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!

A sick mouse’s guide to feasting and fasting

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

 

Summary

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).

Introduction

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.

References

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.

Can genetic variations define Ayurvedic Prakritis?

-A genome- wide study finds allelic differences between individuals that correlate with Ayurvedic body-types (Prakritis)

Snap-Shot of the study

Do the ayurvedic body types have genetic underpinnings? In a first step to answer this question, the authors evaluated differences between individuals whose body-type had been assigned by both Ayurvedic practitioners and a software. They found 52 variations across the genomes of 262 individuals which allowed them to be classified into ayurvedic Prakritis – Pitta, Kapha and Vata.

 Introduction to Ayurvedic prakritis

In Ayurveda, according to the ancient text Charaka Samhita –the body and mind must be brought together to lead a harmonious existence. People can be classified into Prakritis or types on the basis of relative contribution of the three constituents Pitta, Kapha and Vata (roughly translating to – arising from movement, digestion and accumulation – of toxic metabolites for instance) to their body. According to Ayurvedic philosophy- an understanding of this body type and the ability to maintain a diet and lifestyle suited to that body type translate to balance and health. Prakriti or Ayurvedic body-types which define a person’s intrinsic physical abilities, mental states and also have implications for their susceptibility to disease and response to drugs (1,2).

Background for this study

In a recent study (3), researchers have identified genetic variations associated with the traditional classification of people into Ayurvedic Prakritis – specifically if small differences (SNPs, Single nucleotide polymorphisms) throughout the human genome correlate with the Prakriti classification. All humans are genetically very similar to each other, differences between us (populations, races, ethnic groups etc.) are captured in variations of nucleotides which make up the DNA – these are called single nucleotide polymorphisms. Many studies have shown particular SNP or group of SNPs to be correlated with risk of disease, whether a person will develop resistance to therapy, etc. forming the basis for personalized medicine  (4,6).

 What did they do?

3416 individuals were classified for their prakritis by Ayurvedic practitioners as well as a software. Of these, DNA isolated from blood samples of 262 individuals (male, healthy, between 20-30 years), who were reliably classified as having a clear dominance of one of the three constituents (Vata, Pitta or Kapha) representing the “extreme” Prakritis were used for the genome-wide study. A microarray consisting of 1 million positions / SNPs was used to identify the genotype of these individuals.

 What did they find?

This study found 52 out of 1 million SNPs is sufficient to assign the Prakriti of individuals, irrespective of their ethnic background. One of the challenges in the study was that there was no control group – therefore each prakriti was compared to the other two. Subsequently, these 52 SNPs were able to cluster individuals into distinct groups by Principal Component Analysis. Interestingly, one of the SNPs in a PGM1 gene (Phosphoglucomutase 1), which codes for an important enzyme in sugar (glucose) metabolism, is significantly associated with Pitta dominant group that is known for efficient metabolism.

 Things to keep in mind about the study:

It is to be noted that the three categories compared and defined here represent extremes –and according to Ayurvedic principles most people are a composite of all three- Kapha, Vata and Pitta, with the dominant element defining their type. There are some previous studies, which have suggested that the Ayurvedic Prakriti classification may have a genetic or metabolic basis (2,5). They were conducted on fewer subjects and looked at fewer genes/ phenotypes compared to this study, which rigorously recruited a large number of subjects, used multiple methods of classifications (software and Ayurveda practitioners) and a genome wide approach. There is much work to be done in understanding the scientific basis of the Ayurvedic classification system and whether we can independently and reliably assign people (independent of race, gender and ancestry) to a type.

 What does this mean?

The 52 SNPs defined in this study can now be used independently in other populations and also provide a way of identifying new associations with metabolism and other phenotypes. For more than fifteen years now, we have been able to read our genome i.e – information in our genes but not been able to fully understand how it defines us as individuals. So on the one hand, this study by correlating phenotypes with genetic variations, helps us understand a little bit more about how genes make us who we are. On the other hand, by using modern genetic tools in the context of traditional knowledge, this study provides a rigorous way of assessing the framework of ayurvedic medicine.

Citations

1. Understanding personality from Ayurvedic perspective for psychological assessment: A caseS Shilpa and C. G. Venkatesha Murthy. Ayu. 2011 Jan-Mar; 32(1): 12–19.

