Glioblastoma hijacks neuronal mechanisms for brain invasion.

Glioblastomas are incurable tumors infiltrating the brain. A subpopulation of glioblastoma cells forms a functional and therapy-resistant tumor cell network interconnected by tumor microtubes (TMs). Other subpopulations appear unconnected, and their biological role remains unclear. Here, we demonstrate that whole-brain colonization is fueled by glioblastoma cells that lack connections with other tumor cells and astrocytes yet receive synaptic input from neurons. This subpopulation corresponds to neuronal and neural-progenitor-like tumor cell states, as defined by single-cell transcriptomics, both in mouse models and in the human disease. Tumor cell invasion resembled neuronal migration mechanisms and adopted a Lévy-like movement pattern of probing the environment. Neuronal activity induced complex calcium signals in glioblastoma cells followed by the de novo formation of TMs and increased invasion speed. Collectively, superimposing molecular and functional single-cell data revealed that neuronal mechanisms govern glioblastoma cell invasion on multiple levels. This explains how glioblastoma's dissemination and cellular heterogeneity are closely interlinked.

Single-Cell Transcriptome Atlas of Murine Endothelial Cells.

The heterogeneity of endothelial cells (ECs) across tissues remains incompletely inventoried. We constructed an atlas of >32,000 single-EC transcriptomes from 11 mouse tissues and identified 78 EC subclusters, including Aqp7+ intestinal capillaries and angiogenic ECs in healthy tissues. ECs from brain/testis, liver/spleen, small intestine/colon, and skeletal muscle/heart pairwise expressed partially overlapping marker genes. Arterial, venous, and lymphatic ECs shared more markers in more tissues than did heterogeneous capillary ECs. ECs from different vascular beds (arteries, capillaries, veins, lymphatics) exhibited transcriptome similarity across tissues, but the tissue (rather than the vessel) type contributed to the EC heterogeneity. Metabolic transcriptome analysis revealed a similar tissue-grouping phenomenon of ECs and heterogeneous metabolic gene signatures in ECs between tissues and between vascular beds within a single tissue in a tissue-type-dependent pattern. The EC atlas taxonomy enabled identification of EC subclusters in public scRNA-seq datasets and provides a powerful discovery tool and resource value.

A Multiplexed Single-Cell CRISPR Screening Platform Enables Systematic Dissection of the Unfolded Protein Response.

Functional genomics efforts face tradeoffs between number of perturbations examined and complexity of phenotypes measured. We bridge this gap with Perturb-seq, which combines droplet-based single-cell RNA-seq with a strategy for barcoding CRISPR-mediated perturbations, allowing many perturbations to be profiled in pooled format. We applied Perturb-seq to dissect the mammalian unfolded protein response (UPR) using single and combinatorial CRISPR perturbations. Two genome-scale CRISPR interference (CRISPRi) screens identified genes whose repression perturbs ER homeostasis. Subjecting ∼100 hits to Perturb-seq enabled high-precision functional clustering of genes. Single-cell analyses decoupled the three UPR branches, revealed bifurcated UPR branch activation among cells subject to the same perturbation, and uncovered differential activation of the branches across hits, including an isolated feedback loop between the translocon and IRE1α. These studies provide insight into how the three sensors of ER homeostasis monitor distinct types of stress and highlight the ability of Perturb-seq to dissect complex cellular responses.

Studying lineage decision-making in vitro: emerging concepts and novel tools.

Correct and timely lineage decisions are critical for normal embryonic development and homeostasis of adult tissues. Therefore, the search for fundamental principles that underlie lineage decision-making lies at the heart of developmental biology. Here, we review attempts to understand lineage decision-making as the interplay of single-cell heterogeneity and gene regulation. Fluctuations at the single-cell level are an important driving force behind cell-state transitions and the creation of cell-type diversity. Gene regulatory networks amplify such fluctuations and define stable cell types. They also mediate the influence of signaling inputs on the lineage decision. In this review, we focus on insights gleaned from in vitro differentiation of embryonic stem cells. We discuss emerging concepts, with an emphasis on transcriptional regulation, dynamical aspects of differentiation, and functional single-cell heterogeneity. We also highlight some novel tools to study lineage decision-making in vitro.

CD4+ T Cell Help Is Required for the Formation of a Cytolytic CD8+ T Cell Subset that Protects against Chronic Infection and Cancer.

