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Go with your Gut: Be a Health Nut for Heart Health!

May 31, 2016 by Embriette Hyde

May 31st, 2016
By Sharon Thompson, Graduate Research Fellow, and Heather Guetterman, Research Assistant at the Nutrition and Human Microbiome Laboratory


Probiotics (good bacteria) and prebiotics (fibers that bacteria eat) impact gut health. Bacteria are able to both break down dietary fiber that our bodies cannot and make products that are linked to gut health and prevention of diseases like diabetes, cardiovascular disease, obesity, and colon cancer. But what about all of the other foods we eat every day? They come in contact with these bacteria too as they pass through our gut. Foods do not have to be classified as “probiotics” or “prebiotics” to affect the gut microbiome—everything we eat can impact the microbes in our gut.

Let’s take nuts, for example. They have a Qualified Health Claim by the FDA stating that eating 1.5 daily ounces per day of most nuts as part of a diet low in saturated fat and cholesterol may reduce the risk of heart diesase.1 Interestingly, a few studies found that eating nuts lowered blood cholesterol more than what the researchers predicted, leading them to suspect that something else was going on.2,3 This something else may be related to nuts impacting the bacteria that make up the gut microbiome.

So, what’s so great about nuts? In addition to being delicious, nuts are nutrient dense plant foods rich in monounsaturated and polyunsaturated fatty acids. Some of the heart-protecting health effects of nuts are linked to their relatively high monounsaturated and polyunsaturated fat content. Nuts also contain dietary fiber, vitamin E, phytosterols, and other compounds with known health benefits. Bacteria can use dietary fiber for energy and produce byproducts such as butyrate. Butyrate provides energy for cells in the gut and is linked to reduced inflammation.4 Systemic inflammation, or inflammation present throughout the body, is a precursor to metabolic diseases such as obesity and heart disease, and researchers think that these anti-inflammatory bacterial byproducts, including butyrate, may help to partially explain why nuts improve heart health.5

Table 1. Quantity per serving and selected nutrient concentration per ½ oz USDA ounce equivalent serving of nuts1
Quantity per serving Energy (kcal) SFA

(g)

MUFA

(g)

PUFA

(g)

Total Fiber (g)
Pistachios 24 kernels 79 0.8 3.3 2.0 1.5
Walnuts 7 halves 93 0.9 1.3 6.7 0.9
Almonds 12 pieces 82 0.5 4.5 1.7 1.8
Cashews 9 kernels 78 1.1 3.4 1.1 0.5
Hazelnuts 10 kernels 89 0.6 6.4 1.1 1.4


1Data were obtained from the USDA National Nutrient Database for Standard Reference.
Abbreviations: SFA=saturated fatty acids, MUFA=monounsaturated fatty acids, PUFA=polyunsaturated fatty acids


Cardiovascular Benefits of Nut Consumption
A lot of research demonstrates that nuts are heart healthy, with many studies finding that eating nuts can lower total and LDL cholesterol.


  • An analysis of 4 large studies found a 35% lower risk of death related to heart disease in individuals that ate nuts 5 or more times per week.6
  • Eating nuts 5 or more times per week was associated with healthy cholesterol levels in a study involving 6000 women with type 2 diabetes.7
  • A systematic review of 23 nut-focused research studies found that 1.5 to 3.5 ounce servings 5 or more times per week of almonds, peanuts, pecans, and walnuts reduce total cholesterol and LDL cholesterol.3
  • Another review specific to walnuts found that this tree nut lowered LDL and total cholesterol in 13 randomized controlled trials.8

Nut Consumption and the Gut Microbiome
Connections between heart health and the gut microbiome have become more evident in recent years. Certain heart disease risk factors, such as blood cholesterol levels and markers of blood vessel health, have been associated with abundances of specific bacteria in the gut. One study of 893 adults found that certain gut microbes were associated with body weight, triglycerides, and HDL cholesterol.9 Another study found differences in the bacteria that were present in the guts of patients with heart disease compared to a group of healthy adults. Healthy adults had greater abundances of certain bacteria, Roseburia and Eubacterium, than those with heart disease.10 These bacteria produce byproducts such as butyrate that have anti-inflammatory properties.

These studies prompted scientists to work to try to better understand if there is a cause and effect relationship between eating nuts and gut health. A study of 1.5 or 3 servings per day of almonds and pistachios (tree nuts) found that both nuts increased abundances of known butyrate-producing bacteria.11 Recent work from our laboratory, the Nutrition and Human Microbiome Laboratory, found that 1.5 daily ounces of walnuts increased abundances of butyrate-producing bacteria.12 We also found that 1.5 servings per day of almonds resulted in increases of butyrate-producing gut bacteria.13 More work is needed to understand whether and how certain bacteria that produce butyrate, a beneficial by-product, may also be helping improve heart health.

