Decker Stephen R, Sykes Robert W, Turner Geoffrey B, Lupoi Jason S, Doepkke Crissa, Tucker Melvin P, Schuster Logan A, Mazza Kimberly, Himmel Michael E, Davis Mark F, Gjersing Erica
BioEnergy Science Center, National Renewable Energy Laboratory;
BioEnergy Science Center, National Renewable Energy Laboratory.
J Vis Exp. 2015 Sep 15(103):53163. doi: 10.3791/53163.
The conversion of lignocellulosic biomass to fuels, chemicals, and other commodities has been explored as one possible pathway toward reductions in the use of non-renewable energy sources. In order to identify which plants, out of a diverse pool, have the desired chemical traits for downstream applications, attributes, such as cellulose and lignin content, or monomeric sugar release following an enzymatic saccharification, must be compared. The experimental and data analysis protocols of the standard methods of analysis can be time-consuming, thereby limiting the number of samples that can be measured. High-throughput (HTP) methods alleviate the shortcomings of the standard methods, and permit the rapid screening of available samples to isolate those possessing the desired traits. This study illustrates the HTP sugar release and pyrolysis-molecular beam mass spectrometry pipelines employed at the National Renewable Energy Lab. These pipelines have enabled the efficient assessment of thousands of plants while decreasing experimental time and costs through reductions in labor and consumables.
木质纤维素生物质转化为燃料、化学品和其他商品已被探索为减少不可再生能源使用的一种可能途径。为了从多种植物中识别出哪些植物具有下游应用所需的化学特性，必须比较诸如纤维素和木质素含量，或酶促糖化后单糖释放等属性。标准分析方法的实验和数据分析方案可能耗时，从而限制了可测量的样本数量。高通量（HTP）方法克服了标准方法的缺点，并允许快速筛选可用样本以分离出具有所需特性的样本。本研究展示了国家可再生能源实验室采用的高通量糖释放和热解-分子束质谱分析流程。这些流程能够高效评估数千种植物，同时通过减少劳动力和消耗品来降低实验时间和成本。
