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Technologies for Emerging Infectious Diseases

Technologies for Emerging Infectious Diseases Undergraduate Fire Talks

Low-Cost Microfluidic Rapid Detection of Antimicrobial-Resistant Bacteria at the Point of Care

Saturday, October 11, 2025

9:00 AM - 9:10 AM PDT

Location: Room 26B

Presenting Author(s)

Samadhi L. Attanayaka

Undergraduate Researcher
Georgia Institute of Technology & Emory University
Kalamazoo, Michigan, United States

Co-Author(s)

AD

Anjana Dissanayaka

PhD Student
Georgia Institute of Technology/Emory University
Atlanta, Georgia, United States
Ali Haider

Medical Student
University of Tennessee Health and Sciences Center
Memphis, Tennessee, United States
Priscilla Delgado, MS

PhD Candidate
Georgia Tech & Emory University, United States
Luyao Shen, PhD

Postdoctoral Researcher
Georgia Tech & Emory, Georgia, United States
AB

Ahmed Babiker, MBBS, MSc

Assistant Professor
Rush University Medical Center, United States
JW

Jesse J. Waggoner

Assistant Professor, Infectious Disease Specialist
Emory University, United States

Last Author(s)

David Myers

assistant professor
Emory, United States

Primary Investigator(s)

David Myers

assistant professor
Emory, United States

Introduction: : Antimicrobial resistance (AMR) has emerged as one of the most pressing global health crises of the 21st century, contributing to an estimated 4.95 million deaths worldwide in 2019 (Antimicrobial Resistance Collaborators, 2022). Among the most concerning contributors are Extended-Spectrum Beta-Lactamase (ESBL)- and AmpC-producing bacteria, which compromise the efficacy of beta-lactam antibiotics—cornerstones of modern infectious disease treatment (Rodríguez-Baño et al., 2018). These multidrug-resistant pathogens are responsible for a wide range of infections, including sepsis, urinary tract infections, and bloodstream infections. As such, they pose a serious threat in intensive care units, surgical wards, and among immunocompromised patients (Derbyshire et al., 2009).

Diagnosis delays often lead clinicians to rely on last-line carbapenems by default, contributing to overuse and accelerating AMR. Early identification of ESBL-, AmpC-, and carbapenemase-producing bacteria enables treatment with safer, targeted antibiotics such as β-lactam/β-lactamase combinations.

Traditional culture-based diagnostics can take over 5 days, encompassing patient admission, culture growth, species identification, and layered susceptibility testing. This procedure delays appropriate therapy and drives empirical broad-spectrum use, especially in high-risk or immunocompromised patients. Here we present a novel microfluidic-based assay for AMR classification that yields rapid results for GNB (gram-negative bacteria) directly from the culture plate. After a single pipette injection, a colorimetric readout is performed 30+ minutes later.

Our key innovations include stabilized, room-temperature reagents and a user-friendly device. Designed for seamless integration into hospital workflows, this platform enables point-of-care deployment, supports antimicrobial stewardship, and offers a critical step forward in combating antibiotic resistance on a global scale

Materials and

Methods: : The device is fabricated from two acrylic sheets bonded via a laser-cut silicone-based dry-adhesive film, allowing for streamlined manufacturing. We have previously reported on a device detecting carbapenamases, and this work expands these results for more forms of AMR alongside device differences. Building on this prior optimization, where incubation steps were eliminated to enhance signal clarity and reduce turnaround time, this platform now extends its application to include rapid detection of ESBLs and AmpCs as seen in Figure 1.

The microfluidic architecture precisely aliquots 100 µL of bacterial suspension into four discrete test chambers. Each chamber is preloaded with specific cephalosporin substrates: imipenem for carbapenemase activity, cefotaxime for ESBL hydrolysis, and cefoxitin for AmpC detection, applied at defined concentrations to ensure specificity and sensitivity. These antibiotics were selected based on their clinical susceptibility profiles and established disk diffusion test standards. Imipenem acts as a substrate for carbapenemase enzymes, cefotaxime targets ESBL-mediated hydrolysis, and cefoxitin serves as a reliable AmpC marker. Enzymatic hydrolysis of these substrates induces a pH-dependent colorimetric change, yielding an easily interpretable visual readout indicative of resistance phenotypes.