In summary, nuts are nutrient dense foods linked to many health benefits. They reduce the risk of heart disease, and emerging research indicates that nuts also impact the human gut microbiome. More research is needed to understand the full picture and to identify long-term effects of nut consumption on the gut microbiome. As the scientific community learns more about these plant foods, however, one can infer that nut consumption can benefit one’s heart – and potentially one’s gut.

 

References

  1. Administration UF and D. Summary of qualified health claims subject to enforcement discretion: Nuts & heart disease. http://www.fda.gov/Food/IngredientsPackagingLabeling/LabelingNutrition/ucm073992.htm#nuts. Accessed May 16, 2016.
  2. Kris-Etherton PM, Zhao G, Binkoski AE, Coval SM, Etherton TD. The effects of nuts on coronary heart disease risk. Nutr Rev. 2001;59(4):103-111. http://www.ncbi.nlm.nih.gov/pubmed/11368503. Accessed May 20, 2016.
  3. Mukuddem-Petersen J, Oosthuizen W, Jerling JC. A systematic review of the effects of nuts on blood lipid profiles in humans. J Nutr. 2005;135(9):2082-2089.
  4. Brahe LK, Astrup A, Larsen LH. Is butyrate the link between diet, intestinal microbiota and obesity-related metabolic diseases? Obes Rev. 2013;14(12):950-959. doi:10.1111/obr.12068.
  5. Souza RGM, Gomes AC, Naves MM V, Mota JF. Nuts and legume seeds for cardiovascular risk reduction: scientific evidence and mechanisms of action. Nutr Rev. 2015;73(6):335-347. doi:10.1093/nutrit/nuu008.
  6. Kris-Etherton PM, Hu FB, Ros E, Sabate J. The Role of Tree Nuts and Peanuts in the Prevention of Coronary Heart Disease: Multiple Potential Mechanisms. J Nutr. 2008;138(9):1746S – 1751. http://jn.nutrition.org/content/138/9/1746S.full. Accessed May 19, 2016.
  7. Li TY, Brennan AM, Wedick NM, Mantzoros C, Rifai N, Hu FB. Regular consumption of nuts is associated with a lower risk of cardiovascular disease in women with type 2 diabetes. J Nutr. 2009;139:1333-1338. doi:10.3945/jn.108.103622.there.
  8. Banel DK, Hu FB. Effects of walnut consumption on blood lipids and other cardiovascular risk factors : a meta-analysis and systematic review 1 – 3. Ajcn. 2009:56-63.
  9. Fu J, Bonder MJ, Cenit MC, et al. The Gut Microbiome Contributes to a Substantial Proportion of the Variation in Blood LipidsNovelty and Significance. Circ Res. 2015;117(9):817-824. doi:10.1161/CIRCRESAHA.115.306807.
  10. Karlsson FH, Fåk F, Nookaew I, et al. Symptomatic atherosclerosis is associated with an altered gut metagenome. Nat Commun. 2012;3:1245. doi:10.1038/ncomms2266.
  11. Ukhanova M, Wang X, Baer DJ, Novotny JA, Fredborg M, Mai V. Effects of almond and pistachio consumption on gut microbiota composition in a randomised cross-over human feeding study. Br J Nutr. 2014;111(12):2146-2152. doi:10.1017/S0007114514000385.
  12. Guetterman HM, Swanson KS, Novotny JA, Baer DJ, Holscher HD. Walnut Consumption Influences the Human Gut Microbiome. FASEB J. 2016;30(1_Supplement):406.2 – . http://www.fasebj.org/content/30/1_Supplement/406.2.short. Accessed May 19, 2016.
  13. Taylor AM, Swanson KS, Novotny JA, Baer DJ, Holscher HD. Impact of Almond Consumption on the Composition of the Gastrointestinal Microbiota of Healthy Adult Men and Women. FASEB J. 2016;30(1_Supplement):406.5 – . http://www.fasebj.org/content/30/1_Supplement/406.5.short. Accessed May 19, 2016.

 

Sharon Thompson, Graduate Research Fellow, and Heather Guetterman, Research Assistant, work in the Nutrition and Human Microbiome Laboratory directed by Dr. Hannah Holscher at the University of Illinois at Urbana-Champaign. Research in our laboratory focuses on understanding the impact of diet on the human gastrointestinal microbiome with an overarching goal of improving human health through dietary modulation of the gastrointestinal microbiome.

 

Filed Under: Uncategorized

The Microbiome Storms the White House!

