1
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Razzaq MK, Babur MN, Awan MJA, Raza G, Mobeen M, Aslam A, Siddique KHM. Revolutionizing soybean genomics: How CRISPR and advanced sequencing are unlocking new potential. Funct Integr Genomics 2024; 24:153. [PMID: 39223394 DOI: 10.1007/s10142-024-01435-7] [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: 07/03/2024] [Revised: 08/21/2024] [Accepted: 08/23/2024] [Indexed: 09/04/2024]
Abstract
Soybean Glycine max L., paleopolyploid genome, poses challenges to its genetic improvement. However, the development of reference genome assemblies and genome sequencing has completely changed the field of soybean genomics, allowing for more accurate and successful breeding techniques as well as research. During the single-cell revolution, one of the most advanced sequencing tools for examining the transcriptome landscape is single-cell RNA sequencing (scRNA-seq). Comprehensive resources for genetic improvement of soybeans may be found in the SoyBase and other genomics databases. CRISPR-Cas9 genome editing technology provides promising prospects for precise genetic modifications in soybean. This method has enhanced several soybean traits, including as yield, nutritional value, and resistance to both biotic and abiotic stresses. With base editing techniques that allow for precise DNA modifications, the use of CRISPR-Cas9 is further increased. With the availability of the reference genome for soybeans and the following assembly of wild and cultivated soybeans, significant chromosomal rearrangements and gene duplication events have been identified, offering new perspectives on the complex genomic structure of soybeans. Furthermore, major single nucleotide polymorphisms (SNPs) linked to stachyose and sucrose content have been found through genome-wide association studies (GWAS), providing important tools for enhancing soybean carbohydrate profiles. In order to open up new avenues for soybean genetic improvement, future research approaches include investigating transcriptional divergence processes, enhancing genetic resources, and incorporating CRISPR-Cas9 technologies.
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Affiliation(s)
| | | | - Muhammad Jawad Akbar Awan
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College of Pakistan Institute of Engineering and Applied Sciences Jhang Road, Faisalabad, Pakistan
| | - Ghulam Raza
- National Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS) PK, Faisalabad, Pakistan
| | - Mehwish Mobeen
- Institute of Pure and Applied Biology, Zoology Division, Bahauddin Zakariya University, Multan, Pakistan
| | - Ali Aslam
- Faculty of Agriculture and Veterinary Sciences, Superior University, Lahore, Pakistan
| | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The University of Western Australia, Perth, WA, 6001, Australia.
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2
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Wang S, Guo S, Guo J, Du Q, Wu C, Wu Y, Zhang Y. Cell death pathways: molecular mechanisms and therapeutic targets for cancer. MedComm (Beijing) 2024; 5:e693. [PMID: 39239068 PMCID: PMC11374700 DOI: 10.1002/mco2.693] [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: 04/08/2024] [Revised: 07/24/2024] [Accepted: 07/28/2024] [Indexed: 09/07/2024] Open
Abstract
Cell death regulation is essential for tissue homeostasis and its dysregulation often underlies cancer development. Understanding the different pathways of cell death can provide novel therapeutic strategies for battling cancer. This review explores several key cell death mechanisms of apoptosis, necroptosis, autophagic cell death, ferroptosis, and pyroptosis. The research gap addressed involves a thorough analysis of how these cell death pathways can be precisely targeted for cancer therapy, considering tumor heterogeneity and adaptation. It delves into genetic and epigenetic factors and signaling cascades like the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) and mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathways, which are critical for the regulation of cell death. Additionally, the interaction of the microenvironment with tumor cells, and particularly the influence of hypoxia, nutrient deprivation, and immune cellular interactions, are explored. Emphasizing therapeutic strategies, this review highlights emerging modulators and inducers such as B cell lymphoma 2 (BCL2) homology domain 3 (BH3) mimetics, tumour necrosis factor-related apoptosis-inducing ligand (TRAIL), chloroquine, and innovative approaches to induce ferroptosis and pyroptosis. This review provides insights into cancer therapy's future direction, focusing on multifaceted approaches to influence cell death pathways and circumvent drug resistance. This examination of evolving strategies underlines the considerable clinical potential and the continuous necessity for in-depth exploration within this scientific domain.
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Affiliation(s)
- Shaohui Wang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Ethnic Medicine Chengdu University of Traditional Chinese Medicine Chengdu China
| | - Sa Guo
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy Chengdu University of Traditional Chinese Medicine Chengdu China
| | - Jing Guo
- College of Clinical Medicine Hospital of Chengdu University of Traditional Chinese Medicine Chengdu China
| | - Qinyun Du
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy Chengdu University of Traditional Chinese Medicine Chengdu China
| | - Cen Wu
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy Chengdu University of Traditional Chinese Medicine Chengdu China
| | - Yeke Wu
- College of Clinical Medicine Hospital of Chengdu University of Traditional Chinese Medicine Chengdu China
| | - Yi Zhang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Ethnic Medicine Chengdu University of Traditional Chinese Medicine Chengdu China
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3
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Gallo E, De Renzis S, Sharpe J, Mayor R, Hartmann J. Versatile system cores as a conceptual basis for generality in cell and developmental biology. Cell Syst 2024:S2405-4712(24)00209-6. [PMID: 39236709 DOI: 10.1016/j.cels.2024.08.001] [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: 08/16/2023] [Revised: 05/26/2024] [Accepted: 08/07/2024] [Indexed: 09/07/2024]
Abstract
The discovery of general principles underlying the complexity and diversity of cellular and developmental systems is a central and long-standing aim of biology. While new technologies collect data at an ever-accelerating rate, there is growing concern that conceptual progress is not keeping pace. We contend that this is due to a paucity of conceptual frameworks that support meaningful generalizations. This led us to develop the core and periphery (C&P) hypothesis, which posits that many biological systems can be decomposed into a highly versatile core with a large behavioral repertoire and a specific periphery that configures said core to perform one particular function. Versatile cores tend to be widely reused across biology, which confers generality to theories describing them. Here, we introduce this concept and describe examples at multiple scales, including Turing patterning, actomyosin dynamics, multi-cellular morphogenesis, and vertebrate gastrulation. We also sketch its evolutionary basis and discuss key implications and open questions. We propose that the C&P hypothesis could unlock new avenues of conceptual progress in mesoscale biology.
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Affiliation(s)
- Elisa Gallo
- Institute of Molecular Life Sciences, University of Zurich (UZH), 8057 Zurich, Switzerland
| | - Stefano De Renzis
- Developmental Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - James Sharpe
- EMBL Barcelona, European Molecular Biology Laboratory (EMBL), 08003 Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats, 08010 Barcelona, Spain
| | - Roberto Mayor
- Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK
| | - Jonas Hartmann
- Institute of Molecular Life Sciences, University of Zurich (UZH), 8057 Zurich, Switzerland; Developmental Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany; EMBL Barcelona, European Molecular Biology Laboratory (EMBL), 08003 Barcelona, Spain; Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK; Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208, USA; Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA.
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4
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Boukeroui Y, González-Siso MI, DeCastro ME, Arab M, Aissaoui N, Nas F, Saibi ANE, Klouche Khelil N. Characterization, whole-genome sequence analysis, and protease production of a new thermophilic Bacillus licheniformis strain isolated from Debagh hot spring, Algeria. Int Microbiol 2024:10.1007/s10123-024-00569-9. [PMID: 39129036 DOI: 10.1007/s10123-024-00569-9] [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: 05/06/2024] [Revised: 07/26/2024] [Accepted: 07/31/2024] [Indexed: 08/13/2024]
Abstract
A new thermophilic strain, designated as Bacillus sp. LMB3902, was isolated from Hammam Debagh, the hottest spring in Algeria (up to 98 °C). This isolate showed high protease production in skim milk media at 55 °C and exhibited significant specific protease activity by using azocasein as a substrate (157.50 U/mg). Through conventional methods, chemotaxonomic characteristics, 16S rRNA gene sequencing, and comparative genomic analysis with the closely related strain Bacillus licheniformis DSM 13 (ATCC 14580 T), the isolate Bacillus sp. LMB3902 was identified as a potentially new strain of Bacillus licheniformis. In addition, the gene functions of Bacillus sp. LMB3902 strain were predicted using the Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Clusters of Orthologous Groups, Non-Redundant Protein Sequence Database, Swiss-Prot, and Pfam databases. The results showed that the genome size of Bacillus sp. LMB3902 was 4.279.557 bp, with an average GC content of 46%. The genome contained 4.760 predicted genes, including 8 rRNAs, 78 tRNAs, and 24 sRNAs. A total of 235 protease genes were annotated including 50 proteases with transmembrane helix structures and eight secreted proteases with signal peptides. Additionally, the majority of secondary metabolites found by antiSMASH platform showed low similarity to identified natural products, such as fengicin (53%), lichenysin (57%), and surfactin (34%), suggesting that this strain may encode for novel uncharacterized natural products which can be useful for biotechnological applications. This study is the first report that describes the complete genome sequence, taxono-genomics, and gene annotation as well as protease production of the Bacillus genus in this hydrothermal vent.
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Affiliation(s)
- Yasmina Boukeroui
- Laboratory of Applied Microbiology in Food, Biomedical and Environment (LAMAABE Laboratory), Department of Biology, Faculty of Nature and Life, Earth and Universe Sciences, University of Tlemcen, 13000, Tlemcen, Algeria
| | - María-Isabel González-Siso
- Grupo EXPRELA, Centro Interdisciplinar de Química E Bioloxía (CICA), Facultade de Ciencias, Universidade da Coruña, 15071 , A Coruña, Spain
| | - María-Eugenia DeCastro
- Grupo EXPRELA, Centro Interdisciplinar de Química E Bioloxía (CICA), Facultade de Ciencias, Universidade da Coruña, 15071 , A Coruña, Spain
| | - Mounia Arab
- Laboratory of Applied Microbiology in Food, Biomedical and Environment (LAMAABE Laboratory), Department of Biology, Faculty of Nature and Life, Earth and Universe Sciences, University of Tlemcen, 13000, Tlemcen, Algeria
- Faculty of Biological Sciences, University of Sciences and Technology Houari Boumediene, 16000, Algiers, Algeria
| | - Nadia Aissaoui
- Laboratory of Sustainable Management of Natural Resources in Arid and Semi Arid Areas (GDRN), Institute of Sciences, University Center of Naâma, 45000, Naâma, Algeria
| | - Fatima Nas
- Laboratory of Applied Microbiology in Food, Biomedical and Environment (LAMAABE Laboratory), Department of Biology, Faculty of Nature and Life, Earth and Universe Sciences, University of Tlemcen, 13000, Tlemcen, Algeria
| | - Amina Nour Elhouda Saibi
- Laboratory of Applied Microbiology in Food, Biomedical and Environment (LAMAABE Laboratory), Department of Biology, Faculty of Nature and Life, Earth and Universe Sciences, University of Tlemcen, 13000, Tlemcen, Algeria
| | - Nihel Klouche Khelil
- Laboratory of Applied Microbiology in Food, Biomedical and Environment (LAMAABE Laboratory), Department of Biology, Faculty of Nature and Life, Earth and Universe Sciences, University of Tlemcen, 13000, Tlemcen, Algeria.
- Laboratory of Experimental Surgery, Dental Surgery Department, Medical Faculty, University of Tlemcen, 13000, Tlemcen, Algeria.
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5
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Kuhn TM, Paulsen M, Cuylen-Haering S. Accessible high-speed image-activated cell sorting. Trends Cell Biol 2024; 34:657-670. [PMID: 38789300 DOI: 10.1016/j.tcb.2024.04.007] [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: 09/06/2023] [Revised: 04/15/2024] [Accepted: 04/23/2024] [Indexed: 05/26/2024]
Abstract
Over the past six decades, fluorescence-activated cell sorting (FACS) has become an essential technology for basic and clinical research by enabling the isolation of cells of interest in high throughput. Recent technological advancements have started a new era of flow cytometry. By combining the spatial resolution of microscopy with high-speed cell sorting, new instruments allow cell sorting based on simple image-derived parameters or sophisticated image analysis algorithms, thereby greatly expanding the scope of applications. In this review, we discuss the systems that are commercially available or have been described in enough methodological and engineering detail to allow their replication. We summarize their strengths and limitations and highlight applications that have the potential to transform various fields in basic life science research and clinical settings.
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Affiliation(s)
- Terra M Kuhn
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Malte Paulsen
- Novo Nordisk Foundation Center for Stem Cell Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Sara Cuylen-Haering
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
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6
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Nugent PJ, Park H, Wladyka CL, Chen KY, Bynum C, Quarterman G, Hsieh AC, Subramaniam AR. Decoding RNA Metabolism by RNA-linked CRISPR Screening in Human Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.25.605204. [PMID: 39091804 PMCID: PMC11291135 DOI: 10.1101/2024.07.25.605204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
RNAs undergo a complex choreography of metabolic processes in human cells that are regulated by thousands of RNA-associated proteins. While the effects of individual RNA-associated proteins on RNA metabolism have been extensively characterized, the full complement of regulators for most RNA metabolic events remain unknown. Here we present a massively parallel RNA-linked CRISPR (ReLiC) screening approach to measure the responses of diverse RNA metabolic events to knockout of 2,092 human genes encoding all known RNA-associated proteins. ReLiC screens highlight modular interactions between gene networks regulating splicing, translation, and decay of mRNAs. When combined with biochemical fractionation of polysomes, ReLiC reveals striking pathway-specific coupling between growth fitness and mRNA translation. Perturbing different components of the translation and proteostasis machineries have distinct effects on ribosome occupancy, while perturbing mRNA transcription leaves ribosome occupancy largely intact. Isoform-selective ReLiC screens capture differential regulation of intron retention and exon skipping by SF3b complex subunits. Chemogenomic screens using ReLiC decipher translational regulators upstream of mRNA decay and uncover a role for the ribosome collision sensor GCN1 during treatment with the anti-leukemic drug homoharringtonine. Our work demonstrates ReLiC as a versatile platform for discovering and dissecting regulatory principles of human RNA metabolism.
