Why are obese mice so easy to chase?

Dysfunctional signaling in the brain makes obese mice less active

Summary

Obesity is accompanied by a lack of motivation/desire to exercise. This has lead to the idea that lack of exercise leads to obesity. A new study challenges this by showing that both “lazy” and “active” mice gain weight on a fatty diet [1]. All mice on high fat diet become obese and then move around less than mice fed on standard chow. The researchers go on to show that the lack of motivation to exercise that accompanies obesity may well be brought about by neuronal changes in the regions of the mouse brain that respond to movement.

Introduction

The physical inactivity that accompanies obesity is frustrating for those wanting manage their own weight as well as those who want support a near and dear one who does [2,3]. A better understanding of where this seeming ‘lack of motivation’ to exercise comes from may help design better intervention strategies. Previous studies suggest that obese animals and humans may have defects in dopamine signaling in a region of the brain that controls movement behaviours with the result that they may find physical activity less rewarding [4,5]. However, does lack of exercise cause weight gain?

What did they do and find?

Mice were fed standard chow (lean) or high fat diet (obese) for 18 weeks. Mice become both obese and less active when fed a high fat diet. The researchers of this study wanted to understand if the mice became fat because they were less active. To their surprise they found that low activity and weight gain occurred hand in hand but were not cause and effect. The weight gain however was correlated to the high fat diet.

So what was causing the lower activity in obese mice? There is a bit of the brain called the striatum which is responsible for movement and is disrupted in disorders such as Parkinson’s. There are neurons in this region of the brain that are sensitive to the neurotransmitter dopamine and fire (get activated) during movement. The authors of this study reasoned that perhaps it is this region of the brain that is responsible for inactivity in obese mice.

First they looked for components of dopamine signaling, the levels of dopamine itself and the dopamine receptors which when present on neurons allows them to respond to dopamine. They found that the striatum of obese mice had Dopamine Receptors of a specific kind (D2R receptors) which showed decreased binding while the levels dopamine itself and the other receptor for dopamine was the same in lean and obese mice. This reduction in dopamine 2 Receptor binding did not correlate with weight gain but was correlated with movement loss.

So would lean mice also move less if they had lower binding D2Rs?

Indeed, in genetically modified mice that lacked D2R receptors in the striatal region – lower activity levels were observed even in lean mice. This showed that neuronal changes underlie lower activity levels in obese mice.

To probe this further the researchers measured the activity of neurons in the striatum by inserting an electrode in the brain of live obese and lean mice. These recordings showed that during movement there was less overall firing in the brain of obese mice.

In order to test if these brain regions and neurons were indeed responsible for the lower activity observed in obese mice, the researchers used a special set of mice. These mice are specially modified to express a molecule that is usually produced by active Dopamine signaling via D2R binding (Gi) coupled to an opiod receptor only in the neurons of the striata that naturally express D2R. This allows Gi to be uniquely switched on by use of a synthetic chemical (Salvinorin B). When Gi is artificially produced by the D2R expressing neurons of the striatum both lean mice and obese mice become more active.

Reducing the D2R levels artificially in the neurons of the striatum results in mice with lower activity levels however these mice were not more susceptible to weight gain. Nor are mice with low D2R binding in the beginning of the diet predisposed to weight gain.

Take homes from the study

Experiments on animal behaviour are difficult and sometimes hard to extend beyond specific cases because genetic and environmental effects play a large role in shaping observed behaviour and this study is no different. These data convincingly argue that in mice, obesity is accompanied by and not caused by lack of activity. It also gives us a perspective on how integrated an animal’s body and mind are. At the very least it makes us think that in combating obesity, a role for the mind cannot be ignored.

