We thank Stefanie Schirmeier and Takeshi Iwatsubo for providing Drosophila strains. We also thank Patricia Jansma for assisting with imaging in the Marley Imaging Core at the University of Arizona. This work was funded by National Institutes of Health NIH NS091299, NS115514 (to DCZ), HHMI Gilliam Fellowship (to EM) and the Undergraduate Biology Research Program (to HB).

The UAS FLII12Pglu-700&#181;&#948;6 transgenic flies were reported in Volkenhoff et al.10 and kindly provided by Dr. S. Schirmeier. The UAS TDP-43G298S transgenic lines were kindly provided by Dr. T. Iwatsubo13. Recombinant Drosophila lines harboring both UAS FLII12Pglu-700&#181;&#948;6 and UAS TDP-43 transgenes were generated in the Zarnescu laboratory using standard genetic approaches and reported in Manzo et al.9. D42 GAL4 was used to drive the expression of the glucose sensor alone or together with TDP-43G298S in motor neurons. All fly lines are maintained on molasses cornmeal media, at 25 &#176;C in 12 h dark:light cycle.
1. Drosophila Ventral Nerve Cord (VNC) dissections
<ol>
	<li>Make silicone elastomer dissection dishes.
	<ol>
		<li>Pour silicone elastomer components into a 50 mL tube as indicated in the manufacturer&#39;s protocol and stir well.</li>
		<li>Fill 35 mm tissue culture dishes with approximately 2 mL of the elastomer mixture. Use a syringe to remove any bubbles. Cover the dishes and place them on a level surface in a 60 &#176;C oven overnight to cure.</li>
	</ol>
	</li>
	<li>Dissect Drosophila larvae to expose the VNC while maintaining tissue viability.
	<ol>
		<li>Collect a wandering third instar larva, rinse with ddH2O, and then place it in a drop of HL3-buffer (70 mM NaCl, 5 mM KCl, 20 mM MgCl2, 10 mM NaHCO3, 115 mM sucrose, 5 mM trehalose, 5 mM HEPES; pH 7.1) on an elastomer lined dish.</li>
		<li>Using a pair of forceps (#5 or 55 forceps) under a dissecting microscope, pin the anterior and posterior ends of the larva dorsal side up, carefully stretching the larva lengthwise with insect pins (Minutein Pins).</li>
		<li>Make an incision just above the posterior pin using a pair of angled iris scissors. Make a vertical cut starting from the incision toward the anterior end of the larva.</li>
		<li>Add a few drops of HL-3 buffer if needed. Remove the trachea and the rest of the floating organs without disturbing the CNS. Pin the flaps stretching the body wall to expose the CNS while keeping the neuromuscular system (VNCs, axons, and neuromuscular junctions) intact.</li>
	</ol>
	</li>
</ol>
2. Image acquisition
<ol>
	<li>Optimize the imaging parameters.
	<ol>
		<li>Turn on the microscope and lasers before starting dissections. Images must be acquired using an upright confocal microscope with a 40x water immersion lens. Use a 405 nm laser to excite CFP and acquire the images in both the CFP (465-499 nm) and the FRET (535-695 nm) detection channels.</li>
		<li>Optimize acquisition parameters such as scan speed (6), average (2), objective (40x), zoom (1x), pinhole size (1 AU), and spatial resolution (512 x 512). Adjust the gain such that the signal is in the optimal dynamic range. The same parameters must be used for all genotypes.</li>
	</ol>
	</li>
	<li>Image motor neurons within the VNC.
	<ol>
		<li>Place the silicone dish with the dissected sample under the lens. Lower the lens so that it comes in contact with trehalose-sucrose HL3 buffer (see 1.2.1). It is critical to ensure that the lens is completely submerged in the buffer. Add more buffer if required.</li>
		<li>Use the CFP and FRET channels to manually select an optical section that consists of at least 6 motor neurons in focus, located along the VNC midline. The motor neurons are identified based on the expression of the glucose sensor and position along the anterior-posterior axis.</li>
