1
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Hwang Y, Cornman AL, Kellogg EH, Ovchinnikov S, Girguis PR. Genomic language model predicts protein co-regulation and function. Nat Commun 2024; 15:2880. [PMID: 38570504 PMCID: PMC10991518 DOI: 10.1038/s41467-024-46947-9] [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: 05/30/2023] [Accepted: 03/13/2024] [Indexed: 04/05/2024] Open
Abstract
Deciphering the relationship between a gene and its genomic context is fundamental to understanding and engineering biological systems. Machine learning has shown promise in learning latent relationships underlying the sequence-structure-function paradigm from massive protein sequence datasets. However, to date, limited attempts have been made in extending this continuum to include higher order genomic context information. Evolutionary processes dictate the specificity of genomic contexts in which a gene is found across phylogenetic distances, and these emergent genomic patterns can be leveraged to uncover functional relationships between gene products. Here, we train a genomic language model (gLM) on millions of metagenomic scaffolds to learn the latent functional and regulatory relationships between genes. gLM learns contextualized protein embeddings that capture the genomic context as well as the protein sequence itself, and encode biologically meaningful and functionally relevant information (e.g. enzymatic function, taxonomy). Our analysis of the attention patterns demonstrates that gLM is learning co-regulated functional modules (i.e. operons). Our findings illustrate that gLM's unsupervised deep learning of the metagenomic corpus is an effective and promising approach to encode functional semantics and regulatory syntax of genes in their genomic contexts and uncover complex relationships between genes in a genomic region.
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Affiliation(s)
- Yunha Hwang
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
| | | | - Elizabeth H Kellogg
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Sergey Ovchinnikov
- John Harvard Distinguished Science Fellowship Program, Harvard University, Cambridge, MA, USA.
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Peter R Girguis
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
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2
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Hwarari D, Radani Y, Ke Y, Chen J, Yang L. CRISPR/Cas genome editing in plants: mechanisms, applications, and overcoming bottlenecks. Funct Integr Genomics 2024; 24:50. [PMID: 38441816 DOI: 10.1007/s10142-024-01314-1] [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: 01/17/2024] [Revised: 02/11/2024] [Accepted: 02/13/2024] [Indexed: 03/07/2024]
Abstract
The CRISPR/Cas systems have emerged as transformative tools for precisely manipulating plant genomes and enhancement. It has provided unparalleled applications from modifying the plant genomes to resistant enhancement. This review manuscript summarises the mechanism, application, and current challenges in the CRISPR/Cas genome editing technology. It addresses the molecular mechanisms of different Cas genes, elucidating their applications in various plants through crop improvement, disease resistance, and trait improvement. The advent of the CRISPR/Cas systems has enabled researchers to precisely modify plant genomes through gene knockouts, knock-ins, and gene expression modulation. Despite these successes, the CRISPR/Cas technology faces challenges, including off-target effects, Cas toxicity, and efficiency. In this manuscript, we also discuss these challenges and outline ongoing strategies employed to overcome these challenges, including the development of novel CRISPR/Cas variants with improved specificity and specific delivery methods for different plant species. The manuscript will conclude by addressing the future perspectives of the CRISPR/Cas technology in plants. Although this review manuscript is not conclusive, it aims to provide immense insights into the current state and future potential of CRISPR/Cas in sustainable and secure plant production.
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Affiliation(s)
- Delight Hwarari
- State Key Laboratory of Tree Genetics and Breeding, School of Life Sciences, Nanjing Forestry University, Nanjing, 210037, China
| | - Yasmina Radani
- State Key Laboratory of Tree Genetics and Breeding, School of Life Sciences, Nanjing Forestry University, Nanjing, 210037, China
| | - Yongchao Ke
- State Key Laboratory of Tree Genetics and Breeding, School of Life Sciences, Nanjing Forestry University, Nanjing, 210037, China
| | - Jinhui Chen
- State Key Laboratory of Tree Genetics and Breeding, School of Life Sciences, Nanjing Forestry University, Nanjing, 210037, China.
| | - Liming Yang
- State Key Laboratory of Tree Genetics and Breeding, School of Life Sciences, Nanjing Forestry University, Nanjing, 210037, China.
