagnosis predicts faster disability progression and reflects early microglial activation in multiple sclerosis

Multiple sclerosis (MS) is characterized by heterogeneity in disease course and prediction of long-term outcome remains a major challenge. Here, we investigate five myeloid markers - CHIT1, CHI3L1, sTREM2, GPNMB and CCL18 - in the cerebrospinal fluid (CSF) at diagnostic lumbar puncture in a longitudinal cohort of 192 MS patients. Through mixed-effects and machine learning models, we show that CHIT1 is a robust predictor for faster disability progression. Integrative analysis of 11 CSF and 26 central nervous system (CNS) parenchyma single-cell/nucleus RNA sequencing samples reveals CHIT1 to be predominantly expressed by microglia located in active MS lesions and enriched for lipid metabolism pathways. Furthermore, we find CHIT1 expression to accompany the transition from a homeostatic towards a more activated, MS-associated cell state in microglia. Neuropathological evaluation in post-mortem tissue from 12 MS patients confirms CHIT1 production by lipid-laden phagocytes in actively demyelinating lesions, already in early disease stages. Altogether, we provide a rationale for CHIT1 as an early biomarker for faster disability progression in MS.

SpotSweeper: spatially-aware quality control for spatial transcriptomics

Quality control (QC) is a crucial step to ensure the reliability and accuracy of the data obtained from RNA sequencing experiments, including spatially-resolved transcriptomics (SRT). Existing QC approaches for SRT that have been adopted from single-nucleus RNA sequencing (snRNA-seq) methods are confounded by spatial biology and are inappropriate for SRT data. In addition, no methods currently exist for identifying histological tissue artifacts unique to SRT. Here, we introduce SpotSweeper, spatially-aware QC methods for identifying local outliers and regional artifacts in SRT. SpotSweeper evaluates the quality of individual spots relative to their local neighborhood, thus minimizing bias due to biological heterogeneity, and uses multiscale methods to detect regional artifacts. Using SpotSweeper on publicly available data, we identified a consistent set of Visium barcodes/spots as systematically low quality and demonstrate that SpotSweeper accurately identifies two distinct types of regional artifacts, resulting in improved downstream clustering and marker gene detection for spatial domains.

Characterization of dUTPase expression in mouse postnatal development and adult neurogenesis

The enzyme dUTPase has an essential role in maintaining genomic integrity. In mouse, nuclear and mitochondrial isoforms of the enzyme have been described. Here we present the isoform-specific mRNA expression levels in different murine organs during development using RT-qPCR. In this study, we analyzed organs of 14.5-day embryos and of postnatal 2-, 4-, 10-week- and 13-month-old mice. We demonstrate organ-, sex- and developmental stage-specific differences in the mRNA expression levels of both isoforms. We found high mRNA expression level of the nuclear isoform in the embryo brain, and the expression level remained relatively high in the adult brain as well. This was surprising, since dUTPase is known to play an important role in proliferating cells, and mass production of neural cells is completed by adulthood. Thus, we investigated the pattern of the dUTPase protein expression specifically in the adult brain with immunostaining and found that dUTPase is present in the germinative zones, the subventricular and the subgranular zones, where neurogenesis occurs and in the rostral migratory stream where neuroblasts migrate to the olfactory bulb. These novel findings suggest that dUTPase may have a role in cell differentiation and indicate that accurate dTTP biosynthesis can be vital, especially in neurogenesis.