2. Classification of human population based on HLA gene polymorphism and the conceptof Prakriti in Ayurveda. Bhushan P 1 , Kalpana J, Arvind C. J Altern Complement Med. 2005 Apr;11(2):349-53.

3. Genome-wide analysis correlates Ayurveda Prakriti. Govindaraj P, Nizamuddin S, Sharath A, Jyothi V, Rotti H, Raval R, Nayak J, Bhat BK, Prasanna BV, Shintre P, Sule M, Joshi KS, Dedge AP, Bharadwaj R, Gangadharan GG, Nair S, Gopinath PM, Patwardhan B, Kondaiah P, Satyamoorthy K, Valiathan MV, Thangaraj K. Sci Rep. 2015 Oct 29;5:15786. d

4. A database of humans SNPs and their recorded associations can be found here: http://www.snpedia.com/index.

5. Whole genome expression and biochemical correlates of extreme constitutional types defined in Ayurveda . Prasher B, Negi S, Aggarwal S, Mandal AK, Sethi TP, Deshmukh SR, Purohit SG, Sengupta S, Khanna S, Mohammad F, Garg G, Brahmachari SK; Indian Genome Variation Consortium, Mukerji M. J Transl Med. 2008 Sep 9;6:48.

6. http://www.scientificamerican.com/article/a-very-personal-problem/

Interview with Dr. K. Thangaraj

Q. What was the overlap between the prediction by the software, by different Ayurvedic practitioners? Have you tried to estimate if this classification is robust enough to suggest underlying genetic differences?

The first assessment was by Ayurvedic physicians and classified using their knowledge. To double check what they have done, we have used a computer software. The software is also based on various parameters specified by the Ayurveda physicians.There were many questions which the individual had to answer to be assigned a Prakriti. Across the three centres – Bangalore, Pune and Udupi, on average, 75% of the individuals were in concordance.

Q. Why not perform an enzyme profile or measure transcriptional differences for metabolic enzymes? Is there an advantage in taking an SNP approach?

The advantage is that the SNP does not changes, it is there from birth till the individual dies. Whereas transcription profiles may change at different times, depending on time of day, tissue type to tissue type etc. We have looked into that also. This is the very first step. We can extend this across countries, across ethnic groups and cluster them.

Q. Ayurvedic medicine believes in holistic changes including those of lifestyle, dietary along with medicines and does not rely overly on mechanistic explanations beyond the classification into types. There is less emphasis, if you will on dissection of cause-effect and more on restoring the overall balance. Do you agree with this? If yes, then what are the challenges with respect to the study design when you tried to apply the modern framework of science- which relies on a reductionist approach, finding a cause and targeting only that specifically, to the ayurvedic system?

I agree that there is a holistic approach, but the basic approach is to classify the individual. Based on the prakriti, they will make the changes to the diet, prescribe treatment etc., so this is a very important stage. The challenge is the following- I am a geneticist looking at diseases,looking at case-control studies is very easy – for every marker we can ask if the mutation is present or if the prevalence is higher in the patients versus the control. In this case all the individuals are normal and within the same age-group. The only difference is the prakiti. So we wanted to see how to differentiate these individuals- as there are three groups, not two. Then we decided to compare one prakriti against the other two types, and try to see if there is genetic variation between the groups. Then there was a lot of statistical analysis. We used 1 million markers, this has many advantages, the disadvantage is the robustness and having to come up with statistical analysis ourselves. (MT: So, by using 1 million regions, you may increase the chances of false associations, is that the worry?) Not, really false associations. For example we may not have information about a particular SNP in an individual. We need to use markers that are consistent between all the individuals. So, when data is not available, we need ways of retrieving the data. In that process we need to use genetic panel of markers which are Indian specific. We developed our own panel of markers – Dravidian, Indo-European and used as a reference and to extract what is the possible marker in a given position.

Q. Have you tried to validate your classification using the 52 SNP panel with an independent population? For instance, if you knew what a person’s SNP state is, how reliably can you assign their Prakriti? Would it be useful to perform a blind study in which both the SNP panel ayurvedic practitioners and the software performed the classification, with the aim of determining how often they match?

