Single-cell Transcriptomic Approaches Research Articles

Integrating nontargeted metabolomics and RNA sequencing of dexamethasone-treated and untreated asthmatic mice reveals changes of amino acids and aminoacyl-tRNA in group 2 innate lymphoid cells.

Bronchial asthma is the most common multifactorial and heterogeneous disease in childhood. The glucocorticoid dexamethasone is a classic treatment for asthma. Research indicates that group 2 innate lymphoid cells (ILC2s) are crucial to the pathogenesis of asthma. However, few studies have focused on ILC2s metabolism and transcription. This study aims to establish an ovalbumin (OVA)-induced asthma model and a dexamethasone-treated asthma model to explore the regulation of lung ILC2s at the genetic and metabolic levels during the progression and remission of asthma, utilizing single-cell metabolomics and transcriptomics approaches. The results showed that ILC2s regulated the metabolic pathways and transcriptional levels of amino acids (such as arginine, proline, and histidine) and linoleic acid, as well as the metabolic biomarkers of arginine, urocanic acid, and linoleic acid in asthma. Additionally, the cytokine pathways and NF-γB pathways have been altered at the genetic level. At the same time, we revealed that dexamethasone regulates ILC2s amino acid and aminoacyl tRNA metabolism, as well as related genes, thereby alleviating asthma symptoms. Furthermore, we identified the genes Eno3 and Tap1, which are significantly associated with asthma. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the accuracy of the RNA sequencing results. This study, for the first time, revealed the mechanistic changes of ILC2s in the development and treatment of asthma using multiomics techniques, laying a foundation for targeted therapies in asthma.

The transcriptional integration of environmental cues with root cell type development.

Plant roots navigate the soil ecosystem with each cell type uniquely responding to environmental stimuli. Below ground, the plant's response to its surroundings is orchestrated at the cellular level, including morphological and molecular adaptations that shape root system architecture as well as tissue and organ functionality. Our understanding of the transcriptional responses at cell type resolution has been profoundly enhanced by studies of the model plant Arabidopsis thaliana. However, both a comprehensive view of the transcriptional basis of these cellular responses to single and combinatorial environmental cues in diverse plant species remains elusive. In this review, we highlight the ability of root cell types to undergo specific anatomical or morphological changes in response to abiotic and biotic stresses or cues and how they collectively contribute to the plant's overall physiology. We further explore interconnections between stress and the temporal nature of developmental pathways and discuss examples of how this transcriptional reprogramming influences cell type identity and function. Finally, we highlight the power of single-cell and spatial transcriptomic approaches to refine our understanding of how environmental factors fine tune root spatiotemporal development. These complex root system responses underscore the importance of spatiotemporal transcriptional mapping, with significant implications for enhanced agricultural resilience.

Development of anex vivo patient-derived tumor model (PDTM) to assess the tumor microenvironment in renal cell carcinoma (RCC)