Mdivi-1: Effective but complex mitochondrial fission inhibitor

Mdivi-1, Mitochondrial DIVIsion inhibitor 1, has been widely employed in research under the assumption that it exclusively influences mitochondrial fusion, but effects other than mitochondrial dynamics have been underinvestigated. This paper provides transcriptome and DNA methylome-wide analysis for Mdivi-1 treated SH-SY5Y human neuroblastoma cells using RNA sequencing (RNA-seq) and methyl capture sequencing (MC-seq) methods. Gene ontology analysis of RNA sequences revealed that p53 transcriptional gene network and DNA replication initiation-related genes were significantly up and down-regulated, respectively, showing the correlation with the arrest cell cycle in the G1 phase. MC-seq, a powerful sequencing method for capturing DNA methylation status in CpG sites, revealed that although Mdivi-1 does not induce dramatic DNA methylation change, the subtle alterations were concentrated within the CpG island. Integrative analysis of both sequencing data disclosed that the p53 transcriptional network was activated while the Parkinson's disease pathway was halted. Next, we investigated several changes in mitochondria in response to Mdivi-1. Copy number and transcription of mitochondrial DNA were suppressed. ROS levels increased, and elevated ROS triggered mitochondrial retrograde signaling rather than inducing direct DNA damage. In this study, we could better understand the molecular network of Mdivi-1 by analyzing DNA methylation and mRNA transcription in the nucleus and further investigating various changes in mitochondria, providing inspiration for studying nuclear-mitochondrial communications.

Immunoreactive Microenvironment Modulator GBP5 Suppresses Ovarian Cancer Progression by Inducing Canonical Pyroptosis

Ovarian cancer has the highest mortality among gynecological malignancies, and exploring effective strategies to reverse the immunosuppressive tumor microenvironment in patients remains a pressing scientific challenge. In this study, we identified a pyroptosis-related protective factor, GBP5, which significantly inhibits the growth of ovarian cancer cells and patient-derived ovarian cancer organoids, impeding the invasion and migration of ovarian cancer cells. Results of immunohistochemistry and external single-cell data verification were consistent. Further research confirmed that GBP5 in ovarian cancer cell can induce canonical pyroptosis through JAK2/STAT1 pathway, thereby restraining the progression of ovarian cancer. Interestingly, in this study, we also discovered that ovarian cancer cells with high GBP5 expression exhibit increased expressions of CXCL9/10/11 in a co-culture assay. Subsequent immune cell infiltration analyses revealed the remodeling of immunosuppressive microenvironment in ovarian cancer patients, characterized by increased infiltration and polarization of M1 macrophages. External immunotherapy database analysis showed profound potential for the application of GBP5 in immunotherapy strategies for ovarian cancer. Overall, our study demonstrates that the protective factor GBP5 significantly inhibits ovarian cancer progression, triggering canonical pyroptosis through the JAK2-STAT1 pathway. Driven by its pro-inflammatory nature, it can also enhance M1 macrophages polarization and reverse immunosuppressive microenvironment, thus providing new insights for ovarian cancer treatment.

Characterisation of premature cell senescence in Alzheimer's disease using single nuclear transcriptomics

Aging is associated with cell senescence and is the major risk factor for AD. We characterized premature cell senescence in postmortem brains from non-diseased controls (NDC) and donors with Alzheimer's disease (AD) using imaging mass cytometry (IMC) and single nuclear RNA (snRNA) sequencing (> 200,000 nuclei). We found increases in numbers of glia immunostaining for galactosidase beta (> fourfold) and p16INK4A (up to twofold) with AD relative to NDC. Increased glial expression of genes related to senescence was associated with greater β-amyloid load. Prematurely senescent microglia downregulated phagocytic pathways suggesting reduced capacity for β-amyloid clearance. Gene set enrichment and pseudo-time trajectories described extensive DNA double-strand breaks (DSBs), mitochondrial dysfunction and ER stress associated with increased β-amyloid leading to premature senescence in microglia. We replicated these observations with independent AD snRNA-seq datasets. Our results describe a burden of senescent glia with AD that is sufficiently high to contribute to disease progression. These findings support the hypothesis that microglia are a primary target for senolytic treatments in AD.

