Evaluating nanopore sequencing for microbial community characterization in catfish pond water.

Autor: Older, Caitlin E., Richardson, Bradley M., Wood, Monica, Waldbieser, Geoffrey C., Ware, Cynthia, Griffin, Matt J., Ott, Brian D.
Předmět:
Zdroj: Journal of the World Aquaculture Society; Feb2024, Vol. 55 Issue 1, p289-301, 13p
Abstrakt: In the United States, catfish are primarily farmed in earthen ponds, resulting in an aquatic environment influenced both by management practices and natural ecological processes. Profiling pond water microbiota can be useful for understanding what conditions may lead to microbial communities associated with production issues and could inform management practices. The aim of this study was to identify appropriate methods for bacterial community profiling of catfish pond water with nanopore sequencing of the 16S rRNA gene. To this end, two forward primers, two reverse primers, and three different polymerase chain reaction (PCR) cycle numbers were tested on a mock community consisting of aquaculture‐relevant bacteria. The optimized protocol was applied to water samples obtained from three experimental catfish ponds sampled in May, June, August, and September 2020. Applying these methods to pond samples allowed for the identification of 1488 genera, primarily within four dominating phyla: Actinobacteriota, Bacteroidota, Cyanobacteria, and Firmicutes. High variation was observed between individual ponds and sampling timepoints; only 18 of the 1488 genera were found in relative abundances ≥1% in all ponds from at least one sampling point. Despite this variation, consistent results could be observed. Samples obtained from the month of September had the highest number of observed genera, and samples from June had the lowest. Overall, these data demonstrated individual ponds represent distinct microcosms composed of unique bacterial communities, although this pond effect was secondary to the influence of sampling month on pond community composition. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index