References

1. Basal Ganglia Dysfunction Contributes to Physical Inactivity in Obesity. Danielle M. Friend, Kavya Devarakonda, Timothy J. O’Neal, Miguel Skirzewski, Ioannis Papazoglou, Alanna R. Kaplan, Jeih-San Liow, Juen Guo, Sushil G. Rane, Marcelo Rubinstein, Veronica A. Alvarez, Kevin D. Hall, Alexxai V. Kravitz, Cell Metab. 2017 Feb 7

2. The mysterious case of the public health guideline that is (almost) entirely ignored: call for a research agenda on the causes of the extreme avoidance of physical activity in obesity. Ekkekakis P, Vazou S, Bixby WR, Georgiadis E, Obes Rev. 2016 Apr;17(4):313-29

3. Exercise does not feel the same when you are overweight: the impact of self-selected and imposed intensity on affect and exertion, P Ekkekakis and E Lind, International Journal of Obesity (2006) 30, 652–660

4. Reward mechanisms in obesity: new insights and future directions. Kenny PJ. Neuron. 2011 Feb 24;69(4):664-79.

5. Obesity and addiction: neurobiological overlaps (Is food addictive). Volkow ND, Wang GJ, Tomasi D, Baler RD. Obes Rev. 2013 Jan;14(1):2-18.

6. Do Dopaminergic Impairments Underlie Physical Inactivity in People with Obesity? Kravitz AV, O’Neal TJ, Friend DM, Front Hum Neurosci. 2016 Oct 14;10:514. eCollection 2016.

7. Increases in Physical Activity Result in Diminishing Increments in Daily Energy Expenditure in Mice. Timothy J. O’Neal,, Danielle M. Friend, Juen Guo, Kevin D. Hall, Alexxai V. Kravitz Curr Biol. 2017 Feb 6;27(3):423-430.

An Interview with Dr. Alexxai V. Kravitz

1. What is causing the change in dopamine signaling in the neurons responsive to movement in obese mice? Do you have more insights into this from your study of Parkinson’s?

This is a great question, but unfortunately one that we don’t know the answer to. Parkinson’s disease is caused by the death of neurons that make dopamine, and we looked at dopamine neurons in obese mice and learned that they were not dying. So in that way, the mechanism underlying the changes in dopamine signaling in obese mice is very different than with Parkinson’s disease. This is a good thing, as it would frankly be scary if a diet high in fat were causing the death of dopamine neurons! Instead, we observed dysfunction in a specific dopamine receptor (a protein that detects dopamine) in obese mice. We’re looking into what exactly is causing the dysfunction of this receptor, but unfortunately we do not currently know.

2. You data does show that mice become both obese and move less on high fat diet, but which bit convinces you that the “laziness” is because of the obesity? Can they not be two parallel outcomes of a high fat diet? If yes, then would a high fructose or high calorie diet lead to a similar outcome?

Let me clarify here – I don’t think the *weight* of the mice is causing the laziness, I believe dysfunction in their dopamine receptors is causing their laziness [More on this in Ref. 6]. And both this dysfunction and weight gain can be caused by the high fat diet. So in that say, yes, they can be two parallel outcomes of the high fat diet. To answer your second question, I’m not sure if other high calorie diets can cause the same dysfunction. This would be a great follow up experiment!

3. In your paper, you describe the limitations of human studies that have measured Dopamine signalling and its links to obesity. Can you tell us a bit more about what the challenges are?

To date there have been a handful of studies that have compared D2 receptor levels in people with obesity vs. normal weight, and a minority have reported dysfunction in D2Rs in people with obesity. It is not clear why some studies have reported lower levels of D2 receptors, while most have not. However, measuring dopamine receptor levels in humans is difficult. The only technique for measuring receptor levels in humans is PET scanning, a technique where a radioactive tracer is injected and the brain is scanned for the location where the tracer binds. If more tracer binds, it is assumed there are more “available” receptors in that brain area. However, this technique can be affected by many factors, including what other transmitters are bound to that receptor. If internal levels of dopamine are higher during the scan, for instance, the amount of a radio-tracer that binds to a dopamine D2 receptor will be lower. The complexity increases when we consider how many things can alter dopamine levels throughout the day, which include caffeine use, food intake, and sleep. These are some of the challenges that face clinical research. Animal studies are less likely to incur these sources of variance, and have more consistently reported decreases in D2 receptors in association with obesity.

4. Are the changes in the striatum reversible, by forced exercise for example or are there natural molecules that could restore Gi signaling?

There are no known ways to reverse these changes, but there is also very little research on this. There is a small amount of evidence in rats that forced exercise increases D2 receptor levels, but this is very preliminary and has not been replicated, nor studied in humans. This idea of how to alter D2 receptor levels is an extremely important concept for future research!

