Adaptation of Drosophila larva foraging in response to changes in food resources
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Evaluation Summary:
This paper contributes to the growing body of literature that investigates foraging in complex landscapes. It is therefore of interest to neuroscientists and ecologists. The paper effectively combines behavioral experiments with phenomenological modeling to investigate which navigational strategies are responsive to the type and distribution of food patches. The main experimental results pertaining to food strategy are well supported, with secondary results limited by the low sample sizes.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #3 agreed to share their name with the authors.)
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Abstract
All animals face the challenge of finding nutritious resources in a changing environment. To maximize lifetime fitness, the exploratory behavior has to be flexible, but which behavioral elements adapt and what triggers those changes remain elusive. Using experiments and modeling, we characterized extensively how Drosophila larvae foraging adapts to different food quality and distribution and how the foraging genetic background influences this adaptation. Our work shows that different food properties modulated specific motor programs. Food quality controls the traveled distance by modulating crawling speed and frequency of pauses and turns. Food distribution, and in particular the food–no food interface, controls turning behavior, stimulating turns toward the food when reaching the patch border and increasing the proportion of time spent within patches of food. Finally, the polymorphism in the foraging gene (rover–sitter) of the larvae adjusts the magnitude of the behavioral response to different food conditions. This study defines several levels of control of foraging and provides the basis for the systematic identification of the neuronal circuits and mechanisms controlling each behavioral response.
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Author Response
Reviewer #1 (Public Review):
Wosniack et al. perform the analysis of larval trajectories from behavioral experiments and build a phenomenological model and efficiently combine the two to dissect behavioral strategies that Drosophila larvae use during foraging. The paper touches upon several factors that influence foraging: from food quality and distribution to genetic polymorphism and finally the contribution of sensory cues. While the first two are well explored and characterized in the paper, the contribution of different sensory modalities is less investigated. They study how homogeneous food substrates or food distributed in patches influence foraging strategies. They find a modular organization of behavioral strategies that is dependent of food characteristics: food quality modulates crawling speed, turning and …
Author Response
Reviewer #1 (Public Review):
Wosniack et al. perform the analysis of larval trajectories from behavioral experiments and build a phenomenological model and efficiently combine the two to dissect behavioral strategies that Drosophila larvae use during foraging. The paper touches upon several factors that influence foraging: from food quality and distribution to genetic polymorphism and finally the contribution of sensory cues. While the first two are well explored and characterized in the paper, the contribution of different sensory modalities is less investigated. They study how homogeneous food substrates or food distributed in patches influence foraging strategies. They find a modular organization of behavioral strategies that is dependent of food characteristics: food quality modulates crawling speed, turning and pausing while increases in the time spent inside the patches are the result of biasing turning towards the patch center when the larvae are at the food-no food interface. Furthermore, using anosmic animals they determine that olfaction is differentially involved in the foraging decisions depending on the type of food substrates that the larvae are exploring. Finally, they perform this analysis in rover and sitter larvae to determine the effect of the foraging gene polymorphism on these behaviors and show that its expression (where sitter larvae are slower, turn less and pause more compared to rover larvae) is dependent on the food distribution. They propose that larvae adapt the extent of their exploration to the quality of food. This detailed analysis of elements that constitute behavioral strategies sets the basis for identifying genes involved in foraging and the neural substrates of the different behavioral modules and ultimately understanding the neural circuit mechanisms involved.
The paper efficiently combines analysis of larval trajectories from experiments with computational modeling and identifies the behavioral elements that contribute to foraging. The authors show that olfaction has an important role when foraging on yeast substrates but not on sugar-rich substrates using anosmic larvae. They propose that taste could contribute more on sugar and apple juice substates however they do not test this hypothesis. Did the authors try or consider testing the Gr43a mutant on these substrates? Determining to which extent taste contributes to the different strategies completes the picture of how sensory cues contribute to foraging decisions that the authors started to address by tackling the contribution of olfaction to foraging on the different substrates. Also on patchy substrates, is the border completely smooth or could the larvae also sense the border as a rough edge? Could other modalities be involved?
The idea of testing the anosmic animals was to understand to what extent volatile sensory cues influence the search outside the patch. We did not intend to make a complete analysis of the role of different sensory modalities for the foraging adaptation. In particular, investigating taste is complicated since it is not very well known how yeast taste is sensed. Several yeast metabolites have been shown to activate subsets of taste receptor neurons but the work has mostly been done in adult flies. There is a clearer picture regarding sugars where Gr43a is known to be a sucrose and fructose receptor. To understand the role of taste for foraging, we should do a series of experiments which go beyond the scope of this paper.
