Food Labels – Do They Properly Inform Consumers?

The unsurprising and non-controversial role of food labels is to present the ingredients and elements of a food product both independently and in the context of dietary guidelines to ensure consumers are informed to what they are purchasing and how “healthy” the product. In the United States the National Labeling and Education Act (NLEA) in 1990 required the inclusion of nutrition information on packaged foods, with a few exceptions, and set the standard for how the information should be presented. This legislation was important because before the NLEA nutritional information was only required when producers wanted to make claims about specific nutritional benefits derived from consuming their product. However, the lack of standardization in presentation of nutritional information made it difficult to contrast and compare even when the information was available. Thus the famous standardized side panel conveying nutritional information for food products was born.

Interestingly enough very little has changed in the presentation and information of this standard U.S. labeling since the NLEA up until now. Recently the Food and Drug Administration (FDA) released information regarding how this food label would change by 2018; this news was met with cheers from some health circles and jeers from others. Overall the changes are rather uneventful with an increased font size for calorie count, elimination of calories from fat, more nuanced language for per serving and per package identifiers including more empirically based serving sizes, gram amounts in addition to percentages for vitamins (this change seems rather meaningless), Vitamin D and potassium switch required status with Vitamin A and C and more clarification regarding the % Daily Value footnote. The one supposed “big ticket” change is that labels are now required to breakdown the sugar content between natural sugars and added sugars.

The level of usefulness for the consumer within the divergence between natural and added sugars is questionable because without specifically breaking down the sugar content into its molecular complements: glucose, fructose, maltose, etc. the total sugar amount is still the only real meaningful piece of information. Knowing how much sugar was added versus how much sugar naturally occurs in the product is rather irrelevant regarding how the body will process it. Is someone really going to buy product A over product B because it has 28 grams of natural sugar versus 14 grams of natural sugar and 14 grams of added sugar? For some the answer will be yes, although most will not have a good reason why (the only real valid reason would be the contention that added sugars have a higher probability of being simple sugars and negative for health), but for most the answer will be no.

Some individuals could counter-argue that various groups like the AHA, AAP, WHO and Institute of Medicine have recommended decreasing intake of added sugars with general estimates that only about 10 percent of total daily calories should come from added sugar. While all of this is true, the problem is that differentiation between added sugar and natural sugar is more propagandized than meaningful. Again without differentiating between the specific molecules that make up the sugar content, total sugar is the only metric regarding sugar that actually matters. The propaganda stems from individuals promoting the reduced consumption of processed foods, which are more likely to have added sugars. Certainly it is true that added sugars do nothing positive to the nutritional content of the food, but again total sugar is what matters without specific differentiation.

The “debate” about added vs. natural sugar aside, in reality this new label certainly falls short of Michelle Obama’s endorsement “you will no longer need a microscope, a calculator, or a degree in nutrition to figure out whether the food you’re buying is actually good for our kids…” It is difficult to support the accuracy of that statement based on the changes; a sentiment shared by many other individuals who think the food labeling requirements should have been much more substantial.

For example applying the labeling itself is only a part of the battle for the information on the label is only meaningful when consumers read and understand it. There is some question to whether or not the label needs to change for studies have demonstrated that while a vast majority of individuals in the U.S. read food labels, this information does little to influence their food choices.1-3 However, in the EU, which has a more intensive and thorough labeling system, food labels do influence consumer choice.4

While it is difficult to directly determine if the critical factor in this difference in behavior is born from the food labeling methodologies due to cultural differences between the U.S. and the EU, it is also difficult to dismiss the differing labeling strategies as playing an influencing factor. The key difference between the two labeling systems is that the U.S. system places a greater emphasis on the consumer to understand the nutritional context of both product A and how it may differ from the nutritional context of product B versus the more categorized labeling system of the EU in general.

For example in the UK labeling follows four core principles enumerated by the UK Food Standards Agency (FSA) for front of the package:5,6

1) Separate information must be provided on fat, saturated fat, sugars and salt; (this is also a guideline in the U.S. via Facts Up Front, but it is a voluntary program)

2) A red, amber or green color coding, similar to traffic lights, must be utilized to indicate whether the levels of those elements outlined in the first principle are high, medium or low respectively per 100 g (or ml for liquids) of product content;

3) Color metrics are established by nutritional criteria set forth by the FSA;

4) Provide portion ratios relative to the elements outlined in the first principle for color coding;

When this proposal was first made in 2006 there was significant resistance regarding the traffic light identification system as numerous food manufactures and producers questioned the use of the traffic light system and instead favored more of a U.S. style system using percentage of daily recommended values.5 Furthermore food manufactures also disagreed with the use of 100 g/ml as a standard invoking the argument that consumers think more in portions of the consumed product. It would be difficult for consumers to deduce a gram weight-based portion size. This complaint produced an alternative system using the needlessly large number of portion sizes by various food products creating a much more difficult comparison environment for consumers; such was ironic because it produced the result that was exactly the rational used by food companies to argue against the 100 g/ml standard, an overly complicated system.

Regardless of the bumpy road to establishing a universal labeling system and the lack of ideal standardization in the UK (note the confliction between points 2 and 4 from above), numerous studies have demonstrated that front of the package simple signal (like color coding) labeling of the “healthiness” of a food product does influence consumer choice both by increasing the probability that the customer purchases healthier products and increasing the probability that food producers create healthier products;7-10 also traffic light systems have proven superior to other systems like single compounded numbers or guiding star type systems.8,11 Therefore, clearly creating regulations regarding the nutritional or “health value” of a food for the front of the package is a meaningful step to increasing the probability of an informed consumer.

Part of the battle for the front of the package (FOP) is not just to produce a standardized system to convey the health of the product, but to ensure genuine portrayal of the product itself. For example advertising for some food products tends to mislead consumers that the product may contain a larger quantity of a component than in reality. Such is common with fruit juice products; for example in an attempt to draw attention away from the top ingredients commonly being concentrated water and high fructose corn syrup with pictures of fruit. One means that helps support such trickery is that ingredients are only listed in order of percent amount, but the percentages are not given. Actually requiring the percentages may help limit the impact of this type of advertising.

Ensuring proper labeling design is important because studies have demonstrated that simple, transparent and clear labeling engage subconscious emotional elements in the brain including the amygdala.12-14 Therefore, the FDA may need to properly regulate front of the box labeling because the side panel may be at a psychological disadvantage to the “health proclamations” that commonly adorn the front of the box in stylized and eye-catching presentations.

In the past some parties have acknowledge the importance of the front of the box and lamented the U.S. government’s acquiescence of its power to corporations. These parties have proposed taking back the front of the box in such a way to “inform” consumers of whether or not their choice is a healthy one. For example one proposal is that the upper right portion of the box should contain the three most prevalent ingredients in the product, the calorie count and the number of total ingredients beyond those first three in bold and clear font.15

The proponents of such a system believe that it will produce a fast means for consumers to identify healthy food versus unhealthy food that is so easy it is impossible to ignore. However, the problem with such a system is that it can be easily manipulated where producers can fine-tailor their produces where 3 seemingly healthy ingredients can be the 3 most plentiful ingredients by an incredibly small amount before the “unhealthy” ingredients.

Also calorie counts in such a system would have to identify serving size to be placed in proper context and even then such counts may prove to complicate the issue. Note that the above proposition suggests posting the calories per serving on the front of the package. However, if all similar products do not have standardized serving amounts (all listing 100 grams for example vs. ½ cup or 8 to a box) then listing the calories is not simplistic strategy to optimize food choices on the basis of health. Varying serving amounts force the consumer to undertake some general arithmetic. For example suppose Cereal A has 120 calories per ½ cup (10 servings) and Cereal B has 160 calories per ¾ cup (7 servings), front of the box labeling would imply that Cereal A has fewer calories, but that is not the case in either equivalent serving calories or total calories for the entire box. Therefore, front of the package labeling must be less simplistic unless a standardized serving metric is established. Facts Up Front suffers from this serving difference problem limiting its effectiveness.

The possible problems with the above differing option notwithstanding, it is clear that the EU, including the U.K., has a better labeling system than the U.S. with regards to helping consumers acquire and understand nutritional information. So why does so little change in the “updated” U.S. labeling system? Most would argue, probably correctly, that lobbying by food companies prevents the FDA from going further thanks to interference from Congress. If the FDA had the “freedom” to make any changes what changes should they make?

Obviously it is important for there to be some form of comparison information that goes beyond Facts Up Front. A traffic light system certainly holds promise due to its successful application in the UK. However, it is understandable that food companies would balk at such a condition, especially those with significant “red” light products. The proper response to such complaints is two-fold: first, who cares if the food companies have complaints again the proper utilitarian construct of ensuring transparent information. Second, one could attempt to lessen the impact of the traffic light system in the context that a primarily “red” food should not be viewed as something that should never be consumed, otherwise no one would ever eat something like a piece of cheese cake, but instead a food that should be consumed rarely in the context of good health. Thus, the green, yellow and red lights simply transition into anytime, once-a-day and rare, food choices.

Another interesting idea would be to establish a standardized declaration system for the front of the package involving commonly referred health terms against an empirically derived metric. Basically it is commonplace for food producers to put labeling on the front of a package that states: “high in fiber”, “low sodium”, “x number of essential vitamins and minerals”, etc. This newly proposed system would eliminating that ability of food producers to make such claims and instead replace this system with a five or six bullet point checklist in the upper right corner of the package confirming a given “positive health feature”. A check would be earned by meeting a standard floor or ceiling for the given attribute per 100 g of product; where the FDA would establish the standard. For example the “high fiber” box would be checked if a food contained 3 grams of fiber per 100 g of product, not checked otherwise. Five possibilities for such a checklist are shown below.

1) High Fiber;
2) Low Sodium;
3) Whole Grain;
4) Low Sugar;
5) Low Saturated Fat

In the end both of these strategies: the traffic lights and the checkbox, should significantly increase the probability that consumers are informed about the general nutritional value of their food product choices without an unreasonably long analysis period. Overall there is no good reason that the FDA and its surrogates should not establish and enforce such a labeling system.



Citations –

1. Cha, E, et Al. “Health literacy, self-efficacy, food label use, and diet in young adults.” Am. J. Health. Behav. 2014. 38(3):331-339.

2. Campos, S, Doxey, J, and Hammond, D. “Nutrition labels on pre-packaged foods: a systematic review.” Public Health Nutr. 2011. 14(8). 1496-1506.

3. Huang, T, et Al. “Reading nutrition labels and fat consumption in adolescents.” J. Adolesc. Health. 2004. 35(5):399-401.

4. Storcksdieck, G, and Wills, J. “Nutrition labeling to prevent obesity: reviewing the evidence from Europe.” Curr Obes. Rep. 2012. 1(3):134-140.

5. Lobstein, T, and Davies, S. “Defining and labelling ‘healthy’ and ‘unhealthy’ food.” Public Health Nutrition. 12(3):331-340.

