Probes for INS

Distinguishing different contexts is thought to involve a form of pattern separation that minimizes overlap between neural ensembles representing similar experiences. Theoretical models suggest that the dentate gyrus (DG) segregates cortical input patterns before relaying its discriminated output patterns to the CA3 hippocampal field. This suggests that the evaluation of neural ensembles in DG and CA3 could be an important means to investigate the process of pattern separation. In the past, measurement of entorhinal cortex (EC), DG, and CA3 ensembles was largely dependent upon in vivo electrophysiological recording, which is technically difficult. This protocol provides a method to instead measure pattern separation by a molecular method that provides direct spatial resolution at the cellular level.

Highly multiplexed protein and RNA in situ detection on a single tissue section concurrently is highly desirable for both basic and applied biomedical research. CO-detection by inDEXing (CODEX) is a new and powerful platform to visualize up to 60 protein biomarkers in situ, and RNAscope in situ hybridization (RNAscope) is a novel RNA detection system with high sensitivity and unprecedent specificity at a single-cell level. Nevertheless, to our knowledge, the combination of CODEX and RNAscope remained unreported until this study. Here, we report a simple and reproducible combination of CODEX and RNAscope. We also determined the cross-reactivities of CODEX anti-human antibodies to rhesus macaques, a widely used animal model of human disease.

Fluorescence in situ hybridization (FISH) is a useful tool for analyzing RNA expression, but difficulties arise with low-abundance RNA and in tissues that are formalin-fixed paraffin-embedded (FFPE) because reagents can be expensive. In this protocol, we adapt a previously designed FISH amplification protocol (SABER [signal amplification by exchange reaction]) for adult mouse FFPE lung sections by using probes that are extended and branched to amplify the signal. We combine FISH and immunostaining to identify cell-specific RNA. For complete details on the use and execution of this protocol, please refer to Kishi et al.1 and Lyu et al.2.

A patient's genome, Van Eyk noted, contains information about that patient's disease predispositions and drug responses. She added, however, that better information about disease risks and drug responses could be gleaned from the proteome. Although there are only so many protein-encoding genes, the intricacies of protein expression generate various kinds of proteomic information in abundance. According to Van Eyk, information about disease-induced modifications, isoforms, concentration changes, and chemical complexity can inform predictions of what will happen in the body, in the context of the body and the environment. She suggests that a proteomics approach—one that would involve monitoring of not just one protein at a time, but thousands—could generate valuable clinical insights.

Immunohistochemistry (IHC) is a consolidated technique for the identification of surface and cytoplasmic antigens in cells or tissue sections using specific antibodies, yet simultaneous detection of two markers on the same cell may be difficult to achieve. Here we develop a protocol to perform a double staining using RNAscope, a new in-situ hybridization (ISH) technology, to visualize perforin transcripts, and classical IHC to visualize either CD8 or TcRγδ positive intraepithelial lymphocytes (IELs) in small intestinal paraffin sections of celiac disease (CD) patients. This double assay will allow to investigate the cytotoxic properties of two subsets of IELs in different stages of CD, thus contributing to understand the events leading to tissue destruction and healing.

New imaging methodologies with high contrast and molecular specificity allow researchers to analyze dynamic processes in plant cells at multiple scales, from single protein and RNA molecules to organelles and cells, to whole organs and tissues. These techniques produce informative images and quantitative data on molecular dynamics to address questions that cannot be answered by conventional biochemical assays. Here, we review selected microscopy techniques, focusing on their basic principles and applications in plant science, discussing the pros and cons of each technique, and introducing methods for quantitative analysis. This review thus provides guidance for plant scientists in selecting the most appropriate techniques to decipher structures and dynamic processes at different levels, from protein dynamics to morphogenesis.

Background: The identification of differentially expressed genes and their associated biological processes, molecular function, and cellular components are important for genetic diseases studies because they present potential biomarkers and therapeutic targets. Methods: In this study, we developed an o²S²PARC template representing an interactive pipeline for the gene expression data visualization and ontologies data analysis and visualization.  To demonstrate the usefulness of the tool, we performed a case study on a publicly available dataset. Results: The tool enables users to identify the differentially expressed genes (DEGs) and visualize them in a volcano plot format. The ontologies associated with the DEGs are determined and visualized in barplots. Conclusions: The “Expression data visualization” template is publicly available on the o²S²PARC platform.

Here, we describe a protocol to visualize RNA oligos and proteins independently or together using a combination of fluorescence in situ hybridization (FISH) and immunofluorescence in human colonoids, expanding on previously published research. Whole-mount staining is used to preserve the colonoid structure and fix onto glass slides. We describe procedures for efficient plating, fixation, and preservation of the colonoids. This workflow can be adapted to 3D organoid models from other tissues or organisms. For complete details on the use and execution of this protocol, please refer to In et al. (2020).