Analytical validation was performed using well-characterized clinical isolates harboring carbapenemase, ESBL, and AmpC enzymes. Additionally, device stability and reagent shelf life were assessed over a 28-day period.

Results, Conclusions, and Discussions:: This microfluidic-based diagnostic platform significantly reduces diagnostic latency for detecting ESBL-, AmpC-, and carbapenemase-producing bacteria, offering visual, colorimetric results within 3–30 minutes. Compared to conventional workflows that require 24-48 hours after initial growth for AST (Antimicrobial Susceptibility Testing) reporting, this advancement allows for near-immediate, actionable data for clinical decision-making. Figure 2 presents validation with clinical isolates demonstrating 100% accuracy (5/5 ESBLs, 5/5 carbapenemases, 3/3 AmpCs), highlighting the platform’s diagnostic precision.

Stability testing confirmed a 28-day shelf life for preloaded devices, as seen in Figure 3, increasing utility in decentralized and resource-limited settings. The system’s design of integrating pre-deposited β-lactam substrates and pH-sensitive colorimetric readouts enables intuitive, equipment-free interpretation, removing reliance on centralized laboratories or expert personnel. The platform also facilitates real-time evaluation of β-lactam efficacy, enhancing clinical insight for managing resistant infections and supporting antimicrobial stewardship by guiding targeted therapy.

To minimize subjectivity in result interpretation, an AI/ML-based verification system is under development. This tool will analyze smartphone-captured images of the readouts, providing rapid, reproducible, and automated interpretations. Integration of digital health tools not only improves diagnostic accuracy but also enables streamlined data capture, potential linkage with electronic health records, and expanded access in under-resourced regions.

Despite promising accuracy and usability, validation was conducted on a limited set of clinical isolates. Broader testing across diverse bacterial species and settings is necessary to confirm generalizability. Future efforts will also explore quantitative image analysis and enhanced connectivity for digital reporting.

Overall, this platform represents a critical innovation in infectious disease diagnostic by addressing urgent global needs in combating AMR. By enabling same-day antimicrobial decisions and expanding diagnostic access beyond tertiary centers, it has the potential to reshape how and where resistant infections are identified and treated. It is particularly poised to benefit regions most burdened by AMR, particularly due to low cost of fabrication and long-term shelf stability. By uniting speed, simplicity, and digital innovation, this platform redefines the front lines of infectious disease control, bringing precision diagnostics to the point of care and transforming the global response to antimicrobial resistance.

Acknowledgements and/or References (Optional): :

References:
1. Antimicrobial Resistance Collaborators. (2022). Global burden of bacterial antimicrobial resistance in 2019: A systematic analysis. The Lancet, 399(10325), 629-655. https://doi.org/10.1016/S0140-6736(21)02724-0
2. Aslam, B., Wang, W., Arshad, M. I., Khurshid, M., Muzammil, S., Rasool, M. H., & Nisar, M. A. (2020). Antibiotic resistance: A rundown of a global crisis. Infection and Drug Resistance, 13, 1645-1670. https://doi.org/10.2147/IDR.S247865
3. Derbyshire, E., Wright, D., & Baines, R. (2009). The impact of antimicrobial resistance on healthcare systems. Journal of Infection Prevention, 10(4), 145-152. https://doi.org/10.1177/1757177409340583
4. Rodríguez-Baño, J., Navarro, M. D., Retamar, P., Picón, E., & Pascual, A. (2018). β-Lactamase-producing Enterobacteriaceae in infections: Treatment challenges and clinical outcomes. Clinical Microbiology and Infection, 24(2), 117-123. https://doi.org/10.1016/j.cmi.2017.09.030
5. Zhang, R., Liu, L., Zhou, H., & Li, J. (2021). Rapid detection of ESBL and AmpC β-lactamases in Enterobacteriaceae using molecular techniques. Journal of Clinical Microbiology, 59(3), e02456-20. https://doi.org/10.1128/JCM.02456-20