		<li>Acquire images every 10 s for 10 min. These images represent the baseline.</li>
	</ol>
	</li>
	<li>Stimulate with glucose supplemented HL-3.
	<ol>
		<li>Remove the trehalose-sucrose containing HL3-buffer using a Pasteur pipette and replace it with 5 mM glucose supplemented HL-3 (70 mM NaCl, 5 mM KCl, 20 mM MgCl2, 10 mM NaHCO3, 115 mM sucrose, 5 mM glucose, 5 mM HEPES, pH 7.1). This step needs to be performed with great care, to avoid the movement of the VNC as much as possible.</li>
		<li>Acquire images every 10 s for another 10 min. These images represent the stimulation phase.</li>
	</ol>
	</li>
	<li>Save the images as .czi files or any file type supported by the imaging software with a file name including date, genetic background, experimental condition (baseline or stimulation), and channels used.</li>
	<li>Reuse the parameters to image all the genotypes (Figure 2A).</li>
</ol>
3. Image processing and ROI selection
<ol>
	<li>Open the czi files in Fiji/ImageJ and set Color Mode: Grayscale, choose View Stack with: Hyperstack, and select Split Channels into Separate Windows.</li>
	<li>Process images using the drift correction plugins: turboreg and stackreg. Each channel is corrected separately by selecting Stackreg under Plugins, and then choose Transformation: Translation.</li>
	<li>Manually select the Regions of interest (ROIs) to extract the mean gray value of each channel.
	<ol>
		<li>Choose the ROIs by tracing all motor neurons that remain in focus over the entire time series. Use the ROI manager to save each motor neuron outline.</li>
		<li>Use the Multi-measure function to measure the mean gray value in each ROI at each time point. Copy the ROIs traced from the first channel to the second channel for the pre-stimulation image.</li>
		<li>Repeat this process for the post-stimulation images in each channel using the same cells/ROIs selected for the pre-stimulation image.</li>
	</ol>
	</li>
</ol>
4. Data analysis
<ol>
	<li>Calculate the FRET/CFP ratio, using the mean gray values for the FRET and CFP channels. Changes in the FRET/CFP ratios reflect alterations in the intracellular glucose concentration.
	<ol>
		<li>Plot FRET/CFP ratios for each ROI and time point versus time. Within every VNC some of the ROIs will exhibit a drop in FRET/CFP ratios following stimulation. 
		NOTE: This is interpreted as an inability of some neurons to uptake glucose, possibly due to stress caused by dissections and are therefore eliminated from the analysis. The remaining FRET/CFP ratios for each ROI and time point are averaged to generate a single FRET/CFP ratio per time point per genotype (glucose sensor alone and glucose sensor with TDP-43G298S). These single FRET/CFP ratios are used for all subsequent normalizations. 31 ROIs were analyzed for Glucose Sensor controls and 24 ROIs were analyzed for TDP-43G298S.</li>
	</ol>
	</li>
	<li>Baseline normalization: Calculate the average of FRET/CFP ratios for the first 10 min (baseline), and then normalize individual FRET/CFP ratios for each time point of the entire experiment to the 10 min baseline average (see Figure 2B).</li>
	<li>Timepoint normalization: Normalize TDP-43G298S FRET/CFP ratios to FRET/CFP ratios from glucose sensor alone at each time point (see Figure 3A).</li>
	<li>Bar graphs: For baseline versus stimulation comparisons in the form of bar graphs, use FRET/CFP ratios from 5-10 min (baseline) and 15-20 min (stimulation) for each genotype. Normalize stimulation ratio to the baseline ratio (see Figure 3B).</li>
</ol>
5. Statistical analyses
<ol>
	<li>Evaluate the normalized data sets using Mann-Whitney correction (for baseline and timepoint normalizations) or Kruskall-Walis test (for bar graph representation of stimulation versus baseline FRET/CFP ratios).</li>
</ol>

