Classification of low quality cells from single-cell RNA-seq data

Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets

BACKGROUND

Reproducibility is a major concern in biomedical studies, and existing publication guidelines do not solve the problem. Batch effects and quality imbalances between groups of biological samples are major factors hampering reproducibility. Yet, the latter is rarely considered in the scientific literature.

RESULTS

Our analysis uses 40 clinically relevant RNA-seq datasets to quantify the impact of quality imbalance between groups of samples on the reproducibility of gene expression studies. High-quality imbalance is frequent (14 datasets; 35%), and hundreds of quality markers are present in more than 50% of the datasets. Enrichment analysis suggests common stress-driven effects among the low-quality samples and highlights a complementary role of transcription factors and miRNAs to regulate stress response. Preliminary ChIP-seq results show similar trends. Quality imbalance has an impact on the number of differential genes derived by comparing control to disease samples (the higher the imbalance, the higher the number of genes), on the proportion of quality markers in top differential genes (the higher the imbalance, the higher the proportion; up to 22%) and on the proportion of known disease genes in top differential genes (the higher the imbalance, the lower the proportion). We show that removing outliers based on their quality score improves the resulting downstream analysis.

CONCLUSIONS

Thanks to a stringent selection of well-designed datasets, we demonstrate that quality imbalance between groups of samples can significantly reduce the relevance of differential genes, consequently reducing reproducibility between studies. Appropriate experimental design and analysis methods can substantially reduce the problem.

Single-cell analysis of innate spinal cord regeneration identifies intersecting modes of neuronal repair

Adult zebrafish have an innate ability to recover from severe spinal cord injury. Here, we report a comprehensive single nuclear RNA sequencing atlas that spans 6 weeks of regeneration. We identify cooperative roles for adult neurogenesis and neuronal plasticity during spinal cord repair. Neurogenesis of glutamatergic and GABAergic neurons restores the excitatory/inhibitory balance after injury. In addition, a transient population of injury-responsive neurons (iNeurons) show elevated plasticity 1 week post-injury. We found iNeurons are injury-surviving neurons that acquire a neuroblast-like gene expression signature after injury. CRISPR/Cas9 mutagenesis showed iNeurons are required for functional recovery and employ vesicular trafficking as an essential mechanism that underlies neuronal plasticity. This study provides a comprehensive resource of the cells and mechanisms that direct spinal cord regeneration and establishes zebrafish as a model of plasticity-driven neural repair.

Limiting the impact of protein leakage in single-cell proteomics

Limiting artifacts during sample preparation can significantly increase data quality in single-cell proteomics experiments. Towards this goal, we characterize the impact of protein leakage by analyzing thousands of primary single cells that were prepared either fresh immediately after dissociation or cryopreserved and prepared at a later date. We directly identify permeabilized cells and use the data to define a signature for protein leakage. We use this signature to build a classifier for identifying damaged cells that performs accurately across cell types and species.

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

An iPSC-derived small intestine-on-chip with self-organizing epithelial, mesenchymal, and neural cells

Human induced pluripotent stem cell (hiPSC)-derived intestinal organoids are valuable tools for researching developmental biology and personalized therapies, but their closed topology and relative immature state limit applications. Here, we use organ-on-chip technology to develop a hiPSC-derived intestinal barrier with apical and basolateral access in a more physiological in vitro microenvironment. To replicate growth factor gradients along the crypt-villus axis, we locally expose the cells to expansion and differentiation media. In these conditions, intestinal epithelial cells self-organize into villus-like folds with physiological barrier integrity, and myofibroblasts and neurons emerge and form a subepithelial tissue in the bottom channel. The growth factor gradients efficiently balance dividing and mature cell types and induce an intestinal epithelial composition, including absorptive and secretory lineages, resembling the composition of the human small intestine. This well-characterized hiPSC-derived intestine-on-chip system can facilitate personalized studies on physiological processes and therapy development in the human small intestine.

Identifying potential therapeutic targets in lung adenocarcinoma: a multi-omics approach integrating bulk and single-cell RNA sequencing with Mendelian randomization

Our research aimed to identify new therapeutic targets for Lung adenocarcinoma (LUAD), a major subtype of non-small cell lung cancer known for its low 5-year survival rate of 22%. By employing a comprehensive methodological approach, we analyzed bulk RNA sequencing data from 513 LUAD and 59 non-tumorous tissues, identifying 2,688 differentially expressed genes. Using Mendelian randomization (MR), we identified 74 genes with strong evidence for a causal effect on risk of LUAD. Survival analysis on these genes revealed significant differences in survival rates for 13 of them. Our pathway enrichment analysis highlighted their roles in immune response and cell communication, deepening our understanding. We also utilized single-cell RNA sequencing (scRNA-seq) to uncover cell type-specific gene expression patterns within LUAD, emphasizing the tumor microenvironment's heterogeneity. Pseudotime analysis further assisted in assessing the heterogeneity of tumor cell populations. Additionally, protein-protein interaction (PPI) network analysis was conducted to evaluate the potential druggability of these identified genes. The culmination of our efforts led to the identification of five genes (tier 1) with the most compelling evidence, including SECISBP2L, PRCD, SMAD9, C2orf91, and HSD17B13, and eight genes (tier 2) with convincing evidence for their potential as therapeutic targets.

Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis

Single-cell multiomic analysis of the epigenome, transcriptome, and proteome allows for comprehensive characterization of the molecular circuitry that underpins cell identity and state. However, the holistic interpretation of such datasets presents a challenge given a paucity of approaches for systematic, joint evaluation of different modalities. Here, we present Panpipes, a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale. Panpipes allows reliable and customizable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations.

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

Exploring kidney allograft rejection: A proof-of-concept study using spatial transcriptomics

In this proof-of-concept study, spatial transcriptomics combined with public single-cell ribonucleic acid-sequencing data were used to explore the potential of this technology to study kidney allograft rejection. We aimed to map gene expression patterns within diverse pathologic states by examining biopsies classified across nonrejection, T cell-mediated acute rejection, interstitial fibrosis, and tubular atrophy. Our results revealed distinct immune cell signatures, including those of T and B lymphocytes, monocytes, mast cells, and plasma cells, and their spatial organization within the renal interstitium. We also mapped chemokine receptors and ligands to study immune cell migration and recruitment. Finally, our analysis demonstrated differential spatial enrichment of transcription signatures associated with kidney allograft rejection across various biopsy regions. Interstitium regions displayed higher enrichment scores for rejection-associated gene expression patterns than tubular areas, which had negative scores. This implies that these signatures are primarily driven by processes unfolding in the renal interstitium. Overall, this study highlights the value of spatial transcriptomics for revealing cellular heterogeneity and immune signatures in renal transplant biopsies and demonstrates its potential for studying the molecular and cellular mechanisms associated with rejection. However, certain limitations must be borne in mind regarding the development and future applications of this technology.

