CRISPR arrays as high-resolution markers to track microbial transmission during influenza infection

Background The microbial community present in the respiratory tract can be disrupted during influenza virus infection, leading to functional effects on the microbial ecology of the airways and potentially impacting transmission of bacterial pathogens. Determining the transmission of airway commensals, which can carry antibiotic resistance genes that could in turn be transferred to bacterial pathogens, is of public health interest. Metagenomic-type analyses of the microbiome provide the resolution necessary for microbial tracking and functional assessments in the airways. Results We obtained 221 respiratory samples that were collected from 54 individuals at 4 to 5 time points across 10 households, with and without influenza infection, in Managua, Nicaragua. From these samples we generated metagenomic (whole genome shotgun sequencing) and metatranscriptomic (RNA sequencing) datasets to profile microbial taxonomy and gene orthologous groups. Overall, specific bacteria and phages were differentially abundant between influenza positive households and control (no influenza infection) households, with bacterial species like Moraxella catarrhalis and bacteriophages like Chivirus significantly enriched in the influenza positive households. Some of the bacterial taxa found to be differentially abundant were active at the RNA level with genes involved in bacterial physiology differentially enriched between influenza positive and influenza negative samples, primarily for Moraxella . We identified and quantified CRISPR arrays detected in the metagenomic sequence reads and used these as barcodes to track bacteria transmission within and across households. We detected a clear sharing of bacteria commensals and pathobionts, such as Rothia mulcilaginosa and Prevotella bacteria, within and between households, indicating community transmission of these microbes. Antibiotic resistance genes that mapped to Rothia and Prevotella were prevalent across our samples. Due to the relatively small number of households in our study we could not determine if there was a correlation between increased bacteria transmission and influenza infection. Conclusion This study shows that microbial composition and ecological disruption during influenza infection were primarily associated with Moraxella in the households sampled. We demonstrated that CRISPR arrays can be used as high-resolution markers to study bacteria transmission between individuals. Although tracking of antibiotic resistance transmission would require higher resolution mapping of antibiotic resistance genes to specific bacterial genomes, we observed that individuals connected by shared bacteria had more similar antibiotic resistance gene profiles than non-connected individuals from the same households.