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3
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Graver BA, Chakravarty N, Solomon KV. Prokaryotic Argonautes for in vivo biotechnology and molecular diagnostics. Trends Biotechnol 2024; 42:61-73. [PMID: 37451948 DOI: 10.1016/j.tibtech.2023.06.010] [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: 04/20/2023] [Revised: 06/23/2023] [Accepted: 06/26/2023] [Indexed: 07/18/2023]
Abstract
Prokaryotic Argonautes (pAgos) are an emerging class of programmable endonucleases that are believed to be more flexible than existing CRISPR-Cas systems and have significant potential for biotechnology. Current applications of pAgos include a myriad of molecular diagnostics and in vitro DNA assembly tools. However, efforts have historically been centered on thermophilic pAgo variants. To enable in vivo biotechnological applications such as gene editing, focus has shifted to pAgos from mesophilic organisms. We discuss what is known of pAgos, how they are being developed for various applications, and strategies to overcome current challenges to in vivo applications in prokaryotes and eukaryotes.
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Affiliation(s)
- Brett A Graver
- Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA
| | - Namrata Chakravarty
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716, USA
| | - Kevin V Solomon
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716, USA.
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4
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Koonin EV, Gootenberg JS, Abudayyeh OO. Discovery of Diverse CRISPR-Cas Systems and Expansion of the Genome Engineering Toolbox. Biochemistry 2023; 62:3465-3487. [PMID: 37192099 PMCID: PMC10734277 DOI: 10.1021/acs.biochem.3c00159] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/23/2023] [Indexed: 05/18/2023]
Abstract
CRISPR systems mediate adaptive immunity in bacteria and archaea through diverse effector mechanisms and have been repurposed for versatile applications in therapeutics and diagnostics thanks to their facile reprogramming with RNA guides. RNA-guided CRISPR-Cas targeting and interference are mediated by effectors that are either components of multisubunit complexes in class 1 systems or multidomain single-effector proteins in class 2. The compact class 2 CRISPR systems have been broadly adopted for multiple applications, especially genome editing, leading to a transformation of the molecular biology and biotechnology toolkit. The diversity of class 2 effector enzymes, initially limited to the Cas9 nuclease, was substantially expanded via computational genome and metagenome mining to include numerous variants of Cas12 and Cas13, providing substrates for the development of versatile, orthogonal molecular tools. Characterization of these diverse CRISPR effectors uncovered many new features, including distinct protospacer adjacent motifs (PAMs) that expand the targeting space, improved editing specificity, RNA rather than DNA targeting, smaller crRNAs, staggered and blunt end cuts, miniature enzymes, promiscuous RNA and DNA cleavage, etc. These unique properties enabled multiple applications, such as harnessing the promiscuous RNase activity of the type VI effector, Cas13, for supersensitive nucleic acid detection. class 1 CRISPR systems have been adopted for genome editing, as well, despite the challenge of expressing and delivering the multiprotein class 1 effectors. The rich diversity of CRISPR enzymes led to rapid maturation of the genome editing toolbox, with capabilities such as gene knockout, base editing, prime editing, gene insertion, DNA imaging, epigenetic modulation, transcriptional modulation, and RNA editing. Combined with rational design and engineering of the effector proteins and associated RNAs, the natural diversity of CRISPR and related bacterial RNA-guided systems provides a vast resource for expanding the repertoire of tools for molecular biology and biotechnology.
