Robust host source tracking building on the divergent and non-stochastic assembly of gut microbiomes in wild and farmed large yellow croaker

Host-microbiome interaction in fish and shellfish: An overview

The importance of the gut microbiome in the management of various physiological activities including healthy growth and performance of fish and shellfish is now widely considered and being studied in detail for potential applications in aquaculture farming and the future growth of the fish industry. The gut microbiome in all animals including fish is associated with a number of beneficial functions for the host, such as stimulating optimal gastrointestinal development, producing and supplying vitamins to the host, and improving the host's nutrient uptake by providing additional enzymatic activities. Besides nutrient uptake, the gut microbiome is involved in strengthening the immune system and maintaining mucosal tolerance, enhancing the host's resilience against infectious diseases, and the production of anticarcinogenic and anti-inflammatory compounds. Because of its significant role, the gut microbiome is very often considered an "extra organ," as it plays a key role in intestinal development and regulation of other physiological functions. Recent studies suggest that the gut microbiome is involved in energy homeostasis by regulating feeding, digestive and metabolic processes, as well as the immune response. Consequently, deciphering gut microbiome dynamics in cultured fish and shellfish species will play an indispensable role in promoting animal health and aquaculture productivity. It is mentioned that the microbiome community available in the gut tract, particularly in the intestine acts as an innovative source of natural product discovery. The microbial communities that are associated with several marine organisms are the source of natural products with a diverse array of biological activities and as of today, more than 1000 new compounds have been reported from such microbial species. Exploration of such new ingredients from microbial species would create more opportunities for the development of the bio-pharma/aquaculture industries. Considering the important role of the microbiome in the whole life span of fish and shellfish, it is necessary to understand the interaction process between the host and microbial community. However, information pertaining to host-microbiome interaction, particularly at the cellular level, gene expression, metabolic pathways, and immunomodulation mechanisms, the available literature is scanty. It has been reported that there are three ways of interaction involving the host-microbe-environment operates to maintain homeostasis in the fish and shellfish gut i.e. host intrinsic factors, the environment that shapes the gut microbiome composition, and the core microbial community present in the gut system itself has equal influence on the host biology. In the present review, efforts have been made to collect comprehensive information on various aspects of host-microbiome interaction, particularly on the immune system and health maintenance, management of diseases, nutrient uptake, digestion and absorption, gene expression, and metabolism in fish and shellfish.

Characteristics of Microbiota in Different Segments of the Digestive Tract of Lycodon rufozonatus

The gastrointestinal tract of animals contains microbiota, forming a complex microecosystem. Gut microbes and their metabolites can regulate the development of host innate and adaptive immune systems. Animal immune systems maintain intestinal symbiotic microbiota homeostasis. However, relatively few studies have been published on reptiles, particularly snakes, and even fewer studies on different parts of the digestive tracts of these animals. Herein, we used 16S rRNA gene sequencing to investigate the microbial community composition and adaptability in the stomach and small and large intestines of Lycodon rufozonatus. Proteobacteria, Bacteroidetes, and Firmicutes were most abundant in the stomach; Fusobacteria in the small intestine; and Proteobacteria, Bacteroidetes, Fusobacteria, and Firmicutes in the large intestine. No dominant genus could be identified in the stomach; however, dominant genera were evident in the small and large intestines. The microbial diversity index was significantly higher in the stomach than in the small and large intestines. Moreover, the influence of the microbial community structure on function was clarified through function prediction. Collectively, the gut microbes in the different segments of the digestive tract revealed the unique features of the L. rufozonatus gut microbiome. Our results provide insights into the co-evolutionary relationship between reptile gut microbiota and their hosts.

