Parasitic infestations present significant threats to the physiological health and ecological stability of aquatic species, frequently compromising immune defenses and elevating mortality rates. This study was conducted to elucidate the non-specific immune responses induced by Pallisentis (Neosentis) celatus infection in Monopterus albus, with a focus on intestinal histopathology and transcriptome gene expression. A histopathological examination revealed minor alterations in intestinal villi under low-level infection. A transcriptome analysis, performed using Illumina sequencing technology, identified 347 upregulated and 298 downregulated genes involved in critical biological pathways, such as lipid metabolism, immune responses, and the regulation of inflammatory processes. GO and KEGG analyses indicated the upregulation of immune-related pathways, including the RIG-I-like and IL-17 signaling pathways, highlighting a robust intestinal immune response. Conversely, the complement pathway was found to be downregulated, with significant suppression of C9, suggesting that the parasite may engage in immune evasion. Fluorescein-labeled C9 antibody assays confirmed reduced complement C9 levels in the infected tissues. A real-time PCR analysis identified the differential expression of eight genes, including C5, maats1, CFI, and gmnc, which were consistent with the sequencing results. These findings suggest that Pallisentis (Neosentis) celatus infection compromises intestinal health, induces inflammation, and activates non-specific immune responses in Monopterus albus. However, Pallisentis (Neosentis) celatus appears to evade the host immune response by suppressing the activation of complement components, thereby facilitating its reproductive parasitism.

To assess the applicability of environmental DNA (eDNA) technology in monitoring fish diversity in Dongting Lake, located in Hunan Province within the Yangtze River Basin, China, this study combined eDNA metabarcoding with traditional fishing gear to describe the diversity characteristics of the fish community in its habitat. Water samples were collected from 20 representative sites for eDNA analysis, followed by filtration, DNA extraction, and high-throughput sequencing targeting the 12S rDNA region. Concurrently, traditional fishing gear using gill nets and fish traps was conducted at the same locations. The results revealed 82 fish species detected by both methods combined, with eDNA alone identifying 21 species (including rare species encompassing Saurogobio gracilicaudatus and Glyptothorax sinense), while traditional fishing gear detected 27 species. Among the 82 fish species, a total of thirty-four species of fish could be observed in catches from both methods. In terms of α-diversity, eDNA showed higher Chao1, species richness, and ACE indices compared to traditional fishing gear, but lower Shannon and Simpson indices. eDNA was more sensitive to species richness, while traditional fishing gear was better at characterizing community evenness and diversity. β-Diversity analysis showed higher spatial similarity in the fish community structure detected by eDNA, while traditional fishing gear revealed significant differences between the upstream and downstream areas. In summary, eDNA technology has the advantages of non-invasiveness, high sensitivity and broad coverage, effectively serving as a valuable supplementary tool of traditional fishing gear, particularly in monitoring rare species. However, further improvements are needed in terms of species abundance quantification and database dependency. The combination of these two methods provides a more comprehensive scientific basis for fish resource conservation in Dongting Lake.

In the context of the ten-year fishing ban on the Yangtze River, illegal poaching for profit persists. To support the enforcement of this ban and protect the river’s ecosystem, an efficient and precise method for distinguishing between wild and farmed common carp is essential. This study utilized ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) combined with metabolomics technology to analyze and compare the metabolic differences between wild and farmed common carp. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) revealed a clear separation between the two groups, which was further verified by metabolic fingerprint profiles. Moreover, 16 metabolites with high discriminatory potential were identified from 491 differentially metabolites, such as phytosphingosine, succinic acid and threonine. In addition, a cluster analysis of the differential metabolites classified them into four classes: peptides, fatty acyls, steroids and steroid derivatives, and glycerophospholipids. Furthermore, candidate biomarkers, including 3-hydroxybutyrylcarnitine, 3-hydroxyhexanoylcarnitine and jasminoside were identified to potential distinguish wild populations. To our knowledge, this is the first study to apply metabolomics technology to differentiate wild from farmed common carp, providing a new theoretical basis for ecological restoration efforts in the context of the Yangtze River fishing ban.