PHENOS: a high-throughput and flexible tool for microorganism growth phenotyping on solid media

Abstract

BACKGROUNDMicrobial arrays, with a large number of different strains on a single plate printed with robotic precision, underpin an increasing number of genetic and genomic approaches. These include Synthetic Genetic Array analysis, high-throughput Quantitative Trait Loci (QTL) analysis and 2-hybrid techniques. Measuring the growth of individual colonies within these arrays is an essential part of many of these techniques but is useful for any work with arrays. Measurement is typically done using intermittent imagery fed into complex image analysis software, which is not especially accurate and is challenging to use effectively. We have developed a simple and fast alternative technique that uses a pinning robot and a commonplace microplate reader to continuously measure the thickness of colonies growing on solid agar, complemented by a technique for normalizing the amount of cells initially printed to each spot of the array in the first place. We have developed software to automate the process of combining multiple sets of readings, subtracting agar absorbance, and visualizing colony thickness changes in a number of informative ways.RESULTSThe “PHENOS” pipeline (PHENotyping On Solid media), optimized for Saccharomyces yeasts, produces highly reproducible growth curves and is particularly sensitive to low-level growth. We have empirically determined a formula to estimate colony cell count from an absorbance measurement, and shown this to be comparable with estimates from measurements in liquid. We have also validated the technique by reproducing the results of an earlier QTL study done with conventional liquid phenotyping, and found PHENOS to be considerably more sensitive.CONCLUSIONS“PHENOS” is a cost effective and reliable high-throughput technique for quantifying growth of yeast arrays, and is likely to be equally very useful for a range of other types of microbial arrays. A detailed guide to the pipeline and software is provided with the installation files at https://github.com/gact/phenos.

Restoring fertility in yeast hybrids: Breeding and quantitative genetics of beneficial traits

“…Fitness analysis was done following two different strategies, using either Phenosuite software (Singer Instruments) or the PHENOS platform (94). Details of the phenotypic analysis are given in SI Appendix, Supplementary Methods.…”

Prediction of representative phenotypes using Multi-Attribute Subset Selection

“…A lot of work has been done to characterize the phenotypes of microbes for applications ranging from drug discovery to industrial fermentation (Demain & Sanchez, 2009; Schmidt, 2005). Numerous technologies have been developed to facilitate the generation of these data, including Biolog Phenotype MicroArrays (Bochner, 2009; Hosmer et al, 2022), robotic screening tools (Barton et al, 2018), microfluidics devices (Cario et al, 2022), imaging (Kritikos et al, 2017; Ohya et al, 2005) and multiplexed bioreactors such as the eVolver (Wong et al, 2018). However, compared to the extreme speed in the decrease of sequencing cost, measuring phenotypes is still relatively cost and labor intensive; thus, prioritizing which conditions and organisms to measure is a crucial component of experimental design.…”

Genome-Wide Dynamic Evaluation of the UV-Induced DNA Damage Response

“…Although limited in scalability, liquid micro-culture assays, in which the growth curves of mutant strains are analyzed, permit characterization of dynamic growth responses as well as identification of marginal fitness phenotypes (Warringer et al 2003;Toussaint and Conconi 2006). Recent efforts have been made to improve scalability of growth curve analysis by leveraging existing genetic mutant colony array technology (Hartman and Tippery 2004;Shah et al 2007;Banks et al 2012;Zackrisson et al 2016;Barton et al 2018).…”