EASI-FISH for thick tissue defines lateral hypothalamus spatio-molecular organization

Single-cell and spatial omics: exploring hypothalamic heterogeneity

Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.

Dorsolateral septum GLP-1R neurons regulate feeding via lateral hypothalamic projections

OBJECTIVE

Although glucagon-like peptide 1 (GLP-1) is known to regulate feeding, the central mechanisms contributing to this function remain enigmatic. Here, we aim to test the role of neurons expressing GLP-1 receptors (GLP-1R) in the dorsolateral septum (dLS; dLSGLP-1R) that project to the lateral hypothalamic area (LHA) on food intake and determine the relationship with feeding regulation.

METHODS

Using chemogenetic manipulations, we assessed how activation or inhibition of dLSGLP-1R neurons affected food intake in Glp1r-ires-Cre mice. Then, we used channelrhodopsin-assisted circuit mapping, chemogenetics, and electrophysiological recordings to identify and assess the role of the pathway from dLSGLP-1R →LHA projections in regulating food intake.

RESULTS

Chemogenetic inhibition of dLSGLP-1R neurons increases food intake. LHA is a major downstream target of dLSGLP-1R neurons. The dLSGLP-1R→LHA projections are GABAergic, and chemogenetic inhibition of this pathway also promotes food intake. While chemogenetic activation of dLSGLP-1R→LHA projections modestly decreases food intake, optogenetic stimulation of the dLSGLP-1R→LHA projection terminals in the LHA rapidly suppresses feeding behavior. Finally, we demonstrate that the GLP-1R agonist, Exendin 4 enhances dLSGLP-1R →LHA GABA release.

CONCLUSIONS

Together, these results demonstrate that dLS-GLP-1R neurons and the inhibitory pathway to LHA can regulate feeding behavior, which might serve as a potential therapeutic target for the treatment of eating disorders or obesity.

Highly Multiplexed Spatial Transcriptomics in Bacteria

Single-cell decisions made in complex environments underlie many bacterial phenomena. Image-based transcriptomics approaches offer an avenue to study such behaviors, yet these approaches have been hindered by the massive density of bacterial mRNA. To overcome this challenge, we combine 1000-fold volumetric expansion with multiplexed error robust fluorescence in situ hybridization (MERFISH) to create bacterial-MERFISH. This method enables high-throughput, spatially resolved profiling of thousands of operons within individual bacteria. Using bacterial-MERFISH, we dissect the response of E. coli to carbon starvation, systematically map subcellular RNA organization, and chart the adaptation of a gut commensal B. thetaiotaomicron to micron-scale niches in the mammalian colon. We envision bacterial-MERFISH will be broadly applicable to the study of bacterial single-cell heterogeneity in diverse, spatially structured, and native environments.

Spatial mapping of mobile genetic elements and their bacterial hosts in complex microbiomes

The exchange of mobile genetic elements (MGEs) facilitates the spread of functional traits including antimicrobial resistance within bacterial communities. Tools to spatially map MGEs and identify their bacterial hosts in complex microbial communities are currently lacking, limiting our understanding of this process. Here we combined single-molecule DNA fluorescence in situ hybridization (FISH) with multiplexed ribosomal RNA-FISH to enable simultaneous visualization of both MGEs and bacterial taxa. We spatially mapped bacteriophage and antimicrobial resistance (AMR) plasmids and identified their host taxa in human oral biofilms. This revealed distinct clusters of AMR plasmids and prophage, coinciding with densely packed regions of host bacteria. Our data suggest spatial heterogeneity in bacterial taxa results in heterogeneous MGE distribution within the community, with MGE clusters resulting from horizontal gene transfer hotspots or expansion of MGE-carrying strains. Our approach can help advance the study of AMR and phage ecology in biofilms.

Integrated platform for multiscale molecular imaging and phenotyping of the human brain

Understanding cellular architectures and their connectivity is essential for interrogating system function and dysfunction. However, we lack technologies for mapping the multiscale details of individual cells and their connectivity in the human organ-scale system. We developed a platform that simultaneously extracts spatial, molecular, morphological, and connectivity information of individual cells from the same human brain. The platform includes three core elements: a vibrating microtome for ultraprecision slicing of large-scale tissues without losing cellular connectivity (MEGAtome), a polymer hydrogel-based tissue processing technology for multiplexed multiscale imaging of human organ-scale tissues (mELAST), and a computational pipeline for reconstructing three-dimensional connectivity across multiple brain slabs (UNSLICE). We applied this platform for analyzing human Alzheimer's disease pathology at multiple scales and demonstrating scalable neural connectivity mapping in the human brain.

A practical guide to spatial transcriptomics

Spatial transcriptomics is revolutionizing modern biology, offering researchers an unprecedented ability to unravel intricate gene expression patterns within tissues. From pioneering techniques to newly commercialized platforms, the field of spatial transcriptomics has evolved rapidly, ushering in a new era of understanding across various disciplines, from developmental biology to disease research. This dynamic expansion is reflected in the rapidly growing number of technologies and data analysis techniques developed and introduced. However, the expanding landscape presents a considerable challenge for researchers, especially newcomers to the field, as staying informed about these advancements becomes increasingly complex. To address this challenge, we have prepared an updated review with a particular focus on technologies that have reached commercialization and are, therefore, accessible to a broad spectrum of potential new users. In this review, we present the fundamental principles of spatial transcriptomic methods, discuss the challenges in data analysis, provide insights into experimental considerations, offer information about available resources for spatial transcriptomics, and conclude with a guide for method selection and a forward-looking perspective. Our aim is to serve as a guiding resource for both experienced users and newcomers navigating the complex realm of spatial transcriptomics in this era of rapid development. We intend to equip researchers with the necessary knowledge to make informed decisions and contribute to the cutting-edge research that spatial transcriptomics offers.

Spatial motifs reveal patterns in cellular architecture of complex tissues

Spatial organization of cells is crucial to both proper physiological function of tissues and pathological conditions like cancer. Recent advances in spatial transcriptomics have enabled joint profiling of gene expression and spatial context of the cells. The outcome is an information rich map of the tissue where individual cells, or small regions, can be labeled based on their gene expression state. While spatial transcriptomics excels in its capacity to profile numerous genes within the same sample, most existing methods for analysis of spatial data only examine distribution of one or two labels at a time. These approaches overlook the potential for identifying higher-order associations between cell types - associations that can play a pivotal role in understanding development and function of complex tissues. In this context, we introduce a novel method for detecting motifs in spatial neighborhood graphs. Each motif represents a spatial arrangement of cell types that occurs in the tissue more frequently than expected by chance. To identify spatial motifs, we developed an algorithm for uniform sampling of paths from neighborhood graphs and combined it with a motif finding algorithm on graphs inspired by previous methods for finding motifs in DNA sequences. Using synthetic data with known ground truth, we show that our method can identify spatial motifs with high accuracy and sensitivity. Applied to spatial maps of mouse retinal bipolar cells and hypothalamic preoptic region, our method reveals previously unrecognized patterns in cell type arrangements. In some cases, cells within these spatial patterns differ in their gene expression from other cells of the same type, providing insights into the functional significance of the spatial motifs. These results suggest that our method can illuminate the substantial complexity of neural tissues, provide novel insight even in well studied models, and generate experimentally testable hypotheses.

