Obesity, diabetes combating device safe for treatment

A non-surgical and reversible device for people with Type 2 diabetes and obesity.

A non-surgical and reversible device for people with Type 2 diabetes and obesity is safe, effective and should be rolled out across the National Health Service (NHS), researchers say. The device — Endobarrier — is a reversible treatment that provides people with an alternative to drastic gastric bypass surgery. It prevents food from coming into contact with the first part of the small intestine, but without painful invasive surgery. Endobarrier consists of a 60-cm-long tube-like liner or sleeve that coats the inside of the small intestine, allowing food to pass through but not to be absorbed, which can be removed after a year. The procedure aims to kick-start a change in lifestyle and help people achieve better health, improve diabetes control as well as promote weight loss, the researchers said.

What is an Endobarrier

The device, Endobarrier, is a reversible treatment that provides people with an alternative to drastic gastric bypass surgery. It prevents food from coming into contact with the first part of the small intestine, but without painful invasive surgery. Endobarrier consists of a 60-cm-long tube-like liner or sleeve that coats the inside of the small intestine, allowing food to pass through but not to be absorbed, which can be removed after a year. Now you can treat your Type 2 diabetes and obesity with a device based medical treatment which is highly safe and serves the purpose of a total cure says a study. The treatment prevents food from coming into contact with the first part of the small intestine through a surgery. Participants reported considerable improvements in well-being, energy, and the ability to exercise, with around 94 per cent saying that they would recommend the service to their friends and family. For the study, presented at 2017 European Association for the Study of Diabetes (EASD) Annual Meeting in Portugal, the team investigated whether this new therapy could be translated into major clinical success by creating a small NHS Endobarrier service for people having difficulties managing their Type 2 diabetes and obesity.

Gastric band France Reveals Secret to Which are the best foods to help weight loss

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We reveal which are the best foods to help with weight loss??

  1. Eggs
  2. Oatmeal
  3. Pulses
  4. Nuts
  5. Avocados
  6. Berries
  7. Cruciferous vegetables
  8. Considerations
  9. Weight loss tips
Research by scientists has revealed that some foods may have an impact on appetite. These could be beneficial for weight loss when incorporated into a healthful diet and lifestyle. Read on to learn more about seven foods that may be helpful for weight loss.
People should buy nutrient-dense foods if they are trying to lose weight. Foods that provide protein and fiber could be especially helpful for weight management. One study found that some foods — including fruits, vegetables, nuts, whole grains, and yogurt — were connected with weight loss. In the same study, potato chips, sugary beverages, red meats, and processed meats were associated with weight gain. Based on these findings, it may be best to limit fried foods, foods with added sugar, high-fat meats, and processed foods when trying to shift the pounds. Though the right foods may help, physical activity is essential for losing weight and keeping the pounds off. It is important to check with a doctor before starting any physical activity program.

1. Eggs

bowl of oatmeal with nuts and fruitFoods that provide both protein and fiber may help with weight loss.
Eggs are a popular food, particularly for breakfasts, that may help promote weight loss. In a small study of 21 men, researchers compared the effects of eating eggs or eating a bagel for breakfast on food intake, hunger, and satisfaction. They also looked at levels of blood sugar, insulin, and ghrelin, which is also known as the hunger hormone. They found that men who had eaten the egg breakfast ate significantly less at their next meal, and in the following 24 hours, than those who had eaten the bagel breakfast. Those who had eaten the eggs also reported feeling less hungry and more satisfied 3 hours after breakfast than those who had eaten the bagel. After breakfast, the egg group also had less of a change in their blood sugar and insulin levels, as well as lower ghrelin levels than the bagel group.

2. Oatmeal

Starting the day with a bowl of oatmeal could also result in a lower number on the scales. A study involving 47 adults looked at differences in appetite, fullness, and next meal intake after participants ate oatmeal, as opposed to an oat-based ready-to-eat breakfast cereal. After eating oatmeal, participants felt significantly fuller and less hungry than after eating the cereal. Also, their calorie intake at lunch was lower after eating oatmeal than after eating breakfast cereal. While both breakfasts contained the same amount of calories, the oatmeal provided more protein, more fiber, and less sugar than the cereal. The authors concluded that the difference in fiber, specifically a type of soluble fiber called beta-glucan, was probably responsible for the results.

 3. Beans, chickpeas, lentils, and peas

As a group, beans, chickpeas, lentils, and peas are known as pulses. They may influence weight loss due to their effect on fullness, as well as their protein and fiber content. Similarly to oatmeal, pulses contain soluble fiber that may slow down digestion and absorption. Eating protein leads to the release of hormones that signal fullness. Researchers analyzed studies that had looked at the effect of the consumption of pulses on weight loss. Weight loss diets that included pulses resulted in significantly greater weight loss than those that did not. Weight maintenance diets that included pulses also resulted in weight loss compared with those that did not.

4. Nuts

A study involving overweight and obese women compared a weight loss diet supplemented with 50 grams (g) of almonds a day with a weight loss diet that did not include nuts. After 3 months, women in the almond group lost significantly more weight than women in the nut-free group. Women in the almond group also had much greater reductions in their waist size, body mass index (BMI), total cholesterol, triglycerides, and blood sugar. Nuts contain protein and fiber, which may help explain their influence on body weight. They also contain heart-healthy fats and other beneficial nutrients. While nuts can be included as part of a healthful diet, moderation is still essential since they are an energy-dense food. Weight regain is often a concern for individuals after they have lost weight. In a large study in Europe, researchers found that people who consumed the most nuts gained less weight during a 5-year period than people who did not eat nuts. They also had less risk of becoming overweight or obese.

5. Avocados

Avocados are a fruit that provides fiber and beneficial fats, as well as many other nutrients. They may also help promote weight management. A study of American adults found that people who consumed avocado weighed significantly less and had a lower BMI than those who did not. People who ate avocado tended to eat more fruits, vegetables, and fiber than people who did not, as well. The people who ate avocado had an overall healthier diet and consumed significantly less added sugar than those who did not. Similarly, their risk for metabolic syndrome was lower than for those who did not consume avocado.

6. Berries

Fiber has been linked with weight management, and berries tend to be some of the highest-fiber fruits. One cup of raspberries or blackberries provides 8 g of fiber. Berries can be added to many foods, such as oatmeal, yogurt, or salads.

7. Cruciferous vegetables

Cruciferous vegetables, including broccoli, cauliflower, cabbage, and Brussels sprouts also contain fiber that may be helpful for weight loss. One cup of cooked Brussels sprouts provides 6 g of fiber, which is 24 percent of the daily value for fiber.

Things to look for when choosing foods for weight loss

Instead of fried foods, people should choose foods that have been baked, broiled, or grilled. Lean proteins, including beans, chicken, eggs, fish, and turkey are good alternatives to high-fat meats. When choosing foods for weight loss, it is also important to be mindful of portion sizes, even for healthful foods. Sugar-sweetened beverages can provide a significant amount of calories but do not result in the same sense of fullness as solid foods. Choose calorie-free beverages instead of juice and soda, such as water or unsweetened tea.

