Development of a CRISPR-based biosensor for rapid detection of antibiotic resistance genes in bacterial pathogens using cell-free systems

Project Abstract

The rapid and accurate detection of antibiotic resistance genes (ARGs) is a critical driver in guiding effective antimicrobial therapy and surveillance of resistant bacterial pathogens. This study reports the development of a CRISPR-based biosensor integrated with a cell-free system (CFS) for the rapid, sensitive, and field-deployable detection of ARGs directly from clinical and environmental samples. We engineered a CRISPR-Cas12a/ Cas13a-based assay coupled with a minimalistic cell-free transcription-translation (TX-TL) platform to enable signal generation upon ARG recognition. The biosensor exploits collateral cleavage activity of Cas12a or Cas13a to trigger reporter release in a lyophilized, paper- or microfluidic-based format, facilitating operation without sophisticated laboratory infrastructure. To achieve robust performance, a modular detection framework was developed that supports multiple ARG targets, including blaNDM, blaCTX-M, mecA, and vanA, by optimizing guide RNA design, reaction conditions, and reporter configurations. We implemented a rapid preamplification strategy using isothermal methods compatible with CFS to enhance sensitivity while maintaining a low limit of detection suitable for clinically relevant bacterial loads. In optimization studies, key parameters were evaluated guide RNA specificity and binding efficiency, reaction temperature and time, Mg2+ concentration, and reporter stability under ambient conditions. The integration with a cell-free system provided advantages in biosafety, shelf-life, and ease of use, enabling on-site testing with minimal training. A compact readout platform was developed, leveraging colorimetric and fluorescence reporters to ensure flexibility for low-resource settings. Analytical performance was assessed using contrived and clinical samples spiked with resistant strains, yielding limits of detection in the low copy-number range for targeted ARGs and demonstrating high specificity with negligible cross-reactivity against non-target sequences. The platform demonstrated rapid results within 30–60 minutes from sample processing to readout, satisfying the needs of point-of-care diagnostics and epidemiological surveillance. Furthermore, the study assessed robustness across varying sample matrices, including blood, urine, wound swabs, and environmental water samples, as well as resilience to ambient environmental conditions such as humidity and temperature fluctuations. A user-centric evaluation showed straightforward workflow with minimal pipetting steps and failsafe controls to mitigate false positives/negatives. Prospective clinical validation is proposed to establish diagnostic accuracy against standard PCR-based assays and whole-genome sequencing. The outcomes indicate that the CRISPR-based CFS biosensor provides a versatile, scalable, and portable solution for rapid detection of ARGs, enabling timely therapeutic decisions and enhanced antimicrobial stewardship while contributing to global surveillance efforts against antimicrobial resistance.

Project Overview

What This Project Is About

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A straightforward study of a biosensor that uses CRISPR technology in a cell-free system to detect antibiotic resistance genes found in bacteria. The project explores how these gene signals can be detected quickly without living cells, making tests faster and simpler.

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The Problem It Addresses

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Antibiotic resistance is a growing public health threat. Traditional tests can be slow, delaying treatment decisions. This project looks for a faster, easy-to-use test that can identify resistance genes directly from samples, helping clinicians choose effective antibiotics sooner.

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Objectives of the Project

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1. Understand how CRISPR-based detection works in a cell-free system.
2. Design a simple assay to detect common antibiotic resistance genes.
3. Build and test a prototype biosensor using basic lab materials.
4. Evaluate the assay’s speed, sensitivity, and specificity.
5. Identify potential practical challenges for real-world use.

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What You Will Do Step by Step

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1) Review basic concepts of CRISPR and cell-free systems. 2) Select target resistance genes to detect. 3) Develop a minimal assay protocol. 4) Assemble reagents and run test reactions. 5) Measure outcomes with simple readouts (e.g., color change). 6) Analyze data to determine detection limits. 7) Compare to existing tests. 8) Discuss practical improvements and future work.

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Expected Outcome

A functional, cell-free CRISPR biosensor prototype capable of indicating the presence of selected antibiotic resistance genes, with an assessment of its speed and reliability and a plan for potential real-world deployment.