What is the function of bacteria in the human mouth?


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Most of the data available so far identifies bacterial species that tend to be associated with healthy versus diseased oral cavities but not much is known about exactly what health-associated ones do apart from keeping out the disease-associated ones.

Oral Cavity, A Complex Ecosystem Of Several Specialized Ecological Niches

Gaining insight begins with the appreciation that the oral cavity is a complex habitat further sub-divided into distinct smaller ones ranging from the non-keratinized Oral mucosa to the keratinized Tongue and gingiva, i.e., Gums, as well as Tooth enamel and a variety of dental implants. Thus, depending on its proximity to the gum line, dental plaque is either supra- or subgingival, and the bacteria that inhabit these two regions are different, supragingival plaque dominated by gram-positive Streptococci while subgingival by gram-negative anaerobic bacteria (1).

Since the oral cavity is exposed to the outside world, these surfaces are colonized soon after birth, with some evidence suggesting vertical (mother-to-baby) transmission (2) as well as similarities between family members (3). Stable inhabitants, formally called autochthonous, establish Biofilm, a kind of super-organism consisting of cooperating microbes. Being open, oral cavity also gets plenty of visitors, transients, formally called allochthonous.

Older studies suggested oral cavity diseases are associated with changes in microbial diversity (1).

Gum diseases, i.e., Periodontal pathology, and tooth decay, i.e., Dental caries, are associated with increase (4, 5, 6) and decrease (7), respectively, in microbial diversity. More recent state-of-the-art molecular approaches (8, 9) confirm these decades-old findings. This implies oral cavity disease isn’t so much a matter of presence or absence of certain microbes since those with disease-causing potential, i.e., pathobionts, are present even in health (10) but rather about their relative proportions in complex biofilms.

Colonisation resistance Is A Key Feature Of Healthy Oral Cavity Microbiota

Like other microbe-associated body sites, the oral cavity too is a series of specialized niches occupied by specific microbes capable of specialized functions both necessary and predicated on some inherent properties of these niches. The ones who establish stable presence in the form of complex, multi-species biofilms dominate their specific niches by preventing others, including pathogens, from establishing themselves, i.e., Colonization Resistance (11). When the oral cavity is stably colonized by beneficial microbe biofilms, it’s healthy. Instability in beneficial microbe colonization is a weakness that’s then exploited by more harmful and even pathogenic species to dominate oral cavity biofilms, with the outcome either tooth decay (Dental Caries) or gum disease (Periodontitis).

Tooth decay (Dental caries) is associated with certain species of Streptococci such as Streptococcus mutans and species of Lactobacilli (12) while subgingival anaerobes establish their communities within periodontal pockets, some of whom such as Porphyromonas gingivalis are associated with gum disease (Periodontitis) (13, 14).

Obviously diet profoundly influences not only which bacterial species stably establish within oral biofilms but also dominate.

  • Thus though S. mutans is part of normal oral microbiota (15), it doesn’t dominate in healthy oral cavities.
  • However, its capacity to metabolize sucrose more efficiently compared to other oral bacteria (16) gives it a competitive advantage in the oral cavities of those who predominantly consume the highly processed, sucrose-heavy ‘Western’ diet.
  • S. mutans can also convert sucrose to adherent glucans, which helps it to attach more strongly to teeth (17).
  • S. mutans also rapidly converts sucrose to lactic acid, giving it an added selective advantage owing to its intrinsic capacity to withstand such acidic environments (18, 19).
  • These properties may help S. mutans and Lactobacilli dominate in tooth decay, i.e., dental caries, the latter because they metabolize lactic acid generated by S.mutans.

Similar studies done decades apart, scraping plaques from people with or without gum disease and culturing the bacteria that grew out with bacterial species associated with gum disease showed plaques from people without gum disease can inhibit growth of gum disease-associated bacterial species (20, 21). How?

  • Streptococcus sanguinis is considered an inhabitant of normal dental plaque. Less acid-tolerant than its presumed niche competitor, S. mutans, S. sanguinis produces Hydrogen peroxide, toxic for S. mutans, which typically lacks capacity to effectively neutralize it (22, 23). Thus, dental plaques rich in S. sanguinis contain relatively lower proportions of dental caries-associated S. mutans and periodontitis-associated P. gingivalis (20).
  • Veillonella species (24) and S. oligofermentans (25) readily metabolize lactic acid secreted by S. mutans. A revealing window into how inter-species competition can engender colonization resistance, S. oligofermentans not only utilizes S. mutans-generated lactic acid but converts it into hydrogen peroxide, highly toxic to the latter (26).
  • Streptococcus gordonii offers another plausible example of colonization resistance tactic. Another inhabitant of healthy oral cavities, in vitro it could prevent stable S. mutans colonization by inactivating one of its important resistance mechanisms , ability to synthesize a Quorum sensing molecule, CSP (competence-stimulating peptide) (27). When thus hobbled, S. mutans is much less capable of resisting natural salivary antimicrobial peptides such as Histatin (1).
  • Oral cavity bacteria also secrete Bacteriocin. Proteinaceous toxins, bacteriocins differ from antibiotics, having a much narrower killing spectrum and acting on related organisms (1).

Thus, as long as diet is varied enough to also allow stable plaque colonization by base-producing microbes, acid-producing S. mutans wouldn’t be able to predominate and take over local plaque ecosystem.

Food web Relationships Between Normal Oral Cavity Microbes Help Maintain Their Stability

As is the hallmark of ecosystems consisting of mutually dependent residents, the healthy oral cavity too contains microbes engaged in Food web activities, i.e., metabolic end products of one species used by others.

  • Oral biofilm Streptococci synthesize lactate that Veillonella use (1).
  • S. sanguis and S. oralis are inhabitants of healthy oral biofilms. In vitro culture studies suggest their mutually helpful, i.e., synergistic, capacity to digest mucins helps them more efficiently use such complex host sugars as nutrition (28).
  • Oral cavity is constantly bathed in saliva and gingival crevicular fluid. Composite of products of not just human tissue cells but also microbes, some microbial inhabitants appear to engage in synergistic/mutualistic interactions to overcome inherent handicaps to colonize. This seems to be the case with Actinomyces naeslundii and S. oralis that alone colonize saliva-coated surfaces poorly and yet can form extensive biofilms together by presumably combining their metabolic activities (29).

However, food web processes can also help shift oral biofilms to dominance by more pathogenic species. Though inhabitants of normal oral cavity, P. gingivalis, Fusobacterium nucleatum, Treponema denticola and Tannerella forsythia are also implicated in periodontal disease.

  • In vitro culture studies show P. gingivalis can metabolize succinate produced by T. denticola (30) while the latter can use isobutyric acid secreted by the former (31).
  • Both F. nucleatum and T. forsythia seem to secrete factors that stimulate growth of P. gingivalis (1).

Thus, whether mutualistic interactions of beneficial or harmful bacteria dominate in a given oral cavity is outcome of diet, oral hygiene and host genetic polymorphisms.

Why Knowledge Of Bacteria Function In Healthy Oral Cavity Is Better Gleaned From Older, Not Newer, Studies

Since the 2000s an explosion in molecular biological tools, so-called Omics, has led to a similar explosion in human microbiome studies. Since the oral cavity is one of the most easily accessible of all the GI tract niches, human oral cavity microbiome has become the best characterized in terms of the kinds of bacteria present in healthy versus unhealthy mouths.

  • Since such typically technocratically driven processes focus primarily on generating an avalanche of data and explore no underlying hypotheses, one may wonder whether the healthy human oral cavity microbiome’s function is simply absence of disease. That is to say, given the monumental scale of molecular biology data generated on this topic since at least the mid-2000s, it’s shocking how little is known about what any of it even means.
  • With older prejudices implicitly carried forward, there’s also been no attempt so far to synthesize the roles of bacteria and fungi in healthy oral cavities since fungi like Candida albicans were previously assumed to only represent disease states. Their repeated presence in healthy oral cavities suggests this idea needs revising (32).
  • Even less is known about role of Archaea such as Methanobrevibacter species frequently found in healthy oral cavities. Their increasing identification in gum disease (Periodontal pathology) suggests they too may be involved in such disease processes but how? Only in promoting growth of pathogenic bacterial species (33) or as initiators and perpetuators themselves?
  • Meantime overweening allegiance to novel technologies is powering this entire absurd process forward with the implicit hope that Data mining will uncover hidden patterns allowing certain predictive hypotheses to be made.
  • If past is any predictor of future, the failure of past dependence on novel molecular biological approaches alone to yield predictive insight into complex biological phenomena suggests a similar fate awaits the current giddy immersion in the latest molecular biological toys. A useful and telling example from the recent past is Microarray analysis techniques, the focus of tens of thousands of papers since the late 1990s, which nevertheless yielded little or no improved insight into disease processes nor did they much illuminate possible future predictive approaches to better understand them.
  • Necessity of extrapolating data from in vitro culture studies referenced in this answer is their major caveat. Nevertheless, we’d understand oral cavity-bacteria interactions better with more such experiments, especially in vitro co-cultures of human oral epithelial cells with candidate oral cavity commensals, more so co-cultures with commensal biofilms but such experimental approaches are technically much more challenging compared to powering a few cheek swab or saliva samples through the latest molecular biology apparatus. Hence the current absurd status quo.


1. Kuramitsu, Howard K., et al. “Interspecies interactions within oral microbial communities.” Microbiology and molecular biology reviews 71.4 (2007): 653-670. Interspecies Interactions within Oral Microbial Communities

2. Kobayashi, N., et al. “Colonization pattern of periodontal bacteria in Japanese children and their mothers.” Journal of periodontal research 43.2 (2008): 156-161. https://www.researchgate.net/pro…

3. Steenbergen, TJM van, et al. “Intra‐familial transmission and distribution of Prevotella intermedia and Prevotella nigrescens.” Journal of periodontal research 32.4 (1997): 345-350.

4. Löe, Harald, Else Theilade, and S. Börglum Jensen. “Experimental gingivitis in man.” Journal of periodontology 36.3 (1965): 177-187.

5. Listgarten, M. A. “Structure of the Microbial Flora Associated with Periodontal Health and Disease in Man: A Light and Electron Microscopic Study*.” Journal of periodontology 47.1 (1976): 1-18.

6. Syed, S. A., and W. J. Loesche. “Bacteriology of human experimental gingivitis: effect of plaque age.” Infection and immunity 21.3 (1978): 821-829.

7. Simon-Soro, A., et al. “A tissue-dependent hypothesis of dental caries.” Caries research 47.6 (2013): 591-600.

8. Diaz, P. I., A. Hoare, and B. Y. Hong. “Subgingival Microbiome Shifts and Community Dynamics in Periodontal Diseases.” Journal of the California Dental Association 44.7 (2016): 421. http://www.cda.org/Portals/0/jou…

9. Tanner, A. C., C. A. Kressirer, and L. L. Faller. “Understanding Caries From the Oral Microbiome Perspective.” Journal of the California Dental Association 44.7 (2016): 437. http://www.cda.org/Portals/0/jou…

10. Jiao, Y., M. Hasegawa, and N. Inohara. “The role of oral pathobionts in dysbiosis during periodontitis development.” Journal of dental research 93.6 (2014): 539-546. https://www.researchgate.net/pro…

11. Van der Waaij, D., J. M. Berghuis-de Vries, and J. E. C. Lekkerkerk-Van der Wees. “Colonization resistance of the digestive tract in conventional and antibiotic-treated mice.” Journal of Hygiene 69.03 (1971): 405-411. https://www.researchgate.net/pro…

12. Chhour, Kim-Ly, et al. “Molecular analysis of microbial diversity in advanced caries.” Journal of clinical microbiology 43.2 (2005): 843-849. Molecular Analysis of Microbial Diversity in Advanced Caries

13. ÖSterberg, Stic K‐Å., Sara Z. Sudo, and Lars EA Folke. “Microbial succession in subgingival plaque of man.” Journal of periodontal research 11.5 (1976): 243-255.

