Xiaoyu Tang

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Furfural from lignocellulosic hydrolysates is the prevalent inhibitor to microorganisms during cellulosic ethanol production, but the molecular mechanisms of tolerance to this inhibitor in Zymomonas mobilis are still unclear. In this study, genome-wide transcriptional responses to furfural were investigated in Z. mobilis using microarray analysis. We found(More)
UNLABELLED BACKGROUND High tolerance to ethanol is a desirable characteristics for ethanologenic strains used in industrial ethanol fermentation. A deeper understanding of the molecular mechanisms underlying ethanologenic strains tolerance of ethanol stress may guide the design of rational strategies to increase process performance in industrial(More)
Furfural and acetic acid from lignocellulosic hydrolysates are the prevalent inhibitors to Zymomonas mobilis during cellulosic ethanol production. Developing a strain tolerant to furfural or acetic acid inhibitors is difficul by using rational engineering strategies due to poor understanding of their underlying molecular mechanisms. In this study, strategy(More)
BACKGROUND The fermentation inhibition of yeast or bacteria by lignocellulose-derived degradation products, during hexose/pentose co-fermentation, is a major bottleneck for cost-effective lignocellulosic biorefineries. To engineer microbial strains for improved performance, it is critical to understand the mechanisms of inhibition that affect fermentative(More)
Plants can suffer ammonium (NH4 +) toxicity, particularly when NH4 + is supplied as the sole nitrogen source. However, our knowledge about the underlying mechanisms of NH4 + toxicity is still largely unknown. Lemna minor, a model duckweed species, can grow well in high NH4 + environment but to some extent can also suffer toxic effects. The transcriptomic(More)
User profiling techniques play a central role in many Recommender Systems (RS). In recent years, multidimensional data are getting increasing attention for making recommendations. Additional metadata help algorithms better understanding users' behaviors and decisions. Existing user/item profiling techniques for Collaborative Filtering (CF) RS in(More)