May 20, 2016 by Embriette Hyde

May 20th, 2016
By Embriette Hyde, PhD, Project Manager American Gut


One week ago today, I found myself in a place I never imagined I’d ever be-the White House. Well, not exactly. Specifically, I was sitting in an auditorium in the Eisenhower Executive Office Building-the former State, War, and Navy Building-right next to the White House. I had been invited, along with American Gut co-founder and my boss Rob Knight and American Gut collaborator Pieter Dorrestein, to attend the Office of Science and Technology Policy’s unveiling of the National Microbiome Initiative.

The Initiative was the culmination of a few  years’ long journey to get the federal government behind microbiome research-an effort that Rob Knight played an important part of and that seemingly culminated with the call for a unified microbiome initiative, published in Science by Knight and other leaders in the field. The hard work paid off-the White House has answered our call, and in a big way.

A few months ago, the White House issued a call for Microbiome Science Champions-a call that was answered by more than 100 external groups-including myself on behalf of the American Gut Project, and Rob on behalf of the new Center for Microbiome Innovation at UCSD. A few months after submitting descriptions of work being done through American Gut and the Center, Rob and I received our invitations.

At the event, we learned that Federal agencies will be investing over $121 million in microbiome research, with the goals to support interdisciplinary research, facilitate the development of platform technologies, and expand the microbiome workforce. Several organizations have already pledged significant funding, including UCSD, with a contribution of $12 million through the Center for Microbiome Innovation. Everyone at the event was also treated to several panels lead by experts in the field as well as Federal agencies. The excitement and energy in the room was tangible. American Gut collaborator Jack Gilbert was invited to give a flash talk about citizen science, and he highlighted the work being done through American Gut. The American Gut Project has arrived at the White House, ladies and gentlemen! To all of our participants-look what you’ve made possible!

As I sat there, I couldn’t help but think about the future. 5 years, 10 years, 20 years from now, when we see the results of all of our hard work, I will think back on Friday, May 13th, 2016 and remember how it all began, and I’ll remember that I was witness to a very special piece of history that is going to change our field. Perhaps Congresswoman Louise Slaughter said it best: “It’s going to be like splitting the atom when we get all of this done.”


IMAG0573
Congresswoman Louise Slaughter discusses the significance of the NMI.


Rob Knight speaks on a technology panel.
Rob Knight speaks on a technology panel.


Jack Gilbert discusses American Gut as an example of the power of microbiome citizen science.
Jack Gilbert discusses American Gut as an example of the power of microbiome citizen science.


Read the White House National Microbiome Initiative Fact Sheet

For more news pieces see:
White House Goes with Gut, Launching Microbiome Initiative
White House Launches the National Microbiome Initiative
White House Taps UCSD for Microbiome Research
San Diego Scientists Join New National Microbiome
White House launches microbiome initiative
White House Invites UCSD Scientists to Discuss Microbiome
UC San Diego Key Participant in White House Initative

Filed Under: microbiome Tagged With: National Microbiome Initiative

The ICU Microbiome Project: Is There a Better Way to Treat Infections Than Antibiotics?

May 16, 2016 by Embriette Hyde

May 16th, 2016
By Paul E. Wischmeyer M.D., Professor of Anesthesiology and Pediatrics, University of Colorado School of Medicine. Contact him here.


Is Our Current Approach To Infection Working?
A great deal of time and effort are spent in eradicating bacteria and other microbial, fungal, and viral species in the intensive care unit (ICU). The U.S. Centers for Disease Control reports that 55% of all hospitalized patients receive an antibiotic during their stay, and in the ICU this number increases to 70% of patients. As recently described by Singer and Gynne, it is likely that this antibiotic use has in part contributed to an impressive 22-fold fall in crude mortality rates for infectious diseases in the US between 1900 and 1980 (1). Yet, it is troubling that mortality rates from infectious disease (up to 1996) increased—by 50%—with the septicemia rate nearly doubling(1). And in reality, it is unclear if the earlier reductions in mortality and increased life expectancy were due primarily to antibiotics innovations, or more likely, due to improved public health and education.

