Bacterial community plays an important role in keeping the health status of the host. A study on the characteristics of gut bacterial community of sea cucumber (Apostichopus japonicus) not only helps improve the current aquaculture model, but promotes healthy and rapid development of the aquaculture industry as well. Therefore, taking pond‐cultured sea cucumber (A. japonicus) as the studying object, the metagenomic and 16S rRNA sequencing technology were used in this study to explore the characteristics of bacterial community in different parts of the gut of sea cucumber, as well as during gut regeneration after evisceration. The results showed that the compositions of bacterial community are different in varying parts of the gut of sea cucumber (A. japonicus). Specifically, bacterial community in the midgut and hindgut are highly similar, showing significantly diversified bacterial species compared to the foregut. GO annotation indicated that the foregut is associated with richer catalytic activity and binding than the midgut and the hindgut. According to the KEGG annotation, metabolism‐related genes are mainly concentrated in the foregut, while genes related to signal transduction and the immune system are mostly annotated in the midgut and hindgut. During the gut regeneration stage, the structure of bacterial community varied greatly in different stage of the regeneration stage, with significant differences between the earlier and later stage. The dominant bacteria in the earlier stage is Rubritalea, and that in the later stage is Arcobacter. Besides, there were Loktanella, Thalassobacter and Phaeobacter in the gut throughout the entire regeneration stage. Cupriavidus, Hellea, HTCC2207, Methylophaga, Methylotenera, Stenotrophomonas and Tenacibaculum were only present in the earlier stage, and gradually disappeared in the later stage due to improving gut functions. The abundance and diversity of bacteria in the gut were higher in the earlier regeneration stage than that in the later stage, with a peak between the 15th and 25th day of the regeneration stage. At 45th day, the abundance and diversity became stable.

This study investigated microbial community composition as well as their correlation with environmental factors of Apostichopus japonicus culture ponds in northern China by 16S rRNA gene amplicon sequencing. The results showed that microbiota richness varied consistently with diversity in the pond ecosystem. Microbiota richness and diversity were highest in sediment, followed by gut of A. japonicus and water. The dominant bacterial phylum in the pond ecosystem is Proteobacteria. Gammaproteobacteriaeria and Flavobacteria are two dominant bacterial classes in the ecosystem. There is significant difference (p < 0.05) between dominant bacterial communities at the levels of order, family and genus. There is also remarkable regional difference (p < 0.05) between microbial community composition in the pond ecosystems. Specifically, microbial community composition in Changhai and Yingkou show a high similarity, so do those of Laoting and Rushan. According to the redundancy analysis of the microbial community composition and pond environmental factors, chemical oxygen demand is the dominant environmental factor determining microbial community composition in pond water; sulphide has the greatest influence on the microbial community composition in pond sediment; the rest of environmental factors have varied influence on microbial community composition in pond ecosystems.

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Background: To construct and verify a novel prognostic model for thyroid cancer (THCA) based on N7-methylguanosine modification-related lncRNAs (m7G-lncRNAs) and their association with immune cell infiltration. Methods: In this study, we identified m7G-lncRNAs using co-expression analysis and performed differential expression analysis of m7G-lncRNAs between groups. We then constructed a THCA prognostic model, performed survival analysis and risk assessment for the THCA prognostic model, and performed independent prognostic analysis and receiver operating characteristic curve analyses to evaluate and validate the prognostic value of the model. Furthermore, analysis of the regulatory relationship between prognostic differentially expressed m7G-related lncRNAs (PDEm7G-lncRNAs) and mRNAs and correlation analysis of immune cells and risk scores in THCA patients were carried out. Results: We identified 29 N7-methylguanosine modification-related mRNAs and 116 differentially expressed m7G-related lncRNAs, including 87 downregulated and 29 upregulated lncRNAs. Next, we obtained 8 PDEm7G-lncRNAs. A final optimized model was constructed consisting of 5 PDEm7G-lncRNAs (DOCK9−DT, DPP4–DT, TMEM105, SMG7–AS1 and HMGA2–AS1). Six PDEm7G-lncRNAs (DOCK9–DT, DPP4–DT, HMGA2–AS1, LINC01976, MID1IP1–AS1, and SMG7–AS1) had positive regulatory relationships with 10 PDEm7G-mRNAs, while 2 PDEm7G-lncRNAs (LINC02026 and TMEM105) had negative regulatory relationships with 2 PDEm7G-mRNAs. Survival curves and risk assessment predicted the prognostic risk in both groups of patients with THCA. Forest maps and receiver operating characteristic curves were used to evaluate and validate the prognostic value of the model. Finally, we demonstrated a correlation between different immune cells and risk scores. Conclusion: Our results will help identify high-risk or low-risk patients with THCA and facilitate early prediction and clinical intervention in patients with high risk and poor prognosis.