Multiplexed Intact-Tissue Transcriptional Analysis at Cellular Resolution

Deep 3D histology powered by tissue clearing, omics and AI

To comprehensively understand tissue and organism physiology and pathophysiology, it is essential to create complete three-dimensional (3D) cellular maps. These maps require structural data, such as the 3D configuration and positioning of tissues and cells, and molecular data on the constitution of each cell, spanning from the DNA sequence to protein expression. While single-cell transcriptomics is illuminating the cellular and molecular diversity across species and tissues, the 3D spatial context of these molecular data is often overlooked. Here, I discuss emerging 3D tissue histology techniques that add the missing third spatial dimension to biomedical research. Through innovations in tissue-clearing chemistry, labeling and volumetric imaging that enhance 3D reconstructions and their synergy with molecular techniques, these technologies will provide detailed blueprints of entire organs or organisms at the cellular level. Machine learning, especially deep learning, will be essential for extracting meaningful insights from the vast data. Further development of integrated structural, molecular and computational methods will unlock the full potential of next-generation 3D histology.

See-Star: a versatile hydrogel-based protocol for clearing large, opaque and calcified marine invertebrates

Studies of morphology and developmental patterning in adult stages of many invertebrates are hindered by opaque structures, such as shells, skeletal elements, and pigment granules that block or refract light and necessitate sectioning for observation of internal features. An inherent challenge in studies relying on surgical approaches is that cutting tissue is semi-destructive, and delicate structures, such as axonal processes within neural networks, are computationally challenging to reconstruct once disrupted. To address this problem, we developed See-Star, a hydrogel-based tissue clearing protocol to render the bodies of opaque and calcified invertebrates optically transparent while preserving their anatomy in an unperturbed state, facilitating molecular labeling and observation of intact organ systems. The resulting protocol can clear large (> 1 cm3) specimens to enable deep-tissue imaging, and is compatible with molecular techniques, such as immunohistochemistry and in situ hybridization to visualize protein and mRNA localization. To test the utility of this method, we performed a whole-mount imaging study of intact nervous systems in juvenile echinoderms and molluscs and demonstrate that See-Star allows for comparative studies to be extended far into development, facilitating insights into the anatomy of juveniles and adults that are usually not amenable to whole-mount imaging.

Streamlined Full-Length Total RNA Sequencing of Paraformaldehyde-Fixed Brain Tissues

Paraformaldehyde (PFA) fixation is the preferred method for preserving tissue architecture for anatomical and pathological observations. Meanwhile, PFA reacts with the amine groups of biomolecules to form chemical cross-linking, which preserves RNA within the tissue. This has great prospects for RNA sequencing to characterize the molecular underpinnings after anatomical and pathological observations. However, RNA is inaccessible due to cross-linked adducts forming between RNA and other biomolecules in prolonged PFA-fixed tissue. It is also difficult to perform reverse transcription and PCR, resulting in low sequencing sensitivity and reduced reproducibility. Here, we developed a method to perform RNA sequencing in PFA-fixed tissue, which is easy to use, cost-effective, and allows efficient sample multiplexing. We employ cross-link reversal to recover RNA and library construction using random primers without artificial fragmentation. The yield and quality of recovered RNA significantly increased through our method, and sequencing quality metrics and detected genes did not show any major differences compared with matched fresh samples. Moreover, we applied our method for gene expression analysis in different regions of the mouse brain and identified unique gene expression profiles with varied functional implications. We also find significant dysregulation of genes involved in Alzheimer's disease (AD) pathogenesis within the medial septum (MS)/vertical diagonal band of Broca (VDB) of the 5×FAD mouse brain. Our method can thus increase the performance of high-throughput RNA sequencing with PFA-fixed samples and allows longitudinal studies of small tissue regions isolated by their in situ context.

Decoding the tumor microenvironment with spatial technologies

Visualization of the cellular heterogeneity and spatial architecture of the tumor microenvironment (TME) is becoming increasingly important to understand mechanisms of disease progression and therapeutic response. This is particularly relevant in the era of cancer immunotherapy, in which the contexture of immune cell positioning within the tumor landscape has been proven to affect efficacy. Although single-cell technologies have mostly replaced conventional approaches to analyze specific cellular subsets within tumors, those that integrate a spatial dimension are now on the rise. In this Review, we assess the strengths and limitations of emerging spatial technologies with a focus on their applications in tumor immunology, as well as forthcoming opportunities for artificial intelligence (AI) and the value of integrating multiomics datasets to achieve a holistic picture of the TME.

AutoUnmix: an autoencoder-based spectral unmixing method for multi-color fluorescence microscopy imaging

Multiplexed fluorescence microscopy imaging is widely used in biomedical applications. However, simultaneous imaging of multiple fluorophores can result in spectral leaks and overlapping, which greatly degrades image quality and subsequent analysis. Existing popular spectral unmixing methods are mainly based on computational intensive linear models, and the performance is heavily dependent on the reference spectra, which may greatly preclude its further applications. In this paper, we propose a deep learning-based blindly spectral unmixing method, termed AutoUnmix, to imitate the physical spectral mixing process. A transfer learning framework is further devised to allow our AutoUnmix to adapt to a variety of imaging systems without retraining the network. Our proposed method has demonstrated real-time unmixing capabilities, surpassing existing methods by up to 100-fold in terms of unmixing speed. We further validate the reconstruction performance on both synthetic datasets and biological samples. The unmixing results of AutoUnmix achieve the highest SSIM of 0.99 in both three- and four-color imaging, with nearly up to 20% higher than other popular unmixing methods. For experiments where spectral profiles and morphology are akin to simulated data, our method realizes the quantitative performance demonstrated above. Due to the desirable property of data independency and superior blind unmixing performance, we believe AutoUnmix is a powerful tool for studying the interaction process of different organelles labeled by multiple fluorophores.

