Gut microbes play a vital role in the health and disease of animals, especially in relation to pathogen infections. Chinchillas, ferrets, and marmots are commonly used as important laboratory animals for infectious disease research. Here, we studied the bacterial and fungal microbiota and discovered that chinchillas had higher alpha diversity and a higher abundance of bacteria compared to marmots and ferrets by using the metabarcoding of 16S rRNA genes and ITS2, coupled with co-occurrence network analysis. The dominant microbes varied significantly among the three animal species, particularly in the gut mycobiota. In the ferrets, the feces were dominated by yeast such as Rhodotorula and Kurtzmaniella, while in the chinchillas, we found Teunomyces and Penicillium dominating, and Acaulium, Piromyces, and Kernia in the marmots. Nevertheless, the dominant bacterial genera shared some similarities, such as Clostridium and Pseudomonas across the three animal species. However, there were significant differences observed, such as Vagococcus and Ignatzschineria in the ferrets, Acinetobacter and Bacteroides in the chinchillas, and Bacteroides and Cellvibrio in the marmots. Additionally, our differential analysis revealed significant differences in classification levels among the three different animal species, as well as variations in feeding habitats that resulted in distinct contributions from the host microbiome. Therefore, our data are valuable for monitoring and evaluating the impacts of the microbiome, as well as considering potential applications.

PM_2.5, recognized as a potential pathogenic factor for nervous system diseases, remains an area with many unknowns, particularly regarding its effects on human health. After five-month real-ambient PM_2.5 exposure, we observed no significant pathological damage to the lung, liver, spleen, or kidney tissues. However, PM_2.5 exposure led to neuronal degeneration in the hippocampal CA1 region of Brown Norway (BN) rats. The level of IL-6, IL-13, IL-1β, IL-12, IL-4, GRO/KC, MIP-1α, CM-CSF significantly increased in lung lavage fluid (P < 0.05 for all). Notably, we detected a slight impairment in spatial learning ability, as evidenced by the Barnes maze training outcomes. There were no significant changes in the bacterial community in lung lavage fluid (P = 0.621), but the bacterial community in the gut significantly changed (P < 0.001), with more species identified (P < 0.05). The metabolomic analysis revealed 147 and 149 significantly changed metabolites in the pulmonary system and serum, respectively (P < 0.05). PM_2.5 exposure caused a decrease in Nervonic acid (NA) in both the lung and serum, which likely contributed to spatial learning impairment (P < 0.01). The correlation between lung metabolites, gut bacterial species, and serum metabolites indicated that PM_2.5 exposure likely impaired spatial learning through the lung-gut-brain axis pathway. Lung and serum metabolic disorders and intestinal microbial imbalance occurred in BN rats post-five-month real-ambient PM_2.5 exposure. There were two potential ways that PM_2.5 exposure caused the decline of spatial learning ability in wild-type BN rats: (1) PM_2.5 exposure led to a significant decrease of neuroprotective Nervonic acid in lung and serum metabolites. (2) PM_2.5 exposure likely led to reduced spatial learning ability through the lung-gut-brain axis.

Since the outbreak of COVID-19 in 2019, the 2019-nCov coronavirus has appeared diverse mutational characteristics due to its own flexible conformation. One multiple-mutant strain (Omicron) with surprisingly infective activity outburst, and affected the biological activities of current drugs and vaccines, making the epidemic significantly difficult to prevent and control, and seriously threaten health around the world. Importunately exploration of mutant characteristics for novel coronavirus Omicron can supply strong theoretical guidance for learning binding mechanism of mutant viruses. What’s more, full acknowledgement of key mutated-residues on Omicron strain can provide new methodology of the novel pathogenic mechanism to human ACE2 receptor, as well as the subsequent vaccine development. In this research, 3D structures of 32 single-point mutations of 2019-nCov were firstly constructed, and 32-sites multiple-mutant Omicron were finally obtained based one the wild-type virus by homology modeling method. One total number of 33 2019-nCov/ACE2 complex systems were acquired by protein-protein docking, and optimized by using preliminary molecular dynamics simulations. Binding free energies between each 2019-nCov mutation system and human ACE2 receptor were calculated, and corresponding binding patterns especially the regions adjacent to mutation site were analyzed. The results indicated that one total number of 6 mutated sites on the Omicron strain played crucial role in improving binding capacities from 2019-nCov to ACE2 protein. Subsequently, we performed long-term molecular dynamic simulations and protein-protein binding energy analysis for the selected 6 mutations. 3 infected individuals, the mutants T478K, Q493R and G496S with lower binding energies − 66.36, -67.98 and − 67.09 kcal/mol also presents the high infectivity. These findings indicated that the 3 mutations T478K, Q493R and G496S play the crucial roles in enhancing binding affinity of Omicron to human ACE2 protein. All these results illuminate important theoretical guidance for future virus detection of the Omicron epidemic, drug research and vaccine development.

Context: Since the outbreak of COVID-19 in 2019, the 2019-nCov coronavirus has appeared diverse mutational characteristics due to its own flexible conformation. One multiple-mutant strain (Omicron) with surprisingly infective activity outburst, and affected the biological activities of current drugs and vaccines, making the epidemic significantly difficult to prevent and control, and seriously threaten health around the world. Importunately exploration of mutant characteristics for novel coronavirus Omicron can supply strong theoretical guidance for learning binding mechanism of mutant viruses. What’s more, full acknowledgement of key mutated-residues on Omicron strain can provide new methodology of the novel pathogenic mechanism to human ACE2 receptor, as well as the subsequent vaccine development. Methods: In this research, 3D structures of 32 single-point mutations of 2019-nCov were firstly constructed, and 32-sites multiple-mutant Omicron were finally obtained based one the wild-type virus by homology modeling method. One total number of 33 2019-nCov/ACE2 complex systems were acquired by protein-protein docking, and optimized by using preliminary molecular dynamic simulations. Binding free energies between each 2019-nCov mutation system and human ACE2 receptor were calculated, and corresponding binding patterns especially the regions adjacent to mutation site were analyzed. The results indicated that one total number of 6 mutated sites on the Omicron strain played crucial role in improving binding capacities from 2019-nCov to ACE2 protein. Subsequently, we performed long-term molecular dynamic simulations and protein-protein binding energy analysis for the selected 6 mutations. 3 infected individuals, the mutants T478K, Q493R and G496S with lower binding energies -66.36, -67.98 and -67.09 kcal/mol also presents the high infectivity. These findings indicated that the 3 mutations T478K, Q493R and G496S play the crucial roles in enhancing binding affinity of Omicron to human ACE2 protein. All these results illuminate important theoretical guidance for future virus detection of the Omicron epidemic, drug research and vaccine development.