Distinct Cell Types Research Articles

Sex-specific single cell-level transcriptomic signatures of Rett syndrome disease progression

Dominant X-linked diseases are uncommon due to female X chromosome inactivation (XCI). While random XCI usually protects females against X-linked mutations, Rett syndrome (RTT) is a female neurodevelopmental disorder caused by heterozygous MECP2 mutation. After 6-18 months of typical neurodevelopment, RTT girls undergo a poorly understood regression. We performed longitudinal snRNA-seq on cerebral cortex in a construct-relevant Mecp2e1 mutant mouse model of RTT, revealing transcriptional effects of cell type, mosaicism, and sex on progressive disease phenotypes. Across cell types, we observed sex differences in the number of differentially expressed genes (DEGs) with 6x more DEGs in mutant females than males. Unlike males, female DEGs emerged prior to symptoms, were enriched for homeostatic gene pathways in distinct cell types over time and correlated with disease phenotypes and human RTT cortical cell transcriptomes. Non-cell-autonomous effects were prominent and dynamic across disease progression of Mecp2e1 mutant females, indicating that wild-type-expressing cells normalize transcriptional homeostasis. These results advance our understanding of RTT progression and treatment.

Single-cell analysis reveals alternations between the aged and young mice prostates

BackgroundAging of the male prostate is an inevitable process in which the prostate undergoes hyperplasia, and this growth may lead to compression of the urethra, resulting in voiding dysfunction and associated symptoms, and an increased risk of prostate cancer. Despite the significance of prostate aging, the molecular mechanisms involved are still not fully understood.MethodsProstate split by lobes from young (2 months) and aged (24 months) mice were collected for single-cell RNA sequencing (scRNA-seq) analysis. Tissues from both anterior prostate (AP) and ventral/dorsal/lateral prostate (VDLP) were included in the study. Data analysis included unsupervised clustering using the uniform manifold approximation and projection (UMAP) algorithm to identify distinct cell types based on marker gene expression. Differential gene expression analysis was performed to identify age-related changes in gene expression across different cell types. Functional enrichment analysis was conducted to elucidate biological pathways associated with differentially expressed genes. Additionally, cellular interactions and developmental trajectories were analyzed to characterize cellular dynamics during prostate aging.ResultsThe single-cell transcriptome analysis of the mouse prostate during aging revealed heterogeneity across various cell types and their changes during the aging process. We found a significant increase in the proportion of mesenchymal and immune cells in aged mice. Our study unveiled alterations in genes and pathways associated with cellular senescence, oxidative stress, and regeneration in epithelial cells. Furthermore, we observed that basal cells may undergo epithelial-mesenchymal transition (EMT) to become mesenchymal cells, particularly prominent in aged mice. Additionally, immune cells, notably macrophages and T cells, exhibited a heightened inflammatory response in aged mice.ConclusionIn summary, our study provides a comparative analysis of the single-cell transcriptome of the aged and young mice prostates, elucidating cellular and molecular changes between the aged and young mice prostates.

Deconvolution of Human Urine across the Transcriptome and Metabolome.

Early detection of the cell type changes underlying several genitourinary tract diseases largely remains an unmet clinical need, where existing assays, if available, lack the cellular resolution afforded by an invasive biopsy. While messenger RNA in urine could reflect the dynamic signal that facilitates early detection, current measurements primarily detect single genes and thus do not reflect the entire transcriptome and the underlying contributions of cell type-specific RNA. We isolated and sequenced the cell-free RNA (cfRNA) and sediment RNA from human urine samples (n = 6 healthy controls and n = 12 kidney stone patients) and measured the urine metabolome. We analyzed the resulting urine transcriptomes by deconvolving the noninvasively measurable cell type contributions and comparing to plasma cfRNA and the measured urine metabolome. Urine transcriptome cell type deconvolution primarily yielded relative fractional contributions from genitourinary tract cell types in addition to cell types from high-turnover solid tissues beyond the genitourinary tract. Comparison to plasma cfRNA yielded enrichment of metabolic pathways and a distinct cell type spectrum. Integration of urine transcriptomic and metabolomic measurements yielded enrichment for metabolic pathways involved in amino acid metabolism and overlapped with metabolic subsystems associated with proximal tubule function. Noninvasive whole transcriptome measurements of human urine cfRNA and sediment RNA reflects signal from hard-to-biopsy tissues exhibiting low representation in blood plasma cfRNA liquid biopsy at cell type resolution and are enriched in signal from metabolic pathways measurable in the urine metabolome.

