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Human immunodeficiency virus type 1 (HIV-1)-specific monoclonal antibodies with extraordinary potency and breadth have recently been described. In humanized mice, combinations of monoclonal antibodies have been shown to suppress viraemia, but the therapeutic potential of these monoclonal antibodies has not yet been evaluated in primates with an intact immune system. Here we show that administration of a cocktail of HIV-1-specific monoclonal antibodies, as well as the single glycan-dependent monoclonal antibody PGT121, resulted in a rapid and precipitous decline of plasma viraemia to undetectable levels in rhesus monkeys chronically infected with the pathogenic simian-human immunodeficiency virus SHIV-SF162P3. A single monoclonal antibody infusion afforded up to a 3.1 log decline of plasma viral RNA in 7 days and also reduced proviral DNA in peripheral blood, gastrointestinal mucosa and lymph nodes without the development of viral resistance. Moreover, after monoclonal antibody administration, host Gag-specific T-lymphocyte responses showed improved functionality. Virus rebounded in most animals after a median of 56 days when serum monoclonal antibody titres had declined to undetectable levels, although, notably, a subset of animals maintained long-term virological control in the absence of further monoclonal antibody infusions. These data demonstrate a profound therapeutic effect of potent neutralizing HIV-1-specific monoclonal antibodies in SHIV-infected rhesus monkeys as well as an impact on host immune responses. Our findings strongly encourage the investigation of monoclonal antibody therapy for HIV-1 in humans., A series of broad and potent HIV-1 Env-specific monoclonal antibodies have recently been isolated (1,2) and have been shown to target the CD4 binding site (3-7), the V1/V2 loops (8,9), [...]

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) are a promising platform for cardiac studies in vitro, and possibly for tissue repair in humans. However, hiPSC-CM cells tend to retain morphology, metabolism, patterns of gene expression, and electrophysiology similar to that of embryonic cardiomyocytes. We grew hiPSC-CM in patterned islands of different sizes and shapes, and measured the effect of island geometry on action potential waveform and calcium dynamics using optical recordings of voltage and calcium from 970 islands of different sizes. hiPSC-CM in larger islands showed electrical and calcium dynamics indicative of greater functional maturity. We then compared transcriptional signatures of the small and large islands against a developmental time course of cardiac differentiation. Although island size had little effect on expression of most genes whose levels differed between hiPSC-CM and adult primary CM, we identified a subset of genes for which island size drove the majority (58%) of the changes associated with functional maturation. Finally, we patterned hiPSC-CM on islands with a variety of shapes to probe the relative contributions of soluble factors, electrical coupling, and direct cell-cell contacts to the functional maturation. Collectively, our data show that optical electrophysiology is a powerful tool for assaying hiPSC-CM maturation, and that island size powerfully drives activation of a subset of genes involved in cardiac maturation. [ABSTRACT FROM AUTHOR]

Intestinal epithelial cells (IECs) absorb nutrients, respond to microbes, provide barrier function and help coordinate immune responses. We profiled 53,193 individual epithelial cells from mouse small intestine and organoids, and characterized novel subtypes and their gene signatures. We showed unexpected diversity of hormone-secreting enteroendocrine cells and constructed their novel taxonomy. We distinguished between two tuft cell subtypes, one of which expresses the epithelial cytokine TSLP and CD45 (Ptprc), the pan-immune marker not previously associated with non-hematopoietic cells. We also characterized how cell-intrinsic states and cell proportions respond to bacterial and helminth infections. Salmonella infection caused an increase in Paneth cells and enterocytes abundance, and broad activation of an antimicrobial program. In contrast, Heligmosomoides polygyrus caused an expansion of goblet and tuft cell populations. Our survey highlights new markers and programs, associates sensory molecules to cell types, and uncovers principles of gut homeostasis and response to pathogens.

