High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation

Neuronally orchestrated muscular movement and locomotion are defining faculties of multicellular animals. Due to its simple brain and genetic accessibility, the larva of the fruit fly Drosophila melanogaster allows one to study these processes at tractable levels of complexity. However, although the faculty of locomotion clearly pertains to the individual, most studies of locomotion in larvae use measurements aggregated across animals, or animals tested one by one, an extravagance for larger-scale analyses. This prevents grasping the inter- and intra-individual variability in locomotion and its neurogenetic determinants. Here, we present the IMBA (individual maggot behaviour analyser) for analysing the behaviour of individual larvae within groups, reliably resolving individual identity across collisions. We use the IMBA to systematically describe the inter- and intra-individual variability in locomotion of wild-type animals, and how the variability is reduced by associative learning. We then report a novel locomotion phenotype of an adhesion GPCR mutant. We further investigated the modulation of locomotion across repeated activations of dopamine neurons in individual animals, and the transient backward locomotion induced by brief optogenetic activation of the brain-descending ‘mooncrawler’ neurons. In summary, the IMBA is an easy-to-use toolbox allowing an unprecedentedly rich view of the behaviour and its variability of individual larvae, with utility in multiple biomedical research contexts

Generic programming for graph problems using tree decompositions

Zsfassung in dt. SpracheTree decompositions have been an increasingly useful tool for solving prob- lems on graphs due to the important algorithmic properties of the class of graphs of bounded treewidth. An important theorem by Courcelle [Cou90] stated that properties definable in MSO logic can be decided in linear time on graphs of bounded treewidth. This provided a theoretical base which re- vealed tractability of many graph problems, intractable in the general case, for the aforementioned class of graphs and instigated many algorithms solv- ing MSO-definable problems. Bodlaender proposed a dynamic programming approach to designing algorithms using tree decompositions [Bod97]. The approach encompassed several of the algorithms already invented, but was also used as a method for the construction of new ones for a variety of graph problems. In this thesis we studied and implemented this approach, delivering a sys- tem that operates using plug-ins to describe the specific parts of algorithms using Bodlaender's method. Furthermore we implemented a 3 colouring algorithm as a plug-in for the system in order to assess its usability and efficiency.Tree decomposition hat eine zunehmende Bedeutung als Werkzeug zur Lösung von Graphenproblemen, bedingt durch wichtige algorithmische Eigenschaften der Klasse der Graphen mit beschränkter treewidth. Ein wichtiges Theo- rem von Courcelle [Cou90] besagt, dass Eigenschaften eines Graphen die in MSO Logik beschrieben werden können, in linearer Zeit für Graphen mit beschränkter treewidth entschieden werden können. Dies gibt den theoretis- chen Hintergrund für die tractability vieler Graphenprobleme, intractability im Allgemeinen und für die oben erwähnte Graphenklasse regte es zu vie- len Algorithmen für MSO-definierbaren Problemen an. Bodlaender schlägt in [Bod97] einen Ansatz vor zum Design von Algorithmen mittels dynamis- cher Programmierung unter der Verwendung von tree decomposition. Dieser Ansatz stellt eine verallgemeinerte Methode vor, mittels der sich auch bereits vor dieser Arbeit vorgestellte Algorithmen entwerfen hätten lassen, wichtiger jedoch diese Methode kann verwendet werden um neue Algorithmen für eine Vielzahl von Graphenproblemen zu konstruieren. In dieser Diplomarbeit haben wir diesen Ansatz untersucht und imple- mentiert. Das Ergebnis ist ein System, das Bodlaender's Methode ver- wendet und das es erlaubt spezifische Teile des Algorithmuses mittels Plu- gins zu beschreiben. Um die Verwendbarkeit und Effizienz des Systems einzuschätzen haben wir einen Algorithmus für Dreifärbung als Plugin im- plementiert.5

1.csv

A sample drosophila larva track

Common microbehavioral “footprint” of two distinct classes of conditioned aversion