Reanalysis of single-cell RNA sequencing data does not support herpes simplex virus 1 latency in non-neuronal ganglionic cells in mice

Most individuals are latently infected with herpes simplex virus type 1 (HSV-1), and it is well-established that HSV-1 establishes latency in sensory neurons of peripheral ganglia. However, it was recently proposed that latent HSV-1 is also present in immune cells recovered from the ganglia of experimentally infected mice. Here, we reanalyzed the single-cell RNA sequencing (scRNA-Seq) data that formed the basis for that conclusion. Unexpectedly, off-target priming in 3' scRNA-Seq experiments enabled the detection of non-polyadenylated HSV-1 latency-associated transcript (LAT) intronic RNAs. However, LAT reads were near-exclusively detected in mixed populations of cells undergoing cell death. Specific loss of HSV-1 LAT and neuronal transcripts during quality control filtering indicated widespread destruction of neurons, supporting the presence of contaminating cell-free RNA in other cells following tissue processing. In conclusion, the reported detection of latent HSV-1 in non-neuronal cells is best explained using compromised scRNA-Seq datasets.IMPORTANCEMost people are infected with herpes simplex virus type 1 (HSV-1) during their life. Once infected, the virus generally remains in a latent (silent) state, hiding within the neurons of peripheral ganglia. Periodic reactivation (reawakening) of the virus may cause fresh diseases such as cold sores. A recent study using single-cell RNA sequencing (scRNA-Seq) proposed that HSV-1 can also establish latency in the immune cells of mice, challenging existing dogma. We reanalyzed the data from that study and identified several flaws in the methodologies and analyses performed that invalidate the published conclusions. Specifically, we showed that the methodologies used resulted in widespread destruction of neurons which resulted in the presence of contaminants that confound the data analysis. We thus conclude that there remains little to no evidence for HSV-1 latency in immune cells.

Comparative analysis of 10X Chromium vs. BD Rhapsody whole transcriptome single-cell sequencing technologies in complex human tissues

The development of single-cell omics tools has enabled scientists to study the tumor microenvironment (TME) in unprecedented detail. However, each of the different techniques may have its unique strengths and limitations. Here we directly compared two commercially available high-throughput single-cell RNA sequencing (scRNA-seq) technologies - droplet-based 10X Chromium vs. microwell-based BD Rhapsody - using paired samples from patients with localized prostate cancer (PCa) undergoing a radical prostatectomy. Although high technical consistency was observed in unraveling the whole transcriptome, the relative abundance of cell populations differed. Cells with low mRNA content such as T cells were underrepresented in the droplet-based system, at least partly due to lower RNA capture rates. In contrast, microwell-based scRNA-seq recovered less cells of epithelial origin. Moreover, we discovered platform-dependent variabilities in mRNA quantification and cell-type marker annotation. Overall, our study provides important information for selection of the appropriate scRNA-seq platform and for the interpretation of published results.

Long-read direct RNA sequencing of the mitochondrial transcriptome of Saccharomyces cerevisiae reveals condition-dependent intron abundance

Mitochondria fulfil many essential roles and have their own genome, which is expressed as polycistronic transcripts that undergo co- or posttranscriptional processing and splicing. Due to the inherent complexity and limited technical accessibility of the mitochondrial transcriptome, fundamental questions regarding mitochondrial gene expression and splicing remain unresolved, even in the model eukaryote Saccharomyces cerevisiae. Long-read sequencing could address these fundamental questions. Therefore, a method for the enrichment of mitochondrial RNA and sequencing using Nanopore technology was developed, enabling the resolution of splicing of polycistronic genes and the quantification of spliced RNA. This method successfully captured the full mitochondrial transcriptome and resolved RNA splicing patterns with single-base resolution and was applied to explore the transcriptome of S. cerevisiae grown with glucose or ethanol as the sole carbon source, revealing the impact of growth conditions on mitochondrial RNA expression and splicing. This study uncovered a remarkable difference in the turnover of Group II introns between yeast grown in either mostly fermentative or fully respiratory conditions. Whether this accumulation of introns in glucose medium has an impact on mitochondrial functions remains to be explored. Combined with the high tractability of the model yeast S. cerevisiae, the developed method enables to monitor mitochondrial transcriptome responses in a broad range of relevant contexts, including oxidative stress, apoptosis and mitochondrial diseases.