That is very interesting. What we did was, we has more than 300 samples analyzed for these 1 million genetic markers, from our initial studies on population genetics. We used some of those samples, as these are all populations specific – a very endogamous population. We tried to project some of those individuals into these three clusters, we did find that although the individuals have come from the same ethnic background (more homogeneous), they were falling in 2 or 3 different prakritis. The same ethinic background can be placed into different prakriti. This we tried to do with our own data, this is not as detailed as you suggest. Independent blind studies need to be done.

Q. You have excluded women from your study and restricted yourself to the Indian population, does this limit the applicability of your results?

Yes, of course. At this point we selected only males because we did not want any confounding effects, in the females there are many hormonal changes and so on.

Q. You have started a way of examining traditional medicine in the framework of modern science. What are the challenges and the future of this approach?

(The future of this approach) This has paved the way to do many more things. For example, the discovery of PGM1 has given the clue that you can take the phenotype of the particular prakriti and correlate it with the gene, this gene is involved in metabolism and individuals with the pitta prakirti have high metabolism. We can now use the characteristic feature of the prakriti and look into those genes in a detailed way. These are some of the futuristic aspects, one can take the study further with. We did try to look at the network of all the metabolic pathways genes, the problem is this will need transcription or metabolic profiles from tissues of these normal individuals.

 

Emulsifiers bring gut bacteria too close for comfort

Feeding mice with artifical emulsifiers impacts their metabolism

Snap-shot of the study

Emulsifiers are used extensively in the food we eat (ice creams, biscuits etc.). This study examines the effect of feeding mice emulsifiers both in their food and drink (5).

Mice fed on emulsifiers (Carboxymethylycellulose CMC and Polysorbate P-80) showed increased appetite. They also showed signs of low-grade inflammation in the gut and increased fat deposition. The authors attribute these effects to changes in the gut microbiota. While the number of microorganisms in the gut was not altered by diet containing emulsifiers, the kinds of microbiota were completely different. The mucus lining was also depleted and the microbes were closer to the cells in the gut, possibly causing the inflammation. While this study has been done on mice, perhaps the quality and quantity of our microbiota and their response to emulsifiers has some bearing for us too.

What did they do?

 

They added widely used  emulsifiers- Carboxymethyl cellulose (E466) and Polysorbate-80 (E433) to the food and drinking water of young mice at equivalent concentrations commonly used in human food.

They measured the abundance and diversity of the gut microbiota, inflammation of the gut (colitis) and also metabolic disorders (fat accumulation, increase in food intake and fasting blood sugar levels) in the emulsifier-fed mice and compared to control mice (no emulsifier in food or drink)

 

What did they find?

These mice (treated) had same number of bacteria (in their gut) compared to mice that were not fed emulsifier (control mice). The types of microbes however was quite different. The microbes were also found closer to the gut that in control mice. The treated mice showed increased appetite, followed by  fat deposition and low grade inflammation of the gut. Interestingly, transplantation of the microorganisms of the gut from emulsifier fed animals into germ-free mice also resulted in increased fat deposition and inflammation of the gut. Suggesting that changes in the microbiota caused by the emulsifiers may be sufficient to cause the metabolic dysfunction and observed inflammation.

Erosion of the protective mucosal layer around gut epithelium in emulsifier-fed mice resulting in reducing the separation between the microbiota and the gut epithelium. Emulsifiers caused a marked change in gut microbiota composition – Higher pro-inflammatory microbiota including the bacterial species that are the leading cause of colitis like Bilophila and Helicobacter. Changed gut microbiota in emulsifier-fed mice increased gut inflammation and colitis. Emulsifier-fed mice also show – dysregulation of blood sugar levels (mild diabetes), increased food consumption correlated with increased adiposity(fat deposition) and weight gain. In older mice (4 months old) the changes persisted for more that 6 weeks even after emulsifiers were stopped. The observed effects of emulsifiers are exclusively due to the change in gut microbiota as the emulsifiers did not show any effect in mice having no gut microbiota (germ free mice). Interestingly such germ free mice become labile to the effects of the emulsifiers if the regular gut microbiome is reintroduced in them.

 

Background to the study

An undisturbed gut flora is emerging as an important factor in health versus disease (1). Multiple different physiological conditions including obesity and type 2 Diabetes are now associated with changes in the gut microflora (2-3). Recent studies have found that artificial sweeteners can cause blood sugar related disorders in humans (4).

