Neural mechanisms of context-dependent processing of CO2 avoidance behavior in fruit flies

The fruit fly, Drosophila melanogaster, innately avoids even low levels of CO₂. CO₂ is part of the so-called Drosophila stress odor produced by stressed flies, but also a byproduct of fermenting fruit, a main food source, making the strong avoidance behavior somewhat surprising. Therefore, we addressed whether feeding states might influence the fly’s behavior and processing of CO₂. In a recent report, we showed that this innate behavior is differentially processed and modified according to the feeding state of the fly. Interestingly, we found that hungry flies require the function of the mushroom body, a higher brain center required for olfactory learning and memory, but thought to be dispensable for innate olfactory behaviors. In addition, we anatomically and functionally characterized a novel bilateral projection neuron connecting the CO₂ sensory input to the mushroom body. This neuron was essential for processing of CO₂ in the starved fly but not in the fed fly. In this Extra View article, we provide evidence for the potential involvement of the neuromodulator dopamine in state-dependent CO₂ avoidance behavior. Taken together, our work demonstrates that CO₂ avoidance behavior is mediated by alternative neural pathways in a context-dependent manner. Furthermore, it shows that the mushroom body is not only involved in processing of learned olfactory behavior, as previously suggested, but also in context-dependent innate olfaction.     

Measuring the repertoire of age-related behavioral changes in Drosophila melanogaster

Aging affects almost all aspects of an organism—its morphology, its physiology, its behavior. Isolating which biological mechanisms are regulating these changes, however, has proven difficult, potentially due to our inability to characterize the full repertoire of an animal’s behavior across the lifespan. Using data from fruit flies (D. melanogaster) we measure the full repertoire of behaviors as a function of age. We observe a sexually dimorphic pattern of changes in the behavioral repertoire during aging. Although the stereotypy of the behaviors and the complexity of the repertoire overall remains relatively unchanged, we find evidence that the observed alterations in behavior can be explained by changing the fly’s overall energy budget, suggesting potential connections between metabolism, aging, and behavior.     

Lack of Dietary Polyunsaturated Fatty Acids Causes Synapse Dysfunction in the Drosophila Visual System

Polyunsaturated fatty acids (PUFAs) are essential nutrients for animals and necessary for the normal functioning of the nervous system. A lack of PUFAs can result from the consumption of a deficient diet or genetic factors, which impact PUFA uptake and metabolism. Both can cause synaptic dysfunction, which is associated with numerous disorders. However, there is a knowledge gap linking these neuronal dysfunctions and their underlying molecular mechanisms. Because of its genetic manipulability and its easy, fast, and cheap breeding, Drosophila melanogaster has emerged as an excellent model organism for genetic screens, helping to identify the genetic bases of such events. As a first step towards the understanding of PUFA implications in Drosophila synaptic physiology we designed a breeding medium containing only very low amounts of PUFAs. We then used the fly’s visual system, a well-established model for studying signal transmission and neurological disorders, to measure the effects of a PUFA deficiency on synaptic function. Using both visual performance and eye electrophysiology, we found that PUFA deficiency strongly affected synaptic transmission in the fly’s visual system. These defects were rescued by diets containing omega-3 or omega-6 PUFAs alone or in combination. In summary, manipulating PUFA contents in the fly’s diet was powerful to investigate the role of these nutrients on the fly´s visual synaptic function. This study aims at showing how the first visual synapse of Drosophila can serve as a simple model to study the effects of PUFAs on synapse function. A similar approach could be further used to screen for genetic factors underlying the molecular mechanisms of synaptic dysfunctions associated with altered PUFA levels.     

Mitochondria-targeted plastoquinone derivative SkQ1 increases early reproduction of <Emphasis Type="Italic">Drosophila melanogaster</Emphasis> at the cost of early survival

It was previously found that 20 pM SkQ1 (10-(6′-plastoquinonyl) decyltriphenylphosphonium) solution increased lifespan of virgin females and males of the fruit fly Drosophila melanogaster with maximal and highly reproducible effect on early survival of females. In this paper we demonstrate that SkQ1 solution of the same concentration does not increase lifespan of mated females and males, early effect on female survival being absent, whereas early fertility and the total number of progeny are elevated in treated flies. Increase in fertility observed in young mated females instead of increase of survival typical for young virgin females might illustrate the trade-off between the fly’s lifespan and reproduction.     