Avoiding unfavorable situations is a vital skill and a constant task for any animal. Situations can be unfavorable because they feature something that the animal wants to escape from, or because they do not feature something that it seeks to obtain. We investigate whether the microbehavioral mechanisms by which these two classes of aversion come about are shared or distinct. We find that larval Drosophila avoid odors either previously associated with a punishment, or previously associated with the lack of a reward. These two classes of conditioned aversion are found to be strikingly alike at the microbehavioral level. In both cases larvae show more head casts when oriented toward the odor source than when oriented away, and direct fewer of their head casts toward the odor than away when oriented obliquely to it. Thus, conditioned aversion serving two qualitatively different functions—escape from a punishment or search for a reward—is implemented by the modulation of the same microbehavioral features. These features also underlie conditioned approach, albeit with opposite sign. That is, the larvae show conditioned approach toward odors previously associated with a reward, or with the lack of a punishment. In order to accomplish both these classes of conditioned approach the larvae show fewer head casts when oriented toward an odor, and direct more of their head casts toward it when they are headed obliquely. Given that the Drosophila larva is a genetically tractable model organism that is well suited to study simple circuits at the single-cell level, these analyses can guide future research into the neuronal circuits underlying conditioned approach and aversion, and the computational principles of conditioned search and escape

Modulations of microbehaviour by associative memory strength in Drosophila larvae

Finding food is a vital skill and a constant task for any animal, and associative learning of food-predicting cues gives an advantage in this daily struggle. The strength of the associations between cues and food depends on a number of parameters, such as the salience of the cue, the strength of the food reward and the number of joint cue-food experiences. We investigate what impact the strength of an associative odour-sugar memory has on the microbehaviour of Drosophila melanogaster larvae. We find that larvae form stronger memories with increasing concentrations of sugar or odour, and that these stronger memories manifest themselves in stronger modulations of two aspects of larval microbehaviour, the rate and the direction of lateral reorientation manoeuvres (so-called head casts). These two modulations of larval behaviour are found to be correlated to each other in every experiment performed, which is in line with a model that assumes that both modulations are controlled by a common motor output. Given that the Drosophila larva is a genetically tractable model organism that is well suited to the study of simple circuits at the single-cell level, these analyses can guide future research into the neuronal circuits underlying the translation of associative memories of different strength into behaviour, and may help to understand how these processes are organised in more complex systems

The impact of odor–reward memory on chemotaxis in larval Drosophila

How do animals adaptively integrate innate with learned behavioral tendencies? We tackle this question using chemotaxis as a paradigm. Chemotaxis in the Drosophila larva largely results from a sequence of runs and oriented turns. Thus, the larvae minimally need to determine (i) how fast to run, (ii) when to initiate a turn, and (iii) where to direct a turn. We first report how odor-source intensities modulate these decisions to bring about higher levels of chemotactic performance for higher odor-source intensities during innate chemotaxis. We then examine whether the same modulations are responsible for alterations of chemotactic performance by learned odor "valence" (understood throughout as level of attractiveness). We find that run speed (i) is neither modulated by the innate nor by the learned valence of an odor. Turn rate (ii), however, is modulated by both: the higher the innate or learned valence of the odor, the less often larvae turn whenever heading toward the odor source, and the more often they turn when heading away. Likewise, turning direction (iii) is modulated concordantly by innate and learned valence: turning is biased more strongly toward the odor source when either innate or learned valence is high. Using numerical simulations, we show that a modulation of both turn rate and of turning direction is sufficient to account for the empirically found differences in preference scores across experimental conditions. Our results suggest that innate and learned valence organize adaptive olfactory search behavior by their summed effects on turn rate and turning direction, but not on run speed. This work should aid studies into the neural mechanisms by which memory impacts specific aspects of behavior

The impact of odor-reward memory on chemotaxis in larval Drosophila

How do animals adaptively integrate innate with learned behavioral tendencies? We tackle this question using chemotaxis as a paradigm. Chemotaxis in the Drosophila larva largely results from a sequence of runs and oriented turns. Thus, the larvae minimally need to determine (i) how fast to run, (ii) when to initiate a turn, and (iii) where to direct a turn. We first report how odor-source intensities modulate these decisions to bring about higher levels of chemotactic performance for higher odor-source intensities during innate chemotaxis. We then examine whether the same modulations are responsible for alterations of chemotactic performance by learned odor "valence" (understood throughout as level of attractiveness). We find that run speed (i) is neither modulated by the innate nor by the learned valence of an odor. Turn rate (ii), however, is modulated by both: the higher the innate or learned valence of the odor, the less often larvae turn whenever heading toward the odor source, and the more often they turn when heading away. Likewise, turning direction (iii) is modulated concordantly by innate and learned valence: turning is biased more strongly toward the odor source when either innate or learned valence is high. Using numerical simulations, we show that a modulation of both turn rate and of turning direction is sufficient to account for the empirically found differences in preference scores across experimental conditions. Our results suggest that innate and learned valence organize adaptive olfactory search behavior by their summed effects on turn rate and turning direction, but not on run speed. This work should aid studies into the neural mechanisms by which memory impacts specific aspects of behavior.We received project support by the European Commission (FP7-ICT project Miniature Insect Model for Active Learning [MINIMAL]). M.L. and S.F.R. acknowledge further funding from the Spanish Ministry of Science and Innovation (MICINN, BFU2011-483 26208) and the EMBL/CRG Systems Biology Program. A.D. acknowledges support via the grants EP/F500385/1 and BB/F529254/1 for the University of Edinburgh School of Informatics Doctoral Training Centre in Neuroinformatics and Computational Neuroscience, the UK Engineering and Physical Sciences Research Council (EPSRC), UK Biotechnology and Biological Sciences Research Council (BBSRC), and the UK Medical Research Council (MRC). B.G. received additional support from the Deutsche Forschungsgemeinschaft (DFG) (SFB 779 Motivated behavior), and the Bundesministerium fu¨r Bildung und Forschung (BMBF) (Bernstein Network Insect inspired robotics)