 

Take-home and implications

This necessitates a reevaluation of what goes into our food, how it affects our gut microbiota and our health. Standard food safety tests include toxicity and carcinogenicity (ability to cause cancer), however, the importance not perturbing the natural flora of the intestine is becoming clear only now. These findings suggest the following in mice- intake of food/drink containing emulsifiers leads to weight gain and disorders such as diabetes, by directly increasing food intake. These findings need to be verified in humans.The intriguing  realization that dawns on someone after looking at this study is that not just the quantity, but also the quality of the microorganisms in the mouse gut matters. In humans the importance of gut microbial diversity has been documented in other contexts (1-3, video below – courtesy MinuteEarth)

Limitations and Open Questions

Only 2 synthetic emulsifiers have been tested. We feel that this work makes a strong argument for the development of assay systems that monitor microbial health (especially gut microbes) for compounds added to food, medicines etc. Given that the findings have such strong implications, we hope to see in the future a wider spectrum of compounds (including  the more natural products like lecithin) examined similarly by the authors and others.

The authors have only discussed in brief the possible mechanism underlying the change in the microbial population or how these changes result in increased inflammation. This remains a major open question.

Germ free mice already have a really bad situation in their gut, they are somewhat prone to inflammation. It is important to bear this in mind while interpreting the results of the fecal transplantation into germ free mice.

The study is a mouse study, it remains to be extended to humans.

An interview with Dr. Andrew Gewirtz

Q. From your work, it is clear that altered microbiota could lead to weight gain, fat deposition and the loss of the ability to control blood sugar levels, can this be reversed by altering the microbiota?

Our studies in mice indicate it is reversible but it takes some time.

Q. How do you think the emulsifiers are changing the gut microbiota? Can you elaborate on some potential mechanisms?

They seem to promote bacteria breaching the mucus, which promotes inflammation, which changes bacterial populations, possibly by favoring detrimental bacteria.

Q. Are you suggesting that the normal gut flora under different conditions (presence absence of emulsifiers) could turn pro-inflammatory? Are the other missing microbiota (in the presence of emulsifiers) keeping them in check under normal circumstances?

Yes

Q. What according to you are the major caveats of your study?

It is a mouse study.

Q. Did you face challenges in publishing this work, given that it has such strong implications?

Some reviewers suggested a dialog with food industry prior to publication but we argued our tax payer funded research did not require such approval. Nature editors agreed with us.

Q. Do you plan to take this study forward in humans? What would be a suitable cohort for such study?

Yes. Probably start with healthy college students.

Q. Your work clearly has implications for how we decide what to put in our foods.. What Changes would you suggest to the current process by which such compounds are screened, approved and used?

I think major overhaul is needed. Both more tests are needed and more information made readily available to consumers.

Q. Has your study affected your life and food choices?

Yes, my family has cut our consumption of processed foods in general and emulsifiers in particular.

Related Viewing

Teixobactin: Can this new antibiotic help us sail through the doldrums of drug resistance?

iChip based discovery of a potent novel antibiotic

 

Why do we need a new antibiotic?

What can happen if you self-medicate on an antibiotic or do not finish a course of antibiotics that has been prescribed for you? When cattle are fed indiscriminately on antibiotics to keep them healthy? When sewage from hospitals is not completely treated and released into the community? The microbes that survive in these environments stop responding to antibiotics around them (1). Our world at present faces a daunting task of treating people infected with resistant forms of many bacteria. Often clinicians have to resort to potent broad spectrum antibiotics to treat infections that could be treated with the first line of drugs a few decades ago. The other aspect of the problem of antimicrobial resistance is the lack of new treatment options. Many of the current antibiotics are chemical modifications of ones that are known to work. Designing completely novel molecules, with antibiotic activity, synthetically, has not been very successful (2). In this rather bleak situation a new study brings a new ray of hope. In this study the authors have enriched hitherto uncultivated bacteria from the soil (3).

 

What is so special about this?