6. Food Standards Agency. Board Agrees Principles for Front of Pack Labelling. 2006. Food Standards Agency.

7. Lobstein, T, Landon, J, and Lincoln, P. “Misconceptions and misinformation: the problems with guideline daily amounts (GDAs). A review of GDAs and their use for signaling nutritional information on food and drink labels.” National Heart Forum. 2007.

8. Temple, N, and Fraser, J. “Food labels: a critical assessment.” Nutrition. 2014. 30:257-260.

9. Hersey, J, et Al. “Effects of front-of-package and shelf ntrition labeling systems on consumers.” Nutr. Rev. 2013. 71:1-14.

10. Hawley, K, et Al. “The science on front-of-package food labels.” Public Health Nutr. 2013. 16:430-439.

11. Sutherland, L, Kaley, L, and Fischer, L. “Guiding Stars: the effect of a nutrition navigation program on consumer purchases at the supermarket.” Am. J. Clin. Nutr. 2010. 91:1090S-1094S.

12. Grabenhorst, F, et Al. “Food labels promote healthy choices by a decision bias in the amygdala.” NeuroImage. 2013. 74:152-63.

13. Pessoa, L, and Adolphs, R. “Emotion processing and the amygdala: from a ‘low road’ to ‘many roads’ of evaluating biological significance.” Nat. Rev. Neurosci. 2010. 11:773-783.

14. Seymour, B, and Dolan, R. “Emotion, decision-making, and the amygdala.” Neuron. 2008. 58:662-671.

15. Kessler, D. “Toward more comprehensive food labeling.” N. Engl. J. Med. 2014. 371(3):193-195.

Exploring the Biological Nature of Brown and Beige Fat

Over two years ago this blog discussed the possibility of incorporating a specialized preparation routine before exercise in an attempt to stimulate both brown and beige adipose tissue in order to increase the efficiency and overall calorie and fat burning potential of standard exercise. However, that post did not seek to fully understand or discuss the specific biological mechanisms that govern the behavior of brown or beige adipose tissue. This lack of knowledge limits the efficiency for exercise programs as individuals could either be consuming certain foods or performing certain warm-up tasks to increase exercise potential in addition to those suggested in the past blog post. Increasing exercise efficiency could be an easy means to increase the overall health of society without having to devote more precious time to exercise; therefore it would prove useful to better understand the processes that activate these types of fat.

At the most basic level there are two key elements to the fat burning capacity of brown fat. First, brown fat has multiple mitochondria versus the single mitochondria possessed by white fat; these additional mitochondria allow for greater rates of metabolism along with an increased lipid concentration. Also brown fat releases norepinephrine which reacts with lipases to breakdown fat into triglycerides and later to glycerol and non-esterified fatty acids finally producing CO2 and water, which can lead to a positive feedback mechanism.1,2 Second, brown fat contains significant expression rates of uncoupling protein 1 (UCP-1).1 UCP-1 is responsible for dissipating energy, which leads to the decoupling of ATP production and mitochondrial respiration.1 Basically UCP-1 returns protons after they have been pumped out of the mitochondria by the electron transport chain where these protons are released as heat instead of producing energy (i.e. leaking).

It is important to understand that there are two types of brown fat: natural brown fat and intermediate brown fat commonly known as beige fat. Natural brown is typically exemplified by the fat located in the interscapular region and contains cells from muscle-like myf5+ and pax7+ lineage.3 Natural brown fat is typically isolated from white fat and almost entirely synthesized in the prenatal stage of development as a means to produce heat apart from shivering.4 Beige fat is commonly interspaced within white fat, do not have these muscle-like cells (although Myh11 could be involved),5 and can be activated by thermogenic pathway and the strain of exercise. Beige fat also has the potential to influence the conversion of white fat to beige fat through a process commonly called “browning”.6,7

Natural brown fat is thought to have larger concentrations of UCP1-expression because they constitutively express it after differentiation versus beige, which expresses large amounts of UCP-1 in response to thermogenic or exercise cues.1,5 Therefore, natural brown fat is more effective at energy expenditure. However, it may not be possible to develop more natural brown fat after development; therefore, any positive progression in brown fat development will come from beige fat.

Early understanding of brown fat activation involved non-discriminate increases in the activity of the sympathetic nervous system (SNS). The standard pathway governing brown fat activation uses a thermogenic response involving the release of norepinephrine, which initiates cAMP-dependent protein kinase (PKA) and p38-MAPK signaling leading to the production of free fatty acids (FFA) through lipolysis due to UCP-1 induced proton uncoupling.4 UCP-1 concentrations are further increased through secondary pathways involving the phosphorylation of PPAR-gamma co-activator 1alpha (PGC1alpha), cAMP response element binding protein (CREB) and activating transcription factor 2 (ATF2).8 Among these three elements PGC1alpha appears to be the most important co-activating many transcription factors and playing an important role in linking oxidative metabolism and mitochondrial action.9

However, due to the complicated nature of SNS activation and its other downstream activators the attempt to replicate it in the form of weight loss drugs like Fenfluoramine or Ephedra resulted in severe negative cardiovascular side effects like elevated blood pressure and heart rate.10 While some argue that either increasing the sensitivity or the rate of simulation to the SNS can improve upon these results, the underlying elements associated with downstream activation of the SNS makes facilitating direct influence too complicated. Therefore, from a biological perspective it makes more sense to focus on a downstream element that interacts with brown fat at a more localized level.

Just a side note based on the differing interactivity between brown/beige and white fat from the SNS, white fat appears to represent long-term energy storage and brown fat is shorter-term energy, an unsurprising conclusion. However, frequent energy expenditure, like exercise, may condition the body to produce more beige fat versus white fat viewing short-term energy needs as more valuable than long-term energy needs. Basically if the above point is accurate then it stands to reason that a person would see more benefit from 20 minutes of exercise 6 days a week versus 40 minutes of exercise 3 days a week.

Moving away from direct SNS stimulation perhaps the appropriate method of increasing browning involves increasing transcription and translation of UCP1. Interestingly enough empirical evidence exists to support the idea that reinoic acid could be an effective inducer of UCP-1 gene transcription in mice and operates through a non-adrenergic pathway.11,12 However, a more focused study using loss of function techniques involving retinaldehyde dehydrogenase, which is responsible for converting retinal to retinoic acid, determined that retinal, not retinoic acid is the major inducer of brown fat activity.13 Unfortunately there is no direct understanding regarding the proportional response of brown fat to retinal or retinoic acid. Therefore, the general fat-soluble nature of vitamin A will probably make it difficult to utilize its derivatives as biological stimulants for brown fat activation or browning.

Another possible strategy to stimulate browning is through activated (type 2/M2) macrophages induced by eosinophils which are commonly triggered by IL-4 and IL-13 signaling. When activated this way these macrophages recruit around subcutaneous white fat and secrete catecholamines to facilitate browning in mice.14,15 A secondary means by which both IL-4 and IL-13 may influence fat conversion is their direct interaction with Th2 cytokines.16 Unfortunately while on its face this strategy looks promising, in a similar vein to vitamin A, it might not be effective due to unknown long-term side effects associated with IL-4 and IL-13 activation. Due to this lack of knowledge, if IL-4 or 13 is thought to be a viable biochemical strategy for inducing weight loss, long-term proper time lines for effects and dosages must be explored in humans, not just short-term studies in mice.

A more controversial agent in browning is fibronectin type III domain-containing protein 5 or more frequently known as irisin. Due to its significantly increased rate of secretion from muscle under the strain of exercise, some individuals believe that irisin is a key mediator in browning acting as a myokine;17 if this characterization is accurate then irisin could be a significant player in the biological benefits produced by exercise including weight loss, white fat conversion and reduced levels of inflammation.18,19 However, other parties believe that because human studies with irisin have produced results that do not demonstrate benefits similar to those studies using mice, irisin is another molecule that cannot scale-up its effectiveness when faced with the added biological complexity of humans versus a mouse.20-22

The key element within this controversy could be that irisin expression is augmented by the increased expression of PGC1alpha, but PGC1alpha increases the expression of many different proteins and other molecules, so the expression of irisin may not be relevant to the positive changes associated with exercise. Another factor may be that a key difference between mice and humans is the mutation in the start codon of the human gene involved in the production of irisin, which significantly reduces irisin availability.23 Thus this mutation could be the limiting factor to why despite a very conserved genetic sequence, humans do not see anywhere near the benefit mice do. If this explanation is correct it does potentially still leave the door open to directly inject irisin into the body to increase concentrations in an attempt to aid exercise derived results, but if PGC1alpha is the key, then this increased concentration of irisin could be of minimal consequence.

Another potential element that demonstrates a significant concentration increase in accordance to increased PGC1alpha is a hormone known as meteorin-like (Metrnl).24 The concentration of this hormone increases in both skeletal muscle and adipose tissue during exercise and exposure to cold temperatures in accordance to increases in PGC1alpha concentrations. When Metrnl circulates in the blood it seems to produce a widespread effect that induces browning resulting in a significant increase in energy expenditure.24 The influence of Metrnl on white fat does not appear due to direct interaction with the fat, but instead indirect action on various immune cells most notably M2 macrophages via the eosinophil pathway, which then interact with the fat through activation of various pro-thermogenic actions.24 As discussed above this interaction with eosinophil appears to function through IL-4 and IL-13 signaling indicating a common pathway purpose between IL-4/IL-13 and the original SNS pathway. Not surprisingly blocking Metrnl has a negative effect on the biological thermogenic response.24

Another potential strategy for browning may be targeting appropriate receptors instead of specific molecules; with this strategy in mind one potential target could be transient receptor potential vanilloid-4 (TRPV4). TRPV4 acts as a negative regulator for browning through its negative action against PGC1a and the thermogenic pathway in general.25 In addition TRPV4 appears to activate various pro-inflammatory genes that interact with white adipose tissue making it more difficult to facilitate browning even if the appropriate signals are present. TRPV4 inhibition and genetic ablation in mice significantly increase resistance to obesity and insulin resistance.25 The link between inflammation and thermogenesis is highlighted by the activity of TRPV4, which is one of the early triggers for immune cell chemoattraction.25

Obesity may also produce a positive feedback effect through TRPV4 by increasing cellular swelling and stretching through the ERK1/2 pathway, which increases the rate of TRPV4 activation.26,27 However, the validity of TRPV4 as a therapeutic target remains questionable for TRPV4 expression not only influences fat/energy expenditure, but also osmotic regulation, bone formation and plays some role in brain function.25,28,29 Fortunately a number of the issues with TRPV4 mutations/mis-function appear to be developmental in influence versus post-development, thus TRPV4 therapies could still be valid.

Natriuretic peptides (NPs) are hormones typically produced in the heart on two different operational capacities: atrial and ventricular. Both of these hormones appear to play a role in browning through association with the adrenergic pathway.30 The most compelling evidence for supporting this behavior is that a lack of NP clearance receptors demonstrated significant enhanced thermogenic gene expression in both white and brown adipose tissue.30 Also direct application of ventricular NP in mice increased energy expenditure.30 In addition to the above results, NPs are an inherent attractive therapeutic possibility because appropriate receptors are located in white and brown fat of both rats and humans31,32 and these receptors go through periods of significant decline in expression when exposed to fasting,33 which may account for some of the benefits seen from low calorie diets.

