Why are obese mice so easy to chase?

Dysfunctional signaling in the brain makes obese mice less active


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.


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.


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!

A sick mouse’s guide to feasting and fasting

When should you feed a starving mouse and when should you just let it be?



Sick mice, especially those infected with bacteria and viruses often display an anorexic response and eat very little. More than 40 years ago it was recognized that mice sick with a bacterial infection die if you force feed them (1). Is this true for all infections? What about viruses? Should we starve a sick pet or colleague?

In a new series of experiments which explores the scientific basis for the old adage starve a fever, feed a cold, researchers have found that food makes things worse for mice with bacterial infection (such as Listeria monocytogenes) but is required for recovery from viral infections (such as influenza) (2).


When a mouse or any host is infected with a pathogen the events that follow can be resolved around 3 types of harm caused by the

i) pathogen itself – related to the number of pathogens, toxins produced by the pathogen etc.
ii) response of the body – collateral damage from the inflammatory response, immune reaction to pathogen, etc., which can often times be non-specific
iii) inability of the body or tissue to repair or take care of the damage

The authors find that it was the third kind – i.e. the ability to cope with tissue damage that ensues when mice sick with bacterial infections are fed and also when mice sick with viral infections are starved. This suggests that in the onslaught by the pathogen, there is a bystander effect upon non-immune tissues caused by host defenses that is a,critical determinant of bouncing back to health.

What did they do and find?

Mice infected with Listeria monocytogenes died when they were force-fed. The pathogen load (bacterial numbers) and defensive/ response molecules secreted by the mouse were not different between the force-fed (test) mice and mice that were not force-fed (control). The authors of the study then used a model for bacterial infection to look at why the mice are dying. In this model, the mice were challenged with a component of the outer membrane of bacteria – this is known to result in a strong inflammatory reaction – and then looked at the effect on mice upon injection of glucose, casein and olive oil. Glucose was found to be the cause of death.

This however is only one part of the story. The researchers then looked at another infection model, of influenza-infected mice, which also display an anorexic response. Here they observed the opposite – that is, if the mice were stopped from using the glucose, they died. In fact, feeding mice made them better. Viruses invoke response pathways, which are distinct from bacteria, so maybe the immune reaction was different between the fed and not-fed mice? Once again the authors ruled both pathogen numbers (viral load) as well as difference in immune responses in both groups. To understand what was causing death in these mice, the authors dissected mice that had been infected with the virus and then were given either normal saline or a molecule that made glucose unavailable to the body. Mice which were starved of glucose had lower heart rate, slightly lower respiratory rate as well as lower body temperatures about a week post infection. This was the first clue that control centres in the brain, which are responsible for these functions, may be affected. The authors extended this finding to a mouse model which cannot mount the normal immune response to viruses and challenged it with a molecular mimic of virus infection (poly I:C). In this mode, they found that when fed a molecule that made glucose unavailable, the mice died.

So why were starving mice dying in viral infections and fed mice dying in bacterial infection models? This work sheds some light on the differences. When the researchers studied glucose uptake in the brain in both models they found that there was glucose uptake in different parts of the brain during viral and bacterial infections. Viruses enter the host cells and use the sub-cellular compartments and cellular machinery to make copies of themselves. One such compartment- known as the endoplasmic reticulum – is needed both by the host cell and the virus to function normally. Infection results in a stress response in this compartment which usually signals to the cell that it should now shut-down (a particular kind of cellular suicide termed apoptosis). In this model of viral infection, glucose helps keep this compartment stress-free and therefore prevents cell death. This is particularly important for cells in the brain. What about bacterial infections then? In the brains of the mice with simulated bacterial infections and glucose injections, the authors find evidence for the accumulation of reactive oxygen species (ROS) in the brain. These molecules are also potent inducers of the cellular suicide pathways. However, the authors note that in this case, it may not be death of brain cells, but their dysfunction that may be the cause of death. This still does not explain the difference between viral and bacterial infections. To get to this, the authors analysed the starvation response. During starvation, the utilization of fats and proteins results in accumulation of ketone bodies, an important alternative fuel source during fasted states, via ketogenesis. Excessive and prolonged accumulation of ketone bodies is known to be toxic for the body. In the case of bacterial infection, this study suggests that the availability of ketone bodies may be helping cells to detoxify ROS.

