Department of Chemistry and Biochemistry, University of Texas at Austin, Austin, Texas, United States.
Anal Chem. 2011 Mar 15;83(6):2194-200. doi: 10.1021/ac103098u. Epub 2011 Feb 21.
In order to automate the optimization of complex biochemical and molecular biology reactions, we developed a sequential injection analysis (SIA) device and combined this with a design of experiment (DOE) algorithm. This combination of hardware and software automatically explores the parameter space of the reaction and provides continuous feedback for optimizing reaction conditions. As an example, we optimized the endonuclease digest of a fluorogenic substrate and showed that the optimized reaction conditions also applied to the digest of the substrate outside of the device and to the digest of a plasmid. The sequential technique quickly arrived at optimized reaction conditions with less reagent use than a batch process (such as a fluid handling robot exploring multiple reaction conditions in parallel) would have. The device and method should now be amenable to much more complex molecular biology reactions whose variable spaces are correspondingly larger.
为了实现复杂生化和分子生物学反应的自动化优化,我们开发了一种顺序注射分析(SIA)设备,并将其与实验设计(DOE)算法相结合。这种软硬件的结合能够自动探索反应的参数空间,并为优化反应条件提供持续反馈。例如,我们对荧光底物的内切酶消化进行了优化,并表明优化后的反应条件也适用于设备外底物和质粒的消化。与批量处理(例如,流体处理机器人并行探索多种反应条件)相比,顺序技术可以更快地获得优化的反应条件,同时使用的试剂也更少。该设备和方法现在应该适用于更复杂的分子生物学反应,这些反应的变量空间相应更大。