A 3D-printed microfluidic gradient generator with integrated photonic silicon sensors for rapid antimicrobial susceptibility testing

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Heuer, C.; Preuss, J.-A.; Buttkewitz, M.; Scheper, T.; Segal, E. et al.: A 3D-printed microfluidic gradient generator with integrated photonic silicon sensors for rapid antimicrobial susceptibility testing. In: Lab on a Chip 22 (2022), Nr. 24, S. 4950-4961. DOI: https://doi.org/10.1039/d2lc00640e

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/13904

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Abstract: 
With antimicrobial resistance becoming a major threat to healthcare settings around the world, there is a paramount need for rapid point-of-care antimicrobial susceptibility testing (AST) diagnostics. Unfortunately, most currently available clinical AST tools are lengthy, laborious, or are simply inappropriate for point-of-care testing. Herein, we design a 3D-printed microfluidic gradient generator that automatically produces two-fold dilution series of clinically relevant antimicrobials. We first establish the compatibility of these generators for classical AST (i.e., broth microdilution) and then extend their application to include a complete on-chip label-free and phenotypic AST. This is accomplished by the integration of photonic silicon chips, which provide a preferential surface for microbial colonization and allow optical tracking of bacterial behavior and growth at a solid-liquid interface in real-time by phase shift reflectometric interference spectroscopic measurements (PRISM). Using Escherichia coli and ciprofloxacin as a model pathogen-drug combination, we successfully determine the minimum inhibitory concentration within less than 90 minutes. This gradient generator-based PRISM assay provides an integrated AST device that is viable for convenient point-of-care testing and offers a promising and most importantly, rapid alternative to current clinical practices, which extend to 8-24 h.
License of this version: CC BY-NC 3.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2022
Appears in Collections:Naturwissenschaftliche Fakultät

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pos. country downloads
total perc.
1 image of flag of Germany Germany 19 43.18%
2 image of flag of United States United States 13 29.55%
3 image of flag of Czech Republic Czech Republic 6 13.64%
4 image of flag of Russian Federation Russian Federation 3 6.82%
5 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 1 2.27%
6 image of flag of Indonesia Indonesia 1 2.27%
7 image of flag of Brazil Brazil 1 2.27%

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