14. Ximénez‐Fyvie, Laurie Ann, Anne D. Haffajee, and Sigmund S. Socransky. “Microbial composition of supra‐and subgingival plaque in subjects with adult periodontitis.” Journal of clinical periodontology 27.10 (2000): 722-732. https://www.researchgate.net/pro…

15. Aas, Jørn A., et al. “Defining the normal bacterial flora of the oral cavity.” Journal of clinical microbiology 43.11 (2005): 5721-5732. Defining the Normal Bacterial Flora of the Oral Cavity

16. Hamada, Shigeyuki, and HUTTON D. Slade. “Biology, immunology, and cariogenicity of Streptococcus mutans.” Microbiological reviews 44.2 (1980): 331. http://www.ncbi.nlm.nih.gov/pmc/…

17. Gibbons, R. J., and M. Nygaard. “Synthesis of insoluble dextran and its significance in the formation of gelatinous deposits by plaque-forming streptococci.” Archives of oral biology 13.10 (1968): 1249-IN31.

18. Grenier, Daniel. “Antagonistic effect of oral bacteria towards Treponema denticola.” Journal of clinical microbiology 34.5 (1996): 1249-1252. Antagonistic effect of oral bacteria towards Treponema denticola.

19. Doran, A., S. Kneist, and Joanna Verran. “Ecological control: in vitro inhibition of anaerobic bacteria by oral streptococci.” Microbial Ecology in Health and Disease 16.1 (2004): 23-27. https://www.researchgate.net/pro…

20. Hillman, J. D., S. S. Socransky, and Myra Shivers. “The relationships between streptococcal species and periodontopathic bacteria in human dental plaque.” Archives of Oral Biology 30.11-12 (1985): 791-795.

21. van Essche, Mark, et al. “Bacterial antagonism against periodontopathogens.” Journal of periodontology 84.6 (2013): 801-811.

22. Carlsson, Jan, and May‐Britt K. Edlund. “Pyruvate oxidase in Streptococcus sanguis under various growth conditions.” Oral microbiology and immunology 2.1 (1987): 10-14.

23. Kreth, Jens, et al. “Competition and coexistence between Streptococcus mutans and Streptococcus sanguinis in the dental biofilm.” Journal of bacteriology 187.21 (2005): 7193-7203. Competition and Coexistence between Streptococcus mutans and Streptococcus sanguinis in the Dental Biofilm

24. Mikx, F. H. M., and J. S. Van der Hoeven. “Symbiosis of Streptococcus mutans and Veillonella alcalescens in mixed continuous cultures.” Archives of Oral Biology 20.7 (1975): 407-410.

25. Tong, Huichun, et al. “Streptococcus oligofermentans inhibits Streptococcus mutans through conversion of lactic acid into inhibitory H2O2: a possible counteroffensive strategy for interspecies competition.” Molecular microbiology 63.3 (2007): 872-880. https://www.researchgate.net/pro…

26. Bao, Xudong, et al. “Streptococcus oligofermentans inhibits Streptococcus mutans in biofilms at both neutral pH and cariogenic conditions.” PloS one 10.6 (2015): e0130962. http://journals.plos.org/plosone…

27. Wang, Bing-Yan, and Howard K. Kuramitsu. “Interactions between oral bacteria: inhibition of Streptococcus mutans bacteriocin production by Streptococcus gordonii.” Applied and environmental microbiology 71.1 (2005): 354-362. Inhibition of Streptococcus mutans Bacteriocin Production by Streptococcus gordonii.

28. Van der Hoeven, J. S., and P. J. M. Camp. “Synergistic degradation of mucin by Streptococcus oralis and Streptococcus sanguis in mixed chemostat cultures.” Journal of dental research 70.7 (1991): 1041-1044. http://citeseerx.ist.psu.edu/vie…

29. Palmer, Robert J., et al. “Mutualism versus independence: strategies of mixed-species oral biofilms in vitro using saliva as the sole nutrient source.” Infection and immunity 69.9 (2001): 5794-5804. Strategies of Mixed-Species Oral Biofilms In Vitro Using Saliva as the Sole Nutrient Source

30. Grenier, D., and D. Mayrand. “Nutritional relationships between oral bacteria.” Infection and immunity 53.3 (1986): 616-620. Nutritional relationships between oral bacteria.

31. Grenier, D. “Nutritional interactions between two suspected periodontopathogens, Treponema denticola and Porphyromonas gingivalis.” Infection and immunity 60.12 (1992): 5298-5301. Nutritional interactions between two suspected periodontopathogens, Treponema denticola and Porphyromonas gingivalis.

32. Krom, B. P., S. Kidwai, and J. M. Ten Cate. “Candida and Other Fungal Species Forgotten Players of Healthy Oral Microbiota.” Journal of dental research 93.5 (2014): 445-451. https://www.researchgate.net/pro…

33. Bang, Corinna, and Ruth A. Schmitz. “Archaea associated with human surfaces: not to be underestimated.” FEMS microbiology reviews (2015): fuv010. http://femsre.oxfordjournals.org…


How far are we from having our bacteria engineered to reduce obesity?


Refers to: https://www.sciencedaily.com/releases/2016/08/160827162200.htm

Though we’re still far from knowing enough to precisely engineer human weight loss through gut microbe manipulations, ironically, at least one case study (1) shows it’s possible to influence body weight simply by manipulating gut microbiota. Irony because the outcome in that case turned out to be inadvertent weight gain. Nevertheless this example offers

  • An important proof of principle that microbe transfers could mediate metabolic transformation in humans.
  • Insight into conditions necessary for effecting such transformation.
  • Scientific obstacles that stand in the way of using it to reverse obesity in human subjects.

In this report (1),

  • A 32-year old woman with recurrent Clostridium difficile infection (CDI) underwent Fecal microbiota transplant (FMT), her 16-year old daughter the FMT donor.
  • The FMT proceeded as planned after the daughter was screened and declared clear for HIV1 and 2, syphilis, hepatitis A, B and C, C. difficile, Giardia lamblia and other enteric pathogens,.
  • Post-FMT, the patient’s condition improved with no CDI recurrence . However, 16 months post-FMT, patient reported having gained 34 pounds. She now weighed 170 pounds with a BMI of 33, i.e., obese. This even though she hadn’t initially lost any weight over the months she underwent a series of antibiotic Rx for CDI.
  • Prior to FMT, the patient stably weighed 136 pounds with a BMI of 26 while her daughter weighed ~140 pounds with a BMI of 26.4.

How to explain why this happened?

  • The FMT donor, the patient’s daughter, provides the first clue. 140 pounds at the time of FMT, she too steadily gained weight to subsequently become 170 pounds. Obviously 16 years is the tail end of puberty, a life stage with profound hormonal and other physiological changes, which undoubtedly also impact gut microbiota composition.
  • In fact, the FMT donor’s subsequent weight gain suggests that as she completed puberty, her microbiota were changing in profile from one that supported a lighter weight to one more efficient in harvesting energy and thereby in promoting weight gain.
  • Seen in this light, this FMT recipient’s weight gain merely mirrors that of her donor’s, with the microbiota transfer the most likely change agent. Presumably post-FMT transplant, the recipient’s gut microbiota resembled those of the donor’s, i.e., more efficient in harvesting energy and thereby promoting weight gain.

Colonisation resistance Is An Important Obstacle To Microbe Transplant ‘Take’

While this FMT recipient’s weight gain can be plausibly explained as mimicking that of the donor’s, still the question needs further probing because doing so gets us to the crux of scientific obstacles in using microbe transfers to effect weight changes, be it gain or loss. Crux in this case is gut microbiota status quo in normal individuals and how it contrasts with the situation in this case report.

  • Healthy GI tracts have commensal microbes occupying the various GI tract niches as groups of specialized workers performing essential functions predicated on the needs of the niches they occupy. Thus, regardless a body is lean or obese, healthy guts have or should have niches that are microbially replete and successfully repel not only harmful invaders like C.diff but also other outsiders seeking to occupy the same niche, a process called Colonisation resistance.
  • This FMT recipient’s recurrent CDI suggests her gut microbiota was obviously already in considerable turmoil to start with. Prior to resorting to FMT, her already unstable GI tract microbiota was then subjected to antibiotic Rx consisting of metronidazole, vancomycin, amoxicillin, clarithromycin, rifamixin (1). Thus, by the time she underwent FMT, her GI tract was pretty depleted of stable microbial inhabitants, i.e., of robust colonization resistance capability. The microbes she received from her daughter’s poop would thus have been able to easily colonize the now available niches in her GI tract.
  • Genetics is another important factor, as in relatedness between donor and recipient, which presumably increased the likelihood of ‘take’ of donor’s microbes in the recipient’s GI tract (1). A 2016 study (2) was among the first to a) monitor long-term fate of FMT in human recipients, and b) observe different fates of same-donor poop transplants in different recipients, i.e., some microbial species successfully colonized some recipients but not others. Factors that determine such microbial ‘take” are still not fully clear but likely the two most important are the species and strain fitness within the donor pool on the one hand and colonization resistance in the recipient’s GI tract on the other hand. Clearly, genetic relatedness between donor and recipient is likely to play a role in how similar or different microbiota are to start with between different individuals.

Thus, this case report (1)

  • Provides preliminary proof of principle that microbiota transplant may lead to metabolic transformation in the recipient to mimic those of the donor.
  • Suggests unoccupied or available microbial niches may be a prerequisite for such possibility to convert to actuality.

Some Scientific Obstacles To Successful Weight Loss Through Microbe Transplants In The Obese

  • Unless obese recipients’ GI tracts are prepared prior to microbe transplants to create niches that can accept them, such transplants may not work in reducing obesity. In other words, depleting recipients of their indigenous gut microbes may be a necessary preliminary step. Problem is, antibiotics, easiest tools available to do this, are blunt instruments and each such antibiotic’s effect on indigenous gut microbes will differ from person to person since gut microbial populations vary. Which antibiotics optimally prepare a recipient GI tract for optimal ‘take’ is currently unknown as also whether indigenous microbe-depleting effect of any one antibiotic is even generalizable across different individuals.
    • However, antibiotics may not be the only approach to deplete recipients of indigenous microbes prior to microbe transplant since the 2016 study (2) found bowel lavage alone without prior antibiotic Rx allowed stable donor microbe colonization in FMT recipients. By monitoring recipient gut microbes from 84 up to 400 days, this study showed durable co-existence of some donor and recipient microbial species.
    • Much work still needs to be done to understand how to effect efficient ‘take’ of microbe transplants.
  • Obviously obesity is outcome of diet, microbes and genetics. While interventions such as prior antibiotic Rx and bowel lavage may prepare available GI tract niches for microbial transplants to successfully occupy them initially, can sustainable microbial ‘take’ be assured without more profound, long-term habit changes? Doesn’t the principle of colonization resistance suggest that continuing post-transplant with the same diets that sustained their obesity only increase the likelihood their post-transplant GI niches would continue to preferentially support such obesity-associated microbes? Doesn’t that suggest microbe engineering alone may not suffice unless accompanied by diet change?

Misuse Of A Statistical Tool Is An Obvious Weakness Of Mouse Model Studies Of This Kind

Finally, a couple of points to add to Drew Smith‘s thorough analysis of the study quoted in the question.

One, though mouse is the most prevalent preclinical animal model, the travesty is rarely do its findings translate to humans.

Two, important to note the blatant data manipulation all too common in such mouse studies. While the article in question refers to an as-yet unpublished study presented during an August 2016 conference, this group has published on this NAPE mouse model-associated weight loss in 2014 (reference 6 in Drew Smith’s answer, 3 here). The important bit is in the figure legend. This particular experiment has 4 groups with 10 mice per group. So far so good. Not so good? That the authors chose to show not individual data points for each mouse in each group or mean +/- SD (standard deviation) but rather mean +/- SEM (standard error of the mean).

SEM is derived by dividing the standard deviation (SD) by the square root of the number tested. Let’s say SD in one group was 4.7. By dividing this SD by the square root of 10, the number of mice in the group, one can artificially reduce the variation within this group down to 1.6, i.e., its SEM. Such manipulations make the data look much cleaner and clearly separate the trends between the groups but the fact that these authors had to resort to this gimmick in such a small data set suggests much greater actual variation, i.e., considerable variation within groups and therefore considerable overlap between groups.