Although CD4+ T cell "help" is crucial to sustain antiviral immunity, the mechanisms by which CD4+ T cells regulate CD8+ T cell differentiation during chronic infection remain elusive. Here, using single-cell RNA sequencing, we show that CD8+ T cells responding to chronic infection were more heterogeneous than previously appreciated. Importantly, our findings uncovered the formation of a CX3CR1-expressing CD8+ T cell subset that exhibited potent cytolytic function and was required for viral control. Notably, our data further demonstrate that formation of this cytotoxic subset was critically dependent on CD4+ T cell help via interleukin-21 (IL-21) and that exploitation of this developmental pathway could be used therapeutically to enhance the killer function of CD8+ T cells infiltrated into the tumor. These findings uncover additional molecular mechanisms of how "CD4+ T cell help" regulates CD8+ T cell differentiation during persistent infection and have implications toward optimizing the generation of protective CD8+ T cells in immunotherapy.

Single-Cell Transcriptomics of Human and Mouse Lung Cancers Reveals Conserved Myeloid Populations across Individuals and Species.

Tumor-infiltrating myeloid cells (TIMs) comprise monocytes, macrophages, dendritic cells, and neutrophils, and have emerged as key regulators of cancer growth. These cells can diversify into a spectrum of states, which might promote or limit tumor outgrowth but remain poorly understood. Here, we used single-cell RNA sequencing (scRNA-seq) to map TIMs in non-small-cell lung cancer patients. We uncovered 25 TIM states, most of which were reproducibly found across patients. To facilitate translational research of these populations, we also profiled TIMs in mice. In comparing TIMs across species, we identified a near-complete congruence of population structures among dendritic cells and monocytes; conserved neutrophil subsets; and species differences among macrophages. By contrast, myeloid cell population structures in patients' blood showed limited overlap with those of TIMs. This study determines the lung TIM landscape and sets the stage for future investigations into the potential of TIMs as immunotherapy targets.

Epigenetic and transcription factors synergistically promote the high temperature response in plants.

Temperature is one of the main environmental cues affecting plant growth and development, and plants have evolved multiple mechanisms to sense and acclimate to high temperature. Emerging research has shown that transcription factors, epigenetic factors, and their coordination are essential for plant temperature responses and the resulting phenological adaptation. Here, we summarize recent advances in molecular and cellular mechanisms to understand how plants acclimate to high temperature and describe how plant meristems sense and integrate environmental signals. Furthermore, we lay out future directions for new technologies to reveal heterogeneous responses in different cell types thus improving plant environmental plasticity.

Direct observation correlates NFκB cRel in B cells with activating and terminating their proliferative program.

Antibody responses require the proliferative expansion of B cells controlled by affinity-dependent signals. Yet, proliferative bursts are heterogeneous, varying between 0 and 8 divisions in response to the same stimulus. NFκB cRel is activated in response to immune stimulation in B cells and is genetically required for proliferation. Here, we asked whether proliferative heterogeneity is controlled by natural variations in cRel abundance. We developed a fluorescent reporter mTFP1-cRel for the direct observation of cRel in live proliferating B cells. We found that cRel is heterogeneously distributed among naïve B cells, which are enriched for high expressors in a heavy-tailed distribution. We found that high cRel expressors show faster activation of the proliferative program, but do not sustain it well, with population expansion decaying earlier. With a mathematical model of the molecular network, we showed that cRel heterogeneity arises from balancing positive feedback by autoregulation and negative feedback by its inhibitor IκBε, confirmed by mouse knockouts. Using live-cell fluorescence microscopy, we showed that increased cRel primes B cells for early proliferation via higher basal expression of the cell cycle driver cMyc. However, peak cMyc induction amplitude is constrained by incoherent feedforward regulation, decoding the fold change of cRel activity to terminate the proliferative burst. This results in a complex nonlinear, nonmonotonic relationship between cRel expression and the extent of proliferation. These findings emphasize the importance of direct observational studies to complement gene knockout results and to learn about quantitative relationships between biological processes and their key regulators in the context of natural variations.

Cell fate simulation reveals cancer cell features in the tumor microenvironment.