Other useful weight loss tips

young woman trying to choose between fruit and cakes<!--mce:protected %0A-->Branding some foods as “bad” can lead to cravings and guilt.
  • Exercise is a key part of weight loss. The American College of Sports Medicine recommend adults get 150 minutes of moderate intensity exercise per week, which equals 30 minutes 5 days a week. People should speak with a doctor before starting a new workout routine.
  • Concentrate on making healthful changes instead of concentrating only on the number on the scales. Mini goals may feel less overwhelming than one large goal.
  • Avoid labeling foods as “good” and “bad.” Forbidden foods can lead to cravings and then guilt when those foods are eaten. Choose nutritious foods most of the time and enjoy treats in moderation.
  • Avoid getting overly hungry. Waiting to eat until starving can make it harder to be mindful of healthful choices.
  • Planning meals ahead of time can help ensure healthful choices are available, especially since many restaurant meals tend to be higher in calories, fat, and salt.
  • Enlist friends and family members to help support health goals and behavior changes.
  • Consult a registered dietitian who is a food and nutrition expert and can provide individualized information to help with weight loss.
  • Work on getting adequate sleep and managing stress levels in addition to choosing healthful foods and staying active, as sleep and stress affect health.

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How to control your appetite naturally

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Hunger is an important, natural reminder for people to keep their bodies fueled. But often, an appetite can come back even when we have eaten enough. High appetites can be caused by the kinds of food we eat, the way we eat them, and diet plans that leave a person feeling hungry, among other reasons. Weight loss pills make big claims about suppressing appetite but their effectiveness is uncertain, and they often come with dangerous side effects. The following techniques are natural, risk-free methods to suppress appetite. They can be put into action to tackle hunger cravings in a healthful way. Natural ways to suppress appetite There is a range of things a person can due to reduce their appetite, including: 1. Eating more protein or fat high protein food Eating foods rich in protein or fat may help reduce hunger cravings. Not all foods satisfy hunger equally. Protein and fats are better than carbohydrates at reducing hunger, especially those high in sugar. Studies consistently show that protein and fats are essential for satisfying hunger and keeping people full for longer. Protein-rich foods recommended by the Dietary Guidelines for Americans include: lean meats eggs beans and peas nuts soy products Greek yogurt Foods that are good sources of fats include: nuts seeds avocado olive oil cheese coconut grass-fed butter eggs 2. Choosing high-fiber foods Fiber does not break down like other foods, so it stays in the body for longer. This slows down digestion and keeps people feeling full throughout the day. Research suggests that fiber can be an effective appetite suppressant. High-fiber diets are also associated with lower obesity rates. On the other hand, another review found that introducing extra fiber into the diet was effective in less than half of the studies they looked at. More research is needed to identify which sources of fiber are the most effective for suppressing appetite. High-fiber foods include: whole grains beans and pulses fruits, including apples and avocados almonds chia seeds vegetables 3. Drinking more fluids Drinking a large glass of water directly before eating has been found to make a person feel fuller, more satisfied, and less hungry after the meal. Another study, which looked at appetite in 50 overweight females, showed that drinking 1.5 liters of water a day for 8 weeks caused a reduction in appetite and weight, and also led to greater fat loss. A soup starter may also quench the appetite. Research from 2007 showed that people reported feeling fuller immediately after the meal if they had a liquid starter. 4. Eating large volumes of the right foods Reducing general food intake while dieting can leave people with a ravenous appetite. This can cause a relapse into binge eating. Dieting does not have to mean going hungry. Some foods are high in nutrients and energy, but low in calories. These include vegetables, fruits, beans, and whole grains. Eating a large volume of these foods will stop the stomach from growling and still allow a calorie deficit. 5. Practicing mindful eating The brain is a major player in deciding what and when a person eats. If a person pays attention to the food they are eating instead of watching TV during a meal, they may consume less. Research published in the journal Appetite found that eating a huge meal in the dark led people to consume 36 percent more. Paying attention to food during meals can help a person reduce overeating. Another article showed that mindfulness might reduce binge eating and comfort eating, which are two significant factors that influence obesity. The National Institute of Health recommend using mind and body-based techniques, such as meditation and yoga, to curb appetite. 6. Exercising Exercise is another healthy and effective appetite suppressant. A review based on 20 different studies found that appetite hormones are suppressed immediately after exercise, especially high-intensity workouts. They found lower levels of ghrelin in the body, a hormone that makes us hungry, and higher levels of “fullness hormones” such as PPY and GLP-1. 7. Reducing stress Comfort eating due to stress, anger, or sadness is different from physical hunger. Research has linked stress with an increased desire to eat, binge eating, and eating non-nutritious food. Mindfulness practices and mindful eating may reduce stress-related binge eating and comfort eating, according to one review. Regular sleep, social contact, and time spent relaxing can also help tackle stress. Foods that minimize appetite honey Switching from sugar to honey may help suppress appetite. Protein-rich foods and healthful fats are best for reducing appetite. These include lean meats, avocado, beans, nuts, and cheese. High-fiber foods keep a person feeling fuller for longer. Good examples are whole grains, beans, fruits, and vegetables. Pulses, such as beans, lentils, and chickpeas, can directly increase feelings of fullness and may also reduce food intake later, according to a 2017 review. Dark chocolate suppresses appetite compared to milk chocolate. One study showed that people ate less during their next meal after snacking on dark instead of milk chocolate. Eggs are high in protein and fat and may promote feelings of fullness and reduce hunger through the day. Ginger has been shown to reduce appetite and increase fullness, possibly because of its stimulating effect on the digestive system. Cayenne pepper may reduce appetite in people who are not used to spicy foods. Honey may suppress the hunger hormone ghrelin, making people feel fuller for longer. People should try switching from sugar to honey. Tea. Research shows a tea called Yerba Maté can reduce appetite and improve mood when combined with high-intensity exercise. Ginger: Health benefits and dietary tips Ginger: Health benefits and dietary tips Research suggests that ginger could help to reduce appetite. Learn more about the health benefits of this food and its nutritional content here. Read now Takeaway Restricting food consumption too much can lead to a relapse of overeating. Instead, eating a good amount of the right foods can reduce hunger and food cravings throughout the day. A person can suppress their appetite by including more protein, fat, and fiber in their meals. Stocking up on vegetables and pulses can make a person feel fuller for longer. It might also help to try different spices, such as ginger and cayenne pepper, and drink tea to beat unwanted food cravings.

