Glucose levels are maintained within tight limits to ascertain sufficient energy supply to the brain and other peripheral organs and to prevent accumulation to toxic concentrations. Homeostasis is achieved by the hormones insulin and glucagon, affecting glucose uptake, release and metabolism in glucose-responsive tissues. The response of mammalian cells to fluctuations in glucose levels is of major relevance, since alterations are important for pathological conditions, i.e. obesity or type-2 diabetes. It is well established that yeast and other organisms use a complex set of signaling networks to control sugar flux, e.g. to acclimate uptake to availability and needs of the cell, however little is still known about the mechanisms that control glucose flux in glucose-responsive tissues in human cells [1
]. Similar as in yeast, the human genome encodes more than 10 glucose uniporters (GLUTs) for uptake and release and several hexokinases for metabolism. Given that sugars serve as signaling molecules in many organisms, it is conceivable that besides the insulin/glucagon system it also influences other mechanisms to control sugar flux. The recent availability of large siRNA collections in combination with imaging based screening systems have enabled genome-wide screens for signaling components [2
]. Similar screens could be performed if suitable high throughput detection systems would be available for glucose.
To monitor the glucose flux in living cells, a FRET glucose-imaging platform has recently been developed consisting of a set of sensors with different affinity for glucose. These glucose nanosensors exploit resonance energy transfer between a coupled pair of cyan and yellow fluorescent proteins (eYFP, eCFP) to detect conformational changes induced by sugar-binding [3
]. The glucose-binding domain was derived from chemotactic receptors of bacteria, namely the glucose/galactose binding protein of E. coli
(MglB). A decrease in energy transfer was observed upon glucose binding for the first generation of FRET sensors [5
]. While this sensor was used successfully to monitor glucose flux in the cytosol, nucleus and ER of COS-7 or HepG2 cells, both the range of FLIPglu-600μ () as well as the signal-to-noise ratio (SNR) appear too limited and would thus reduce the discovery rate in high throughput screens for signaling components via siRNA [5
Figure 1 In vivo detection range of FLIP nanosensors. The detection range of FLII12Pglu-700μδ 6 (pink) and FLIPglu-600μ (blue) was determined using in vivo FRET measurements (shown in ). The eCFP/(Ctrine-eYFP) emission ratio was normalized (more ...)
As a first step to make the sensors more robust, the Ph and chloride-sensitive eYFP was replaced by citrine [6
]. Glucose sensors with improved SNR and a larger dynamic range had been developed by two approaches, namely linker deletions and by insertion of the fluorophore into the backbone of MglB with the rationale of decreasing the degrees of freedom of rotation of the fluorophores [7
]. The artificial linker and less well-structured domains at the termini of MglB and eCFP and MglB and Citrine-eYFP variants (together comprising the “composite linker”) presumably allow flexible rotation of Citrine-eYFP and thus affect the probability of obtaining a productive resonance energy transfer [7
]. Deletion of these domains lead to FLIPglu-600μ 13 which showed a over four times higher ratio change compared to the original sensor. The insertional sensor FLII12
Pglu-600μ showed a >10 times higher ratio change over the original FLIPglu-600μ as determined in vitro
. Here, the two strategies were combined to improve in vivo
SNR and thus the detection range.
The improved FRET-sensors, which cover the physiological blood glucose range, were used to determine the contribution of GLUT glucose uniporters to glucose uptake in HepG2 cells using qPCR, GFP fusions as well as a GLUT siRNA collection in a small imaging-based screen. The results demonstrate the feasibility of high throughput screens using the novel FRET sensors and shows that GLUT1 and GLUT9 are the major contributors to glucose uptake in HepG2 cells.