Variation is a given in biology especially when experiments involve such complex entities as live animals and human beings. This is compounded by less than optimal precision and accuracy of many biological assays, and widely variable skill and rigor of experimenters. As with any statistical tool, SEM has value when used appropriately as for example when trying to account for inevitable variations between experiments. Repeat the same experiment over time with experimental animals divided into the same 4 groups and there’s likely to be some variation even in the same group across experiments. SEM can help offset such variation and its use in such circumstances is not only appropriate but also tempered by the fact that combining data from different experiments adds more statistical power to the dataset not only by simply increasing the number of subjects per group but also by accounting for inter-experimental variations. That was clearly not the case here. The authors themselves describe this experiment in their paper’s Materials and Methods (3) as one experiment of 40 male mice divided into 4 groups of 10 mice each. In other words, this is misuse of the SEM statistical tool.

If within-group variations are larger than between-group variations, obviously we can’t conclude much especially in small studies where each group has only 10 subjects. Obviously such studies couldn’t get published. With the Publish or perish imperative only strengthening not weakening in recent decades, resorting to Data dredging is also at epidemic proportions. As gatekeepers, scientific peer reviewers and journal editors are responsible for stemming the tide of such abuse of statistics, a factor that also plays an important role in the current biomedicine data irreproducibility crisis. Obviously and dismayingly this example shows that even respectable scientific journals with quite high impact factors like Journal of Clinical Investigation (JCI) still aren’t performing due diligence on the data they choose to publish. No wonder the data irreproducibility crisis shows no sign of abating.


1. Alang, Neha, and Colleen R. Kelly. “Weight gain after fecal microbiota transplantation.” Open forum infectious diseases. Vol. 2. No. 1. Oxford University Press, 2015. Weight Gain After Fecal Microbiota Transplantation

2. Li, Simone S., et al. “Durable coexistence of donor and recipient strains after fecal microbiota transplantation.” Science 352.6285 (2016): 586-589.

3. Chen, Zhongyi, et al. “Incorporation of therapeutically modified bacteria into gut microbiota inhibits obesity.” The Journal of clinical investigation 124.8 (2014): 3391-3406. Incorporation of therapeutically modified bacteria into gut microbiota inhibits obesity


What ramifications has current research on the human microbiome yielded (besides pre- and probiotics)?


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Among the ramifications of current human microbiota research perhaps nothing could be more important than to reconsider what it even means to be a human being, to acknowledge that our individual identity isn’t quite what we’ve thought all along, that instead of autonomous entities we’re each an ecosystem, i.e., super-organisms, entities so dynamic as to even fundamentally alter, albeit temporarily, when we just change our diet or even just travel, perhaps even a Holobiont. And who knows when some of these changes we’re used to making without a second thought actually end up altering us just a bit more permanently simply because they permanently alter our microbial components?

For example, does a person who switches permanently from a meat-eating to a vegetarian diet or vice-versa remain the same person with the same kinds of thoughts and feelings or does the microbiota change accompanying their diet change also alter them more fundamentally? When two flu-naive persons (neither previously exposed nor vaccinated) get equally exposed to seasonal flu and only one becomes sick, is one better protected than the other because their respiratory microbes were better suited to joining battle with their human cell partners to fend off the flu strain (1)?

We aren’t used to asking such questions of ourselves. After all, the notion we’re each an autonomous entity is so ingrained in us, it may seem more than a bit bizarre initially to ask such ecological questions of ourselves. To acknowledge and reconcile that the multitude others we each harbor within our selves at all times influence just about every aspect of our physiology and thereby our identity is thus perhaps the most important ramification of human microbiota research. We are only beginning to understand just how much of who we are is outcome of not just the bacteria but also the varieties of viruses (2) and eukaryotes (fungi (3) and helminths (4)) we harbor within our bodies.

The focus of so much research attention in recent years, it would take several theses to lay out all the ramifications in detail. Perhaps the best one could do in one answer on an issue so revelatory and essentially revolutionary is to just take a bird’s eye view of some key findings and their implications for not just human health but also identity, the latter in terms of pondering how much of what we do, and who and how we are may be actually for the benefit of our microbial partners, for their nourishment, survival and transmission.


  • We’re used to thinking of our skin as a barrier protecting us from outside threats. The largest organ in the body, the skin doesn’t lack for microbial cohabitants. That a microbial multitude inhabits the top dead cell skin layer isn’t novel. What is remarkable is a select few actually penetrate below to reside within the living dermis (5), yes, even in healthy skin. Thus appearing more than a little passe, the notion of the skin as a barrier instead cedes ground to the idea it’s a dynamic filter engaged in interactions with microbial multitudes, constantly negotiating for peaceful co-existence (6).
  • Cumulative evidence suggests skin microbial imbalance accompanies many skin diseases such as Acne vulgaris, Atopic dermatitis, Psoriasis (7). Whether such Dysbiosis is cause or effect of such diseases is the subject of ongoing research (8). Implication: skin diseases may be outcome of discord between skin cells and their microbial neighbors.
  • Ever noticed how some people seem to be the disproportionate targets of mosquitoes and other biting insects? What is it about them? Do they release different scents more attractive to such insects? Turns out people preferentially targeted by mosquitoes and other biting insects emit different volatile scents from those who aren’t and this mostly boils down to differences in skin microbial composition (9).

Gastrointestinal Tract

  • Gut microbes not only help digest food but also expand our base of what’s digestible by providing calories from material human gut epithelial cells can’t digest, a salient example being Dietary fiber (10).
  • The fact that such microbial digestion entails fermentation which yields not only calories but also nutrients such as butyrate essential for gut epithelial cell health and maintenance (10, 11, 12) begs the question whether over evolutionary time we ate for our health or rather to nurture the microbes necessary for our health.
  • A quick glance at cultures the world over suffices to confirm fermentation practices for making a variety of foods (breads, cheeses, pickled foods), and drinks (beers, wines, toddies) developed globally (13, 14). Over evolutionary time, what drove our global propensity for fermented foods, our taste buds or the microbes we harbor that depend on such foods for nutrition?
  • Gut microbes synthesize key vitamins such as B and K (15, 16), catabolize Xenobiotic, drugs and toxins (17) and mediate cholesterol and bile acid synthesis (10).
  • Gut microbes are also immensely important in training neonatal immune responses (18, 19).


  • Gut microbes synthesize Neurotransmitter (20, 21, 22). Through circulation and through their effect on the Vagus nerve, gut microbes may thus influence physiological states ranging from anxiety to mood and stress (23, 24). In short, much of our behavior may be the outcome of interactions with the microbes we harbor. Seen in this light, it may be justified to speculate whether we evolved social behaviors such as kissing, social grooming and other social traditions to maximize chances of transmitting our microbial partners (25).
  • Only recently has consensus coalesced around the notion that many cognitive and behavioral disorders also involve gastrointestinal disturbances (26, 27, 28). This is especially so in the case of Autism spectrum disorders (12).

Mother & Child

  • Initial microbial colonization starts with the process of birth as the baby passes through the mother’s birth canal and vagina. Thus vertical (mother-to-child) transmission of microbes is a fundamental feature of human life and epidemiological studies suggest interfering with this process through procedures like C-section may also interfere with long-term health, given lifelong higher risk of allergies and autoimmunities among C-section babies compared to vaginal births (18).
  • Specific microbial species preferentially colonize infant gut during breast feeding (29) while breast milk itself is rich in specific sugars, oligosaccharides that act as Prebiotic (nutrition), i.e., nutrient beds that create a milieu to specifically promote growth of human infant gut beneficial microbes such as bifidobacteria (30).
  • In fact, so specialized does human breast milk seem to be in promoting colonization by specific infant gut microbes that scientists are even coming around to the idea that rather than provide nutrition to newborns, breastmilk’s true purpose may be as a prebiotic to promote infant gut colonization by specific microbial species (31, 32, 33, 34).
  • One of the most compelling examples is of mothers capable of secreting 2′-fucosylated glycans in their breast milk. People with active FUT2 alleles are called secretors. One study (35) found nursing infants of such secretors (n=32) were colonized much earlier by colonic bifidobacteria, specifically Bifidobacterium longum, compared to infants nursed by FUT2 non-secreting mothers (n=12), who were instead colonized by a different bifido, B. breve. Relevance of this difference? Infants nursing from FUT2 secretor mothers had lower fecal levels of lactate, suggesting they better utilized milk sugars.

Female Reproductive Tract

  • Reinforcing the body-as-ecosystem idea, a study suggests vaginal microbiota influence risk of contracting sexually transmitted infections (36).
  • Importance of urinary tract (37), cervical, vaginal microbiota in maintaining reproductive health (38, 39) obviously begs the question of their role in birth, and especially how it’s different in preterm and still births (40, 41).
  • Healthy human placenta seems to specifically promote residence of a unique subset of microbes that most closely resemble those in healthy mouths (42). Microbes specifically residing in the placenta! As research continues to plumb the depths of our microbial partnership, will any tissue turn out to be microbe-free?

Obviously microbes predate us. Patterns of genetic variations of microbes such as Mycobacterium tuberculosis (43) and Helicobacter pylori (44, 45, 46) suggest they’ve evidently also accompanied us on our global migrations (47, 48), i.e., that human-microbial associations may not be happenstance but rather evolutionarily conserved. No longer autonomous entities but rather each human an unique ecosystem, proof positive that we’re also holobionts awaits the discovery that each one of us invariably harbors the same specific microbial species or two or three or more.


1. Furman, David, et al. “Cytomegalovirus infection enhances the immune response to influenza.” Science translational medicine 7.281 (2015): 281ra43-281ra43. https://www.researchgate.net/pro…

2. Tirumalai Kamala’s answer to What do we know about the function of viruses in the microbiome?

3. Tirumalai Kamala’s answer to What do we know about the function of fungi in the human microbiome?

4. Tirumalai Kamala’s answer to How might parasites turn out to be good for their hosts?

5. Nakatsuji, Teruaki, et al. “The microbiome extends to subepidermal compartments of normal skin.” Nature communications 4 (2013): 1431. http://www.nature.com/ncomms/jou…


7. Nakamizo, Satoshi, et al. “Commensal bacteria and cutaneous immunity.” Seminars in immunopathology. Vol. 37. No. 1. Springer Berlin Heidelberg, 2015.

8. Fry, L., et al. “Is chronic plaque psoriasis triggered by microbiota in the skin?.” British Journal of Dermatology 169.1 (2013): 47-52.

9. Tirumalai Kamala’s answer to Why do fleas, ticks and mosquitoes show individual preference?

10. Tirumalai Kamala’s answer to What portion of our dietary calories do our gut bacteria consume?

11. Tirumalai Kamala’s answer to Microbiology: What different kinds of symbioses do humans have with bacteria?

12. Tirumalai Kamala’s answer to What is the role of bacteria in the gut?

13. LEGRAS, JEAN‐LUC, et al. “Bread, beer and wine: Saccharomyces cerevisiae diversity reflects human history.” Molecular ecology 16.10 (2007): 2091-2102. https://www.researchgate.net/pro…

14. Salque, Mélanie, et al. “Earliest evidence for cheese making in the sixth millennium BC in northern Europe.” Nature 493.7433 (2013): 522-525.

15. LeBlanc, Jean Guy, et al. “Bacteria as vitamin suppliers to their host: a gut microbiota perspective.” Current opinion in biotechnology 24.2 (2013): 160-168. http://datateca.unad.edu.co/cont…

16. Magnúsdóttir, Stefanía, et al. “Systematic genome assessment of B-vitamin biosynthesis suggests co-operation among gut microbes.” Frontiers in genetics 6 (2015): 148. Systematic genome assessment of B-vitamin biosynthesis suggests co-operation among gut microbes

17. Carmody, Rachel N., and Peter J. Turnbaugh. “Host-microbial interactions in the metabolism of therapeutic and diet-derived xenobiotics.” The Journal of clinical investigation 124.10 (2014): 4173-4181. Host-microbial interactions in the metabolism of therapeutic and diet-derived xenobiotics

18. Tirumalai Kamala’s answer to Is giving birth in water bad for the development of the child’s immune system?

19. Tirumalai Kamala’s answer to How do vaccines work in newborns if the adaptive immune system only really starts working 3 months or so after birth?

