Ladder-shaped microfluidic systems for rapid antibiotic susceptibility testing

The possibility of rapidly identifying antibiotic resistant bacteria can play a significant role in solving the global antibiotic crisis by facilitating the targeted and timely administration of pharmaceutical drugs. At present, ...

In a new report now published in Communications Engineering , Ann V. Nguyen and a research team at the Cornell University, New York, reported the development of a microfluidic system with a ladder-shaped design to generate a two-fold serial dilution of antibiotics, suited for national and international testing standards. The design and application process allowed them to scale-down the testing timeframe of antibiotic susceptibility to about 4–5 hours. The research outcomes were consistent with commercially available kits to provide an adaptable and efficient diagnostic tool for antibiotic susceptibility testing.

Antibiotic resistance and antibiotic susceptibility testing The effects of antibiotic resistance are world-wide, and are credited to antibiotic overuse in human and veterinary medicine, and is associated with defects in animal handling . Researchers have noted the cause to be due to overprescribed antibiotics, and a lack of rapid laboratory tests and the circulation of prescription antibiotics that are only marginally effective. The capacity to develop and use rapid diagnostic tests can identify and characterize resistant bacteria to combat antibiotic resistance . The existing workflow of diagnosing antibacterial infection usually takes up to 2–3 days, during which a patient undergoes isolation, sensitivity, and identification .

Device design and principle of operation. (a) A schematic representation of the ladder microfluidic system including an on-chip water bath. Insets showing the key features of the device: (i) the microchamber triplicates, (ii) the modified serpentine mixer, and (iii) the hydraulic resistor pinch on the side channels. (b) The protocol for platform operation: (i) device is loaded with bacteria suspension (blue), then (ii) loaded with culture medium containing antibiotic (red) and culture medium alone (blue) from two different inlets. The LCGG automatically generates a stable exponential decay concentration gradient of antibiotic, which diffuses into the microchambers. Finally, (iii) the channels are washed with oil (yellow), after a certain loading time, to isolate the microchambers. (c) The fluorescent intensities of resazurin in selected microchambers (M1–M9; PC = positive growth control) changes after 4–5 h of incubation at 37°C indicating bacteria metabolism. Three scenarios are possible where the test shows (i) a minimum inhibitory concentration (MIC) for the bacteria/antibiotic combination, (ii) resistance or MIC higher than the testing range, and (iii) invalid result due to no growth of bacteria. Credit: Communications Engineering (2023). DOI: 10.1038/s44172-023-00064-5 Read more

Computational fluid dynamics simulation and the pressure nodes network. (a) Flow distribution in the ladder. In the inset unique numbers are assigned to the pressure nodes before and after each resistor feature, and at the junctions. The red arrows show the direction of the flow. (i and k) are counters for the resistors and nodes, respectively. (b) Contours of pressure for constriction of (i) L = 420 μm (ii) L = 1650 μm (iii) L = 4950 μm and (iv) the standard mixer resistors for the flow rate of 130 μL h−1 for each of the channels. (c) The pressure at the inlet of the features in A. (d) Hydraulic resistance of the constriction, as a function of the length for width of 40 μm. Simulations for seven constrictions are shown (L = 420 μm, 1649 μm, 4070 μm, 4949 μm, 7990 μm, 10795 μm). At L = 655 μm, the hydraulic resistance of the constriction is equal to that of the mixer. (e) Ratio of the flow rates of the drug and the diluent at their respective inlets will affect the concentration profile of the microchambers. These results are from network simulations. (f) The dilution factor in the Concentration(%)=50×E1−i needs to be E = 2, where i is the chamber number. The formula is fitted to the results in the part E to solve for E using least square algorithm. Credit: Communications Engineering (2023). DOI: 10.1038/s44172-023-00064-5 Read more

Characterization of the concentration gradient. (a) images of the microchambers showing the process of molecules diffusing into the microchambers from the main channel at t = 0 s and t = 3 min, and after the main channel is washed with oil. (b) the average concentration of resazurin diffused into the microchambers over time, represented as the area under the curve of the concentration profile at each time point (n = 5). (c) the concentration profile formed in ten microchambers of the ladder microfluidic system after a loading time of three min (n = 3). (d) linear correlation between the concentration profiles from computer simulation, of resazurin, fluorescein, and Calcein formed in the ladder microfluidic system, and theoretical 2-fold dilution concentration profile. (e) Comparison of the concentration profiles of resazurin, fluorescein, and Calcein loaded with their specific loading time and theoretical profile. Dash line with blue zone shows the theoretical concentration profile with 5% error. All data are shown as average ±standard deviation. Credit: Communications Engineering (2023). DOI: 10.1038/s44172-023-00064-5 Read more

a Comparison of match vs. un-match between MICs obtained on-chip using the ladder microfluidic system and the gold standard method conducted at veterinary diagnostic lab. Targeted bacteria are Escherichia coli (EC), Proteus mirabilis (PRM), Enterococcus faecalis (EF), and Staphylococcus pseudintermedius (SP). b Detailed percentage of matched vs. unmatched for each antibiotic/bacteria combination. c Probability of obtaining an accurate MIC for each antibiotic/bacteria combination. Credit: Communications Engineering (2023). DOI: 10.1038/s44172-023-00064-5 Read more