Type IV CRISPR-Cas are a distinct variety of highly derived CRISPR-Cas systems that appear to have evolved from type III systems through the loss of the target-cleaving nuclease and partial deterioration of the large subunit of the effector complex. All known type IV CRISPR-Cas systems are encoded on plasmids, integrative and conjugative elements (ICEs), or prophages, and are thought to contribute to competition between these elements, although the mechanistic details of their function remain unknown. There is a clear parallel between the compositions and likely origin of type IV and type I systems recruited by Tn7-like transposons and mediating RNA-guided transposition. We investigated the diversity and evolutionary relationships of type IV systems, with a focus on those in Acidithiobacillia, where this variety of CRISPR is particularly abundant and always found on ICEs. Our analysis revealed remarkable evolutionary plasticity of type IV CRISPR-Cas systems, with adaptation and ancillary genes originating from different ancestral CRISPR-Cas varieties, and extensive gene shuffling within the type IV loci. The adaptation module and the CRISPR array apparently were lost in the type IV ancestor but were subsequently recaptured by type IV systems on several independent occasions. We demonstrate a high level of heterogeneity among the repeats with type IV CRISPR arrays, which far exceed the heterogeneity of any other known CRISPR repeats and suggest a unique adaptation mechanism. The spacers in the type IV arrays, for which protospacers could be identified, match plasmid genes, in particular those encoding the conjugation apparatus components. Both the biochemical mechanism of type IV CRISPR-Cas function and their role in the competition among mobile genetic elements remain to be investigated.
Get full access to this article
View all access options for this article.
References
1.
MakarovaKS, WolfYI, IranzoJ, et al.Evolutionary classification of CRISPR-Cas systems: a burst of class 2 and derived variants. Nat Rev Microbiol, 2020; 18:67–83. DOI: 10.1038/s41579-019-0299-x.
2.
MakarovaKS, HaftDH, BarrangouR, et al.Evolution and classification of the CRISPR-Cas systems. Nat Rev Microbiol, 2011; 9:467–477. DOI: 10.1038/nrmicro2577.
3.
BustamanteP, CovarrubiasPC, LevicanG, et al.ICE Afe 1, an actively excising genetic element from the biomining bacterium Acidithiobacillus ferrooxidans. J Mol Microbiol Biotechnol, 2012; 22:399–407. DOI: 10.1159/000346669.
ValdesJ, PedrosoI, QuatriniR, et al.Acidithiobacillus ferrooxidans metabolism: from genome sequence to industrial applications. BMC Genomics, 2008; 9:597. DOI: 10.1186/1471-2164-9-597.
6.
Pinilla-RedondoR, Mayo-MunozD, RusselJ, et al.Type IV CRISPR-Cas systems are highly diverse and involved in competition between plasmids. Nucleic Acids Res, 2020; 48:2000–2012. DOI: 10.1093/nar/gkz1197.
7.
OzcanA, PauschP, LindenA, et al.Type IV CRISPR RNA processing and effector complex formation in Aromatoleum aromaticum. Nat Microbiol, 2019; 4:89–96. DOI: 10.1038/s41564-018-0274-8.
8.
ZhouY, BravoJPK, TaylorHN, et al.Structure of a type IV CRISPR-Cas ribonucleoprotein complex. iScience, 2021; 24:102201.
9.
MakarovaKS, AravindL, WolfYI, et al.Unification of Cas protein families and a simple scenario for the origin and evolution of CRISPR-Cas systems. Biol Direct, 2011; 6:38. DOI: 10.1186/1745-6150-6-38.
10.
ShmakovSA, MakarovaKS, WolfYI, et al.Systematic prediction of genes functionally linked to CRISPR-Cas systems by gene neighborhood analysis. Proc Natl Acad Sci U S A, 2018; 115:E5307–E5316. DOI: 10.1073/pnas.1803440115.
11.