20. Donia, Mohamed S., and Michael A. Fischbach. “Small molecules from the human microbiota.” Science 349.6246 (2015): 1254766. http://www.ncbi.nlm.nih.gov/pmc/…

21. Neuman, Hadar, et al. “Microbial endocrinology: the interplay between the microbiota and the endocrine system.” FEMS microbiology reviews (2015): fuu010. https://www.researchgate.net/pro…

22. Sampson, Timothy R., and Sarkis K. Mazmanian. “Control of brain development, function, and behavior by the microbiome.” Cell host & microbe 17.5 (2015): 565-576. http://ac.els-cdn.com/S193131281…

23. Schmidt, Charles. “Mental health: thinking from the gut.” Nature 518.7540 (2015): S12-S15; Dinan, Timothy G., et al. “Collective unconscious: how gut microbes shape human behavior.” Journal of psychiatric research 63 (2015): 1-9. http://ac.els-cdn.com/S002239561…

24. Stilling, Roman M., et al. “Friends with social benefits: host-microbe interactions as a driver of brain evolution and development?.” Frontiers in cellular and infection microbiology 4 (2014): 147. Friends with social benefits: host-microbe interactions as a driver of brain evolution and development?

25. Montiel-Castro, Augusto J., et al. “The microbiota–gut–brain axis: neurobehavioral correlates, health and sociality.” Beyond the borders: The gates and fences of Neuroimmune interaction (2014). https://www.researchgate.net/pro…

26. Kennedy, Paul J., et al. “Microbiome in brain function and mental health.” Trends in Food Science & Technology (2016).

27. Dinan, Timothy G., and John F. Cryan. “Microbes, Immunity, and Behavior: Psychoneuroimmunology Meets the Microbiome.” Neuropsychopharmacology (2016).

28. Rea, Kieran, Timothy G. Dinan, and John F. Cryan. “The microbiome: A key regulator of stress and neuroinflammation.” Neurobiology of Stress (2016). The microbiome: A key regulator of stress and neuroinflammation

29. Mueller, Noel T., et al. “The infant microbiome development: mom matters.” Trends in molecular medicine 21.2 (2015): 109-117. http://www.ncbi.nlm.nih.gov/pmc/…

30. Chichlowski, Maciej, et al. “Bifidobacteria isolated from infants and cultured on human milk oligosaccharides affect intestinal epithelial function.” Journal of pediatric gastroenterology and nutrition 55.3 (2012): 321. http://www.ncbi.nlm.nih.gov/pmc/…

31. Allen-Blevins, Cary R., David A. Sela, and Katie Hinde. “Milk bioactives may manipulate microbes to mediate parent–offspring conflict.” Evolution, medicine, and public health 2015.1 (2015): 106-121. Milk bioactives may manipulate microbes to mediate parent-offspring conflict

32. Sela, D. A., et al. “The genome sequence of Bifidobacterium longum subsp. infantis reveals adaptations for milk utilization within the infant microbiome.” Proceedings of the National Academy of Sciences 105.48 (2008): 18964-18969. http://www.pnas.org/content/105/…

33. Sela, David A., and David A. Mills. “Nursing our microbiota: molecular linkages between bifidobacteria and milk oligosaccharides.” Trends in microbiology 18.7 (2010): 298-307. https://www.researchgate.net/pro…

34. Smilowitz, Jennifer T., et al. “Breast milk oligosaccharides: structure-function relationships in the neonate.” Annual review of nutrition 34 (2014): 143. http://lebrilla.faculty.ucdavis….

35. Lewis, Zachery T., et al. “Maternal fucosyltransferase 2 status affects the gut bifidobacterial communities of breastfed infants.” Microbiome 3.1 (2015): 1. Microbiome

36. Borgdorff, Hanneke, et al. “Lactobacillus-dominated cervicovaginal microbiota associated with reduced HIV/STI prevalence and genital HIV viral load in African women.” The ISME journal 8.9 (2014): 1781-1793. http://www.nature.com/ismej/jour…

37. Whiteside, Samantha A., et al. “The microbiome of the urinary tract [mdash] a role beyond infection.” Nature Reviews Urology 12.2 (2015): 81-90. https://www.researchgate.net/pro…

38. Li, Jingru, et al. “Importance of vaginal microbes in reproductive health.” Reproductive Sciences 19.3 (2012): 235-242.

39. Taylor, Brandie DePaoli, Toni Darville, and Catherine L. Haggerty. “Does bacterial vaginosis cause pelvic inflammatory disease?.” Sexually transmitted diseases 40.2 (2013): 117-122. Does Bacterial Vaginosis Cause Pelvic Inflammatory Disease? : Sexually Transmitted Diseases

40. Payne, Matthew S., and Sara Bayatibojakhi. “Exploring preterm birth as a polymicrobial disease: an overview of the uterine microbiome.” Frontiers in immunology 5 (2014): 595. Exploring Preterm Birth as a Polymicrobial Disease: An Overview of the Uterine Microbiome

41. Prince, Amanda L., et al. “The microbiome, parturition, and timing of birth: more questions than answers.” Journal of reproductive immunology 104 (2014): 12-19. http://www.ncbi.nlm.nih.gov/pmc/…

42. Aagaard, Kjersti, et al. “The placenta harbors a unique microbiome.” Science translational medicine 6.237 (2014): 237ra65-237ra65. https://www.researchgate.net/pro…

43. Tirumalai Kamala’s answer to What if Mycobacterium tuberculosis evolved as a cohabitating organism within the human body?

44. Tirumalai Kamala’s answer to Is there any strong research about the effects of increased exposure to pathogens from grouping children in settings like day care centers or schools?

45. Tirumalai Kamala’s answer to Can we convert a pathogenic bacteria to a probiotic?

46. Maixner, Frank, et al. “The 5300-year-old Helicobacter pylori genome of the Iceman.” Science 351.6269 (2016): 162-165. https://www.researchgate.net/pro…

47. Dominguez-Bello, Maria Gloria, and Martin J. Blaser. “The Human Microbiota as a Marker for Migrations of Individuals and Populations*.” Annual Review of Anthropology 40 (2011): 451-474. http://www.annualreviews.org/doi…

48. Henne, Karsten, et al. “Global analysis of saliva as a source of bacterial genes for insights into human population structure and migration studies.” BMC evolutionary biology 14.1 (2014): 1. BMC Evolutionary Biology


What kind of experimental design is used to measure placebo effect?


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What Is The Placebo Effect

As any practicing physician worth their salt knows, whether we like it or not, since time immemorial the Placebo effect and its counterpart, Nocebo, are a large component of response to medications and medical procedures. Most important aspect about the placebo effect is it exists even without a placebo, i.e., operates regardless whether the Rx is a highly specialized and well-validated drug with a known mechanism of action or a real procedure on the one hand or placebo or sham procedure on the other. In other words, ipso facto, drug effects include placebo effects.

However, for too long, placebo effect research got bogged down in what placebos are, i.e., placebo pill or sham treatment content took precedence over the context in which treatments, be they real or placebo, are given. Placebo context or placebo ritual encompasses all the disparate elements of any treatment environment including beliefs, expectations, past experiences, not just the patient’s but also the physician’s (see below from 1) and everyone else involved in it.

The focus of cutting-edge placebo research is to uncover and understand the components and processes of this effect. Change in focus from placebo content to context is not only unprecedented but has the potential to truly revolutionize medicine, if it gets the attention it surely deserves like none other but which it unfortunately doesn’t get, given the perennial short-sightedness of biomedicine funders, and biotech and pharma companies. And of course, the medical community also needs to get on board with what the latest in placebo effects research teaches us about how medicines actually work, as in how much a person’s psychological response to being treated plays a major role in a treatment’s effectiveness.

How To Study Placebo Effects

Randomized controlled trial (RCT) which are also Placebo-controlled study don’t help understand the placebo effect since that isn’t really their focus. Rather they merely seek to account for the placebo fait accompli in order to more accurately assess the ‘real’ treatment’s effect. As well, many of them don’t include the key no treatment group necessary to assess the magnitude of the placebo effect separately. However, comparing placebo and no treatment groups doesn’t fully reveal the entirety of placebo effects either.

An early placebo effects RCT (2) found the cholecystokinin antagonist Proglumide to be more effective against post-operative pain compared to placebo. So far so good. However, this study, done by the groundbreaking placebo researcher, Fabrizio Benedetti, included a further group, those who got proglumide but weren’t told about it, i.e., a hidden treatment group. Such patients reported no alleviation of their pain, even though they’d received the same dose of painkiller! How to explain this? When given openly, proglumide presumably interacts with and enhances expectation pathways, i.e., one type of placebo effect. In other words, proglumide doesn’t act on pain pathways itself and thus is only effective when combined with psychosocial mechanisms operating during physician-patient interactions.

A Representative Example Of Experiments That Uncover & Study Placebo Effects Separately From Placebo

A pioneering placebo effect study by the groundbreaking placebo researcher, Ted Kaptchuk, in this RCT on 262 Irritable bowel syndrome (IBS) patients, placebo effects were separated into their 2 main components or combined together and compared to no treatment (3).

  • Placebo ritual alone: a validated placebo acupuncture device which retracts into the needle handle instead of penetrating the skin.
  • Placebo ritual plus patient-clinician relationship. The latter consisted of a prospectively scripted process that entailed attention, warmth, confidence and thoughtful silence.

3 weeks into the trial, using a validated measure for IBS, patients reporting improvement were

  • 28% in the no treatment group.
  • 44% in the placebo ritual group alone.
  • 62% in the placebo ritual plus patient-clinician relationship.

The 62% improvement seen in the placebo ritual plus patient-clinician relationship was similar to that seen in an earlier RCT where patients were treated with Alosetron, a drug used for IBS Rx (4). In other words, this study’s placebo effects were just as effective as active IBS Rx was reported to have been in a previous study.

What kind of experimental design helps uncover, maybe even quantify, placebo effects, which operate regardless of real medication or placebo? The Open-Hidden Study Design.

  • First, to consider that any medical treatment has specific and non-specific effects. The latter could ensue simply from knowledge that a treatment’s being given, i.e., expectation.
  • Second, assess the treatment’s effectiveness by
    • Eliminating its specific effect, i.e., a placebo study: No active Rx, only placebo.
    • Eliminating non-specific effects, i.e., hidden treatment: Active Rx but patient doesn’t know.

Called the Open-Hidden Study Design (see below from 5), this experiment design has thus far best elucidated magnitude and duration of placebo effects, and uncovered their two main drivers, expectations and classic conditioning, i.e., learning.

Open-Hidden Study Design Reveals Placebo Effects Can Ensue From Expectations Of Symptom Improvement

Consider a physician-administered drug.

  • In open treatment, the physician injects the drug into the patient openly with normal verbal and contextual interactions, i.e., complete representation of routine physician-patient psychosocial interaction.
  • In hidden treatment, patient gets the drug infused via a computer pump in the absence of a physician and the therapeutic context. Hidden treatment patients only know they’re supposed to get a drug injection at some point, not when. Thus they don’t experience the expectation component and other contextual factors associated with their treatment.

With such a design the placebo component is defined as the difference between open and hidden treatments, even though no placebo is given (5, 6).

Several open-hidden studies on painkillers such as Buprenorphine, Ketorolac, Metamizole, Morphine, Tramadol found hidden treatment markedly less effective compared to open treatment.

  • One study had open versus hidden pain treatment groups among both healthy and post-operative patients (7).
    • Healthy volunteers (n=86) subjected to experimental ischemic arm pain (combination of venous blood draw and Esmarch bandage): Hidden treatment group had higher pain ratings.
    • Post-thoracic surgery patients (n=278) with post-operative pain: Hidden treatment group needed much higher doses of pain medication to reduce pain by 50%.
  • One study examined effect of open versus hidden treatment with morphine among 42 patients with post-operative pain, open versus hidden treatment with Diazepam among 30 thoracotomized patients with anxiety, and open versus hidden stimulations of the subthalamic nucleus in 10 Parkinson’s patients (8).
    • In all these cases, pain medications were much less effective in the hidden treatment groups.
    • In all these cases, the open treatment condition differed from the hidden one in three important parameters, namely, patient was aware of the treatment, the therapist was present in the room and thus patient had an expectation of the outcome.

Studies on painful rectal distention balloon in IBS patients given local anesthetic or placebo found subtle manipulation of expectations directly influenced placebo response magnitude.

  • In one study (9), patients were told they ‘may receive an active or placebo agent’.
  • In the other study (10), they were told ‘the agent you have been given is known to significantly reduce pain in some patients’.
  • The second study with the more specific instructions elicited stronger placebo responses.

Implication: Better defined, more specific instructions may improve treatment response.