Combined Treatments Reduce Chilling Injury and Maintain Fruit Quality in Avocado Fruit during Cold Quarantine

Quarantine treatment enables export of avocado fruit (Persea americana) to parts of the world that enforce quarantine against fruit fly. The recommended cold-based quarantine treatment (storage at 1.1°C for 14 days) was studied with two commercial avocado cultivars ‘Hass’ and ‘Ettinger’ for 2 years. Chilling injuries (CIs) are prevalent in the avocado fruit after cold-quarantine treatment. Hence, we examined the effect of integrating several treatments: modified atmosphere (MA; fruit covered with perforated polyethylene bags), methyl jasmonate (MJ; fruit dipped in 2.5 μM MJ for Hass or 10 μM MJ for Ettinger for 30 s), 1-methylcyclopropene (1-MCP; fruit treated with 300 ppb 1-MCP for 18 h) and low-temperature conditioning (LTC; a gradual decrease in temperature over 3 days) on CI reduction during cold quarantine. Avocado fruit stored at 1°C suffered from severe CI, lipid peroxidation, and increased expression of chilling-responsive genes of fruit peel. The combined therapeutic treatments alleviated CI in cold-quarantined fruit to the level in fruit stored at commercial temperature (5°C). A successful therapeutic treatment was developed to protect ‘Hass’ and ‘Ettinger’ avocado fruit during cold quarantine against fruit fly, while maintaining fruit quality. Subsequently, treated fruit stored at 1°C had a longer shelf life and less decay than the fruit stored at 5°C. This therapeutic treatment could potentially enable the export of avocado fruit to all quarantine-enforcing countries. Similar methods might be applicable to other types of fruit that require cold quarantine.     

Paraquat administration in Drosophila for use in metabolic studies of oxidative stress

Paraquat (PQ) is widely used in the laboratory to induce in vivo oxidative stress, particularly in the fruit fly, Drosophila melanogaster. PQ administration to the fly traditionally involves feeding in a 1% sucrose solution; however, a diet high in sucrose can itself be stressful. We examined a novel method of PQ administration: incorporation into the fly’s standard cornmeal–sucrose–yeast diet. This method successfully delivers PQ to the fly at concentrations similar to those of the traditional method but with fewer possibly confounding complications.     

Task-induced neural covariability as a signature of approximate Bayesian learning and inference

Perception is often characterized computationally as an inference process in which uncertain or ambiguous sensory inputs are combined with prior expectations. Although behavioral studies have shown that observers can change their prior expectations in the context of a task, robust neural signatures of task-specific priors have been elusive. Here, we analytically derive such signatures under the general assumption that the responses of sensory neurons encode posterior beliefs that combine sensory inputs with task-specific expectations. Specifically, we derive predictions for the task-dependence of correlated neural variability and decision-related signals in sensory neurons. The qualitative aspects of our results are parameter-free and specific to the statistics of each task. The predictions for correlated variability also differ from predictions of classic feedforward models of sensory processing and are therefore a strong test of theories of hierarchical Bayesian inference in the brain. Importantly, we find that Bayesian learning predicts an increase in so-called “differential correlations” as the observer’s internal model learns the stimulus distribution, and the observer’s behavioral performance improves. This stands in contrast to classic feedforward encoding/decoding models of sensory processing, since such correlations are fundamentally information-limiting. We find support for our predictions in data from existing neurophysiological studies across a variety of tasks and brain areas. Finally, we show in simulation how measurements of sensory neural responses can reveal information about a subject’s internal beliefs about the task. Taken together, our results reinterpret task-dependent sources of neural covariability as signatures of Bayesian inference and provide new insights into their cause and their function.     

