Rapid antibiotic susceptibility testing and species identification for mixed infections
Kandavalli, V.; Karempudi, P.; Larsson, J.; Elf, J.
Show abstract
Antimicrobial resistance is an increasing problem globally. Rapid antibiotic susceptibility testing (AST) is urgently needed in the clinic to enable personalized prescription in high-resistance environments and limit the use of broad-spectrum drugs. Previously we have described a 30 min AST method based on imaging of individual bacterial cells. However, current phenotypic AST methods do not include species identification (ID), leaving time-consuming plating or culturing as the only available option when ID is needed to make the sensitivity call. Here we describe a method to perform phenotypic AST at the single-cell level in a microfluidic chip that allows subsequent genotyping by in situ FISH. By stratifying the phenotypic AST response on the species of individual cells, it is possible to determine the susceptibility profile for each species in a mixed infection sample in 1.5 h. In this proof-of-principle study, we demonstrate the operation with four antibiotics and a mixed sample with four species.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Tracking bacterial lineages in complex and dynamic environments with applications to growth control and persistence 96%
- Rational Design of Frontline Institutional Phage Cocktail for the Treatment of Nosocomial Enterobacter cloacae Complex Infections 93%
- Phosphate starvation stops bacteria digesting algal fucan that sequesters carbon 93%
Similar papers in this journal
- Single-cell motion of magnetotactic bacteria in microfluidic confinement: interplay between surface interaction and magnetic torque 95%
- HyDrop: droplet-based scATAC-seq and scRNA-seq using dissolvable hydrogel beads 94%
- Modular DNA Barcoding of Nanobodies Enables Multiplexed in situ Protein Imaging and High-throughput Biomolecule Detection 94%
Similar papers in this journal
- Cell-free expression with a quartz crystal microbalance enables rapid, dynamic, and label-free characterization of membrane-interacting proteins 94%
- A multiscale 3D chemotaxis assay reveals bacterial navigation mechanisms 94%
- Harnessing droplet microfluidics and morphology-based deep learning for the label-free study of polymicrobial-phage interactions 93%
"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.