This work was supported by NIH grants NIH34958 to I. E and NS061952 to J. C.

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T., Kramer, A., Edery, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+phospho-occupancy+of+an+atypical+SLIMB-binding+site+on+PERIOD+that+is+phosphorylated+by+DOUBLETIME+controls+the+pace+of+the+clock.">The phospho-occupancy of an atypical SLIMB-binding site on PERIOD that is phosphorylated by DOUBLETIME controls the pace of the clock.</a> Genes Dev. 22, 1758-1772 (2008).</li><li>Dubruille, R., Murad, A., Rosbash, M., Emery, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+constant+light-genetic+screen+identifies+KISMET+as+a+regulator+of+circadian+photoresponses.">A constant light-genetic screen identifies KISMET as a regulator of circadian photoresponses.</a> PLoS Genet. 12, e1000787-e1000787 (2009).</li><li>Glaser, F. T., Stanewsky, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temperature+synchronization+of+the+Drosophila+circadian+clock.">Temperature synchronization of the Drosophila circadian clock.</a> Curr Biol. 15, 1352-1363 (2005).</li><li>Helfrich-F&#246;rster, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+control+of+morning+and+evening+components+in+the+activity+rhythm+of+Drosophila+melanogaster-+sex-specific+differences+suggest+a+different+quality+of+activity.">Differential control of morning and evening components in the activity rhythm of Drosophila melanogaster- sex-specific differences suggest a different quality of activity.</a> J Biol Rhythms. 15, 135-154 (2000).</li><li>Hendricks, J. C., Finn, S. M., Pancleri, K. A., Chavkin, J., Williams, J., Sehgal, A., Pack, A. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rest+in+Drosophila+is+a+sleep-like+state.">Rest in Drosophila is a sleep-like state.</a> Neuron. 25, 129-138 (2000).</li><li>Ho, K. S., 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=Drosophila+melanogaster:+an+insect+model+for+fundamental+studies+of+sleep.">Drosophila melanogaster: an insect model for fundamental studies of sleep.</a> Methods Enzymol. 393, 772-793 (2005).</li><li>Koh, K., Evans, J. M., Hendricks, J. C., 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=A+Drosophila+model+for+age-associated+changes+in+sleep:+wake+cycles.">A Drosophila model for age-associated changes in sleep: wake cycles.</a> Proc Natl Acad Sci USA. 103, 13843-13847 (2006).</li><li>Konopka, R. J., Benzer, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clock+mutants+of+Drosophila+melanogaster.">Clock mutants of Drosophila melanogaster.</a> Proc Natl Acad Sci USA. 68, 2112-2116 (1971).</li><li>McGuire, S. E., Roman, G., Davis, R. 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P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+locomotor+activity+rhythms+in+Drosophila.">Analysis of locomotor activity rhythms in Drosophila.</a> Nature Protocols. 1, 559-568 (2006).</li><li>Sehadova, H., Glaser, F. T., Gentile, C., Simoni, A., Giesecke, A., Albert, J. T., Stanewsky, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temperature+entrainment+of+Drosophila's+circadian+clock+involves+the+gene+nocte+and+signaling+from+peripheral+sensory+tissues+to+the+brain.">Temperature entrainment of Drosophila's circadian clock involves the gene nocte and signaling from peripheral sensory tissues to the brain.</a> Neuron. 64, 251-266 (2009).</li><li>Zimmerman, J. E., Raizen, D. M., Maycock, M. H., Maislin, G., Pack, A. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+video+method+to+study+Drosophila+sleep.">A video method to study Drosophila sleep.</a> Sleep. 31, 1587-1598 (2008).</li><li>Zordan, M. A., Benna, C., Mazzotta, G., Rosato, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Monitoring+and+analyzing+Drosophila+circadian+locomotor+activity.">Monitoring and analyzing Drosophila circadian locomotor activity.</a> In Circadian Rhythms Methods and Protocols. , (2007).</li></ol>

No conflicts of interest declared.