Abstract Background With the rise of immune checkpoint inhibitors (ICIs) as the primary treatment option for metastatic RCC, investigating the role of T cells within the tumor microenvironment (TME) is a critical component of understanding both treatment response and resistance. Prior efforts, including single-cell transcriptomic approaches, have provided an important landscape of T cell transcriptional phenotypes. However, these immuno-profiling efforts require validation through functional interrogation of the TME to facilitate the development of novel immunomodulatory therapies. Thus, we established a patient derived tumor model (PDTM) system to directly assess the effect of inhibitory immune interactions on T cell function and anti-tumor activity in the RCC TME. In this initial proof-of-concept study, we evaluated T cell activation in the RCC TME using the PDTM system. Methods Fresh tumor samples were obtained from surgical resections of RCC at Yale-New Haven Hospital. The tumor was minced to ~1-3 mm³ pieces and suspended in an air-liquid interface system, consisting of tumor fragments embedded in a collagen matrix on an insert with a semi-permeable membrane, exposed to culture media. The tumor fragment and matrix suspension were carefully pipetted onto the Millicell insert, which served as the top layer. The PDTM setup includes an inner dish containing the bottom gel layer and the tissue-containing top layer. To complete the assembly, 1.5 ml of DMEM media with or without an anti-CD3 monoclonal antibody (aCD3mAb) and 500 nM of anti-PD-1 monoclonal antibody (aPD1mAb) was added to the outer dish surrounding the insert. Results We successfully optimized PDTM experimental workflows for culture, dissociation, and analysis using immunohistochemistry (IHC), flow cytometry (FCM), and enzyme-linked immunosorbent assays (ELISA). Hematoxylin and eosin (H&E) staining and IHC showed that the TME cellular architecture and immune cell composition was broadly preserved during the three day experimental period. Using FCM to analyze the dissociated tumor samples, we identified well-preserved CA9+ tumor cells, CD4+ and CD8+ T cell populations, CD4+CD25+ regulatory T cells, CD56+ natural killer cells, CD20+ B cells, and CD14+CD11b+ myeloid subsets including monocytes and CD163-/+macrophages. Among the T cells, we detected PD1+, LAG3+, TIM3+, and TIGIT+ cells. For dose-response analysis of aCD3mAb, we observed that stimulation with 0.025 ng/mL aCD3mAb for T cells from healthy donor peripheral blood mononuclear cells (PBMCs) yielded significant but non-saturating levels of interferon gamma (IFN-γ) production as quantified by ELISA. We tested the effect of the anti-PD-1 antibody on PDTM under the low-dose of aCD3mAb, and importantly, found that treatment of the PDTM with aPD1mAb resulted in more activated CD8 T cells and higher IFN-γ production than the control samples. Conclusions Through optimization of assays evaluating T cell cytokine production, we were able to assess multiple axes of T-cell function in the RCC TME. This study revealed that our PDTM system preserves the RCC TME for functional interrogation. Furthermore, our system for assessing T cell phenotype and cytokine production successfully demonstrated the activity of PD-1 blockade ex vivo. Taken together, this novel ex vivo PDTM system has extensive applications in the study of RCC, including assessing the impact of ICIs on T cell function. DOD CDMRP Funding: yes

Hypoxia coordinates the spatial landscape of myeloid cells within glioblastoma to affect survival.

Myeloid cells are highly prevalent in glioblastoma (GBM), existing in a spectrum of phenotypic and activation states. We now have limited knowledge of the tumor microenvironment (TME) determinants that influence the localization and the functions of the diverse myeloid cell populations in GBM. Here, we have utilized orthogonal imaging mass cytometry with single-cell and spatial transcriptomic approaches to identify and map the various myeloid populations in the human GBM tumor microenvironment (TME). Our results show that different myeloid populations have distinct and reproducible compartmentalization patterns in the GBM TME that is driven by tissue hypoxia, regional chemokine signaling, and varied homotypic and heterotypic cellular interactions. We subsequently identified specific tumor subregions in GBM, based on composition of identified myeloid cell populations, that were linked to patient survival. Our results provide insight into the spatial organization of myeloid cell subpopulations in GBM, and how this is predictive of clinical outcome.

Effects of SPI1-mediated transcriptome remodeling on Alzheimer’s disease-related phenotypes in mouse models of Aβ amyloidosis

SPI1 was recently reported as a genetic risk factor for Alzheimer’s disease (AD) in large-scale genome-wide association studies. However, it is unknown whether SPI1 should be downregulated or increased to have therapeutic benefits. To investigate the effect of modulating SPI1 levels on AD pathogenesis, we performed extensive biochemical, histological, and transcriptomic analyses using both Spi1-knockdown and Spi1-overexpression mouse models. Here, we show that the knockdown of Spi1 expression significantly exacerbates insoluble amyloid-β (Aβ) levels, amyloid plaque deposition, and gliosis. Conversely, overexpression of Spi1 significantly ameliorates these phenotypes and dystrophic neurites. Further mechanistic studies using targeted and single-cell transcriptomics approaches demonstrate that altered Spi1 expression modulates several pathways, such as immune response pathways and complement system. Our data suggest that transcriptional reprogramming by targeting transcription factors, like Spi1, might hold promise as a therapeutic strategy. This approach could potentially expand the current landscape of druggable targets for AD.

