An evaluation of genetically encoded FRET-based biosensors for quantitative metabolite analyses in vivo

Moussa, Roland; Baierl, Anna; Steffen, Victoria; Kubitzki, T.; Wiechert, Wolfgang; Pohl, Martina

doi:10.1016/j.jbiotec.2014.07.007

Cited by 32 publications

(41 citation statements)

References 46 publications

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“…The in situ FLII calibration curve displayed Michaelis-Menten kinetics and a K m of 1.9 mM, which was 2.7-fold higher than its in vitro K m value (51). This illustrates the importance of in situ calibration (52) and demonstrates that FLII most sensitively reports [GLC] c when [GLC] c is near 1.9 mM. Of note, discrepancies between in situ and in vitro K m values are not uncommon, as illustrated by the eightfold increase in K m for the proteinaceous Ca 2þ sensor PericamR when expressed in the mitochondrial matrix (53).…”

Section: In Situ Calibration and Validation Of The Flii Glc Sensormentioning

confidence: 80%

Mitoenergetic Dysfunction Triggers a Rapid Compensatory Increase in Steady-State Glucose Flux

Liemburg-Apers

Schirris

Rüssel

et al. 2015

Biophysical Journal

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ATP can be produced in the cytosol by glycolytic conversion of glucose (GLC) into pyruvate. The latter can be metabolized into lactate, which is released by the cell, or taken up by mitochondria to fuel ATP production by the tricarboxylic acid cycle and oxidative phosphorylation (OXPHOS) system. Altering the balance between glycolytic and mitochondrial ATP generation is crucial for cell survival during mitoenergetic dysfunction, which is observed in a large variety of human disorders including cancer. To gain insight into the kinetic properties of this adaptive mechanism we determined here how acute (30 min) inhibition of OXPHOS affected cytosolic GLC homeostasis. GLC dynamics were analyzed in single living C2C12 myoblasts expressing the fluorescent biosensor FLII(12)Pglu-700μδ6 (FLII). Following in situ FLII calibration, the kinetic properties of GLC uptake (V1) and GLC consumption (V2) were determined independently and used to construct a minimal mathematical model of cytosolic GLC dynamics. After validating the model, it was applied to quantitatively predict V1 and V2 at steady-state (i.e., when V1 = V2 = Vsteady-state) in the absence and presence of OXPHOS inhibitors. Integrating model predictions with experimental data on lactate production, cell volume, and O2 consumption revealed that glycolysis and mitochondria equally contribute to cellular ATP production in control myoblasts. Inhibition of OXPHOS induced a twofold increase in Vsteady-state and glycolytic ATP production flux. Both in the absence and presence of OXPHOS inhibitors, GLC was consumed at near maximal rates, meaning that GLC consumption is rate-limiting under steady-state conditions. Taken together, we demonstrate here that OXPHOS inhibition increases steady-state GLC uptake and consumption in C2C12 myoblasts. This activation fully compensates for the reduction in mitochondrial ATP production, thereby maintaining the balance between cellular ATP supply and demand.

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Section: In Situ Calibration and Validation Of The Flii Glc Sensormentioning

confidence: 80%

Mitoenergetic Dysfunction Triggers a Rapid Compensatory Increase in Steady-State Glucose Flux

Liemburg-Apers

Schirris

Rüssel

et al. 2015

Biophysical Journal

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“…As previously described for FRET-based sugar sensors [15], cells were harvested by centrifugation, afterwards disrupted, and the sensor proteins were then purified. Therefore, 20 g of wet cells were resuspended in 80 mL 3-(N-morpholino)propanesulfonic acid (MOPS) buffer (20 mM MOPS, 300 mM NaCl, pH 7.3, with one tablet of cOmplete protease inhibitor (Roche, Basel, Switzerland)) and disrupted by sonication using an UP200s (S3 sonotrode, Hielscher, Teltow, Germany).…”

Section: Methodsmentioning

confidence: 99%

“…To ensure constant l -lysine concentrations, respective stock solutions containing 0–1 M l -lysine were prepared in 20 mM MOPS buffer (pH 7.3) with adjusted pH and were stored at −20 °C and diluted 1:10. As in previous measurements [15], all data points represent the arithmetic average of 10 measurement cycles of the microtiter plate reader. The standard deviation given for each data point denotes the difference between three independent replicates.…”