One study (11) assessed post-operative pain alleviation. Intravenous (iv) saline was the placebo, buprenorphine on request the standard analgesic Rx. Patients were divided into three groups

  • Group One was told iv saline was a rehydrating solution.
  • Group Two that it was a powerful painkiller.
  • Group Three that it may or may not be a powerful painkiller.
  • Group Two took 33% less buprenorphine compared to Group One.
  • Group Three took 20% less buprenorphine compared to Group One.

Implication: Active Rx plus placebo effects could reduce total analgesic usage.

Open-Hidden Study Design Reveals Placebo Effects Can Ensue From Learning To Expect Symptom Improvement, i.e., Pre-Conditioning

For long, the assumption prevailed that in order to work, placebos required deception or concealment. Pioneering placebo effects studies show this isn’t so, that they entail learning processes that allow placebos to work in reducing symptoms even with patients knowing about them.

  • In one study (12), 30 healthy right-handed volunteers were given pain stimulus (electric shock) to their non-dominant hand. At the same time, placebo effect was introduced by surreptitiously reducing pain stimulus to make volunteers believe an analgesic Rx was effective. This subterfuge yielded real 3 to 5-fold pain reductions that lasted as long as 4 to 7 days later, as assessed by repeat experiments when patients knew they were getting placebo, not drug.
  • In one study (13), 54 adult female volunteers were told the study compared analgesia from a topical cream compared to placebo. Patients were randomly assigned to long (4 days) or short (1 day) pre-conditioning, i.e., surreptitious Rx with placebo cream. Placebo effect, i.e., perceived analgesia relief, persisted in the long pre-conditioning group even when they were later openly treated with placebo.

Implication: Reinforcing treatment cues with positive outcomes can create placebo effects independent of expectations, i.e., placebo effects can also be learned.

  • In a study (14) by Benedetti‘s group, 229 adult volunteers were subjected to experimental ischemic arm pain (combination of venous blood draw and Esmarch bandage), and conditioned with either opioid morphine or non-opioid Ketorolac. Placebo effect associated with morphine but not by ketorolac could be reversed by Naloxone. Benedetti interprets this data to suggest that morphine related placebo effect involves Endorphins while ketorolac involves Cannabinoid (15).

Implications: Placebo effects associated with different drugs tap different neurochemical pathways.

Implications Of Placebo-Associated Learning Effects: Placebos As Drugs Have Potential To Reduce Drug Costs, Dependency, Dose, Side-effects, Tolerance

  • In a pioneering randomized, two group, open-label placebo study (16) on 80 IBS patients, Kaptchuk et al openly gave sugar pills to one of the groups as ‘placebo pills made of an inert substance, like sugar pills, that have been shown in clinical studies to produce significant improvement in IBS symptoms through mind-body self-healing processes‘. Both groups involved similar patient-provider interactions, the only difference between them being that one got sugar pills. Those who took sugar pills (22/37, 59%) reported significantly higher improvement in symptom relief compared to the no treatment group (15/43, 35%).
  • In a 2016 study on 42 Parkinson’s disease patients (17), Benedetti et al showed that timing of pre-conditioning with placebo during treatment with apomorphine could
    • Produce both clinical and neuronal responses.
    • Convert even placebo non-responders to responders.
    • Clearest sign that active learning was involved was evident in the fact that greater the number of prior exposures to apomorphine, greater magnitude and longer duration of clinical and neuronal placebo responses.
  • A 2016 review (18) of 22 placebo effects studies on conditions as varied as Attention deficit hyperactivity disorder (ADHD), experimental immunosuppression, insomnia and pain concluded placebos have the potential to be used openly to reduce drug costs, dependency, dose, side-effects and tolerance. Such usage could be especially propitious and timely in the case of opioid use whose per capita use in US is double that in the UK, 3X that in the Netherlands and 26X that in Japan (18), stoking an unprecedented public health crisis that even appears to have truncated life expectencies among white, non-Hispanic Americans (19).


1. Finniss, Damien G., et al. “Biological, clinical, and ethical advances of placebo effects.” The Lancet 375.9715 (2010): 686-695. http://www.thblack.com/links/RSD…

2. Benedetti, Fabrizio, Martina Amanzio, and Giuliano Maggi. “Potentiation of placebo analgesia by proglumide.” The Lancet 346.8984 (1995): 1231.

3. Kaptchuk, Ted J., et al. “Components of placebo effect: randomised controlled trial in patients with irritable bowel syndrome.” Bmj 336.7651 (2008): 999-1003. http://www.bmj.com/content/bmj/3…

4. Camilleri, Michael, et al. “Efficacy and safety of alosetron in women with irritable bowel syndrome: a randomised, placebo-controlled trial.” The Lancet 355.9209 (2000): 1035-1040. https://www.researchgate.net/pro…

5. Colloca, Luana, et al. “Overt versus covert treatment for pain, anxiety, and Parkinson’s disease.” The Lancet Neurology 3.11 (2004): 679-684. https://www.researchgate.net/pro…

6. Price, Donald D. “Assessing placebo effects without placebo groups: an untapped possibility?.” Pain 90.3 (2001): 201-203.

7. Amanzio, Martina, et al. “Response variability to analgesics: a role for non-specific activation of endogenous opioids.” Pain 90.3 (2001): 205-215. https://www.researchgate.net/pro…

8. Benedetti, Fabrizio, et al. “Open versus hidden medical treatments: The patient’s knowledge about a therapy affects the therapy outcome.” Prevention & Treatment 6.1 (2003): 1a.

9. Verne, G. Nicholas, et al. “Reversal of visceral and cutaneous hyperalgesia by local rectal anesthesia in irritable bowel syndrome (IBS) patients.” Pain 105.1 (2003): 223-230.

10. Vase, Lene, et al. “The contributions of suggestion, desire, and expectation to placebo effects in irritable bowel syndrome patients: An empirical investigation.” Pain 105.1 (2003): 17-25. http://citeseerx.ist.psu.edu/vie…

11. Pollo, Antonella, et al. “Response expectancies in placebo analgesia and their clinical relevance.” Pain 93.1 (2001): 77-84. https://www.researchgate.net/pro…

12. Colloca, Luana, and Fabrizio Benedetti. “How prior experience shapes placebo analgesia.” Pain 124.1 (2006): 126-133. https://www.researchgate.net/pro…

13. Schafer, Scott M., Luana Colloca, and Tor D. Wager. “Conditioned placebo analgesia persists when subjects know they are receiving a placebo.” The Journal of Pain 16.5 (2015): 412-420. https://www.ncbi.nlm.nih.gov/pmc…

14. Amanzio, Martina, and Fabrizio Benedetti. “Neuropharmacological dissection of placebo analgesia: expectation-activated opioid systems versus conditioning-activated specific subsystems.” The Journal of Neuroscience 19.1 (1999): 484-494. https://www.researchgate.net/pro…

15. Marchant, Jo. “Placebos: Honest fakery.” Nature 535.7611 (2016): S14-S15. http://www.nature.com/nature/jou…

16. Kaptchuk, Ted J., et al. “Placebos without deception: a randomized controlled trial in irritable bowel syndrome.” PloS one 5.12 (2010): e15591. http://journals.plos.org/plosone…

17. Benedetti, Fabrizio, et al. “Teaching neurons to respond to placebos.” The Journal of physiology (2016). http://onlinelibrary.wiley.com/d…

18. Colloca, Luana, Paul Enck, and David DeGrazia. “Relieving pain using dose-extending placebos: a scoping review.” Pain (2016).

19. Case, Anne, and Angus Deaton. “Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century.” Proceedings of the National Academy of Sciences 112.49 (2015): 15078-15083. http://www.pnas.org/content/112/…


How do SSRIs affect the microbiome?


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Question details: 90% of serotonin goes to the gut. Could this be a possible mechanism why SSRIs cause weight gain in some people?

90% Serotonin (5-hydroxytryptamine, 5-HT) refers to where it’s made. ~90% of the body’s 5-HT is apparently made by the gastrointestinal Enterochromaffin cell, ~5% each by the myenteric (gut-associated) neurons and the brain (1, 2). However, the bulk of enterochromaffin-derived 5-HT isn’t kept locally but rather deposited into the blood circulation inside densely packed Platelet granules and how it’s delivered to distant sites is still a mystery as is whether it indeed acts as an endocrine hormone (3).

Selective serotonin reuptake inhibitor (SSRI) & Weight Gain: Not Universal, Depends On The Drug

According to a systematic literature review, SSRI’s influence on weight depends on the specific SSRI (see table below from 4).

Weight gain: Paroxetine, Citalopram, Clomipramine, Duloxetine, Escitalopram

Minimal effect: Fluvoxamine, Fluvoxamine CR (Controlled Release), Sertraline, Fluoxetine

Given 5-HT’s abundant production in the GI tract and such striking differences in how different SSRIs influence weight, it would indeed seem obvious to assess

Of three possible ways to assess how SSRIs could affect gut microbiota, i.e., study their effect on human or animal model gut microbiota or their direct effect on microbes, only the last is best studied to date.

Human Gut Microbiota Are Different Between Major depressive disorder (MDD) Patients & Healthy Controls (4 studies as of 2016). Relevance? Not Clear.

As of 2016, a handful of studies compared gut microbiota composition differences between MDD patients and healthy controls. However, none adequately addressed how SSRIs affect gut microbiota composition.

  • At least 4 different studies found fecal microbiota of MDD patients and healthy controls to be different (5, 6, 7, 8). However, with respect to what’s different there’s little consensus between these studies so not yet clear what these data imply. As for how SSRI might affect gut microbiota, only one of these studies (6) addressed that tangentially without coming to a clear conclusion so even less is known about it.
  • Two of these studies even transferred fecal microbiota samples from MDD patients and healthy controls into experimental mice (7) or rats (8) to see if animals that receive MDD fecal microbiota recapitulate depression features, as assessed in experimental animals. Apparently they recapitulated some features such as alterations in FST (forced swim test, Behavioural despair test), and Anhedonia and other anxiety-like behaviors, implying gut microbiota may have a causative role in depression.
  • A few individuals with clinically diagnosed depression including those on antidepressants were part of two linked, much larger gut microbiota studies (9, 10) attempting to build a picture of the core human gut microbiota. While one of these studies found antidepressants to be among the 13 drugs associated with gut microbiota variation, unfortunately the antidepressant in question wasn’t SSRI but rather the SNRI (Serotonin–norepinephrine reuptake inhibitor), Venlafaxine (10). In any case, those on Venlafaxine (23 women and 6 men) were a tiny proportion of the total study population of 1106, making the linkage statistically weak so this is very much preliminary data.

Direct SSRI effect on microbes: Direct & Synergistic Antimicrobial Effects On Microbial Cultures In Vitro

A number of studies reported direct antimicrobial effect of psychotropic drugs like SSRI (11, 12, 13). Majority of such studies found Sertraline to be active against bacteria, fungi and even an eukaryotic parasite, a quite surprising effect since human epidemiological data suggest Sertraline minimally affects weight.

While early speculation suggested such activity is non-specific (23), subsequent studies showed that SSRIs can also synergize with traditional antibiotics (24) and antifungals (25, 26).

SSRI may inhibit or kill microbes through their effect on the microbial Efflux (microbiology) pump, i.e., generalizable energy-dependent mechanisms that vastly different microbes use to pump out substances that are toxic for them. Efflux pump mechanisms being greatly conserved between microbes as disparate as bacteria, fungi and eukaryotic parasites suggests it may be quite difficult for them to successfully mutate molecules that SSRIs target.

On the one hand SSRIs being able to inhibit and/or kill microbes in culture indirectly suggests they could affect human gut microbiota. On the other hand bulk of such data is for Sertraline which epidemiological studies suggest has minimal effect on weight. In other words, we’re still firmly at square one as to whether and how SSRIs could affect human gut microbiota.


1. Gershon, Michael D., Anna B. Drakontides, and Leonard L. Ross. “Serotonin: synthesis and release from the myenteric plexus of the mouse intestine.” Science 149.3680 (1965): 197-199.

