Literature DB >> 29784811

Systematic prediction of genes functionally linked to CRISPR-Cas systems by gene neighborhood analysis.

Sergey A Shmakov1,2, Kira S Makarova2, Yuri I Wolf2, Konstantin V Severinov1,3,4, Eugene V Koonin5.   

Abstract

The CRISPR-Cas systems of bacterial and archaeal adaptive immunity consist of direct repeat arrays separated by unique spacers and multiple CRISPR-associated (cas) genes encoding proteins that mediate all stages of the CRISPR response. In addition to the relatively small set of core cas genes that are typically present in all CRISPR-Cas systems of a given (sub)type and are essential for the defense function, numerous genes occur in CRISPR-cas loci only sporadically. Some of these have been shown to perform various ancillary roles in CRISPR response, but the functional relevance of most remains unknown. We developed a computational strategy for systematically detecting genes that are likely to be functionally linked to CRISPR-Cas. The approach is based on a "CRISPRicity" metric that measures the strength of CRISPR association for all protein-coding genes from sequenced bacterial and archaeal genomes. Uncharacterized genes with CRISPRicity values comparable to those of cas genes are considered candidate CRISPR-linked genes. We describe additional criteria to predict functionally relevance for genes in the candidate set and identify 79 genes as strong candidates for functional association with CRISPR-Cas systems. A substantial majority of these CRISPR-linked genes reside in type III CRISPR-cas loci, which implies exceptional functional versatility of type III systems. Numerous candidate CRISPR-linked genes encode integral membrane proteins suggestive of tight membrane association of CRISPR-Cas systems, whereas many others encode proteins implicated in various signal transduction pathways. These predictions provide ample material for improving annotation of CRISPR-cas loci and experimental characterization of previously unsuspected aspects of CRISPR-Cas system functionality.

Entities:  

Keywords:  CRISPR-Cas; computational genomics; gene neighborhoods; membrane proteins; signaling

Mesh:

Substances:

Year:  2018        PMID: 29784811      PMCID: PMC6003329          DOI: 10.1073/pnas.1803440115

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  104 in total

1.  Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes.

Authors:  A Krogh; B Larsson; G von Heijne; E L Sonnhammer
Journal:  J Mol Biol       Date:  2001-01-19       Impact factor: 5.469

2.  Genome alignment, evolution of prokaryotic genome organization, and prediction of gene function using genomic context.

Authors:  Y I Wolf; I B Rogozin; A S Kondrashov; E V Koonin
Journal:  Genome Res       Date:  2001-03       Impact factor: 9.043

3.  A DNA repair system specific for thermophilic Archaea and bacteria predicted by genomic context analysis.

Authors:  Kira S Makarova; L Aravind; Nick V Grishin; Igor B Rogozin; Eugene V Koonin
Journal:  Nucleic Acids Res       Date:  2002-01-15       Impact factor: 16.971

Review 4.  CRISPR-Cas9 Structures and Mechanisms.

Authors:  Fuguo Jiang; Jennifer A Doudna
Journal:  Annu Rev Biophys       Date:  2017-03-30       Impact factor: 12.981

5.  Structure of an RNA silencing complex of the CRISPR-Cas immune system.

Authors:  Michael Spilman; Alexis Cocozaki; Caryn Hale; Yaming Shao; Nancy Ramia; Rebeca Terns; Michael Terns; Hong Li; Scott Stagg
Journal:  Mol Cell       Date:  2013-10-10       Impact factor: 17.970

6.  Cryo-EM Structures of the Magnesium Channel CorA Reveal Symmetry Break upon Gating.

Authors:  Doreen Matthies; Olivier Dalmas; Mario J Borgnia; Pawel K Dominik; Alan Merk; Prashant Rao; Bharat G Reddy; Shahidul Islam; Alberto Bartesaghi; Eduardo Perozo; Sriram Subramaniam
Journal:  Cell       Date:  2016-02-11       Impact factor: 41.582

7.  Diversity and evolution of class 2 CRISPR-Cas systems.

Authors:  Sergey Shmakov; Aaron Smargon; David Scott; David Cox; Neena Pyzocha; Winston Yan; Omar O Abudayyeh; Jonathan S Gootenberg; Kira S Makarova; Yuri I Wolf; Konstantin Severinov; Feng Zhang; Eugene V Koonin
Journal:  Nat Rev Microbiol       Date:  2017-01-23       Impact factor: 60.633

