Name: combining quantitative food-intake assays and forcibly activating neurons to study appetite in drosophila
Uploaded: 2018-04-24T12:30:00
Description: Watch this Scientific Journal Video about Combining Quantitative Food-intake Assays and Forcibly Activating Neurons to Study Appetite in Drosophila at JoVE.com

This work was supported in part by National Basic Research Program of China (2012CB825504), National Natural Science Foundation of China (91232720 and 9163210042), Chinese Academy of Sciences (CAS) (GJHZ201302 and QYZDY-SSW-SMC015), Bill and Melinda Gates Foundation (OPP1119434), and 100-Talents Program of CAS to Y. Zhu.

1. Preparing the feeding chamber
Note: The feeding chamber for dye-labeling feeding assay consists of two parts: the outside container (as a cover) and the inside container (as food source).
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	<li>Modify the outside container from a glass vial for culturing Drosophila (with an internal diameter of 31.8 mm and a height of 80 mm) (Figure 1A, 1C). Cover the bottom of the container with a layer of 1% agarose (5 mL) to k...

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	<li>Gao, Q., Horvath, T. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neurobiology+of+feeding+and+energy+expenditure.">Neurobiology of feeding and energy expenditure.</a> Annu Rev Neurosci. 30, 367-398 (2007).</li><li>Bjordal, M., Arquier, N., Kniazeff, J., Pin, J. P., Leopold, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sensing+of+amino+acids+in+a+dopaminergic+circuitry+promotes+rejection+of+an+incomplete+diet+in+Drosophila.">Sensing of amino acids in a dopaminergic circuitry promotes rejection of an incomplete diet in Drosophila.</a> Cell. 156 (3), 510-521 (2014).</li><li>Edgecomb, R. S., Harth, C. E., Schneiderman, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+feeding+behavior+in+adult+Drosophila+melanogaster+varies+with+feeding+regime+and+nutritional+state.">Regulation of feeding behavior in adult Drosophila melanogaster varies with feeding regime and nutritional state.</a> J Exp Biol. 197, 215-235 (1994).</li><li>Miyamoto, T., Slone, J., Song, X., Amrein, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+fructose+receptor+functions+as+a+nutrient+sensor+in+the+Drosophila+brain.">A fructose receptor functions as a nutrient sensor in the Drosophila brain.</a> Cell. 151 (5), 1113-1125 (2012).</li><li>Morton, G. J., Cummings, D. E., Baskin, D. G., Barsh, G. S., Schwartz, M. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Central+nervous+system+control+of+food+intake+and+body+weight.">Central nervous system control of food intake and body weight.</a> Nature. 443 (7109), 289-295 (2006).</li><li>Pool, A. H., Scott, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Feeding+regulation+in+Drosophila.">Feeding regulation in Drosophila.</a> Curr Opin Neurobiol. 29, 57-63 (2014).</li><li>Soderberg, J. A., Carlsson, M. A., Nassel, D. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Insulin-Producing+Cells+in+the+Drosophila+Brain+also+Express+Satiety-Inducing+Cholecystokinin-Like+Peptide,+Drosulfakinin.">Insulin-Producing Cells in the Drosophila Brain also Express Satiety-Inducing Cholecystokinin-Like Peptide, Drosulfakinin.</a> Front Endocrinol (Lausanne). 3, 109 (2012).</li><li>Stafford, J. W., Lynd, K. M., Jung, A. Y., Gordon, M. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integration+of+taste+and+calorie+sensing+in+Drosophila.">Integration of taste and calorie sensing in Drosophila.</a> J Neurosci. 32 (42), 14767-14774 (2012).</li><li>Wu, Q., Zhang, Y., Xu, J., Shen, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+hunger-driven+behaviors+by+neural+ribosomal+S6+kinase+in+Drosophila.">Regulation of hunger-driven behaviors by neural ribosomal S6 kinase in Drosophila.</a> Proc Natl Acad Sci U S A. 102 (37), 13289-13294 (2005).</li><li>Itskov, P. 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=Automated+monitoring+and+quantitative+analysis+of+feeding+behaviour+in+Drosophila.">Automated monitoring and quantitative analysis of feeding behaviour in Drosophila.</a> Nat Commun. 5, 4560 (2014).</li><li>Mair, W., Piper, M. D., Partridge, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Calories+do+not+explain+extension+of+life+span+by+dietary+restriction+in+Drosophila.">Calories do not explain extension of life span by dietary restriction in Drosophila.</a> PLoS Biol. 3 (7), e223 (2005).</li><li>Diegelmann, 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=The+CApillary+FEeder+Assay+Measures+Food+Intake+in+Drosophila+melanogaster.">The CApillary FEeder Assay Measures Food Intake in Drosophila melanogaster.</a> J Vis Exp. (121), (2017).</li><li>Ja, W. W., 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=Prandiology+of+Drosophila+and+the+CAFE+assay.">Prandiology of Drosophila and the CAFE assay.</a> Proc Natl Acad Sci U S A. 104 (20), 8253-8256 (2007).</li><li>Shiraiwa, T., Carlson, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Proboscis+extension+response+(PER)+assay+in+Drosophila.">Proboscis extension response (PER) assay in Drosophila.</a> J Vis Exp. (3), e193 (2007).</li><li>Qi, W., 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=A+quantitative+feeding+assay+in+adult+Drosophila+reveals+rapid+modulation+of+food+ingestion+by+its+nutritional+value.">A quantitative feeding assay in adult Drosophila reveals rapid modulation of food ingestion by its nutritional value.</a> Mol Brain. 8, 87 (2015).</li><li>Ja, W. W., 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=Water-+and+nutrient-dependent+effects+of+dietary+restriction+on+Drosophila+lifespan.">Water- and nutrient-dependent effects of dietary restriction on Drosophila lifespan.</a> Proc Natl Acad Sci U S A. 106 (44), 18633-18637 (2009).</li><li>Deshpande, S. A., 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=Quantifying+Drosophila+food+intake:+comparative+analysis+of+current+methodology.">Quantifying Drosophila food intake: comparative analysis of current methodology.</a> Nat Methods. 11 (5), 535-540 (2014).</li><li>Deshpande, S. A., 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=Acidic+Food+pH+Increases+Palatability+and+Consumption+and+Extends+Drosophila+Lifespan.">Acidic Food pH Increases Palatability and Consumption and Extends Drosophila Lifespan.</a> J Nutr. 145 (12), 2789-2796 (2015).</li><li>Dus, M., Min, S., Keene, A. C., Lee, G. Y., Suh, G. