Background Sub-lakes are important for the maintenance of the ecosystem integrity of Lake Poyang, and zooplankton play an important role in its substance and energy flow. Methods A seasonal investigation of zooplankton was conducted in spring (April), summer (July), autumn (October) and winter (January of the following year) from 2012 to 2016 in a sub-lake of Lake Poyang. The aim of the present study was to understand the seasonal dynamics and interannual variation of zooplankton communities and their relationship to environmental factors. Results A total of 115 species were identified in all samples in the four years, which comprised of 87 Rotifera, 13 Cladocera and 15 Copepoda. Rotifera was the dominant group in terms of quantity, and its species richness and abundance were significantly higher when compared to Cladocera and Copepoda (P < 0.05), while Cladocera dominated in terms of biomass. The species richness of Rotifera exhibited a significant seasonal difference (P < 0.05). Both the density and biomass of zooplankton revealed significant seasonal differences (P < 0.05). In general, the density and biomass of zooplankton were higher in summer and autumn, when compared to winter and spring. Biodiversity indices were dramatically lower in spring than in the other seasons. The non-metric multidimensional scaling (NMDS) analysis suggested that these zooplankton communities can be divided into three groups: spring community, summer-autumn community, and winter community. The seasonal succession of zooplankton communities did not have interannual reproducibility. In high water level years, the dominant species of zooplankton (Cladocerans and Copepods) in the wet season had a lower density, and the result in low water level years was exactly the opposite. The redundancy analysis revealed that water temperature (WT), conductivity, pH and dissolved oxygen (DO) had significant effects on the zooplankton community. Conclusions The community structure of zooplankton has a significant seasonal pattern, but has no interannual repeatability. In high water level years, the dominant species of zooplankton (Cladocerans and Copepods) in the wet season had a lower density, and the result in low water level years was exactly the opposite. The density, biomass and diversity indices of zooplankton were significantly different in different seasons. The present study was helpful in the further understanding of the ecosystem stability of lakes connected with rivers, providing scientific guidance for the protection of lake wetlands.

The growth of all methanogens is limited to a specific temperature range. However, Methanothermobacter thermautotrophicus can be found in a variety of natural and artificial environments, the temperatures of which sometimes even exceed the temperature growth ranges of thermophiles. As a result, the extent to which methane production and survival are affected by temperature remains unclear. To investigate the mechanisms of methanogenesis that Archaea have evolved to cope with drastic temperature shifts, the responses of Methanothermobacter thermautotrophicus to temperature were investigated under a high temperature growth (71°C) and cold shock (4°C) using Isobaric tags for relative and absolute quantitation (iTRAQ). The results showed that methane formation is decreased and that protein folding and degradation are increased in both high‐ and low‐temperature treatments. In addition, proteins predicted to be involved in processing environmental information processing and in cell membrane/wall/envelope biogenesis may play key roles in affecting methane formation and enhancing the response of M. thermautotrophicus to temperature stress. Analysis of the genomic locations of the genes corresponding to these temperature‐dependent proteins predicted that 77 of the genes likely to form 32 gene clusters. Here, we assess the response of M. thermautotrophicus to different temperatures and provide a new level of understanding of methane formation and cellular putative adaptive responses.

To explore the differences in the nutritional quality of the muscles of bighead carp from different environments and aquaculture systems, we investigated three types of water bodies typically used for aquaculture: A common culture pond (NC), a natural lake (PY), and a cold water reservoir (XHK). Parameters affecting quality were evaluated, including muscle microstructure, fatty acid profiles, amino acid profiles, and volatile compounds. Fish from the XHK reservoir had the smallest muscle fiber diameter and the highest muscle fiber density (25.3 fibers/0.01 mm 2 ), while muscle fiber density was lowest in fish from the NC pond (9.7 fibers/0.01 mm 2 ). The bighead carp from the XHK reservoir had a much wider variety of unsaturated fatty acids, as well as higher levels of total polyunsaturated fatty acids. Eicosapentaenoic acid (EPA), docosahexenoic acid (DHA), and arachidonic acid (AA) were all significantly more abundant in the XHK group, increases of 7.48%, 12.12%, and 17.49%, respectively ( P < 0.05). The bighead carp from NC contained more “fishy” volatile flavor substances, as well as hydrocarbons with higher threshold values. Fish from XHK and NC had a greater umami intensity due to the presence of abundant volatiles with special aromas, including 1-Octene-3ol, DL-Menthol, and 2-ethyl-.

Two metallothionein genes (HsMT1 and HsMT2) were first identified and described from Hyriopsis schlegelii. The open reading frame of HsMT1 and HsMT2 were 216 and 222 bp, encoding a protein of 71 and 73 amino acid residues. The deduced amino acid sequences showed they contained parts of typical MT characteristics, apart from HsMT2 lacked Cys-Cys motifs. The phylogenetic tree showed HsMT1 shared a high similarity with that of other molluscs, but HsMT2 was split into a distinct group separated from known molluscan MTs. HsMT1 exhibited constitutive expression in all examined tissues and the highest expression occurred in hepatopancreas, however, nearly all HsMT2 was just detected in gonad. After Cd exposure, their mRNA levels presented similar expression patterns. The transgenic bacteria of HsMT1 showed higher tolerance than HsMT2 in Cd environment. It was implied that HsMT1 and HsMT2 were involved in metal response but HsMT2 might have other physiological functions.

The commercial aquatic animal microbiome may markedly affect the successful host's farming in various aquaculture systems. However, very little was known about it. Here, two different aquaculture systems, the rice–fish culture (RFC) and intensive pond culture (IPC) systems, were compared to deconstruct the skin, oral, and gut microbiome, as well as the gut metabolome of juvenile Chinese softshell turtle (Pelodiscus sinensis). Higher alpha‐diversity and functional redundancy of P. sinensis microbial community were found in the RFC than those of the IPC. The aquaculture systems have the strongest influence on the gut microbiome, followed by the skin microbiome, and finally the oral microbiome. Source‐tracking analysis showed that the RFC's microbial community originated from more unknown sources than that of the IPC across all body regions. Strikingly, the RFC's oral and skin microbiome exhibited a significantly higher proportion of generalists and broader habitat niche breadth than those of the IPC, but not the gut. Null model analysis revealed that the RFC's oral and skin microbial community assembly was governed by a significantly greater proportion of deterministic processes than that of the IPC, but not the gut. We further identified the key gene and microbial contribution to five significantly changed gut metabolites, 2‐oxoglutarate, N‐acetyl‐d‐mannosamine, cis‐4‐hydroxy‐d‐proline, nicotinamide, and l‐alanine, which were significantly correlated with important categories of microbe‐mediated processes, including the amino acid metabolism, GABAergic synapse, ABC transporters, biosynthesis of unsaturated fatty acids, as well as citrate cycle. Moreover, different aquaculture systems have a significant impact on the hepatic lipid metabolism and body shape of P. sinensis. Our results provide new insight into the influence of aquaculture systems on the microbial community structure feature and assembly mechanism in an aquatic animal, also highlighting the key microbiome and gene contributions to the metabolite variation in the gut microbiome‐metabolome association.