Single-cell transcriptomics: background, technologies, applications, and challenges.

Single-cell sequencing was developed as a high-throughput tool to elucidate unusual and transient cell states that are barely visible in the bulk. This technology reveals the evolutionary status of cells and differences between populations, helps to identify unique cell subtypes and states, reveals regulatory relationships between genes, targets and molecular mechanisms in disease processes, tumor heterogeneity, the state of the immune environment, etc. However, the high cost and technical limitations of single-cell sequencing initially prevented its widespread application, but with advances in research, numerous new single-cell sequencing techniques have been discovered, lowering the cost barrier. Many single-cell sequencing platforms and bioinformatics methods have recently become commercially available, allowing researchers to make fascinating observations. They are now increasingly being used in various industries. Several protocols have been discovered in this context and each technique has unique characteristics, capabilities and challenges. This review presents the latest advancements in single-cell transcriptomics technologies. This includes single-cell transcriptomics approaches, workflows and statistical approaches to data processing, as well as the potential advances, applications, opportunities and challenges of single-cell transcriptomics technology. You will also get an overview of the entry points for spatial transcriptomics and multi-omics.

Abstract 1592: Single-cell transcriptomics reveals unique stromal and metabolic heterogeneity in liver metastatic pancreatic cancer

Abstract Pancreatic ductal adenocarcinoma (PDA) is the 3rd leading cause of cancer related death in the US. This mortality is strongly linked to the complex PDA tumor microenvironment that drives resistance to chemotherapy and immune suppression. Most patients succumb to metastatic disease, with liver being the most frequently colonized organ. Despite this, most pre-clinical studies have focused on primary PDA models to study the disease. Accordingly, the extent that the liver metastatic niche promotes immune evasion and resistance to treatment remains unclear.To directly compare primary vs. metastatic tumors in PDA tumors, we have optimized a syngeneic experimental model to contrast primary vs. metastatic lesions. To define the similarities and differences between cell types present in these tumors, we employed a single-cell transcriptomics approach. Our analysis has identified shared populations of malignant epithelial, stromal, and immune cells between lesions, allowing for a direct comparison of programming. Here, we have observed that the dominant populations of PDA cells in pancreas vs. liver tumors engage in distinct metabolic programs that suggest different actionable vulnerabilities.Beyond these, we also observed fibroblasts and myeloid sub-populations that are exclusive to liver tumors. These data further support our hypothesis that alternative mechanisms of metabolic, immune, and stromal interactions take place in the metastatic tumor microenvironment. To define these crosstalk networks, we employed the interactome tool CellChat, which has uncovered unique signaling interactions between the CAF and cancer cell populations in pancreatic or liver tumors. Overall, these data have the potential to lead to new avenues to directly target cancer cells or engage an effective immune response that can be designed to treat metastatic pancreatic cancer- an urgent clinical need. Citation Format: Rima Singh, Christopher Halbrook. Single-cell transcriptomics reveals unique stromal and metabolic heterogeneity in liver metastatic pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1592.

Navigating colorectal cancer prognosis: A Treg-related signature discovered through single-cell and bulk transcriptomic approaches.

The significance of regulatory T cells (Tregs) in colorectal cancer is unclear. The single-cell sequencing data for colorectal cancer, specifically GSE132465 and GSE188711, were retrieved from the GEO database. Simultaneously, bulk transcriptome data were obtained from the UCSC Xena website. To delve into the heterogeneity of Treg cells and identify key genes at the single-cell sequencing level, we employed dimensionality reduction techniques alongside clustering and conducted differential expression gene analysis. For the bulk transcriptome data, we utilized weighted co-expression network analysis to investigate critical gene modules. Additionally, we employed COX regression and Lasso regression methodologies to construct prognostic models, thereby assessing patient outcomes. To facilitate outcome evaluation, nomograms were constructed. The integration of these diverse approaches aims to comprehensively study colorectal cancer, encompassing single-cell heterogeneity, key gene identification, and prognosis modeling using both single-cell and bulk transcriptome data. Polymerase chain reaction (PCR) experiments are used to verify mRNA expression levels of key genes. The analysis software was R software (version 4.3.2). Through single-cell sequencing analysis and bulk transcriptome analysis, we constructed a prognostic model composed with Treg-associated signatures. The high-risk group demonstrated significantly worse prognosis compared with the low-risk group, highlighting the clinical relevance of our models. PCR confirmed that the key gene DEAH-box helicase 15 (DHX15) was significantly overexpressed in colorectal cancer. The prognostic models developed in this study offer a potential tool for risk assessment, guiding treatment decisions for colorectal cancer patients.

