With demands and reliance on aquaculture still growing, there are various challenges to allow sustainable growth and the shift from fishmeal (FM) to other protein sources in aquafeed formulations is one of the most important. In this regard, interest in the use of insect meal (IM) in aquafeeds has grown rapidly. Accordingly, the aim of the present study was to assess the effects of dietary IM from Hermetia illucens (Hi) larvae included in a low-FM diet on gut microbial communities of rainbow trout (Oncorhynchus mykiss), in terms of both composition and function of microbiome. A feeding trial was conducted using 192 trout of about 100-g mean initial weight. Fish were fed in quadruplicate (4 tanks/diet) for 131 days with two diets: the control (Ctrl) contained 20% of FM as well as other protein sources, whereas the Hi diet contained 15% of Hi larvae meal to replace 50% of the FM contained in the Ctrl diet. High-throughput sequencing of 16S rRNA gene was used to identify the major feed and gut bacterial taxa, whereas Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis was performed on gut bacterial genomes to identify the major active biological pathways. The inclusion of IM led to an increase in Firmicutes, mainly represented by Bacilli class and to a drastic reduction of Proteobacteria. Beneficial genera, such as Lactobacillus and Bacillus, were enriched in the gut of fish fed with the Hi diet, whereas the number of bacteria assigned to the pathogenic Aeromonas genus was drastically reduced in the same fish group. The metagenome functional data provided evidence that dietary IM inclusion can shape the metabolic activity of trout gut microbiota. In particular, intestinal microbiome of fish fed with IM may have the capacity to improve dietary carbohydrate utilization. Therefore, H. illucens meal is a promising protein source for trout nutrition, able to modulate gut microbial community by increasing the abundance of some bacteria taxa that are likely to play a key role in fish health.

Oxford Nanopore Technology (ONT) allows for the rapid profiling of aquaculture microbiomes. However, not all the experimental and downstream methodological possibilities have been benchmarked. Here, we aimed to offer novel insights into the use of different library preparation methods (standard-RAP and native barcoding-LIG), primers (V3–V4, V1–V3, and V1–V9), and basecalling models (fast-FAST, high-HAC, and super-accuracy-SUP) implemented in ONT to elucidate the microbiota associated with the aquatic environment and farmed fish, including faeces, skin, and intestinal mucus. Microbial DNA from water and faeces samples could be amplified regardless of the library–primer strategy, but only with LIG and V1–V3/V1–V9 primers in the case of skin and intestine mucus. Low taxonomic assignment levels were favoured by the use of full-length V1–V9 primers, though in silico hybridisation revealed a lower number of potential matching sequences in the SILVA database, especially evident with the increase in Actinobacteriota in real datasets. SUP execution allowed for a higher median Phred quality (24) than FAST (11) and HAC (17), but its execution time (6–8 h) was higher in comparison to the other models (0.6–7 h). Altogether, we optimised the use of ONT for water- and fish-related microbial analyses, validating, for the first time, the use of the LIG strategy. We consider that LIG–V1–V9-HAC is the optimal time/cost-effective option to amplify the microbial DNA from environmental samples. However, the use of V1–V3 could help to maximise the dataset microbiome diversity, representing an alternative when long amplicon sequences become compromised by microbial DNA quality and/or high host DNA loads interfere with the PCR amplification/sequencing procedures, especially in the case of gut mucus.

Gut microbiomes of fish species consist of thousands of bacterial taxa that interact among each other, their environment, and the host. These complex networks of interactions are regulated by a diverse range of factors, yet little is known about the hierarchy of these interactions. Here, we introduce SAMBA (Structure-Learning of Aquaculture Microbiomes using a Bayesian Approach), a computational tool that uses a unified Bayesian network approach to model the network structure of fish gut microbiomes and their interactions with biotic and abiotic variables associated with typical aquaculture systems. SAMBA accepts input data on microbial abundance from 16S rRNA amplicons as well as continuous and categorical information from distinct farming conditions. From this, SAMBA can create and train a network model scenario that can be used to (i) infer information of how specific farming conditions influence the diversity of the gut microbiome or pan-microbiome, and (ii) predict how the diversity and functional profile of that microbiome would change under other variable conditions. SAMBA also allows the user to visualize, manage, edit, and export the acyclic graph of the modelled network. Our study presents examples and test results of Bayesian network scenarios created by SAMBA using data from a microbial synthetic community, and the pan-microbiome of gilthead sea bream (Sparus aurata) in different feeding trials. It is worth noting that the usage of SAMBA is not limited to aquaculture systems as it can be used for modelling microbiome–host network relationships of any vertebrate organism, including humans, in any system and/or ecosystem.

