From empirical to data-driven host selection: a broad-host-range expression platform to facilitate chassis screening

Abstract

Nature has provided a vast landscape of organisms through evolution, each with unique phenotypic traits adapted to varying environments. Nevertheless, host selection in biotechnological research is exceedingly dominated by empirical preference, where the endogenous physiology of the selected host is often not suited to the desired application. Considering that large parts of cellular regulation and metabolism remain obscure, empirical selection of a preferred model organism may lead to undue caveats in further engineering attempts, arising from intrinsic metabolism. One reason for the empirical host selection is the lack of engineering tools for screening novel organisms. In this study, we provide a modular, single vector-based expression platform, compatible with a wide range of prokaryotes. It centers around a tight and titratable promoter system, inducible by anhydrotetracyclin within an 84-fold dynamic range. It enables easy screening of recombinant proteins and pathways in both mesophilic and thermophilic Gram-negative and Gram-positive hosts. Overall, this platform enables simple screening of heterologous expression and production in a variety of hosts, including the exploration of previously unconsidered hosts thereby aiding the transition from empirical to data-driven host selection.