5. Are there common themes about obesity and lower activity levels that have emerged from animal studies and how would you extend them, if at al, to humans? For instance, you say mice and rats are different, then would you expect people to be more similar to mice than rats? Why?

It is very difficult to extend results from mice to humans, so I will be cautious on this one. However, there are some concepts from animal work that are relevant to humans. Many researchers have noted that animals voluntarily over-eat high fat diets, and that this leads to weight gain and obesity. While the specific macronutrient (fat vs. carbs vs. protein) content of human diets is the subject of a lot of debate when it comes to human obesity, it is fair to say that diets that induce over-eating will lead to obesity. Typically, foods that induce over-eating are highly palatable, such as junk foods that pack large numbers of calories into small volumes. While people are all different from one another, understanding the foods that a specific person overeats will inform what is likely to cause that person to gain weight.

As another concept that I believe is relevant to human s, in our study we reported that physical inactivity did not correlate with weight gain in mice. That is, we examined inactive mice that lacked D2 receptors, and found that they gained weight at the same rate as normal active mice. We also examined the natural variation of activity levels of normal mice and did not note any relationship here either. This seems to counter the conventional wisdom that inactivity should cause weight gain. However, this conventional wisdom is based largely on correlations between obesity and inactivity, rather than causal tests of this hypothesis. We all know that correlation does not imply causation, but it is very easy to get caught in this trap. In fact, in causal tests, the contribution of exercise alone (without changes in diet) to weight loss in humans is fairly small, generally resulting in 3-5 pounds of weight loss over the first year. This is consistent with our conclusions in mice. Studies in mice can help us understand at a mechanistic level why changes in activity (both increases and decreases) don’t translate into large changes in body weight [More on this in Ref.7].

6. In their natural habitats animals such as mice and rat consume high fat diets. Do you think your results would hold in wild rodents instead of lab reared ones, especially if they were allowed to interact freely with each other and the environment?

Wow, what a great question! We use lab mice, which have been bred in captivity for many decades. This is somewhat similar to studying domesticated dogs vs. wild dogs. And in many ways, our laboratory mice are quite different from wild mice. However, I believe that even wild mice would become inactive on a high fat diet. The association between obesity and inactivity has been seen in many species including humans adults, children, non-human primates, domesticated cats and dogs, rats, and mice. When an association occurs across so many species of animals, I think it is likely that it would extend to wild mice as well as laboratory mice. This would be a great student project to find some wild mice and test!

Game of Theories: A Policy of Bribery and Punishment

Theoretical study suggests that encouraging complaints from citizens may be the most effective way of reducing incidents of bribery

 

Article

Data analysis is critical for the formation of any robust policy. But reliable data in economics is not always available, since unlike in the natural sciences, controlled experiments at the population level are not possible.  Moreover, present data may not have sufficient predictive power, since population behavior changes over time. Economists use theoretical models to account for variables and parameters to predict end-results in such situations. These models can serve as prototype systems on which to test the possible consequences of a new policy.

In this particular study, the authors use evolutionary game theory to approach bribery, a prevalent problem in may societies.

What is Game Theory?

Economics, broadly defined, is the science of human behavior. And much like in the natural sciences, economists look for “bottom-up” explanations of phenomena, where simple underlying rules give rise to complex behavior. The rules generally take the form of mathematical equations, the solutions to which are expected to capture (and predict) the essential features of social dynamics.

A central theory which has proved useful is game theory. A more accurate name for it is “multi-person decision theory” – because that’s exactly what it is. It deals with situations where multiple players engage with each other, each armed with a repertoire of possible strategies, and the outcome (or “payoff”, as it is called) for each player depends on the strategy adopted by all the players.  The aim of each player is to choose the strategy that maximizes her payoff. As you can see, the theory potentially covers a very broad range of human interactions, and thus the widespread application of game theory in economics is hardly surprising.

But how do we adopt and revise our strategies over time? A set of perfectly rational beings with complete information would quickly reach a unique equilibrium situation (provided such a situation is allowed by the dynamics of the game). But in the real world, people are neither perfect computing machines, nor do they have perfect information. So the strategies we use, and the way we update them with further experience, depends a lot on the context.

