Microbial and Transcriptomic Profiling Reveals Diet-Related Alterations of Metabolism in Metabolic Disordered Mice

Metabolic disorders are the prelude of metabolic diseases, which are mainly due to the high-energy intake and genetic contribution. High-fat diet (HFD) or high-sucrose diet is widely used for inducing metabolic disorders characterized by increased body weight, insulin resistance, hepatic steatosis, and alteration of gut microbiome. However, the triangle relationship among diets, gut microbiome, and host metabolism is poorly understood. In our study, we investigated the dynamic changes in gut microbiota, and host metabolism in mice that were fed with either chow diet, HFD, or chow diet with 30% sucrose in drinking water (HSD) for continued 12 weeks. The gut microbiota was analyzed with 16S rDNA sequencing on feces. Hepatic gene expression profile was tested with transcriptomics analysis on liver tissue. The host metabolism was evaluated by measuring body weight, insulin sensitivity, serum lipids, and expression of proteins involved in lipid metabolism of liver. The results showed that HFD feeding affected body weight, insulin resistance, and hepatic steatosis more significantly than HSD feeding. 16S rRNA gene sequencing showed that HFD rapidly and steadily suppressed species richness, altered microbiota structure and function, and increased the abundance of bacteria responsible for fatty acid metabolism and inflammatory signaling. In contrast, HSD had minor impact on the overall bacteria structure or function but activated microbial bile acid biosynthesis. Fecal microbiota transplantation suggested that some metabolic changes induced by HFD or HSD feeding were transferrable, especially in the weight of white adipose tissue and hepatic triglyceride level that were consistent with the phenotypes in donor mice. Moreover, transcriptomic results showed that HFD feeding significantly inhibited fatty acid degradation and increase inflammation, while HSD increased hepatic de novo lipogenesis and inhibited primary bile acid synthesis alternative pathway. In general, our study revealed the dynamic and diversified impacts of HFD and HSD on gut microbiota and host metabolism

Technology and Application of Salty Slurry Harmlessness Reduction and Resource Utilization Treatment

Salt slurry is a special sludge produced in the process of brine purification in chlor-alkali industry. In order to eliminate the harm of salty slurry to the environment and realize its economic value, a salty slurry harmlessness, reduction and resource utilization treatment method was proposed. Through this method, salty slurry will be transformed into desulfurizer with its water content and Cl- content reduced to 15% and 0.5% respectively. This method has been applied to projects, bringing environmental and economic benefits

Rapid bacteria identification using structured illumination microscopy and machine learning

Traditionally, optical microscopy is used to visualize the morphological features of pathogenic bacteria, of which the features are further used for the detection and identification of the bacteria. However, due to the resolution limitation of conventional optical microscopy as well as the lack of standard pattern library for bacteria identification, the effectiveness of this optical microscopy-based method is limited. Here, we reported a pilot study on a combined use of Structured Illumination Microscopy (SIM) with machine learning for rapid bacteria identification. After applying machine learning to the SIM image datasets from three model bacteria (including Escherichia coli, Mycobacterium smegmatis, and Pseudomonas aeruginosa), we obtained a classification accuracy of up to 98%. This study points out a promising possibility for rapid bacterial identification by morphological features

Gut microbiota remodeling improves natural aging-related disorders through Akkermansia muciniphila and its derived acetic acid

Accumulating evidence indicates gut microbiota contributes to aging-related disorders. However, the exact mechanism underlying gut dysbiosis-related pathophysiological changes during aging remains largely unclear. In the current study, we first performed gut microbiota remodeling on old mice by fecal microbiota transplantation (FMT) from young mice, and then characterized the bacteria signature that was specifically altered by FMT. Our results revealed that FMT significantly improved natural aging-related systemic disorders, particularly exerted hepatoprotective effects, and improved glucose sensitivity, hepatosplenomegaly, inflammaging, antioxidative capacity and intestinal barrier. Moreover, FMT particularly increased the abundance of fecal A.muciniphila, which was almost nondetectable in old mice. Interestingly, A.muciniphila supplementation also exerted similar benefits with FMT on old mice. Notably, targeted metabolomics on short chain fatty acids (SCFAs) revealed that only acetic acid was consistently reversed by FMT. Then, acetic acid intervention exerted beneficial actions on both Caenorhabditis elegans and natural aging mice. In conclusion, our current study demonstrated that gut microbiota remodeling improved natural aging-related disorders through A.muciniphila and its derived acetic acid, suggesting that interventions with potent stimulative capacity on A. muciniphila growth and production of acetic acid was alternative and effective way to maintain healthy aging. Data availability statement: The data of RNAseq and 16 S rRNA gene sequencing can be accessed in NCBI with the accession number PRJNA848996 and PRJNA849355

Application of Dynamic 18F-FDG PET/CT for Distinguishing Intrapulmonary Metastases from Synchronous Multiple Primary Lung Cancer

It has been a big challenge to distinguish synchronous multiple primary lung cancer (sMPLC) from primary lung cancer with intrapulmonary metastases (IPM). We aimed to assess the clinical application of dynamic 18F-FDG PET/CT in patients with multiple lung cancer nodules. We enrolled patients with multiple pulmonary nodules who had undergone dynamic 18F-FDG PET/CT and divided them into sMPLC and IPM groups based on comprehensive features. The SUVmax, fitted Ki value based on dynamic scanning, and corresponding maximum diameter (Dmax) from the two largest tumors were determined in each patient. We determined the absolute between-tumor difference of SUVmax/Dmax and Ki/Dmax (ΔSUVmax/Dmax; ΔKi/Dmax) and assessed the between-group differences. Further, the diagnostic accuracy was evaluated by ROC analysis and the correlation between ΔSUVmax/Dmax and ΔKi/Dmax from all groups was determined. There was no significant difference for ΔSUVmax/Dmax between the IPM and sMPLC groups, while the IPM group had a significantly higher ΔKi/Dmax than the sMPLC group. The AUC of ΔKi/Dmax for differentiating sMPLC from IPM was 0.80 (cut-off value of Ki=0.0059, sensitivity 79%, specificity 75%, p0.05). Dynamic 18F-FDG PET/CT could be a useful tool for distinguishing sMPLC from IPM. Ki calculation based on Patlak graphic analysis could be more sensitive than SUVmax in discriminating IPM from sMPLC in patients with multiple lung cancer nodules