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Affiliation(s)
- Eugene V. Koonin
- National
Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States
| | - Jonathan S. Gootenberg
- McGovern
Institute for Brain Research at MIT, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Omar O. Abudayyeh
- McGovern
Institute for Brain Research at MIT, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02139, United States
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5
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Altae-Tran H, Kannan S, Suberski AJ, Mears KS, Demircioglu FE, Moeller L, Kocalar S, Oshiro R, Makarova KS, Macrae RK, Koonin EV, Zhang F. Uncovering the functional diversity of rare CRISPR-Cas systems with deep terascale clustering. Science 2023; 382:eadi1910. [PMID: 37995242 PMCID: PMC10910872 DOI: 10.1126/science.adi1910] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 09/28/2023] [Indexed: 11/25/2023]
Abstract
Microbial systems underpin many biotechnologies, including CRISPR, but the exponential growth of sequence databases makes it difficult to find previously unidentified systems. In this work, we develop the fast locality-sensitive hashing-based clustering (FLSHclust) algorithm, which performs deep clustering on massive datasets in linearithmic time. We incorporated FLSHclust into a CRISPR discovery pipeline and identified 188 previously unreported CRISPR-linked gene modules, revealing many additional biochemical functions coupled to adaptive immunity. We experimentally characterized three HNH nuclease-containing CRISPR systems, including the first type IV system with a specified interference mechanism, and engineered them for genome editing. We also identified and characterized a candidate type VII system, which we show acts on RNA. This work opens new avenues for harnessing CRISPR and for the broader exploration of the vast functional diversity of microbial proteins.
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Affiliation(s)
- Han Altae-Tran
- Howard Hughes Medical Institute; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- McGovern Institute for Brain Research at MIT; Cambridge, MA 02139, USA
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
| | - Soumya Kannan
- Howard Hughes Medical Institute; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- McGovern Institute for Brain Research at MIT; Cambridge, MA 02139, USA
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
| | - Anthony J. Suberski
- Howard Hughes Medical Institute; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- McGovern Institute for Brain Research at MIT; Cambridge, MA 02139, USA
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
| | - Kepler S. Mears
- Howard Hughes Medical Institute; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- McGovern Institute for Brain Research at MIT; Cambridge, MA 02139, USA
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
| | - F. Esra Demircioglu
- Howard Hughes Medical Institute; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- McGovern Institute for Brain Research at MIT; Cambridge, MA 02139, USA
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
| | - Lukas Moeller
- Howard Hughes Medical Institute; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- McGovern Institute for Brain Research at MIT; Cambridge, MA 02139, USA
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
| | - Selin Kocalar
- Howard Hughes Medical Institute; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- McGovern Institute for Brain Research at MIT; Cambridge, MA 02139, USA
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
| | - Rachel Oshiro
- Howard Hughes Medical Institute; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- McGovern Institute for Brain Research at MIT; Cambridge, MA 02139, USA
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
| | - Kira S. Makarova
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD 20894, USA
| | - Rhiannon K. Macrae
- Howard Hughes Medical Institute; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- McGovern Institute for Brain Research at MIT; Cambridge, MA 02139, USA
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
| | - Eugene V. Koonin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD 20894, USA
| | - Feng Zhang
- Howard Hughes Medical Institute; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- McGovern Institute for Brain Research at MIT; Cambridge, MA 02139, USA
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
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6
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Diversity-Generating Retroelements in Prokaryotic Immunity. Int J Mol Sci 2023; 24:ijms24065614. [PMID: 36982690 PMCID: PMC10053308 DOI: 10.3390/ijms24065614] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 03/10/2023] [Accepted: 03/12/2023] [Indexed: 03/17/2023] Open
Abstract
Adaptive immunity systems found in different organisms fall into two major types. Prokaryotes possess CRISPR-Cas systems that recognize former invaders using memorized (captured) pieces of their DNA as pathogen signatures. Mammals possess a vast repertoire of antibodies and T-cell receptor variants generated in advance. In this second type of adaptive immunity, a pathogen presentation to the immune system specifically activates the cells that express matching antibodies or receptors. These cells proliferate to fight the infection and form the immune memory. The principle of preemptive production of diverse defense proteins for future use can hypothetically take place in microbes too. We propose a hypothesis that prokaryotes employ diversity-generating retroelements to prepare defense proteins against yet-unknown invaders. In this study, we test this hypothesis with the methods of bioinformatics and identify several candidate defense systems based on diversity-generating retroelements.
