Open Droplet Microfluidics for Testing Multi-Drug Resistance and Antibiotic Resilience in Bacteria
Taejoon Kong, Nicholas Backes, Gregory Phillips, Santosh Pandey

TL;DR
This paper introduces a droplet microfluidics platform that enables rapid, high-throughput testing of bacterial resistance to multiple antibiotics, combining imaging and search algorithms for efficient analysis.
Contribution
It presents a novel multi-drug screening platform integrating droplet microfluidics, imaging, and algorithms to assess bacterial resilience quickly and accurately.
Findings
Tested 12 antibiotic combinations on resistant bacteria
Detected bacterial resistance within 8 hours
Potential application in biofilms and microbial aggregates
Abstract
New combinations of existing antibiotics are being investigated to combat bacterial resilience. This requires detection technologies with reasonable cost, accuracy, resolution, and throughput. Here, we present a multi -drug screening platform for bacterial cultures by combining droplet microfluidics, search algorithms, and imaging with a wide field of view. We remotely alter the chemical microenvironment around cells and test 12 combinations of resistant cell types and chemicals. Fluorescence intensity readouts allow us to infer bacterial resistance to specific antibiotics within 8 hours. The platform has potential to detect and identify parameters of bacterial resilience in cell cultures, biofilms, and microbial aggregates.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