The massive global reliance on antibiotic use comes at great financial expense with antibiotics accounting for up to 30% of a hospital’s drug budget (2). Unfortunately, greater than the financial costs are the potential risks that inappropriate antibiotic use and overuse carry for patients. Evidence suggests that as many as 37% of antibiotic regimens are unnecessary or uncompliant with guidelines(3). This inappropriate antibiotic use leads to the emergence of multi-drug resistant bacterial infections; the incidence of these infections is rising rapidly both in the U.S. and worldwide (4).  A recent New England Journal of Medicine Article estimates antibiotic-resistant Clostridium difficile occurs now in >450,000 patients per year in the U.S. alone (4). Unfortunately, these multi-drug resistant infections are also becoming increasingly lethal. For example, Clostridium difficile is estimated to contribute to ~30,000 deaths/year in the U.S. (4, 5). Further, The U.S. Centers for Disease Control indicates death rates from sepsis following infections (like C. diff) have increased at a rate greater than any other common cause of mortality in the last year for which data was available (6). And, while age adjusted death rates are decreasing in the U.S., the death rate from sepsis continues to rise significantly (2). And as stated, this is punctuated by mortality rates from infectious disease in general (up to 1996) increasing by 50%, again with the septicemia rate nearly doubling (1). Thus, more advanced antibiotics do not appear to be translating to increased survival from infectious disease, but instead increasingly aggressive resistant organisms and emergence of newly lethal pathogens like C. diff.  Is it possible we need to rethink our strategy towards microbial therapy in the ICU?

Antibiotics Kill More Than Just Pathogens…
These concerns around antibiotics are compounded by the fact that antibiotics currently used to attempt treat infection not only kill pathogens, but also “health promoting” microbes. These adverse effects include the hypothesized loss of commensal gastrointestinal (GI) microbiota, which enables overgrowth of unwanted organisms (dysbiosis). This may have significant implications for organs far outside the GI tract as well. The gut has long been described as the “motor” of systemic inflammatory response syndrome (SIRS) and organ failure, regardless of the location of the initial infection (7). Thus, the effect of alterations in the gut microbiota and gut barrier homeostasis are thought to be transmitted to and propagated by downstream organs, such as the spleen and lung where large immune cell populations are harbored (7-9), leading to inflammation-induced organ failure in the ICU.

Further, it is important to realize that at the cellular level, multiple organ failure, which is a final common cause of death in the ICU, has long been attributed to mitochondrial failure. It has been long known that mitochondria trace their evolution from bacteria that produce energy for our cells. Recent literature not surprisingly reveals that mitochondria are known to be damaged by many of the antibiotics we commonly administer in the ICU (1). Thus, we and others hypothesize that antibiotics may be contributing to organ failure by not only leading to dysbiosis, but also by damaging the very core of our cells’ energy production (1).

Is There Another, Perhaps Better, Way To Prevent And Treat Infections?
As described in a number of very recent and comprehensive review articles (7, 10) laboratory based studies in animals have shown that alterations in intestinal homeostasis and gut microbiota in experimental critical illness have been associated with increased inflammatory cytokine production, gut barrier dysfunction, and increased cellular apoptosis, all of which can contribute to multiple organ failure (MOF). To modulate this “motor” of systemic inflammation it has been hypothesized that repletion of health promoting bacteria via probiotics, prebiotics, stool transplantation or combination therapies may be a promising intervention to maintain gut integrity and prevent pathologic alterations in the gut (and other body sites) microbiota or “dysbiosis” (11-13). Early clinical trials of probiotic use in the ICU have demonstrated some promise in reducing overall infections(14). These studies use a range of probiotic strains and doses, but no ideal probiotic or probiotic mixture has been identified based on actual microbiome-based characterization of the effect of critical illness on patient microbiota.

Thus, before large trials of “dysbiosis therapy” can be meaningfully undertaken, confirmation and characterization of the hypothesized “dysbiosis” of critical illness is urgently needed.  Major funding bodies and experts in the field are indicating more generalizable clinical studies of the ICU microbiome changes are required to better diagnose dysbiosis, and a few pilot (<15 patients) microbiome analysis-based studies have begun to assess these changes (15, 16). The results of these early studies show signals of concerning dysbiosis and loss of microbial diversity. These initial findings have led experts and major funding bodies in the field to conclude there is urgent need for larger, more generalizable, prospective studies that characterize the microbiome in a larger critical care population to confirm and characterize this potential dysbiosis and move towards therapeutic interventions using microbiome signatures (17).

The ICU Microbiome Project: Can We Characterize The Dysbiosis Of Critical Illness?
To attempt to address this question, a collaboration between The Knight Lab and Paul Wischmeyer, M.D.-a researcher and critical care physician at the University of Colorado-was formed a few years ago. This collaboration, which could not have happened without the essential efforts of Daniel McDonald and Gail Ackerman in the Knight Lab, sought to collect fecal, oral, and skin microbiome samples at two timepoints, within 48 hours of ICU admission, and at ICU discharge or ICU day 10. Four hospital centers in the United States and Canada participated using the existing International Nutrition Survey framework developed by Dr. Wischmeyer’s close collaborator, Dr. Daren Heyland at the Clinical Evaluation and Research Unit in Canada. Using this structure we collected samples from 115 patients using standard Earth Microbiome Project protocols for collection and processing as was utilized in the American Gut Project. ICU patient results were compared to a range of existing microbiome databases including a “healthy” cohort of American Gut Subjects.