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Taste-independent+detection+of+the+caloric+content+of+sugar+in+Drosophila.">Taste-independent detection of the caloric content of sugar in Drosophila.</a> Proc Natl Acad Sci U S A. 108 (28), 11644-11649 (2011).</li><li>Shen, P., Cai, H. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Drosophila+neuropeptide+F+mediates+integration+of+chemosensory+stimulation+and+conditioning+of+the+nervous+system+by+food.">Drosophila neuropeptide F mediates integration of chemosensory stimulation and conditioning of the nervous system by food.</a> J Neurobiol. 47 (1), 16-25 (2001).</li><li>Yang, Z., 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=Octopamine+mediates+starvation-induced+hyperactivity+in+adult+Drosophila.">Octopamine mediates starvation-induced hyperactivity in adult Drosophila.</a> Proc Natl Acad Sci U S A. 112 (16), 5219-5224 (2015).</li><li>Ramdya, P., Schneider, J., Levine, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+neurogenetics+of+group+behavior+in+Drosophila+melanogaster.">The neurogenetics of group behavior in Drosophila melanogaster.</a> J Exp Biol. 220 (Pt 1), 35-41 (2017).</li><li>Sanchez-Alcaniz, J. A., Zappia, G., Marion-Poll, F., Benton, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+mechanosensory+receptor+required+for+food+texture+detection+in+Drosophila.">A mechanosensory receptor required for food texture detection in Drosophila.</a> Nat Commun. 8, 14192 (2017).</li><li>Zhan, Y. P., Liu, L., Zhu, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Taotie+neurons+regulate+appetite+in+Drosophila.">Taotie neurons regulate appetite in Drosophila.</a> Nat Commun. 7, 13633 (2016).</li><li>Yu, Y., 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=Regulation+of+starvation-induced+hyperactivity+by+insulin+and+glucagon+signaling+in+adult+Drosophila.">Regulation of starvation-induced hyperactivity by insulin and glucagon signaling in adult Drosophila.</a> Elife. 5, (2016).</li><li>Wood, J. G., 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=Sirtuin+activators+mimic+caloric+restriction+and+delay+ageing+in+metazoans.">Sirtuin activators mimic caloric restriction and delay ageing in metazoans.</a> Nature. 430 (7000), 686-689 (2004).</li><li>Inagaki, H. K., 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=Visualizing+Neuromodulation+In+Vivo:+TANGO-Mapping+of+Dopamine+Signaling+Reveals+Appetite+Control+of+Sugar+Sensing.">Visualizing Neuromodulation In Vivo: TANGO-Mapping of Dopamine Signaling Reveals Appetite Control of Sugar Sensing.</a> Cell. 148 (3), 583-595 (2012).</li><li>Wong, R., Piper, M. D., Wertheim, B., Partridge, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantification+of+food+intake+in+Drosophila.">Quantification of food intake in Drosophila.</a> PLoS One. 4 (6), e6063 (2009).</li><li>Sen, 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=Moonwalker+Descending+Neurons+Mediate+Visually+Evoked+Retreat+in+Drosophila.">Moonwalker Descending Neurons Mediate Visually Evoked Retreat in Drosophila.</a> Curr Biol. 27 (5), 766-771 (2017).</li><li>Ewing, L. S., Ewing, A. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Courtship+of+Drosophila+melanogaster+in+large+observation+chambers:+the+influence+of+female+reproductive+state.">Courtship of Drosophila melanogaster in large observation chambers: the influence of female reproductive state.</a> Behaviour. 101 (1), 243-252 (1987).</li><li>Chatterjee, A., Tanoue, S., Houl, J. H., Hardin, P. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+gustatory+physiology+and+appetitive+behavior+by+the+Drosophila+circadian+clock.">Regulation of gustatory physiology and appetitive behavior by the Drosophila circadian clock.</a> Curr Biol. 20 (4), 300-309 (2010).</li><li>Xu, K., Zheng, X., Sehgal, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+feeding+and+metabolism+by+neuronal+and+peripheral+clocks+in+Drosophila.">Regulation of feeding and metabolism by neuronal and peripheral clocks in Drosophila.</a> Cell Metab. 8 (4), 289-300 (2008).</li><li>Hamada, F. N., 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=An+internal+thermal+sensor+controlling+temperature+preference+in+Drosophila.">An internal thermal sensor controlling temperature preference in Drosophila.</a> Nature. 454 (7201), 217-255 (2008).</li><li>Viswanath, V., 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=Ion+channels+-+Opposite+thermosensor+in+fruitfly+and+mouse.">Ion channels - Opposite thermosensor in fruitfly and mouse.</a> Nature. 423 (6942), 822-823 (2003).</li><li>Yu, Y., 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=Regulation+of+starvation-induced+hyperactivity+by+insulin+and+glucagon+signaling+in+adult+Drosophila.">Regulation of starvation-induced hyperactivity by insulin and glucagon signaling in adult Drosophila.</a> Elife. 5, (2016).</li><li>Klapoetke, N. C., 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=Independent+optical+excitation+of+distinct+neural+populations.">Independent optical excitation of distinct neural populations.</a> Nat Methods. 11 (3), 338-346 (2014).</li><li>Viswanath, V., 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=Opposite+thermosensor+in+fruitfly+and+mouse.">Opposite thermosensor in fruitfly and mouse.</a> Nature. 423 (6942), 822-823 (2003).</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>Lee, K. S., You, K. H., Choo, J. K., Han, Y. M., Yu, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Drosophila+short+neuropeptide+F+regulates+food+intake+and+body+size.">Drosophila short neuropeptide F regulates food intake and body size.</a> J Biol Chem. 279 (49), 50781-50789 (2004).</li><li>Marella, S., Mann, K., Scott, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dopaminergic+Modulation+of+Sucrose+Acceptance+Behavior+in+Drosophila.">Dopaminergic Modulation of Sucrose Acceptance Behavior in Drosophila.</a> Neuron. 73 (5), 941-950 (2012).</li><li>Albin, S. D., 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=A+Subset+of+Serotonergic+Neurons+Evokes+Hunger+in+Adult+Drosophila.">A Subset of Serotonergic Neurons Evokes Hunger in Adult Drosophila.</a> Current Biology. 25 (18), 2435-2440 (2015).</li><li>Ro, J., 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=Serotonin+signaling+mediates+protein+valuation+and+aging.">Serotonin signaling mediates protein valuation and aging.</a> eLife. 5, e16843 (2016).</li></ol>

