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3D microfluidic gradient generator for combination antimicrobial susceptibility testing
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DOI：10.1038/s41378-020-00200-7.png)
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Abstract
En 中文
Microfluidic concentration gradient generators (mu -CGGs) have been utilized to identify optimal drug compositions through antimicrobial susceptibility testing (AST) for the treatment of antimicrobial-resistant (AMR) infections. Conventional mu -CGGs fabricated via photolithography-based micromachining processes, however, are fundamentally limited to two-dimensional fluidic routing, such that only two distinct antimicrobial drugs can be tested at once. This work addresses this limitation by employing Multijet-3D-printed microchannel networks capable of fluidic routing in three dimensions to generate symmetric multidrug concentration gradients. The three-fluid gradient generation characteristics of the fabricated 3D mu -CGG prototype were quantified through both theoretical simulations and experimental validations. Furthermore, the antimicrobial effects of three highly clinically relevant antibiotic drugs, tetracycline, ciprofloxacin, and amikacin, were evaluated via experimental single-antibiotic minimum inhibitory concentration (MIC) and pairwise and three-way antibiotic combination drug screening (CDS) studies against model antibiotic-resistant Escherichia coli bacteria. As such, this 3D mu -CGG platform has great potential to enable expedited combination AST screening for various biomedical and diagnostic applications. Microfluidics: 3-D microfluidic gradient generator for antimicrobial susceptibility testingMicrofluidic concentration gradient generators (mu -CGGs) have been used to identify optimal drug compositions through antimicrobial susceptibility testing (AST) to treat antimicrobial-resistant infections, and a new method has been developed to overcome previous 2-D limitations. Conventional mu -CGGs fabricated through photolithography-based micromachining processes are limited to 2-D fluidic routing, which allows only two distinct antimicrobial drugs to be tested simultaneously. However, a team headed by Eric Sweet at the University of California, Berkeley, United States employed 3-D-printed microchannel networks that are capable of 3-D fluidic routing to generate symmetrical multi-drug concentration gradients. The authors were able to confirm their 3-D mu -CGG prototype by means of both theoretical simulations and experimental validations. The team believes that its 3-D mu -CGG platform offers considerable potential for conducting multi-drug AST evaluations for a variety of biomedical and diagnostic applications.
Keywords:
ESCHERICHIA-COLI
ANTIBIOTIC SUSCEPTIBILITY
INHIBITORY CONCENTRATION
BACTERIA
DEVICE
CHIP
INFECTIONS
RESISTANCE
TOXICITY
AMIKACIN
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