A very small percentage of bacteria in the soil can actually be grown in the laboratory (4). The development of tools/methods to grow more bacteria opens up a window for isolating new compounds with potential antimicrobial activities that these bacteria may be producing to their advantage in the complex niche of the soil. In this study, the authors diluted soil sample to contain single cells and grew them in special chambers embedded in the soil which allow for nutrient exchange with the soil. Earlier studies have shown this method to recover 50% of the bacteria from the soil. Previous studies have also demonstrated that once isolated, many of these bacteria can be grown in the lab.

 

How was this antibiotic found?

After screening over 10000 bacterial isolates in this way Ling et al., identified a new species Eleftheria terrae that produced a potent compound against Staphylococcus aureus (S. aureus can cause infections especially in hospitals, it also notorious for acquiring resistance to commonly used antibiotics). They examined this compound in greater detail, asking questions like- what does it look like (chemical structure)? How is it made in the bacteria (biosynthetic pathway)? To answer these questions, they undertook detailed chemical analysis by NMR and Marfeys’ structure analysis. The active compound which the authors named Teixobactin, was found to be a uricylated oligopeptide (the details of the structure are provided in the paper). They analyzed and were able to predict the pathway by which the E. terrae makes this antibiotic. The compound was found to be completely novel.

 

How does it work?

How does this antibiotic kill the target bacteria? The first clue was that it was more effective against gram positive that gram negative bacteria. These two classes  (distinguished on the basis of their appearance after staining them with dyes) of bacteria differ in the number and nature of protective coverings around them. Gram positive bacteria have a thick cell wall around them, whereas gram negative bacteria have a thin cell wall but also have an additional outer membrane. The cell wall is made up of repeating units of modified sugars known as peptidoglycan and is essential for structural integrity of bacteria. A breach in this structure would lead to the bacterium’s death. Interestingly, Teixobactin is not active against gram negative bacteria which have an outer membrane. However, a strain of E coli (a gram negative bacteria) with defects in the outer membrane is susceptible to this antibiotic. These data suggest that Teixobactin needs to have access to the bacterial cell wall for its activity. Consistent with this idea, they find that Teixobactin binds specifically to precursors of peptidoglycan and does not allow their incorporation into the cell wall. Instead of targeting the enzymes that carry out cell wall synthesis, Teixobactin, like the potent antibiotic, Vancomycin, interacts with structural components of the cell wall itself. It seems to target multiple precursors and bacteria die not only from lack of cell wall but also from accumulation of toxic intermediates of cell wall synthesis.

 

Does it work against pathogens?

They then asked, how effective is this antibiotic against common pathogens? Teixobactin was found to have potent activity against Staphylococcus aureus (which can cause disease under certain circumstances), Clostridium difficile (causes colitis) and Bacillus anthracis (anthrax). It also had good activity against hard to treat microorganisms like Mycobacterium tuberculosis (Tuberculosis) and enteroccocci (are intrinsically antibiotic resistant, causally associated with urinary tract infection among others). All of this is good news, however, how do we know that once in use, bacteria will not become resistant to Teixobactin? One way to answer this question is to subject bacteria to low levels of the antibiotic for prolonged period and then test if they still respond to it. Fortunately, no resistance to Teixobactin  emerged in either M tuberculosis (M Tuberculosis is notorious for acquiring resistance to multiple drugs) (6) or S aureus. Suggesting that resistance will probably be slow to evolve  against this antibiotic. The next step then was to assess if it was toxic to animal cells and/ or effective when used in animals.

The compound was found to be eminently suited for being used as a drug in animals. It was not toxic to mammalian cells, was active even in the presence of serum and was stable in  blood. Moreover, Teixobactin seems to have no carcinogenic properties. In mouse models of septicemia and pneumonia, mice treated with Teixobactin survived and responded well to  treatment. This makes Teixobactin a remarkable candidate for further studies with the  possibility of clinical trials in humans.

 

What does this finding mean?

The approach used to isolate and characterize Teixobactin is novel and paves way for the identification and characterization of many such compounds. We think that this may well be the beginning of a mining exercise where we explore more antimicrobials from the soil. It remains to be seen if Teixobactin can actually be used in humans, it is unclear how long that will take or last. At the very least, Teixobactin offers a tempting glimpse of what’s hidden in the soil and gives us a better appreciation for the microbial community we nonchalantly read upon.

Why are we more likely to get a cold in cold weather?

