Diet energy is a key component of pet food, but it is usually ignored during pet food development and pet owners also have limited knowledge of its importance. This study aimed to explore the effect of diet energy on the body condition, glucolipid metabolism, fecal microbiota and metabolites of adult beagles and analyze the relation between diet and host and gut microbiota. Eighteen healthy adult neutered male beagles were selected and randomly divided into three groups. Diets were formulated with three metabolizable energy (ME) levels: the low-energy (Le) group consumed a diet of 13.88 MJ/kg ME; the medium-energy (Me) group consumed a diet of 15.04 MJ/kg ME; and the high-energy (He) group consumed a diet of 17.05 MJ/kg ME. Moreover, the protein content of all these three diets was 29%. The experiment lasted 10 weeks, with a two-week acclimation period and an eight-week test phase. Body weight, body condition score (BCS), muscle condition score (MCS) and body fat index (BFI) decreased in the Le group, and the changes in these factors in the Le group were significantly higher than in the other groups (p < 0.05). The serum glucose and lipid levels of the Le and He groups changed over time (p < 0.05), but those of the Me group were stable (p > 0.05). The fecal pH of the Le and He groups decreased at the end of the trial (p < 0.05) and we found that the profiles of short-chain fatty acids (SCFAs) and bile acids (BAs) changed greatly, especially secondary BAs (p < 0.05). As SCFAs and secondary BAs are metabolites of the gut microbiota, the fecal microbiota was also measured. Fecal 16S rRNA gene sequencing found that the Me group had higher α-diversity indices (p < 0.05). The Me group had notably higher levels of gut probiotics, such as Faecalibacterium prausnitzii, Bacteroides plebeius and Blautia producta (p < 0.05). The diet–host–fecal microbiota interactions were determined by network analysis, and fecal metabolites may help to determine the best physical condition of dogs, assisting pet food development. Overall, feeding dogs low- or high-energy diets was harmful for glucostasis and promoted the relative abundance of pathogenic bacteria in the gut, while a medium-energy diet maintained an ideal body condition. We concluded that dogs that are fed a low-energy diet for an extended period may become lean and lose muscle mass, but diets with low energy levels and 29% protein may not supply enough protein for dogs losing weight.

Most zoonotic pathogens originate from mammals and avians, but viral diversity and related biosafety risk assessment in lower vertebrates also need to be explored. Amphibians are an important group of lower vertebrates that played a momentous role in animal evolution. To elucidate the diversity of RNA viruses in one important species of amphibians, the Asiatic toad (Bufo gargarizans), we obtained 44 samples including lung, gut, liver, and kidney tissues from Asiatic toads in Sichuan and Jilin provinces, China, for viral metagenomics sequencing. More than 20 novel RNA viruses derived from the order Bunyavirales and 7 families of Astroviridae, Dicistroviridae, Leviviridae, Partitiviridae, Picornaviridae, Rhabdoviridae, and Virgaviridae were discovered, which were distinct from previously described viruses and formed new clusters, as revealed by phylogenetic analyses. Notably, a novel bastrovirus, AtBastV/GCCDC11/2022, of the family Astroviridae was identified from the gut library, the genome of which contains three open reading frames, with the RNA-dependent RNA polymerase (RdRp) coded by ORF1 closely related to that of hepeviruses, and ORF2 encoding an astrovirus-related capsid protein. Notably, phenuiviruses were discovered for the first time in amphibians. AtPhenV1/GCCDC12/2022 and AtPhenV2/GCCDC13/2022 clustered together and formed a clade with the group of phenuiviruses identified from rodents. Picornaviruses and several invertebrate RNA viruses were also detected. These findings improve our understanding of the high RNA viral diversity in the Asiatic toad and provide new insights in the evolution of RNA viruses in amphibians.

