Abstract
Microalgae are promising as prebiotics in aquaculture. Arthrospira maxima has potential nutritional value but is poorly studied. We assessed A. maxima feed supplementation in tilapia fry and evaluated its effect on growth performance and gut microbiota. Fish were cultivated in ponds under 0%, 5%, 10%, and 15% A. maxima inclusion treatments. Growth parameters and biomass proximate analysis were assessed. A meta-amplicon analysis was performed on the gut microbiota using DADA2 and PICRUST2 for functional prediction. Among treatments, the 5% supplementation group seemed to present no negative effect on growth parameters and did not compromise the nutritional quality of tilapia fry biomass. Microbial composition was characterized by Cetobacterium, Pseudomonas and Aeromonas genera, and a predominance of beneficial metabolic pathways. Microbiota of tilapia fry fed with A. maxima showed unique genera with reported beneficial functions in tilapia. The abundance of potential pathogenic taxa was significantly decreased in supplementation treatments, possibly related to valuable compounds of A. maxima. The inclusion of the microalgae supported the stability of the microbiota, favoring the growth of commensal species. This seems to have an effect on decreasing the presence of pathogenic genera in the gastrointestinal tract. Overall, our work proposes 5% feed inclusion of A. maxima to be the most suitable for tilapia fry aquaculture to maintain production rates while improving general health.
| Translated title of the contribution | Impacto de la suplementación alimenticia con Arthrospira maxima sobre la microbiota intestinal y el rendimiento del crecimiento de los alevines de tilapia (Oreochromis niloticus) |
|---|---|
| Original language | English |
| Article number | 374 |
| Number of pages | 21 |
| Journal | Fishes |
| Volume | 9 |
| Issue number | 10 |
| DOIs | |
| State | Published - 25 Sep 2024 |
Keywords
- aquaculture
- gastrointestinal microbiota
- meta-amplicon analysis
- microalgae supplementation
- microbiome profiling
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