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Multiethnic Genome-Wide Meta-Analysis of Ectopic Fat Deposits

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Multiethnic Genome-Wide Meta-Analysis of Ectopic Fat Depots Identifies Loci Associated With Adipocyte Development and Differentiation.
Figure 1 Functional characterization of Atxn1, Ebf1, Rreb1 and Ube2e2
(a,b,e) Data is displayed as box/whisker plots where the center line represents the median, box limits contain the 25th–75th percentiles, and whiskers span max/min values. (a) Gene expression measured by qPCR in murine subcutaneous (SAT), perigonadal visceral (VAT), and pericardial (PAT) adipose tissues (n=6 mice). Statistical significance was assessed using ANOVA and Sidak’s correction for multiple comparisons. (b) Gene expression measured by qPCR in murine adipose tissues after 8 weeks of high fat feeding compared to normal chow fed controls (n=5 mice per group). Statistical significance was assigned using a two-sided T-test. (c) Gene expression measured by qPCR in cultured adipocyte progenitors isolated from the subcutaneous (SAT) or perigonadal visceral (VAT) depots (n=4 replicates). Cells were expanded to confluence and then collected at intervals after induction of adipogenic differentiation. Data displayed as mean, error bar=s.e.m. Statistical significance was assessed using ANOVA and Sidak’s correction for multiple comparisons to time 0. (d) Oil-red-o staining of progenitors isolated from subcutaneous adipose and exposed to retroviral delivery of shRNA constructs during ex vivo expansion and induction of adipogenesis. Relative to control vector carrying a scramble sequence, shRNA constructs specific for Atxn1 and Ube2e2 impaired adipogenic differentiation. Scale=1mm. (e) Oil-red-o stain was alcohol extracted and quantified at OD520 (n=9 technical replicates). Statistical significance was assessed using ANOVA and Sidak’s correction for multiple comparisons to control (Scramble). Data representative of 3 independent experiments.

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Trouble losing weight? This might be why

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Trouble losing weight?  This might be why !
Some people find it harder to lose weight than others, but why is this? A new study has identified a molecule in fat cells that could be to blame.
Woman standing on scales with a measuring tapeResearchers have uncovered one reason why some people may find it hard to lose weight.
Researchers found that the fat cells of people who are obese show higher expression of a molecule called lysyl oxidase (LOX). LOX is associated with fibrosis, or “scarring,” of fat tissue, which, as previous research has shown, can hamper weight loss efforts. Study co-author Dr. Katarina Kos, who works in the Diabetes and Obesity Research Group at the University of Exeter Medical School in the United Kingdom, and colleagues recently reported their findings in the journal Metabolism. It is thought that around 1 in 3 adults in the United States are obese, which puts them at increased risk of type 2 diabetes, stroke, heart disease, and some forms of cancer. A lack of exercise and a poor diet are the primary causes of obesity, so it’s no surprise that eating a healthful diet and increasing physical activity are the first strategies we try in an attempt to shed the pounds. But these interventions can produce mixed results: some individuals see the pounds fall off, while others find it much more challenging. The new study may have uncovered one explanation for the latter.

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How to lose water weight naturally

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How to lose weight naturally by losing water weight

Water weight, also called edema, is very common and rarely a cause for concern. However, it may feel uncomfortable and can cause unwanted bloating or puffiness in the body. This article outlines simple, healthy lifestyle tips for tackling water weight. Fast facts on water weight: Water normally makes up 50 to 60 percent of an adult’s total body weight. Any extra water being held in the body is referred to as “water weight.” When water builds up in the body, it can cause bloating and puffiness, especially in the abdomen, legs, and arms. Water levels can make a person’s weight fluctuate by as much as 2 to 4 pounds in a single day. Severe water retention can be a symptom of heart or kidney disease. More often, it is temporary and goes away on its own or with some simple lifestyle changes.

Ways to lose water weight

There are a variety of ways a person can lose water weight quickly and naturally. We look at the most effective techniques: 1. Reduce sodium (salt) intake bottle of water with measuring tape Water weight may feel uncomfortable and cause bloating or puffiness in the body. An easy first step for beating water weight is to replace sodium-rich foods with low-sodium equivalents. Too much sodium, or salt, can cause immediate water retention. This is because the body needs to keep its sodium-to-water ratio balanced to function properly, so will hold on to water if too much salt is consumed. The latest Dietary Guidelines for Americans recommend no more than 2,300 milligrams (mg) of sodium per day. An average American will eat over 3,400 mg every day. Table salt is very high in sodium, but 75 percent of the sodium people consume is hidden in processed foods. These include cheese, cold meats, bread, frozen meals, soup mixes, and savory snacks. Natural foods, such as vegetables, nuts, and seeds, are very low in sodium. Some foods can even reduce sodium levels, including bananas, avocados, and leafy vegetables. 2. Drink more water While counterintuitive, drinking water can actually reduce water weight. Dehydration can make the body hold on to extra water to make up for lack of incoming water. Water also improves kidney function, allowing excess water and sodium to be flushed out of the system. Adults should drink around 2 liters of water a day. Replacing sugary drinks with pure water is a great way to keep up with the body’s daily water needs.
3. Reduce carbohydrate intake
Carbohydrates, or carbs, also cause the body to store extra water. When we eat carbs, the energy that we do not use right away is stored as glycogen molecules. Each gram (g) of glycogen comes with 3 g of water attached. Cutting down on carbs is a quick way to use up the glycogen stores, which means that the water weight will also be reduced. According to the Institute of Medicine’s Food and Nutrition Board, adults need at least 130 g of carbohydrates to function each day, but the average American diet includes much more than this. Common carbs include bread, rice, and pasta. Replacing some daily sources of carbs with high-protein foods, such as lean meats, eggs, and soy products, can reduce the buildup of water weight.

4. Supplements

Vitamin B-6 and magnesium oxide can be effective natural remedies for fluid retention. These supplements work with the kidneys to help the body flush extra water and sodium from the system. Studies show that these two supplements are very effective at relieving the symptoms of premenstrual syndrome or PMS, including water retention. They can also reduce abdominal bloating, swelling in the legs, and breast tenderness. It is best for someone to talk to a doctor before taking new supplements, as they can have side effects or interactions with other medications.

5. Exercise

Exercise lets the body sweat out extra water. This causes water weight to drop immediately after exercise. A workout also stimulates blood flow and improves circulation, which can reduce fluid buildup throughout the body, especially in the legs and feet. Exercise reduces water weight even more by burning through glycogen energy stores. However, replacing lost fluids is vital after any physical activity to avoid dehydration.

6. Water pills

Water pills can treat mild fluid retention, as prescribed by a doctor. These pills work as diuretics, meaning they make a person urinate more often. Urination lets the body get rid of excess water and sodium. Water pills are not recommended for long-term use. They should always be used as instructed by a doctor to avoid dehydration or mineral deficits.