Dorsolateral septum GLP-1R neurons regulate feeding via lateral hypothalamic projections

Objective

Although glucagon-like peptide 1 (GLP-1) is known to regulate feeding, the central mechanisms contributing to this function remain enigmatic. Here, we aim to test the role of neurons expressing GLP-1 receptors (GLP-1R) in the dorsolateral septum (dLS; dLS GLP-1R ) and their downstream projections on food intake and determine the relationship with feeding regulation.

Methods

Using chemogenetic manipulations, we assessed how activation or inhibition of dLS GLP-1R neurons affected food intake in Glp1r-ires-Cre mice. Then, we used channelrhodopsin-assisted circuit mapping, chemogenetics, and electrophysiological recordings to identify and assess the role of the pathway from dLS GLP-1R neurons to the lateral hypothalamic area (LHA) in regulating food intake.

Results

Chemogenetic inhibition of dLS GLP-1R neurons increases food intake. LHA is a major downstream target of dLS GLP-1R neurons. The dLS GLP-1R →LHA projections are GABAergic, and chemogenetic inhibition of this pathway also promotes food intake. While chemogenetic activation of dLS GLP-1R →LHA projections modestly decreases food intake, optogenetic stimulation of the dLS GLP-1R →LHA projection terminals in the LHA rapidly suppressed feeding behavior. Finally, we demonstrate that the GLP-1R agonist, Exendin 4 enhances dLS GLP-1R →LHA GABA release.

Conclusions

Together, these results demonstrate that dLS-GLP-1R neurons and the inhibitory pathway to LHA can regulate feeding behavior, which might serve as a potential therapeutic target for the treatment of eating disorders or obesity.

Highlights

Chemogenetic inhibition of dLS GLP-1R neurons boosts food intake in mice dLS GLP-1R neuron activation does not alter feeding, likely by collateral inhibition dLS GLP-1R neurons project to LHA and release GABA Activation of dLS GLP-1R →LHA axonal terminals suppresses food intake GLP-1R agonism enhances dLS GLP-1R →LHA GABA release via a presynaptic mechanism.

Transcript-specific enrichment enables profiling rare cell states via scRNA-seq

Single-cell genomics technologies have accelerated our understanding of cell-state heterogeneity in diverse contexts. Although single-cell RNA sequencing (scRNA-seq) identifies many rare populations of interest that express specific marker transcript combinations, traditional flow sorting limits our ability to enrich these populations for further profiling, including requiring cell surface markers with high-fidelity antibodies. Additionally, many single-cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers. To address these limitations, we describe Programmable Enrichment via RNA Flow-FISH by sequencing (PERFF-seq), a scalable assay that enables scRNA-seq profiling of subpopulations from complex cellular mixtures defined by the presence or absence of specific RNA transcripts. Across immune populations (n = 141,227 cells) and fresh-frozen and formalin-fixed paraffin-embedded brain tissue (n = 29,522 nuclei), we demonstrate the sorting logic that can be used to enrich for cell populations via RNA-based cytometry followed by high-throughput scRNA-seq. Our approach provides a rational, programmable method for studying rare populations identified by one or more marker transcripts.

Mapping human tissues with highly multiplexed RNA in situ hybridization

In situ transcriptomic techniques promise a holistic view of tissue organization and cell-cell interactions. There has been a surge of multiplexed RNA in situ mapping techniques but their application to human tissues has been limited due to their large size, general lower tissue quality and high autofluorescence. Here we report DART-FISH, a padlock probe-based technology capable of profiling hundreds to thousands of genes in centimeter-sized human tissue sections. We introduce an omni-cell type cytoplasmic stain that substantially improves the segmentation of cell bodies. Our enzyme-free isothermal decoding procedure allows us to image 121 genes in large sections from the human neocortex in <10 h. We successfully recapitulated the cytoarchitecture of 20 neuronal and non-neuronal subclasses. We further performed in situ mapping of 300 genes on a diseased human kidney, profiled >20 healthy and pathological cell states, and identified diseased niches enriched in transcriptionally altered epithelial cells and myofibroblasts.

Expansion and Light-Sheet Microscopy for Nanoscale 3D Imaging

Expansion Microscopy (ExM) and Light-Sheet Fluorescence Microscopy (LSFM) are forefront imaging techniques that enable high-resolution visualization of biological specimens. ExM enhances nanoscale investigation using conventional fluorescence microscopes, while LSFM offers rapid, minimally invasive imaging over large volumes. This review explores the joint advancements of ExM and LSFM, focusing on the excellent performance of the integrated modality obtained from the combination of the two, which is refer to as ExLSFM. In doing so, the chemical processes required for ExM, the tailored optical setup of LSFM for examining expanded samples, and the adjustments in sample preparation for accurate data collection are emphasized. It is delve into various specimen types studied using this integrated method and assess its potential for future applications. The goal of this literature review is to enrich the comprehension of ExM and LSFM, encouraging their wider use and ongoing development, looking forward to the upcoming challenges, and anticipating innovations in these imaging techniques.

Nested neural circuits generate distinct acoustic signals during Drosophila courtship

Many motor control systems generate multiple movements using a common set of muscles. How are premotor circuits able to flexibly generate diverse movement patterns? Here, we characterize the neuronal circuits that drive the distinct courtship songs of Drosophila melanogaster. Male flies vibrate their wings toward females to produce two different song modes-pulse and sine song-which signal species identity and male quality. Using cell-type-specific genetic reagents and the connectome, we provide a cellular and synaptic map of the circuits in the male ventral nerve cord that generate these songs and examine how activating or inhibiting each cell type within these circuits affects the song. Our data reveal that the song circuit is organized into two nested feedforward pathways with extensive reciprocal and feedback connections. The larger network produces pulse song, the more complex and ancestral song form. A subset of this network produces sine song, the simpler and more recent form. Such nested organization may be a common feature of motor control circuits in which evolution has layered increasing flexibility onto a basic movement pattern.