Population-level comparisons of gene regulatory networks modeled on high-throughput single-cell transcriptomics data

Single-cell technologies enable high-resolution studies of phenotype-defining molecular mechanisms. However, data sparsity and cellular heterogeneity make modeling biological variability across single-cell samples difficult. Here we present SCORPION, a tool that uses a message-passing algorithm to reconstruct comparable gene regulatory networks from single-cell/nuclei RNA-sequencing data that are suitable for population-level comparisons by leveraging the same baseline priors. Using synthetic data, we found that SCORPION outperformed 12 existing gene regulatory network reconstruction techniques. Using supervised experiments, we show that SCORPION can accurately identify differences in regulatory networks between wild-type and transcription factor-perturbed cells. We demonstrate SCORPION's scalability to population-level analyses using a single-cell RNA-sequencing atlas containing 200,436 cells from colorectal cancer and adjacent healthy tissues. The differences between tumor regions detected by SCORPION are consistent across multiple cohorts as well as with our understanding of disease progression, and elucidate phenotypic regulators that may impact patient survival.

Macrophage profiling in atherosclerosis: understanding the unstable plaque

The development and rupture of atherosclerotic plaques is a major contributor to myocardial infarctions and ischemic strokes. The dynamic evolution of the plaque is largely attributed to monocyte/macrophage functions, which respond to various stimuli in the plaque microenvironment. To this end, macrophages play a central role in atherosclerotic lesions through the uptake of oxidized low-density lipoprotein that gets trapped in the artery wall, and the induction of an inflammatory response that can differentially affect the stability of the plaque in men and women. In this environment, macrophages can polarize towards pro-inflammatory M1 or anti-inflammatory M2 phenotypes, which represent the extremes of the polarization spectrum that include Mhem, M(Hb), Mox, and M4 populations. However, this traditional macrophage model paradigm has been redefined to include numerous immune and nonimmune cell clusters based on in-depth unbiased single-cell approaches. The goal of this review is to highlight (1) the phenotypic and functional properties of monocyte subsets in the circulation, and macrophage populations in atherosclerotic plaques, as well as their contribution towards stable or unstable phenotypes in men and women, and (2) single-cell RNA sequencing studies that have advanced our knowledge of immune, particularly macrophage signatures present in the atherosclerotic niche. We discuss the importance of performing high-dimensional approaches to facilitate the development of novel sex-specific immunotherapies that aim to reduce the risk of cardiovascular events.

Pan-Cancer Single-Nucleus Total RNA Sequencing Using snHH-Seq

Tumor heterogeneity and its drivers impair tumor progression and cancer therapy. Single-cell RNA sequencing is used to investigate the heterogeneity of tumor ecosystems. However, most methods of scRNA-seq amplify the termini of polyadenylated transcripts, making it challenging to perform total RNA analysis and somatic mutation analysis.Therefore, a high-throughput and high-sensitivity method called snHH-seq is developed, which combines random primers and a preindex strategy in the droplet microfluidic platform. This innovative method allows for the detection of total RNA in single nuclei from clinically frozen samples. A robust pipeline to facilitate the analysis of full-length RNA-seq data is also established. snHH-seq is applied to more than 730 000 single nuclei from 32 patients with various tumor types. The pan-cancer study enables it to comprehensively profile data on the tumor transcriptome, including expression levels, mutations, splicing patterns, clone dynamics, etc. New malignant cell subclusters and exploring their specific function across cancers are identified. Furthermore, the malignant status of epithelial cells is investigated among different cancer types with respect to mutation and splicing patterns. The ability to detect full-length RNA at the single-nucleus level provides a powerful tool for studying complex biological systems and has broad implications for understanding tumor pathology.