Functional Optimization in Distinct Tissues and Conditions Constrains the Rate of Protein Evolution.

Understanding the main determinants of protein evolution is a fundamental challenge in biology. Despite many decades of active research, the molecular and cellular mechanisms underlying the substantial variability of evolutionary rates across cellular proteins are not currently well understood. It also remains unclear how protein molecular function is optimized in the context of multicellular species and why many proteins, such as enzymes, are only moderately efficient on average. Our analysis of genomics and functional datasets reveals in multiple organisms a strong inverse relationship between the optimality of protein molecular function and the rate of protein evolution. Furthermore, we find that highly expressed proteins tend to be substantially more functionally optimized. These results suggest that cellular expression costs lead to more pronounced functional optimization of abundant proteins and that the purifying selection to maintain high levels of functional optimality significantly slows protein evolution. We observe that in multicellular species both the rate of protein evolution and the degree of protein functional efficiency are primarily affected by expression in several distinct cell types and tissues, specifically, in developed neurons with upregulated synaptic processes in animals and in young and fast-growing tissues in plants. Overall, our analysis reveals how various constraints from the molecular, cellular, and species' levels of biological organization jointly affect the rate of protein evolution and the level of protein functional adaptation.

Myxococcus xanthus fruiting body morphology is important for spore recovery after exposure to environmental stress.

Environmental microorganisms have evolved a variety of strategies to survive fluctuations in environmental conditions, including the production of biofilms and differentiation into spores. Myxococcus xanthus are ubiquitous soil bacteria that produce starvation-induced multicellular fruiting bodies filled with environmentally resistant spores (a specialized biofilm). Isolated spores have been shown to be more resistant than vegetative cells to heat, ultraviolet radiation, and desiccation. The evolutionary advantage of producing spores inside fruiting bodies is not clear. Here, we examine a hypothesis that the fruiting body provides additional protection from environmental insults. We developed a high-throughput method to compare the recovery (outgrowth) of distinct cell types (vegetative cells, free spores, and spores within intact fruiting bodies) after exposure to ultraviolet radiation or desiccation. Our data indicate that haystack-shaped fruiting bodies protect spores from extended UV radiation but do not provide additional protection from desiccation. Perturbation of fruiting body morphology strongly impedes recovery from both UV exposure and desiccation. These results hint that the distinctive fruiting bodies produced by different myxobacterial species may have evolved to optimize their persistence in distinct ecological niches.IMPORTANCEEnvironmental microorganisms play an important role in the production of greenhouse gases that contribute to changing climate conditions. It is imperative to understand how changing climate conditions feedback to influence environmental microbial communities. The myxobacteria are environmentally ubiquitous social bacteria that influence the local microbial community composition. Defining how these bacteria are affected by environmental insults is a necessary component of predicting climatic feedback effects. When starved, myxobacteria produce multicellular fruiting bodies filled with spores. As spores are resistant to a variety of environmental insults, the evolutionary advantage of building a fruiting body is not clear. Using the model myxobacterium, Myxococcus xanthus, we demonstrate that the tall, haystack-shaped fruiting body morphology enables significantly more resistance to UV exposure than the free spores. In contrast, fruiting bodies are slightly detrimental to recovery from extended desiccation, an effect that is strongly exaggerated if fruiting body morphology is perturbed. These results suggest that the variety of fruiting body morphologies observed in the myxobacteria may dictate their relative resistance to changing climate conditions.