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7
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Frenkel M, Corban JE, Hujoel MLA, Morris Z, Raman S. Large-scale discovery of chromatin dysregulation induced by oncofusions and other protein-coding variants. Nat Biotechnol 2024:10.1038/s41587-024-02347-4. [PMID: 39048711 DOI: 10.1038/s41587-024-02347-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 07/02/2024] [Indexed: 07/27/2024]
Abstract
Population-scale databases have expanded to millions of protein-coding variants, yet insight into their mechanistic consequences has lagged. Here we present PROD-ATAC, a high-throughput method for discovering the effects of protein-coding variants on chromatin regulation. A pooled variant library is expressed in a disease-agnostic cell line, and single-cell assay for transposase-accessible chromatin resolves each variant's effect on the chromatin landscape. Using PROD-ATAC, we characterized the effects of more than 100 oncofusions (cancer-causing chimeric proteins) and controls and revealed that chromatin remodeling is common to fusions spanning an enormous range of fusion frequencies. Furthermore, fusion-induced dysregulation can be context agnostic, as observed mechanisms often overlapped with cancer and cell-type-specific prior knowledge. We also showed that gain-of-function activity is common among oncofusions. This work begins to outline a global map of fusion-induced chromatin alterations. We suggest that there might be convergent mechanisms among disparate oncofusions and shared modes of dysregulation among fusions present in tumors at different frequencies. PROD-ATAC is generalizable to any set of protein-coding variants.
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Affiliation(s)
- Max Frenkel
- Cellular and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI, USA
- Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - James E Corban
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Margaux L A Hujoel
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Zachary Morris
- Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Srivatsan Raman
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI, USA.
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8
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Frenkel M, Raman S. Discovering mechanisms of human genetic variation and controlling cell states at scale. Trends Genet 2024; 40:587-600. [PMID: 38658256 DOI: 10.1016/j.tig.2024.03.010] [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: 02/24/2024] [Revised: 03/29/2024] [Accepted: 03/29/2024] [Indexed: 04/26/2024]
Abstract
Population-scale sequencing efforts have catalogued substantial genetic variation in humans such that variant discovery dramatically outpaces interpretation. We discuss how single-cell sequencing is poised to reveal genetic mechanisms at a rate that may soon approach that of variant discovery. The functional genomics toolkit is sufficiently modular to systematically profile almost any type of variation within increasingly diverse contexts and with molecularly comprehensive and unbiased readouts. As a result, we can construct deep phenotypic atlases of variant effects that span the entire regulatory cascade. The same conceptual approach to interpreting genetic variation should be applied to engineering therapeutic cell states. In this way, variant mechanism discovery and cell state engineering will become reciprocating and iterative processes towards genomic medicine.
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Affiliation(s)
- Max Frenkel
- Cellular and Molecular Biology Graduate Program, University of Wisconsin, Madison, WI, USA; Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Biochemistry, University of Wisconsin, Madison, WI, USA.
| | - Srivatsan Raman
- Department of Biochemistry, University of Wisconsin, Madison, WI, USA; Department of Bacteriology, University of Wisconsin, Madison, WI, USA; Department of Chemical and Biological Engineering, University of Wisconsin, Madison, WI, USA.
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9
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Bai D, Ellington CN, Mo S, Song L, Xing EP. AttentionPert: accurately modeling multiplexed genetic perturbations with multi-scale effects. Bioinformatics 2024; 40:i453-i461. [PMID: 38940174 PMCID: PMC11211811 DOI: 10.1093/bioinformatics/btae244] [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] [Indexed: 06/29/2024] Open
Abstract
MOTIVATION Genetic perturbations (e.g. knockouts, variants) have laid the foundation for our understanding of many diseases, implicating pathogenic mechanisms and indicating therapeutic targets. However, experimental assays are fundamentally limited by the number of measurable perturbations. Computational methods can fill this gap by predicting perturbation effects under novel conditions, but accurately predicting the transcriptional responses of cells to unseen perturbations remains a significant challenge. RESULTS We address this by developing a novel attention-based neural network, AttentionPert, which accurately predicts gene expression under multiplexed perturbations and generalizes to unseen conditions. AttentionPert integrates global and local effects in a multi-scale model, representing both the nonuniform system-wide impact of the genetic perturbation and the localized disturbance in a network of gene-gene similarities, enhancing its ability to predict nuanced transcriptional responses to both single and multi-gene perturbations. In comprehensive experiments, AttentionPert demonstrates superior performance across multiple datasets outperforming the state-of-the-art method in predicting differential gene expressions and revealing novel gene regulations. AttentionPert marks a significant improvement over current methods, particularly in handling the diversity of gene perturbations and in predicting out-of-distribution scenarios. AVAILABILITY AND IMPLEMENTATION Code is available at https://github.com/BaiDing1234/AttentionPert.
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Affiliation(s)
- Ding Bai
- Machine Learning Department, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, 00000, United Arabic Emirates
| | - Caleb N Ellington
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, 15213, United States
| | - Shentong Mo
- Machine Learning Department, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, 00000, United Arabic Emirates
| | - Le Song
- Machine Learning Department, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, 00000, United Arabic Emirates
| | - Eric P Xing
- Machine Learning Department, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, 00000, United Arabic Emirates
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, 15213, United States
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10
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Enright AL, Heelan WJ, Ward RD, Peters JM. CRISPRi functional genomics in bacteria and its application to medical and industrial research. Microbiol Mol Biol Rev 2024; 88:e0017022. [PMID: 38809084 PMCID: PMC11332340 DOI: 10.1128/mmbr.00170-22] [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] [Indexed: 05/30/2024] Open
Abstract
SUMMARYFunctional genomics is the use of systematic gene perturbation approaches to determine the contributions of genes under conditions of interest. Although functional genomic strategies have been used in bacteria for decades, recent studies have taken advantage of CRISPR (clustered regularly interspaced short palindromic repeats) technologies, such as CRISPRi (CRISPR interference), that are capable of precisely modulating expression of all genes in the genome. Here, we discuss and review the use of CRISPRi and related technologies for bacterial functional genomics. We discuss the strengths and weaknesses of CRISPRi as well as design considerations for CRISPRi genetic screens. We also review examples of how CRISPRi screens have defined relevant genetic targets for medical and industrial applications. Finally, we outline a few of the many possible directions that could be pursued using CRISPR-based functional genomics in bacteria. Our view is that the most exciting screens and discoveries are yet to come.
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Affiliation(s)
- Amy L. Enright
- Pharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Microbiology Doctoral Training Program, University of Wisconsin-Madison, Madison, Wisconsin, USA
- DOE Great Lakes Bioenergy Research Center University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - William J. Heelan
- Pharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Ryan D. Ward
- Pharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, USA
- DOE Great Lakes Bioenergy Research Center University of Wisconsin-Madison, Madison, Wisconsin, USA
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jason M. Peters
- Pharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, USA
- DOE Great Lakes Bioenergy Research Center University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, Wisconsin, USA
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11
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Li K, Shu D, Li H, Lan A, Zhang W, Tan Z, Huang M, Tomasi ML, Jin A, Yu H, Shen M, Liu S. SMAD4 depletion contributes to endocrine resistance by integrating ER and ERBB signaling in HR + HER2- breast cancer. Cell Death Dis 2024; 15:444. [PMID: 38914552 PMCID: PMC11196642 DOI: 10.1038/s41419-024-06838-9] [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: 01/24/2024] [Revised: 06/11/2024] [Accepted: 06/14/2024] [Indexed: 06/26/2024]
Abstract
Endocrine resistance poses a significant clinical challenge for patients with hormone receptor-positive and human epithelial growth factor receptor 2-negative (HR + HER2-) breast cancer. Dysregulation of estrogen receptor (ER) and ERBB signaling pathways is implicated in resistance development; however, the integration of these pathways remains unclear. While SMAD4 is known to play diverse roles in tumorigenesis, its involvement in endocrine resistance is poorly understood. Here, we investigate the role of SMAD4 in acquired endocrine resistance in HR + HER2- breast cancer. Genome-wide CRISPR screening identifies SMAD4 as a regulator of 4-hydroxytamoxifen (OHT) sensitivity in T47D cells. Clinical data analysis reveals downregulated SMAD4 expression in breast cancer tissues, correlating with poor prognosis. Following endocrine therapy, SMAD4 expression is further suppressed. Functional studies demonstrate that SMAD4 depletion induces endocrine resistance in vitro and in vivo by enhancing ER and ERBB signaling. Concomitant inhibition of ER and ERBB signaling leads to aberrant autophagy activation. Simultaneous inhibition of ER, ERBB, and autophagy pathways synergistically impacts SMAD4-depleted cells. Our findings unveil a mechanism whereby endocrine therapy-induced SMAD4 downregulation drives acquired resistance by integrating ER and ERBB signaling and suggest a rational treatment strategy for endocrine-resistant HR + HER2- breast cancer patients.
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MESH Headings
- Humans
- Smad4 Protein/metabolism
- Smad4 Protein/genetics
- Female
- Breast Neoplasms/metabolism
- Breast Neoplasms/genetics
- Breast Neoplasms/pathology
- Breast Neoplasms/drug therapy
- Signal Transduction/drug effects
- Drug Resistance, Neoplasm/drug effects
- Drug Resistance, Neoplasm/genetics
- Receptor, ErbB-2/metabolism
- Receptor, ErbB-2/genetics
- Receptors, Estrogen/metabolism
- Cell Line, Tumor
- Animals
- Tamoxifen/pharmacology
- Tamoxifen/therapeutic use
- Tamoxifen/analogs & derivatives
- Mice
- Antineoplastic Agents, Hormonal/pharmacology
- Antineoplastic Agents, Hormonal/therapeutic use
- Mice, Nude
- Gene Expression Regulation, Neoplastic/drug effects
- Autophagy/drug effects
- ErbB Receptors/metabolism
- ErbB Receptors/genetics
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Affiliation(s)
- Kang Li
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, 400016, Chongqing, China
| | - Dan Shu
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, 400016, Chongqing, China
| | - Han Li
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, 400016, Chongqing, China
| | - Ailin Lan
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, 400016, Chongqing, China
| | - Wenjie Zhang
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, 400016, Chongqing, China
| | - Zhaofu Tan
- Department of Dermatology and Venereology, The First Affiliated Hospital of Chongqing Medical University, 400016, Chongqing, China
| | - Man Huang
- Department of Breast Center, Chongqing University Three Gorges Hospital, Wanzhou, 404000, Chongqing, China
| | - Maria Lauda Tomasi
- Department of Medicine, Cedars-Sinai Medical Center, DAVIS Research Building 3096A, 8700 Beverly Blv, Los Angeles, CA, 90048, USA
| | - Aishun Jin
- Department of Immunology, School of Basic Medical Sciences, Chongqing Medical University, 400010, Chongqing, China
| | - Haochen Yu
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, 400016, Chongqing, China.
| | - Meiying Shen
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, 400016, Chongqing, China.
| | - Shengchun Liu
- Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, 400016, Chongqing, China.
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12
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Lobel JH, Ingolia NT. Precise measurement of molecular phenotypes with barcode-based CRISPRi systems. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.21.600132. [PMID: 38948701 PMCID: PMC11213135 DOI: 10.1101/2024.06.21.600132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Genome-wide CRISPR-Cas9 screens have untangled regulatory networks and revealed the genetic underpinnings of diverse biological processes. Their success relies on experimental designs that interrogate specific molecular phenotypes and distinguish key regulators from background effects. Here, we realize these goals with a generalizable platform for CRISPR interference with barcoded expression reporter sequencing (CiBER-seq) that dramatically improves the sensitivity and scope of genome-wide screens. We systematically address technical factors that distort phenotypic measurements by normalizing expression reporters against closely-matched control promoters, integrated together into the genome at single copy. To test our ability to capture post-transcriptional and post-translational regulation through sequencing, we screened for genes that affected nonsense-mediated mRNA decay and Doa10-mediated cytosolic protein decay. Our optimized CiBER-seq screens accurately capture the known components of well-studied RNA and protein quality control pathways with minimal background. These results demonstrate the precision and versatility of CiBER-seq for dissecting the genetic networks controlling cellular behaviors.