Take home from this study

This study gives us a new way of thinking about infections, host response to infection (immunity) and the rest of the organs and tissues in the body, particularly the brain which must keep working normally through the pathogen-host cross-fire. There are clearly many unanswered question that this opens up, and while it demonstrates that glucose plays different roles in viral and bacterial infection of mice, the underlying mechanisms still remain to be understood in detail. It is interesting that the main difference of glucose utilization seems to be in the brain. The processes that connect what we eat, to what our body makes of it to how we feel or behave form a fascinating network with new links emerging all the time. It is not too soon to have convictions on what is good for us, our colleagues, our pets or our mice, but it is too early to really know or accept information without doubt.


1. Anorexia of infection as a mechanism of host defense.” M J Murray and A B Murray , Am J Clin Nutr. 1979

2. Opposing Effects of Fasting Metabolism on Tissue Tolerance in Bacterial and Viral Inflammation,Andrew Wang et al., Cell. 2016

An interview with L.Harding, S.Huen and A.Wang

Q. The idea that the there is tissue tolerance to injury caused by a pathogen-host battle seems reasonable, can you tell us more about the evolution of this idea and its implications for how people now view disease? Are there biomarkers of tissue tolerance?

The idea evolved from the recognition that oftentimes in sepsis, the immune response is more detrimental to the host than the damage incurred by the pathogen. The robustness of a tissue’s ability to tolerate inflammatory challenge can be measured by the ability of tissues to perform their function during inflammatory challenge. Clinically, physicians use plasma biomarkers of tissue dysfunction—for example, troponins for cardiac dysfunction, creatinine for kidney function, transaminases for liver function—as surrogates for tissue function.

Q. How easy or hard is it to distinguish between bacterial and viral infections in a clinical setting – in humans? Are there good diagnostic tests for this?

It is currently very difficult to distinguish the type of infection at the time of admission. This is an area of active research. Currently, clinicians rely on biomarkers such as procalcitonin, which have poor specificity for infection type, and/or detection of the pathogen itself, which often takes many hours if not days to verify, if at all.

Q. What about mixed infections? How do mice respond to a mixed Listeria and Influenza infections? Your group has explored this co-infection model previously, do you understand it better now?

Historically, it has been observed that mixed infections are worse for the host than either of the infections separately. The most famous example is influenza infection followed by a staphylococcus aureus infection. We have previously looked at influenza followed by listeria monocytogenes, and then at influenza followed by legionella pneumophilia. Generally, it appears that viral “priming” potentiates severe disease from otherwise sublethal challenges with bacteria. The mechanisms operating in these different infection pairs was different, but we are trying to understand if there are more general principles that could make this specific sequence of virus then bacteria more lethal.

Q. Do you plan to study this in humans? If yes, then how would you control for cultural variables, the availability of food and the process of habitual eating that many human beings now live by?

We do plan on studying this in humans. The setting where much of this can be best controlled is the intensive care unit (ICU). In patients admitted to the ICU, many are unconscious for one reason or another. Currently, these patients are fed by tube feeding very shortly after they are admitted. The goal of our initial studies will be to see if restricting glucose in feeds delivered to individuals with documented infections would be better for their outcome compared to standard formula feeds.

Q. Do you suspect that there is a strong genetic component to tissue tolerance, set-points or points of no return?

There is likely a strong genetic component to tissue tolerance. Since the immune response has been subject to great selective pressure, it should follow that tissue response to inflammatory signals generated by the immune response would also be under the same selective pressures, especially because it is ultimately tissue dysfunction that leads to death and thus the inability to transmit genetic material. However, because the field of tissue tolerance is relatively unstudied, no studies that try to identify those genetic components exist.