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Why your body size perception could be wrong

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Why your body size perception could be wrong

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Identifying risk factors for pancreatitis in children

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Identifying risk factors for pancreatitis in children

Research Update Nov. 28, 2016
In the largest study of its kind, an international group of researchers found that genetics, birth defects, and ethnicity may play important roles in the occurrence of pancreatitis in children. Pancreatitis, or inflammation of the pancreas, is accompanied by abdominal pain, nausea, vomiting, and, in severe cases, permanent tissue damage. Pancreatitis can be acute (occurring suddenly and usually self-resolving after a few days) or chronic (long-lasting). In some cases, recurring acute episodes can lead to the more debilitating chronic form of the disease. While both forms of pancreatitis are more common in adults, they can also develop in children. However, researchers have struggled to identify the factors that put young people at risk for pancreatitis, partly because the most common risk factors for adults—gallstones and heavy alcohol use—are rare in children. The multinational INSPPIRE (International Study Group of Pediatric Pancreatitis: In Search for a Cure) consortium was established to investigate the risk factors and outcomes of pediatric pancreatitis. The consortium, which has enrolled the largest cohort of pediatric pancreatitis patients to date, collected genetic, demographic, and clinical data from 301 children (girls and boys aged 19 and under) with acute recurrent or chronic forms of pancreatitis. The most common risk factor for pancreatitis in children was at least one mutation in any of four genes that are known to be associated with pancreatitis—CFTR, PRSS1, SPINK1, and CTRC. Mutations in PRSS1 and SPINK1 were more common in children with chronic pancreatitis than in children with acute recurrent pancreatitis, which means that mutations in these genes may increase the risk of transitioning from acute to chronic pancreatitis. Another risk factor found was obstruction of the pancreatic duct, most frequently by a relatively common birth defect known as pancreas divisum, in which the pancreas is drained by two smaller ducts instead of a single one. Other risk factors for pancreatitis that were identified were toxic or metabolic factors and autoimmune diseases, but they were not as common as genetic or obstructive factors. Many of the children in the study were found to have multiple risk factors for pancreatitis, suggesting that the disease may result from a complex interplay among more than one factor. The researchers also found that non-Hispanic children were more likely than Hispanic children to develop chronic pancreatitis. In addition to identifying risk factors, the INSPPIRE researchers also examined the burden of disease in children with pancreatitis. They found that children with both forms of pancreatitis endured significant abdominal pain, along with a number of emergency room visits and hospitalizations. Children with chronic pancreatitis had a higher number of emergency room visits and hospitalization than children with recurrent acute episodes, underscoring the need to diagnose and treat pancreatitis early to avoid progression of the disease to the chronic form. Additional research is needed to tease out how these factors drive pancreatitis development and progression in children. However, overall, the results in this study suggest that there are potential ways to screen for increased risk of pancreatitis in children, such as genetic testing, possibly providing the opportunity for early intervention before the disease develops or becomes chronic.

References

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Sitting down can build fat around your organs, study shows

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The potential results of how Sitting down can build fat around your organs, according to a new study.

Besides the ever-so-annoying belly fat, there’s also a much more “invisible” — but just as harmful — kind of fat: one that sits around our internal organs. What causes this, and is it possible to get rid of it? A new study has some answers.
people sitting down on bench
Too much sitting down can build ‘invisible’ fat, says new study.
For one thing, we need get off our tushies, and pronto! Sedentary time correlates directly with how much fat we build around our organs, according to the new study, which was published in the journal Obesity. For another, we need to exercise. The research shows that sitting has an even more harmful effect for those who don’t work out enough. You might be tempted to think, “Thank you, Captain Obvious,” but actually, few people are aware of the importance of body fat distribution and the fact that the fat around our organs puts us at serious risk of chronic illness. The new study was led by Dr. Joe Henson, research associate at the University of Leicester in the United Kingdom, who comments on the importance of the study, saying, “We know that spending long periods of time sedentary is unhealthy and a risk factor for chronic illnesses, such as type 2 diabetes and heart disease.” “Likewise, the amount of fat deposited around our internal organs may also predispose us to these diseases,” Dr. Henson says, and he’s not the only one. In a previous study we reported on, visceral fat inside the abdominal cavity was shown to raise the risk of heart disease.

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Effects of a Gut Pathobiont in a Gnotobiotic Mouse Model of Childhood Undernutrition.

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Effects of a Gut Pathobiont in a Gnotobiotic Mouse Model of Childhood Undernutrition.

Uncultured fecal gut microbiota from an underweight donor confers weight loss on gnotobiotic mice

We used anthropometric data collected from members of a birth cohort study (14) of 100 children living in Mirpur thana in Dhaka, Bangladesh, to define whether they were healthy or undernourished (table S1). Those with height-for-age z scores (HAZ) greater than or equal to −2 were classified as “healthy,” whereas those with scores less than or equal to −3 were deemed severely stunted. At 18 months, 30 and 25 children satisfied these criteria for healthy and severely stunted, respectively, whereas at 24 months, 27 and 20 children received these designations; the remaining children were classified as moderately stunted (HAZ between −2 and −3). A PCR-based screen for ETBF targeting all three fragilysin gene subtypes (14) was performed using DNA isolated from fecal samples that had been collected from these children at 18 and 24 months of age. The results revealed that ETBF was variably present between individuals and within a given individual over time, with a total of 25% of 18-month-old and 14% of 24-month-old children having a positive test (table S1). In this small cohort, ETBF carriage was not significantly correlated with indices of linear or ponderal growth [HAZ, weight-for-age z score (WAZ), and weight-for-height z score (WHZ) measured at 12 and 24 months of age (P = 0.8 and P = 0.4, P = 0.7 and P = 0.2, and P = 0.5 and P = 0.2, respectively; two-tailed Student’s t test)]. We combined anthropometric and PCR data to select fecal samples collected at 24 months from two children: (i) a healthy individual (child ID 7114 in table S1) with a HAZ score of −0.71, a WAZ score of −1.49, and a WHZ score of −1.62 who was ETBF-negative at the two time points tested, and (ii) a severely stunted and moderately underweight individual (child ID 7004) with a HAZ score of −3.02, a WAZ score of −2.51, and a WHZ score of −1.34 who was ETBF-positive at both time points. Of the 35 individuals with a positive ETBF test at either time point, only this stunted/underweight child was positive at both 18 and 24 months of age. Fecal samples obtained from members of this singleton birth cohort were screened for parasites using microscopic methods (5); neither of the two donors tested positive (see Materials and Methods for details).

To define the effects of diet and these two childrens’ gut microbiota on host biology, we generated three representative versions (embodiments) of the diets consumed by the population represented by the donors. To do so, we determined the relative daily caloric contributions of various selected ingredient types, based on a study by Arsenault and coworkers (16). Selection of specific food items as representative of each ingredient type was based on consumption incidence surveys tabulated by Islam et al. (17), and the results were incorporated into a database consisting of 54 food ingredients. We filtered this database to remove items consumed by <20% of households and categorized each of the remaining 39 items (see Materials and Methods for additional details). From the resulting diet ingredient matrix, we randomly sampled (without replacement) one item each from cereals, pulse vegetables, roots/tubers, leafy vegetables, fruits, and fish, plus three nonleafy vegetables, to populate three separate diet lists. Using the U.S. Department of Agriculture National Nutrient Database for Standard References (18), we determined the caloric information for each ingredient and subsequently calculated proportions required to match the predetermined contributions of each ingredient type. Food items were cooked in a manner intended to simulate Bangladeshi practices, and the resulting three embodiments of a Bangladeshi diet were sterilized by irradiation. This approach allowed us to generate several representative Bangladeshi diets that were not dominated by the idiosyncrasies of a single individual’s diet or by our own biases. The composition and results of nutritional analysis of the three diet embodiments are described in table S2 (A and B). The nutritional requirements of mice and children are compared in table S2C.