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

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

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. Molecular mechanisms of 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 (4 Patient and 8 Control) 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 (CM) and Epicardium-Derived Cells (EPDC). Data integration and comparative analyses of Patient and Control cells found cell type and lineage differentially expressed genes (DEG) with enrichment to support pathway dysregulation. Top DEG 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 CM; LMNA and epigenetic regulation and DDIT4 and mTORC1 signaling in EPDC. Top DEG also included: XIST and other X-linked genes, six imprinted genes: SNRPN , PWAR6 , NDN , PEG10 , MEG3 , MEG8 , and enriched gene sets in 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.

Elevated phagocytic capacity directs innate spinal cord repair

Immune cells elicit a continuum of transcriptional and functional states after spinal cord injury (SCI). In mammals, inefficient debris clearance and chronic inflammation impede recovery and overshadow pro-regenerative immune functions. We found that, unlike mammals, zebrafish SCI elicits transient immune activation and efficient debris clearance, without causing chronic inflammation. Single-cell transcriptomics and inducible genetic ablation showed zebrafish macrophages are highly phagocytic and required for regeneration. Cross-species comparisons between zebrafish and mammalian macrophages identified transcription and immune response regulator ( tcim ) as a macrophage-enriched zebrafish gene. Genetic deletion of zebrafish tcim impairs phagocytosis and regeneration, causes aberrant and chronic immune activation, and can be rescued by transplanting wild-type immune precursors into tcim mutants. Conversely, genetic expression of human TCIM accelerates debris clearance and regeneration by reprogramming myeloid precursors into activated phagocytes. This study establishes a central requirement for elevated phagocytic capacity to achieve innate spinal cord repair.

Single-Cell Dissection of the Immune Response After Acute Myocardial Infarction

BACKGROUND

The immune system's role in ST-segment-elevated myocardial infarction (STEMI) remains poorly characterized but is an important driver of recurrent cardiovascular events. While anti-inflammatory drugs show promise in reducing recurrence risk, their broad immune system impairment may induce severe side effects. To overcome these challenges, a nuanced understanding of the immune response to STEMI is needed.

METHODS

For this, we compared peripheral blood mononuclear single-cell RNA-sequencing (scRNA-seq) and plasma protein expression over time (hospital admission, 24 hours, and 6-8 weeks post-STEMI) in 38 patients and 38 controls (95 995 diseased and 33 878 control peripheral blood mononuclear cells).

RESULTS

Compared with controls, classical monocytes were increased and CD56dim natural killer cells were decreased in patients with STEMI at admission and persisted until 24 hours post-STEMI. The largest gene expression changes were observed in monocytes, associating with changes in toll-like receptor, interferon, and interleukin signaling activity. Finally, a targeted cardiovascular biomarker panel revealed expression changes in 33/92 plasma proteins post-STEMI. Interestingly, interleukin-6R, MMP9 (matrix metalloproteinase-9), and LDLR (low-density lipoprotein receptor) were affected by coronary artery disease-associated genetic risk variation, disease status, and time post-STEMI, indicating the importance of considering these aspects when defining potential future therapies.

CONCLUSIONS

Our analyses revealed the immunologic pathways disturbed by STEMI, specifying affected cell types and disease stages. Additionally, we provide insights into patients expected to benefit most from anti-inflammatory treatments by identifying the genetic variants and disease stage at which these variants affect the outcome of these (drug-targeted) pathways. These findings advance our knowledge of the immune response post-STEMI and provide guidance for future therapeutic studies.

Tango-seq: overlaying transcriptomics on connectomics to identify neurons downstream of Drosophila clock neurons

Knowing how neural circuits change with neuronal plasticity and differ between individuals is important to fully understand behavior. Connectomes are typically assembled using electron microscopy, but this is low throughput and impractical for analyzing plasticity or mutations. Here, we modified the trans-Tango genetic circuit-tracing technique to identify neurons synaptically downstream of Drosophila s-LNv clock neurons, which show 24hr plasticity rhythms. s-LNv target neurons were labeled specifically in adult flies using a nuclear reporter gene, which facilitated their purification and then single cell sequencing. We call this Tango-seq, and it allows transcriptomic data - and thus cell identity - to be overlayed on top of anatomical data. We found that s-LNvs preferentially make synaptic connections with a subset of the CNMa+ DN1p clock neurons, and that these are likely plastic connections. We also identified synaptic connections between s-LNvs and mushroom body Kenyon cells. Tango-seq should be a useful addition to the connectomics toolkit.

BASiCS workflow: a step-by-step analysis of expression variability using single cell RNA sequencing data

Cell-to-cell gene expression variability is an inherent feature of complex biological systems, such as immunity and development. Single-cell RNA sequencing is a powerful tool to quantify this heterogeneity, but it is prone to strong technical noise. In this article, we describe a step-by-step computational workflow that uses the BASiCS Bioconductor package to robustly quantify expression variability within and between known groups of cells (such as experimental conditions or cell types). BASiCS uses an integrated framework for data normalisation, technical noise quantification and downstream analyses, propagating statistical uncertainty across these steps. Within a single seemingly homogeneous cell population, BASiCS can identify highly variable genes that exhibit strong heterogeneity as well as lowly variable genes with stable expression. BASiCS also uses a probabilistic decision rule to identify changes in expression variability between cell populations, whilst avoiding confounding effects related to differences in technical noise or in overall abundance. Using a publicly available dataset, we guide users through a complete pipeline that includes preliminary steps for quality control, as well as data exploration using the scater and scran Bioconductor packages. The workflow is accompanied by a Docker image that ensures the reproducibility of our results.

Reproducible single cell annotation of programs underlying T-cell subsets, activation states, and functions

T-cells recognize antigens and induce specialized gene expression programs (GEPs) enabling functions including proliferation, cytotoxicity, and cytokine production. Traditionally, different classes of helper T-cells express mutually exclusive responses - for example, Th1, Th2, and Th17 programs. However, new single-cell RNA sequencing (scRNA-Seq) experiments have revealed a continuum of T-cell states without discrete clusters corresponding to these subsets, implying the need for new analytical frameworks. Here, we advance the characterization of T-cells with T-CellAnnoTator (TCAT), a pipeline that simultaneously quantifies pre-defined GEPs capturing activation states and cellular subsets. From 1,700,000 T-cells from 700 individuals across 38 tissues and five diverse disease contexts, we discover 46 reproducible GEPs reflecting the known core functions of T-cells including proliferation, cytotoxicity, exhaustion, and T helper effector states. We experimentally characterize several novel activation programs and apply TCAT to describe T-cell activation and exhaustion in Covid-19 and cancer, providing insight into T-cell function in these diseases.