Neuroanatomical, electrophysiological, and morphological characterization of melanin-concentrating hormone cells coexpressing cocaine- and amphetamine-regulated transcript

Melanin-concentrating hormone (MCH) cells in the hypothalamus regulate fundamental physiological functions like energy balance, sleep, and reproduction. This diversity may be ascribed to the neurochemical heterogeneity among MCH cells. One prominent subpopulation of MCH cells coexpresses cocaine- and amphetamine-regulated transcript (CART), and as MCH and CART can have opposing actions, MCH/CART+ and MCH/CART- cells may differentially modulate behavioral outcomes. However, it is not known if there are differences in the cellular properties underlying their functional differences; thus, we compared the neuroanatomical, electrophysiological, and morphological properties of MCH cells in male and female Mch-cre;L10-Egfp reporter mice. Half of MCH cells expressed CART and were most prominent in the medial hypothalamus. Whole-cell patch-clamp recordings revealed differences in their passive and active membrane properties in a sex-dependent manner. Female MCH/CART+ cells had lower input resistances, but male cells largely differed in their firing properties. All MCH cells increased firing when stimulated, but their firing frequency decreases with sustained stimulation. MCH/CART+ cells showed stronger spike rate adaptation than MCH/CART- cells. The kinetics of excitatory events at MCH cells also differed by cell type, as the rising rate of excitatory events was slower at MCH/CART+ cells. By reconstructing the dendritic arborization of our recorded cells, we found no sex differences, but male MCH/CART+ cells had less dendritic length and fewer branch points. Overall, distinctions in topographical division and cellular properties between MCH cells add to their heterogeneity and help elucidate their response to stimuli or effect on modulating their respective neural networks.

Gene panel selection for targeted spatial transcriptomics

Targeted spatial transcriptomics hold particular promise in analyzing complex tissues. Most such methods, however, measure only a limited panel of transcripts, which need to be selected in advance to inform on the cell types or processes being studied. A limitation of existing gene selection methods is their reliance on scRNA-seq data, ignoring platform effects between technologies. Here we describe gpsFISH, a computational method performing gene selection through optimizing detection of known cell types. By modeling and adjusting for platform effects, gpsFISH outperforms other methods. Furthermore, gpsFISH can incorporate cell type hierarchies and custom gene preferences to accommodate diverse design requirements.

Designing a Hybrid Chain Reaction Probe for Multiplex Transcripts Assay with High-Level Imaging

The hybrid chain reaction (HCR), an isothermal and enzyme-free amplification strategy, has found extensive use in fluorescent in situ hybridization (FISH) assays. However, the existing HCRs are limited, being time-consuming processes and low-efficiency imaging due to weak signal, significantly restricting their application in transcriptomic assays. To address the limitations, we developed nine orthogonal HCR hairpin-pair (hp) probes in this study to enable efficient signal amplification for multiplex assays. To enhance the efficiency and imaging quality of multiplex assays using these HCR probes, we employed two strategies. First, we coupled fluorescent molecules to HCR hairpins via disulfide bonds, facilitating easy removal through chemical cleavage. As a result, the workflow was greatly simplified. Second, we combined HCR with in situ rolling circle amplification (ISRCA), creating ISRCA-HCR, which achieved a 17-fold signal amplification. ISRCA-HCR demonstrated a high-level imaging capability for spatial cell type assays. This study shows the application for cell typing based on the developed HCR probes, enabling accurate and high-level signal amplification for multiplex FISH imaging. This provides an effective research tool for transcriptome and spatial cell type analysis.

Believing is seeing - the deceptive influence of bias in quantitative microscopy

The visual allure of microscopy makes it an intuitively powerful research tool. Intuition, however, can easily obscure or distort the reality of the information contained in an image. Common cognitive biases, combined with institutional pressures that reward positive research results, can quickly skew a microscopy project towards upholding, rather than rigorously challenging, a hypothesis. The impact of these biases on a variety of research topics is well known. What might be less appreciated are the many forms in which bias can permeate a microscopy experiment. Even well-intentioned researchers are susceptible to bias, which must therefore be actively recognized to be mitigated. Importantly, although image quantification has increasingly become an expectation, ostensibly to confront subtle biases, it is not a guarantee against bias and cannot alone shield an experiment from cognitive distortions. Here, we provide illustrative examples of the insidiously pervasive nature of bias in microscopy experiments - from initial experimental design to image acquisition, analysis and data interpretation. We then provide suggestions that can serve as guard rails against bias.

Dopamine in the nucleus accumbens shell controls systemic glucose metabolism via the lateral hypothalamus and hepatic vagal innervation in rodents

BACKGROUND

Growing evidence demonstrates the role of the striatal dopamine system in the regulation of glucose metabolism. Treatment with dopamine antagonists is associated with insulin resistance and hyperglycemia, while dopamine agonists are used in treatment of type 2 diabetes. The mechanism underlying striatal dopamine effects in glucose metabolism, however is not fully understood. Here, we provide mechanistic insights into the role of nucleus accumbens shell (sNAc) dopaminergic signaling in systemic glucose metabolism.

METHODS

Endogenous glucose production (EGP), blood glucose and mRNA expression in the lateral hypothalamic area (LHA) in male Wistar rats were measured following infusion of vanoxerine (VNX, dopamine reuptake inhibitor) in the sNAc. Thereafter, we analyzed projections from sNAc Drd1-expressing neurons to LHA using D1-Cre male Long-Evans rats, Cre-dependent viral tracers and fluorescence immunohistochemistry. Brain slice electrophysiology in adult mice was used to study spontaneous excitatory postsynaptic currents of sNAc Drd1-expressing neurons following VNX application. Finally, we assessed whether GABAergic LHA activity and hepatic vagal innervation were required for the effect of sNAc-VNX on glucose metabolism by combining infusion of sNAc-VNX with LHA-bicuculline, performing vagal recordings and combining infusion of sNAc-VNX with hepatic vagal denervation.

RESULTS

VNX infusion in the sNAc strongly decreased endogenous glucose production, prevented glucose increases over time, reduced Slc17A6 and Hcrt mRNA in LHA, and increased vagal activity. Furthermore, sNAc Drd1-expressing neurons increased spontaneous firing following VNX application, and viral tracing of sNAc Drd1-expressing neurons revealed direct projections to LHA with on average 67 % of orexin cells directly targeted by sNAc Drd1-expressing neurons. Importantly, the sNAc-VNX-induced effect on glucose metabolism was dependent on GABAergic signaling in the LHA and on intact hepatic vagal innervation.

CONCLUSIONS

We show that sNAc dopaminergic signaling modulates hepatic glucose metabolism through GABAergic inputs to glutamatergic LHA cells and hepatic vagal innervation. This demonstrates that striatal control of glucose metabolism involves a dopaminergic sNAc-LHA-liver axis and provides a potential explanation for the effects of dopamine agonists and antagonists on glucose metabolism.

