(Dr.Payam Ghiaci)Scan-o-matic: A platform for massive directed evolution

Dr.Payam Ghiaci: Post- Doc Reasercher at  Chalmers University of Technology

The capacity to map traits over large cohorts of individuals - phenomics - lags far behind the explosive development in genomics. For microbes the estimation of growth is the key phenotype because of its link to fitness. We introduce an automated microbial phenomics framework that delivers accurate, precise and highly resolved growth phenotypes at an unprecedented scale. Advancements were achieved through introduction of transmissive scanning hardware and software technology, frequent acquisition of exact colony population size measurements, extraction of population growth rates from growth curves and removal of spatial bias by reference-surface normalization. Our prototype arrangement automatically records and analyzes close to 100,000 growth curves in parallel. The introduced framework represents a major advance in microbial phenomics by providing high-quality data for extensive cohorts of individuals and generating well-populated and standardized phenomics databases. Couple of real-life applications of this platform will be presented as well.