Maximally efficient prediction in the early fly visual system may support evasive flight maneuvers

The visual system must make predictions to compensate for inherent delays in its processing. Yet little is known, mechanistically, about how prediction aids natural behaviors. Here, we show that despite a 20-30ms intrinsic processing delay, the vertical motion sensitive (VS) network of the blowfly achieves maximally efficient prediction. This prediction enables the fly to fine-tune its complex, yet brief, evasive flight maneuvers according to its initial ego-rotation at the time of detection of the visual threat. Combining a rich database of behavioral recordings with detailed compartmental modeling of the VS network, we further show that the VS network has axonal gap junctions that are critical for optimal prediction. During evasive maneuvers, a VS subpopulation that directly innervates the neck motor center can convey predictive information about the fly’s future ego-rotation, potentially crucial for ongoing flight control. These results suggest a novel sensory-motor pathway that links sensory prediction to behavior.     

Synaptic abnormalities in a Drosophila model of Alzheimer’s disease

Alzheimer’s disease (AD) is an age-related neurodegenerative disease characterized by memory loss and decreased synaptic function. Advances in transgenic animal models of AD have facilitated our understanding of this disorder, and have aided in the development, speed and efficiency of testing potential therapeutics. Recently, we have described the characterization of a novel model of AD in the fruit fly, Drosophila melanogaster, where we expressed the human AD-associated proteins APP and BACE in the central nervous system of the fly. Here we describe synaptic defects in the larval neuromuscular junction (NMJ) in this model. Our results indicate that expression of human APP and BACE at the larval NMJ leads to defective larval locomotion behavior, decreased presynaptic connections, altered mitochondrial localization in presynaptic motor neurons and decreased postsynaptic protein levels. Treating larvae expressing APP and BACE with the γ-secretase inhibitor L-685,458 suppresses the behavioral defects as well as the pre- and postsynaptic defects. We suggest that this model will be useful to assess and model the synaptic dysfunction normally associated with AD, and will also serve as a powerful in vivo tool for rapid testing of potential therapeutics for AD.KEY WORDS: APP, Alzheimer’s disease, Drosophila, BACE, Synapse, NMJ     

Integrating Evolution into Ecological Modelling: Accommodating Phenotypic Changes in Agent Based Models

Evolutionary change is a characteristic of living organisms and forms one of the ways in which species adapt to changed conditions. However, most ecological models do not incorporate this ubiquitous phenomenon. We have developed a model that takes a ‘phenotypic gambit’ approach and focuses on changes in the frequency of phenotypes (which differ in timing of breeding and fecundity) within a population, using, as an example, seasonal breeding. Fitness per phenotype calculated as the individual’s contribution to population growth on an annual basis coincide with the population dynamics per phenotype. Simplified model variants were explored to examine whether the complexity included in the model is justified. Outputs from the spatially implicit model underestimated the number of individuals across all phenotypes. When no phenotype transitions are included (i.e. offspring always inherit their parent’s phenotype) numbers of all individuals are always underestimated. We conclude that by using a phenotypic gambit approach evolutionary dynamics can be incorporated into individual based models, and that all that is required is an understanding of the probability of offspring inheriting the parental phenotype.     

Multistability in Large Scale Models of Brain Activity

Noise driven exploration of a brain network’s dynamic repertoire has been hypothesized to be causally involved in cognitive function, aging and neurodegeneration. The dynamic repertoire crucially depends on the network’s capacity to store patterns, as well as their stability. Here we systematically explore the capacity of networks derived from human connectomes to store attractor states, as well as various network mechanisms to control the brain’s dynamic repertoire. Using a deterministic graded response Hopfield model with connectome-based interactions, we reconstruct the system’s attractor space through a uniform sampling of the initial conditions. Large fixed-point attractor sets are obtained in the low temperature condition, with a bigger number of attractors than ever reported so far. Different variants of the initial model, including (i) a uniform activation threshold or (ii) a global negative feedback, produce a similarly robust multistability in a limited parameter range. A numerical analysis of the distribution of the attractors identifies spatially-segregated components, with a centro-medial core and several well-delineated regional patches. Those different modes share similarity with the fMRI independent components observed in the “resting state” condition. We demonstrate non-stationary behavior in noise-driven generalizations of the models, with different meta-stable attractors visited along the same time course. Only the model with a global dynamic density control is found to display robust and long-lasting non-stationarity with no tendency toward either overactivity or extinction. The best fit with empirical signals is observed at the edge of multistability, a parameter region that also corresponds to the highest entropy of the attractors.     