Atrial NPs increase lipolysis in human adipocytes similar to catecholamines (increasing cAMP levels and activation of PKA) although whether or not this increase is induced through interaction with beta-adrenergic receptors is unclear.34 Some believe that NPs activate the guanylyl cyclase containing NPRA producing the second messenger cGMP activating cGMP-dependent protein kinase (PKG).35,36 PKA and PKG have similar mechanisms for substrate phosphorylation including similar targets in adipocytes,36 thus this interaction may explain why atrial NPs act similar to catecholamines.

Recall from above that one of the means of inducing browning, especially for those tissues that are distant from SNS-based neurons, is macrophage recruitment. This recruitment appears to be initiated by CCR2 and IL-4 for when either is eliminated from mice models the conversion no longer occurs.15 Tyrosine hydroxylase (Th) is also important in this process facilitating the biosynthesis of catecholamines and later PKA levels.

With respects to producing a biomedical agent to enhance browning there appear to be three major pathways in play: 1) the SNS pathway producing a direct activation response; 2) macrophage recruitment pathway potentially involving Metrnl, which activates IL-4 and IL-13 eventually leading to PKA activation and an indirect activation response; 3) NPs activation pathway, which eventually leads to PKG activation and an indirect activation response. As mentioned earlier SNS pathway enhancement has already been attempted by at least two drugs and failed miserably, so that method is probably out. In addition the SNS pathway does not appear to have as much browning potential as the PKA or PKG pathways due to the reliance on the location of certain nerve fibers.

Enhancing macrophage recruitment could be a good strategy, but there appears to be little information regarding negative effects associated with short-term high frequency enhancement of IL-4 or IL-13 concentrations. Some reports have suggested an increase in allergic symptoms, but any more severe consequences are unknown. This is not to say that enhancing IL-4 or IL-13 is not a valid therapeutic strategy, but its overall value is unknown. In contrast enhancement of NPs appear to be a more stable choice due to positive results in initial exploration of both the application and the expected negative side effects. First, NPs can be administrated via the nose-brain pathway enabling access to the brain avoiding some potential systemic side effects.37 Second, there appear to be few, if any significant side effects to intranasal NP application, at least in the short-term.38

Overall the above discussion has merely identified some of the more promising candidates to enhance browning white fat. One could argue that resorting to drugs to enhance the overall health of an individual versus simple diet and exercise is a regretful strategy. Unfortunately the reality of modern society is that more and more people seem to have less available time to exercise or eat right. In addition to a mounting negative weight external environment (increased pollution and industrial chemicals like BPAs) this drug enhancement strategy may be the most time and economically efficient means to ensure proper weight control and overall health for the future.

Citations –

1. van Marken Lichtenbelt, W, et Al. “Cold-activated brown adipose tissue in healthy men.” The New England Journal of Medicine. 2009. 360:1500-08.

2. Lowell, B, and Spiegelman, B. “Towards a molecular understanding of adaptive thermogenesis.” Nature. 2000. 404:652-60.

3. Seale, P, et Al. “PRDM16 controls a brown fat/skeletal muscle switch.” Nature. 2008. 454:961–967.

4. Sidossis, L and Kajimura, S. “Brown and beige fat in humans: thermogenic adipocytes that control energy and glucose homeostasis.” J. Clin. Invest. 2015. 125(2):478-486.

5. Long, J, et Al. “A smooth muscle-like origin for beige adipocytes.” Cell Metab. 2014. 19(5):810–820.

6. Kajimura, S, and Saito, M. “A new era in brown adipose tissue biology: molecular control of brown fat development and energy homeostasis.” Annu Rev Physiol. 2014. 76:225–249.

7. Harms, M, and Seale, P. “Brown and beige fat: development, function and therapeutic potential.” Nat Med. 2013. 19(10):1252–1263.

8. Collins, S. “β-Adrenoceptor signaling networks in adipocytes for recruiting stored fat and energy expenditure.” Front Endocrinol (Lausanne). 2011. 2:102.

9. Handschin, C, and Spiegelman, B. “Peroxisome proliferatoractivated receptor gamma coactivator 1 coactivators, energy homeostasis, and metabolism.” Endocr. Rev. 2006. 27:728–735.

10. Yen, M, and Ewald, M. “Toxicity of weight loss agents.” J. Med. Toxicol. 2012. 8:145–152.

11. Alvarez, R, et Al. “A novel regulatory pathway of brown fat themogenesis, retinoic acid is transcriptional activator of the mitochondrial uncoupling protein gene.” J. Biol. Chem. 270:5666-5673.

12. Mercader, J, et Al. “Remodeling of white adipose tissue after retinoic acid administration in mice.” Endocrinology. 2006. 147:5325–5332.

13. Kiefer, F, et Al. “Retinaldehyde dehydrogenase 1 regulates a thermogenic program in white adipose tissue.” Nat. Med. 2012. 18:918–925.

14. Nguyen, K, et Al. “Alternatively activated macrophages produce catecholamines to sustain adaptive thermogenesis.” Nature. 2011. 480(7375):104–108.

15. Qiu, Y, et Al. “Eosinophils and type 2 cytokine signaling in macrophages orchestrate development of functional beige fat.” Cell. 2014. 157(6):1292–1308.

16. Stanya, K, et Al. “Direct control of hepatic glucose production by interleukins-13 in mice.” The Journal of Clinical Investigation. 2013. 123(1):261-271.

17. Pedersen, B, and Febbraio, M “Muscle as an endocrine organ: focus on muscle-derived interleukin-6.” Physiological Reviews. 2008. 88(4):1379–406.

18. Bostrom, P, et Al. “A PGC1-α-dependent myokine that drives brown-fat-like development of white fat and thermogenesis.” Nature. 2012. 481(7382):463–468.

19. Lee, P, et Al. “Irisin and FGF21 are cold-induced endocrine activators of brown fat function in humans.” Cell Metab. 2014. 19(2):302–309.

20. Erickson, H. “Irisin and FNDC5 in retrospect: An exercise hormone or a transmembrane receptor?” Adipocyte. 2013. 2(4):289-293.

21. Timmons, J, et Al. “Is irisin a human exercise gene?” Nature. 2012. 488(7413):E9-11.

22. Albrecht, E, et Al. “Irisin - a myth rather than an exercise-inducible myokine.” Scientific Reports. 2015. 5:8889.

23. Ivanov, I, et Al. “Identification of evolutionarily conserved non-AUG-initiated N-terminal extensions in human coding sequences.” Nucleic Acids Research. 2011. 39(10):4220-4234.

24. Rao, R, et Al. “Meteorin-like is a hormone that regulates immune-adipose interactions to increase beige fat thermogenesis.” Cell. 2014. 157:1279-1291.

25. Ye, L, et Al. “TRPV4 is a regulator of adipose oxidative metabolism, inflammation, and energy homeostasis.” Cell. 2012. 151:96-110.

26. Gao, X, Wu, L, and O’Neil, R. “Temperature-modulated diversity of TRPV4 channel gating: activation by physical stresses and phorbol ester derivatives through protein kinase C-dependent and -independent pathways.” J. Biol. Chem. 2003. 278:27129–27137.

27. Thodeti, C, et Al. “TRPV4 channels mediate cyclic strain-induced endothelial cell reorientation through integrin-to-integrin signaling.” Circ. Res. 2009. 104:1123–1130.

28. Masuyama, R, et Al. “TRPV4-mediated calcium influx regulates terminal differentiation of osteoclasts.” Cell Metab. 2008. 8:257–265.

29. Phelps, C, et Al. “Differential regulation of TRPV1, TRPV3, and TRPV4 sensitivity through a conserved binding site on the ankyrin repeat domain.” J. Biol. Chem. 2010. 285:731–740.

30. Bordicchia, M, et Al. “Cardiac natriuretic peptides act via p38 MAPK to induce the brown fat thermogenic program in mouse and human adipocytes.” The Journal of Clinical Investigation. 2012. 122(3):1022-1036.

31. Sarzani, R, et Al. “Comparative analysis of atrial natriuretic peptide receptor expression in rat tissues.” J Hypertens Suppl. 1993. 11(5):S214–215.

32. Sarzani, R, et Al. “Expression of natriuretic peptide receptors in human adipose and other tissues.” J Endocrinol Invest. 1996. 19(9):581–585.

33. Sarzani, R, et Al. “Fasting inhibits natriuretic peptides clearance receptor expression in rat adipose tissue.” J Hypertens. 1995. 13(11):1241–1246.

34. Sengenes, C, et Al. “Natriuretic peptides: a new lipolytic pathway in human adipocytes.” FASEB J. 2000. 14(10):1345–1351.

35. Potter, L, and Hunter, T. “Guanylyl cyclase-linked natriuretic peptide receptors: structure and regulation.” J Biol Chem. 2001. 276(9):6057–6060.

36. Sengenes, C, et Al. “Involvement of a cGMP-dependent pathway in the natriuretic peptide-mediated hormone-sensitive lipase phosphorylation in human adipocytes.” J Biol Chem. 2003. 278(49):48617–48626.

37. Illum, L. “Transport of drugs from nasal cavity to the central nervous system.” Eur. J. Pharm. Sci. 11:1-18.

38. Koopmann, A, et Al. “The impact of atrial natriuretic peptide on anxiety, stress and craving in patients with alcohol dependence.” Alcohol and Alcoholism. 2014. 49(3):282-286.

A Theory Behind the Relationship Between Processed Foods and Obesity

While there has been a general slowing in the progression of global obesity, especially in the developed world, there has yet to be a reversal of this detrimental trend. A recent study has suggested that one aspect of influence regarding obesity progression lies with the consumption of foods that have incorporated emulsifiers and how they interact with intestinal bacteria including increasing the probability of developing negative metabolic syndromes in mice.1 Based on this result understanding the digestive process may be an important element to understanding how emulsifiers and emulsions may influence weight outcomes.

An emulsion is a mixture of at least two liquids where multiple components are immiscible, a characteristic commonly seen when oil is added to water resulting in a two-layer system where the oil floats on the surface of the water before it is mixed to form the emulsion. However, due to this immiscible aspect most emulsions are inherently unstable as “similar” droplets join together once again creating two distinct layers. When separated these layers are divided into two separate elements: a continuous phase and a droplet phase depending on the concentrations of the present liquids. Due to their inherent instability most emulsions are stabilized with the addition of an emulsifier. These agents are commonly used in many food products including various breads, pastas/noodles, and milk/ice cream.

Emulsifier-based stabilization occurs by reducing interfacial tension between immiscible phases and by increasing the repulsion effect between the dispersed phases through either increasing the steric repulsion or electrostatic repulsion. Emulsifiers can produce these effects because they are amphiphiles (have two different ends): a hydrophilic end that is able to interact with the water layer, but not the oil layer and a hydrophobic end that is able to interact with the oil layer, but not the water layer. Steric repulsion is born from volume restrictions from direct physical barriers while electrostatic repulsion is based on exactly its namesake electrically charged surfaces producing repulsion when approaching each other. As previously mentioned above some recent research has suggested that the consumption of certain emulsifiers in mice have produced negative health outcomes relative to controls. Why would such an outcome occur?

