Fluorescent Nano-Optodes for Glucose Detection

Billingsley, Kelvin L.; Balaconis, Mary K.; Dubach, J. Matthew; Zhang, Ning; Lim, E. C.; Francis, Kevin P.; Clark, Heather A.

doi:10.1021/ac100042e

Cited by 87 publications

(88 citation statements)

References 29 publications

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“…Various methods are available for concentration measurements through the use of enzymatic 1 , chemical 2 , or binding assays 3 . An interesting option is the use of fluorescent, protein-based in vivo biological sensors as reporters of the intracellular concentration of key metabolites.…”

Section: Introductionmentioning

confidence: 99%

FIBS-enabled Noninvasive Metabolic Profiling

Behjousiar

Constantinou

Polizzi

et al. 2014

JoVE

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In the era of computational biology, new high throughput experimental systems are necessary in order to populate and refine models so that they can be validated for predictive purposes. Ideally such systems would be low volume, which precludes sampling and destructive analyses when time course data are to be obtained. What is needed is an in situ monitoring tool which can report the necessary information in realtime and noninvasively. An interesting option is the use of fluorescent, protein-based in vivo biological sensors as reporters of intracellular concentrations. One particular class of in vivo biosensors that has found applications in metabolite quantification is based on Förster Resonance Energy Transfer (FRET) between two fluorescent proteins connected by a ligand binding domain. FRET integrated biological sensors (FIBS) are constitutively produced within the cell line, they have fast response times and their spectral characteristics change based on the concentration of metabolite within the cell. In this paper, the method for constructing Chinese hamster ovary (CHO) cell lines that constitutively express a FIBS for glucose and glutamine and calibrating the FIBS in vivo in batch cell culture in order to enable future quantification of intracellular metabolite concentration is described. Data from fed-batch CHO cell cultures demonstrates that the FIBS was able in each case to detect the resulting change in the intracellular concentration. Using the fluorescent signal from the FIBS and the previously constructed calibration curve, the intracellular concentration was accurately determined as confirmed by an independent enzymatic assay.

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Section: Introductionmentioning

confidence: 99%

FIBS-enabled Noninvasive Metabolic Profiling

Behjousiar

Constantinou

Polizzi

et al. 2014

JoVE

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“…Our group utilizes a similar competitive binding scheme as the basis for functional nanosensors, but the sensing components are embedded in a lipophilic, highly plasticized polymeric particle into which glucose is extracted. 10,11 The hydrophobic particle design has several advantages that include isolation of the sensing components from biological fluid to prevent biofouling 12 and tunability of the system to adjust the dynamic range. 13 Our glucose-sensitive nanosensors successfully tracked changes in glucose levels when injected subcutaneously along the backs of mice.…”

Section: Introductionmentioning

confidence: 99%

“…13 Our glucose-sensitive nanosensors successfully tracked changes in glucose levels when injected subcutaneously along the backs of mice. 10 However, the monitoring time was limited to 1 h because of the loss of signal intensity at the injection site. Studies conducted by Gopee and coauthors 14 with intradermally injected quantum dots found that quantum dots migrated from the site of injection, with 60% of quantum dots remaining at the injection site after 24 h. Our nanosensors were implanted similarly in the skin, and migration was assumed to be the main cause of signal loss over time.…”

Section: Introductionmentioning

confidence: 99%

Gel Encapsulation of Glucose Nanosensors for Prolonged In Vivo Lifetime

Balaconis

Clark

2013

J Diabetes Sci Technol

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“…They would benefit from the fact that signal generation is based on a binding equilibrium (that means without consuming glucose) and is not sensitive to oxygen and other electrode-active interferences. [26][27][28][29][30][31][32][33][34][35][36][37][38][39] Also, the fluorescence signal is available immediately after system turn-on during operation, while the electroenzymatic sensors require a certain warm-up time until stable signal levels are reached.…”

Section: Introductionmentioning

confidence: 99%

Acute In Vivo Performance Evaluation of the Fluorescence Affinity Sensor in the Intravascular and Interstitial Space in Swine

Dutt-Ballerstadt

Evans

Pillai

et al. 2013

J Diabetes Sci Technol

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Abbreviations: (BG) blood glucose, (FAS) fluorescence affinity sensor, (FRET) fluorescence resonance energy transfer, (MARE) mean absolute relative error, (SD) standard deviation Keywords: concanavalin A, fluorescence affinity sensor, glucose monitoring, hollow fiber Abstract Objective:We assessed and compared the performance levels of a fiber-coupled fluorescence affinity sensor (FAS) for glucose detection in the intradermal tissue and intravascular bed during glucose clamping and insulin administration in a large animal model. Research Design and Methods:The FAS (BioTex Inc., Houston, TX) was implanted in interstitial tissue and in the intravenous space in nondiabetic, anesthetized pigs over 6-7 h. For intradermal assessment, a needle-type FAS was implanted in the upper back using a hypodermic needle. For intravenous assessment, the FAS was inserted through a catheter into the femoral artery and vein. Blood glucose changes were induced by infusion of dextrose and insulin through a catheterized ear or jugular vein. Results:Based on retrospective analysis, the mean absolute relative error (MARE) of the sensor in blood and interstitial tissue was 11.9% [standard deviation (SD) = ±9.6%] and 23.8% (SD = ±19.4%), respectively. When excluding data sets from sensors that were affected by exogenous insulin, the MARE for those sensors tested in interstitial tissue was reduced to 16.3% (SD = ±12.5%). Conclusions:The study demonstrated that the performance level of the FAS device implanted in interstitial tissue and blood can be very high. However, under certain circumstances, exogenous insulin caused the glucose concentration in interstitial tissue to be lower than in blood, which resulted in an overall lower level of accuracy of the FAS device. How significant this physiological effect is in insulin-treated persons with diabetes remains to be seen. In contrast, the level of accuracy of the FAS device in blood was very high because of high mass transfer conditions in blood. While the use of the FAS in both body sites will need further validation, its application in critically ill patients looks particularly promising.

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Fluorescent Nano-Optodes for Glucose Detection

Cited by 87 publications

References 29 publications

FIBS-enabled Noninvasive Metabolic Profiling

FIBS-enabled Noninvasive Metabolic Profiling

Gel Encapsulation of Glucose Nanosensors for Prolonged In Vivo Lifetime

Acute In Vivo Performance Evaluation of the Fluorescence Affinity Sensor in the Intravascular and Interstitial Space in Swine

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