Going with the flow: New insights regarding flow induced K+ secretion in the distal nephron.

K+ secretion in the distal nephron has a critical role in K+ homeostasis and is the primary route by which K+ is lost from the body. Renal K+ secretion is enhanced by increases in dietary K+ intake and by increases in tubular flow rate in the distal nephron. This review addresses new and important insights regarding the mechanisms underlying flow-induced K+ secretion (FIKS). While basal K+ secretion in the distal nephron is mediated by renal outer medullary K+ (ROMK) channels in principal cells (PCs), FIKS is mediated by large conductance, Ca2+/stretch activated K+ (BK) channels in intercalated cells (ICs), a distinct cell type. BK channel activation requires an increase in intracellular Ca2+ concentration ([Ca2+]i), and both PCs and ICs exhibit increases in [Ca2+]i in response to increases in tubular fluid flow rate, associated with an increase in tubular diameter. PIEZO1, a mechanosensitive, nonselective cation channel, is expressed in the basolateral membranes of PCs and ICs, where it functions as a mechanosensor. The loss of flow-induced [Ca2+]i transients in ICs and BK channel-mediated FIKS in microperfused collecting ducts isolated from mice with IC-specific deletion of Piezo1 in the CCD underscores the importance of PIEZO1 in the renal regulation of K+ transport.

Dissecting the Single-Cell Diversity and Heterogeneity Underlying Cervical Precancerous Lesions and Cancer Tissues.

The underlying cellular diversity and heterogeneity from cervix precancerous lesions to cervical squamous cell carcinoma (CSCC) is investigated. Four single-cell datasets including normal tissues, normal adjacent tissues, precancerous lesions, and cervical tumors were integrated to perform disease stage analysis. Single-cell compositional data analysis (scCODA) was utilized to reveal the compositional changes of each cell type. Differentially expressed genes (DEGs) among cell types were annotated using BioCarta. An assay for transposase-accessible chromatin sequencing (ATAC-seq) analysis was performed to correlate epigenetic alterations with gene expression profiles. Lastly, a logistic regression model was used to assess the similarity between the original and new cohort data (HRA001742). After global annotation, seven distinct cell types were categorized. Eight consensus-upregulated DEGs were identified in B cells among different disease statuses, which could be utilized to predict the overall survival of CSCC patients. Inferred copy number variation (CNV) analysis of epithelial cells guided disease progression classification. Trajectory and ATAC-seq integration analysis identified 95 key transcription factors (TF) and one immunohistochemistry (IHC) testified key-node TF (YY1) involved in epithelial cells from CSCC initiation to progression. The consistency of epithelial cell subpopulation markers was revealed with single-cell sequencing, bulk sequencing, and RT-qPCR detection. KRT8 and KRT15, markers of Epi6, showed progressively higher expression with disease progression as revealed by IHC detection. The logistic regression model testified the robustness of the resemblance of clusters among the various datasets utilized in this study. Valuable insights into CSCC cellular diversity and heterogeneity provide a foundation for future targeted therapy.

Single-nucleus and spatial transcriptomics of paediatric ovary: Molecular insights into the dysregulated signalling pathways underlying premature ovarian insufficiency in classic galactosemia.

