Drosophila larvae are able to associate odor stimuli with gustatory reward. Here we describe a simple behavioral paradigm that allows the analysis of appetitive associative olfactory learning.
In the following we describe the methodological details of appetitive associative olfactory learning in Drosophila larvae. The setup, in combination with genetic interference, provides a handle to analyze the neuronal and molecular fundamentals of specifically associative learning in a simple larval brain.
Organisms can use past experience to adjust present behavior. Such acquisition of behavioral potential can be defined as learning, and the physical bases of these potentials as memory traces1-4. Neuroscientists try to understand how these processes are organized in terms of molecular and neuronal changes in the brain by using a variety of methods in model organisms ranging from insects to vertebrates5,6. For such endeavors it is helpful to use model systems that are simple and experimentally accessible. The Drosophila larva has turned out to satisfy these demands based on the availability of robust behavioral assays, the existence of a variety of transgenic techniques and the elementary organization of the nervous system comprising only about 10,000 neurons (albeit with some concessions: cognitive limitations, few behavioral options, and richness of experience questionable)7-10.
Drosophila larvae can form associations between odors and appetitive gustatory reinforcement like sugar11-14. In a standard assay, established in the lab of B. Gerber, animals receive a two-odor reciprocal training: A first group of larvae is exposed to an odor A together with a gustatory reinforcer (sugar reward) and is subsequently exposed to an odor B without reinforcement 9. Meanwhile a second group of larvae receives reciprocal training while experiencing odor A without reinforcement and subsequently being exposed to odor B with reinforcement (sugar reward). In the following both groups are tested for their preference between the two odors. Relatively higher preferences for the rewarded odor reflect associative learning – presented as a performance index (PI). The conclusion regarding the associative nature of the performance index is compelling, because apart from the contingency between odors and tastants, other parameters, such as odor and reward exposure, passage of time and handling do not differ between the two groups9.
1. Preparation
2. Sugar Reward Training and Test
First group | CS1 / (+) – CS2 / (-) | Reciprocal group | CS2 / (+) – CS1 / (-) |
CS1 / (-) – CS2 / (+) | CS2 / (-) – CS1 / (+) | ||
CS2 / (+) – CS2 / (-) | CS1 / (+) – CS2 / (-) | ||
CS2 / (-) – CS1 / (+) | CS1 / (-) – CS2 / (+) |
To prevent systematic effects of stimuli in the surrounding experimental environment, one should perform the test in one-half of the cases such that OCT is presented on the left and AM to the right. In the other half of the cases AM should be presented on the left and OCT on the right.
3. Tests for Task-relevant Sensory-motor Faculties
The design of the above described experiments allows for analyzing odor-sugar learning in wild type feeding 3rd instar larvae on its own. However, in daily lab life researchers usually use two or more different experimental groups of larvae to compare, if olfactory learning depends on a particular gene, a specific set of neurons, a mutant stock, a special food diet, different rearing conditions, toxic chemicals added during development, etc. Thus, in all cases when two or more experimental groups of larvae are tested one has to do a set of mandatory control experiments to test, if the different groups of larvae show proper sensory-motor acuities. This becomes mandatory as potential phenotypes are not necessarily due to reduced or abolished abilities to associate odors with sugar. Rather, potential learning defects could be based on defects at any step of the sensory-motor circuitry in the processing of odors and/or sugar. Or in other words, if a mutant larva is not able to sense sugar, it cannot establish a sugar memory. But this does not allow concluding that the larva cannot learn. In detail the following control experiments have to be done to test for proper OCT, AM and fructose processing of transgenic larvae.
1. Test for naïve OCT preference
Collect 30 feeding 3rd instar larvae from a food vial. Wash them carefully in tap water as described in 2.1. Put a single OCT odor container on one side of an agarose Petri dish, add the larvae onto the middle of the Petri dish, close the lid and wait for 5 min, such that the larvae can crawl on the Petri dish and orient towards the OCT odor source. Subsequently count the number of larvae on the left side, in the middle and on the right side of the test Petri dish.
2. Test for naïve AM preference
Collect 30 feeding 3rd instar larvae from a food vial. Wash them carefully in tap water as described in 2.1. Put a single AM odor container on one side of an agarose Petri dish, add the larvae onto the middle of the Petri dish, close the lid and wait for 5 min, such that the larvae can crawl on the Petri dish and orient towards the AM odor source. Subsequently count the number of larvae on the left side, in the middle and on the right side of the test Petri dish.
3. Test for naïve sugar preference
Collect 30 feeding 3rd instar larvae from a food vial. Wash them carefully in tap water as described in 2.1. Prepare Petri dishes that contain 2.5% agarose in one half and a 2M fructose-agarose mixture in the other half. Add the larvae onto the Petri dish, close the lid and wait for 5 min, such that the larvae can crawl on the Petri dish and orient towards the fructose containing side. Subsequently count the number of larvae on the left side, in the middle and on the right side of the test Petri dish.
