Antidiabetic effect of an engineered bacterium Lactobacillus plantarum-pMG36e-GLP-1 in monkey model

Glucagon-like peptide-1(GLP-1)reduces postprandial hyperglycaemia,but its short half-life inhibits clinical application.The aim of the current study was to evaluate the treatment efforts of an engineered strain,Lactobacillus plantarum-pMG36e-GLP-1(L.plantarum-pMG36e-GLP-1),that continuously expresses GLP-1 in spontaneous type 2 diabetes mellitus(T2DM)monkeys.After 7 weeks of oral supplementation with L.plantarum-pMG36e-GLP-1,the fasting blood glucose(FPG)of monkeys was significantly(p<0.05)reduced to a normal level and only a small amount of weight was lost.The results of metagenomic sequencing showed that L.plantarum-pMG36e-GLP-1 caused a substantial(p<0.05)reduction in the intestinal pathogen Prevotella and marked enhancement of butyrate-producing Alistipes genera.According to the functional analysis using Kyoto Encyclopaedia of Genes and Genomes(KEGG)pathways,19 metabolism-related pathways were significantly enriched in T2DM monkeys after treatment with L.plantarum-pMG36e-GLP-1.LC-MS faecal metabolomics analysis found 41 significant differential metabolites(11 higher and 30 lower)in monkeys after treatment pathways linked to the metabolism of cofactors and vitamins were the most relevant.The present study suggests that L.plantarum-pMG36e-GLP-1 had an impact on the gut microbial composition and faecal metabolomic profile in spontaneous T2DM monkeys and may be a novel candidate for diabetes treatment.

Quantification of parametric uncertainty in c-Reh model for typical flat plate and airfoil transitional flows

Owing to the lack of physical knowledge of boundary layer transition,the c-Reh transi-tion model introduces closure parameters,which increase the uncertainty of transition prediction.The objective of this work is to quantify the uncertainties of closure parameters in the quantities of interests and identify the key parameters.The six closure parameters in the uncertainty intervals are used as input variables,and the uncertainties of the output results are propagated by a stochas-tic expansion based on the point-collocation nonintrusive polynomial chaos method.The relative contribution of each parameter to uncertainty is evaluated by the Sobol index.The computational cases include natural and bypass transitional flows on zero-pressure-gradient flat plates,and sub-sonic and transonic flows around airfoils.For most cases,c_(e2),c_(a2),and c_(a1)dominate the uncertainty,and the influence of r ht is also significant when the history effects of flow are evident.The contri-bution of parameters in airfoils is more complex than that in flat plates.The transonic airfoil case shows that flow separation dramatically changes the distribution of Sobol indices,which poses a challenge to the accurate prediction of transition.Generally,c_(e2)and c_(a2)are the key parameters of the c-Reh model.

酶祖先序列重建与定向进化

酶祖先序列重建是指通过计算机算法推导来自灭绝生物的祖先酶的氨基酸序列的技术。通常可分为6个步骤,依次为现代酶的核酸/氨基酸序列收集、多序列比对、系统发育树构建、祖先酶序列的计算机推测、基因克隆、酶学性质表征。该方法广泛应用于研究分子在行星时间尺度上对环境条件不断变化的适应性和进化机制。随着酶在生物催化领域中扮演越来越重要的角色,该方法逐渐成为研究酶序列、结构和功能关系的有力手段。同时,祖先酶大多具有温度稳定性、突变稳定性等特性,使其成为进一步定向进化的理想蛋白质支架。文中综述了酶祖先序列重建的计算机算法、应用和常用计算机软件,并结合最新研究进展,展望其在酶定向进化领域中的应用前景。