Biology subjects

Ingle, C.

Publications and source records attributed to Ingle, C..

4 recordsLinked to original sources

bioRxiv2026

Systematic CRISPRi screening reveals genetic modulators of E. coli isoprenoid production

Isoprenoid biosynthesis in E. coli is a promising source of high-value natural products. However, isoprenoid production imposes a substantial metabolic burden on cellular carbon and cofactor metabolism. Optimizing yields thus requires rebalancing gene expression throughout metabolism. To systematically identify the genes in E. coli central metabolism shaping isoprenoid yield, we established a high-throughput CRISPR interference (CRISPRi) assay to examine the impact of gene repression on production of the bright red carotenoid, lycopene. Our approach enables repression of both essential and non-essential genes and links gene expression perturbations to pathway yield and biomass. We screened a CRISPRi library targeting 180 E. coli genes and found 31 genes for which repression significantly modified lycopene yield. Genes whose repression increased lycopene yield were found across fatty acid, amino acid, central carbon, and isoprenoid metabolism as well as stress response pathways. This set included four genes in amino acid biosynthesis, one in phospholipid biosynthesis, and one in the stringent response that, to our knowledge, have not previously been implicated in lycopene production. In contrast, genes for which repression decreased yield were limited to isoprenoid biosynthesis, central carbon metabolism, and stress response pathways. Together, our work reveals genetic targets for increasing lycopene yield throughout metabolism, and defines a tractable, generalizable approach to mapping genetic factors that modulate biosynthetic pathway yield.

synthetic biology↗

bioRxiv2023

The Genetic Landscape of a Metabolic Interaction

Enzyme abundance, catalytic activity, and ultimately sequence are all shaped by the need of growing cells to maintain metabolic flux while minimizing accumulation of deleterious intermediates. While much prior work has explored the constraints on protein sequence and evolution induced by physical protein-protein interactions, the sequence-level constraints emerging from non-binding functional interactions in metabolism remain unclear. To quantify how variation in the activity of one enzyme constrains the biochemical parameters and sequence of another, we focused on dihydrofolate reductase (DHFR) and thymidylate synthase (TYMS), a pair of enzymes catalyzing consecutive reactions in folate metabolism. We used deep mutational scanning to quantify the growth rate effect of 2,696 DHFR single mutations in 3 TYMS backgrounds under conditions selected to emphasize biochemical epistasis. Our data are well-described by a relatively simple enzyme velocity to growth rate model that quantifies how metabolic context tunes enzyme mutational tolerance. Together our results reveal the structural distribution of epistasis in a metabolic enzyme and establish a foundation for the design of multi-enzyme systems.

biochemistry↗

bioRxiv2019

Modulating the cellular context broadly reshapes the mutational landscape of a model enzyme

Protein mutational landscapes are shaped by the cellular environment, but key factors and their quantitative effects are often unknown. Here we show that Lon, a quality control protease naturally absent in common E. coli expression strains, drastically reshapes the mutational landscape of the metabolic enzyme dihydrofolate reductase (DHFR). Selection under conditions that resolve highly active mutants reveals that 23.3% of all single point mutations in DHFR are advantageous in the absence of Lon, but advantageous mutations are largely suppressed when Lon is reintroduced. Protein stability measurements demonstrate extensive activity-stability tradeoffs for the advantageous mutants and provide a mechanistic explanation for Lons widespread impact. Our findings suggest possibilities for tuning mutational landscapes by modulating the cellular environment, with implications for protein design and combatting antibiotic resistance.

biophysics↗

bioRxiv2017

An evolutionary module in central metabolism

Metabolic enzyme function and evolution is influenced by the larger context of a biochemical pathway - deleterious mutations or perturbations in one enzyme can often be compensated by mutations to others. To explore strategies for mapping adaptive dependencies between enzymes, we used a combination of comparative genomics and experiments to examine interactions with the model metabolic enzyme Dihydrofolate Reductase (DHFR). Biochemically, DHFR shares a metabolic intermediate with numerous folate metabolic enzymes. In contrast, comparative genomics analyses of synteny and gene co-occurrence indicate a sparse pattern of evolutionary couplings in which DHFR is coupled to the enzyme thymidylate synthase (TYMS), but is relatively independent from the rest of folate metabolism. To test this apparent modularity, we used quantitative growth rate measurements and forward evolution in E. coli to demonstrate that the two enzymes are coupled to one another, and can adapt independently from the remainder of the genome. Mechanistically, the coupling between DHFR and TYMS is driven by a constraint wherein TYMS activity must not greatly exceed that of DHFR - both to avoid depletion of reduced folates and prevent accumulation of the metabolic intermediate dihydrofolate. Extending our comparative genomics analyses genome-wide reveals over 200 gene pairs with statistical signatures similar to DHFR/TYMS, suggesting the possibility that cellular pathways might be decomposed into small adaptive units.

systems biology↗