Network analysis reveals significant joint effects of microplastics and tetracycline on the gut than the gill microbiome of marine medaka

Microplastics could accumulate and enrich antibiotics in the aquatic environment. Despite this, the joint effects of microplastics and antibiotics on aquatic organisms are not clear. Here, we investigated the changes of microbial interactions in both gill and gut of marine medaka exposed to polystyrene microbeads (PS) and/or tetracycline for 30 days by using co-occurrence network analysis based on 16S rRNA gene amplicon sequences. We found that the single and combined effects of PS and tetracycline were more profound on the gut than on the gill microbiome. SourceTracker analysis showed that the relative contributions from the gill microbiome to the gut microbiome increased under combined exposure. Moreover, the combined exposure reduced the complexity and stability of the gut microbial network more than those induced by any single exposure, suggesting the synergistic effects of PS and tetracycline on the gut microbiome. The PS and tetracycline combined exposure also caused a shift in the keystone taxa of the gut microbial network. However, no similar pattern was found for gill microbial networks. Furthermore, single and combined exposure to PS and/or tetracycline altered the associations between the gut network taxa and indicator liver metabolites. Altogether, these findings enhanced our understanding of the hazards of the co-occurring environmental microplastics and antibiotics to the fish commensal microbiome.

Using machine learning models to predict the effects of seasonal fluxes on Plesiomonas shigelloides population density

Seasonal variations (SVs) affect the population density (PD), fate, and fitness of pathogens in environmental water resources and the public health impacts. Therefore, this study is aimed at applying machine learning intelligence (MLI) to predict the impacts of SVs on P. shigelloides population density (PDP) in the aquatic milieu. Physicochemical events (PEs) and PDP from three rivers acquired via standard microbiological and instrumental techniques across seasons were fitted to MLI algorithms (linear regression (LR), multiple linear regression (MR), random forest (RF), gradient boosted machine (GBM), neural network (NN), K-nearest neighbour (KNN), boosted regression tree (BRT), extreme gradient boosting (XGB) regression, support vector regression (SVR), decision tree regression (DTR), M5 pruned regression (M5P), artificial neural network (ANN) regression (with one 10-node hidden layer (ANN10), two 6- and 4-node hidden layers (ANN64), and two 5- and 5-node hidden layers (ANN55)), and elastic net regression (ENR)) to assess the implications of the SVs of PEs on aquatic PDP. The results showed that SVs significantly influenced PDP and PEs in the water (p < 0.0001), exhibiting a site-specific pattern. While MLI algorithms predicted PDP with differing absolute flux magnitudes for the contributing variables, DTR predicted the highest PDP value of 1.707 log unit, followed by XGB (1.637 log unit), but XGB (mean-squared-error (MSE) = 0.0025; root-mean-squared-error (RMSE) = 0.0501; R² =0.998; medium absolute deviation (MAD) = 0.0275) outperformed other models in terms of regression metrics. Temperature and total suspended solids (TSS) ranked first and second as significant factors in predicting PDP in 53.3% (8/15) and 40% (6/15), respectively, of the models, based on the RMSE loss after permutations. Additionally, season ranked third among the 7 models, and turbidity (TBS) ranked fourth at 26.7% (4/15), as the primary significant factor for predicting PDP in the aquatic milieu. The results of this investigation demonstrated that MLI predictive modelling techniques can promisingly be exploited to complement the repetitive laboratory-based monitoring of PDP and other pathogens, especially in low-resource settings, in response to seasonal fluxes and can provide insights into the potential public health risks of emerging pathogens and TSS pollution (e.g., nanoparticles and micro- and nanoplastics) in the aquatic milieu. The model outputs provide low-cost and effective early warning information to assist watershed managers and fish farmers in making appropriate decisions about water resource protection, aquaculture management, and sustainable public health protection.