Understanding spatiotemporal coupling of gene expression using single molecule RNA imaging technologies

Across all kingdoms of life, gene regulatory mechanisms underlie cellular adaptation to ever-changing environments. Regulation of gene expression adjusts protein synthesis and, in turn, cellular growth. Messenger RNAs are key molecules in the process of gene expression. Our ability to quantitatively measure mRNA expression in single cells has improved tremendously over the past decades. This revealed an unexpected coordination between the steps that control the life of an mRNA, from transcription to degradation. Here, we provide an overview of the state-of-the-art imaging approaches for measurement and quantitative understanding of gene expression, starting from the early visualizations of single genes by electron microscopy to current fluorescence-based approaches in single cells, including live-cell RNA-imaging approaches to FISH-based spatial transcriptomics across model organisms. We also highlight how these methods have shaped our current understanding of the spatiotemporal coupling between transcriptional and post-transcriptional events in prokaryotes. We conclude by discussing future challenges of this multidisciplinary field.Abbreviations: mRNA: messenger RNA; rRNA: ribosomal rDNA; tRNA: transfer RNA; sRNA: small RNA; FISH: fluorescence in situ hybridization; RNP: ribonucleoprotein; smFISH: single RNA molecule FISH; smiFISH: single molecule inexpensive FISH; HCR-FISH: Hybridization Chain-Reaction-FISH; RCA: Rolling Circle Amplification; seqFISH: Sequential FISH; MERFISH: Multiplexed error robust FISH; UTR: Untranslated region; RBP: RNA binding protein; FP: fluorescent protein; eGFP: enhanced GFP, MCP: MS2 coat protein; PCP: PP7 coat protein; MB: Molecular beacons; sgRNA: single guide RNA.

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.

TSA-PACT: a method for tissue clearing and immunofluorescence staining on zebrafish brain with improved sensitivity, specificity and stability

For comprehensive studies of the brain structure and function, fluorescence imaging of the whole brain is essential. It requires large-scale volumetric imaging in cellular or molecular resolution, which could be quite challenging. Recent advances in tissue clearing technology (e.g. CLARITY, PACT) provide new solutions by homogenizing the refractive index of the samples to create transparency. However, it has been difficult to acquire high quality results through immunofluorescence (IF) staining on the cleared samples. To address this issue, we developed TSA-PACT, a method combining tyramide signal amplification (TSA) and PACT, to transform samples into hydrogel polymerization frameworks with covalent fluorescent biomarkers assembled. We show that TSA-PACT is able to reduce the opacity of the zebrafish brain by more than 90% with well-preserved structure. Compared to traditional method, TSA-PACT achieves approximately tenfold signal amplification and twofold improvement in signal-to-noise ratio (SNR). Moreover, both the structure and the fluorescent signal persist for at least 16 months with excellent signal retention ratio. Overall, this method improves immunofluorescence signal sensitivity, specificity and stability in the whole brain of juvenile and adult zebrafish, which is applicable for fine structural analysis, neural circuit mapping and three-dimensional cell counting.

European Society of Toxicologic Pathology (Pathology 2.0 Molecular Pathology Special Interest Group): Review of In Situ Hybridization Techniques for Drug Research and Development

In situ hybridization (ISH) is used for the localization of specific nucleic acid sequences in cells or tissues by complementary binding of a nucleotide probe to a specific target nucleic acid sequence. In the last years, the specificity and sensitivity of ISH assays were improved by innovative techniques like synthetic nucleic acids and tandem oligonucleotide probes combined with signal amplification methods like branched DNA, hybridization chain reaction and tyramide signal amplification. These improvements increased the application spectrum for ISH on formalin-fixed paraffin-embedded tissues. ISH is a powerful tool to investigate DNA, mRNA transcripts, regulatory noncoding RNA, and therapeutic oligonucleotides. ISH can be used to obtain spatial information of a cell type, subcellular localization, or expression levels of targets. Since immunohistochemistry and ISH share similar workflows, their combination can address simultaneous transcriptomics and proteomics questions. The goal of this review paper is to revisit the current state of the scientific approaches in ISH and its application in drug research and development.

Tissue clearing and immunostaining to visualize the spatial organization of vasculature and tumor cells in mouse liver

The liver has a complex and hierarchical segmental organization of arteries, portal veins, hepatic veins and lymphatic vessels. In-depth imaging of liver vasculature and malignancies could improve knowledge on tumor micro-environment, local tumor growth, invasion, as well as metastasis. Non-invasive imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI) and positron-emission transmission (PET) are routine for clinical imaging, but show inadequate resolution at cellular and subcellular level. In recent years, tissue clearing – a technique rendering tissues optically transparent allowing enhanced microscopy imaging – has made great advances. While mainly used in the neurobiology field, recently more studies have used clearing techniques for imaging other organ systems as well as tumor tissues. In this study, our aim was to develop a reproducible tissue clearing and immunostaining model for visualizing intrahepatic blood microvasculature and tumor cells in murine colorectal liver metastases. CLARITY and 3DISCO/iDISCO+ are two established clearing methods that have been shown to be compatible with immunolabelling, most often in neurobiology research. In this study, CLARITY unfortunately resulted in damaged tissue integrity of the murine liver lobes and no specific immunostaining. Using the 3DISCO/iDISCO+ method, liver samples were successfully rendered optically transparent. After which, successful immunostaining of the intrahepatic microvasculature using panendothelial cell antigen MECA-32 and colorectal cancer cells using epithelial cell adhesion molecule (EpCAM) was established. This approach for tumor micro-environment tissue clearing would be especially valuable for allowing visualization of spatial heterogeneity and complex interactions of tumor cells and their environment in future studies.

