Detection of ESKAPE pathogens and Clostridioides difficile in Simulated Skin Transmission Events with Metagenomic and Metatranscriptomic Sequencing

Background Antimicrobial resistance is a significant global threat, posing major public health risks and economic costs to healthcare systems. Bacterial cultures are typically used to diagnose healthcare-acquired infections (HAI); however, culture-dependent methods provide limited presence/absence information and are not applicable to all pathogens. Next generation sequencing (NGS) has the capacity to detect a wide variety of pathogens, virulence elements, and antimicrobial resistance (AMR) signatures in healthcare settings without the need for culturing, but few research studies have explored how NGS could be used to detect viable human pathogen transmission events under different HAI-relevant scenarios. Methods The objective of this project was to assess the capability of NGS-based methods to detect the direct and indirect transmission of high priority healthcare-related pathogens. DNA was extracted and sequenced from a previously published study exploring pathogen transfer with simulated skin containing background microorganisms, which allowed for complementary culture and metagenomic analysis comparisons. RNA was also isolated from an additional set of samples to evaluate metatranscriptomic analysis methods at different concentrations. Results Using various analysis methods and custom reference databases, both pathogenic and non-pathogenic members of the microbial community were taxonomically identified. Virulence and AMR genes known to reside within the community were also routinely detected. Ultimately, pathogen abundance within the overall microbial community played the largest role in successful taxonomic classification and gene identification. Conclusions These results illustrate the utility of metagenomic analysis in clinical settings or for epidemiological studies, but also highlight the limits associated with the detection and characterization of pathogens at low abundance in a microbial community. ### Competing Interest Statement The authors have declared no competing interest. * HAI : Healthcare-acquired infections NGS : Next Generation Sequencing ESKAPE+C : Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter species and Clostridioides difficile CDC : Centers for Disease Control and Prevention AR : Antibiotic resistance AMR : Antimicrobial resistance ATCC : American Type Culture Collection CFU : Colony forming units PBS : Phosphate buffered saline mRNA : messenger ribonucleic acid mL : milliliter polymerase chain reaction : PCR Enterococcus faecium : E. faecium Enterobacter cloacae : E. cloacae Staphylococcus aureus : S. aureus Klebsiella pneumoniae : K. pneumoniae Klebsiella aerogenes : K. aerogenes Acinetobacter baumannii : A. baumannii Pseudomonas aeruginosa : P. aeruginosa Clostridioides difficile : C. difficile Brevibacterium linens : B. linens Corynebacterium matruchotii : C. matruchotii Cutibacterium acnes : C. acnes Escherichia coli : E. coli Lactobacillus gasseri : L. gasseri Micrococcus luteus : M. luteus Staphylococcus epidermidis : S. epidermidis Streptococcus pyogenes : S. pyogenes