Abstract
Strain engineering has been traditionally centered on the use of mutation, selection, and screening to develop improved strains. Although mutational and screening methods are well-characterized, selection remains poorly understood. We hypothesized that we could use a genome-wide method for assessing laboratory selections to design selections with enhanced sensitivity (true positives) and specificity (true negatives) towards a single desired phenotype. To test this hypothesis, we first applied multi-SCale Analysis of Library Enrichments (SCALEs) to identify genes conferring increased fitness in continuous flow selections with increasing levels of 3-hydroxypropionic acid (3-HP). We found that this selection not only enriched for 3-HP tolerance phenotypes but also for wall adherence phenotypes (41% false positives). Using this genome-wide data, we designed a serial-batch selection with a decreasing 3-HP gradient. Further examination by ROC analysis confirmed that the serial-batch approach resulted in significantly increased sensitivity (46%) and specificity (10%) for our desired phenotype (3-HP tolerance). © 2008 Elsevier Inc. All rights reserved.
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Warnecke, T. E., Lynch, M. D., Karimpour-Fard, A., Sandoval, N., & Gill, R. T. (2008). A genomics approach to improve the analysis and design of strain selections. Metabolic Engineering, 10(3–4), 154–165. https://doi.org/10.1016/j.ymben.2008.04.004
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