A multi-view latent variable model reveals cellular heterogeneity in complex tissues for paired multimodal single-cell data

MOTIVATION

Single-cell multimodal assays allow us to simultaneously measure two different molecular features of the same cell, enabling new insights into cellular heterogeneity, cell development and diseases. However, most existing methods suffer from inaccurate dimensionality reduction for the joint-modality data, hindering their discovery of novel or rare cell subpopulations.

RESULTS

Here, we present VIMCCA, a computational framework based on variational-assisted multi-view canonical correlation analysis to integrate paired multimodal single-cell data. Our statistical model uses a common latent variable to interpret the common source of variances in two different data modalities. Our approach jointly learns an inference model and two modality-specific non-linear models by leveraging variational inference and deep learning. We perform VIMCCA and compare it with 10 existing state-of-the-art algorithms on four paired multi-modal datasets sequenced by different protocols. Results demonstrate that VIMCCA facilitates integrating various types of joint-modality data, thus leading to more reliable and accurate downstream analysis. VIMCCA improves our ability to identify novel or rare cell subtypes compared to existing widely used methods. Besides, it can also facilitate inferring cell lineage based on joint-modality profiles.

AVAILABILITY AND IMPLEMENTATION

The VIMCCA algorithm has been implemented in our toolkit package scbean (≥0.5.0), and its code has been archived at https://github.com/jhu99/scbean under MIT license.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Network Neuroscience Untethered: Brain-Wide Immediate Early Gene Expression for the Analysis of Functional Connectivity in Freely Behaving Animals

Studying how spatially discrete neuroanatomical regions across the brain interact is critical to advancing our understanding of the brain. Traditional neuroimaging techniques have led to many important discoveries about the nature of these interactions, termed functional connectivity. However, in animal models these traditional neuroimaging techniques have generally been limited to anesthetized or head-fixed setups or examination of small subsets of neuroanatomical regions. Using the brain-wide expression density of immediate early genes (IEG), we can assess brain-wide functional connectivity underlying a wide variety of behavioural tasks in freely behaving animal models. Here, we provide an overview of the necessary steps required to perform IEG-based analyses of functional connectivity. We also outline important considerations when designing such experiments and demonstrate the implications of these considerations using an IEG-based network dataset generated for the purpose of this review.

biPACT: A method for three-dimensional visualization of mouse spinal cord circuits of long segments with high resolution

BACKGROUND

The spatial complexity of neuronal circuits in the central nervous system is a hurdle in understanding and treating brain and spinal cord injury (SCI). Although several methods have recently been developed to render the spinal cord transparent and label specific neural circuits, three-dimensional visualization of long segments of spinal cord with high resolution remains challenging for SCI researchers.

NEW METHOD

We present a method that combines tissue staining of neuronal tracts traced with biotinylated dextran amine (BDA) and a modified passive clarity clearing protocol to describe individual fibers in long segments of mouse spinal cord.

RESULTS

Corticospinal tract was traced with BDA with a mouse model of thoracic spinal cord injury. The spinal cord was stained and cleared in two weeks with four solutions: staining solution, hydrogel solution, clearing solution, and observation solution. The samples were observed with a light-sheet microscope, and three-dimensional reconstruction was performed with ImageJ software. High resolution-images comparable with tissue sections were obtained continuously and circumferentially. By tiling, it was possible to obtain high-resolution images of long segments of the spinal cord. The tissue could be easily re-stained in case of fading.

COMPARISON WITH EXISTING METHODS

The present method does not require special equipment such as vacuum devices, can label specific circuits without genetic technology, and re-staining rounds can be easily implemented.

CONCLUSIONS

By using simple neural staining and clearing methods, it was possible to acquire a wide range of high-resolution three-dimensional images of the spinal cord.

A transcriptomic axis predicts state modulation of cortical interneurons

Transcriptomics has revealed that cortical inhibitory neurons exhibit a great diversity of fine molecular subtypes^1-6, but it is not known whether these subtypes have correspondingly diverse patterns of activity in the living brain. Here we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, which are organized by a single factor: position along the main axis of transcriptomic variation. We combined in vivo two-photon calcium imaging of mouse V1 with a transcriptomic method to identify mRNA for 72 selected genes in ex vivo slices. We classified inhibitory neurons imaged in layers 1-3 into a three-level hierarchy of 5 subclasses, 11 types and 35 subtypes using previously defined transcriptomic clusters³. Responses to visual stimuli differed significantly only between subclasses, with cells in the Sncg subclass uniformly suppressed, and cells in the other subclasses predominantly excited. Modulation by brain state differed at all hierarchical levels but could be largely predicted from the first transcriptomic principal component, which also predicted correlations with simultaneously recorded cells. Inhibitory subtypes that fired more in resting, oscillatory brain states had a smaller fraction of their axonal projections in layer 1, narrower spikes, lower input resistance and weaker adaptation as determined in vitro⁷, and expressed more inhibitory cholinergic receptors. Subtypes that fired more during arousal had the opposite properties. Thus, a simple principle may largely explain how diverse inhibitory V1 subtypes shape state-dependent cortical processing.

Hybridisation chain reaction-based visualisation and screening for lncRNA profiles in clear-cell renal-cell carcinoma

BACKGROUND

Analysis of long noncoding RNA (lncRNA) localisation at both the tissue and subcellular levels can provide important insights into the cell types that are important for their function.

METHODS

By applying new fluorescent in situ hybridisation technique called hybridisation chain reaction (HCR), we achieved a high-throughput lncRNA visualisation and evaluation of clinical samples.

RESULTS

Assessing 1728 pairs of 16 lncRNAs and clear-cell renal-cell carcinoma (ccRCC) specimens, three lncRNAs (TUG1, HOTAIR and CDKN2B-AS1) were associated with ccRCC prognosis. Furthermore, we derived a new lncRNA risk group of ccRCC prognosis by combining the expression levels of these three lncRNAs. Examining genomic alterations underlying this classification revealed prominent features of tumours that could serve as potential biomarkers for targeting lncRNAs. We then derived combination of HCR with expansion microscopy and visualised nanoscale-resolution HCR signals in cell nuclei, uncovering intracellular colocalization of three lncRNA (TUG1, HOTAIR and CDKN2B-AS1) signals such as those located intra- or out of the nucleus or nucleolus in cancer cells.

