Rearing water microbiomes in white leg shrimp (Litopenaeus vannamei) larviculture assemble stochastically and are influenced by the microbiomes of live feed products

Abstract

The development of effective management strategies to reduce the occurrence of diseases in aquaculture is hampered by the limited knowledge on the microbial ecology of these systems. In this study, the dynamics and dominant community assembly processes in the rearing water of Litopenaeus vannamei larviculture tanks were determined. Additionally, the contribution of peripheral microbiomes, such as those of live and dry feeds, to the rearing water microbiome were quantified. The community assembly in the hatchery rearing water over time was dominated by stochasticity, which explains the observed heterogeneity between replicate cultivations. The community undergoes two shifts that match with the dynamics of the algal abundances in the rearing water. Source tracking analysis revealed that 37% of all bacteria in the hatchery rearing water were introduced either by the live or dry feeds, or during water exchanges. The contribution of the microbiome from the algae was the largest, followed by that of the Artemia, the exchange water and the dry feeds. Our findings provide fundamental knowledge on the assembly processes and dynamics of rearing water microbiomes and illustrate the crucial role of these peripheral microbiomes in maintaining health-promoting rearing water microbiomes.

Predicting the presence and abundance of bacterial taxa in environmental communities through flow cytometric fingerprinting

“…In this study, we used published flow cytometry and 16S rRNA gene amplicon data from an 18-day sampling campaign in a L. vannamei hatchery where five replicate cultivations were studied (Heyse et al ., 2021). The replicate cultivation tanks were sampled at a resolution of 3 hours for flow cytometry and once per day for 16S rRNA gene sequencing.…”

“…These disease outbreaks are not caused by the presence of a pathogen alone, but rather by complex changes in the microbial community structure (Lemire et al ., 2015; Dai et al ., 2020; Huang et al ., 2020; Infante-villamil et al ., 2020). Additionally, the onset of mortality typically occurs very fast (Lucas et al ., 2010; Heyse et al ., 2021). Fast and high-throughput monitoring of bacterial community composition is a first step to mitigate the disease outbreaks, and is therefore a crucial aspect for microbial management.…”

“…(Rubbens et al ., 2020). Standalone community level metrics such as diversity or stability may be difficult to interpret, and, therefore, to couple to specific management actions, because of the high bacterial heterogeneity and fast dynamics that are typically observed in aquaculture microbiomes (Schmidt et al ., 2017; Chun et al ., 2018; Heyse et al ., 2021). Additionally, different pathogens or dysbiotic states may require a different treatment.…”

“…In this study, we used a combination of previous published flow cytometry and 16S rRNA gene amplicon data from a L. vannamei hatchery (Heyse et al, 2021) and new generated 16S rRNA gene amplicon data on sorted sub-communities of samples originating from this previous study. This dataset is referred to as the “aquaculture dataset”.…”

“…In this study, we aimed to further integrate 16S rRNA gene amplicon sequencing and flow cytometry survey data in order to construct models that enable the prediction of both the presence and the abundance of multiple individual bacterial taxa in mixed communities using flow cytometric fingerprinting (Figure 1). As a case study, we used samples taken from a whiteleg shrimp ( Litopenaeus vannamei ) hatchery of which the dynamics have been previously described (Heyse et al ., 2021). We first verified the taxonomic stratification in the cytometric fingerprints using cell sorting.…”