<ol>
	<li>Ingre, C., Roos, P. M., Piehl, F., Kamel, F., Fang, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Risk+factors+for+amyotrophic+lateral+sclerosis.">Risk factors for amyotrophic lateral sclerosis.</a> Clinical Epidemiology. 7, 181-193 (2015).</li><li>Dupuis, L., Pradat, P. F., Ludolph, A. C., Loeffler, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Energy+metabolism+in+amyotrophic+lateral+sclerosis.">Energy metabolism in amyotrophic lateral sclerosis.</a> The Lancet Neurology. 10 (1), 75-82 (2011).</li><li>Buratti, E., Baralle, F. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+and+functional+implications+of+the+RNA+binding+properties+of+nuclear+factor+TDP-43,+a+novel+splicing+regulator+of+CFTR+exon+9.">Characterization and functional implications of the RNA binding properties of nuclear factor TDP-43, a novel splicing regulator of CFTR exon 9.</a> The Journal of Biological Chemistry. 276 (39), 36337-36343 (2001).</li><li>Polymenidou, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Long+pre-mRNA+depletion+and+RNA+missplicing+contribute+to+neuronal+vulnerability+from+loss+of+TDP-43.">Long pre-mRNA depletion and RNA missplicing contribute to neuronal vulnerability from loss of TDP-43.</a> Nature Neuroscience. 14 (4), 459-468 (2011).</li><li>Tollervey, J. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterizing+the+RNA+targets+and+position-dependent+splicing+regulation+by+TDP-43.">Characterizing the RNA targets and position-dependent splicing regulation by TDP-43.</a> Nature Neuroscience. 14 (4), 452-458 (2011).</li><li>Ling, S. C., Polymenidou, M., Cleveland, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Converging+mechanisms+in+ALS+and+FTD:+disrupted+RNA+and+protein+homeostasis.">Converging mechanisms in ALS and FTD: disrupted RNA and protein homeostasis.</a> Neuron. 79 (3), 416-438 (2013).</li><li>Estes, P. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wild-type+and+A315T+mutant+TDP-43+exert+differential+neurotoxicity+in+a+Drosophila+model+of+ALS.">Wild-type and A315T mutant TDP-43 exert differential neurotoxicity in a Drosophila model of ALS.</a> Human Molecular Genetics. 20 (12), 2308-2321 (2011).</li><li>Estes, P. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Motor+neurons+and+glia+exhibit+specific+individualized+responses+to+TDP-43+expression+in+a+Drosophila+model+of+amyotrophic+lateral+sclerosis.">Motor neurons and glia exhibit specific individualized responses to TDP-43 expression in a Drosophila model of amyotrophic lateral sclerosis.</a> Disease Models &amp; Mechanisms. 6 (3), 721-733 (2013).</li><li>Manzo, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Glycolysis+upregulation+is+neuroprotective+as+a+compensatory+mechanism+in+ALS.">Glycolysis upregulation is neuroprotective as a compensatory mechanism in ALS.</a> eLife. 8, 45114 (2019).</li><li>Volkenhoff, A., Hirrlinger, J., Kappel, J. M., Klambt, C., Schirmeier, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Live+imaging+using+a+FRET+glucose+sensor+reveals+glucose+delivery+to+all+cell+types+in+the+Drosophila+brain.">Live imaging using a FRET glucose sensor reveals glucose delivery to all cell types in the Drosophila brain.</a> Journal of Insect Physiology. 106, 55-64 (2018).</li><li>Fehr, M., Lalonde, S., Lager, I., Wolff, M. W., Frommer, W. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+imaging+of+the+dynamics+of+glucose+uptake+in+the+cytosol+of+COS-7+cells+by+fluorescent+nanosensors.">In vivo imaging of the dynamics of glucose uptake in the cytosol of COS-7 cells by fluorescent nanosensors.</a> The Journal of Biological Chemistry. 278 (21), 19127-19133 (2003).</li><li>Takanaga, H., Chaudhuri, B., Frommer, W. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=GLUT1+and+GLUT9+as+major+contributors+to+glucose+influx+in+HepG2+cells+identified+by+a+high+sensitivity+intramolecular+FRET+glucose+sensor.">GLUT1 and GLUT9 as major contributors to glucose influx in HepG2 cells identified by a high sensitivity intramolecular FRET glucose sensor.</a> Biochimedica et Biophysica Acta. 1778 (4), 1091-1099 (2008).</li><li>Ihara, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA+binding+mediates+neurotoxicity+in+the+transgenic+Drosophila+model+of+TDP-43+proteinopathy.">RNA binding mediates neurotoxicity in the transgenic Drosophila model of TDP-43 proteinopathy.</a> Human Molecular Genetics. 22 (22), 4474-4484 (2013).</li><li>Brand, A. H., Perrimon, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeted+gene+expression+as+a+means+of+altering+cell+fates+and+generating+dominant+phenotypes.">Targeted gene expression as a means of altering cell fates and generating dominant phenotypes.</a> Development. 118 (2), 401-415 (1993).</li><li>Diaz-Garcia, C. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+in+vivo+imaging+of+neuronal+glucose+concentrations+with+a+genetically+encoded+fluorescence+lifetime+sensor.">Quantitative in vivo imaging of neuronal glucose concentrations with a genetically encoded fluorescence lifetime sensor.</a> Journal of Neuroscience Research. 97 (8), 946-960 (2019).</li><li>Mergenthaler, P., Lindauer, U., Dienel, G. A., Meisel, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sugar+for+the+brain:+the+role+of+glucose+in+physiological+and+pathological+brain+function.">Sugar for the brain: the role of glucose in physiological and pathological brain function.</a> Trends in Neurosciences. 36 (10), 587-597 (2013).</li><li>Lu, B., Vogel, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Drosophila+models+of+neurodegenerative+diseases.">Drosophila models of neurodegenerative diseases.</a> Annual Review of Pathology. 4, 315-342 (2009).</li></ol>