Headspace–gas chromatography–ion mobility spectrometry (HS-GC-IMS) combined with chemometrics was employed to track volatile aroma compounds during the nine-steaming and nine-drying process. A total of 84 volatile signals (including monomers, dimers, and polymers) were tentatively identified, of which 73 volatile compounds were semi-quantified. Principal component analysis (PCA) revealed a mixed clustering pattern across cycles, indicating that unsupervised methods alone could not adequately resolve the volatile changes. A partial least squares discriminant analysis (PLS-DA) model supported clear chemical discrimination among the three hypothesized stages—early (cycles 1–3), middle (4–6), and late (7–9). Based on VIP > 1 and ANOVA (q < 0.05), 29 key differential compounds were screened and categorized into three dynamic groups (decreasing, transient, and accumulating), revealing three proposed transformation windows: green-grassy odor dissipation (cycles 1–3), roasted/malty aroma generation (cycles 4–6), and aroma stabilization via end-product accumulation (cycles 7–9). Relative odor activity value (ROAV) analysis revealed a decoupling between abundance and sensory impact: high-abundance Maillard products like maltol showed negligible ROAV (<0.0003), whereas esters and aldehydes dominated the ROAV profiles, suggesting their potential as important contributors to the fruity, sweet, and malty notes. The maltol/α-cedrol ratio (M/C) increased by an order of magnitude after the seventh steaming, and color parameters E*ab correlated negatively with ester accumulation. This study provides chemical insights and quantitative indicators for aroma quality control and process determination in black ginseng production.

The volatile compounds (VOCs) evolution of wild ginseng (WG) across growth years is not a unidirectional process but a divergent remodeling of the chemical fingerprint. In this study, HS-GC-IMS combined with chemometrics was employed to characterize the dynamic changes in VOCs in WG at four growth stages (10, 15, 20, and 25 years). Samples were collected from three independent sites, with ≥5 roots pooled per site per age group to obtain population-representative composite samples. A total of 68 VOCs were tentatively identified and semi-quantified. Terpenes and pyrazines exhibited the most pronounced directional trends: terpenes such as camphene, (E,E)-α-farnesene, and β-ionone accumulated progressively (increases of 242%, 74.6%, and 93.4%, respectively), whereas pyrazines showed an overall decline through distinct trajectories—2,3,5-trimethylpyrazine declined monotonically (57.3%), 2-ethyl-6-methylpyrazine decreased moderately (27.7%), and 2,5-dimethylpyrazine exhibited a transient peak at 20 years before a sharp terminal decline (52.3%). In contrast, the majority of compounds (66%) displayed non-monotonic patterns, underscoring the complexity of this divergent evolution. Partial least squares-discriminant analysis (PLS-DA) effectively distinguished samples across growth years (R²Y = 0.997, Q² = 0.993), with a 200-times permutation test confirming no overfitting. 29 differential compounds (VIP > 1) were identified. The divergent accumulation patterns of terpenes and pyrazines, together with 29 VIP-identified differential compounds, provide chemical evidence that the VOCs fingerprint could serve as a supplementary tool for growth-year assessment. These findings provide chemical evidence that WG flavor quality evolves divergently over time, suggesting that VOCs fingerprint could serve as a supplementary tool for growth-year assessment, particularly for “high-quality but poor-shape” specimens that are undervalued by traditional morphology-based methods.

The chemical composition and perceived quality of wild ginseng (WG) are influenced by its geographical origin, yet clear chemical criteria for origin authentication remain lacking, and this problem is further complicated by the confounding effect of growth year. In this study, volatile and non-volatile fingerprints of 15- and 20-year-old WG from Huanren, Tonghua, and Ji’an (China) were characterized using HS-GC-IMS and HPLC. Partial least squares discriminant analysis (PLS-DA) models constructed separately for each growth-year group achieved complete origin separation of volatile fingerprints, with ten shared VIP markers identified. However, none maintained a consistent origin ranking across years, suggesting that the geographical signal may reside in the multivariate patterns. Ginsenoside profiling revealed a hierarchical candidate marker system: Rf, Rg1, Rc, Rb2 as robust candidate markers for Huanren, and Re as a 20-year-specific discriminator for Tonghua. The pervasive origin × growth year interaction observed across both volatile and non-volatile fractions indicates that growth-year-specific chemometric models are a necessity for reliable WG origin authentication. A practical two-step workflow—growth year determination followed by age-matched origin assignment—is proposed. These findings provide a scientific foundation for the geographical traceability and quality evaluation of WG.