Classification and characterization of neuronal types are critical for understanding their function and dysfunction. Neuronal classification schemes typically rely on measurements of electrophysiological, morphological, and molecular features, but aligning such datasets has been challenging. Here, we present a unified classification of mouse retinal ganglion cells (RGCs), the sole retinal output neurons. We use visually evoked responses to classify 1,859 mouse RGCs into 42 types. We also obtain morphological or transcriptomic data from subsets and use these measurements to align the functional classification to publicly available morphological and transcriptomic datasets. We create an online database that allows users to browse or download the data and to classify RGCs from their light responses using a machine learning algorithm. This work provides a resource for studies of RGCs, their upstream circuits in the retina, and their projections in the brain, and establishes a framework for future efforts in neuronal classification and open data distribution. [Display omitted] • Function, morphology, and gene expression jointly specify retinal ganglion cell type • 42 classified types in mice comprise 89% of the total population • Online resource at rgctypes.org to explore and download the data Function, morphology, and gene expression are the most common criteria used to classify neurons. Goetz et al. use all three criteria to create a unified classification of mouse retinal ganglion cells and build an interactive online resource for exploring the data. [ABSTRACT FROM AUTHOR]

Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses. [ABSTRACT FROM AUTHOR]

HIV-1-specific monoclonal antibodies (mAbs) with extraordinary potency and breadth have recently been described. In humanized mice, combinations of mAbs have been shown to suppress viremia, but the therapeutic potential of these mAbs has not yet been evaluated in primates with an intact immune system. Here we show that administration of a cocktail of HIV-1-specific mAbs, as well as the single glycan-dependent mAb PGT121, resulted in a rapid and precipitous decline of plasma viremia to undetectable levels in rhesus monkeys chronically infected with the pathogenic virus SHIV-SF162P3. A single mAb infusion afforded up to a 3.1 log decline of plasma viral RNA in 7 days and also reduced proviral DNA in peripheral blood, gastrointestinal mucosa, and lymph nodes without the development of viral resistance. Moreover, following mAb administration, host Gag-specific T lymphocyte responses exhibited improved functionality. Virus rebounded in the majority of animals after a median of 56 days when serum mAb titers had declined to undetectable levels, although a subset of animals maintained long-term virologic control in the absence of further mAb infusions. These data demonstrate a profound therapeutic effect of potent neutralizing HIV-1-specific mAbs in SHIV-infected rhesus monkeys as well as an impact on host immune responses. Our findings strongly encourage the investigation of mAb therapy for HIV-1 in humans.

Neuronal types in the central nervous system differ dramatically in their resilience to injury or other insults. Here we studied the selective resilience of mouse retinal ganglion cells (RGCs) following optic nerve crush (ONC), which severs their axons and leads to death of ∼80% of RGCs within 2 weeks. To identify expression programs associated with differential resilience, we first used single-cell RNA-seq (scRNA-seq) to generate a comprehensive molecular atlas of 46 RGC types in adult retina. We then tracked their survival after ONC; characterized transcriptomic, physiological, and morphological changes that preceded degeneration; and identified genes selectively expressed by each type. Finally, using loss- and gain-of-function assays in vivo , we showed that manipulating some of these genes improved neuronal survival and axon regeneration following ONC. This study provides a systematic framework for parsing type-specific responses to injury and demonstrates that differential gene expression can be used to reveal molecular targets for intervention. • 46 transcriptionally distinct type of retinal ganglion cells (RGCs) in mice • RGC types differ dramatically in survival following axonal transection • Different genes expressed by resilient and vulnerable RGC types • Manipulation of differentially expressed genes promotes RGC survival and regeneration High-throughput single-cell RNA-seq characterizes 46 types of adult mouse retinal ganglion cells and documents dramatic differences among them in their ability to survive axotomy. Manipulation of genes differentially expressed between resilient and vulnerable types enhances survival and axon regeneration. [ABSTRACT FROM AUTHOR]