Q. Is the brain the most vulnerable organ – as opposed to say the kidneys which flush out toxins from the body, in terms of coping with damage from an infection? Did this finding surprise you?

In any injury, there is usually an organ or small set of organs, which, if dysfunctional, becomes limiting for the organism’s survival. The limiting organ in turn depends on the type of insult. In general, if the heart, lungs, or brain fail, it is rapidly lethal for the host in the absence of medical intervention. There is a lot of precedence for central nervous system dysfunction in bacterial sepsis, but we were surprised to find that the brain also appeared to be limiting in our influenza model, which is primarily a lung-injury model.

Q. For some bacterial diseases, tuberculosis is a case in point, we know that malnutrition makes the condition worse. How do you reconcile these observations with your finding?

There is a big difference between acute infection and chronic infection. What we were studying was the response to acute self-limited infections. In chronic infection, the persistence of the inflammatory response, persistence of the pathogen, and the changes that this dynamic imposes on the host is very different than the acute phase response. So, it is likely that the metabolic requirements of chronic infections are very different from the metabolic requirements of acute infections. Also, even in the acute setting, bacteria have co-evolved with their hosts and in the process may have developed mechanisms that interfere with the tissue tolerance mechanisms that we have described here. Therefore, our current work may not be generalizable to the full spectrum of bacterial and viral infections.

Frigate birds keep their eyes wide open during flight – most of the time!

Sleep patterns of flying birds

Snap-Shot of the study

Birds fly enormous distances during migratory flight. It seemed reasonable therefore to think that birds sleep while flying, especially since birds can go to sleep -one brain-half at a time.

But then, how can they function and be attentive to the demands of flying, foraging, avoiding predators, finding their route, often over water, over such long periods of time? Imagine the frigate birds with the wind on their wings as they begin their flight across the ocean, flying continuously and majestically for upto 2 months! In an elegant and well written piece of research, the authors find that frigate birds sleep very little during their long flight (1). By recording brain activity in flying birds, the authors show for the first time that these birds take short and light naps but mostly forgo sleep during migratory flight.

Background to this study

A single late night is enough to send most adult humans into a downward spiral the next day, fruit-flies that don’t sleep have their lives cut short (2-4). Birds however have been shown i) to go on long flights without resting (5) ii) to sleep uni-hemispherically – single eye open – keeping one part of the brain alert to the requirements of the environment while the other part rests (6). iii) are able to function more or less normally even when deprived of sleep (7)

So what happens during flight? Given the high energy/metabolic demands of flying the need for rest and sleep must be high, on the other hand the need for attention is also high during flight, can birds afford to sleep on the wing? One way to find out is to record the patterns of brain activity in migratory birds during flight and look for patterns of sleep and wakefulness.

What did they do?

In this study (1), sleep patterns of 15 female great frigate birds flying over the Pacific Ocean and after returning to their nest on Genovesa Island (Galápagos) were recorded using implanted devices that measured brain activity (EEG – electroencephalogram), movement of the head as well as acceleration. No behavioural differences were observed in the birds with implants during and after removal of the devices. Using these devices, the researchers measured movement of the bird, acceleration, deceleration, flapping of the wings and brain activity near the primary visual area and also collected data on weather conditions. Measuring movement of the head allowed them to separate patterns formed by head movement from actual changes in brain activity.

What did they find?

The overall EEG patterns were similar in the birds on land and during flight, allowing the researchers to look at duration and intensity of sleep. They describe three sleep-awake states roughly – wakefulness, rare episodes of REM sleep (like in humans, this is deep sleep characterized by rapid eye movement) and slow wave sleep – this is the most frequent type of sleep described in birds which can be bi-hemispherical or uni-hemispherical or assymetric (6).

