Genetic interaction mapping with microfluidic-based single cell sequencing

• Published in: PloS one Vol. 12; no. 2; p. e0171302
• Main Authors: Haliburton, John R., Shao, Wenjun, Deutschbauer, Adam, Arkin, Adam, Abate, Adam R.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 07.02.2017; Public Library of Science (PLoS)
• Subjects: Adaptation; Analysis; Bacteria; Bioengineering; Biology; Biology and Life Sciences; Cell culture; Chromosome Mapping - methods; Decision making; Deoxyribonucleic acid; DNA; DNA sequencing; E coli; Engineering and Technology; Epistasis, Genetic; Escherichia coli; Gene Library; Gene mapping; Gene sequencing; Genes; Genetic aspects; Genetic engineering; Genomes; Genomics; High-Throughput Nucleotide Sequencing - methods; Lab-On-A-Chip Devices; Laboratories; Library collections; Mapping; Medical screening; Metabolism; Methods; Microfluidics; Microorganisms; Nucleotide sequence; Proteins; Research and Analysis Methods; Saccharomyces cerevisiae; Science; Science & Technology - Other Topics; Single-Cell Analysis; Studies; Yeast; United States > US; San Francisco California; California
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0171302

Genetic interaction mapping is useful for understanding the molecular basis of cellular decision making, but elucidating interactions genome-wide is challenging due to the massive number of gene combinations that must be tested. Here, we demonstrate a simple approach to thoroughly map genetic interactions in bacteria using microfluidic-based single cell sequencing. Using single cell PCR in droplets, we link distinct genetic information into single DNA sequences that can be decoded by next generation sequencing. Our approach is scalable and theoretically enables the pooling of entire interaction libraries to interrogate multiple pairwise genetic interactions in a single culture. The speed, ease, and low-cost of our approach makes genetic interaction mapping viable for routine characterization, allowing the interaction network to be used as a universal read out for a variety of biology experiments, and for the elucidation of interaction networks in non-model organisms.