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Korhonen PK, Wang T, Young ND, Byrne JJ, Campos TL, Chang BC, Taki AC, Gasser RB. Analysis of Haemonchus embryos at single cell resolution identifies two eukaryotic elongation factors as intervention target candidates. Comput Struct Biotechnol J 2024; 23:1026-1035. [PMID: 38435301 PMCID: PMC10907403 DOI: 10.1016/j.csbj.2024.01.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 01/14/2024] [Accepted: 01/15/2024] [Indexed: 03/05/2024] Open
Abstract
Advances in single cell technologies are allowing investigations of a wide range of biological processes and pathways in animals, such as the multicellular model organism Caenorhabditis elegans - a free-living nematode. However, there has been limited application of such technology to related parasitic nematodes which cause major diseases of humans and animals worldwide. With no vaccines against the vast majority of parasitic nematodes and treatment failures due to drug resistance or inefficacy, new intervention targets are urgently needed, preferably informed by a deep understanding of these nematodes' cellular and molecular biology - which is presently lacking for most worms. Here, we created the first single cell atlas for an early developmental stage of Haemonchus contortus - a highly pathogenic, C. elegans-related parasitic nematode. We obtained and curated RNA sequence (snRNA-seq) data from single nuclei from embryonating eggs of H. contortus (150,000 droplets), and selected high-quality transcriptomic data for > 14,000 single nuclei for analysis, and identified 19 distinct clusters of cells. Guided by comparative analyses with C. elegans, we were able to reproducibly assign seven cell clusters to body wall muscle, hypodermis, neuronal, intestinal or seam cells, and identified eight genes that were transcribed in all cell clusters/types, three of which were inferred to be essential in H. contortus. Two of these genes (i.e. Hc-eef-1A and Hc-eef1G), coding for eukaryotic elongation factors (called Hc-eEF1A and Hc-eEF1G), were also demonstrated to be transcribed and expressed in all key developmental stages of H. contortus. Together with these findings, sequence- and structure-based comparative analyses indicated the potential of Hc-eEF1A and/or Hc-eEF1G as intervention targets within the protein biosynthesis machinery of H. contortus. Future work will focus on single cell studies of all key developmental stages and tissues of H. contortus, and on evaluating the suitability of the two elongation factor proteins as drug targets in H. contortus and related nematodes, with a view to finding new nematocidal drug candidates.
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Affiliation(s)
- Pasi K. Korhonen
- Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Tao Wang
- Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Neil D. Young
- Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Joseph J. Byrne
- Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Tulio L. Campos
- Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Bill C.H. Chang
- Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Aya C. Taki
- Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Robin B. Gasser
- Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, Victoria 3010, Australia
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2
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Trapnell C. Revealing gene function with statistical inference at single-cell resolution. Nat Rev Genet 2024; 25:623-638. [PMID: 38951690 DOI: 10.1038/s41576-024-00750-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/21/2024] [Indexed: 07/03/2024]
Abstract
Single-cell and spatial molecular profiling assays have shown large gains in sensitivity, resolution and throughput. Applying these technologies to specimens from human and model organisms promises to comprehensively catalogue cell types, reveal their lineage origins in development and discern their contributions to disease pathogenesis. Moreover, rapidly dropping costs have made well-controlled perturbation experiments and cohort studies widely accessible, illuminating mechanisms that give rise to phenotypes at the scale of the cell, the tissue and the whole organism. Interpreting the coming flood of single-cell data, much of which will be spatially resolved, will place a tremendous burden on existing computational pipelines. However, statistical concepts, models, tools and algorithms can be repurposed to solve problems now arising in genetic and molecular biology studies of development and disease. Here, I review how the questions that recent technological innovations promise to answer can be addressed by the major classes of statistical tools.
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Affiliation(s)
- Cole Trapnell
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA.
- Seattle Hub for Synthetic Biology, Seattle, WA, USA.
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3
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Xu L, Li Z, Ren J, Liu S, Xu Y. Single-cell RNA sequencing data analysis utilizing multi-type graph neural networks. Comput Biol Med 2024; 179:108921. [PMID: 39059210 DOI: 10.1016/j.compbiomed.2024.108921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2024] [Revised: 07/08/2024] [Accepted: 07/16/2024] [Indexed: 07/28/2024]
Abstract
Single-cell RNA sequencing (scRNA-seq) is the sequencing technology of a single cell whose expression reflects the overall characteristics of the individual cell, facilitating the research of problems at the cellular level. However, the problems of scRNA-seq such as dimensionality reduction processing of massive data, technical noise in data, and visualization of single-cell type clustering cause great difficulties for analyzing and processing scRNA-seq data. In this paper, we propose a new single-cell data analysis model using denoising autoencoder and multi-type graph neural networks (scDMG), which learns cell-cell topology information and latent representation of scRNA-seq data. scDMG introduces the zero-inflated negative binomial (ZINB) model into a denoising autoencoder (DAE) to perform dimensionality reduction and denoising on the raw data. scDMG integrates multiple-type graph neural networks as the encoder to further train the preprocessed data, which better deals with various types of scRNA-seq datasets, resolves dropout events in scRNA-seq data, and enables preliminary classification of scRNA-seq data. By employing TSNE and PCA algorithms for the trained data and invoking Louvain algorithm, scDMG has better dimensionality reduction and clustering optimization. Compared with other mainstream scRNA-seq clustering algorithms, scDMG outperforms other state-of-the-art methods in various clustering performance metrics and shows better scalability, shorter runtime, and great clustering results.
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Affiliation(s)
- Li Xu
- College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, Heilongjiang, China
| | - Zhenpeng Li
- College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, Heilongjiang, China.
| | - Jiaxu Ren
- College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, Heilongjiang, China
| | - Shuaipeng Liu
- College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, Heilongjiang, China
| | - Yiming Xu
- College of Engineering, Tokyo Institute of Technology, Tokyo, 226-0026, Tokyo, Japan
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4
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Pir MS, Begar E, Yenisert F, Demirci HC, Korkmaz ME, Karaman A, Tsiropoulou S, Firat-Karalar EN, Blacque OE, Oner SS, Doluca O, Cevik S, Kaplan OI. CilioGenics: an integrated method and database for predicting novel ciliary genes. Nucleic Acids Res 2024; 52:8127-8145. [PMID: 38989623 DOI: 10.1093/nar/gkae554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/21/2024] [Accepted: 07/09/2024] [Indexed: 07/12/2024] Open
Abstract
Uncovering the full list of human ciliary genes holds enormous promise for the diagnosis of cilia-related human diseases, collectively known as ciliopathies. Currently, genetic diagnoses of many ciliopathies remain incomplete (1-3). While various independent approaches theoretically have the potential to reveal the entire list of ciliary genes, approximately 30% of the genes on the ciliary gene list still stand as ciliary candidates (4,5). These methods, however, have mainly relied on a single strategy to uncover ciliary candidate genes, making the categorization challenging due to variations in quality and distinct capabilities demonstrated by different methodologies. Here, we develop a method called CilioGenics that combines several methodologies (single-cell RNA sequencing, protein-protein interactions (PPIs), comparative genomics, transcription factor (TF) network analysis, and text mining) to predict the ciliary capacity of each human gene. Our combined approach provides a CilioGenics score for every human gene that represents the probability that it will become a ciliary gene. Compared to methods that rely on a single method, CilioGenics performs better in its capacity to predict ciliary genes. Our top 500 gene list includes 258 new ciliary candidates, with 31 validated experimentally by us and others. Users may explore the whole list of human genes and CilioGenics scores on the CilioGenics database (https://ciliogenics.com/).
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Affiliation(s)
- Mustafa S Pir
- Rare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye
| | - Efe Begar
- Department of Molecular Biology and Genetics, Koc University, Istanbul 34450, Turkiye
| | - Ferhan Yenisert
- Rare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye
| | - Hasan C Demirci
- Rare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye
| | - Mustafa E Korkmaz
- Rare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye
| | - Asli Karaman
- Istanbul Medeniyet University, Science and Advanced Technologies Research Center (BILTAM), 34700 Istanbul, Turkiye
| | - Sofia Tsiropoulou
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland
| | - Elif Nur Firat-Karalar
- Department of Molecular Biology and Genetics, Koc University, Istanbul 34450, Turkiye
- School of Medicine, Koç University, Istanbul 34450, Turkiye
| | - Oliver E Blacque
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland
| | - Sukru S Oner
- Istanbul Medeniyet University, Science and Advanced Technologies Research Center (BILTAM), 34700 Istanbul, Turkiye
- Goztepe Prof. Dr. Suleyman Yalcin City Hospital, Istanbul, Turkiye
| | - Osman Doluca
- Izmir University of Economics, Faculty of Engineering, Department of Biomedical Engineering, Izmir, Turkiye
| | - Sebiha Cevik
- Rare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye
| | - Oktay I Kaplan
- Rare Disease Laboratory, School of Life and Natural Sciences, Abdullah Gul University, Kayseri, Turkiye
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5
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Cao W, Fan Q, Amparado G, Begic D, Godini R, Gopal S, Pocock R. A nucleic acid binding protein map of germline regulation in Caenorhabditis elegans. Nat Commun 2024; 15:6884. [PMID: 39128930 PMCID: PMC11317507 DOI: 10.1038/s41467-024-51212-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Accepted: 08/01/2024] [Indexed: 08/13/2024] Open
Abstract
Fertility requires the faithful proliferation of germ cells and their differentiation into gametes. Controlling these cellular states demands precise timing and expression of gene networks. Nucleic acid binding proteins (NBPs) play critical roles in gene expression networks that influence germ cell development. There has, however, been no functional analysis of the entire NBP repertoire in controlling in vivo germ cell development. Here, we analyzed germ cell states and germline architecture to systematically investigate the function of 364 germline-expressed NBPs in the Caenorhabditis elegans germ line. Using germline-specific knockdown, automated germ cell counting, and high-content analysis of germ cell nuclei and plasma membrane organization, we identify 156 NBPs with discrete autonomous germline functions. By identifying NBPs that control the germ cell cycle, proliferation, differentiation, germline structure and fertility, we have created an atlas for mechanistic dissection of germ cell behavior and gamete production.
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Affiliation(s)
- Wei Cao
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Melbourne, VIC, 3800, Australia.
| | - Qi Fan
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Melbourne, VIC, 3800, Australia
| | - Gemmarie Amparado
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Melbourne, VIC, 3800, Australia
| | - Dean Begic
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Melbourne, VIC, 3800, Australia
| | - Rasoul Godini
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Melbourne, VIC, 3800, Australia
| | - Sandeep Gopal
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Melbourne, VIC, 3800, Australia.
- Lund Stem Cell Center, Department of Experimental Medical Science, Lund University, Lund, Sweden.
| | - Roger Pocock
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Melbourne, VIC, 3800, Australia.
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6
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Wang J, Barr MM, Wehman AM. Extracellular vesicles. Genetics 2024; 227:iyae088. [PMID: 38884207 PMCID: PMC11304975 DOI: 10.1093/genetics/iyae088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 05/21/2024] [Indexed: 06/18/2024] Open
Abstract
Extracellular vesicles (EVs) encompass a diverse array of membrane-bound organelles released outside cells in response to developmental and physiological cell needs. EVs play important roles in remodeling the shape and content of differentiating cells and can rescue damaged cells from toxic or dysfunctional content. EVs can send signals and transfer metabolites between tissues and organisms to regulate development, respond to stress or tissue damage, or alter mating behaviors. While many EV functions have been uncovered by characterizing ex vivo EVs isolated from body fluids and cultured cells, research using the nematode Caenorhabditis elegans has provided insights into the in vivo functions, biogenesis, and uptake pathways. The C. elegans EV field has also developed methods to analyze endogenous EVs within the organismal context of development and adult physiology in free-living, behaving animals. In this review, we summarize major themes that have emerged for C. elegans EVs and their relevance to human health and disease. We also highlight the diversity of biogenesis mechanisms, locations, and functions of worm EVs and discuss open questions and unexplored topics tenable in C. elegans, given the nematode model is ideal for light and electron microscopy, genetic screens, genome engineering, and high-throughput omics.