The results of a 12-year survey of demographic variations in the nutritional status of 16,278 Bangladeshi children found no significant sex differences in WHZ, WAZ, or HAZ (19). Therefore, in these and subsequent experiments, we eliminated gender as an experimental variable and only studied male mice. We gavaged separate groups of 8- to 9-week-old germfree C57BL/6 mice with the intact uncultured fecal microbiota samples obtained from the healthy or stunted/underweight Bangladeshi donors (two independent experiments; n = 4 singly caged mice per donor microbiota per experiment; see fig. S1A for study design). Fecal microbiota transplantation occurred 2 days after mice had been switched from an irradiated, nutritionally complete, low-fat/high-plant polysaccharide (LF/HPP) mouse chow that they had received since weaning to the first of the three embodiments of the Bangladeshi diet. Animals were subsequently fed, ad libitum, embodiment 1 for 1 week, followed by embodiment 2 for 1 week, and finally embodiment 3 for 1 week, with frequent sampling of their fecal microbiota during the course of each diet. Sequencing PCR amplicons generated from variable region 4 (V4) of bacterial 16S ribosomal RNA (rRNA) genes present in the donor’s fecal sample and in fecal samples collected over time from recipient gnotobiotic mice (table S3) provided an in vivo assay of colonization efficiency for each human donor sample. 16S rRNA sequencing reads were grouped into operational taxonomic units (OTUs) on the basis of a threshold of ≥97% nucleotide sequence identity (97% ID). The results revealed that at the conclusion of the experiment, 65.8 ± 2.5% (mean ± SEM) of OTUs in the stunted/underweight donor’s fecal microbiota sample and 68.4 ± 8.8% (mean ± SEM) of the OTUs in the healthy donor’s microbiota were detectable in recipient mice (that is, each OTU had a relative abundance of ≥0.1% in ≥1% of fecal samples obtained from the animals).

Although gnotobiotic animals colonized with the healthy donor’s intact uncultured fecal microbiota maintained weight, recipients of the severely stunted/underweight donor’s intact uncultured fecal microbiota exhibited progressive and significant weight loss (P < 0.005, paired two-tailed Student’s t test, comparison of final versus initial weights between the two treatment groups; Fig. 1A). In contrast to mice colonized with the healthy donor’s microbiota, those that received the stunted donor’s microbiota exhibited statistically significant weight loss at 10 days postgavage (dpg), during consumption of diet embodiment 2. Weight loss in this group worsened progressively, reaching 31 ± 6% (mean ± SEM) of original starting weight by 21 dpg (P < 0.001, two-tailed Student’s t test, comparison of final weights; Fig. 1A); in a linear mixed-effects model, both dpg and the interaction between microbiota and dpg were significant factors affecting weight throughout the experiment (P < 1 × 10−7 for each). Food consumption was not different between the two treatment groups as their weight phenotypes diverged. The relative abundance of B. fragilis, defined by V4-16S rRNA analysis of fecal samples obtained at the time of killing, was significantly greater in mice colonized with the stunted/underweight donor’s microbiota than in mice colonized with the healthy donor’s microbiota (P = 1.9 × 10−6, two-tailed Student’s t test; Fig. 1B).

Fig. 1. Intact uncultured human fecal microbiota and derived culture collections from healthy and undernourished Bangladeshi children transmit discordant weight phenotypes to gnotobiotic mice.

(A) Germfree male C57BL/6 mice (8 to 9 weeks old) (n = 8 per treatment group) gavaged with intact uncultured fecal microbiota from Bangladeshi donors were fed a sequence of three embodiments of a representative Bangladeshi diet consumed by members of the donor population. See fig. S1A for experimental design. Mean weights (±SEM) as a function of dpg are shown as percentages of weights immediately before fecal microbiota transplantation. (B) Efficiency of capture of bacterial OTUs present in the donor’s intact uncultured fecal samples in gnotobiotic mice. Mean relative abundances (±SEM) of 97% ID OTUs representing ≥1% of the total fecal microbial communities in recipient animals. Results are based on V4-16S rRNA data sets and summarized at the species level (or genus when species could not be determined). OTUs present at lower abundances are not shown and account for the proportion not represented in each stacked barplot. (C) Transplantation of culture collections (dashed lines) generated from the fecal microbiota of the healthy or stunted/underweight donors recapitulated the discordant weight phenotype seen with the corresponding intact uncultured microbiota (solid lines) (n = 6 mice per treatment group, mean weights ± SEM plotted). *P < 0.05 (paired two-tailed Student’s t test and linear mixed-effects model, as above). (D) The weight-loss phenotype observed in recipients of the stunted/underweight donor’s culture collection is not significantly different between the three Bangladeshi diet embodiments tested (P > 0.05; two-tailed Student’s t test). Mean weights (±SEM) are plotted as a function of dpg (n = 6 mice per culture collection per diet embodiment). Significant weight differences were seen between mice colonized with the healthy donor’s compared to the stunted/underweight donor’s culture collection in the context of all three embodiments of the Bangladeshi diet. *P < 0.05 (paired two-tailed Student’s t test and linear mixed effects model). (E) Intergenerational transmission of discordant weight phenotypes. See fig. S1C for experimental design. Mean weights (±SEM) of offspring of female gnotobiotic mice colonized with the indicated donors’ microbiota (n = 3 to 4 mice per treatment group) are plotted as a function of age. Animals were switched from a nutrient sufficient LF/HPP mouse chow to embodiments of the Bangladeshi diets beginning on postnatal day 56. *P < 0.05 (tested by both paired two-tailed Student’s t test comparing weights at killing and linear mixed effects model assessing interaction of weight, dpg, and microbiota through the experiment). The efficiency of intergenerational transmission of 97% ID OTUs was 96 ± 1.8% and 88 ± 2.3% (mean ± SEM) for the healthy and stunted/underweight donor’s microbiota, respectively (defined at the time of killing).