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Affiliation(s)
- Joseph H. Lobel
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Nicholas T. Ingolia
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
- Lead contact
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13
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Zhang H, Feng H, Xing XH, Jiang W, Zhang C, Gu Y. Pooled CRISPR Interference Screening Identifies Crucial Transcription Factors in Gas-Fermenting Clostridium ljungdahlii. ACS Synth Biol 2024; 13:1893-1905. [PMID: 38825826 DOI: 10.1021/acssynbio.4c00175] [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] [Indexed: 06/04/2024]
Abstract
Gas-fermenting Clostridium species hold tremendous promise for one-carbon biomanufacturing. To unlock their full potential, it is crucial to unravel and optimize the intricate regulatory networks that govern these organisms; however, this aspect is currently underexplored. In this study, we employed pooled CRISPR interference (CRISPRi) screening to uncover a wide range of functional transcription factors (TFs) in Clostridium ljungdahlii, a representative species of gas-fermenting Clostridium, with a special focus on TFs associated with the utilization of carbon resources. Among the 425 TF candidates, we identified 75 and 68 TF genes affecting the heterotrophic and autotrophic growth of C. ljungdahlii, respectively. We focused our attention on two of the screened TFs, NrdR and DeoR, and revealed their pivotal roles in the regulation of deoxyribonucleoside triphosphates (dNTPs) supply, carbon fixation, and product synthesis in C. ljungdahlii, thereby influencing the strain performance in gas fermentation. Based on this, we proceeded to optimize the expression of deoR in C. ljungdahlii by adjusting its promoter strength, leading to an improved growth rate and ethanol synthesis of C. ljungdahlii when utilizing syngas. This study highlights the effectiveness of pooled CRISPRi screening in gas-fermenting Clostridium species, expanding the horizons for functional genomic research in these industrially important bacteria.
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Affiliation(s)
- Huan Zhang
- CAS-Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huibao Feng
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, California 91125, United States
| | - Xin-Hui Xing
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
- Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China
| | - Weihong Jiang
- CAS-Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
- Key Laboratory of Plant Carbon Capture, CAS, Shanghai 200032, China
| | - Chong Zhang
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
- Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China
| | - Yang Gu
- CAS-Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
- Key Laboratory of Plant Carbon Capture, CAS, Shanghai 200032, China
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14
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Zheng X, Wu B, Liu Y, Simmons SK, Kim K, Clarke GS, Ashiq A, Park J, Li J, Wang Z, Tong L, Wang Q, Rajamani KT, Muñoz-Castañeda R, Mu S, Qi T, Zhang Y, Ngiam ZC, Ohte N, Hanashima C, Wu Z, Xu X, Levin JZ, Jin X. Massively parallel in vivo Perturb-seq reveals cell-type-specific transcriptional networks in cortical development. Cell 2024; 187:3236-3248.e21. [PMID: 38772369 PMCID: PMC11193654 DOI: 10.1016/j.cell.2024.04.050] [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: 09/08/2023] [Revised: 11/30/2023] [Accepted: 04/30/2024] [Indexed: 05/23/2024]
Abstract
Leveraging AAVs' versatile tropism and labeling capacity, we expanded the scale of in vivo CRISPR screening with single-cell transcriptomic phenotyping across embryonic to adult brains and peripheral nervous systems. Through extensive tests of 86 vectors across AAV serotypes combined with a transposon system, we substantially amplified labeling efficacy and accelerated in vivo gene delivery from weeks to days. Our proof-of-principle in utero screen identified the pleiotropic effects of Foxg1, highlighting its tight regulation of distinct networks essential for cell fate specification of Layer 6 corticothalamic neurons. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% by lentivirus, to achieve analysis of over 30,000 cells in one experiment and enable massively parallel in vivo Perturb-seq. Compatible with various phenotypic measurements (single-cell or spatial multi-omics), it presents a flexible approach to interrogate gene function across cell types in vivo, translating gene variants to their causal function.
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Affiliation(s)
- Xinhe Zheng
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Boli Wu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Yuejia Liu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Sean K Simmons
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kwanho Kim
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Grace S Clarke
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Abdullah Ashiq
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Joshua Park
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Jiwen Li
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Zhilin Wang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Liqi Tong
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Qizhao Wang
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Keerthi T Rajamani
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Rodrigo Muñoz-Castañeda
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Shang Mu
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Tianbo Qi
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Yunxiao Zhang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Zi Chao Ngiam
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Naoto Ohte
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Carina Hanashima
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Zhuhao Wu
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Xiangmin Xu
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Joshua Z Levin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Xin Jin
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA.
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15
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Kwon JJ, Pan J, Gonzalez G, Hahn WC, Zitnik M. On knowing a gene: A distributional hypothesis of gene function. Cell Syst 2024; 15:488-496. [PMID: 38810640 PMCID: PMC11189734 DOI: 10.1016/j.cels.2024.04.008] [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: 04/19/2023] [Revised: 02/25/2024] [Accepted: 04/30/2024] [Indexed: 05/31/2024]
Abstract
As words can have multiple meanings that depend on sentence context, genes can have various functions that depend on the surrounding biological system. This pleiotropic nature of gene function is limited by ontologies, which annotate gene functions without considering biological contexts. We contend that the gene function problem in genetics may be informed by recent technological leaps in natural language processing, in which representations of word semantics can be automatically learned from diverse language contexts. In contrast to efforts to model semantics as "is-a" relationships in the 1990s, modern distributional semantics represents words as vectors in a learned semantic space and fuels current advances in transformer-based models such as large language models and generative pre-trained transformers. A similar shift in thinking of gene functions as distributions over cellular contexts may enable a similar breakthrough in data-driven learning from large biological datasets to inform gene function.
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Affiliation(s)
- Jason J Kwon
- Dana-Farber Cancer Institute and Harvard Medical School, Department of Medical Oncology, Boston, MA 02215, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Joshua Pan
- Dana-Farber Cancer Institute and Harvard Medical School, Department of Medical Oncology, Boston, MA 02215, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Guadalupe Gonzalez
- Department of Computing, Faculty of Engineering, Imperial College, London SW7 2AZ, UK
| | - William C Hahn
- Dana-Farber Cancer Institute and Harvard Medical School, Department of Medical Oncology, Boston, MA 02215, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Marinka Zitnik
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Medical School, Department of Biomedical Informatics, Boston, MA 02115, USA; Harvard Data Science Initiative, Harvard University, Cambridge, MA 02138, USA; Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, Allston, MA 02134, USA.
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16
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Vitale GA, Geibel C, Minda V, Wang M, Aron AT, Petras D. Connecting metabolome and phenotype: recent advances in functional metabolomics tools for the identification of bioactive natural products. Nat Prod Rep 2024; 41:885-904. [PMID: 38351834 PMCID: PMC11186733 DOI: 10.1039/d3np00050h] [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: 10/11/2023] [Indexed: 06/20/2024]
Abstract
Covering: 1995 to 2023Advances in bioanalytical methods, particularly mass spectrometry, have provided valuable molecular insights into the mechanisms of life. Non-targeted metabolomics aims to detect and (relatively) quantify all observable small molecules present in a biological system. By comparing small molecule abundances between different conditions or timepoints in a biological system, researchers can generate new hypotheses and begin to understand causes of observed phenotypes. Functional metabolomics aims to investigate the functional roles of metabolites at the scale of the metabolome. However, most functional metabolomics studies rely on indirect measurements and correlation analyses, which leads to ambiguity in the precise definition of functional metabolomics. In contrast, the field of natural products has a history of identifying the structures and bioactivities of primary and specialized metabolites. Here, we propose to expand and reframe functional metabolomics by integrating concepts from the fields of natural products and chemical biology. We highlight emerging functional metabolomics approaches that shift the focus from correlation to physical interactions, and we discuss how this allows researchers to uncover causal relationships between molecules and phenotypes.
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Affiliation(s)
- Giovanni Andrea Vitale
- CMFI Cluster of Excellence, Interfaculty Institute of Microbiology and Medicine, University of Tuebingen, Tuebingen, Germany
| | - Christian Geibel
- CMFI Cluster of Excellence, Interfaculty Institute of Microbiology and Medicine, University of Tuebingen, Tuebingen, Germany
| | - Vidit Minda
- Division of Pharmacology and Pharmaceutical Sciences, University of Missouri - Kansas City, Kansas City, USA
- Department of Chemistry and Biochemistry, University of Denver, Denver, USA.
| | - Mingxun Wang
- Department of Computer Science, University of California Riverside, Riverside, USA.
| | - Allegra T Aron
- Department of Chemistry and Biochemistry, University of Denver, Denver, USA.
| | - Daniel Petras
- CMFI Cluster of Excellence, Interfaculty Institute of Microbiology and Medicine, University of Tuebingen, Tuebingen, Germany
- Department of Biochemistry, University of California Riverside, Riverside, USA.
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17
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Ben-Tov D, Mafessoni F, Cucuy A, Honig A, Melamed-Bessudo C, Levy AA. Uncovering the dynamics of precise repair at CRISPR/Cas9-induced double-strand breaks. Nat Commun 2024; 15:5096. [PMID: 38877047 PMCID: PMC11178868 DOI: 10.1038/s41467-024-49410-x] [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: 02/06/2023] [Accepted: 06/05/2024] [Indexed: 06/16/2024] Open
Abstract
CRISPR/Cas9 is widely used for precise mutagenesis through targeted DNA double-strand breaks (DSBs) induction followed by error-prone repair. A better understanding of this process requires measuring the rates of cutting, error-prone, and precise repair, which have remained elusive so far. Here, we present a molecular and computational toolkit for multiplexed quantification of DSB intermediates and repair products by single-molecule sequencing. Using this approach, we characterize the dynamics of DSB induction, processing and repair at endogenous loci along a 72 h time-course in tomato protoplasts. Combining this data with kinetic modeling reveals that indel accumulation is determined by the combined effect of the rates of DSB induction processing of broken ends, and precise versus error repair. In this study, 64-88% of the molecules were cleaved in the three targets analyzed, while indels ranged between 15-41%. Precise repair accounts for most of the gap between cleavage and error repair, representing up to 70% of all repair events. Altogether, this system exposes flux in the DSB repair process, decoupling induction and repair dynamics, and suggesting an essential role of high-fidelity repair in limiting the efficiency of CRISPR-mediated mutagenesis.
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Affiliation(s)
- Daniela Ben-Tov
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Fabrizio Mafessoni
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Amit Cucuy
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Arik Honig
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Cathy Melamed-Bessudo
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel.
| | - Avraham A Levy
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel.
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18
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Roohani Y, Huang K, Leskovec J. Predicting transcriptional outcomes of novel multigene perturbations with GEARS. Nat Biotechnol 2024; 42:927-935. [PMID: 37592036 PMCID: PMC11180609 DOI: 10.1038/s41587-023-01905-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 07/12/2023] [Indexed: 08/19/2023]
Abstract
Understanding cellular responses to genetic perturbation is central to numerous biomedical applications, from identifying genetic interactions involved in cancer to developing methods for regenerative medicine. However, the combinatorial explosion in the number of possible multigene perturbations severely limits experimental interrogation. Here, we present graph-enhanced gene activation and repression simulator (GEARS), a method that integrates deep learning with a knowledge graph of gene-gene relationships to predict transcriptional responses to both single and multigene perturbations using single-cell RNA-sequencing data from perturbational screens. GEARS is able to predict outcomes of perturbing combinations consisting of genes that were never experimentally perturbed. GEARS exhibited 40% higher precision than existing approaches in predicting four distinct genetic interaction subtypes in a combinatorial perturbation screen and identified the strongest interactions twice as well as prior approaches. Overall, GEARS can predict phenotypically distinct effects of multigene perturbations and thus guide the design of perturbational experiments.
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Affiliation(s)
- Yusuf Roohani
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Kexin Huang
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Jure Leskovec
- Department of Computer Science, Stanford University, Stanford, CA, USA.
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19
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Fang Y, Li X, Tian R. Unlocking Glioblastoma Vulnerabilities with CRISPR-Based Genetic Screening. Int J Mol Sci 2024; 25:5702. [PMID: 38891890 PMCID: PMC11171782 DOI: 10.3390/ijms25115702] [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: 03/31/2024] [Revised: 05/17/2024] [Accepted: 05/22/2024] [Indexed: 06/21/2024] Open
Abstract
Glioblastoma (GBM) is the most common malignant brain tumor in adults. Despite advancements in treatment, the prognosis for patients with GBM remains poor due to its aggressive nature and resistance to therapy. CRISPR-based genetic screening has emerged as a powerful tool for identifying genes crucial for tumor progression and treatment resistance, offering promising targets for tumor therapy. In this review, we provide an overview of the recent advancements in CRISPR-based genetic screening approaches and their applications in GBM. We highlight how these approaches have been used to uncover the genetic determinants of GBM progression and responsiveness to various therapies. Furthermore, we discuss the ongoing challenges and future directions of CRISPR-based screening methods in advancing GBM research.
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Affiliation(s)
- Yitong Fang
- Department of Medical Neuroscience, School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China; (Y.F.); (X.L.)
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xing Li
- Department of Medical Neuroscience, School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China; (Y.F.); (X.L.)
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen 518055, China
| | - Ruilin Tian
- Department of Medical Neuroscience, School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China; (Y.F.); (X.L.)