Our initial results demonstrate that, when compared to healthy American Gut Subjects, critical illness shows rapid and distinct changes from a “healthy” fecal and oral microbiome. (Figure 1) Fecal ICU samples tend to have a lower relative abundance of Firmicutes (Figure 2), and increased relative abundance of Proteobacteria.


fig2
Figure 1. A PCoA plot of ICU samples (large spheres) together with a subset of American Gut samples (small spheres). Spheres are colored by body site.


fig1
Figure 2. A PCoA plot of ICU samples (large spheres) together with a subset of American Gut samples (small spheres). Spheres are colored by abundance of Firmicutes in the sample (red=higher abundance).


Large depletions were observed in organisms shown to confer anti-inflammatory benefits, such as Faecalibacterium (18), which produces short chain fatty acids that are vital to the gut. Conversely, many of the taxa that increased in ICU patients contain well-recognized pathogens such as Enterobacter and Staphylococcus. Ongoing analysis (and perhaps the subject of future blogs) by Daniel, Rob, and Paul will utilize SourceTracker to assess source composition of ICU samples and will use Qiita to examine the effects of critical illness on microbial diversity. Additionally, examination of potential relationships between changes in the ICU microbiome and clinical outcome will be examined. In summary, our initial data from the ICU Microbiome Project confirms that severe dysbiosis occurs in a broad, larger population of critically ill subjects. This data may help guide creation of targeted microbial therapies, focused on correcting potentially “illness-promoting” dysbioses using specific probiotics or targeted, multi-microbe “stool pills” to restore a healthy microbiome and improve outcomes in critical illness. And in the end, perhaps this is the beginning of a road to a better way to treat and prevent infection than the ubiquitous (and maybe questionably effective…in the long run) antibiotics universally given to most all patients in hospitals and ICUs today!

References:

  1. T Singer M, Glynne P. Treating critical illness: the importance of first doing no harm. PLoS Med. 2005;2(6):e167.
  2. Ruttimann S, Keck B, Hartmeier C, Maetzel A, Bucher HC. Long-term antibiotic cost savings from a comprehensive intervention program in a medical department of a university-affiliated teaching hospital. Clin Infect Dis. 2004;38(3):348-56.
  3. Fridkin S, Baggs J, Fagan R, Magill S, Pollack LA, Malpiedi P, et al. Vital signs: improving antibiotic use among hospitalized patients. MMWR Morb Mortal Wkly Rep. 2014;63(9):194-200.
  4. Lessa FC, Mu Y, Bamberg WM, Beldavs ZG, Dumyati GK, Dunn JR, et al. Burden of Clostridium difficile infection in the United States. N Engl J Med. 2015;372(9):825-34.
  5. Rello J, Quintana E, Ausina V, Net A, Prats G. A three-year study of severe community-acquired pneumonia with emphasis on outcome. Chest. 1993;103(1):232-5.
  6. Milbrandt EB, Kersten A, Rahim MT, Dremsizov TT, Clermont G, Cooper LM, et al. Growth of intensive care unit resource use and its estimated cost in Medicare. Crit Care Med. 2008;36(9):2504-10.
  7. Klingensmith NJ, Coopersmith CM. The Gut as the Motor of Multiple Organ Dysfunction in Critical Illness. Crit Care Clin. 2016;32(2):203-12.
  8. Broquet A, Roquilly A, Jacqueline C, Potel G, Caillon J, Asehnoune K. Depletion of natural killer cells increases mice susceptibility in a Pseudomonas aeruginosa pneumonia model. Crit Care Med. 2014;42(6):e441-50.
  9. Khailova L, Baird CH, Rush AA, McNamee EN, Wischmeyer PE. Lactobacillus rhamnosus GG improves outcome in experimental pseudomonas aeruginosa pneumonia: potential role of regulatory T cells. Shock. 2013;40(6):496-503.
  10. Dickson RP. The microbiome and critical illness. Lancet Respir Med. 2016;4(1):59-72.
  11. Marini JJ, Gattinoni L, Ince C, Kozek-Langenecker S, Mehta RL, Pichard C, et al. A few of our favorite unconfirmed ideas. Critical care. 2015;19 Suppl 3:S1.
  12. Krezalek MA, DeFazio J, Zaborina O, Zaborin A, Alverdy JC. The Shift of an Intestinal “Microbiome” to a “Pathobiome” Governs the Course and Outcome of Sepsis Following Surgical Injury. Shock. 2016;45(5):475-82.
  13. Andrade ME, Araujo RS, de Barros PA, Soares AD, Abrantes FA, Generoso Sde V, et al. The role of immunomodulators on intestinal barrier homeostasis in experimental models. Clinical nutrition. 2015;34(6):1080-7.
  14. Petrof EO, Dhaliwal R, Manzanares W, Johnstone J, Cook D, Heyland DK. Probiotics in the critically ill: a systematic review of the randomized trial evidence. Crit Care Med. 2012;40(12):3290-302.
  15. Ojima M, Motooka D, Shimizu K, Gotoh K, Shintani A, Yoshiya K, et al. Metagenomic Analysis Reveals Dynamic Changes of Whole Gut Microbiota in the Acute Phase of Intensive Care Unit Patients. Dig Dis Sci. 2015.
  16. Zaborin A, Smith D, Garfield K, Quensen J, Shakhsheer B, Kade M, et al. Membership and behavior of ultra-low-diversity pathogen communities present in the gut of humans during prolonged critical illness. MBio. 2014;5(5):e01361-14.
  17. Lyons JD, Ford ML, Coopersmith CM. The Microbiome in Critical Illness: Firm Conclusions or Bact to Square One? Dig Dis Sci. 2016.
  18. Sokol H, Pigneur B, Watterlot L, Lakhdari O, Bermudez-Humaran LG, Gratadoux JJ, et al. Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc Natl Acad Sci U S A. 2008;105(43):16731-6.

