BackgroundFibroblast growth factor 21 (FGF21) is a promising drug candidate to combat metabolic diseases. However, high-level expression and purification of recombinant FGF21 (rFGF21) in Escherichia coli (E. coli) is difficult because rFGF21 forms inclusion bodies in the bacteria making it difficult to purify and obtain high concentrations of bioactive rFGF21. To overcome this problem, we fused the FGF21 with SUMO (Small ubiquitin-related modifier) by polymerase chain reaction (PCR), and expressed the fused gene in E. coli BL21(DE3).ResultsBy inducing with IPTG, SUMO-FGF21 was expressed at a high level. Its concentration reached 30% of total protein, and exceeded 95% of all soluble proteins. The fused protein was purified by DEAE sepharose FF and Ni-NTA affinity chromatography. Once cleaved by the SUMO protease, the purity of rFGF21 by high performance liquid chromatography (HPLC) was shown to be higher than 96% with low endotoxin level (<1.0 EU/ml). The results of in vivo animal experiments showed that rFGF21 produced by using this method, could decrease the concentration of plasma glucose in diabetic rats by streptozotocin (STZ) injection.ConclusionsThis study demonstrated that SUMO, when fused with FGF21, was able to promote its soluble expression of the latter in E. coli, making it more convenient to purify rFGF21 than previously. This may be a better method to produce rFGF21 for pharmaceutical research and development.

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Swine erysipelas (SE) is one of the best-known and most serious diseases that affect domestic pigs, which is caused by Erysipelothrix rhusiopathiae. It is endemic in Nanning and has been circulating for decades, causing considerable economic losses. The aim of this study was to investigate the effect of meteorological-related variations on the epidemiology of swine erysipelas in Nanning City, a subtropical city of China. Data on monthly counts of reported swine erysipelas and climate data in Nanning are provided by the authorities over the period from 2006 to 2015. Cross-correlation analysis was applied to identify the lag effects of meteorological variables. A zero-inflated negative binomial (ZINB) regression model was used to evaluate the independent contribution of meteorological factors to SE transmission. After controlling seasonality, autocorrelation and lag effects, the results of the model indicated that Southern Oscillation Index (SOI) has a positive effect on SE transmission. Moreover, there is a positive correlation between monthly mean maximum temperature and relative humidity at 0-1 month lag and the number of cases. Furthermore, there is a positive association between the number of SE incidences and precipitation, with a lagged effect of 2 months. In contrast, monthly mean wind velocity negatively correlated with SE of the current month. These findings indicate that meteorological variables may play a significant role in SE transmission in southern China. Finally, more public health actions should be taken to prevent and control the increase of SE disease with consideration of local weather variations.

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