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen 518055, China
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20
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Hsiung CCS, Wilson CM, Sambold NA, Dai R, Chen Q, Teyssier N, Misiukiewicz S, Arab A, O'Loughlin T, Cofsky JC, Shi J, Gilbert LA. Engineered CRISPR-Cas12a for higher-order combinatorial chromatin perturbations. Nat Biotechnol 2024:10.1038/s41587-024-02224-0. [PMID: 38760567 DOI: 10.1038/s41587-024-02224-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 03/28/2024] [Indexed: 05/19/2024]
Abstract
Multiplexed genetic perturbations are critical for testing functional interactions among coding or non-coding genetic elements. Compared to double-stranded DNA cutting, repressive chromatin formation using CRISPR interference (CRISPRi) avoids genotoxicity and is more effective for perturbing non-coding regulatory elements in pooled assays. However, current CRISPRi pooled screening approaches are limited to targeting one to three genomic sites per cell. We engineer an Acidaminococcus Cas12a (AsCas12a) variant, multiplexed transcriptional interference AsCas12a (multiAsCas12a), that incorporates R1226A, a mutation that stabilizes the ribonucleoprotein-DNA complex via DNA nicking. The multiAsCas12a-KRAB fusion improves CRISPRi activity over DNase-dead AsCas12a-KRAB fusions, often rescuing the activities of lentivirally delivered CRISPR RNAs (crRNA) that are inactive when used with the latter. multiAsCas12a-KRAB supports CRISPRi using 6-plex crRNA arrays in high-throughput pooled screens. Using multiAsCas12a-KRAB, we discover enhancer elements and dissect the combinatorial function of cis-regulatory elements in human cells. These results instantiate a group testing framework for efficiently surveying numerous combinations of chromatin perturbations for biological discovery and engineering.
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Affiliation(s)
- C C-S Hsiung
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Urology, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Arc Institute, Palo Alto, CA, USA
| | - C M Wilson
- Department of Urology, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Arc Institute, Palo Alto, CA, USA
- Tetrad Graduate Program, University of California, San Francisco, CA, USA
| | | | - R Dai
- Department of Urology, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Arc Institute, Palo Alto, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Q Chen
- Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - N Teyssier
- Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - S Misiukiewicz
- Department of Urology, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - A Arab
- Arc Institute, Palo Alto, CA, USA
| | - T O'Loughlin
- Department of Urology, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - J C Cofsky
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - J Shi
- Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - L A Gilbert
- Department of Urology, University of California, San Francisco, CA, USA.
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
- Arc Institute, Palo Alto, CA, USA.
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21
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Lin X, Zheng J, Cai X, Liu L, Jiang S, Liu Q, Sun Y. Glycometabolism and lipid metabolism related genes predict the prognosis of endometrial carcinoma and their effects on tumor cells. BMC Cancer 2024; 24:571. [PMID: 38720279 PMCID: PMC11080313 DOI: 10.1186/s12885-024-12327-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 05/01/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Glycometabolism and lipid metabolism are critical in cancer metabolic reprogramming. The primary aim of this study was to develop a prognostic model incorporating glycometabolism and lipid metabolism-related genes (GLRGs) for accurate prognosis assessment in patients with endometrial carcinoma (EC). METHODS Data on gene expression and clinical details were obtained from publicly accessible databases. GLRGs were obtained from the Genecards database. Through nonnegative matrix factorization (NMF) clustering, molecular groupings with various GLRG expression patterns were identified. LASSO Cox regression analysis was employed to create a prognostic model. Use rich algorithms such as GSEA, GSVA, xCELL ssGSEA, EPIC,CIBERSORT, MCPcounter, ESTIMATE, TIMER, TIDE, and Oncoppredict to analyze functional pathway characteristics of the forecast signal, immune status, anti-tumor therapy, etc. The expression was assessed using Western blot and quantitative real-time PCR techniques. A total of 113 algorithm combinations were combined to screen out the most significant GLRGs in the signature for in vitro experimental verification, such as colony formation, EdU cell proliferation, wound healing, apoptosis, and Transwell assays. RESULTS A total of 714 GLRGs were found, and 227 of them were identified as prognostic-related genes. And ten GLRGs (AUP1, ESR1, ERLIN2, ASS1, OGDH, BCKDHB, SLC16A1, HK2, LPCAT1 and PGR-AS1) were identified to construct the prognostic model of patients with EC. Based on GLRGs, the risk model's prognosis and independent prognostic value were established. The signature of GLRGs exhibited a robust correlation with the infiltration of immune cells and the sensitivity to drugs. In cytological experiments, we selected HK2 as candidate gene to verify its value in the occurrence and development of EC. Western blot and qRT-PCR revealed that HK2 was substantially expressed in EC cells. According to in vitro experiments, HK2 knockdown can increase EC cell apoptosis while suppressing EC cell migration, invasion, and proliferation. CONCLUSION The GLRGs signature constructed in this study demonstrated significant prognostic value for patients with endometrial carcinoma, thereby providing valuable guidance for treatment decisions.
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Affiliation(s)
- Xuefen Lin
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Jin'an District, Fuzhou City, Fujian Province, 350014, P. R. China
- Fujian Provincial Key Laboratory of Tumor Biotherapy, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Jianfeng Zheng
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Jin'an District, Fuzhou City, Fujian Province, 350014, P. R. China
- Fujian Provincial Key Laboratory of Tumor Biotherapy, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Xintong Cai
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Jin'an District, Fuzhou City, Fujian Province, 350014, P. R. China
| | - Li Liu
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Jin'an District, Fuzhou City, Fujian Province, 350014, P. R. China
| | - Shan Jiang
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Jin'an District, Fuzhou City, Fujian Province, 350014, P. R. China
- Fujian University of Chinese Medicine, Fuzhou, 350014, China
| | - Qinying Liu
- Fujian Provincial Key Laboratory of Tumor Biotherapy, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Yang Sun
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Jin'an District, Fuzhou City, Fujian Province, 350014, P. R. China.
- Fujian Provincial Key Laboratory of Tumor Biotherapy, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China.
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Shao F, Yao Y, Weng D, Wang R, Liu R, Zhang Y, Li E, Wang M, Tang Y, Ding Y, Xie Y. Causal association of plasma circulating metabolites with nephritis: a Mendelian randomization study. Front Nutr 2024; 11:1364841. [PMID: 38765814 PMCID: PMC11099270 DOI: 10.3389/fnut.2024.1364841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 04/16/2024] [Indexed: 05/22/2024] Open
Abstract
Background Nephritis is a pivotal catalyst in chronic kidney disease (CKD) progression. Although epidemiological studies have explored the impact of plasma circulating metabolites and drugs on nephritis, few have harnessed genetic methodologies to establish causal relationships. Methods Through Mendelian randomization (MR) in two substantial cohorts, spanning large sample sizes, we evaluated over 100 plasma circulating metabolites and 263 drugs to discern their causal effects on nephritis risk. The primary analytical tool was the inverse variance weighted (IVW) analysis. Our bioinformatic scrutiny of GSE115857 (IgA nephropathy, 86 samples) and GSE72326 (lupus nephritis, 238 samples) unveiled anomalies in lipid metabolism and immunological characteristics in nephritis. Thorough sensitivity analyses (MR-Egger, MR-PRESSO, leave-one-out analysis) were undertaken to verify the instrumental variables' (IVs) assumptions. Results Unique lipoprotein-related molecules established causal links with diverse nephritis subtypes. Notably, docosahexaenoic acid (DHA) emerged as a protective factor for acute tubulointerstitial nephritis (ATIN) (OR1 = 0.84, [95% CI 0.78-0.90], p1 = 0.013; OR2 = 0.89, [95% CI 0.82-0.97], p2 = 0.007). Conversely, multivitamin supplementation minus minerals notably increased the risk of ATIN (OR = 31.25, [95% CI 9.23-105.85], p = 0.004). Reduced α-linolenic acid (ALA) levels due to lipid-lowering drugs were linked to both ATIN (OR = 4.88, [95% CI 3.52-6.77], p < 0.001) and tubulointerstitial nephritis (TIN) (OR = 7.52, [95% CI 2.78-20.30], p = 0.042). While the non-renal drug indivina showed promise for TIN treatment, the use of digoxin, hydroxocobalamin, and liothyronine elevated the risk of chronic tubulointerstitial nephritis (CTIN). Transcriptome analysis affirmed that anomalous lipid metabolism and immune infiltration are characteristic of IgA nephropathy and lupus nephritis. The robustness of these causal links was reinforced by sensitivity analyses and leave-one-out tests, indicating no signs of pleiotropy. Conclusion Dyslipidemia significantly contributes to nephritis development. Strategies aimed at reducing plasma low-density lipoprotein levels or ALA supplementation may enhance the efficacy of existing lipid-lowering drug regimens for nephritis treatment. Renal functional status should also be judiciously considered with regard to the use of nonrenal medications.
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Affiliation(s)
- Fengling Shao
- The Ministry of Education, Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
| | - Yingling Yao
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Dunchu Weng
- The Ministry of Education, Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
| | - Runzhi Wang
- The Ministry of Education, Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
| | - Ruiling Liu
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Yongjia Zhang
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Erhan Li
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Mengdi Wang
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Yuewu Tang
- Department of Nephrology, Chongqing Three Gorges Central Hospital, Chongqing University Three Gorges Hospital, Chongqing, China
| | - Yubin Ding
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Yajun Xie
- The Ministry of Education, Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
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23
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Liu W, Wang W, Wang Z, Fan X, Li W, Huang Y, Yang X, Tang Z. CRISPR Screen Identifies the RNA-Binding Protein Eef1a1 as a Key Regulator of Myogenesis. Int J Mol Sci 2024; 25:4816. [PMID: 38732031 PMCID: PMC11084334 DOI: 10.3390/ijms25094816] [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: 03/19/2024] [Revised: 04/22/2024] [Accepted: 04/26/2024] [Indexed: 05/13/2024] Open
Abstract
Skeletal muscle myogenesis hinges on gene regulation, meticulously orchestrated by molecular mechanisms. While the roles of transcription factors and non-coding RNAs in myogenesis are widely known, the contribution of RNA-binding proteins (RBPs) has remained unclear until now. Therefore, to investigate the functions of post-transcriptional regulators in myogenesis and uncover new functional RBPs regulating myogenesis, we employed CRISPR high-throughput RBP-KO (RBP-wide knockout) library screening. Through this approach, we successfully identified Eef1a1 as a novel regulatory factor in myogenesis. Using CRISPR knockout (CRISPRko) and CRISPR interference (CRISPRi) technologies, we successfully established cellular models for both CRISPRko and CRISPRi. Our findings demonstrated that Eef1a1 plays a crucial role in promoting proliferation in C2C12 myoblasts. Through siRNA inhibition and overexpression methods, we further elucidated the involvement of Eef1a1 in promoting proliferation and suppressing differentiation processes. RIP (RNA immunoprecipitation), miRNA pull-down, and Dual-luciferase reporter assays confirmed that miR-133a-3p targets Eef1a1. Co-transfection experiments indicated that miR-133a-3p can rescue the effect of Eef1a1 on C2C12 myoblasts. In summary, our study utilized CRISPR library high-throughput screening to unveil a novel RBP, Eef1a1, involved in regulating myogenesis. Eef1a1 promotes the proliferation of myoblasts while inhibiting the differentiation process. Additionally, it acts as an antagonist to miR-133a-3p, thus modulating the process of myogenesis.
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Affiliation(s)
- Weiwei Liu
- Guangxi Key Laboratory of Animal Breeding, Disease Control and Prevention, College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (W.L.); (W.L.); (Y.H.)
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 528226, China; (W.W.); (Z.W.); (X.F.)
| | - Wei Wang
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 528226, China; (W.W.); (Z.W.); (X.F.)
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan 430070, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Zishuai Wang
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 528226, China; (W.W.); (Z.W.); (X.F.)
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Xinhao Fan
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 528226, China; (W.W.); (Z.W.); (X.F.)
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan 430070, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Wangchang Li
- Guangxi Key Laboratory of Animal Breeding, Disease Control and Prevention, College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (W.L.); (W.L.); (Y.H.)
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 528226, China; (W.W.); (Z.W.); (X.F.)
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Yuxin Huang
- Guangxi Key Laboratory of Animal Breeding, Disease Control and Prevention, College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (W.L.); (W.L.); (Y.H.)
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 528226, China; (W.W.); (Z.W.); (X.F.)
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Xiaogan Yang
- Guangxi Key Laboratory of Animal Breeding, Disease Control and Prevention, College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (W.L.); (W.L.); (Y.H.)
| | - Zhonglin Tang
- Guangxi Key Laboratory of Animal Breeding, Disease Control and Prevention, College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (W.L.); (W.L.); (Y.H.)
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Foshan 528226, China; (W.W.); (Z.W.); (X.F.)
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan 430070, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
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24
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Franks SN, Heon-Roberts R, Ryan BJ. CRISPRi: a way to integrate iPSC-derived neuronal models. Biochem Soc Trans 2024; 52:539-551. [PMID: 38526223 PMCID: PMC11088925 DOI: 10.1042/bst20230190] [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: 09/07/2023] [Revised: 02/28/2024] [Accepted: 03/13/2024] [Indexed: 03/26/2024]
Abstract
The genetic landscape of neurodegenerative diseases encompasses genes affecting multiple cellular pathways which exert effects in an array of neuronal and glial cell-types. Deconvolution of the roles of genes implicated in disease and the effects of disease-associated variants remains a vital step in the understanding of neurodegeneration and the development of therapeutics. Disease modelling using patient induced pluripotent stem cells (iPSCs) has enabled the generation of key cell-types associated with disease whilst maintaining the genomic variants that predispose to neurodegeneration. The use of CRISPR interference (CRISPRi), alongside other CRISPR-perturbations, allows the modelling of the effects of these disease-associated variants or identifying genes which modify disease phenotypes. This review summarises the current applications of CRISPRi in iPSC-derived neuronal models, such as fluorescence-activated cell sorting (FACS)-based screens, and discusses the future opportunities for disease modelling, identification of disease risk modifiers and target/drug discovery in neurodegeneration.