This report focuses on the technical process of dye-labeling feeding assays of food consumption in the context of thermogenetic and optogenetic activation to manipulate neurons controlling feeding. This simple and reliable protocol will help to elucidate the function of candidate neurons in feeding control, to measure the food preference of flies, and to identify novel players in the feeding control circuits via feeding-based genetic screens24.
The dye labeling strategy...

Quantifying the amount of food ingested is important for evaluating multiple aspects of feeding controls by the brain in responding to the internal needs (such as hunger states) and external factors (such as food quality and palatability)1,2,3,4,5,6,7,8,9. In recent years, the efforts of deciphering the neural substrates of feeding control in Drosophila lead to the development of multiple assays to directly quantify the amount of food ingested or serve as an indicator of feeding motivation10,11,12,13,14,15,16.
The CApillary FEeder (CAFE) assay12,13 was developed to measure the amount of consumption of liquid food in a glass microcapillary. The CAFE assay is highly sensitive and reproducible17 and simplifies the measurement of food consumption, especially for quantifying long-term feeding18. However, this assay requires the flies to climb to the tip of the microcapillary and feed upside-down, which is not suitable for all strains. Additionally, because the flies to be tested using the CAFE assay have to be reared on liquid food, the effect of these rearing conditions on metabolism status or the potential malnutrition remains to be determined.
The Proboscis Extension Response (PER) assay11,14 counts the frequency of proboscis extension responses toward gentle touches of food drops. PER assay proved as an excellent way to evaluate feeding motivation of individual fly and asses the influence of palatability and content of food18,19. However, it is not a direct quantification of intake amount.
Recently, a semi-automatic method, the manual feeding assay (MAFE)15, was developed. In MAFE, a single immobilized fly is fed manually with a microcapillary containing food. Given that proboscis extension responses and food consumption can be monitored simultaneously, MAFE is suitable for assessing nutrient values and the effects of pharmacological manipulation. However, immobilizing a fly might negatively impact its behavioral performance, including feeding.
Additionally, fly Proboscis and Activity Detector (FlyPAD)10 was developed to automatically quantify feeding behavior. Using machine vision methods, FlyPAD records physical interactions between a fly and food to quantify the frequency and duration of proboscis extensions as an indicator of feeding motivation. FlyPAD provides a high-throughput approach to monitor the feeding behaviors of a free-moving fly, although the sensitivity and robustness of this system remains to be further confirmed by more studies12.
Labeling strategies are frequently used to estimate food ingestion in flies. It is common to label food with chemical tracers and, after feeding, measure the amount of ingested tracer to calculate the quantity of food intake. Radioactive tracers16,17,20,21,22,23,24,25 allow for the detection through the cuticle without homogenization of the flies. This method provides remarkably low variability and high sensitivity18, and is feasible for long-term study of food intake. However, the availability of usable radioisotopes and different rates of absorbance and excretion should be taken into consideration when working with this assay.
Labeling and tracing food intake with non-toxic food colors is a safer and simpler alternative2,3,26,27,28. Flies are homogenized after feeding with food containing soluble and non-absorbable dyes, and the amount of the ingested dye is later quantified using a spectrophotometer3,24,28,29. The labeling strategy is easy to perform and provides high efficiency, but with a caveat. The volume of food intake estimated from the ingested dye is smaller than the actual volume because excretion begins as early as 15 min after flies start feeding17. Additionally, the assay assesses food ingestion typically within a 60-min period, which is only suitable for investigation of short-term feeding behavior24,28. Moreover, multiple internal and external factors, such as genotype17, gender17, mated state17, rearing density30, circadian rhythm31,32, and food quality3,8,16, influence food intake. Therefore, the feeding duration might need to be adjusted according to specific experimental conditions. Besides facilitating the quantification of food intake, food colors are also used to assess food choices2,19,27, and to visualize the meniscus in a microcapillary in CAFE assay12.
Here, we introduce a protocol combined manipulation of neuronal activity with dye-labeling approach. This strategy has been proved useful in our neurogenetic study on feeding control in adult fruit flies24. The visual scoring method allows for a quick estimation of food consumption; thus, it is useful for screening through a large number of strains in a timely fashion. The candidates from the screen are then analyzed in detail using a colorimetric method to provide objective and precise quantification in additional study.
Besides the feeding assays, we also describe the thermogenetic27,33,34,35 and optogenetic36 methods of forcibly activating target neurons in Drosophila. To activate neurons by thermogenetic operation is simple and convenient with Drosophila Transient Receptor Potential Ankyrin 1 (dTRPA1), which is a temperature- and voltage-gated cation channel that increases neuronal excitability when the ambient temperature rises above 23 &#176;C33,37; however, testing animals at high temperatures might produce adverse effects on behavior. Another effective approach to activate neurons in Drosophila is using optogenetics with CsChrimson36, which is a red-shifted variant of channelrhodopsin that increases the excitability of neurons when exposed to light. Optogenetics offers higher temporal resolution and lesser disturbance to behaviors than thermogenetics. Combining the quantitative measurement of food intake with the manipulation of neuronal activity represents an effective approach for studying the neural mechanisms of feeding.
We describe in detail the preparation of the feeding chamber and the flies to be tested. Using Taotie-Gal4 flies as a model24, we describe activating neurons by thermogenetics and optogenetics. Two assays of quantification of food consumption with dye-labeled food are also described in the protocol.