Universal, label-free, single-molecule visualization of DNA origami nanodevices across biological samples using origamiFISH

Structural DNA nanotechnology enables the fabrication of user-defined DNA origami nanostructures (DNs) for biological applications. However, the role of DN design during cellular interactions and subsequent biodistribution remain poorly understood. Current methods for tracking DN fates in situ, including fluorescent-dye labelling, suffer from low sensitivity and dye-induced artifacts. Here we present origamiFISH, a label-free and universal method for the single-molecule fluorescence detection of DNA origami nanostructures in cells and tissues. origamiFISH targets pan-DN scaffold sequences with hybridization chain reaction probes to achieve 1,000-fold signal amplification. We identify cell-type- and DN shape-specific spatiotemporal distribution patterns within a minute of uptake and at picomolar DN concentrations, 10,000× lower than field standards. We additionally optimize compatibility with immunofluorescence and tissue clearing to visualize DN distribution within tissue cryo-/vibratome sections, slice cultures and whole-mount organoids. Together, origamiFISH enables the accurate mapping of DN distribution across subcellular and tissue barriers for guiding the development of DN-based therapeutics.

A tridimensional atlas of the developing human head

The evolution and development of the head have long captivated researchers due to the crucial role of the head as the gateway for sensory stimuli and the intricate structural complexity of the head. Although significant progress has been made in understanding head development in various vertebrate species, our knowledge of early human head ontogeny remains limited. Here, we used advanced whole-mount immunostaining and 3D imaging techniques to generate a comprehensive 3D cellular atlas of human head embryogenesis. We present detailed developmental series of diverse head tissues and cell types, including muscles, vasculature, cartilage, peripheral nerves, and exocrine glands. These datasets, accessible through a dedicated web interface, provide insights into human embryogenesis. We offer perspectives on the branching morphogenesis of human exocrine glands and unknown features of the development of neurovascular and skeletomuscular structures. These insights into human embryology have important implications for understanding craniofacial defects and neurological disorders and advancing diagnostic and therapeutic strategies.

Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology

Metabolic reprogramming in cancer and immune cells occurs to support their increasing energy needs in biological tissues. Here we propose Single Cell Spatially resolved Metabolic (scSpaMet) framework for joint protein-metabolite profiling of single immune and cancer cells in male human tissues by incorporating untargeted spatial metabolomics and targeted multiplexed protein imaging in a single pipeline. We utilized the scSpaMet to profile cell types and spatial metabolomic maps of 19507, 31156, and 8215 single cells in human lung cancer, tonsil, and endometrium tissues, respectively. The scSpaMet analysis revealed cell type-dependent metabolite profiles and local metabolite competition of neighboring single cells in human tissues. Deep learning-based joint embedding revealed unique metabolite states within cell types. Trajectory inference showed metabolic patterns along cell differentiation paths. Here we show scSpaMet's ability to quantify and visualize the cell-type specific and spatially resolved metabolic-protein mapping as an emerging tool for systems-level understanding of tissue biology.

Microscopy and spectroscopy approaches to study GPCR structure and function

The GPCR signalling cascade is a key pathway responsible for the signal transduction of a multitude of physical and chemical stimuli, including light, odorants, neurotransmitters and hormones. Understanding the structural and functional properties of the GPCR cascade requires direct observation of signalling processes in high spatial and temporal resolution, with minimal perturbation to endogenous systems. Optical microscopy and spectroscopy techniques are uniquely suited to this purpose because they excel at multiple spatial and temporal scales and can be used in living objects. Here, we review recent developments in microscopy and spectroscopy technologies which enable new insights into GPCR signalling. We focus on advanced techniques with high spatial and temporal resolution, single-molecule methods, labelling strategies and approaches suitable for endogenous systems and large living objects. This review aims to assist researchers in choosing appropriate microscopy and spectroscopy approaches for a variety of applications in the study of cellular signalling.

Neurocircuits for motivation

The nervous system coordinates various motivated behaviors such as feeding, drinking, and escape to promote survival and evolutionary fitness. Although the precise behavioral repertoires required for distinct motivated behaviors are diverse, common features such as approach or avoidance suggest that common brain substrates are required for a wide range of motivated behaviors. In this Review, I describe a framework by which neural circuits specified for some innate drives regulate the activity of ventral tegmental area (VTA) dopamine neurons to reinforce ongoing or planned actions to fulfill motivational demands. This framework may explain why signaling from VTA dopamine neurons is ubiquitously involved in many types of diverse volitional motivated actions, as well as how sensory and interoceptive cues can initiate specific goal-directed actions.

Advanced Omics Techniques for Understanding Cochlear Genome, Epigenome, and Transcriptome in Health and Disease

Advanced genomics, transcriptomics, and epigenomics techniques are providing unprecedented insights into the understanding of the molecular underpinnings of the central nervous system, including the neuro-sensory cochlea of the inner ear. Here, we report for the first time a comprehensive and updated overview of the most advanced omics techniques for the study of nucleic acids and their applications in cochlear research. We describe the available in vitro and in vivo models for hearing research and the principles of genomics, transcriptomics, and epigenomics, alongside their most advanced technologies (like single-cell omics and spatial omics), which allow for the investigation of the molecular events that occur at a single-cell resolution while retaining the spatial information.

A comprehensive neuroanatomical survey of the Drosophila Lobula Plate Tangential Neurons with predictions for their optic flow sensitivity

Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow, the pattern of changes in the visual scene induced by locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic flow patterns have been studied for decades, primarily in large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are the large tangential cells of the dipteran lobula plate, whose visual-motion responses, and to a lesser extent, their morphology, have been explored using single-neuron neurophysiology. Most of these studies have focused on the large, Horizontal and Vertical System neurons, yet the lobula plate houses a much larger set of 'optic-flow' sensitive neurons, many of which have been challenging to unambiguously identify or to reliably target for functional studies. Here we report the comprehensive reconstruction and identification of the Lobula Plate Tangential Neurons in an Electron Microscopy (EM) volume of a whole Drosophila brain. This catalog of 58 LPT neurons (per brain hemisphere) contains many neurons that are described here for the first time and provides a basis for systematic investigation of the circuitry linking self-motion to locomotion control. Leveraging computational anatomy methods, we estimated the visual motion receptive fields of these neurons and compared their tuning to the visual consequence of body rotations and translational movements. We also matched these neurons, in most cases on a one-for-one basis, to stochastically labeled cells in genetic driver lines, to the mirror-symmetric neurons in the same EM brain volume, and to neurons in an additional EM data set. Using cell matches across data sets, we analyzed the integration of optic flow patterns by neurons downstream of the LPTs and find that most central brain neurons establish sharper selectivity for global optic flow patterns than their input neurons. Furthermore, we found that self-motion information extracted from optic flow is processed in distinct regions of the central brain, pointing to diverse foci for the generation of visual behaviors.