CONCLUSION

LncRNAs are expected to be desirable noncoding targets for cancer diagnosis or treatments. HCR involves plural probes consisting of small DNA oligonucleotides, clinically enabling us to detect cancerous lncRNA signals simply and rapidly at a lower cost.

In situ identification of cellular drug targets in mammalian tissue

The lack of tools to observe drug-target interactions at cellular resolution in intact tissue has been a major barrier to understanding in vivo drug actions. Here, we develop clearing-assisted tissue click chemistry (CATCH) to optically image covalent drug targets in intact mammalian tissues. CATCH permits specific and robust in situ fluorescence imaging of target-bound drug molecules at subcellular resolution and enables the identification of target cell types. Using well-established inhibitors of endocannabinoid hydrolases and monoamine oxidases, direct or competitive CATCH not only reveals distinct anatomical distributions and predominant cell targets of different drug compounds in the mouse brain but also uncovers unexpected differences in drug engagement across and within brain regions, reflecting rare cell types, as well as dose-dependent target shifts across tissue, cellular, and subcellular compartments that are not accessible by conventional methods. CATCH represents a valuable platform for visualizing in vivo interactions of small molecules in tissue.

PICASSO allows ultra-multiplexed fluorescence imaging of spatially overlapping proteins without reference spectra measurements

Ultra-multiplexed fluorescence imaging requires the use of spectrally overlapping fluorophores to label proteins and then to unmix the images of the fluorophores. However, doing this remains a challenge, especially in highly heterogeneous specimens, such as the brain, owing to the high degree of variation in the emission spectra of fluorophores in such specimens. Here, we propose PICASSO, which enables more than 15-color imaging of spatially overlapping proteins in a single imaging round without using any reference emission spectra. PICASSO requires an equal number of images and fluorophores, which enables such advanced multiplexed imaging, even with bandpass filter-based microscopy. We show that PICASSO can be used to achieve strong multiplexing capability in diverse applications. By combining PICASSO with cyclic immunofluorescence staining, we achieve 45-color imaging of the mouse brain in three cycles. PICASSO provides a tool for multiplexed imaging with high accessibility and accuracy for a broad range of researchers.

Ultra-multiplexed fluorescence imaging is currently difficult. Here the authors report PICASSO which enables 15-colour imaging of spatially overlapping proteins in a single-round of imaging; they combine it with cyclic immunofluorescence to achieve 45-colour imaging of the mouse brain in 3 cycles.

Robust and sensitive in situ RNA detection using Yn-situ

We describe a cost-effective, highly sensitive, and quantitative method for in situ detection of RNA molecules in tissue sections. This method, dubbed Yn-situ, standing for Y-branched probe in situ hybridization, uses a single-strand DNA preamplifier with multiple initiation sites that trigger a hybridization chain reaction (HCR) to detect polynucleotides. By characterizing the performance of this method, we show that the Yn-situ method, in conjunction with an improved fixation step, is sensitive enough to allow detection of RNA molecules using fewer probes targeting short nucleotide sequences than existing methods. A set of five probes can produce quantitative results with smaller puncta and higher signal-to-noise ratio than the 20-probe sets commonly required for HCR and RNAscope. We show that the high sensitivity and wide dynamic range allow quantification of genes expressed at different levels in the olfactory sensory neurons. We describe key steps of this method to enable broad utility by individual laboratories.

Quantitative intracellular retention of delivered RNAs through optimized cell fixation and immunostaining

Detection of nucleic acids within subcellular compartments is key to understanding their function. Determining the intracellular distribution of nucleic acids requires quantitative retention and estimation of their association with different organelles by immunofluorescence microscopy. This is particularly important for the delivery of nucleic acid therapeutics, which depends on endocytic uptake and endosomal escape. However, the current protocols fail to preserve the majority of exogenously delivered nucleic acids in the cytoplasm. To solve this problem, by monitoring Cy5-labeled mRNA delivered to primary human adipocytes via lipid nanoparticles (LNP), we optimized cell fixation, permeabilization, and immunostaining of a number of organelle markers, achieving quantitative retention of mRNA and allowing visualization of levels that escape detection using conventional procedures. The optimized protocol proved effective on exogenously delivered siRNA, miRNA, as well as endogenous miRNA. Our protocol is compatible with RNA probes of single molecule fluorescence in situ hybridization (smFISH) and molecular beacon, thus demonstrating that it is broadly applicable to study a variety of nucleic acids in cultured cells.

Advanced Technologies for Local Neural Circuits in the Cerebral Cortex

The neural network in the brain can be viewed as an integrated system assembled from a large number of local neural circuits specialized for particular brain functions. Activities of neurons in local neural circuits are thought to be organized both spatially and temporally under the rules optimized for their roles in information processing. It is well perceived that different areas of the mammalian neocortex have specific cognitive functions and distinct computational properties. However, the organizational principles of the local neural circuits in different cortical regions have not yet been clarified. Therefore, new research principles and related neuro-technologies that enable efficient and precise recording of large-scale neuronal activities and synaptic connections are necessary. Innovative technologies for structural analysis, including tissue clearing and expansion microscopy, have enabled super resolution imaging of the neural circuits containing thousands of neurons at a single synapse resolution. The imaging resolution and volume achieved by new technologies are beyond the limits of conventional light or electron microscopic methods. Progress in genome editing and related technologies has made it possible to label and manipulate specific cell types and discriminate activities of multiple cell types. These technologies will provide a breakthrough for multiscale analysis of the structure and function of local neural circuits. This review summarizes the basic concepts and practical applications of the emerging technologies and new insight into local neural circuits obtained by these technologies.

