Literature DB >> 16912038

Conversion of a putative Agrobacterium sugar-binding protein into a FRET sensor with high selectivity for sucrose.

Ida Lager1, Loren L Looger, Melanie Hilpert, Sylvie Lalonde, Wolf B Frommer.   

Abstract

Glucose is the main sugar transport form in animals, whereas plants use sucrose to supply non-photosynthetic organs with carbon skeletons and energy. Many aspects of sucrose transport, metabolism, and signaling are not well understood, including the route of sucrose efflux from leaf mesophyll cells and transport across vacuolar membranes. Tools that can detect sucrose with high spatial and temporal resolution in intact organs may help elucidate the players involved. Here, FRET sensors were generated by fusing putative sucrose-binding proteins to green fluorescent protein variants. Plant-associated bacteria such as Rhizobium and Agrobacterium can use sucrose as a nutrient source; sugar-binding proteins were, thus, used as scaffolds for developing sucrose nanosensors. Among a set of putative sucrose-binding protein genes cloned in between eCFP and eYFP and tested for sugar-dependent FRET changes, an Agrobacterium sugar-binding protein bound sucrose with 4 mum affinity. This FLIPsuc-4mu protein also recognized other sugars including maltose, trehalose, and turanose and, with lower efficiency, glucose and palatinose. Homology modeling enabled the prediction of binding pocket mutations to modulate the relative affinity of FLIPsuc-4mu for sucrose, maltose, and glucose. Mutant nanosensors showed up to 50- and 11-fold increases in specificity for sucrose over maltose and glucose, respectively, and the sucrose binding affinity was simultaneously decreased to allow detection in the physiological range. In addition, the signal-to-noise ratio of the sucrose nanosensor was improved by linker engineering. This novel reagent complements FLIPs for glucose, maltose, ribose, glutamate, and phosphate and will be used for analysis of sucrose-derived carbon flux in bacterial, fungal, plant, and animal cells.

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Year:  2006        PMID: 16912038     DOI: 10.1074/jbc.M605257200

Source DB:  PubMed          Journal:  J Biol Chem        ISSN: 0021-9258            Impact factor:   5.157


  26 in total

1.  Optical sensors for monitoring dynamic changes of intracellular metabolite levels in mammalian cells.

Authors:  Bi-Huei Hou; Hitomi Takanaga; Guido Grossmann; Li-Qing Chen; Xiao-Qing Qu; Alexander M Jones; Sylvie Lalonde; Oliver Schweissgut; Wolfgang Wiechert; Wolf B Frommer
Journal:  Nat Protoc       Date:  2011-10-27       Impact factor: 13.491

Review 2.  Fluxomics: mass spectrometry versus quantitative imaging.

Authors:  Wolfgang Wiechert; Oliver Schweissgut; Hitomi Takanaga; Wolf B Frommer
Journal:  Curr Opin Plant Biol       Date:  2007-05-03       Impact factor: 7.834

3.  Fluxomics with ratiometric metabolite dyes.

Authors:  Bhavna Chaudhuri; Totte Niittylä; Friederike Hörmann; Wolf B Frommer
Journal:  Plant Signal Behav       Date:  2007-03

4.  Circular permutation of ligand-binding module improves dynamic range of genetically encoded FRET-based nanosensor.

Authors:  Satoshi Okada; Kazuhisa Ota; Takashi Ito
Journal:  Protein Sci       Date:  2009-12       Impact factor: 6.725

Review 5.  Role of green fluorescent proteins and their variants in development of FRET-based sensors.

Authors:  Neha Soleja; Ovais Manzoor; Imran Khan; Altaf Ahmad; Mohd Mohsin
Journal:  J Biosci       Date:  2018-09       Impact factor: 1.826

6.  Rapid metabolism of glucose detected with FRET glucose nanosensors in epidermal cells and intact roots of Arabidopsis RNA-silencing mutants.

Authors:  Karen Deuschle; Bhavna Chaudhuri; Sakiko Okumoto; Ida Lager; Sylvie Lalonde; Wolf B Frommer
Journal:  Plant Cell       Date:  2006-08-25       Impact factor: 11.277

7.  Protonophore- and pH-insensitive glucose and sucrose accumulation detected by FRET nanosensors in Arabidopsis root tips.

Authors:  Bhavna Chaudhuri; Friederike Hörmann; Sylvie Lalonde; Siobhan M Brady; David A Orlando; Philip Benfey; Wolf B Frommer
Journal:  Plant J       Date:  2008-09-18       Impact factor: 6.417

8.  Bridging the gap between in vitro and in vivo RNA folding.

Authors:  Kathleen A Leamy; Sarah M Assmann; David H Mathews; Philip C Bevilacqua
Journal:  Q Rev Biophys       Date:  2016-06-24       Impact factor: 5.318

9.  A genetically encoded metabolite sensor for malonyl-CoA.

Authors:  Jessica M Ellis; Michael J Wolfgang
Journal:  Chem Biol       Date:  2012-10-26

Review 10.  Comparison of quantitative metabolite imaging tools and carbon-13 techniques for fluxomics.

Authors:  Totte Niittylae; Bhavna Chaudhuri; Uwe Sauer; Wolf B Frommer
Journal:  Methods Mol Biol       Date:  2009
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