2. Gershon, Michael D., and Jan Tack. “The serotonin signaling system: from basic understanding to drug development for functional GI disorders.” Gastroenterology 132.1 (2007): 397-414. https://www.researchgate.net/pro…

3. Gershon, Michael D. “5-Hydroxytryptamine (serotonin) in the gastrointestinal tract.” Current opinion in endocrinology, diabetes, and obesity 20.1 (2013): 14. http://www.ncbi.nlm.nih.gov/pmc/…

4. Dent, Robert, et al. “Changes in body weight and psychotropic drugs: a systematic synthesis of the literature.” PLoS One 7.6 (2012): e36889. http://journals.plos.org/plosone…

5. Naseribafrouei, A., et al. “Correlation between the human fecal microbiota and depression.” Neurogastroenterology & Motility 26.8 (2014): 1155-1162. http://onlinelibrary.wiley.com/d…

6. Jiang, Haiyin, et al. “Altered fecal microbiota composition in patients with major depressive disorder.” Brain, behavior, and immunity 48 (2015): 186-194. Elsevier: Article Locator

7. Zheng, P., et al. “Gut microbiome remodeling induces depressive-like behaviors through a pathway mediated by the host’s metabolism.” Molecular psychiatry 21.6 (2016): 786-796.

8. Kelly, John R., et al. “Transferring the blues: Depression-associated gut microbiota induces neurobehavioural changes in the rat.” Journal of Psychiatric Research 82 (2016): 109-118.

9. Zhernakova, Alexandra, et al. “Population-based metagenomics analysis reveals markers for gut microbiome composition and diversity.” Science 352.6285 (2016): 565-569.

10. Falony, Gwen, et al. “Population-level analysis of gut microbiome variation.” Science 352.6285 (2016): 560-564.

11. Munoz-Bellido, J. L., S. Munoz-Criado, and J. A. Garcıa-Rodrıguez. “Antimicrobial activity of psychotropic drugs: selective serotonin reuptake inhibitors.” International journal of antimicrobial agents 14.3 (2000): 177-180).

12. Samanta, Amalesh, et al. “Evaluation of in vivo and in vitro antimicrobial activities of a selective Serotonin reuptake inhibitor Sertraline Hydrochloride.” Anti-Infective Agents 10.2 (2012): 95-104. https://www.researchgate.net/pro…

13. Kalaycı, Sadık, Selami Demirci, and Fikrettin Sahin. “Antimicrobial Properties of Various Psychotropic Drugs Against Broad Range Microorganisms.” Current Psychopharmacology 3.3 (2014): 195-202. https://www.researchgate.net/pro…

14. Kaatz, Glenn W., et al. “Phenylpiperidine selective serotonin reuptake inhibitors interfere with multidrug efflux pump activity in Staphylococcus aureus.” International journal of antimicrobial agents 22.3 (2003): 254-261. https://www.researchgate.net/pro…

15. Bohnert, Jürgen A., et al. “Efflux inhibition by selective serotonin reuptake inhibitors in Escherichia coli.” Journal of antimicrobial chemotherapy 66.9 (2011): 2057-2060. Efflux inhibition by selective serotonin reuptake inhibitors in Escherichia coli

16. Lass-Flörl, C., et al. “Antifungal properties of selective serotonin reuptake inhibitors against Aspergillus species in vitro.” Journal of Antimicrobial Chemotherapy 48.6 (2001): 775-779. Antifungal properties of selective serotonin reuptake inhibitors against Aspergillus species in vitro

17. Lass-Flörl, Cornelia, et al. “Interaction of sertraline with Candida species selectively attenuates fungal virulence in vitro.” FEMS Immunology & Medical Microbiology 35.1 (2003): 11-15. http://femsim.oxfordjournals.org…

18. Rainey, Meredith M., et al. “The antidepressant sertraline targets intracellular vesiculogenic membranes in yeast.” Genetics 185.4 (2010): 1221-1233. http://www.genetics.org/content/…

19. Zhai, Bing, et al. “The antidepressant sertraline provides a promising therapeutic option for neurotropic cryptococcal infections.” Antimicrobial agents and chemotherapy 56.7 (2012): 3758-3766. The Antidepressant Sertraline Provides a Promising Therapeutic Option for Neurotropic Cryptococcal Infections

20. Treviño-Rangel, Rogelio de J., et al. “Activity of sertraline against Cryptococcus neoformans: in vitro and in vivo assays.” Medical mycology (2015): myv109.

21. Paul, Simon, Roger B. Mortimer, and Marilyn Mitchell. “Sertraline demonstrates fungicidal activity in vitro for Coccidioides immitis.” Mycology (2016): 1-3. http://www.tandfonline.com/doi/p…

22. Palit, Partha, and Nahid Ali. “Oral therapy with sertraline, a selective serotonin reuptake inhibitor, shows activity against Leishmania donovani.” Journal of antimicrobial chemotherapy 61.5 (2008): 1120-1124. Oral therapy with sertraline, a selective serotonin reuptake inhibitor, shows activity against Leishmania donovani

23. Young, T. J., et al. “Antifungal activity of selective serotonin reuptake inhibitors attributed to non-specific cytotoxicity.” Journal of Antimicrobial Chemotherapy 51.4 (2003): 1045-1047. Antifungal activity of selective serotonin reuptake inhibitors attributed to non-specific cytotoxicity

24. Ayaz, Muhammad, et al. “Sertraline enhances the activity of antimicrobial agents against pathogens of clinical relevance.” Journal of Biological Research-Thessaloniki 22.1 (2015): 1. https://www.researchgate.net/pro…

25. Nayak, Rahul, and Jianping Xu. “Effects of sertraline hydrochloride and fluconazole combinations on Cryptococcus neoformans and Cryptococcus gattii.” Mycology 1.2 (2010): 99-105. http://www.tandfonline.com/doi/p…

26. Rossato, Luana, et al. “In vitro synergistic effects of chlorpromazine and sertraline in combination with amphotericin B against Cryptococcus neoformans var. grubii.” Folia microbiologica (2016): 1-5.


Do IV antibiotics spare the gut microbiome?


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Short answer: Caveats apply to how IV (intravenous) antibiotics might influence gut microbiota,

  • Antibiotics are usually oral (peroral to be precise). Far from the norm, IV antibiotics are usually given
    • To seriously ill, usually hospitalized, people strongly suspected of having systemic bacterial infection or
    • As a precaution to patients about to undergo invasive surgery or
    • To severely ill newborns.
  • When given to the seriously ill, how to decipher if changes to gut microbiota were because the antibiotics were given IV or because the person was really sick to start with?
  • When given to severely ill newborns, is the IV antibiotic effect, whatever it may be, due to route or age?
  • Dose, another important difference, also influences how oral versus IV antibiotics could influence gut microbiota.

Study of human microbiota is in its infancy and using modern molecular biological tools to study how antibiotics affect it is of even more recent vintage. Many older studies have examined how oral antibiotics change gut microbiota but far fewer what happens after IV antibiotics. The following summarizes key features and findings of some of the few such studies as of 2016. Again, there are caveats.

  • Many are old studies that assessed change by looking at what grew out in bacterial cultures, something we now know misses accounting for the bulk of gut microbiota.
  • Some studies were observational, not randomized controlled clinical trials, i.e., subject to design bias.
  • Some were randomized, prospective clinical trials on small numbers of healthy volunteers given IV antibiotics or not.
  • None of the studies compared changes in gut microbiota of healthy people after either oral or IV antibiotics versus no antibiotics, which would be a more definitive experiment.
  • All studies but one, 3 each on sick (1, 3, 4) and healthy (5, 6, 7) people, found profound, transient to long-term changes in gut microbiota. The exception (8) was for GSK1322322, a new antibiotic.

Thus, existing human data suggest IV antibiotics tested so far (Piperacillin, Tazobactam, Ampicillin, Gentamicin, Cefazolin, Meropenem, Ciprofloxacin) don’t spare gut microbiota.

Longer answer for those interested

Intravenous (IV) Antibiotics Alter Gut Microbiota In Sick People

Long before human microbiota became a separate field of study, a 1993 Swedish study (1) found IV Piperacillin/Tazobactam reduced the numbers of Bifidobacteria, Clostridia, Enterobacteria, Eubacteria, Lactobacilli, and anaerobic Gram-positive cocci (see below from 2). Fourteen men and 6 women hospitalized for intra-abdominal infections were treated for 4 to 8 days with Piperacillin (4 grams) and Tazobactam (500mg) every 8 hours by IV for 30 minutes.

Caveat to the study: We now know assessing gut microbiota by culture misses the vast majority of gut microbiota since most aren’t yet cultivable. As well, if some bacteria grew from pre- but not post- antibiotic Rx stool samples, it could be because antibiotics altered their physiology such that they no longer grew on the culture media used, i.e., the same microbes were still present but just didn’t grow in the culture medium researchers used. Combining culture plus molecular biology would give a more definitive result.

A 2012 Irish study gave IV antibiotics to sick newborns and observed how their gut microbiota changed compared to that of similarly aged untreated healthy newborns (3). Nine newborns who got parenteral (presumably IV) Ampicillin and Gentamicin within 48 hours of birth had alterations in their gut microbiota assessed using 16S ribosomal RNA analysis.

  • Four weeks after antibiotic Rx was stopped, compared to non-antibiotic Rx healthy infants (n=9), these infants had
    • Significantly higher proportions of Proteobacteria.
    • Significantly lower proportions of Actinobacteria, including Bifidobacteria and Lactobacillus.
  • Eight weeks after antibiotic Rx was stopped,
    • Significantly higher proportions of Proteobacteria remained.
    • Actinobacteria, including Bifidobacteria and Lactobacillus, levels were similar to those in untreated infants. However, the number of Bifidobacterium species was reduced.
  • Implications? Given their health benefits, Bifidobacteria and Lactobacillus reduction could have long-term effects.

An observational 2012 German-Spanish study (4) on a 68 year old man hospitalized for an infected cardiac pacemaker and treated with IV Cefazolin for 14 days found dramatic changes in gut microbiota composition using 16S rRNA and rDNA analysis. Researchers collected stool samples before, during and 40 days post-Rx.

  • Firmicutes dominated before and during start of Rx but by day 11 of Rx, biodiversity collapsed and Firmicutes was displaced by Bacteroidetes (Bacteroides and Parabacteroides genera).
  • However, 40 days after Rx stopped, total and active intestinal bacterial composition were similar to the pre-Rx state.

Researchers also analyzed the intestinal microbiota using proteomics and metabolomics.

  • By day 6 of IV antibiotics, major metabolic changes appeared. Intestinal microbiota activated drug-detoxifying mechanisms to avoid the anti-microbial effects of the antibiotics. They started expressing beta-lactamases and multi-drug efflux pumps, and reduced the metabolism and transport of bile acids, cholesterol, hormones and vitamins.

Intravenous (IV) Antibiotics Alter Gut Microbiota In Healthy People

In a 1991 Norwegian study (5), 10 healthy young adult men got 500mg of IV Meropenem over 30 minutes 3 times daily for 7 days. Researchers collected stool samples before, during (days 2, 4, 7) and 2, 4, 7, 14 days post-Rx.

  • Bacteroides, Clostridia, Enterobacteria, Streptococci and Gram-negative cocci decreased during Rx while Enterococci increased (see below from 2).
  • Intestinal flora returned to normal within 2 weeks post-Rx.
  • Caveat to the study: Bacterial changes were assessed by culture, which we now know misses the vast majority of gut microbiota since most aren’t yet cultivable.

In a 1997 randomized German study (6), 16 healthy, young adult men and women got 400mg of IV Ciprofloxacin over 60 minutes every 12 hours for 4 days. Researchers collected stool samples before, during (every day) and post-Rx (see below from 2).

  • In all volunteers, Enterobacteriaceae counts decreased.
  • Enterococci and Lactobacilli remained unchanged.
  • Caveat to the study: Bacterial changes were assessed by culture, which we now know misses the vast majority of gut microbiota since most aren’t yet cultivable.

In a 2002 French study (7) on 24 healthy young adult men, 20 got IV Quinupristin /Dalfopristin 7.5mg/kg for 5 days in 500ml infusions over 1 hour every 12 hours while 4 got placebo infusions. Researchers collected stool samples before, at the end of (day 6) and post-Rx. During treatment

  • Anaerobes (sporulating and Gram-negative bacteria) decreased slightly.
  • Enterobacteriaceae and Enterococci increased significantly.
  • Anaerobes and Enterococci resistant to erythromycin and Quinupristin/Dalfopristin increased significantly.
  • Changes disappeared within 12 weeks of post-Rx.
  • Caveat to the study: Bacterial changes were assessed by culture, which we now know misses the vast majority of gut microbiota since most aren’t yet cultivable.

