Dataset Information

Identification of Natural CRISPR Systems and Targets in the Human Microbiome.

ABSTRACT: Many bacteria resist invasive DNA by incorporating sequences into CRISPR loci, which enable sequence-specific degradation. CRISPR systems have been well studied from isolate genomes, but culture-independent metagenomics provide a new window into their diversity. We profiled CRISPR loci and cas genes in the body-wide human microbiome using 2,355 metagenomes, yielding functional and taxonomic profiles for 2.9 million spacers by aligning the spacer content to each sample's metagenome and corresponding gene families. Spacer and repeat profiles agree qualitatively with those from isolate genomes but expand their diversity by approximately 13-fold, with the highest spacer load present in the oral microbiome. The taxonomy of spacer sequences parallels that of their source community, with functional targets enriched for viral elements. When coupled with cas gene systems, CRISPR-Cas subtypes are highly site and taxon specific. Our analysis provides a comprehensive collection of natural CRISPR-cas loci and targets in the human microbiome.

SUBMITTER: Munch PC

PROVIDER: S-EPMC7813156 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Identification of Natural CRISPR Systems and Targets in the Human Microbiome.

Münch Philipp C PC Franzosa Eric A EA Stecher Bärbel B McHardy Alice C AC Huttenhower Curtis C

Cell host & microbe 20201119 1

Many bacteria resist invasive DNA by incorporating sequences into CRISPR loci, which enable sequence-specific degradation. CRISPR systems have been well studied from isolate genomes, but culture-independent metagenomics provide a new window into their diversity. We profiled CRISPR loci and cas genes in the body-wide human microbiome using 2,355 metagenomes, yielding functional and taxonomic profiles for 2.9 million spacers by aligning the spacer content to each sample's metagenome and correspond ...[more]

PMID: 33217332

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Project description:The human gut microbiome is composed of a diverse consortium of microorganisms. Relatively little is known about the diversity of the bacteriophage population and their interactions with microbial organisms in the human microbiome. Due to the persistent rivalry between microbial organisms (hosts) and phages (invaders), genetic traces of phages are found in the hosts' CRISPR-Cas adaptive immune system. Mobile genetic elements (MGEs) found in bacteria include genetic material from phage and plasmids, often resultant from invasion events. We developed a computational pipeline (BacMGEnet), which can be used for inference and exploratory analysis of putative interactions between microbial organisms and MGEs (phages and plasmids) and their interaction network. Given a collection of genomes as the input, BacMGEnet utilizes computational tools we have previously developed to characterize CRISPR-Cas systems in the genomes, which are then used to identify putative invaders from publicly available collections of phage/prophage sequences. In addition, BacMGEnet uses a greedy algorithm to summarize identified putative interactions to produce a bacteria-MGE network in a standard network format. Inferred networks can be utilized to assist further examination of the putative interactions and for discovery of interaction patterns. Here we apply the BacMGEnet pipeline to a few collections of genomic/metagenomic datasets to demonstrate its utilities. BacMGEnet revealed a complex interaction network of the Phocaeicola vulgatus pangenome with its phage invaders, and the modularity analysis of the resulted network suggested differential activities of the different P. vulgatus' CRISPR-Cas systems (Type I-C and Type II-C) against some phages. Analysis of the phage-bacteria interaction network of human gut microbiome revealed a mixture of phages with a broad host range (resulting in large modules with many bacteria and phages), and phages with narrow host range. We also showed that BacMGEnet can be used to infer phages that invade bacteria and their interactions in wound microbiome. We anticipate that BacMGEnet will become an important tool for studying the interactions between bacteria and their invaders for microbiome research.