What game does this article study?

The study employs different players and their corresponding strategies; an honest officer, a bribe-taking officer, an honest citizen, a bribe-paying citizen who doesn’t report on the crime, and a bribe-paying citizen who reports on the crime. The advantage to reporting, of course, is that you have a chance of getting your bribe refunded. These players (citizens and officers) interact at random and such interactions can potentially involve a corrupt transaction (depending on the strategies of the interacting players) leading to payment of a bribe. Like Kaushik Basu, the authors focus on the problem of harassment bribes. These are bribes paid by citizens to corrupt officers for getting access to a service they are legally entitled to (such as acquiring a passport or getting a driver’s license)

The authors also consider two different ways in which the citizens and officers may update their strategies over time. First is the Replicator model, where an officer or citizen randomly chooses a fellow officer or citizen, and tends to imitate their strategy if they have been more successful. In the second scenario, called the Alternative Strategy Exploration model, they first make their moves and receive their payoffs, then consider whether the possible alternatives may have given them a higher payoff, and if so, update their strategies accordingly. In both the cases, it is found that the population finally reaches a fixed frequency distribution of the various strategies.

What is the question?

The authors consider two major punishment models:

1. Symmetric punishment, where both bribe taker and bribe giver are punished

2. Asymmetric punishment, where only the bribe taker is punished.

In fact, a major motivating point for the study was the claim by economist Kaushik Basu that bribe-giving, as opposed to bribe-taking, should be legalized for harassment bribes, as this would increase the frequency of complaints and help bring down bribery.

The authors numerically simulate the evolution of strategies under both kind of punishment models to find out which might be better in curbing bribery incidents. They further analyze conditions under which a decrease in incidents of harassment bribery might be possible.

What do they find?

Contrary to the claims by Basu, they find that the effect of asymmetric punishment depends on the update strategies used by the players, and cannot be considered a universal solution. Lowering the cost of complaint, however, seems to work under both the asymmetric and symmetric punishment models. However, the extent of bribery reduction depends on other parameters as well.

What are the conclusions?

Bribery is a very complex and dynamic issue. While there can be no single way to get rid of it, the authors suggest that bringing down the cost of complaint to negligible might be important in an overall reduction in incidents of bribery, irrespective of the punishment model. On the other hand, what happens under more complicated updated strategies is still an open question. As the authors say in their article, “It would perhaps be more pragmatic to look at a combination of technological fixes and public policies targeting the myriad underlying causes of bribery in order to effect reduction in bribery and ease the toll it takes on public finances.”

It is interesting to note that even in relatively idealized economic models, a simple and universal solution may prove to be elusive. This should make us more skeptical of quick fixes suggested by policy leaders that seem to make intuitive sense, and look for solutions that are customized to individual scenarios.

References

Bribe and Punishment: An Evolutionary Game-Theoretic Analysis of Bribery,Prateek Verma, Supratim Sengupta, PLoS One. 2015 Jul 23;10(7):e0133441.

An interview with Dr. Supratim Sengupta

Q. Basu (2011) had submitted a report to the Government to inform on policy for bribery punishment. Why did you choose to study this report using game theory and which facets of this report have your study addressed in more depth?

When this report came out, a literature search revealed that there was practically no quantitative analysis of the issues raised and claims made in the report. The principle claim was that incidents of harassment bribery could be substantially reduced if only the bribe-taker but not the bribe-giver was penalized for the crime. It was also evident to us that the problem was ideally suited to be analyzed using evolutionary game theory since it presented a very well-defined scenario of social conflict with mutually exclusive interests of the principle parties (bribe-giver and bribe-taker) involved. Our main objective was to quantitatively examine in great detail the principle claim of Basu’s report (mentioned above) and understand how reduction in incidents of bribery depend on factors like the amount of bribe demanded, the cost of complaining about a bribery incident, the penalty to a bribe-taker if caught. We also examined how the manner in which individuals updates their strategies in response to a bribery incident affect the prevalence of bribery in the population. None of these aspects had been examined in such detail using the framework of evolutionary game theory and our work (carried out with my PhD student Prateek Verma) is the first to do so.

Q. Your models indicate that low cost of complaint may eradicate bribery. In countries with low bribery, are there platforms which make registering complaints easier?

