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3D-printed dip slides miniaturize bacterial identification and antibiotic susceptibility tests allowing direct mastitis sample analysis

Diep, T. T. ORCID:, Bizley, S. ORCID: and Edwards, A. D. ORCID: (2022) 3D-printed dip slides miniaturize bacterial identification and antibiotic susceptibility tests allowing direct mastitis sample analysis. Micromachines, 13 (6). p. 941. ISSN 2072-666X

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To link to this item DOI: 10.3390/mi13060941


The early detection of antimicrobial resistance remains an essential step in the selection and optimization of antibiotic treatments. Phenotypic antibiotic susceptibility testing including the measurement of minimum inhibitory concentration (MIC) remains critical for surveillance and diagnostic testing. Limitations to current testing methods include bulky labware and laborious methods. Furthermore, the requirement of a single strain of bacteria to be isolated from samples prior to antibiotic susceptibility testing delays results. The mixture of bacteria present in a sample may also have an altered resistance profile to the individual strains, and so measuring the susceptibility of the mixtures of organisms found in some samples may be desirable. To enable simultaneous MIC and bacterial species detection in a simple and rapid miniaturized format, a 3D-printed frame was designed for a multi-sample millifluidic dip-slide device that combines panels of identification culture media with a range of antibiotics (Ampicillin, Amoxicillin, Amikacin, Ceftazidime, Cefotaxime, Ofloxacin, Oxytetracycline, Streptomycin, Gentamycin and Imipenem) diluted in Muëller–Hinton Agar. Our proof-of-concept evaluation confirmed that the direct detection of more than one bacterium parallel to measuring MIC in samples is possible, which is validated using reference strains E.coli ATCC 25922, Klebsiella pneumoniae ATCC 13883, Pseudomonas aeruginosa ATCC 10145, and Staphylococcus aureus ATCC 12600 and with mastitis milk samples collected from Reading University Farm. When mixtures were tested, a MIC value was obtained that reflected the most resistant organism present (i.e., highest MIC), suggesting it may be possible to estimate a minimum effective antibiotic concentration for mixtures directly from samples containing multiple pathogens. We conclude that this simple miniaturized approach to the rapid simultaneous identification and antibiotic susceptibility testing may be suitable for directly testing agricultural samples, which is achieved through shrinking conventional tests into a simple “dip-and-incubate” device that can be 3D printed anywhere.

Item Type:Article
Divisions:Life Sciences > School of Chemistry, Food and Pharmacy > School of Pharmacy > Pharmaceutics Research Group
ID Code:105741


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