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7
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Abstract
Abstract
Discovery of the CRISPR/Cas system revolutionized biology and biomedicine in the 21st century. Here we discuss the milestones in the development of CRISPR/Cas genome editing technology, from the history of discovery to current developments, including medical applications. Technical and ethical problems associated with the use of CRISPR/Cas for editing human embryonic genomes are also discussed.
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8
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Lu Y, Li Q, Li T. PPA-GCN: A Efficient GCN Framework for Prokaryotic Pathways Assignment. Front Genet 2022; 13:839453. [PMID: 35444686 PMCID: PMC9013948 DOI: 10.3389/fgene.2022.839453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 03/17/2022] [Indexed: 11/17/2022] Open
Abstract
With the rapid development of sequencing technology, completed genomes of microbes have explosively emerged. For a newly sequenced prokaryotic genome, gene functional annotation and metabolism pathway assignment are important foundations for all subsequent research work. However, the assignment rate for gene metabolism pathways is lower than 48% on the whole. It is even lower for newly sequenced prokaryotic genomes, which has become a bottleneck for subsequent research. Thus, the development of a high-precision metabolic pathway assignment framework is urgently needed. Here, we developed PPA-GCN, a prokaryotic pathways assignment framework based on graph convolutional network, to assist functional pathway assignments using KEGG information and genomic characteristics. In the framework, genomic gene synteny information was used to construct a network, and ideas of self-supervised learning were inspired to enhance the framework’s learning ability. Our framework is applicable to the genera of microbe with sufficient whole genome sequences. To evaluate the assignment rate, genomes from three different genera (Flavobacterium (65 genomes) and Pseudomonas (100 genomes), Staphylococcus (500 genomes)) were used. The initial functional pathway assignment rate of the three test genera were 27.7% (Flavobacterium), 49.5% (Pseudomonas) and 30.1% (Staphylococcus). PPA-GCN achieved excellence performance of 84.8% (Flavobacterium), 77.0% (Pseudomonas) and 71.0% (Staphylococcus) for assignment rate. At the same time, PPA-GCN was proved to have strong fault tolerance. The framework provides novel insights into assignment for metabolism pathways and is likely to inform future deep learning applications for interpreting functional annotations and extends to all prokaryotic genera with sufficient genomes.
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Affiliation(s)
- Yuntao Lu
- Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China.,College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Qi Li
- Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
| | - Tao Li
- Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
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9
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Schneider T, Tan Y, Li H, Fisher JS, Zhang D. Photoglobin, a distinct family of non-heme binding globins, defines a potential photosensor in prokaryotic signal transduction systems. Comput Struct Biotechnol J 2022; 20:261-273. [PMID: 35024098 PMCID: PMC8717448 DOI: 10.1016/j.csbj.2021.12.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 12/14/2021] [Accepted: 12/15/2021] [Indexed: 11/17/2022] Open
Abstract
Globins constitute an ancient superfamily of proteins, exhibiting enormous structural and functional diversity, as demonstrated by many heme-binding families and two non-heme binding families that were discovered in bacterial stressosome component RsbR and in light-harvesting phycobiliproteins (phycocyanin) in cyanobacteria and red algae. By comprehensively exploring the globin repertoire using sensitive computational analyses of sequences, structures, and genomes, we present the identification of the third family of non-heme binding globins—the photoglobin. By conducting profile-based comparisons, clustering analyses, and structural modeling, we demonstrate that photoglobin is related to, but distinct from, the phycocyanin family. Photoglobin preserves a potential ligand-binding pocket, whose residue configuration closely resembles that of phycocyanin, indicating that photoglobin potentially binds to a comparable linear tetrapyrrole. By exploring the contextual information provided by the photoglobin’s domain architectures and gene-neighborhoods, we found that photoglobin is frequently associated with the B12-binding light sensor domain and many domains typical of prokaryotic signal transduction systems. Structural modeling using AlphaFold2 demonstrated that photoglobin and B12-binding domains form a structurally conserved hub among different domain architecture contexts. Based on these strong associations, we predict that the coupled photoglobin and B12-binding domains act as a light-sensing regulatory bundle, with each domain sensing different wavelengths of light resulting in switch-like regulation of downstream signaling effectors. Thus, based on the above lines of evidence, we present a distinct non-heme binding globin family and propose that it may define a new type of light sensor, by means of a linear tetrapyrrole, in complex prokaryotic signal transduction systems.
