# Scavenging for Hydroxybenzoic Acids in Cupriavidus necator: Studying Ligand Sensitivity Using a Biosensor-Based Approach

## TL;DR

This paper uses biosensors to study how bacteria detect and respond to different hydroxybenzoic acids, revealing insights into their catabolic sensitivity and potential applications in metabolic engineering.

## Contribution

The study introduces a TF-based biosensor approach to quantify ligand sensitivity in Cupriavidus necator for hydroxybenzoic acids.

## Key findings

- 2-HBA and 4-HBA sensors in C. necator have low activation thresholds and EC50 values, indicating high sensitivity.
- The biosensor method enables evaluation of gene activation thresholds and effective concentrations for hydroxybenzoic acids.
- The approach informs understanding of gene regulation and can guide metabolic engineering strategies.

## Abstract

The increasing demand for rapid identification of bacteria capable of degrading environmentally relevant organic compounds highlights the need for scalable and selective analytical tools. Cupriavidus necator catabolizes several hydroxybenzoic acids, including 2-hydroxybenzoate (salicylate, 2-HBA), 4-hydroxybenzoate (4-HBA), and 3-hydroxybenzoate (3-HBA), funneling them into central aromatic catabolism via monooxygenation to 2,5-dihydroxybenzoate (gentisate, 2,5-dHBA) and 3,4-dihydroxybenzoate (protocatechuate, 3,4-dHBA) followed by the oxidative cleavage reaction, enabling complete conversion to tricarboxylic acid (TCA) cycle intermediates. To quantify how readily C. necator is able to activate catabolic genes in response to hydroxybenzoic acid, an extracellular ligand, we applied an approach centered on a transcription-factor (TF)-based biosensor that combines ligand-bound regulator activity with a fluorescent reporter. This approach allowed to evaluate the ligand sensitivity by determining gene activation threshold ACmin and half-maximal effective concentration EC50. Amongst studied hydroxybenzoic acids, 2-HBA and 4-HBA sensors from C. necator showed very low thresholds 4.8 and 2.4 μM and EC50 values of 19.91 and 13.06 μM, indicating high sensitivity to these compounds and implicating a scavenging characteristic of associated catabolism. This study shows that the TF-based-biosensor approach applied for mapping functional sensing ranges of hydroxybenzoates combined with the research and informatics of catabolism can advance our understanding of how gene expression regulation systems have evolved to respond differentially to the availability and concentration of carbon sources. Furthermore, it can inform metabolic engineering strategies in the prevention of premature pathway activation or in predicting competitive substrate hierarchies in complex mixed environments.