A typical dietary starch, which is one of the common foods that utilize emulsifiers is composed of long chains of glucose called amylose, a polysaccharide.2 These polysaccharides are first broken down in the mouth by chewing and saliva converting the food structure from a cohesive macro state to scattered smaller chains of glucose. Other more complex sugars like lactose and sucrose are broken down into their glucose and secondary sugar (galactose, fructose, etc.) structures.

Absorption and complete degradation begins in earnest through hydrolysis by salivary and pancreatic amylase in the upper small intestine with little hydrolyzation occurring in the stomach.3 There is little contact or membrane digestion through absorption on brush border membranes.4 Polysaccharides break down into oligosaccharides that are then broken down into monosaccharides by surface enzymes on the brush borders of enterocytes.5 Microvilli in the entercytes then direct the newly formed monosaccharides to the appropriate transport site.5 Disaccharidases in the brush border ensure that only monosaccharides are properly transported, not lingering disaccharides. This process differs from protein digestion, which largely involves degradation in gastric juices comprised of hydrochloric acid and pepsin and later transfer to the duodenum.

Within the small intestine free fatty acid concentration increases significantly as oils and fats are hydrolyzed at a faster rate than in the stomach due to the increased presence of bile salts and pancreatic lipase.3 It is thought that droplet size of emulsified lipids influences digestion and absorption where the smaller sizes allow for gastric lipase digestion in the duodenal lipolysis.6,7 The smaller the droplet size the finer the emulsion in the duodenum leading to a higher degree of lipolysis.8 Not surprisingly gastric lipase activity is also greater in thoroughly mixed emulsions versus coarse ones.

Typically hydrophobic interactions are responsible for the self-assembly of amphiphiles where water molecules react to a disordered state gaining entropy as the hydrophobes of the amphiphilic molecules are buried in the cores of micelles due to repelling forces.9 However, in emulsions the presence of oils produce a low-polarity interaction that can facilitate reverse self-assembly10,11 with a driving force born from the attraction of hydrogen bonding. For example lecithin is a zwitterionic phospholipid with two hydrocarbon tails that form reverse spherical or ellipsoidal micelles when exposed to oil.21 Basically emulsions could have the potential to significantly increase the hydrogen concentration of the stomach.

This potential increase in free hydrogen could be an important aspect to why emulsions produce negative health outcomes in model organisms.1 One of the significant interactions that govern the concentrations and types of intestinal bacteria is the rate of interspecies hydrogen transfer between hydrogen producing bacteria to hydrogen consuming methanogens. Note that non-obese individuals have small methanogen-based intestinal populations whereas obese individuals have larger populations where it is thought that the population of methanogen bacteria expands first before one gains significant weight.13,14 The importance behind this relationship is best demonstrated by understanding the biochemical process involved in the formation of fatty acids in the body.

Methanogens like Methanobrevibacter smithii enhance fermentation efficiency by removing excess free hydrogen and formate in the colon. A reduced concentration of hydrogen leads to an increased rate of conversion of insoluble fibers into short-chain fatty acids (SCFAs).13 Proprionate, acetate, butyrate and formate are the most common SCFAs formed and absorbed across the intestinal epithelium providing a significant portion of the energy for intestinal epithelial cells promoting survival, differentiation and proliferation ensuring effective stomach lining.13,15,16 Butyric acid is also utilized by the colonocytes.17 Formate also can be directly used by hydrogenotrophic methanogens and propionate and lactate can be fermented to acetate and H2.13

Overall the population of Archaea bacteria in the gut, largely associated to Methanobrevibacter smithii, is tied to obesity with the key factor being availability of free hydrogen. If there is a lot of free hydrogen then there is a higher probability for a lot of Archaea, otherwise there is a very low population of Archaea because there is a limited ‘food source’. Therefore, the consumption of food products with emulsions or emulsion-like characteristics or components could increase available free hydrogen concentrations, which will change the intestinal bacteria composition in a negative manner that will increase the probability that an individual becomes obese. This hypothesis coincides with existing evidence from model organisms that emulsion consumption has potential negative intestinal bacteria outcomes. One possible methodology governing this negative influence is how the change in bacteria concentration influences the available concentration of SCFAs, which could change the stability of stomach lining.

In addition to influencing hydrogen concentrations in the gut, emulsions also appear to have a significant influence on cholecystokinin (CCK) concentrations. CCK plays a meaningful role in both digestion and satiety, two components of food consumption that significantly influence both body weight and intestinal bacteria composition. Most of these concentration changes occur in the small intestine, most notably in the duodenum and jejunum.18 The largest influencing element for CCK release is the amount and level of fatty acid presence in the chyme.18 CCK is responsible for inhibiting gastric emptying, decreasing gastric acid secretion and increased production of specific digestive enzymes like hepatic bile and other bile salts, which form amphipathic lipids that emulsify fats.

When compared against non-emulsions, emulsion consumption appears to reduce the feedback effect that suppresses hunger after food intake. This effect is principally the result of changes in CCK concentrations versus other signaling molecules like GLP-1.19 Emulsion digestion begins when lipases bind to the surface of the emulsion droplets; the effectiveness of lipase binding increases with decreasing droplet size. Small emulsion droplets tend to have more complex microstructures, which produce more surface area that allow for more effective digestion.

This higher rate of breakdown produces a more rapid release of fatty acids as the presences of free fatty acids in the small intestinal lumen is critical for gastric emptying and CCK release.20 This accelerated breakdown creates a relationship between CCK concentration and emulsion droplet size where the larger the droplet size the lower the released CCK concentration.21 One of the main reasons why larger emulsions produce less hunger satisfaction is that with the reduced rate of CCK concentration and emulsion breakdown there is less feedback slowing of intestinal transit. Basically the rate at which the food is traveling through the intestine proceeds at a faster rate because there are fewer cues (feedback) due to digestion to slow transit for the purpose of digestion.

As alluded to above the type of emulsifier used to produce the emulsion appears to be the most important element to how an emulsion influences digestion. For example the lipids and fatty acid concentrations produced from digestion of a yolk lecithin emulsion were up to 50% smaller than one using polysorbate 20 (i.e. Tween 20) or caseinate.7 Basically if certain emulsifiers are used the rate of emulsion digestion can be reduced potentially increasing the concentration of bile salts in the small intestine, which could produce a higher probability for negative intestinal related events.

Furthermore studies using low-molecular mass emulsifiers (two non-ionic, two anionic and one cationic) demonstrated three tiers of TG lipolysis governed by emulsifier-to-bile salt ratio.3 At low emulsifier-bile ratios (<0.2 mM) there was no change in solubilization capacity of micelles whereas at ratios between 0.2 mM and 2 mM solubilization capacity significantly increased, which limited interactions between the oil and destabilization reaction products reducing oil degradation.3 At higher ratios (> 2 mM) emulsifier molecules remain in the adsorption layer heavily limiting lipase activity, which significantly reduces digestion and oil degradiation.3

Another possible influencing factor could be change in glucagon concentrations. There is evidence suggesting that increasing glucagon concentration in already fed rats can produce hypersecretory activity in both the jejunum and ileum.22-24 It stands to reason that due to activation potential of glucagon-like peptide-1 (GLP-1) in consort with CCK, glucagon plays some role. However, there are no specifics regarding how glucagon directly interacts with intestinal bacteria and the changes in digestion rate associated with emulsions.

The methodology behind why emulsions and their associated emulsifiers produce negative health outcomes in mice is unknown, but it stands to reason that both how emulsions change the rate of digestion and the present hydrogen concentration play significant roles. These two factors have sufficient influence on the composition and concentration of intestinal bacteria, which have corresponding influence on a large number of digestive properties including nutrient extraction and SCFA concentration management. SCFA management may be the most pertinent issue regarding the metabolic syndrome outcomes seen in mice born from emulsifiers.

It appears that creating emulsions that produce smaller drop sizes could mitigate negative outcomes, which can be produced by using lecithin over other types of emulsifiers. Overall while emulsifiers may be a necessary element in modern life to ensure food quality, instructing companies on the proper emulsifier to use at the appropriate ratios should have a positive effect on managing any detrimental interaction between emulsions and gut bacteria.



Citations –

1. Chassaing, B, et Al. “Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome.” Nature. 2015. 519(7541):92-96.

2. Choy, A, et Al. “The effects of microbial transglutaminase, sodium stearoyl lactylate and water on the quality of instant fried noodles.” Food Chemistry. 2010. 122:957e964.

3. Vinarov, Z, et Al. “Effects of emulsifiers charge and concentration on pancreatic lipolysis: 2. interplay of emulsifiers and biles.” Langmuir. 2012. 28:12140-12150.

4. Ugolev, A, and Delaey, P. “membrane digestion – a concept of enzymic hydrolysis on cell membranes.” Biochim Biophys Acta. 1973. 300:105-128.

5. Levin, R. “Digestion and absoption of carbohydrates from molecules and membranes to humans.” Am. J. Clin. Nutr. 1994. 59:690S-85.

6. Mu, H, and Hoy, C. “The digestion of dietary triacylglycerols.” Progress in Lipid Research. 2004. 43:105e-133.

7. Hur, S, et Al. “Effect of emulsifiers on microstructural changes and digestion of lipids in instant noodle during in vitro human digestion.” LWT – Food Science and Technology. 2015. 60:630e-636.

8. Armand, M, et Al. “Digestion and absorption of 2 fat emulsions with different droplet sizes in the human digestive tract.” American Journal of Clinical Nutrition. 1999. 70:1096e1106

9. Njauw, C-W, et Al. “Molecular interactions between lecithin and bile salts/acids in oils and their effects on reverse micellization.” Langmuir. 2013. 29:3879-3888.

10. Israelachvili, J. “Intermolecular and surface forces. 3rd ed. Academic Press; San Diego. 2011.

11. Evans, D, and Wennerstrom, H. “The colloidal domain: where physics, chemistry biology, and technology meet.” Wiley-VCH: New York. 2001.

12. Tung, S, et Al. “A new reverse wormlike micellar system: mixtures of bile salt and lecithin in organic liquids.” J. Am. Chem. Soc. 2006. 128:5751-5756.

13. Zhang, H, et, Al. “Human gut microbiota in obesity and after gastric bypass.” PNAS. 2009. 106(7): 2365-2370.

14. Turnbaugh, P, et, Al. “An obesity-associated gut microbiome with increased capacity for energy harvest.” Nature. 2006. 444(7122):1027–31.

15. Son, G, Kremer, M, Hines, I. “Contribution of Gut Bacteria to Liver Pathobiology.” Gastroenterology Research and Practice. 2010. doi:10.1155/2010/453563.

16. Luciano, L, et Al. “Withdrawal of butyrate from the colonic mucosa triggers ‘mass apoptosis’ primarily in the G0/G1 phase of the cell cycle.” Cell and Tissue Research. 1996. 286(1):81–92.

17. Cummings, J, and Macfarlane, G. “The control and consequences of bacterial fermentation in the human colon.” Journal of Applied Bacteriology. 1991. 70:443459.