A New Intravenous (IV) Antibiotic Doesn’t Alter Gut Microbiota In Healthy People

In a 2015 US Phase I randomized, double-blinded, placebo-controlled study, 62 healthy volunteers got either placebo, IV-only or repeat oral-IV dosing of a new antibiotic, GSK1322322, for 5 to 6 days (8). Researchers collected stool samples before and post-Rx. 16S rRNA analysis showed

  • Oral-IV Rx yielded significant decreases in Firmicutes and Bacteroides and increases in Betaproteobacteria, Gammaproteobacteria and Bifidobacteriaceae.
  • IV-only was similar to placebo, no significant changes in relative abundance of GI tract OTU (Operational taxonomic unit) between pre- and post-study stool samples.


1. Nord, C. E., et al. “Effect of piperacillin/tazobactam treatment on human bowel microflora.” Journal of Antimicrobial Chemotherapy 31.suppl A (1993): 61-65.

2. Sullivan, Åsa, Charlotta Edlund, and Carl Erik Nord. “Effect of antimicrobial agents on the ecological balance of human microflora.” The Lancet infectious diseases 1.2 (2001): 101-114.

3. Fouhy, Fiona, et al. “High-throughput sequencing reveals the incomplete, short-term recovery of infant gut microbiota following parenteral antibiotic treatment with ampicillin and gentamicin.” Antimicrobial agents and chemotherapy 56.11 (2012): 5811-5820. High-Throughput Sequencing Reveals the Incomplete, Short-Term Recovery of Infant Gut Microbiota following Parenteral Antibiotic Treatment with Ampicillin and Gentamicin

4. Pérez-Cobas, Ana Elena, et al. “Gut microbiota disturbance during antibiotic therapy: a multi-omic approach.” Gut 62.11 (2013): 1591-1601. a multi-omic approach

5. Bergan, T., C. E. Nord, and S. B. Thorsteinsson. “Effect of meropenem on the intestinal microflora.” European Journal of Clinical Microbiology and Infectious Diseases 10.6 (1991): 524-527.

6. Krueger, W. A., G. Ruckdeschel, and K. Unertl. “Influence of intravenously administered ciprofloxacin on aerobic intestinal microflora and fecal drug levels when administered simultaneously with sucralfate.” Antimicrobial agents and chemotherapy 41.8 (1997): 1725-1730. Influence of intravenously administered ciprofloxacin on aerobic intestinal microflora and fecal drug levels when administered simultaneously with sucralfate.

7. Scanvic-Hameg, A., et al. “Impact of quinupristin/dalfopristin (RP59500) on the faecal microflora in healthy volunteers.” Journal of Antimicrobial Chemotherapy 49.1 (2002): 135-139. Impact of quinupristin/dalfopristin (RP59500) on the faecal microflora in healthy volunteers

8. Arat, Seda, et al. “Microbiome changes in healthy volunteers treated with GSK1322322, a novel antibiotic targeting bacterial peptide deformylase.” Antimicrobial agents and chemotherapy 59.2 (2015): 1182-1192. Microbiome Changes in Healthy Volunteers Treated with GSK1322322, a Novel Antibiotic Targeting Bacterial Peptide Deformylase


Why do fleas, ticks and mosquitoes show individual preference?


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Biting insects (bugs, fleas, flies, mites, mosquitoes, ticks) locate and bite their blood host targets from the chemical cues they release. Such cues are Volatile organic compound (VOC) produced by their skin microbes after they metabolize human skin gland secretions, i.e., an individual’s VOC profile is largely the product of their Skin flora. Thus, biting preference is the outcome of how each biting insect’s odorant receptors detect the VOCs unique to the individual it bites.

Skin glands include apocrine and eccrine sweat glands, and sebaceous glands (see below from 1).

Skin glands are differentially distributed across the body and human skin microbe abundance matches theirs (see below from 1).

The human odor profile consists of >400 compounds (2). Research on which ones are most important in attracting biting insects is very much in its infancy.

One small study (n = 48 adult male volunteers) on the African malaria mosquito Anopheles gambiae sensu stricto found that individuals the mosquitoes found highly attractive had different skin bacteria compared to individuals they found poorly attractive, specifically greater abundance but lower diversity of skin-associated bacteria (see below from 3).

In another small study (n = 48 adult male volunteers) Anopheles gambiae sensu stricto found individuals carrying the Human leukocyte antigen gene Cw*07 more attractive (4). Since different individuals have different HLA haplotypes,

  • Each individual’s unique HLA system generates different peptides, i.e., source material their skin-associated microbes metabolize and convert to VOCs is unique.
  • As well, each individual’s unique HLA is involved in the immunological processes that culminate in their unique microbial profile since immune responses select which microbes to keep or reject.

Individual genetics also influence skin temperature and humidity profiles, and metabolic rate, which are other factors that influence individuals’ differential attractiveness to biting insects. Metabolic rate influences local carbon dioxide levels, which along with ammonia and lactic acid and other aliphatic carboxylic acids influence landing rates of biting insects like mosquitoes (5).

Each human thus has a largely individual VOC profile, product of their unique genetics and unique skin microbial profile. In turn, biting insects have each their specific odorant receptors. Combination of these two parameters likely make some humans more attractive to each such biting insect compared to others. Research on this topic is still nascent and there’s more data for disease-carrying mosquitoes than for other biting insects.

Since human lifestyle, especially diet can actively sculpt human microbiota profiles, it’s likely future research will reveal how different diets could influence an individual’s VOC profile and in turn increase or decrease a biting insects’s preference for a particular individual.

Similar processes likely explain differences between dogs who get ticks versus those who don’t. However, in the case of ticks that’s only the first step since immune status probably determines whether or not they successfully establish an infection, healthier dogs fending off ticks that could stably colonize less healthy ones.


1. Verhulst, Niels O., et al. “Chemical ecology of interactions between human skin microbiota and mosquitoes.” FEMS microbiology ecology 74.1 (2010): 1-9. http://femsec.oxfordjournals.org…

2. Verhulst, Niels O., and Willem Takken. “Skin Microbiota and Attractiveness to Mosquitoes.” Encyclopedia of Metagenomics. Springer US, 2015. 591-595.

3. Verhulst, Niels O., et al. “Composition of human skin microbiota affects attractiveness to malaria mosquitoes.” PloS one 6.12 (2011): e28991. http://journals.plos.org/plosone…

4. Verhulst, Niels O., et al. “Relation between HLA genes, human skin volatiles and attractiveness of humans to malaria mosquitoes.” Infection, Genetics and Evolution 18 (2013): 87-93. https://www.researchgate.net/pro…

5. Smallegange, Renate C., Niels O. Verhulst, and Willem Takken. “Sweaty skin: an invitation to bite?.” Trends in parasitology 27.4 (2011): 143-148. https://www.researchgate.net/pro…


What are the limits of cytokine therapies for tumor treatment? Also, does local administration of cytokines outperform systemic administration?


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Not one but several problems hobble Cytokine therapy in cancer.

Small, soluble, typically secreted but also membrane-bound, cytokines are a key effector arm of the immune system. By binding to surface receptors on cells, cytokines trigger a variety of biochemical cascades that ultimately alter gene expression within those cells.

Cytokine binding to their receptors is very high affinity, which explains their profound biological effects even at very low concentrations. Their biological effects primarily but not solely on lymphocytes, it isn’t a stretch to postulate that cytokines can regulate the A-to-Z of a responding cell’s physiology by influencing its differentiation, proliferation, migration.

Drawbacks Of Cytokine Therapies For Cancer

  • Though cytokines are extremely potent, for the most part Nature seems to have designed them to work locally. Thus, they inherently have short half-lives, something that necessitates prolonged administration.
  • Major problem is how to maintain effective cytokine dose over a prolonged time period. This becomes even more of a problem when a cytokine’s given systemically.
  • Given that cytokines are not just potent but rather pluripotent, prolonged administration brings with it the cost of undesirable side effects, even more of a concern when given systemically. Some of these effects can even be unpredictable since so much more of cytokine biology is deciphered using mouse models that often translate poorly to human biology.
    • Human Interleukin 12 clinical trial history offers an extremely pertinent case in point. With its potent effect against tumors, IL-12 is perhaps a prototypic anti-cancer cytokine. No surprise then that all the way back in 1995, in partnership with Wyeth, https://en.wikipedia.org/wiki/Ge…. was testing systemic IL-12 in renal cell carcinoma patients. 12 of 17 patients suffered severe toxicity, needing to be hospitalized, with 2 deaths (1). Dosing and sequence of dosing turned out be key weaknesses of this study (2). However, this early setback was also a warning sign that cytokine therapies for cancer would likely involve a long, hard slog which indeed they have proven to be.
  • Cytokine therapy for cancer thus needed several years of back to the drawing board. In the interim, cancer immunotherapy improved by leaps and bounds in the one area where cytokine therapy can’t possibly improve and which may perhaps be its biggest drawback, lack of specificity. After all, unlike tumor antigen-specific T cells and monoclonal antibodies (mAbs), not being antigen-specific, cytokines are and can only ever be blunt instruments, akin to swatting a fly with a hammer. Thus, newer cytokine therapy approaches naturally fit in as adjuncts in this new cancer immunotherapy landscape (see below from 3 for approaches in general and from 4 for approaches for IL-12 in particular).
  • Meantime a variety of technological approaches are now also being tested to improve cytokine half-lives and their ability to more efficiently target tumors. One of the most straightforward and technically simpler approach to increase a cytokine’s half-life is to PEG-ylate it, i.e., conjugate the cytokine molecules to Polyethylene glycol (PEG). However, advances in technology make it just one of many approaches currently under test in pre-clinical animal models and clinical trials (see figure below from 5).

Despite such improvements, cytokine therapy’s still fraught with risk as we can surmise from Ziopharm Oncology’s recent Glioblastoma clinical trial death (6). Ziopharm Oncology’s approach consists of using adenovirus as the vector (carrier). Cargo it’s engineered to carry and deliver is human IL-12, designed to be conditionally expressed using a non-steroidal analog of the insect hormone ecdysone such that default IL-12 expression is low but capable of high inducibility in response to oral delivery of the specific heterodimerizer drug INX-1001 (veledimex) (5).

Cytokines Currently (mid-2016) Approved For Cancer Therapies

  • In 1992, the US FDA approved IL-2 as a single agent for metastatic renal cell carcinoma and in 1998 for metastatic melanoma (7).
  • PEG-ylated IFN-alpha is safer and requires less frequent dosing. The FDA approved it as adjuvant treatment for high-risk Stage III melanoma (8, 9).
    • A meta-analysis showed IFN-alpha’s significant association with disease-free survival in 10 of 17 multi-institutional clinical trials and improved overall survival in 4 of 14 comparison studies (10).
    • IFN-alpha is also approved for
      • Hematologic malignancies such as AIDS-related Kaposi’s sarcoma.
      • Advanced renal cancer as a component with the anti-angiogenic Bevacizumab.
  • In 1991, the US FDA approved recombinant Granulocyte macrophage colony-stimulating factor (GM-CSF) for acute myelogenous leukemia, not for its direct anti-tumor effect but to shorten the time for neutrophil recovery and help reduce risk of infections following induction chemotherapy (11).


1. Leonard, John P., et al. “Effects of single-dose interleukin-12 exposure on interleukin-12–associated toxicity and interferon-γ production.” Blood 90.7 (1997): 2541-2548. https://www.researchgate.net/pro…

2. Cohen, Jon. “IL-12 deaths: explanation and a puzzle.” Science 270.5238 (1995): 908-908.

3. Petrozziello, Elisabetta, Tabea Sturmheit, and Anna Mondino. “Exploiting cytokines in adoptive T-cell therapy of cancer.” Immunotherapy 7.5 (2015): 573-584.

4. Hernandez-Alcoceba, Ruben, et al. “Gene therapy approaches against cancer using in vivo and ex vivo gene transfer of interleukin-12.” Immunotherapy 8.2 (2016): 179-198.