Following the Birth, Life, and Death of mRNAs in Single Cells

Recent advances in single-molecule imaging of mRNAs in fixed and living cells have enabled the lives of mRNAs to be studied with unprecedented spatial and temporal detail. These approaches have moved beyond simply being able to observe specific events and have begun to allow an understanding of how regulation is coupled between steps in the mRNA life cycle. Additionally, these methodologies are now being applied in multicellular systems and animals to provide more nuanced insights into the physiological regulation of RNA metabolism.

Harnessing computational spatial omics to explore the spatial biology intricacies

Spatially resolved transcriptomics (SRT) has unlocked new dimensions in our understanding of intricate tissue architectures. However, this rapidly expanding field produces a wealth of diverse and voluminous data, necessitating the evolution of sophisticated computational strategies to unravel inherent patterns. Two distinct methodologies, gene spatial pattern recognition (GSPR) and tissue spatial pattern recognition (TSPR), have emerged as vital tools in this process. GSPR methodologies are designed to identify and classify genes exhibiting noteworthy spatial patterns, while TSPR strategies aim to understand intercellular interactions and recognize tissue domains with molecular and spatial coherence. In this review, we provide a comprehensive exploration of SRT, highlighting crucial data modalities and resources that are instrumental for the development of methods and biological insights. We address the complexities and challenges posed by the use of heterogeneous data in developing GSPR and TSPR methodologies and propose an optimal workflow for both. We delve into the latest advancements in GSPR and TSPR, examining their interrelationships. Lastly, we peer into the future, envisaging the potential directions and perspectives in this dynamic field.

Ghrelin's orexigenic action in the lateral hypothalamic area involves indirect recruitment of orexin neurons and arcuate nucleus activation

OBJECTIVE

Ghrelin is a potent orexigenic hormone, and the lateral hypothalamic area (LHA) has been suggested as a putative target mediating ghrelin's effects on food intake. Here, we aimed to investigate the presence of neurons expressing ghrelin receptor (a.k.a. growth hormone secretagogue receptor, GHSR) in the mouse LHA (LHAGHSR neurons), its physiological implications and the neuronal circuit recruited by local ghrelin action.

METHODS

We investigated the distribution of LHAGHSR neurons using different histologic strategies, including the use of a reporter mice expressing enhanced green fluorescent protein under the control of the GHSR promoter. Also, we investigated the physiological implications of local injections of ghrelin within the LHA, and the extent to which the orexigenic effect of intra-LHA-injected ghrelin involves the arcuate nucleus (ARH) and orexin neurons of the LHA (LHAorexin neurons) RESULTS: We found that: 1) LHAGHSR neurons are homogeneously distributed throughout the entire LHA; 2) intra-LHA injections of ghrelin transiently increase food intake and locomotor activity; 3) ghrelin's orexigenic effect in the LHA involves the indirect recruitment of LHAorexin neurons and the activation of ARH neurons; and 4) LHAGHSR neurons are not targeted by plasma ghrelin.

CONCLUSIONS

We provide a compelling neuroanatomical and functional characterization of LHAGHSR neurons in male mice that indicates that LHAGHSR cells are part of a hypothalamic neuronal circuit that potently induces food intake.

Spatial transcriptomics in neuroscience

The brain is one of the most complex living tissue types and is composed of an exceptional diversity of cell types displaying unique functional connectivity. Single-cell RNA sequencing (scRNA-seq) can be used to efficiently map the molecular identities of the various cell types in the brain by providing the transcriptomic profiles of individual cells isolated from the tissue. However, the lack of spatial context in scRNA-seq prevents a comprehensive understanding of how different configurations of cell types give rise to specific functions in individual brain regions and how each distinct cell is connected to form a functional unit. To understand how the various cell types contribute to specific brain functions, it is crucial to correlate the identities of individual cells obtained through scRNA-seq with their spatial information in intact tissue. Spatial transcriptomics (ST) can resolve the complex spatial organization of cell types in the brain and their connectivity. Various ST tools developed during the past decade based on imaging and sequencing technology have permitted the creation of functional atlases of the brain and have pulled the properties of neural circuits into ever-sharper focus. In this review, we present a summary of several ST tools and their applications in neuroscience and discuss the unprecedented insights these tools have made possible.

Expansion microscopy using a single anchor molecule for high-yield multiplexed imaging of proteins and RNAs

Expansion microscopy (ExM), by physically enlarging specimens in an isotropic fashion, enables nanoimaging on standard light microscopes. Key to existing ExM protocols is the equipping of different kinds of molecules, with different kinds of anchoring moieties, so they can all be pulled apart from each other by polymer swelling. Here we present a multifunctional anchor, an acrylate epoxide, that enables proteins and RNAs to be equipped with anchors in a single experimental step. This reagent simplifies ExM protocols and reduces cost (by 2-10-fold for a typical multiplexed ExM experiment) compared to previous strategies for equipping RNAs with anchors. We show that this united ExM (uniExM) protocol can be used to preserve and visualize RNA transcripts, proteins in biologically relevant ultrastructures, and sets of RNA transcripts in patient-derived xenograft (PDX) cancer tissues and may support the visualization of other kinds of biomolecular species as well. uniExM may find many uses in the simple, multimodal nanoscale analysis of cells and tissues.

Spatial transcriptomics for profiling the tropism of viral vectors in tissues

A barrier to advancing engineered adeno-associated viral vectors (AAVs) for precision access to cell subtypes is a lack of high-throughput, high-resolution assays to characterize in vivo transduction profiles. In this study, we developed an ultrasensitive, sequential fluorescence in situ hybridization (USeqFISH) method for spatial transcriptomic profiling of endogenous and viral RNA with a short barcode in intact tissue volumes by integrating hydrogel-based tissue clearing, enhanced signal amplification and multiplexing using sequential labeling. Using USeqFISH, we investigated the transduction and cell subtype tropisms across mouse brain regions of six systemic AAVs, including AAV-PHP.AX, a new variant that transduces robustly and efficiently across neurons and astrocytes. Here we reveal distinct cell subtype biases of each AAV variant, including a bias of AAV-PHP.N toward excitatory neurons. USeqFISH also enables profiling of pooled regulatory cargos, as we show for a 13-variant pool of microRNA target sites in AAV genomes. Lastly, we demonstrate potential applications of USeqFISH for in situ AAV profiling and multimodal single-cell analysis in non-human primates.