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Affiliation(s)
- Juan Wang
- Department of Genetics, Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ 08854, USA
| | - Maureen M Barr
- Department of Genetics, Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ 08854, USA
| | - Ann M Wehman
- Department of Biological Sciences, University of Denver, Denver, CO 80210, USA
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7
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Eastburn DJ, White KS, Jayne ND, Camiolo S, Montis G, Ha S, Watson KG, Yeakley JM, McComb J, Seligmann B. High-throughput gene expression analysis with TempO-LINC sensitively resolves complex brain, lung and kidney heterogeneity at single-cell resolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.03.606484. [PMID: 39149288 PMCID: PMC11326174 DOI: 10.1101/2024.08.03.606484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
We report the development and performance of a novel genomics platform, TempO-LINC, for conducting high-throughput transcriptomic analysis on single cells and nuclei. TempO-LINC works by adding cell-identifying molecular barcodes onto highly selective and high-sensitivity gene expression probes within fixed cells, without having to first generate cDNA. Using an instrument-free combinatorial-indexing approach, all probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000+ cells per run. The TempO-LINC approach is easily scalable based on the number of barcodes and rounds of barcoding performed; however, for the experiments reported in this study, the assay utilized over 5.3 million unique barcodes. TempO-LINC has a robust protocol for fixing and banking cells and displays high-sensitivity gene detection from multiple diverse sample types. We show that TempO-LINC has an observed multiplet rate of less than 1.1% and a cell capture rate of ∼50%. Although the assay can accurately profile the whole transcriptome (19,683 human or 21,400 mouse genes), it can be targeted to measure only actionable/informative genes and molecular pathways of interest - thereby reducing sequencing requirements. In this study, we applied TempO-LINC to profile the transcriptomes of 89,722 cells across multiple sample types, including nuclei from mouse lung, kidney and brain tissues. The data demonstrated the ability to identify and annotate at least 50 unique cell populations and positively correlate expression of cell type-specific molecular markers within them. TempO-LINC is a robust new single-cell technology that is ideal for large-scale applications/studies across thousands of samples with high data quality.
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8
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Skinner DJ, Lemaire P, Mani M. Physical modeling of embryonic transcriptomes identifies collective modes of gene expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.26.605398. [PMID: 39131269 PMCID: PMC11312445 DOI: 10.1101/2024.07.26.605398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Starting from one totipotent cell, complex multicellular organisms form through a series of differentiation and morphogenetic events, culminating in a multitude of cell types arranged in a functional and intricate spatial pattern. To do so, cells coordinate with each other, resulting in dynamics which follow a precise developmental trajectory, constraining the space of possible embryo-to-embryo variation. Using recent single-cell sequencing data of early ascidian embryos, we leverage natural variation together with modeling and inference techniques from statistical physics to investigate development at the level of a complete interconnected embryo - an embryonic transcriptome. After developing a robust and biophysically motivated approach to identifying distinct transcriptomic states or cell types, a statistical analysis reveals correlations within embryos and across cell types demonstrating the presence of collective variation. From these intra-embryo correlations, we infer minimal networks of cell-cell interactions, which reveal the collective modes of gene expression. Our work demonstrates how the existence and nature of spatial interactions along with the collective modes of expression that they give rise to can be inferred from single-cell gene expression measurements, opening up a wider range of biological questions that can be addressed using sequencing-based modalities.
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Affiliation(s)
- Dominic J Skinner
- Center for Computational Biology, Flatiron Institute, 162 5th Ave, New York, NY 10010, USA
- NSF-Simons Center for Quantitative Biology, Northwestern University, 2205 Tech Drive, Evanston, IL 60208, USA
| | - Patrick Lemaire
- CRBM, Université de Montpellier, CNRS, 34293 Montpellier, France
| | - Madhav Mani
- NSF-Simons Center for Quantitative Biology, Northwestern University, 2205 Tech Drive, Evanston, IL 60208, USA
- Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL 60208, USA
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Shabani P, Ohanyan V, Alghadeer A, Gavazzi D, Dong F, Yin L, Kolz C, Shockling L, Enrick M, Zhang P, Shi X, Chilian W. Bone marrow cells contribute to seven different endothelial cell populations in the heart. Basic Res Cardiol 2024; 119:699-715. [PMID: 38963562 PMCID: PMC11319501 DOI: 10.1007/s00395-024-01065-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 06/20/2024] [Accepted: 06/21/2024] [Indexed: 07/05/2024]
Abstract
Understanding the mechanisms underlying vascular regeneration in the heart is crucial for developing novel therapeutic strategies for myocardial ischemia. This study investigates the contribution of bone marrow-derived cells to endothelial cell populations in the heart, and their role in cardiac function and coronary circulation following repetitive ischemia (RI). Chimeric rats were created by transplanting BM cells from GFP female rats into irradiated male recipients. After engraftment chimeras were subjected to RI for 17 days. Vascular growth was assessed from recovery of cardiac function and increases in myocardial blood flow during LAD occlusion. After sorting GFP+ BM cells from heart and bone of Control and RI rats, single-cell RNA sequencing was implemented to determine the fate of BM cells. Our in vivo RI model demonstrated an improvement in cardiac function and myocardial blood flow after 17 days of RI with increased capillary density in the rats subjected to RI compared to Controls. Single-cell RNA sequencing of bone marrow cells isolated from rats' hearts identified distinct endothelial cell (EC) subpopulations. These ECs exhibited heterogeneous gene expression profiles and were enriched for markers of capillary, artery, lymphatic, venous, and immune ECs. Furthermore, BM-derived ECs in the RI group showed an angiogenic profile, characterized by upregulated genes associated with blood vessel development and angiogenesis. This study elucidates the heterogeneity of bone marrow-derived endothelial cells in the heart and their response to repetitive ischemia, laying the groundwork for targeting specific subpopulations for therapeutic angiogenesis in myocardial ischemia.
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Affiliation(s)
- Parisa Shabani
- Department of Integrative Medical Sciences, Northeast Ohio Medical University, Rootstown, OH, 44272, USA
| | - Vahagn Ohanyan
- Department of Integrative Medical Sciences, Northeast Ohio Medical University, Rootstown, OH, 44272, USA
| | - Ammar Alghadeer
- Department of Biomedical Dental Sciences, College of Dentistry, Imam Abdulrahman Bin Faisal University, 31441, Dammam, Saudi Arabia
- Institute for Stem Cell and Regenerative Medicine, University of Washington, School of Medicine, Seattle, WA, 98109, USA
| | - Daniel Gavazzi
- Hiram College Physics and Computer Science Department, Hiram, OH, USA
| | - Feng Dong
- Department of Integrative Medical Sciences, Northeast Ohio Medical University, Rootstown, OH, 44272, USA
| | - Liya Yin
- Department of Integrative Medical Sciences, Northeast Ohio Medical University, Rootstown, OH, 44272, USA
| | - Christopher Kolz
- Department of Integrative Medical Sciences, Northeast Ohio Medical University, Rootstown, OH, 44272, USA
| | - Lindsay Shockling
- Department of Integrative Medical Sciences, Northeast Ohio Medical University, Rootstown, OH, 44272, USA
| | - Molly Enrick
- Department of Integrative Medical Sciences, Northeast Ohio Medical University, Rootstown, OH, 44272, USA
| | - Ping Zhang
- Department of Integrative Medical Sciences, Northeast Ohio Medical University, Rootstown, OH, 44272, USA
| | - Xin Shi
- Department of Integrative Medical Sciences, Northeast Ohio Medical University, Rootstown, OH, 44272, USA
| | - William Chilian
- Department of Integrative Medical Sciences, Northeast Ohio Medical University, Rootstown, OH, 44272, USA.
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Pepin AS, Schneider R. Emerging toolkits for decoding the co-occurrence of modified histones and chromatin proteins. EMBO Rep 2024; 25:3202-3220. [PMID: 39095610 PMCID: PMC11316037 DOI: 10.1038/s44319-024-00199-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 05/10/2024] [Accepted: 06/10/2024] [Indexed: 08/04/2024] Open
Abstract
In eukaryotes, DNA is packaged into chromatin with the help of highly conserved histone proteins. Together with DNA-binding proteins, posttranslational modifications (PTMs) on these histones play crucial roles in regulating genome function, cell fate determination, inheritance of acquired traits, cellular states, and diseases. While most studies have focused on individual DNA-binding proteins, chromatin proteins, or histone PTMs in bulk cell populations, such chromatin features co-occur and potentially act cooperatively to accomplish specific functions in a given cell. This review discusses state-of-the-art techniques for the simultaneous profiling of multiple chromatin features in low-input samples and single cells, focusing on histone PTMs, DNA-binding, and chromatin proteins. We cover the origins of the currently available toolkits, compare and contrast their characteristic features, and discuss challenges and perspectives for future applications. Studying the co-occurrence of histone PTMs, DNA-binding proteins, and chromatin proteins in single cells will be central for a better understanding of the biological relevance of combinatorial chromatin features, their impact on genomic output, and cellular heterogeneity.
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Affiliation(s)
- Anne-Sophie Pepin
- Institute of Functional Epigenetics (IFE), Helmholtz Zentrum München, Neuherberg, Germany
| | - Robert Schneider
- Institute of Functional Epigenetics (IFE), Helmholtz Zentrum München, Neuherberg, Germany.
- Faculty of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
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11
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Zhou T, Zhang R, Jia D, Doty RT, Munday AD, Gao D, Xin L, Abkowitz JL, Duan Z, Ma J. GAGE-seq concurrently profiles multiscale 3D genome organization and gene expression in single cells. Nat Genet 2024; 56:1701-1711. [PMID: 38744973 PMCID: PMC11323187 DOI: 10.1038/s41588-024-01745-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 04/05/2024] [Indexed: 05/16/2024]
Abstract
The organization of mammalian genomes features a complex, multiscale three-dimensional (3D) architecture, whose functional significance remains elusive because of limited single-cell technologies that can concurrently profile genome organization and transcriptional activities. Here, we introduce genome architecture and gene expression by sequencing (GAGE-seq), a scalable, robust single-cell co-assay measuring 3D genome structure and transcriptome simultaneously within the same cell. Applied to mouse brain cortex and human bone marrow CD34+ cells, GAGE-seq characterized the intricate relationships between 3D genome and gene expression, showing that multiscale 3D genome features inform cell-type-specific gene expression and link regulatory elements to target genes. Integration with spatial transcriptomic data revealed in situ 3D genome variations in mouse cortex. Observations in human hematopoiesis unveiled discordant changes between 3D genome organization and gene expression, underscoring a complex, temporal interplay at the single-cell level. GAGE-seq provides a powerful, cost-effective approach for exploring genome structure and gene expression relationships at the single-cell level across diverse biological contexts.
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Affiliation(s)
- Tianming Zhou
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ruochi Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Deyong Jia
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Raymond T Doty
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA
| | - Adam D Munday
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA
| | - Daniel Gao
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
- Department of Chemistry, Pomona College, Claremont, CA, USA
| | - Li Xin
- Department of Urology, University of Washington, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Janis L Abkowitz
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Zhijun Duan
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA.
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA.
| | - Jian Ma
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
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12
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Metzner E, Southard KM, Norman TM. Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.26.605307. [PMID: 39091800 PMCID: PMC11291144 DOI: 10.1101/2024.07.26.605307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Pseudotime analysis of perturbations connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state.
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Affiliation(s)
- Eli Metzner
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Tri-Institutional Training Program in Computational Biology and Medicine, New York, NY, USA
| | - Kaden M. Southard
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Thomas M. Norman
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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13
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Fung W, Kolotuev I, Heiman MG. Specialized structure and function of the apical extracellular matrix at sense organs. Cells Dev 2024:203942. [PMID: 39067521 DOI: 10.1016/j.cdev.2024.203942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 07/21/2024] [Accepted: 07/23/2024] [Indexed: 07/30/2024]
Abstract
Apical extracellular matrix (aECM), which covers every surface of the body, exhibits tissue-specific structures that carry out specialized functions. This is particularly striking at sense organs, where aECM forms the interface between sensory neurons and the environment, and thus plays critical roles in how sensory stimuli are received. Here, we review the extraordinary adaptations of aECM across sense organs and discuss how differences in protein composition and matrix structure assist in sensing mechanical forces (tactile hairs, campaniform sensilla, and the tectorial membrane of the cochlea); tastes and smells (uniporous gustatory sensilla and multiporous olfactory sensilla in insects, and salivary and olfactory mucus in vertebrates); and light (cuticle-derived lenses in arthropods and mollusks). We summarize the power of using C. elegans, in which defined sense organs associate with distinct aECM, as a model for understanding the tissue-specific structural and functional specializations of aECM. Finally, we synthesize results from recent studies in C. elegans and Drosophila into a conceptual framework for aECM patterning, including mechanisms that involve transient cellular or matrix scaffolds, mechanical pulling or pushing forces, and localized secretion or endocytosis.