Classic galactosemia (CG) is an inborn error of galactose metabolism caused by mutations in the GALT gene. Premature ovarian insufficiency (POI) is a later complication that affects 80% of women with CG due to a significant decline in ovarian reserve (primordial follicle pool). The definite mechanisms underlying the early onset of POI in CG patients are not fully understood. In this study, we performed single-nucleus RNA sequencing (snRNA-seq) and spatial transcriptomics on ovary tissue biopsies from prepubertal girls diagnosed with CG to investigate dynamic changes in gene expression and altered signalling pathways in granulosa cells, oocytes, and stromal cells. We generated single-nucleus and spatial transcriptomics atlas of human ovaries from prepubertal girls diagnosed with and without CG. snRNA-seq profiling of the paediatric ovary revealed a diverse ovarian microenvironment with seven distinct major cell types. Our transcriptomic analysis revealed an increase in the expression of several endoplasmic reticulum stress and oxidative stress associated genes, which can promote apoptosis of granulosa cells in CG. PTEN/PI3K/AKT signalling, which is crucial for primordial follicle activation and survival was dysregulated as supported by upregulated PTEN transcripts and a significant reduction in phospho-AKT levels in the granulosa cells and oocytes. We also found a marked increase in expression of phospho-H2A.X, LC3A/B and CASP9 in the primordial follicles of CG ovaries suggesting DNA damage, autophagy, and accelerated follicular atresia. Furthermore, we noticed genes participating in extracellular matrix organisation, integrin and gap junction signalling, essential for structural support of the ovarian stroma were profoundly altered. Our findings provide molecular insights into the dysregulated cellular signalling pathways essential for primordial follicle growth and survival that can explain the etiology of POI in CG patients. This study has implications in the development of future therapeutic interventions to preserve ovarian function and promote femalereproductive health. Created a comprehensive single-nucleus transcriptomic atlas and spatial landscape of paediatric ovary tissue from prepubertal girls diagnosed with classic galactosemia (CG). Our transcriptomic analysis revealed activation of genes associated with ER-stress signalling, oxidative stress response and ATM signalling/DNA damage response as shown by significant increase in expression of p-EIF2A, p-H2A.X and LC3A/B in the primordial follicles of CG ovary. PTEN/PI3K/AKT signalling pathways was dysregulated evidenced by a significant reduction in phospho-AKT expression in the primordial follicles of CG ovary, suggesting impaired follicle activation and survival.

Peptidoglycan accumulates in distinct brain regions and cell types over lifetime but is absent in newborns

Peptidoglycan (PGN) is a large complex polymer critical to structure and function of all bacterial species. Intact PGN and its fragments are inflammatory, contributing to infectious and autoimmune disease. Recent studies show that PGN physiologically contributes to immune setpoints, and importantly also to mouse brain development and behavior. However, for the human brain, it remains unknown whether PGN and its fragments differentially gain access to distinct brain regions, which cell types accumulate it, and whether PGN brain load varies with age. Therefore, we investigated human postmortem brain samples of donors with an extensive age range, from newborns to nonagenarians. We examined two monoclonal antibodies against PGN which were validated using dot blot analysis, competition assays and immunofluorescence experiments on bacteria sacculi, which jointly showed specific detection of Gram-positive PGN. As positive reference tissue, brain tissue from sepsis patients, and human liver were used, both showing the expected high PGN levels. In adult brain tissue of different age (34- to 94-year-old) and sex, we detected PGN signals in seven different brain regions, with highest loads in the occipital cortex, hippocampal formation, frontal cortex, the periventricular region and the olfactory bulb. Age-dependent increase of signals was not evident by microscopic observations and only weak correlation was found by statistical analysis in this cohort. PGN was found intracellularly in the cytoplasm surrounding the cell nucleus in astrocytes, oligodendrocytes, neurons, and endothelial cells, but not in macrophages like microglia. PGN was absent in brain tissues of three human newborns (stillbirth to four weeks old). For comparison, three brain regions from non-human primates of varying age (newborn to 21 years) were immunohistochemically stained. The highest PGN-load was observed in brain tissue from 18- to 21-year-old macaques.This first systematic evaluation of PGN in human postmortem brain suggests that PGN accumulates during lifetime until it reaches a plateau by homeostatic turnover and highlights the ubiquitous presence of PGN in human brain tissues, and their ability to participate in physiological as well as pathological processes throughout life.