Tissue clearing to examine tumour complexity in three dimensions

The visualization of whole organs and organisms through tissue clearing and fluorescence volumetric imaging has revolutionized the way we look at biological samples. Its application to solid tumours is changing our perception of tumour architecture, revealing signalling networks and cell interactions critical in tumour progression, and provides a powerful new strategy for cancer diagnostics. This Review introduces the latest advances in tissue clearing and three-dimensional imaging, examines the challenges in clearing epithelia - the tissue of origin of most malignancies - and discusses the insights that tissue clearing has brought to cancer research, as well as the prospective applications to experimental and clinical oncology.

Adaptation and genomic erosion in fragmented Pseudomonas aeruginosa populations in the sinuses of people with cystic fibrosis

Pseudomonas aeruginosa notoriously adapts to the airways of people with cystic fibrosis (CF), yet how infection-site biogeography and associated evolutionary processes vary as lifelong infections progress remains unclear. Here we test the hypothesis that early adaptations promoting aggregation influence evolutionary-genetic trajectories by examining longitudinal P. aeruginosa from the sinuses of six adults with CF. Highly host-adapted lineages harbored mutator genotypes displaying signatures of early genome degradation associated with recent host restriction. Using an advanced imaging technique (MiPACT-HCR [microbial identification after passive clarity technique]), we find population structure tracks with genome degradation, with the most host-adapted, genome-degraded P. aeruginosa (the mutators) residing in small, sparse aggregates. We propose that following initial adaptive evolution in larger populations under strong selection for aggregation, P. aeruginosa persists in small, fragmented populations that experience stronger effects of genetic drift. These conditions enrich for mutators and promote degenerative genome evolution. Our findings underscore the importance of infection-site biogeography to pathogen evolution.

A roadmap for the Human Developmental Cell Atlas

The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development.

Tissue clearing and 3D imaging - putting immune cells into context

A better understanding of cell-cell and cell-niche interactions is crucial to comprehend the complexity of inflammatory or pathophysiological scenarios such as tissue damage during viral infections, the tumour microenvironment and neuroinflammation. Optical clearing and 3D volumetric imaging of large tissue pieces or whole organs is a rapidly developing methodology that holds great promise for the in-depth study of cells in their natural surroundings. These methods have mostly been applied to image structural components such as endothelial cells and neuronal architecture. Recent work now highlights the possibility of studying immune cells in detail within their respective immune niches. This Review summarizes recent developments in tissue clearing methods and 3D imaging, with a focus on the localization and quantification of immune cells. We first provide background to the optical challenges involved and their solutions before discussing published protocols for tissue clearing, the limitations of 3D imaging of immune cells and image analysis. Furthermore, we highlight possible applications for tissue clearing and propose future developments for the analysis of immune cells within homeostatic or inflammatory immune niches.

Basic principles of hydrogel-based tissue transformation technologies and their applications

Emerging tissue transformation technologies provide an unprecedented opportunity to investigate system-level molecular and anatomical features in situ. Hydrogel-based methods engineer physicochemical tissue properties to render intact organs optically transparent and size and shape adjustable while preserving biomolecules at their physiological locations. When combined with advanced molecular tools, labeling, and imaging techniques, tissue transformation enables three-dimensional (3D) mapping of molecules, cells, and their interrelationships at increasing speeds and resolutions. In this review, we discuss the basic engineering principles of tissue transformation and labeling techniques as well as their broad applications, current challenges, and future potential.

Progress towards a cellularly resolved mouse mesoconnectome is empowered by data fusion and new neuroanatomy techniques

Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for instance, allow us to study the role of circuit motifs in cognitive processes. In this work, we review advanced neuroanatomical and data fusion techniques within the context of a proposed Multimodal Connectomic Integration Framework for augmenting the cellularly resolved mouse mesoconnectome. First, we emphasize the importance of registering data modalities to a common reference atlas. We then review a number of novel experimental techniques that can provide data for characterizing cell-types in the mouse brain. Furthermore, we examine a number of data integration strategies, which involve fine-grained cell-type classification, spatial inference of cell densities, latent variable models for the mesoconnectome and multi-modal factorisation. Finally, we discuss a number of use cases which depend on connectome augmentation techniques, such as model simulations of functional connectivity and generating mechanistic hypotheses for animal disease models.

Tissue Optical Clearing for Biomedical Imaging: From In Vitro to In Vivo

Tissue optical clearing technique provides a prospective solution for the application of advanced optical methods in life sciences. This chapter firstly gives a brief introduction to mechanisms of tissue optical clearing techniques, from the physical mechanism to chemical mechanism, which is the most important foundation to develop tissue optical clearing methods. During the past years, in vitro and in vivo tissue optical clearing methods were developed. In vitro tissue optical clearing techniques, including the solvent-based clearing methods and the hydrophilic reagents-based clearing methods, combined with labeling technique and advanced microscopy, can be applied to image 3D microstructure of tissue blocks or whole organs such as brain and spinal cord with high resolution. In vivo skin or skull optical clearing, promise various optical imaging techniques to detect cutaneous or cortical cell and vascular structure and function without surgical window.

Tissue clearing techniques for three-dimensional optical imaging of intact human prostate and correlations with multi-parametric MRI

BACKGROUND

Tissue clearing technologies have enabled remarkable advancements for in situ characterization of tissues and exploration of the three-dimensional (3D) relationships between cells, however, these studies have predominantly been performed in non-human tissues and correlative assessment with clinical imaging has yet to be explored. We sought to evaluate the feasibility of tissue clearing technologies for 3D imaging of intact human prostate and the mapping of structurally and molecularly preserved pathology data with multi-parametric volumetric MR imaging (mpMRI).