Section: Methodsmentioning

confidence: 99%

“…As FRET-based sensors measure the change of the FRET-ratio between two FRET-partners in response to metabolite binding to a central metabolite binding protein, the signal is independent of the absolute sensor concentration in the cell. Although such sensors are widely used for metabolite analyses in different cells [14], we have recently demonstrated that the FRET-ratio change is influenced by a broad range of parameters that can hardly be controlled inside cells [15]. Thus, in this study we evaluate such sensors for extracellular metabolite analysis specifically for the analysis of l -lysine in culture supernatants of a C. glutamicum l -lysine producer.…”

Section: Introductionmentioning

confidence: 99%

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A Toolbox of Genetically Encoded FRET-Based Biosensors for Rapid l-Lysine Analysis

Steffen

Otten

Engelmann

et al. 2016

Sensors

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Background: The fast development of microbial production strains for basic and fine chemicals is increasingly carried out in small scale cultivation systems to allow for higher throughput. Such parallelized systems create a need for new rapid online detection systems to quantify the respective target compound. In this regard, biosensors, especially genetically encoded Förster resonance energy transfer (FRET)-based biosensors, offer tremendous opportunities. As a proof-of-concept, we have created a toolbox of FRET-based biosensors for the ratiometric determination of l-lysine in fermentation broth. Methods: The sensor toolbox was constructed based on a sensor that consists of an optimized central lysine-/arginine-/ornithine-binding protein (LAO-BP) flanked by two fluorescent proteins (enhanced cyan fluorescent protein (ECFP), Citrine). Further sensor variants with altered affinity and sensitivity were obtained by circular permutation of the binding protein as well as the introduction of flexible and rigid linkers between the fluorescent proteins and the LAO-BP, respectively. Results: The sensor prototype was applied to monitor the extracellular l-lysine concentration of the l-lysine producing Corynebacterium glutamicum (C. glutamicum) strain DM1933 in a BioLector® microscale cultivation device. The results matched well with data obtained by HPLC analysis and the Ninhydrin assay, demonstrating the high potential of FRET-based biosensors for high-throughput microbial bioprocess optimization.

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“…Although the ratiometric FRET signals provide higher accuracy than the use of a single fluorophore, both signal strength and ratios are still very sensitive to environmental changes (Constantinou and Polizzi, 2013). Great care must be taken to ensure changes in factors such as pH, salt, and temperature are not misinterpreted as changes in the metabolite of interest (Moussa et al, 2014).…”

Section: Protein Activity-based Biosensorsmentioning

confidence: 99%

Applications and advances of metabolite biosensors for metabolic engineering

Liu

Evans

Zhang

2015

Metabolic Engineering

169

138

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Quantification and regulation of pathway metabolites is crucial for optimization of microbial production bioprocesses. Genetically encoded biosensors provide the means to couple metabolite sensing to several outputs invaluable for metabolic engineering. These include semi-quantification of metabolite concentrations to screen or select strains with desirable metabolite characteristics, and construction of dynamic metabolite-regulated pathways to enhance production. Taking inspiration from naturally occurring systems, biosensor functions are based on highly diverse mechanisms including metabolite responsive transcription factors, two component systems, cellular stress responses, regulatory RNAs, and protein activities. We review recent developments in biosensors in each of these mechanistic classes, with considerations towards how these sensors are engineered, how new sensing mechanisms have led to improved function, and the advantages and disadvantages of each of these sensing mechanisms in relevant applications. We particularly highlight recent examples directly using biosensors to improve microbial production, and the great potential for biosensors to further inform metabolic engineering practices.

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An evaluation of genetically encoded FRET-based biosensors for quantitative metabolite analyses in vivo

Cited by 32 publications

References 46 publications

Mitoenergetic Dysfunction Triggers a Rapid Compensatory Increase in Steady-State Glucose Flux

Mitoenergetic Dysfunction Triggers a Rapid Compensatory Increase in Steady-State Glucose Flux

A Toolbox of Genetically Encoded FRET-Based Biosensors for Rapid l-Lysine Analysis

Applications and advances of metabolite biosensors for metabolic engineering

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