Summary High-acuity vision in primates, including humans, is mediated by a small central retinal region called the fovea. As more accessible organisms lack a fovea, its specialized function and its dysfunction in ocular diseases remain poorly understood. We used 165,000 single-cell RNA-seq profiles to generate comprehensive cellular taxonomies of macaque fovea and peripheral retina. More than 80% of >60 cell types match between the two regions but exhibit substantial differences in proportions and gene expression, some of which we relate to functional differences. Comparison of macaque retinal types with those of mice reveals that interneuron types are tightly conserved. In contrast, projection neuron types and programs diverge, despite exhibiting conserved transcription factor codes. Key macaque types are conserved in humans, allowing mapping of cell-type and region-specific expression of >190 genes associated with 7 human retinal diseases. Our work provides a framework for comparative single-cell analysis across tissue regions and species. Graphical Abstract Highlights • Macaque fovea and peripheral retina each contain >65 cell types • Most types correspond between regions but differ in proportions and gene expression • Greater conservation of interneuron than ganglion cell types between macaque and mouse • Cell-type- and region-specific expression of genes implicated in human blindness Single-cell-based analysis provides a comprehensive molecular and cellular taxonomy of the primate retina. [ABSTRACT FROM AUTHOR]

Summary The identification of cell types and marker genes is critical for dissecting neural development and function, but the size and complexity of the brain has hindered the comprehensive discovery of cell types. We combined single-cell RNA-seq (scRNA-seq) with anatomical brain registration to create a comprehensive map of the zebrafish habenula, a conserved forebrain hub involved in pain processing and learning. Single-cell transcriptomes of ∼13,000 habenular cells with 4× cellular coverage identified 18 neuronal types and dozens of marker genes. Registration of marker genes onto a reference atlas created a resource for anatomical and functional studies and enabled the mapping of active neurons onto neuronal types following aversive stimuli. Strikingly, despite brain growth and functional maturation, cell types were retained between the larval and adult habenula. This study provides a gene expression atlas to dissect habenular development and function and offers a general framework for the comprehensive characterization of other brain regions. [ABSTRACT FROM AUTHOR]

Summary Patterns of gene expression can be used to characterize and classify neuronal types. It is challenging, however, to generate taxonomies that fulfill the essential criteria of being comprehensive, harmonizing with conventional classification schemes, and lacking superfluous subdivisions of genuine types. To address these challenges, we used massively parallel single-cell RNA profiling and optimized computational methods on a heterogeneous class of neurons, mouse retinal bipolar cells (BCs). From a population of ∼25,000 BCs, we derived a molecular classification that identified 15 types, including all types observed previously and two novel types, one of which has a non-canonical morphology and position. We validated the classification scheme and identified dozens of novel markers using methods that match molecular expression to cell morphology. This work provides a systematic methodology for achieving comprehensive molecular classification of neurons, identifies novel neuronal types, and uncovers transcriptional differences that distinguish types within a class. [ABSTRACT FROM AUTHOR]

• Temporally regulated gene modules are expressed at distinct phases of postmitotic RGC differentiation in mice. • Transcription factors and recognition molecules are selectively expressed by subsets of 45 developing or adult RGC types. • Three models of visual deprivation showed that vision is dispensable for RGC type specification. • Visual deprivation does, however, affect molecular aspects of RGC maturation and maintenance. The development and connectivity of retinal ganglion cells (RGCs), the retina's sole output neurons, are patterned by activity-independent transcriptional programs and activity-dependent remodeling. To inventory the molecular correlates of these influences, we applied high-throughput single-cell RNA sequencing (scRNA-seq) to mouse RGCs at six embryonic and postnatal ages. We identified temporally regulated modules of genes that correlate with, and likely regulate, multiple phases of RGC development, ranging from differentiation and axon guidance to synaptic recognition and refinement. Some of these genes are expressed broadly while others, including key transcription factors and recognition molecules, are selectively expressed by one or a few of the 45 transcriptomically distinct types defined previously in adult mice. Next, we used these results as a foundation to analyze the transcriptomes of RGCs in mice lacking visual experience due to dark rearing from birth or to mutations that ablate either bipolar or photoreceptor cells. 98.5% of visually deprived (VD) RGCs could be unequivocally assigned to a single RGC type based on their transcriptional profiles, demonstrating that visual activity is dispensable for acquisition and maintenance of RGC type identity. However, visual deprivation significantly reduced the transcriptomic distinctions among RGC types, implying that activity is required for complete RGC maturation or maintenance. Consistent with this notion, transcriptomic alternations in VD RGCs significantly overlapped with gene modules found in developing RGCs. Our results provide a resource for mechanistic analyses of RGC differentiation and maturation, and for investigating the role of activity in these processes. [ABSTRACT FROM AUTHOR]

