Integrating short- and full-length 16S rRNA gene sequencing to elucidate microbiome profiles in Pacific white shrimp (Litopenaeus vannamei) ponds.

Abstract

Despite their immense economic value as a key aquaculture species, the production of Pacific white shrimp (Litopenaeus vannamei) faces significant challenges from intensive farming practices and disease outbreaks. Routine microbial profiling for disease surveillance could be a promising approach to anticipate and control disease outbreaks. To achieve this, accuracy in microbial profiling in shrimp ponds is crucial for enabling targeted action and prevention. Extensive documentation emphasizes that, beyond biological factors (related to the host, diet, or health status during the rearing period), technical elements, including sequencing techniques significantly influence bacterial community profiling. This study investigated the influence of short- and long-read sequencing of 16S rRNA genes on the microbial profiles in shrimp intestines, water, and sediments. The origin of the samples (intestine or environmental) in shrimp culture ponds primarily drove the observed differences in core microbial species. The ecological niches accounted for 56% of bacterial community variations in culture ponds. Both sequencing approaches showed consistent results in identifying higher-rank taxa and assessing alpha and beta diversity. However, at the species level, full-length 16S rRNA gene sequences provided better resolution than V3-V4 sequences. For routine microbial profiling in shrimp culture ponds, our study suggests that short-read sequences were sufficient for determining overall bacterial community.IMPORTANCEThis interdisciplinary study investigated the influence of sequencing techniques on bacterial communities profiling within Pacific white shrimp (Litopenaeus vannamei) ponds. By integrating aquaculture, microbiology, and environmental science, we revealed the role of ecological niches and factors like salinity and pH on microbiota diversity and composition in shrimp intestines, pond water, and sediment. Additionally, we compared the taxonomic resolution using partial versus full-length 16S rRNA gene sequences, highlighting the value of longer amplicons for precise identification of key taxa. These findings provide novel insights into microbial dynamics underlying environmental effects in shrimp aquaculture. Comprehensive characterization of the pond microbiome could lead to management strategies that promote shrimp health and productivity. Furthermore, the potential of a multi-omics approach for integrating complementary data streams to elucidate environment-microbiome-host interactions was highlighted.