<table border="0" cellpadding="0" cellspacing="0" width="942">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:332px;">UAS-CsChrimson</td>
			<td style="width:163px;">Bloomintoon</td>
			<td style="width:176px;">55135</td>
			<td style="width:272px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:332px;">UAS-dTrpA1</td>
			<td style="width:163px;">Bloomintoon</td>
			<td>26263</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">TDC1-GAL4&#160;</td>
			<td style="width:163px;">Bloomintoon</td>
			<td style="width:176px;">9312</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:332px;">TDC2-GAL4</td>
			<td style="width:163px;">Bloomintoon</td>
			<td style="width:176px;">9313</td>
			<td></td>
		</tr>
		<tr height="24">
			<td height="24" style="height:24px;">sNPF-GAL4</td>
			<td></td>
			<td></td>
			<td style="width:272px;">Provided by Z. Zhao</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">NPF-GAL4</td>
			<td></td>
			<td></td>
			<td style="width:272px;">Provided by Y. Rao</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">TH-GAL4</td>
			<td></td>
			<td></td>
			<td style="width:272px;">Provided by Y. Rao</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">5-HT-GAL4</td>
			<td></td>
			<td></td>
			<td style="width:272px;">Provided by Y. Rao</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">AKH-GAL4</td>
			<td></td>
			<td></td>
			<td style="width:272px;">Provided by Y. Rao</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">dip2-GAL4</td>
			<td></td>
			<td></td>
			<td>Provided by Y. Rao</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:332px;">Taotie-GAL4</td>
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			<td>Provided by J. Carlson</td>
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			<td height="20" style="height:20px;width:332px;">Agarose</td>
			<td>Biowest</td>
			<td style="width:176px;">G-10</td>
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		<tr height="20">
			<td height="20" style="height:20px;width:332px;">Sucrose</td>
			<td>Sigma</td>
			<td style="width:176px;">S7903</td>
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			<td height="20" style="height:20px;">Erioglaucine disodium salt</td>
			<td>Sigma</td>
			<td>861146</td>
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			<td height="20" style="height:20px;">all-trans-retinal&#160;</td>
			<td style="width:163px;">Sigma&#160;</td>
			<td style="width:176px;">R2500</td>
			<td>stored in darkness</td>
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			<td height="20" style="height:20px;">Triton X-100</td>
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			<td>9002-93-01</td>
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			<td height="146" style="height:146px;width:332px;">Fly food</td>
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			<td style="width:176px;">1 L food contains: 77.7 g corn meal, 32.19 g yeast, 5 g agar, 0.726 g CaCl2, 31.62 g sucrose, 63.2 g glucose, 2 g potassium sorbate, pH&#160;&#160;&#160;</td>
			<td></td>
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			<td height="92" style="height:92px;">&#160;1x PBS buffer&#160;</td>
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			<td style="width:176px;">1 L 1X PBS contains: 8 g Nacl, 0.2 g Kcl, 1.44 g Na2HPO4, 0.24 g KH2PO4, pH 7.4</td>
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		<tr height="20">
			<td height="20" style="height:20px;width:332px;">PBST buffer</td>
			<td style="width:163px;"></td>
			<td colspan="2">1X PBS with 1% Triton X-100</td>
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		<tr height="20">
			<td height="20" style="height:20px;">&#160;Grinding mill</td>
			<td style="width:163px;">Shang Hai Jing Xin</td>
			<td>Tissuelyser-24</td>
			<td></td>
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		<tr height="20">
			<td height="20" style="height:20px;width:332px;">Incubator</td>
			<td style="width:163px;">Ning Bo Jiang Nan</td>
			<td>HWS-80</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Magnetic stirrer with a heat plate</td>
			<td style="width:163px;">Chang Zhou Bo Yuan</td>
			<td style="width:176px;">CJJ 78-1</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Spectrometer</td>
			<td style="width:163px;">Thorlabs</td>
			<td style="width:176px;">CCS200/M</td>
			<td></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:332px;">Microplate Spectrophotometer</td>
			<td>Thermo Scientific&#160;</td>
			<td style="width:176px;">Multiskan GO Type: 1510, REF 51119200</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Fluorescence stereo microscope&#160;</td>
			<td style="width:163px;">Leica</td>
			<td style="width:176px;">&#160;M205FA</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Stereo microscope</td>
			<td style="width:163px;">Leica&#160;</td>
			<td style="width:176px;">S6E</td>
			<td></td>
		</tr>
		<tr height="80">
			<td height="80" style="height:80px;width:332px;">Outside container</td>
			<td>Jiang Su Hai Men</td>
			<td style="width:176px;">glass vial with a diameter of 31.8 mm and a height of 80 mm (inside dimension)</td>
			<td></td>
		</tr>
		<tr height="80">
			<td height="80" style="height:80px;width:332px;">Inside container&#160;</td>
			<td>Beijing Yi Ran machinery factory</td>
			<td style="width:176px;">plastic dish with a diameter of 13.6 mm and a height of 7.5 mm (inside dimension)</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:332px;">1.5 mL Eppendorf tubes</td>
			<td style="width:163px;">Hai Men Ning Mong</td>
			<td style="width:176px;"></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">&#160;96 well plate</td>
			<td style="width:163px;">Corning Incorporated</td>
			<td style="width:176px;">&#160;Costar 3599</td>
			<td></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:332px;">LEDs</td>
			<td style="width:163px;">Xin Xing Yuan Guangdian</td>
			<td style="width:176px;">607 nm, 3W&#160;</td>
			<td>https://item.taobao.com/item.htm?id=20158878058</td>
		</tr>
	</tbody>
</table>

