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Expanding the biotechnological scope of metabolic sensors through computational-aided designs

ABSTRACT: Metabolic sensors are microbial strains modified such that biomass formation correlates with the availability of specific target metabolites. These sensors are essential for bioengineering (e.g. in growth-coupled selection of synthetic pathways), but their design is often time-consuming and low-throughput. In contrast, in silico analysis can accelerate their development. We present a systematic workflow for designing, implementing, and testing versatile metabolic sensors using Escherichia coli as a model. Glyoxylate, a key metabolite in synthetic CO2 fixation and carbon-conserving pathways, served as the test molecule. Through iterative screening of a compact metabolic reconstruction, we identified non-trivial growth-coupled designs that resulted in six metabolic sensors with different glyoxylate-to-biomass ratios. These metabolic sensors had a linear correlation between biomass formation and glyoxylate concentration spanning three orders of magnitude and were further adapted for glycolate sensing. We demonstrate the utility of these sensors in pathway engineering (implementing a synthetic route for one-carbon assimilation via glyoxylate) and environmental applications (quantifying glycolate produced by photosynthetic microalgae). The versatility and ease of implementation of this workflow make it suitable for designing and building multiple metabolic sensors for diverse biotechnological applications.

INSTRUMENT(S): Orbitrap Exploris 480

ORGANISM(S): Escherichia Coli

SUBMITTER: Timo Glatter

LAB HEAD: Timo Glatter

PROVIDER: PXD054993 | Pride | 2025-01-16

REPOSITORIES: pride

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Project description:Metabolism is fundamental to life, all life activities are sustained through metabolism. Metabolic engineering, while modifying host endogenous metabolic network or introducing heterologous pathway for biotechnological applications, often results in unfitness and suboptimal characteristics, because of the lack of full knowledge on host metabolism. Adaptive laboratory evolution (ALE), harnessing the nature of life -- evolution, has become a potent approach in phenotype optimization, environmental adaptation, and cell biology study1–3. Through ALE, alternative pathways of β-alanine biosynthesis4, pyridoxal 5’-phosphate (PLP) biosynthesis5, isoleucine biosynthesis6, as well as ATP generation7 have been uncovered; E. coli aerobic citrate utilization8,9 and various synthetic C1-trophy10–14 have been realized. In this study, we describe E. coli recruits the same workforce, Sad, in evolution through various strategies, i.e., catalytic efficiency improvement, gene dose increase, and gene expression regulations, to overcome metabolic damages (Fig. 1). Sad, i.e. NAD(P)+-dependent succinate semialdehyde dehydrogenase (SSADH), is an aldehyde dehydrogenase (ALDH) family protein. Sad oxidizes succinate semialdehyde to succinate, preventing accumulation of the toxic aldehyde intermediate in nitrogen metabolism, such as putrescine, arginine and γ-aminobutyrate (GABA) degradations15–17. Some bacteria, for example E. coli, possess also a NADP+-dependent SSADH, GabD15,18. SSADH is ubiquitous in both prokaryotes and eukaryotes. In human, it involves in catabolism of GABA, a major neurotransmitter, its malfunction leads to a disorder SSADH deficiency19. In plants, SSADH involves in leaf development and morphogenesis20 as well as defense of abiotic stress21. And in cyanobacteria, SSADH is an essential enzyme of its uncanonical tricarboxylic acid cycle. SSADH was also found to be able to oxidize glutarate semialdehyde, participating in lysine catabolism in bacteria.

Project description:Obesity is becoming increasingly widespread in developed countries, and is often associated with heart diseases and diabetes. Elevated levels of plasma free fatty acids are a biochemical hallmark of obesity. Unlike plants and bacteria, mammals cannot utilize fatty acids to generate glucose because of the lack of glyoxylate shunt enzymes. Instead, fatty acids are used for energy storage, and their utilization is regulated at multiple levels ranging from hormonal to metabolic ensuring that glucose is preferentially oxidized before fatty acids. Here we designed a synthetic gene-metabolic circuit to alter the intracellular signaling and metabolic pathways that control fatty acid metabolism. By introducing the Escherichia coli glyoxylate shunt enzymes, isocitrate lyase (AceA) and malate synthase (AceB), into the mitochondria of human hepatocytes, we demonstrated that fatty acid utilization is preferentially increased while glucose uptake is significantly reduced. This bacterial pathway diverts signal metabolites (citrate, acetyl-CoA, and malonyl-CoA) that inhibits fatty acid uptake and provides an additional channel for fatty acid utilization. Remarkably, the hepatocytes readily adapted to the synthetic circuit by a series of global transcriptional and post-translational changes in metabolic and signal transduction pathways that further advanced our design objective. This systems approach illustrates the logic of the synergistic interaction between metabolism and signal transduction. The ready acceptance of this non-native pathway by hepatocytes suggests the plasticity of liver metabolism and opens a possibility for the synthetic approach in regulating human metabolism. Experiment Overall Design: Wild type (WT) human hepatocyte HepG2 and HepG2 cells stably transfected with pBudaceAB (designated ACE), a vector containing isocitrate lyase and malate synthase from E. coli, were analyzed after 24hour exposure to palmitate. Cells were seeded at 70% confluency in 10cm plates with DMEM growth media augmented with 300uM palmitate. After 24hours, total RNA was harvested and hybrized to Affymetrix HG_U133A 2.0 GeneChips. Data was processed using GCOS 1.2 software. Experiment Overall Design: 2 WT biological replicates and 2 ACE biological replicates were analyzed. Experiment Overall Design:

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Expanding the biotechnological scope of metabolic sensors through computational-aided designs

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