In this protocol, we described procedures for measuring Drosophila locomotor activity rhythms, a reliable behavioral output of fly circadian clocks that is used as the standard readout of clock function. This assay has been used in large-scale screens for novel clock mutants (e.g. Konopka and Benzer 1971; Dubruille et al. 2009) and is continually used to dissect and understand clock function in vivo. It has also been used to study sleep wake cycle in flies, even though recent reports suggest that video digital analysis is much more reliable in quantifying sleep than using locomotor activity rhythms (Zimmerman et al. 2008). When using locomotor activity rhythms to analyze sleep, percentage of sleep in the daytime tend to be overestimated.
To ensure the success and reproducibility of this protocol, it is critical to assay flies that are similar in age, genetic background, and reared under the same conditions, as behavioral phenotypes in fruit flies such as circadian rhythmicity and sleep/rest activity are very sensitive to all these factors. When using multiple incubators for a single experiment, it is important to make sure all incubators are at the anticipated temperature since some circadian parameters may change as a function of temperature. One word of caution when considering purchasing incubators for working with flies; not all are created equal. While we hesitate to recommend any particular unit there are many options. A good resource for finding companies that sell incubators for Drosophila work is provided at &lt;www.flybase.org&gt;. Some companies even sell "Drosophila circadian" incubators, wherein additional features are available, such as already wired for the Trikinetics system and temperature ramping (e.g., Tritech). Important features include the ability for diurnal light control and good temperature control in the physiological range of Drosophila (~15-30&deg;C). Prices and sizes of incubators vary a lot but with the newer activity monitors from Trikinetics, even small incubators can accommodate quite a number of these devices. Also, although incubators with humidity control can be used, this added feature is not necessary as long as you place a small pan with water to provide humidity (50-70% is fine). Finally, although we routinely use FaasX and Insomniac for data analysis in this protocol, there are alternative programs and softwares available (Rosato and Kyriacou 2006), e.g. ClockLab (ActiMetrics), Brandeis Rhythm Package (D. Wheeler, Baylor College of Medicine, Houston), and MAZ (Zordan et al. 2007).

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		<div>
		<table border="1">
		<thead>
		<tr>
		<th>Material Name</th>
		<th>Type</th>
		<th>Company</th>
		<th>Catalogue Number</th>
		<th>Comment</th>
		</tr>
		</thead>
		<tbody>
		
