Back

A portable and high-integrated 3D microfluidic chip for bacterial quantification and antibiotic susceptibility testing

Wu, W.; Cai, G.; Liu, Y.

2021-11-22 microbiology
10.1101/2021.11.22.469235 bioRxiv
Show abstract

On-site single-cell antibiotic susceptibility testing (sc-AST) provides unprecedented technical potential to improve the treatment of bacterial infections and study heterogeneous resistance to antibiotics. Herein, we developed a portable and high-integrated 3D polydimethylsiloxane (PDMS) chip to perform fast and on-site bacteria quantification and sc-AST. The 3D arrangement of the chambers significantly improved the integration of reaction units ([~]10000/cm2) and widened the dynamic range to 5 orders of magnitude. A capillary valve-based flow distributor was adopted for flow equidistribution in 64 parallel channels and uniform sample loading in as short as 2 s. The degassed PDMS enabled this device to independently dispense the sample into 3D chamber array with almost 100% efficiency. The quantification of Escherichia coli (E. coli) strains with various activity was accomplished in 0.5-2 h, shortened by 20 h in comparison to the traditional plate counting. The functionality of our platform was demonstrated with several effective antibiotics by determining minimum inhibitory concentrations at single-cell level. Furthermore, we utilized the lyophilization of test reagents and needle-mediated reagents rehydration to realize one-step on-site sc-AST. The results indicate that the proposed sc-AST platform is portable, highly sensitive, fast, accurate and user-friendly, thus it has the potential to facilitate precise therapy in time and monitor the treatment. Meanwhile, it could serve as an approach for investigating the mechanisms of heteroresistance at single-cell resolution.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.