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Prakash A, Kumar M. Characterizing the transcripts of Leptospira CRISPR I-B array and its processing with endoribonuclease LinCas6. Int J Biol Macromol 2021; 182:785-795. [PMID: 33862076 DOI: 10.1016/j.ijbiomac.2021.04.066] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 04/08/2021] [Accepted: 04/10/2021] [Indexed: 12/26/2022]
Abstract
In Leptospira interrogans serovar Copenhageni, the CRISPR-Cas I-B locus possesses a CRISPR array between the two independent cas-operons. Using the reverse transcription-PCR and the in vitro endoribonuclease assay with Cas6 of Leptospira (LinCas6), we account that the CRISPR is transcriptionally active and is conventionally processed. The LinCas6 specifically excises at one site within the synthetic cognate repeat RNA or the repeats of precursor-CRISPR RNA (pre-crRNA) in the sense direction. In contrast, the antisense repeat RNA is cleaved at multiple sites. LinCas6 functions as a single turnover endoribonuclease on its repeat RNA substrate, where substitution of one of predicted active site residues (His38) resulted in reduced activity. This study highlights the comprehensive understanding of the Leptospira CRISPR array transcription and its processing by LinCas6 that is central to RNA-mediated CRISPR-Cas I-B adaptive immunity.
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Affiliation(s)
- Aman Prakash
- Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India
| | - Manish Kumar
- Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India.
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2
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Mitrofanov A, Alkhnbashi OS, Shmakov SA, Makarova K, Koonin E, Backofen R. CRISPRidentify: identification of CRISPR arrays using machine learning approach. Nucleic Acids Res 2021; 49:e20. [PMID: 33290505 PMCID: PMC7913763 DOI: 10.1093/nar/gkaa1158] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 11/09/2020] [Accepted: 11/11/2020] [Indexed: 02/02/2023] Open
Abstract
CRISPR–Cas are adaptive immune systems that degrade foreign genetic elements in archaea and bacteria. In carrying out their immune functions, CRISPR–Cas systems heavily rely on RNA components. These CRISPR (cr) RNAs are repeat-spacer units that are produced by processing of pre-crRNA, the transcript of CRISPR arrays, and guide Cas protein(s) to the cognate invading nucleic acids, enabling their destruction. Several bioinformatics tools have been developed to detect CRISPR arrays based solely on DNA sequences, but all these tools employ the same strategy of looking for repetitive patterns, which might correspond to CRISPR array repeats. The identified patterns are evaluated using a fixed, built-in scoring function, and arrays exceeding a cut-off value are reported. Here, we instead introduce a data-driven approach that uses machine learning to detect and differentiate true CRISPR arrays from false ones based on several features. Our CRISPR detection tool, CRISPRidentify, performs three steps: detection, feature extraction and classification based on manually curated sets of positive and negative examples of CRISPR arrays. The identified CRISPR arrays are then reported to the user accompanied by detailed annotation. We demonstrate that our approach identifies not only previously detected CRISPR arrays, but also CRISPR array candidates not detected by other tools. Compared to other methods, our tool has a drastically reduced false positive rate. In contrast to the existing tools, our approach not only provides the user with the basic statistics on the identified CRISPR arrays but also produces a certainty score as a practical measure of the likelihood that a given genomic region is a CRISPR array.
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Affiliation(s)
| | | | - Sergey A Shmakov
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA
| | - Kira S Makarova
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA
| | - Eugene V Koonin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA
| | - Rolf Backofen
- To whom correspondence should be addressed. Tel: +49 761/203 7461; Fax: +49 761/203 7462;
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The CARF Protein MM_0565 Affects Transcription of the Casposon-Encoded cas1-solo Gene in Methanosarcina mazei Gö1. Biomolecules 2020; 10:biom10081161. [PMID: 32784796 PMCID: PMC7465815 DOI: 10.3390/biom10081161] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 08/04/2020] [Accepted: 08/04/2020] [Indexed: 12/25/2022] Open
Abstract
Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) loci are found in bacterial and archaeal genomes where they provide the molecular machinery for acquisition of immunity against foreign DNA. In addition to the cas genes fundamentally required for CRISPR activity, a second class of genes is associated with the CRISPR loci, of which many have no reported function in CRISPR-mediated immunity. Here, we characterize MM_0565 associated to the type I-B CRISPR-locus of Methanosarcina mazei Gö1. We show that purified MM_0565 composed of a CRISPR-Cas Associated Rossmann Fold (CARF) and a winged helix-turn-helix domain forms a dimer in solution; in vivo, the dimeric MM_0565 is strongly stabilized under high salt stress. While direct effects on CRISPR-Cas transcription were not detected by genetic approaches, specific binding of MM_0565 to the leader region of both CRISPR-Cas systems was observed by microscale thermophoresis and electromobility shift assays. Moreover, overexpression of MM_0565 strongly induced transcription of the cas1-solo gene located in the recently reported casposon, the gene product of which shows high similarity to classical Cas1 proteins. Based on our findings, and taking the absence of the expressed CRISPR locus-encoded Cas1 protein into account, we hypothesize that MM_0565 might modulate the activity of the CRISPR systems on different levels.