The authors declare no conflicts of interest.

The technique described in detail here can be applied to measure glucose uptake in a specific cell type of interest in live Drosophila using FLII12Pglu-700&#181;&#948;6, a FRET based sensor which can detect changes in glucose levels to a millimolar range10,11,12. This sensor has been previously used in conjunction with the UAS-GAL4 system to target its expression to specific cell types, including neurons<sup class="xref...

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder that is currently incurable. ALS affects upper and lower motor neurons leading to loss of motor coordination, irreversible paralysis, respiratory failure, and eventual death within 2-5 years of diagnosis1. ALS is associated with metabolic defects such as weight loss, dyslipidemia, and hypermetabolism (reviewed in2); however, it remains unclear how these alterations in metabolism relate to motor neuron degeneration. A common denominator in ALS and related neurodegenerative diseases is TDP-43, a nucleic acid binding protein involved in several steps of RNA processing3,4,5. Although mutations in TDP-43 only affect 3%-5% of patients, wild-type TDP-43 protein is found within cytoplasmic aggregates in &#62;97% of ALS cases (reviewed in6). This pathology was modeled in Drosophila by overexpression of human wildtype or mutant TDP-43 (G298S) in motor neurons, which recapitulates multiple aspects of ALS, including cytoplasmic inclusions, locomotor dysfunction and reduced lifespan7,8. Using these models, it was recently reported that TDP-43 proteinopathy causes a significant increase in pyruvate levels and phosphofructokinase (PFK) mRNA, the rate limiting enzyme of glycolysis9. Similar increases in PFK transcripts were found in patient-derived motor neurons and spinal cords, suggesting that glycolysis is upregulated in the context of TDP-43 proteinopathy. Interestingly, further increase in glycolysis using dietary and genetic manipulations mitigated several ALS phenotypes such as locomotor dysfunction and increased lifespan in fly models of TDP-43 proteinopathy, consistent with a compensatory, neuroprotective mechanism in degenerating motor neurons.
To further probe changes in glycolysis and measure glucose uptake in Drosophila models of TDP-43 proteinopathy, a previously reported genetically encoded FRET-based sensor FLII12Pglu-700&#181;&#948;610 was expressed in motor neurons specifically using the UAS-GAL4 expression system. The FLII12Pglu-700&#181;&#948;6 glucose sensor uses resonance energy transfer between two variants of green fluorescent protein, cyan and yellow fluorescent proteins (CFP and YFP) to detect glucose at the cellular level. It consists of a bacterial glucose binding domain from the E. coli MglB gene fused to CFP and YFP at opposite ends of the molecule. When bound to a glucose molecule, the sensor undergoes a conformational change bringing CFP and YFP closer together and allowing FRET to occur, which can then be used to quantify intracellular glucose levels10,11,12 (Figure 1). Here, we show how the FLII12Pglu-700&#181;&#948;6 sensor can be used to determine changes in glucose uptake caused by TDP-43 proteinopathy in motor neurons. The experiments described here show that overexpression of an ALS-associated mutant, TDP-43G298S, in motor neurons causes a significant increase in glucose uptake compared to controls. This approach can be used in other types of ALS (e.g., SOD1, C9orf72, etc.) and/or other cell types (e.g., glia, muscles) to determine changes in glucose uptake associated with neurodegeneration.

<table><tbody><tr><td>35 mm tissue culture dishes</td><td>Sigma Aldrich</td><td>CLS430165</td><td></td></tr><tr><td>40X water immersion lens</td><td>Zeiss</td><td>440090</td><td>dippable, N.A. 0.8</td></tr><tr><td>dissection scissors</td><td>Roboz</td><td>RS-5618</td><td></td></tr><tr><td>Dumont #5 forceps</td><td>VWR</td><td>100189-236</td><td></td></tr><tr><td>Dumont #55 forceps</td><td>VWR</td><td>100189-244</td><td></td></tr><tr><td>Minutien pins</td><td>Fine Science tools</td><td>26002-10</td><td>used for dissections</td></tr><tr><td>SYLGARD 184 Silicone Elastomer Kit</td><td>Dow</td><td>1317318</td><td></td></tr><tr><td>Zeiss LSM880 NLO upright multiphoton/confocal microscope</td><td>Zeiss</td><td>N/A</td><td></td></tr></tbody></table>

measuring glucose uptake in drosophila models of tdp-43 proteinopathy

Amyotrophic lateral sclerosis is a neurodegenerative disorder causing progressive muscle weakness and death within 2-5 years following diagnosis. Clinical manifestations include weight loss, dyslipidemia, and hypermetabolism; however, it remains unclear how these relate to motor neuron degeneration. Using a Drosophila model of TDP-43 proteinopathy that recapitulates several features of ALS including cytoplasmic inclusions, locomotor dysfunction, and reduced lifespan, we recently identified broad ranging metabolic deficits. Among these, glycolysis was found to be upregulated and genetic interaction experiments provided evidence for a compensatory neuroprotective mechanism. Indeed, despite upregulation of phosphofructokinase, the rate limiting enzyme in glycolysis, an increase in glycolysis using dietary and genetic manipulations was shown to mitigate locomotor dysfunction and increased lifespan in fly models of TDP-43 proteinopathy. To further investigate the effect on TDP-43 proteinopathy on glycolytic flux in motor neurons, a previously reported genetically encoded, FRET-based sensor, FLII12Pglu-700&#181;&#948;6, was used. This sensor is comprised of a bacterial glucose-sensing domain and cyan and yellow fluorescent proteins as the FRET pair. Upon glucose binding, the sensor undergoes a conformational change allowing FRET to occur. Using FLII12Pglu-700&#181;&#948;6, glucose uptake was found to be significantly increased in motor neurons expressing TDP-43G298S, an ALS causing variant. Here, we show how to measure glucose uptake, ex vivo, in larval ventral nerve cord preparations expressing the glucose sensor FLII12Pglu-700&#181;&#948;6 in the context of TDP-43 proteinopathy. This approach can be used to measure glucose uptake and assess glycolytic flux in different cell types or in the context of various mutations causing ALS and related neurodegenerative disorders.

