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.
"No specific sucrose-binding periplasmic binding proteins have been found in bacteria. Since microorganisms in the rhizosphere developed sucrosesensing protein, several candidates from Rhizobium and Agrobacterium were tested, and a homologue of the rhizobial protein (ThuE) from A. tumefacians was found to bind sucrose (Lager et al. 2006). Sucrosebinding protein, ThuE, was then fused to the ECFP and EYFP. "
[Show abstract][Hide abstract] ABSTRACT: Neighboring cells in the same tissue can exist in different states of dynamic activities. After genomics, proteomics and metabolomics, fluxomics is now equally important for generating accurate quantitative information on the cellular and sub-cellular dynamics of ions and metabolite, which is critical for functional understanding of organisms. Various spectrometry techniques are used for monitoring ions and metabolites, although their temporal and spatial resolutions are limited. Discovery of the fluorescent proteins and their variants has revolutionized cell biology. Therefore, novel tools and methods targeting sub-cellular compartments need to be deployed in specific cells and targeted to sub-cellular compartments in order to quantify the target-molecule dynamics directly. We require tools that can measure cellular activities and protein dynamics with sub-cellular resolution. Biosensors based on fluorescence resonance energy transfer (FRET) are genetically encoded and hence can specifically target sub-cellular organelles by fusion to proteins or targetted sequences. Since last decade, FRET-based genetically encoded sensors for molecules involved in energy production, reactive oxygen species and secondary messengers have helped to unravel key aspects of cellular physiology. This review, describing the design and principles of sensors, presents a database of sensors for different analytes/processes, and illustrate examples of application in quantitative live cell imaging.
"amino acid terminal truncations; aid: ABA interaction domain; cd: catalytic domain; ed, m: enhanced dimerization or monomeric variant DOI: 10.7554/eLife.01741.003 Research article Gu et al., 2006; Lager et al., 2006). Sensory domain proteolysis was circumvented by using a protease-deficient yeast strain (strain BJ5465 lacking Pep4 and Prb1, Figure 2) for expression and purification. "
[Show abstract][Hide abstract] ABSTRACT: Cytosolic hormone levels must be tightly controlled at the level of influx, efflux, synthesis, degradation and compartmentation. To determine ABA dynamics at the single cell level, FRET sensors (ABACUS) covering a range ∼0.2–800 µM were engineered using structure-guided design and a high-throughput screening platform. When expressed in yeast, ABACUS1 detected concentrative ABA uptake mediated by the AIT1/NRT1.2 transporter. Arabidopsis roots expressing ABACUS1-2µ (Kd∼2 µM) and ABACUS1-80µ (Kd∼80 µM) respond to perfusion with ABA in a concentration-dependent manner. The properties of the observed ABA accumulation in roots appear incompatible with the activity of known ABA transporters (AIT1, ABCG40). ABACUS reveals effects of external ABA on homeostasis, that is, ABA-triggered induction of ABA degradation, modification, or compartmentation. ABACUS can be used to study ABA responses in mutants and quantitatively monitor ABA translocation and regulation, and identify missing components. The sensor screening platform promises to enable rapid fine-tuning of the ABA sensors and engineering of plant and animal hormone sensors to advance our understanding of hormone signaling. DOI: http://dx.doi.org/10.7554/eLife.01741.001
"The sensor was capable of quantifying lactate levels in the range between 1 µM and 10 mM. The extended range of detection was unexpected as previously developed metabolite sensors span only two orders of magnitude –. Affinity is chiefly determined by the properties of the recognition element and not by the fluorescent partners, so the distinctive kinetic behavior of this LldR-based sensor and its sensitivity to mM levels of pyruvate may be of interest for researchers working on transcriptional regulation. Laconic offers advantages over alternative methods, the first being resolution. "
[Show abstract][Hide abstract] ABSTRACT: Lactate is shuttled between and inside cells, playing metabolic and signaling roles in healthy tissues. Lactate is also a harbinger of altered metabolism and participates in the pathogenesis of inflammation, hypoxia/ischemia, neurodegeneration and cancer. Many tumor cells show high rates of lactate production in the presence of oxygen, a phenomenon known as the Warburg effect, which has diagnostic and possibly therapeutic implications. In this article we introduce Laconic, a genetically-encoded Forster Resonance Energy Transfer (FRET)-based lactate sensor designed on the bacterial transcription factor LldR. Laconic quantified lactate from 1 µM to 10 mM and was not affected by glucose, pyruvate, acetate, betahydroxybutyrate, glutamate, citrate, α-ketoglutarate, succinate, malate or oxalacetate at concentrations found in mammalian cytosol. Expressed in astrocytes, HEK cells and T98G glioma cells, the sensor allowed dynamic estimation of lactate levels in single cells. Used in combination with a blocker of the monocarboxylate transporter MCT, the sensor was capable of discriminating whether a cell is a net lactate producer or a net lactate consumer. Application of the MCT-block protocol showed that the basal rate of lactate production is 3-5 fold higher in T98G glioma cells than in normal astrocytes. In contrast, the rate of lactate accumulation in response to mitochondrial inhibition with sodium azide was 10 times lower in glioma than in astrocytes, consistent with defective tumor metabolism. A ratio between the rate of lactate production and the rate of azide-induced lactate accumulation, which can be estimated reversibly and in single cells, was identified as a highly sensitive parameter of the Warburg effect, with values of 4.1 ± 0.5 for T98G glioma cells and 0.07 ± 0.007 for astrocytes. In summary, this article describes a genetically-encoded sensor for lactate and its use to measure lactate concentration, lactate flux, and the Warburg effect in single mammalian cells.
PLoS ONE 02/2013; 8(2):e57712. DOI:10.1371/journal.pone.0057712 · 3.23 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.