A high-throughput screening platform integrating a microbial whole-cell biosensor into a double-layer plate assay, enabling rapid identification of bacteria producing cell wall-targeting antibiotics from environmental samples, and accelerating the discovery of novel antibiotic producers from complex environmental communities.
Abstract
ABSTRACT The escalating antimicrobial resistance crisis demands innovative strategies for antibiotic discovery. Conventional approaches for identifying antibiotic-producing microorganisms from environmental samples are often laborious and low-throughput, requiring prior isolation and purification of individual strains. Here, we developed a high-throughput screening platform integrating a microbial whole-cell biosensor into a double-layer plate assay, enabling rapid identification of bacteria producing cell wall-targeting antibiotics from environmental samples. The biosensor is based on the PghKR two-component system from the gram-negative bacterium Shewanella oneidensis MR-1. Upon exposure to cell wall-targeting antibiotics, PghKR activates the promoter of blaA, driving expression of the luxCDABE reporter and generating luminescence. A highly sensitive biosensor was engineered through the synergistic deletion of blaA and ampG, which greatly improved its responsiveness. The method was then applied to screen soil samples. From the primary screen, 103 colonies producing distinct luminescent signals were identified. Of these, 36 isolates consistently activated the biosensor in a confirmation assay, and 5 exhibited antibacterial activity against a multidrug-resistant indicator strain. This integrated approach combines microbial separation with immediate biosensor-based detection, thereby accelerating the discovery of novel antibiotic producers from complex environmental communities. IMPORTANCE The rise of antimicrobial resistance calls for faster, more efficient ways to discover new antibiotics from environmental microbes. Traditional methods are slow because they require laborious, one-by-one isolation and purification of individual strains before any activity testing. To overcome this bottleneck, we developed a simple double-layer plate assay that directly identifies bacteria producing cell wall-targeting antibiotics while they grow. This “grow-and-detect” strategy bypasses traditional isolation steps, dramatically speeding up the initial discovery pipeline. Our platform enables large-scale, low-cost screening of environmental samples for antibiotic producers. The rise of antimicrobial resistance calls for faster, more efficient ways to discover new antibiotics from environmental microbes. Traditional methods are slow because they require laborious, one-by-one isolation and purification of individual strains before any activity testing. To overcome this bottleneck, we developed a simple double-layer plate assay that directly identifies bacteria producing cell wall-targeting antibiotics while they grow. This “grow-and-detect” strategy bypasses traditional isolation steps, dramatically speeding up the initial discovery pipeline. Our platform enables large-scale, low-cost screening of environmental samples for antibiotic producers.
Industrial biomanufacturing relies on microorganisms to efficiently synthesize target products under engineered conditions. However, wild-type strains often lack the capability to do so due to their native metabolic networks. Therefore, the rapid and accurate screening of high-performance strains from large-scale mutant libraries is a critical step in industrial microbial breeding. In recent years, droplet microfluidic technology has attracted significant attention for its high throughput, low consumption, and single-cell compartmentalization capabilities, leading to the development of numerous single-cell sorting systems. A high‑throughput screening protocol for industrial microbial strains using an automated droplet microfluidic platform is presented in this study. The integrated workflow comprises four key stages: construction of a mutant library via atmospheric and room-temperature plasma (ARTP) mutagenesis; high‑efficiency single‑cell encapsulation and controlled micro‑cultivation within picoliter‑scale droplets; precise pico‑injection of a fluorescent biosensor, followed by fluorescence‑activated droplet sorting (FADS) to isolate droplets containing high‑producing variants; and validation of the sorted candidate strains through microplate and shake‑flask fermentation. A complete and integrated screening workflow is intended as a standardized template, and its validation is demonstrated through the isolation of high‑yielding L-lactic acid‑producing mutants of B. coagulans as a specific example. This automated, high-throughput screening platform offers a powerful technical solution with significant potential to accelerate industrial breeding of high-performance strains.