18. Rasoamanana, R, et Al. “Dietary fibers solubilized in water or an oil emulsion induce satiation through CCK-mediated vagal signaling in mice.” J. Nutr. 2012. 142:2033-2039.

19. Adam, T, and Westerterp-Plantenga, M. “Glucagon-like peptide-1 release and satiety after a nutrient challenge in normal-weight and obese subjects.” Br J Nutr. 2005. 93:845–51.

20. Little, T, et Al. “Free fatty acids have more potent effects on gastric emptying, gut hormones, and appetite than triacylglycerides.” Gastroenterology. 2007. 133:1124–31.

21. Seimon, R, et Al. “The droplet size of intraduodenal fat emulsions influences antropyloroduodenal motility, hormone release, and appetite in healthy males.” Am. J. Clin. Nutr. 2009. 89:1729-1736.

22. Young, A, and Levin, R. “Diarrhoea of famine and malnutrition: investigations using a rat model. 1. Jejunal hypersecretion induced by starvation.” Gut. 1990. 31:43-53.

23. Youg, A, Levin, R. “Diarrhoea of famine and malnutrition: investigations using a rat model. 2. Ileal hypersection induced by starvation.” Gut. 1990. 31:162-169.

24. Lane, A, Levin, R. “Enhanced electrogenic secretion in vitro by small intestine from glucagon treated rats: implications for the diarrhoea of starvation.” Exp. Physiol. 1992. 77:645-648.

Tapping into Brown Fat?

One of the impending health threats in the future is the increasing rate of obesity in the United States as well as the rest of the world. While the rate of obesity has ebbed slightly in the last year the number of obese individuals is still increasing in absolute terms due to population growth and greater access to food choices in developing countries. Numerous rationalities have been given to explain this increase ranging from too much food and not enough exercise to changing bacterial concentrations in the intestinal tract. Certainty the type of bacteria in one’s intestine affects the ability to process fats, carbohydrates and proteins from various food sources.1,2 However, despite the claims of numerous food products and their positive probiotic messages there is no proof that any of these products have a net positive benefit in managing weight. Gastro bypass surgery has a mixed history of success and for some patients has serious side effects. Therefore, the only truly viable proven method for consistently controlling weight is physical exercise and an appropriate diet.

Unfortunately numerous individuals do not enjoy exercise, so it would behoove many to develop a methodology that increased its effectiveness. Numerous “entrepreneurs” have made attempts at “increasing” exercise effectiveness with various pieces of equipment or programs, yet almost all of them are questionable in their viability. What needs to be addressed is a biochemical methodology that has influence in a majority of individuals. One strategy may be to tap into the unique properties of brown adipose tissue (a.k.a. brown fat).

There are two key elements to the fat burning capacity of brown fat. First, brown fat have multiple mitochondria versus the single mitochondria possessed by white fat which allows for greater rates of metabolism along with an increased lipid concentration. Also brown fat releases norepinephrine which reacts with lipases to breakdown fat into triglycerides and later to glycerol and non-esterified fatty acids and finally CO2 and water acting in as a positive feedback mechanism, in a sense.3,4 Second, brown fat contains uncoupling protein 1 (UCP-1).3 UCP-1 is responsible for dissipating energy, which leads to the decoupling of ATP production and mitochondrial respiration.3 Basically UCP-1 returns protons after they have been pumped out of the mitochondria by the electron transport chain where the protons are released as heat instead of producing energy.

The shiver response involves the activation of the primary motor in the posterior hypothalamus when inhibitory signals from the anterior hypothalamic-preoptic are overridden by temperature dependent sensory information from the skin and spinal cord.5 In response to this sensory information muscles begin to vibrate (i.e. shake) resulting in the production of heat as a byproduct to the activity. The key physiological role brown fat plays in mammals, especially those who do not have a shiver response, is it operates as a thermogenic organ where mitochondrial respiration is uncoupled from ATP production.4 The shiver response relies on volume of produced heat versus heat per unit, without the ability of volume brown fat augments the heat per unit amount, due to the lack of ATP production instead focusing on heat alone, in an attempt to compensate.

For a number of years it was thought that humans lost their brown fat after infancy, but numerous PET and CT studies have confirmed that adults do have concentrations of brown fat most notably in the supraclavicular area.6,7 Therefore, one could increase metabolic activity by activating brown fat in some individuals. It is important to note that global patterns of obesity are not viewed as complete enough to determine whether obesity rates are higher in warmer countries versus colder countries to provide a form of empirical support for increased brown fat despots relative to surface temperature; however, any correlation due to ambient temperatures would probably be weak because of adaptation of the shiver response.

While cold is the most common method for activating brown fat, it is not the only method to accelerate the mitochondrial activity of brown fat. Catecholamines have a similar activation effect largely because of their involvement in the fight or flight response. It makes sense that the more efficient energy producers in the body would be activated when facing a stressful life-or-death situation. Unfortunately beta blockers, which are commonly used to control high blood pressure, a common symptom in obese individuals, block catecholamines and reduce the probability of activating brown fat through catecholamine interaction. Epinephrine and caffeine also show promise in increasing brown fat activation, but epinephrine derived from drugs have too many side effects and caffeine consumption could result in too many additional calories counteracting the increase in brown fat activation.

As noted earlier norepinephrine appears especially important in triggering additional brown fat activation resulting in an increased rate of oxygen consumption and fatty acid release. Thus, the consumption of foods high in norepinephrine precursors could aid in increasing brown fat efficiency probability. Another advantage to utilizing brown fat as an augmented element to increased metabolic activity is that its decoupled nature from ATP production should result in limited to no additional oxidative free radical production from its specific mitochondria. Therefore, activation of this methodology should not increase possibilities for cellular damage and increase the rate of aging in a given subject.

Still, many questions remain before those next steps can be taken. For one thing, why is it that obese people tend to have very little brown fat compared with lean people? One possibility is that as brown fat can “eat” white fat, brown fat could also become white fat. If brown fat is not utilized it may experience apoptotic consequences. An aspect of this die-off could occur because brown fat chief role is its thermogenesis response, but more obese individuals have greater thermal insulation due to their fat content, thus have more difficulty initiating brown fat activation due to external temperature changes and competition with the shiver response.

It is also probably worth remembering how researchers discovered that adults retained stores of brown fat in the first place: they were studying head and neck scans of patients with cancer and noticed that in addition to tumor sites, certain parts of the neck also showed higher rates of glucose consumption.8 This additional rate of glucose consumption was theoretically driven by additional brown fat because brown fat appeared to be at greater concentrations in cancer patients versus individuals without cancer/tumors.8 One explanation for this additional brown fat could be that the excess energy requirements for cells that have shed their growth limitations demand conversion of white fat into brown fat through the methodology discussed above. If this theory is accurate then brown fat follows tumor development not that other way around, thus increasing brown fat stores will not increase the probability that an individual develops cancer.

While some individuals believe that one way to utilize brown fat is to develop a “cold sauna” that individuals can simply sit in, wouldn’t it be better to combine brown fat activation with white fat “activation”? There still is limited information on what type of exposure regiment is optimal for brown fat activation. For example is it better to be exposed to high intensity cold at low volume (-50 degrees F for 30 seconds) or low intensity cold at high volume (20 degrees F for 5 minutes)? Note that brown fat activates as long as the temperature is cold enough whether it is acute cold or eventual chronic cold; however, prolonged exposure to certain cold conditions can produce negative results for exposed skin, so determining a differentiated methodology would be advisable. Also gyms or cold saunas would have to set up a stepwise exposure protocol allowing users to move gradually from initial temperatures to final temperatures because a near instant temperature change from say 70 degrees F to 0 degrees F would be detrimental to the body, especially those with health problems.

Outside this methodology one could have short-term cold exposure (40 degrees F for 10 minutes) and then engage in cardiovascular exercise. The cold exposure will stimulate the brown fat with the later exercise continuing the brown fat stimulation and initiating some level of white fat loss. Another possibility would be the increased rate of norepinephrine release increasing the probability of white fat becoming brown fat due to increased activation rates along with the release of norepinephrine possibly reducing pain associated with exercising (acting as a biological pain killer). Overall with available brown fat stores still in adults, no risk for increased cancer development and the ability to produce more brown fat when routinely activated it seems that gyms should think about installing “cold saunas” not necessarily for solitary fat burning, but instead as a preparation element for a more complete calorie and fat burning workout.


--
Citations:

1. Backhed, F, et, Al. “The gut microbiota as an environmental factor that regulates fat storage.” PNAS. 2004. 101(44): 15718–23.

2. Cani, P, et, Al. “Role of gut microflora in the development of obesity and insulin resistance following high-fat diet feeding.” Pathologie Biologie. 2008. 56:305–309.

3. van Marken Lichtenbelt, W, et Al. “Cold-activated brown adipose tissue in healthy men.” The New England Journal of Medicine. 2009. 360:1500-08.

4. Lowell, B, and Spiegelman, B. “Towards a molecular understanding of adaptive thermogenesis.” Nature. 2000. 404:652-60.

5. http://www.nlm.nih.gov/cgi/mesh/2011/MB_cgi?mode=& term=Shivering

6. Hany, T, et Al. “Brown adipose tissue: a factor to consider in symmetrical tracer uptake in the neck and upper chest region.” Eur J. Nucl Med. Mol Imaging. 2002. 29:1393-8.

7. Nedergaard, J, Bengtsson, T, and Cannon, B. “Unexpected evidence for active brown
adipose tissue in adult humans.” Am. J. Physiol. Endocrinol. Metab. 2007. 293:E444-
E452.

8. Rousseau, C, et Al. “Brown fat in breast cancer patients: analysis of serial (18)F-FDG PET/CT scans.” Eur J. Nucl Med. Mol Imaging. 2006. 33:785-91.

Eating and Counting at the Same Time – Calorie Charts in Restaurants

Regrettably the rate of obesity has grown significantly in the last 20 years in both adults and children. While some individuals lament the simplistic explanation that most have derived for this outcome, over-consumption of food, instead favoring other explanations like environmental toxins or changes in gut bacteria concentrations; the reality is that the primary reason for an individual being overweight is an imbalance in calorie intake vs. biochemical caloric consumption. Outside influencing factors like toxins and gut bacteria simply influence intake and consumption. One of the explanations for the significant increase in this imbalance is the change in food consumption behavior.1,2 For example it is thought that modern Americans consume approximately 1/3 of their total calories along with approximately ½ of the total money spent on food not at home, but at restaurants.3,4

Even when food is not consumed in the home one still must take measure of its nutritional content. Unfortunately most consumers appear generally unaware of the need to measure calorie content, do not care to count or inaccurately estimate the number of calories they consume when eating out. Part of this problem stems from the fact that few people can accurately estimate the number of calories in a meal by simply looking at it; some surveys have identified that most respondents underestimated the calorie count in various take-out items by nearly ½ with some inaccuracies on single items amounting to 650 calories.5,6 In addition various other studies further demonstrated the inconsistency in consumer knowledge regarding calorie counts and using them to improve decision making as some studies identified different and healthier food choices when exposed to visually presented calorie counts and other studies with similar methodologies, but different people, identified no significant difference in food choice.7-12

It must be noted that the concerns with obesity and out of home eating are only one element behind increasing obesity rates. If one does not track how one eats at home or in non-chain restaurants where calorie counts are typically not available then tracking nutrition when eating at chain restaurants loses most of its purpose. Also people must be committed to using the information which means accepting that they cannot eat whatever they want whenever they want otherwise posting calorie counts will not produce the results that some hope for.