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Affiliation(s)
- Theresa Schneider
- Department of Biology, College of Arts & Sciences, Saint Louis University, Saint Louis, MO 63105, United States
| | - Yongjun Tan
- Department of Biology, College of Arts & Sciences, Saint Louis University, Saint Louis, MO 63105, United States
| | - Huan Li
- Department of Biology, College of Arts & Sciences, Saint Louis University, Saint Louis, MO 63105, United States
| | - Jonathan S Fisher
- Department of Biology, College of Arts & Sciences, Saint Louis University, Saint Louis, MO 63105, United States
| | - Dapeng Zhang
- Department of Biology, College of Arts & Sciences, Saint Louis University, Saint Louis, MO 63105, United States.,Program of Bioinformatics and Computational Biology, College of Arts & Sciences, Saint Louis University, MO 63103, United States
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10
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Rybarski JR, Hu K, Hill AM, Wilke CO, Finkelstein IJ. Metagenomic discovery of CRISPR-associated transposons. Proc Natl Acad Sci U S A 2021; 118:e2112279118. [PMID: 34845024 PMCID: PMC8670466 DOI: 10.1073/pnas.2112279118] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 10/26/2021] [Indexed: 12/26/2022] Open
Abstract
CRISPR-associated Tn7 transposons (CASTs) co-opt cas genes for RNA-guided transposition. CASTs are exceedingly rare in genomic databases; recent surveys have reported Tn7-like transposons that co-opt Type I-F, I-B, and V-K CRISPR effectors. Here, we expand the diversity of reported CAST systems via a bioinformatic search of metagenomic databases. We discover architectures for all known CASTs, including arrangements of the Cascade effectors, target homing modalities, and minimal V-K systems. We also describe families of CASTs that have co-opted the Type I-C and Type IV CRISPR-Cas systems. Our search for non-Tn7 CASTs identifies putative candidates that include a nuclease dead Cas12. These systems shed light on how CRISPR systems have coevolved with transposases and expand the programmable gene-editing toolkit.