 

Paul Wischmeyer M.D., EDIC, is a Professor of Anesthesiology and Pediatrics (Nutrition Section) at the University of Colorado School of Medicine. My current research focuses on the role of the microbiome and dybiosis in the pathobiology and treatment of critical illness, surgery, and trauma. We also have long-standing interests in the role of nutrition and probiotics to improve outcome from critical illness, surgery, cancer, and other acute/chronic illnesses. Our past and current projects span the range of translational research from basic mechanistic pathways in cellular systems and in vivo proof–of–concept modeling to human pilot trials and large multi-center randomized controlled clinical trials.

Filed Under: antibiotics, data analysis

Intra-Family Microbial Dynamics

April 19, 2016 by Embriette Hyde

April 19th, 2016
By Naseer Sangwan, PhD


The gut microbiome (total microbial gene content existing in the gastrointestinal tract) has been established as a significant factor in the development of human health (1). Interaction between co-habitating individuals and their physical environment, e.g. shared physical space, has significant impact on their associated microbiome (2). Recent studies have shown that ‘nuclear families’ provides a unique framework to analyze how perturbations to one family member’s microbiome would impact the microbiome of others in the family. Here we present a brief summary of the microbiome analysis of a nuclear family with two children (juvenile female=12 years, juvenile male=8 years, adult female=42 years, adult male=44 years) who have distinct interpersonal health profiles. As an example, metadata highlighted that both juveniles suffered from seasonal allergies, while the juvenile male also suffered from eczema and food allergies to peanuts, lentils, soy and wheat. Neither adult family member suffered from these conditions. We performed whole genome shot gun metagenomic sequencing of fecal samples (one sample per individual) of all family members. Metagenome sequences were analyzed to characterize the taxonomic and functional potential of the gut microbiota using MetaPhlAn (3) and HUMAnN, respectively (4).


figure1
Figure 1.  Intra-family microbial dynamics. (A) Meta data and total microbial gene content assembled across all family members. (B) Bargraph representing relative abundance of the signature genera in all family members. (C) Table presenting pairwise simialrity of microbiome samples measured by pairwise distance based on quantitative taxa abundance data. (D) Whole genome based synteny (order of similar genes) comparison of complete genome of A. muciniphila ATCC BAA-835 and Akkermansia Meta assembled across adult male microbiome.