But we agree it is an interesting question and have added a new section in the discussion. See line 634: “An experiment using the gustatory sweet sensor Gr43a mutant on sucrose, which is not volatile and does not produce smell, could help discerning the contribution of taste at the border of the patch (Fujishiro et al. 1984; Marella et al., 2006; Miyamoto et al. 2013; Wang et al.,2004; Mishra et al.,2013). For yeast, the lack of smell completely changed the response of the larvae, which did not show differences inside and outside the patch for most foraging parameters (Figure 4B, C, E, G). In this instance, taste was not sufficient to retain larvae inside the yeast patch (compare Figure 3H with Figure 4F) even though several gustatory receptors have been shown to be activated by yeast metabolites (Wisotsky et al., 2011, Ganguly et al.,2017, Croset et al., 2016).”
Regarding the edge sensation, the revised version includes two control experiments where we have tested the impact of the edges in the absence of nutrients. In the first control experiment, we prepared wells for food patches like in the “sucrose” and “apple juice” conditions, but we filled them with agar. In the second experiment, to control for the “yeast” condition, we made patches with gel. The results are presented in Figure 3-figure supplement 2 and they show that in both cases, in the absence of nutrients, the edge does not have a significant influence on the turning rate towards the center.
The revised version also includes mentions to mechanosensation:
Line 337 : “We observed that inward turns occur more often than outward turns at the border of the patch for the three substrates (Figure 3B, inward turns are shown in black). To control for possible mechanosensory effects due to the border edges, we prepared new arenas with patches that contained no nutrients, either using the same agar that composed the rest of the arena, or using ultrasound gel (Methods). Larvae in the agar-agar or the agar-gel border did not show any changes in their preference to turn towards the patch center, confirming that the behavioral change observed in response to food is specific (Figure 3-figure supplement 2).”
Line 646: “However, when larvae are crawling, they leave a print of their denticle attachment on the agar, that could inform them about their previous location and help returning to the food.”
In Figure 3C the crawling speed is lower in yeast and apple juice experiments both inside and outside of patches (and in both rovers and sitters) compared to sucrose experiments. Do the authors have an explanation for this? Also, as they note, surprisingly the turn bias persisted when the larvae exited the patches. Are these two related? Do larvae turn more frequently?
The speed outside the patches of yeast and apple juice is indeed lower than outside sucrose. We now mention this in the main text and propose an explanation:
Line 313: “Outside yeast and apple juice patches, the crawling speed increased but did not return to levels similar to the agar-only condition, suggesting that the behavior of larvae that exit the patch is influenced by the recent food experience or that larvae might still be sensing the food (Figure 3-figure supplement 1E). In line with this, in yeast the number of turns outside the patch was higher than inside the patch.”
The authors describe and discuss handedness in larval turning. While this in itself is an interesting characterisation, it does not appear to be thoroughly addressed in the context of its influence on foraging behavior. The authors conclude that the presence of patches induces turning bias that overrides handedness. It would be interesting to determine whether there are differences in turn size and/or reorientation frequency depending if the larvae are turning on the preferred side versus the non-preferred side.
Thank you for pointing this, the sentence was somewhat misleading. We corrected it and added a quantification of the percentage of larvae whose handedness changes when comparing in and out behaviour, in Figure 3-figure supplement 1F. This is generally around 20% so larvae mostly adjust their angles rather than their handedness.
Line 354: “This is accomplished by turning towards the patch center while maintaining the handedness (Figure 3J and Figure 3-figure supplement 1F) and represents an important mechanism to remain inside the food.”During different types of taxes, the larvae modulate crawling speed, duration, turn rate, size and direction to avoid unfavourable conditions and approach unfavourable conditions. This is true across different types of sensory gradients. Some of these strategies are also described in this paper. The authors make a link between behaviour on patch-no patch interface and taxis behaviour. It would be interesting to further develop the comparison between the behavioural elements described here and those in navigational strategies in sensory gradients. The commonalities and possible modular organisation of both could point to an existence of neural circuits for the different behavioural modules that are recruited differentially dependent on the sensory context, motivation state, or a combination of both (and based on different types of sensory information).