Single-cell RNA sequencing reveals the heterogeneity of adipose tissue-derived mesenchymal stem cells under chondrogenic induction

This study investigated how adipose tissue-derived mesenchymal stem cells (AT-MSCs) respond to chondrogenic induction using droplet-based single-cell RNA sequencing (scRNA-seq). We analyzed 37,219 high-quality transcripts from control cells and cells induced for 1 week (1W) and 2 weeks (2W). Four distinct cell clusters (0-3), undetectable by bulk analysis, exhibited varying proportions. Cluster 1 dominated in control and 1W cells, whereas clusters (3, 2, and 0) exclusively dominated in control, 1W, and 2W cells, respectively. Furthermore, heterogeneous chondrogenic markers expression within clusters emerged. Gene ontology (GO) enrichment analysis of differentially expressed genes unveiled cluster-specific variations in key biological processes (BP): (1) Cluster 1 exhibited up-regulation of GO-BP terms related to ribosome biogenesis and translational control, crucial for maintaining stem cell properties and homeostasis; (2) Additionally, cluster 1 showed up-regulation of GO-BP terms associated with mitochondrial oxidative metabolism; (3) Cluster 3 displayed up-regulation of GO-BP terms related to cell proliferation; (4) Clusters 0 and 2 demonstrated similar up-regulation of GO-BP terms linked to collagen fibril organization and supramolecular fiber organization. However, only cluster 0 showed a significant decrease in GO-BP terms related to ribosome production, implying a potential correlation between ribosome regulation and the differentiation stages of AT-MSCs. Overall, our findings highlight heterogeneous cell clusters with varying balances between proliferation and differentiation before, and after, chondrogenic stimulation. This provides enhanced insights into the single-cell dynamics of AT-MSCs during chondrogenic differentiation. [BMB Reports 2024; 57(5): 232-237].

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.

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Aortic Cellular Heterogeneity in Health and Disease: Novel Insights Into Aortic Diseases From Single-Cell RNA Transcriptomic Data Sets

Aortic diseases such as atherosclerosis, aortic aneurysms, and aortic stiffening are significant complications that can have significant impact on end-stage cardiovascular disease. With limited pharmacological therapeutic strategies that target the structural changes in the aorta, surgical intervention remains the only option for some patients with these diseases. Although there have been significant contributions to our understanding of the cellular architecture of the diseased aorta, particularly in the context of atherosclerosis, furthering our insight into the cellular drivers of disease is required. The major cell types of the aorta are well defined; however, the advent of single-cell RNA sequencing provides unrivaled insights into the cellular heterogeneity of each aortic cell type and the inferred biological processes associated with each cell in health and disease. This review discusses previous concepts that have now been enhanced with recent advances made by single-cell RNA sequencing with a focus on aortic cellular heterogeneity.

Gastrulation-stage gene expression in Nipbl+/- mouse embryos foreshadows the development of syndromic birth defects

In animal models, Nipbl deficiency phenocopies gene expression changes and birth defects seen in Cornelia de Lange syndrome, the most common cause of which is Nipbl haploinsufficiency. Previous studies in Nipbl+/- mice suggested that heart development is abnormal as soon as cardiogenic tissue is formed. To investigate this, we performed single-cell RNA sequencing on wild-type and Nipbl+/- mouse embryos at gastrulation and early cardiac crescent stages. Nipbl+/- embryos had fewer mesoderm cells than wild-type and altered proportions of mesodermal cell subpopulations. These findings were associated with underexpression of genes implicated in driving specific mesodermal lineages. In addition, Nanog was found to be overexpressed in all germ layers, and many gene expression changes observed in Nipbl+/- embryos could be attributed to Nanog overexpression. These findings establish a link between Nipbl deficiency, Nanog overexpression, and gene expression dysregulation/lineage misallocation, which ultimately manifest as birth defects in Nipbl+/- animals and Cornelia de Lange syndrome.

Single-cell RNA sequencing reveals Immune Education promotes T cell survival in mice subjected to the cecal ligation and puncture sepsis model

Background

Individual T cell responses vary significantly based on the microenvironment present at the time of immune response and on prior induced T cell memory. While the cecal ligation and puncture (CLP) model is the most commonly used murine sepsis model, the contribution of diverse T cell responses has not been explored. We defined T cell subset responses to CLP using single-cell RNA sequencing and examined the effects of prior induced T cell memory (Immune Education) on these responses. We hypothesized that Immune Education prior to CLP would alter T cell responses at the single cell level at a single, early post-CLP time point.

Methods

Splenic T cells were isolated from C57BL/6 mice. Four cohorts were studied: Control, Immune-Educated, CLP, and Immune-Educated CLP. At age 8 weeks, Immune-Educated and Immune-Educated CLP mice received anti-CD3ϵ antibody; Control and CLP mice were administered an isotype control. CLP (two punctures with a 22-gauge needle) was performed at 12-13 weeks of life. Mice were sacrificed at baseline or 24-hours post-CLP. Unsupervised clustering of the transcriptome library identified six distinct T cell subsets: quiescent naïve CD4+, primed naïve CD4+, memory CD4+, naïve CD8+, activated CD8+, and CD8+ cytotoxic T cell subsets. T cell subset specific gene set enrichment analysis and Hurdle analysis for differentially expressed genes (DEGs) were performed.

Results

T cell responses to CLP were not uniform - subsets of activated and suppressed T cells were identified. Immune Education augmented specific T cell subsets and led to genomic signatures favoring T cell survival in unoperated and CLP mice. Additionally, the combination of Immune Education and CLP effected the expression of genes related to T cell activity in ways that differed from CLP alone. Validating our finding that IL7R pathway markers were upregulated in Immune-Educated CLP mice, we found that Immune Education increased T cell surface IL7R expression in post-CLP mice.

Conclusion

Immune Education enhanced the expression of genes associated with T cell survival in unoperated and CLP mice. Induction of memory T cell compartments via Immune Education combined with CLP may increase the model's concordance to human sepsis.

Direct male development in chromosomally ZZ zebrafish

The genetics of sex determination varies across taxa, sometimes even within a species. Major domesticated strains of zebrafish (Danio rerio), including AB and TU, lack a strong genetic sex determining locus, but strains more recently derived from nature, like Nadia (NA), possess a ZZ male/ZW female chromosomal sex-determination system. AB fish pass through a juvenile ovary stage, forming oocytes that survive in fish that become females but die in fish that become males. To understand mechanisms of gonad development in NA zebrafish, we studied histology and single cell transcriptomics in developing ZZ and ZW fish. ZW fish developed oocytes by 22 days post-fertilization (dpf) but ZZ fish directly formed testes, avoiding a juvenile ovary phase. Gonads of some ZW and WW fish, however, developed oocytes that died as the gonad became a testis, mimicking AB fish, suggesting that the gynogenetically derived AB strain is chromosomally WW. Single-cell RNA-seq of 19dpf gonads showed similar cell types in ZZ and ZW fish, including germ cells, precursors of gonadal support cells, steroidogenic cells, interstitial/stromal cells, and immune cells, consistent with a bipotential juvenile gonad. In contrast, scRNA-seq of 30dpf gonads revealed that cells in ZZ gonads had transcriptomes characteristic of testicular Sertoli, Leydig, and germ cells while ZW gonads had granulosa cells, theca cells, and developing oocytes. Hematopoietic and vascular cells were similar in both sex genotypes. These results show that juvenile NA zebrafish initially develop a bipotential gonad; that a factor on the NA W chromosome, or fewer than two Z chromosomes, is essential to initiate oocyte development; and without the W factor, or with two Z doses, NA gonads develop directly into testes without passing through the juvenile ovary stage. Sex determination in AB and TU strains mimics NA ZW and WW zebrafish, suggesting loss of the Z chromosome during domestication. Genetic analysis of the NA strain will facilitate our understanding of the evolution of sex determination mechanisms.