Spatially resolved transcriptomics: a comprehensive review of their technological advances, applications, and challenges

The ability to explore life kingdoms is largely driven by innovations and breakthroughs in technology, from the invention of the microscope 350 years ago to the recent emergence of single-cell sequencing, by which the scientific community has been able to visualize life at an unprecedented resolution. Most recently, the Spatially Resolved Transcriptomics (SRT) technologies have filled the gap in probing the spatial or even three-dimensional organization of the molecular foundation behind the molecular mysteries of life, including the origin of different cellular populations developed from totipotent cells and human diseases. In this review, we introduce recent progresses and challenges on SRT from the perspectives of technologies and bioinformatic tools, as well as the representative SRT applications. With the currently fast-moving progress of the SRT technologies and promising results from early adopted research projects, we can foresee the bright future of such new tools in understanding life at the most profound analytical level.

Control of energy homeostasis by the lateral hypothalamic area

The lateral hypothalamic area (LHA) is a subcortical brain region that exerts control over motivated behavior, feeding, and energy balance across species. Recent single-cell sequencing studies have defined at least 30 distinct LHA neuron types. Some of these influence specific aspects of energy homeostasis; however, the functions of many LHA cell types remain unclear. This review addresses the rapidly emerging evidence from cell-type-specific investigations that the LHA leverages distinct neuron populations to regulate energy balance through complex connections with other brain regions. It will highlight recent findings demonstrating that LHA control of energy balance extends beyond mere food intake and propose outstanding questions to be addressed by future research.

Mapping Human Tissues with Highly Multiplexed RNA in situ Hybridization

In situ transcriptomic techniques promise a holistic view of tissue organization and cell-cell interactions. Recently there has been a surge of multiplexed RNA in situ techniques but their application to human tissues and clinical biopsies has been limited due to their large size, general lower tissue quality and high background autofluorescence. Here we report DART-FISH, a versatile padlock probe-based technology capable of profiling hundreds to thousands of genes in centimeter-sized human tissue sections at cellular resolution. We introduced an omni-cell type cytoplasmic stain, dubbed RiboSoma that substantially improves the segmentation of cell bodies. We developed a computational decoding-by-deconvolution workflow to extract gene spots even in the presence of optical crowding. Our enzyme-free isothermal decoding procedure allowed us to image 121 genes in a large section from the human neocortex in less than 10 hours, where we successfully recapitulated the cytoarchitecture of 20 neuronal and non-neuronal subclasses. Additionally, we demonstrated the detection of transcripts as short as 461 nucleotides, including neuropeptides and discovered new cortical layer markers. We further performed in situ mapping of 300 genes on a diseased human kidney, profiled >20 healthy and pathological cell states, and identified diseased niches enriched in transcriptionally altered epithelial cells and myofibroblasts.

Spatial transcriptomics: recent developments and insights in respiratory research

The respiratory system's complex cellular heterogeneity presents unique challenges to researchers in this field. Although bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) have provided insights into cell types and heterogeneity in the respiratory system, the relevant specific spatial localization and cellular interactions have not been clearly elucidated. Spatial transcriptomics (ST) has filled this gap and has been widely used in respiratory studies. This review focuses on the latest iterative technology of ST in recent years, summarizing how ST can be applied to the physiological and pathological processes of the respiratory system, with emphasis on the lungs. Finally, the current challenges and potential development directions are proposed, including high-throughput full-length transcriptome, integration of multi-omics, temporal and spatial omics, bioinformatics analysis, etc. These viewpoints are expected to advance the study of systematic mechanisms, including respiratory studies.

Multiplexed single-cell 3D spatial gene expression analysis in plant tissue using PHYTOMap

Retrieving the complex responses of individual cells in the native three-dimensional tissue context is crucial for a complete understanding of tissue functions. Here, we present PHYTOMap (plant hybridization-based targeted observation of gene expression map), a multiplexed fluorescence in situ hybridization method that enables single-cell and spatial analysis of gene expression in whole-mount plant tissue in a transgene-free manner and at low cost. We applied PHYTOMap to simultaneously analyse 28 cell-type marker genes in Arabidopsis roots and successfully identified major cell types, demonstrating that our method can substantially accelerate the spatial mapping of marker genes defined in single-cell RNA-sequencing datasets in complex plant tissue.

Brain-wide mapping of efferent projections of glutamatergic (Onecut3+ ) neurons in the lateral mouse hypothalamus

AIM

This study mapped the spatiotemporal positions and connectivity of Onecut3+ neuronal populations in the developing and adult mouse brain.

METHODS

We generated fluorescent reporter mice to chart Onecut3+ neurons for brain-wide analysis. Moreover, we crossed Onecut3-iCre and Mapt-mGFP (Tau-mGFP) mice to visualize axonal projections. A dual Cre/Flp-dependent AAV construct in Onecut3-iCre cross-bred with Slc17a6-FLPo mice was used in an intersectional strategy to map the connectivity of glutamatergic lateral hypothalamic neurons in the adult mouse.

RESULTS

We first found that Onecut3 marks a hitherto undescribed Slc17a6+ /Vglut2+ neuronal cohort in the lateral hypothalamus, with the majority expressing thyrotropin-releasing hormone. In the adult, Onecut3+ /Vglut2+ neurons of the lateral hypothalamus had both intra- and extrahypothalamic efferents, particularly to the septal complex and habenula, where they targeted other cohorts of Onecut3+ neurons and additionally to the neocortex and hippocampus. This arrangement suggests that intrinsic reinforcement loops could exist for Onecut3+ neurons to coordinate their activity along the brain's midline axis.

CONCLUSION

We present both a toolbox to manipulate novel subtypes of hypothalamic neurons and an anatomical arrangement by which extrahypothalamic targets can be simultaneously entrained.

Esr1+ hypothalamic-habenula neurons shape aversive states

Excitatory projections from the lateral hypothalamic area (LHA) to the lateral habenula (LHb) drive aversive responses. We used patch-sequencing (Patch-seq) guided multimodal classification to define the structural and functional heterogeneity of the LHA-LHb pathway. Our classification identified six glutamatergic neuron types with unique electrophysiological properties, molecular profiles and projection patterns. We found that genetically defined LHA-LHb neurons signal distinct aspects of emotional or naturalistic behaviors, such as estrogen receptor 1-expressing (Esr1⁺) LHA-LHb neurons induce aversion, whereas neuropeptide Y-expressing (Npy⁺) LHA-LHb neurons control rearing behavior. Repeated optogenetic drive of Esr1⁺ LHA-LHb neurons induces a behaviorally persistent aversive state, and large-scale recordings showed a region-specific neural representation of the aversive signals in the prelimbic region of the prefrontal cortex. We further found that exposure to unpredictable mild shocks induced a sex-specific sensitivity to develop a stress state in female mice, which was associated with a specific shift in the intrinsic properties of bursting-type Esr1⁺ LHA-LHb neurons. In summary, we describe the diversity of LHA-LHb neuron types and provide evidence for the role of Esr1⁺ neurons in aversion and sexually dimorphic stress sensitivity.