<tr>
<td>Drosophila activity monitor (DAM)</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>DAM2 or DAM5</td>
<td>DAM2 monitors are more compact, and more can fit into a single incubator</td>
</tr>
<tr>
<td>Power supply interface unit (for DAM system)</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>PSIU9</td>
<td>Includes PS9-1 AC Power Supply</td>
</tr>
<tr>
<td>Light controller</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>LC6</td>
<td>&nbsp;</td>
<tr>
<td>Pyrex glass tubes</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>PGT5, PGT7, and PGT10</td>
<td>&nbsp;</td>
<tr>
<td>Plastic activity tube caps</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>CAP5</td>
<td>Yarn can be used instead of plastic caps.</td>
</tr>
<tr>
<td>DAM System data collection software</td>
<td>&nbsp;</td>
<td>Trikinetics Inc.; Waltham, MA</td>
<td>&nbsp;</td>
<td>Versions available for both Mac and PC</td>
</tr>
<tr>
<td>FaasX software</td>
<td>&nbsp;</td>
<td>M. Boudinot and F. Rouyer, Centre National de la Recherche Scientifique, Gif-sur-Yvette Cedex, France</td>
<td>&nbsp;</td>
<td>Only for Mac</td>
</tr>
<tr>
<td>Insomniac 2.0 software</td>
<td>&nbsp;</td>
<td>Leslie Ashmore, Department of Pharmacology &amp; Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA</td>
<td>&nbsp;</td>
<td>Runs on Matlab. Can be used on both PC and Macintosh.</td>
</tr>
<tr>
<td>Environmental incubator with temperature and diurnal control, e.g. Percival incubator</td>
<td>&nbsp;</td>
<td>Percival Scientific, Inc.</td>
<td>I-30BLL</td>
<td>Interior space dimension:
Width: 65cm;
Height: 86cm;
Depth: 55cm</td>
</tr>
<tr>
<td>Environmental incubator with temperature and diurnal control, e.g. DigiTherm Heating/Cooling Incubator with Circadian Timed Lighting and Timed Temperature</td>
<td>&nbsp;</td>
<td>Tritech Research, Inc.</td>
<td>05DT2CIRC001</td>
<td>Interior space dimension:
Width: 36m;
Height: 56m;
Depth: 28cm</td>
</tr>
<tr>
<td>APC Smart-UPS 2200VA 120V (Emergency power backup unit)</td>
<td>&nbsp;</td>
<td>APC</td>
<td>SU2200NET</td>
<td>Output Power Capacity of 1600 Watts</td>
</tr>
<tr>
<td>Sucrose</td>
<td>&nbsp;</td>
<td>Sigma</td>
<td>S7903</td>
<td>&nbsp;</td>
<tr>
<td>Bacto Agar</td>
<td>&nbsp;</td>
<td>Becton Dickinson</td>
<td>214010</td>
<td>&nbsp;</td>
<tr>
<td>TissuePrep Paraffin pellets</td>
<td>&nbsp;</td>
<td>Fisher Scientific</td>
<td>T565</td>
<td>Melting point 56&deg;C-57&deg;C</td>
</tr>
<tr>
<td>Block heater </td>
<td>&nbsp;</td>
<td>VWR</td>
<td>12621-014</td>
<td>&nbsp;</td>		</tbody>
		</table>
		</div>

assaying locomotor activity to study circadian rhythms and sleep parameters in drosophila

Most life forms exhibit daily rhythms in cellular, physiological and behavioral phenomena that are driven by endogenous circadian (&equiv;24 hr) pacemakers or clocks. Malfunctions in the human circadian system are associated with numerous diseases or disorders. Much progress towards our understanding of the mechanisms underlying circadian rhythms has emerged from genetic screens whereby an easily measured behavioral rhythm is used as a read-out of clock function. Studies using Drosophila have made seminal contributions to our understanding of the cellular and biochemical bases underlying circadian rhythms. The standard circadian behavioral read-out measured in Drosophila is locomotor activity. In general, the monitoring system involves specially designed devices that can measure the locomotor movement of Drosophila. These devices are housed in environmentally controlled incubators located in a darkroom and are based on using the interruption of a beam of infrared light to record the locomotor activity of individual flies contained inside small tubes. When measured over many days, Drosophila exhibit daily cycles of activity and inactivity, a behavioral rhythm that is governed by the animal's endogenous circadian system. The overall procedure has been simplified with the advent of commercially available locomotor activity monitoring devices and the development of software programs for data analysis. We use the system from Trikinetics Inc., which is the procedure described here and is currently the most popular system used worldwide. More recently, the same monitoring devices have been used to study sleep behavior in Drosophila. Because the daily wake-sleep cycles of many flies can be measured simultaneously and only 1 to 2 weeks worth of continuous locomotor activity data is usually sufficient, this system is ideal for large-scale screens to identify Drosophila manifesting altered circadian or sleep properties.

Watch this Scientific Journal Video about Assaying Locomotor Activity to Study Circadian Rhythms and Sleep Parameters in Drosophila at JoVE.com

Assaying Locomotor Activity to Study Circadian Rhythms and Sleep Parameters in Drosophila

We describe procedures for recording daily locomotor activity rhythms of Drosophila and subsequent data analysis. Locomotor activity rhythms are a reliable behavioral output of animal circadian clocks and are used as the standard readout of clock function when studying circadian mutants or examining how the environment regulates the circadian system.