combining quantitative food-intake assays and forcibly activating neurons to study appetite in drosophila

Food consumption is under the tight control of the brain, which integrates the physiological status, palatability, and nutritional contents of the food, and issues commands to start or stop feeding. Deciphering the processes underlying the decision-making of timely and moderate feeding carries major implications in our understanding of physiological and psychological disorders related to feeding control. Simple, quantitative, and robust methods are required to measure the food ingestion of animals after experimental manipulation, such as forcibly increasing the activities of certain target neurons. Here, we introduced dye-labeling-based feeding assays to facilitate the neurogenetic study of feeding control in adult fruit flies. We review available feeding assays, and then describe our methods step-by-step from setup to analysis, which combine thermogenetic and optogenetic manipulation of neurons controlling feeding motivation with dye-labeled food intake assay. We also discuss the advantages and limitations of our methods, compared with other feeding assays, to help readers choose an appropriate assay.

Thermogenetic screen.
Abnormally increased appetite causes elevated food intake, regardless of physiological needs. We utilized this scheme to design a high-throughput behavioral screen to obtain genetic handles of neurons related to hunger and satiated states (Figure 1). The screen yielded Taotie-Gal424. When the Taotie-Gal4 neurons were forcibly activated ...

Watch this Scientific Journal Video about Combining Quantitative Food-intake Assays and Forcibly Activating Neurons to Study Appetite in Drosophila at JoVE.com

Combining Quantitative Food-intake Assays and Forcibly Activating Neurons to Study Appetite in Drosophila

Quantitative food-intake assays with dyed food provide a robust and high-throughput means to evaluate feeding motivation. Combining the food consumption assay with thermogenetic and optogenetic screens is a powerful approach to investigate the neural circuits underlying appetite in adult Drosophila melanogaster.

Combining Quantitative Food-intake Assays and Forcibly Activating Neurons to Study Appetite in Drosophila

Food consumption is under the tight control of the brain, which integrates the physiological status, palatability, and nutritional contents of the food, ...

The overall goal of this procedure is to quantitatively measure the food-intake of adult Drosophila, which provides a means to evaluate the effects of genetic manipulations such as thermogenetic and optogenetic activations of neurons. These measures can help answer key questions in the feeding field such as the neuro mechanics of hunger satiety and appetite. The main advantage of this technique is that it simultaneously quantifies food intake of multiple groups of flies, making it especially useful to identify abnormally feeding flies in genetic screens.To be begin gather supplies to prepare the outside container. Suspend 0.5 grams of agarose and 50 milliliters of double-distilled water. Heat with frequent agitation, and boil to dissolve completely on a magnetic stirrer with a heat plate.When the 1%agarose cools to about 60 degrees Celsius, transfer five milliliters to an empty outside container and keep the container open until the agarose has cooled down to room temperature to yield an agarose pad. Next, add 0.5 grams of agarose to 50 milliliters of double-distilled water. Heat with frequent agitation and boil to dissolve completely on a magnetic stirrer with a heat plate.When the 1%agarose cools to about 60 degrees Celsius, add 1.71 grams of sucrose to the agarose to obtain 100 millimole of sucrose. Add 0.25 grams of blue dye to the agarose solution to obtain 0.5%weight per volume dyed labeled food. Then prepare the inside container.Put the empty inside containers on a flat horizontal surface. Then add 750 microliter of blue dye labeled food to individual food containers. Let solidify for at least five minutes.Transfer a filled inside container into a prepared outside container and position it at the center of the agarose pad. Prepare feeding chambers with dye-free food for background subtraction. Leave the feeding chambers open at room temperature for 40 minutes, until the wall of the outside container is free of condensation.Before behavioral experiments, equilibrate the prepared feeding chambers at the experimental temperature of 30 degrees Celsius for two hours to ensure the temperature is relatively uniform in the feeding chambers. To start the feeding process, carefully transfer 20 flies from their home vial into a preheated feeding chamber by gentle tapping. Continue the feeding process at 30 degrees Celsius for 60 minutes.Cease feeding by freezing the feeding chambers at negative 80 degrees Celsius for 30 minutes. Carefully transfer 20 flies from one vial into a feeding chamber by gentle tapping. And then place the chamber sideways on the illumination setup.For optogenetic manipulation, use an array of orange LEDs as the source of light stimulation, and fix a horizontal plexiglass plate above the LEDs to support the feeding chambers during illumination. Keep the setup in an incubator at 25 degrees Celsius with 60%humidity. Stimulate the genetic control flies in parallel with the Taotie-GAL4 UAS CsChrimson flies, but in different feeding chambers.Continue the feeding process for 60 minutes with back illumination by the orange light. Then freeze the feeding chambers at negative 80 degrees Celsius for 30 minutes. After ceasing the feeding, pour out all 20 flies from the feeding chamber on to a piece of weighing paper.Then transfer them into a 1.5 milliliter tube using a soft brush. Add 500 microliters of PBST to the tube and homogenize the flies using a grinding mill at 60 hertz for five seconds. Then confirm sufficient homogenization by observation when there are no detectable fragments of body parts.Spin the tubes with homogenates for 30 minutes at 1300 RPM to clear the debris. After centrifugation, transfer 100 microliters of supernatant to a well of 96 well plate. To avoid the miscalculation of absorbents caused by debris, gently take the tube used out of the centrifuge and carefully drop the supernatant without disturbing the pallet.After all the samples are loaded, place the plate into a plate reader to measure the absorbents of the samples at 630 nanometers. The feeding response was quantified by visually inspecting and scoring flies with detectable dye in the gut. After activation of Taotie neurons, about 58%of Taotie dTRPA1 flies exhibited strong feeding behaviors.And 23%of these showed mild feeding behaviors. Acute activated Taotie-GAL4 neurons by TRPA1 dramatically increased food intake, suggesting that the Taotie-GAL4 labeled neurons participate in regulation of food intake of adult Drosophila. After watching this video, you should have a good understanding of how to quantify the amount of food intake after manipulating the activity of neurons to investigate neuro mechanisms of feeding control in adult Drosophila melanogaster.