FaureG, ShmakovSA, YanWX, et al.CRISPR-Cas in mobile genetic elements: counter-defence and beyond. Nat Rev Microbiol, 2019; 17:513–525. DOI: 10.1038/s41579-019-0204-7.
12.
NewireE, AydinA, JumaS, et al.Identification of a type IV-A CRISPR-Cas system located exclusively on IncHI1B/IncFIB plasmids in Enterobacteriaceae. Front Microbiol, 2020; 11:1937. DOI: 10.3389/fmicb.2020.01937.
13.
KamruzzamanM, IredellJR. CRISPR-Cas system in antibiotic resistance plasmids in Klebsiella pneumoniae. Front Microbiol, 2019; 10:2934. DOI: 10.3389/fmicb.2019.02934.
14.
TaylorHN, WarnerEE, ArmbrustMJ, et al.Structural basis of Type IV CRISPR RNA biogenesis by a Cas6 endoribonuclease. RNA Biol, 2019; 16:1438–1447. DOI: 10.1080/15476286.2019.1634965.
15.
CrowleyVM, CatchingA, TaylorHN, et al.A type IV-A CRISPR-Cas system in Pseudomonas aeruginosa mediates RNA-guided plasmid interference in vivo. CRISPR J, 2019; 2:434–440. DOI: 10.1089/crispr.2019.0048.
16.
AcunaLG, CardenasJP, CovarrubiasPC, et al.Architecture and gene repertoire of the flexible genome of the extreme acidophile Acidithiobacillus caldus. PLoS One, 2013; 8:e78237. DOI: 10.1371/journal.pone.0078237.
17.
Moya-BeltranA, BeardS, Rojas-VillalobosC, et al. Genomic evolution of the class Acidithiobacillia: deep-branching Proteobacteria living in extreme acidic conditions. ISME J 2021 May 18 [Epub ahead of print]; DOI: 10.1038/s41396-021-00995-x.
18.
AltschulSF, MaddenTL, SchafferAA, et al.Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res, 1997; 25:3389–3402.
19.
Marchler-BauerA, ZhengC, ChitsazF, et al.CDD: conserved domains and protein three-dimensional structure. Nucleic Acids Res, 2013; 41:D348–352. DOI: 10.1093/nar/gks1243.
20.
SodingJ. Protein homology detection by HMM-HMM comparison. Bioinformatics, 2005; 21:951–960. DOI: 10.1093/bioinformatics/bti125.
21.
RusselJ, Pinilla-RedondoR, Mayo-MunozD, et al.CRISPRCasTyper: automated identification, annotation, and classification of CRISPR-Cas loci. CRISPR J, 2020; 3:462–469. DOI: 10.1089/crispr.2020.0059.
22.
BlandC, RamseyTL, SabreeF, et al.CRISPR recognition tool (CRT): a tool for automatic detection of clustered regularly interspaced palindromic repeats. BMC Bioinformatics, 2007; 8:209. DOI: 10.1186/1471-2105-8-209.
23.
GrissaI, VergnaudG, PourcelC. CRISPRFinder: a web tool to identify clustered regularly interspaced short palindromic repeats. Nucleic Acids Res, 2007; 35:W52–57. DOI: 10.1093/nar/gkm360.
24.
BiswasA, GagnonJN, BrounsSJ, et al.CRISPRTarget: bioinformatic prediction and analysis of crRNA targets. RNA Biol, 2013; 10:817–827. DOI: 10.4161/rna.24046.
25.
SteineggerM, SodingJ. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol, 2017; 35:1026–1028. DOI: 10.1038/nbt.3988.
26.
EdgarRC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res, 2004; 32:1792–1797.
27.
NguyenLT, SchmidtHA, von HaeselerA, et al.IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol, 2015; 32:268–274. DOI: 10.1093/molbev/msu300.
28.