The search for new alternatives for the revalorization of porcine blood is crucial due to the large quantities that are annually generated in slaughterhouses. In this study, a sequential enzymatic hydrolysis of pig blood was optimized using different combinations of the enzymes, namely, Alcalase 4.0 L and Protana™ Prime, Flavourzyme 1000 L, and Protamex^®, as a sustainable method for obtaining extracts rich in bioactive peptides. All the assayed hydrolysates exhibited different peptide profiles and showed in vitro antioxidant, hypoglycemic, and anti-inflammatory activity, although their values differed significantly depending on the type of hydrolysis in ABTS, FRAP, and ORAC assays, as well as in the determination of the inhibitory activity of DPP-IV, NEP, TACE, and MGL enzymes. The hydrolysate obtained by the combination of Alcalase 4.0 L, Flavourzyme 1000 L, and Protana™ Prime (AFPP) resulted in the highest hydrolysis degree (33.39 ± 0.98%), and its peptide profile reflected a higher amount of peptides < 3 kDa. This hydrolysate also obtained significantly higher values for ABTS and the inhibition of TACE and MGL. However, APP2 stood out in NEP inhibition (79.39 ± 3.91%), while APPP was notable for DPP-IV inhibition (43.02 ± 1.39%). The analysis of the hydrolysates using mass spectrometry in tandem allowed for the identification of those sequences that are potentially responsible for the biological activities determined, which were characterized using in silico bioinformatic tools. The results show the potential of using sequential enzymatic hydrolysis in porcine blood to obtain multifunctional peptides.

The significant microbiota variability represents a key feature that makes the full comprehension of the functional interaction between microbiota and the host an ongoing challenge. To overcome this limitation, in this study, fish intestinal microbiota was analyzed through a meta-analysis, identifying the core microbiota and constructing stochastic Bayesian network (BN) models with SAMBA. We combined three experiments performed with gilthead sea bream juveniles of the same hatchery batch, reared at the same season/location, and fed with diets enriched on processed animal proteins (PAP) and other alternative ingredients (NOPAP-PP, NOPAP-SCP). Microbiota data analysis disclosed a high individual taxonomic variability, a high functional homogeneity within trials and highlighted the importance of the core microbiota, clustering PAP and NOPAP fish microbiota composition. For both NOPAP and PAP BNs, >99% of the microbiota population were modelled, with a significant proportion of bacteria (55–69%) directly connected with the diet variable. Functional enrichment identified 11 relevant pathways expressed by different taxa across the different BNs, confirming the high metabolic plasticity and taxonomic heterogeneity. Altogether, these results reinforce the comprehension of the functional bacteria–host interactions and in the near future, allow the use of microbiota as a species-specific growth and welfare benchmark of livestock animals, and farmed fish in particular.

A confinement stress test with 75% tank space reduction and behavioural monitoring through tri-axial accelerometers externally attached to the operculum was designed. This procedure was validated by demonstrating the less pronounced stress response in gilthead sea bream than in European sea bass (950–1200 g). Our study aimed to assess habituation to high stocking densities with such procedure in gilthead sea bream. Animals (420–450 g) were reared (June–August) in a flow-through system at two stocking densities (CTRL: 10–15 kg/m³; HD: 18–24 kg/m³), with natural photoperiod and temperature (21–29 °C), and oxygen levels at 5.2–4.2 (CTRL) and 4.2–3.2 ppm (HD). At the end, blood and muscle were sampled for haematology and transcriptomic analyses, and external tissue damage was assessed by image-based scoring. Four days later, fish underwent a 45 min confinement stress test over two consecutive days. HD fish showed reduced feed intake, growth rates and haematopoietic activity. Muscle transcriptome changes indicated a shift from systemic to local growth regulation and a primed muscle regeneration over protein accretion in HD animals with slight external injuries. After stress testing, HD fish exhibited a decreased recovery time in activity and respiration rates, which was shorter after a second stressor exposure, confirming habituation to high densities.