Many of the organisms currently employed in SynBio applications are derived from wild organisms, these cells conserve their complex native regulatory programs which helps to maximize their survival in typically variable natural environments. The mechanisms that prepare an organism for an environmental change or fore coming stress are called “hedging functions” and they have a cost in terms of cellular resources, so when a synthetic function is introduced in stable laboratory conditions the performance is not optimal. Conversely, synthetic cells need to be designed to be specialists, hence, they need to show specialized behaviours for very specific environments, cellular resources should be efficiently allocated for an optimal use and maximization of the capacity of the introduced synthetic function.
In the last years our team has focused on the study of the principles behind the economy of bacterial cellular resource allocation using SysBio approaches. We aim to generate tools and methodologies that facilitate the streamlined design of synthetic phenotypes. One of the lines we've addressed, is the use of the Transcriptional Regulatory Network (TRN), as a control layer for cellular resource assignment. The idea raised by the fact that by sensing and interpreting intricate environmental and intracellular signals, the TRN can modulate the expression of genes in a condition-specific way. The trick: rewire the TRN to achieve any desired cellular state.
Following this line, we came up with ReProMin (Regulation based Proteome Minimization) a new top-down cell engineering strategy. By combining high-throughput proteomic information, regulatory network interactions and genetic essentiality observations, ReProMin identifies the transcription factors (TFs) involved in the expression of proteome fractions that are not used in a particular environment. Figure 1.
Figure 1. ReProMin main pipeline. A) Gene essentiality profile is defined by combining in vivo and in silico essentiality observations for a specific growth condition. B) Integration of TRN data for TF essentiality classification. C) Integration of proteomic data to discover potential candidate TFs for elimination. D) Combinatorial analysis to find the set of genetic interventions that maximizes resource liberation. E) Construction of mutant strains based on combinatorial analysis. F) Mutant strains characterization and testing.
In our recently published paper in Nat Chem Bio, we show the efficiency and flexibility of ReProMin. We were able to reduce the hedging proteome by 0.5% deleting only three TFs, resulting in strains with higher capacity for expression of synthetic pathways.
We think that SysBio based tools like ReProMin will lay the ground to future approaches for the streamlined design synthetic organisms. Evolving technologies like Chip-seq and Ribo-seq combined with novel AI algorithms will enable genome-scale precise reconstruction and characterization of TRNs from different organisms, greatly expanding the capabilities of our approach.