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Affiliation(s)
- Sarah N.J. Franks
- Oxford Parkinson's Disease Centre and Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QU, UK
- Kavli Institute for Nanoscience Discovery, Dorothy Crowfoot Hodgkin Building, University of Oxford, Oxford OX1 3QU, UK
| | - Rachel Heon-Roberts
- Oxford Parkinson's Disease Centre and Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QU, UK
- Kavli Institute for Nanoscience Discovery, Dorothy Crowfoot Hodgkin Building, University of Oxford, Oxford OX1 3QU, UK
| | - Brent J. Ryan
- Oxford Parkinson's Disease Centre and Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QU, UK
- Kavli Institute for Nanoscience Discovery, Dorothy Crowfoot Hodgkin Building, University of Oxford, Oxford OX1 3QU, UK
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25
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Gawlitt S, Collins SP, Yu Y, Blackman SA, Barquist L, Beisel CL. Expanding the flexibility of base editing for high-throughput genetic screens in bacteria. Nucleic Acids Res 2024; 52:4079-4097. [PMID: 38499498 DOI: 10.1093/nar/gkae174] [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: 07/12/2023] [Revised: 02/07/2024] [Accepted: 02/28/2024] [Indexed: 03/20/2024] Open
Abstract
Genome-wide screens have become powerful tools for elucidating genotype-to-phenotype relationships in bacteria. Of the varying techniques to achieve knockout and knockdown, CRISPR base editors are emerging as promising options. However, the limited number of available, efficient target sites hampers their use for high-throughput screening. Here, we make multiple advances to enable flexible base editing as part of high-throughput genetic screening in bacteria. We first co-opt the Streptococcus canis Cas9 that exhibits more flexible protospacer-adjacent motif recognition than the traditional Streptococcus pyogenes Cas9. We then expand beyond introducing premature stop codons by mutating start codons. Next, we derive guide design rules by applying machine learning to an essentiality screen conducted in Escherichia coli. Finally, we rescue poorly edited sites by combining base editing with Cas9-induced cleavage of unedited cells, thereby enriching for intended edits. The efficiency of this dual system was validated through a conditional essentiality screen based on growth in minimal media. Overall, expanding the scope of genome-wide knockout screens with base editors could further facilitate the investigation of new gene functions and interactions in bacteria.
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Affiliation(s)
- Sandra Gawlitt
- Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz Centre for Infection Research (HZI), 97080 Würzburg, Germany
| | - Scott P Collins
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695, USA
| | - Yanying Yu
- Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz Centre for Infection Research (HZI), 97080 Würzburg, Germany
| | - Samuel A Blackman
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695, USA
| | - Lars Barquist
- Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz Centre for Infection Research (HZI), 97080 Würzburg, Germany
- Department of Biology, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, Canada
- Medical Faculty, University of Würzburg, 97080 Würzburg, Germany
| | - Chase L Beisel
- Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz Centre for Infection Research (HZI), 97080 Würzburg, Germany
- Medical Faculty, University of Würzburg, 97080 Würzburg, Germany
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26
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Barry T, Roeder K, Katsevich E. Exponential family measurement error models for single-cell CRISPR screens. Biostatistics 2024:kxae010. [PMID: 38649751 DOI: 10.1093/biostatistics/kxae010] [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: 03/24/2022] [Revised: 01/10/2024] [Accepted: 03/11/2024] [Indexed: 04/25/2024] Open
Abstract
CRISPR genome engineering and single-cell RNA sequencing have accelerated biological discovery. Single-cell CRISPR screens unite these two technologies, linking genetic perturbations in individual cells to changes in gene expression and illuminating regulatory networks underlying diseases. Despite their promise, single-cell CRISPR screens present considerable statistical challenges. We demonstrate through theoretical and real data analyses that a standard method for estimation and inference in single-cell CRISPR screens-"thresholded regression"-exhibits attenuation bias and a bias-variance tradeoff as a function of an intrinsic, challenging-to-select tuning parameter. To overcome these difficulties, we introduce GLM-EIV ("GLM-based errors-in-variables"), a new method for single-cell CRISPR screen analysis. GLM-EIV extends the classical errors-in-variables model to responses and noisy predictors that are exponential family-distributed and potentially impacted by the same set of confounding variables. We develop a computational infrastructure to deploy GLM-EIV across hundreds of processors on clouds (e.g. Microsoft Azure) and high-performance clusters. Leveraging this infrastructure, we apply GLM-EIV to analyze two recent, large-scale, single-cell CRISPR screen datasets, yielding several new insights.
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Affiliation(s)
- Timothy Barry
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Building 2 435, 655 Huntington Ave, Boston, MA 02115, United States
| | - Kathryn Roeder
- Department of Statistics and Data Science, Carnegie Mellon University, Baker Hall 228B, 4909 Frew St, Pittsburgh, PA 15213, United States
| | - Eugene Katsevich
- Department of Statistics and Data Science, University of Pennsylvania, Academic Research Building 311, 265 South 37th Street Philadelphia, PA 19104, United States
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27
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Twentyman J, Emerman M, Ohainle M. Capsid-dependent lentiviral restrictions. J Virol 2024; 98:e0030824. [PMID: 38497663 PMCID: PMC11019884 DOI: 10.1128/jvi.00308-24] [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] [Indexed: 03/19/2024] Open
Abstract
Host antiviral proteins inhibit primate lentiviruses and other retroviruses by targeting many features of the viral life cycle. The lentiviral capsid protein and the assembled viral core are known to be inhibited through multiple, directly acting antiviral proteins. Several phenotypes, including those known as Lv1 through Lv5, have been described as cell type-specific blocks to infection against some but not all primate lentiviruses. Here we review important features of known capsid-targeting blocks to infection together with several blocks to infection for which the genes responsible for the inhibition still remain to be identified. We outline the features of these blocks as well as how current methodologies are now well suited to find these antiviral genes and solve these long-standing mysteries in the HIV and retrovirology fields.
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Affiliation(s)
- Joy Twentyman
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Michael Emerman
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Molly Ohainle
- Department of Molecular and Cell Biology, Division of Immunology and Molecular Medicine, University of California Berkeley, Berkeley, California, USA
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28
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Wu J, Feng S, Luo Y, Ning Y, Qiu P, Lin Y, Ma F, Zhuo Y. Transcriptomic profile of premature ovarian insufficiency with RNA-sequencing. Front Cell Dev Biol 2024; 12:1370772. [PMID: 38655066 PMCID: PMC11035783 DOI: 10.3389/fcell.2024.1370772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 03/27/2024] [Indexed: 04/26/2024] Open
Abstract
Introduction This study aimed to explore the transcriptomic profile of premature ovarian insufficiency (POI) by investigating alterations in gene expression. Methods A total of sixty-one women, comprising 31 individuals with POI in the POI group and 30 healthy women in the control group (HC group), aged between 24 and 40 years, were recruited for this study. The transcriptomic profiles of peripheral blood samples from all study subjects were analyzed using RNA-sequencing. Results The results revealed 39 differentially expressed genes in individuals with POI compared to healthy controls, with 10 upregulated and 29 downregulated genes. Correlation analysis highlighted the relationship between the expression of SLC25A39, CNIH3, and PDZK1IP1 and hormone levels. Additionally, an effective classification model was developed using SLC25A39, CNIH3, PDZK1IP1, SHISA4, and LOC389834. Functional enrichment analysis demonstrated the involvement of these differentially expressed genes in the "haptoglobin-hemoglobin complex," while KEGG pathway analysis indicated their participation in the "Proteoglycans in cancer" pathway. Conclusion The identified genes could play a crucial role in characterizing the genetic foundation of POI, potentially serving as valuable biomarkers for enhancing disease classification accuracy.
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Affiliation(s)
- Jiaman Wu
- Department of Chinese Medicine, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, China
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shiyu Feng
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yan Luo
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yan Ning
- Department of Chinese Medicine, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, China
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Pingping Qiu
- Department of Chinese Medicine, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, China
| | - Yanting Lin
- Department of Chinese Medicine, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, China
| | - Fei Ma
- Department of Chinese Medicine, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, China
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yuanyuan Zhuo
- Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
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29
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Longhurst AD, Wang K, Suresh HG, Ketavarapu M, Ward HN, Jones IR, Narayan V, Hundley FV, Hassan AZ, Boone C, Myers CL, Shen Y, Ramani V, Andrews BJ, Toczyski DP. The PRC2.1 Subcomplex Opposes G1 Progression through Regulation of CCND1 and CCND2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.18.585604. [PMID: 38562687 PMCID: PMC10983909 DOI: 10.1101/2024.03.18.585604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Progression through the G1 phase of the cell cycle is the most highly regulated step in cellular division. We employed a chemogenomics approach to discover novel cellular networks that regulate cell cycle progression. This approach uncovered functional clusters of genes that altered sensitivity of cells to inhibitors of the G1/S transition. Mutation of components of the Polycomb Repressor Complex 2 rescued growth inhibition caused by the CDK4/6 inhibitor palbociclib, but not to inhibitors of S phase or mitosis. In addition to its core catalytic subunits, mutation of the PRC2.1 accessory protein MTF2, but not the PRC2.2 protein JARID2, rendered cells resistant to palbociclib treatment. We found that PRC2.1 (MTF2), but not PRC2.2 (JARID2), was critical for promoting H3K27me3 deposition at CpG islands genome-wide and in promoters. This included the CpG islands in the promoter of the CDK4/6 cyclins CCND1 and CCND2, and loss of MTF2 lead to upregulation of both CCND1 and CCND2. Our results demonstrate a role for PRC2.1, but not PRC2.2, in promoting G1 progression.
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Affiliation(s)
- Adam D Longhurst
- University of California, San Francisco, San Francisco, CA 94158, USA
- Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Kyle Wang
- Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada
- The Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Harsha Garadi Suresh
- Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada
| | - Mythili Ketavarapu
- Gladstone Institute for Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, CA, USA
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Henry N Ward
- Bioinformatics and Computational Biology Graduate Program, University of Minnesota - Twin Cities Minneapolis MN USA
| | - Ian R Jones
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California
| | - Vivek Narayan
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Frances V Hundley
- University of California, San Francisco, San Francisco, CA 94158, USA
- Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Cell Biology, Blavatnik Institute of Harvard Medical School, Boston, MA 02115, USA
| | - Arshia Zernab Hassan
- Department of Computer Science and Engineering, University of Minnesota - Twin Cities Minneapolis MN USA
| | - Charles Boone
- Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada
- The Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Chad L Myers
- Bioinformatics and Computational Biology Graduate Program, University of Minnesota - Twin Cities Minneapolis MN USA
- Department of Cell Biology, Blavatnik Institute of Harvard Medical School, Boston, MA 02115, USA
| | - Yin Shen
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Vijay Ramani
- Gladstone Institute for Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, CA, USA
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Brenda J Andrews
- The Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - David P Toczyski
- University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
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30
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McGee AV, Liu YV, Griffith AL, Szegletes ZM, Wen B, Kraus C, Miller NW, Steger RJ, Escude Velasco B, Bosch JA, Zirin JD, Viswanatha R, Sontheimer EJ, Goodale A, Greene MA, Green TM, Doench JG. Modular vector assembly enables rapid assessment of emerging CRISPR technologies. CELL GENOMICS 2024; 4:100519. [PMID: 38484704 PMCID: PMC10943585 DOI: 10.1016/j.xgen.2024.100519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 12/31/2023] [Accepted: 02/08/2024] [Indexed: 03/19/2024]
Abstract
The diversity of CRISPR systems, coupled with scientific ingenuity, has led to an explosion of applications; however, to test newly described innovations in their model systems, researchers typically embark on cumbersome, one-off cloning projects to generate custom reagents that are optimized for their biological questions. Here, we leverage Golden Gate cloning to create the Fragmid toolkit, a modular set of CRISPR cassettes and delivery technologies, along with a web portal, resulting in a combinatorial platform that enables scalable vector assembly within days. We further demonstrate that multiple CRISPR technologies can be assessed in parallel in a pooled screening format using this resource, enabling the rapid optimization of both novel technologies and cellular models. These results establish Fragmid as a robust system for the rapid design of CRISPR vectors, and we anticipate that this assembly approach will be broadly useful for systematic development, comparison, and dissemination of CRISPR technologies.