Cell fate decision in erythropoiesis: Insights from multiomics studies

Every second, the body produces 2 million red blood cells through a process called erythropoiesis. Erythropoiesis is hierarchical in that it results from a series of cell fate decisions whereby hematopoietic stem cells progress toward the erythroid lineage. Single-cell transcriptomic and proteomic approaches have revolutionized the way we understand erythropoiesis, revealing it to be a gradual process that underlies a progressive restriction of fate potential driven by quantitative changes in lineage-specifying transcription factors. Despite these major advances, we still know very little about what cell fate decision entails at the molecular level. Novel approaches that simultaneously measure additional properties in single cells, including chromatin accessibility, transcription factor binding, and/or cell surface proteins are being developed at a fast pace, providing the means to exciting new advances in the near future. In this review, we briefly summarize the main findings obtained from single-cell studies of erythropoiesis, highlight outstanding questions, and suggest recent technological advances to address them.

Abstract C024: Single-cell transcriptomics reveals unique stromal and metabolic heterogeneity in liver metastatic pancreatic cancer

Abstract Pancreatic ductal adenocarcinoma (PDA) is the 3rd leading cause of cancer related deaths in the US. This mortality is strongly linked to the complex PDA tumor microenvironment that drives resistance to chemotherapy and immune suppression. Most patients succumb to metastatic disease, with liver being the most frequently colonized organ. Despite this, most pre-clinical studies have focused on primary PDA models to study the disease. Accordingly, the extent that the liver metastatic niche promotes immune evasion and resistance to treatment remains unclear. To directly compare primary vs. metastatic tumors in PDA tumors, we have optimized a syngeneic experimental model to contrast primary vs. metastatic lesions. To define the similarities and differences between cell types present in these tumors, we employed a single-cell transcriptomics approach. Our analysis has identified shared populations of malignant epithelial, stromal, and immune cells between lesions, allowing for a direct comparison of programming. Here, we have observed that the dominant populations of PDA cells in pancreas vs. liver tumors engage in distinct metabolic programs that suggest different actionable vulnerabilities. Beyond these, we also observed fibroblasts and myeloid sub-populations that are exclusive to liver tumors. These data further support our hypothesis that alternative mechanisms of metabolic, immune, and stromal interactions take place in the metastatic tumor microenvironment. To define these crosstalk networks, we employed the interactome tool CellChat, which has uncovered unique signaling interactions between the CAF and cancer cell populations in pancreatic and liver tumors. Overall, these data have the potential to lead to new avenues to directly target cancer cells or engage an effective immune response that can be designed to treat metastatic pancreatic cancer- an urgent clinical need. Citation Format: Rima Singh, Natalie Yousefian, Nina Steele, Christopher Halbrook. Single-cell transcriptomics reveals unique stromal and metabolic heterogeneity in liver metastatic pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C024.

Spatial transcriptomics of fetal membrane-Decidual interface reveals unique contributions by cell types in term and preterm births.