Genus level analysis revealed quite a few bacteria that were common to all members, such as the genera Escherichia, Bacteroides, Eubacterium and Faecalibacterium (Figure 1B). High abundance of Bacteroides was clearly evident across all members (i.e. Adult male=40.8%, Adult female=24.5%, juvenile female=36.0%, juvenile male=34.6%). However, upon closer inspection it was revealed that a certain species of the genus Bacteroides, called Bacteroides intestinalis, was enriched in the adult male and female and juvenile female samples, where it comprised >5% of the community. However, in the juvenile male, this species was mostly absent, instead Bacteroides vulgatus was highly abundant (>5% of the community). Overall, the juvenile male’s microbiome was the most different (Figure 1C), and contained bacterial genomic sequences that are related to organisms that can produce butyrate (a short chain fatty acid; SCFA), such as the species Roseburia intestinalis, Bacteroides vulgatus and Ruminococcus bromii. This species specific SCFA production helps in developing tolerance acquisition, e.g. (i) Expansion of intraepithelial lymphocytes, (ii) lowers the pH, favoring the colonization of other commonsel anaerobes. It is possible that the juvenile male’s microbiome is responding to his allergies, as we have shown in previous studies (5) by increasing the abundance of taxa that can produce SCFAs. The adult male and female had genomic DNA related to Akkermansia municiphilia, which has been identified as being a negatively correlated with obesity (6). A. muciniphila has been shown to regulate human metabolism through increasing intestinal levels of endocannabinoids that control inflammation and gut peptide secretion. Using metagenome assembly and binning methods we compared the genome of Akkermansia municiphilia found in the microbiome of the adult male and female against genome sequenced strains in the public databases (specifically A. muciniphila ATCC BAA-835; (7); Fig. 1D). Th A. muciniphila species found in the adults had a different gene content and a different order for the same genes when compared to the known strains. This points to the individuality of each person’s microbiome; A. municiphilia in one person may be different to A. municiphilia in another!

We further analyzed the functional potential of each person’s microbiome, and determined how well conserved microbial function was between family members. We randomly picked and annotated 76,000 genes from the microbiome of each member, and mapped these genes to metabolic pathways. Most metabolic pathways were found in similar abundance in each family member. However, the juvenile male had a significant enrichment for lipid metabolism, which may be related to his diet. To achieve higher resolution we focused our analysis on determining the differences in enzyme potential between individuals, ignoring core metabolic functions such as energy metabolism, and DNA/RNA transcription and translation). Enzymes involved in Acetyl-CoA-based butyrate production were at very different abundances in each family member. The enzyme 3-hydroxy-3-methylglutaryl-CoA reductase and butyrate kinase were significant enriched (average mean proportion > 5%) in the microbiome of the juvenile male compared to the other family members. This could be related, as shown previously (Canini et al., 2015) to the juvenile male’s allergies (Figure 1A). Although, in the present study it is not possible to determine the mechanism by which seasonal and food allergy influence microbial composition.

We further quantified the ‘equivalent’ genes, i.e. orthologous genes, across all family members. Orthologs are defined as similar genes that are related through speciation from a single ancestral gene, not through gene duplication. Pairwise analysis revealed 12,512 genes as orthologous across all family members, and 19,069 genes in parents versus progeny analysis. In addition, 30,668 and 35,621 genes were characterized as orthologous across the pairwise analysis of parents and progeny samples, respectively. Our results indicate that the parents share similar gene content with each other more than they do to the children, and vice versa. Finally, we analyzed the microbial antibiotic resistance potential across all family members. The juvenile male showed the highest number of microbial antibiotic resistance genes (n = 170) in comparison to other family members, i.e. (Adult male = 117, adult female = 142, juvenile female=110). However, the importance of this observation is hard to define.

In summary, we demonstrated clear differences in the microbiome recovered from the members of a nuclear family with various aged children. Also, the juvenile male’s microbiome showed signatures that relate to his food allergies. We expect that further inclusion of data from more families in future studies would help to understand the role of microbiome in tolerance acquisition against food and seasonal allergies.

References

  1. Marchesi JR, Dutilh BE, Hall N, Peters WHM, Roelofs R, Boleij A, Tjalsma H. 2011. Towards the Human Colorectal Cancer Microbiome. PLOS ONE 6:e20447.
  2. Schloss PD, Iverson KD, Petrosino JF, Schloss SJ. 2014. The dynamics of a family’s gut microbiota reveal variations on a theme. Microbiome 2:25.
  3. Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C. 2012. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods 9:811–814.
  4. Abubucker S, Segata N, Goll J, Schubert AM, Izard J, Cantarel BL, Rodriguez-Mueller B, Zucker J, Thiagarajan M, Henrissat B, White O, Kelley ST, Methé B, Schloss PD, Gevers D, Mitreva M, Huttenhower C. 2012. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput Biol 8:e1002358.
  5. Berni Canani R, Sangwan N, Stefka AT, Nocerino R, Paparo L, Aitoro R, Calignano A, Khan AA, Gilbert JA, Nagler CR. 2015. Lactobacillus rhamnosus GG-supplemented formula expands butyrate-producing bacterial strains in food allergic infants. ISME J.
  6. Everard A, Belzer C, Geurts L, Ouwerkerk JP, Druart C, Bindels LB, Guiot Y, Derrien M, Muccioli GG, Delzenne NM, Vos WM de, Cani PD. 2013. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc Natl Acad Sci 110:9066–9071.
  7. Passel MWJ van, Kant R, Zoetendal EG, Plugge CM, Derrien M, Malfatti SA, Chain PSG, Woyke T, Palva A, Vos WM de, Smidt H. 2011. The Genome of Akkermansia muciniphila , a Dedicated Intestinal Mucin Degrader, and Its Use in Exploring Intestinal Metagenomes. PLOS ONE 6:e16876.