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Reimann V, Ziemann M, Li H, Zhu T, Behler J, Lu X, Hess WR. Specificities and functional coordination between the two Cas6 maturation endonucleases in Anabaena sp. PCC 7120 assign orphan CRISPR arrays to three groups. RNA Biol 2020; 17:1442-1453. [PMID: 32453626 DOI: 10.1080/15476286.2020.1774197] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Many bacteria and archaea possess an RNA-guided adaptive and inheritable immune system that consists of clustered regularly interspaced short palindromic repeats (CRISPRs) and CRISPR-associated (Cas) proteins. In most CRISPR-Cas systems, the maturation of CRISPR-derived small RNAs (crRNAs) is essential for functionality. Cas6 endonucleases function as the most frequent CRISPR RNA maturation enzymes. In the cyanobacterium Anabaena sp. PCC 7120, ten CRISPR loci are present, but only two cas gene cassettes plus a Tn7-associated eleventh array. In this study, we deleted the two cas6 genes alr1482 (Type III-D) or alr1566 (Type I-D) and tested the specificities of the two corresponding enzymes in the resulting mutant strains, as recombinant proteins and in a cell-free transcription-translation system. The results assign the direct repeats (DRs) to three different groups. While Alr1566 is specific for one group, Alr1482 has a higher preference for the DRs of the second group but can also cleave those of the first group. We found that this cross-recognition limits crRNA accumulation for the Type I-D system in vivo. We also show that the DR of the cas gene-free CRISPR array of cyanophage N-1 is processed by these enzymes, suggesting that it is fully competent in association with host-encoded Cas proteins. The data support the functionality of CRISPR arrays that frequently appear fragmented to multiple genomic loci in multicellular cyanobacteria and disfavour other possibilities, such as the nonfunctionality of these orphan repeat-spacer arrays. Our results show the functional coordination of Cas6 endonucleases with both neighbouring and remote repeat-spacer arrays in the CRISPR-Cas system of cyanobacteria.
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Affiliation(s)
- Viktoria Reimann
- Faculty of Biology, Institute of Biology III, University of Freiburg , Germany
| | - Marcus Ziemann
- Faculty of Biology, Institute of Biology III, University of Freiburg , Germany
| | - Hui Li
- Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT), Chinese Academy of Sciences , Qingdao, China.,College of Life Sciences, University of Chinese Academy of Sciences , Beijing, China
| | - Tao Zhu
- Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT), Chinese Academy of Sciences , Qingdao, China
| | - Juliane Behler
- Faculty of Biology, Institute of Biology III, University of Freiburg , Germany
| | - Xuefeng Lu
- Key Laboratory of Biofuels, Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT), Chinese Academy of Sciences , Qingdao, China
| | - Wolfgang R Hess
- Faculty of Biology, Institute of Biology III, University of Freiburg , Germany
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Zheng Y, Li J, Wang B, Han J, Hao Y, Wang S, Ma X, Yang S, Ma L, Yi L, Peng W. Endogenous Type I CRISPR-Cas: From Foreign DNA Defense to Prokaryotic Engineering. Front Bioeng Biotechnol 2020; 8:62. [PMID: 32195227 PMCID: PMC7064716 DOI: 10.3389/fbioe.2020.00062] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 01/24/2020] [Indexed: 12/18/2022] Open
Abstract
Establishment of production platforms through prokaryotic engineering in microbial organisms would be one of the most efficient means for chemicals, protein, and biofuels production. Despite the fact that CRISPR (clustered regularly interspaced short palindromic repeats)–based technologies have readily emerged as powerful and versatile tools for genetic manipulations, their applications are generally limited in prokaryotes, possibly owing to the large size and severe cytotoxicity of the heterogeneous Cas (CRISPR-associated) effector. Nevertheless, the rich natural occurrence of CRISPR-Cas systems in many bacteria and most archaea holds great potential for endogenous CRISPR-based prokaryotic engineering. The endogenous CRISPR-Cas systems, with type I systems that constitute the most abundant and diverse group, would be repurposed as genetic manipulation tools once they are identified and characterized as functional in their native hosts. This article reviews the major progress made in understanding the mechanisms of invading DNA immunity by type I CRISPR-Cas and summarizes the practical applications of endogenous type I CRISPR-based toolkits for prokaryotic engineering.
