PT  - JOURNAL ARTICLE
AU  - Stéphane Poulain
AU  - Ophélie Arnaud
AU  - Sachi Kato
AU  - Iris Chen
AU  - Hiro Ishida
AU  - Piero Carninci
AU  - Charles Plessy
TI  - Machine-driven parameter optimisation of biochemical reactions
AID  - 10.1101/739771
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 739771
4099  - http://biorxiv.org/content/early/2019/08/21/739771.short
4100  - http://biorxiv.org/content/early/2019/08/21/739771.full
AB  - The development of complex, multi-step methods in molecular biology is a laborious, costly, iterative and often intuition-bound process where an optimum is sought in a multidimensional parameter space through step-by-step optimisations. The difficulty of miniaturising reactions under the microliter volumes usually handled in multiwell plates by robots, plus the cost of the experiments, limit the number of parameters and the dynamic ranges that can be explored. Nevertheless, because of non-linearities of the response of biochemical systems to their reagent concentrations, broad dynamic ranges are necessary. Here we use a high-performance nanoliter handling platform and computer generation of liquid transfer programs to explore in quadruplicates more than 600 combinations of 4 parameters of a biochemical reaction, the reverse-transcription, which lead us to uncover non-linear responses, parameter interactions and novel mechanistic insights. With the increased availability of computer-driven laboratory platforms for biotechnology, our results demonstrate the feasibility and advantage of methods development based on reproducible, computer-aided exhaustive characterisation of biochemical systems.