The impact of odor-reward memory on chemotaxis in larval Drosophila

How do animals adaptively integrate innate with learned behavioral tendencies? We tackle this question using chemotaxis as a paradigm. Chemotaxis in the Drosophila larva largely results from a sequence of runs and oriented turns. Thus, the larvae minimally need to determine (i) how fast to run, (ii) when to initiate a turn, and (iii) where to direct a turn. We first report how odor-source intensities modulate these decisions to bring about higher levels of chemotactic performance for higher odor-source intensities during innate chemotaxis. We then examine whether the same modulations are responsible for alterations of chemotactic performance by learned odor "valence" (understood throughout as level of attractiveness). We find that run speed (i) is neither modulated by the innate nor by the learned valence of an odor. Turn rate (ii), however, is modulated by both: the higher the innate or learned valence of the odor, the less often larvae turn whenever heading toward the odor source, and the more often they turn when heading away. Likewise, turning direction (iii) is modulated concordantly by innate and learned valence: turning is biased more strongly toward the odor source when either innate or learned valence is high. Using numerical simulations, we show that a modulation of both turn rate and of turning direction is sufficient to account for the empirically found differences in preference scores across experimental conditions. Our results suggest that innate and learned valence organize adaptive olfactory search behavior by their summed effects on turn rate and turning direction, but not on run speed. This work should aid studies into the neural mechanisms by which memory impacts specific aspects of behavior.We received project support by the European Commission (FP7-ICT project Miniature Insect Model for Active Learning [MINIMAL]). M.L. and S.F.R. acknowledge further funding from the Spanish Ministry of Science and Innovation (MICINN, BFU2011-483 26208) and the EMBL/CRG Systems Biology Program. A.D. acknowledges support via the grants EP/F500385/1 and BB/F529254/1 for the University of Edinburgh School of Informatics Doctoral Training Centre in Neuroinformatics and Computational Neuroscience, the UK Engineering and Physical Sciences Research Council (EPSRC), UK Biotechnology and Biological Sciences Research Council (BBSRC), and the UK Medical Research Council (MRC). B.G. received additional support from the Deutsche Forschungsgemeinschaft (DFG) (SFB 779 Motivated behavior), and the Bundesministerium fu¨r Bildung und Forschung (BMBF) (Bernstein Network Insect inspired robotics)

High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation

Neuronally orchestrated muscular movement and locomotion are defining faculties of multicellular animals. Due to its simple brain and genetic accessibility, the larva of the fruit fly Drosophila melanogaster allows one to study these processes at tractable levels of complexity. However, although the faculty of locomotion clearly pertains to the individual, most studies of locomotion in larvae use measurements aggregated across animals, or animals tested one by one, an extravagance for larger-scale analyses. This prevents grasping the inter- and intra-individual variability in locomotion and its neurogenetic determinants. Here, we present the IMBA (individual maggot behaviour analyser) for analysing the behaviour of individual larvae within groups, reliably resolving individual identity across collisions. We use the IMBA to systematically describe the inter- and intra-individual variability in locomotion of wild-type animals, and how the variability is reduced by associative learning. We then report a novel locomotion phenotype of an adhesion GPCR mutant. We further investigated the modulation of locomotion across repeated activations of dopamine neurons in individual animals, and the transient backward locomotion induced by brief optogenetic activation of the brain-descending 'mooncrawler' neurons. In summary, the IMBA is an easy-to-use toolbox allowing an unprecedentedly rich view of the behaviour and its variability of individual larvae, with utility in multiple biomedical research contexts