Bacterial culture collections from donor fecal microbiota transmit contrasting weight phenotypes

We next cultured bacterial strains from the healthy and stunted/underweight donors’ fecal samples (20, 21). Each collection of cultured strains was clonally arrayed in multiwell plates so each well contained a monoculture of a given bacterial isolate (20). Each culture collection consisted of organisms that had coexisted in the donor’s gut and thus were the products of the donor’s history of environmental exposures to various microbial reservoirs (including those of family members and various enteropathogens endemic to the Mirpur thana), as well as the selective pressures and evolutionary events placed on and operating within their microbiota (for example, immune, antibiotic, dietary, and horizontal gene transfer). Individual isolates in the clonally arrayed culture collection were grouped into “strains” if they shared an overall level of nucleotide sequence identity of >96% across their assembled draft genomes (21). On the basis of this criterion and the results of sequencing amplicons generated from the isolates’ 16S rRNA genes, we determined that the healthy and stunted donors’ culture collections contained 53 and 37 strains, respectively. Only one strain was shared between the two culture collections: Bifidobacterium breve hVEW9 [see table S4 for a list of all isolates in the culture collection derived from the stunted/underweight child and (21) for details of the healthy donor’s culture collection]. The two B. fragilis strains present in the healthy donor’s culture collection (hVEW46 and hVEW47) lacked a BfPAI and were therefore classified as NTBF. The stunted donor’s collection contained a single B. fragilis strain (mVEW4) with a bft-3 allele. ETBF strains of this type are globally distributed but most common in Southeast Asia (22) (see table S5 for a comparison of the functions encoded by genes in the genomes of these ETBF and NTBF strains and the reference B. fragilis type strain ATCC 25285).

To ascertain whether the contrasting weight phenotypes conferred by the two intact uncultured fecal microbiota samples could be transmitted by the strains captured in their derivative culture collections, we colonized 8-week-old adult male germfree C57BL/6 mice with all members of either of these two culture collections (n = 6 singly caged mice per collection; all mice receiving a given culture collection were maintained in a single gnotobiotic isolator). As a reference control for this experiment, and to compare results between this and the previous experiment, we colonized mice with the corresponding intact uncultured fecal microbiota samples, housing these mice in separate isolators from those used for the culture collection transplants. All mice were fed three embodiments of the Bangladeshi diet (1 week per diet) in the same order described for the previous experiment. As with the intact uncultured microbiota, the corresponding culture collections transmitted discordant weight phenotypes to recipient animals (P < 0.002, two-tailed Student’s t test, comparison of final weights; Fig. 1C). Moreover, the weight phenotypes (change in body weight over time as a percentage of initial weight before gavage) observed with each intact uncultured fecal microbiota and the corresponding derivative culture collection were not significantly different (P > 0.05 for both microbiota donors, two-tailed Student’s t test; Fig. 1C). The difference in weight phenotypes first became statistically significant between the two groups of mice midway through consumption of diet embodiment 2, continued to increase with diet embodiment 3 (Fig. 1C), and again were not attributable to differences in food consumption.

Effect of diet.

To test whether the weight loss phenotype was sensitive or robust to diet embodiment type, we gavaged the two clonally arrayed bacterial culture collections into separate groups of 8-week-old adult male germfree C57BL/6 mice who were monotonously fed Bangladeshi diet embodiment 1, 2, or 3 for 3 weeks (n = 6 singly caged recipient mice per culture collection per diet embodiment; fig. S1B). The discordant weight phenotype observed previously was preserved irrespective of the Bangladeshi diet embodiment consumed (P < 0.01, two-tailed Student’s t test, comparison of final weights of mice regardless of diet embodiment consumed; n = 18 mice per culture collection; Fig. 1D). Moreover, no significant differences in weights were noted between groups of mice colonized with the same culture collection but fed different diet embodiments (P > 0.05 for embodiments 1 versus 2, 1 versus 3, and 2 versus 3; two-tailed Student’s t test, comparison of final weights; Fig. 1D).

Transmission of strains was assessed by short-read shotgun sequencing of DNA isolated from fecal samples collected at the end of the experiment. This method, known as community profiling by sequencing (COPRO-Seq) (21), maps reads onto the draft genome assemblies of community members. At the depth of sequencing used [354,352 ± 23,216 (mean ± SEM), 50-nucleotide (nt) unidirectional reads/fecal DNA sample], we could reliably detect strains whose relative abundance is ≥0.1%. COPRO-Seq demonstrated that transplantation of the culture collections was efficient and reproducible, with 98.1 ± 0.6% and 94.5 ± 1.6% (mean ± SEM) of strains in the collections derived from the healthy and stunted donors, respectively, appearing in recipient animals. The relative abundance of ETBF in the fecal microbiota of mice containing the stunted/underweight donor’s culture collection was significantly greater than the cumulative relative abundance of the two NTBF strains in recipients of the healthy culture collection irrespective of the diet embodiment consumed (75.5 ± 4.1% versus 17.0 ± 4.4%; P = 2.8 × 10−9, two-tailed Student’s t test; Fig. 2A). The relative abundances of the ETBF strain in recipients of the stunted/underweight donor’s culture collection, the two NTBF strains in the healthy donor’s collection, and all other Bacteroides species did not differ significantly between diet embodiments [P > 0.2 for all Bacteroides, one-way analysis of variance (ANOVA); Fig. 2B].

Fig. 2. ETBF is necessary but not sufficient to produce weight loss in recipient gnotobiotic mice.

(A) Gut microbial community composition, defined by COPRO-Seq, in mice colonized with either of the two unmanipulated culture collections or the derived manipulated versions. Mean values for relative abundances ± SEM are plotted using aggregate data generated from fecal samples collected from mice colonized with a given community. Taxa present at abundances lower than 1% are not represented in the stacked barplots. (B) The proportional representation of Bacteroides taxa in unmanipulated culture collections installed in gnotobiotic mice does not differ significantly as a function of the diet embodiments animals were fed. Means ± SEM for data generated from feces are shown (n = 5 to 6 per group; one-way ANOVA). (C) Schematic illustrating the different groups of gnotobiotic mice generated by manipulating the presence/absence of ETBF and NTBF within the stunted/underweight or healthy donors’ culture collections and the questions addressed by the indicated comparisons. (D) Removal of ETBF prevents weight loss in mice colonized with the stunted/underweight donor’s culture collection. In contrast, addition of ETBF with the simultaneous removal of NTBF does not significantly affect weight in mice colonized with the culture collection derived from the healthy child (n = 5 to 6 mice per treatment group). Means ± SEM are plotted. *P < 0.05 (paired two-tailed Student’s t test and linear mixed effects model as above). (E) Addition of NTBF to the stunted/underweight donor’s culture collection ameliorates ETBF-associated weight loss in gnotobiotic mice fed embodiment 2 of a representative Bangladeshi diet (n = 6 mice per treatment group). Means ± SEM are plotted. *P < 0.05 (paired two-tailed Student’s t test and linear mixed effects model as above).

Intergenerational transmission of weight phenotypes.