Spatial Mapping of Mobile Genetic Elements and their Cognate Hosts in Complex Microbiomes

The frequent exchange of mobile genetic elements (MGEs) between bacteria accelerates the spread of functional traits, including antimicrobial resistance, within the human microbiome. Yet, progress in understanding these intricate processes has been hindered by the lack of tools to map the spatial spread of MGEs in complex microbial communities, and to associate MGEs to their bacterial hosts. To overcome this challenge, we present an imaging approach that pairs single molecule DNA Fluorescence In Situ Hybridization (FISH) with multiplexed ribosomal RNA FISH, thereby enabling the simultaneous visualization of both MGEs and host bacterial taxa. We used this methodology to spatially map bacteriophage and antimicrobial resistance (AMR) plasmids in human oral biofilms, and we studied the heterogeneity in their spatial distributions and demonstrated the ability to identify their host taxa. Our data revealed distinct clusters of both AMR plasmids and prophage, coinciding with densely packed regions of host bacteria in the biofilm. These results suggest the existence of specialized niches that maintain MGEs within the community, possibly acting as local hotspots for horizontal gene transfer. The methods introduced here can help advance the study of MGE ecology and address pressing questions regarding antimicrobial resistance and phage therapy.

Spatial Transcriptomics: Technical Aspects of Recent Developments and Their Applications in Neuroscience and Cancer Research

Spatial transcriptomics is a newly emerging field that enables high-throughput investigation of the spatial localization of transcripts and related analyses in various applications for biological systems. By transitioning from conventional biological studies to "in situ" biology, spatial transcriptomics can provide transcriptome-scale spatial information. Currently, the ability to simultaneously characterize gene expression profiles of cells and relevant cellular environment is a paradigm shift for biological studies. In this review, recent progress in spatial transcriptomics and its applications in neuroscience and cancer studies are highlighted. Technical aspects of existing technologies and future directions of new developments (as of March 2023), computational analysis of spatial transcriptome data, application notes in neuroscience and cancer studies, and discussions regarding future directions of spatial multi-omics and their expanding roles in biomedical applications are emphasized.

Target cell-specific synaptic dynamics of excitatory to inhibitory neuron connections in supragranular layers of human neocortex

Rodent studies have demonstrated that synaptic dynamics from excitatory to inhibitory neuron types are often dependent on the target cell type. However, these target cell-specific properties have not been well investigated in human cortex, where there are major technical challenges in reliably obtaining healthy tissue, conducting multiple patch-clamp recordings on inhibitory cell types, and identifying those cell types. Here, we take advantage of newly developed methods for human neurosurgical tissue analysis with multiple patch-clamp recordings, post-hoc fluorescent in situ hybridization (FISH), machine learning-based cell type classification and prospective GABAergic AAV-based labeling to investigate synaptic properties between pyramidal neurons and PVALB- vs. SST-positive interneurons. We find that there are robust molecular differences in synapse-associated genes between these neuron types, and that individual presynaptic pyramidal neurons evoke postsynaptic responses with heterogeneous synaptic dynamics in different postsynaptic cell types. Using molecular identification with FISH and classifiers based on transcriptomically identified PVALB neurons analyzed by Patch-seq, we find that PVALB neurons typically show depressing synaptic characteristics, whereas other interneuron types including SST-positive neurons show facilitating characteristics. Together, these data support the existence of target cell-specific synaptic properties in human cortex that are similar to rodent, thereby indicating evolutionary conservation of local circuit connectivity motifs from excitatory to inhibitory neurons and their synaptic dynamics.

Gene panel selection for targeted spatial transcriptomics

Targeted spatial transcriptomics hold particular promise in analysis of complex tissues. Most such methods, however, measure only a limited panel of transcripts, which need to be selected in advance to inform on the cell types or processes being studied. A limitation of existing gene selection methods is that they rely on scRNA-seq data, ignoring platform effects between technologies. Here we describe gpsFISH, a computational method to perform gene selection through optimizing detection of known cell types. By modeling and adjusting for platform effects, gpsFISH outperforms other methods. Furthermore, gpsFISH can incorporate cell type hierarchies and custom gene preferences to accommodate diverse design requirements.

Current Progress in Expansion Microscopy: Chemical Strategies and Applications

Expansion microscopy (ExM) is a newly developed super-resolution technique, allowing visualization of biological targets at nanoscale resolution on conventional fluorescence microscopes. Since its introduction in 2015, many efforts have been dedicated to broaden its application range or increase the resolution that can be achieved. As a consequence, recent years have witnessed remarkable advances in ExM. This review summarizes recent progress in ExM, with the focus on the chemical aspects of the method, from chemistries for biomolecule grafting to polymer synthesis and the impact on biological analysis. The combination of ExM with other microscopy techniques, in search of additional resolution improvement, is also discussed. In addition, we compare pre- and postexpansion labeling strategies and discuss the impact of fixation methods on ultrastructure preservation. We conclude this review with a perspective on existing challenges and future directions. We believe that this review will provide a comprehensive understanding of ExM and facilitate its usage and further development.

Lateral hypothalamic leptin receptor neurons drive hunger-gated food-seeking and consummatory behaviours in male mice

For survival, it is crucial for eating behaviours to be sequenced through two distinct seeking and consummatory phases. Heterogeneous lateral hypothalamus (LH) neurons are known to regulate motivated behaviours, yet which subpopulation drives food seeking and consummatory behaviours have not been fully addressed. Here, in male mice, fibre photometry recordings demonstrated that LH leptin receptor (LepR) neurons are correlated explicitly in both voluntary seeking and consummatory behaviours. Further, micro-endoscope recording of the LH^LepR neurons demonstrated that one subpopulation is time-locked to seeking behaviours and the other subpopulation time-locked to consummatory behaviours. Seeking or consummatory phase specific paradigm revealed that activation of LH^LepR neurons promotes seeking or consummatory behaviours and inhibition of LH^LepR neurons reduces consummatory behaviours. The activity of LH^LepR neurons was increased via Neuropeptide Y (NPY) which acted as a tonic permissive gate signal. Our results identify neural populations that mediate seeking and consummatory behaviours and may lead to therapeutic targets for maladaptive food seeking and consummatory behaviours.

Spatial profiling technologies illuminate the tumor microenvironment

The tumor microenvironment (TME) is composed of many different cellular and acellular components that together drive tumor growth, invasion, metastasis, and response to therapies. Increasing realization of the significance of the TME in cancer biology has shifted cancer research from a cancer-centric model to one that considers the TME as a whole. Recent technological advancements in spatial profiling methodologies provide a systematic view and illuminate the physical localization of the components of the TME. In this review, we provide an overview of major spatial profiling technologies. We present the types of information that can be extracted from these data and describe their applications, findings and challenges in cancer research. Finally, we provide a future perspective of how spatial profiling could be integrated into cancer research to improve patient diagnosis, prognosis, stratification to treatment and development of novel therapeutics.