Image acquisition of the glucose sensor in the ventral nerve cord (VNC), ex vivo 
To determine differences in glucose uptake in a Drosophila model of ALS based on TDP-43, a genetically encoded FRET-based glucose sensor was used. The sensor comprised CFP and YFP fused to the glucose binding domain from the E. coli MglB gene. Glucose binding elicits a conformational change, which can be detected by fluorescence resonance energy transfer (FRET) between the CF...

Watch this Scientific Journal Video about Measuring Glucose Uptake in Drosophila Models of TDP-43 Proteinopathy at JoVE.com

Measuring Glucose Uptake in Drosophila Models of TDP-43 Proteinopathy

Glucose uptake is increased in Drosophila motor neurons affected by TAR DNA binding protein (TDP-43) proteinopathy, as indicated by a FRET-based, genetically encoded glucose sensor.

Measuring Glucose Uptake in Drosophila Models of TDP-43 Proteinopathy

Amyotrophic lateral sclerosis is a neurodegenerative disorder causing progressive muscle weakness and death within 2-5 years following diagnosis. Clinical ...

measuring-glucose-uptake-in-drosophila-models-of-tdp-43-proteinopathy

Research

JoVE Journal

Neuroscience

2.7K Views.  University of Arizona, Tucson. Deze techniek is belangrijk omdat het de glucoseopname in specifieke cellen in levende Drosophila-weefsels kan meten. De FRET-gebaseerde sensor biedt een directe meting van veranderingen in intracellulaire glucosespiegels. Deze techniek stelt onderzoekers in staat om veranderingen in glucosespiegels in realtime te evalueren, binnen levende motorneuronen van ALS-modellen versus controles.Een uitdagend aspect is het in beeld brengen van dezelfde set neuronen na het veranderen van de buff...

Video: Measuring Glucose Uptake in Drosophila Models of TDP-43 Proteinopathy

Extracellular Glucose Depletion as an Indirect Measure of Glucose Uptake in Cells and Tissues Ex Vivo

The ongoing worldwide epidemic of diabetes increases the demand for the identification of environmental, nutritional, endocrine, genetic, and epigenetic factors affecting glucose uptake. The measurement of intracellular fluorescence is a widely used method to test the uptake of fluorescently-labeled glucose (FD-glucose) in cells in vitro, or for imaging glucose-consuming tissues in vivo. This assay assesses glucose uptake at a chosen time point. The intracellular analysis assumes that the metabolism of FD-glucose is slower than that of endogenous glucose, which participates in catabolic and anabolic reactions and signaling. However, dynamic glucose metabolism also alters uptake mechanisms, which would require kinetic measurements of glucose uptake in response to different factors. This article describes a method for measuring extracellular FD-glucose depletion and validates its correlation with intracellular FD-glucose uptake in cells and tissues ex vivo. Extracellular glucose depletion may be potentially applicable for high-throughput kinetic and dose-dependent studies, as well as identifying compounds with glycemic activity and their tissue-specific effects.

Extracellular Glucose Depletion as an Indirect Measure of Glucose Uptake in Cells and Tissues Ex Vivo

Extracellular depletion of fluorescently labeled glucose correlates with glucose uptake and could be used for high-throughput screening of glucose uptake in excised organs and cell cultures.

The ongoing worldwide epidemic of diabetes increases the demand for the identification of environmental, nutritional, endocrine, genetic, and epigenetic ...

Biochemistry

Insulin Injection and Hemolymph Extraction to Measure Insulin Sensitivity in Adult Drosophila melanogaster

Conserved nutrient sensing mechanisms exist between mammal and fruit fly where peptides resembling mammalian insulin and glucagon, respectively function to maintain glucose homeostasis during developmental larval stages 1,2. Studies on largely post-mitotic adult flies have revealed perturbation of glucose homeostasis as the result of genetic ablation of insulin-like peptide (ILP) producing cells (IPCs) 3. Thus, adult fruit flies hold great promise as a suitable genetic model system for metabolic disorders including type II diabetes. To further develop the fruit fly system, comparable physiological assays used to measure glucose tolerance and insulin sensitivity in mammals must be established. To this end, we have recently described a novel procedure for measuring oral glucose tolerance response in the adult fly and demonstrated the importance of adult IPCs in maintaining glucose homeostasis 4,5. Here, we have modified a previously described procedure for insulin injection 6 and combined it with a novel hemolymph extraction method to measure peripheral insulin sensitivity in the adult fly. Uniquely, our protocol allows direct physiological measurements of the adult fly's ability to dispose of a peripheral glucose load upon insulin injection, a methodology that makes it feasible to characterize insulin signaling mutants and potential interventions affecting glucose tolerance and insulin sensitivity in the adult fly.

