Abstract
Antibiotic resistance is an important global public health problem. Human gut human microbiota is an accumulator of resistance genes potentially providing them to pathogens. It is important to develop tools for identifying the mechanisms of how resistance is transmitted between gut microbial species and pathogens. We developed MetaCherchant - an algorithm for extracting the genomic environment of antibiotic resistance genes from metagenomic data in the form of a graph. The algorithm was validated on simulated datasets and applied to new "shotgun" metagenomes of gut microbiota from patients with Helicobacter pylori who underwent antibiotic therapy. Genomic context was reconstructed for several dominant resistance genes; taxonomic annotation of the context showed the species carrying the genes. Application of MetaCherchant in differential mode produced specific graph structures suggesting the evidence of possible resistance gene transmission within a mobile element that occurred as a result of the antibiotic therapy. MetaCherchant is a promising tool giving researchers an opportunity to get an insight into dynamics of resistance transmission in vivo based on metagenomic data.