SODB facilitates comprehensive exploration of spatial omics data

Spatial omics technologies generate wealthy but highly complex datasets. Here we present Spatial Omics DataBase (SODB), a web-based platform providing both rich data resources and a suite of interactive data analytical modules. SODB currently maintains >2,400 experiments from >25 spatial omics technologies, which are freely accessible as a unified data format compatible with various computational packages. SODB also provides multiple interactive data analytical modules, especially a unique module, Spatial Omics View (SOView). We conduct comprehensive statistical analyses and illustrate the utility of both basic and advanced analytical modules using multiple spatial omics datasets. We demonstrate SOView utility with brain spatial transcriptomics data and recover known anatomical structures. We further delineate functional tissue domains with associated marker genes that were obscured when analyzed using previous methods. We finally show how SODB may efficiently facilitate computational method development. The SODB website is https://gene.ai.tencent.com/SpatialOmics/ . The command-line package is available at https://pysodb.readthedocs.io/en/latest/ .

Highly efficient and robust π-FISH rainbow for multiplexed in situ detection of diverse biomolecules

In the unprecedented single-cell sequencing and spatial multiomics era of biology, fluorescence in situ hybridization (FISH) technologies with higher sensitivity and robustness, especially for detecting short RNAs and other biomolecules, are greatly desired. Here, we develop the robust multiplex π-FISH rainbow method to detect diverse biomolecules (DNA, RNA, proteins, and neurotransmitters) individually or simultaneously with high efficiency. This versatile method is successfully applied to detect gene expression in different species, from microorganisms to plants and animals. Furthermore, we delineate the landscape of diverse neuron subclusters by decoding the spatial distribution of 21 marker genes via only two rounds of hybridization. Significantly, we combine π-FISH rainbow with hybridization chain reaction to develop π-FISH+ technology for short nucleic acid fragments, such as microRNA and prostate cancer anti-androgen therapy-resistant marker ARV7 splicing variant in circulating tumour cells from patients. Our study provides a robust biomolecule in situ detection technology for spatial multiomics investigation and clinical diagnosis.

Dorsoventral Arrangement of Lateral Hypothalamus Populations in the Mouse Hypothalamus: a Prosomeric Genoarchitectonic Analysis

The lateral hypothalamus (LH) has a heterogeneous cytoarchitectonic organization that has not been elucidated in detail. In this work, we analyzed within the framework of the prosomeric model the differential expression pattern of 59 molecular markers along the ventrodorsal dimension of the medial forebrain bundle in the mouse, considering basal and alar plate subregions of the LH. We found five basal (LH1-LH5) and four alar (LH6-LH9) molecularly distinct sectors of the LH with neuronal cell groups that correlate in topography with previously postulated alar and basal hypothalamic progenitor domains. Most peptidergic populations were restricted to one of these LH sectors though some may have dispersed into a neighboring sector. For instance, histaminergic Hdc-positive neurons were mostly contained within the basal LH3, Nts (neurotensin)- and Tac2 (tachykinin 2)-expressing cells lie strictly within LH4, Hcrt (hypocretin/orexin)-positive and Pmch (pro-melanin-concentrating hormone)-positive neurons appeared within separate LH5 subdivisions, Pnoc (prepronociceptin)-expressing cells were mainly restricted to LH6, and Sst (somatostatin)-positive cells were identified within the LH7 sector. The alar LH9 sector, a component of the Foxg1-positive telencephalo-opto-hypothalamic border region, selectively contained Satb2-expressing cells. Published studies of rodent LH subdivisions have not described the observed pattern. Our genoarchitectonic map should aid in systematic approaches to elucidate LH connectivity and function.

RS-FISH: precise, interactive, fast, and scalable FISH spot detection

Fluorescent in-situ hybridization (FISH)-based methods extract spatially resolved genetic and epigenetic information from biological samples by detecting fluorescent spots in microscopy images, an often challenging task. We present Radial Symmetry-FISH (RS-FISH), an accurate, fast, and user-friendly software for spot detection in two- and three-dimensional images. RS-FISH offers interactive parameter tuning and readily scales to large datasets and image volumes of cleared or expanded samples using distributed processing on workstations, clusters, or the cloud. RS-FISH maintains high detection accuracy and low localization error across a wide range of signal-to-noise ratios, a key feature for single-molecule FISH, spatial transcriptomics, or spatial genomics applications.

Application of Fluorescence In Situ Hybridization (FISH) in Oral Microbial Detection

Varieties of microorganisms reside in the oral cavity contributing to the occurrence and development of microbes associated with oral diseases; however, the distribution and in situ abundance in the biofilm are still unclear. In order to promote the understanding of the ecosystem of oral microbiota and the diagnosis of oral diseases, it is necessary to monitor and compare the oral microorganisms from different niches of the oral cavity in situ. The fluorescence in situ hybridization (FISH) has proven to be a powerful tool for representing the status of oral microorganisms in the oral cavity. FISH is one of the most routinely used cytochemical techniques for genetic detection, identification, and localization by a fluorescently labeled nucleic acid probe, which can hybridize with targeted nucleic acid sequences. It has the advantages of rapidity, safety, high sensitivity, and specificity. FISH allows the identification and quantification of different oral microorganisms simultaneously. It can also visualize microorganisms by combining with other molecular biology technologies to represent the distribution of each microbial community in the oral biofilm. In this review, we summarized and discussed the development of FISH technology and the application of FISH in oral disease diagnosis and oral ecosystem research, highlighted its advantages in oral microbiology, listed the existing problems, and provided suggestions for future development..

SOTIP is a versatile method for microenvironment modeling with spatial omics data

The rapidly developing spatial omics generated datasets with diverse scales and modalities. However, most existing methods focus on modeling dynamics of single cells while ignore microenvironments (MEs). Here we present SOTIP (Spatial Omics mulTIPle-task analysis), a versatile method incorporating MEs and their interrelationships into a unified graph. Based on this graph, spatial heterogeneity quantification, spatial domain identification, differential microenvironment analysis, and other downstream tasks can be performed. We validate each module's accuracy, robustness, scalability and interpretability on various spatial omics datasets. In two independent mouse cerebral cortex spatial transcriptomics datasets, we reveal a gradient spatial heterogeneity pattern strongly correlated with the cortical depth. In human triple-negative breast cancer spatial proteomics datasets, we identify molecular polarizations and MEs associated with different patient survivals. Overall, by modeling biologically explainable MEs, SOTIP outperforms state-of-art methods and provides some perspectives for spatial omics data exploration and interpretation.