Xin Da, Shuang Li, Qingyuan Wang et al.· Journal of Visualized Experi...· 0 citations
The rapid and specific detection of foodborne bacteria in complex matrices remains a critical analytical challenge. Conventional nucleic acid amplification and immunological methods offer high analytical sensitivity, but they often provide limited information on bacterial viability because nucleic acids and antigenic epitopes may persist after cell death. As obligate parasites, bacteriophages (phages) initiate infection through the adsorption stage, relying on highly specific recognition between tail proteins and host receptors. This early interaction provides a rapid recognition window before signals from downstream replication or lysis become dominant. Herein, this review presents a systematic overview of biosensors based on the bacteriophage adsorption stage for the detection of foodborne bacteria developed over the past five years. It explores how whole phages and their derived proteins can serve as biorecognition elements in combination with different transducers for bacterial capture and signal transduction, with emphasis on interface-oriented immobilization, signal attribution, matrix effects, and adaptation to point-of-care testing (POCT), especially lateral flow assays (LFAs) for instrument-free analysis. Meanwhile, it highlights that whole phages retain the native adsorption architecture and may support interpretation of viability when appropriate validation models are used, whereas phage-derived proteins provide more flexible recognition modules for interface design and signal generation but require attention to effective avidity, conformational context, and consistency between batches. Furthermore, future phage-based analytical platforms are discussed in relation to time-resolved kinetic validation, computationally assisted readout, and adsorption-coupled detection and containment.
Xingying Mou, Xinge Cui, Yongkang Zhang et al.· In Analysis· 0 citations
Whole-cell biosensors provide a cost-effective and sensitive approach for real-time monitoring of toxic metals in environmental samples. In this study, a bacterial whole-cell biosensor was engineered using Escherichia coli BL21(DE3) by integrating the cadC regulatory gene from Bacillus megaterium TWSL_4 with a green fluorescent protein (GFP) reporter to enable fluorescence-based detection of heavy metals. The biosensor gene cassette (Pcad + cadC + gfp) was first cloned into the pUC19 vector and then subcloned into the pET28a(+) expression vector to generate the recombinant plasmid pETCG28. Functional characterization showed that the engineered strain E. coli BL21/pETCG28 exhibited enhanced tolerance to heavy metals, sustaining growth at Pb²⁺ concentrations up to 1600 ppm, Cd²⁺ up to 200 ppm, and Zn²⁺ up to 60 ppm, significantly higher than the wild-type strain. Fluorescence analyses demonstrated strong concentration-dependent responses to heavy metal exposure. Corrected total cell fluorescence increased nearly fourfold between 1 ppb and 10 ppb of Pb²⁺ (R² = 0.95, p < 0.0001). Cd²⁺ exposure produced an approximately threefold increase (R² = 0.96, p < 0.0001), while Zn²⁺ generated a moderate twofold response (R² = 0.94, p < 0.0001). Optimal biosensor performance occurred at pH 7.0 and 37°C, demonstrating potential for portable environmental monitoring applications.
D. C. Dissanayake, N. V. Chandrasekharan, M. Wachi et al.· FEMS Microbiology Letters· 0 citations
Antimicrobial resistance (AMR) is a growing global threat to human health, and rapid methods for characterising emerging antimicrobial resistance genes (ARGs) are needed. Here, we develop a semi-automated workflow using cell-free gene expression (CFE) systems to measure the activity of two ARGs encoded on plasmid DNA that produce rifampicin-inactivating and gentamicin-inactivating enzymes. We validated the use of a small benchtop Myra liquid handling system compared to manual pipetting, with no statistical differences observed. After optimising the pre-incubation time of ARGs and dispensing protocol, expression of aac(3)-IIa increased the half-maximal inhibition concentration (IC50) of gentamicin by over 150-fold, while arr-3 increased the IC50 of rifampicin by approximately 20-fold compared to controls. This methodology for rapid, semi-automated ARG characterisation offers a strategy to combat AMR by assessing novel ARGs identified through genomic surveillance or profiling activity of new or derivative antibiotics.
Molly Bergum, Sahana Suthakaran, Bethany Martin et al.· Synthetic Biology· 0 citations