Insulin Injection and Hemolymph Extraction to Measure Insulin Sensitivity in Adult Drosophila melanogaster

Conserved insulin signaling pathways found in the fruit fly Drosophila melanogaster make this organism a potential tool for modeling metabolic disorders including type II diabetes. To this end, it is critical to establish physiological assays to effectively measure systemic insulin action in peripheral glucose disposal in the adult fly.

Conserved nutrient sensing mechanisms exist between mammal and fruit fly where peptides resembling mammalian insulin and glucagon, respectively function ...

Biology

Mass Histology to Quantify Neurodegeneration in Drosophila

Progressive neurodegenerative diseases like Alzheimer&#39;s disease (AD) or Parkinson&#39;s disease (PD) are an increasing threat to human health worldwide. Although mammalian models have provided important insights into the underlying mechanisms of pathogenicity, the complexity of mammalian systems together with their high costs are limiting their use. Therefore, the simple but well-established Drosophila model-system&#160;provides an alternative for investigating the molecular pathways that are affected in these diseases. Besides behavioral deficits, neurodegenerative diseases are characterized by histological phenotypes such as neuronal death and axonopathy. To quantify neuronal degeneration and to determine how it is affected by genetic and environmental factors, we use a histological approach that is based on measuring the vacuoles in adult fly brains. To minimize the effects of systematic error and to directly compare sections from control and experimental flies in one preparation, we use the &#39;collar&#39; method for paraffin sections. Neurodegeneration is then assessed by measuring the size and/or number of vacuoles that have developed in the fly brain. This can either be done by focusing on a specific region of interest or by analyzing the entire brain by obtaining serial sections that span the complete head. Therefore, this method allows one to measure not only severe degeneration but also relatively mild phenotypes that are only detectable in a few sections, as occurs during normal aging.

Mass Histology to Quantify Neurodegeneration in Drosophila

Drosophila is widely used as a model system to study neurodegeneration. This protocol describes a method by which degeneration, as determined by vacuole formation in the brain, can be quantified. It also minimizes effects due to the experimental procedure by processing and sectioning control and experimental flies as one sample.

Progressive neurodegenerative diseases like Alzheimer&#39;s disease (AD) or Parkinson&#39;s disease (PD) are an increasing threat to human health ...

Monitoring Cell-to-cell Transmission of Prion-like Protein Aggregates in Drosophila Melanogaster

Protein aggregation is a central feature of most neurodegenerative diseases, including Alzheimer&#39;s disease (AD), Parkinson&#39;s disease (PD), Huntington&#39;s disease (HD), and amyotrophic lateral sclerosis (ALS). Protein aggregates are closely associated with neuropathology in these diseases, although the exact mechanism by which aberrant protein aggregation disrupts normal cellular homeostasis is not known. Emerging data provide strong support for the hypothesis that pathogenic aggregates in AD, PD, HD, and ALS have many similarities to prions, which are protein-only infectious agents responsible for the transmissible spongiform encephalopathies. Prions self-replicate by templating the conversion of natively-folded versions of the same protein, causing spread of the aggregation phenotype. How prions and prion-like proteins in AD, PD, HD, and ALS move from one cell to another is currently an area of intense investigation. Here, a Drosophila melanogaster model that permits monitoring of prion-like, cell-to-cell transmission of mutant huntingtin (Htt) aggregates associated with HD is described. This model takes advantage of powerful tools for manipulating transgene expression in many different Drosophila tissues and utilizes a fluorescently-tagged cytoplasmic protein to directly report prion-like transfer of mutant Htt aggregates. Importantly, the approach we describe here can be used to identify novel genes and pathways that mediate spreading of protein aggregates between diverse cell types in vivo. Information gained from these studies will expand the limited understanding of the pathogenic mechanisms that underlie neurodegenerative diseases and reveal new opportunities for therapeutic intervention.

Monitoring Cell-to-cell Transmission of Prion-like Protein Aggregates in Drosophila Melanogaster

Accumulating evidence supports the idea that pathogenic protein aggregates associated with neurodegenerative diseases spread between cells with prion-like properties. Here, we describe a method that enables visualization of cell-to-cell spreading of prion-like aggregates in the model organism, Drosophila melanogaster.

Protein aggregation is a central feature of most neurodegenerative diseases, including Alzheimer&#39;s disease (AD), Parkinson&#39;s disease (PD), ...

