Exploiting the gut microbiota to predict the origins and quality traits of cultured sea cucumbers

"Candidatus Intestinibacterium parameciiphilum"-member of the "Candidatus Paracaedibacteraceae" family (Alphaproteobacteria, Holosporales) inhabiting the ciliated protist Paramecium

Protists frequently host diverse bacterial symbionts, in particular those affiliated with the order Holosporales (Alphaproteobacteria). All characterised members of this bacterial lineage have been retrieved in obligate association with a wide range of eukaryotes, especially multiple protist lineages (e.g. amoebozoans, ciliates, cercozoans, euglenids, and nucleariids), as well as some metazoans (especially arthropods and related ecdysozoans). While the genus Paramecium and other ciliates have been deeply investigated for the presence of symbionts, known members of the family "Candidatus Paracaedibacteraceae" (Holosporales) are currently underrepresented in such hosts. Herein, we report the description of "Candidatus Intestinibacterium parameciiphilum" within the family "Candidatus Paracaedibacteraceae", inhabiting the cytoplasm of Paramecium biaurelia. This novel bacterium is almost twice as big as its relative "Candidatus Intestinibacterium nucleariae" from the opisthokont Nuclearia and does not present a surrounding halo. Based on phylogenetic analyses of 16S rRNA gene sequences, we identified six further potential species-level lineages within the genus. Based on the provenance of the respective samples, we investigated the environmental distribution of the representatives of "Candidatus Intestinibacterium" species. Obtained results are consistent with an obligate endosymbiotic lifestyle, with protists, in particular freshwater ones, as hosts. Thus, available data suggest that association with freshwater protists could be the ancestral condition for the members of the "Candidatus Intestinibacterium" genus.

Meta-analysis of wastewater microbiome for antibiotic resistance profiling

The microbial composition and stress molecules are main drivers influencing the development and spread of antibiotic resistance bacteria (ARBs) and genes (ARGs) in the environment. A reliable and rapid method for identifying associations between microbiome composition and resistome remains challenging. In the present study, secondary metagenome data of sewage and hospital wastewaters were assessed for differential taxonomic and ARG profiling. Subsequently, Random Forest (RF)-based ML models were used to predict ARG profiles based on taxonomic composition and model validation on hospital wastewaters. Total ARG abundance was significantly higher in hospital wastewaters (15 ppm) than sewage (5 ppm), while the resistance towards methicillin, carbapenem, and fluoroquinolone were predominant. Although, Pseudomonas constituted major fraction, Streptomyces, Enterobacter, and Klebsiella were characteristic of hospital wastewaters. Prediction modeling showed that the relative abundance of pathogenic genera Escherichia, Vibrio, and Pseudomonas contributed most towards variations in total ARG count. Moreover, the model was able to identify host-specific patterns for contributing taxa and related ARGs with >90% accuracy in predicting the ARG subtype abundance. More than >80% accuracy was obtained for hospital wastewaters, demonstrating that the model can be validly extrapolated to different types of wastewater systems. Findings from the study showed that the ML approach could identify ARG profile based on bacterial composition including 16S rDNA amplicon data, and can serve as a viable alternative to metagenomic binning for identification of potential hosts of ARGs. Overall, this study demonstrates the promising application of ML techniques for predicting the spread of ARGs and provides guidance for early warning of ARBs emergence.

Stochastic Assembly Increases the Complexity and Stability of Shrimp Gut Microbiota During Aquaculture Progression