Exogenous antibiotic resistance gene contributes to intestinal inflammation by modulating the gut microbiome and inflammatory cytokine responses in mouse

Dysregulation of the gut microbiota by environmental factors is associated with a variety of autoimmune and immune-mediated diseases. In addition, naturally-occurring extracellular antibiotic resistance genes (eARGs) might directly enter the gut via the food chain. However, following gut microbiota exposure to eARGs, the ecological processes shaping the microbiota community assembly, as well as the interplay between the microbiota composition, metabolic function, and the immune responses, are not well understood. Increasing focus on the One Health approach has led to an urgent need to investigate the direct health damage caused by eARGs. Herein, we reveal the significant influence of eARGs on microbiota communities, strongly driven by stochastic processes. How eARGs-stimulate variations in the composition and metabolomic function of the gut microbiota led to cytokine responses in mice of different age and sex were investigated. The results revealed that cytokines were significantly associated with immunomodulatory microbes, metabolites, and ARGs biomarkers. Cytokine production was associated with specific metabolic pathways (arachidonic acid and tryptophan metabolic pathways), as confirmed by ex vivo cytokine responses and recovery experiments in vivo. Furthermore, the gut microbial profile could be applied to accurately predict the degree of intestinal inflammation ascribed to the eARGs (area under the curve = 0.9616). The present study provided a comprehensive understanding of the influence of an eARGs on immune responses and intestinal barrier damage, shedding light on the interplay between eARGs, microbial, metabolites, and the gut antibiotic resistome in modulating the human immune system.

Midgut Bacterial Microbiota of 12 Fish Species from a Marine Protected Area in the Aegean Sea (Greece)

Fish microbiome science is progressing fast, but it is biased toward farmed or laboratory fish species against natural fish populations, which remain considerably underinvestigated. We analyzed the midgut bacterial microbiota of 45 specimens of 12 fish species collected from the Gyaros Island marine protected area (Aegean Sea, Greece). The species belong to seven taxonomic families and are either herbivores or omnivores. Mucosa midgut bacterial diversity was assessed by amplicon metabarcoding of the 16S rRNA V3-V4 gene region. A total of 854 operational taxonomic units (OTUs) were identified. In each fish species, between 2 and 18 OTUs dominated with cumulative relative abundance ≥ 70%. Most of the dominating bacterial taxa have been reported to occur both in wild and farmed fish populations. The midgut bacterial communities were different among the 12 fish species, except for Pagrus pagrus and Pagellus erythrinus, which belong to the Sparidae family. No differentiation of the midgut bacterial microbiota was found based on feeding habits, i.e., omnivorous vs. carnivorous. Comparing wild and farmed P. pagrus midgut bacterial microbiota revealed considerable variation between them. Our results expand the gut microbiota of wild fish and support the host species effect as the more likely factor shaping intestinal bacterial microbiota.

Exploring the interactions between the gut microbiome and the shifting surrounding aquatic environment in fisheries and aquaculture: A review

The rise of "new" sequencing technologies and the development of sophisticated bioinformatics tools have dramatically increased the study of the aquaculture microbiome. Microbial communities exist in complex and dynamic communities that play a vital role in the stability of healthy ecosystems. The gut microbiome contributes to multiple aspects of the host's physiological health status, ranging from nutritional regulation to immune modulation. Although studies of the gut microbiome in aquaculture are growing rapidly, the interrelationships between the aquaculture microbiome and its aquatic environment have not been discussed and summarized. In particular, few reviews have focused on the potential mechanisms driving the alteration of the gut microbiome by surrounding aquatic environmental factors. Here, we review current knowledge on the host gut microbiome and its interrelationship with the microbiome of the surrounding environment, mainly including the main methods for characterizing the gut microbiome, the composition and function of microbial communities, the dynamics of microbial interactions, and the relationship between the gut microbiome and the surrounding water/sediment microbiome. Our review highlights two potential mechanisms for how surrounding aquatic environmental factors drive the gut microbiome. This may deepen the understanding of the interactions between the microbiome and environmental factors. Lastly, we also briefly describe the research gaps in current knowledge and prospects for the future orientation of research. This review provides a framework for studying the complex relationship between the host gut microbiome and environmental stresses to better facilitate the widespread application of microbiome technologies in fisheries and aquaculture.