A single-cell genomic strategy for alternative transcript start sites identification

Alternative transcription start sites (TSSs) usage plays a critical role in gene transcription regulation in mammals. However, precisely identifying alternative TSSs remains challenging at the genome-wide level. We report a single-cell genomic technology for alternative TSSs annotation and cell heterogeneity detection. In the method, we utilize Fluidigm C1 system to capture individual cells of interest, SMARTer cDNA synthesis kit to recover full-length cDNAs, then dual priming oligonucleotide system to specifically enrich TSSs for genomic analysis. We apply this method to a genome-wide study of alternative TSSs identification in two different IFN-β stimulated mouse embryonic fibroblasts (MEFs). The data clearly discriminate two IFN-β stimulated MEFs. Moreover, our results indicate 81% expressed genes in these two cell types containing multiple TSSs, which is much higher than previous predictions based on Cap-Analysis Gene Expression (CAGE) (58%) or empirical determination (54%) in various cell types. This indicates that alternative TSSs are more pervasive than expected and implies our strategy could position them at an unprecedented sensitivity. It would be helpful for elucidating their biological insights in future.

Comparison of high-throughput single-cell RNA-seq methods for ex vivo drug screening

Functional precision medicine (FPM) aims to optimize patient-specific drug selection based on the unique characteristics of their cancer cells. Recent advancements in high throughput ex vivo drug profiling have accelerated interest in FPM. Here, we present a proof-of-concept study for an integrated experimental system that incorporates ex vivo treatment response with a single-cell gene expression output enabling barcoding of several drug conditions in one single-cell sequencing experiment. We demonstrate this through a proof-of-concept investigation focusing on the glucocorticoid-resistant acute lymphoblastic leukemia (ALL) E/R+ Reh cell line. Three different single-cell transcriptome sequencing (scRNA-seq) approaches were evaluated, each exhibiting high cell recovery and accurate tagging of distinct drug conditions. Notably, our comprehensive analysis revealed variations in library complexity, sensitivity (gene detection), and differential gene expression detection across the methods. Despite these differences, we identified a substantial transcriptional response to fludarabine, a highly relevant drug for treating high-risk ALL, which was consistently recapitulated by all three methods. These findings highlight the potential of our integrated approach for studying drug responses at the single-cell level and emphasize the importance of method selection in scRNA-seq studies. Finally, our data encompassing 27 327 cells are freely available to extend to future scRNA-seq methodological comparisons.

Applications of single-cell omics for chimeric antigen receptor T cell therapy

Chimeric antigen receptor (CAR) T cell therapy is a promising cancer treatment modality. The breakthroughs in CAR T cell therapy were, in part, possible with the help of cell analysis methods, such as single-cell analysis. Bulk analyses have provided invaluable information regarding the complex molecular dynamics of CAR T cells, but their results are an average of thousands of signals in CAR T or tumour cells. Since cancer is a heterogeneous disease where each minute detail of a subclone could change the outcome of the treatment, single-cell analysis could prove to be a powerful instrument in deciphering the secrets of tumour microenvironment for cancer immunotherapy. With the recent studies in all aspects of adoptive cell therapy making use of single-cell analysis, a comprehensive review of the recent preclinical and clinical findings in CAR T cell therapy was needed. Here, we categorized and summarized the key points of the studies in which single-cell analysis provided insights into the genomics, epigenomics, transcriptomics and proteomics as well as their respective multi-omics of CAR T cell therapy.

Spitting in the wind?-The challenges of RNA sequencing for biomarker discovery from saliva

Forensic trace contextualization, i.e., assessing information beyond who deposited a biological stain, has become an issue of great and steadily growing importance in forensic genetic casework and research. The human transcriptome encodes a wide variety of information and thus has received increasing interest for the identification of biomarkers for different aspects of forensic trace contextualization over the past years. Massively parallel sequencing of reverse-transcribed RNA ("RNA sequencing") has emerged as the gold standard technology to characterize the transcriptome in its entirety and identify RNA markers showing significant expression differences not only between different forensically relevant body fluids but also within a single body fluid between forensically relevant conditions of interest. Here, we analyze the quality and composition of four RNA sequencing datasets (whole transcriptome as well as miRNA sequencing) from two different research projects (the RNAgE project and the TrACES project), aiming at identifying contextualizing forensic biomarker from the forensically relevant body fluid saliva. We describe and characterize challenges of RNA sequencing of saliva samples arising from the presence of oral bacteria, the heterogeneity of sample composition, and the confounding factor of degradation. Based on these observations, we formulate recommendations that might help to improve RNA biomarker discovery from the challenging but forensically relevant body fluid saliva.

Single-Cell Transcriptomic Profiling Identifies Molecular Phenotypes of Newborn Human Lung Cells

While animal model studies have extensively defined the mechanisms controlling cell diversity in the developing mammalian lung, there exists a significant knowledge gap with regards to late-stage human lung development. The NHLBI Molecular Atlas of Lung Development Program (LungMAP) seeks to fill this gap by creating a structural, cellular and molecular atlas of the human and mouse lung. Transcriptomic profiling at the single-cell level created a cellular atlas of newborn human lungs. Frozen single-cell isolates obtained from two newborn human lungs from the LungMAP Human Tissue Core Biorepository, were captured, and library preparation was completed on the Chromium 10X system. Data was analyzed in Seurat, and cellular annotation was performed using the ToppGene functional analysis tool. Transcriptional interrogation of 5500 newborn human lung cells identified distinct clusters representing multiple populations of epithelial, endothelial, fibroblasts, pericytes, smooth muscle, immune cells and their gene signatures. Computational integration of data from newborn human cells and with 32,000 cells from postnatal days 1 through 10 mouse lungs generated by the LungMAP Cincinnati Research Center facilitated the identification of distinct cellular lineages among all the major cell types. Integration of the newborn human and mouse cellular transcriptomes also demonstrated cell type-specific differences in maturation states of newborn human lung cells. Specifically, newborn human lung matrix fibroblasts could be separated into those representative of younger cells (n = 393), or older cells (n = 158). Cells with each molecular profile were spatially resolved within newborn human lung tissue. This is the first comprehensive molecular map of the cellular landscape of neonatal human lung, including biomarkers for cells at distinct states of maturity.

High-throughput mapping of single-neuron projection and molecular features by retrograde barcoded labeling

Deciphering patterns of connectivity between neurons in the brain is a critical step toward understanding brain function. Imaging-based neuroanatomical tracing identifies area-to-area or sparse neuron-to-neuron connectivity patterns, but with limited throughput. Barcode-based connectomics maps large numbers of single-neuron projections, but remains a challenge for jointly analyzing single-cell transcriptomics. Here, we established a rAAV2-retro barcode-based multiplexed tracing method that simultaneously characterizes the projectome and transcriptome at the single neuron level. We uncovered dedicated and collateral projection patterns of ventromedial prefrontal cortex (vmPFC) neurons to five downstream targets and found that projection-defined vmPFC neurons are molecularly heterogeneous. We identified transcriptional signatures of projection-specific vmPFC neurons, and verified Pou3f1 as a marker gene enriched in neurons projecting to the lateral hypothalamus, denoting a distinct subset with collateral projections to both dorsomedial striatum and lateral hypothalamus. In summary, we have developed a new multiplexed technique whose paired connectome and gene expression data can help reveal organizational principles that form neural circuits and process information.