Assaying Locomotor Activity to Study Circadian Rhythms and Sleep Parameters in Drosophila

Most life forms exhibit daily rhythms in cellular, physiological and behavioral phenomena that are driven by endogenous circadian (&equiv;24 hr) ...

assaying-locomotor-activity-to-study-circadian-rhythms-sleep

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46.2K Views.  Rutgers University. We describe procedures for recording daily locomotor activity rhythms of Drosophila and subsequent data analysis. Locomotor activity rhythms are a reliable behavioral output of animal circadian clocks and are used as the standard readout of clock function when studying circadian mutants or examining how the environment regulates the circadian system.

Video: Assaying Locomotor Activity to Study Circadian Rhythms and Sleep Parameters in Drosophila

Laser Capture Microdissection of Drosophila Peripheral Neurons

The dendritic arborization (da) neurons of the Drosophila peripheral nervous system (PNS) provide an excellent model system in which to investigate the molecular mechanisms underlying class-specific dendrite morphogenesis1,2. To facilitate molecular analyses of class-specific da neuron development, it is vital to obtain these cells in a pure population. Although a range of different cell, and tissue-specific RNA isolation techniques exist for Drosophila cells, including magnetic bead based cell purification3,4, Fluorescent Activated Cell Sorting (FACS)5-8, and RNA binding protein based strategies9, none of these methods can be readily utilized for isolating single or multiple class-specific Drosophila da neurons with a high degree of spatial precision. Laser Capture Microdissection (LCM) has emerged as an extremely powerful tool that can be used to isolate specific cell types from tissue sections with a high degree of spatial resolution and accuracy. RNA obtained from isolated cells can then be used for analyses including qRT-PCR and microarray expression profiling within a given cell type10-16. To date, LCM has not been widely applied in the analysis of Drosophila tissues and cells17,18, including da neurons at the third instar larval stage of development. 
Here we present our optimized protocol for isolation of Drosophila da neurons using the infrared (IR) class of LCM. This method allows for the capture of single, class-specific or multiple da neurons with high specificity and spatial resolution. Age-matched third instar larvae expressing a UAS-mCD8::GFP19 transgene under the control of either the class IV da neuron specific ppk-GAL420 driver or the pan-da neuron specific 21-7-GAL421 driver were used for these experiments. RNA obtained from the isolated da neurons is of very high quality and can be directly used for downstream applications, including qRT-PCR or microarray analyses. Furthermore, this LCM protocol can be readily adapted to capture other Drosophila cell types a various stages of development dependent upon the cell type specific, GAL4-driven expression pattern of GFP.

Laser Capture Microdissection of Drosophila Peripheral Neurons

In this video-article we present a method for isolating single or multiple Drosophila da neurons from third instar larvae using the infrared capture (IR) class of Laser Capture Microdissection (LCM). RNA obtained from the isolated neurons can be readily used for downstream applications including qRT-PCR or microarray analyses.

The dendritic arborization (da) neurons of the Drosophila peripheral nervous system (PNS) provide an excellent model system in which to investigate the ...

Measuring Circadian and Acute Light Responses in Mice using Wheel Running Activity

Circadian rhythms are physiological functions that cycle over a period of approximately 24 hours (circadian- circa: approximate and diem: day)1, 2. They are responsible for timing our sleep/wake cycles and hormone secretion. Since this timing is not precisely 24-hours, it is synchronized to the solar day by light input. This is accomplished via photic input from the retina to the suprachiasmatic nucleus (SCN) which serves as the master pacemaker synchronizing peripheral clocks in other regions of the brain and peripheral tissues to the environmental light dark cycle3-7. The alignment of rhythms to this environmental light dark cycle organizes particular physiological events to the correct temporal niche, which is crucial for survival8. For example, mice sleep during the day and are active at night. This ability to consolidate activity to either the light or dark portion of the day is referred to as circadian photoentrainment and requires light input to the circadian clock9. Activity of mice at night is robust particularly in the presence of a running wheel. Measuring this behavior is a minimally invasive method that can be used to evaluate the functionality of the circadian system as well as light input to this system. Methods that will covered here are used to examine the circadian clock, light input to this system, as well as the direct influence of light on wheel running behavior.

