Droplet Microfluidics: Coding of Experimental Conditions in Microfluidic Droplet Assays Using Colored Beads and Machine Learning Supported Image Analysis (Small 4/2019). Issue 4 (24th January 2019)

• Record Type: Journal Article
• Authors: Svensson, Carl‐Magnus; Shvydkiv, Oksana; Dietrich, Stefanie; Mahler, Lisa; Weber, Thomas; Choudhary, Mahipal; Tovar, Miguel; Figge, Marc Thilo; Roth, Martin
• Is Part Of: Small. Volume 15:Issue 4(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-01-24
• Subjects: antibiotic susceptibility testing -- Bayesian inference -- droplet coding -- droplet microfluidics -- image analysis; Nanotechnology -- Periodicals; Nanoparticles -- Periodicals; Microtechnology -- Periodicals; 620.5
• DOI: 10.1002/smll.201970021
• Languages: English
• ISSNs: 1613-6810

Abstract

Abstract : In article number1802384, Miguel Tovar, Marc Thilo Figge, and co‐workers encode a population of microfluidic pico‐liter droplets with colored polystyrene beads for the simultaneous study of multiple experimental conditions. Droplets are imaged using brightfield microscopy and are successfully decoded and evaluated by machine learning supported image analysis. The novel encoding strategy is applied to antibiotic susceptibility testing of droplet‐encapsulated E. coli bacteria as a proof‐of‐principle.