PriceMN, DehalPS, ArkinAP. FastTree 2—approximately maximum-likelihood trees for large alignments. PLoS One, 2010; 5:e9490. DOI: 10.1371/journal.pone.0009490.
29.
KatohK, StandleyDM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol, 2013; 30:772–780. DOI: 10.1093/molbev/mst010.
30.
NietoPA, CovarrubiasPC, JedlickiE, et al.Selection and evaluation of reference genes for improved interrogation of microbial transcriptomes: case study with the extremophile Acidithiobacillus ferrooxidans. BMC Mol Biol, 2009; 10:63. DOI: 10.1186/1471-2199-10-63.
31.
BickJA, DennisJJ, ZylstraGJ, et al.Identification of a new class of 5′-adenylylsulfate (APS) reductases from sulfate-assimilating bacteria. J Bacteriol, 2000; 182:135–142. DOI: 10.1128/jb.182.1.135-142.2000.
32.
XiongL, LiuS, ChenS, et al.A new type of DNA phosphorothioation-based antiviral system in archaea. Nat Commun, 2019; 10:1688. DOI: 10.1038/s41467-019-09390-9.
33.
XuT, YaoF, ZhouX, et al.A novel host-specific restriction system associated with DNA backbone S-modification in Salmonella. Nucleic Acids Res, 2010; 38:7133–7141. DOI: 10.1093/nar/gkq610.
34.
FarlowJ, BolkvadzeD, LeshkasheliL, et al.Genomic characterization of three novel Basilisk-like phages infecting Bacillus anthracis. BMC Genomics, 2018; 19:685. DOI: 10.1186/s12864-018-5056-4.
35.
GarciaP, MonjardinC, MartinR, et al.Isolation of new Stenotrophomonas bacteriophages and genomic characterization of temperate phage S1. Appl Environ Microbiol, 2008; 74:7552–7560. DOI: 10.1128/AEM.01709-08.
36.
SummerEJ, GillJJ, UptonC, et al.Role of phages in the pathogenesis of Burkholderia, or “Where are the toxin genes in Burkholderia phages?”. Curr Opin Microbiol, 2007; 10:410–417. DOI: 10.1016/j.mib.2007.05.016.
37.
KoprivaS, KoprivovaA. Plant adenosine 5′-phosphosulphate reductase: the past, the present, and the future. J Exp Bot, 2004; 55:1775–1783. DOI: 10.1093/jxb/erh185.
38.
TaylorHN, LadermanE, ArmbrustM, et al.Positioning diverse type IV structures and functions within class 1 CRISPR-Cas systems. Front Microbiol, 2021; 12:671522. DOI: 10.3389/fmicb.2021.671522.
39.
YangJC, LessardPA, SenguptaN, et al.TraA is required for megaplasmid conjugation in Rhodococcus erythropolis AN12. Plasmid, 2007; 57:55–70. DOI: 10.1016/j.plasmid.2006.08.002.
40.
RogozinIB, MakarovaKS, WolfYI, et al.Computational approaches for the analysis of gene neighbourhoods in prokaryotic genomes. Brief Bioinform, 2004; 5:131–149. DOI: 10.1093/bib/5.2.131.
41.
DysonZA, TucciJ, SeviourRJ, et al.Isolation and characterization of bacteriophage SPI1, which infects the activated-sludge-foaming bacterium Skermania piniformis. Arch Virol, 2016; 161:149–158. DOI: 10.1007/s00705-015-2631-8.
CastilloF, BenmohamedA, SzatmariG. Xer site specific recombination: double and single recombinase systems. Front Microbiol, 2017; 8:453. DOI: 10.3389/fmicb.2017.00453.
44.
KaurG, BurroughsAM, IyerLM, et al.Highly regulated, diversifying NTP-dependent biological conflict systems with implications for the emergence of multicellularity. Elife, 2020; 9. DOI: 10.7554/eLife.52696.
45.