5. Tugues, S., et al. “New insights into IL-12-mediated tumor suppression.” Cell Death & Differentiation 22.2 (2015): 237-246. http://www.nature.com/cdd/journa…

6. GEN News Highlights, July 15, 2016. Ziopharm Confirms 3 Patient Deaths in Gene Therapy Trial | GEN News Highlights | GEN

7. Rosenberg, Steven A. “IL-2: the first effective immunotherapy for human cancer.” The Journal of Immunology 192.12 (2014): 5451-5458. https://www.roswellpark.edu/site…

8. Eggermont, Alexander MM, et al. “Adjuvant therapy with pegylated interferon alfa-2b versus observation alone in resected stage III melanoma: final results of EORTC 18991, a randomised phase III trial.” The Lancet 372.9633 (2008): 117-126. https://www.researchgate.net/pro…

9. Bottomley, Andrew, et al. “Adjuvant therapy with pegylated interferon alfa-2b versus observation in resected stage III melanoma: a phase III randomized controlled trial of health-related quality of life and symptoms by the European Organisation for Research and Treatment of Cancer Melanoma Group.” Journal of clinical oncology 27.18 (2009): 2916-2923. Adjuvant Therapy With Pegylated Interferon Alfa-2b Versus Observation in Resected Stage III Melanoma: A Phase III Randomized Controlled Trial of Health-Related Quality of Life and Symptoms by the European Organisation for Research and Treatment of Cancer Melanoma Group

10. Mocellin, Simone, et al. “Interferon alpha adjuvant therapy in patients with high-risk melanoma: a systematic review and meta-analysis.” Journal of the National Cancer Institute 102.7 (2010): 493-501. A Systematic Review and Meta-analysis

11. Lee, Sylvia, and Kim Margolin. “Cytokines in cancer immunotherapy.” Cancers 3.4 (2011): 3856-3893. http://www.mdpi.com/2072-6694/3/…


Can we assume that no dengue epidemic in the U.S. implies little chance of a Zika epidemic? (both diseases are transmitted by the same mosquito)


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Not too long back Dengue epidemics were part and parcel of life in certain parts of the US (1). Florida had its last Dengue epidemic in 1934. Keeping mosquito-borne diseases at bay in the lush, warm, wet sub-tropical Florida climate is a constant tug-of-war and recent history ominously suggests that laxity in stringent, community-wide mosquito control could deliver net advantage to mosquitoes and the diseases they carry. Florida’s climate allows year-around residence of Aedes aegypti, the mosquito species that transmits Dengue and Zika in Central and South America. Thus, there’s no guarantee Dengue won’t make a comeback or that Zika can’t gain a foothold in the state. Exploring chances of Dengue and Zika in Florida helps appraise their capacity to spread into continental US and suggests that holding them at arm’s length is a fragile standoff at the best of times.

The Three Mosquiteers* In Florida’s History: Dengue, Malaria, Yellow Fever

Since at least the 1970s, Florida’s become one of the foremost global tourist destinations but a 2013 article on the history of mosquito-borne diseases in Florida (2) reminds us just how recent that transformation is. For long Florida was sparsely inhabited, its entire population numbering just 34730 in 1830 (3). As recently as the 1950s, Florida was a place to flee from in summer (4), of course only by those who could afford to do so.

Why? Simply, until recently, life in much of Florida was considered so unbearable (5), much of its population stayed concentrated in the north between Alabama and Georgia, the Florida Panhandle, a largely disease- and poverty-stricken area between Jacksonville and Pensacola, known as the ‘malaria belt’, also home to cholera, dengue, diphtheria, hookworm, influenza, pellagra, pertussis, smallpox, tetanus, typhoid, yellow fever. Though largely forgotten today, mosquito-borne diseases in the form of malaria, dengue and yellow fever thus inform a great deal of Florida’s history. Maurice Provost, the first director of what would become the Florida Medical Entomological Laboratory recalled in 1973 (see below from 6),

“My most vivid memories of malaria-control days in Florida are of the morning-after inspections of so many of the humble shacks we sprayed with DDT. The poor housewife often enough would come to me with tears of joy and show me a basketful of dead bedbugs, roaches, and other vermin, and she would exclaim that her family had spent the first night of their lives without annoyance from biting or creeping things”

Florida’s last dengue epidemic was in 1934. Reads like so much ancient history now. Why? Mosquito control (7), a stupendous achievement pretty much taken for granted not just now but already a generation back in 1981 (see below from 8, emphasis mine).

Florida would not be where it is today were it not for mosquito control. That alone makes a lot of people mad, but they weren’t around when you could not go outside after dark and most of the coastal communities closed down during the summer. Most of the people who fight your programs are newcomers. A newcomer is now somebody who came here after 1970.”

Complacence Belied, After 1934, In 2009 Locally Acquired (autochthonous) Dengue Returned To Florida

While sporadic travel-related Dengue infections remained, Florida didn’t report any locally acquired (autochthonous) Dengue since 1934, a record broken in 2009. Starting in July 2009 and continuing until April of the following year, a total of 28 locally acquired Dengue cases were reported in Key West, FL (See figure below left from 9). Eventually a total of >90 locally acquired Dengue cases were reported in Key West alone (See figure right from 10).

Starting from tiny Key West in 2009 (see left from 11), by 2013, locally acquired Dengue had expanded upward to encompass at least 8 Florida counties (see right from 12).

Local acquisition means complete local mosquito-to-local human-to-local mosquito cycle, the step necessary for outbreaks and eventually epidemics too. Definitely the opposite of welcome news. The silver lining in this dismaying story was that Maimi-Dade County, a port with heavy traffic from Dengue-endemic countries, doesn’t appear to have conditions sufficient to sustain local Dengue transmission. Puzzling similarities in the Counties with the most number of cases, namely Key West-containing Monroe in 2009-2010 and Martin in 2013, were

  • Neither is a major port of entry for either aviation or shipping.
  • Both had larger numbers of locally acquired cases compared to other Florida counties.

How did Key West and Martin favor local Dengue transmission? Studies suggest factors they have in common are (12, see table below from 11)

  • Tendency to keep open-air water receptacles such as bird-baths without frequently changing them.
  • Keep windows open >50% of the time.
  • Have >50% vegetation on their property.

OTOH, local Dengue transmission was greatly reduced if

  • Empty standing water containers were changed weekly.
  • Air-Conditioners (A-Cs) were used >50% of the time.
  • Mosquito repellents were used routinely.

Situation in Florida is even more precarious given the fact that one study found local Florida Ae. aegypti mosquitoes capable of Vertically transmitted infection of the Dengue strain isolated from the 2009 Key West outbreak (13). When infected with Dengue virus, ~8% of these Florida mosquitoes were found capable of vertically transferring it to their eggs. Thus, Florida’s just barely keeping Dengue at arm’s length and even the slightest laxity could be all it takes for it to gain a stable foot-hold. Threat of Zika just adds to the strain on public health. Not to mention the really scary scenario if Aedes albopictus also became capable of transmitting Dengue and Zika, something it can’t at present. This would be really scary given how much more widespread this mosquito species is all across the continental US and indeed much of the temperate regions of the world.

Trouble is collective memory’s fickle and easily breeds complacence. When persistent, deeply vexing problems such as the perennial scourge of mosquitoes get intensively abated within just a generation, as happened in Florida, it doesn’t take long for collective, generation-spanning amnesia to dictate the conversation. Already back in 1991, public opinion apparently supported the idea that mosquito control officials greatly exaggerate the threat of disease to justify their jobs (4). What’s easily forgotten in such short-sighted political and economic debates is that mosquito (vector) control is inherently resource and personnel intensive and only works with sustained community support and participation (14). To quote Hribar (2, emphasis mine),

‘Is it too expensive to control Aedes aegypti? Equipment, training, pesticides, and people cost money. To do the job right, a lot of time must be devoted to seeking out larval habitats and eliminating them. Adult emergences must be dealt with promptly. The public must cooperate with public health and mosquito control agencies in the fight against Aedes aegypti. Whatever the cost surely it will be less than the hospitalization, medicines, lost wages, and funeral expenses that may be the alternative ‘

Though climate and location render Florida and other states in the Gulf Coast of the United States vulnerable to Dengue and Zika, common-sense, practical measures can do a great deal to minimize and even prevent them from getting established in the US. Apart from aggressive, community-based mosquito (vector) control, air-conditioning and using screens on doors and windows can greatly stem Ae. aegypti‘s capacity to complete Dengue and Zika‘s transmission cycle. Of course, prevention is greatly facilitated by widespread use of centralized air-conditioning and heating systems, something only to be expected in an advanced economy like the US. Given how important tourism is to Florida’s economy, one would hope the state apparatus wouldn’t hesitate to pull out all stops to prevent mosquito-borne Dengue and Zika from taking root in the state.

*: Defined here as mosquito-borne parasitic and viral diseases.


1. Bouri, Nidhi, et al. “Return of epidemic dengue in the United States: implications for the public health practitioner.” Public health reports 127.3 (2012): 259. http://www.ncbi.nlm.nih.gov/pmc/…

2. Hribar, L. G. “Influence and impact of mosquito-borne diseases on the history of Florida, USA.” Life Excit. Biol 1 (2013): 53-68. https://blaypublishers.files.wor…

3. Cody, Scott K. “Florida’s population center migrates through history.” Florida Focus 2.1 (2006): 1-5) http://www.bebr.ufl.edu/sites/de…

4. Mulrennan, J. A. “Benefits of mosquito control.” Mosquito control pesticides: ecological impacts and management alternatives. Conference Proceedings. Scientific Publishers, Inc. Gainesville, Florida, USA. 1991.

5. Gaiser, D. “The importance of mosquito control to tourism in Florida.” Proceedings of the Florida Anti Mosquito Association (1980).

6. Provost, Maurice W. “Environmental Quality and the Control of Biting Flies.” Symposium on Biting-Fly Control and Environmental Quality. 1973.

7. Mulrennan Jr, John Andrew. “Mosquito control-Its impact on the growth and development of Florida.” Insect Potpourri: Adventures in Entomology (1992): 75.

8. Harden, F.W. 1981. You and the environment. Journal of the Florida Anti-Mosquito Association 52:60-61. http://floridamosquito.org/Archi…

9. Trout, A., et al. “Locally Acquired Dengue-Key West, Florida, 2009-2010.” Morbidity and Mortality Weekly Report 59.19 (2010): 577-581. http://www.cdc.gov/mmwr/pdf/wk/m…

10. Rey, Jorge R. “Dengue in Florida (USA).” Insects 5.4 (2014): 991-1000. Dengue in Florida (USA)

11. Radke, Elizabeth G., et al. “Dengue outbreak in key west, Florida, USA, 2009.” Emerg Infect Dis 18.1 (2012): 135-7. http://wwwnc.cdc.gov/eid/article…

12. Teets, Frank D., et al. “Origin of the dengue virus outbreak in Martin County, Florida, USA 2013.” Virology reports 1 (2014): 2-8. https://www.researchgate.net/pro…

13. Buckner, Eva A., Barry W. Alto, and L. Philip Lounibos. “Vertical transmission of Key West dengue-1 virus by Aedes aegypti and Aedes albopictus (Diptera: Culicidae) mosquitoes from Florida.” Journal of medical entomology 50.6 (2013): 1291-1297. https://www.researchgate.net/pro…

14. Parks, Will, and Linda Lloyd. Planning social mobilization and communication for dengue fever prevention and control: a step-by-step guide. World Health Organization, 2004. https://www.researchgate.net/pro…


Does a strong immune system prevent you from getting sick or does it just fight off infection more efficiently?


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Strong versus weak is an unhelpful yardstick to assess whether or not immune function is sufficient. After all, aren’t allergies and autoimmunities signs of strong immune responses? Clearly, immune responses being strong don’t preclude them from also being counter-productive.

In addition, often what differentiates individuals who successfully fight off infections from those who develop its chronic consequences is the nature rather than the strength of their immune responses, i.e., what rather than how much. A classic example is tuberculosis (TB). The vast majority of TB infected people never go on to develop disease. The relatively minor proportion who do are largely characterized by strong antibody responses that are nevertheless ineffective in getting rid of it, i.e., immune responses that vary not in strength but in type/class from the ones in those who successfully fight off TB.

Such examples highlight that rather than strength, ability to efficiently fight off infections comes from launching and sustaining the classes of immune responses that can appropriately deal with a threat while causing least harm to the body itself. Thus, rather than strength, immune response class better predicts capacity to efficiently fight off infections. When the right immune response classes are deployed against a threat, they appear to also carry the capacity for requisite strength to see the threat off with minimal collateral damage.