Summary Phigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated ‘prophage genome maps’ and marks possible transposon insertion spots inside prophages. It is applicable for mining prophage regions from large metagenomic datasets. Availability and implementation Source code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python. Supplementary information Supplementary data are available at Bioinformatics online.

The human gut microbiome plays an important role both in health and disease. Use of antibiotics can alter gut microbiota composition, which can lead to various deleterious events. Here we report a whole genome sequencing metagenomic/genomic study of the intestinal microbiota changes caused by Helicobacter pylori (HP) eradication therapy. Using approaches for metagenomic data analysis we revealed a statistically significant decrease in alpha-diversity and relative abundance of Bifidobacterium adolescentis due to HP eradication therapy, while the relative abundance of Enterococcus faecium increased. We have detected changes in general metagenome resistome profiles as well: after HP eradication therapy, the ermB, CFX group, and tetQ genes were overrepresented, while tetO and tetW genes were underrepresented. We have confirmed these results with genome-resolved metagenomic approaches. MAG (metagenome-assembled genomes) abundance profiles have changed dramatically after HP eradication therapy. Focusing on ermB gene conferring resistance to macrolides, which were included in the HP eradication therapy scheme, we have shown a connection between antibiotic resistance genes (ARGs) and some overrepresented MAGs. Moreover, some E. faecium strains isolated from stool samples obtained after HP eradication have manifested greater antibiotic resistance in vitro in comparison to other isolates, as well as the higher number of ARGs conferring resistance to macrolides and tetracyclines.

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AbstractSummaryPhigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated “prophage genome maps” and marks possible transposon insertion spots inside prophages. It provides putative taxonomic annotations that can distinguish tailed from non-tailed phages. It is applicable for mining prophage regions from large metagenomic datasets.AvailabilitySource code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python.

Antibiotic resistance is increasing among pathogens, and the human microbiome contains a reservoir of antibiotic resistance genes. Acidaminococcus intestini is the first Negativicute bacterium (Gram-negative Firmicute) shown to be resistant to beta-lactam antibiotics. Resistance is conferred by the aci1 gene, but its evolutionary history and prevalence remain obscure. We discovered that ACI-1 proteins are phylogenetically distinct from beta-lactamases of Gram-positive Firmicutes and that aci1 occurs in bacteria scattered across the Negativicute clade, suggesting lateral gene transfer. In the reference A. intestini RyC-MR95 genome, we found transposons residing within a tailed prophage context are likely vehicles for aci1's mobility. We found aci1 in 56 (4.4%) of 1,267 human gut metagenomes, mostly hosted within A. intestini, and, where could be determined, mostly within a consistent mobile element constellation. These samples are from Europe, China and the USA, showing that aci1 is distributed globally. We found that for most Negativicute assemblies with aci1, the prophage observed in A. instestini is absent, but in all cases aci1 is flanked by varying transposons. The chimeric mobile elements we identify here likely have a complex evolutionary history and potentially provide multiple complementary mechanisms for antibiotic resistance gene transfer both within and between cells.