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Affiliation(s)
- Abby V McGee
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yanjing V Liu
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Audrey L Griffith
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Zsofia M Szegletes
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Bronte Wen
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Carolyn Kraus
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Nathan W Miller
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ryan J Steger
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Berta Escude Velasco
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Justin A Bosch
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Jonathan D Zirin
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Raghuvir Viswanatha
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Erik J Sontheimer
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA; Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA; Li Weibo Institute for Rare Diseases Research, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Amy Goodale
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Matthew A Greene
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Thomas M Green
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - John G Doench
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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31
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Honeywell ME, Isidor MS, Harper NW, Fontana RE, Birdsall GA, Cruz-Gordillo P, Porto SA, Jerome M, Fraser CS, Sarosiek KA, Guertin DA, Spinelli JB, Lee MJ. Functional genomic screens with death rate analyses reveal mechanisms of drug action. Nat Chem Biol 2024:10.1038/s41589-024-01584-7. [PMID: 38480981 PMCID: PMC11393183 DOI: 10.1038/s41589-024-01584-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 02/20/2024] [Indexed: 03/22/2024]
Abstract
A common approach for understanding how drugs induce their therapeutic effects is to identify the genetic determinants of drug sensitivity. Because 'chemo-genetic profiles' are performed in a pooled format, inference of gene function is subject to several confounding influences related to variation in growth rates between clones. In this study, we developed Method for Evaluating Death Using a Simulation-assisted Approach (MEDUSA), which uses time-resolved measurements, along with model-driven constraints, to reveal the combination of growth and death rates that generated the observed drug response. MEDUSA is uniquely effective at identifying death regulatory genes. We apply MEDUSA to characterize DNA damage-induced lethality in the presence and absence of p53. Loss of p53 switches the mechanism of DNA damage-induced death from apoptosis to a non-apoptotic death that requires high respiration. These findings demonstrate the utility of MEDUSA both for determining the genetic dependencies of lethality and for revealing opportunities to potentiate chemo-efficacy in a cancer-specific manner.
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Affiliation(s)
- Megan E Honeywell
- Department of Systems Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Marie S Isidor
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicholas W Harper
- Department of Systems Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Rachel E Fontana
- Department of Systems Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Gavin A Birdsall
- Department of Systems Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Peter Cruz-Gordillo
- Department of Systems Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Sydney A Porto
- Department of Systems Biology, UMass Chan Medical School, Worcester, MA, USA
| | - Madison Jerome
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA, USA
| | - Cameron S Fraser
- John B. Little Center for Radiation Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kristopher A Sarosiek
- John B. Little Center for Radiation Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - David A Guertin
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA, USA
| | - Jessica B Spinelli
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA, USA
| | - Michael J Lee
- Department of Systems Biology, UMass Chan Medical School, Worcester, MA, USA.
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA, USA.
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32
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Wilson EL, Yu Y, Leal NS, Woodward JA, Patikas N, Morris JL, Field SF, Plumbly W, Paupe V, Chowdhury SR, Antrobus R, Lindop GE, Adia YM, Loh SHY, Prudent J, Martins LM, Metzakopian E. Genome-wide CRISPR/Cas9 screen shows that loss of GET4 increases mitochondria-endoplasmic reticulum contact sites and is neuroprotective. Cell Death Dis 2024; 15:203. [PMID: 38467609 PMCID: PMC10928201 DOI: 10.1038/s41419-024-06568-y] [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: 06/26/2023] [Revised: 02/13/2024] [Accepted: 02/19/2024] [Indexed: 03/13/2024]
Abstract
Organelles form membrane contact sites between each other, allowing for the transfer of molecules and signals. Mitochondria-endoplasmic reticulum (ER) contact sites (MERCS) are cellular subdomains characterized by close apposition of mitochondria and ER membranes. They have been implicated in many diseases, including neurodegenerative, metabolic, and cardiac diseases. Although MERCS have been extensively studied, much remains to be explored. To uncover novel regulators of MERCS, we conducted a genome-wide, flow cytometry-based screen using an engineered MERCS reporter cell line. We found 410 genes whose downregulation promotes MERCS and 230 genes whose downregulation decreases MERCS. From these, 29 genes were selected from each population for arrayed screening and 25 were validated from the high population and 13 from the low population. GET4 and BAG6 were highlighted as the top 2 genes that upon suppression increased MERCS from both the pooled and arrayed screens, and these were subjected to further investigation. Multiple microscopy analyses confirmed that loss of GET4 or BAG6 increased MERCS. GET4 and BAG6 were also observed to interact with the known MERCS proteins, inositol 1,4,5-trisphosphate receptors (IP3R) and glucose-regulated protein 75 (GRP75). In addition, we found that loss of GET4 increased mitochondrial calcium uptake upon ER-Ca2+ release and mitochondrial respiration. Finally, we show that loss of GET4 rescues motor ability, improves lifespan and prevents neurodegeneration in a Drosophila model of Alzheimer's disease (Aβ42Arc). Together, these results suggest that GET4 is involved in decreasing MERCS and that its loss is neuroprotective.
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Affiliation(s)
- Emma L Wilson
- UK Dementia Research Institute, University of Cambridge, Clifford Albutt building, Cambridge biomedical campus, Cambridge, CB2 0AH, UK
- MRC Mitochondrial Biology Unit, University of Cambridge, The Keith Peters building, Cambridge Biomedical Campus, Cambridge, CB2 0XY, UK
- MRC Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR, UK
| | - Yizhou Yu
- MRC Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR, UK
| | - Nuno S Leal
- MRC Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR, UK
| | - James A Woodward
- MRC Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR, UK
| | - Nikolaos Patikas
- UK Dementia Research Institute, University of Cambridge, Clifford Albutt building, Cambridge biomedical campus, Cambridge, CB2 0AH, UK
| | - Jordan L Morris
- MRC Mitochondrial Biology Unit, University of Cambridge, The Keith Peters building, Cambridge Biomedical Campus, Cambridge, CB2 0XY, UK
| | - Sarah F Field
- UK Dementia Research Institute, University of Cambridge, Clifford Albutt building, Cambridge biomedical campus, Cambridge, CB2 0AH, UK
| | - William Plumbly
- UK Dementia Research Institute, University of Cambridge, Clifford Albutt building, Cambridge biomedical campus, Cambridge, CB2 0AH, UK
| | - Vincent Paupe
- MRC Mitochondrial Biology Unit, University of Cambridge, The Keith Peters building, Cambridge Biomedical Campus, Cambridge, CB2 0XY, UK
| | - Suvagata R Chowdhury
- MRC Mitochondrial Biology Unit, University of Cambridge, The Keith Peters building, Cambridge Biomedical Campus, Cambridge, CB2 0XY, UK
| | - Robin Antrobus
- Cambridge Institute for Medical Research, University of Cambridge, The Keith Peters Building, Cambridge Biomedical Campus, Hills Rd, Cambridge, CB2 0XY, UK
| | - Georgina E Lindop
- Cambridge Advanced Imaging Centre, University of Cambridge, Anatomy Building, Downing Site, Cambridge, CB2 3DY, UK
| | - Yusuf M Adia
- MRC Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR, UK
| | - Samantha H Y Loh
- MRC Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR, UK
| | - Julien Prudent
- MRC Mitochondrial Biology Unit, University of Cambridge, The Keith Peters building, Cambridge Biomedical Campus, Cambridge, CB2 0XY, UK.
| | - L Miguel Martins
- MRC Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR, UK.
| | - Emmanouil Metzakopian
- UK Dementia Research Institute, University of Cambridge, Clifford Albutt building, Cambridge biomedical campus, Cambridge, CB2 0AH, UK.
- bit bio, The Dorothy Hodgkin Building, Babraham Research Campus, Cambridge, CB22 3FH, UK.
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33
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Peidli S, Green TD, Shen C, Gross T, Min J, Garda S, Yuan B, Schumacher LJ, Taylor-King JP, Marks DS, Luna A, Blüthgen N, Sander C. scPerturb: harmonized single-cell perturbation data. Nat Methods 2024; 21:531-540. [PMID: 38279009 DOI: 10.1038/s41592-023-02144-y] [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: 01/28/2023] [Accepted: 12/04/2023] [Indexed: 01/28/2024]
Abstract
Analysis across a growing number of single-cell perturbation datasets is hampered by poor data interoperability. To facilitate development and benchmarking of computational methods, we collect a set of 44 publicly available single-cell perturbation-response datasets with molecular readouts, including transcriptomics, proteomics and epigenomics. We apply uniform quality control pipelines and harmonize feature annotations. The resulting information resource, scPerturb, enables development and testing of computational methods, and facilitates comparison and integration across datasets. We describe energy statistics (E-statistics) for quantification of perturbation effects and significance testing, and demonstrate E-distance as a general distance measure between sets of single-cell expression profiles. We illustrate the application of E-statistics for quantifying similarity and efficacy of perturbations. The perturbation-response datasets and E-statistics computation software are publicly available at scperturb.org. This work provides an information resource for researchers working with single-cell perturbation data and recommendations for experimental design, including optimal cell counts and read depth.
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Affiliation(s)
- Stefan Peidli
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität, Berlin, Germany.
- Institute of Biology, Humboldt-Universität, Berlin, Germany.
| | - Tessa D Green
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Ciyue Shen
- Departments of Cell Biology and Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | | | - Joseph Min
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Samuele Garda
- Institute of Biology, Humboldt-Universität, Berlin, Germany
- Institute for Computer Science, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Bo Yuan
- Departments of Cell Biology and Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | - Linus J Schumacher
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | | | - Debora S Marks
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | - Augustin Luna
- Departments of Cell Biology and Systems Biology, Harvard Medical School, Boston, MA, USA.
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
- Broad Institute, Cambridge, MA, USA.
- Computational Biology Branch, National Library of Medicine and Developmental Therapeutics Branch, National Cancer Institute, Bethesda, MD, USA.
| | - Nils Blüthgen
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität, Berlin, Germany.
- Institute of Biology, Humboldt-Universität, Berlin, Germany.
| | - Chris Sander
- Departments of Cell Biology and Systems Biology, Harvard Medical School, Boston, MA, USA.
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
- Broad Institute, Cambridge, MA, USA.
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34
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Wang Y, Engel T, Teng X. Post-translational regulation of the mTORC1 pathway: A switch that regulates metabolism-related gene expression. BIOCHIMICA ET BIOPHYSICA ACTA. GENE REGULATORY MECHANISMS 2024; 1867:195005. [PMID: 38242428 DOI: 10.1016/j.bbagrm.2024.195005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 12/15/2023] [Accepted: 01/03/2024] [Indexed: 01/21/2024]
Abstract
The mechanistic target of rapamycin complex 1 (mTORC1) is a kinase complex that plays a crucial role in coordinating cell growth in response to various signals, including amino acids, growth factors, oxygen, and ATP. Activation of mTORC1 promotes cell growth and anabolism, while its suppression leads to catabolism and inhibition of cell growth, enabling cells to withstand nutrient scarcity and stress. Dysregulation of mTORC1 activity is associated with numerous diseases, such as cancer, metabolic disorders, and neurodegenerative conditions. This review focuses on how post-translational modifications, particularly phosphorylation and ubiquitination, modulate mTORC1 signaling pathway and their consequential implications for pathogenesis. Understanding the impact of phosphorylation and ubiquitination on the mTORC1 signaling pathway provides valuable insights into the regulation of cellular growth and potential therapeutic targets for related diseases.
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Affiliation(s)
- Yitao Wang
- College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu 215123, China; Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, University of Medicine and Health Sciences, Dublin D02 YN77, Ireland
| | - Tobias Engel
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, University of Medicine and Health Sciences, Dublin D02 YN77, Ireland; FutureNeuro, SFI Research Centre for Chronic and Rare Neurological Diseases, RCSI University of Medicine and Health Sciences, Dublin D02 YN77, Ireland
| | - Xinchen Teng
- College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu 215123, China.
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35
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Kim SH, Park JH, Shin S, Shin S, Chun D, Kim YG, Yoo J, You WK, Lee JS, Lee GM. Genome-Wide CRISPR/Cas9 Screening Unveils a Novel Target ATF7IP-SETDB1 Complex for Enhancing Difficult-to-Express Protein Production. ACS Synth Biol 2024; 13:634-647. [PMID: 38240694 DOI: 10.1021/acssynbio.3c00646] [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] [Indexed: 02/17/2024]
Abstract
With the emerging novel biotherapeutics that are typically difficult-to-express (DTE), improvement is required for high-yield production. To identify novel targets that can enhance DTE protein production, we performed genome-wide fluorescence-activated cell sorting (FACS)-based clustered regularly interspaced short palindromic repeats (CRISPR) knockout screening in bispecific antibody (bsAb)-producing Chinese hamster ovary (CHO) cells. The screen identified the two highest-scoring genes, Atf7ip and Setdb1, which are the binding partners for H3K9me3-mediated transcriptional repression. The ATF7IP-SETDB1 complex knockout in bsAb-producing CHO cells suppressed cell growth but enhanced productivity by up to 2.7-fold. Decreased H3K9me3 levels and an increased transcriptional expression level of the transgene were also observed. Furthermore, perturbation of the ATF7IP-SETDB1 complex in monoclonal antibody (mAb)-producing CHO cells led to substantial improvements in mAb production, increasing the productivity by up to 3.9-fold without affecting the product quality. Taken together, the genome-wide FACS-based CRISPR screen identified promising targets associated with histone methylation, whose perturbation enhanced the productivity by unlocking the transgene expression.