Chronic hepatitis C virus (HCV) infection is one of the leading causes of liver failure and liver cancer, affecting around 3% of the world's population. The extreme sequence variability of the virus resulting from error-prone replication has thwarted the discovery of a universal prophylactic vaccine. It is known that vigorous and multispecific cellular immune responses, involving both helper CD4+ and cytotoxic CD8+ T cells, are associated with the spontaneous clearance of acute HCV infection. Escape mutations in viral epitopes can, however, abrogate protective T-cell responses, leading to viral persistence and associated pathologies. Despite the propensity of the virus to mutate, there might still exist substitutions that incur a fitness cost. In this paper, we identify groups of coevolving residues within HCV nonstructural protein 3 (NS3) by analyzing diverse sequences of this protein using ideas from random matrix theory and associated methods. Our analyses indicate that one of these groups comprises a large percentage of residues for which HCV appears to resist multiple simultaneous substitutions. Targeting multiple residues in this group through vaccine-induced immune responses should either lead to viral recognition or elicit escape substitutions that compromise viral fitness. Our predictions are supported by published clinical data, which suggested that immune genotypes associated with spontaneous clearance of HCV preferentially recognized and targeted this vulnerable group of residues. Moreover, mapping the sites of this group onto the available protein structure provided insight into its functional significance. An epitope-based immunogen is proposed as an alternative to the NS3 epitopes in the peptide-based vaccine IC41. [ABSTRACT FROM AUTHOR]

Summary Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell’s RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts’ cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. Video Abstract [ABSTRACT FROM AUTHOR]

Retinal ganglion cells (RGCs) form an array of feature detectors, which convey visual information to central brain regions. Characterizing RGC diversity is required to understand the logic of the underlying functional segregation. Using single-cell transcriptomics, we systematically classified RGCs in adult and larval zebrafish, thereby identifying marker genes for >30 mature types and several developmental intermediates. We used this dataset to engineer transgenic driver lines, enabling specific experimental access to a subset of RGC types. Expression of one or few transcription factors often predicts dendrite morphologies and axonal projections to specific tectal layers and extratectal targets. In vivo calcium imaging revealed that molecularly defined RGCs exhibit specific functional tuning. Finally, chemogenetic ablation of eomesa + RGCs, which comprise melanopsin-expressing types with projections to a small subset of central targets, selectively impaired phototaxis. Together, our study establishes a framework for systematically studying the functional architecture of the visual system. • Transcriptional profiling classifies >30 distinct retinal ganglion cell types • Molecular profiles of RGCs correlate with morphological and physiological features • Genome-engineered driver lines provide selective access to RGC types • Perturbation of a genetically defined visual pathway disrupts phototaxis A molecular catalog of retinal ganglion cell (RGC) types is essential for understanding the organization and development of the visual system. Kölsch et al. used single-cell RNA-seq to identify >30 larval and adult zebrafish RGC types. Using genetic methods, they linked transcriptomically defined types to morphology, physiology, and a visual behavior. [ABSTRACT FROM AUTHOR]

Summary In the small intestine, a niche of accessory cell types supports the generation of mature epithelial cell types from intestinal stem cells (ISCs). It is unclear, however, if and how immune cells in the niche affect ISC fate or the balance between self-renewal and differentiation. Here, we use single-cell RNA sequencing (scRNA-seq) to identify MHC class II (MHCII) machinery enrichment in two subsets of Lgr5+ ISCs. We show that MHCII+ Lgr5+ ISCs are non-conventional antigen-presenting cells in co-cultures with CD4+ T helper (Th) cells. Stimulation of intestinal organoids with key Th cytokines affects Lgr5+ ISC renewal and differentiation in opposing ways: pro-inflammatory signals promote differentiation, while regulatory cells and cytokines reduce it. In vivo genetic perturbation of Th cells or MHCII expression on Lgr5+ ISCs impacts epithelial cell differentiation and IEC fate during infection. These interactions between Th cells and Lgr5+ ISCs, thus, orchestrate tissue-wide responses to external signals. Graphical Abstract Highlights • Intestinal stem cells (ISCs) are non-conventional antigen-presenting cells by MHCII • Interactions between ISCs and T helper subsets modulate distinct ISC fates • Epithelial MHCII is important for epithelial-cell remodeling following infection • Regulatory T cells and their key cytokine IL-10 support ISC renewal Intestinal stem cells act as non-conventional antigen presenting cells, and these interactions with T helper cells modulate ISC renewal and differentiation to shape the intestine. [ABSTRACT FROM AUTHOR]