Stimulating at the right time to recover network states in a model of the cortico-basal ganglia-thalamic circuit

Synchronization of neural oscillations is thought to facilitate communication in the brain. Neurodegenerative pathologies such as Parkinson’s disease (PD) can result in synaptic reorganization of the motor circuit, leading to altered neuronal dynamics and impaired neural communication. Treatments for PD aim to restore network function via pharmacological means such as dopamine replacement, or by suppressing pathological oscillations with deep brain stimulation. We tested the hypothesis that brain stimulation can operate beyond a simple “reversible lesion” effect to augment network communication. Specifically, we examined the modulation of beta band (14–30 Hz) activity, a known biomarker of motor deficits and potential control signal for stimulation in Parkinson’s. To do this we setup a neural mass model of population activity within the cortico-basal ganglia-thalamic (CBGT) circuit with parameters that were constrained to yield spectral features comparable to those in experimental Parkinsonism. We modulated the connectivity of two major pathways known to be disrupted in PD and constructed statistical summaries of the spectra and functional connectivity of the resulting spontaneous activity. These were then used to assess the network-wide outcomes of closed-loop stimulation delivered to motor cortex and phase locked to subthalamic beta activity. Our results demonstrate that the spatial pattern of beta synchrony is dependent upon the strength of inputs to the STN. Precisely timed stimulation has the capacity to recover network states, with stimulation phase inducing activity with distinct spectral and spatial properties. These results provide a theoretical basis for the design of the next-generation brain stimulators that aim to restore neural communication in disease.     

Proteasome,but Not Autophagy,Disruption Results in Severe Eye and Wing Dysmorphia: A Subunit- and Regulator-Dependent Process in Drosophila

Proteasome-dependent and autophagy-mediated degradation of eukaryotic cellular proteins represent the two major proteostatic mechanisms that are critically implicated in a number of signaling pathways and cellular processes. Deregulation of functions engaged in protein elimination frequently leads to development of morbid states and diseases. In this context, and through the utilization of GAL4/UAS genetic tool, we herein examined the in vivo contribution of proteasome and autophagy systems in Drosophila eye and wing morphogenesis. By exploiting the ability of GAL4-ninaE. GMR and P{GawB}Bx^MS1096 genetic drivers to be strongly and preferentially expressed in the eye and wing discs, respectively, we proved that proteasomal integrity and ubiquitination proficiency essentially control fly’s eye and wing development. Indeed, subunit- and regulator-specific patterns of severe organ dysmorphia were obtained after the RNAi-induced downregulation of critical proteasome components (Rpn1, Rpn2, α5, β5 and β6) or distinct protein-ubiquitin conjugators (UbcD6, but not UbcD1 and UbcD4). Proteasome deficient eyes presented with either rough phenotypes or strongly dysmorphic shapes, while transgenic mutant wings were severely folded and carried blistered structures together with loss of vein differentiation. Moreover, transgenic fly eyes overexpressing the UBP2-yeast deubiquitinase enzyme were characterized by an eyeless-like phenotype. Therefore, the proteasome/ubiquitin proteolytic activities are undoubtedly required for the normal course of eye and wing development. In contrast, the RNAi-mediated downregulation of critical Atg (1, 4, 7, 9 and 18) autophagic proteins revealed their non-essential, or redundant, functional roles in Drosophila eye and wing formation under physiological growth conditions, since their reduced expression levels could only marginally disturb wing’s, but not eye’s, morphogenetic organization and architecture. However, Atg9 proved indispensable for the maintenance of structural integrity of adult wings in aged flies. In toto, our findings clearly demonstrate the gene-specific fundamental contribution of proteasome, but not autophagy, in invertebrate eye and wing organ development.     

