RT Journal Article
SR Electronic
T1 Scan-o-matic: high-resolution microbial phenomics at a massive scale
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 031443
DO 10.1101/031443
A1 Zackrisson, Martin
A1 Hallin, Johan
A1 Ottosson, Lars-Göran
A1 Dahl, Peter
A1 Fernandez-Parada, Esteban
A1 Ländström, Erik
A1 Fernandez-Ricaud, Luciano
A1 Kaferle, Petra
A1 Skyman, Andreas
A1 Omholt, Stig
A1 Petrovic, Uros
A1 Warringer, Jonas
A1 Blomberg, Anders
YR 2015
UL http://biorxiv.org/content/early/2015/11/12/031443.abstract
AB 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. We introduce an automated microbial phenomics framework that delivers accurate and highly resolved growth phenotypes at an unprecedented scale. Advancements were achieved through introduction of transmissive scanning hardware and software technology, frequent acquisition of precise 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 analyses 100,000 experiments in parallel. We demonstrate the power of the approach by extending and nuancing the known salt defence biology in baker’s yeast. The introduced framework will have a transformative impact by providing high-quality microbial phenomics data for extensive cohorts of individuals and generating well-populated and standardized phenomics databases.