This article will review methods that can be used to determine circadian function and light responsiveness in mice.

Circadian rhythms are physiological functions that cycle over a period of approximately 24 hours (circadian- circa: approximate and diem: day)1, 2.  They ...

Assaying Locomotor, Learning, and Memory Deficits in Drosophila Models of Neurodegeneration

Advances in genetic methods have enabled the study of genes involved in human neurodegenerative diseases using Drosophila as a model system1. Most of these diseases, including Alzheimer's, Parkinson's and Huntington's disease are characterized by age-dependent deterioration in learning and memory functions and movement coordination2. Here we use behavioral assays, including the negative geotaxis assay3 and the aversive phototaxic suppression assay (APS assay)4,5, to show that some of the behavior characteristics associated with human neurodegeneration can be recapitulated in flies. In the negative geotaxis assay, the natural tendency of flies to move against gravity when agitated is utilized to study genes or conditions that may hinder locomotor capacities. In the APS assay, the learning and memory functions are tested in positively-phototactic flies trained to associate light with aversive bitter taste and hence avoid this otherwise natural tendency to move toward light. Testing these trained flies 6 hours post-training is used to assess memory functions. Using these assays, the contribution of any genetic or environmental factors toward developing neurodegeneration can be easily studied in flies.

Assaying Locomotor, Learning, and Memory Deficits in Drosophila Models of Neurodegeneration

Behavior assays for measuring locomotor functions, learning, and memory abilities in Drosophila.

Advances in genetic methods have enabled the study of genes involved in human neurodegenerative diseases using Drosophila as a model system1. Most of ...

Non-Laser Capture Microscopy Approach for the Microdissection of Discrete Mouse Brain Regions for Total RNA Isolation and Downstream Next-Generation Sequencing and Gene Expression Profiling

As technological platforms, approaches such as next-generation sequencing, microarray, and qRT-PCR have great promise for expanding our understanding of the breadth of molecular regulation. Newer approaches such as high-resolution RNA sequencing (RNA-Seq)1 provides new and expansive information about tissue- or state-specific expression such as relative transcript levels, alternative splicing, and micro RNAs2-4. Prospects for employing the RNA-Seq method in comparative whole transcriptome profiling5 within discrete tissues or between phenotypically distinct groups of individuals affords new avenues for elucidating molecular mechanisms involved in both normal and abnormal physiological states. Recently, whole transcriptome profiling has been performed on human brain tissue, identifying gene expression differences associated with disease progression6. However, the use of next-generation sequencing has yet to be more widely integrated into mammalian studies.
Gene expression studies in mouse models have reported distinct profiles within various brain nuclei using laser capture microscopy (LCM) for sample excision7,8. While LCM affords sample collection with single-cell and discrete brain region precision, the relatively low total RNA yields from the LCM approach can be prohibitive to RNA-Seq and other profiling approaches in mouse brain tissues and may require sub-optimal sample amplification steps. Here, a protocol is presented for microdissection and total RNA extraction from discrete mouse brain regions. Set-diameter tissue corers are used to isolate 13 tissues from 750-&mu;m serial coronal sections of an individual mouse brain. Tissue micropunch samples are immediately frozen and archived. Total RNA is obtained from the samples using magnetic bead-enabled total RNA isolation technology. Resulting RNA samples have adequate yield and quality for use in downstream expression profiling. This microdissection strategy provides a viable option to existing sample collection strategies for obtaining total RNA from discrete brain regions, opening possibilities for new gene expression discoveries.

