Projects per year
Abstract
Responding to change is a fundamental property of life, making time-series data invaluable in biology. For microbes, plate readers are a popular, convenient means to measure growth and also gene expression using fluorescent reporters. Nevertheless, the difficulties of analysing the resulting data can be a bottleneck, particularly when combining measurements from different wells and plates. Here we present omniplate, a Python module that corrects and normalises plate-reader data, estimates growth rates and fluorescence per cell as functions of time, calculates errors, exports in different formats, and enables meta-analysis of multiple plates. The software corrects for auto fluorescence, the optical density's non-linear dependence on the number of cells, and the effects of the media. We use omniplate to measure the Monod relationship for growth of budding yeast in raffinose, showing that raffinose is a convenient carbon source for controlling growth rates. Using fluorescent tagging, we study yeast's glucose transport. Our results are consistent with the regulation of the hexose transporter (HXT) genes being approximately bipartite: the medium and high affinity transporters are predominately regulated by both the high affinity glucose sensor Snf3 and the kinase complex SNF1 via the repressorsMth1, Mig1, and Mig2; the low affinity transporters are predominately regulated by the low affnity sensor Rgt2 via the co-repressor Std1. We thus demonstrate that omniplate is a powerful tool for exploiting the advantages offered by time-series data in revealing biological regulation.
Original language | English |
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Article number | e1010138 |
Number of pages | 12 |
Journal | PLoS Computational Biology |
Volume | 18 |
Issue number | 5 |
DOIs | |
Publication status | Published - 26 May 2022 |
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Dive into the research topics of 'Analysing and meta-analysing time-series data of microbial growth and gene expression from plate readers'. Together they form a unique fingerprint.Projects
- 2 Finished
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Quantifying and modelling cellular-decision making at the single-cell level
1/09/18 → 30/11/21
Project: Research
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Understanding the regulation of glucose sensing and transport in budding yeast using dynamic inputs
6/01/18 → 30/11/21
Project: Research
Datasets
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Analysing and meta-analysing time-series data of microbial growth and gene expression from plate readers
Montano Gutierrez, L. F. (Creator), Manzanaro Moreno, N. (Creator) & Swain, P. (Creator), Edinburgh DataShare, 16 Dec 2021
DOI: 10.7488/ds/3263
Dataset