Thank you for the comment. We have added a new section in the discussion. Line 651: “One of the strengths of our phenomenological model is that it incorporates a modular organization of foraging that could reflect how the crawl and turn modules are controlled. First, we modelled a stochastic search where no information regarding food is available outside of the current location, because food is absent or because the larvae cannot sense it. This corresponds to an autonomous search behavior implemented by circuits located in the ventral nerve cord without input from the brain (Berni et. al 2012; Sims et al. 2019). Second, we have incorporated a goal-directed navigation that allows larvae return to the food. Our phenomenological model includes a distance-dependent probability to turn inwards that mimics the effect of chemotaxis (when present), as much as any other possible mechanism that contributes to the turning probability. As a consequence, we observed that simulated larvae, even when the resources are fractioned in eight patches, could stay inside the food patch for longer periods, in line with experimental observations (Figure 5 and Figure 6). The model could be improved by setting the turning properties outside the patch to match as closely as possible experimental observations. To this end, we could consider studies of larvae crawling in different attractive gradients, where the changes in turning probability and angle, including weathervaning, have been investigated in relation to precise spatio-temporal information of odorants (Louis et al., 2008; Gomez-Marin et al., 2011; Davies et al.,2015). It would also be helpful to have information about other attractive gradients, like taste, to know if a common set of mechanisms is used regardless of the sensory modality. Using this information, our model could be used to investigate how crawling speed and turning properties are controlled via descending pathways from the brain (Tastekin et al. 2018; Jovanic et al. 2019). Finally, in the presence of nutrients, our model adjusts movements to stay on the food patch. The concerted decrease in turning rate and crawling speed and the increase in the number of pauses, suggests that a neuromodulatory depression of movement (Marder, 2012) could be relevant in this phase. It would be interesting to investigate more generally how neuromodulators influence the decision to remain or explore new food resources in relation to the resources available and the larval motivational state.”
Reviewer #3 (Public Review):
The authors of the paper study foraging strategy in crawling Drosophila larvae. They utilize single-larva tracking in isotropic and patchy food nutrition environments, detailed quantitative analysis of the animals' behavioral states and transitions, and a random-walk-style Monte Carlo simulation setting. They investigate how specific components of behavior are modulated for the animal to locate suitable food resources.
Strengths:
- The main results of the paper, laying out how crawling speed, turn/pause rates, and turn direction bias work together cause larvae to find the food they need are interesting, nicely presented, and important for ultimately understanding how foraging really works in detail, here at the behavioral level, and somewhere down the road at the circuit and/or molecular levels too.
- Comparing rovers and sitters throughout the experimental parts of the paper was a really nice idea, with interesting results, and it is well motivated in the introduction.
- The handedness of individuals is a nice finding as well, I think the first time this has been published for larval Drosophila.
- Simulations that use empirical results as probability distributions make for a nice environment for testing ideas about larva behavior.
- Creating the patchy food environments was a great idea, as it puts the larva behavior in a more realistic setting, but still controlled enough to be analyzed clearly.
Weaknesses:
- For an animal that tends to have a very high variance in its behavior, the number of larvae used in each experiment seems pretty low to me. As a result, some of the secondary claims are perhaps not as well supported when they rely on "not significant" statistical test results. * The introduction is generally good, but could perhaps better motivate why fly larva foraging should be of interest to a more general audience.
We answered the question about the number of larvae used in our experiments in the required revisions above.
We have added a section in the introduction to explain the relevance and generality of our work:
Line 45: “These models postulate that animals will use different strategies depending on the distribution of the resources. In environments where resources are abundant, animals will search and exploit them performing short movements in random directions, in patterns well approximated by Brownian random walks. When resources are sparse, and foragers have incomplete knowledge about their location, a more diffusive strategy is needed, with an alternation between short-range and long-range movements, which can be modelled as a Lévy random walk. Analysis of animal movements in the wild has demonstrated that environmental context can induce the switch between Levy to Brownian movement patterns (Humphries et al., 2010), but the mechanisms behind the implementation of such a behavior (e.g., cognitive capacity, memory) often remain elusive (Budaev et al., 2019). Understanding the motor mechanisms that regulate the execution of different movement strategies and the transitions between them could provide insight into how the nervous system can drive the search for resources in complex and ever-changing environments. Drosophila larva is an excellent model to study this question, because the movement of single animals can be tracked for long periods of time in a controlled environment.”
- The execution of the simulations seems reasonable, but perhaps don't add a lot to this particular paper, especially given how much of the manuscript they take up.
We now specifically highlight the unique contributions of the model that go beyond the performed experiments, especially in terms of making experimental predictions. See our answer to the specific point in the requires revisions above. Overall, the primary results of the paper do achieve the stated goals and set the stage nicely for further studies into the underlying mechanisms of foraging in larvae.
