Dataset Information

Extended Metabolic Biosensor Design for Dynamic Pathway Regulation of Cell Factories.

ABSTRACT: Transcription factor-based biosensors naturally occur in metabolic pathways to maintain cell growth and to provide a robust response to environmental fluctuations. Extended metabolic biosensors, i.e., the cascading of a bio-conversion pathway and a transcription factor (TF) responsive to the downstream effector metabolite, provide sensing capabilities beyond natural effectors for implementing context-aware synthetic genetic circuits and bio-observers. However, the engineering of such multi-step circuits is challenged by stability and robustness issues. In order to streamline the design of TF-based biosensors in metabolic pathways, here we investigate the response of a genetic circuit combining a TF-based extended metabolic biosensor with an antithetic integral circuit, a feedback controller that achieves robustness against environmental fluctuations. The dynamic response of an extended biosensor-based regulated flavonoid pathway is analyzed in order to address the issues of biosensor tuning of the regulated pathway under industrial biomanufacturing operating constraints.

SUBMITTER: Boada Y

PROVIDER: S-EPMC7334618 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Extended Metabolic Biosensor Design for Dynamic Pathway Regulation of Cell Factories.

Boada Yadira Y Vignoni Alejandro A Picó Jesús J Carbonell Pablo P

iScience 20200623 7

Transcription factor-based biosensors naturally occur in metabolic pathways to maintain cell growth and to provide a robust response to environmental fluctuations. Extended metabolic biosensors, i.e., the cascading of a bio-conversion pathway and a transcription factor (TF) responsive to the downstream effector metabolite, provide sensing capabilities beyond natural effectors for implementing context-aware synthetic genetic circuits and bio-observers. However, the engineering of such multi-step ...[more]

PMID: 32629420

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Project description:BackgroundThe identification of genetic target genes is a key step for rational engineering of production strains towards bio-based chemicals, fuels or therapeutics. This is often a difficult task, because superior production performance typically requires a combination of multiple targets, whereby the complex metabolic networks complicate straightforward identification. Recent attempts towards target prediction mainly focus on the prediction of gene deletion targets and therefore can cover only a part of genetic modifications proven valuable in metabolic engineering. Efficient in silico methods for simultaneous genome-scale identification of targets to be amplified or deleted are still lacking.ResultsHere we propose the identification of targets via flux correlation to a chosen objective flux as approach towards improved biotechnological production strains with optimally designed fluxes. The approach, we name Flux Design, computes elementary modes and, by search through the modes, identifies targets to be amplified (positive correlation) or down-regulated (negative correlation). Supported by statistical evaluation, a target potential is attributed to the identified reactions in a quantitative manner. Based on systems-wide models of the industrial microorganisms Corynebacterium glutamicum and Aspergillus niger, up to more than 20,000 modes were obtained for each case, differing strongly in production performance and intracellular fluxes. For lysine production in C. glutamicum the identified targets nicely matched with reported successful metabolic engineering strategies. In addition, simulations revealed insights, e.g. into the flexibility of energy metabolism. For enzyme production in A.niger flux correlation analysis suggested a number of targets, including non-obvious ones. Hereby, the relevance of most targets depended on the metabolic state of the cell and also on the carbon source.ConclusionsObjective flux correlation analysis provided a detailed insight into the metabolic networks of industrially relevant prokaryotic and eukaryotic microorganisms. It was shown that capacity, pathway usage, and relevant genetic targets for optimal production partly depend on the network structure and the metabolic state of the cell which should be considered in future metabolic engineering strategies. The presented strategy can be generally used to identify priority sorted amplification and deletion targets for metabolic engineering purposes under various conditions and thus displays a useful strategy to be incorporated into efficient strain and bioprocess optimization.

Project description:Re-programming microorganisms to modify their existing functions and/or to bestow bacteria with entirely new-to-Nature tasks have largely relied so far on specialized molecular biology tools. Such endeavors are not only relevant in the burgeoning metabolic engineering arena but also instrumental to explore the functioning of complex regulatory networks from a fundamental point of view. À la carte modification of bacterial genomes thus calls for novel tools to make genetic manipulations easier. We propose the use of a series of new broad-host-range mini-Tn5-vectors, termed pBAMDs, for the delivery of gene(s) into the chromosome of Gram-negative bacteria and for generating saturated mutagenesis libraries in gene function studies. These delivery vectors endow the user with the possibility of easy cloning and subsequent insertion of functional cargoes with three different antibiotic-resistance markers (kanamycin, streptomycin, and gentamicin). After validating the pBAMD vectors in the environmental bacterium Pseudomonas putida KT2440, their use was also illustrated by inserting the entire poly(3-hydroxybutyrate) (PHB) synthesis pathway from Cupriavidus necator in the chromosome of a phosphotransacetylase mutant of Escherichia coli. PHB is a completely biodegradable polyester with a number of industrial applications that make it attractive as a potential replacement of oil-based plastics. The non-selective nature of chromosomal insertions of the biosynthetic genes was evidenced by a large landscape of PHB synthesis levels in independent clones. One clone was selected and further characterized as a microbial cell factory for PHB accumulation, and it achieved polymer accumulation levels comparable to those of a plasmid-bearing recombinant. Taken together, our results demonstrate that the new mini-Tn5-vectors can be used to confer interesting phenotypes in Gram-negative bacteria that would be very difficult to engineer through direct manipulation of the structural genes.

Dataset Information

Extended Metabolic Biosensor Design for Dynamic Pathway Regulation of Cell Factories.

Publications

Extended Metabolic Biosensor Design for Dynamic Pathway Regulation of Cell Factories.

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