The gut microbiota of aquaculture species contributes to their food metabolism and regulates their health, which has been shown to vary during aquaculture progression of their hosts. However, limited research has examined the outcomes and mechanisms of these changes in the gut microbiota of hosts. Here, Kuruma shrimps from the beginning, middle, and late stages of aquaculture progression (about a time duration of 2 months between each stage) were collected and variations in the gut microbiota of Kuruma shrimp during the whole aquaculture process were examined. High-throughput sequencing demonstrated increases in the diversity and richness of the shrimp gut microbiota with aquaculture progression. In addition, the gut microbiota composition differed among cultural stages, with enrichment of Firmicutes, RF39, and Megamonas and a reduction in Proteobacteria in the mid-stage. Notably, only very few taxa were persistent in the shrimp gut microbiota during the whole aquaculture progression, while the number of taxa that specific to the end of aquaculture was high. Network analysis revealed increasing complexity of the shrimp gut microbiota during aquaculture progression. Moreover, the shrimp gut microbiota became significantly more stable towards the end of aquaculture. According to the results of neutral community model, contribution of stochastic processes for shaping the shrimp gut microbiota was elevated along the aquaculture progression. This study showed substantial variations in shrimp gut microbiota during aquaculture progression and explored the underlying mechanisms regulating these changes.

Succession and assembly mechanisms of seawater prokaryotic communities along an extremely wide salinity gradient

Salinity is an important environmental factor in microbial ecology for affecting the microbial communities in diverse environments. Understanding the salinity adaptation mechanisms of a microbial community is a significant issue, while most previous studies only covered a narrow salinity range. Here, variations in seawater prokaryotic communities during the whole salt drying progression (salinity from 3% to 25%) were investigated. According to high-throughput sequencing results, the diversity, composition, and function of seawater prokaryotic communities varied significantly along the salinity gradient, expressing as decreased diversity, enrichment of some halophilic archaea, and powerful nitrate reduction in samples with high salt concentrations. More importantly, a sudden and dramatic alteration of prokaryotic communities was observed when salinity reached 16%, which was recognized as the change point. Combined with the results of network analysis, we found the increasing of complexity but decreasing of stability in prokaryotic communities when salinity exceeded the change point. Moreover, prokaryotic communities became more deterministic when salinity exceeded the change point due to the niche adaptation of halophilic species. Our study showed that substantial variations in seawater prokaryotic communities along an extremely wide salinity gradient, and also explored the underlying mechanisms regulating these changes.

Unveiling the early life core microbiome of the sea cucumber Apostichopus japonicus and the unexpected abundance of the growth-promoting Sulfitobacter

BACKGROUND

Microbiome in early life has long-term effects on the host's immunological and physiological development and its disturbance is known to trigger various diseases in host Deuterostome animals. The sea cucumber Apostichopus japonicus is one of the most valuable marine Deuterostome invertebrates in Asia and a model animal in regeneration studies. To understand factors that impact on host development and holobiont maintenance, host-microbiome association has been actively studied in the last decade. However, we currently lack knowledge of early life core microbiome during its ontogenesis and how it benefits the host's growth.

RESULTS

We analyzed the microbial community in 28 sea cucumber samples from a laboratory breeding system, designed to replicate aquaculture environments, across six developmental stages (fertilized eggs to the juvenile stage) over a three years-period to examine the microbiomes' dynamics and stability. Microbiome shifts occurred during sea cucumber larval ontogenesis in every case. Application of the most sophisticated core microbiome extraction methodology, a hybrid approach with abundance-occupancy core microbiome analyses (top 75% of total reads and > 70% occupation) and core index calculation, first revealed early life core microbiome consisted of Alteromonadaceae and Rhodobacteraceae, as well as a stage core microbiome consisting of pioneer core microbe Pseudoalteromonadaceae in A. japonicus, suggesting a stepwise establishment of microbiome related to ontogenesis and feeding behavior in A. japonicus. More interestingly, four ASVs affiliated to Alteromonadaceae and Rhodobacteraceae were extracted as early life core microbiome. One of the ASV (ASV0007) was affiliated to the Sulfitobactor strain BL28 (Rhodobacteraceae), isolated from blastula larvae in the 2019 raring batch. Unexpectedly, a bioassay revealed the BL28 strain retains a host growth-promoting ability. Further meta-pangenomics approach revealed the BL28 genome reads were abundant in the metagenomic sequence pool, in particular, in that of post-gut development in early life stages of A. japonicus.

