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Biology subjects

Mi, K.

Publications and source records attributed to Mi, K..

4 recordsLinked to original sources

RFW captures species-level full profile of metagenomic functions via integrating genome annotation information

Functional profiling on whole-metagenome shotgun sequencing (WMS) has made great contribution to the development of our understanding in microbe-host interactions. In this work, we revealed that severe microbial functional information loss of current functional profiling methods existed at both taxon-level and community-level. To correct the distortion brought by information incompleteness, we developed a new framework, RFW (Reference based functional profile inference on WMS), to infer microbial functional abundance on WMS through utilizing information from genome function annotation and WMS taxonomic profile. Furthermore, we built up a new algorithm for absolute abundance change quantification of microbial function between groups under RFW framework. By applying RFW to several datasets related to autism spectrum disorder and colorectal cancer, we revealed that RFW greatly renewed our knowledge in downstream analysis, including differential microbial function identification, association analysis between microbial function and host phenotype, etc. RFW are open-source and freely available at https://github.com/Xingyinliu-Lab/RFW.

microbiology↗

Experimental Evolution Reveals Redox State Modulates Mycobacterial Pathogenicity

Understanding how Mycobacterium tuberculosis has evolved into a professional pathogen is helpful in studying its pathogenesis and for designing vaccines. We investigated how the evolutionary adaptation of M. smegmatis mc251 to an important clinical stressor H2O2 allows bacteria undergo coordinated genetic mutations, resulting in increased pathogenicity. Whole-genome sequencing identified a mutation site in the fur gene, which caused increased expression of katG. Using a Wayne dormancy model, mc251 showed a growth advantage over its parental strain mc2155 in recovering from dormancy under anaerobic conditions. Meanwhile, the high level of KatG in mc251 was accompanied by a low level of ATP, which meant that mc251 is at a low respiratory level. Additionally, the redox-related protein Rv1996 showed different phenotypes in different specific redox states in M. smegmatis mc2155, mc251, M. bovis BCG and M. tuberculosis mc27000. In conclusion, our study shows that the same gene presents different phenotypes under different physiological conditions. This may partly explain why M. smegmatis and M. tuberculosis have similar virulence factors and signaling transduction systems such as two-component systems and sigma factors, but due to the different redox states in the corresponding bacteria, M. smegmatis is a nonpathogen, while M. tuberculosis is a pathogen. As mc251 overcomes its shortcomings of rapid removal, it can be potentially developed as a vaccine vector.

genetics↗

Exploration of clinical breakpoint of Danofloxacin for Glaesserella parasuis in plasma and in PELF

BackgroundTo establish the clinical breakpoint (CBP) of danofloxacin to G. parasuis, three cutoff values, including epidemiological cutoff value (ECV), pharmacodynamic cutoff value (COPD) and clinical cutoff value (COCL), was obtained in the present study. MethodsThe ECV was calculated using ECOFFinder base on MIC distribution of 347 G. parasuis collected from disease pigs. The COPD was established base on in vivo and ex vivo pharmacokinetic (PK) - pharmacodynamic (PD) modeling of danofloxacin both in plasma and pulmonary epithelial lining fluid (PELF) using Hill formula and Monte Carlo analysis. The COCL was established based on the relationship between possibility of cure (POC) and MIC in the clinical trials using "WindoW" approach, nonlinear regression and CART analysis. ResultsThe MIC50 and MIC90 of danofloxacin against 347 G. parasuis were 2 g/mL and 8 g/mL, respectively. The ECV value was set up as 8 g/mL using ECOFFinder. Concentration-time curve of danofloxacin indicated a two-compartment model for PK analysis. The PK parameters of the maximum concentration (Cmax) and area under concentration-time curve (AUC) in PELF were 3.67 {+/-} 0.25 g/mL and 24.28 {+/-} 2.70 h{middle dot}g/mL, higher than those in plasma (0.67 {+/-} 0.01g/mL and 4.47 {+/-} 0.51 h{middle dot}g/mL). The peak time (Tmax) in plasma was 0.23 {+/-} 0.07 h, shorter than that in PELF (1.61 {+/-} 0.15 h). The COPD in plasma and PELF were 0.125 g/mL and 0.5 g/mL, respectively. The COCL calculated by WindoW approach, nonlinear regression and CART analysis were 0.125[~]4 g/mL, 0.428 g/mL and 0.56 g/mL, respectively. The 0.5 g/mL was selected as eligible COCL. The ECV is much higher than the COPD and COCL, and the clinical breakpoint based on data in plasma was large different with that of in PELF. ConclusionsOur study firstly established three cutoff values of danofloxacin against G. parasuis. It suggested that epidemiological danofloxacin-resistant G. parasuis may lead to the ineffective treatment by danofloxacin. ImportanceG. parasuis, a gram-negative respiratory pathogen, can colonize in the upper respiratory tract in swine and cause Glassers disease. As the abuse of antibiotics, antimicrobial resistant G. parasuis emerged in different degrees, which brought serious threat to global economy and public health. Danofloxacin in quinolones are one of the best choices for treatment of G. parasuis infection, because of their strong bactericidal activity and good absorption into blood and great distribution in the lung. However, the clinical breakpoint (CBP) for danofloxacin against G. parasuis had not yet been established by clinical laboratory of standard Institute (CLSI) and European Commission of antimicrobial susceptibility testing (EUCAST). Our study firstly established three cutoff values of danofloxacin against G. parasuis. It suggested that epidemiological danofloxacin-resistant G. parasuis may lead to the ineffective treatment by danofloxacin.

microbiology↗

A framework for detecting and quantifying relationship alterations in microbial community

Dysbiosis of gut microbiota is associated with the pathogenesis of human disease. Observing shifts in the microbe abundance cannot fully reveal underlying perturbations. Examining the relationship alteration (RA) in microbiome between different healthy status provides additional hints about the pathogenesis of human disease. However, no methods were designed to directly detect and quantify the RA between different conditions. Here, we present PM2RA (Profile Monitoring for Microbial Relationship Alteration), an analysis framework to identify and quantify the microbial RAs. The performance of PM2RA were evaluated in synthetic data, and found to show higher specificity and sensitivity than the co-occurrence-based methods. Analyses of real microbial dataset show that PM2RA is robust for quantifying microbial RA across different datasets in several diseases. By applying PM2RA, we identified both previously reported and novel microbes implicated in multiple diseases. The PM2RA is implemented as a web-based application available at http://www.pm2ra-xingyinliulab.cn/.

microbiology↗