Single-cell RNA sequencing reveals the transcriptional heterogeneity of Tbx18-positive cardiac cells during heart development

The T-box family transcription factor 18 (Tbx18) has been found to play a critical role in regulating the development of the mammalian heart during the primary stages of embryonic development while the cellular heterogeneity and landscape of Tbx18-positive (Tbx18+) cardiac cells remain incompletely characterized. Here, we analyzed prior published single-cell RNA sequencing (scRNA-seq) mouse heart data to explore the heterogeneity of Tbx18+ cardiac cell subpopulations and provide a comprehensive transcriptional landscape of Tbx18+ cardiac cells during their development. Bioinformatic analysis methods were utilized to identify the heterogeneity between cell groups. Based on the gene expression characteristics, Tbx18+ cardiac cells can be classified into a minimum of two distinct cell populations, namely fibroblast-like cells and cardiomyocytes. In terms of temporal heterogeneity, these cells exhibit three developmental stages, namely the MEM stage, ML_P0 stage, and P stage Tbx18+ cardiac cells. Furthermore, Tbx18+ cardiac cells encompass several cell types, including cardiac progenitor-like cells, cardiomyocytes, and epicardial/stromal cells, as determined by specific transcriptional regulatory networks. The scRNA-seq results revealed the involvement of extracellular matrix (ECM) signals and epicardial epithelial-to-mesenchymal transition (EMT) in the development of Tbx18+ cardiac cells. The utilization of a lineage-tracing model served to validate the crucial function of Tbx18 in the differentiation of cardiac cells. Consequently, these findings offer a comprehensive depiction of the cellular heterogeneity within Tbx18+ cardiac cells.

ZEBRA: a hierarchically integrated gene expression atlas of the murine and human brain at single-cell resolution

The molecular causes and mechanisms of neurodegenerative diseases remain poorly understood. A growing number of single-cell studies have implicated various neural, glial, and immune cell subtypes to affect the mammalian central nervous system in many age-related disorders. Integrating this body of transcriptomic evidence into a comprehensive and reproducible framework poses several computational challenges. Here, we introduce ZEBRA, a large single-cell and single-nucleus RNA-seq database. ZEBRA integrates and normalizes gene expression and metadata from 33 studies, encompassing 4.2 million human and mouse brain cells sampled from 39 brain regions. It incorporates samples from patients with neurodegenerative diseases like Alzheimer's disease, Parkinson's disease, and Multiple sclerosis, as well as samples from relevant mouse models. We employed scVI, a deep probabilistic auto-encoder model, to integrate the samples and curated both cell and sample metadata for downstream analysis. ZEBRA allows for cell-type and disease-specific markers to be explored and compared between sample conditions and brain regions, a cell composition analysis, and gene-wise feature mappings. Our comprehensive molecular database facilitates the generation of data-driven hypotheses, enhancing our understanding of mammalian brain function during aging and disease. The data sets, along with an interactive database are freely available at https://www.ccb.uni-saarland.de/zebra.

Mitochondrial reverse electron transport in myeloid cells perpetuates neuroinflammation

Sustained smouldering, or low grade, activation of myeloid cells is a common hallmark of several chronic neurological diseases, including multiple sclerosis (MS) 1 . Distinct metabolic and mitochondrial features guide the activation and the diverse functional states of myeloid cells 2 . However, how these metabolic features act to perpetuate neuroinflammation is currently unknown. Using a multiomics approach, we identified a new molecular signature that perpetuates the activation of myeloid cells through mitochondrial complex II (CII) and I (CI) activity driving reverse electron transport (RET) and the production of reactive oxygen species (ROS). Blocking RET in pro-inflammatory myeloid cells protected the central nervous system (CNS) against neurotoxic damage and improved functional outcomes in animal disease models in vivo . Our data show that RET in myeloid cells is a potential new therapeutic target to foster neuroprotection in smouldering inflammatory CNS disorders 3 .

State transition and intercellular communication of synovial fibroblasts in response to chronic and acute shoulder injuries unveiled by single-cell transcriptomic analyses

PURPOSE

We aimed to investigate the heterogeneity of synovial fibroblasts and their potential to undergo cell state transitions at the resolution of single cells.

MATERIALS AND METHODS

We employed the single-cell RNA sequencing (scRNA-seq) approach to comprehensively map the cellular landscape of the shoulder synovium in individuals with chronic rotator cuff tears (RCTs) and acute proximal humerus fractures (PHFs). Utilizing unbiased clustering analysis, we successfully identified distinct subpopulations of fibroblasts within the synovial environment. We utilized Monocle 3 to delineate the trajectory of synovial fibroblast state transition. And we used CellPhone DB v2.1.0 to predict cell-cell communication patterns within the synovial microenvironment.