combining-quantitative-food-intake-assays-forcibly-activating-neurons

Research

JoVE Journal

Behavior

A Procedure to Study the Effect of Prolonged Food Restriction on Heroin Seeking in Abstinent Rats

In human drug addicts, exposure to drug-associated cues or environments that were previously associated with drug taking can trigger relapse during abstinence. Moreover, various environmental challenges can exacerbate this effect, as well as increase ongoing drug intake.
The procedure we describe here highlights the impact of a common environmental challenge, food restriction, on drug craving that is expressed as an augmentation of drug seeking in abstinent rats.
Rats are implanted with chronic intravenous i.v. catheters, and then trained to press a lever for i.v. heroin over a period of 10-12 days. Following the heroin self-administration phase the rats are removed from the operant conditioning chambers and housed in the animal care facility for a period of at least 14 days. While one group is maintained under unrestricted access to food (sated group), a second group (FDR group) is exposed to a mild food restriction regimen that results in their body weights maintained at 90% of their nonrestricted body weight. On day 14 of food restriction the rats are transferred back to the drug-training environment, and a drug-seeking test is run under extinction conditions (i.e.&#160;lever presses do not result in heroin delivery).
The procedure presented here results in a highly robust augmentation of heroin seeking on test day in the food restricted rats. In addition, compared to the acute food deprivation manipulations we have used before, the current procedure is a more clinically relevant model for the impact of caloric restriction on drug seeking. Moreover, it might be closer to the human condition as the rats are not required to go through an extinction-training phase before the drug-seeking test, which is an integral component of the popular reinstatement procedure.

A procedure that allows a demonstration of robust augmentation of drug seeking in food-restricted rats is described. Following heroin self-administration training, rats go through an abstinence period, in a drug-free environment, during which they are mildly food restricted. Drug seeking is then tested in the drug-associated environment.

In human drug addicts, exposure to drug-associated cues or environments that were previously associated with drug taking can trigger relapse during ...

Uncovering Beat Deafness: Detecting Rhythm Disorders with Synchronized Finger Tapping and Perceptual Timing Tasks

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here with the goal of uncovering rhythm disorders, such as beat deafness. Beat deafness is characterized by poor performance in perceiving durations in auditory rhythmic patterns or poor synchronization of movement with auditory rhythms (e.g., with musical beats). These tasks include the synchronization of finger tapping to the beat of simple and complex auditory stimuli and the detection of rhythmic irregularities (anisochrony detection task) embedded in the same stimuli. These tests, which are easy to administer, include an assessment of both perceptual and sensorimotor timing abilities under different conditions (e.g., beat rates and types of auditory material) and are based on the same auditory stimuli, ranging from a simple metronome to a complex musical excerpt. The analysis of synchronized tapping data is performed with circular statistics, which provide reliable measures of synchronization accuracy (e.g., the difference between the timing of the taps and the timing of the pacing stimuli) and consistency. Circular statistics on tapping data are particularly well-suited for detecting individual differences in the general population. Synchronized tapping and anisochrony detection are sensitive measures for identifying profiles of rhythm disorders and have been used with success to uncover cases of poor synchronization with spared perceptual timing. This systematic assessment of perceptual and sensorimotor timing can be extended to populations of patients with brain damage, neurodegenerative diseases (e.g., Parkinson&#8217;s disease), and developmental disorders (e.g., Attention Deficit Hyperactivity Disorder).

Behavioral tasks that allow for the assessment of perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) are presented. Synchronization of finger tapping to the beat of an auditory stimuli and detecting rhythmic irregularities provides a means of uncovering rhythm disorders.

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here ...

Combining Multiple Data Acquisition Systems to Study Corticospinal Output and Multi-segment Biomechanics

Transcranial magnetic stimulation techniques allow for an in-depth investigation into the neural mechanisms that underpin human behavior. To date, the use of TMS to study human movement, has been limited by the challenges related to precisely timing the delivery of TMS to features of the unfolding movement and, also, by accurately characterizing kinematics and kinetics. To overcome these technical challenges, TMS delivery and acquisition systems should be integrated with an online motion tracking system. The present manuscript details technical innovations that integrate multiple acquisition systems to facilitate and advance the use of TMS to study human movement. Using commercially available software and hardware systems, a step-by-step approach to both the hardware assembly and the software scripts necessary to perform TMS studies triggered by specific features of a movement is provided. The approach is focused on the study of upper limb, planar, multi-joint reaching movements. However, the same integrative system is amenable to a multitude of sophisticated studies of human motor control.

The use of transcranial magnetic stimulation (TMS) to study human motor control requires the integration of data acquisition systems to control TMS delivery and simultaneously record human behavior. The present manuscript provides a detailed methodology for integrating data acquisition systems for the purpose of investigating human movement via TMS.