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Affiliation(s)
- Wendy Fung
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | | | - Maxwell G Heiman
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA.
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14
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Sun F, Li H, Sun D, Fu S, Gu L, Shao X, Wang Q, Dong X, Duan B, Xing F, Wu J, Xiao M, Zhao F, Han JDJ, Liu Q, Fan X, Li C, Wang C, Shi T. Single-cell omics: experimental workflow, data analyses and applications. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-023-2561-0. [PMID: 39060615 DOI: 10.1007/s11427-023-2561-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/18/2024] [Indexed: 07/28/2024]
Abstract
Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
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Affiliation(s)
- Fengying Sun
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China
| | - Haoyan Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Dongqing Sun
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Shaliu Fu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Lei Gu
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Shao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China
| | - Qinqin Wang
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Dong
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Bin Duan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Feiyang Xing
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Jun Wu
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Minmin Xiao
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Qi Liu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China.
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China.
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China.
- Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
| | - Chen Li
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Chenfei Wang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Tieliu Shi
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
- Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai, 200062, China.
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15
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Shin SW, Mudvari P, Thaploo S, Wheeler MA, Douek DC, Quintana FJ, Boritz EA, Abate AR, Clark IC. FIND-seq: high-throughput nucleic acid cytometry for rare single-cell transcriptomics. Nat Protoc 2024:10.1038/s41596-024-01021-y. [PMID: 39039320 DOI: 10.1038/s41596-024-01021-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 05/09/2024] [Indexed: 07/24/2024]
Abstract
Rare cells have an important role in development and disease, and methods for isolating and studying cell subsets are therefore an essential part of biology research. Such methods traditionally rely on labeled antibodies targeted to cell surface proteins, but large public databases and sophisticated computational approaches increasingly define cell subsets on the basis of genomic, epigenomic and transcriptomic sequencing data. Methods for isolating cells on the basis of nucleic acid sequences powerfully complement these approaches by providing experimental access to cell subsets discovered in cell atlases, as well as those that cannot be otherwise isolated, including cells infected with pathogens, with specific DNA mutations or with unique transcriptional or splicing signatures. We recently developed a nucleic acid cytometry platform called 'focused interrogation of cells by nucleic acid detection and sequencing' (FIND-seq), capable of isolating rare cells on the basis of RNA or DNA markers, followed by bulk or single-cell transcriptomic analysis. This platform has previously been used to characterize the splicing-dependent activation of the transcription factor XBP1 in astrocytes and HIV persistence in memory CD4 T cells from people on long-term antiretroviral therapy. Here, we outline the molecular and microfluidic steps involved in performing FIND-seq, including protocol updates that allow detection and whole transcriptome sequencing of rare HIV-infected cells that harbor genetically intact virus genomes. FIND-seq requires knowledge of microfluidics, optics and molecular biology. We expect that FIND-seq, and this comprehensive protocol, will enable mechanistic studies of rare HIV+ cells, as well as other cell subsets that were previously difficult to recover and sequence.
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Affiliation(s)
- Seung Won Shin
- Department of Bioengineering, College of Engineering, California Institute for Quantitative Biosciences (QB3), University of California Berkeley, Berkeley, CA, USA
| | - Prakriti Mudvari
- Virus Persistence and Dynamics Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Shravan Thaploo
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael A Wheeler
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel C Douek
- Human Immunology Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Francisco J Quintana
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Eli A Boritz
- Virus Persistence and Dynamics Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Adam R Abate
- Department of Bioengineering and Therapeutic Sciences, School of Pharmacy, University of California San Francisco, San Francisco, CA, USA
| | - Iain C Clark
- Department of Bioengineering, College of Engineering, California Institute for Quantitative Biosciences (QB3), University of California Berkeley, Berkeley, CA, USA.
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16
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Mozin E, Massouridès E, Mournetas V, Lièvre C, Bourdon A, Jackson DL, Packer JS, Seong J, Trapnell C, Le Guiner C, Adjali O, Pinset C, Mack DL, Dupont JB. Dystrophin deficiency impairs cell junction formation during embryonic myogenesis from pluripotent stem cells. iScience 2024; 27:110242. [PMID: 39040067 PMCID: PMC11261405 DOI: 10.1016/j.isci.2024.110242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 05/02/2024] [Accepted: 06/07/2024] [Indexed: 07/24/2024] Open
Abstract
Mutations in the DMD gene lead to Duchenne muscular dystrophy (DMD), a severe neuromuscular disorder affecting young boys as they acquire motor functions. DMD is typically diagnosed at 2-4 years of age, but the absence of dystrophin has negative impacts on skeletal muscles before overt symptoms appear in patients, which poses a serious challenge in current standards of care. Here, we investigated the consequences of dystrophin deficiency during skeletal muscle development. We used single-cell transcriptome profiling to characterize the myogenic trajectory of human pluripotent stem cells and showed that DMD cells bifurcate to an alternative branch when they reach the somite stage. Dystrophin deficiency was linked to marked dysregulations of cell junction proteins involved in the cell state transitions characteristic of embryonic somitogenesis. Altogether, this work demonstrates that in vitro, dystrophin deficiency has deleterious effects on cell-cell communication during myogenic development, which should be considered in future therapeutic strategies for DMD.
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Affiliation(s)
- Elise Mozin
- Nantes Université, CHU Nantes, INSERM, TARGET, F-44000 Nantes, France
| | | | | | - Clémence Lièvre
- Nantes Université, CHU Nantes, INSERM, TARGET, F-44000 Nantes, France
| | - Audrey Bourdon
- Nantes Université, CHU Nantes, INSERM, TARGET, F-44000 Nantes, France
| | - Dana L. Jackson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98105, USA
| | - Jonathan S. Packer
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98105, USA
| | - Juyoung Seong
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, South Korea
- Institute for Stem Cell and Regenerative Medicine, Department of Rehabilitation Medicine, University of Washington, Seattle, WA 98109, USA
| | - Cole Trapnell
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98105, USA
| | | | - Oumeya Adjali
- Nantes Université, CHU Nantes, INSERM, TARGET, F-44000 Nantes, France
| | - Christian Pinset
- Centre d’Etude des Cellules Souches, I-Stem, AFM, F-91100 Corbeil-Essonnes, France
| | - David L. Mack
- Institute for Stem Cell and Regenerative Medicine, Department of Rehabilitation Medicine, University of Washington, Seattle, WA 98109, USA
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17
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Hasegawa Y, Franks JM, Tanaka Y, Uehara Y, Read DF, Williams C, Srivatsan S, Pitstick LB, Nikolaidis NM, Shaver CM, Kropski J, Ware LB, Taylor CJ, Banovich NE, Wu H, Gardner JC, Osterburg AR, Yu JJ, Kopras EJ, Teitelbaum SL, Wikenheiser-Brokamp KA, Trapnell C, McCormack FX. Pulmonary osteoclast-like cells in silica induced pulmonary fibrosis. SCIENCE ADVANCES 2024; 10:eadl4913. [PMID: 38985878 PMCID: PMC11235167 DOI: 10.1126/sciadv.adl4913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 06/05/2024] [Indexed: 07/12/2024]
Abstract
The pathophysiology of silicosis is poorly understood, limiting development of therapies for those who have been exposed to the respirable particle. We explored mechanisms of silica-induced pulmonary fibrosis in human lung samples collected from patients with occupational exposure to silica and in a longitudinal mouse model of silicosis using multiple modalities including whole-lung single-cell RNA sequencing and histological, biochemical, and physiologic assessments. In addition to pulmonary inflammation and fibrosis, intratracheal silica challenge induced osteoclast-like differentiation of alveolar macrophages and recruited monocytes, driven by induction of the osteoclastogenic cytokine, receptor activator of nuclear factor κΒ ligand (RANKL) in pulmonary lymphocytes, and alveolar type II cells. Anti-RANKL monoclonal antibody treatment suppressed silica-induced osteoclast-like differentiation in the lung and attenuated pulmonary fibrosis. We conclude that silica induces differentiation of pulmonary osteoclast-like cells leading to progressive lung injury, likely due to sustained elaboration of bone-resorbing proteases and hydrochloric acid. Interrupting osteoclast-like differentiation may therefore constitute a promising avenue for moderating lung damage in silicosis.
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Affiliation(s)
- Yoshihiro Hasegawa
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Jennifer M. Franks
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Yusuke Tanaka
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Yasuaki Uehara
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - David F. Read
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Claire Williams
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Sanjay Srivatsan
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Lori B. Pitstick
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Nikolaos M. Nikolaidis
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Ciara M. Shaver
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jonathan Kropski
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lorraine B. Ware
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Chase J. Taylor
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nicholas E. Banovich
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Huixing Wu
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Jason C. Gardner
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Andrew R. Osterburg
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Jane J. Yu
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Elizabeth J. Kopras
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Steven L. Teitelbaum
- Department of Pathology and Immunology, and Division of Bone and Mineral Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Kathryn A. Wikenheiser-Brokamp
- Division of Pathology and Laboratory Medicine and Perinatal Institute, Division of Pulmonary Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Pathology and Laboratory Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Cole Trapnell
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Francis X. McCormack
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA
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18
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Kim SY, Zo S, Kim DH, Shin SJ, Jhun BW. Single-cell transcriptomics by clinical course of Mycobacterium avium complex pulmonary disease. Sci Rep 2024; 14:15663. [PMID: 38977917 PMCID: PMC11231222 DOI: 10.1038/s41598-024-66523-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 07/02/2024] [Indexed: 07/10/2024] Open
Abstract
Mycobacterium avium complex pulmonary disease (MAC-PD) has a heterogeneous clinical course. However, immune profiles associated with MAC-PD clinical course are limited. We performed single-cell RNA sequencing of peripheral blood mononuclear cells from 21 MAC-PD patients divided into three clinical courses: group A, spontaneous culture conversion; group B, stable disease without antibiotic treatment; and group C, progressive disease with antibiotic treatment. A lower proportion of NK cells and higher proportion of monocytes were noted in group C compared to combined groups A and B. The proportion of classical monocytes was higher in group C compared to groups A and B, while the proportion of non-classical monocytes decreased. EGR1, HSPA1A, HSPA1B, and CD83 were up-regulated in spontaneous culture conversion group A compared to progressive disease group C. Up-regulation of MYOM2 and LILRA4 and down-regulation of MT-ATP8, CD83, and CCL3L1 was found in progressive disease group C. PCBP1, FOS, RGCC, S100B, G0S2, AREG, and LYN were highly expressed in favorable treatment response compared to unfavorable response. Our findings may offer a comprehensive understanding of the host immune profiles that influence a particular MAC-PD clinical course and could suggest an immunological mechanism associated with the disease progression of MAC-PD.
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Affiliation(s)
- Su-Young Kim
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Sungmin Zo
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Dae Hun Kim
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Sung Jae Shin
- Department of Microbiology, Institute for Immunology and Immunological Disease, Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine, Seoul, South Korea
| | - Byung Woo Jhun
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
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19
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Kong JN, Dipon Ghosh D, Savvidis A, Sando SR, Droste R, Robert Horvitz H. Transcriptional landscape of a hypoxia response identifies cell-specific pathways for adaptation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.02.601765. [PMID: 39005398 PMCID: PMC11245032 DOI: 10.1101/2024.07.02.601765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
How the HIF-1 (Hypoxia-Inducible) transcription factor drives and coordinates distinct responses to low oxygen across diverse cell types is poorly understood. We present a multi-tissue single-cell gene-expression atlas of the hypoxia response of the nematode Caenorhabditis elegans . This atlas highlights how cell-type-specific HIF-1 responses overlap and diverge among and within neuronal, intestinal, and muscle tissues. Using the atlas to guide functional analyses of candidate muscle-specific HIF-1 effectors, we discovered that HIF-1 activation drives downregulation of the tspo-1 ( TSPO, Translocator Protein) gene in vulval muscle cells to modulate a hypoxia-driven change in locomotion caused by contraction of body-wall muscle cells. We further showed that in human cardiomyocytes HIF-1 activation decreases levels of TSPO and thereby alters intracellular cholesterol transport and the mitochondrial network. We suggest that TSPO-1 is an evolutionarily conserved mediator of HIF-1-dependent modulation of muscle and conclude that our gene-expression atlas can help reveal how HIF-1 drives cell-specific adaptations to hypoxia.
