Unmixing of fluorescence spectra to resolve quantitative time-series measurements of gene expression in plate readers

BMC Biotechnology

Catherine A Lichten¹  Rachel White³  Ivan BN Clark²  Peter S Swain² 

[1] Department of Physiology, McGill University, Promenade Sir William Osler, Montreal, Canada

[2] SynthSys, University of Edinburgh, Mayfield Road, Edinburgh, UK

[3] Biological Sciences, University of Edinburgh, Mayfield Road, Edinburgh, UK

关键词: Systems biology;    High throughput measurements;    Budding yeast;    Spectral unmixing;    Plate readers;    Fluorescence;    Gene expression;   

Others  :  834911
DOI  :  10.1186/1472-6750-14-11

 received in 2013-11-11, accepted in 2014-01-20,  发布年份 2014

【 摘 要 】

Background

To connect gene expression with cellular physiology, we need to follow levels of proteins over time. Experiments typically use variants of Green Fluorescent Protein (GFP), and time-series measurements require specialist expertise if single cells are to be followed. Fluorescence plate readers, however, a standard in many laboratories, can in principle provide similar data, albeit at a mean, population level. Nevertheless, extracting the average fluorescence per cell is challenging because autofluorescence can be substantial.

Results

Here we propose a general method for correcting plate reader measurements of fluorescent proteins that uses spectral unmixing and determines both the fluorescence per cell and the errors on that fluorescence. Combined with strain collections, such as the GFP fusion collection for budding yeast, our methodology allows quantitative measurements of protein levels of up to hundreds of genes and therefore provides complementary data to high throughput studies of transcription. We illustrate the method by following the induction of the GAL genes in Saccharomyces cerevisiae for over 20 hours in different sugars and argue that the order of appearance of the Leloir enzymes may be to reduce build-up of the toxic intermediate galactose-1-phosphate. Further, we quantify protein levels of over 40 genes, again over 20 hours, after cells experience a change in carbon source (from glycerol to glucose).

Conclusions

Our methodology is sensitive, scalable, and should be applicable to other organisms. By allowing quantitative measurements on a per cell basis over tens of hours and over hundreds of genes, it should increase our understanding of the dynamic changes that drive cellular behaviour.

【 授权许可】

   
2014 Lichten et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

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