Revealing bacteria-phage interactions in human microbiome through the CRISPR-Cas immune systems.

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