Identification of functional heterogeneity of immune cells and tubular-immune cellular interplay action in diabetic kidney disease.

Renal inflammation plays key roles in the pathogenesis of diabetic kidney disease (DKD). Immune cell infiltration is the main pathological feature in the progression of DKD. Sodium glucose cotransporter 2 inhibitor (SGLT2i) were reported to have antiinflammatory effects on DKD. While the heterogeneity and molecular basis of the pathogenesis and treatment with SGLT2i in DKD remains poorly understood. To address this question, we performed a single-cell transcriptomics data analysis and cell cross-talk analysis based on the database (GSE181382). The single-cell transcriptome analysis findings were validated using multiplex immunostaining. A total of 58760 cells are categorized into 25 distinct cell types. A subset of macrophages with anti-inflammatory potential was identified. We found that Ccl3+ (S100a8/a9 high) macrophages with anti-inflammatory and antimicrobial in the pathogenesis of DKD decreased and reversed the dapagliflozin treatment. Besides, dapagliflozin treatment enhanced the accumulation of Pck1+ macrophage, characterized by gluconeogenesis signaling pathway. Cell-cross talk analysis showed the GRN/SORT1 pair and CD74 related signaling pathways were enriched in the interactions between tubular epithelial cells and immune cells. Our study depicts the heterogeneity of macrophages and clarifies a new possible explanation of dapagliflozin treatment, showing the metabolism shifts toward gluconeogenesis in macrophages, fueling the anti-inflammatory function of M2 macrophages, highlighting the new molecular features and signaling pathways and potential therapeutic targets, which has provided an important reference for the study of immune-related mechanisms in the progression of the disease.

Single-cell analysis of preimplantation embryonic development in guinea pigs

BackgroundGuinea pigs exhibit numerous physiological similarities to humans, yet the details of their preimplantation embryonic development remain largely unexplored.ResultsTo address this, we conducted single-cell sequencing on the transcriptomes of cells isolated from the zygote stage through preimplantation stages in guinea pigs. This study identified seven distinct cell types within guinea pig preimplantation embryos and pinpointed the timing of zygotic gene activation (ZGA). Trajectory analysis revealed a bifurcation into two lineage-specific branches, accompanied by alterations in specific pathways, including oxidative phosphorylation and vascular endothelial growth factor (VEGF). Additionally, co-expressed gene network analysis highlighted the most enriched functional modules for the epiblast (EPI), primitive endoderm (PrE), and inner cell mass (ICM). Finally, we compared the similarities and differences between human and guinea pig epiblasts (EPIs).ConclusionThis study systematically constructs a cell atlas of guinea pig preimplantation embryonic development, offering fresh insights into mammalian embryonic development and providing alternative experimental models for studying human embryonic development.

The role of neuron-like cell lines and primary neuron cell models in unraveling the complexity of neurodegenerative diseases: a comprehensive review.

Neurodegenerative diseases (NDs) are characterized by the progressive loss of neurons. As to developing effective therapeutic interventions, it is crucial to understand the underlying mechanisms of NDs. Cellular models have become invaluable tools for studying the complex pathogenesis of NDs, offering insights into disease mechanisms, determining potential therapeutic targets, and aiding in drug discovery. This review provides a comprehensive overview of various cellular models used in ND research, focusing on Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. Cell lines, such as SH-SY5Y and PC12 cells, have emerged as valuable tools due to their ease of use, reproducibility, and scalability. Additionally, co-culture models, involving the growth of distinct cell types like neurons and astrocytes together, are highlighted for simulating brain interactions and microenvironment. While cell lines cannot fully replicate the complexity of the human brain, they provide a scalable method for examining important aspects of neurodegenerative diseases. Advancements in cell line technologies, including the incorporation of patient-specific genetic variants and improved co-culture models, hold promise for enhancing our understanding and expediting the development of effective treatments. Integrating multiple cellular models and advanced technologies offers the potential for significant progress in unraveling the intricacies of these debilitating diseases and improving patient outcomes.