Preparation of half-half Petri dishes: Prepare normal agarose plates as described above in section 1.2. When the agarose filled Petri dishes are cooled down, carefully cut the agarose along the vertical axis with a scalpel. Remove one half of the agarose from the Petri dish. Add a hot fructose-agarose solution (for preparation see 1.3) to the empty half of the Petri dish. Be careful that both halves match and do not form a defined edge – this affects the larval choice behavior and renders a behavioral analysis rather difficult.4.
Sham training
Despite testing if transgenic feeding 3rd instar larvae are able to distinguish on a wild type level between OCT and air (3.1), AM and air (3.2) and sugar and pure agarose (3.3), an additional set of test experiments has recently been introduced (for discussion see Gerber and Stocker, 2007). The rationale for these experiments is the following. During the training larvae undergo massive handling and successive odor and sugar stimulation. Thus, it is well possible that the observed learning phenotype is misleading (although naïve odor and sugar perception tests are on a wild type level!). Indeed, it is possible that the transgenic animals differ from wild type larvae with respect to stress resistance, motivation, fatigue, sensory adaptation, contextual learning, and changes in satiety. Thus, Michels et al. (2005) introduced controls that test whether a given mutant is able to (1) detect AM versus an empty odor container if you treat the larvae exactly as during training except that you omit the reward and merely expose to both odors; (2) detect OCT after the same regime; (3) detect AM versus an empty odor container, if you treat the larvae in a training-like way except that you omit the odors and merely expose to the reward; and (4) detect OCT after the same regimen. For a comprehensive discussion and further details on the methods please see Michels et al (2005) and Gerber and Stocker (2007).
4. Data Analysis for Sugar Reward Learning
5. Data Analysis for Task-relevant Sensory-motor Faculties
Figure 1A shows an overview of the experimental procedures for larval olfactory associative learning. By pairing one of the two presented odors with a sugar reward larvae acquire the behavior potential to express an attractive response towards the rewarded odor in comparison to the unrewarded odor. Two groups of larvae are always trained by either pairing the reinforcer with the odor OCT or AM. The performance index (PI) measures the associative function as the difference in preference between the reciprocally trained groups.
In case associative function is analyzed in transgenic larvae, tests for basic sensory-motor ability are required. This is done by offering them the choice between a filled odor container and air or between pure agarose and agarose plus a sugar. (Sham training is not shown here). The final distribution of the larvae is noted in a specific data sheet (Figure 2) and visualized as a box plot (Figure 3). Positive results indicate an attractive choice behavior for the preference indices and appetitive learning in case of the performance indices. Negative values indicate an aversive choice behavior for the calculated preference indices and aversive learning in case of the performance indices.
Figure 1. Scheme of the behavioral experiments to measure larval associative olfactory learning, naïve olfactory preferences and naïve gustatory preferences.
Figure 2. Example of a raw data sheet for registering and processing data obtained for A) sugar reward learning, B) naïve odor preferences and C) naïve gustatory preferences. For all experiments the number of larvae on the left side, in the middle and on the right side of the Petri dishes are noted. Out of this information preference indices (PREF) are calculated. Larval learning is depicted as performance indices (PI) deriving from computating the PREFs of two reciprocally trained groups. Click here to view larger figure.
Figure 3. Example data visualization obtained for A) sugar reward learning, B) naïve odor preferences and C) naïve gustatory preferences. Boxplots represent data as follows: median (bold line within box); the box indicates 50% of all data points whereas the upper and lower whisker represents the other 25% each. Therefore without outliers the minimum and maximum values are indicated by the whisker boundaries. Outliers are depicted as small circles they are defined as any point more than 1.5 times the interquartile range from the 1st and 3rd quartiles. Statistical analysis of single data points is done with Wilcoxon signed-rank test, whereas Wilcoxon rank sum test is used for comparison of two data groups. Significance levels are indicated as n.s. for p>0.05, * for p<0.05, ** for p<0.01 or *** for p<0.001. Sample size of each experiment: N=15.
For the learning experiments in A) always two preference indices (PREF) of reciprocal experiments are taken to calculate the final performance index (PI). Performance Indices (PI) are depicted as box plots accordingly.
Figure 4. Examples of GAL4 lines each of which labels a specific set of cells within the larval brain. Always full z-projections of frontal views of the larval brain are shown. Specific sets of neurons are labelled by anti-green fluorescent protein (green) in the whole larval CNS that is visualized by anti-FasII/anti-ChAT doublestaining (magenta). A) NP225 labels a set of second order olfactory neurons, called projection neurons (arrow) and the developing adult visual system (arrowhead). B) NP2426 marks a set of olfactory interneurons (arrow) at the first olfactory relay station, called the antennal lobe. C) GR66a labels exclusively a set of gustatory sensory neurons that project from peripheral gustatory sensory organs to the subeosophageal ganglion (arrow). D) NP3128 labels several sets of different types of neurons. The arrow marks olfactory interneurons of the antennal lobe similar to B. The arrowhead highlights a set of dopaminergic neurons that project onto a neuropil region called mushroom body. E) H24 marks a set of mushroom body Kenyon cells (arrow), neurons that where shown to be necessary for larval olfactory learning. F) NP7493 is an example of a relatively unspecific expression pattern that includes several sets of developing neurons (arrows) that will further differentiate during metamorphosis to form the brain of the fly. Scale bars = 50 μm.
