Targeted overexpression of inducible 6-phosphofructo-2-kinase in adipose tissue increases fat deposition but protects against diet-induced insulin resistance and inflammatory responses

Increasing evidence demonstrates the dissociation of fat deposition, the inflammatory response, and insulin resistance in the development of obesity-related metabolic diseases. As a regulatory enzyme of glycolysis, inducible 6-phosphofructo-2-kinase (iPFK2, encoded by PFKFB3) protects against diet-induced adipose tissue inflammatory response and systemic insulin resistance independently of adiposity. Using aP2-PFKFB3 transgenic (Tg) mice, we explored the ability of targeted adipocyte PFKFB3/iPFK2 overexpression to modulate diet-induced inflammatory responses and insulin resistance arising from fat deposition in both adipose and liver tissues. Compared with wild-type littermates (controls) on a high fat diet (HFD), Tg mice exhibited increased adiposity, decreased adipose inflammatory response, and improved insulin sensitivity. In a parallel pattern, HFD-fed Tg mice showed increased hepatic steatosis, decreased liver inflammatory response, and improved liver insulin sensitivity compared with controls. In both adipose and liver tissues, increased fat deposition was associated with lipid profile alterations characterized by an increase in palmitoleate. Additionally, plasma lipid profiles also displayed an increase in palmitoleate in HFD-Tg mice compared with controls. In cultured 3T3-L1 adipocytes, overexpression of PFKFB3/iPFK2 recapitulated metabolic and inflammatory changes observed in adipose tissue of Tg mice. Upon treatment with conditioned medium from iPFK2-overexpressing adipocytes, mouse primary hepatocytes displayed metabolic and inflammatory responses that were similar to those observed in livers of Tg mice. Together, these data demonstrate a unique role for PFKFB3/iPFK2 in adipocytes with regard to diet-induced inflammatory responses in both adipose and liver tissues.     

Expressions and purification of a mature form of recombinant human Chemerin in Escherichia coli

Chemerin is a novel chemokine that binds to the G protein-coupled receptor (GPCR) ChemR23, also known as chemokine-like receptor 1 (CMKLR1). It is secreted as a precursor and executes pro-inflammatory functions when the last six amino acids are removed from its C-terminus by serine proteases. After maturation, Chemerin attracts dendritic cells and macrophages through binding to ChemR23. We report a new method for expression and purification of mature recombinant human Chemerin (rhChemerin) using a prokaryotic system. After being expressed in bacteria, rhChemerin in inclusion bodies was denatured using 6 M guanidine chloride. Soluble rhChemerin was prepared by the protein-specific renaturation solution under defined conditions. It was subsequently purified using ion-exchange columns to more than 95% purity with endotoxin level <1.0 EU/μg. We further demonstrated its biological activities for attracting migration of human dendritic cells and murine macrophages in vitro using established chemotaxis assays.     

宁夏蝗虫地理分布格局的聚类分析

根据宁夏的自然环境和行政区划将宁夏分为22个分布区域。为方便聚类分析,根据分布范围将宁夏蝗虫分为全布种(22个区域有分布)、多布种(2～21区域有分布)和独布种(只分布在1个区域)3类。在以分布区域为特征做聚类分析的基础上,把多布种分组并确定重叠的分布格局,共分为14个组。各组蝗虫在宁夏的自然分布作为其分布格局。结果表明：宁夏蝗虫的多布种多呈不连续分布;分布格局与国内外基本相似;贺兰山是宁夏蝗虫分布的热点。不连续的环境是造成宁夏蝗虫多布种不连续分布的主要原因。     

Assessing the limits of restraint-based 3D modeling of genomes and genomic domains

Restraint-based modeling of genomes has been recently explored with the advent of Chromosome Conformation Capture (3C-based) experiments. We previously developed a reconstruction method to resolve the 3D architecture of both prokaryotic and eukaryotic genomes using 3C-based data. These models were congruent with fluorescent imaging validation. However, the limits of such methods have not systematically been assessed. Here we propose the first evaluation of a mean-field restraint-based reconstruction of genomes by considering diverse chromosome architectures and different levels of data noise and structural variability. The results show that: first, current scoring functions for 3D reconstruction correlate with the accuracy of the models; second, reconstructed models are robust to noise but sensitive to structural variability; third, the local structure organization of genomes, such as Topologically Associating Domains, results in more accurate models; fourth, to a certain extent, the models capture the intrinsic structural variability in the input matrices and fifth, the accuracy of the models can be a priori predicted by analyzing the properties of the interaction matrices. In summary, our work provides a systematic analysis of the limitations of a mean-field restrain-based method, which could be taken into consideration in further development of methods as well as their applications.