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Affiliation(s)
- James R Rybarski
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712
| | - Kuang Hu
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX 78712
| | - Alexis M Hill
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX 78712
| | - Claus O Wilke
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX 78712;
| | - Ilya J Finkelstein
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712;
- Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX 78712
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11
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Foflonker F, Blaby-Haas CE. Colocality to Cofunctionality: Eukaryotic Gene Neighborhoods as a Resource for Function Discovery. Mol Biol Evol 2021; 38:650-662. [PMID: 32886760 PMCID: PMC7826186 DOI: 10.1093/molbev/msaa221] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Diverging from the classic paradigm of random gene order in eukaryotes, gene proximity can be leveraged to systematically identify functionally related gene neighborhoods in eukaryotes, utilizing techniques pioneered in bacteria. Current methods of identifying gene neighborhoods typically rely on sequence similarity to characterized gene products. However, this approach is not robust for nonmodel organisms like algae, which are evolutionarily distant from well-characterized model organisms. Here, we utilize a comparative genomic approach to identify evolutionarily conserved proximal orthologous gene pairs conserved across at least two taxonomic classes of green algae. A total of 317 gene neighborhoods were identified. In some cases, gene proximity appears to have been conserved since before the streptophyte–chlorophyte split, 1,000 Ma. Using functional inferences derived from reconstructed evolutionary relationships, we identified several novel functional clusters. A putative mycosporine-like amino acid, “sunscreen,” neighborhood contains genes similar to either vertebrate or cyanobacterial pathways, suggesting a novel mosaic biosynthetic pathway in green algae. One of two putative arsenic-detoxification neighborhoods includes an organoarsenical transporter (ArsJ), a glyceraldehyde 3-phosphate dehydrogenase-like gene, homologs of which are involved in arsenic detoxification in bacteria, and a novel algal-specific phosphoglycerate kinase-like gene. Mutants of the ArsJ-like transporter and phosphoglycerate kinase-like genes in Chlamydomonas reinhardtii were found to be sensitive to arsenate, providing experimental support for the role of these identified neighbors in resistance to arsenate. Potential evolutionary origins of neighborhoods are discussed, and updated annotations for formerly poorly annotated genes are presented, highlighting the potential of this strategy for functional annotation.
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12
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Isaev AB, Musharova OS, Severinov KV. Microbial Arsenal of Antiviral Defenses - Part I. BIOCHEMISTRY (MOSCOW) 2021; 86:319-337. [PMID: 33838632 DOI: 10.1134/s0006297921030081] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Bacteriophages or phages are viruses that infect bacterial cells (for the scope of this review we will also consider viruses that infect Archaea). Constant threat of phage infection is a major force that shapes evolution of the microbial genomes. To withstand infection, bacteria had evolved numerous strategies to avoid recognition by phages or to directly interfere with phage propagation inside the cell. Classical molecular biology and genetic engineering have been deeply intertwined with the study of phages and host defenses. Nowadays, owing to the rise of phage therapy, broad application of CRISPR-Cas technologies, and development of bioinformatics approaches that facilitate discovery of new systems, phage biology experiences a revival. This review describes variety of strategies employed by microbes to counter phage infection, with a focus on novel systems discovered in recent years. First chapter covers defense associated with cell surface, role of small molecules, and innate immunity systems relying on DNA modification.
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Affiliation(s)
- Artem B Isaev
- Skolkovo Institute of Science and Technology, Moscow, 143028, Russia.
| | - Olga S Musharova
- Skolkovo Institute of Science and Technology, Moscow, 143028, Russia. .,Institute of Molecular Genetics, Moscow, 119334, Russia
| | - Konstantin V Severinov
- Skolkovo Institute of Science and Technology, Moscow, 143028, Russia. .,Waksman Institute of Microbiology, Piscataway, NJ 08854, USA
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13
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Mckay A, Burgio G. Harnessing CRISPR-Cas system diversity for gene editing technologies. J Biomed Res 2021; 35:91-106. [PMID: 33797415 PMCID: PMC8038530 DOI: 10.7555/jbr.35.20200184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
The discovery and utilization of RNA-guided surveillance complexes, such as CRISPR-Cas9, for sequence-specific DNA or RNA cleavage, has revolutionised the process of gene modification or knockdown. To optimise the use of this technology, an exploratory race has ensued to discover or develop new RNA-guided endonucleases with the most flexible sequence targeting requirements, coupled with high cleavage efficacy and specificity. Here we review the constraints of existing gene editing and assess the merits of exploiting the diversity of CRISPR-Cas effectors as a methodology for surmounting these limitations.
