Date Published: March 14, 2019
Publisher: Public Library of Science
Author(s): Zachary M. Burcham, Carl J. Schmidt, Jennifer L. Pechal, Christopher P. Brooks, Jason W. Rosch, M. Eric Benbow, Heather R. Jordan, Brenda A. Wilson.
Population-based public health data on antibiotic resistance gene carriage is poorly surveyed. Research of the human microbiome as an antibiotic resistance reservoir has primarily focused on gut associated microbial communities, but data have shown more widespread microbial colonization across organs than originally believed, with organs previously considered as sterile being colonized. Our study demonstrates the utility of postmortem microbiome sampling during routine autopsy as a method to survey antibiotic resistance carriage in a general population. Postmortem microbial sampling detected pathogens of public health concern including genes for multidrug efflux pumps, carbapenem, methicillin, vancomycin, and polymixin resistances. Results suggest that postmortem assessments of host-associated microbial communities are useful in acquiring community specific data while reducing selective-participant biases.
Antibiotic resistance (AR) mechanisms are creating an enormous clinical and financial burden on healthcare systems worldwide, and have greatly contributed to newly emerging pathogens, epidemics, and pandemics [1–3]. In the US, the CDC reports that at least 2 million people become infected with antibiotic resistant bacteria each year, and at least 23,000 people die as a result of those infections . Furthermore, a WHO report issued in May 2014 estimated a yearly cost of $21 to $34 billion attributed to AR within the US healthcare system alone, with 8 million additional days spent in the hospital .
All but one case yielded detection of ARGs associated with activity against multiple antibiotic classes. Macrolide resistance genes were most common in qPCR assays, while multidrug efflux pumps were common in metagenomes. However, both tetracycline and beta-lactam resistance genes were widely detected. Additionally, we detected clinically relevant ARGs associated with polymixins, carbapenem, vancomycin, and methicillin resistance. Differences between the two methods is likely due to the specific targeting of 84 genes in the qPCR assay while the metagenomic sequence alignment detected all genes in the CARD. Additionally, when comparing the two methods, qPCR assays can detect specific genes in lower abundances than sequencing due to the nature of targeted amplicon amplification of qPCR while sequencing can miss low abundance genes. Metagenomic sequencing is beneficial in that it can detect a broad range of genes, and qPCR detection is beneficial for relatively rapid and specific gene detection. Both of these methods can yield valuable surveillance data depending upon whether the research goal is to determine which genes are present in a population (sequencing), or if determining the abundance of a specific array of genes (qPCR) is the aim. However, underreporting of ARGs could occur from both methods. Underreporting can occur with qPCR assays as this method focuses on specific genes and gene detection is often based on semi-quantitative data. Underreporting in sequence data can be limited by sequencing depth and the database being used. It is also important to note that our qPCR analysis focused on DNA pooled from multiple body sites while sequencing analysis focused on the brain space. Therefore, it is not completely clear the extent to which body site affects which ARGs are detected and in what abundance. However, our methodology allowed detection of known ARGs of concern in body sites besides the human gut, which has largely been the resistome study focus.