To elucidate the dynamic evolution of cancer cell characteristics within the tumor microenvironment (TME), we developed an integrative approach combining single-cell tracking, cell fate simulation, and 3D TME modeling. We began our investigation by analyzing the spatiotemporal behavior of individual cancer cells in cultured pancreatic (MiaPaCa2) and cervical (HeLa) cancer cell lines, with a focus on the α2-6 sialic acid (α2-6Sia) modification on glycans, which is associated with cell stemness. Our findings revealed that MiaPaCa2 cells exhibited significantly higher levels of α2-6Sia modification, correlating with enhanced reproductive capabilities, whereas HeLa cells showed less prevalence of this modification. To accommodate the in vivo variability of α2-6Sia levels, we employed a cell fate simulation algorithm that digitally generates cell populations based on our observed data while varying the level of sialylation, thereby simulating cell growth patterns. Subsequently, we performed a 3D TME simulation with these deduced cell populations, considering the microenvironment that could impact cancer cell growth. Immune cell landscape information derived from 193 cervical and 172 pancreatic cancer cases was used to estimate the degree of the positive or negative impact. Our analysis suggests that the deduced cells generated based on the characteristics of MiaPaCa2 cells are less influenced by the immune cell landscape within the TME compared to those of HeLa cells, highlighting that the fate of cancer cells is shaped by both the surrounding immune landscape and the intrinsic characteristics of the cancer cells.

Targeting the key players of phenotypic plasticity in cancer cells by phytochemicals.

Plasticity of phenotypic traits refers to an organism's ability to change in response to environmental stimuli. As a result, the response may alter an organism's physiological state, morphology, behavior, and phenotype. Phenotypic plasticity in cancer cells describes the considerable ability of cancer cells to transform phenotypes through non-genetic molecular signaling activities that promote therapy evasion and tumor metastasis via amplifying cancer heterogeneity. As a result of metastable phenotypic state transitions, cancer cells can tolerate chemotherapy or develop transient adaptive resistance. Therefore, new findings have paved the road in identifying factors and agents that inhibit or suppress phenotypic plasticity. It has also investigated novel multitargeted agents that may promise new effective strategies in cancer treatment. Despite the efficiency of conventional chemotherapeutic agents, drug toxicity, development of resistance, and high-cost limit their use in cancer therapy. Recent research has shown that small molecules derived from natural sources are capable of suppressing cancer by focusing on the plasticity of phenotypic responses. This systematic, comprehensive, and critical review analyzes the current state of knowledge regarding the ability of phytocompounds to target phenotypic plasticity at both preclinical and clinical levels. Current challenges/pitfalls, limitations, and future perspectives are also discussed.

Molecular divergence of mammalian astrocyte progenitor cells at early gliogenesis.

During mammalian brain development, how different astrocytes are specified from progenitor cells is not well understood. In particular, whether astrocyte progenitor cells (APCs) start as a relatively homogenous population or whether there is early heterogeneity remains unclear. Here, we have dissected subpopulations of embryonic mouse forebrain progenitors using single-cell transcriptome analyses. Our sequencing data revealed two molecularly distinct APC subgroups at the start of gliogenesis from both dorsal and ventral forebrains. The two APC subgroups were marked, respectively, by specific expression of Sparc and Sparcl1, which are known to function in mature astrocytes with opposing activities for regulating synapse formation. Expression analyses showed that SPARC and SPARCL1 mark APC subgroups that display distinct temporal and spatial patterns, correlating with major waves of astrogliogenesis during development. Our results uncover an early molecular divergence of APCs in the mammalian brain and provide a useful transcriptome resource for the study of glial cell specification.

CAKE: a flexible self-supervised framework for enhancing cell visualization, clustering and rare cell identification.

Single cell sequencing technology has provided unprecedented opportunities for comprehensively deciphering cell heterogeneity. Nevertheless, the high dimensionality and intricate nature of cell heterogeneity have presented substantial challenges to computational methods. Numerous novel clustering methods have been proposed to address this issue. However, none of these methods achieve the consistently better performance under different biological scenarios. In this study, we developed CAKE, a novel and scalable self-supervised clustering method, which consists of a contrastive learning model with a mixture neighborhood augmentation for cell representation learning, and a self-Knowledge Distiller model for the refinement of clustering results. These designs provide more condensed and cluster-friendly cell representations and improve the clustering performance in term of accuracy and robustness. Furthermore, in addition to accurately identifying the major type cells, CAKE could also find more biologically meaningful cell subgroups and rare cell types. The comprehensive experiments on real single-cell RNA sequencing datasets demonstrated the superiority of CAKE in visualization and clustering over other comparison methods, and indicated its extensive application in the field of cell heterogeneity analysis. Contact: Ruiqing Zheng. (rqzheng@csu.edu.cn).

All mixed up: defining roles for ß-cell subtypes in mature islets.