Upregulation of developmentally-downregulated miR-1247-5p promotes neuroprotection and axon regeneration in vivo

Numerous micro-RNAs (miRNAs) affect neurodevelopment and neuroprotection, but potential roles of many miRNAs in regulating these processes are still unknown. Here, we used the retinal ganglion cell (RGC) central nervous system (CNS) projection neuron and optic nerve crush (ONC) injury model, to optimize a mature miRNA arm-specific quantification method for characterizing the developmental regulation of miR-1247-5p in RGCs, investigated whether injury affects its expression, and tested whether upregulating miR-1247-5p-mimic in RGCs promotes neuroprotection and axon regeneration. We found that, miR-1247-5p is developmentally-downregulated in RGCs, and is further downregulated after ONC. Importantly, RGC-specific upregulation of miR-1247-5p promoted neuroprotection and axon regeneration after injury in vivo. To gain insight into the underlying mechanisms, we analyzed by bulk-mRNA-seq embryonic and adult RGCs, along with adult RGCs transduced by miR-1247-5p-expressing viral vector, and identified developmentally-regulated cilial and mitochondrial biological processes, which were reinstated to their embryonic levels in adult RGCs by upregulation of miR-1247-5p. Since axon growth is also a developmentally-regulated process, in which mitochondrial dynamics play important roles, it is possible that miR-1247-5p promoted neuroprotection and axon regeneration through regulating mitochondrial functions.

Gastrulation-stage gene expression in Nipbl +/- mouse embryos foreshadows the development of syndromic birth defects

In animal models, Nipbl-deficiency phenocopies gene expression changes and birth defects seen in Cornelia de Lange Syndrome (CdLS), the most common cause of which is Nipbl-haploinsufficiency. Previous studies in Nipbl+/- mice suggested that heart development is abnormal as soon as cardiogenic tissue is formed. To investigate this, we performed single-cell RNA-sequencing on wildtype (WT) and Nipbl+/- mouse embryos at gastrulation and early cardiac crescent stages. Nipbl+/- embryos had fewer mesoderm cells than WT and altered proportions of mesodermal cell subpopulations. These findings were associated with underexpression of genes implicated in driving specific mesodermal lineages. In addition, Nanog was found to be overexpressed in all germ layers, and many gene expression changes observed in Nipbl+/- embryos could be attributed to Nanog overexpression. These findings establish a link between Nipbl-deficiency, Nanog overexpression, and gene expression dysregulation/lineage misallocation, which ultimately manifest as birth defects in Nipbl+/- animals and CdLS.

Teaser

Gene expression changes during gastrulation of Nipbl-deficient mice shed light on early origins of structural birth defects.

Enabling methanol fixation of pediatric nasal wash during respiratory illness for single cell sequencing in comparison with fresh samples

BACKGROUND

Lower respiratory tract infection (LRTI) including pneumonia, bronchitis, and bronchiolitis is the sixth leading cause of mortality around the world and leading cause of death in children under 5 years. Systemic immune response to viral infection is well characterized. However, there is little data regarding the immune response at the upper respiratory tract mucosa. The upper respiratory mucosa is the site of viral entry, initial replication and the first barrier against respiratory infections. Lower respiratory tract samples can be challenging to obtain and require more invasive procedures. However, nasal wash (NW) samples from the upper respiratory tract can be obtained with minimal discomfort to the patient.

METHOD

In a pilot study, we developed a protocol using NW samples obtained from hospitalized children with LRTI that enables single cell RNA sequencing (scRNA-seq) after the NW sample is methanol-fixed.

RESULTS

We found no significant changes in scRNA-seq qualitative and quantitative parameters between methanol-fixed and fresh NW samples.

CONCLUSIONS

We present a novel protocol to enable scRNA-seq in NW samples from children admitted with LRTI. With the inherent challenges associated with clinical samples, the protocol described allows for processing flexibility as well as multicenter collaboration.

IMPACT

There are no significant differences in scRNA-seq qualitative and quantitative parameters between methanol fixed and fresh Pediatric Nasal wash samples. The study demonstrates the effectiveness of methanol fixation process on preserving respiratory samples for single cell sequencing. This enables Pediatric Nasal wash specimen for single cell RNA sequencing in pediatric patients with respiratory tract infection and allows processing flexibility and multicenter collaboration.

Method for Collecting Single Epithelial Cells from the Mouse Larynx

OBJECTIVE

The larynx is lined by specialized epithelial cell populations. Studying molecular changes occurring in individual epithelial cell types requires a reliable method for removing these cells from the larynx. Our objective was to develop a method to harvest individual epithelial cells from the mouse larynx while minimizing contamination from non-laryngeal sites and non-epithelial laryngeal cells.

METHODS

Mice were euthanized, and the larynx was carefully exposed and separated from non-laryngeal sites. A small dental brush was inserted into the laryngeal inlet and rotated to obtain epithelial cells. Cells were transferred to collection media, counted, and cytospin preparations stained for laryngeal epithelial (i.e., Pan-Keratin, EpCAM, NGFR, p63, K5, β-tubulin, MUC5AC) and non-epithelial (i.e., vimentin) cell markers. Histopathology was completed on brushed laryngeal tissue sections to evaluate the depth of cell collection. Preliminary Single-cell RNA sequencing (scRNA-seq) was performed to confirm this method can capture diverse laryngeal cell types.

RESULTS

We collected 6000-8000 cells from a single larynx and 35000-40000 cells from combining brushings from three tissues. Histopathology demonstrated brushing removed the epithelial layer of the larynx and some underlying tissue. Immunofluorescence staining demonstrated the phenotype of harvested cells was primarily epithelial. Preliminary scRNA-seq was successfully conducted and displayed nine unique cell clusters.

CONCLUSION

We developed a reliable method of harvesting individual epithelial cells from the mouse larynx. This method will be useful for collection of laryngeal cells for a variety of downstream cellular and molecular assays, including scRNA-seq, protein analyses, and cell-culture-based experiments, following laryngeal injury.

LEVEL OF EVIDENCE

NA Laryngoscope, 134:786-794, 2024.

Association between spatial distribution of leukocyte subsets and clinical presentation of head and neck squamous cell carcinoma

Background

Interactions between tumor cells and cells in the microenvironment contribute to tumor development and metastasis. The spatial arrangement of individual cells in relation to each other influences the likelihood of whether and how these cells interact with each other.

Methods

This study investigated the effect of spatial distribution on the function of leukocyte subsets in the microenvironment of human head and neck squamous cell carcinoma (HNSCC) using multiplex immunohistochemistry (IHC). Leukocyte subsets were further classified based on analysis of two previously published HNSCC single-cell RNA datasets and flow cytometry (FC).