Quantitative Cell Biology of Neurodegeneration in Drosophila Through Unbiased Analysis of Fluorescently Tagged Proteins Using ImageJ

With the rising prevalence of neurodegenerative diseases, it is increasingly important to understand the underlying pathophysiology that leads to neuronal dysfunction and loss. Fluorescence-based imaging tools and technologies enable unprecedented analysis of subcellular neurobiological processes, yet there is still a need for unbiased, reproducible, and accessible approaches for extracting quantifiable data from imaging studies. We have developed a simple and adaptable workflow to extract quantitative data from fluorescence-based imaging studies using Drosophila models of neurodegeneration. Specifically, we describe an easy-to-follow, semi-automated approach using Fiji/ImageJ to analyze two cellular processes: first, we quantify protein aggregate content and profile in the Drosophila optic lobe using fluorescent-tagged mutant huntingtin proteins; and second, we assess autophagy-lysosome flux in the Drosophila visual system with ratiometric-based quantification of a tandem fluorescent reporter of autophagy. Importantly, the protocol outlined here includes a semi-automated segmentation step to ensure all fluorescent structures are analyzed to minimize selection bias and to increase resolution of subtle comparisons. This approach can be extended for the analysis of other cell biological structures and processes implicated in neurodegeneration, such as proteinaceous puncta (stress granules and synaptic complexes), as well as membrane-bound compartments (mitochondria and membrane trafficking vesicles). This method provides a standardized, yet adaptable reference point for image analysis and quantification, and could facilitate reliability and reproducibility across the field, and ultimately enhance mechanistic understanding of neurodegeneration.

Quantitative Cell Biology of Neurodegeneration in Drosophila Through Unbiased Analysis of Fluorescently Tagged Proteins Using ImageJ

We have developed a simple and adaptable workflow to extract quantitative data from fluorescence-imaging-based cell biological studies of protein aggregation and autophagic flux in the central nervous system of Drosophila models of neurodegeneration.

With the rising prevalence of neurodegenerative diseases, it is increasingly important to understand the underlying pathophysiology that leads to neuronal ...

Purification of Transcripts and Metabolites from Drosophila Heads

For the last decade, we have tried to understand the molecular and cellular mechanisms of neuronal degeneration using Drosophila as a model organism. Although fruit flies provide obvious experimental advantages, research on neurodegenerative diseases has mostly relied on traditional techniques, including genetic interaction, histology, immunofluorescence, and protein biochemistry. These techniques are effective for mechanistic, hypothesis-driven studies, which lead to a detailed understanding of the role of single genes in well-defined biological problems. However, neurodegenerative diseases are highly complex and affect multiple cellular organelles and processes over time. The advent of new technologies and the omics age provides a unique opportunity to understand the global cellular perturbations underlying complex diseases. Flexible model organisms such as Drosophila are ideal for adapting these new technologies because of their strong annotation and high tractability. One challenge with these small animals, though, is the purification of enough informational molecules (DNA, mRNA, protein, metabolites) from highly relevant tissues such as fly brains. Other challenges consist of collecting large numbers of flies for experimental replicates (critical for statistical robustness) and developing consistent procedures for the purification of high-quality biological material. Here, we describe the procedures for collecting thousands of fly heads and the extraction of transcripts and metabolites to understand how global changes in gene expression and metabolism contribute to neurodegenerative diseases. These procedures are easily scalable and can be applied to the study of proteomic and epigenomic contributions to disease.

Purification of Transcripts and Metabolites from Drosophila Heads

We describe here the procedures for the extraction and purification of mRNA and metabolites from Drosophila heads. We are applying these techniques to better understand the cellular perturbations underlying neuronal degeneration. These methodologies can be easily scaled and adapted for other "omic" projects.

For the last decade, we have tried to understand the molecular and cellular mechanisms of neuronal degeneration using Drosophila as a model organism. ...

Measurement of Metabolic Rate in Drosophila using Respirometry

Metabolic disorders are a frequent problem affecting human health. Therefore, understanding the mechanisms that regulate metabolism is a crucial scientific task. Many disease causing genes in humans have a fly homologue, making Drosophila a good model to study signaling pathways involved in the development of different disorders. Additionally, the tractability of Drosophila simplifies genetic screens to aid in identifying novel therapeutic targets that may regulate metabolism. In order to perform such a screen a simple and fast method to identify changes in the metabolic state of flies is necessary. In general, carbon dioxide production is a good indicator of substrate oxidation and energy expenditure providing information about metabolic state. In this protocol we introduce a simple method to measure CO2 output from flies. This technique can potentially aid in the identification of genetic perturbations affecting metabolic rate.

Measurement of Metabolic Rate in Drosophila using Respirometry

Metabolic disorders are among one of the most common diseases in humans. The genetically tractable model organism D. melanogaster can be used to identify novel genes that regulate metabolism. This paper describes a relatively simple method which allows studying the metabolic rate in flies by measuring their CO2 production.

Metabolic disorders are a frequent problem affecting human health. Therefore, understanding the mechanisms that regulate metabolism is a crucial ...