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Affiliation(s)
- Alexander Mckay
- Department of Immunology and Infectious Diseases, John Curtin School of Medical Research, Australian National University, Canberra, ACT 2601, Australia
| | - Gaetan Burgio
- Department of Immunology and Infectious Diseases, John Curtin School of Medical Research, Australian National University, Canberra, ACT 2601, Australia
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14
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Shmakov SA, Utkina I, Wolf YI, Makarova KS, Severinov KV, Koonin EV. CRISPR Arrays Away from cas Genes. CRISPR J 2020; 3:535-549. [PMID: 33346707 PMCID: PMC7757702 DOI: 10.1089/crispr.2020.0062] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
CRISPR-Cas systems typically consist of a CRISPR array and cas genes that are organized in one or more operons. However, a substantial fraction of CRISPR arrays are not adjacent to cas genes. Definitive identification of such isolated CRISPR arrays runs into the problem of false-positives, with unrelated types of repetitive sequences mimicking CRISPR. We developed a computational pipeline to eliminate false CRISPR predictions and found that up to 25% of the CRISPR arrays in complete bacterial and archaeal genomes are located away from cas genes. Most of the repeats in these isolated arrays are identical to repeats in cas-adjacent CRISPR arrays in the same or closely related genomes, indicating an evolutionary relationship between isolated arrays and arrays in typical CRISPR-cas loci. The spacers in isolated CRISPR arrays show nearly as many matches to viral genomes as spacers from complete CRISPR-cas loci, suggesting that the isolated arrays were either functionally active recently or continue to function. Reconstruction of evolutionary events in closely related bacterial genomes suggests three routes of evolution of isolated CRISPR arrays: (1) loss of cas genes in a CRISPR-cas locus, (2) de novo generation of arrays from off-target spacer integration into sequences resembling the corresponding repeats, and (3) transfer by mobile genetic elements. Both combination of de novo emerging arrays with cas genes and regain of cas genes by isolated arrays via recombination likely contribute to functional diversification in CRISPR-Cas evolution.
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Affiliation(s)
- Sergey A. Shmakov
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA; Rutgers, State University of New Jersey, Piscataway, New Jersey, USA
| | - Irina Utkina
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA; Rutgers, State University of New Jersey, Piscataway, New Jersey, USA
- Skolkovo Institute of Science and Technology, Skolkovo, Russia; Rutgers, State University of New Jersey, Piscataway, New Jersey, USA
- The Hospital for Sick Children, University of Toronto, Toronto, Canada; Rutgers, State University of New Jersey, Piscataway, New Jersey, USA
| | - Yuri I. Wolf
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA; Rutgers, State University of New Jersey, Piscataway, New Jersey, USA
| | - Kira S. Makarova
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA; Rutgers, State University of New Jersey, Piscataway, New Jersey, USA
| | - Konstantin V. Severinov
- Institute of Molecular Genetics, Russian Academy of Sciences, Moscow, Russia; and Rutgers, State University of New Jersey, Piscataway, New Jersey, USA
- Waksman Institute of Microbiology, Rutgers, State University of New Jersey, Piscataway, New Jersey, USA
| | - Eugene V. Koonin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA; Rutgers, State University of New Jersey, Piscataway, New Jersey, USA
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15
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Westra ER, Levin BR. It is unclear how important CRISPR-Cas systems are for protecting natural populations of bacteria against infections by mobile genetic elements. Proc Natl Acad Sci U S A 2020; 117:27777-27785. [PMID: 33122438 PMCID: PMC7668106 DOI: 10.1073/pnas.1915966117] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Articles on CRISPR commonly open with some variant of the phrase "these short palindromic repeats and their associated endonucleases (Cas) are an adaptive immune system that exists to protect bacteria and archaea from viruses and infections with other mobile genetic elements." There is an abundance of genomic data consistent with the hypothesis that CRISPR plays this role in natural populations of bacteria and archaea, and experimental demonstrations with a few species of bacteria and their phage and plasmids show that CRISPR-Cas systems can play this role in vitro. Not at all clear are the ubiquity, magnitude, and nature of the contribution of CRISPR-Cas systems to the ecology and evolution of natural populations of microbes and the strength of selection mediated by different types of phage and plasmids to the evolution and maintenance of CRISPR-Cas systems. In this perspective, with the aid of heuristic mathematical-computer simulation models, we explore the a priori conditions under which exposure to lytic and temperate phage and conjugative plasmids will select for and maintain CRISPR-Cas systems in populations of bacteria and archaea. We review the existing literature addressing these ecological and evolutionary questions and highlight the experimental and other evidence needed to fully understand the conditions responsible for the evolution and maintenance of CRISPR-Cas systems and the contribution of these systems to the ecology and evolution of bacteria, archaea, and the mobile genetic elements that infect them.
