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Geology topics

Allison R. Cauvin

Publications and source records attributed to Allison R. Cauvin.

2 recordsLinked to original sources

Assessment of antibiotic resistance genes in Caribbean corals, including those treated with amoxicillin

The decimation of reefs from stony coral tissue loss disease prompted the use of a topical amoxicillin treatment to prevent coral mortality. Application of this treatment led to concerns about unintentional impacts such as potential alteration of the coral microbiome and possible spread of antibiotic resistance. We used three different methodologies—microbial RNA sequencing, 16S rRNA amplicon surveys, and microbial qPCR array—to assess these concerns and to establish a baseline of antibiotic resistance genes (ARGs) in untreated coral microbes. We conducted microbial RNA sequencing on wild Montastraea cavernosa coral mucus samples collected before and 24 h after amoxicillin application. While diverse antibiotic resistance genes (ARGs) were expressed, no differences in ARG expression were detected after amoxicillin treatment. Additionally, there were no notable changes in the microbial communities between the before and after samples. In a separate experiment, a microbial qPCR array was used to assess differences in ARGs over longer timescales using cores from wild Colpophyllia natans , comparing never-treated corals with ones treated a single time seven months prior and with those treated multiple times seven months and more prior. No clinically relevant ARGs were detected across any samples. A small number of above-detection reads (4 in the never-treated corals, 2 in the once-treated corals, and 0 in the multi-treated corals) may indicate weak amplification of similar environmental (non-anthropogenic) ARGs in the corals. Results indicate that the localized topical application of amoxicillin to prevent mortality of SCTLD-affected corals does not: (1) significantly disrupt microbiomes, (2) increase ARG expression in adjacent tissues of these species within 24 h, nor (3) increase abundance of clinically relevant ARGs over a 7 month time period.

Florida

Environmental DNA metabarcoding read numbers and their variability predict species abundance, but weakly in non-dominant species

Metabarcoding of environmental DNA (eDNA) provides more comprehensive, efficient, and non-invasive sampling of biological communities than conventional methods. However, limitations of metabarcoding include taxon-specific biases in amplification and sequencing that distort assessments of community composition. Further, hyper-abundant species may disproportionately affect community composition assessments and impair the detection of rare species (i.e., “species masking”). In this study, we examine methodological approaches to improve eDNA metabarcoding assessments of community structure using fish community diversity in a pond in south Florida using MiFish primers modified to improve cichlid detection. Mitochondrial 12S eDNA amplicon sequencing via Illumina NovaSeq was analyzed using the DADA2 model-based exact sequence inference. The fish species and abundances in the system were recorded during piscicide treatment and subsequent native species restocking. Our results demonstrate that (1) ultra-high-throughput sequencing on the newer NovaSeq patterned flow cell provided reliable detection of very rare taxa—with detections of a single individual. (2) Read numbers were significantly correlated to the total surface area of the fish population, and numerical abundance to a lesser degree; however, dominant taxa largely drove those correlations, and simulations showed that biases in the most abundant taxa will have disproportionate effects on the strength of the correlation. (3) The read number coefficient of variation for each species across spatially separated replicate samples may provide less biased abundance estimates compared with estimates based on average read counts. Finally, (4) exact sequence inference detected multiple haplotypes and population genetic diversity within a species. Our results demonstrate the real-world metabarcoding capacity to reveal community structure and reliably detect rare species and unique haplotypes and shows that read numbers can, to a limited degree, be used to infer the size of fish populations. Careful examination of detection biases among dominant taxa and spatial variation among samples are required for rigorous eDNA-based estimates of community structure. Our results demonstrate the capacity of NovaSeq metabarcoding to reveal freshwater fish community structure and reliably detect rare species and unique haplotypes. Metabarcoding read numbers were significantly correlated to the total surface area of the fish species' populations, allowing for conditional inferences of population sizes. However, dominant taxa largely drove those correlations, and simulations indicated that biases toward the most abundant taxa will have disproportionate effects on the strength of the correlation.

Florida