Recent innovations in single-cell technologies have opened up exciting possibilities for profiling the omics of individual cells. Minimally invasive analysis tools that probe and remove the contents of living cells enable cells to remain in their standard microenvironment with little impact on their viability. This negates the requirement of lysing cells to access their contents, an advancement from previous single-cell manipulation methods. These novel methods have the potential to be used for dynamic studies on single cells, with many already providing high intracellular spatial resolution. In this article, we highlight key technological advances that aim to remove the contents of living cells for downstream analysis. Recent applications of these techniques are reviewed, along with their current limitations. We also propose recommendations for expanding the scope of these technologies to achieve comprehensive single-cell tracking in the future, anticipating the discovery of subcellular mechanisms and novel therapeutic targets and treatments, ultimately transforming the fields of spatial transcriptomics and personalised medicine.

Spatial gene expression, achieved classically through in situ hybridization, is a fundamental tool for topographic phenotyping of cell types in the nervous system. Newly developed techniques allow for visualization of multiple mRNAs at single-cell resolution and greatly expand the ability to link gene expression to tissue topography, yet there are challenges in efficient quantification and analysis of these high-dimensional datasets. We have therefore developed the single-cell automated multiplex pipeline for RNA (SCAMPR), facilitating rapid and accurate segmentation of neuronal cell bodies using a dual immunohistochemistry-RNAscope protocol and quantification of low- and high-abundance mRNA signals using open-source image processing and automated segmentation tools. Proof of principle using SCAMPR focused on spatial mapping of gene expression by peripheral (vagal nodose) and central (visual cortex) neurons. The analytical effectiveness of SCAMPR is demonstrated by identifying the impact of early life stress on gene expression in vagal neuron subtypes.

GenoLab M is a recently developed next-generation sequencing (NGS) platform from GeneMind Biosciences. To establish the performance of GenoLab M, we present the first report to benchmark and compare the WGS and WES sequencing data of the GenoLab M sequencer to NovaSeq 6000 and NextSeq 550 platform in various types of analysis. For WGS, thirty-fold sequencing from Illumina NovaSeq platform and processed by GATK pipeline is currently considered as the golden standard. Thus this dataset is generated as a benchmark reference in this study.GenoLab M showed an average of 94.62% of Q20 percentage for base quality, while the NovaSeq was slightly higher at 96.97%. However, GenoLab M outperformed NovaSeq or NextSeq at a duplication rate, suggesting more usable data after deduplication. For WGS short variant calling, GenoLab M showed significant accuracy improvement over the same depth dataset from NovaSeq, and reached similar accuracy to NovaSeq 33X dataset with 22x depth. For 100X WES, the F-score and Precision in GenoLab M were higher than NovaSeq or NextSeq, especially for InDel calling.GenoLab M is a promising NGS platform for high-performance WGS and WES applications. For WGS, 22X depth in the GenoLab M sequencing platform offers a cost-effective alternative to the current mainstream 33X depth on Illumina.

Single-cell RNA sequencing (scRNA-seq) approaches have transformed our ability to resolve cellular properties across systems, but are currently tailored toward large cell inputs (>1,000 cells). This renders them inefficient and costly when processing small, individual tissue samples, a problem that tends to be resolved by loading bulk samples, yielding confounded mosaic cell population read-outs. Here, we developed a deterministic, mRNA-capture bead and cell co-encapsulation dropleting system, DisCo, aimed at processing low-input samples (<500 cells). We demonstrate that DisCo enables precise particle and cell positioning and droplet sorting control through combined machine-vision and multilayer microfluidics, enabling continuous processing of low-input single-cell suspensions at high capture efficiency (>70%) and at speeds up to 350 cells per hour. To underscore DisCo's unique capabilities, we analyzed 31 individual intestinal organoids at varying developmental stages. This revealed extensive organoid heterogeneity, identifying distinct subtypes including a regenerative fetal-like Ly6a+ stem cell population that persists as symmetrical cysts, or spheroids, even under differentiation conditions, and an uncharacterized 'gobloid' subtype consisting predominantly of precursor and mature (Muc2+) goblet cells. To complement this dataset and to demonstrate DisCo's capacity to process low-input, in vivo-derived tissues, we also analyzed individual mouse intestinal crypts. This revealed the existence of crypts with a compositional similarity to spheroids, which consisted predominantly of regenerative stem cells, suggesting the existence of regenerating crypts in the homeostatic intestine. These findings demonstrate the unique power of DisCo in providing high-resolution snapshots of cellular heterogeneity in small, individual tissues.