To assess whether this weight loss phenotype was transmissible across generations of mice, two C57BL/6 male mice from the transplant experiment, one containing the stunted/underweight donor’s culture collection and the other containing the healthy donor’s collection, were switched to and subsequently maintained on an irradiated nutritionally enhanced mouse breeder chow from 21 to 48 dpg, at which time they were each cohoused with two germfree 6-week-old female mice that had received breeder chow since weaning. Seven days after cohousing, each male mouse was withdrawn from each mating trio, and the female mice were subsequently maintained on breeder chow throughout their pregnancy and as their pups completed the suckling period (fig. S1C). Male pups (n = 3 to 4 per litter) were then weaned onto an irradiated, nutritionally sufficient, LF/HPP chow, until they were 9 weeks old, at which time they were switched to the Bangladeshi diets (10 days per diet; same order of sequential presentation of the embodiments as before). Mice born to mothers colonized with either of these arrayed culture collections experienced identical weight gain profiles while consuming the LF/HPP diet (P = 0.9, two-tailed Student’s t test; table S6). However, once they were transitioned to the sequence of three Bangladeshi diet embodiments (consumed from postnatal days 56 to 86), mice born to mothers harboring a stunted/underweight donor’s microbial community exhibited significantly greater weight loss (P = 0.03, two-tailed Student’s t test comparing weights at killing). The total relative abundance of the two NTBF strains in fecal samples obtained from recipients of the healthy donor’s culture collection was 4.2 ± 0.7% at the conclusion of the LF/HPP diet period and 4.6 ± 0.9% at the conclusion of the Bangladeshi diet embodiment sequence, whereas the relative abundance of ETBF at these two time points was 34.3 ± 4.2% and 50.0 ± 0.7%, respectively, in mice colonized with the stunted/underweight donor’s culture collection.

An independent intergenerational transfer experiment was performed, in this case using the donors’ intact uncultured fecal microbiota. The efficiency of ETBF and NTBF transmission from mothers to pups was 100%. As with the culture collections, there was diet-dependent transmission of the discordant weight loss phenotype (Fig. 1E; compare with Fig. 1A).

Microbial community context determines the effects of ETBF on community members and host

To establish whether ETBF is necessary and sufficient to cause marked weight loss in multiple community contexts, we performed a series of manipulations that involved removing the ETBF strain from the stunted/underweight donor’s culture collection and adding it to the healthy donor’s culture collection, with or without subtraction of its two NTBF strains (Fig. 2C). These manipulations allowed us to characterize (i) the role of community context in determining ETBF pathogenicity, (ii) the community/host responses to ETBF, (iii) the ability of NTBF to modulate ETBF effects, and (iv) the effects of ETBF on NTBF. Recipient C57BL/6 male mice in each of the different treatment groups were 8 to 9 weeks old at the time of colonization; all were placed on diet embodiment 2 for 2 days before gavage and subsequently maintained on this diet for 14 days until they were killed (n = 5 singly caged animals per treatment group, maintained in separate gnotobiotic isolators). Fecal samples were collected at the time points described in fig. S1D.

Weight phenotypes.

Removal of the ETBF strain from the stunted/underweight donor’s culture collection prevented the transmissible weight loss phenotype (Fig. 2D; P = 5.9 × 10−8, two-tailed Student’s t test, comparison of weights at killing). However, addition of the ETBF strain to the healthy donor’s culture collection did not produce significant weight loss, regardless of whether the NTBF strains were present or absent (P = 0.3 and P = 0.2, respectively, two-tailed Student’s t test, comparison of weights at killing; Fig. 2D). On the basis of these findings, we concluded that whether ETBF produces weight loss (cachexia) is dependent on microbial community context.

COPRO-Seq analysis of the fecal microbiota of recipients of the unmanipulated ETBF(−) NTBF(+) healthy donor’s culture collection revealed that it contained the two NTBF strains [total relative abundance of 14.5 ± 3.0% (mean ± SEM), with B. fragilis hVEW46 and B. fragilis hVEW47 comprising 1.1 and 13.5%, respectively], two other Bacteroides (B. thetaiotaomicron and B. caccae), plus Bifidobacterium breve and Enterococcus. The relative abundance of B. fragilis was not significantly different between mice harboring the transplanted unmanipulated healthy donor’s culture collection and its two manipulated ETBF(+) NTBF(−) and ETBF(+) NTBF(+) versions (P > 0.5, two-tailed Student’s t test; Fig. 2A). (The term “unmanipulated” indicates that all bacterial isolates that comprise a culture collection were pooled before transplantation, whereas “manipulated” refers to the inclusion and/or exclusion of B. fragilis strains as part of the gavaged consortium.) The fecal microbiota of recipients of the unmanipulated stunted donor’s culture collection was dominated by ETBF (relative abundance, 62.3 ± 4.0%). Removal of ETBF led to significant increases in the relative abundances of B. breve, another Bifidobacterium strain, Enterococcus lactis, and Enterococcus gallinarum (P < 0.02, two-tailed Student’s t test; Fig. 2A).

To determine whether NTBF alone is sufficient to protect mice from ETBF’s cachectic effects, we colonized three groups of C57BL/6 male gnotobiotic mice, each with a different version of the stunted donor’s culture collection: the unmanipulated culture collection containing ETBF alone or one of two manipulated versions, one with NTBF alone, and the other with both ETBF and NTBF strains. Mice were placed on diet embodiment 2 for 2 days before gavage and maintained on this diet for 2 weeks until killed (n = 6 animals per treatment group, all singly caged; one treatment group per gnotobiotic isolator; fig. S1D). We observed a significant difference in weight phenotypes between mice colonized with the unmanipulated undernourished donor’s ETBF(+) NTBF(−) culture collection compared to the manipulated ETBF(−) NTBF(+) version (P = 0.01, one-tailed Student’s t test; Fig. 2E). Addition of NTBF [yielding the ETBF(+) NTBF(+) community] markedly ameliorated the weight loss phenotype (P = 0.0004 for weights at killing compared to mice with the unmanipulated community, one-tailed Student’s t test; Fig. 2E). Follow-up COPRO-Seq analysis revealed that the relative abundances of ETBF at the conclusion of the experiment were 38.9 ± 3.9% and 39.0 ± 3.5% when animals were colonized with and without NTBF, respectively. Thus, NTBF does not appear to mediate its effects by reducing the fractional representation of ETBF in the community. However, ETBF appears to reduce the relative abundance of NTBF, which constituted 41.8 ± 3.2% of the total community when ETBF was absent but only 19.2 ± 2.6% when ETBF was present (P = 0.04, one-tailed Student’s t test).

The effects of intraspecific interactions on microbial gene expression.

We performed microbial RNA sequencing (RNA-seq) of cecal contents harvested at killing to characterize the transcriptomes of members of the unmanipulated and manipulated versions of the healthy and stunted communities. Our goal was to assess (i) the effects of intraspecific competition (NTBF on ETBF and vice versa) in the healthy and stunted community contexts, (ii) the effects of the cultured stunted/underweight versus healthy donor community on ETBF, and (iii) the effects of cocolonization with ETBF on other bacterial members (including other Bacteroides). ETBF genes with significant differential expression attributable to the presence or absence of NTBF, in both healthy and stunted community contexts, are listed in table S8 (B and F). Conversely, NTBF genes with significant differential expression attributable to the presence or absence of ETBF, in both healthy and stunted community contexts, are highlighted in table S8 (C and E).