CONCLUSION

Repeated rearing efforts of A. japonicus using laboratory aquaculture replicating aquaculture environments and hybrid core microbiome extraction approach first revealed particular ASVs affiliated to Alteromonadaceae and Rhodobacteraceae as the A. japonicus early life core microbiome. Further bioassay revealed the growth promoting ability to the host sea cucumber in one of the core microbes, the Sulfitobactor strain BL28 identified as ASV0007. Genome reads of the BL28 were abundant in post-gut development of A. japonicus, which makes us consider effective probiotic uses of those core microbiome for sea cucumber resource production and conservation. The study also emphasizes the importance of the core microbiome in influencing early life stages in marine invertebrates. Understanding these dynamics could offer pathways to improve growth, immunity, and disease resistance in marine invertebrates.

Temporal stability and assembly mechanisms of gut microbiota in sea cucumbers response to nanoplastics treatment

Aquaculture provides essential food for humans, and the health of farmed species is particularly important for the aquaculture industry. Aquaculture environment could be a sink of plastic debris (PDs) due to the enclosed character and heavy use of plastics. Gut microbiota of aquaculture species could respond to the exogenous pollutants and regulate the health of hosts. Here, variations in gut microbiota of Apostichopus japonicus induced by the ingested nanoplastics (NPs) were investigated by a lab experiment. We selected a NPs concentration gradient of 100 mg/kg and 500 mg/kg to simulate microplastic pollution to A. japonicus, and the significant differences in gut microbiota composition after 21 days of NP exposure were evaluated. According to the high-throughput sequencing from time series samples, a decrease of diversity in gut microbiota of A. japonicus with dietary NPs was observed. In addition, the gut microbiota compositions of sea cucumbers with and without NPs exposure were also distinct, expressing as enrichment of Bacteroidota while reducement of Proteobacteria under NPs stresses. Combined the results of network analysis, the less complexity and stability of gut microbiota in sea cucumbers with dietary NPs were proved. Based on the neutral community model, the ingested NPs elevated the contribution of stochastic processes for the gut microbiota assembly in sea cucumbers. Our study showed that substantial variations in gut microbiota of A. japonicus under NPs stresses, and also explored the underlying mechanisms regulating these changes. This research would offer new meaningful insights into the toxicity of NPs on sea cucumbers, contributing a solid fundament to improve the health of sea cucumbers under NPs stresses.

Accurate prediction of huanglongbing occurrence in citrus plants by machine learning-based analysis of symbiotic bacteria

Huanglongbing (HLB), the most prevalent citrus disease worldwide, is responsible for substantial yield and economic losses. Phytobiomes, which have critical effects on plant health, are associated with HLB outcomes. The development of a refined model for predicting HLB outbreaks based on phytobiome markers may facilitate early disease detection, thus enabling growers to minimize damages. Although some investigations have focused on differences in the phytobiomes of HLB-infected citrus plants and healthy ones, individual studies are inappropriate for generating common biomarkers useful for detecting HLB on a global scale. In this study, we therefore obtained bacterial information from several independent datasets representing hundreds of citrus samples from six continents and used these data to construct HLB prediction models based on 10 machine learning algorithms. We detected clear differences in the phyllosphere and rhizosphere microbiomes of HLB-infected and healthy citrus samples. Moreover, phytobiome alpha diversity indices were consistently higher for healthy samples. Furthermore, the contribution of stochastic processes to citrus rhizosphere and phyllosphere microbiome assemblies decreased in response to HLB. Comparison of all constructed models indicated that a random forest model based on 28 bacterial genera in the rhizosphere and a bagging model based on 17 bacterial species in the phyllosphere predicted the health status of citrus plants with almost 100% accuracy. Our results thus demonstrate that machine learning models and phytobiome biomarkers may be applied to evaluate the health status of citrus plants.