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Affiliation(s)
- Yanli Zheng
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
| | - Jie Li
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
| | - Baiyang Wang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
| | - Jiamei Han
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
| | - Yile Hao
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
| | - Shengchen Wang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
| | - Xiangdong Ma
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
| | - Shihui Yang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
| | - Lixin Ma
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
| | - Li Yi
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
| | - Wenfang Peng
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, China
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Burmistrz M, Krakowski K, Krawczyk-Balska A. RNA-Targeting CRISPR-Cas Systems and Their Applications. Int J Mol Sci 2020; 21:ijms21031122. [PMID: 32046217 PMCID: PMC7036953 DOI: 10.3390/ijms21031122] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 01/29/2020] [Accepted: 02/04/2020] [Indexed: 12/16/2022] Open
Abstract
Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR-associated (Cas) systems have revolutionized modern molecular biology. Numerous types of these systems have been discovered to date. Many CRISPR-Cas systems have been used as a backbone for the development of potent research tools, with Cas9 being the most widespread. While most of the utilized systems are DNA-targeting, recently more and more attention is being gained by those that target RNA. Their ability to specifically recognize a given RNA sequence in an easily programmable way makes them ideal candidates for developing new research tools. In this review we summarize current knowledge on CRISPR-Cas systems which have been shown to target RNA molecules, that is type III (Csm/Cmr), type VI (Cas13), and type II (Cas9). We also present a list of available technologies based on these systems.
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Alkhnbashi OS, Meier T, Mitrofanov A, Backofen R, Voß B. CRISPR-Cas bioinformatics. Methods 2020; 172:3-11. [PMID: 31326596 DOI: 10.1016/j.ymeth.2019.07.013] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 06/19/2019] [Accepted: 07/15/2019] [Indexed: 02/07/2023] Open
Abstract
Clustered regularly interspaced short palindromic repeats (CRISPR) and their associated proteins (Cas) are essential genetic elements in many archaeal and bacterial genomes, playing a key role in a prokaryote adaptive immune system against invasive foreign elements. In recent years, the CRISPR-Cas system has also been engineered to facilitate target gene editing in eukaryotic genomes. Bioinformatics played an essential role in the detection and analysis of CRISPR systems and here we review the bioinformatics-based efforts that pushed the field of CRISPR-Cas research further. We discuss the bioinformatics tools that have been published over the last few years and, finally, present the most popular tools for the design of CRISPR-Cas9 guides.
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Affiliation(s)
| | - Tobias Meier
- Computational Biology, Institute of Biochemical Engineering, University of Stuttgart, Stuttgart, Germany.
| | | | - Rolf Backofen
- Chair of Bioinformatics, University of Freiburg, Freiburg, Germany; Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Germany.
| | - Björn Voß
- Computational Biology, Institute of Biochemical Engineering, University of Stuttgart, Stuttgart, Germany.
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Charpentier E, Elsholz A, Marchfelder A. CRISPR-Cas: more than ten years and still full of mysteries. RNA Biol 2019; 16:377-379. [PMID: 31009325 PMCID: PMC6546415 DOI: 10.1080/15476286.2019.1591659] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Affiliation(s)
| | - Alexander Elsholz
- Max Planck Unit for the Science of Pathogens, Charitéplatz 1, Berlin, Germany
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