Antibiotic resistance is prevalent in an isolated cave microbiome

Abstract

Antibiotic resistance is a global challenge that impacts all pharmaceutically used antibiotics. The origin of the genes associated with this resistance is of significant importance to our understanding of the evolution and dissemination of antibiotic resistance in pathogens. A growing body of evidence implicates environmental organisms as reservoirs of these resistance genes; however, the role of anthropogenic use of antibiotics in the emergence of these genes is controversial. We report a screen of a sample of the culturable microbiome of Lechuguilla Cave, New Mexico, in a region of the cave that has been isolated for over 4 million years. We report that, like surface microbes, these bacteria were highly resistant to antibiotics; some strains were resistant to 14 different commercially available antibiotics. Resistance was detected to a wide range of structurally different antibiotics including daptomycin, an antibiotic of last resort in the treatment of drug resistant Gram-positive pathogens. Enzyme-mediated mechanisms of resistance were also discovered for natural and semi-synthetic macrolide antibiotics via glycosylation and through a kinase-mediated phosphorylation mechanism. Sequencing of the genome of one of the resistant bacteria identified a macrolide kinase encoding gene and characterization of its product revealed it to be related to a known family of kinases circulating in modern drug resistant pathogens. The implications of this study are significant to our understanding of the prevalence of resistance, even in microbiomes isolated from human use of antibiotics. This supports a growing understanding that antibiotic resistance is natural, ancient, and hard wired in the microbial pangenome.

Figure 1. Plan and profile maps of Lechuguilla Cave, Carlsbad Caverns National Park, New Mexico.

The sites where microbial strains were collected (LCECE, LCDS1 and LCEA1) are shown relative to the entrance and depth. tN represents true North on the plan, while the profile has an exaggerated vertical profile of 1.5×.

Figure 2. Resistance levels of Lechuguilla cave bacteria at 20 µg/ml against various antibiotics: (top) Gram-positive strains (bottom) Gram-negative strains.

Antibiotics are grouped according to their mode of action/target, where each color represents a different target.

Figure 3. MIC of antibiotics determined in this study.

Heat Plot for (A) Gram-positive strains (B) Gram-negative strains against various antibiotics. Antibiotics are grouped according to their mode of action and the gradient from light blue to dark blue represents the range from lowest MIC value (0.3 µg/ml) to highest MIC value (256 µg/ml) as shown in the legend. White means no MIC was determined.

Figure 4. Inactivation of Telithromycin by B. paraconglomeratum strain LC44.

After incubation of B. paraconglomeratum in the presence of 20 µg/ml telithromycin, chemical modification was determined by the loss of antimicrobial activity of the clarified culture supernatant associated with modification of telithromycin as assessed by LC-MS. LC-MS analysis of the resulting inactive extract indicated a shift of retention time and an increase in m/z by 80 consistent with phosphorylation.

Figure 5. Induction of daptomycin resistance in Paenibacillus lautus LC231.

LC231 was cultured in TSB supplemented with 1.25 mM CaCl₂ and 4 µg/ml daptomycin added from start (zero time point) (1) or early log phase (2). Growth was compared to growth control with no drug (3). Arrow represents the time point at which daptomycin was added during early log phase.

Figure 6. Genetic context of mph genes in Brachybacterium strains.

A genetic map was constructed using available genome sequences of Brachybacterium strains and shown above is a schematic of translated protein query based on BLAST analysis. The MPH sequence is shown in red and homologous sequences are marked with identical colors.