Yes, most western European countries and places like USA, Canada etc., have efficient grievance redressal systems and harassment bribes are practically non-existent for basic services provided by the government. Even in India, a website called ipaidabribe.com started by an NGO in Bangalore has made it easy to report incidents of bribery and bring grievances to the notice of public officials. Such steps have led to positive outcomes which suggest that reducing the cost of reporting bribery incidents and establishing an efficient grievance redressal system by using technology can be quite helpful. If there is one policy proposal that we could advocate to reduce incidents of bribery, it would be this.

Q. Countries with low corruption indices seem to have a higher national income and lower inequality. But these factors do not seem to be explicitly incorporated in your model. Would you like to comment on that?

Bribery is a multi-faceted social problem and has many underlying causes including (but not restricted to) high levels of income inequality, as you have pointed out. However it is quite difficult to quantify the impact of such income inequality on the problem of harassment bribes. We took into consideration the most relevant factors that directly affect harassment bribery and that could be incorporated into a tractable mathematical model that would enable us to obtain insights into the problem and identify steps that can be taken to reduce such incidents of bribery.

Q. Why did you choose the two strategies: Replicator dynamics and alternative strategies dynamics for the study? What other scenarios might have been considered?

We wanted to highlight the difference in outcome when individuals choose two completely different methods to update their strategies over the course of time. We found that in the alternative strategy exploration case, the reduction in incidents of bribery was far less pronounced even when we followed Kaushik Basu’s proposal. However, these two methods are not the only ways individuals can choose to update their strategies and hence the outcome would indeed depend on the method followed. For instance, different individuals in the population could choose different methods to update their strategies and that would affect the outcome.

Q. Since collecting bribery data is difficult due to the secretive nature of the phenomenon, how do we check if some bribery-related policy has worked?

Collecting bribery data may not be as difficult as it seems. The government can ask citizens to fill out a simple questionnaire given by the service provider to report incidents of bribery. For example, the regional passport office can ask citizens applying for a passport to submit their feedback online by filling out an online questionnaire at the end of the process. Statistics based on such documents can be a very useful indicator of the prevailing levels of bribery in different services. It would also provide clues on how to allocate resources to reduce incidents of bribery in different services provided by the government.

Q. Do you expect your study or other related studies to have an impact on government policy?

It is difficult to predict whether any study of this kind will impact public policy. This is a topic of great public interest and Kaushik Basu’s original proposal certainly garnered a lot of attention. But that was in no small measure due to the important position he held at that time (Chief Economic Advisor to the PM) as well as his influence as a well-known economist. However, many (but not all) of the responses to that article in the press at that time were simplistic, knee-jerk reactions. Moreover, they were not grounded on objective analysis. We hope our work along with those of others have contributed towards a critical analysis and will at least rekindle the debate and stimulate new proposals on how to reduce harassment bribery. Despite the controversial nature of the proposal, we believe there are concrete and simple steps that can be taken that may have an impact. As I mentioned in my previous response, using web-based technology to streamline access to services, gather critical feedback and reduce the cost of complaining can definitely have a positive impact. However, we also acknowledge that technological fixes alone cannot and will not get rid of such a complex social problem that is definitely affected by income-inequality, the efficiency of the public justice system etc.

Q. In general, how much do you think game theory models accurately capture real world dynamics?

Evolutionary game theory is employed when the effectiveness of a strategy depends on the presence of other competing strategies in the population. It relies on specifying the net gain or loss (referred to as “payoffs”) to each strategy when it interacts with different strategies. It is very useful in analyzing how the number of individuals employing different strategies change over time and the conditions under which a specific strategy can out-compete all other strategies and take over the population. Unlike conventional game theory used by economists, which is involved only in finding equilibrium solutions (the so-called Nash equilibrium), evolutionary game theory allows us to see how the population gradually progresses towards an equilibrium state by tracking the change in number of individuals employing different strategies over time. The usefulness of evolutionary game theory in accurately capturing real world scenarios depends on the question being asked. There have been some criticisms (valid in my opinion) of using game theory to understand how cooperative behavior can spread or be sustained among groups of individuals. Experiments have revealed that people have an intrinsic tendency to cooperate more than game theoretic analysis predicts, despite cooperation being costly. In such scenarios, it is necessary to be cautious in drawing conclusions based on game theory. However, in the current scenario, such concerns do not apply since the primary interests of the principle players are at cross-purposes. We therefore feel that evolutionary game theory is well suited to accurately address the bribery problem. Nevertheless, some words of caution are in order. Our models employ quantities like the prosecution rate and penalty when prosecuted to understand the effects of punishment and its deterrence on bribery. In reality, these depend on the efficiency and integrity of the public grievance redressal systems and justice systems. These can vary a lot not just across countries but also across jurisdictions within the same country. These factors need to be given serious consideration before framing any public policy dealing with bribery.

