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Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale

Journal article
Authors Martin Zackrisson
Johan Hallin
Lars-Göran Ottosson
Peter Dahl
Esteban Fernandez-Parada
Erik Ländström
Luciano Fernandez-Ricaud
Petra Kaferle
Andreas Skyman
Simon Stenberg
Stig Omholt
Uros Petrovic
Jonas Warringer
Anders Blomberg
Published in G3: Genes, Genomes, Genetics
Volume 6
Issue 9
Pages 3003-3014
ISSN 2160-1836
Publication year 2016
Published at Department of marine sciences
Department of Chemistry and Molecular Biology
Pages 3003-3014
Language en
Links dx.doi.org/10.1534/g3.116.032342
www.g3journal.org/content/6/9/3003....
Keywords phenomics, micro biology, genetics, high throughput, mutant, screening, open source
Subject categories Bioanalytical engineering, Bioengineering Equipment, Genetics, Microbiology, Functional genomics

Abstract

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 the 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. We demonstrate the power of the approach by extending and nuancing the known salt-defense biology in baker’s yeast. 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

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