Reconstruction of the Genomes of Drug-Resistant Pathogens for Outbreak Investigation through Metagenomic Sequencing

The study results reported here perfectly demonstrate the power and promise of clinical metagenomics to recover genome sequences of important drug-resistant bacteria and to rapidly provide rich data that inform outbreak investigations and treatment decisions, independently of the need to culture the organisms.Culture-independent methods that target genome fragments have shown promise in identifying certain pathogens, but the holy grail of comprehensive pathogen genome detection from microbiologically complex samples for subsequent forensic analyses remains a challenge. In the context of an investigation of a nosocomial outbreak, we used shotgun metagenomic sequencing of a human fecal sample and a neural network algorithm based on tetranucleotide frequency profiling to reconstruct microbial genomes and tested the same approach using rectal swabs from a second patient. The approach rapidly and readily detected the genome of Klebsiella pneumoniae carbapenemase (KPC)-producing K. pneumoniae in the patient fecal specimen and in the rectal swab sample, achieving a level of strain resolution that was sufficient for confident transmission inference during a highly clonal outbreak. The analysis also detected previously unrecognized colonization of the patient by vancomycin-resistant Enterococcus faecium, another multidrug-resistant bacterium

Microbe-Metabolite Associations Linked to the Rebounding Murine Gut Microbiome Postcolonization with Vancomycin-Resistant Enterococcus faecium.

Vancomycin-resistant Enterococcus faecium (VREfm) is an emerging antibiotic-resistant pathogen. Strain-level investigations are beginning to reveal the molecular mechanisms used by VREfm to colonize regions of the human bowel. However, the role of commensal bacteria during VREfm colonization, in particular following antibiotic treatment, remains largely unknown. We employed amplicon 16S rRNA gene sequencing and metabolomics in a murine model system to try and investigate functional roles of the gut microbiome during VREfm colonization. First-order taxonomic shifts between Bacteroidetes and Tenericutes within the gut microbial community composition were detected both in response to pretreatment using ceftriaxone and to subsequent VREfm challenge. Using neural networking approaches to find cooccurrence profiles of bacteria and metabolites, we detected key metabolome features associated with butyric acid during and after VREfm colonization. These metabolite features were associated with Bacteroides, indicative of a transition toward a preantibiotic naive microbiome. This study shows the impacts of antibiotics on the gut ecosystem and the progression of the microbiome in response to colonization with VREfm. Our results offer insights toward identifying potential nonantibiotic alternatives to eliminate VREfm through metabolic reengineering to preferentially select for BacteroidesIMPORTANCE This study demonstrates the importance and power of linking bacterial composition profiling with metabolomics to find the interactions between commensal gut bacteria and a specific pathogen. Knowledge from this research will inform gut microbiome engineering strategies, with the aim of translating observations from animal models to human-relevant therapeutic applications