During pregnancy, two fetomaternal interfaces, the placenta-decidua basalis and the fetal membrane-decidua parietals, allow for fetal growth and maturation and fetal-maternal crosstalk, and protect the fetus from infectious and inflammatory signaling that could lead to adverse pregnancy outcomes. While the placenta has been studied extensively, the fetal membranes have been understudied, even though they play critical roles in pregnancy maintenance and the initiation of term or preterm parturition. Fetal membrane dysfunction has been associated with spontaneous preterm birth (PTB, < 37 weeks gestation) and preterm prelabor rupture of the membranes (PPROM), which is a disease of the fetal membranes. However, it is unknown how the individual layers of the fetal membrane decidual interface (the amnion epithelium [AEC], the amnion mesenchyme [AMC], the chorion [CTC], and the decidua [DEC]) contribute to these pregnancy outcomes. In this study, we used a single-cell transcriptomics approach to unravel the transcriptomics network at spatial levels to discern the contributions of each layer of the fetal membranes and the adjoining maternal decidua during the following conditions: scheduled caesarian section (term not in labor [TNIL]; n = 4), vaginal term in labor (TIL; n = 3), preterm labor with and without rupture of membranes (PPROM; n = 3; and PTB; n = 3). The data included 18,815 genes from 13 patients (including TIL, PTB, PPROM, and TNIL) expressed across the four layers. After quality control, there were 11,921 genes and 44 samples. The data were processed by two pipelines: one by hierarchical clustering the combined cases and the other to evaluate heterogeneity within the cases. Our visual analytical approach revealed spatially recognized differentially expressed genes that aligned with four gene clusters. Cluster 1 genes were present predominantly in DECs and Cluster 3 centered around CTC genes in all labor phenotypes. Cluster 2 genes were predominantly found in AECs in PPROM and PTB, while Cluster 4 contained AMC and CTC genes identified in term labor cases. We identified the top 10 differentially expressed genes and their connected pathways (kinase activation, NF-κB, inflammation, cytoskeletal remodeling, and hormone regulation) per cluster in each tissue layer. An in-depth understanding of the involvement of each system and cell layer may help provide targeted and tailored interventions to reduce the risk of PTB.

#5461 KIDNEY TUBULE POLYPLOIDIZATION DURING PHYSIOLOGIC AGEING IN MICE

Abstract Background and Aims The aged population is constantly increasing, and kidney-aging is a risk factor for both acute kidney injury (AKI) and chronic kidney disease (CKD). Accordingly, CKD is a major global health problem with an increasing prevalence in older population. Therefore, there is an urgent need to understand the age-related mechanisms underpinning CKD development during ageing. Recent findings contributed to clarify the cellular and molecular mechanisms underlying CKD development and progression, posing tubular cells (TC) at the center of this process. In this regard, we have demonstrated that polyploidization of TC promotes fibrosis, CKD development and its progression in the long run. Here, we aimed to investigate TC polyploidization during physiologic ageing in mice. Method To investigate TC polyploidization during ageing, we took advantage of inducible Pax8/FUCCI2aR mice. In these mice, FUCCI2aR reporter is expressed by all TC after doxycycline hyclate induction. Mice were sacrificed and analyzed at 2, 5, 11 and 20 months of age. By combining DNA content with detection of FUCCI2aR fluorescent proteins, FACS analysis shows diploid (2C), tetraploid (4C) and octaploid or greater (≥8C) TC. Single cell RNA-sequencing (scRNA-seq) analysis was performed on mouse kidneys at 2 and 20 months of age to dissect the transcriptomic profile of polyploid TC and interrogate putative altered signaling pathways. Renal function parameters were assessed at 2, 5, 11 and 20 months before sacrifice. Kidneys were analyzed for senescence and interstitial fibrosis at 2, 5, 11 and 20 months of age. Results Genetic and single-cell transcriptomic approaches in mice were used to investigate TC polyploidization during ageing. Pax8/FUCCI2aR mice showed a progressive increase of polyploid TC during ageing starting from 5 months of age. ScRNA-seq analysis on kidneys of mice at 2 and 20 months of age revealed that polyploid TC were characterized by polyploidy regulators, p21 expression, accumulation of DNA damage and by acquiring senescent/fibrotic markers, demonstrating that polyploid TC rather than diploid TC accumulate DNA damage and acquire a senescent/pro-fibrotic state during physiologic ageing in vivo. In accordance with the increase of polyploid TC, mice developed interstitial fibrosis, showed a marked senescent phenotype and an age-related decline of renal function starting from 5 months of age. Collectively, these results suggest TC polyploidization is a potential trigger for CKD development and progression during physiologic kidney ageing in mice. Conclusion This study demonstrates the increase of TC polyploidization, which is associated with a progressive fibrosis, senescence and CKD development during physiologic kidney ageing in mice.