Exploring copper metabolism-induced cell death in gastric cancer: a single-cell RNA sequencing study and prognostic model development

BackgroundGastric cancer (GC) is the third leading cause of cancer-related deaths globally. Despite advancements in treatment, the overall 5-year survival rate remains below 30%, particularly in advanced stages. Copper metabolism, vital for various cellular processes, has been linked to cancer progression, but its role in GC, especially at the single-cell level, is not well understood.ObjectiveThis study aims to investigate copper metabolism in GC by integrating single-cell RNA sequencing (scRNA-seq) data and developing a prognostic model based on copper metabolism-related gene (CMRG) expression. The study explores how copper metabolism affects the tumor microenvironment and identifies potential therapeutic targets.MethodsscRNA-seq data from gastric cancer and normal tissues were analyzed using the Seurat package. Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) were used for dimensionality reduction and clustering. Non-negative matrix factorization (NMF) was employed for T cell subpopulation analysis. A high-dimensional weighted gene co-expression network analysis (HdWGCNA) identified key molecular features. LASSO regression and Random Survival Forest (RSF) techniques were used to create and validate a prognostic model. Survival analysis, immune microenvironment assessment, and drug sensitivity analysis were conducted.ResultsSixteen cell clusters and nine distinct cell types were identified, with T cells showing significant roles in cell communication. The NMF analysis of CD8 +T cells revealed five copper metabolism-related subtypes. The prognostic model based on nine CMRGs indicated significant survival differences between high- and low-risk groups. High-risk patients showed shorter survival times, increased immune cell infiltration, and altered immune responses. Drug sensitivity analysis suggested higher efficacy of certain drugs in high-CMRG patients.

Specific retinal neurons regulate context-dependent defensive responses to visual threat.

While encountering a visual threat, an animal assesses multiple factors to choose an appropriate defensive strategy. For example, when a rodent detects a looming aerial predator, its behavioral response can be influenced by a specific environmental context, such as the availability of a shelter. Indeed, rodents typically escape from a looming stimulus when a shelter is present; otherwise, they typically freeze. Here we report that context-dependent behavioral responses can be initiated at the earliest stage of the visual system by distinct types of retinal ganglion cells (RGCs), the retina's output neurons. Using genetically defined cell ablation in mature mice, we discovered that some RGC types were necessary for either escaping (alpha RGCs) or freezing (intrinsically photosensitive RGCs) in response to a looming stimulus but not for both behaviors; whereas other RGC types were not required for either behavior (direction-selective RGCs preferring vertical motion). Altogether, our results suggest that specific RGC types regulate distinct behavioral responses elicited by the same threatening stimulus depending on contextual signals in the environment. These findings emphasize the unique contribution of early visual pathways to evolutionally conserved behavioral reactions.

Investigating the cis-regulatory basis of C3 and C4 photosynthesis in grasses at single-cell resolution

While considerable knowledge exists about the enzymes pivotal for C4 photosynthesis, much less is known about the cis-regulation important for specifying their expression in distinct cell types. Here, we use single-cell-indexed ATAC-seq to identify cell-type-specific accessible chromatin regions (ACRs) associated with C4 enzymes for five different grass species. This study spans four C4 species, covering three distinct photosynthetic subtypes: Zea mays and Sorghum bicolor (NADP-dependent malic enzyme), Panicum miliaceum (NAD-dependent malic enzyme), Urochloa fusca (phosphoenolpyruvate carboxykinase), along with the C3 outgroup Oryza sativa. We studied the cis-regulatory landscape of enzymes essential across all C4 species and those unique to C4 subtypes, measuring cell-type-specific biases for C4 enzymes using chromatin accessibility data. Integrating these data with phylogenetics revealed diverse co-option of gene family members between species, showcasing the various paths of C4 evolution. Besides promoter proximal ACRs, we found that, on average, C4 genes have two to three distal cell-type-specific ACRs, highlighting the complexity and divergent nature of C4 evolution. Examining the evolutionary history of these cell-type-specific ACRs revealed a spectrum of conserved and novel ACRs, even among closely related species, indicating ongoing evolution of cis-regulation at these C4 loci. This study illuminates the dynamic and complex nature of cis-regulatory elements evolution in C4 photosynthesis, particularly highlighting the intricate cis-regulatory evolution of key loci. Our findings offer a valuable resource for future investigations, potentially aiding in the optimization of C3 crop performance under changing climatic conditions.