During the day, the birds showed patterns of wakefulness (fast head movements together with high amplitude signals in the EEG), even at night during flapping of wings wakefulness patterns were observed. These were interspersed with slow waves which the authors identify as slow wave sleep. Rarely, between bouts of slow wave sleep, short bursts of deep sleep or REM sleep patterns characterized by dropping of the head, and twitching were also observed. Interestingly, birds ascended in altitude during slow wave sleep and descended during wakefulness. All types of slow wave sleep, including unihemsipherical, asymmetrical (when one hemisphere was more active than the other)  and bihemispherical slow wave sleep were observed during flight. There was an increase in asymmetric sleep in flight than on land but this was not correlated with any one type of movement.

Overall, frigate birds seemed to sleep very little during flight – in shorter bursts and less soundly –  a homeostatic balance was restored when these birds landed. Further, preliminary evidence from this study suggests that these bursts of sleep are enough to sustain the birds during flight.

Why is this interesting?

The very fact that these birds are able to accomplish Himalayan tasks such as follow migration routes, feed themselves, with such low levels of sleep suggests that, at least for frigate birds, sleep may be dispensable during flight. Are they postponing this need? What sort of adaptations allow them to postpone sleep or perform sleeplessly? This study is a step towards understanding adaptations to lack of sleep and perhaps a way to understand the very nature of sleep itself.

1. Evidence that birds sleep in mid-flight. Rattenborg NC, Voirin B, Cruz SM, Tisdale R, Dell’Omo G, Lipp HP, Wikelski M, Vyssotski AL. Nat Commun. 2016 Aug 3;7:12468. doi: 10.1038/ncomms12468. PMID: 27485308

2.Reduced sleep in Drosophila Shaker mutants. Nature. 2005 Apr 28;434(7037):1087-92  Cirelli C, Bushey D, Hill S, Huber R, Kreber R, Ganetzky B, Tononi G.

3. Genetics of sleep and sleep disorders. Cell. 2011 Jul 22;146(2):194-207. doi: 10.1016/j.cell.2011.07.004. Sehgal A, Mignot E.

4. http://www.curiouscascade.com/blogpost/clocking/

5. Frigate birds track atmospheric conditions over months-long transoceanic flights. Science. 2016 Jul 1;353(6294):74-8. doi: 10.1126/science.aaf4374. Weimerskirch H, Bishop C, Jeanniard-du-Dot T, Prudor A, Sachs G.

6. Half-awake to the risk of predation Nature 397, 397-398 (4 February 1999) | doi:10.1038/17037 Niels C. Rattenborg, Steven L. Lima & Charles J. Amlaner

7. Adaptive sleep loss in polygynous pectoral sandpipers. Science. 2012 Sep 28;337(6102):1654-8. Epub 2012 Aug 9 Lesku JA, Rattenborg NC, Valcu M, Vyssotski AL, Kuhn S, Kuemmeth F, Heidrich W, Kempenaers B.


An interview with Alexei Vyssotski

Q. Can you tell us a little more on how you determined that the birds were sleeping? How did you identify the pattern corresponding to sleep when you got all your recordings?

Sleep was identified by visual inspection of 4-sec episodes of raw EEG records. Slow-wave sleep is characterized by large amplitude low-frequency oscillations in EEG. These episodes are easily-detectable. Visual scoring was used because automated methods of sleep staging can’t separate properly large-amplitude EEG events from movement artifacts in all cases. Locomotor artifacts can have similar amplitude to slow-waves during in sleep.

Q. Do you think these birds sleep a lot during an annual cycle? Do migratory birds tend to sleep longer than non-migratory birds on average – there must surely be some compensatory mechanisms?