Summary

We don’t really know, what we do know is that some cold causing viruses grow better at lower temperatures. Rhinoviruses, one of the most common causes of the common cold, display a temperature dependent growth pattern. They were shown to grow better at cooler temperatures (33°C­ – 35°C)​ (1,2) like that in the upper respiratory tract than at the core body temperature of 37°C. Scientists hit a wall when they looked for a reason for this by analyzing the viruses themselves. Entry of the virus inside the cell, for instance, was not affected at cooler temperatures (33°C- 35°C). The failure to find a convincing mechanism such as a temperature dependent viral enzyme or gene product was puzzling until recently, when scientists turned the table and started looking at the virus infected cell rather than the virus itself.

More about the study

A study published in the Proceedings of the National Academy of Science (PNAS) looks at cellular defense mechanisms and anti­viral responses that come into play when Rhinoviruses infect cells (3). ​

​The authors of this study compared the response to infection at the warmer body temperatures (37°C) and at cooler temperatures as found in the nasal cavity (33°C).

In what we think is the first step to understanding the role of the host (human) in this process, this study used a mouse adapted strain of the virus. They generated this strain by growing the virus for many generations in mouse cells. Subsequently the virus acquired mutations, adapted and was able to infect mouse airway cells. Foxman et al., isolated mouse airway epithelial cells and used the adapted strain to infect these cells in the laboratory. In order to test the temperature sensitivity, they carried out infection experiments at 33°C (cooler) and 37°C (warmer) temperatures. They observed the expected decrease in number of viral particles (titers*) starting from 7 hours after infection at 37°C but not at 33°C, confirming that temperature does impact viral numbers. The changes observed were in fact in the infected cells which showed a lower antiviral response to the virus at cooler temperature.

When a cell gets infected by a virus, it puts out a signal saying “I am infected” by secreting molecules such as interferons and this is critical for mounting an antiviral response​ (4)​. The study by Foxman et al., shows that cells infected at cooler temperatures have lower expression of molecules critical to the anti­viral response. The authors artificially activated a defense pathway (The RLR pathway) which results in interferon production, and show that this pathway has a lower response at 33°C than at 37°C. In other words there is lower production of interferons, at cooler temperatures. Further, by genetically mutating either molecules of this pathway or a receptor of interferon in mouse airway cells, the authors find an increase in viral titers even at warmer temperature (37°C).

These data suggest the cells may be able to ward off a Rhinovirus infection at warmer temperatures (37°C) due to a robust anti­viral response resulting in the production of interferons. In the nasal epithelium which is in constant contact with the outside air, the temperature of the cells is likely to be low enough for Rhinovirus to get away with a successful infection. Rhinoviruses of course are one of many agents that cause cold and it is not known if other cold viruses are similarly checked at higher temperatures. It is likely that they use a repertoire of counter ­strategies to the host defense response, some aspects of which may be temperature dependent. The experiments in this study have been conducted on mouse cells grown in the lab. It remains to be seen if this holds true within living animals and whether it can be extended to human- ­cold virus interactions.

An interview with Dr. Ellen Foxman

Q. How would you place this work in context of the unanswered questions in the field?

Question #1: Why do Rhinoviruses grow better at nasal cavity temperature than at lung temperature? It has been known since the 1960s that most Rhinovirus strains replicate poorly at body temperature (37°C) and better at slightly cooler temperatures (33 – 35°C) such as the temperatures found in the nasal cavity. However, the reason for this was not known. In our study, we observed that Rhinovirus ­infected cells fight back against infection more at 37°C than at 33°C—in other words, the immune response triggered by the virus within infected is more robust at 37°C, and this is an important mechanism suppressing growth of the virus at 37°C. b. Question #2: Does temperature affect the immune response to diverse pathogens, or just the immune response to Rhinovirus? We found that two cardinal signaling pathways involved in immune defense were more active at body temperature than at nasal temperature: RIG­I like receptor signaling and Type I interferon receptor signaling. Since these pathways help defend us against in many viral different infections, our results raise the possibility that cool temperature also provides an advantage to viruses other than Rhinovirus. For example, many respiratory viruses cause colds more often than they cause lung infections; perhaps this is a reason why. That being said, it will be important to directly test other viruses, since viruses are tricky and many viruses have evolved ways to interfere with the immune responses we studied.