Q. What do you think is the role of theory in economics, in general terms? I come from a background in theoretical physics (says Jabali) and now work in biology. And I and others like me sometimes wonder about whether we are making the right kind of assumptions in our models, or whether the phenomena we are describing are really reducible to a mathematical description, given the current state of knowledge. Does a theoretical study in economics contain the same kind of concerns? Or is the picture there very different?

You raise a very pertinent point here that I will not be able to satisfactorily address. I am not an economist by training. Like you, I am a theoretical physicist interested in analyzing complex social and biological systems using quantitative tools inspired by Physics and Mathematics. I am therefore not qualified to comment about the real-world relevance and drawbacks of theoretical models in Economics in general. However, the concerns you raise are surely relevant to studies of this kind and any honest scientist/economist needs to ponder about them. These concerns certainly informed our formulation of the problem and we tried to make the model as realistic as possible. But we also admit that some simplification was inevitable and we could not incorporate every single factor (like income-inequality for example) that may play a role in the prevalence of harassment bribes. Sometimes, even the factors incorporated, like prosecution rate, penalty for taking bribes etc. may not reveal the true complexity of the real world problem where such quantities depend on the efficiency and integrity of the police and justice systems. In some cases, the simplifications (like our assumption of a mixed population) can be addressed by studying the effects of a structured population of citizens and officers, as we are currently doing in an ongoing work (with Prateek Verma and Anjan Nandi) which is being written up. It is therefore important to acknowledge the potential consequences of the underlying assumptions and the associated simplifications while proposing new public policy based on such studies. It is also important for us (the community of social and natural scientists) to continue to strive to develop more realistic models by improving on existing ones whenever possible. Finally, I believe it is necessary for policy makers to pay attention to such studies and start a dialogue with social scientists to critically examine the consequences of such studies on public policy.

Scouting for the forager ant

– Identifying the basis of labour division in carpenter ants

 

Short summary

What determines the way animals behave? Is this almost unalterably in their genes or in their environment or a complex interaction between what is within and without? A recent study explores the division of roles within the worker caste of the carpenter ant and shows for the first time that these roles can be reversed using mind-altering drugs (1).

 

“Minor”carpenter ants are the foragers

Anyone who has observed the incessant activity of a beehive or a column of ants between their nest and a food source can appreciate how wonderfully co-ordinated and orderly it all looks. This coordination is brought about by a fascinating division of labour – well separated roles of who must do what for the colony. How do insects develop these identities? This becomes especially intriguing in insect colonies in which all inhabitants are children of the same parents and hence genetically related to each other. In carpenter ants, which are the subject of this study, there are two castes within the female workers – minor and major. The minors are smaller do most of the foraging whereas the majors rarely forage. This was established by setting up an arena for foraging around an ant nest and measuring to which caste they belonged and how many individuals came out to forage. While foraging activity for both minor and majors increased with age of the ants, the minors still performed most of the foraging. Additionally, the lead foragers – called scouts were also mostly minors and older scouts were much better/faster foragers than young ones -even when they were foraging in unfamiliar arenas. Hence, the foraging activity was established as a minor worker specific behaviour in these ants.

 

What makes “minor” ants better at foraging?