For those studying foraging, especially in flies/larvae but probably other animals as well, this should be an important paper that highlights the utility of individual animal tracking with high resolution, analyzing specific components of behavior, and creating simulation environments as playgrounds for investigating the impact of those components.
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Evaluation Summary:
This paper contributes to the growing body of literature that investigates foraging in complex landscapes. It is therefore of interest to neuroscientists and ecologists. The paper effectively combines behavioral experiments with phenomenological modeling to investigate which navigational strategies are responsive to the type and distribution of food patches. The main experimental results pertaining to food strategy are well supported, with secondary results limited by the low sample sizes.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #3 agreed to share their name with the authors.)
-
Reviewer #1 (Public Review):
Wosniack et al. perform the analysis of larval trajectories from behavioral experiments and build a phenomenological model and efficiently combine the two to dissect behavioral strategies that Drosophila larvae use during foraging. The paper touches upon several factors that influence foraging: from food quality and distribution to genetic polymorphism and finally the contribution of sensory cues. While the first two are well explored and characterized in the paper, the contribution of different sensory modalities is less investigated. They study how homogeneous food substrates or food distributed in patches influence foraging strategies. They find a modular organization of behavioral strategies that is dependent of food characteristics: food quality modulates crawling speed, turning and pausing while …
Reviewer #1 (Public Review):
Wosniack et al. perform the analysis of larval trajectories from behavioral experiments and build a phenomenological model and efficiently combine the two to dissect behavioral strategies that Drosophila larvae use during foraging. The paper touches upon several factors that influence foraging: from food quality and distribution to genetic polymorphism and finally the contribution of sensory cues. While the first two are well explored and characterized in the paper, the contribution of different sensory modalities is less investigated. They study how homogeneous food substrates or food distributed in patches influence foraging strategies. They find a modular organization of behavioral strategies that is dependent of food characteristics: food quality modulates crawling speed, turning and pausing while increases in the time spent inside the patches are the result of biasing turning towards the patch center when the larvae are at the food-no food interface. Furthermore, using anosmic animals they determine that olfaction is differentially involved in the foraging decisions depending on the type of food substrates that the larvae are exploring. Finally, they perform this analysis in rover and sitter larvae to determine the effect of the foraging gene polymorphism on these behaviors and show that its expression (where sitter larvae are slower, turn less and pause more compared to rover larvae) is dependent on the food distribution. They propose that larvae adapt the extent of their exploration to the quality of food. This detailed analysis of elements that constitute behavioral strategies sets the basis for identifying genes involved in foraging and the neural substrates of the different behavioral modules and ultimately understanding the neural circuit mechanisms involved.
The paper efficiently combines analysis of larval trajectories from experiments with computational modeling and identifies the behavioral elements that contribute to foraging. The authors show that olfaction has an important role when foraging on yeast substrates but not on sugar-rich substrates using anosmic larvae. They propose that taste could contribute more on sugar and apple juice substates however they do not test this hypothesis. Did the authors try or consider testing the Gr43a mutant on these substrates? Determining to which extent taste contributes to the different strategies completes the picture of how sensory cues contribute to foraging decisions that the authors started to address by tackling the contribution of olfaction to foraging on the different substrates. Also on patchy substrates, is the border completely smooth or could the larvae also sense the border as a rough edge? Could other modalities be involved?
In Figure 3C the crawling speed is lower in yeast and apple juice experiments both inside and outside of patches (and in both rovers and sitters) compared to sucrose experiments. Do the authors have an explanation for this? Also, as they note, surprisingly the turn bias persisted when the larvae exited the patches. Are these two related? Do larvae turn more frequently?
The authors describe and discuss handedness in larval turning. While this in itself is an interesting characterisation, it does not appear to be thoroughly addressed in the context of its influence on foraging behavior. The authors conclude that the presence of patches induces turning bias that overrides handedness. It would be interesting to determine whether there are differences in turn size and/or reorientation frequency depending if the larvae are turning on the preferred side versus the non-preferred side.
During different types of taxes, the larvae modulate crawling speed, duration, turn rate, size and direction to avoid unfavourable conditions and approach unfavourable conditions. This is true across different types of sensory gradients. Some of these strategies are also described in this paper. The authors make a link between behaviour on patch-no patch interface and taxis behaviour. It would be interesting to further develop the comparison between the behavioural elements described here and those in navigational strategies in sensory gradients. The commonalities and possible modular organisation of both could point to an existence of neural circuits for the different behavioural modules that are recruited differentially dependent on the sensory context, motivation state, or a combination of both (and based on different types of sensory information).