The above points notwithstanding clearly the public needs some assistance because despite what some want to believe the health of general society affects everyone in some context solely due to the interconnectivity of the healthcare system and its limited resources. Therefore, after watching some state governments poke around the edges of regulation, the federal government finally demanded some form of concrete information structure for a calorie information program in section 4205 of the Affordable Care Act passed in 2010. This structure was designed so that ‘chain restaurants’ (restaurants with more than 20 locations) had to provide calorie data and additional nutritional information for basically all food items (menu and self-service), so patrons could make more informed food choices.

Unfortunately there was no generally required format to these calorie postings relying instead upon the FDA to accept recommendations for what type and how mandatory information should be presented. The FDA has proposed five general recommendations: 1) Calories for items are displayed in proximity to food items on the menu board; 2) Menu board contains a statement that written nutritional information is available on request; 3) Menu board contains a succinct statement regarding suggested caloric intake; 4) Menu board contains a statement that puts the calories in context of total requirements; 5) Menu board provides nutrient content for standard menu items that come in different flavors, varieties, or combinations but are listed as a single menu item;12 however, of the five recommendations only the first and last ones have been given any type of guidelines for implementation with the remaining three lacking any type of guidelines. Not surprisingly the three recommendations lacking guidelines are rarely implemented. New guidelines are scheduled to be released sometime in July 2012.

Note that it is estimated that at least ½ of U.S. chain restaurants provided nutrition information publicly either apart from the menu at the restaurant itself or on the company’s website;14 however, it stands to reason that such postings, especially on websites, heavily limits the usefulness of the information due to availability issues when that information is most desired by the consumer.

An improved and firm structure for presenting calorie information is required because a vast majority of postings offered by most restaurants do not provide sufficient information to accurately access the caloric intake of most meal combinations even if the patron is committed to counting calories. There are limited problems presenting calorie information for single static items like black coffee or an egg mcmuffin when there is no ability to change the ingredients; the most glaring problems arise with combination or multi-serving items where the exact ingredients utilized are at the whim of the patron.

There are two chief problems: first due to space limitations on the physical menu calorie counts are actually restricted to ranges due to the different choices associated with a given meal option.13 These calorie postings do not differentiate between the different options instead indicating that the options range between say 500 to 1860 calories. It is almost impossible to expect even active patrons to be able to effectively manage their diets with such a large gap and a lack of more specific information. Second, there is some concern that those ranges are inaccurate, accidentally or purposely lowered on the menu versus actual calorie counts or even information on the restaurant’s own website.13,14 Unfortunately the five options currently being considered by the FDA to present calorie information do not appear to alleviate the problems with combination menu items. The five considered options are: 1) a single average value; 2) a minimum to maximum range; 3) means; 4) medians; 5) hybrid models;13

What is almost insulting about this list of options is that clearly the first four options will do almost nothing to help individuals make informed food selections because of the lack of specificity. The hybrid model does little better due to its complexity because the calorie count posted would depend on the overall range of calories in all of the offered food combinations, but still not good enough.13

The almost silly thing about all of these options is that they seem to exist to avoid inconveniencing or ‘over-burdening’ food establishments. What is the point of applying a food calorie regulation to these establishments if one allows them to skirt along the edge of the requirement. It gives the impression that government is saying to patrons, “well those establishments have some form of calorie count it is not our job to require them to simplify it to the point where you don’t need to do your own intensive research or have a degree in biochemistry to track the amount of calories you are consuming for today’s meal.” The FDA needs to either require transparent simplicity or just not bother at all.

What would transparent simplicity look like? First, the requirement of the calorie posting next to the meal item on the menu itself is understandable in its intent, but as mentioned the limited space significantly reduces specific item combination accuracy. Every ‘chain’ restaurant has available wall space near the ordering area. In this wall space the restaurant should post a large nutritional chart with sufficient sized font (at least 12) providing information on each individual item with outline formatting for each additional option for a given item. Individual ingredient listing will be especially important for ‘construction’ food projects like sub sandwiches, fried chicken and pizzas. An example of this formatting is shown in the below figure (note that the associated numbers are fictional calorie counts)

Looking at the above figure note that the numbers are additive, thus if one orders a medium pizza with onions and olives the total calorie count will 970. The placement of this chart should have its ceiling at six and half feet above the floor allowing for easy viewing for most adults and the items should be listed in alphabetical order to reduce searching time. Also for restaurants that have a lot of combination potential it would also help to provide patrons a quick means of summating the total calorie counts of their meals. To this end the restaurants should supply a calculator tethered to the chart similar to how a bank has pens attached to various writing surfaces. Obviously the calculator does not need to be an expensive scientific model just one that can add, subtract and multiply.

Although there are arguments that it has been politicized due to special interests, a copy of the new FDA food chart should be displayed next to the nutritional information to provide an additional element of context with regard to balanced eating. The calorie chart could then show how each of the major areas in the chart (Grain, Protein, Fruit and Vegetable) is represented in each menu item. Some may argue that this is too much to expect from restaurants, but most menu items in restaurants are static, thus food chart/plate analysis will only need to be conducted once.

However, simply providing the calorie information may not be enough. Some researchers identified interesting self-destructive behavior by some individuals that utilized calorie counts when making food purchases. In certain circumstances the net amount of calories consumed in a day did not significantly change between a group that was exposed to calorie information versus a group that was not exposed to any calorie information.8 There are two possible explanations for this behavior: first, individuals purposely ate less when eating in the restaurant leaving them hungrier later in the day to which their response was to eat more food than those who ordered more food in the restaurant. Second, individuals took a psychological ‘reward’ approach in that because they were ‘good’ and ordered a lower calorie meal at the restaurant there was more leeway to eat more later. Interestingly when patrons were ‘reminded’ that the average person should consume approximately 2000 calories per day this ‘catch-up calorie consumption’ tendency is lessened.8 The reason for this change is not overly clear, but the explanation may be in the next paragraph.

What the above study may identify is that consumers still need a context in which to apply the counted calories. Without floors and ceilings the counts are simply just meaningless numbers. In addition to reminding patrons of the generally acknowledged calorie ceiling, they should also be reminded to actually count calories. A sign near each register asking if the patron is satisfied with the calorie count of their meal with the 2000 calorie per day reminder should be sufficient. It must be understood that restaurants are not responsible for whether or not individuals make healthy food selections; it is simply their responsibility to ensure that patrons are properly informed regarding the nutritional content of their food options and not to favor any food choice over another.

If the above recommendations were accurately followed then patrons should have requisite information to make informed decisions regarding what foods they consume outside of the home. However, there are some other issues that need to be addressed. One important element of addressing calorie count charts, especially for the poor, is monetary efficiency. If a patron can see that one food item costs $2 and has 500 calories and another food item costs $2 and has 300 calories the individual may select the first item because he/she receives more calories for money spent. Also there is some evidence to suggest that providing calorie information could reduce the motivation to tax unhealthy foods.15,16

The potential of calorie counts to shift responsibility on consumers over service providers, thus possibly reducing the probability of applying a tax to unhealthy foods is also a notable consequence. One important issue with regards to changing eating habits is that healthy food is typically more expensive than unhealthy food. Clearly from an economic and health perspective it is important to close, if not reverse, that gap. However, some studies have reported that lowering the costs of healthy foods do not translate into increased purchase, but increasing unhealthy food price does.17,18 Thus policy makers must ensure that creating regulation for posting calorie charts is not the end result of regulation if the obesity problem continues.

In addition accurate calorie information could eliminate a psychological tactics used by some dieters in inherently overestimating calorie counts on high calorie items. The psychology goes that a dieter will see a high calorie food item and assume that based on the ingredients the calorie count has to be x large. If the calorie count is available the dieter may realize that he/she had overestimated the calorie count and justify purchase by presuming overestimation of calories on other food items. However, while it is important to point out these concerns so they can be appropriately addressed none of these above concerns are significant enough to warrant terminating the idea of posting accurate calorie count information in restaurants.

Overall the general idea behind posting calorie counts is sound as long as the regulations surrounding it are genuinely applied. However, one cannot simply presume that the application of this strategy will single-handily end the rise in obesity rates; it is just one element in the fight against societal expansion of obesity.

--

1. Bowman, S and Vinyard, B. Fast food consumption of US adults: impact on energy and nutrient intakes and overweight status. J. Am. Coll. Nutr. 2004;23:163–168.

2. Kuo, T, et Al. “Menu Labeling as a Potential Strategy for Combating the Obesity Epidemic: A Health Impact Assessment.” Amer. J. Public Health. Sept. 2009. 99(9): 1680-1686.

3. Industry at a glance. National Restaurant Association Web site. Available at: http://www.restaurant.org/pdfs/research/2009Factbook.pdf. 2009.

4. Keystone center backgrounder—Keystone forum on away-from-home foods: opportunities for prevention weight gain and obesity report. 2006.

http://www.ers.usda.gov/Briefing/CPIFoodAndExpenditures/Data.

5. Burton, S and Creyer, E. “What consumers don’t know can hurt them: consumer evaluations and disease risk perceptions of restaurant menu items.” J. Consum. Aff. 2004. 38: 121–145.

6. Burton, S, et Al. “Attacking the obesity epidemic: the potential health benefits of providing nutrition information in restaurants. Am. J. Public Health. 2006. 96:1669–75.”

7. Finkelstein, E, et Al. “Mandatory menu labeling in one fast food chain in King County, Washington.” Am J Prev Med. 2011. 40(2): 122–127.

8. Pulos, E and Leng, K. “Evaluation of a voluntary menu-labeling program in full-service restaurants.” Am J Public Health. 2010. 100(6): 1035–1039.

9. Roberto, C, et Al. “Evaluating the impact of menu labeling on food choices and intake.” Am J Public Health. 2010. 100(2): 312–318.

10. Elbel, B, et Al. “Calorie labeling and food choices: a first look at the effects on low-income people in New York City.” Health Aff 2009. 28: 1110–21.

11. Downs, J, Loewenstein, G, and Wisdom, J. “Strategies for promoting healthier food choices.” Am Econ Rev 2009. 99:159–64.

12. Harnack, L and French, S. “Effect of point-of-purchase calorie labeling on restaurant and cafeteria food choices: a review of the literature.” Int J Behav Nutr Phys Act 2008. 5:51.

13. Cohn, E, et Al. “Calorie Postings in Chain Restaurants in a Low-Income Urban Neighborhood: Measuring Practical Utility and Policy Compliance.” Journal of Urban Health. 2012. DOI: 10.1007/s11524-012-9671-0

14. Wootan, M and Osborn, M. “Availability of nutrition information from chain restaurants in the United States.” Am J Prev Med. 2006. 30(3):266–268.