Results

IHC revealed distinct distribution patterns of leukocytes differentiated by CD68 and CD163. While CD68hiCD163lo and CD68hiCD163hi cells accumulated near tumor sites, CD68loCD163hi cells were more evenly distributed in the tumor stroma. PD-L1hi and PD-1hi cells accumulated predominantly around tumor sites. High cell density of PD-L1hi CD68hiCD163hi cells or PD-1hi T cells near the tumor site correlated with improved survival. FC and single cell RNA revealed high variability within the CD68/CD163 subsets. CD68hiCD163lo and CD68hiCD163hi cells were predominantly macrophages (MΦ), whereas CD68loCD163hi cells appeared to be predominantly dendritic cells (DCs). Differentiation based on CD64, CD80, CD163, and CD206 revealed that TAM in HNSCC occupy a broad spectrum within the classical M1/M2 polarization. Notably, the MΦ subsets expressed predominantly CD206 and little CD80. The opposite was observed in the DC subsets.

Conclusion

The distribution patterns and their distinct interactions via the PD-L1/PD-1 pathway suggest divergent roles of CD68/CD163 subsets in the HNSCC microenvironment. PD-L1/PD-1 interactions appear to occur primarily between specific cell types close to the tumor site. Whether PD-L1/PD-1 interactions have a positive or negative impact on patient survival appears to depend on both the spatial localization and the entity of the interacting cells. Co-expression of other markers, particularly CD80 and CD206, supports the hypothesis that CD68/CD163 IHC subsets have distinct functions. These results highlight the association between spatial leukocyte distribution patterns and the clinical presentation of HNSCC.

Species-agnostic transfer learning for cross-species transcriptomics data integration without gene orthology

Novel hypotheses in biomedical research are often developed or validated in model organisms such as mice and zebrafish and thus play a crucial role. However, due to biological differences between species, translating these findings into human applications remains challenging. Moreover, commonly used orthologous gene information is often incomplete and entails a significant information loss during gene-id conversion. To address these issues, we present a novel methodology for species-agnostic transfer learning with heterogeneous domain adaptation. We extended the cross-domain structure-preserving projection toward out-of-sample prediction. Our approach not only allows knowledge integration and translation across various species without relying on gene orthology but also identifies similar GO among the most influential genes composing the latent space for integration. Subsequently, during the alignment of latent spaces, each composed of species-specific genes, it is possible to identify functional annotations of genes missing from public orthology databases. We evaluated our approach with four different single-cell sequencing datasets focusing on cell-type prediction and compared it against related machine-learning approaches. In summary, the developed model outperforms related methods working without prior knowledge when predicting unseen cell types based on other species' data. The results demonstrate that our novel approach allows knowledge transfer beyond species barriers without the dependency on known gene orthology but utilizing the entire gene sets.

Activating p53 abolishes self-renewal of quiescent leukaemic stem cells in residual CML disease

Whilst it is recognised that targeting self-renewal is an effective way to functionally impair the quiescent leukaemic stem cells (LSC) that persist as residual disease in chronic myeloid leukaemia (CML), developing therapeutic strategies to achieve this have proved challenging. We demonstrate that the regulatory programmes of quiescent LSC in chronic phase CML are similar to that of embryonic stem cells, pointing to a role for wild type p53 in LSC self-renewal. In support of this, increasing p53 activity in primitive CML cells using an MDM2 inhibitor in combination with a tyrosine kinase inhibitor resulted in reduced CFC outputs and engraftment potential, followed by loss of multilineage priming potential and LSC exhaustion when combination treatment was discontinued. Our work provides evidence that targeting LSC self-renewal is exploitable in the clinic to irreversibly impair quiescent LSC function in CML residual disease - with the potential to enable more CML patients to discontinue therapy and remain in therapy-free remission.

nPCA: a linear dimensionality reduction method using a multilayer perceptron

Background: Linear dimensionality reduction techniques are widely used in many applications. The goal of dimensionality reduction is to eliminate the noise of data and extract the main features of data. Several dimension reduction methods have been developed, such as linear-based principal component analysis (PCA), nonlinear-based t-distributed stochastic neighbor embedding (t-SNE), and deep-learning-based autoencoder (AE). However, PCA only determines the projection direction with the highest variance, t-SNE is sometimes only suitable for visualization, and AE and nonlinear methods discard the linear projection. Results: To retain the linear projection of raw data and generate a better result of dimension reduction either for visualization or downstream analysis, we present neural principal component analysis (nPCA), an unsupervised deep learning approach capable of retaining richer information of raw data as a promising improvement to PCA. To evaluate the performance of the nPCA algorithm, we compare the performance of 10 public datasets and 6 single-cell RNA sequencing (scRNA-seq) datasets of the pancreas, benchmarking our method with other classic linear dimensionality reduction methods. Conclusion: We concluded that the nPCA method is a competitive alternative method for dimensionality reduction tasks.

Dysfunctional Epithelial Barrier Is Characterized by Reduced E-Cadherin in Idiopathic Subglottic Stenosis

OBJECTIVES

To aim of the study was to characterize the molecular profile and functional phenotype of idiopathic subglottic stenosis (iSGS)-scar epithelium.

METHODS

Human tracheal biopsies from iSGS scar (n = 6) and matched non-scar (n = 6) regions were analyzed using single-cell RNA sequencing (scRNA-seq). Separate specimens were used for epithelial cell expansion in vitro to assess average growth rate and functional capabilities using transepithelial-electrical resistance (TEER), fluorescein isothiocyanate-dextran flux permeability assay, ciliary coverage, and cilia beating frequency (CBF). Finally, epithelial tight junction protein expression of cultured cells was quantified using immunoblot assay (n = 4) and immunofluorescence (n = 6).

RESULTS

scRNA-seq analysis revealed a decrease in goblet, ciliated, and basal epithelial cells in the scar iSGS cohort. Furthermore, mRNA expression of proteins E-cadherin, claudin-3, claudin-10, occludin, TJP1, and TJP2 was also reduced (p < 0.001) in scar epithelium. Functional assays demonstrated a decrease in TEER (paired 95% confidence interval [CI], 195.68-890.83 Ω × cm2 , p < 0.05), an increase in permeability (paired 95% CI, -6116.00 to -1401.99 RFU, p < 0.05), and reduced epithelial coverage (paired 95% CI, 0.1814-1.766, fold change p < 0.05) in iSGS-scar epithelium relative to normal controls. No difference in growth rate (p < 0.05) or CBF was found (paired 95% CI, -2.118 to 3.820 Hz, p > 0.05). Immunoblot assay (paired 95% CI, 0.0367-0.605, p < 0.05) and immunofluorescence (paired 95% CI, 13.748-59.191 mean grey value, p < 0.05) revealed E-cadherin reduction in iSGS-scar epithelium.

CONCLUSION

iSGS-scar epithelium has a dysfunctional barrier and reduced structural protein expression. These results are consistent with dysfunctional epithelium seen in other airway pathology. Further studies are warranted to delineate the causality of epithelial dysfunction on the downstream fibroinflammatory cascade in iSGS.