METHODS

Whole-mount prostates were processed with either hydrogel-based CLARITY or solvent-based iDISCO. The samples were stained with a nuclear dye or fluorescently labeled with antibodies against androgen receptor, alpha-methylacyl coenzyme-A racemase, or p63, and then imaged with 3D confocal microscopy. The apparent diffusion coefficient and K^trans maps were computed from preoperative mpMRI.

RESULTS

Quantitative analysis of cleared normal and tumor prostate tissue volumes displayed differences in 3D tissue architecture, marker-specific cell staining, and cell densities that were significantly correlated with mpMRI measurements in this initial, pilot cohort.

CONCLUSIONS

3D imaging of human prostate volumes following tissue clearing is a feasible technique for quantitative radiology-pathology correlation analysis with mpMRI and provides an opportunity to explore functional relationships between cellular structures and cross-sectional clinical imaging.

Three-Dimensional Imaging in Stem Cell-Based Researches

Stem cells have an important role in regenerative therapies, developmental biology studies and drug screening. Basic and translational research in stem cell technology needs more detailed imaging techniques. The possibility of cell-based therapeutic strategies has been validated in the stem cell field over recent years, a more detailed characterization of the properties of stem cells is needed for connectomics of large assemblies and structural analyses of these cells. The aim of stem cell imaging is the characterization of differentiation state, cellular function, purity and cell location. Recent progress in stem cell imaging field has included ultrasound-based technique to study living stem cells and florescence microscopy-based technique to investigate stem cell three-dimensional (3D) structures. Here, we summarized the fundamental characteristics of stem cells via 3D imaging methods and also discussed the emerging literatures on 3D imaging in stem cell research and the applications of both classical 2D imaging techniques and 3D methods on stem cells biology.

Deficient spermiogenesis in mice lacking Rlim

The X-linked gene Rlim plays major roles in female mouse development and reproduction, where it is crucial for the maintenance of imprinted X chromosome inactivation in extraembryonic tissues of embryos. However, while females carrying a systemic Rlim knockout (KO) die around implantation, male Rlim KO mice appear healthy and are fertile. Here, we report an important role for Rlim in testis where it is highly expressed in post-meiotic round spermatids as well as in Sertoli cells. Systemic deletion of the Rlim gene results in lower numbers of mature sperm that contains excess cytoplasm, leading to decreased sperm motility and in vitro fertilization rates. Targeting the conditional Rlim cKO specifically to the spermatogenic cell lineage largely recapitulates this phenotype. These results reveal functions of Rlim in male reproduction specifically in round spermatids during spermiogenesis.

Tissue clearing technique: Recent progress and biomedical applications

Organisms are inherently three dimensional, thus comprehensive understanding of the complicated biological system requires analysis of organs or even whole bodies in the context of three dimensions. However, this is a tremendous task since the biological specimens are naturally opaque, a major obstacle in whole-body and whole-organ imaging. Tissue clearing technique provides a prospective solution and has become a powerful tool for three-dimensional imaging and quantification of organisms. Tissue clearing technique aims to make tissue transparent by minimizing light scattering and light absorption, thus allowing deep imaging of large volume samples. When combined with diverse molecular labeling methods and high-throughput optical sectioning microscopes, tissue clearing technique enables whole-body and whole-organ imaging at cellular or subcellular resolution, providing detailed and comprehensive information about the intact biological systems. Here, we give an overview of recent progress and biomedical applications of tissue clearing technique. We introduce the mechanisms and basic principles of tissue clearing, and summarize the current tissue clearing methods. Moreover, the available imaging techniques and software packages for data processing are also presented. Finally, we introduce the recent advances in applications of tissue clearing in biomedical fields. Tissue clearing contributes to the investigation of structure-function relationships in intact mammalian organs, and opens new avenues for cellular and molecular mapping of intact human organs. We hope this review contributes to a better understanding of tissue clearing technique and can help researchers to select the best-suited clearing protocol for their experiments.

Current Status of Tissue Clearing and the Path Forward in Neuroscience

Due to the complexity and limited availability of human brain tissues, for decades, pathologists have sought to maximize information gained from individual samples, based on which (patho)physiological processes could be inferred. Recently, new understandings of chemical and physical properties of biological tissues and multiple chemical profiling have given rise to the development of scalable tissue clearing methods allowing superior optical clearing of across-the-scale samples. In the past decade, tissue clearing techniques, molecular labeling methods, advanced laser scanning microscopes, and data visualization and analysis have become commonplace. Combined, they have made 3D visualization of brain tissues with unprecedented resolution and depth widely accessible. To facilitate further advancements and applications, here we provide a critical appraisal of these techniques. We propose a classification system of current tissue clearing and expansion methods that allows users to judge the applicability of individual ones to their questions, followed by a review of the current progress in molecular labeling, optical imaging, and data processing to demonstrate the whole 3D imaging pipeline based on tissue clearing and downstream techniques for visualizing the brain. We also raise the path forward of tissue-clearing-based imaging technology, that is, integrating with state-of-the-art techniques, such as multiplexing protein imaging, in situ signal amplification, RNA detection and sequencing, super-resolution imaging techniques, multiomics studies, and deep learning, for drawing the complete atlas of the human brain and building a 3D pathology platform for central nervous system disorders.