Project description:Background: While CRISPR-Cas systems have been identified in bacteria from a wide variety of ecological niches, there are no studies to describe CRISPR-Cas elements in Bacteroides species, the most prevalent anaerobic bacteria in the lower intestinal tract. Microbes of the genus Bacteroides make up ~25% of the total gut microbiome. Bacteroides fragilis comprises only 2% of the total Bacteroides in the gut, yet causes of >70% of Bacteroides infections. The factors causing it to transition from benign resident of the gut microbiome to virulent pathogen are not well understood, but a combination of horizontal gene transfer (HGT) of virulence genes and differential transcription of endogenous genes are clearly involved. The CRISPR-Cas system is a multi-functional system described in prokaryotes that may be involved in control both of HGT and of gene regulation. Results: Clustered regularly interspaced short palindromic repeats (CRISPR) elements in all strains of B. fragilis (n = 109) with publically available genomes were identified. Three different CRISPR-Cas types, corresponding most closely to Type IB, Type IIIB, and Type IIC, were identified. Thirty-five strains had two CRISPR-Cas types, and three strains included all three CRISPR-Cas types in their respective genomes. The cas1 gene in the Type IIIB system encoded a reverse-transcriptase/Cas1 fusion protein rarely found in prokaryotes. We identified a short CRISPR (3 DR) with no associated cas genes present in most of the isolates; these CRISPRs were found immediately upstream of a hipA/hipB operon and we speculate that this element may be involved in regulation of this operon related to formation of persister cells during antimicrobial exposure. Also, blood isolates of B. fragilis did not have Type IIC CRISPR-Cas systems and had atypical Type IIIB CRISPR-Cas systems that were lacking adjacent cas genes. Conclusions: This is the first systematic report of CRISPR-Cas systems in a wide range of B. fragilis strains from a variety of sources. There are four apparent CRISPR-Cas systems in B. fragilis-three systems have adjacent cas genes. Understanding CRISPR/Cas function in B. fragilis will elucidate their role in gene expression, DNA repair and ability to survive exposure to antibiotics. Also, based on their unique CRISPR-Cas arrays, their phylogenetic clustering and their virulence potential, we are proposing that blood isolates of B. fragilis be viewed a separate subgroup.

Project description:The highly personalized human skin microbiome may serve as a viable marker in personal identification. Amplicon sequencing resolution using 16S rRNA cannot identify bacterial communities sufficiently to discriminate between individuals. Thus, novel higher-resolution genetic markers are required for forensic purposes. The clustered regularly interspaced short palindromic repeats (CRISPRs) are prokaryotic genetic elements that can provide a history of infections encountered by the bacteria. The sequencing of CRISPR spacers may provide phylogenetic information with higher resolution than other markers. However, using spacer sequencing for discrimination of personal skin microbiome is difficult due to limited information on CRISPRs in human skin microbiomes. It remains unclear whether personal microbiome discrimination can be achieved using spacer diversity or which CRISPRs will be forensically relevant. We identified common CRISPRs in the human skin microbiome via metagenomic reconstruction and used amplicon sequencing for deep sequencing of spacers. We successfully reconstructed 24 putative CRISPR arrays using metagenomic data sets. A total of 1,223,462 reads from three CRISPR arrays revealed that spacers in the skin microbiome were highly personalized, and conserved repeats were commonly shared between individuals. These individual specificities observed using CRISPR typing were confirmed by comparing the CRISPR diversity to microbiome diversity assessed using 16S rRNA amplicon sequencing. CRISPR typing achieved 95.2% accuracy in personal classification, whereas 16S rRNA sequencing only achieved 52.6%. These results suggest that sequencing CRISPRs in the skin microbiome may be a more powerful approach for personal identification and ecological studies compared to conventional 16S rRNA sequencing.IMPORTANCE Microbial community diversity analysis can be utilized to characterize the personal microbiome that varies between individuals. CRISPR sequences, which reflect virome structure, in the human skin environment may be highly personalized similar to the structures of individual viromes. In this study, we identified 24 putative CRISPR arrays using a shotgun metagenome data set of the human skin microbiome. The findings of this study expand our understanding of the nature of CRISPRs by identifying novel CRISPR candidates. We developed a method to efficiently determine the diversity of three CRISPR arrays. Our analysis revealed that the CRISPR spacer diversity in the human skin microbiome is highly personalized compared with the microbiome diversity assessed by 16S rRNA sequencing, providing a new perspective on the study of the skin microbiome.

Dataset Information

Identification of Natural CRISPR Systems and Targets in the Human Microbiome.

Publications

Identification of Natural CRISPR Systems and Targets in the Human Microbiome.

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