RESULTS

We identified eight main cell clusters in the shoulder synovium. Unbiased clustering analysis identified four synovial fibroblast subpopulations, with diverse biological functions associated with protein secretion, ECM remodeling, inflammation regulation and cell division. Lining, mesenchymal, pro-inflammatory and proliferative fibroblasts subsets were identified. Combining the results from StemID and characteristic gene features, mesenchymal fibroblasts exhibited characteristics of fibroblast progenitor cells. The trajectory of synovial fibroblast state transition showed a transition from mesenchymal to pro-inflammatory and lining phenotypes. In addition, the cross talk between fibroblast subclusters increased in degenerative shoulder diseases compared to acute trauma.

CONCLUSION

We successfully generated the scRNA-seq transcriptomic atlas of the shoulder synovium, which provides a comprehensive understanding of the heterogeneity of synovial fibroblasts, their potential to undergo state transitions, and their intercellular communication in the context of chronic degenerative and acute traumatic shoulder diseases.

Comparison of Single Cell Transcriptome Sequencing Methods: Of Mice and Men

Single cell RNAseq has been a big leap in many areas of biology. Rather than investigating gene expression on a whole organism level, this technology enables scientists to get a detailed look at rare single cells or within their cell population of interest. The field is growing, and many new methods appear each year. We compared methods utilized in our core facility: Smart-seq3, PlexWell, FLASH-seq, VASA-seq, SORT-seq, 10X, Evercode, and HIVE. We characterized the equipment requirements for each method. We evaluated the performances of these methods based on detected features, transcriptome diversity, mitochondrial RNA abundance and multiplets, among others and benchmarked them against bulk RNA sequencing. Here, we show that bulk transcriptome detects more unique transcripts than any single cell method. While most methods are comparable in many regards, FLASH-seq and VASA-seq yielded the best metrics, e.g., in number of features. If no equipment for automation is available or many cells are desired, then HIVE or 10X yield good results. In general, more recently developed methods perform better. This also leads to the conclusion that older methods should be phased out, and that the development of single cell RNAseq methods is still progressing considerably.

Automatic quality control of single-cell and single-nucleus RNA-seq using valiDrops

Single-cell and single-nucleus RNA-sequencing (sxRNA-seq) measures gene expression in individual cells or nuclei enabling comprehensive characterization of cell types and states. However, isolation of cells or nuclei for sxRNA-seq releases contaminating RNA, which can distort biological signals, through, for example, cell damage and transcript leakage. Thus, identifying barcodes containing high-quality cells or nuclei is a critical analytical step in the processing of sxRNA-seq data. Here, we present valiDrops, an automated method to identify high-quality barcodes and flag dead cells. In valiDrops, barcodes are initially filtered using data-adaptive thresholding on community-standard quality metrics, and subsequently, valiDrops uses a novel clustering-based approach to identify barcodes with distinct biological signals. We benchmark valiDrops and show that biological signals from cell types and states are more distinct, easier to separate and more consistent after filtering by valiDrops compared to existing tools. Finally, we show that valiDrops can predict and flag dead cells with high accuracy. This novel classifier can further improve data quality or be used to identify dead cells to interrogate the biology of cell death. Thus, valiDrops is an effective and easy-to-use method to improve data quality and biological interpretation. Our method is openly available as an R package at www.github.com/madsen-lab/valiDrops.

Integrative single-cell RNA-seq analysis of vascularized cerebral organoids

BACKGROUND

Cerebral organoids are three-dimensional in vitro cultured brains that mimic the function and structure of the human brain. One of the major challenges for cerebral organoids is the lack of functional vasculature. Without perfusable vessels, oxygen and nutrient supplies may be insufficient for long-term culture, hindering the investigation of the neurovascular interactions. Recently, several strategies for the vascularization of human cerebral organoids have been reported. However, the generalizable trends and variability among different strategies are unclear due to the lack of a comprehensive characterization and comparison of these vascularization strategies. In this study, we aimed to explore the effect of different vascularization strategies on the nervous system and vasculature in human cerebral organoids.