Influence of fruit traits on the infestation of Dacus persicus in two fruit morphs of Calotropis procera

The larvae of Dacus (Leptoxyda) persicus (aak fruit fly) are key predispersal seed predators in Calotropis procera (Asclepiadaceae). Based on fruit characteristics, two morphs are distinguishable in C. procera viz., the soft-fruited morph (SF morph) and the hard-fruited morph (HF morph). The work reported here examined whether the fruit characteristics influenced the infestation by the aak fruit fly and, if so, what mechanism(s) were operative. Fruits in the SF morph were significantly more acceptable to the aak fruit fly than those of the HF morph irrespective of their size class and availability or fly population density. A general ranking of fruit acceptability for oviposition by the aak fruit fly within the fruit size class was: size class III ≥ size class II > size class I and IV. The negative relationship between fruit infestation and pericarp toughness, which is suggestive of trade-offs between the fly’s oviposition obligation and energy/time (predation risk) constraint, was found to correlate with the requirement of greater force to puncture the pericarp in the hard fruits. Lower penetrability of the pericarp in the hard fruits appeared to be primarily due to the thickness of pericarp and secondarily on account of the thickened walls of endocarpic–mesocarpic cells in the inner pericarpic layer. The present data point to the existence of two fruit morphs in C. procera differing in the acceptability of fruits for oviposition by the aak fruit fly primarily on account of toughness and internal structure of the pericarp.     

How Skill Expertise Shapes the Brain Functional Architecture: An fMRI Study of Visuo-Spatial and Motor Processing in Professional Racing-Car and Na?ve Drivers

The present study was designed to investigate the brain functional architecture that subserves visuo-spatial and motor processing in highly skilled individuals. By using functional magnetic resonance imaging (fMRI), we measured brain activity while eleven Formula racing-car drivers and eleven ‘naïve’ volunteers performed a motor reaction and a visuo-spatial task. Tasks were set at a relatively low level of difficulty such to ensure a similar performance in the two groups and thus avoid any potential confounding effects on brain activity due to discrepancies in task execution. The brain functional organization was analyzed in terms of regional brain response, inter-regional interactions and blood oxygen level dependent (BOLD) signal variability. While performance levels were equal in the two groups, as compared to naïve drivers, professional drivers showed a smaller volume recruitment of task-related regions, stronger connections among task-related areas, and an increased information integration as reflected by a higher signal temporal variability. In conclusion, our results demonstrate that, as compared to naïve subjects, the brain functional architecture sustaining visuo-motor processing in professional racing-car drivers, trained to perform at the highest levels under extremely demanding conditions, undergoes both ‘quantitative’ and ‘qualitative’ modifications that are evident even when the brain is engaged in relatively simple, non-demanding tasks. These results provide novel evidence in favor of an increased ‘neural efficiency’ in the brain of highly skilled individuals.     

Models of Electrical Activity: Calibration and Prediction Testing on?the?Same Cell

Mathematical models are increasingly important in biology, and testability is becoming a critical issue. One limitation is that one model simulation tests a parameter set representing one instance of the biological counterpart, whereas biological systems are heterogeneous in their properties and behavior, and a model often is fitted to represent an ideal average. This is also true for models of a cell’s electrical activity; even within a narrowly defined population there can be considerable variation in electrophysiological phenotype. Here, we describe a computational experimental approach for parameterizing a model of the electrical activity of a cell in real time. We combine the inexpensive parallel computational power of a programmable graphics processing unit with the flexibility of the dynamic clamp method. The approach involves 1), recording a cell’s electrical activity, 2), parameterizing a model to the recording, 3), generating predictions, and 4), testing the predictions on the same cell used for the calibration. We demonstrate the experimental feasibility of our approach using a cell line (GH4C1). These cells are electrically active, and they display tonic spiking or bursting. We use our approach to predict parameter changes that can convert one pattern to the other.