Protocol | Published:

Optical sensors for measuring dynamic changes of cytosolic metabolite levels in yeast

Nature Protocols volume 6, pages 18061817 (2011) | Download Citation

Abstract

Optical sensors allow dynamic quantification of metabolite levels with subcellular resolution. Here we describe protocols for analyzing cytosolic glucose levels in yeast using genetically encoded Förster resonance energy transfer (FRET) sensors. FRET glucose sensors with different glucose affinities (Kd) covering the low nano- to mid- millimolar range can be targeted genetically to the cytosol or to subcellular compartments. The sensors detect the glucose-induced conformational change in the bacterial periplasmic glucose/galactose binding protein MglB using FRET between two fluorescent protein variants. Measurements can be performed with a single sensor or multiple sensors in parallel. In one approach, cytosolic glucose accumulation is measured in yeast cultures in a 96-well plate using a fluorimeter. Upon excitation of the cyan fluorescent protein (CFP), emission intensities of CFP and YFP (yellow fluorescent protein) are captured before and after glucose addition. FRET sensors provide temporally resolved quantitative data of glucose for the compartment of interest. In a second approach, reversible changes of cytosolic free glucose are measured in individual yeast cells trapped in a microfluidic platform, allowing perfusion of different solutions while FRET changes are monitored in a microscope setup. By using the microplate fluorimeter protocol, 96 cultures can be measured in less than 1 h; analysis of single cells of a single genotype can be completed in <2 h. FRET-based analysis has been performed with glucose, maltose, ATP and zinc sensors, and it can easily be adapted for high-throughput screening using a wide spectrum of sensors.

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Acknowledgements

This work was made possible by grants to W.B.F. from National Institutes of Health (National Institute of Diabetes and Digestive and Kidney Diseases; 1RO1DK079109). Frommer lab members are acknowledged for helpful discussions in the preparation of this protocol.

Author information

Author notes

    • Clara Bermejo
    • , Farzad Haerizadeh
    •  & Hitomi Takanaga

    Present addresses: Codexis, Inc., Redwood City, California, USA (C.B.); Life Technologies Corporation, Carlsbad, California, USA (F.H.); Santen Inc., Napa, California, USA (H.T).

Affiliations

  1. Carnegie Institution for Science, Stanford, California, USA.

    • Clara Bermejo
    • , Farzad Haerizadeh
    • , Hitomi Takanaga
    • , Diane Chermak
    •  & Wolf B Frommer

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Contributions

C.B., F.H., H.T. and W.B.F. designed research; C.B., F.H., H.T. and D.C. performed research; C.B., F.H., H.T., D.C. and W.B.F. analyzed the data; C.B., F.H. and W.B.F. wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Wolf B Frommer.

Supplementary information

Excel files

  1. 1.

    Supplementary Data 1

    A data set of CFP and YFP variant intensities over time are located in the A-H columns of the spreadsheet. Background subtraction and ratios are calculated in the columns J-O of the spreadsheet. Columns P-V include the reorganized ratios over the time for the same culture. Normalization of the ratios is performed in columns X-AD. Graphs are displayed in columns AE-AK of the spreadsheet. Average of three different transformants and graphs are shown in columns AM-BA of the spreadsheet.

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DOI

https://doi.org/10.1038/nprot.2011.391

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