Transcranial magnetic stimulation techniques allow for an in-depth investigation into the neural mechanisms that underpin human behavior. To date, the use ...

Feeding Experimentation Device (FED): Construction and Validation of an Open-source Device for Measuring Food Intake in Rodents

Food intake measurements are essential for many research studies. Here, we provide a detailed description of a novel solution for measuring food intake in mice: the Feeding Experimentation Device (FED). FED is an open-source system that was designed to facilitate flexibility in food intake studies. Due to its compact and battery powered design, FED can be placed within standard home cages or other experimental equipment. Food intake measurements can also be synchronized with other equipment in real-time via FED's transistor-transistor logic (TTL) digital output, or in post-acquisition processing as FED timestamps every event with a real-time clock. When in use, a food pellet sits within FED's food well where it is monitored via an infrared beam. When the pellet is removed by the mouse, FED logs the timestamp onto its internal secure digital (SD) card and dispenses another pellet. FED can run for up to 5 days before it is necessary to charge the battery and refill the pellet hopper, minimizing human interference in data collection. Assembly of FED requires minimal engineering background, and off-the-shelf materials and electronics were prioritized in its construction. We also provide scripts for analysis of food intake and meal patterns. Finally, FED is open-source and all design and construction files are online, to facilitate modifications and improvements by other researchers.

Feeding Experimentation Device FED: Construction and Validation of an Open-source Device for Measuring Food Intake in Rodents

Feeding Experimentation Device (FED) is an open-source device for measuring food intake in mice. FED can also synchronize food intake measurements with other techniques via a real-time digital output. Here, we provide a step-by-step tutorial for the construction, validation, and usage of FED.

Food intake measurements are essential for many research studies. Here, we provide a detailed description of a novel solution for measuring food intake in ...

Application of MultiColor FlpOut Technique to Study High Resolution Single Cell Morphologies and Cell Interactions of Glia in Drosophila

Cells display different morphologies and complex anatomical relationships. How do cells interact with their neighbors? Do the interactions differ between cell types or even within a given type? What kinds of spatial rules do they follow? The answers to such fundamental questions in vivo have been hampered so far by a lack of tools for high resolution single cell labeling. Here, a detailed protocol to target single cells with a MultiColor FlpOut (MCFO) technique is provided. This method relies on three differently tagged reporters (HA, FLAG and V5) under UAS control that are kept silent by a transcriptional terminator flanked by two FRT sites (FRT-stop-FRT). A heat shock pulse induces the expression of a heat shock-induced Flp recombinase, which randomly removes the FRT-stop-FRT cassettes in individual cells: expression occurs only in cells that also express a GAL4 driver. This leads to an array of differently colored cells of a given cell type that allows the visualization of individual cell morphologies at high resolution. As an example, the MCFO technique can be combined with specific glial GAL4 drivers to visualize the morphologies of the different glial subtypes in the adult Drosophila brain.

Application of MultiColor FlpOut Technique to Study High Resolution Single Cell Morphologies and Cell Interactions of Glia in Drosophila

Cells display different morphologies and establish a variety of interactions with their neighbors. This protocol describes how to reveal the morphology of single cells and to investigate cell-cell interaction by using the well-established Gal4/UAS expression system.

Cells display different morphologies and complex anatomical relationships. How do cells interact with their neighbors? Do the interactions differ between ...

Reversible Cooling-induced Deactivations to Study Cortical Contributions to Obstacle Memory in the Walking Cat

On complex, naturalistic terrain, sensory information about an environmental obstacle can be used to rapidly adjust locomotor movements for avoidance. For example, in the cat, visual information about an impending obstacle can modulate stepping for avoidance. Locomotor adaptation can also occur independent of vision, as sudden tactile inputs to the leg by an expected obstacle can modify the stepping of all four legs for avoidance. Such complex locomotor coordination involves supraspinal structures, such as the parietal cortex. This protocol describes the use of reversible, cooling-induced cortical deactivation to assess parietal cortex contributions to memory-guided obstacle locomotion in the cat. Small cooling loops, known as cryoloops, are specially shaped to deactivate discrete regions of interest to assess their contributions to an overt behavior. Such methods have been used to elucidate the role of parietal area 5 in memory-guided obstacle avoidance in the cat.

Complex locomotion in naturalistic environments requiring careful coordination of the limbs involves regions of the parietal cortex. The following protocol describes the use of reversible cooling-induced deactivation to demonstrate the role of parietal area 5 in memory-guided obstacle avoidance in the walking cat.

On complex, naturalistic terrain, sensory information about an environmental obstacle can be used to rapidly adjust locomotor movements for avoidance. For ...

An Automated Method to Determine the Performance of Drosophila in Response to Temperature Changes in Space and Time

Temperature is a ubiquitous environmental factor that affects how species distribute and behave. Different species of Drosophila fruit flies have specific responses to changing temperatures according to their physiological tolerance and adaptability. Drosophila flies also possess a temperature sensing system that has become fundamental to understanding the neural basis of temperature processing in ectotherms. We present here a temperature-controlled arena that permits fast and precise temperature changes with temporal and spatial control to explore the response of individual flies to changing temperatures. Individual flies are placed in the arena and exposed to pre-programmed temperature challenges, such as uniform gradual increases in temperature to determine reaction norms or spatially distributed temperatures at the same time to determine preferences. Individuals are automatically tracked, allowing the quantification of speed or location preference. This method can be used to rapidly quantify the response over a large range of temperatures to determine temperature performance curves in Drosophila or other insects of similar size. In addition, it can be used for genetic studies to quantify temperature preferences and reactions of mutants or wild-type flies. This method can help uncover the basis of thermal speciation and adaptation, as well as the neural mechanisms behind temperature processing.