RESULTS

We integrated single-cell RNA sequencing data of multiple vascularized and vascular organoids and fetal brains from publicly available datasets and assessed the protocol-dependent and culture-day-dependent effects on the cell composition and transcriptomic profiles in neuronal and vascular cells. We revealed the similarities and uniqueness of multiple vascularization strategies and demonstrated the transcriptomic effects of vascular induction on neuronal and mesodermal-like cell populations. Moreover, our data suggested that the interaction between neurons and mesodermal-like cell populations is important for the cerebrovascular-specific profile of endothelial-like cells.

CONCLUSIONS

This study highlights the current challenges to vascularization strategies in human cerebral organoids and offers a benchmark for the future fabrication of vascularized organoids.

Sources of variability in the human platelet transcriptome

Platelets are anucleated cells produced by megakaryocytes, from which they inherit all the components necessary to carry their functions. They circulate in blood vessels where they play essential roles in coagulation, wound repair or inflammation, and have been implicated in various pathological conditions such as thrombosis, viral infection or cancer progression. The importance of these cells has been established over a century ago, and effective anti-platelet medications with different mechanisms of action have since been developed. However, these therapies are not always effective and can incur adverse events, thus a better understanding of platelets molecular processes is needed to address these issues and improve our understanding of platelet functions. In recent years, an increasing number of studies have leveraged OMICs technologies to analyze their content and identify molecular signatures and mechanisms associated with platelet functions and platelet related disorders. In particular, the increased accessibility of microarrays and RNA sequencing opened the way for studies of the platelet transcriptome under a wide array of conditions. These studies revealed distinct expression profiles in diverse pathologies, which could lead to the discovery of novel biomarkers and therapeutic targets, and suggests a dynamic transcriptome that could influence platelet mechanisms. In this review, we highlight the different sources of transcript level variability in platelets while summarizing recent advances and discoveries from this emerging field.

Construction of a hepatocytes-related and protein kinase-related gene signature in HCC based on ScRNA-Seq analysis and machine learning algorithm

With recent advancements in single-cell sequencing and machine learning methods, new insights into hepatocellular carcinoma (HCC) progression have been provided. Protein kinase-related genes (PKRGs) affect cell growth, differentiation, apoptosis, and signaling during HCC progression, making the predictive relevance of PKRGs in HCC highly necessary for personalized medicine. In this study, we analyzed single-cell data of HCC and used the machine learning method of LASSO regression to construct PKRG prediction models in six major cell types. CDK4 and AURKB were found to be the best PKRG prognostic signature for predicting the overall survival of HCC patients (including TCGA, ICGC, and GEO datasets) in hepatocytes. Independent clinical factors were further screened out using the COX regression method, and a nomogram combining PKRGs and cancer status was created. Treatment with Palbociclib (CDK4 Inhibitor) and Barasertib (AURKB Inhibitor) inhibited HCC cell migration. Patients classified as PKRG high- or low-risk groups showed different tumor mutation burdens, immune infiltrations, and gene enrichment. The PKRG high-risk group showed higher tumor mutation burdens and gene set enrichment analysis indicated that cell cycle, base excision repair, and RNA degradation pathways were more enriched in these patients. Additionally, the PKRG high-risk group demonstrated higher infiltration levels of Naïve CD8+ T cells, Endothelial cells, M2 macrophage, and Tregs than the low-risk group. In summary, this study established the hepatocytes-related PKRG signature for prognostic stratification at the single-cell level by using machine learning algorithms in HCC and identified potential HCC treatment targets based on the PKRG signature.

CRISPR/Cas9-based depletion of 16S ribosomal RNA improves library complexity of single-cell RNA-sequencing in planarians

BACKGROUND

Single-cell RNA-sequencing (scRNA-seq) relies on PCR amplification to retrieve information from vanishingly small amounts of starting material. To selectively enrich mRNA from abundant non-polyadenylated transcripts, poly(A) selection is a key step during library preparation. However, some transcripts, such as mitochondrial genes, can escape this elimination and overwhelm libraries. Often, these transcripts are removed in silico, but whether physical depletion improves detection of rare transcripts in single cells is unclear.