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20
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Pickett SJ, Taylor RW, McFarland R. Fit for purpose: Selecting the best mitochondrial DNA for the job. Cell Metab 2024; 36:1436-1438. [PMID: 38959860 DOI: 10.1016/j.cmet.2024.06.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 06/13/2024] [Accepted: 06/13/2024] [Indexed: 07/05/2024]
Abstract
The factors determining levels of pathogenic mitochondrial DNA in cells and tissues are critical to disease pathology but remain poorly understood and contentious. In Nature, Kotrys et al. published a single-cell-based analysis casting fresh light on this thorny problem and introduced a powerful new investigative tool.
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Affiliation(s)
- Sarah J Pickett
- Mitochondrial Research Group, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK; Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Robert W Taylor
- Mitochondrial Research Group, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK; NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK
| | - Robert McFarland
- Mitochondrial Research Group, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK; NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE1 4LP, UK.
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21
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Bilous M, Hérault L, Gabriel AA, Teleman M, Gfeller D. Building and analyzing metacells in single-cell genomics data. Mol Syst Biol 2024; 20:744-766. [PMID: 38811801 PMCID: PMC11220014 DOI: 10.1038/s44320-024-00045-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 05/03/2024] [Accepted: 05/08/2024] [Indexed: 05/31/2024] Open
Abstract
The advent of high-throughput single-cell genomics technologies has fundamentally transformed biological sciences. Currently, millions of cells from complex biological tissues can be phenotypically profiled across multiple modalities. The scaling of computational methods to analyze and visualize such data is a constant challenge, and tools need to be regularly updated, if not redesigned, to cope with ever-growing numbers of cells. Over the last few years, metacells have been introduced to reduce the size and complexity of single-cell genomics data while preserving biologically relevant information and improving interpretability. Here, we review recent studies that capitalize on the concept of metacells-and the many variants in nomenclature that have been used. We further outline how and when metacells should (or should not) be used to analyze single-cell genomics data and what should be considered when analyzing such data at the metacell level. To facilitate the exploration of metacells, we provide a comprehensive tutorial on the construction and analysis of metacells from single-cell RNA-seq data ( https://github.com/GfellerLab/MetacellAnalysisTutorial ) as well as a fully integrated pipeline to rapidly build, visualize and evaluate metacells with different methods ( https://github.com/GfellerLab/MetacellAnalysisToolkit ).
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Affiliation(s)
- Mariia Bilous
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, 1011, Lausanne, Switzerland
- Agora Cancer Research Centre, 1011, Lausanne, Switzerland
- Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland
| | - Léonard Hérault
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, 1011, Lausanne, Switzerland
- Agora Cancer Research Centre, 1011, Lausanne, Switzerland
- Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland
| | - Aurélie Ag Gabriel
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, 1011, Lausanne, Switzerland
- Agora Cancer Research Centre, 1011, Lausanne, Switzerland
- Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland
| | - Matei Teleman
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, 1011, Lausanne, Switzerland
- Agora Cancer Research Centre, 1011, Lausanne, Switzerland
- Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland
| | - David Gfeller
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, 1011, Lausanne, Switzerland.
- Agora Cancer Research Centre, 1011, Lausanne, Switzerland.
- Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
- Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland.
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22
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Gao SM, Qi Y, Zhang Q, Guan Y, Lee YT, Ding L, Wang L, Mohammed AS, Li H, Fu Y, Wang MC. Aging atlas reveals cell-type-specific effects of pro-longevity strategies. NATURE AGING 2024; 4:998-1013. [PMID: 38816550 PMCID: PMC11257944 DOI: 10.1038/s43587-024-00631-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 04/10/2024] [Indexed: 06/01/2024]
Abstract
Organismal aging involves functional declines in both somatic and reproductive tissues. Multiple strategies have been discovered to extend lifespan across species. However, how age-related molecular changes differ among various tissues and how those lifespan-extending strategies slow tissue aging in distinct manners remain unclear. Here we generated the transcriptomic Cell Atlas of Worm Aging (CAWA, http://mengwanglab.org/atlas ) of wild-type and long-lived strains. We discovered cell-specific, age-related molecular and functional signatures across all somatic and germ cell types. We developed transcriptomic aging clocks for different tissues and quantitatively determined how three different pro-longevity strategies slow tissue aging distinctively. Furthermore, through genome-wide profiling of alternative polyadenylation (APA) events in different tissues, we discovered cell-type-specific APA changes during aging and revealed how these changes are differentially affected by the pro-longevity strategies. Together, this study offers fundamental molecular insights into both somatic and reproductive aging and provides a valuable resource for in-depth understanding of the diversity of pro-longevity mechanisms.
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Affiliation(s)
- Shihong Max Gao
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Program in Developmental Biology, Baylor College of Medicine, Houston, TX, USA
| | - Yanyan Qi
- Huffington Center on Aging, Baylor College of Medicine, Houston, TX, USA
| | - Qinghao Zhang
- Huffington Center on Aging, Baylor College of Medicine, Houston, TX, USA
| | - Youchen Guan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Molecular and Cellular Biology Graduate Program, Baylor College of Medicine, Houston, TX, USA
| | - Yi-Tang Lee
- Integrative Program of Molecular and Biochemical Science, Baylor College of Medicine, Houston, TX, USA
| | - Lang Ding
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Graduate Program in Chemical, Physical & Structural Biology, Graduate School of Biomedical Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Lihua Wang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Aaron S Mohammed
- Department of Biomedical Sciences, Creighton University School of Medicine, Omaha, NE, USA
| | - Hongjie Li
- Huffington Center on Aging, Baylor College of Medicine, Houston, TX, USA.
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
| | - Yusi Fu
- Huffington Center on Aging, Baylor College of Medicine, Houston, TX, USA.
- Department of Biomedical Sciences, Creighton University School of Medicine, Omaha, NE, USA.
| | - Meng C Wang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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23
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Chang X, Zheng Y, Xu K. Single-Cell RNA Sequencing: Technological Progress and Biomedical Application in Cancer Research. Mol Biotechnol 2024; 66:1497-1519. [PMID: 37322261 PMCID: PMC11217094 DOI: 10.1007/s12033-023-00777-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 05/23/2023] [Indexed: 06/17/2023]
Abstract
Single-cell RNA-seq (scRNA-seq) is a revolutionary technology that allows for the genomic investigation of individual cells in a population, allowing for the discovery of unusual cells associated with cancer and metastasis. ScRNA-seq has been used to discover different types of cancers with poor prognosis and medication resistance such as lung cancer, breast cancer, ovarian cancer, and gastric cancer. Besides, scRNA-seq is a promising method that helps us comprehend the biological features and dynamics of cell development, as well as other disorders. This review gives a concise summary of current scRNA-seq technology. We also explain the main technological steps involved in implementing the technology. We highlight the present applications of scRNA-seq in cancer research, including tumor heterogeneity analysis in lung cancer, breast cancer, and ovarian cancer. In addition, this review elucidates potential applications of scRNA-seq in lineage tracing, personalized medicine, illness prediction, and disease diagnosis, which reveals that scRNA-seq facilitates these events by producing genetic variations on the single-cell level.
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Affiliation(s)
- Xu Chang
- Department of Otolaryngology, Head and Neck Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, 330006, Jiangxi, People's Republic of China
| | - Yunxi Zheng
- Department of Otolaryngology, Head and Neck Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, 330006, Jiangxi, People's Republic of China
| | - Kai Xu
- Department of Otolaryngology, Head and Neck Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, 330006, Jiangxi, People's Republic of China.
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24
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Korshoj LE, Kielian T. Bacterial single-cell RNA sequencing captures biofilm transcriptional heterogeneity and differential responses to immune pressure. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.28.601229. [PMID: 38979200 PMCID: PMC11230364 DOI: 10.1101/2024.06.28.601229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Biofilm formation is an important mechanism of survival and persistence for many bacterial pathogens. These multicellular communities contain subpopulations of cells that display vast metabolic and transcriptional diversity along with high recalcitrance to antibiotics and host immune defenses. Investigating the complex heterogeneity within biofilm has been hindered by the lack of a sensitive and high-throughput method to assess stochastic transcriptional activity and regulation between bacterial subpopulations, which requires single-cell resolution. We have developed an optimized bacterial single-cell RNA sequencing method, BaSSSh-seq, to study Staphylococcus aureus diversity during biofilm growth and transcriptional adaptations following immune cell exposure. We validated the ability of BaSSSh-seq to capture extensive transcriptional heterogeneity during biofilm compared to planktonic growth. Application of new computational tools revealed transcriptional regulatory networks across the heterogeneous biofilm subpopulations and identification of gene sets that were associated with a trajectory from planktonic to biofilm growth. BaSSSh-seq also detected alterations in biofilm metabolism, stress response, and virulence that were tailored to distinct immune cell populations. This work provides an innovative platform to explore biofilm dynamics at single-cell resolution, unlocking the potential for identifying biofilm adaptations to environmental signals and immune pressure.
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25
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Campos TL, Korhonen PK, Young ND, Wang T, Song J, Marhoefer R, Chang BCH, Selzer PM, Gasser RB. Inference of Essential Genes of the Parasite Haemonchus contortus via Machine Learning. Int J Mol Sci 2024; 25:7015. [PMID: 39000124 PMCID: PMC11240989 DOI: 10.3390/ijms25137015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 06/19/2024] [Accepted: 06/21/2024] [Indexed: 07/16/2024] Open
Abstract
Over the years, comprehensive explorations of the model organisms Caenorhabditis elegans (elegant worm) and Drosophila melanogaster (vinegar fly) have contributed substantially to our understanding of complex biological processes and pathways in multicellular organisms generally. Extensive functional genomic-phenomic, genomic, transcriptomic, and proteomic data sets have enabled the discovery and characterisation of genes that are crucial for life, called 'essential genes'. Recently, we investigated the feasibility of inferring essential genes from such data sets using advanced bioinformatics and showed that a machine learning (ML)-based workflow could be used to extract or engineer features from DNA, RNA, protein, and/or cellular data/information to underpin the reliable prediction of essential genes both within and between C. elegans and D. melanogaster. As these are two distantly related species within the Ecdysozoa, we proposed that this ML approach would be particularly well suited for species that are within the same phylum or evolutionary clade. In the present study, we cross-predicted essential genes within the phylum Nematoda (evolutionary clade V)-between C. elegans and the pathogenic parasitic nematode H. contortus-and then ranked and prioritised H. contortus proteins encoded by these genes as intervention (e.g., drug) target candidates. Using strong, validated predictors, we inferred essential genes of H. contortus that are involved predominantly in crucial biological processes/pathways including ribosome biogenesis, translation, RNA binding/processing, and signalling and which are highly transcribed in the germline, somatic gonad precursors, sex myoblasts, vulva cell precursors, various nerve cells, glia, or hypodermis. The findings indicate that this in silico workflow provides a promising avenue to identify and prioritise panels/groups of drug target candidates in parasitic nematodes for experimental validation in vitro and/or in vivo.
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Affiliation(s)
- Túlio L Campos
- Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia
- Bioinformatics Core Facility, Aggeu Magalhães Institute (Fiocruz), Recife 50740-465, PE, Brazil
| | - Pasi K Korhonen
- Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Neil D Young
- Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Tao Wang
- Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Jiangning Song
- Department of Data Science and AI, Faculty of IT, Monash University, Melbourne, VIC 3800, Australia
- Biomedicine Discovery Institute, Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia
- Monash Data Futures Institute, Monash University, Clayton, VIC 3800, Australia
| | - Richard Marhoefer
- Boehringer Ingelheim Animal Health, Binger Strasse 173, 55216 Ingelheim am Rhein, Germany
| | - Bill C H Chang
- Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Paul M Selzer
- Boehringer Ingelheim Animal Health, Binger Strasse 173, 55216 Ingelheim am Rhein, Germany
| | - Robin B Gasser
- Department of Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia
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26
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Shen K, Durieux J, Mena CG, Webster BM, Tsui CK, Zhang H, Joe L, Berendzen KM, Dillin A. The germline coordinates mitokine signaling. Cell 2024:S0092-8674(24)00650-0. [PMID: 38959891 DOI: 10.1016/j.cell.2024.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 04/01/2024] [Accepted: 06/08/2024] [Indexed: 07/05/2024]
Abstract
The ability of mitochondria to coordinate stress responses across tissues is critical for health. In C. elegans, neurons experiencing mitochondrial stress elicit an inter-tissue signaling pathway through the release of mitokine signals, such as serotonin or the Wnt ligand EGL-20, which activate the mitochondrial unfolded protein response (UPRMT) in the periphery to promote organismal health and lifespan. We find that germline mitochondria play a surprising role in neuron-to-periphery UPRMT signaling. Specifically, we find that germline mitochondria signal downstream of neuronal mitokines, Wnt and serotonin, and upstream of lipid metabolic pathways in the periphery to regulate UPRMT activation. We also find that the germline tissue itself is essential for UPRMT signaling. We propose that the germline has a central signaling role in coordinating mitochondrial stress responses across tissues, and germline mitochondria play a defining role in this coordination because of their inherent roles in germline integrity and inter-tissue signaling.