15. Giesen, J, et Al. “Exploring how calorie information and taxes on high-calorie foods influence lunch decisions.” Am J Clin Nutr. 2011. 93:689–94.

16. Epstein, L, et Al. “The influence of taxes and subsidies on energy purchased in an experimental purchasing study.” Psychol Sci. 2010. 21:406–14.

17. Epstein, L, et Al. “Purchases of food in youth. Influence of price and income.” Psychol. Sci. 2006. 17:82–9.

18. Epstein, L, et Al. “Price and maternal obesity influence purchasing of low- and high-energy-dense foods.” Am. J. Clin Nutr. 2007. 86:914–22.

Intestinal Bacteria and Obesity

Some important biochemical interactions and responses to obesity have previously been discussed here.

In recent years explanations for the sudden rise in obesity have ranged from a further unbalanced internal biological energy balance to environmental pollution. Another accompanying explanation that is gaining support is that the type of bacteria residing in an individual’s intestinal tract is important relative to what foods an individual consumes. There is widespread belief that particular bacteria types drive certain metabolic rates and processes that have a significant effect on weight loss vs. weight retention.

The digestive process can be broken down into three stages after chewing. First, the food enters the stomach and is rendered into chyme by hydrochloric acid. Second, the chyme goes into the small intestine where a vast majority of the nutrient absorption occurs through osmosis, active transport and diffusion to nearby capillaries and eventual transport to the blood stream. Third, the indigestible and unabsorbed material passes through the large intestine where some of the indigestible material is processed (usually fermentation) by appropriate intestinal bacteria, water is reabsorbed and remaining material is packaged for excretion. It is this third element that is of particular interest here.

The human intestinal “metagenome” consists of trillions of microbes that provide enhanced metabolic capabilities due to absent enzyme inclusion (polysaccharide metabolization), protection against pathogens (indirect mucosal defense and luminal colonization competition), immune system support and aids gastrointestinal development and maintenance through interaction with epithelial cells.1-5 The two major elements which drive the specific populations of the metagenome in a given individual are genetics and diet. At the moment there is little that can be done regarding genetics, but the influence of diet is prevalent and that influence begins as early as infancy.1 In fact there is reason to believe that this “metagenome” is most influenced within the first few years of life and can have significant effect on immunity development.6,7

A vast majority of intestinal bacteria belong to one of two phylum of bacteria: Firmicutes and Bacteroidetes. Among these two phylum the bacteria in the intestinal with the largest populations are thought to be (in no particular order) genera Bacteroides (bact.), Clostridium (firm.), Bifidobacterium (bact.), Peptostreptococcus (firm.) and Ruminococcus (firm.) with minor populations of Escherichia (proteo), Lactobacillus (firm), Enterobacter (proteo) and Enterococcus (firm) with various methanogens.3,8,9. The parentheses identify the phylum type for the particular bacteria. It must be emphasized that specifics regarding exact populations are still far and few between relative to the specific genus which make up the Firmicutes and Bacteroidetes phylums for they contain 250 and 20 genera respectively;10 however, it is thought that Ruminococcus makes up a significant percentage of the Firmicutes phylum. On a side note Firmicutes bacteria are typically gram-positive (outside a very small few which have pseudo membrane walls) and Bacteroidetes bacteria are typically gram-negative.

Not surprisingly various intestinal bacteria populations are not evenly distributed throughout the digestive system, but each specific bacteria group has some environmental niche, notable is that higher bacterial populations are found in the lower portion of the intestinal tract vs. the upper portion. Also the upper portion has a large percentage of aerobic bacteria vs. the lower portion having a large percentage of anaerobic bacteria with the terminal ileum as the transition zone.7,11

The principle reason why intestinal bacteria have perked interest in the obesity ‘epidemic’ originated from an experiment in mice which demonstrated that intestinal bacteria play an important role in energy metabolism and weight changes. The study involved using a set of control mice and axenic mice (note that axenic mice are mice without any significant amounts of intestinal bacteria i.e. germ-free mice). Under normal conditions the axenic mice, controlled for age and background, weighted about 40% less than the control mice. However, after colonizing intestinal microflora (from the distal section) derived from the control mice within the axenic mice, the weight of the axenic mice increased by 60% over a short period of time.12 The inclusion of the microflora is thought to influence weight gain through three mechanisms: increases in intestinal glucose absorption, energy extraction from indigestible foods and concomitant higher glycemia and insulinemia.12,13

Changes in the suggested mechanisms from above are though to occur through influence on the action of two signaling proteins: carbohydrate response element-binding protein (ChREBP) and liver sterol response element-binding protein type-1 (SREBP-1) which in turn influence intestinal fasting-induced adipocyte factor [Fiaf; a.k.a. (angiopoietin-like protein 4)].14 When Fiaf is expressed it inhibits lipoprotein lipase activity, which increases the probability that fatty acids are released from triacylglycerols; these fatty acids can then be absorbed by muscles and adipose tissues to be used as energy (basically the fatty acids are consumed). If Fiaf is not expressed then lipoprotein lipase activity increases, increasing the probability of more fat synthesis. Germ-free mice seem to avoid obesity due to excess food consumption, commonly called diet-induced obesity, through three independent mechanisms: increased levels of Fiaf, increased levels of adenosine monophosphate activated protein kinase and reduced food consumption.14

Since the original study more studies have demonstrated differing intestinal bacteria populations in individuals of various weights. Most studies have developed support for a similar pattern between the obese and the non-obese in that more obese mice have a higher population of Firmicutes over Bacteroidetes.15-18 However, other studies have demonstrated no changes with populations in these bacteria or even the reverse with Bacteroidetes at higher population than Firmicutes.19,20 Thus the principle question becomes: do bacteria x protect against obesity in some way or are they simply preferentially selected in non-obese individuals vs. bacteria x which are preferentially selected in obese individuals?

Associate these elements with the fact that the Firmicutes/Bacteroidetes ratio drops when obese individuals lose weight (assuming no dramatic increase in fiber consumption) and Firmicutes population could be tied to fat, possibly through lipid production and storage. One study did demonstrate specific enzymatic activity in obese individuals associated with gram positive bacteria (Firmicutes) over gram negative bacteria (Bacteroidetes).21,22

The problem with fully determining the role of the Firmicutes/Bacteroidetes relationship is the contrasting results. For example some studies report that Bacteroidetes population increases from 3% to 15% with a hypocaloric diet in obese individuals where the Firmicutes population does not undergo significant changes.13,19 If this case is accurate it indicates that Firmicutes growth is not augmented by increased calories/fat, but instead Bacteroidetes growth is inhibited by those elements in some way. However, others report a decrease in Firmicutes population with weight loss and a decrease in Bacteroidetes (50% reduction) in obese individuals vs. non-obese.19

The issue with the Firmicutes/Bacteroidetes ratio may not be the change in the ratio, but instead the change in absolute population. For example in obese individuals what drives the change in the ratio, a decrease in Bacteroidetes population, an increase in Firmicutes population or do both change in general consort with each other? For example if an increase in the Firmicutes population is the dominating factor then it could be possible that Firmicutes responds to non-insoluble fiber elements. However, if a decrease in the Bacteroidetes population is the dominating factor then it could be possible that Bacteroidetes reduces fat absorption.

Other results have shown that axenic mice gain more weight when colonized with microbiota from obese mice opposed to lean mice.15 This result leads to the question of whether Firmicutes are able to extract more energy from a conventional diet over Bacteroidetes or do Firmicutes drive greater amounts of fat storage over Bacteroidetes? The second possibility sees support in that decreases in Bifidobacterium in mice fed a high fat diet also correlated to an increase in lipid polysaccharide (LPS) concentrations.23

The ‘battle’ between Firmicutes and Bacteroidetes begins at birth. The most influential element in early childhood appears to be the duration of time an infant spends consuming breast milk over solid foods and formulas.1 Based on comparisons of Firmicutes and Bacteroidetes populations between infants who consume breast milk and infants who consume formula, infants that consume breast milk longer have lower Firmicutes/Bacteroidetes ratios and seem to have lower probabilities for future obesity1,24-26 (E/A, Gillman et al. 2001, Kalies et al. 2005, Mayer-Davis et al. 2006). Examination of different populations of infants between Africa and Europe supported this conclusion of higher Bacteroidetes populations and lower Firmicutes populations in children breastfeed longer. The rationality behind the difference between African and European children is that Africa infants had to be breastfeed for additional time due to financial limitation or resource availability regarding formula.

One of the major reasons for this developmental difference seems to be the population growth of Lactobacilli and Bifidobacteria in breastfeed infants vs. formula feed infants, which fail to develop these two types of bacteria in significant proportions.27-29 The colonization of Bifidobacteria is thought to be especially important in the maturation of the intestinal lining and localized lymphoid tissue and delayed Bifidobacterial colonization increases the probability of a variety of gastrointestinal and/or allergic conditions.30-32

Originally it was thought that the bacteria present in breast milk was from skin contaminates, but recent testing has developed support for the idea that the bacteria is, not surprisingly, derived from the maternal intestine and follows the entero-mammary pathway to the mammary gland.33 Also no Bifidobacteria has ever been isolated from skin samples from women who have Bifidobacteria in their breast milk.30 The derivation of these bacterium from the mother’s own intestinal system may provide insight into why obese mothers have children that are pre-disposed to becoming obese and why fit mothers have children that have resistance against obesity as those bacteria populations heavily influence the populations in the infants.

Another important association between intestinal bacteria and obesity is the role of interspecies hydrogen transfer from hydrogen producing bacterium to hydrogen consuming methanogens. Non-obese individuals have very small methanogen-based intestinal populations whereas obese individuals have larger populations.10 This population shift has also been associated with genetically homogeneous obese mice (ob+/ob+) over heterogeneous mice (ob+/ob-) and homogeneous non-obese (ob-/ob-).15 The association with genetically obese mice over mice that have become obese through food consumption supports the notion that methanogen population influences weight over methanogen bacteria being selected for based on weight. Basically the methanogen population of bacteria expands first before one gains significant weight. The importance behind this relationship is best demonstrated by understanding the biochemical process involved in the formation of fatty acids in the body.

Methanogens like Methanobrevibacter smithii enhance fermentation efficiency by removing excess free hydrogen and formate in the colon. A reduced concentration of hydrogen leads to an increased rate of conversion of insoluble fibers into short-chain fatty acids.10 Proprionate, acetate, butyrate and formate are the most common SCFAs formed and absorbed across the intestinal epithelium providing a significant portion of the energy for intestinal epithelial cells promoting survival, differentiation and proliferation ensuring effective stomach lining.3,10,34 Butyric acid is also utilized by the colonocytes.35 Formate also can be directly used by hydrogenotrophic methanogens and propionate and lactate can be fermented to acetate and H2.10

The Methanobrevibacter smithii population in non-obese individuals is very small on an absolute level whereas the population in obese individuals is much higher (gastric). This result is supported by metagenomic study which identified more Archaea gene fragments in ob+/ob+ mice over leaner heterogeneous ob+/- or ob-/ob- mice.15 Overall the population of Archaea bacteria in the gut, largely associated to Methanobrevibacter smithii, is tied to obesity with the key factor being availability of free hydrogen. If there is a lot of free hydrogen then there is a higher probability for a lot of Archaea, otherwise there is a very low population of Archaea because there is a limited ‘food source’.