Non-Laser Capture Microscopy Approach for the Microdissection of Discrete Mouse Brain Regions for Total RNA Isolation and Downstream Next-Generation Sequencing and Gene Expression Profiling  |

RNA expression profiling of discrete mouse brain regions requires a precise and repeatable tissue collection strategy. A protocol that uses both coronal brain sectioning and tissue corer-assisted microdissection is described here. The yield and quality of total RNA obtained from the resulting samples confirms the utility of the outlined method.

As technological platforms, approaches such as next-generation sequencing, microarray, and qRT-PCR have great promise for expanding our understanding of ...

Simultaneous Electroencephalography, Real-time Measurement of Lactate Concentration and Optogenetic Manipulation of Neuronal Activity in the Rodent Cerebral Cortex

Although the brain represents less than 5% of the body by mass, it utilizes approximately one quarter of the glucose used by the body at rest1. The function of non rapid eye movement sleep (NREMS), the largest portion of sleep by time, is uncertain. However, one salient feature of NREMS is a significant reduction in the rate of cerebral glucose utilization relative to wakefulness2-4. This and other findings have led to the widely held belief that sleep serves a function related to cerebral metabolism. Yet, the mechanisms underlying the reduction in cerebral glucose metabolism during NREMS remain to be elucidated.
	One phenomenon associated with NREMS that might impact cerebral metabolic rate is the occurrence of slow waves, oscillations at frequencies less than 4 Hz, in the electroencephalogram5,6. These slow waves detected at the level of the skull or cerebral cortical surface reflect the oscillations of underlying neurons between a depolarized/up state and a hyperpolarized/down state7. During the down state, cells do not undergo action potentials for intervals of up to several hundred milliseconds. Restoration of ionic concentration gradients subsequent to action potentials represents a significant metabolic load on the cell8; absence of action potentials during down states associated with NREMS may contribute to reduced metabolism relative to wake.
	Two technical challenges had to be addressed in order for this hypothetical relationship to be tested. First, it was necessary to measure cerebral glycolytic metabolism with a temporal resolution reflective of the dynamics of the cerebral EEG (that is, over seconds rather than minutes). To do so, we measured the concentration of lactate, the product of aerobic glycolysis, and therefore a readout of the rate of glucose metabolism in the brains of mice. Lactate was measured using a lactate oxidase based real time sensor embedded in the frontal cortex. The sensing mechanism consists of a platinum-iridium electrode surrounded by a layer of lactate oxidase molecules. Metabolism of lactate by lactate oxidase produces hydrogen peroxide, which produces a current in the platinum-iridium electrode. So a ramping up of cerebral glycolysis provides an increase in the concentration of substrate for lactate oxidase, which then is reflected in increased current at the sensing electrode. It was additionally necessary to measure these variables while manipulating the excitability of the cerebral cortex, in order to isolate this variable from other facets of NREMS.
	We devised an experimental system for simultaneous measurement of neuronal activity via the elecetroencephalogram, measurement of glycolytic flux via a lactate biosensor, and manipulation of cerebral cortical neuronal activity via optogenetic activation of pyramidal neurons. We have utilized this system to document the relationship between sleep-related electroencephalographic waveforms and the moment-to-moment dynamics of lactate concentration in the cerebral cortex. The protocol may be useful for any individual interested in studying, in freely behaving rodents, the relationship between neuronal activity measured at the electroencephalographic level and cellular energetics within the brain.

A procedure is described for manipulating the activity of cerebral cortical pyramidal neurons optogenetically while the electroencephalogram, electromyogram, and cerebral lactate concentration are monitored. Experimental recordings are performed on cable-tethered mice while they undergo spontaneous sleep/wake cycles. Optogenetic equipment is assembled in our laboratory; recording equipment is commercially available.

Although the brain represents less than 5% of the body  by mass, it utilizes approximately one quarter of the glucose used by the body  at rest1. The ...