Figure 5. Overview summarizing successful attempts to study associative learning in Drosophila larvae. Olfactory stimuli as well as light can be used as a conditioned stimulus to be associated with either reward or punishment (unconditioned stimulus). Rewarding stimuli include sugar and low concentrations of salt; punishing stimuli comprise high concentrations of salt, quinine, electric shock, heat, mechanical stimulation through vibration (buzz) and light11,12,17-24. Click here to view larger figure.
GAL4 / UAS constructs often used in our lab | |||
Abbreviation | Protein | Function | Literature |
Visualization | |||
UAS-mCD8::GFP | green fluorescent protein | membrane marker | Lee et al., 1999 |
UAS-n-syb::GFP | green fluorescent protein | presynaptic marker | Ito et al., 1998 |
UAS-Dscam17.1::GFP | green fluorescent protein | postsynaptic marker | Wang et al., 2004 |
UAS-NLS::GFP | green fluorescent protein | cell body marker | Robertson et al., 2003 |
Interference with neuronal signaling | |||
UAS-hid | head involution defective | induces apoptosis | Zhou et al., 1997 |
UAS-rpr | reaper | induces apoptosis | Zhou et al., 1997 |
UAS-shits | dominant negative dynamin | blocks vesicle recycling | Kitamoto, 2001 |
UAS-Kir.2.1::EGFP | inwardly rectifying K+ channel | no membrane depolarization | Baines et al., 2001 |
UAS-TRPA1 | cation channel | temperature dependent activation | Rosenzweig et al., 2005 |
UAS-ChR2 | Channelrhodopsin | light dependent activation | Schroll et al., 2006 |
Table 1. UAS effector constructs often used in the lab to visualize the neuronal anatomy and manipulate synaptic transmission25-33.
The described setup in Drosophila larvae allows for the investigation of associative olfactory learning within a comparably elementary brain. The approach is simple, cheap, easy to establish in a lab and does not require high-tech equipment9. We present a version of the experiment, to study appetitive associative learning reinforced by fructose reward11. The described setup is based on a series of parametrical studies that comprehensively investigated variations in the number of training trials, single assay versus mass assay, retention time, used odors and odor concentrations and gender9,15,34,35. Thus, the depicted behavioral setup integrates this information in an exceptionally reproducible approach to study higher brain functions in Drosophila. Ultimately, based on its simple setup the rewarding or punishing effect of any dissoluble substance can be easily tested with this assay.
In addition, several variants of the paradigm were recently published that allow the investigation of associative visual learning in the larvae23,36 (established in Gerber et al. (2004)); and electric shock, light, heat, quinine or vibrations were also successfully implemented as aversive reinforcers for associative olfactory learning9,17,19-21,37-40. Thus, a comprehensive set of experimental setups exists to analyze the behavioral, neuronal and molecular basis of learning and memory in Drosophila larvae (Figure 5)13,14,41,42. Here, we focused exclusively on odor-fructose learning due to the robustness of the assay and the relatively high performance indices that can be achieved. Especially some of the aversive variants lead to only small behavioral changes. This limits to some extent the application of the method, besides developmental issues of the animals that make studies on larval long-term memory rather impossible.
The larval brain consists of only about 10,000 neurons in its entirety. Thus due to its relative simple (in terms of numbers) organization it is well accessible to genetic interference, which in turn allows for advanced studies on the molecular and neuronal basis of learning and memory. Especially the GAL4/UAS systems and its recent modifications allow for the genetic manipulation of defined sets of neurons and up to even single cells in a spatio-temporal manner (Figure 4)7,10. Hereby a comprehensive set of effector lines offers the possibility to visualize these defined sets of neurons (Figure 4)25,43 or, alternatively to manipulate their neuronal output (Table 1). Most often effector genes are applied that can cell-autonomously induce cell death or inhibit neuronal transmission29,30,33. More recently technologies were developed that allow for a controlled artificial activation of neurons driven by light or temperature (Table 1)31,32,44.
In summary, the combination of sophisticated ways of genetic interference and the here described behavioral experiments allow uncovering the neuronal, molecular and behavioral basis of learning and memory in the elementary brain of Drosophila larvae.
The authors have nothing to disclose.
We especially want to thank the members of the Gerber lab for technical instructions on their experimental setup and comments on the manuscript. We also thank Lyubov Pankevych for fly care and maintenance of the wild type CantonS stock. This work is supported by the DFG grant TH1584/1-1, the SNF grant 31003A_132812/1 and the Zukunftskolleg of the University of Konstanz (all to AST).
Name of the reagent | Company | Catalogue number | CAS number |
Fructose | Sigma | 47740 | 57-48-7 |
NaCl | Fluka | 71350 | 7647-14-5 |
Agarose | Sigma | A5093 | 9012-36-6 |
1-octanol | Sigma | 12012 | 111-87-5 |
Amylacetate | Sigma | 46022 | 628-63-7 |
Paraffin oil | Sigma | 18512 | 8012-95-1 |