LEVEL OF EVIDENCE

NA Laryngoscope, 134:374-381, 2024.

Plasticity of intragraft alloreactive T cell clones in human gut correlates with transplant outcomes

The site of transition between tissue-resident memory (TRM) and circulating phenotypes of T cells is unknown. We integrated clonotype, alloreactivity, and gene expression profiles of graft-repopulating recipient T cells in the intestinal mucosa at the single-cell level after human intestinal transplantation. Host-versus-graft (HvG)-reactive T cells were mainly distributed to TRM, effector T (Teff)/TRM, and T follicular helper compartments. RNA velocity analysis demonstrated a trajectory from TRM to Teff/TRM clusters in association with rejection. By integrating pre- and post-transplantation (Tx) mixed lymphocyte reaction-determined alloreactive repertoires, we observed that pre-existing HvG-reactive T cells that demonstrated tolerance in the circulation were dominated by TRM profiles in quiescent allografts. Putative de novo HvG-reactive clones showed a transcriptional profile skewed to cytotoxic effectors in rejecting grafts. Inferred protein regulon network analysis revealed upstream regulators that accounted for the effector and tolerant T cell states. We demonstrate Teff/TRM interchangeability for individual T cell clones with known (allo)recognition in the human gut, providing novel insight into TRM biology.

Data Analysis Pipeline for scRNA-seq Experiments to Study Early Oogenesis

Germ cells as the means for the transmission of genetic information between generations have been a hot topic of research for decades. The analysis of the transcriptomes, that is of the RNA transcripts produced by the genotype at a given time, of germ cells and the surrounding somatic cells, is essential to unravel the cellular and molecular processes regulating gametogenesis. However, the asynchronized differentiation of germ cells and high cellular heterogeneity in the developing ovary or testis represent two unsurmountable challenges for delineating the transcription regulation mechanism of germ cells using traditional bulk RNA sequencing. By performing single-cell RNA sequencing (scRNA-seq), it is now possible to dissect the transcriptome of germ cell development at single-cell resolution, and apply powerful bioinformatics methods to translate raw sequencing data into meaningful information. Here, using the 10× Genomic platform and the most widely cited bioinformatics tools, we describe how to analyze early female germ cell development using scRNA-seq data generated from mouse E11.5 to E14.5 ovaries. This pipeline will provide a guide for exploring the processes of early germ cell development at single-cell resolution.

The effects of methylphenidate and atomoxetine on Drosophila brain at single-cell resolution and potential drug repurposing for ADHD treatment

The stimulant methylphenidate (MPH) and the non-stimulant atomoxetine (ATX) are frequently used for the treatment of attention-deficit/hyperactivity disorder (ADHD); however, the function of these drugs in different types of brain cells and their effects on related genes remain largely unknown. To address these questions, we built a pipeline for the simultaneous examination of the activity behavior and transcriptional responses of Drosophila melanogaster at single-cell resolution following drug treatment. We selected the Drosophila with significantly increased locomotor activities (hyperactivity-like behavior) following the administration of each drug in comparison with the control (same food as the drug-treated groups with 5% sucrose, yeast, and blue food dye solution) using EasyFlyTracker. Subsequently, single cell RNA sequencing (scRNASEQ) was used to capture the transcriptome of 82,917 cells, unsupervised clustering analysis of which yielded 28 primary cell clusters representing the major cell types in adult Drosophila brain. Indeed, both neuronal and glial cells responded to MPH and ATX. Further analysis of differentially expressed genes (DEGs) revealed distinct transcriptional changes associated with these two drugs, such as two well-studied dopamine receptor genes (Dop2R and DopEcR) were responsive to MPH but not to ATX at their optimal doses, in addition to genes involved in dopamine metabolism pathways such as Syt1, Sytalpha, Syt7, and Ih in different cell types. More importantly, MPH also suppressed the expression of genes encoding other neurotransmitter receptors and synaptic signaling molecules in many cell types, especially those for Glu and GABA, while the responsive effects of ATX were much weaker. In addition to monoaminergic neuronal transmitters, other neurotransmitters have also shown a similar pattern with respect to a stronger effect associated with MPH than with ATX. Moreover, we identified four distinct glial cell subtypes responsive to the two drugs and detected a greater number of differentially expressed genes associated with ensheathing and astrocyte-like glia. Furthermore, our study provides a rich resource of candidate target genes, supported by drug set enrichment analysis (P = 2.10E-4; hypergeometric test), for the further exploration of drug repurposing. The whole list of candidates can be found at ADHDrug ( http://adhdrug.cibr.ac.cn/ ). In conclusion, we propose a fast and cost-efficient pipeline to explore the underlying molecular mechanisms of ADHD drug treatment in Drosophila brain at single-cell resolution, which may further facilitate drug repurposing applications.

Direct Male Development in Chromosomally ZZ Zebrafish

The genetics of sex determination varies across taxa, sometimes even within a species. Major domesticated strains of zebrafish ( Danio rerio ), including AB and TU, lack a strong genetic sex determining locus, but strains more recently derived from nature, like Nadia (NA), possess a ZZ male/ZW female chromosomal sex-determination system. AB strain fish pass through a juvenile ovary stage, forming oocytes that survive in fish that become females but die in fish that become males. To understand mechanisms of gonad development in NA zebrafish, we studied histology and single cell transcriptomics in developing ZZ and ZW fish. ZW fish developed oocytes by 22 days post-fertilization (dpf) but ZZ fish directly formed testes, avoiding a juvenile ovary phase. Gonads of some ZW and WW fish, however, developed oocytes that died as the gonad became a testis, mimicking AB fish, suggesting that the gynogenetically derived AB strain is chromosomally WW. Single-cell RNA-seq of 19dpf gonads showed similar cell types in ZZ and ZW fish, including germ cells, precursors of gonadal support cells, steroidogenic cells, interstitial/stromal cells, and immune cells, consistent with a bipotential juvenile gonad. In contrast, scRNA-seq of 30dpf gonads revealed that cells in ZZ gonads had transcriptomes characteristic of testicular Sertoli, Leydig, and germ cells while ZW gonads had granulosa cells, theca cells, and developing oocytes. Hematopoietic and vascular cells were similar in both sex genotypes. These results show that juvenile NA zebrafish initially develop a bipotential gonad; that a factor on the NA W chromosome or fewer than two Z chromosomes is essential to initiate oocyte development; and without the W factor or with two Z doses, NA gonads develop directly into testes without passing through the juvenile ovary stage. Sex determination in AB and TU strains mimics NA ZW and WW zebrafish, suggesting loss of the Z chromosome during domestication. Genetic analysis of the NA strain will facilitate our understanding of the evolution of sex determination mechanisms.