Coordinated, multicellular patterns of transcriptional variation that stratify patient cohorts are revealed by tensor decomposition.

Tissue-level and organism-level biological processes often involve the coordinated action of multiple distinct cell types. The recent application of single-cell assays to many individuals should enable the study of how donor-level variation in one cell type is linked to that in other cell types. Here we introduce a computational approach called single-cell interpretable tensor decomposition (scITD) to identify common axes of interindividual variation by considering joint expression variation across multiple cell types. scITD combines expression matrices from each cell type into a higher-order matrix and factorizes the result using the Tucker tensor decomposition. Applying scITD to single-cell RNA-sequencing data on 115 persons with lupus and 83 persons with coronavirus disease 2019, we identify patterns of coordinated cellular activity linked to disease severity and specific phenotypes, such as lupus nephritis. scITD results also implicate specific signaling pathways likely mediating coordination between cell types. Overall, scITD offers a tool for understanding the covariation of cell states across individuals, which can yield insights into the complex processes that define and stratify disease.

Transcriptomic characterization of human lateral septum neurons reveals conserved and divergent marker genes across species.

The lateral septum (LS) is a midline, subcortical structure, which regulates social behaviors that are frequently impaired in neurodevelopmental disorders including schizophrenia and autism spectrum disorder. Mouse studies have identified neuronal populations within the LS that express a variety of molecular markers, including vasopressin receptor, oxytocin receptor, and corticotropin releasing hormone receptor, which control specific facets of social behavior. Despite its critical role in regulating social behavior and notable gene expression patterns, comprehensive molecular profiling of the human LS has not been performed. Here, we conducted single nucleus RNA-sequencing (snRNA-seq) to generate the first transcriptomic profiles of the human LS using postmortem human brain tissue samples from 3 neurotypical donors. Our analysis identified 5 transcriptionally distinct neuronal cell types within the human LS that are enriched for TRPC4, the gene encoding Trp-related protein 4. Differential expression analysis revealed a distinct LS neuronal cell type that is enriched for OPRM1, the gene encoding the μ-opioid receptor. Leveraging recently generated mouse LS snRNA-seq datasets, we conducted a cross-species analysis. Our results demonstrate that TRPC4 enrichment in the LS is highly conserved between human and mouse, while FREM2, which encodes FRAS1 related extracellular matrix protein 2, is enriched only in the human LS. Together, these results highlight transcriptional heterogeneity of the human LS, and identify robust marker genes for the human LS.

Single‐cell and spatial transcriptomics: Discovery of human placental development and disease

AbstractThe human placenta is a vital organ, encompassing many distinct cell types, that maintains the growth and development of the fetus and is essential for substance exchange, defense, synthesis, and immunity. Abnormalities in placental cells can lead to various pregnancy complications, but the mechanisms remain largely unclear. Single‐cell and spatial transcriptomics technologies have been developed in recent years to demonstrate placental cell heterogeneity and spatial molecular localization. Here, we review and summarize the current literature, demonstrating these technologies and showing the heterogeneity of various placenta cells and cell–cell communication of normal human placenta, as well as placenta‐related diseases, such as preeclampsia, gestational diabetes mellitus, advanced maternal age, recurrent pregnancy loss, and placenta accreta spectrum disorders. Meanwhile, current weaknesses and future direction were discussed.

