Vandereyken, K;Sifrim, A;Thienpont, B;Voet, T;
PMID: 36864178 | DOI: 10.1038/s41576-023-00580-2
The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a decade, the field has seen tremendous technological revolutions that enable crucial new insights into the interplay between intracellular and intercellular molecular mechanisms that govern development, physiology and pathogenesis. In this Review, we highlight advances in the fast-developing field of single-cell and spatial multi-omics technologies (also known as multimodal omics approaches), and the computational strategies needed to integrate information across these molecular layers. We demonstrate their impact on fundamental cell biology and translational research, discuss current challenges and provide an outlook to the future.
Bennett, HM;Stephenson, W;Rose, CM;Darmanis, S;
PMID: 36864196 | DOI: 10.1038/s41592-023-01791-5
In the last decade, single-cell RNA sequencing routinely performed on large numbers of single cells has greatly advanced our understanding of the underlying heterogeneity of complex biological systems. Technological advances have also enabled protein measurements, further contributing to the elucidation of cell types and states present in complex tissues. Recently, there have been independent advances in mass spectrometric techniques bringing us one step closer to characterizing single-cell proteomes. Here we discuss the challenges of detecting proteins in single cells by both mass spectrometry and sequencing-based methods. We review the state of the art for these techniques and propose that there is a space for technological advancements and complementary approaches that maximize the advantages of both classes of technologies.
Methods in Molecular Biology
Scheiffele, P;Mauger, O;
| DOI: 10.1007/978-1-0716-2521-7
This detailed volume collects commonly used and cutting-edge methods to analyze alternative splicing, a key step in gene regulation. After an introduction of the alternative splicing mechanism and its targeting for therapeutic strategies, the book continues with techniques for analyzing alternative splicing profiles in complex biological systems, visualizing and localizing alternative spliced transcripts with cellular and sub-cellular resolution, probing regulators of alternative splicing, as well as assessing the functional consequences of alternative splicing. Written for the highly successful _Methods in Molecular Biology_ series, chapters include introduction to their respective topics, lists of the necessary materials and reagents, step-by-step, reproducible protocols, and tips on troubleshooting and avoiding known pitfalls.
Gerber, A;van Otterdijk, S;Bruggeman, FJ;Tutucci, E;
PMID: 37050882 | DOI: 10.1080/21541264.2023.2199669
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.
Chemello, F;Sales, G;Cagnin, S;
| DOI: 10.1016/b978-0-323-91810-7.00011-x
Recent years have seen a dramatic improvement in RNA and DNA sequencing technologies allowing the analysis of gene expression and chromatin conformation at the single-cell or nuclei level. This permitted to evidence that cells of the human brain may have different genomes, the different cell types living in a tumor or during its development, and many other biological features, promising significant future biomedical and clinical impacts. In this chapter, we will develop the concept of single-cell or nucleus RNA sequencing discussing methods and applications in the field of muscle pathologies. We will focus on all the three types of muscles: skeletal muscle is particularly important to sustain the body and regulate the metabolism, cardiac muscle is fundamental for blood movement within vessels and oxygen and nutrient distribution, and smooth muscle is involved in the maintenance of blood pressure and in the movement of the bolus within the intestine.
邱丹丹, ;蒋松, ;
| DOI: 10.3969/j.issn.1006-298X.2022.03.011
In the last decade, single cell RNAsequencing (scRNAseq) has made significant advances in obtaining quantitative geneexpression of individual cells and identifying previously uncharacterized cell types and functions. However, scRNAseq technologies have the intrinsic limitation of losing original positional information during tissue dissociation into single cells. Spatial localization of cells in tissue microenvironments is essential to further identify cell types, elucidate the complex celltocell communication and spatial division of labor among cells, and explore the relationship between the tissue microenvironments imbalance and the development and progression of diseases. Tissuelevel systems biology requires obtaining wholegenome expression profiles while retaining the spatial positional information of cells. Spatial transcriptomics emerged at the proper time and developed rapidly in recent years. In this review, we introduced the common techniques of spatial transcriptomics and the integrated applications of spatial transcriptomics with other omics (spatialomics). Finally, we summarized current applications and future opportunities in the field of kidney diseases.
Jiang, M;Wei, K;Li, M;Lin, C;Ke, R;
PMID: 36813533 | DOI: 10.1261/rna.079482.122
Although RNA plays a vital role in the process of gene expression, it is less used as an in situ biomarker for clinical diagnostics compared to DNA and protein. This is mainly due to technical challenges caused by the low expression level and easy degradation of RNA molecules themselves. To tackle this issue, methods that are sensitive and specific are needed. Here we present an RNA single molecule chromogenic in situ hybridization assay based on DNA probe proximity ligation and rolling circle amplification. When the DNA probes hybridize into close proximity on the RNA molecules, they form V shape structure and mediate the circularization of circle probes. Thus, our method was termed vsmCISH. We not only successfully applied our method to assess HER2 RNA mRNA expression status in invasive breast cancer tissue, but also to investigate the utility of albumin mRNA ISH for differentiating primary from metastatic liver cancer. The promising results on clinical samples indicates the great potential of our method to be applied in the diagnosis of disease using RNA biomarkers.
Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc
O'Toole, AD;Zhang, J;Williams, LBA;Brown, CC;
PMID: 36171733 | DOI: 10.1177/10406387221126999
We made 2 Z-based in situ hybridization (ISH) probes for the detection of rabbit hemorrhagic disease virus 2 (RHDV2; Lagovirus GI.2) nucleic acid in formalin-fixed, paraffin-embedded tissues from European rabbits (Oryctolagus cuniculus) that had died during an outbreak of RHD in Washington, USA. One probe system was made for detection of negative-sense RNA (i.e., the replicative intermediate RNA for the virus), and the other probe system was constructed for detection of genomic and mRNA of the virus (viral mRNA). Tissue sets were tested separately, and the viral mRNA probe system highlighted much broader tissue distribution than that of the replicative intermediate RNA probe system. The latter was limited to liver, lung, kidney, spleen, myocardium, and occasional endothelial staining, whereas signal for the viral mRNA was seen in many more tissues. The difference in distribution suggests that innate phagocytic activity of various cell types may cause overestimation of viral replication sites when utilizing ISH of single-stranded, positive-sense viruses.
Nature reviews. Molecular cell biology
Baysoy, A;Bai, Z;Satija, R;Fan, R;
PMID: 37280296 | DOI: 10.1038/s41580-023-00615-w
Single-cell multi-omics technologies and methods characterize cell states and activities by simultaneously integrating various single-modality omics methods that profile the transcriptome, genome, epigenome, epitranscriptome, proteome, metabolome and other (emerging) omics. Collectively, these methods are revolutionizing molecular cell biology research. In this comprehensive Review, we discuss established multi-omics technologies as well as cutting-edge and state-of-the-art methods in the field. We discuss how multi-omics technologies have been adapted and improved over the past decade using a framework characterized by optimization of throughput and resolution, modality integration, uniqueness and accuracy, and we also discuss multi-omics limitations. We highlight the impact that single-cell multi-omics technologies have had in cell lineage tracing, tissue-specific and cell-specific atlas production, tumour immunology and cancer genetics, and in mapping of cellular spatial information in fundamental and translational research. Finally, we discuss bioinformatics tools that have been developed to link different omics modalities and elucidate functionality through the use of better mathematical modelling and computational methods.
Artificial intelligence (AI) is now a powerful tool which can be applied to significantly improve the safety de-risking process early in discovery, with AI-driven pipelines of biotechs expanding at a very fast rate. Data from screening studies with DNA-encoded libraries together with high throughput in silico data are screened through AI-enabled computational platforms. These platforms leverage a wide range of in vitro and in vivo models and along with computational predictive models to help identify targets, predicting ‘druggable’ characteristics and target selectivity of molecules from a vast space. In terms of safety, AI can also be used to predict potential interactions and by leveraging publicly available data or proprietary databases can predict potential on- and off-target safety liabilities. A major advantage of AI systems is that they include an active learning loop, referred to as machine learning, which helps to improve the accuracy of prediction and to identify advanceable lead series or candidate molecules leading to a very high success rate, which improves as more data is gathered. Critically AI can also be used to screen billions of molecules virtually, reducing costs and resource requirements and improving the discovery process by more efficient use of molecular biology, public and private databases and other resources.
Methods in molecular biology (Clifton, N.J.)
Aldana, R;Freed, D;
PMID: 35751805 | DOI: 10.1007/978-1-0716-2293-3_1
Public and private genomic sequencing initiatives generate ever-increasing amounts of genomic data creating a need for improved solutions for genomics data processing (Stephens et al.PLoS Biol 13:e1002195, 2015). The Sentieon Genomics software enables rapid and accurate analysis of next-generation sequence data. In this work, we present a typical use of the Sentieon Genomics software for germline variant calling. The Sentieon germline variant calling pipeline produces more accurate results than other tools on third-party benchmarks (Katherine et al. Front Genet 10:736, 2019; Shen et al. bioRxiv, 885517, 2019) in one tenth the time of comparable pipelines. Parts of this guide come from the official Sentieon Genomics software manual in https://support.sentieon.com/manual (Sentieon. Sentieon Genomics software manual, n.d.) and from the official Sentieon Genomics software application notes in https://support.sentieon.com/appnotes (Sentieon. Sentieon Genomics software application notes, n.d.) and are republished with permission. For additional details and advanced usage instructions of the Sentieon tools, refer to the software manual.
International journal for parasitology
Britton, C;Laing, R;McNeilly, TN;Perez, MG;Otto, TD;Hildersley, KA;Maizels, RM;Devaney, E;Gillan, V;
PMID: 36931423 | DOI: 10.1016/j.ijpara.2022.11.012
How parasites develop and survive, and how they stimulate or modulate host immune responses are important in understanding disease pathology and for the design of new control strategies. Microarray analysis and bulk RNA sequencing have provided a wealth of data on gene expression as parasites develop through different life-cycle stages and on host cell responses to infection. These techniques have enabled gene expression in the whole organism or host tissue to be detailed, but do not take account of the heterogeneity between cells of different types or developmental stages, nor the spatial organisation of these cells. Single-cell RNA-seq (scRNA-seq) adds a new dimension to studying parasite biology and host immunity by enabling gene profiling at the individual cell level. Here we review the application of scRNA-seq to establish gene expression cell atlases for multicellular helminths and to explore the expansion and molecular profile of individual host cell types involved in parasite immunity and tissue repair. Studying host-parasite interactions in vivo is challenging and we conclude this review by briefly discussing the applications of organoids (stem-cell derived mini-tissues) to examine host-parasite interactions at the local level, and as a potential system to study parasite development in vitro. Organoid technology and its applications have developed rapidly, and the elegant studies performed to date support the use of organoids as an alternative in vitro system for research on helminth parasites.