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents

When rodents have free access to a running wheel in their home cage, voluntary use of this wheel will depend on the time of day1-5. Nocturnal rodents, including rats, hamsters, and mice, are active during the night and relatively inactive during the day. Many other behavioral and physiological measures also exhibit daily rhythms, but in rodents, running-wheel activity serves as a particularly reliable and convenient measure of the output of the master circadian clock, the suprachiasmatic nucleus (SCN) of the hypothalamus. In general, through a process called entrainment, the daily pattern of running-wheel activity will naturally align with the environmental light-dark cycle (LD cycle; e.g. 12 hr-light:12 hr-dark). However circadian rhythms are endogenously generated patterns in behavior that exhibit a ~24 hr period, and persist in constant darkness. Thus, in the absence of an LD cycle, the recording and analysis of running-wheel activity can be used to determine the subjective time-of-day. Because these rhythms are directed by the circadian clock the subjective time-of-day is referred to as the circadian time (CT). In contrast, when an LD cycle is present, the time-of-day that is determined by the environmental LD cycle is called the zeitgeber time (ZT).
Although circadian rhythms in running-wheel activity are typically linked to the SCN clock6-8, circadian oscillators in many other regions of the brain and body9-14 could also be involved in the regulation of daily activity rhythms. For instance, daily rhythms in food-anticipatory activity do not require the SCN15,16 and instead, are correlated with changes in the activity of extra-SCN oscillators17-20. Thus, running-wheel activity recordings can provide important behavioral information not only about the output of the master SCN clock, but also on the activity of extra-SCN oscillators. Below we describe the equipment and methods used to record, analyze and display circadian locomotor activity rhythms in laboratory rodents.

Circadian rhythms in voluntary wheel-running activity in mammals are tightly coupled to the molecular oscillations of a master clock in the brain. As such, these daily rhythms in behavior can be used to study the influence of genetic, pharmacological, and environmental factors on the functioning of this circadian clock.

When rodents have free access to a running wheel in their home cage, voluntary use of this wheel will depend on the time of day1-5. Nocturnal rodents, ...

Light Preference Assay to Study Innate and Circadian Regulated Photobehavior in Drosophila Larvae

Light acts as environmental signal to control animal behavior at various levels. The Drosophila larval nervous system is used as a unique model to answer basic questions on how light information is processed and shared between rapid and circadian behaviors. Drosophila larvae display a stereotypical avoidance behavior when exposed to light. To investigate light dependent behaviors comparably simple light-dark preference tests can be applied. In vertebrates and arthropods the neural pathways involved in sensing and processing visual inputs partially overlap with those processing photic circadian information. The fascinating question of how the light sensing system and the circadian system interact to keep behavioral outputs coordinated remains largely unexplored. Drosophila is an impacting biological model to approach these questions, due to a small number of neurons in the brain and the availability of genetic tools for neuronal manipulation. The presented light-dark preference assay allows the investigation of a range of visual behaviors including circadian control of phototaxis.

Light Preference Assay to Study Innate and Circadian Regulated Photobehavior in Drosophila Larvae

Here we describe a light-dark preference test for Drosophila larva. This assay provides information about innate and circadian regulation of light sensing and processing photobehavior.

Light acts as environmental signal to control animal behavior at various levels. The Drosophila larval nervous system is used as a unique model to answer ...

Determination of the Spontaneous Locomotor Activity in Drosophila melanogaster

Drosophila melanogaster has been used as an excellent model organism to study environmental and genetic manipulations that affect behavior. One such behavior is spontaneous locomotor activity. Here we describe our protocol that utilizes Drosophila population monitors and a tracking system that allows continuous monitoring of the spontaneous locomotor activity of flies for several days at a time. This method is simple, reliable, and objective and can be used to examine the effects of aging, sex, changes in caloric content of food, addition of drugs, or genetic manipulations that mimic human diseases.

Determination of the Spontaneous Locomotor Activity in Drosophila melanogaster

Drosophila melanogaster are useful in studying genetic or environmental manipulations that affect behaviors such as spontaneous locomotor activity.&#160; Here we describe a protocol that utilizes monitors with infrared beams and data analysis software to quantify spontaneous locomotor activity.&#160;

Drosophila melanogaster has been used as an excellent model organism to study environmental and genetic manipulations that affect behavior. One such ...

