TitleDynamic analysis of MAPK signaling using a high-throughput microfluidic single-cell imaging platform.
Publication TypeJournal Article
Year of Publication2009
AuthorsTaylor, RJ, Falconnet, D, Niemistö, A, Ramsey, SA, Prinz, S, Shmulevich, I, Galitski, T, Hansen, CL
JournalProc Natl Acad Sci U S A
Date Published2009 Mar 10
KeywordsImaging, Three-Dimensional, MAP Kinase Signaling System, Mating Factor, Microfluidics, Mutation, Peptides, Phenotype, Pheromones, Saccharomyces cerevisiae

Cells have evolved biomolecular networks that process and respond to changing chemical environments. Understanding how complex protein interactions give rise to emergent network properties requires time-resolved analysis of cellular response under a large number of genetic perturbations and chemical environments. To date, the lack of technologies for scalable cell analysis under well-controlled and time-varying conditions has made such global studies either impossible or impractical. To address this need, we have developed a high-throughput microfluidic imaging platform for single-cell studies of network response under hundreds of combined genetic perturbations and time-varying stimulant sequences. Our platform combines programmable on-chip mixing and perfusion with high-throughput image acquisition and processing to perform 256 simultaneous time-lapse live-cell imaging experiments. Nonadherent cells are captured in an array of 2,048 microfluidic cell traps to allow for the imaging of eight different genotypes over 12 h and in response to 32 unique sequences of stimulation, generating a total of 49,000 images per run. Using 12 devices, we carried out >3,000 live-cell imaging experiments to investigate the mating pheromone response in Saccharomyces cerevisiae under combined genetic perturbations and changing environmental conditions. Comprehensive analysis of 11 deletion mutants reveals both distinct thresholds for morphological switching and new dynamic phenotypes that are not observed in static conditions. For example, kss1Delta, fus3Delta, msg5Delta, and ptp2Delta mutants exhibit distinctive stimulus-frequency-dependent signaling phenotypes, implicating their role in filtering and network memory. The combination of parallel microfluidic control with high-throughput imaging provides a powerful tool for systems-level studies of single-cell decision making.

Alternate JournalProc Natl Acad Sci U S A
PubMed ID19223588
PubMed Central IDPMC2644260
Grant ListP50 GM076547 / GM / NIGMS NIH HHS / United States
R21 EB005757 / EB / NIBIB NIH HHS / United States
P50-GM076547 / GM / NIGMS NIH HHS / United States
R21 EB005757-01 / EB / NIBIB NIH HHS / United States