8.  Discovery and Functional Characterization of Diverse Class 2 CRISPR-Cas Systems.

Authors:  Sergey Shmakov; Omar O Abudayyeh; Kira S Makarova; Yuri I Wolf; Jonathan S Gootenberg; Ekaterina Semenova; Leonid Minakhin; Julia Joung; Silvana Konermann; Konstantin Severinov; Feng Zhang; Eugene V Koonin
Journal:  Mol Cell       Date:  2015-10-22       Impact factor: 17.970

9.  CRISPR adaptive immune systems of Archaea.

Authors:  Gisle Vestergaard; Roger A Garrett; Shiraz A Shah
Journal:  RNA Biol       Date:  2014-02-07       Impact factor: 4.652

10.  Comparative genomic analyses reveal a vast, novel network of nucleotide-centric systems in biological conflicts, immunity and signaling.

Authors:  A Maxwell Burroughs; Dapeng Zhang; Daniel E Schäffer; Lakshminarayan M Iyer; L Aravind
Journal:  Nucleic Acids Res       Date:  2015-11-20       Impact factor: 16.971

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  50 in total

1.  Multiple origins of reverse transcriptases linked to CRISPR-Cas systems.

Authors:  Nicolás Toro; Francisco Martínez-Abarca; Mario Rodríguez Mestre; Alejandro González-Delgado
Journal:  RNA Biol       Date:  2019-07-11       Impact factor: 4.652

2.  Large-Scale Analyses of Human Microbiomes Reveal Thousands of Small, Novel Genes.

Authors:  Hila Sberro; Brayon J Fremin; Soumaya Zlitni; Fredrik Edfors; Nicholas Greenfield; Michael P Snyder; Georgios A Pavlopoulos; Nikos C Kyrpides; Ami S Bhatt
Journal:  Cell       Date:  2019-08-08       Impact factor: 41.582

3.  The ecology and evolution of microbial CRISPR-Cas adaptive immune systems.

Authors:  Edze R Westra; Stineke van Houte; Sylvain Gandon; Rachel Whitaker
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-05-13       Impact factor: 6.237

4.  CRISPR Arrays Away from cas Genes.

Authors:  Sergey A Shmakov; Irina Utkina; Yuri I Wolf; Kira S Makarova; Konstantin V Severinov; Eugene V Koonin
Journal:  CRISPR J       Date:  2020-12

Review 5.  Chemistry of Class 1 CRISPR-Cas effectors: Binding, editing, and regulation.

Authors:  Tina Y Liu; Jennifer A Doudna
Journal:  J Biol Chem       Date:  2020-08-14       Impact factor: 5.157

Review 6.  Three New Cs for CRISPR: Collateral, Communicate, Cooperate.

Authors:  Andrew Varble; Luciano A Marraffini
Journal:  Trends Genet       Date:  2019-04-27       Impact factor: 11.639

7.  CRISPRidentify: identification of CRISPR arrays using machine learning approach.

Authors:  Alexander Mitrofanov; Omer S Alkhnbashi; Sergey A Shmakov; Kira S Makarova; Eugene V Koonin; Rolf Backofen
Journal:  Nucleic Acids Res       Date:  2021-02-26       Impact factor: 16.971

8.  Evolutionary and functional classification of the CARF domain superfamily, key sensors in prokaryotic antivirus defense.

Authors:  Kira S Makarova; Albertas Timinskas; Yuri I Wolf; Ayal B Gussow; Virginijus Siksnys; Česlovas Venclovas; Eugene V Koonin
Journal:  Nucleic Acids Res       Date:  2020-09-18       Impact factor: 16.971

9.  Diverse enzymatic activities mediate antiviral immunity in prokaryotes.

Authors:  Linyi Gao; Han Altae-Tran; Francisca Böhning; Kira S Makarova; Michael Segel; Jonathan L Schmid-Burgk; Jeremy Koob; Yuri I Wolf; Eugene V Koonin; Feng Zhang
Journal:  Science       Date:  2020-08-28       Impact factor: 47.728

10.  Predicted highly derived class 1 CRISPR-Cas system in Haloarchaea containing diverged Cas5 and Cas7 homologs but no CRISPR array.

Authors:  Kira S Makarova; Svetlana Karamycheva; Shiraz A Shah; Gisle Vestergaard; Roger A Garrett; Eugene V Koonin
Journal:  FEMS Microbiol Lett       Date:  2019-04-01       Impact factor: 2.742

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