Measurement of Carbon Dioxide Production from Radiolabeled Substrates in Drosophila melanogaster

The power of Drosophila genetics is increasingly being applied to questions of hormone signaling and metabolism and to the development of models of human disease in this organism. Sensitive methods for measurements of parameters such as metabolic rates are needed to drive the understanding of physiology and disease in small animals such as the fruit fly. The method described here assesses fuel oxidation in small numbers of adult flies fed food containing trace amounts of 14C-labeled substrates such as glucose or fatty acid. After the feeding period and any additional experimental manipulations, flies are transferred to short tubes capped with mesh, which are then placed in glass vials containing KOH-saturated filter paper that traps exhaled, radiolabeled CO2 generated from oxidation of radiolabeled substrates as potassium bicarbonate, KHCO3. This radiolabeled bicarbonate is measured by scintillation counting. This is a quantitative, reproducible, and simple approach for the study of fuel oxidation. The use of radiolabeled glucose, fatty acids, or amino acids allows determination of the contribution of these different fuel sources to energy metabolism under different conditions such as feeding and fasting and in different genetic backgrounds. This complements other approaches used to measure in vivo energy metabolism and should further the understanding of metabolic regulation.

Measurement of Carbon Dioxide Production from Radiolabeled Substrates in Drosophila melanogaster

This paper describes a method for the measurement of fuel oxidation in Drosophila melanogaster in which trace amounts of specific radiolabeled metabolic substrates are fed to flies. The exhaled radiolabeled CO2 that is a produced from fuel oxidation is collected and measured.

The power of Drosophila genetics is increasingly being applied to questions of hormone signaling and metabolism and to the development of models of human ...

Monitoring Brain Metabolite Transport in Drosophila Using FRET Sensors

Visualizing Monocarboxylates and Other Relevant Metabolites in the Ex Vivo Drosophila Larval Brain Using Genetically Encoded Sensors

The high energy requirements of brains due to electrical activity are one of their most distinguishing features. These requirements are met by the production of ATP from glucose and its metabolites, such as the monocarboxylates lactate and pyruvate. It is still unclear how this process is regulated or who the key players are, particularly in Drosophila.
Using genetically encoded F&#246;rster resonance energy transfer-based sensors, we present a simple method for measuring the transport of monocarboxylates and glucose in glial cells and neurons in an ex-vivo Drosophila larval brain preparation. The protocol describes how to dissect and adhere a larval brain expressing one of the sensors to a glass coverslip. 
We present the results of an entire experiment in which lactate transport was measured in larval brains by knocking down previously identified monocarboxylate transporters in glial cells. Furthermore, we demonstrate how to rapidly increase neuronal activity and track metabolite changes in the active brain. The described method, which provides all necessary information, can be used to analyze other Drosophila living tissues.

Author Spotlight: Advances in Brain Energy Metabolism Research Using the Drosophila Model

Here we present a protocol to visualize the transport of monocarboxylates, glucose, and ATP in glial cells and neurons using genetically encoded F&#246;rster resonance energy transfer-based sensors in an ex-vivo Drosophila larval brain preparation.

The high energy requirements of brains due to electrical activity are one of their most distinguishing features. These requirements are met by the ...

Measuring Uptake of the Glucose Analog, 6-(N-(7-Nitrobenz-2-Oxa-1,3-Diazol-4-yl)Amino)-6-Deoxyglucose, in Intact Murine Neural Retina

The retina is a highly metabolic tissue with multiple cell types requiring glucose and its derivatives to produce energy in the form of ATP. Retinal cells, including endothelial cells, neurons, photoreceptors, and glial cells, express glucose transporters (GLUTs; e.g., GLUT1-4) to enable the uptake of glucose for energy production. GLUT1 is the most abundantly expressed glucose transporter in the retina. This protocol enables researchers to measure the uptake of glucose in the neural murine retina in ex vivo conditions using the fluorescent glucose analog 6-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-6-Deoxyglucose (6-NBDG). After retinal dissection, total retinal 6-NBDG levels can be easily determined via fluorescence endpoint measurement using a plate reader. For consistency, we recommend normalizing results to total protein levels. Although 6-NBDG is highly specific for GLUT1, uptake of this analog is detected in the presence of GLUT1 inhibitor BAY-876. As such, this assay provides a relatively quick and inexpensive method to measure glucose uptake ex vivo in whole mouse neural retina, which is partially mediated by GLUT1.

Multiple cell types in the retina, including endothelial cells, neurons, and glial cells, express glucose transporters (GLUTs) to enable glucose uptake into cells. Using ex vivo mouse neural retina and the fluorescent glucose analog 6-NBDG, we describe a relatively quick and inexpensive method to measure glucose uptake in the whole mouse retina.

The retina is a highly metabolic tissue with multiple cell types requiring glucose and its derivatives to produce energy in the form of ATP. Retinal ...

Measuring Glucose Uptake in Drosophila Models of TDP-43 Proteinopathy

Samenvatting

Meer video's verkennen

Hoofdstukken in deze video