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Affiliation(s)
- Edze R Westra
- Environment and Sustainability Institute, Biosciences, University of Exeter, Penryn, TR10 9FE Cornwall, United Kingdom;
| | - Bruce R Levin
- Department of Biology, Emory University, Atlanta, GA 30307
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16
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Gao L, Altae-Tran H, Böhning F, Makarova KS, Segel M, Schmid-Burgk JL, Koob J, Wolf YI, Koonin EV, Zhang F. Diverse enzymatic activities mediate antiviral immunity in prokaryotes. Science 2020; 369:1077-1084. [PMID: 32855333 DOI: 10.1126/science.aba0372] [Citation(s) in RCA: 241] [Impact Index Per Article: 60.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 07/06/2020] [Indexed: 12/18/2022]
Abstract
Bacteria and archaea are frequently attacked by viruses and other mobile genetic elements and rely on dedicated antiviral defense systems, such as restriction endonucleases and CRISPR, to survive. The enormous diversity of viruses suggests that more types of defense systems exist than are currently known. By systematic defense gene prediction and heterologous reconstitution, here we discover 29 widespread antiviral gene cassettes, collectively present in 32% of all sequenced bacterial and archaeal genomes, that mediate protection against specific bacteriophages. These systems incorporate enzymatic activities not previously implicated in antiviral defense, including RNA editing and retron satellite DNA synthesis. In addition, we computationally predict a diverse set of other putative defense genes that remain to be characterized. These results highlight an immense array of molecular functions that microbes use against viruses.
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Affiliation(s)
- Linyi Gao
- Howard Hughes Medical Institute, Cambridge, MA 02139, USA.,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Han Altae-Tran
- Howard Hughes Medical Institute, Cambridge, MA 02139, USA.,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Francisca Böhning
- Howard Hughes Medical Institute, Cambridge, MA 02139, USA.,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kira S Makarova
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Michael Segel
- Howard Hughes Medical Institute, Cambridge, MA 02139, USA.,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jonathan L Schmid-Burgk
- Howard Hughes Medical Institute, Cambridge, MA 02139, USA.,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jeremy Koob
- Howard Hughes Medical Institute, Cambridge, MA 02139, USA.,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yuri I Wolf
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Eugene V Koonin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Feng Zhang
- Howard Hughes Medical Institute, Cambridge, MA 02139, USA. .,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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17
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Makarova KS, Wolf YI, Iranzo J, Shmakov SA, Alkhnbashi OS, Brouns SJJ, Charpentier E, Cheng D, Haft DH, Horvath P, Moineau S, Mojica FJM, Scott D, Shah SA, Siksnys V, Terns MP, Venclovas Č, White MF, Yakunin AF, Yan W, Zhang F, Garrett RA, Backofen R, van der Oost J, Barrangou R, Koonin EV. Evolutionary classification of CRISPR–Cas systems: a burst of class 2 and derived variants. Nat Rev Microbiol 2019; 18:67-83. [DOI: 10.1038/s41579-019-0299-x] [Citation(s) in RCA: 797] [Impact Index Per Article: 159.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/04/2019] [Indexed: 12/16/2022]
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