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Affiliation(s)
- Koning Shen
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Jenni Durieux
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Cesar G Mena
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Brant M Webster
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - C Kimberly Tsui
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Hanlin Zhang
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Larry Joe
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Kristen M Berendzen
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Andrew Dillin
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA 94720, USA; The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA.
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27
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Bardan Sarmiento M, Gang SS, van Oosten-Hawle P, Troemel ER. CUL-6/cullin ubiquitin ligase-mediated degradation of HSP-90 by intestinal lysosomes promotes thermotolerance. Cell Rep 2024; 43:114279. [PMID: 38795346 PMCID: PMC11238739 DOI: 10.1016/j.celrep.2024.114279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 04/10/2024] [Accepted: 05/10/2024] [Indexed: 05/27/2024] Open
Abstract
Heat shock can be a lethal stressor. Previously, we described a CUL-6/cullin-ring ubiquitin ligase complex in the nematode Caenorhabditis elegans that is induced by intracellular intestinal infection and proteotoxic stress and that promotes improved survival upon heat shock (thermotolerance). Here, we show that CUL-6 promotes thermotolerance by targeting the heat shock protein HSP-90 for degradation. We show that CUL-6-mediated lowering of HSP-90 protein levels, specifically in the intestine, improves thermotolerance. Furthermore, we show that lysosomal function is required for CUL-6-mediated promotion of thermotolerance and that CUL-6 directs HSP-90 to lysosome-related organelles upon heat shock. Altogether, these results indicate that a CUL-6 ubiquitin ligase promotes organismal survival upon heat shock by promoting HSP-90 degradation in intestinal lysosomes. Thus, HSP-90, a protein commonly associated with protection against heat shock and promoting degradation of other proteins, is itself degraded to protect against heat shock.
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Affiliation(s)
| | - Spencer S Gang
- School of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
| | | | - Emily R Troemel
- School of Biological Sciences, University of California, San Diego, La Jolla, CA, USA.
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28
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Sheloukhova L, Watanabe H. Evolution of glial cells: a non-bilaterian perspective. Neural Dev 2024; 19:10. [PMID: 38907299 PMCID: PMC11193209 DOI: 10.1186/s13064-024-00184-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 06/06/2024] [Indexed: 06/23/2024] Open
Abstract
Nervous systems of bilaterian animals generally consist of two cell types: neurons and glial cells. Despite accumulating data about the many important functions glial cells serve in bilaterian nervous systems, the evolutionary origin of this abundant cell type remains unclear. Current hypotheses regarding glial evolution are mostly based on data from model bilaterians. Non-bilaterian animals have been largely overlooked in glial studies and have been subjected only to morphological analysis. Here, we provide a comprehensive overview of conservation of the bilateral gliogenic genetic repertoire of non-bilaterian phyla (Cnidaria, Placozoa, Ctenophora, and Porifera). We overview molecular and functional features of bilaterian glial cell types and discuss their possible evolutionary history. We then examine which glial features are present in non-bilaterians. Of these, cnidarians show the highest degree of gliogenic program conservation and may therefore be crucial to answer questions about glial evolution.
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Affiliation(s)
- Larisa Sheloukhova
- Evolutionary Neurobiology Unit, Okinawa Institute of Science and Technology, 1919-1 Tancha, Onna-son, Kunigami-gun, Okinawa, 904-0412, Japan
| | - Hiroshi Watanabe
- Evolutionary Neurobiology Unit, Okinawa Institute of Science and Technology, 1919-1 Tancha, Onna-son, Kunigami-gun, Okinawa, 904-0412, Japan.
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29
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Bhuiyan SA, Xu M, Yang L, Semizoglou E, Bhatia P, Pantaleo KI, Tochitsky I, Jain A, Erdogan B, Blair S, Cat V, Mwirigi JM, Sankaranarayanan I, Tavares-Ferreira D, Green U, McIlvried LA, Copits BA, Bertels Z, Del Rosario JS, Widman AJ, Slivicki RA, Yi J, Sharif-Naeini R, Woolf CJ, Lennerz JK, Whited JL, Price TJ, Robert W Gereau Iv, Renthal W. Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia. SCIENCE ADVANCES 2024; 10:eadj9173. [PMID: 38905344 DOI: 10.1126/sciadv.adj9173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 05/16/2024] [Indexed: 06/23/2024]
Abstract
Sensory neurons in the dorsal root ganglion (DRG) and trigeminal ganglion (TG) are specialized to detect and transduce diverse environmental stimuli to the central nervous system. Single-cell RNA sequencing has provided insights into the diversity of sensory ganglia cell types in rodents, nonhuman primates, and humans, but it remains difficult to compare cell types across studies and species. We thus constructed harmonized atlases of the DRG and TG that describe and facilitate comparison of 18 neuronal and 11 non-neuronal cell types across six species and 31 datasets. We then performed single-cell/nucleus RNA sequencing of DRG from both human and the highly regenerative axolotl and found that the harmonized atlas also improves cell type annotation, particularly of sparse neuronal subtypes. We observed that the transcriptomes of sensory neuron subtypes are broadly similar across vertebrates, but the expression of functionally important neuropeptides and channels can vary notably. The resources presented here can guide future studies in comparative transcriptomics, simplify cell-type nomenclature differences across studies, and help prioritize targets for future analgesic development.
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Affiliation(s)
- Shamsuddin A Bhuiyan
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Mengyi Xu
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
- Alan Edwards Center for Research on Pain and Department of Physiology, McGill University, Montreal, QC, H3G 1Y6, Canada
| | - Lite Yang
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
- Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Evangelia Semizoglou
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Parth Bhatia
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Katerina I Pantaleo
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ivan Tochitsky
- F.M. Kirby Neurobiology Center and Department of Neurobiology, Boston Children's Hospital and Harvard Medical School, 3 Blackfan Cir., Boston, MA 02115, USA
| | - Aakanksha Jain
- F.M. Kirby Neurobiology Center and Department of Neurobiology, Boston Children's Hospital and Harvard Medical School, 3 Blackfan Cir., Boston, MA 02115, USA
| | - Burcu Erdogan
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Steven Blair
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Victor Cat
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Juliet M Mwirigi
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX, 75080, USA
| | - Ishwarya Sankaranarayanan
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX, 75080, USA
| | - Diana Tavares-Ferreira
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX, 75080, USA
| | - Ursula Green
- Department of Pathology, Center for Integrated Diagnostics, Massachussetts General Hospital and Havard Medical School, Boston, MA 02114, USA
| | - Lisa A McIlvried
- Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Bryan A Copits
- Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Zachariah Bertels
- Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - John S Del Rosario
- Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Allie J Widman
- Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Richard A Slivicki
- Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Jiwon Yi
- Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Reza Sharif-Naeini
- Alan Edwards Center for Research on Pain and Department of Physiology, McGill University, Montreal, QC, H3G 1Y6, Canada
| | - Clifford J Woolf
- F.M. Kirby Neurobiology Center and Department of Neurobiology, Boston Children's Hospital and Harvard Medical School, 3 Blackfan Cir., Boston, MA 02115, USA
| | - Jochen K Lennerz
- Department of Pathology, Center for Integrated Diagnostics, Massachussetts General Hospital and Havard Medical School, Boston, MA 02114, USA
| | - Jessica L Whited
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Theodore J Price
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX, 75080, USA
| | - Robert W Gereau Iv
- Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - William Renthal
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
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30
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Tan CH, Wang TY, Park H, Lomenick B, Chou TF, Sternberg PW. Single-tissue proteomics in Caenorhabditis elegans reveals proteins resident in intestinal lysosome-related organelles. Proc Natl Acad Sci U S A 2024; 121:e2322588121. [PMID: 38861598 PMCID: PMC11194598 DOI: 10.1073/pnas.2322588121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Accepted: 05/06/2024] [Indexed: 06/13/2024] Open
Abstract
The nematode intestine is the primary site for nutrient uptake and storage as well as the synthesis of biomolecules; lysosome-related organelles known as gut granules are important for many of these functions. Aspects of intestine biology are not well understood, including the export of the nutrients it imports and the molecules it synthesizes, as well as the complete functions and protein content of the gut granules. Here, we report a mass spectrometry (MS)-based proteomic analysis of the intestine of the Caenorhabditis elegans and of its gut granules. Overall, we identified approximately 5,000 proteins each in the intestine and the gonad and showed that most of these proteins can be detected in samples extracted from a single worm, suggesting the feasibility of individual-level genetic analysis using proteomes. Comparing proteomes and published transcriptomes of the intestine and the gonad, we identified proteins that appear to be synthesized in the intestine and then transferred to the gonad. To identify gut granule proteins, we compared the proteome of individual intestines deficient in gut granules to the wild type. The identified gut granule proteome includes proteins known to be exclusively localized to the granules and additional putative gut granule proteins. We selected two of these putative gut granule proteins for validation via immunohistochemistry, and our successful confirmation of both suggests that our strategy was effective in identifying the gut granule proteome. Our results demonstrate the practicability of single-tissue MS-based proteomic analysis in small organisms and in its future utility.
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Affiliation(s)
- Chieh-Hsiang Tan
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125
| | - Ting-Yu Wang
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, Pasadena, CA 91125
| | - Heenam Park
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125
| | - Brett Lomenick
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, Pasadena, CA 91125
| | - Tsui-Fen Chou
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, Pasadena, CA 91125
| | - Paul W Sternberg
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125
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31
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Peysson A, Zariohi N, Gendrel M, Chambert-Loir A, Frébault N, Cheynet E, Andrini O, Boulin T. Wnt-Ror-Dvl signalling and the dystrophin complex organize planar-polarized membrane compartments in C. elegans muscles. Nat Commun 2024; 15:4935. [PMID: 38858388 PMCID: PMC11164867 DOI: 10.1038/s41467-024-49154-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 05/24/2024] [Indexed: 06/12/2024] Open
Abstract
Cell polarity mechanisms allow the formation of specialized membrane domains with unique protein compositions, signalling properties, and functional characteristics. By analyzing the localization of potassium channels and proteins belonging to the dystrophin-associated protein complex, we reveal the existence of distinct planar-polarized membrane compartments at the surface of C. elegans muscle cells. We find that muscle polarity is controlled by a non-canonical Wnt signalling cascade involving the ligand EGL-20/Wnt, the receptor CAM-1/Ror, and the intracellular effector DSH-1/Dishevelled. Interestingly, classical planar cell polarity proteins are not required for this process. Using time-resolved protein degradation, we demonstrate that -while it is essentially in place by the end of embryogenesis- muscle polarity is a dynamic state, requiring continued presence of DSH-1 throughout post-embryonic life. Our results reveal the unsuspected complexity of the C. elegans muscle membrane and establish a genetically tractable model system to study cellular polarity and membrane compartmentalization in vivo.
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Affiliation(s)
- Alice Peysson
- Université Claude Bernard Lyon 1, CNRS UMR 5284, INSERM U1314, MeLiS, Lyon, 69008, France
| | - Noura Zariohi
- Université Claude Bernard Lyon 1, CNRS UMR 5284, INSERM U1314, MeLiS, Lyon, 69008, France
| | - Marie Gendrel
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, Université Paris Sciences et Lettres Research University, Paris, 75005, France
| | - Amandine Chambert-Loir
- Université Claude Bernard Lyon 1, CNRS UMR 5284, INSERM U1314, MeLiS, Lyon, 69008, France
| | - Noémie Frébault
- Université Claude Bernard Lyon 1, CNRS UMR 5284, INSERM U1314, MeLiS, Lyon, 69008, France
| | - Elise Cheynet
- Université Claude Bernard Lyon 1, CNRS UMR 5284, INSERM U1314, MeLiS, Lyon, 69008, France
| | - Olga Andrini
- Université Claude Bernard Lyon 1, CNRS UMR 5284, INSERM U1314, MeLiS, Lyon, 69008, France
| | - Thomas Boulin
- Université Claude Bernard Lyon 1, CNRS UMR 5284, INSERM U1314, MeLiS, Lyon, 69008, France.