Naseer Sangwan, PhD, is a post-doc in the Gilbert lab at the University of Chicago. His research is focused on understanding the food allergies-induced dysbiosis of intestinal microbiota using comparative population genomics of microbial gene-complements re-assembled across deeply sequenced metagenome datasets.

Filed Under: data analysis, metagenomics, microbiome

QIIME 2 will revolutionize microbiome bioinformatics

April 15, 2016 by Embriette Hyde

April 15th, 2016
By Greg Caporaso, PhD


It’s official: QIIME, the primary microbiome bioinformatics platform used by the American Gut project, is now NSF funded. This is a very exciting step for the QIIME development team, and we’re already hard at work building the platform that we expect to revolutionize microbiome bioinformatics.

From a user perspective there are a few key features to look forward to in QIIME 2. First, we’ll be completely rewriting our visualization framework to support interactive visualizations that will greatly simplify exploratory analysis, and allow for exporting of publication quality graphics. Users will no longer have to run multiple QIIME scripts to sort, filter, and group data into the desired figure — simply point-and-click to produce beautiful and informative visualizations! We’ll also be providing support for many updated analytic tools, including ANCOM for identifying differentially abundant OTUs, diverse sequence count normalization techniques (including those discussed in McMurdie et al., 2014 – those are now available in QIIME 1, but will be central to QIIME 2), and new quality control and OTU assignment tools, including vsearch, DADA2 and swarm. These tools will all be made available as QIIME 2 plugins, and we will provide detailed plugin developer documentation so that it’s straight-forward for other bioinformatics developers to make their methods accessible in QIIME. For our users, this plugin-based approach means quicker access to the latest tools: you won’t have to wait for a new QIIME release to get access to the latest functionality, as new plugins can be easily added to an existing QIIME deployment.

One of the most exciting new features from my perspective, and one of the reasons why I think QIIME 2 will revolutionize microbiome bioinformatics, is that QIIME 2 is completely interface-agnostic. We provide a software development kit (SDK), which developers can use to build interfaces around QIIME. QIIME 1 was tightly coupled to its command line interface. This worked well for power users, but supporting graphical interfaces for QIIME 1 is very challenging. As a result, existing graphical interfaces for QIIME 1, such as Qiita and BaseSpace, generally provide access to only limited functionality. The QIIME 2 SDK will make it straightforward to develop diverse, fully featured interfaces, including graphical interfaces (for end users) and command line interfaces (for power users). We’ll provide some of these, but we’re also very excited to see new interfaces that the community develops. Some additional exciting features include a semantic type system, which will help guide users to relevant analyses (and help them avoid invalid analyses), and decentralized provenance tracking, which will help users keep track of where their data from and which ultimately will be used to automate the generation of “Methods section” flowcharts. Taken together, these features will make QIIME 2 accessible to anyone, and will improve the quality and reporting of microbiome data.

As promised in my recent QIIME Blog post, Toward QIIME 2, we now have an experimental QIIME 2 web interface available as a public prototype. We’re currently working on finalizing some components of the framework, developing a command line interface and a web interface, and interfacing QIIME 2 with Qiita to support meta-analysis of microbiome and mutli-omics data sets. Once these pieces are in place, we’ll be coordinating with a large team of collaborators to develop plugins. We’re still on track to have an alpha release out this summer, which we’ll present at SciPy 2016 and in the ISME 16 Bioinformatics workshop (the official announcement for that will go live next week).

So what does all of this mean for American Gut participants? First, it means that your results will get to you faster, as the bioinformatics processing will be more straight-forward. It also means that the data you receive will be based on the most recent methods, and will be presented to you using the latest generation visualization techniques which will make it easier to interpret. And finally, for users who are so inclined, QIIME 2 will provide a very straight-forward way for you to access your own raw data (and others’ de-identified raw data) and perform your own custom analyses.

Finally, thanks to the QIIME developers, the National Science Foundation, and our active user community. All of this is only possible because of you! To stay up-to-date with news on QIIME 2, follow us on Twitter. Happy QIIME-ing!

Greg Caporaso is an Assistant Professor at Northern Arizona University, one of the lead developers of QIIME, and principal investigator on the 2016 NSF QIIME 2 grant mentioned here.

Filed Under: bioinformatics, data analysis, microbiome

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