RESULTS

We find that a single 16S ribosomal RNA is widely enriched in planarian scRNA-seq datasets, independent of the library preparation method. To deplete this transcript from scRNA-seq libraries, we design 30 single-guide RNAs spanning its length. To evaluate the effects of depletion, we perform a side-by-side comparison of the effects of eliminating the 16S transcript and find a substantial increase in the number of genes detected per cell, coupled with virtually complete loss of the 16S RNA. Moreover, we systematically determine that library complexity increases with a limited number of PCR cycles following CRISPR treatment. When compared to in silico depletion of 16S, physically removing it reduces dropout rates, retrieves more clusters, and reveals more differentially expressed genes.

CONCLUSIONS

Our results show that abundant transcripts reduce the retrieval of informative transcripts in scRNA-seq and distort the analysis. Physical removal of these contaminants enables the detection of rare transcripts at lower sequencing depth, and also outperforms in silico depletion. Importantly, this method can be easily customized to deplete any abundant transcript from scRNA-seq libraries.

Deletion of the inhibitory co-receptor CTLA-4 enhances and invigorates chimeric antigen receptor T cells

Chimeric antigen receptor (CAR) T cell therapy targeting CD19 has achieved tremendous success treating B cell malignancies; however, some patients fail to respond due to poor autologous T cell fitness. To improve response rates, we investigated whether disruption of the co-inhibitory receptors CTLA4 or PD-1 could restore CART function. CRISPR-Cas9-mediated deletion of CTLA4 in preclinical models of leukemia and myeloma improved CAR T cell proliferation and anti-tumor efficacy. Importantly, this effect was specific to CTLA4 and not seen upon deletion of CTLA4 and/or PDCD1 in CAR T cells. Mechanistically, CTLA4 deficiency permitted unopposed CD28 signaling and maintenance of CAR expression on the T cell surface under conditions of high antigen load. In clinical studies, deletion of CTLA4 rescued the function of T cells from patients with leukemia that previously failed CAR T cell treatment. Thus, selective deletion of CTLA4 reinvigorates dysfunctional chronic lymphocytic leukemia (CLL) patient T cells, providing a strategy for increasing patient responses to CAR T cell therapy.

Effect of methanol fixation on single-cell RNA sequencing of the murine dentate gyrus

Single-cell RNA sequencing (scRNA-seq) provides a powerful tool to evaluate the transcriptomic landscape and heterogeneity of thousands of cells in parallel. However, complex study designs or the unavailability of in-house instruments require the temporal disconnection between sample preparation and library construction, raising the need for efficient sample preservation methods which are compatible with scRNA-seq downstream analysis. Several studies evaluated the effect of methanol fixation as preservation method, yet none of them deeply assessed its effect on adult primary dissociated brain tissue. Here, we evaluated its effect on murine dentate gyrus (DG) single cell suspensions and on subsequent scRNA-seq downstream analysis by performing SOrting and Robot-assisted Transcriptome SEQuencing (SORT-seq), a partially robotized version of the CEL-seq2 protocol. Our results show that MeOH fixation preserves RNA integrity and has no apparent effects on cDNA library construction. They also suggest that fixation protects from sorting-induced cell stress and increases the proportion of high-quality cells. Despite evidence of mRNA leakage in fixed cells, their relative gene expression levels correlate well with those of fresh cells and fixation does not significantly affect the variance of the dataset. Moreover, it allows the identification of all major DG cell populations, including neural precursors, granule neurons and different glial cell types, with a tendency to preserve more neurons that are underrepresented in fresh samples. Overall, our data show that MeOH fixation is suitable for preserving primary neural cells for subsequent single-cell RNA profiling, helping to overcome challenges arising from complex workflows, improve experimental flexibility and facilitate scientific collaboration.