Single-Cell RNA Sequencing Reveals Microevolution of the Stickleback Immune System.

The risk and severity of pathogen infections in humans, livestock, or wild organisms depend on host immune function, which can vary between closely related host populations or even among individuals. This immune variation can entail between-population differences in immune gene coding sequences, copy number, or expression. In recent years, many studies have focused on population divergence in immunity using whole-tissue transcriptomics. But, whole-tissue transcriptomics cannot distinguish between evolved differences in gene regulation within cells, versus changes in cell composition within the focal tissue. Here, we leverage single-cell transcriptomic approaches to document signatures of microevolution of immune system structure in a natural system, the three-spined stickleback (Gasterosteus aculeatus). We sampled nine adult fish from three populations with variability in resistance to a cestode parasite, Schistocephalus solidus, to create the first comprehensive immune cell atlas for G. aculeatus. Eight broad immune cell types, corresponding to major vertebrate immune cells, were identified. We were also able to document significant variation in both abundance and expression profiles of the individual immune cell types among the three populations of fish. Furthermore, we demonstrate that identified cell type markers can be used to reinterpret traditional transcriptomic data: we reevaluate previously published whole-tissue transcriptome data from a quantitative genetic experimental infection study to gain better resolution relating infection outcomes to inferred cell type variation. Our combined study demonstrates the power of single-cell sequencing to not only document evolutionary phenomena (i.e., microevolution of immune cells) but also increase the power of traditional transcriptomic data sets.

Unraveling Psychiatric Disorders through Neural Single-Cell Transcriptomics Approaches.

The development of single-cell and single-nucleus transcriptome technologies is enabling the unraveling of the molecular and cellular heterogeneity of psychiatric disorders. The complexity of the brain and the relationships between different brain regions can be better understood through the classification of individual cell populations based on their molecular markers and transcriptomic features. Analysis of these unique cell types can explain their involvement in the pathology of psychiatric disorders. Recent studies in both human and animal models have emphasized the importance of transcriptome analysis of neuronal cells in psychiatric disorders but also revealed critical roles for non-neuronal cells, such as oligodendrocytes and microglia. In this review, we update current findings on the brain transcriptome and explore molecular studies addressing transcriptomic alterations identified in human and animal models in depression and stress, neurodegenerative disorders (Parkinson's and Alzheimer's disease), schizophrenia, opioid use disorder, and alcohol and psychostimulant abuse. We also comment on potential future directions in single-cell and single-nucleus studies.

Thyroid hormone regulators in human cerebral cortex development.

Brain development is critically dependent on the timely supply of thyroid hormones. The thyroid hormone transporters are central to the action of thyroid hormones in the brain, facilitating their passage through the blood-brain barrier. Mutations of the monocarboxylate transporter 8 (MCT8) cause the Allan-Herndon-Dudley syndrome, with altered thyroid hormone concentrations in the blood and profound neurological impairment and intellectual deficit. Mouse disease models have revealed interplay between transport, deiodination, and availability of T3 to receptors in specific cells. However, the mouse models are not satisfactory, given the fundamental differences between the mouse and human brains. The goal of the present work is to review human neocortex development in the context of thyroid pathophysiology. Recent developments in single-cell transcriptomic approaches aimed at the human brain make it possible to profile the expression of thyroid hormone regulators in single-cell RNA-Seq datasets of the developing human neocortex. The data provide novel insights into the specific cellular expression of thyroid hormone transporters, deiodinases, and receptors.

Transcriptional glucocorticoid effects in the brain: Finding the relevant target genes.

