Precision Medicine Technologies
Applications of Single Cell Analysis to Disease Studies
The inoculum effect describes a dependency between the minimum inhibitory concentration (MIC) of an antibiotic and the concentration of bacteria in the sample: the less the bacteria, the less concentrated antibiotic is needed to stop their growth. MIC for populations consisting of a single cell is known as single-cell MIC (scMIC). scMIC is important for public health, as the presence of antibiotic at concentration of scMIC in a large population of bacteria drives the evolutionary pressure towards resistant strains1, and the inoculum effect is a source of errors in MIC assessment in the clinic. However, efficient assessment of scMIC values for large numbers of cells has not been shown until now.
Here, we demonstrate a method of determining scMIC values in hundreds of replications per experimental run, and we achieve this without optical labeling of the reaction conditions. We generate a series of emulsions of different concentration of antibiotic at a step emulsifier2. We encapsulate single cells in each emulsion droplet due to stochastic confinement. Each emulsion is separated from the others by being encapsulated in a third immiscible phase, and transferred to a piece of tubing, where all the separated emulsions can be incubated to provide for growth of bacteria. We measured the scMIC value of cefotaxime in E. coli for hundreds of cells, recording the inoculum effect when we used higher initial cell densities, and observing distribution of resistance level in a population of bacteria. Currently, we use our platform to generate up to 20 separate emulsions with different and known reaction conditions of ca. 2000 droplets each with immediate plans to upscale. In the near future we plan to screen for interactions of antibiotics in relation to inoculum effect, including the measurements at the single-cell level.
The described method might be useful in the field of antibiotic resistance at a single-cell level, which is unbiased by the inoculum density. A microfluidic method of screening multiple chemical conditions in emulsions without labeling can be also deployed in other fields of research, wherever several reaction conditions should be replicated hundreds or thousands of times. For now3, to establish whether the bacteria grow or not, we detect fluorescence from fluorescent proteins produced by bacteria, but we are currently working on an add-on module to detect growth without labelling. We are also integrating our system with optical detection of moving droplets to automate the liquid handling protocol.
1 T. Artemova, Y. Gerardin, C. Dudley, N. M. Vega and J. Gore, Mol. Syst. Biol., 2015, 11, 822.
2 W. Postek, T. S. Kaminski and P. Garstecki, Lab Chip, 2017, 17, 1323–1331.
3 W. Postek, P. Gargulinski, O. Scheler, T. S. Kaminski and P. Garstecki, Lab Chip, 2018, 18, 3668–3677.