How early sensory experience during "critical periods" of postnatal life affects the organization of the mammalian neocortex at the resolution of neuronal cell types is poorly understood. We previously reported that the functional and molecular profiles of layer 2/3 (L2/3) cell types in the primary visual cortex (V1) are vision-dependent (Tan et al., Neuron, 108 (4), 2020; Cheng et al., Cell, 185 (2), 2022). Here, we characterize the spatial organization of L2/3 cell types with and without visual experience. Spatial transcriptomic profiling based on 500 genes recapitulates the zonation of L2/3 cell types along the pial-ventricular axis in V1. By applying multi-tasking theory (Adler et al., Cell Systems, 8, 2019), we suggest that the spatial zonation of L2/3 cell types is linked to the continuous nature of their gene expression profiles, which can be represented as a 2D manifold bounded by three archetypal cell types ("A", "B", and "C"). By comparing normally reared and dark reared L2/3 cells, we show that visual deprivation-induced transcriptomic changes comprise two independent gene programs. The first, induced specifically in the visual cortex, includes immediate-early genes and genes associated with metabolic processes. It manifests as a change in cell state that is orthogonal to cell type-specific gene expression programs. By contrast, the second program impacts L2/3 cell type identity, regulating a subset of cell type-specific genes and shifting the distribution of cells within the L2/3 manifold, with a depression of the B-type and C-type and a gain of the A-type. Through an integrated analysis of spatial transcriptomic measurements with single-nucleus RNA-seq data from our previous study, we describe how vision patterns L2/3 cortical cell types during the postnatal critical period., Significance Statement: Layer 2/3 (L2/3) glutamatergic neurons are important sites of experience-dependent plasticity and learning in the mammalian cortex. Their properties vary continuously with cortical depth and depend upon experience. Here, by applying spatial transcriptomics and different computational approaches in the mouse primary visual cortex, we show that vision regulates orthogonal gene expression programs underlying cell states and cell types. Visual deprivation not only induces an activity-dependent cell state, but also alters the composition of L2/3 cell types, which are appropriately described as a transcriptomic continuum. Our results provide insights into how experience shapes transcriptomes that may, in turn, sculpt brain wiring, function, and behavior., Competing Interests: Declaration of interests The authors declare no competing interests.

Mouse whisker somatosensory cortex (wS1) is a major model system to study the experience-dependent plasticity of cortical neuron physiology, morphology, and sensory coding. However, the role of sensory experience in regulating neuronal cell type development and gene expression in wS1 remains poorly understood. We assembled and annotated a transcriptomic atlas of wS1 during postnatal development comprising 45 molecularly distinct neuronal types that can be grouped into eight excitatory and four inhibitory neuron subclasses. Using this atlas, we examined the influence of whisker experience from postnatal day (P) 12, the onset of active whisking, to P22, on the maturation of molecularly distinct cell types. During this developmental period, when whisker experience was normal, ~250 genes were regulated in a neuronal subclass-specific fashion. At the resolution of neuronal types, we found that only the composition of layer (L) 2/3 glutamatergic neuronal types, but not other neuronal types, changed substantially between P12 and P22. These compositional changes resemble those observed previously in the primary visual cortex (V1), and the temporal gene expression changes were also highly conserved between the two regions. In contrast to V1, however, cell type maturation in wS1 is not substantially dependent on sensory experience, as 10-day full-face whisker deprivation did not influence the transcriptomic identity and composition of L2/3 neuronal types. A one-day competitive whisker deprivation protocol also did not affect cell type identity but induced moderate changes in plasticity-related gene expression. Thus, developmental maturation of cell types is similar in V1 and wS1, but sensory deprivation minimally affects cell type development in wS1.