Glucocorticoids are powerful modulators of brain function. They act via mineralocorticoid and glucocorticoid receptors (MR and GR). These are best understood as transcription factors. Although many glucocorticoid effects depend on the modulation of gene transcription, it is a major challenge to link gene expression to function given the large-scale, apparently pleiotropic genomic responses. The extensive sets of MR and GR target genes are highly specific per cell type, and the brain contains many different (neuronal and non-neuronal) cell types. Next to the set "trait" of cellular context, the "state" of other active signaling pathways will affect MR and GR transcriptional activity. Here, we discuss receptor specificity and contextual factors that determine the transcriptional outcome of MR/GR signaling, experimental possibilities offered by single-cell transcriptomics approaches, and reflect on how to make sense of lists of target genes in relation to understanding the functional effects of steroid receptor activation.

Comparative single-cell analysis of the adult heart and coronary vasculature

The structure and function of the circulatory system, including the heart, have undergone substantial changes with the vertebrate evolution. Although the basic function of the heart is to pump blood through the body, its size, shape, speed, regeneration capacity, etc. vary considerably across species. Here, we address the differences among vertebrate hearts using a single-cell transcriptomics approach. Published datasets of macaque (Macaca fascicularis), mouse, and zebrafish hearts were integrated and compared to the human heart as a reference. While the three mammalian hearts integrated well, the zebrafish heart showed very little overlap with the other species. Our analysis revealed a mouse-specific cell subpopulation of ventricular cardiomyocytes (CM), represented by strikingly different expression patterns of specific genes related to high-energy metabolism. Interestingly, the observed differences between mouse and human CM coincided with actual biological differences between the two species. Smooth muscle and endothelial cells (EC) exhibited species-specific differences in clustering and gene expression, respectively, which we attribute to the tissues selected for sequencing, given different focuses of the original studies. Finally, we compared human and zebrafish heart-specific fibroblasts (FB) and identified a distinctively high expression of genes associated with heart regeneration following injury in zebrafish. Together, our results show that integration of numerous datasets of different species and different sequencing technologies is feasible and that this approach can identify species-specific differences and similarities in the heart.

Sex differences in resilience to ferroptosis underlie sexual dimorphism in kidney injury and repair.

In both humans and mice, repair of acute kidney injury is worse in males than in females. Here, we provide evidence that this sexual dimorphism results from sex differences in ferroptosis, an iron-dependent, lipid-peroxidation-driven regulated cell death. Using genetic and single-cell transcriptomic approaches in mice, we report that female sex confers striking protection against ferroptosis, which was experimentally induced in proximal tubular (PT) cells by deleting glutathione peroxidase 4 (Gpx4). Single-cell transcriptomic analyses further identify the NFE2-related factor 2 (NRF2) antioxidant protective pathway as a female resilience mechanism against ferroptosis. Genetic inhibition and pharmacological activation studies show that NRF2 controls PT cell fate and plasticity by regulating ferroptosis. Importantly, pharmacological NRF2 activation protects male PT cells from ferroptosis and improves cellular plasticity as in females. Our data highlight NRF2 as a potential therapeutic target to prevent failed renal repair after acute kidney injury in both sexes by modulating cellular plasticity.

The secret to longevity, plasma cell style.

An enduring antibody response is ultimately dependent on the generation and maintenance of long-lived plasma cells. New research describes the use of single-cell transcriptomics approaches to reveal the defining features of longevity in plasma cells.

Unravelling the landscape of skin cancer through single-cell transcriptomics

The human skin is a complex organ that forms the first line of defense against pathogens and external injury. It is composed of a wide variety of cells that work together to maintain homeostasis and prevent disease, such as skin cancer. The exponentially rising incidence of skin malignancies poses a growing public health challenge, particularly when the disease course is complicated by metastasis and therapeutic resistance. Recent advances in single-cell transcriptomics have provided a high-resolution view of gene expression heterogeneity that can be applied to skin cancers to define cell types and states, understand disease evolution, and develop new therapeutic concepts. This approach has been particularly valuable in characterizing the contribution of immune cells in skin cancer, an area of great clinical importance given the increasing use of immunotherapy in this setting. In this review, we highlight recent skin cancer studies utilizing bulk RNA sequencing, introduce various single-cell transcriptomics approaches, and summarize key findings obtained by applying single-cell transcriptomics to skin cancer.