Different living environments drive deterministic microbial community assemblages in the gut of Alpine musk deer (Moschus chrysogaster)

Substantial variation in the environment directly causes remodeling of the colonized gut microbiota, controlling community diversity, and functions in the host to tune-up their adaptive states. However, the mechanisms of microbial community assembly in response to environmental changes remain unclear, especially in endangered ruminants. In this study, we analyzed the microbial communities of 37 fecal samples collected from captive and wild Alpine musk deer (Moschus chrysogaster) to characterize the complexity and assembly processes using 16S rRNA gene sequencing. We found significantly different diversities and compositions of gut microbiota among both groups associated with different living environments. Heterogeneous selection was the predominant factor regulating the gut microbiota community under similar climatic conditions, indicating that microbial community assembly was largely driven by deterministic mechanisms. The species co-occurrence network showed complex and tight connections with a higher positive correlation in the wild environment. Moreover, the captive group exhibited significant differences in chemoheterotrophy and fermentation compared with the wild group, but the opposite was observed in animal parasites or symbionts, which might be closely related to diet, energy supply, and healthcare of animals. This study provides a framework basis and new insights into understanding gut microbiota in different environments.

Predicting the abundance of metal resistance genes in subtropical estuaries using amplicon sequencing and machine learning

Heavy metals are a group of anthropogenic contaminants in estuary ecosystems. Bacteria in estuaries counteract the highly concentrated metal toxicity through metal resistance genes (MRGs). Presently, metagenomic technology is popularly used to study MRGs. However, an easier and less expensive method of acquiring MRG information is needed to deepen our understanding of the fate of MRGs. Thus, this study explores the feasibility of using a machine learning approach-namely, random forests (RF)-to predict MRG abundance based on the 16S rRNA amplicon sequenced datasets from subtropical estuaries in China. Our results showed that the total MRG abundance could be predicted by RF models using bacterial composition at different taxonomic levels. Among them, the relative abundance of bacterial phyla had the highest predicted accuracy (71.7 %). In addition, the RF models constructed by bacterial phyla predicted the abundance of six MRG types and nine MRG subtypes with substantial accuracy (R² > 0.600). Five bacterial phyla (Firmicutes, Bacteroidetes, Patescibacteria, Armatimonadetes, and Nitrospirae) substantially determined the variations in MRG abundance. Our findings prove that RF models can predict MRG abundance in South China estuaries during the wet season by using the bacterial composition obtained by 16S rRNA amplicon sequencing.

Host Species Influence the Gut Microbiota of Endemic Cold-Water Fish in Upper Yangtze River

The fish gut microbiome plays an important role in nutrition absorption and energy metabolism. Studying the gut microbes of cold-water fish is important to understand the dietary adaptation strategies in extreme environments. In this study, the gut samples of Schizothorax wangchiachii (SW, herbivorous), Schizothorax kozlovi (SK, omnivorous), and Percocypris pingi (PP, carnivorous) in the upper Yangtze River were collected, and we sequenced 16S rRNA amplicon to study the potential relationship between gut microbes and host species. The results showed that gut microbial composition and diversity were significantly different between the three cold-water fishes. These fishes had different key taxa in their gut microbes, including bacteria involved in the breakdown of food (e.g., Cetobacterium, Aeromonas, and Clostridium sensu stricto 10). The highest alpha diversity indices (e.g., Chao 1 index) were identified in the herbivore (SW), followed by the carnivore (PP), and the lowest in the omnivore (SK). Non-metric multidimensional scaling (NMDS) results revealed that the gut microbial community of these species was different between host species. The neutral community model (NCM) showed that the microbial community structure of SW was shaped by stochastic processes, and the highest species dispersal was found in SW, followed by PP, and the lowest in SK. The results of niche breadth agreed with these findings. Our results demonstrated that host species influenced the gut microbiome composition, diversity, and microbial community assembly processes of the three cold-water fishes. These findings implied that the variation of gut microbiome composition and function plays a key role in digesting and absorbing nutrients from different foods in cold-water fish.