Flores-RiosR, Moya-BeltranA, Pareja-BarruetoC, et al.The type IV secretion system of ICEAfe1: formation of a conjugative pilus in Acidithiobacillus ferrooxidans. Front Microbiol, 2019; 10:30. DOI: 10.3389/fmicb.2019.00030.
46.
CabezonE, Ripoll-RozadaJ, PenaA, et al.Towards an integrated model of bacterial conjugation. FEMS Microbiol Rev, 2015; 39:81–95. DOI: 10.1111/1574-6976.12085.
47.
GuglielminiJ, QuintaisL, Garcillan-BarciaMP, et al.The repertoire of ICE in prokaryotes underscores the unity, diversity, and ubiquity of conjugation. PLoS Genet, 2011; 7:e1002222. DOI: 10.1371/journal.pgen.1002222.
48.
WozniakRA, WaldorMK. Integrative and conjugative elements: mosaic mobile genetic elements enabling dynamic lateral gene flow. Nat Rev Microbiol, 2010; 8:552–563. DOI: 10.1038/nrmicro2382.
49.
Moya-BeltranA, Rojas-VillalobosC, DiazM, et al.Nucleotide second messenger-based signaling in extreme acidophiles of the Acidithiobacillus species complex: partition between the core and variable gene complements. Front Microbiol, 2019; 10:381. DOI: 10.3389/fmicb.2019.00381.
50.
LuMJ, HenningU. The immunity (imm) gene of Escherichia coli bacteriophage T4. J Virol, 1989; 63:3472–3478. DOI: 10.1128/JVI.63.8.3472-3478.1989.
51.
KooninEV, ZhangF. Coupling immunity and programmed cell suicide in prokaryotes: life-or-death choices. Bioessays, 2017; 39:1–9. DOI: 10.1002/bies.201600186.
52.
MakarovaKS, WolfYI, SnirS, et al.Defense islands in bacterial and archaeal genomes and prediction of novel defense systems. J Bacteriol, 2011; 193:6039–6056. DOI: 10.1128/JB.05535-11.
53.
DoronS, MelamedS, OfirG, et al.Systematic discovery of antiphage defense systems in the microbial pangenome. Science, 2018; 359. DOI: 10.1126/science.aar4120.
54.
BeardS, OssandonFJ, RawlingsDE, et al.The flexible genome of acidophilic prokaryotes. Curr Issues Mol Biol, 2021; 40:231–266. DOI: 10.21775/cimb.040.231.
55.
KlompeSE, VoPLH, Halpin-HealyTS, et al.Transposon-encoded CRISPR-Cas systems direct RNA-guided DNA integration. Nature, 2019; 571:219–225. DOI: 10.1038/s41586-019-1323-z.
56.
StreckerJ, LadhaA, GardnerZ, et al.RNA-guided DNA insertion with CRISPR-associated transposases. Science, 2019; 365:48–53. DOI: 10.1126/science.aax9181.
57.
MakarovaKS, WolfYI, KooninEV. Classification and nomenclature of CRISPR-Cas systems: where from here?. CRISPR J, 2018; 1:325–336. DOI: 10.1089/crispr.2018.0033.
58.
MakarovaKS, WolfYI, ShmakovSA, et al.Unprecedented diversity of unique CRISPR-Cas-related systems and Cas1 homologs in Asgard archaea. CRISPR J, 2020; 3:156–163. DOI: 10.1089/crispr.2020.0012.
59.
ChartronJ, CarrollKS, ShiauC, et al.Substrate recognition, protein dynamics, and iron-sulfur cluster in Pseudomonas aeruginosa adenosine 5′-phosphosulfate reductase. J Mol Biol, 2006; 364:152–169. DOI: 10.1016/j.jmb.2006.08.080.
60.
Buetti-DinhA, HeroldM, ChristelS, et al.Systems biology of acidophile biofilms for efficient metal extraction. Sci Data, 2020; 7:215. DOI: 10.1038/s41597-020-0519-2.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