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Reviewer #2 (Public Review):
The study by Wosniack et al. investigates the impact of polymorphism on effective foraging behavior in patchy environments. The paper combines behavioral tracking data and phenomenological modelling to effectively describe and understand the navigational strategies underlying patch foraging in Drosophila larvae.
A major strength of the work is the use and integration of the model that accompanies the experimental findings and is refined with evidence from experiments throughout the paper. A key result is that the genetic differences between rover/sitter larvae only manifest in patchy environments and are effectively hidden when larvae are exposed to homogeneous environments.
This is a well-written and clear manuscript that effectively uses relatively simple techniques of behavioral tracking to quantify …
Reviewer #2 (Public Review):
The study by Wosniack et al. investigates the impact of polymorphism on effective foraging behavior in patchy environments. The paper combines behavioral tracking data and phenomenological modelling to effectively describe and understand the navigational strategies underlying patch foraging in Drosophila larvae.
A major strength of the work is the use and integration of the model that accompanies the experimental findings and is refined with evidence from experiments throughout the paper. A key result is that the genetic differences between rover/sitter larvae only manifest in patchy environments and are effectively hidden when larvae are exposed to homogeneous environments.
This is a well-written and clear manuscript that effectively uses relatively simple techniques of behavioral tracking to quantify larval navigation (and patch residency, albeit this is not connected explicitly to optimal foraging in the text.)
One aspect where the work could be strengthened is by highlighting where the differences in patch residence times between the model and data might arise. Especially in the anosmic animals, this removes one sensory aspect and one might feasibly expect the trajectory models to match better with the measured data. If this is not the case, it would be helpful for the readers to discuss the differences more explicitly.
The modeling approach taken here is generalizable to a number of model- and non-model species which can be tracked, e.g., nematodes, where similar models have been used to describe navigation albeit not in the context of sparse patches.
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Reviewer #3 (Public Review):
The authors of the paper study foraging strategy in crawling Drosophila larvae. They utilize single-larva tracking in isotropic and patchy food nutrition environments, detailed quantitative analysis of the animals' behavioral states and transitions, and a random-walk-style Monte Carlo simulation setting. They investigate how specific components of behavior are modulated for the animal to locate suitable food resources.
Strengths:
* The main results of the paper, laying out how crawling speed, turn/pause rates, and turn direction bias work together cause larvae to find the food they need are interesting, nicely presented, and important for ultimately understanding how foraging really works in detail, here at the behavioral level, and somewhere down the road at the circuit and/or molecular levels too.
* …Reviewer #3 (Public Review):
The authors of the paper study foraging strategy in crawling Drosophila larvae. They utilize single-larva tracking in isotropic and patchy food nutrition environments, detailed quantitative analysis of the animals' behavioral states and transitions, and a random-walk-style Monte Carlo simulation setting. They investigate how specific components of behavior are modulated for the animal to locate suitable food resources.
Strengths:
* The main results of the paper, laying out how crawling speed, turn/pause rates, and turn direction bias work together cause larvae to find the food they need are interesting, nicely presented, and important for ultimately understanding how foraging really works in detail, here at the behavioral level, and somewhere down the road at the circuit and/or molecular levels too.
* Comparing rovers and sitters throughout the experimental parts of the paper was a really nice idea, with interesting results, and it is well motivated in the introduction.
* The handedness of individuals is a nice finding as well, I think the first time this has been published for larval Drosophila.
* Simulations that use empirical results as probability distributions make for a nice environment for testing ideas about larva behavior.
* Creating the patchy food environments was a great idea, as it puts the larva behavior in a more realistic setting, but still controlled enough to be analyzed clearly.Weaknesses:
* For an animal that tends to have a very high variance in its behavior, the number of larvae used in each experiment seems pretty low to me. As a result, some of the secondary claims are perhaps not as well supported when they rely on "not significant" statistical test results.
* The introduction is generally good, but could perhaps better motivate why fly larva foraging should be of interest to a more general audience.
* The execution of the simulations seems reasonable, but perhaps don't add a lot to this particular paper, especially given how much of the manuscript they take up.Overall, the primary results of the paper do achieve the stated goals and set the stage nicely for further studies into the underlying mechanisms of foraging in larvae.
For those studying foraging, especially in flies/larvae but probably other animals as well, this should be an important paper that highlights the utility of individual animal tracking with high resolution, analyzing specific components of behavior, and creating simulation environments as playgrounds for investigating the impact of those components.
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