Fragipain is a cysteine protease that activates fragilysin by removing its autoinhibitory prodomain. In mouse models of colitis, host proteases can also serve this function, but fragipain is required for sepsis to occur (23, 24). In the presence of NTBF, ETBF expression of fragilysin (bft-3) in the cecal metatranscriptome of mice harboring the manipulated ETBF(+) NTBF(+) healthy donor’s community was significantly decreased compared to the manipulated version of the community where ETBF, but not NTBF, was present (39-fold, based on normalized transcript counts; P = 0.002, one-tailed Student’s t test). Fragipain expression was also significantly reduced (14.2-fold; P = 0.0005, one-tailed Student’s t test) (table S8B). In the context of the stunted community, the reduction in bft-3 expression associated with introducing NTBF was considerably more modest (5.9-fold; P = 0.09, one-tailed Student’s t test), whereas fragipain expression was not significantly different between the two treatment groups (P > 0.5, one-tailed Student’s t test; table S8).

When we abrogated fragilysin (bft-3) expression through insertional mutagenesis (fig. S2), the mutant Δbft-3 strain grew robustly in vitro. However, when germfree mice were gavaged with a manipulated version of the stunted donor’s culture collection containing this isogenic strain with a disrupted bft-3 locus substituted for the wild-type ETBF strain, we observed no detectable colonization of the mutant (n = 5 mice fed diet embodiment 2 for 14 days); the number of COPRO-Seq reads mapping to the mutant Δbft-3 strain was no greater than background, and a PCR assay that used B. fragilis–specific bft primers was negative. However, these results led us to conclude that this locus functions as an important colonization factor for this particular ETBF strain in this community context. However, these experiments did not allow us to directly address the hypothesis that attenuation of bft-3 expression produced by inclusion of NTBF in the stunted community contributed to the observed mitigation of weight loss.

Looking beyond the effects of intraspecific interactions on btf-3 expression, we compared the cecal metatranscriptomes of gnotobiotic mice colonized with the unmanipulated NTBF(+) ETBF(−) healthy donor’s culture collection versus mice harboring the two manipulated versions where ETBF was added, with or without removal of the two NTBF strains. The results revealed that ETBF in the absence of NTBF produced significant alterations in the expression of a number of transcripts related to various features of stress responses in several community members [Enterococcus faecalis, E. gallinarum, B. breve, and two members of Enterobacteriaceae; differentially expressed genes identified using the Robinson and Smyth exact negative binomial test (25), with Bonferroni correction for multiple hypotheses] (Fig. 3). Both rpoS, which is a key general stress response sigma factor that positively controls expression of genes involved in transport of carbon sources and iron acquisition, and recD, which is involved in DNA repair, exhibited significant increases in their expression in the setting of ETBF without NTBF (P < 0.05). Several genes involved in the acquisition and metabolism of iron were either up-regulated in the presence of ETBF (for example, ferric aerobactin receptor, ferric uptake regulation protein, and aerobactin synthase) or repressed (for example, an Enterobacteriaceae strain hVEW34 homolog of the Escherichia coli BasSR system component BasS, which is normally induced under high-iron conditions) (26). ETBF’s effect on expression of these latter genes was mitigated when NTBF was present (Fig. 3), highlighting the importance of iron in intraspecific and interspecific interactions in the healthy donor’s consortium of transplanted cultured bacterial strains. In contrast, the presence or absence of ETBF or NTBF did not evoke significant changes in the expression of these or other genes involved in iron metabolism in the context of the stunted/underweight donor’s community. Numerous genes related to prophage and mobile DNA element biology were also expressed at significantly higher levels by healthy community members when ETBF was present in the absence of NTBF (P < 0.05; Fig. 3). Prophage activation occurs in response to stress. Some studies have postulated that phage induction can “shuffle” community structure to favor an increased proportion of pathobionts (27).

Fig. 3. The effects of intraspecific NTBF-ETBF interactions on the community metatranscriptome.

Adult mice were colonized with the indicated unmanipulated and manipulated versions of the healthy donor’s culture collection. All treatment groups were monotonously fed diet embodiment 2. Cecal contents were collected at the time of killing 14 days after initial colonization, and gene expression in the community was analyzed by microbial RNA-Seq. Each column represents data from an individual mouse. Each row represents the levels of a given transcript, normalized across that row. Addition of ETBF to and removal of NTBF from the healthy donor’s culture collection (middle set of columns) produced an increase in expression of the indicated genes in strains whose identity is denoted by the color code on the left, compared to their expression in the unmanipulated ETBF(−) NTBF(+) version (left set of columns) or the manipulated version where the NTBF strains were retained when ETBF was added (right set of columns). UniProt-based annotations are shown on the right. ATP, adenosine triphosphate; HTH, helix-turn-helix.

Studies in gnotobiotic mice have shown that signaling by members of the human gut microbiota involving the quorum sensing molecule, autoinducer-2 (AI-2), can alter virulence factor expression in enteropathogens (28) and have linked AI-2 signaling to modulation of the levels of Bacteroidetes in the gut (29). LuxQ is involved in the detection of AI-2. In the context of the healthy community, expression of three of the four luxQ homologs in the ETBF genome was decreased when NTBF was present [log2(fold change) of −2.8, −4.4, and −9.5, P < 0.005, exact negative binomial test; table S8B]. Comparing the mice colonized with the unmanipulated ETBF(−) NTBF(+) and manipulated ETBF(+) NTBF(+) versions of the healthy donor’s culture collection revealed differential regulation of five other luxQ transcripts encoded by Bacteroides members (three in B. thetaiotaomicron hVEW3, and two in B. caccae hVEW51; table S8D). In the context of the stunted donor’s community, the presence of ETBF had no significant effects on lux gene expression in NTBF or any other community members, nor did the presence of NTBF have any effect on lux expression in ETBF (table S8, E and F). Together, these results illustrate the importance of community context in determining the transcriptional effects of intraspecific (and interspecific) interactions involving ETBF.

Metabolism.

The metabolic effects of manipulating the representation of ETBF and NTBF in the healthy and stunted donor’s communities were studied by targeted mass spectrometry (MS) of tissue samples obtained from mice in the fed state (table S7). Quantifying amino acids, organic acids, acylcarnitines, and acyl-CoAs in livers obtained from animals colonized with either of the two unmanipulated culture collections disclosed that compared to mice harboring the healthy donor’s ETBF(−) NTBF(+) culture collection, those colonized with the stunted donor’s ETBF(+) NTBF(−) culture collection had higher concentrations of propionyl-CoA and isovaleryl-CoA [by-products of oxidation of branched-chain and other amino acids; P < 0.05, false discovery rate (FDR)–adjusted two-tailed Student’s t test; Fig. 4A], and lower concentrations of acetyl-CoA (P = 0.07) and its cognate metabolite acetyl carnitine (that is, C2 acylcarnitine; P = 0.001; Fig. 4B). Mirroring these trends, cecal contents harvested at the time of killing from mice harboring the stunted donor’s unmanipulated culture collection contained higher concentrations of branched-chain amino acids (P = 0.066 for isoleucine/leucine and P = 0.1 for valine) and lower concentrations of acetyl-carnitine (P = 0.067). However, these trends were not observed in skeletal muscle.

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