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Affiliation(s)
- Su Hyun Kim
- Department of Biological Sciences, KAIST, Daejeon 34141, Republic of Korea
| | - Jong-Ho Park
- Department of Biological Sciences, KAIST, Daejeon 34141, Republic of Korea
- Biotherapeutics Translational Research Center, KRIBB, Daejeon 34141, Republic of Korea
| | - Sungwook Shin
- Department of Molecular Science and Technology, Ajou University, Suwon 16499, Republic of Korea
| | - Seunghyeon Shin
- Department of Biological Sciences, KAIST, Daejeon 34141, Republic of Korea
| | - Dahyun Chun
- Department of R&D, ABL Bio Inc, Seongnam 13488, Republic of Korea
| | - Yeon-Gu Kim
- Biotherapeutics Translational Research Center, KRIBB, Daejeon 34141, Republic of Korea
- Department of Bioprocess Engineering, KRIBB School of Biotechnology, UST, , Daejeon 34113, Republic of Korea
| | - Jiseon Yoo
- Department of R&D, ABL Bio Inc, Seongnam 13488, Republic of Korea
| | - Weon-Kyoo You
- Department of R&D, ABL Bio Inc, Seongnam 13488, Republic of Korea
| | - Jae Seong Lee
- Department of Molecular Science and Technology, Ajou University, Suwon 16499, Republic of Korea
| | - Gyun Min Lee
- Department of Biological Sciences, KAIST, Daejeon 34141, Republic of Korea
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36
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Fukuda K. The role of transposable elements in human evolution and methods for their functional analysis: current status and future perspectives. Genes Genet Syst 2024; 98:289-304. [PMID: 37866889 DOI: 10.1266/ggs.23-00140] [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] [Indexed: 10/24/2023] Open
Abstract
Transposable elements (TEs) are mobile DNA sequences that can insert themselves into various locations within the genome, causing mutations that may provide advantages or disadvantages to individuals and species. The insertion of TEs can result in genetic variation that may affect a wide range of human traits including genetic disorders. Understanding the role of TEs in human biology is crucial for both evolutionary and medical research. This review discusses the involvement of TEs in human traits and disease susceptibility, as well as methods for functional analysis of TEs.
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Affiliation(s)
- Kei Fukuda
- Integrative Genomics Unit, The University of Melbourne
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37
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Hsiung CC, Wilson CM, Sambold NA, Dai R, Chen Q, Misiukiewicz S, Arab A, Teyssier N, O'Loughlin T, Cofsky JC, Shi J, Gilbert LA. Higher-order combinatorial chromatin perturbations by engineered CRISPR-Cas12a for functional genomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.18.558350. [PMID: 37781594 PMCID: PMC10541102 DOI: 10.1101/2023.09.18.558350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
Multiplexed genetic perturbations are critical for testing functional interactions among coding or non-coding genetic elements. Compared to double-stranded DNA cutting, repressive chromatin formation using CRISPR interference (CRISPRi) avoids genotoxicity and is more effective for perturbing non-coding regulatory elements in pooled assays. However, current CRISPRi pooled screening approaches are limited to targeting 1-3 genomic sites per cell. To develop a tool for higher-order ( > 3) combinatorial targeting of genomic sites with CRISPRi in functional genomics screens, we engineered an Acidaminococcus Cas12a variant -- referred to as mul tiplexed transcriptional interference AsCas12a (multiAsCas12a). multiAsCas12a incorporates a key mutation, R1226A, motivated by the hypothesis of nicking-induced stabilization of the ribonucleoprotein:DNA complex for improving CRISPRi activity. multiAsCas12a significantly outperforms prior state-of-the-art Cas12a variants in combinatorial CRISPRi targeting using high-order multiplexed arrays of lentivirally transduced CRISPR RNAs (crRNA), including in high-throughput pooled screens using 6-plex crRNA array libraries. Using multiAsCas12a CRISPRi, we discover new enhancer elements and dissect the combinatorial function of cis-regulatory elements. These results instantiate a group testing framework for efficiently surveying potentially numerous combinations of chromatin perturbations for biological discovery and engineering.
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38
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Guzman UH, Martinez-Val A, Ye Z, Damoc E, Arrey TN, Pashkova A, Renuse S, Denisov E, Petzoldt J, Peterson AC, Harking F, Østergaard O, Rydbirk R, Aznar S, Stewart H, Xuan Y, Hermanson D, Horning S, Hock C, Makarov A, Zabrouskov V, Olsen JV. Ultra-fast label-free quantification and comprehensive proteome coverage with narrow-window data-independent acquisition. Nat Biotechnol 2024:10.1038/s41587-023-02099-7. [PMID: 38302753 DOI: 10.1038/s41587-023-02099-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 12/13/2023] [Indexed: 02/03/2024]
Abstract
Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here we present the narrow-window data-independent acquisition (nDIA) strategy consisting of high-resolution MS1 scans with parallel tandem MS (MS/MS) scans of ~200 Hz using 2-Th isolation windows, dissolving the differences between data-dependent and -independent methods. This is achieved by pairing a quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer which provides >200-Hz MS/MS scanning speed, high resolving power and sensitivity, and low-ppm mass accuracy. The nDIA strategy enables profiling of >100 full yeast proteomes per day, or 48 human proteomes per day at the depth of ~10,000 human protein groups in half-an-hour or ~7,000 proteins in 5 min, representing 3× higher coverage compared with current state-of-the-art MS. Multi-shot acquisition of offline fractionated samples provides comprehensive coverage of human proteomes in ~3 h. High quantitative precision and accuracy are demonstrated in a three-species proteome mixture, quantifying 14,000+ protein groups in a single half-an-hour run.
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Affiliation(s)
- Ulises H Guzman
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Ana Martinez-Val
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Zilu Ye
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China
| | - Eugen Damoc
- Thermo Fisher Scientific (Bremen) GmbH, Bremen, Germany
| | | | - Anna Pashkova
- Thermo Fisher Scientific (Bremen) GmbH, Bremen, Germany
| | | | | | | | | | - Florian Harking
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Ole Østergaard
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Rasmus Rydbirk
- Center for Functional Genomics and Tissue Plasticity (ATLAS), Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Susana Aznar
- Centre for Neuroscience and Stereology, Copenhagen University Hospital, Copenhagen, Denmark
| | | | - Yue Xuan
- Thermo Fisher Scientific (Bremen) GmbH, Bremen, Germany
| | | | | | | | | | | | - Jesper V Olsen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.
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39
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Ertl H. Efficient computation reveals rare CRISPR-Cas systems. Nat Rev Genet 2024; 25:80. [PMID: 38114787 DOI: 10.1038/s41576-023-00690-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
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40
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Heo SJ, Enriquez LD, Federman S, Chang AY, Mace R, Shevade K, Nguyen P, Litterman AJ, Shafer S, Przybyla L, Chow ED. Compact CRISPR genetic screens enabled by improved guide RNA library cloning. Genome Biol 2024; 25:25. [PMID: 38243310 PMCID: PMC10797759 DOI: 10.1186/s13059-023-03132-3] [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: 06/09/2023] [Accepted: 11/29/2023] [Indexed: 01/21/2024] Open
Abstract
CRISPR genome editing approaches theoretically enable researchers to define the function of each human gene in specific cell types, but challenges remain to efficiently perform genetic perturbations in relevant models. In this work, we develop a library cloning protocol that increases sgRNA uniformity and greatly reduces bias in existing genome-wide libraries. We demonstrate that our libraries can achieve equivalent or better statistical power compared to previously reported screens using an order of magnitude fewer cells. This improved cloning protocol enables genome-scale CRISPR screens in technically challenging cell models and screen formats.
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Affiliation(s)
- Seok-Jin Heo
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Lauren D Enriquez
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Scot Federman
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Amy Y Chang
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Rachel Mace
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Kaivalya Shevade
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Phuong Nguyen
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Adam J Litterman
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Shawn Shafer
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA
- GSK, San Francisco, CA, 94158, USA
| | - Laralynne Przybyla
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Eric D Chow
- Laboratory for Genomics Research, San Francisco, CA, 94158, USA.
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA.
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41
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Schubach M, Maass T, Nazaretyan L, Röner S, Kircher M. CADD v1.7: using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions. Nucleic Acids Res 2024; 52:D1143-D1154. [PMID: 38183205 PMCID: PMC10767851 DOI: 10.1093/nar/gkad989] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 10/14/2023] [Accepted: 10/17/2023] [Indexed: 01/07/2024] Open
Abstract
Machine Learning-based scoring and classification of genetic variants aids the assessment of clinical findings and is employed to prioritize variants in diverse genetic studies and analyses. Combined Annotation-Dependent Depletion (CADD) is one of the first methods for the genome-wide prioritization of variants across different molecular functions and has been continuously developed and improved since its original publication. Here, we present our most recent release, CADD v1.7. We explored and integrated new annotation features, among them state-of-the-art protein language model scores (Meta ESM-1v), regulatory variant effect predictions (from sequence-based convolutional neural networks) and sequence conservation scores (Zoonomia). We evaluated the new version on data sets derived from ClinVar, ExAC/gnomAD and 1000 Genomes variants. For coding effects, we tested CADD on 31 Deep Mutational Scanning (DMS) data sets from ProteinGym and, for regulatory effect prediction, we used saturation mutagenesis reporter assay data of promoter and enhancer sequences. The inclusion of new features further improved the overall performance of CADD. As with previous releases, all data sets, genome-wide CADD v1.7 scores, scripts for on-site scoring and an easy-to-use webserver are readily provided via https://cadd.bihealth.org/ or https://cadd.gs.washington.edu/ to the community.
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Affiliation(s)
- Max Schubach
- Exploratory Diagnostic Sciences, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Thorben Maass
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck, Lübeck, Germany
| | - Lusiné Nazaretyan
- Exploratory Diagnostic Sciences, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Sebastian Röner
- Exploratory Diagnostic Sciences, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Martin Kircher
- Exploratory Diagnostic Sciences, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
- Institute of Human Genetics, University Hospital Schleswig-Holstein, University of Lübeck, Lübeck, Germany
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42
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Yang C, Lei Y, Ren T, Yao M. The Current Situation and Development Prospect of Whole-Genome Screening. Int J Mol Sci 2024; 25:658. [PMID: 38203828 PMCID: PMC10779205 DOI: 10.3390/ijms25010658] [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: 11/21/2023] [Revised: 12/22/2023] [Accepted: 12/29/2023] [Indexed: 01/12/2024] Open
Abstract
High-throughput genetic screening is useful for discovering critical genes or gene sequences that trigger specific cell functions and/or phenotypes. Loss-of-function genetic screening is mainly achieved through RNA interference (RNAi), CRISPR knock-out (CRISPRko), and CRISPR interference (CRISPRi) technologies. Gain-of-function genetic screening mainly depends on the overexpression of a cDNA library and CRISPR activation (CRISPRa). Base editing can perform both gain- and loss-of-function genetic screening. This review discusses genetic screening techniques based on Cas9 nuclease, including Cas9-mediated genome knock-out and dCas9-based gene activation and interference. We compare these methods with previous genetic screening techniques based on RNAi and cDNA library overexpression and propose future prospects and applications for CRISPR screening.
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Affiliation(s)
| | | | | | - Mingze Yao
- Shanxi Provincial Key Laboratory for Medical Molecular Cell Biology, Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education and Institute of Biomedical Sciences, Shanxi University, Taiyuan 030006, China; (C.Y.); (Y.L.); (T.R.)
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43
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Collins C, Baker S, Brown J, Zheng H, Chan A, Stenius U, Narita M, Korhonen A. Text mining for contexts and relationships in cancer genomics literature. Bioinformatics 2024; 40:btae021. [PMID: 38258418 PMCID: PMC10822582 DOI: 10.1093/bioinformatics/btae021] [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: 04/13/2023] [Revised: 09/27/2023] [Accepted: 01/15/2024] [Indexed: 01/24/2024] Open
Abstract
MOTIVATION Scientific advances build on the findings of existing research. The 2001 publication of the human genome has led to the production of huge volumes of literature exploring the context-specific functions and interactions of genes. Technology is needed to perform large-scale text mining of research papers to extract the reported actions of genes in specific experimental contexts and cell states, such as cancer, thereby facilitating the design of new therapeutic strategies. RESULTS We present a new corpus and Text Mining methodology that can accurately identify and extract the most important details of cancer genomics experiments from biomedical texts. We build a Named Entity Recognition model that accurately extracts relevant experiment details from PubMed abstract text, and a second model that identifies the relationships between them. This system outperforms earlier models and enables the analysis of gene function in diverse and dynamically evolving experimental contexts. AVAILABILITY AND IMPLEMENTATION Code and data are available here: https://github.com/cambridgeltl/functional-genomics-ie.