So what determines the foraging behaviour of minors? Genetic differences were undermined by the relatedness of minors and majors (they are sisters (2)) – suggesting that the differences is unlikely to be due to differences in genes. Also, multiple studies suggest that such behaviours are likely to be controlled by epigenetic mechanisms. Epigenetic modifications are modifications of the genetic material, without changes to the genetic material/ DNA itself (check out a beautiful introduction to the world of epigentics from MinuteEarth in the video below). These modifications which are chemical groups added on proteins that bind DNA, determine the context in which genes are expressed i.e form a basis for the conversion of genotype to phenotype. In this study they focused on the presence of a chemical group (an acetyl group) on histones. Previous studies have suggested that these marks may determine caste specific behaviour in other eusocial insects.

Consistent with this idea, a drastic increase in foraging activity of both majors and minors was brought about by feeding them drugs that inhibit the enzymes that remove the acetyl marks from the histone – or histone deacetylase inhibitors (Valproic acid – used to treat mood disorders in humans and Trichostatin A).  However, the minors continued to forage more and performed almost all the scouting.

Molecules and mechanisms of caste-identity

The authors then determined the molecular mechanisms of how the acetyl marks were placed on the histones in the first place what genes were responsive to these changes. When they inhibited the enzyme responsible for this behaviour (the histone acetyl transferase domain of the Creb binding protein (CBP)) they saw a drastic decrease in scouting. This established the scouts as a distinct behavioural caste within the minors and suggested that acetylation of histones by CBP is the molecular mechanisms that generate this behaviour.

They then looked at what makes major and minor workers different from the perspective of gene expression and came up with a different idea. What if there was a basal behaviour – “to forage” in ants and this was actively suppressed by all these molecular mechanisms? This suggested that injecting drugs at an early stage may prevent this suppression of behaviour. Voilà! in ants injected with drugs (Trichostatin A) the majors started to forage actively! In this case, it seems like timing was everything (look above for what happens when the treatment is started later!). Surprisingly, even when tested as a whole colony (with minors), the majors upon treatment participated more often in foraging. To dissect this further, the authors directly inhibited a single enzyme HDAC1 (Histone deacetylase 1 also called Rpd3) and found the same increase in foraging activity in the majors. This suggests a central role for HDAC1 in repressing foraging behaviour in majors.

Learning from ants

Behaviours are baffling and possibly emerge from complex interactions between genes, how these genes get expressed and what triggers them. Such triggers can come from what we eat, what we smell, how we interact with our environment and one another. Animal behaviour – especially in the context of colonies or societies, is likely to involve intricate rules for function and order. Unraveling these rules is an exciting area of ongoing research. In a surprising but retrospectively sensible turn of events, the authors of this study have found that the division of labour among worker ants lies in the mind, is set up very early and can be reversed.

Acknowledgement

Thank you!  Riley J Graham for helping out with this post

More about the cool process of epigenetic inheritance from the wonderful Minute Earth

youtu.be/AvB0q3mg4sQ

An interview with Riley J. Graham

 

Q. You note in your study, that a carpenter ant colony in nature, maintains a 2:1 ratio of minors to major worker ant. What do you think are the mechanisms for maintaining that ratio? Is it likely to be the same mechanism (HDAC and HAT dependent) as you describe?

It’s difficult to say how this could occur, and there is likely a degree of variation in caste ratio in wild colonies. One of our ongoing questions is whether caste fate can be influenced during development by epigenetic drugs. To address this, we are developing methods to deliver controlled treatment doses to during larval development to determine if this influences caste fate. Such a result would strongly suggest that HDAC and HAT activity is important for regulating the generation of caste specific morphological traits, which could account for how this ratio is maintained in our experimental colonies.

Q. Will the drug reversed majors show increased foraging even when there is an abundance of resources? 

Yes, in fact this is precisely what we saw. All of our colonies were fed ad libitum, for 10 days after injection, and majors treated with HDACi foraged significantly more than controls. However, because minor workers can feed their major sisters after foraging, a mixed caste setting may keep majors full of food even when they never forage. To control for this type of between-caste effect we did a different test in which we separated major and minor workers and withheld sugar water. This ensured all of our test subjects had a similar motivation to exit the nest in search of sugar, and prevented intrinsic behaviors of one caste from biasing behavior of the other.

Q. Have you or others seen such role reversals/ caste reversals in a natural setting? For example – colonies that are stressed for food.

