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Scan-o-matic: high-resolution microbial phenomics at a massive scale

Martin Zackrisson, Johan Hallin, Lars-Göran Ottosson, Peter Dahl, Esteban Fernandez-Parada, Erik Ländström, Luciano Fernandez-Ricaud, Petra Kaferle, Andreas Skyman, Stig Omholt, Uros Petrovic, Jonas Warringer, Anders Blomberg
doi: https://doi.org/10.1101/031443
Martin Zackrisson
1Department of Chemistry and Molecular Biology, University of Gothenburg, PO Box 462, 40530 Gothenburg, Sweden
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Johan Hallin
2IRCAN, CNRS UMR 6267, INSERM U998, University of Nice, 06107 Nice, France
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Lars-Göran Ottosson
1Department of Chemistry and Molecular Biology, University of Gothenburg, PO Box 462, 40530 Gothenburg, Sweden
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Peter Dahl
1Department of Chemistry and Molecular Biology, University of Gothenburg, PO Box 462, 40530 Gothenburg, Sweden
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Esteban Fernandez-Parada
1Department of Chemistry and Molecular Biology, University of Gothenburg, PO Box 462, 40530 Gothenburg, Sweden
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Erik Ländström
1Department of Chemistry and Molecular Biology, University of Gothenburg, PO Box 462, 40530 Gothenburg, Sweden
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Luciano Fernandez-Ricaud
7Department of Marine Sciences, University of Gothenburg, PO Box 462, 40530 Gothenburg, Sweden
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Petra Kaferle
3Department of Molecular and Biomedical Sciences, Jozef Stefan Institute, Jamova 39, SI-1000 Ljubljana, Slovenia
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Andreas Skyman
4Department of Earth and Space Sciences, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden
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Stig Omholt
5NTNU Norwegian University of Science and Technology, Faculty of Natural Sciences and Technology, Department of Biotechnology, N-7491 Trondheim, Norway
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Uros Petrovic
3Department of Molecular and Biomedical Sciences, Jozef Stefan Institute, Jamova 39, SI-1000 Ljubljana, Slovenia
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Jonas Warringer
1Department of Chemistry and Molecular Biology, University of Gothenburg, PO Box 462, 40530 Gothenburg, Sweden
6Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences (UMB), PO Box 5003, 1432 Ås, Norway
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Anders Blomberg
7Department of Marine Sciences, University of Gothenburg, PO Box 462, 40530 Gothenburg, Sweden
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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. 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.

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Posted November 12, 2015.
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Scan-o-matic: high-resolution microbial phenomics at a massive scale
Martin Zackrisson, Johan Hallin, Lars-Göran Ottosson, Peter Dahl, Esteban Fernandez-Parada, Erik Ländström, Luciano Fernandez-Ricaud, Petra Kaferle, Andreas Skyman, Stig Omholt, Uros Petrovic, Jonas Warringer, Anders Blomberg
bioRxiv 031443; doi: https://doi.org/10.1101/031443
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Scan-o-matic: high-resolution microbial phenomics at a massive scale
Martin Zackrisson, Johan Hallin, Lars-Göran Ottosson, Peter Dahl, Esteban Fernandez-Parada, Erik Ländström, Luciano Fernandez-Ricaud, Petra Kaferle, Andreas Skyman, Stig Omholt, Uros Petrovic, Jonas Warringer, Anders Blomberg
bioRxiv 031443; doi: https://doi.org/10.1101/031443

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