Identifying primary aldosteronism patients who require adrenal venous sampling: a multi-center study

Adrenal venous sampling (AVS) is crucial for subtyping primary aldosteronism (PA) to explore the possibility of curing hypertension. Because AVS availability is limited, efforts have been made to develop strategies to bypass it. However, it has so far proven unsuccessful in applying clinical practice, partly due to heterogeneity and missing values of the cohorts. For this purpose, we retrospectively assessed 210 PA cases from three institutions where segment-selective AVS, which is more accurate and sensitive for detecting PA cases with surgical indications, was available. A machine learning-based classification model featuring a new cross-center domain adaptation capability was developed. The model identified 102 patients with PA who benefited from surgery in the present cohort. A new data imputation technique was used to address cross-center heterogeneity, making a common prediction model applicable across multiple cohorts. Logistic regression demonstrated higher accuracy than Random Forest and Deep Learning [(0.89, 0.86) vs. (0.84, 0.84), (0.82, 0.84) for surgical or medical indications in terms of f-score]. A derived integrated flowchart revealed that 35.2% of PA cases required AVS with 94.1% accuracy. The present model enabled us to reduce the burden of AVS on patients who would benefit the most.

Single-cell analysis of innate spinal cord regeneration identifies intersecting modes of neuronal repair

Adult zebrafish have an innate ability to recover from severe spinal cord injury. Here, we report a comprehensive single nuclear RNA sequencing atlas that spans 6 weeks of regeneration. We identify cooperative roles for adult neurogenesis and neuronal plasticity during spinal cord repair. Neurogenesis of glutamatergic and GABAergic neurons restores the excitatory/inhibitory balance after injury. In addition, transient populations of injury-responsive neurons (iNeurons) show elevated plasticity between 1 and 3 weeks post-injury. Using cross-species transcriptomics and CRISPR/Cas9 mutagenesis, we found iNeurons are injury-surviving neurons that share transcriptional similarities with a rare population of spontaneously plastic mouse neurons. iNeurons are required for functional recovery and employ vesicular trafficking as an essential mechanism that underlies neuronal plasticity. This study provides a comprehensive resource of the cells and mechanisms that direct spinal cord regeneration and establishes zebrafish as a model of plasticity-driven neural repair.

Proximal tubule cells in blood and urine as potential biomarkers for kidney disease biopsy

Early diagnosis and treatment are crucial for managing kidney disease, yet there remains a need to further explore pathological mechanisms and develop minimally invasive diagnostic methods. In this study, we employed single-cell RNA sequencing (scRNA-seq) to assess the cellular heterogeneity of kidney diseases. We analyzed gene expression profiles from renal tissue, peripheral blood mononuclear cells (PBMCs), and urine of four patients with nephritis. Our findings identified 12 distinct cell subsets in renal tissues and leukocytes. These subsets encompassed fibroblast cells, mesangial cells, epithelial cells, proximal tubule cells (PTCs), and six immune cell types: CD8+ T cells, macrophages, natural killer cells, dendritic cells, B cells, and neutrophils. Interestingly, PTCs were present in both PBMCs and urine samples but absent in healthy blood samples. Furthermore, several populations of fibroblast cells, mesangial cells, and PTCs exhibited pro-inflammatory or pro-apoptotic behaviors. Our gene expression analysis highlighted the critical role of inflammatory PTCs and fibroblasts in nephritis development and progression. These cells showed high expression of pro-inflammatory genes, which could have chemotactic and activating effect on neutrophils. This was substantiated by the widespread in these cells. Notably, the gene expression profiles of inflammatory PTCs in PBMCs, urine, and kidney tissues had high similarity. This suggests that PTCs in urine and PBMCs hold significant potential as alternative markers to invasive kidney biopsies.

Avoiding false discoveries in single-cell RNA-seq by revisiting the first Alzheimer's disease dataset

Mathys et al. conducted the first single-nucleus RNA-seq (snRNA-seq) study of Alzheimer's disease (AD) (Mathys et al., 2019). With bulk RNA-seq, changes in gene expression across cell types can be lost, potentially masking the differentially expressed genes (DEGs) across different cell types. Through the use of single-cell techniques, the authors benefitted from increased resolution with the potential to uncover cell type-specific DEGs in AD for the first time. However, there were limitations in both their data processing and quality control and their differential expression analysis. Here, we correct these issues and use best-practice approaches to snRNA-seq differential expression, resulting in 549 times fewer DEGs at a false discovery rate of 0.05. Thus, this study highlights the impact of quality control and differential analysis methods on the discovery of disease-associated genes and aims to refocus the AD research field away from spuriously identified genes.

Impaired Efferocytosis Enables Apoptotic Osteoblasts to Escape Osteoimmune Surveillance During Aging

Macrophage efferocytosis of apoptotic osteoblasts (apoOBs) is a key osteoimmune process for bone homeostasis. However, apoOBs frequently accumulate in aged bone marrow, where they may mount proinflammatory responses and progressive bone loss. The reason why apoOBs are not cleared during aging remains unclear. In this study, it is demonstrated that aged apoOBs upregulate the immune checkpoint molecule CD47, which is controlled by SIRT6-regulated transcriptional pausing, to evade clearance by macrophages. Using osteoblast- and myeloid-specific gene knockout mice, SIRT6 is further revealed to be a critical modulator for apoOBs clearance via targeting CD47-SIRPα checkpoint. Moreover, apoOBs activate SIRT6-mediated chemotaxis to recruit macrophages by releasing apoptotic vesicles. Two targeting delivery strategies are developed to enhance SIRT6 activity, resulting in rejuvenated apoOBs clearance and delayed age-related bone loss. Collectively, the findings reveal a previously unknown linkage between immune surveillance and bone homeostasis and targeting the SIRT6-regulated mechanism can be a promising therapeutic strategy for age-related bone diseases.

Meta-Analysis of COVID-19 BAL Single-Cell RNA Sequencing Reveals Alveolar Epithelial Transitions and Unique Alveolar Epithelial Cell Fates

Single-cell RNA sequencing (scRNA-seq) of BAL cells has provided insights into coronavirus disease (COVID-19). However, reports have been limited by small patient cohorts. We performed a meta-analysis of BAL scRNA-seq data from healthy control subjects (n = 13) and patients with COVID-19 (n = 20), sourced from six independent studies (167,280 high-quality cells in total). Consistent with the source reports, increases in infiltrating leukocyte subtypes were noted, several with type I IFN signatures and unique gene expression signatures associated with transcellular chemokine signaling. Noting dramatic reductions of inferred NKX2-1 and NR4A1 activity in alveolar epithelial type II (AT-II) cells, we modeled pseudotemporal AT-II-to-AT-I progression. This revealed changes in inferred AT-II cell metabolic activity, increased transitional cells, and a previously undescribed AT-I state. This cell state was conspicuously marked by the induction of genes of the epidermal differentiation complex, including the cornified envelope protein SPRR3 (small proline-rich protein 3), upregulation of multiple KRT (keratin) genes, inferred mitochondrial dysfunction, and cell death signatures including apoptosis and ferroptosis. Immunohistochemistry of lungs from patients with COVID-19 confirmed upregulation and colocalization of KRT13 and SPRR3 in the distal airspaces. Forced overexpression of SPRR3 in human alveolar epithelial cells ex vivo did not activate caspase-3 or upregulate KRT13, suggesting that SPRR3 marks an AT-I cornification program in COVID-19 but is not sufficient for phenotypic changes.

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.