Camponotus floridanus and its relatives in the subfamily Formicinae are interesting because of their discrete morphological caste systems, (e.g. minor, major) but all eusocial insect species rely on some form of caste-based division of labor to survive. Brian Herb and colleagues reported differences in genome-wide patterns of DNA methylation between nurse and forager honeybees. These two groups are behavioral subcastes that arise as younger nurse workers age and progressively become active foragers later in life. Experimental reversion of foragers back to nurses caused a coordinated reversal of DNA methylation to reflect this behavioral change, suggesting epigenetic regulation of behavior is a common trait among social insects, and that behavioral castes are sensitive to environmental changes.

Q. What major contribution do you think will come out of studying eusocial insects like ants or honeybees when compared to solitary insects like fruit flies? 

Fruit flies do not exhibit the vast range of behaviors seen in social insects. Over evolutionary time, some eusocial insect species have acquired sophisticated division of labor strategies, enabling colonies to undertake complex collective tasks including nest architecture, cooperative brood care, and even horticulture, as in the leaf-cutter ants Atta and Acromyrmex. Given that single queens can give rise to millions of individuals in thier lifetime, epigenetic regulation, rather than genetic differences between individuals are expected to have an important role in the expression of caste specific traits. We have not found allelic predictors of caste identity in C. floridanus, suggesting that the exceptional phenotypic differences between major and minor workers are likely attributable to epigenetic mechanisms. Eusocial insects are therefore excellent models for the study of how epigenetic changes can contribute to morphological and behavioral variation.

Q. Earlier studies, for example those by Sokolwaski et. al. have shown single locus polymorphisms controlling foraging behaviour in fruit flies. In the light of this evidence, one might think that epigenetic control of foraging behaviour in ants could be an adaptation to their social lives. What do you think?

I believe you are referring to Marla Sokolowski’s work showing that mutations in the gene foraging (for) can lead to differences in foraging behavior in flies. Such polymorphisms might cause variation in foraging behavior in flies, but in ants, this SNP would contribute to increased foraging in all castes, perhaps even the queen. Given that queen foraging would typically be highly damaging to a colony’s survival, this SNP would be evolutionarily suppressed in queens, but could become positively selected for in minor workers. This variation in the fitness landscape between castes is one reason to think that epigenetic regulators could be important when different castes need to express different genetic profiles from a common genome. Molecular heterochrony allows different genes to be expressed at different times in an animal’s life, and while a very young queen might benefit from a SNP causing increased foraging, a mature queen would not. The genome’s ability to activate or suppress genes depending on caste and age is an important aspect of social insect biology that likely relies on epigenetic mechanisms.

Q. Carpenter ant workers in the study are genetically related, which led you to investigate the possible epigenetic mechanisms determining the cast specific behaviours. Would you expect genetic bases for caste identity in species where genetic relatedness among the workers is not as high as the carpenter ants?

A number of studies describing genetic aspects of caste fate also suggest that the interaction of each genotype with the environment influences caste fate. In this light, it seems that genetic variation primarily alters an organism’s likelihood of becoming a particular caste, rather than rigidly determining caste fate. Allelic predictors of caste identity were not found in our ant species, suggesting behavioral and morphological phenotypes in social insects are likely the product of a gene by environment interaction that is facilitated by the epigenome.

Q. Insect colonies are fascinating systems to study genetic links to behaviour. Your study added valuable insights in mechanisms of determination of a caste specific behaviour. How easy (or hard) would it be to study more complex behaviours in other social animals (not necessarily insects)? 

Our work is among the first to look for indications that social insect behavior can be altered by the epigenome without any change in DNA sequence. Ants are a fascinating middle ground between the moderate behavioral variability seen in solitary insects, and the overwhelming complexity of higher order social behaviors, such as the relationships between kin grooming and reproductive hierarchies in primates. As scientists begin to consider more complex social features, they must also consider the vast array of behaviors that can be performed by each individual. In the case of kin grooming, researchers might be compelled to annotate a complex and fluid social network of kin grooming interactions, which may require a model that considers the behavior of each animal, as well as the behaviors of their social partners. This can get complicated quickly. This is not an insurmountable goal, but it is certainly harder to conceptualize and design experiments around. However, any molecular variation in the population that robustly contributes to behavior can hypothetically be measured, so it is not impossible to study organisms with greater behavioral complexity.