We have found that frigatebirds sleep on average 9.3 hours per day when on land and only 0.69 hours per day when flying. We did measurements only during breeding period. While the frigatebirds live in equatorial area with relatively small weather seasonal changes, one can suppose that the duration of sleep is linked stronger with the pattern of animal activity than with the time of the year per se. It is known that migratory species can stay on the wing for a long time. Extrapolating our findings to these species one can suppose that they should sleep in the flight smaller amount of time than on land, and might compensate migratory sleep loss on land later like our frigatebirds did. However, the compensatory increase in sleep duration and intensity upon landing after the trip is relatively small comparatively to missed amount of sleep on the wing. One can speak only about partial compensation of sleep loss. The birds have, probably evolutionary formed, an ability to stay without sleep significant amount of time without physiological dysfunctions. Unlike most mammals, the birds do not have so called sleep-deprivation syndrome. If a rat will be forced to stay without a sleep for significant time, it will die, but a homing pigeon can stay month-long awake and still behave properly. Migratory birds definitely reduce amount of sleep during migration, but whether they sleep longer than non-migratory birds in other situations is difficult to say.

Q. Do you think that migratory birds produce neurochemicals that resist the urge to sleep or have special brain structures?

The neurochemistry of avian sleep is investigated in much less extent than mammalian sleep. To the best of my knowledge, no special anatomical structures that are responsible for sleepless in birds have been discovered. It is assumed that the avian sleep control brain system is similar to mammalian. However, additional studies are needed to check how strong this similarity is indeed and what are the differences.

Q. Does the slow sleep wave recordings refer to the activity of only certain regions of the brain?

No. It is assumed that like in mammals, the vigilance states in birds are controlled by deep brain structures that modulate activity of superficial brain regions in a synchronous manner. However, contrary to most of mammals that have only bi-hemispheric sleep, the birds have so- called unilateral sleep, when one hemisphere is sleeping and another is awake. Thus, the avian brain hemispheres are more independent from each other than mammalian. One should note that the phenomenon of “local sleep” has been also discovered in birds. This means that if a particular region of the brain has been used intensively in a wake state, the slow waves of increased amplitude will be observed during the following sleep in this brain area.

Q. Did you have independent recordings of some of the parameters using a high speed camera to set the baseline for each bird?

Do you mean Ca2+ brain cells imaging? No, we did not do this, but of course, if would be nice to monitor how activity of different cells ensembles changes in sleep in birds. The recently developed head-attached microscopes can help to film brain in freely behaving animals.

Q. It is astonishing that you got so much information that you could put together, did you expect that when you captured the 15 birds? What were the unexpected challenges in the study?

That is true, this time we collected more information than in our previous studies. We alreadyhad experience with EEG and GPS logging. This time we compensated luck of GPS precision by the acceleration data to reveal the flight mode of the animal. 3-D acceleration data practically doubled the dataflow, but this was not a problem to log in 1 GB onboard flash memory. We did not predict the particular way of the data analysis in advance, but observing three-modal distribution of sway acceleration leaded us to separate analysis of EEG in three different flight modes (straight flight, circling to the left and to the right). The real challenge was to master the surgery and handling in an animal-friendly way to have the birds back with the equipment. Indeed, the rate of return 14 from 15 birds exceeded our expectations. To be honest, I expected larger losses and was very happy when returns exceeded 50%.

Q. Have you been to the Galapagos? What is it like to do research in that setting? Do you think that nearly 180 years after Darwin’s voyage, the biodiversity of Galapagos still holds new discoveries?

Yes, I have a real luck to spend a week at the Darvin station in Santa Cruz and then a week on Genovesa island working in the bird colony. My colleagues Bryson Voirin and Ryan Tisdale spent two weeks more waiting for birds return. This is the best place for animal study that I have ever seen. Wild birds behave almost like tame animals there and do not run away from humans. Thus, it is easy to handle them. This is, of course, one of the features that attracts biologists. The biodiversity of these islands is definitely not studied completely and will attract scientists for a long time.

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.


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

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


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.