High-throughput Analysis of Locomotor Behavior in the Drosophila Island Assay

Advances in next-generation sequencing technologies contribute to the identification of (candidate) disease genes for movement disorders and other neurological diseases at an increasing speed. However, little is known about the molecular mechanisms that underlie these disorders. The genetic, molecular, and behavioral toolbox of Drosophila melanogaster makes this model organism particularly useful to characterize new disease genes and mechanisms in a high-throughput manner. Nevertheless, high-throughput screens require efficient and reliable assays that, ideally, are cost-effective and allow for the automatized quantification of traits relevant to these disorders. The island assay is a cost-effective and easily set-up method to evaluate Drosophila locomotor behavior. In this assay, flies are thrown onto a platform from a fixed height. This induces an innate motor response that enables the flies to escape from the platform within seconds. At present, quantitative analyses of filmed island assays are done manually, which is a laborious undertaking, particularly when performing large screens.
This manuscript describes the &#34;Drosophila Island Assay&#34; and &#34;Island Assay Analysis&#34; algorithms for&#160;high-throughput, automated data processing and quantification of island assay data. In the setup, a simple webcam connected to a laptop collects an image series of the platform while the assay is performed. The &#34;Drosophila Island Assay&#34; algorithm developed for the open-source software Fiji processes these image series and quantifies, for each experimental condition, the number of flies on the platform over time. The &#34;Island Assay Analysis&#34; script, compatible with the free software R, was developed to automatically process the obtained data and to calculate whether treatments/genotypes are statistically different. This greatly improves the efficiency of the island assay and makes it a powerful readout for basic locomotion and flight behavior. It can thus be applied to large screens investigating fly locomotor ability, Drosophila models of movement disorders, and drug efficacy.

High-throughput Analysis of Locomotor Behavior in the Drosophila Island Assay

The island assay is a relatively new, cost-effective assay that can be used to evaluate the basic locomotor behavior of Drosophila melanogaster. This manuscript describes algorithms for automatic data processing and objective quantification of island assay data, making this assay a sensitive, high-throughput readout for large genetic or pharmacological screens.

Advances in next-generation sequencing technologies contribute to the identification of (candidate) disease genes for movement disorders and other ...

Single-cell Resolution Fluorescence Live Imaging of Drosophila Circadian Clocks in Larval Brain Culture

The circadian pacemaker circuit orchestrates rhythmic behavioral and physiological outputs coordinated with environmental cues, such as day/night cycles. The molecular clock within each pacemaker neuron generates circadian rhythms in gene expression, which underlie the rhythmic neuronal functions essential to the operation of the circuit. Investigation of the properties of the individual molecular oscillators in different subclasses of pacemaker neurons and their interaction with neuronal signaling yields a better understanding of the circadian pacemaker circuit. Here, we present a time-lapse fluorescent microscopy approach developed to monitor the molecular clockwork in clock neurons of cultured Drosophila larval brain. This method allows the multi-day recording of the rhythms of genetically encoded fluorescent circadian reporters at single-cell resolution. This setup can be combined with pharmacological manipulations to closely analyze real-time response of the molecular clock to various compounds. Beyond circadian rhythms, this multipurpose method in combination with powerful Drosophila genetic techniques offers the possibility to study diverse neuronal or molecular processes in live brain tissue.

Single-cell Resolution Fluorescence Live Imaging of Drosophila Circadian Clocks in Larval Brain Culture

The goal of this protocol is to establish ex vivo Drosophila larval brain culture optimized to monitor circadian molecular rhythms with long-term fluorescence time-lapse imaging. The application of this method to pharmacological assays is also discussed.

The circadian pacemaker circuit orchestrates rhythmic behavioral and physiological outputs coordinated with environmental cues, such as day/night cycles. ...