Comparisons of clustered regularly interspaced short palindromic repeats and viromes in human saliva reveal bacterial adaptations to salivary viruses - PubMed (original) (raw)

Comparisons of clustered regularly interspaced short palindromic repeats and viromes in human saliva reveal bacterial adaptations to salivary viruses

David T Pride et al. Environ Microbiol. 2012 Sep.

Abstract

Explorations of human microbiota have provided substantial insight into microbial community composition; however, little is known about interactions between various microbial components in human ecosystems. In response to the powerful impact of viral predation, bacteria have acquired potent defences, including an adaptive immune response based on the clustered regularly interspaced short palindromic repeats (CRISPRs)/Cas system. To improve our understanding of the interactions between bacteria and their viruses in humans, we analysed 13 977 streptococcal CRISPR sequences and compared them with 2 588 172 virome reads in the saliva of four human subjects over 17 months. We found a diverse array of viruses and CRISPR spacers, many of which were specific to each subject and time point. There were numerous viral sequences matching CRISPR spacers; these matches were highly specific for salivary viruses. We determined that spacers and viruses coexist at the same time, which suggests that streptococcal CRISPR/Cas systems are under constant pressure from salivary viruses. CRISPRs in some subjects were just as likely to match viral sequences from other subjects as they were to match viruses from the same subject. Because interactions between bacteria and viruses help to determine the structure of bacterial communities, CRISPR-virus analyses are likely to provide insight into the forces shaping the human microbiome.

© 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.

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Figures

Figure 1

Figure 1

Putative biological assignments for contigs from human salivary viromes. Contigs were assigned to biological groups based on significant blastX E-scores based on the NCBI non-redundant database. The percentage of contigs assigned to each biological group is demonstrated for each subject at all time points. Subjects #1 and #2 were sampled at additional the additional time points of Month -6 and Month -3, however, no intervention took place during the study.

Figure 2

Figure 2

Percentage of spacers (Panels A and B) and diagram of SGII CRISPR spacer homologous to various bacteria, phage, and plasmids (Panel C). The percentage of spacers in each subject and time point that were not identified at prior time points is demonstrated in blue. The percentage of those spacers that match virome reads is demonstrated in red, and the percentage of those spacers that have homologues in the NCBI NR database are shown in green. Panel A - SGII spacers and Panel B - SGI spacers. For the initial time point for each subject, homologues to CRISPR spacer complements are demonstrated in Panel C. At each subsequent time point, only homologues to newly identified spacers that were not present in prior time points are shown. For example, in subject #3 (Panel C3), spacers homologous to streptococcal phage PH-10 are identified on Day 1, while on Day 30 newly identified spacers that were not present on Day 1 also have homology to phage PH-10. Panel C1-Subject #1, Panel C2 - Subject #2, Panel C3 - Subject #3, and Panel C4 - Subject #4. Homologues to phage are shown in red, plasmids in blue, and bacteria in green.

Figure 2

Figure 2

Percentage of spacers (Panels A and B) and diagram of SGII CRISPR spacer homologous to various bacteria, phage, and plasmids (Panel C). The percentage of spacers in each subject and time point that were not identified at prior time points is demonstrated in blue. The percentage of those spacers that match virome reads is demonstrated in red, and the percentage of those spacers that have homologues in the NCBI NR database are shown in green. Panel A - SGII spacers and Panel B - SGI spacers. For the initial time point for each subject, homologues to CRISPR spacer complements are demonstrated in Panel C. At each subsequent time point, only homologues to newly identified spacers that were not present in prior time points are shown. For example, in subject #3 (Panel C3), spacers homologous to streptococcal phage PH-10 are identified on Day 1, while on Day 30 newly identified spacers that were not present on Day 1 also have homology to phage PH-10. Panel C1-Subject #1, Panel C2 - Subject #2, Panel C3 - Subject #3, and Panel C4 - Subject #4. Homologues to phage are shown in red, plasmids in blue, and bacteria in green.

Figure 3

Figure 3

Fraction of virome reads with SGI CRISPR spacer matches over time within each subject. The virome reads with CRISPR spacer matches are normalized by virome size. Each column represents the SGI CRISPR spacer repertoire characterized at the individual labeled time point, and the Y axis represents the normalized percentages of unique reads with matches to CRISPR spacers recovered from each of the time points. Blue represents spacer-read matches from Month -6, red represents Month -3, green represents Day 1, purple represents Day 30, cyan represents Day 60, and orange represents Month 11.

Figure 4

Figure 4

Percentage of spacers with matches to virome reads in each subject. The percentage of spacers that are unique to individual time points and those that are shared between multiple time points are shown. The percentage of spacers with matches to reads in each virome is demonstrated on the Y axis.

Figure 5

Figure 5

Heatmap of virome reads with CRISPR spacer matches for SGI and SGII CRISPR spacers. Each row represents a unique virome read, and each column represents the CRISPR spacer repertoire found on that day for that subject. Reads from viromes of each subject are identified on the left of each diagram, and the day from which each read was recovered is shown on the right of each diagram. The intensity scale bar is shown below each panel, and its values correspond to the percentage of CRISPR spacer matches present in each subject and time point. Panel A – SGI CRISPR spacer-read matches, Panel B – SGII CRISPR spacer-read matches.

Figure 6

Figure 6

Number of virome contigs with multiple SGI and SGII CRISPR spacer matches. The number of contigs is represented on the Y-axis, the number of CRISPR spacer matches for each contig is represented on the X-axis, and the different colors represent the subject from which each CRISPR spacer was derived.

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