The ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) and Clostridium difficile have been identified as the leading global cause of multidrug-resistant bacterial infections in hospitals. CRISPR–Cas systems are bacterial immune systems, empowering the bacteria with defense against invasive mobile genetic elements that may carry the antimicrobial resistance (AMR) genes, among others. On the other hand, the CRISPR–Cas systems are themselves mobile. In this study, we annotated and compared the CRISPR–Cas systems in these pathogens, utilizing their publicly available large numbers of sequenced genomes (e.g., there are more than 12 thousands of S. aureus genomes). The presence of CRISPR–Cas systems showed a very broad spectrum in these pathogens: S. aureus has the least tendency of obtaining the CRISPR–Cas systems with only 0.55% of its isolates containing CRISPR–Cas systems, whereas isolates of C. difficile we analyzed have CRISPR–Cas systems each having multiple CRISPRs. Statistical tests show that CRISPR–Cas containing isolates tend to have more AMRs for four of the pathogens (A. baumannii, E. faecium, P. aeruginosa, and S. aureus). We made available all the annotated CRISPR–Cas systems in these pathogens with visualization at a website (https://omics.informatics.indiana.edu/CRISPRone/pathogen), which we believe will be an important resource for studying the pathogens and their arms-race with invaders mediated through the CRISPR–Cas systems, and for developing potential clinical applications of the CRISPR–Cas systems for battles against the antibiotic resistant pathogens.
Background CRISPR-Cas (clustered regularly interspaced short palindromic repeats—CRISPR-associated proteins) systems are adaptive immune systems commonly found in prokaryotes that provide sequence-specific defense against invading mobile genetic elements (MGEs). The memory of these immunological encounters are stored in CRISPR arrays, where spacer sequences record the identity and history of past invaders. Analyzing such CRISPR arrays provide insights into the dynamics of CRISPR-Cas systems and the adaptation of their host bacteria to rapidly changing environments such as the human gut. Results In this study, we utilized 601 publicly available Bacteroides fragilis genome isolates from 12 healthy individuals, 6 of which include longitudinal observations, and 222 available B. fragilis reference genomes to update the understanding of B. fragilis CRISPR-Cas dynamics and their differential activities. Analysis of longitudinal genomic data showed that some CRISPR array structures remained relatively stable over time whereas others involved radical spacer acquisition during some periods, and diverse CRISPR arrays (associated with multiple isolates) co-existed in the same individuals with some persisted over time. Furthermore, features of CRISPR adaptation, evolution, and microdynamics were highlighted through an analysis of host-MGE network, such as modules of multiple MGEs and hosts, reflecting complex interactions between B. fragilis and its invaders mediated through the CRISPR-Cas systems. Conclusions We made available of all annotated CRISPR-Cas systems and their target MGEs, and their interaction network as a web resource at https://omics.informatics.indiana.edu/CRISPRone/Bfragilis. We anticipate it will become an important resource for studying of B. fragilis, its CRISPR-Cas systems, and its interaction with mobile genetic elements providing insights into evolutionary dynamics that may shape the species virulence and lead to its pathogenicity.
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.
The CRISPR-Cas systems are important prokaryotic adaptive immune systems and effectively record the arms-race between bacteria and invading mobile elements in their CRISPR arrays. Using data from culture-based population genomics and metagenomics, we investigated the CRISPR-Cas systems associated with Bacteriodes fragilis, an important gut bacterium, and studied their diversity and dynamics. We analyzed genomes of 601 B. fragilis isolates derived from 12 healthy individuals, among which include time-series isolates from 6 individuals. In addition, we analyzed 222 reference B. fragilis genomes. Three different types of CRISPR-Cas systems (Type I-B, II-C and III-B) were found in analyzed B. fragilis genomes, with Type III-B being the most prevalent whereas the Type II-C being the most dynamic with varying arrays among isolates. Our graph-based summary and visualization of CRISPR arrays provided a holistic view of the organization and the composition of the CRISPR spacers. We observed insertions of different new spacers at the leader ends of the CRISPR arrays of Type II-C CRISPR-Cas systems in different B. fragilis sub-populations in one individual, an example of B. fragilis' adaptation and parallel evolution within individual microbiomes. A network of B. fragilis and its predicted invaders also revealed microdynamics of B. fragilis CRISPR array, with hairball-like structures representing spacers with multi-target capabilities and network modules revealing the collective targeting of selected mobile elements by many spacers. This work demonstrates the power of using culture-based population genomics to reveal the activities and evolution of the CRISPR-Cas systems of the important gut bacterium B. fragilis in human population.
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