Search bioRxiv⌕ Search

bioRxiv · 10.1101/2022.01.12.475730

Dynamic control systems that mimic natural regulation of catabolic pathways enable rapid production of lignocellulose-derived bioproducts

Abstract

Expanding the catabolic repertoire of engineered microbial bioproduction hosts enables more complete use of complex feedstocks such as lignocellulosic hydrolysates and deconstructed mixed plastics, but the deleterious effects of existing expression systems limit the maximum carry capacity for heterologous catabolic pathways. Here, we demonstrate use of a conditionally beneficial oxidative xylose catabolic pathway to improve performance of a Pseudomonas putida strain that has been engineered for growth-coupled bioconversion of glucose into the valuable bioproduct cis,cis-muconic acid. In the presence of xylose, the pathway enhances growth rate, and therefore productivity, by >60%, but the metabolic burden of constitutive pathway expression reduces growth rate by >20% in the absence of xylose. To mitigate this growth defect, we develop a xylose biosensor based on the XylR transcription factor from Caulobacter crescentus NA1000 to autonomously regulate pathway expression. We generate a library of engineered xylose-responsive promoters that cover a three order-of-magnitude range of expression levels to tune pathway expression. Using structural modeling to guide mutations, we engineer XylR with two and three orders-of-magnitude reduced sensitivity to xylose and L-arabinose, respectively. A previously developed heterologous xylose isomerase pathway is placed under control of the biosensor, which improves the growth rate with xylose as a carbon source by 10% over the original constitutively expressed pathway. Finally, the oxidative xylose catabolic pathway is placed under control of the biosensor, enabling the bioproduction strain to maintain the increased growth rate in the presence of xylose, without the growth defect incurred from constitutive pathway expression in the absence of xylose. Utilizing biosensors to autonomously regulate conditionally beneficial catabolic pathways is generalizable approach that will be critical for engineering bioproduction hosts bacteria with the wide range of catabolic pathways required for bioconversion of complex feedstocks.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Elmore, J. R., Peabody, G. L., Jha, R. K., Dexter, G. N., Dale, T., Guss, A. M.. 2022-01-13. Dynamic control systems that mimic natural regulation of catabolic pathways enable rapid production of lignocellulose-derived bioproducts. https://doi.org/10.1101/2022.01.12.475730

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Living electronic transistors with tunable conductivity

Electroactive bacteria, like Shewanella oneidensis, can couple the oxidation of organic electron donors to the reduction of external conductive surfaces, such as minerals and electrodes, by utilizing multiheme cytochromes to carry charge from within the cell to external surfaces. Additionally, multiheme cytochromes facilitate gateable, long-distance (micrometer-scale) redox conduction along the outer membrane and across multiple cells bridging electrodes. While electroactive microbes are being used to develop bioelectrochemical devices, there have been limited efforts to use synthetic biology to exert additional control over microbes serving as device components. Thus, this work implements an optogenetic biofilm patterning gene circuit and a small molecule sensor in S. oneidensis to simultaneously control cell deposition and cytochrome expression. This allows for photolithographic patterning of biofilms possessing tunable electrical properties controlled with small molecules. This system demonstrates tunable electrochemical activity, redox conduction, intrinsic biofilm conductivity, and negative differential transconductance as a function of cytochrome expression. Additionally, temperature-dependent measurements of this tunable biofilm conduction reveal changes in activation energy as a function of cytochrome expression. Through this combination of synthetic biology and electrochemistry, simultaneous control over biofilm geometry and conductivity sheds light on fundamental microbial electron transport processes, and it enables the construction of living electronic devices.

synthetic biology↗

Evolutionary stabilisation of stressful metabolism via integrated biocomputing and essential-gene metabolic locking circuits

Synthetic genetic circuits enable microbial differentiation from growth to production, yet metabolic burden, imbalance and toxicity frequently drive strain degeneration. Yeast strains engineered to produce different terpene products exhibited divergent genetic responses to metabolic stresses, but commonly underwent progressive loss of induction of synthetic GAL regulatory circuits, either across the entire population or within subpopulations. Using di- and tri-input biocomputing circuits, the essential glutamine synthetase gene GLN1 was coupled to GAL induction, thereby enabling stabilisation and evolutionary adaptation of the synthetic genetic circuits and stressful heterologous terpene synthetic pathways. The integrated biocomputing and metabolic coupling circuit systems not only prevent strain degeneration but also enable interrogation of non-degenerative evolutionary shifts, providing a platform for metabolic engineering optimisation.

synthetic biology↗

Unbiased and scalable reduction of diverse bacterial genomes

The genome is a complex, integrated system where the functions and regulatory interactions of its many components remain poorly understood. Genome minimization aims to reduce genomic complexity by removing non-essential elements to reveal the fundamental building blocks of cellular life. However, current minimization strategies are often slow and species-specific due to a reliance on prior information, and limited to producing single, isolated strains, which obscures the diverse ways a genome can adapt to large-scale DNA removal. Here we show the development and application of Stochastic Lineage-based Iterative Minimization (SLIM) a modular, high-throughput platform for unbiased genome reduction across phylogenetically diverse bacteria. We apply SLIM to generate a library of genome-reduced Escherichia coli lineages. We then interrogate the lineages, identifying both universal and lineage-specific transcriptional and translational reprogramming in response to deletions. We demonstrate that these expression dynamics drive environment-dependent fitness, allowing us to pinpoint a single gene deletion in one genome-reduced lineage as the driver of a measurable environmental growth defect. Beyond E. coli, we successfully deploy SLIM in phylogenetically distinct bacterial taxa to rapidly reduce the genomes of Shigella flexneri and Pseudomonas putida, distinct genus and order respectively from E. coli, without species-specific optimization. Our results establish a scalable, generalizable framework for navigating the vast landscape of minimized genomes, providing a powerful new tool for functional discovery and the rational design of synthetic genomic chassis.

synthetic biology↗