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Affiliation(s)
- Charlotte Collins
- Language Technology Laboratory, Theoretical and Applied Linguistics, Faculty of Modern and Medieval Languages and Linguistics, University of Cambridge, Cambridge CB3 9DA, United Kingdom
| | - Simon Baker
- Language Technology Laboratory, Theoretical and Applied Linguistics, Faculty of Modern and Medieval Languages and Linguistics, University of Cambridge, Cambridge CB3 9DA, United Kingdom
| | - Jason Brown
- Language Technology Laboratory, Theoretical and Applied Linguistics, Faculty of Modern and Medieval Languages and Linguistics, University of Cambridge, Cambridge CB3 9DA, United Kingdom
| | - Huiyuan Zheng
- Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Adelyne Chan
- Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge CB2 0RE, United Kingdom
| | - Ulla Stenius
- Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Masashi Narita
- Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge CB2 0RE, United Kingdom
| | - Anna Korhonen
- Language Technology Laboratory, Theoretical and Applied Linguistics, Faculty of Modern and Medieval Languages and Linguistics, University of Cambridge, Cambridge CB3 9DA, United Kingdom
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44
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Fair T, Pavlovic BJ, Schaefer NK, Pollen AA. Mapping cis- and trans-regulatory target genes of human-specific deletions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.27.573461. [PMID: 38234800 PMCID: PMC10793408 DOI: 10.1101/2023.12.27.573461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Deletion of functional sequence is predicted to represent a fundamental mechanism of molecular evolution1,2. Comparative genetic studies of primates2,3 have identified thousands of human-specific deletions (hDels), and the cis-regulatory potential of short (≤31 base pairs) hDels has been assessed using reporter assays4. However, how structural variant-sized (≥50 base pairs) hDels influence molecular and cellular processes in their native genomic contexts remains unexplored. Here, we design genome-scale libraries of single-guide RNAs targeting 7.2 megabases of sequence in 6,358 hDels and present a systematic CRISPR interference (CRISPRi) screening approach to identify hDels that modify cellular proliferation in chimpanzee pluripotent stem cells. By intersecting hDels with chromatin state features and performing single-cell CRISPRi (Perturb-seq) to identify their cis- and trans-regulatory target genes, we discovered 19 hDels controlling gene expression. We highlight two hDels, hDel_2247 and hDel_585, with tissue-specific activity in the liver and brain, respectively. Our findings reveal a molecular and cellular role for sequences lost in the human lineage and establish a framework for functionally interrogating human-specific genetic variants.
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Affiliation(s)
- Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Bryan J Pavlovic
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Nathan K Schaefer
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
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45
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Shen W, Hu F, Lei P, Tang Y. Applications of CRISPR screening to lung cancer treatment. Front Cell Dev Biol 2023; 11:1295555. [PMID: 38169973 PMCID: PMC10760454 DOI: 10.3389/fcell.2023.1295555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 11/14/2023] [Indexed: 01/05/2024] Open
Abstract
Lung cancer is an extremely aggressive and highly prevalent disease worldwide, and it is one of the leading causes of cancer death. Deciphering intrinsic genetic mechanism, finding new targets, and overcoming drug resistance are the key to lung cancer treatment. High-throughput CRISPR screening has been extensively used to obtain the genes related to cancers including lung cancer. This review describes CRISPR/Cas9 or CRISPR/dCas9-based technologies for high-throughput screening. We summarize the applications of CRISPR screening technology in exploring the mechanism of lung cancer development in vivo or in vitro, overcoming drug resistance, improving the effect of immunotherapy, and discovering new therapeutic targets. This review highlights the potential of CRISPR screening in combination with tumor barcoding and high-throughput sequencing (Tuba-seq) to precisely quantify the impact of alterations in many tumor suppressor genes on lung cancer.
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Affiliation(s)
- Wanying Shen
- Department of Neurosurgery, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, China
| | - Fangli Hu
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, China
| | - Pan Lei
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, China
- Hubei Clinical Research Center for Precise Diagnosis and Treatment of Liver Cancer, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Yijun Tang
- Department of Neurosurgery, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, China
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46
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Piya D, Nolan N, Moore ML, Ramirez Hernandez LA, Cress BF, Young R, Arkin AP, Mutalik VK. Systematic and scalable genome-wide essentiality mapping to identify nonessential genes in phages. PLoS Biol 2023; 21:e3002416. [PMID: 38048319 PMCID: PMC10695390 DOI: 10.1371/journal.pbio.3002416] [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: 05/23/2023] [Accepted: 11/02/2023] [Indexed: 12/06/2023] Open
Abstract
Phages are one of the key ecological drivers of microbial community dynamics, function, and evolution. Despite their importance in bacterial ecology and evolutionary processes, phage genes are poorly characterized, hampering their usage in a variety of biotechnological applications. Methods to characterize such genes, even those critical to the phage life cycle, are labor intensive and are generally phage specific. Here, we develop a systematic gene essentiality mapping method scalable to new phage-host combinations that facilitate the identification of nonessential genes. As a proof of concept, we use an arrayed genome-wide CRISPR interference (CRISPRi) assay to map gene essentiality landscape in the canonical coliphages λ and P1. Results from a single panel of CRISPRi probes largely recapitulate the essential gene roster determined from decades of genetic analysis for lambda and provide new insights into essential and nonessential loci in P1. We present evidence of how CRISPRi polarity can lead to false positive gene essentiality assignments and recommend caution towards interpreting CRISPRi data on gene essentiality when applied to less studied phages. Finally, we show that we can engineer phages by inserting DNA barcodes into newly identified inessential regions, which will empower processes of identification, quantification, and tracking of phages in diverse applications.
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Affiliation(s)
- Denish Piya
- Innovative Genomics Institute, University of California-Berkeley, Berkeley, California, United States of America
| | - Nicholas Nolan
- Department of Bioengineering, University of California-Berkeley, Berkeley, California, United States of America
| | - Madeline L. Moore
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Luis A. Ramirez Hernandez
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Brady F. Cress
- Innovative Genomics Institute, University of California-Berkeley, Berkeley, California, United States of America
- Department of Molecular and Cell Biology, University of California-Berkeley, Berkeley, California, United States of America
| | - Ry Young
- Department of Biochemistry and Biophysics, Center for Phage Technology, Texas A&M University, College Station, Texas, United States of America
| | - Adam P. Arkin
- Innovative Genomics Institute, University of California-Berkeley, Berkeley, California, United States of America
- Department of Bioengineering, University of California-Berkeley, Berkeley, California, United States of America
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Vivek K. Mutalik
- Innovative Genomics Institute, University of California-Berkeley, Berkeley, California, United States of America
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
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47
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McGee AV, Liu YV, Griffith AL, Szegletes ZM, Wen B, Kraus C, Miller NW, Steger RJ, Velasco BE, Bosch JA, Zirin JD, Viswanatha R, Sontheimer EJ, Goodale A, Greene MA, Green TM, Doench JG. Modular vector assembly enables rapid assessment of emerging CRISPR technologies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.25.564061. [PMID: 37961518 PMCID: PMC10634825 DOI: 10.1101/2023.10.25.564061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The diversity of CRISPR systems, coupled with scientific ingenuity, has led to an explosion of applications; however, to test newly-described innovations in their model systems, researchers typically embark on cumbersome, one-off cloning projects to generate custom reagents that are optimized for their biological questions. Here, we leverage Golden Gate cloning to create the Fragmid toolkit, a modular set of CRISPR cassettes and delivery technologies, along with a web portal, resulting in a combinatorial platform that enables scalable vector assembly within days. We further demonstrate that multiple CRISPR technologies can be assessed in parallel in a pooled screening format using this resource, enabling the rapid optimization of both novel technologies and cellular models. These results establish Fragmid as a robust system for the rapid design of CRISPR vectors, and we anticipate that this assembly approach will be broadly useful for systematic development, comparison, and dissemination of CRISPR technologies.
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Affiliation(s)
- Abby V McGee
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yanjing V Liu
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Audrey L Griffith
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Zsofia M Szegletes
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Bronte Wen
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Carolyn Kraus
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Nathan W Miller
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ryan J Steger
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Berta Escude Velasco
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Justin A Bosch
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Jonathan D Zirin
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Raghuvir Viswanatha
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Erik J Sontheimer
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Li Weibo Institute for Rare Diseases Research, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Amy Goodale
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Matthew A Greene
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Thomas M Green
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - John G Doench
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
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48
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Ravichandran M, Maddalo D. Applications of CRISPR-Cas9 for advancing precision medicine in oncology: from target discovery to disease modeling. Front Genet 2023; 14:1273994. [PMID: 37908590 PMCID: PMC10613999 DOI: 10.3389/fgene.2023.1273994] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 09/27/2023] [Indexed: 11/02/2023] Open
Abstract
The clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9) (CRISPR/Cas9) system is a powerful tool that enables precise and efficient gene manipulation. In a relatively short time, CRISPR has risen to become the preferred gene-editing system due to its high efficiency, simplicity, and programmability at low costs. Furthermore, in the recent years, the CRISPR toolkit has been rapidly expanding, and the emerging advancements have shown tremendous potential in uncovering molecular mechanisms and new therapeutic strategies for human diseases. In this review, we provide our perspectives on the recent advancements in CRISPR technology and its impact on precision medicine, ranging from target identification, disease modeling, and diagnostics. We also discuss the impact of novel approaches such as epigenome, base, and prime editing on preclinical cancer drug discovery.
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Affiliation(s)
- Mirunalini Ravichandran
- Department of Translational Oncology, Genentech, Inc., South San Francisco, CA, United States
| | - Danilo Maddalo
- Department of Translational Oncology, Genentech, Inc., South San Francisco, CA, United States
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49
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Gilan O, Talarmain L, Bell CC, Neville D, Knezevic K, Ferguson DT, Boudes M, Chan YC, Davidovich C, Lam EYN, Dawson MA. CRISPR-ChIP reveals selective regulation of H3K79me2 by Menin in MLL leukemia. Nat Struct Mol Biol 2023; 30:1592-1606. [PMID: 37679565 DOI: 10.1038/s41594-023-01087-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 08/03/2023] [Indexed: 09/09/2023]
Abstract
Chromatin regulation involves the selective recruitment of chromatin factors to facilitate DNA repair, replication and transcription. Here we demonstrate the utility of coupling unbiased functional genomics with chromatin immunoprecipitation (CRISPR-ChIP) to identify the factors associated with active chromatin modifications in mammalian cells. Specifically, an integrated reporter containing a cis-regulatory element of interest and a single guide RNA provide a chromatinized template for a direct readout for regulators of histone modifications associated with actively transcribed genes such as H3K4me3 and H3K79me2. With CRISPR-ChIP, we identify all the nonredundant COMPASS complex members required for H3K4me3 and demonstrate that RNA polymerase II is dispensable for the maintenance of H3K4me3. As H3K79me2 has a putative oncogenic function in leukemia cells driven by MLL translocations, using CRISPR-ChIP we reveal a functional partitioning of H3K79 methylation into two distinct regulatory units: an oncogenic DOT1L complex directed by the MLL fusion protein in a Menin-dependent manner and a separate endogenous DOT1L complex, where catalytic activity is directed by MLLT10. Overall, CRISPR-ChIP provides a powerful tool for the unbiased interrogation of the mechanisms underpinning chromatin regulation.
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Affiliation(s)
- Omer Gilan
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia.
- Australian Centre for Blood Diseases, Monash University, Melbourne, Victoria, Australia.
| | - Laure Talarmain
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Charles C Bell
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Daniel Neville
- Australian Centre for Blood Diseases, Monash University, Melbourne, Victoria, Australia
| | - Kathy Knezevic
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Daniel T Ferguson
- Australian Centre for Blood Diseases, Monash University, Melbourne, Victoria, Australia
| | - Marion Boudes
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
| | - Yih-Chih Chan
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Chen Davidovich
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
- EMBL-Australia, Clayton, Victoria, Australia
| | - Enid Y N Lam
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Mark A Dawson
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia.
- Department of Clinical Haematology, Peter MacCallum Cancer Centre & Royal Melbourne Hospital, Melbourne, Victoria, Australia.
- Centre for Cancer Research, University of Melbourne, Melbourne, Victoria, Australia.
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50
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Frenkel M, Hujoel ML, Morris Z, Raman S. Discovering chromatin dysregulation induced by protein-coding perturbations at scale. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.20.555752. [PMID: 37781603 PMCID: PMC10541138 DOI: 10.1101/2023.09.20.555752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
Although population-scale databases have expanded to millions of protein-coding variants, insight into variant mechanisms has not kept pace. We present PROD-ATAC, a high-throughput method for discovering the effects of protein-coding variants on chromatin. A pooled library of variants is expressed in a disease-agnostic cell line, and single-cell ATAC resolves each variant's effect on chromatin. Using PROD-ATAC, we characterized the effects of >100 oncofusions (a class of cancer-causing chimeric proteins) and controls and revealed that pioneer activity is a common feature of fusions spanning an enormous range of fusion frequencies. Further, fusion-induced dysregulation can be context-agnostic as observed mechanisms often overlapped with cancer and cell-type specific prior knowledge. We also showed that gain-of-function pioneering is common among oncofusions. This work provides a global view of fusion-induced chromatin. We uncovered convergent mechanisms among disparate oncofusions and shared modes of dysregulation across different cancers. PROD-ATAC is generalizable to any set of protein-coding variants.
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Affiliation(s)
- Max Frenkel
- Cellular and Molecular Biology Graduate Program, University of Wisconsin, Madison, Wisconsin, USA
- Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, USA
| | - Margaux L.A. Hujoel
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Zachary Morris
- Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Srivatsan Raman
- Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, USA
- Department of Bacteriology, University of Wisconsin, Madison, Wisconsin, USA
- Department of Chemical and Biological Engineering, University of Wisconsin, Madison, Wisconsin, USA
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