CRISPRs for Strain Tracking and Their Application to Microbiota Transplantation Data Analysis

Abstract

CRISPR-Cas systems are adaptive immune systems naturally found in bacteria and archaea. Prokaryotes use these immune systems to defend against invaders, which include phages, plasmids, and other mobile genetic elements. Relying on the integration of spacers derived from invader sequences (protospacers) into CRISPR loci (forming spacers flanked by repeats), CRISPR-Cas systems are able to store the memory of past immunological encounters. While CRISPR-Cas systems have evolved in response to invading mobile genetic elements, invaders have also developed mechanisms to avoid detection. As a result of an arms race between CRISPR-Cas systems and their targets, CRISPR arrays typically undergo rapid turnover of spacers through the acquisition and loss events. Additionally, microbiomes of different individuals rarely share spacers. Here, we present a computational pipeline, CRISPRtrack, for strain tracking based on CRISPR spacer content, and we applied it to fecal transplantation microbiome data to study the retention of donor strains in recipients. Our results demonstrate the potential use of CRISPRs as a simple yet effective tool for donor-strain tracking in fecal transplantation and as a general purpose tool for quantifying microbiome similarity.

FIG. 1.

Subset of CRISPR-Cas systems found in common human gut-associated bacterial species used to generate reference CRISPR repeats. The arrows in different colors represent the cas genes, and the open hexagons represent the CRISPR repeat-spacer arrays, with numbers following the letter x indicating the number of repeats found in each array.

FIG. 2.

Sharing of the CRISPR spacers among HMP individuals. These two figures show the boxplots of spacer content similarity between microbiomes from different individuals (diff) and microbiomes from the same human subject (same). (A) Based on spacers identified using the reference-based approach. (B) Based on de novo identification of CRISPR arrays.

FIG. 3.

Tracking of donor spacers and recipient's own spacers over time after fecal microbiota transplantation (FMT). (A) CRISPR spacer similarity between the recipients and their corresponding donors. (B) CRISPR spacer similarity between the recipients after FMT and their pre-FMT counterparts. Lines connect time-point samples from the same individual. The time axis (i.e., the x-axis) was not scaled for clarity. The dotted black lines in the plots indicate the 95th percentiles of the spacer similarities between different individuals, inferred from the HMP data sets.

FIG. 4.

CRISPRtrack results for the FMT-Smillie data set. (A) Tracking of the donor- and pre-FMT recipient-specific spacers in recipient MGH02R. (B) Principle component plot of principle component 1 and principle component 2. Donor samples are depicted as triangles, whereas recipients are depicted as circles. Samples are colored by subject.