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32
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Zheng Y, Cong X, Liu H, Storey KB, Chen M. Neuronal cell populations in circumoral nerve ring of sea cucumber Apostichopus japonicus: Ultrastructure and transcriptional profile. COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY. PART D, GENOMICS & PROTEOMICS 2024; 52:101263. [PMID: 38850626 DOI: 10.1016/j.cbd.2024.101263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 05/24/2024] [Accepted: 06/03/2024] [Indexed: 06/10/2024]
Abstract
The echinoderm nervous system has been studied as a model for understanding the evolution of the chordate nervous system. Neuronal cells are essential groups that release a 'cocktail' of messenger molecules providing a spectrum of biological actions in the nervous system. Among echinoderms, most evidence on neuronal cell types has been obtained from starfish and sea urchin. In sea cucumbers, most research has focused on the location of neuronal cells, whereas their transcriptional features have rarely been investigated. Here, we observed the ultrastructure of neuronal cells in the sea cucumber, Apostichopus japonicus. The transcriptional profile of neuronal cells from the circumoral nerve ring (CNR) was investigated using single-cell RNA sequencing (scRNA-seq), and a total of six neuronal cell types were identified. 26 neuropeptide precursor genes (NPPs) and 28 G-protein-coupled receptors (GPCR) were expressed in the six neuronal cell types, comprising five NPP/NP-GPCR pairs. Unsupervised pseudotime analysis of neuronal cells showed their different differentiation status. We also located the neuronal cells in the CNR by immunofluorescence (IF) and identified the potential hub genes of key cell populations. This broad resource serves as a valuable support in the development of cell-specific markers for accurate cell-type identification in sea cucumbers. It also contributes to facilitating comparison across species, providing a deeper understanding of the evolutionary processes of neuronal cells.
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Affiliation(s)
- Yingqiu Zheng
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, PR China. https://twitter.com/Yingqiu_Zheng
| | - Xiao Cong
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, PR China
| | - Huachen Liu
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, PR China
| | - Kenneth B Storey
- Institute of Biochemistry, Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S 5B6, Canada
| | - Muyan Chen
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, PR China.
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33
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Lyu J, Chen C. Linearly Amplified Single-Stranded RNA-Derived Transcriptome Sequencing (LAST-seq). Bio Protoc 2024; 14:e4998. [PMID: 38873015 PMCID: PMC11166533 DOI: 10.21769/bioprotoc.4998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 05/08/2024] [Indexed: 06/15/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) stands as a cutting-edge technology widely used in biological and biomedical research. Existing scRNA-seq methods rely on reverse transcription (RT) and second-strand synthesis (SSS) to convert RNA to cDNA before amplification. However, these methods often suffer from limited RT/SSS efficiency, which compromises the sensitivity of RNA detection. Here, we develop a new method, linearly amplified single-stranded RNA-derived transcriptome sequencing (LAST-seq), which directly amplifies the original single-stranded RNA without prior RT and SSS and offers high-sensitivity RNA detection and a low level of technical noise in single-cell transcriptome analysis. LAST-seq has been applied to quantify transcriptional bursting kinetics in human cells, advancing our understanding of chromatin organization's role in regulating gene expression. Key features • An RNase H/DNA polymerase-based strategy to attach the T7 promoter to single-stranded RNA. • T7 promoter mediated IVT on single stranded RNA template at single cell level.
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Affiliation(s)
- Jun Lyu
- Laboratory of Biochemistry and Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Chongyi Chen
- Laboratory of Biochemistry and Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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34
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Gupta P, O’Neill H, Wolvetang E, Chatterjee A, Gupta I. Advances in single-cell long-read sequencing technologies. NAR Genom Bioinform 2024; 6:lqae047. [PMID: 38774511 PMCID: PMC11106032 DOI: 10.1093/nargab/lqae047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/18/2024] [Accepted: 04/29/2024] [Indexed: 05/24/2024] Open
Abstract
With an increase in accuracy and throughput of long-read sequencing technologies, they are rapidly being assimilated into the single-cell sequencing pipelines. For transcriptome sequencing, these techniques provide RNA isoform-level information in addition to the gene expression profiles. Long-read sequencing technologies not only help in uncovering complex patterns of cell-type specific splicing, but also offer unprecedented insights into the origin of cellular complexity and thus potentially new avenues for drug development. Additionally, single-cell long-read DNA sequencing enables high-quality assemblies, structural variant detection, haplotype phasing, resolving high-complexity regions, and characterization of epigenetic modifications. Given that significant progress has primarily occurred in single-cell RNA isoform sequencing (scRiso-seq), this review will delve into these advancements in depth and highlight the practical considerations and operational challenges, particularly pertaining to downstream analysis. We also aim to offer a concise introduction to complementary technologies for single-cell sequencing of the genome, epigenome and epitranscriptome. We conclude by identifying certain key areas of innovation that may drive these technologies further and foster more widespread application in biomedical science.
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Affiliation(s)
- Pallavi Gupta
- University of Queensland – IIT Delhi Research Academy, Hauz Khas, New Delhi 110016, India
- Australian Institute of Bioengineering and Nanotechnology (AIBN), The University of Queensland, St Lucia, QLD 4072, Australia
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
| | - Hannah O’Neill
- Department of Pathology, Dunedin School of Medicine, University of Otago, 58 Hanover Street, Dunedin 9054, New Zealand
| | - Ernst J Wolvetang
- Australian Institute of Bioengineering and Nanotechnology (AIBN), The University of Queensland, St Lucia, QLD 4072, Australia
| | - Aniruddha Chatterjee
- Department of Pathology, Dunedin School of Medicine, University of Otago, 58 Hanover Street, Dunedin 9054, New Zealand
| | - Ishaan Gupta
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
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35
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Ma F, Zheng C. Single-cell phylotranscriptomics of developmental and cell type evolution. Trends Genet 2024; 40:495-510. [PMID: 38490933 DOI: 10.1016/j.tig.2024.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 02/16/2024] [Accepted: 02/16/2024] [Indexed: 03/17/2024]
Abstract
Single-cell phylotranscriptomics is an emerging tool to reveal the molecular and cellular mechanisms of evolution. We summarize its utility in studying the hourglass pattern of ontogenetic evolution and for understanding the evolutionary history of cell types. The developmental hourglass model suggests that the mid-embryonic stage is the most conserved period of development across species, which is supported by morphological and molecular studies. Single-cell phylotranscriptomic analysis has revealed previously underappreciated heterogeneity in transcriptome ages among lineages and cell types throughout development, and has identified the lineages and tissues that drive the whole-organism hourglass pattern. Single-cell transcriptome age analyses also provide important insights into the origin of germ layers, the different selective forces on tissues during adaptation, and the evolutionary relationships between cell types.
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Affiliation(s)
- Fuqiang Ma
- School of Biological Sciences, The University of Hong Kong, Hong Kong SAR, China
| | - Chaogu Zheng
- School of Biological Sciences, The University of Hong Kong, Hong Kong SAR, China.
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36
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Kumar R, Zemaitis KJ, Fulcher JM, Paša-Tolić L. Advances in mass spectrometry-enabled multiomics at single-cell resolution. Curr Opin Biotechnol 2024; 87:103096. [PMID: 38432187 DOI: 10.1016/j.copbio.2024.103096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 02/06/2024] [Indexed: 03/05/2024]
Abstract
Biological organisms are multifaceted, intricate systems where slight perturbations can result in extensive changes in gene expression, protein abundance and/or activity, and metabolic flux. These changes occur at different timescales, spatially across cells of heterogeneous origins, and within single-cells. Hence, multimodal measurements at the smallest biological scales are necessary to capture dynamic changes in heterogeneous biological systems. Of the analytical techniques used to measure biomolecules, mass spectrometry (MS) has proven to be a powerful option due to its sensitivity, robustness, and flexibility with regard to the breadth of biomolecules that can be analyzed. Recently, many studies have coupled MS to other analytical techniques with the goal of measuring multiple modalities from the same single-cell. It is with these concepts in mind that we focus this review on MS-enabled multiomic measurements at single-cell or near-single- cell resolution.
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Affiliation(s)
- Rashmi Kumar
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Kevin J Zemaitis
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - James M Fulcher
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
| | - Ljiljana Paša-Tolić
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
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37
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Liu W, Li Q. Single-cell transcriptomics dissecting the development and evolution of nervous system in insects. CURRENT OPINION IN INSECT SCIENCE 2024; 63:101201. [PMID: 38608931 DOI: 10.1016/j.cois.2024.101201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 04/07/2024] [Accepted: 04/08/2024] [Indexed: 04/14/2024]
Abstract
Insects can display a vast repertoire of complex and adaptive behaviors crucial for survival and reproduction. Yet, how the neural circuits underlying insect behaviors are assembled throughout development and remodeled during evolution remains largely obscure. The advent of single-cell transcriptomics has opened new paths to illuminate these historically intractable questions. Insect behavior is governed by its brain, whose functional complexity is realized through operations across multiple levels, from the molecular and cellular to the circuit and organ. Single-cell transcriptomics enables dissecting brain functions across all these levels and allows tracking regulatory dynamics throughout development and under perturbation. In this review, we mainly focus on the achievements of single-cell transcriptomics in dissecting the molecular and cellular architectures of nervous systems in representative insects, then discuss its applications in tracking the developmental trajectory and functional evolution of insect brains.
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Affiliation(s)
- Weiwei Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Yunnan Key Laboratory of Biodiversity Information, Kunming, China.
| | - Qiye Li
- BGI Research, Shenzhen 518083, China; BGI Research, Wuhan 430074, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.
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38
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Chu LX, Wang WJ, Gu XP, Wu P, Gao C, Zhang Q, Wu J, Jiang DW, Huang JQ, Ying XW, Shen JM, Jiang Y, Luo LH, Xu JP, Ying YB, Chen HM, Fang A, Feng ZY, An SH, Li XK, Wang ZG. Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine. Mil Med Res 2024; 11:31. [PMID: 38797843 PMCID: PMC11129507 DOI: 10.1186/s40779-024-00537-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 05/07/2024] [Indexed: 05/29/2024] Open
Abstract
Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.
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Affiliation(s)
- Liu-Xi Chu
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Wen-Jia Wang
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Xin-Pei Gu
- School of Pharmaceutical Sciences, Guangdong Provincial Key Laboratory of New Drug Screening, Southern Medical University, Guangzhou, 510515, China
- Department of Human Anatomy, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China
| | - Ping Wu
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Chen Gao
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Quan Zhang
- Integrative Muscle Biology Laboratory, Division of Regenerative and Rehabilitative Sciences, University of Tennessee Health Science Center, Memphis, TN, 38163, United States
| | - Jia Wu
- Key Laboratory for Laboratory Medicine, Ministry of Education, Zhejiang Provincial Key Laboratory of Medical Genetics, School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Da-Wei Jiang
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Jun-Qing Huang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Hospital of Zhejiang University, Lishui, 323000, Zhejiang, China
| | - Xin-Wang Ying
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Jia-Men Shen
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Yi Jiang
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Li-Hua Luo
- School and Hospital of Stomatology, Wenzhou Medical University, Wenzhou, 324025, Zhejiang, China
| | - Jun-Peng Xu
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Yi-Bo Ying
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Hao-Man Chen
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Ao Fang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Zun-Yong Feng
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- Departments of Diagnostic Radiology, Surgery, Chemical and Biomolecular Engineering, and Biomedical Engineering, Yong Loo Lin School of Medicine and College of Design and Engineering, National University of Singapore, Singapore, 119074, Singapore.
- Clinical Imaging Research Centre, Centre for Translational Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117599, Singapore.
- Nanomedicine Translational Research Program, NUS Center for Nanomedicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117597, Singapore.
- Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research (A*STAR), Singapore, 138673, Singapore.
| | - Shu-Hong An
- Department of Human Anatomy, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China.
| | - Xiao-Kun Li
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
| | - Zhou-Guang Wang
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China.
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Hospital of Zhejiang University, Lishui, 323000, Zhejiang, China.
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39
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Shi W, Zhang J, Huang S, Fan Q, Cao J, Zeng J, Wu L, Yang C. Next-Generation Sequencing-Based Spatial Transcriptomics: A Perspective from Barcoding Chemistry. JACS AU 2024; 4:1723-1743. [PMID: 38818076 PMCID: PMC11134576 DOI: 10.1021/jacsau.4c00118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 03/22/2024] [Accepted: 03/26/2024] [Indexed: 06/01/2024]
Abstract
Gene expression profiling of tissue cells with spatial context is in high demand to reveal cell types, locations, and intercellular or molecular interactions for physiological and pathological studies. With rapid advances in barcoding chemistry and sequencing chemistry, spatially resolved transcriptome (SRT) techniques have emerged to quantify spatial gene expression in tissue samples by correlating transcripts with their spatial locations using diverse strategies. These techniques provide both physical tissue structure and molecular characteristics and are poised to revolutionize many fields, such as developmental biology, neuroscience, oncology, and histopathology. In this context, this Perspective focuses on next-generation sequencing-based SRT methods, particularly highlighting spatial barcoding chemistry. It delves into optically manipulated spatial indexing methods and DNA array-barcoded spatial indexing methods by exploring current advances, challenges, and future development directions in this nascent field.