Following differentiation during fetal development, ß cells further adapt to their postnatal role through functional maturation. While adult islets are thought to contain functionally mature ß cells, recent analyses of transgenic rodent and human pancreata reveal a number of novel heterogeneity markers in mammalian ß cells. The marked heterogeneity long after maturation raises the prospect that diverse populations harbor distinct roles aside from glucose-stimulated insulin secretion. In this review, we outline our current understanding of the ß-cell maturation process, emphasize recent literature on novel heterogeneity markers, and offer perspectives on reconciling the findings from these two areas.

Obesogenic diet disrupts tissue-specific mitochondrial gene signatures in the artery and capillary endothelium.

Endothelial cells (ECs) adapt to the unique needs of their resident tissue and metabolic perturbations, such as obesity. We sought to understand how obesity affects EC metabolic phenotypes, specifically mitochondrial gene expression. We investigated the mesenteric and adipose endothelium because these vascular beds have distinct roles in lipid homeostasis. Initially, we performed bulk RNA sequencing on ECs from mouse adipose and mesenteric vasculatures after a normal chow (NC) diet or high-fat diet (HFD) and found higher mitochondrial gene expression in adipose ECs compared with mesenteric ECs in both NC and HFD mice. Next, we performed single-cell RNA sequencing and categorized ECs as arterial, capillary, venous, or lymphatic. We found mitochondrial genes to be enriched in adipose compared with mesentery under NC conditions in artery and capillary ECs. After HFD, these genes were decreased in adipose ECs, becoming like mesenteric ECs. Transcription factor analysis revealed that peroxisome proliferator-activated receptor-γ (PPAR-γ) had high specificity in NC adipose artery and capillary ECs. These findings were recapitulated in single-nuclei RNA-sequencing data from human visceral adipose. The sum of these findings suggests that mesenteric and adipose arterial ECs metabolize lipids differently, and the transcriptional phenotype of the vascular beds converges in obesity due to downregulation of PPAR-γ in adipose artery and capillary ECs.NEW & NOTEWORTHY Using bulk and single-cell RNA sequencing on endothelial cells from adipose and mesentery, we found that an obesogenic diet induces a reduction in adipose endothelial oxidative phosphorylation gene expression, resulting in a phenotypic convergence of mesenteric and adipose endothelial cells. Furthermore, we found evidence that PPAR-γ drives this phenotypic shift. Mining of human data sets segregated based on body mass index supported these findings. These data point to novel mechanisms by which obesity induces endothelial dysfunction.

Unveiling cell subpopulations in T1D mouse islets using single-cell RNA sequencing.

Type 1 diabetes (T1D) is an autoimmune disease characterized by the destruction of beta cells by immune cells. The interactions among cells within the islets may be closely linked to the pathogenesis of T1D. In this study, we used single-cell RNA sequencing (scRNA-Seq) to analyze the cellular heterogeneity within the islets of a T1D mouse model. We established a T1D mouse model induced by streptozotocin and identified cell subpopulations using scRNA-Seq technology. Our results revealed 11 major cell types in the pancreatic islets of T1D mice, with heterogeneity observed in the alpha and beta cell subgroups, which may play a crucial role in the progression of T1D. Flow cytometry further confirmed a mature alpha and beta cell reduction in T1D mice. Overall, our scRNA-Seq analysis provided insights into the cellular heterogeneity of T1D islet tissue and highlighted the potential importance of alpha and beta cells in developing T1D.NEW & NOTEWORTHY In this study, we created a comprehensive single-cell atlas of pancreatic islets in a T1D mouse model using scRNA-Seq and identified 11 major cell types in the islets, highlighting the role of alpha and beta cells in T1D. This study revealed a significant reduction in the maturity alpha and beta cells in T1D mice through flow cytometry. It also demonstrated the heterogeneity of alpha and beta cells, potentially crucial for T1D progression. Overall, our scRNA-Seq analysis provided new insights for understanding and treating T1D by studying cell subtype changes and functions.

A high-resolution view of the heterogeneous aging endothelium.

Vascular endothelial cell (EC) aging has a strong impact on tissue perfusion and overall cardiovascular health. While studies confined to the investigation of aging-associated vascular readouts in one or a few tissues have already drastically expanded our understanding of EC aging, single-cell omics and other high-resolution profiling technologies have started to illuminate the intricate molecular changes underlying endothelial aging across diverse tissues and vascular beds at scale. In this review, we provide an overview of recent insights into the heterogeneous adaptations of the aging vascular endothelium. We address critical questions regarding tissue-specific and universal responses of the endothelium to the aging process, EC turnover dynamics throughout lifespan, and the differential susceptibility of ECs to acquiring aging-associated traits. In doing so, we underscore the transformative potential of single-cell approaches in advancing our comprehension of endothelial aging, essential to foster the development of future innovative therapeutic strategies for aging-associated vascular conditions.