Q. How do you plan to take this study forward? What are the strengths and limitations of your model system?

The strength of our study was that we used a very well­ defined experimental system in which we could change one variable at a time to identify the immune system machinery needed to fight Rhinovirus within infected cells and to examine the effect of changing the temperature without changing anything else. Specifically, we used mouse primary airway cells grown in the laboratory. This way, we could compare cells from normal mice with cells from mice that differed by only one gene within the immune system. This allowed us to pinpoint which molecules within the immune system were important for defense against Rhinovirus, and which defenses were (or weren’t) affected by temperature. Also, by culturing cells in the lab, we were able to place them in incubators with controlled temperatures to clearly assess the effect of temperature without other confounding factors. b. Limitations/next steps: Although in general mice have been a good animal model for the human immune system, mice aren’t humans, and the next step in the study will be to examine in more detail how these mechanisms work within the human airway.

Q. Rhinoviruses are known to sometimes infect the lower respiratory tract (5) ​ what do you think is going on there?

One possibility is that the immune mechanisms required to block Rhinovirus infection don’t work as well in people who tend to have lung symptoms with Rhinovirus infection—for example, people with asthma. In our study, we found that if we used mouse cells lacking the necessary immune system machinery to block Rhinovirus infection, the virus could grow quite well at 37°C. There is some evidence that in airway cells from people with asthma, this machinery may not function properly; if this is the case, this might be what permits the virus to thrive at the warmer temperatures of the lung.

Q. Do you think alternating the temperatures (for example in a real world scenario inhaling steam or hot water gargling versus eating an ice cream) impact the success of Rhinovirus infection? In other words you perform the entire infection at one temperature, are there shorter time windows within which a temperature change would positively impact disease outcomes (for example gargling every morning or drinking hot water after eating an ice cream?)​ ?

We did do some temperature shift experiments (see Figure S3 in the paper.) We found that the level of the immune response tracked with the temperature of the cells during the time window when the virus was actively replicating; the temperature before the infection didn’t matter much. I would speculate that some exposure of infected cells to warm temperature at any point when the virus is actively replicating might be beneficial.

Q. What kind of experiments would you need to conduct to suggest to people that using different methods to increase the temperature of the upper respiratory tract – like drinking hot water may help fight cold? Have they been done?

The best way to prove that an intervention works is to directly test it, as you are suggesting. In this case, the best experiment would be to expose a group of volunteers to a fixed dose of Rhinovirus, and then place half of them on a well ­defined hot water drinking program (perhaps the other half could drink only cold water. If hot water program were effective, you would expect to see fewer colds develop in the hot water group than in the other group. This is a difficult study to perform: ideally, you would want to test a group of people who are identical in every way (genetics, behavior, environment, history of exposure to infections, etc.) except for the hot water drinking. In reality, this is quite hard to do, since every person is different! However, it might be possible to see an effect by studying a large group of people, especially if hot water drinking had a big impact (rather than a small effect) on whether or not colds developed after exposure to Rhinovirus. These types of studies can be very informative, but also can be complicated to interpret due to the inability to control all of the variables that may affect the outcome you are measuring (in this case, development of cold symptoms.) b. I do not know of any study considered to be definitive on this subject. However, I did a literature search and found a number of studies that have looked at the effect of hot liquids or steam inhalation on common cold symptoms, and I did find a number of these. You can read a few of these to get a feeling for the strengths and limitations. For example: i. Sanu and Eccles, 2008: This study tested the effect of hot liquid drinking on cold and flu symptoms in subjects who were recruited when they already had symptoms—the pathogen causing the symptoms is unknown. ii. Singh and Singh, 2013, meta-analysis of multiple studies looking at steam inhalation and common cold symptoms.

Q. You have emphasized on cell autonomous response to viral infections, what about the other aspects of the immune response? Do you think they could also contribute to temperature sensitivity?

We only looked at the cell autonomous immune responses in this study, and these were solely responsible for the temperature ­dependent blockade of Rhinovirus in our experiments. In the body, where many cell types are present, the responses we examined (RIG­I like receptor signaling and the Type I interferon response) can profoundly affect nearby and even distant cells through the action of secreted chemicals (cytokines). In this way, the phenomena we observed could also contribute to the temperature ­dependence of other immune responses; however, as yet we have no evidence for this.