Optimization and evaluation of fluorescence in situ hybridization chain reaction in cleared fresh-frozen brain tissues

Transcript labeling in intact tissues using in situ hybridization chain reaction has potential to provide vital spatiotemporal information for molecular characterization of heterogeneous neuronal populations. However, large tissue labeling in non-perfused or fresh-frozen rodent and postmortem human samples, which provide more flexible utilization than perfused tissues, is largely unexplored. In the present study, we optimized the combination of in situ hybridization chain reaction in fresh-frozen rodent brains and then evaluated the uniformity of neuronal labeling between two clearing methods, CLARITY and iDISCO⁺. We found that CLARITY yielded higher signal-to-noise ratios but more limited imaging depth and required longer clearing times, whereas, iDISCO⁺ resulted in better tissue clearing, greater imaging depth and a more uniform labeling of larger samples. Based on these results, we used iDISCO⁺-cleared fresh-frozen rodent brains to further validate this combination and map the expression of a few genes of interest pertaining to mood disorders. We then examined the potential of in situ hybridization chain reaction to label transcripts in cleared postmortem human brain tissues. The combination failed to produce adequate mRNA labeling in postmortem human cortical slices but produced visually adequate labeling in the cerebellum tissues. We next, investigated the multiplexing ability of in situ hybridization chain reaction in cleared tissues which revealed inconsistent fluorescence output depending upon the fluorophore conjugated to the hairpins. Finally, we applied our optimized protocol to assess the effect of glucocorticoid receptor overexpression on basal somatostatin expression in the mouse cortex. The constitutive glucocorticoid receptor overexpression resulted in lower number density of somatostatin-expressing neurons compared to wild type. Overall, the combination of in situ hybridization chain reaction with clearing methods, especially iDISCO⁺, may find broad application in the transcript analysis in rodent studies, but its limited use in postmortem human tissues can be improved by further optimizations.

Optical Tissue Clearing: Illuminating Brain Function and Dysfunction

Tissue optical clearing technology has been developing rapidly in the past decade due to advances in microscopy equipment and various labeling techniques. Consistent modification of primary methods for optical tissue transparency has allowed observation of the whole mouse body at single-cell resolution or thick tissue slices at the nanoscale level, with the final aim to make intact primate and human brains or thick human brain tissues optically transparent. Optical clearance combined with flexible large-volume tissue labeling technology can not only preserve the anatomical structure but also visualize multiple molecular information from intact samples in situ. It also provides a new strategy for studying complex tissues, which is of great significance for deciphering the functional structure of healthy brains and the mechanisms of neurological pathologies. In this review, we briefly introduce the existing optical clearing technology and discuss its application in deciphering connection and structure, brain development, and brain diseases. Besides, we discuss the standard computational analysis tools for large-scale imaging dataset processing and information extraction. In general, we hope that this review will provide a valuable reference for researchers who intend to use optical clearing technology in studying the brain.

Specific detection and determination of cysteine by a luminescent samarium macrocycle-based fluorescent probe platform

A samarium macrocycle-based chemosensor bearing two imine bonds and a Sm(iii) emitter provides an indirect approach to detect and determine cysteine.

Tissue Clearing and Expansion Methods for Imaging Brain Pathology in Neurodegeneration: From Circuits to Synapses and Beyond

Studying the structural alterations occurring during diseases of the nervous system requires imaging heterogeneous cell populations at the circuit, cellular and subcellular levels. Recent advancements in brain tissue clearing and expansion methods allow unprecedented detailed imaging of the nervous system through its entire scale, from circuits to synapses, including neurovascular and brain lymphatics elements. Here, we review the state-of-the-art of brain tissue clearing and expansion methods, mentioning their main advantages and limitations, and suggest their parallel implementation for circuits-to-synapses brain imaging using conventional (diffraction-limited) light microscopy -such as confocal, two-photon and light-sheet microscopy- to interrogate the cellular and molecular basis of neurodegenerative diseases. We discuss recent studies in which clearing and expansion methods have been successfully applied to study neuropathological processes in mouse models and postmortem human brain tissue. Volumetric imaging of cleared intact mouse brains and large human brain samples has allowed unbiased assessment of neuropathological hallmarks. In contrast, nanoscale imaging of expanded cells and brain tissue has been used to study the effect of protein aggregates on specific subcellular structures. Therefore, these approaches can be readily applied to study a wide range of brain processes and pathological mechanisms with cellular and subcellular resolution in a time- and cost-efficient manner. We consider that a broader implementation of these technologies is necessary to reveal the full landscape of cellular and molecular mechanisms underlying neurodegenerative diseases.

Three-dimensional single-cell imaging for the analysis of RNA and protein expression in intact tumour biopsies

Microscopy analysis of tumour samples is commonly performed on fixed, thinly sectioned and protein-labelled tissues. However, these examinations do not reveal the intricate three-dimensional structures of tumours, nor enable the detection of aberrant transcripts. Here, we report a method, which we name DIIFCO (for diagnosing in situ immunofluorescence-labelled cleared oncosamples), for the multimodal volumetric imaging of RNAs and proteins in intact tumour volumes and organoids. We used DIIFCO to spatially profile the expression of diverse coding RNAs and non-coding RNAs at the single-cell resolution in a variety of cancer tissues. Quantitative single-cell analysis revealed spatial niches of cancer stem-like cells, and showed that the niches were present at a higher density in triple-negative breast cancer tissue. The improved molecular phenotyping and histopathological diagnosis of cancers may lead to new insights into the biology of tumours of patients.

dotdotdot: an automated approach to quantify multiplex single molecule fluorescent in situ hybridization (smFISH) images in complex tissues

Multiplex single-molecule fluorescent in situ hybridization (smFISH) is a powerful method for validating RNA sequencing and emerging spatial transcriptomic data, but quantification remains a computational challenge. We present a framework for generating and analyzing smFISH data in complex tissues while overcoming autofluorescence and increasing multiplexing capacity. We developed dotdotdot (https://github.com/LieberInstitute/dotdotdot) as a corresponding software package to quantify RNA transcripts in single nuclei and perform differential expression analysis. We first demonstrate robustness of our platform in single mouse neurons by quantifying differential expression of activity-regulated genes. We then quantify spatial gene expression in human dorsolateral prefrontal cortex (DLPFC) using spectral imaging and dotdotdot to mask lipofuscin autofluorescence. We lastly apply machine learning to predict cell types and perform downstream cell type-specific expression analysis. In summary, we provide experimental workflows, imaging acquisition and analytic strategies for quantification and biological interpretation of smFISH data in complex tissues.