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Affiliation(s)
- Weixiong Shi
- Institute
of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry
and Nanomedicine, Renji Hospital, Shanghai
Jiao Tong University School of Medicine, Shanghai 200127, China
- The
MOE Key Laboratory of Spectrochemical Analysis & Instrumentation,
Discipline of Intelligent Instrument and Equipment, Department of
Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Jing Zhang
- State
Key Laboratory of Cellular Stress Biology, School of Life Sciences,
Faculty of Medicine and Life Sciences, Xiamen
University, Xiamen 361102, China
| | - Shanqing Huang
- The
MOE Key Laboratory of Spectrochemical Analysis & Instrumentation,
Discipline of Intelligent Instrument and Equipment, Department of
Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Qian Fan
- Institute
of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry
and Nanomedicine, Renji Hospital, Shanghai
Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Jiao Cao
- Institute
of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry
and Nanomedicine, Renji Hospital, Shanghai
Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Jun Zeng
- Institute
of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry
and Nanomedicine, Renji Hospital, Shanghai
Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Lingling Wu
- Institute
of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry
and Nanomedicine, Renji Hospital, Shanghai
Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Chaoyong Yang
- Institute
of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry
and Nanomedicine, Renji Hospital, Shanghai
Jiao Tong University School of Medicine, Shanghai 200127, China
- The
MOE Key Laboratory of Spectrochemical Analysis & Instrumentation,
Discipline of Intelligent Instrument and Equipment, Department of
Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
- State
Key Laboratory of Cellular Stress Biology, School of Life Sciences,
Faculty of Medicine and Life Sciences, Xiamen
University, Xiamen 361102, China
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40
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Hong CKY, Ramu A, Zhao S, Cohen BA. Effect of genomic and cellular environments on gene expression noise. Genome Biol 2024; 25:137. [PMID: 38790076 PMCID: PMC11127367 DOI: 10.1186/s13059-024-03277-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND Individual cells from isogenic populations often display large cell-to-cell differences in gene expression. This "noise" in expression derives from several sources, including the genomic and cellular environment in which a gene resides. Large-scale maps of genomic environments have revealed the effects of epigenetic modifications and transcription factor occupancy on mean expression levels, but leveraging such maps to explain expression noise will require new methods to assay how expression noise changes at locations across the genome. RESULTS To address this gap, we present Single-cell Analysis of Reporter Gene Expression Noise and Transcriptome (SARGENT), a method that simultaneously measures the noisiness of reporter genes integrated throughout the genome and the global mRNA profiles of individual reporter-gene-containing cells. Using SARGENT, we perform the first comprehensive genome-wide survey of how genomic locations impact gene expression noise. We find that the mean and noise of expression correlate with different histone modifications. We quantify the intrinsic and extrinsic components of reporter gene noise and, using the associated mRNA profiles, assign the extrinsic component to differences between the CD24+ "stem-like" substate and the more "differentiated" substate. SARGENT also reveals the effects of transgene integrations on endogenous gene expression, which will help guide the search for "safe-harbor" loci. CONCLUSIONS Taken together, we show that SARGENT is a powerful tool to measure both the mean and noise of gene expression at locations across the genome and that the data generatd by SARGENT reveals important insights into the regulation of gene expression noise genome-wide.
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Affiliation(s)
- Clarice K Y Hong
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Avinash Ramu
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Siqi Zhao
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Barak A Cohen
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA.
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA.
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41
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Funk OH, Levy DL, Fay DS. Epidermal cell fusion promotes the transition from an embryonic to a larval transcriptome in C. elegans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.22.595354. [PMID: 38826300 PMCID: PMC11142173 DOI: 10.1101/2024.05.22.595354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Cell fusion is a fundamental process in the development of multicellular organisms, yet its impact on gene regulation, particularly during crucial developmental stages, remains poorly understood. The Caenorhabditis elegans epidermis comprises 8-10 syncytial cells, with the largest integrating 139 individual nuclei through cell-cell fusion governed by the fusogenic protein EFF-1. To explore the effects of cell fusion on developmental progression and associated gene expression changes, we conducted transcriptomic analyses of eff-1 fusion-deficient mutants. Our RNAseq findings showed widespread transcriptomic changes that were enriched for epidermal genes and key molecular pathways involved in epidermal function during larval development. Subsequent single-molecule fluorescence in situ hybridization validated the altered expression of mRNA transcripts, confirming quantifiable changes in gene expression in the absence of embryonic epidermal fusion. These results underscore the significance of cell-cell fusion in shaping transcriptional programs during development and raise questions regarding the precise identities and specialized functions of different subclasses of nuclei within developing syncytial cells and tissues.
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42
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Amontree J, Chen K, Varillas J, Fan ZH. A Capillary-Force-Driven, Single-Cell Transfer Method for Studying Rare Cells. Bioengineering (Basel) 2024; 11:542. [PMID: 38927778 PMCID: PMC11200440 DOI: 10.3390/bioengineering11060542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 06/28/2024] Open
Abstract
The characterization of individual cells within heterogeneous populations (e.g., rare tumor cells in healthy blood cells) has a great impact on biomedical research. To investigate the properties of these specific cells, such as genetic biomarkers and/or phenotypic characteristics, methods are often developed for isolating rare cells among a large number of background cells before studying their genetic makeup and others. Prior to using real-world samples, these methods are often evaluated and validated by spiking cells of interest (e.g., tumor cells) into a sample matrix (e.g., healthy blood) as model samples. However, spiking tumor cells at extremely low concentrations is challenging in a standard laboratory setting. People often circumvent the problem by diluting a solution of high-concentration cells, but the concentration becomes inaccurate after series dilution due to the fact that a cell suspension solution can be inhomogeneous, especially when the cell concentration is very low. We report on an alternative method for low-cost, accurate, and reproducible low-concentration cell spiking without the use of external pumping systems. By inducing a capillary force from sudden pressure drops, a small portion of the cellular membrane was aspirated into the reservoir tip, allowing for non-destructive single-cell transfer. We investigated the surface membrane tensions induced by cellular aspiration and studied a range of tip/tumor cell diameter combinations, ensuring that our method does not affect cell viability. In addition, we performed single-cell capture and transfer control experiments using human acute lymphoblastic leukemia cells (CCRF-CEM) to develop calibrated data for the general production of low-concentration samples. Finally, we performed affinity-based tumor cell isolation using this method to generate accurate concentrations ranging from 1 to 15 cells/mL.
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Affiliation(s)
- Jacob Amontree
- Interdisciplinary Microsystems Group (IMG), Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611, USA;
| | - Kangfu Chen
- Interdisciplinary Microsystems Group (IMG), Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611, USA;
- Department of Biomedical Engineering, Northwestern University, Chicago, IL 60611, USA
| | - Jose Varillas
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA;
| | - Z. Hugh Fan
- Interdisciplinary Microsystems Group (IMG), Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611, USA;
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA;
- Department of Chemistry, University of Florida, Gainesville, FL 32611, USA
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43
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Li L, Sun J, Fu Y, Changrob S, McGrath JJC, Wilson PC. A hybrid demultiplexing strategy that improves performance and robustness of cell hashing. Brief Bioinform 2024; 25:bbae254. [PMID: 38828640 PMCID: PMC11145454 DOI: 10.1093/bib/bbae254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 04/27/2024] [Accepted: 05/08/2024] [Indexed: 06/05/2024] Open
Abstract
Cell hashing, a nucleotide barcode-based method that allows users to pool multiple samples and demultiplex in downstream analysis, has gained widespread popularity in single-cell sequencing due to its compatibility, simplicity, and cost-effectiveness. Despite these advantages, the performance of this method remains unsatisfactory under certain circumstances, especially in experiments that have imbalanced sample sizes or use many hashtag antibodies. Here, we introduce a hybrid demultiplexing strategy that increases accuracy and cell recovery in multi-sample single-cell experiments. This approach correlates the results of cell hashing and genetic variant clustering, enabling precise and efficient cell identity determination without additional experimental costs or efforts. In addition, we developed HTOreader, a demultiplexing tool for cell hashing that improves the accuracy of cut-off calling by avoiding the dominance of negative signals in experiments with many hashtags or imbalanced sample sizes. When compared to existing methods using real-world datasets, this hybrid approach and HTOreader consistently generate reliable results with increased accuracy and cell recovery.
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Affiliation(s)
- Lei Li
- Gale and Ira Drukier Institute for Children’s Health, Weill Cornell Medicine, 413 E. 69th Street, New York, NY 10021, United States
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, United States
| | - Jiayi Sun
- Gale and Ira Drukier Institute for Children’s Health, Weill Cornell Medicine, 413 E. 69th Street, New York, NY 10021, United States
| | - Yanbin Fu
- Gale and Ira Drukier Institute for Children’s Health, Weill Cornell Medicine, 413 E. 69th Street, New York, NY 10021, United States
| | - Siriruk Changrob
- Gale and Ira Drukier Institute for Children’s Health, Weill Cornell Medicine, 413 E. 69th Street, New York, NY 10021, United States
| | - Joshua J C McGrath
- Gale and Ira Drukier Institute for Children’s Health, Weill Cornell Medicine, 413 E. 69th Street, New York, NY 10021, United States
| | - Patrick C Wilson
- Gale and Ira Drukier Institute for Children’s Health, Weill Cornell Medicine, 413 E. 69th Street, New York, NY 10021, United States
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44
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Nakayama A, Watanabe M, Yamashiro R, Kuroyanagi H, Matsuyama HJ, Oshima A, Mori I, Nakano S. A hyperpolarizing neuron recruits undocked innexin hemichannels to transmit neural information in Caenorhabditis elegans. Proc Natl Acad Sci U S A 2024; 121:e2406565121. [PMID: 38753507 PMCID: PMC11127054 DOI: 10.1073/pnas.2406565121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 04/19/2024] [Indexed: 05/18/2024] Open
Abstract
While depolarization of the neuronal membrane is known to evoke the neurotransmitter release from synaptic vesicles, hyperpolarization is regarded as a resting state of chemical neurotransmission. Here, we report that hyperpolarizing neurons can actively signal neural information by employing undocked hemichannels. We show that UNC-7, a member of the innexin family in Caenorhabditis elegans, functions as a hemichannel in thermosensory neurons and transmits temperature information from the thermosensory neurons to their postsynaptic interneurons. By monitoring neural activities in freely behaving animals, we find that hyperpolarizing thermosensory neurons inhibit the activity of the interneurons and that UNC-7 hemichannels regulate this process. UNC-7 is required to control thermotaxis behavior and functions independently of synaptic vesicle exocytosis. Our findings suggest that innexin hemichannels mediate neurotransmission from hyperpolarizing neurons in a manner that is distinct from the synaptic transmission, expanding the way of neural circuitry operations.