Deciphering Transcriptomic Variations in Hematopoietic Lineages: HSCs, EBs, and MKs.

In the realm of hematopoiesis, hematopoietic stem cells (HSCs) serve as pivotal entities responsible for generating various blood cell types, initiating both the myeloid and lymphoid branches within the hematopoietic lineage. This intricate process is marked by genetic variations that underscore the crucial role of genes in regulating cellular functions and interactions. Recognizing the significance of genetic factors in this context, this article delves into a genetic perspective, aiming to unravel the biological factors that govern the transition from one cell's fate to another within the hematopoietic system. To gain deeper insights into the genetic traits of three distinct blood cell types-HSCs, erythroblasts (EBs), and megakaryocytes (MKs)-we conducted a comprehensive transcriptomic analysis. Leveraging diverse hematopoietic cell datasets from healthy individuals, sourced from The BLUEPRINT consortium, our investigation targeted the identification of genetic variants responsible for changes in gene expression levels and epigenetic modifications across the entire human genome in each of these cell types. The total number of normalized expressed transcripts includes 14,233 novel trinity lncRNAs, 13,749 mRNAs, and 3092 lncRNAs. This scrutiny revealed a total of 31,074 transcripts, with a notable revelation that 14,233 of them were previously unidentified or novel lncRNAs, highlighting a substantial reservoir of genetic information yet to be explored. Examining their expression across distinct lineages further unveiled 2845 differentially expressed (DE) mRNAs and 354 DE long noncoding RNAs (lncRNAs) notably enriched among the three distinct blood cell types: HSCs, EBs, and MKs. Our investigation extended beyond mRNA to focus on the dynamic expression of lncRNAs, revealing a well-defined pattern that played a significant role in regulating differentiation and cell-fate specification. This coordination of lncRNA dynamics extended to aberrations in both mRNA and lncRNA transcriptomes within HSCs, EBs, and MKs. We specifically characterized lncRNAs with preferential expression in HSCs, as well as in various downstream differentiated lineage progenitors of EBs and MKs, providing a comprehensive perspective on lncRNAs in human hematopoietic cells. Notably, the expression of lncRNAs exhibited substantial cell-to-cell variation, a phenomenon discernible only through single-cell analysis. The comparative analysis undertaken in this study provides valuable insights into the distinctive genetic signatures guiding the differentiation of these crucial hematopoietic cell types.

A Review on Single-Cell analysis of Macrophages in Cancer

Cancer is characterized by uncontrolled cell growth and spread into surrounding tissue. According to the North American Association of Central Cancer Registries (NAACCR) and the National Center for Health Statistics, there were 1,918,030 cancer cases and a total of 609,360 deaths estimated in the US in 2022. Although the direct cause of cancer is not fully understood, it is recognized that the immune system plays a major role in the development and progression of tumors. Investigating tumor-associated macrophages (TAMs) is crucial for understanding the immunosuppressive role that they may play in the tumor microenvironment, which makes them a target for immunotherapies to combat cancer. However, angiogenesis, tumor initiation and invasion promoting signals prevent gaining deeper insight into the intricate molecular mechanisms involved in TAMs and the tumor microenvironment. While researchers in the past have used population samples to analyze cells, recent efforts have incorporated single-cell technologies to study the complex mixture of cells in a tumor, monitor the effects of immunotherapies and more. With the revolutionary advent of the first single-cell RNA sequencing (scRNA-seq), researchers have since been able to gain insight into single-cell data with unprecedented accuracy and develop new immunotherapies through different single-cell technologies, such as polymethylsiloxane (PDMS) and Multiplexed Ion Beam Imaging (MIBI) multiplexing. In this review, we underline the benefits of adopting single-cell technologies to identify distinct cell types in complex environments (i.e., tumors) and highlight the potential application of these technologies along with various multiplexing techniques to immunotherapies.