Uncovering an Organ's Molecular Architecture at Single-Cell Resolution by Spatially Resolved Transcriptomics

Revealing fine-scale cellular heterogeneity among spatial context and the functional and structural foundations of tissue architecture is fundamental within biological research and pharmacology. Unlike traditional approaches involving single molecules or bulk omics, cutting-edge, spatially resolved transcriptomics techniques offer near-single-cell or even subcellular resolution within tissues. Massive information across higher dimensions along with position-coordinating labels can better map the whole 3D transcriptional landscape of tissues. In this review, we focus on developments and strategies in spatially resolved transcriptomics, compare the cell and gene throughput and spatial resolution in detail for existing methods, and highlight the enormous potential in biomedical research.

Molecular atlas of the adult mouse brain

Brain maps are essential for integrating information and interpreting the structure-function relationship of circuits and behavior. We aimed to generate a systematic classification of the adult mouse brain based purely on the unbiased identification of spatially defining features by employing whole-brain spatial transcriptomics. We found that the molecular information was sufficient to deduce the complex and detailed neuroanatomical organization of the brain. The unsupervised (non-expert, data-driven) classification revealed new area- and layer-specific subregions, for example in isocortex and hippocampus, and new subdivisions of striatum. The molecular atlas further supports the characterization of the spatial identity of neurons from their single-cell RNA profile, and provides a resource for annotating the brain using a minimal gene set-a brain palette. In summary, we have established a molecular atlas to formally define the spatial organization of brain regions, including the molecular code for mapping and targeting of discrete neuroanatomical domains.

Elasticizing tissues for reversible shape transformation and accelerated molecular labeling

We developed entangled link-augmented stretchable tissue-hydrogel (ELAST), a technology that transforms tissues into elastic hydrogels to enhance macromolecular accessibility and mechanical stability simultaneously. ELASTicized tissues are highly stretchable and compressible, which enables reversible shape transformation and faster delivery of probes into intact tissue specimens via mechanical thinning. This universal platform may facilitate rapid and scalable molecular phenotyping of large-scale biological systems, such as human organs.

Whole-Brain Profiling of Cells and Circuits in Mammals by Tissue Clearing and Light-Sheet Microscopy

Tissue clearing and light-sheet microscopy have a 100-year-plus history, yet these fields have been combined only recently to facilitate novel experiments and measurements in neuroscience. Since tissue-clearing methods were first combined with modernized light-sheet microscopy a decade ago, the performance of both technologies has rapidly improved, broadening their applications. Here, we review the state of the art of tissue-clearing methods and light-sheet microscopy and discuss applications of these techniques in profiling cells and circuits in mice. We examine outstanding challenges and future opportunities for expanding these techniques to achieve brain-wide profiling of cells and circuits in primates and humans. Such integration will help provide a systems-level understanding of the physiology and pathology of our central nervous system.

Multiplex bioimaging of single-cell spatial profiles for precision cancer diagnostics and therapeutics

Cancers exhibit functional and structural diversity in distinct patients. In this mass, normal and malignant cells create tumor microenvironment that is heterogeneous among patients. A residue from primary tumors leaks into the bloodstream as cell clusters and single cells, providing clues about disease progression and therapeutic response. The complexity of these hierarchical microenvironments needs to be elucidated. Although tumors comprise ample cell types, the standard clinical technique is still the histology that is limited to a single marker. Multiplexed imaging technologies open new directions in pathology. Spatially resolved proteomic, genomic, and metabolic profiles of human cancers are now possible at the single-cell level. This perspective discusses spatial bioimaging methods to decipher the cascade of microenvironments in solid and liquid biopsies. A unique synthesis of top-down and bottom-up analysis methods is presented. Spatial multi-omics profiles can be tailored to precision oncology through artificial intelligence. Data-driven patient profiling enables personalized medicine and beyond.

Tissue clearing and its applications in neuroscience

State-of-the-art tissue-clearing methods provide subcellular-level optical access to intact tissues from individual organs and even to some entire mammals. When combined with light-sheet microscopy and automated approaches to image analysis, existing tissue-clearing methods can speed up and may reduce the cost of conventional histology by several orders of magnitude. In addition, tissue-clearing chemistry allows whole-organ antibody labelling, which can be applied even to thick human tissues. By combining the most powerful labelling, clearing, imaging and data-analysis tools, scientists are extracting structural and functional cellular and subcellular information on complex mammalian bodies and large human specimens at an accelerated pace. The rapid generation of terabyte-scale imaging data furthermore creates a high demand for efficient computational approaches that tackle challenges in large-scale data analysis and management. In this Review, we discuss how tissue-clearing methods could provide an unbiased, system-level view of mammalian bodies and human specimens and discuss future opportunities for the use of these methods in human neuroscience.

A rhodol-enone dye platform with dual reaction triggers for specific detection of Cys

In this work, we have developed a rhodol-enone dye platform with bis-reaction-triggers for the selective detection of Cys.

Expansion Microscopy: Scalable and Convenient Super-Resolution Microscopy

Expansion microscopy (ExM) is a physical form of magnification that increases the effective resolving power of any microscope. Here, we describe the fundamental principles of ExM, as well as how recently developed ExM variants build upon and apply those principles. We examine applications of ExM in cell and developmental biology for the study of nanoscale structures as well as ExM's potential for scalable mapping of nanoscale structures across large sample volumes. Finally, we explore how the unique anchoring and hydrogel embedding properties enable postexpansion molecular interrogation in a purified chemical environment. ExM promises to play an important role complementary to emerging live-cell imaging techniques, because of its relative ease of adoption and modification and its compatibility with tissue specimens up to at least 200 μm thick.