Effect of chromosomal integration on catalytic performance of a multi-component P450 system in Escherichia coli.

Cytochromes P450 are useful biocatalysts in synthetic chemistry and important bio-bricks in synthetic biology. Almost all bacterial P450s require separate redox partners for their activity, which are often expressed in recombinant Escherichia coli using multiple plasmids. However, the application of CRISPR/Cas recombineering facilitated chromosomal integration of heterologous genes which enables more stable and tunable expression of multi-component P450 systems for whole-cell biotransformations. Herein, we compared three E. coli strains W3110, JM109, and BL21(DE3) harboring three heterologous genes encoding a P450 and two redox partners either on plasmids or after chromosomal integration in two genomic loci. Both loci proved to be reliable and comparable for the model regio- and stereoselective two-step oxidation of (S)-ketamine. Furthermore, the CRISPR/Cas-assisted integration of the T7 RNA polymerase gene enabled an easy extension of T7 expression strains. Higher titers of soluble active P450 were achieved in E. coli harboring a single chromosomal copy of the P450 gene compared to E. coli carrying a medium copy pET plasmid. In addition, improved expression of both redox partners after chromosomal integration resulted in up to 80% higher (S)-ketamine conversion and more than fourfold increase in total turnover numbers.

Emerging Opportunities Provided by Technology to Advance Research in Child Health Globally.

Current approaches to longitudinal assessment of children's developmental and psychological well-being, as mandated in the United Nations Sustainable Development Goals, are expensive and time consuming. Substantive understanding of global progress toward these goals will require a suite of new robust, cost-effective research tools designed to assess key developmental processes in diverse settings. While first steps have been taken toward this end through efforts such as the National Institutes of Health's Toolbox, experience-near approaches including naturalistic observation have remained too costly and time consuming to scale to the population level. This perspective presents 4 emerging technologies with high potential for advancing the field of child health and development research, namely (1) affective computing, (2) ubiquitous computing, (3) eye tracking, and (4) machine learning. By drawing attention of scientists, policy makers, investors/funders, and the media to the applications and potential risks of these emerging opportunities, we hope to inspire a fresh wave of innovation and new solutions to the global challenges faced by children and their families.