An Automated Method to Determine the Performance of Drosophila in Response to Temperature Changes in Space and Time

Here we present a protocol to automatically determine the locomotor performance of Drosophila at changing temperatures using a programmable temperature-controlled arena that produces fast and accurate temperature changes in time and space.

Temperature is a ubiquitous environmental factor that affects how species distribute and behave. Different species of Drosophila fruit flies have specific ...

Assessing the Coherence of Parents' Short Narratives Regarding their Child Using the Five-Minute Speech Sample Procedure

Valid and efficient measures for assessing the quality of parent-child relationships are needed to facilitate research and evidence-based practice with parents. This paper focuses on such a method, namely Five-Minute Speech Sample-Coherence (FMSS-Coherence). In this method, a parent is asked to speak for five uninterrupted minutes about her/his child and their relationship. The resulted narrative is coded for coherence, namely the extent to which the parent provides&#160;in the narrative&#160;a clear, consistent, multidimensional and well-supported portrayal of the child. FMSS-Coherence is based on attachment research that shows that the coherence of parents&#8217; narratives is indicative of the quality of the parent-child relationship and child adjustment. It overcomes the limitations of attachment narrative measures which are typically labor intensive. FMSS-Coherence is less nuanced than extant attachment narrative measures. Yet, studies of families from different cultural backgrounds, across different child ages and in the context of typically developing children as well as children with special needs suggest that coherence can be reliably evaluated using the FMSS procedure. Furthermore, parents&#8217; FMSS-Coherence is associated with parenting quality and children&#8217;s socio-emotional adjustment. Thus, it holds promise for researchers and practitioners who seek a relatively time- and cost-effective method for assessing the coherence of parents&#8217; narratives regarding their child.

Assessing the Coherence of Parents&#039; Short Narratives Regarding their Child Using the Five-Minute Speech Sample Procedure

This paper introduces a method for assessing the coherence of parents' short narratives regarding their child and their relationship using the five-minute speech sample procedure.

Valid and efficient measures for assessing the quality of parent-child relationships are needed to facilitate research and evidence-based practice with ...

Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method

The vast majority of dietary and eating behavior assessment methods are based on self-reports. They are burdensome and also prone to measurement errors. Recent technological innovations allow for the development of more accurate and precise dietary and eating behavior assessment tools that require less effort for both the user and the researcher. Therefore, a new sensor-based device to assess food intake and eating behavior was developed. The device is a regular dining tray equipped with a video camera and three separate built-in weighing stations. The weighing stations measure the weight of the bowl, plate, and drinking cup continuously over the course of a meal. The video camera positioned to the face records eating behavior characteristics (chews, bites), which are analyzed using artificial intelligence (AI)-based automatic facial expression software. The tray weight and the video data are transported at real-time to a personal computer (PC) using a wireless receiver. The outcomes of interest, such as the amount eaten, eating rate and bite size, can be calculated by subtracting the data of these measures at the timepoints of interest. The information obtained by the current version of the tray can be used for research purposes, an upgraded version of the device would also facilitate the provision of more personalized advice on dietary intake and eating behavior. Contrary to the conventional dietary assessment methods, this dietary assessment device measures food intake directly within a meal and is not dependent on memory or the portion size estimation. Ultimately, this device is therefore suited for daily main meal food intake and eating behavior measures. In the future, this technology based dietary assessment method can be linked to health applications or smart watches to obtain a complete overview of exercise, energy intake, and eating behavior.

This protocol shows and explains a new technology-based dietary assessment method. The method consists of a dining tray with multiple built-in weighing scales and a video camera. The device is unique in the sense that it incorporates automated measures of food and drink intake and eating behavior over the course of a meal.

The vast majority of dietary and eating behavior assessment methods are based on self-reports. They are burdensome and also prone to measurement errors. ...

Drosophila Passive Avoidance Behavior as a New Paradigm to Study Associative Aversive Learning

This protocol describes a new paradigm for analyzing aversive associative learning in adult flies (Drosophila melanogaster). The paradigm is analogous to passive avoidance behavior in laboratory rodents in which animals learn to avoid a compartment where they have previously received an electric shock. The assay takes advantage of negative geotaxis in flies, which manifests as an urge to climb up when they are placed on a vertical surface. The setup consists of vertically oriented upper and lower compartments. On the first trial, a fly is placed into a lower compartment from where it usually exits&#160;within 3-15 s, and steps into the upper compartment where it receives an electric shock. During the second trial, 24 h later, the latency is significantly increased. At the same time, the number of shocks is decreased compared to the first trial, indicating that flies formed long-term memory about the upper compartment. The recordings of latencies and number of shocks could be performed with a tally counter and a stopwatch or with an Arduino-based simple device. To illustrate how the assay can be used, the passive avoidance behavior of D. melanogaster and D. simulans male and female were characterized here. Comparison of latencies and number of shocks revealed that both D. melanogaster and D. simulans flies efficiently learned the passive avoidance behavior. No statistical differences were observed between male and female flies. However, males were a little faster while entering the upper compartment on the first trial, while females received a slightly higher number of shocks in every retention trial. The Western diet (WD) significantly impaired learning and memory in male flies while flight exercise counterbalanced this effect. Taken together, the passive avoidance behavior in flies offers a simple and reproducible assay that could be used for studying basic mechanisms of learning and memory.

Drosophila Passive Avoidance Behavior as a New Paradigm to Study Associative Aversive Learning

This work describes a simple behavioral paradigm that allows the analysis of aversive associative learning in adult fruit flies. The method is based on suppressing the innate negative geotaxis behavior due to the association formed between a specific environmental context and an electric shock.

This protocol describes a new paradigm for analyzing aversive associative learning in adult flies (Drosophila melanogaster). The paradigm is analogous to ...