How does evolution act on neuronal populations to match computational characteristics to functional demands? We address this problem by comparing visual code and retinal cell composition in closely related murid species with different behaviours. Rhabdomys pumilio are diurnal and have substantially thicker inner retina and larger visual thalamus than nocturnal Mus musculus. High-density electrophysiological recordings of visual response features in the dorsal lateral geniculate nucleus (dLGN) reveals that Rhabdomys attains higher spatiotemporal acuity both by denser coverage of the visual scene and a selective expansion of elements of the code characterised by non-linear spatiotemporal summation. Comparative analysis of single cell transcriptomic cell atlases reveals that realignment of the visual code is associated with increased relative abundance of bipolar and ganglion cell types supporting OFF and ON-OFF responses. These findings demonstrate how changes in retinal cell complement can reconfigure the coding of visual information to match changes in visual needs., Competing Interests: Declaration of interests The authors declare no competing interests

We describe a computational workflow to analyze single-cell RNA-sequencing (scRNA-seq) profiles of axotomized retinal ganglion cells (RGCs) in mice. Our goal is to identify differences in the dynamics of survival among 46 molecularly defined RGC types together with molecular signatures that correlate with these differences. The data consists of scRNA-seq profiles of RGCs collected at six time points following optic nerve crush (ONC) (see companion chapter by Jacobi and Tran). We use a supervised classification-based approach to map injured RGCs to type identities and quantify type-specific differences in survival at 2 weeks post crush. As injury-related changes in gene expression confound the inference of type identity in surviving cells, the approach deconvolves type-specific gene signatures from injury responses by using an iterative strategy that leverages measurements along the time course. We use these classifications to compare expression differences between resilient and susceptible subpopulations, identifying potential mediators of resilience. The conceptual framework underlying the method is sufficiently general for analysis of selective vulnerability in other neuronal systems., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The genesis of broad neuronal classes from multipotential neural progenitor cells has been extensively studied, but less is known about the diversification of a single neuronal class into multiple types. We used single-cell RNA-seq to study how newly born (postmitotic) mouse retinal ganglion cell (RGC) precursors diversify into ~45 discrete types. Computational analysis provides evidence that RGC transcriptomic type identity is not specified at mitotic exit, but acquired by gradual, asynchronous restriction of postmitotic multipotential precursors. Some types are not identifiable until a week after they are generated. Immature RGCs may be specified to project ipsilaterally or contralaterally to the rest of the brain before their type identity emerges. Optimal transport inference identifies groups of RGC precursors with largely nonoverlapping fates, distinguished by selectively expressed transcription factors that could act as fate determinants. Our study provides a framework for investigating the molecular diversification of discrete types within a neuronal class., Competing Interests: KS, IW, SB, YP, JS No competing interests declared, (© 2022, Shekhar et al.)

Little is known about how interactions of diet, intestinal stem cells (ISCs), and immune cells affect early-stage intestinal tumorigenesis. We show that a high-fat diet (HFD) reduces the expression of the major histocompatibility complex class II (MHC class II) genes in intestinal epithelial cells, including ISCs. This decline in epithelial MHC class II expression in a HFD correlates with reduced intestinal microbiome diversity. Microbial community transfer experiments suggest that epithelial MHC class II expression is regulated by intestinal flora. Mechanistically, pattern recognition receptor (PRR) and interferon-gamma (IFNγ) signaling regulates epithelial MHC class II expression. MHC class II-negative (MHC-II-) ISCs exhibit greater tumor-initiating capacity than their MHC class II-positive (MHC-II+) counterparts upon loss of the tumor suppressor Apc coupled with a HFD, suggesting a role for epithelial MHC class II-mediated immune surveillance in suppressing tumorigenesis. ISC-specific genetic ablation of MHC class II increases tumor burden cell autonomously. Thus, HFD perturbs a microbiome-stem cell-immune cell interaction that contributes to tumor initiation in the intestine., Competing Interests: Declaration of interests The authors declare no competing financial interests. S.H.O. serves as an advisory board member for Cell Stem Cell. S.B. received research funding from Elstar Therapeutics and Revitope Oncology for research that is not related to this study., (Copyright © 2021 Elsevier Inc. All rights reserved.)