When form meets function: the cells and signals that shape the lymphatic vasculature during development.

The lymphatic vasculature is an integral component of the cardiovascular system. It is essential to maintain tissue fluid homeostasis, direct immune cell trafficking and absorb dietary lipids from the digestive tract. Major advances in our understanding of the genetic and cellular events important for constructing the lymphatic vasculature during development have recently been made. These include the identification of novel sources of lymphatic endothelial progenitor cells, the recognition of lymphatic endothelial cell specialisation and heterogeneity, and discovery of novel genes and signalling pathways underpinning developmental lymphangiogenesis. Here, we review these advances and discuss how they inform our understanding of lymphatic network formation, function and dysfunction.

The heterogeneity of erythroid cells: insight at the single-cell transcriptome level.

Erythroid cells, the most prevalent cell type in blood, are one of the earliest products and permeate through the entire process of hematopoietic development in the human body, the oxygen-transporting function of which is crucial for maintaining overall health and life support. Previous investigations into erythrocyte differentiation and development have primarily focused on population-level analyses, lacking the single-cell perspective essential for comprehending the intricate pathways of erythroid maturation, differentiation, and the encompassing cellular heterogeneity. The continuous optimization of single-cell transcriptome sequencing technology, or single-cell RNA sequencing (scRNA-seq), provides a powerful tool for life sciences research, which has a particular superiority in the identification of unprecedented cell subgroups, the analyzing of cellular heterogeneity, and the transcriptomic characteristics of individual cells. Over the past decade, remarkable strides have been taken in the realm of single-cell RNA sequencing technology, profoundly enhancing our understanding of erythroid cells. In this review, we systematically summarize the recent developments in single-cell transcriptome sequencing technology and emphasize their substantial impact on the study of erythroid cells, highlighting their contributions, including the exploration of functional heterogeneity within erythroid populations, the identification of novel erythrocyte subgroups, the tracking of different erythroid lineages, and the unveiling of mechanisms governing erythroid fate decisions. These findings not only invigorate erythroid cell research but also offer new perspectives on the management of diseases related to erythroid cells.

Single-cell transcriptomics reveals heterogeneity in plant responses to the environment: a focus on biotic and abiotic interactions.

Biotic and abiotic environmental cues are major factors influencing plant growth and productivity. Interactions with biotic (e.g. symbionts and pathogens) and abiotic (e.g. changes in temperature, water, or nutrient availability) factors trigger signaling and downstream transcriptome adjustments in plants. While bulk RNA-sequencing technologies have traditionally been used to profile these transcriptional changes, tissue homogenization may mask heterogeneity of responses resulting from the cellular complexity of organs. Thus, whether different cell types respond equally to environmental fluctuations, or whether subsets of the responses are cell-type specific, are long-lasting questions in plant biology. The recent breakthrough of single-cell transcriptomics in plant research offers an unprecedented view of cellular responses under changing environmental conditions. In this review, we discuss the contribution of single-cell transcriptomics to the understanding of cell-type-specific plant responses to biotic and abiotic environmental interactions. Besides major biological findings, we present some technical challenges coupled to single-cell studies of plant-environment interactions, proposing possible solutions and exciting paths for future research.

10× single-cell sequencing revealed cellular composition heterogeneity in cardiac myxoma with malignant glandular properties.

Cardiac myxoma is the most common primary cardiac tumor in adults. The histogenesis and cellular composition of myxoma are still unclear. This study aims to reveal the role of myxoma cell components and their gene expression in tumor development. We obtained single living cells by enzymatic digestion of tissues from 4 cases of surgically resected cardiac myxoma. Of course, there was 1 case of glandular myxoma and 3 cases of nonglandular myxoma. Then, 10× single-cell sequencing was performed. We identified 12 types and 11 types of cell populations in glandular myxoma and nonglandular myxoma, respectively. Heterogeneous epithelial cells are the main components of glandular myxoma. The similarities and differences in T cells in both glandular and nonglandular myxoma were analyzed by KEGG and GO. The most important finding was that there was active communication between T cells and epithelial cells. These results clarify the possible tissue occurrence and heterogeneity of cardiac myxoma and provide a theoretical basis and guidance for clinical diagnosis and treatment.