Interestingly anorexic individuals also see an increase in Methanogen bacteria (Methanobrevibacter) over non-obese healthy individuals.21 This increase in anorexic individuals seems to make sense as fermentation rates probably increase in effort to maximize energy optimization from food intake due to reduced food consumption. Increased fermentation rates would increase H2 concentrations resulting in increased Methanogen populations.

Other investigators have looked at how receptor interaction with intestinal microbes influences weight. A promising avenue of research is Toll-like receptor (TLR) 5, a transmembrane protein expressed in the intestinal mucosa that recognizes bacterial flagellin.35 Analysis of TLR5 knockout mice vs. controls demonstrates a 20% greater body mass in the knockouts, a weight which corresponds to an increase in visceral fat.35 This additional body mass is thought to occur through greater food consumption (knockout mice consume 10% more food than controls), which seems to lead to greater fat deposit formation. However, despite this increased food consumption there were no significant changes in short-chain fatty acid concentrations between knockouts and controls.35 Also due to mixed results it is difficult to draw any conclusions regarding differing influences on orexigenic or anorexic hormones between knockouts and control.35

Elimination of intestinal bacteria through broad spectrum antibiotic treatment supported the contention that intestinal bacteria and TLR5 had an interactive relationship in controlling an individual’s weight as germfree TLR5 knockout mice did not suffer from the same weight gain as their TLR5 knockout non-germ free kin.35 The implantation of the microbiota from a TLR5 knockout mouse into a previously germ-free non-knockout mouse lead to the development of a similar phenotype to the TLR5 knockout in the germ-free mouse.35 This result suggests that there are certain bacteria that interact with TLR5 because despite the non-knockouts having the necessary receptors they still develop attributes similar the knockouts, thus the microbiota of the knockouts do not appear to have the required bacteria for activation. This lacking makes sense because without TLR5 receptors it stands to reason that bacteria, which activate TLR5, would be selected against.

Based on the information above it appears that activation of TLR5 somehow reduces weight gain. This result occurs either through interaction between TLR5 and orexigenic and anorexic hormones (which would influence appetite) or involves the reduction in fat deposit synthesis from soluble elements. Due to the results from germfree knockouts and the mixed hormone results, the second possibility seems viable. For example interaction between Bacteroidetes and TLR5 could lead to the inhibition of lipoprotein lipase activity (possibility through increased expression of Fiaf). This action would result in less fat storage and less overall weight gain.

If the above contention were true this action of changing Fiaf expression probably has a positive feedback effect in lean individuals and a negative feedback effect in obese individuals. For example as individuals lose weight the Bacteroidetes population increases which would lead to more TLR5 activation and less fat storage. However, as individuals gain weight Bacteroidetes population decreases which would lead to less TLR5 activation and increase the probability for greater fat storage.

One of the big remaining questions is how do the populations of Bacteroidetes and Firmicutes change to influence weight changes? One possibility is that while both Bacteroidetes and Firmicutes assist in fermentation perhaps Bacteroidetes are more responsive to complex sugars and other complex carbohydrates and Firmicutes are more responsive to simple sugars. Usually obese individuals consume lots of fat and simple sugars which are converted more easily to fat. The consumption of these types of foods select for Firmicutes over Bacteroidetes. When an individual loses weight it typically involves changes in the diet largely a reduction the amount of simple sugars and fats. This change could lead to a reduction in Firmicutes and due to less competition from the Firmicutes a corresponding increase in Bacteroidetes.

Another possibility for the increase in Bacteroidetes is that weight loss (excluding surgical intervention) involves a large amount of exercise. This additional exercise would lead to larger demands for energy consumption both in currently stored fat and newly consumed food. Such a change should reduce the amount of fat storage possibly involving the increased expression of TLR5 which could increase the population of Bacteroidetes if Bacteroidetes do indeed activate TLR5.

Overall it certainly appears that Firmicutes and Bacteroidetes play an important role in controlling weight. This influence seems to stem from two different mechanisms: overall food consumption and the extraction of energy from that food and probability of fat storage vs. fat consumption. While the exact mechanisms have not been discovered, Bacteroidetes appears to favor lean bodies and Firmicutes appears to favor obese bodies. Whether or not there is an evolutionary element is unclear. Beastfeeding also appears to be an important early element in driving either a lean or obese future. Due to potential feedback elements associated with fat content and intestinal bacteria populations like Firmicutes doping individuals with Bacteroidetes like Bifidobacteria may seem like a good idea, but the best option for weight loss involves the old stable tactics of high quality diet with insoluble fibers and exercise.

--
Citations:

1. Filippo, C, et, Al. “Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa.” PNAS. 2010. 107(33): 14691-14696.

2. Backhed, F, et, Al. “Host-bacterial mutualism in the human intestine.” Science. 307:1915-1920.

3. Son, G, Kremer, M, Hines, I. “Contribution of Gut Bacteria to Liver Pathobiology.” Gastroenterology Research and Practice. 2010. doi:10.1155/2010/453563.

4. DiBaise, J, Young, R, and Vanderhoof, J. “Enteric microbial flora, bacterial overgrowth and short bowel syndrome.” Clin Gastroenterol Hepatol. 2006. 4(1):11-20.

5. Gorbach, S. “Probiotics and gastrointestinal health.” Am J Gastroenterol. 2000. 95(1 suppl):S2-S4.

6. Palmer, C, et, Al. “Development of the human infant intestinal microbiota.” PLoS Biol. 2007. 5(7):e177. doi:10.1371/journal.pbio.0050177.

7. Berg, R. “The indigenous gastrointestinal microflora.” Trends Microbiol. 1996. 4(11):430-435.

8. Guarner, F and Malagelada, J. “Gut flora in health and disease.” Lancet. 2003. 361(9356): 512–519.

9. Moore, W and Moore, L. “Intestinal floras of populations that have a high risk of colon cancer.” Applied and Environmental Microbiology. 1995. 61(9):3202–3207.

10. Zhang, H, et, Al. “Human gut microbiota in obesity and after gastric bypass.” PNAS. 2009. 106(7): 2365-2370.

11. Rolf, R. “Interactions among microorganisms of the indigenous intestinal flora and their influence on the host.” Rev Infect Dis. 1984. (6)(suppl 1): S73-S79.

12. Backhed, F, et, Al. “The gut microbiota as an environmental factor that regulates fat storage.” PNAS. 2004. 101(44): 15718–23.

13. Cani, P, et, Al. “Role of gut microflora in the development of obesity and insulin resistance following high-fat diet feeding.” Pathologie Biologie. 2008. 56:305–309.

14. DiBaise, J, et, Al. “Gut Microbiota and Its Possible Relationship With Obesity.” Mayo Clin. Proc. 2008. 83(4): 460-469.

15. Turnbaugh, P, et, Al. “An obesity-associated gut microbiome with increased capacity for energy harvest.” Nature. 2006. 444(7122):1027–31.

16. Ley, R, et, Al. “Obesity alters gut microbial ecology.” PNAS. 2005. 102:11070–11075.

17. Armougom, F and Raoult, D. “Use of pyrosequencing and DNA barcodes to monitor variations in Firmicutes and Bacteroidetes communities in the gut microbiota of obese humans.” BMC Genomics. 9:576, 2008.

18. Guo, X, et, Al. “Real-time PCR quantification of the predominant bacterial divisions in the distal gut of Meishan and Landrace pigs.” Anaerobe. 2008. 14:224-228.

19. Ley, R, et, Al. “Microbial ecology: Human gut microbes associated with obesity.” Nature. 2006. 444:1022–1023.

20. Duncan, S, et, al. “Human colonic microbiota associated with diet, obesity, and weight loss.” Int J Obes. 2008.

21. Armougom, F, et, Al. “Monitoring Bacterial Community of Human Gut Microbiota Reveals an Increase in Lactobacillus in Obese Patients and Methanogens in Anorexic Patients.” PLoS ONE. 2009. 4(9):e7125.

22. Turnbaugh, P, et, Al. “A core gut microbiome in obese and lean twins.” Nature. 2009. 457:480–484.

23. Cani, P, et, Al. “Selective increases of bifidobacteria in gut microflora improves high-fat diet-induced diabetes in mice through a mechanism associated with endotoxemia.” Diabetologia. 2007. 50(11):2374–83.

24. Gillman, M, et, Al. “Risk of overweight among adolescents who were breastfed as infants.” JAMA. 2001. 285:2461-2467.

25. Kalies, H, et, Al. “The effect of breastfeeding on weight gain in infants: results of a birth cohort study.” Eur J Med Res. 2005. 10:36-42.

26. Mayer-Davis, E, et, Al. “Breast-feeding and risk for childhood obesity: does maternal diabetes or obesity status matter?” Diabetes Care. 2006. 29:2231-2237.

27. Balmer, S and Wharton, B. “Diet and faecal flora in the newborn: breast milk and infant formula. Arch. Dis. Child. 1989. 64:1672–1677.

28. Favier, C, De Vos, W, Akkermans, A. “Development of bacterial and bifidobacterial communities in feces of newborn babies.” Anaerobe. 2003. 9:219–229.

29. Haarman, M and Knol, J. “Quantitative real-time PCR assays to identify and quantify fecal Bifidobacterium species in infants receiving a prebiotic infant formula.” Appl. Environ. Microbiol. 2005. 71:2318–2324.

30. Martín, R, et, Al. “Isolation of Bifidobacteria from Breast Milk and Assessment of the Bifidobacterial Population by PCR-Denaturing Gradient Gel Electrophoresis and Quantitative Real-Time PCR.” Applied and Environmental Microbiology. 2009. 75(4):965-969.

31. Arvola, T, et, Al. “Rectal bleeding in infancy: clinical, allergological, and microbiological
examination.” Pediatrics. 2006. 117:e760–e768.

32. Mah, K, et, Al. “Distinct pattern of commensal gut microbiota in toddlers with eczema.” Int. Arch. Allergy Immunol. 2006. 140:157–163.

33. Perez, P, et, Al. “Bacterial imprinting of the neonatal immune system: lessons from maternal cells?” Pediatrics. 2007. 119:e724–e732.

34. L. Luciano, R. Hass, R. Busche, W. V. Engelhardt, and E. Reale, “Withdrawal of butyrate from the colonic mucosa triggers ’mass apoptosis’ primarily in the G0/G1 phase of the cell cycle.” Cell and Tissue Research. 1996. 286(1):81–92.

35. Cummings, J and Macfarlane, G. “The control and consequences of bacterial fermentation in the human colon.” Journal of Applied Bacteriology. 1991. 70:443459.

36. Vijay-Kumar, M, et, Al. “Metabolic Syndrome and Altered Gut Microbiota in Mice Lacking Toll-Like Receptor 5.” Sciencexpress. 2010. 10.1126/science.1179721.