It has been known for over a century that the basic organization of the retina is conserved across vertebrates. It has been equally clear that retinal cells can be classified into numerous types, but only recently have methods been devised to explore this diversity in unbiased, scalable, and comprehensive ways. Advances in high-throughput single-cell RNA sequencing (scRNA-seq) have played a pivotal role in this effort. In this article, we outline the experimental and computational components of scRNA-seq and review studies that have used them to generate retinal atlases of cell types in several vertebrate species. These atlases have enabled studies of retinal development, responses of retinal cells to injury, expression patterns of genes implicated in retinal disease, and the evolution of cell types. Recently, the inquiry has expanded to include the entire eye and visual centers in the brain. These studies have enhanced our understanding of retinal function and dysfunction and provided tools and insights for exploring neural diversity throughout the brain.

Unprecedented technological advances in single-cell RNA-sequencing (scRNA-seq) technology have now made it possible to profile genome-wide expression in single cells at low cost and high throughput. There is substantial ongoing effort to use scRNA-seq measurements to identify the "cell types" that form components of a complex tissue, akin to taxonomizing species in ecology. Cell type classification from scRNA-seq data involves the application of computational tools rooted in dimensionality reduction and clustering, and statistical analysis to identify molecular signatures that are unique to each type. As datasets continue to grow in size and complexity, computational challenges abound, requiring analytical methods to be scalable, flexible, and robust. Moreover, careful consideration needs to be paid to experimental biases and statistical challenges that are unique to these measurements to avoid artifacts. This chapter introduces these topics in the context of cell-type identification, and outlines an instructive step-by-step example bioinformatic pipeline for researchers entering this field.

Understanding how populations of human T cells leverage cellular heterogeneity, plasticity, and diversity to achieve a wide range of functional flexibility, particularly during dynamic processes such as development, differentiation, and antigenic response, is a core challenge that is well suited for single-cell analysis. Hypothesis-free evaluation of cellular states and subpopulations by transcriptional profiling of single T cells can identify relationships that may be obscured by targeted approaches such as FACS sorting on cell-surface antigens, or bulk expression analysis. While this approach is relevant to all cell types, it is of particular interest in the study of T cells for which classical phenotypic criteria are now viewed as insufficient for distinguishing different T cell subtypes and transitional states, and defining the changes associated with dysfunctional T cell states in autoimmunity and tumor-related exhaustion. This unit describes a protocol to generate single-cell transcriptomic libraries of human blood CD4 + and CD8 + T cells, and also introduces the basic bioinformatic steps to process the resulting sequence data for further computational analysis. We show how cellular subpopulations can be identified from transcriptional data, and derive characteristic gene expression signatures that distinguish these states. We believe single-cell RNA-seq is a powerful technique to study the cellular heterogeneity in complex tissues, a paradigm that will be of great value for the immune system.

Studies of individual T cell antigen receptors (TCRs) have shed some light on structural features that underlie self-reactivity. However, the general rules that can be used to predict whether TCRs are self-reactive have not been fully elucidated. Here we found that the interfacial hydrophobicity of amino acids at positions 6 and 7 of the complementarity-determining region CDR3β robustly promoted the development of self-reactive TCRs. This property was found irrespective of the member of the β-chain variable region (Vβ) family present in the TCR or the length of the CDR3β. An index based on these findings distinguished Vβ2(+), Vβ6(+) and Vβ8.2(+) regulatory T cells from conventional T cells and also distinguished CD4(+) T cells selected by the major histocompatibility complex (MHC) class II molecule I-A(g7) (associated with the development of type 1 diabetes in NOD mice) from those selected by a non-autoimmunity-promoting MHC class II molecule I-A(b). Our results provide a means for distinguishing normal T cell repertoires versus autoimmunity-prone T cell repertoires.