title: Sequential injection analysis for optimization of molecular biology reactions.
abstract: 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.
authors.affiliation: Department of Chemistry and Biochemistry, University of Texas at Austin, Austin, Texas, United States.
authors.forename: Peter B
authors.initials: PB
authors.lastname: Allen
authors.forename: Andrew D
authors.initials: AD
authors.lastname: Ellington
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D015252:Deoxyribonucleases, Type II Site-Specific / Q000378:metabolism; D005456:Fluorescent Dyes / Q000378:metabolism; D007202:Indicators and Reagents / Q000737:chemistry; D007267:Injections / Q000295:instrumentation / Q000379:methods*; D008967:Molecular Biology / Q000295:instrumentation / Q000379:methods*; D013997:Time Factors
chemical_list: D005456:Fluorescent Dyes; D007202:Indicators and Reagents; D015252:Deoxyribonucleases, Type II Site-Specific; C024403:GGCC-specific type II deoxyribonucleases