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Affiliation(s)
- Airi Nakayama
- Department of Biological Science, Graduate School of Science, Nagoya University, Nagoya, Aichi464-8602, Japan
| | - Masakatsu Watanabe
- Laboratory of Pattern Formation, Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka565-0871, Japan
| | - Riku Yamashiro
- Department of Biological Science, Graduate School of Science, Nagoya University, Nagoya, Aichi464-8602, Japan
| | - Hiroo Kuroyanagi
- Department of Biological Science, Graduate School of Science, Nagoya University, Nagoya, Aichi464-8602, Japan
| | - Hironori J. Matsuyama
- Group of Molecular Neurobiology, Neuroscience Institute, Graduate School of Science, Nagoya University, Nagoya, Aichi464-8602, Japan
| | - Atsunori Oshima
- Department of Basic Biology, Cellular and Structural Physiology Institute, Nagoya University, Chikusa, Nagoya464-8601, Japan
- Department of Basic Medicinal Sciences, Graduate School of Pharmaceutical Sciences, Nagoya University, Nagoya, Aichi464-8601, Japan
- Molecular Physiology Division, Institute for Glyco-core Research, Nagoya University, Chikusa-ku, Nagoya464-8601, Japan
- Division of Innovative Modality Development, Center for One Medicine Innovative Translational Research, Gifu University Institute for Advanced Study, Gifu501-11193, Japan
| | - Ikue Mori
- Group of Molecular Neurobiology, Neuroscience Institute, Graduate School of Science, Nagoya University, Nagoya, Aichi464-8602, Japan
- Chinese Institute for Brain Research, Changping District, Beijing102206, China
| | - Shunji Nakano
- Department of Biological Science, Graduate School of Science, Nagoya University, Nagoya, Aichi464-8602, Japan
- Group of Molecular Neurobiology, Neuroscience Institute, Graduate School of Science, Nagoya University, Nagoya, Aichi464-8602, Japan
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45
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Soni J, Pandey R. Single cell genomics based insights into the impact of cell-type specific microbial internalization on disease severity. Front Immunol 2024; 15:1401320. [PMID: 38835769 PMCID: PMC11148356 DOI: 10.3389/fimmu.2024.1401320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Accepted: 04/19/2024] [Indexed: 06/06/2024] Open
Abstract
Host-microbe interactions are complex and ever-changing, especially during infections, which can significantly impact human physiology in both health and disease by influencing metabolic and immune functions. Infections caused by pathogens such as bacteria, viruses, fungi, and parasites are the leading cause of global mortality. Microbes have evolved various immune evasion strategies to survive within their hosts, which presents a multifaceted challenge for detection. Intracellular microbes, in particular, target specific cell types for survival and replication and are influenced by factors such as functional roles, nutrient availability, immune evasion, and replication opportunities. Identifying intracellular microbes can be difficult because of the limitations of traditional culture-based methods. However, advancements in integrated host microbiome single-cell genomics and transcriptomics provide a promising basis for personalized treatment strategies. Understanding host-microbiota interactions at the cellular level may elucidate disease mechanisms and microbial pathogenesis, leading to targeted therapies. This article focuses on how intracellular microbes reside in specific cell types, modulating functions through persistence strategies to evade host immunity and prolong colonization. An improved understanding of the persistent intracellular microbe-induced differential disease outcomes can enhance diagnostics, therapeutics, and preventive measures.
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Affiliation(s)
- Jyoti Soni
- Division of Immunology and Infectious Disease Biology, INtegrative GENomics of HOst PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Rajesh Pandey
- Division of Immunology and Infectious Disease Biology, INtegrative GENomics of HOst PathogEn (INGEN-HOPE) Laboratory, Council of Scientific & Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
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46
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Samanta P, Cooke SF, McNulty R, Hormoz S, Rosenthal A. ProBac-seq, a bacterial single-cell RNA sequencing methodology using droplet microfluidics and large oligonucleotide probe sets. Nat Protoc 2024:10.1038/s41596-024-01002-1. [PMID: 38769144 DOI: 10.1038/s41596-024-01002-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 03/12/2024] [Indexed: 05/22/2024]
Abstract
Methods that measure the transcriptomic state of thousands of individual cells have transformed our understanding of cellular heterogeneity in eukaryotic cells since their introduction in the past decade. While simple and accessible protocols and commercial products are now available for the processing of mammalian cells, these existing technologies are incompatible with use in bacterial samples for several fundamental reasons including the absence of polyadenylation on bacterial messenger RNA, the instability of bacterial transcripts and the incompatibility of bacterial cell morphology with existing methodologies. Recently, we developed ProBac sequencing (ProBac-seq), a method that overcomes these technical difficulties and provides high-quality single-cell gene expression data from thousands of bacterial cells by using messenger RNA-specific probes. Here we provide details for designing large oligonucleotide probe sets for an organism of choice, amplifying probe sets to produce sufficient quantities for repeated experiments, adding unique molecular indexes and poly-A tails to produce finalized probes, in situ probe hybridization and single-cell encapsulation and library preparation. This protocol, from the probe amplification to the library preparation, requires ~7 d to complete. ProBac-seq offers several advantages over other methods by capturing only the desired target sequences and avoiding nondesired transcripts, such as highly abundant ribosomal RNA, thus enriching for signal that better informs on cellular state. The use of multiple probes per gene can detect meaningful single-cell signals from cells expressing transcripts to a lesser degree or those grown in minimal media and other environmentally relevant conditions in which cells are less active. ProBac-seq is also compatible with other organisms that can be profiled by in situ hybridization techniques.
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Affiliation(s)
- Prosenjit Samanta
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, USA
| | - Samuel F Cooke
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, USA
| | - Ryan McNulty
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Sahand Hormoz
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Adam Rosenthal
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, USA.
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47
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Huang S, Shi W, Li S, Fan Q, Yang C, Cao J, Wu L. Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis. LAB ON A CHIP 2024; 24:2601-2621. [PMID: 38669201 DOI: 10.1039/d4lc00105b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/28/2024]
Abstract
Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.
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Affiliation(s)
- Shanqing Huang
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Weixiong Shi
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Shiyu Li
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Qian Fan
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
| | - Chaoyong Yang
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Jiao Cao
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
| | - Lingling Wu
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
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48
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Leite DJ, Schönauer A, Blakeley G, Harper A, Garcia-Castro H, Baudouin-Gonzalez L, Wang R, Sarkis N, Nikola AG, Koka VSP, Kenny NJ, Turetzek N, Pechmann M, Solana J, McGregor AP. An atlas of spider development at single-cell resolution provides new insights into arthropod embryogenesis. EvoDevo 2024; 15:5. [PMID: 38730509 PMCID: PMC11083766 DOI: 10.1186/s13227-024-00224-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 04/15/2024] [Indexed: 05/13/2024] Open
Abstract
Spiders are a diverse order of chelicerates that diverged from other arthropods over 500 million years ago. Research on spider embryogenesis, particularly studies using the common house spider Parasteatoda tepidariorum, has made important contributions to understanding the evolution of animal development, including axis formation, segmentation, and patterning. However, we lack knowledge about the cells that build spider embryos, their gene expression profiles and fate. Single-cell transcriptomic analyses have been revolutionary in describing these complex landscapes of cellular genetics in a range of animals. Therefore, we carried out single-cell RNA sequencing of P. tepidariorum embryos at stages 7, 8 and 9, which encompass the establishment and patterning of the body plan, and initial differentiation of many tissues and organs. We identified 20 cell clusters, from 18.5 k cells, which were marked by many developmental toolkit genes, as well as a plethora of genes not previously investigated. We found differences in the cell cycle transcriptional signatures, suggestive of different proliferation dynamics, which related to distinctions between endodermal and some mesodermal clusters, compared with ectodermal clusters. We identified many Hox genes as markers of cell clusters, and Hox gene ohnologs were often present in different clusters. This provided additional evidence of sub- and/or neo-functionalisation of these important developmental genes after the whole genome duplication in an arachnopulmonate ancestor (spiders, scorpions, and related orders). We also examined the spatial expression of marker genes for each cluster to generate a comprehensive cell atlas of these embryonic stages. This revealed new insights into the cellular basis and genetic regulation of head patterning, hematopoiesis, limb development, gut development, and posterior segmentation. This atlas will serve as a platform for future analysis of spider cell specification and fate, and studying the evolution of these processes among animals at cellular resolution.
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Affiliation(s)
- Daniel J Leite
- Department of Biological and Medical Sciences, Oxford Brookes University, Oxford, OX3 0BP, UK.
- Department of Biosciences, Durham University, Durham, DH1 3LE, UK.
| | - Anna Schönauer
- Department of Biological and Medical Sciences, Oxford Brookes University, Oxford, OX3 0BP, UK
| | - Grace Blakeley
- Department of Biological and Medical Sciences, Oxford Brookes University, Oxford, OX3 0BP, UK
| | - Amber Harper
- Department of Biological and Medical Sciences, Oxford Brookes University, Oxford, OX3 0BP, UK
| | - Helena Garcia-Castro
- Department of Biological and Medical Sciences, Oxford Brookes University, Oxford, OX3 0BP, UK
| | | | - Ruixun Wang
- Institute for Zoology, Biocenter, University of Cologne, Zuelpicher Str. 47B, 50674, Cologne, Germany
| | - Naïra Sarkis
- Institute for Zoology, Biocenter, University of Cologne, Zuelpicher Str. 47B, 50674, Cologne, Germany
| | - Alexander Günther Nikola
- Evolutionary Ecology, Faculty of Biology, Biocenter, Ludwig-Maximilians-University Munich, Planegg-Martinsried, Germany
| | - Venkata Sai Poojitha Koka
- Evolutionary Ecology, Faculty of Biology, Biocenter, Ludwig-Maximilians-University Munich, Planegg-Martinsried, Germany
| | - Nathan J Kenny
- Department of Biological and Medical Sciences, Oxford Brookes University, Oxford, OX3 0BP, UK
- Department of Biochemistry Te Tari Matū Koiora, University of Otago, Dunedin, New Zealand
| | - Natascha Turetzek
- Evolutionary Ecology, Faculty of Biology, Biocenter, Ludwig-Maximilians-University Munich, Planegg-Martinsried, Germany
| | - Matthias Pechmann
- Institute for Zoology, Biocenter, University of Cologne, Zuelpicher Str. 47B, 50674, Cologne, Germany
| | - Jordi Solana
- Department of Biological and Medical Sciences, Oxford Brookes University, Oxford, OX3 0BP, UK.
| | - Alistair P McGregor
- Department of Biological and Medical Sciences, Oxford Brookes University, Oxford, OX3 0BP, UK.
- Department of Biosciences, Durham University, Durham, DH1 3LE, UK.
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49
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Lotfollahi M, Yuhan Hao, Theis FJ, Satija R. The future of rapid and automated single-cell data analysis using reference mapping. Cell 2024; 187:2343-2358. [PMID: 38729109 PMCID: PMC11184658 DOI: 10.1016/j.cell.2024.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 03/05/2024] [Accepted: 03/08/2024] [Indexed: 05/12/2024]
Abstract
As the number of single-cell datasets continues to grow rapidly, workflows that map new data to well-curated reference atlases offer enormous promise for the biological community. In this perspective, we discuss key computational challenges and opportunities for single-cell reference-mapping algorithms. We discuss how mapping algorithms will enable the integration of diverse datasets across disease states, molecular modalities, genetic perturbations, and diverse species and will eventually replace manual and laborious unsupervised clustering pipelines.
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Affiliation(s)
- Mohammad Lotfollahi
- Institute of Computational Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Neuherberg, Germany; Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Yuhan Hao
- Center for Genomics and Systems Biology, New York University, New York, NY, USA; New York Genome Center, New York, NY, USA
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Neuherberg, Germany; Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK; Department of Mathematics, Technical University of Munich, Garching, Germany.
| | - Rahul Satija
- Center for Genomics and Systems Biology, New York University, New York, NY, USA; New York Genome Center, New York, NY, USA.
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50
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VanDerMolen KR, Newman MA, Breen PC, Huff LA, Dowen RH. Non-cell-autonomous regulation of mTORC2 by Hedgehog signaling maintains lipid homeostasis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.06.592795. [PMID: 38766075 PMCID: PMC11100691 DOI: 10.1101/2024.05.06.592795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Organisms must appropriately allocate energetic resources between essential cellular processes to maintain homeostasis and in turn, maximize fitness. The nutritional and homeostatic regulators of energy homeostasis have been studied in detail; however, how developmental signals might impinge on these pathways to govern cellular metabolism is poorly understood. Here, we identify a non-canonical role for Hedgehog (Hh), a classic regulator of development, in maintaining intestinal lipid homeostasis in C. elegans . We find that expression of two Hh ligands, GRD-3 and GRD-4, is controlled by the LIN-29/EGR transcription factor in the hypodermis, where the Hh secretion factor CHE-14/Dispatched also facilitates non-cell autonomous Hh signaling. We demonstrate, using C. elegans and mouse hepatocytes, that Hh metabolic regulation does not occur through the canonical Hh transcription factor, TRA-1/GLI, but rather through non-canonical signaling that engages mTOR Complex 2 (mTORC2) in the intestine. Hh mutants display impaired lipid homeostasis, including reduced lipoprotein synthesis and fat accumulation, decreased growth, and upregulation of autophagy factors, mimicking loss of mTORC2. Additionally, we found that Hh inhibits p38 MAPK signaling in parallel to mTORC2 activation and that both pathways act together to modulate of lipid homeostasis. Our findings show a non-canonical role for Hedgehog signaling in lipid metabolism via regulation of core homeostatic pathways and reveal a new mechanism by which developmental timing events govern metabolic decisions.
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