Dataset Information

MetaCRAST: reference-guided extraction of CRISPR spacers from unassembled metagenomes.

ABSTRACT: Clustered regularly interspaced short palindromic repeat (CRISPR) systems are the adaptive immune systems of bacteria and archaea against viral infection. While CRISPRs have been exploited as a tool for genetic engineering, their spacer sequences can also provide valuable insights into microbial ecology by linking environmental viruses to their microbial hosts. Despite this importance, metagenomic CRISPR detection remains a major challenge. Here we present a reference-guided CRISPR spacer detection tool (Metagenomic CRISPR Reference-Aided Search Tool-MetaCRAST) that constrains searches based on user-specified direct repeats (DRs). These DRs could be expected from assembly or taxonomic profiles of metagenomes. We compared the performance of MetaCRAST to those of two existing metagenomic CRISPR detection tools-Crass and MinCED-using both real and simulated acid mine drainage (AMD) and enhanced biological phosphorus removal (EBPR) metagenomes. Our evaluation shows MetaCRAST improves CRISPR spacer detection in real metagenomes compared to the de novo CRISPR detection methods Crass and MinCED. Evaluation on simulated metagenomes show it performs better than de novo tools for Illumina metagenomes and comparably for 454 metagenomes. It also has comparable performance dependence on read length and community composition, run time, and accuracy to these tools. MetaCRAST is implemented in Perl, parallelizable through the Many Core Engine (MCE), and takes metagenomic sequence reads and direct repeat queries (FASTA or FASTQ) as input. It is freely available for download at https://github.com/molleraj/MetaCRAST.

SUBMITTER: Moller AG

PROVIDER: S-EPMC5592083 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

MetaCRAST: reference-guided extraction of CRISPR spacers from unassembled metagenomes.

Moller Abraham G AG Liang Chun C

PeerJ 20170907

Clustered regularly interspaced short palindromic repeat (CRISPR) systems are the adaptive immune systems of bacteria and archaea against viral infection. While CRISPRs have been exploited as a tool for genetic engineering, their spacer sequences can also provide valuable insights into microbial ecology by linking environmental viruses to their microbial hosts. Despite this importance, metagenomic CRISPR detection remains a major challenge. Here we present a reference-guided CRISPR spacer detect ...[more]

PMID: 28894651

Similar Datasets

Project description:Viral infection exerts selection pressure on marine microbes, as virus-induced cell lysis causes 20 to 50% of cell mortality, resulting in fluxes of biomass into oceanic dissolved organic matter. Archaeal and bacterial populations can defend against viral infection using the clustered regularly interspaced short palindromic repeat (CRISPR)-associated (Cas) system, which relies on specific matching between a spacer sequence and a viral gene. If a CRISPR spacer match to any gene within a viral genome is equally effective in preventing lysis, no viral genes should be preferentially matched by CRISPR spacers. However, if there are differences in effectiveness, certain viral genes may demonstrate a greater frequency of CRISPR spacer matches. Indeed, homology search analyses of bacterioplankton CRISPR spacer sequences against virioplankton sequences revealed preferential matching of replication proteins, nucleic acid binding proteins, and viral structural proteins. Positive selection pressure for effective viral defense is one parsimonious explanation for these observations. CRISPR spacers from virioplankton metagenomes preferentially matched methyltransferase and phage integrase genes within virioplankton sequences. These virioplankton CRISPR spacers may assist infected host cells in defending against competing phage. Analyses also revealed that half of the spacer-matched viral genes were unknown, some genes matched several spacers, and some spacers matched multiple genes, a many-to-many relationship. Thus, CRISPR spacer matching may be an evolutionary algorithm, agnostically identifying those genes under stringent selection pressure for sustaining viral infection and lysis. Investigating this subset of viral genes could reveal those genetic mechanisms essential to virus-host interactions and provide new technologies for optimizing CRISPR defense in beneficial microbes.IMPORTANCE The CRISPR-Cas system is one means by which bacterial and archaeal populations defend against viral infection which causes 20 to 50% of cell mortality in the ocean. We tested the hypothesis that certain viral genes are preferentially targeted for the initial attack of the CRISPR-Cas system on a viral genome. Using CASC, a pipeline for CRISPR spacer discovery, and metagenome data from oceanic microbes and viruses, we found a clear subset of viral genes with high match frequencies to CRISPR spacers. Moreover, we observed a many-to-many relationship of spacers and viral genes. These high-match viral genes were involved in nucleotide metabolism, DNA methylation, and viral structure. It is possible that CRISPR spacer matching is an evolutionary algorithm pointing to those viral genes most important to sustaining infection and lysis. Studying these genes may advance the understanding of virus-host interactions in nature and provide new technologies for leveraging CRISPR-Cas systems in beneficial microbes.

Project description:Clustered regularly interspaced short palindromic repeat (CRISPR)-Cas systems incorporate short DNA fragments from invasive genetic elements into host CRISPR arrays in order to generate host immunity. Recently, we demonstrated that the Csa3a regulator protein triggers CCN protospacer-adjacent motif (PAM)-dependent CRISPR spacer acquisition in the subtype I-A CRISPR-Cas system of Sulfolobus islandicus However, the mechanisms underlying specific protospacer selection and spacer insertion remained unclear. Here, we demonstrate that two Cas4 family proteins (Cas4 and Csa1) have essential roles (i) in recognizing the 5' PAM and 3' nucleotide motif of protospacers and (ii) in determining both the spacer length and its orientation. Furthermore, we identify amino acid residues of the Cas4 proteins that facilitate these functions. Overexpression of the Cas4 and Csa1 proteins, and also that of an archaeal virus-encoded Cas4 protein, resulted in strongly reduced adaptation efficiency, and the former proteins yielded a high incidence of PAM-dependent atypical spacer integration or of PAM-independent spacer integration. We further demonstrated that in plasmid challenge experiments, overexpressed Cas4-mediated defective spacer acquisition in turn potentially enabled targeted DNA to escape subtype I-A CRISPR-Cas interference. In summary, these results define the specific involvement of diverse Cas4 proteins in in vivo CRISPR spacer acquisition. Furthermore, we provide support for an anti-CRISPR role for virus-encoded Cas4 proteins that involves compromising CRISPR-Cas interference activity by hindering spacer acquisition.IMPORTANCE The Cas4 family endonuclease is an essential component of the adaptation module in many variants of CRISPR-Cas adaptive immunity systems. The CrenarchaeotaSulfolobus islandicus REY15A carries two cas4 genes (cas4 and csa1) linked to the CRISPR arrays. Here, we demonstrate that Cas4 and Csa1 are essential to CRISPR spacer acquisition in this organism. Both proteins specify the upstream and downstream conserved nucleotide motifs of the protospacers and define the spacer length and orientation in the acquisition process. Conserved amino acid residues, in addition to those recently reported, were identified to be important for these functions. More importantly, overexpression of the Sulfolobus viral Cas4 abolished spacer acquisition, providing support for an anti-CRISPR role for virus-encoded Cas4 proteins that inhibit spacer acquisition.

Dataset Information

MetaCRAST: reference-guided extraction of CRISPR spacers from unassembled metagenomes.

Publications

MetaCRAST: reference-guided extraction of CRISPR spacers from unassembled metagenomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets