Investigation of the Gut Microbiota in Regulating Nutrient Absorption in Humans
Phase: PHASE2
Conditions: Obesity
Sponsor: National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

 
Date: 03/09/2019 
1
Investigation of the Gut Microbiota in Regulating Nutrient 
Absorption in Humans  
Version 1.5 
 
Principal Investigator: 
Jonathan Krakoff, MD* 
ODRCS, PECRB, NIDDK 
4212 North 16th Street 
Phoenix, AZ  85016 
Tel 602-200-5217 
jkrakoff@mail.nih.gov 
 
Type: 
 
 
Clinical Trial: Intervention 
 
Associate Investigators: 
Alessio Basolo, MD ODCRS, PECRB, NIDDK* 
 
602-200-5304 alessio.basolo@nih.gov 
Douglas Chang, MD ODCRS, PECRB, NIDDK* 
 
602-200-5312 douglas.chang2@nih.gov 
Key Research Personnel 
Susan Bonfiglio, PA 
ODCRS, PECRB, NIDDK*  
602-200-5325   bonfiglios@mail.nih.gov 
 
Cathy Trinidad,   
ODCRS, PECRB, NIDDK 602-200-5313 ctrinida@mail.nih.gov 
Nurse Coordinator 
 
 
Non-NIH Collaborator: 
 
Virginia Stallings, MD    Childrens Hospital of Philadelphia  215-590-1664     stallingsv@email.chop.edu 
 
Peter Turnbaugh, PhD   G.W. Hooper Research Foundation, UCSF      415-502-3237  
  
 peter.turnbaugh@ucsf.edu 
 
 
About the Protocol: 
Uses Ionizing radiation?  
 
 
Yes 
Requires IND/IDE? 
 
 
 
No 

 
Date: 03/09/2019 
2
Sponsor: 
 
 
 
 
None 
Uses “Durable Power of Attorney” 
 
No 
Study Location  
 
 
 
Clinical Research Unit, NIDDK-Phoenix 
Multi-Institutional Project? 
 
 
No 
Expedited Review Request? 
 
 
No 
 
*Denotes those able to obtain informed consent

 
Date: 03/09/2019 
3
Table of Contents 
PRECIS ............................................................................................................................................................ 5 
INTRODUCTION .............................................................................................................................................. 7 
Energy loss in stool .................................................................................................................................... 7 
The gut microbiota .................................................................................................................................... 9 
Effects of antibiotics on gut microbiota .................................................................................................. 10 
AIMS OF THE STUDY: ................................................................................................................................... 13 
A. Primary objectives ............................................................................................................................... 13 
B. Secondary objectives........................................................................................................................... 14 
HYPOTHESES ................................................................................................................................................ 15 
Primary Hypotheses: ............................................................................................................................... 15 
Secondary Hypotheses: ........................................................................................................................... 15 
METHODOLOGY ........................................................................................................................................... 16 
Study design ............................................................................................................................................ 16 
Subjects ................................................................................................................................................... 16 
Eligibility criteria ...................................................................................................................................... 16 
Inclusion Criteria .................................................................................................................................. 16 
Exclusion Criteria ................................................................................................................................. 17 
Experimental design: ................................................................................................................................... 20 
Overview of the Study ............................................................................................................................. 23 
Detailed experimental design ................................................................................................................. 24 
TESTS AND ANALYSES .................................................................................................................................. 31 
Study diets ............................................................................................................................................... 31 
Dye marker: ............................................................................................................................................. 32 
Body composition by DEXA ..................................................................................................................... 32 
Oral glucose tolerance test ..................................................................................................................... 33 
Twenty four hour energy expenditure and basal metabolic rate: .......................................................... 33 
Antibiotic treatment and placebo: .......................................................................................................... 34 
Heparin boli and post-heparin blood sampling:...................................................................................... 34 
Stool and urine collection and storage: .................................................................................................. 35 
Calorie content of food during experimental diet periods (gross energy intake): ................................. 36 

 
Date: 03/09/2019 
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Calorie content in stool and urine: .......................................................................................................... 37 
Preparation and measurement of calorie content of stool: ................................................................... 37 
Block Questionnaire: ............................................................................................................................... 38 
Blood analyses ......................................................................................................................................... 38 
Glucagon-like peptide (GLP-1,2) and leptin measurements ............................................................... 38 
DATA ANALYSIS ............................................................................................................................................ 39 
Sample size .............................................................................................................................................. 40 
BENEFITS ...................................................................................................................................................... 41 
PROTECTION OF HUMAN SUBJECTS........................................................................................................ 42 
Rationale of human selection.................................................................................................................. 42 
Possible risk and hazards ......................................................................................................................... 42 
Radiation exposure due to DEXA: ........................................................................................................ 42 
Oral glucose tolerance test: ................................................................................................................. 43 
Twenty-four hour energy expenditure measurement: ....................................................................... 43 
Oral antibiotic treatment: .................................................................................................................... 44 
Intravenous heparin boli: .................................................................................................................... 44 
Twenty-four hour stool and urinary collection for energy and bacterial content: ............................. 45 
Digestion of dye marker ...................................................................................................................... 45 
Disclosure of medical conditions............................................................................................................. 45 
Data and safety monitoring ..................................................................................................................... 46 
Adverse event reporting.......................................................................................................................... 47 
Definitions ............................................................................................................................................ 47 
a) Adverse event .................................................................................................................................. 47 
b) Serious adverse event ..................................................................................................................... 47 
c) Intensity or severity of adverse event ............................................................................................. 47 
Relatedness of adverse event to an intervention ............................................................................... 48 
Research Use of Stored Human Samples, Specimens or Data ................................................................ 49 
COMPENSATION .......................................................................................................................................... 50 
REFERENCE LIST ........................................................................................................................................... 52 
SCHEDULE OF PROCEDURES ........................................................................................................................ 60 
 

 
Date: 03/09/2019 
5
PRECIS 
 
The prevalence of obesity has risen to epidemic proportions in the world, resulting from 
both excessive energy intake and low levels of energy expenditure. The effect of nutrient 
absorption on energy balance, that is, the relative amount of nutrients consumed vs. the amount 
excreted in stool, has been reported only in small studies in which energy waste in feces and 
urine between lean and obese individuals was not found to be different. New studies have 
shown that bacteria in the gut may play an important role in calorie absorption. We have 
recently shown that leaner individuals absorbed more calories when overfed compared to when 
they were given a diet with just enough calories to maintain their own weight. Our studies have 
also found that overfeeding also changes the kinds of bacteria found in the gut. In lean 
individuals, these changes in gut bacterial communities with overfeeding were associated with 
changes in how many calories were absorbed. Our results are similar to those seen in other 
studies in animals and humans that suggest a role for gut bacteria in weight gain and obesity. 
To try to better understand the role of gut bacteria in absorbing food, we propose to investigate 
1) whether energy loss (as measured in stool and urine) changes following over- and 
underfeeding relative to body size and 2) whether changes in the gut bacteria, induced by an 
antibiotic medication, affect nutrient absorption and glucose tolerance. We plan to study 24 
healthy non-smoking volunteers age 18 – 45 years old, not taking any medications (including 
medications for weight loss, antibiotics or probiotics) for the examination. All participants will be 
admitted to the Clinical Research Unit for 31 days. During their stay, subjects will be fed a 
weight maintaining diet for 3 days, followed by two experimental diets (150% and 50% of weight 
maintaining calories) in a random order. After this, volunteers will be randomly assigned to one 
of two groups: group 1 will take oral antibiotic medication; group 2 will receive pills that look the 
same but will not contain any active medication (placebos). Feces (stool) will be collected 
throughout the study. Additionally, twenty four-hour urine collections will take place each day of 

 
Date: 03/09/2019 
6
the experimental diet period and when stool is collected on the antibiotics. The energy content 
of these waste products as well as that of the diet (using duplicate plate analysis) will be 
measured by bomb calorimetry. Bacterial components in feces will be extracted by repeated 
fractional centrifugation to obtain bacterial mass and by using 16S rDNA-based oligonucleotide 
probes to obtain data on gut bacteria. Primary results will examine how many calories remain in 
stool during relative over- and underfeeding and whether changes in gut bacteria, induced by an 
antibiotic medication, affect nutrient absorption and glucose tolerance.

 
7 
 
INTRODUCTION 
 
Obesity is one of world’s greatest health problems. The prevalence of obesity has been 
steadily increasing in developing as well as industrialized countries (1). In the U.S., more than 
60% of the adult population is either overweight or obese (2). Obesity is associated with an 
increased risk of all-cause mortality with many specific health consequences, including coronary 
heart disease, hypertension, and diabetes mellitus, among others (1). Excess caloric intake and 
low levels of energy expenditure are important factors that can cause an energy imbalance, 
leading to obesity. Energy balance is defined as the equilibrium between energy intake and 
energy expenditure using the formula below: 
EFD = ERMR ETE + EPA + EFE + EUR 
where E=energy and the subscripts stand for the quantity of energy in food (FD); the resting 
metabolic rate (RMR); the thermic effect of food (TE); physical activity (PA); the feces (FE); and, 
the urine (UR). Many of these components have been widely studied under a variety of 
conditions  (3–10) and in different ethnic groups (11–15).  
Energy loss in stool 
 
One frequently overlooked, but potentially important, piece of the energy balance 
equation is energy loss in stool and urine. In carefully conducted early studies of energy 
balance, Atwater et al. calculated energy loss from stool and urine as 142 kcal/d and 149 kcal/d, 
respectively, representing approximately 5% of total daily energy expenditure (16). Stool energy 
losses, in particular, can be affected by disease states, such as gastrointestinal disorders (17–
19), age (20–23), and diet composition.  

 
8 
 
 
High fiber diets induce an increase in the quantity and energy content of the stool by 
causing shortened colonic transit time, thus shortening absorption time, and by increasing stool 
bulk and water holding capacity, thereby reducing digestive diffusion capacity (24,25). Fecal 
energy loss is higher in individuals consuming high fiber diets compared to lower fiber diets, 
even when the caloric content is the same (26–28). Whether the macronutrient content of the 
diet, apart from fiber, may affect stool energy loss is unclear. A study by Webb found no 
differences in stool energy loss in individuals consuming diets with different macronutrient 
composition (29), while other studies indicate that dietary carbohydrate, calcium and saturated 
fatty acids may affect stool energy loss (21,22,30–34).  
Energy content in stool may also be affected by colonic transit time (CTT). Although 
data from our previous study (35) did not show an association between stool calories and 
gastrointestinal transit time, previous studies have described differences in CTT by ethnicity 
(36–38),  age (39)  and menstrual cycle (39) but not by gender (38,40). The investigations of 
effect of body size on CTT have produced inconsistent results, however, those studies were 
limited in the range of the BMI of the study population. 
Whether obese individuals may preferentially absorb more nutrients, and hence have 
lower stool energy loss (which may account for a propensity to gain weight, difficulty losing 
weight, and/or problems maintaining weight loss) is not clear. To date, only one study has 
addressed this issue. Webb studied 4 lean and 4 obese individuals under three dietary 
conditions: a high protein/high fat diet, an ‘average’ diet, and a high carbohydrate diet. Stool and 
urine energy loss varied between individuals, but overall, obese individuals had only slightly and 
not significantly lower stool energy loss compared to lean individuals (178 ± 45 kcal/day vs. 208 
± 100 kcal/day, respectively) (41). Our recently published data in 9 obese and 12 lean 
individuals also showed no difference in nutrient absorption between lean and obese 

 
9 
 
individuals. However we did find that lean individuals had lower stool calories, therefore 
absorbed relatively more calories on a 3400 kcal/day diet compared to a 2400 kcal/day diet (-
1.3±1.9%, p=0.04). This was not seen in obese individuals (-0.2±1.2%, p=0.59). However, 
because of the study design, the degree of overfeeding in obese subjects was much smaller 
compared to the lean subjects (calculated as a percent of their weight maintaining calories) (35). 
Therefore, it remains unclear whether only lean individuals have increased nutrient absorption 
with increased calorie load or whether this was just due to the difference in the degree of 
overfeeding.  
The gut microbiota 
 
Nutrient absorption may also be influenced by enteric bacteria. According to Ley R.E., 
there is a difference in composition of gut microbial communities between lean and obese mice 
i.e., ob/ob mice have a 50% reduction in the abundance of Bacteroidetes and a significantly 
greater proportion of Firmicutes that are the two most abundant bacterial divisions in either mice 
or human. This was further supported by studies in lean and obese human twins(42). Our data 
did not show a statistically significant difference in the relative abundance of Bacteroidetes and 
Firmicutes between lean and obese individuals (22.36±11.58% of 16S rRNA gene sequences 
(lean) vs. 18.77±15.93% (obese), p=0.56 for Bacteroidetes; 74.85±12.05% vs. 78.69±17.05%, 
p=0.55 for Firmicutes) (35). However, the observed variation in bacterial abundance on phylum 
level was consistent with previously published data. Our initial studies did find an association 
between nutrient load and changes in gut microbial community composition. For instance on the 
3400 kcal/day diet we found percent weight maintaining energy needs (%WMEN, [calculated as 
calories fed/weight maintaining calories]*100) were associated with an increase/decrease in 
Firmicutes and Bacteroidetes (r=0.47, p=0.04; r=-0.47, p=0.04). As stool samples on each 
prescribed diet were collected within 2 days of starting the diet, these changes occurred rapidly. 

 
10 
 
These findings are consistent with several independent studies showing how switching mice 
(whether with a mouse microbiota or a transplanted human gut microbiota) from a 
polysaccharide-rich/low-fat to a high-sugar/high-fat diet resulted in a reduced representation of 
Bacteriodetes and an increased representation of Firmicutes (43–45). Changes in the ratio of 
Firmicutes to Bacteroidetes in mice and humans may promote adiposity or alternatively 
represent a host-mediated adaptive response to limit energy uptake/storage (46). In a series of 
experiments in mice, Turnbaugh et al. demonstrated that the gut microbiota is not only linked to 
obesity but can also increase the capacity of energy harvest from the gut(43,44,47). In humans, 
Ley et al noted a correlation between change in % body weight over one year and increase in 
Bacteroidetes abundance (48) . However, several studies have found no association between 
specific gut microbiota and adiposity in humans(49). Specifically, Duncan et al using fluorescent 
in situ hybridization (FISH) did not find any difference in relative abundance of Bacteroidetes 
between lean and obese individuals, nor did they find any change in relative abundance of 
Bacteroidetes or Firmicutes with weight loss.   In our initial shorter term study, we found that 
changes in the Firmicutes and Bacteroidetes with altered nutrient load were associated with 
directly measured stool calories in the lean subgroup (r=-0.50, p=0.02, r=0.52, p=0.01, 
respectively). The magnitude of this effect indicated that this may be a clinically relevant 
difference in nutrient absorption as a 20% change in the major phylotypes (increase in 
Firmicutes and decrease in Bacteroidetes) was associated with a 150 kcal/d difference in stool 
calories.  
Effects of antibiotics on gut microbiota 
While over (and possibly under) feeding may influence enteric bacteria and nutrient 
absorption, antibiotic medications will also alter these communities. Recent studies have 
explored the effect of antibiotics on gut microbial communities using new metagenomic methods 

 
11 
 
which accurately identify and quantify members of the gut microbiota. Antonopoulos et al. 
investigated community dynamics of the gut microbiota in mice using 16S rRNA analyses 
following treatment with metronidazole and amoxicillin and cefoperazone. For the 
amoxicillin/metronidazole combination, 10 days of treatment, lead to substantial reductions of 
the representation of Firmicutes, while cefoperazone decreased Bacteroidetes (50). However, 
these effects were examined only in two and three mice respectively.   In humans, ciprofloxacin 
reduces gut microbiota diversity after 3 days. However the effect on specific taxa appears to be 
uneven(51). Oral vancomycin has been examined in a model of the distal colon and in mice. 
Oral vancomycin does cause a decrease in the major phyla with reductions in the relative 
abundance of both Bacteroidetes and Firmicutes(52–54). In the case of the latter phyla, there is 
relative preservation of the Lactobacillacea family.  Moreover, mice treated with vancomycin 
were resistant to weight gain despite no changes in calorie intake (53). Mice treated with 
vancomycin also had lower glucose concentrations although it is not clear if this was due to 
alteration of gut microbiota or from lack of weight gain. In contrast, intravenous vancomycin has 
been associated with weight gain in humans treated for endocarditis(55).  Oral vancomycin  has 
the advantage of having minimal systemic absorption (in the absence of renal disease and/or 
clinical colitis) and thereby would be expected to have limited systemic effects.   
Several groups have proposed a mechanism by which the microbiota influences glucose 
metabolism.  Cani et al. and others have demonstrated that Lipopolysaccharids(LPS) derived 
from gram-negative bacteria can pass the mucosal barrier of the gut and induce low-grade 
inflammation. These processes are mediated by proinflammatory markers such as TNFα and IL-
6 which ultimately lead to insulin resistance(56,57). Membrez et al. showed that antibiotic 
treatment of two weeks lead to reduced circulating LPS and improved glucose tolerance(57). 
 

 
12 
 
The mechanism by which gut microbiota influence energy harvest is not clear. In mice, 
Backhed et al. have shown that gut bacteria affect fat storage not only by increasing delivery of 
monosaccharides to the liver and increasing transactivation of lipogenic enzymes but also by 
promoting storage of triglycerides in adipocytes through suppression of intestinal expression of 
a circulating lipoprotein lipase inhibitor called angiopoietin-like protein 4 (Angptl4)(58). It was 
shown by  Mandard et al. that over-expression of Angptl4 leads to inhibition of fat storage(59). 
Even further, Aronsson  et al. demonstrated that treatment with certain Lactobacilli was linked to 
increased expression of Angptl4 and this was associated with decreased LPL activity (60). 
The identification of the gut microbiota can be performed using either conventional 
culturing techniques that are less accurate due to difficulty with culturing anaerobic bacteria or 
sequence analysis of cloned microbial small-subunit ribosomal RNA genes [16S ribosomal 
DNA,(rDNA)] which is a more accurate technique (61). There may be some limitations to a 
single measurement of the gut microbiota. Bacterial gut communities may be affected by diet 
and health status of their host (62). Measurements of the gut microflora are performed using 
fecal samples or mucosal tissue achieved from biopsy. Although there are some differences in 
the representation of gut bacteria measured by fecal sample versus mucosal tissue sample, 
fecal microbiota is thought to adequately represent the adherent and non-adherent bacterial 
population(63). 
Nutrient absorption may also be regulated by gut and adipocyte hormones. Several 
investigations in animal models indicate that glucagon-like peptide 1 (GLP-1) reduces lipid 
absorption (64), whereas GLP-2 increases macronutrient absorption (65). The role of the 
adipocyte-derived hormone leptin in balancing the intestinal absorption of dietary proteins and 
fats has also been reported (66). However, information on this aspect in humans is still unclear. 

 
13 
 
According to Atwater et al(16), energy loss in urine and stool respectively is 
approximately 5% of total energy expenditure. Our preliminary data demonstrated that mean 
stool energy loss in lean and obese individuals is close to this (4.9±1.8%, 4.8±1.4%). Energy 
content in urine may also be affected by dietary calorie content (21,22,29,41) and age (21–23). 
However based on our preliminary data, urine calories were not different between lean and 
obese individuals, but further information about energy loss in urine in relation to obesity is 
needed (35). 
We propose to study both stool and urine energy loss in 24 individuals on two 
experimental diets (50% increased and 50% reduced nutrient load relative to body size) in a 
random cross-over design. Following this over/underfeeding, volunteers will also be randomly 
assigned to a placebo versus oral antibiotic medication arm. This study will extend our previous 
findings by investigating whether 1) nutrient absorption changes upon similar 
increases/decreases in relative nutrient load and 2) whether manipulation of gut microbial 
communities with antibiotics alters nutrient absorption and 3) how these changes may affect 
glucose tolerance and fat storage.  
 
AIMS OF THE STUDY: 
A. Primary objectives 
1. To investigate energy loss in stool and urine when volunteers are fed diets in which 
the calories are 50% and 150% of their weight maintaining calorie needs.  
2. To investigate the effects of oral antibiotic vancomycin on nutrient absorption. 

 
14 
 
B. Secondary objectives 
1. 
To investigate the effect of  over and underfeeding on the gut microbial community 
structure 
2. 
To investigate the effect of the oral antibiotic vancomycin on the gut microbial 
community structure 
3. 
To investigate whether antibiotic manipulations of gut microbiota affect fat storage 
by measuring lipoprotein lipase activity and Angptl4 
4. 
To investigate whether manipulation of the microbiota by over and underfeeding 
affects Angptl4 secretion. 
5. 
To investigate whether antibiotic manipulations of the gut microbial community 
structure are associated with changes in 24 hour energy expenditure. 
6. 
To examine whether gastrointestinal transit time is altered when volunteers are fed 
50% and 150% of their weight maintaining calories and whether it is altered by 
antibiotic treatment with vancomycin 
7. 
To examine plasma concentrations of glucagon-like peptides 1 and 2 (GLP-1, GLP-
2) and leptin in relationship to stool energy loss. 
 
 
 

 
15 
 
HYPOTHESES 
In the course of this study we will test the following hypotheses: 
Primary Hypotheses: 
1. 
Percent stool calories will increase and decrease respectively when individuals 
are fed diets that are 50% and 150% of their weight maintaining energy 
requirements.   
2. 
Oral vancomycin treatment will be associated with decreased nutrient absorption 
as measured by an increase in stool calories. 
Secondary Hypotheses: 
1. 
Antibiotic induced changes in gut microbiota will decrease lipoprotein lipase 
activity 
2. 
Higher relative nutrient load decreases Bacteroidetes/Firmicutes ratio and lower 
nutrient load increases Bacteroidetes/Firmicutes ratio. 
3. 
Antibiotic-induced changes in the gut microbiota will improve glucose tolerance 
(lower fasting glucose and decrease glucose area under the curve). 
4. 
Changes in the microbial community structure induced by antibiotics will be 
associated with changes in 24 hour energy expenditure  
5. 
Circulating GLP-1 and GLP-2 will be associated with nutrient absorption 
 

 
16 
 
METHODOLOGY 
Study design  
This is a controlled diet intervention study involving random ordered over and 
underfeeding followed by double blind randomized placebo controlled assignment to 
administration of oral vancomycin or placebo. 
Subjects 
 
Seventy, non-diabetic (67) individuals aged 18-45 y (in order to minimize the effect of 
aging on nutrient absorption) and on no medications (see details below) will be admitted for this 
study. All subjects will be recruited from the Phoenix greater metropolitan area by 
newspaper/internet advertisement. The study will end once 24 subjects have completed the 
entire in-patient part of the study. 
Eligibility criteria 
Inclusion Criteria 
• 
Free of acute and chronic diseases (especially GI disorders) as determined by medical 
history, physical examination and laboratory tests. 
• 
Individuals may be taking laxative drugs but they must be discontinued 3 or more weeks 
before admission. 
• 
Age 18-45 y (in order to minimize the affect of aging on nutrient absorption) 
 

 
17 
 
 
Exclusion Criteria 
Because it is unclear how chronic illnesses or substance abuse could affect nutrient absorption 
we will exclude volunteers with chronic diseases or current substance abuse. This is especially 
important because the limited number of study subjects in this study will make it hard to control 
for these confounders. We will therefore exclude subjects with a history or clinical manifestation 
of: 
- Current smoking 
- Type 2 diabetes (according to the World Health Organization diagnostic criteria) (67)  
- Endocrine disorders, such as Cushing’s disease, pituitary disorders, and hypo- and 
hyperthyroidism 
- HIV infection (self-report), due to effects on weight and body composition of HIV and 
medications used to treat HIV 
- Active tuberculosis (self-report) 
- Asthma on active daily treatment with medications 
- Pulmonary disorders including physician diagnosed chronic obstructive pulmonary 
diseases and obstructive sleep apnea syndrome 
- Cardiovascular diseases, including coronary heart disease, heart failure, arrhythmias, 
and peripheral artery disease 

 
18 
 
- Hypertension (according to the World Health Organization diagnostic criteria) (68), 
treated or uncontrolled 
- Gastrointestinal disease, including inflammatory bowel diseases (e.g. Crohn’s disease 
and ulcerative colitis), malabsorption syndromes (e.g. celiac disease), gastric ulcer 
(active) and irritable bowel syndrome. 
- Lactose intolerance 
- Anemia (defined as hemoglobin < 11 mg/dl), leucopenia (defined as white blood cell 
count < 4,000/µL) or thrombocytopenia (defined as platelet count < 150,000/µL) 
- Liver disease, including non-alcoholic fatty liver disease or current elevated liver 
enzymes  over 1.5 times the normal range for AST, ALT or GGT or a history and 
physical exam that indicates a potential liver disease as describe by Giannini et al(69)  
- Evidence of chronic renal disease as defined by estimated glomerular filtration rate of < 
60 ml/min or evidence of overt proteinuria on urine dipstick. (70)  
- Central nervous system disease, including previous history of cerebrovascular 
accidents, dementia, and neurodegenerative disorders  
- Cancer requiring treatment in the past five years, except for non-melanoma skin 
cancers or cancers that have clearly been cured or in the opinion of the investigator 
carry an excellent prognosis  
- Behavioral or psychiatric conditions that would be incompatible with a safe and 
successful participation in the study (such as major depression, schizophrenia and 
presence of psychotic symptoms) 

 
19 
 
- Eating disorders such as anorexia nervosa, bulimia or binge eating syndrome 
- Taking weight loss drugs 
- Weight change of more than 5% of total body weight in the 3 months before admission 
- Use of any antibiotic or probiotic agents within 6 months prior to minimize the potential 
effects of these substances on the gut microbiota. 
- Use of antacids (Proton pump inhibitors, H2 antagonists or aluminum/magnesium 
hydroxide)   3 months prior to the study assessed by self-report because a modified 
gastric pH might affect the gut microbiota as well 
- Evidence of alcohol and/or drug abuse (more than 3 drinks per day and use of drugs, 
such as amphetamines, cocaine, heroin, or marijuana) 
- Pregnant (due to use of research related radiation) and breastfeeding women (because 
of the prolonged inpatient stay and use of medication) are also excluded.  
The following exclusion criteria are necessary because of the substances given or tests 
performed during the study 
- Known allergies to vancomycin 
- Known allergies to heparin or a history of heparin-induced thrombocytopenia 
- Personal history or evidence of a bleeding disorder 
All individuals will be fully informed of the aim, nature, and risks of the study prior to giving 
written informed consent. The study’s informed consent will be obtained by a principal or 

 
20 
 
associate investigator, research physician or physician assistant working in the clinical research 
unit. Should we enroll a non-English speaking subject, we will obtain IRB approval to use the 
short form consent process as outline in SOP 12. 
 
Experimental design: 
Individuals will be admitted to the Clinical Research Unit for approximately 31 days. On the day 
of admission, volunteers will be instructed to limit their physical activity during the study. 
Specifically, volunteers will be asked not to exercise and activities will include only those 
permitted on the research unit such as playing pool, board games, and occasional supervised 
outings from the unit which involve a short walk. From admission, all stool samples will be 
collected both for 16S rRNA sequencing of the gut microbiota and during the period of diet 
manipulation and antibiotic for direct measurement of stool calories (stool will not be collected 
when volunteers are in the metabolic chamber). Initially, volunteers will be placed on a weight 
maintaining diet for three days. During this time body composition will be measured using dual-
energy x-ray absorptiometry and on day 3 volunteers will undergo a 75 g oral glucose tolerance 
test. On day 4, volunteers will begin consuming diets consisting of 50% and 150% of their 
weight maintaining calories in random order. Each intervention diet will last 3 days interrupted 
by a 3 day weight maintaining phase to eliminate potential carry-over effects. Volunteers will 
consume blue dye markers at the beginning and end of each experimental diet. Precisely the 
dye capsules will be taken before breakfast on day 1 of each experimental diet, and before  
breakfast on the day following each intervention diet. Stool for caloric content measurements 
will be collected from appearance of the first dye marker in stool (dyed stool included) until 
appearance of the second dye marker (dyed stool excluded). Because the dye marker does not 

 
21 
 
appear in urine, urine collections for caloric content measurements will begin right after 
breakfast on day 1 of the first experimental diet and stop before breakfast of the day after the 3 
day intervention diet. The gastrointestinal transit time for the two intervention period will also be 
recorded as time between ingestion of the dye marker and appearance in stool. Weight 
maintaining and experimental diets will be similar in their relative macronutrient content for each 
volunteer to allow for comparison of stool energy content between diets and intervention groups. 
During the experimental diets and during 3 days under antibiotic/placebo, meals will be 
prepared in duplicates with one meal being chosen at random for consumption by the volunteer 
and the other meal for exact caloric content measurement via bomb calorimetry. The 
gastrointestinal transit time for this period will also be recorded. In case the gastrointestinal 
transit time of the dye marker takes longer than expected, we will extend stool collection time as 
well as study period to make sure volunteers complete the study. Following the 
over/underfeeding diets, volunteers will again be placed on a weight maintaining diet for 3 days. 
Following this (on study day 16), they will undergo a second OGTT. The next day they will enter 
the metabolic chamber at 0800 for approximately 23.5 hours for measurements of energy 
expenditure and substrate utilization. In the morning of the next day after exiting the metabolic 
chamber, volunteers receive a heparin bolus in the fasting state with subsequent blood 
sampling 15 minute later for measurement of lipoprotein lipase activity. Then while remaining on 
the weight maintaining diet, volunteers will be randomly assigned to either receive vancomycin 
125mg qid or identical placebo pills for 12 days. Volunteers and investigators including nursing 
staff will be blinded to the randomization. The randomization and release of the medication will 
be managed by the pharmacy of the Phoenix Indian Medical Center. After 5 days on the 
vancomycin or placebo volunteers , while continuing the weight maintaining diet, will undergo 
measurement of stool and urine calories as described above over the next 3 days. Following 

 
22 
 
this, (and while still on vancomycin or placebo), volunteers will undergo a third OGTT. One the 
day after the third OGTT, they will have a second 23.5 hour stay in the metabolic chamber. On 
exiting the metabolic chamber, volunteers will undergo a repeat measurement of lipoprotein 
lipase activity post heparin bolus as described above. After this 12 day period 
vancomycin/placebo will be discontinued. The following morning, after checking their platelet 
count, volunteers will be discharged. Volunteers will be asked to return with stool samples, one 
week, one month and 6 months after discharge. Weight and height will be recorded at the 6 
month visit. 
During the inpatient stay, fluid consumption may affect the outcome of the study by changes in 
gastrointestinal transit time. Fluid intake, therefore, will also be controlled during the study. Each 
volunteer will be allowed to drink up to 2000 ml of non-carbonated or carbonated, non-
caffeinated, non-caloric beverages or water plus fluids brought with each meal. The liquid drunk 
for the oral glucose tolerance test will not be counted toward the 2000 ml daily fluid. We will also 
record total fluid intake and urine output. The experimental design is shown in Figure 1. 
 
 
 
 
 
 
 

 
23 
 
 
 
 
 
Figure 1: Overview of the Study 
 
WMD: weight maintaining diet, OF/UF : (overfeeding/underfeeding) experimental diet with either 
150% or 50% of weight maintaining calories, CH: 24 hour measurements of energy expenditure 
in metabolic chamber, DXA: dual-energy x-ray absorptiometry; OGTT: oral glucose tolerance 
test; FB: Fasting blood sample for measurements of GLP1&2 and Leptin; LPL: Measurement of 
Lipoproteinlipase activity. CBC; complete blood count for assessment of platelet count after 
Heparin injection. Duplicated Meals: experimental meals are provided in duplicates with one 
meal for consumption by the volunteer and the other chosen at random for measurement of 
caloric content,  

 
24 
 
 
 
 
 
Detailed experimental design 
DAY 1: 
• 
Admission, medical history, physical examination, nutritional history (Block 
questionnaire(71))  
• 
Resting 12-lead electrocardiogram 
• 
Blood tests: complete blood cell count, platelet count, prothrombin time, partial 
thromboplastin time, glucose, electrolytes, plasma urea nitrogen, plasma osmolarity, 
creatinine, SGOT, SGPT, gamma-GT, bilirubin, calcium, phosphorus, total protein, albumin, 
alkaline phosphatase, TSH 
• 
IgA anti tissue transglutaminase for celiac disease 
• 
Lactose intolerance screening (using volunteer’s self- report) 
• 
Urine drug screening for Cocaine, Opiates, Meth-Amphetamine, THC and Nicotine (if the 
results of the urine drug screen are positive, the volunteer will be ineligible for the study. The 
volunteer will be informed confidentially of their results and referred to their primary care 
provider to get counseling or treatment. The results of the positive urine drug screen will be 

 
25 
 
part of the volunteer’s medical records. This information will be treated with the same 
protection and confidentiality as all other medical records) 
• 
Begin 24-hour stool collection  
• 
Fecal tests for parasites and occult blood  
• 
Begin regular weight maintenance diet (50% carbohydrate, 30% fat and 20% protein) for 
weight stabilization 
DAY 2 - 3  
• 
Continue weight maintaining diet 
• 
Measurement of body composition (DEXA) 
• 
Fecal tests for parasites and occult blood  
• 
Explanation of the changes in stool color when the marker is used 
• 
Continue 24 hour stool collection 
• 
Start special weight maintaining diet on Day 3 
DAY 4 
• 
Oral glucose tolerance test (OGTT) for diabetes status determination 
• 
Continue special weight maintaining diet 
DAY 5-7 

 
26 
 
• 
Fasting blood collection  
• 
Begin first intervention diet (under/overfeeding diet, random order) with dye capsule 
administered just prior to breakfast 
• 
Continue 24-hour stool collection; before having breakfast, volunteers will be asked to 
urinate, thereafter begin 24-hour urine collection for caloric measurement during first 
experimental diet 
• 
 Prepare duplicate meals  
 
DAY 8-10 
• 
Fasting blood collection on day 8 
• 
Before having breakfast, volunteers will be asked to urinate and this urine sample  will 
complete the urine collection for the first diet period 
• 
Administer dye capsule administered just prior to breakfast of day 8 
• 
Begin 3 day weight maintaining diet. 
• 
Continue 24-hour stool collection; finish first stool collection for caloric measurement with 
appearance of the second marker in stool 
• 
No duplicate meals  
 
DAY 11-13 

 
27 
 
• 
Fasting blood collection on day 11 
• 
Begin second intervention diet (under/overfeeding, random order) with third dye capsule 
administered just prior to breakfast 
• 
Continue 24-hour stool collection; before having breakfast, volunteers will be asked to 
urinate, thereafter begin 24-hour urine collection for caloric measurement during second 
intervention diet 
• 
Prepare duplicate meals 
 
DAY 14-15 
• 
Fasting blood collection on day 14 
• 
Before having breakfast, volunteers will be asked to urinate and this urine sample  will 
complete the urine collection for the second diet period  
• 
Begin weight maintaining diet with fourth marker prior to breakfast meal of day 14 
• 
No duplicate meals 
• 
Finish stool collection for caloric measurement for second experimental diet period with 
appearance of the fourth marker in stool 
• 
Continue 24-hour stool collection for microbiota 
DAY 16 
• 
Oral glucose tolerance test  

 
28 
 
• 
Assessment of blood electrolytes and creatinine 
• 
Continue weight maintaining diet  
• 
Continue 24-hour stool collection for microbiota 
DAY 17 
• 
Measure 24h energy expenditure in the metabolic chamber 
• 
Discontinue stool collection during 24h energy expenditure measurements in metabolic 
chamber 
• 
Continue weight maintaining diet 
DAY 18 
• 
Fasting blood collection 
• 
Administration of first heparin bolus with subsequent blood collection after 15 min. 
• 
Start oral vancomycin or placebo in the morning after LPL measurement 
• 
Continue weight maintaining diet 
DAY 19-22 
• 
Blood collection to assess platelet count on day 19 
• 
Continue weight maintaining diet 
• 
Continue oral vancomycin or placebo 
• 
Continue to collect stool samples for microbiota 

 
29 
 
• 
Special weight maintaining diet on day 20 and 21 
DAY 23-25 
• 
Administer dye capsule prior to breakfast 
• 
Start 24 hour urine collections for measurement of urine calories; collect stool samples 
• 
 Duplicate meals 
• 
Continue weight maintaining diet  
• 
Continue oral vancomycin or placebo 
• 
Continue to collect stool/urine samples. 
 
 
DAY 26 and 27 
• 
Before having breakfast, volunteers will be asked to urinate and this urine sample  will 
complete the urine collection for the antibiotic/placebo period 
• 
Administer blue dye capsule prior to breakfast  
• 
Continue weight maintaining diet 
• 
Continue stool collection for microbiota 
 
DAY 28 
• 
Oral glucose tolerance test 
• 
Collecting blood for complete blood count 

 
30 
 
• 
Control of blood electrolytes and creatinine 
• 
Continue weight maintaining diet 
• 
Continue oral vancomycin or placebo 
• 
Continue to collect stool samples until dye marker is present. 
• 
End stool collection for caloric measurments study after dye marker appears 
• 
End stool collection for microbiota on evening of day 28 
 
DAY 29 
• 
Measure 24h energy expenditure in the metabolic chamber 
• 
Continue weight maintaining diet 
 
DAY 30 
• 
Volunteer exits metabolic chamber 
• 
End oral vancomycin or placebo after morning dose was taken 
• 
Collect fasting blood sample 
 
• 
While fasting receives heparin bolus and then 15 minutes later has blood drawn. 
DAY 31 
• 
Blood collection for complete blood count, if normal, volunteer can be discharged home. 
 

 
31 
 
DAY 6-8 after discharge 
• 
Blood collection for complete blood count 
• 
Volunteer is asked to return with most recent stool sample (dated and timed) 
DAY 30 after discharge 
• 
Volunteers will be asked to  return with most recent stool samples (dated and timed) 
• 
All volunteers will  asked about possible side effects and general state of health 
Six Months after discharge: 
• 
Volunteer will be asked to return with most recent stool sample 
• 
Volunteer will have weight and height recorded. 
 
 
 
 
TESTS AND ANALYSES 
 
Study diets:  
 
Weight maintaining and experimental diets have similar macronutrient profiles (Protein 
20%, Fat 30%, Carbohydrates 50%). Daily calorie needs for the weight maintaining diets are 
calculated as: body weight (in kg) x 9.5 + 1973(72). In order to diminish the effect of consumed 
food on the gut microbiota, the menu and order of the meals will be kept exactly the same over 
the course of the study; only the quantity of food will differ. This will ensure that volunteers eat 
proportionally  the same amount of macronutrients and fiber during the study. In addition, in 

 
32 
 
order to minimize the effect of lactose intolerance during the study which will only be screened 
by patient self report, the meal will be made to minimize the quantity of dairy products. 
Experimental diets are characterized by either 150% or 50% of weight maintaining calories and 
will be offered in random order. During the experimental diet period and during 3 days under 
antibiotic/placebo, meals will be prepared in duplicates and chosen at random to either be 
offered for consumption to the volunteer or used for caloric measurement by bomb calorimetry. 
The same diet will be fed to volunteers (but at 100% of weight maintaining calories) during the 3 
day stool collection period while on vancomycin or placebo.  
Dye marker:  
 
An inert colored dye, brilliant blue (FD&C blue) will be used to define the dietary periods. 
This colored dye is not absorbed in transit, does not undergo secondary metabolism by 
gastrointestinal bacteria, and thus is recovered fully in the stool. In addition, the average time 
between ingestion and the first appearance in stool of brilliant blue is 34 hours and complete 
passage of this dye takes 85 hours (73). However, this dye does not appear in urine. The dye 
marker can be purchased commercially.      
 Body composition by DEXA:  
 
DEXA will be used to accurately measure body composition. DEXA is an X-ray device 
which non-invasively assesses both skeletal density and soft tissue composition by region with 
a precision of <1% for bone and 4-5% for soft tissue densities. Total body scan requires 10-50 
minutes depending on the stature and thickness of the subject. The major limitation of the 
apparatus is the width of the scanning table. We validated the use of a half-body scan as an 
indicator of whole body composition in obese subjects who do not fit entirely on the scanning 

 
33 
 
area. This half body method is valid for individuals weighing as much as 350 pounds (74). 
During the procedure, the subject is asked to lie flat on the table and to remain motionless, 
since the precision of the measurement can be compromised by subject's movement during the 
scan. Proper subject positioning is also important. Once the proper alignment is determined, the 
subject’s ankles and knees are loosely strapped to maintain the position. When the machine is 
turned on, a 150 mA current flows through the X-ray tube to produce X-rays. As the scan table 
arms move from the top of the subject’s head downward towards the subject’s feet, the shutter 
opens and a narrow beam of radiation projects upward through the table top and subject. After 
the scan, the arm clears the subject’s feet, the scanner stops, and the source shutter closes. 
The software then calculates body composition in grams of fat tissue and lean tissue and 
percentage of body fat. The operator remains in the room with the subject during the scan. 
 
 
Oral glucose tolerance test:  
 
Oral glucose tolerance tests will be used to assess glucose metabolism. After an 
overnight fast, an intravenous catheter will be placed in the forearm vein for blood withdrawal. 
Each subject will ingest 75 g of glucose over 2 minutes. Blood will be drawn at -15, 0, 30, 60, 
90, and 120 minutes for assessment of plasma glucose and insulin.  
Twenty four hour energy expenditure and basal metabolic rate:  
 
The respiratory chamber is a comfortable, air-tight room (approximately 10 feet x 8 feet x 
7 feet) constructed as a large open-circuit indirect calorimeter. It is furnished with a toilet, sink, 
bed, desk, chair, color television and radio. The air temperature is maintained constant at 75 oF 

 
34 
 
by an air conditioning system. Visual contact with the subject is possible through one of the 
windows. Food is provided into the chamber through an airtight interlock. Spontaneous physical 
activity is continuously monitored by a radar system based on the Doppler Effect. The flow rate 
through the chamber and the CO2 and O2 concentrations of the out-flowing air are continuously 
computed and calculations of oxygen consumption, carbon dioxide production, respiratory 
quotient and spontaneous physical activity are made every minute. The subject will enter the 
chamber at 7:45 am for 23.5 hours.  
Antibiotic treatment and placebo:  
 
Volunteers will be randomly assigned to either oral antibiotic or placebo medication for 
12 days. The antibiotic treatment group will receive vancomycin 125mg orally four times per day 
starting in the morning of day 18. The last dose will be given in the morning of day 30. The 
duration of the vancomycin or placebo phase is a combination of a loading phase of five days 
(to allow for changes in gut microbiota to change and stabilize) followed by a series of tests that 
will be done over the next 7 days.(24 hour energy expenditure measurement, collection of stools 
for caloric measurements over 6 days, OGTT and LPL measurements). Placebo medication will 
be given in the exact same manner. All investigators including nursing personnel as well as the 
volunteer him-/herself will be blinded to the randomization code. The randomization and release 
of the medication/placebo compounds will be managed by the pharmacy of the Phoenix Indian 
Medical Center. 
 
Heparin boli and post-heparin blood sampling: Lipoprotein lipase(LPL) is anchored to 
endothelial cells and is needed to remove triglycerides (TG) from chylomicrons and very low 
density lipoproteins and then transfer these TG into parenchymal cells. A bolus of heparin 

 
35 
 
releases LPL from the endothelium and allows the measurement of LPL activity in a blood 
sample(75). On day 18 before starting the antibiotic/placebo medication, volunteers will be given 
an intravenous bolus of 75 IU/kg heparin after a 12-hour overnight fast. This  method has been 
applied previously by our collaborators (76–78). Before the injection of the heparin bolus, 10ml 
venous blood from the cubital vein will be drawn into a Monoject© sodium heparin collection 
tube and 10ml will be drawn into a Monoject© 15% EDTA collection tube. 15 min after the 
heparin bolus another 10ml will be drawn into a Monoject© sodium heparin collection tube. This 
procedure will be repeated on day 26. Directly after the blood sampling, collection tubes will be 
kept cold on ice until centrifugation and subsequently stored at -70ºC until measurement of the 
lipoprotein lipase (LPL) activity in Dr. Gloria Vega's lab. Briefly, total lipase activity will be 
measured in the presence of apoC-II at physiological NaCl concentration. LPL activity will be 
calculated as total LPL activity subtracted by salt-resistant LPL activity (hepatic lipase). Details 
to this method are described elsewhere (79).  
Stool and urine collection and storage:  
 
The first stool sample obtained after admission will be used as baseline measure of the 
microbiota. During the inpatient stay all stool will be collected for determination of the 
microbiota. Additionally to that we will assess caloric content of the stool during both under and 
overfeeding as well as for 3 days during the antibiotic/placebo part of the study. These periods 
will be marked using a dye marker. Right after receiving the first experimental meal with the dye 
marker, stool and urine collections for caloric content measurements will begin. The urine 
collection will be stopped before the volunteer has breakfast on the first day after each 3 day 
intervention diet. Before this meal the volunteer will swallow the second dye marker The two 
intervention diets will be interrupted by a 3 day weight-maintaining diet to wash out the effects of 
the prior diet. The stool collection of the first experimental diet period will be stopped as the 

 
36 
 
second dye marker appears. These processes for stool and urine collection will be repeated for 
the second experimental diet period and during three days of stool collection for caloric 
measurements while the volunteer is on vancomycin/placebo. Only the stool samples collected 
between the appearance of the first marker and before the appearance of the second marker of 
each diet period and the urine samples collected during the these 3-day periods will be used for 
analysis of energy content. A small aliquot to determine the microbiota will be obtained from 
every stool sample from day one till day 31. This will not be more than several grams of stool. 
The aliquot will be frozen at -70° directly after collection of the stool. Volunteers will defecate 
into plastic bag that is held by a special container. The bag can easily be detached from the 
container and will be sealed and labeled by the volunteer. Then the plastic bag is put into a 
second container and will be given to our nursing stuff immediately who will then obtain the 
small aliquot for determination of the microbiome. Sample for bomb-calorimetry will be frozen at 
-20°C.  The procedure of high throughput sequencing does not require anaerobic conditions. 
Bacterial overgrowth of aerobic bacterial species will be prevented by freezing samples 
immediately after collection.  
 
Calorie content of food during experimental diet periods (gross energy intake):  
 
 
During the marked diet period, volunteers will eat under supervision and they will be 
encouraged to eat all food provided in each experimental meal. Moreover, to determine the 
energy content of the consumed food, each meal consumed during the over-/underfeeding part 
of the study and during three days of the weight maintaining diet will be duplicated. One meal 
will be given to the volunteer. The other meal will be homogenized then burned to determine the 
heat released after complete combustion using bomb calorimetry methodology. Volunteers who 

 
37 
 
are unable to consume 90% of provided calories will not continue in the study. In addition, any 
unconsumed calories will then be subtracted from the total calories to determine the overall 
intake. 
Calorie content in stool and urine:  
 
Three days of stool collection on each experimental diet will be pooled. The samples will 
be homogenized and freeze-dried.  Three days of urine collection on each experiment diet will 
also be pooled and freeze-dried prior to analysis. Urine and fecal energy content of these 
pooled samples will be obtained using bomb calorimetry methodology.  
Preparation and measurement of calorie content of stool:  
 
Prior to analysis, distilled water, equal to the weight of the feces, will be added. The 
feces-water mixture will be homogenized then. Because some of the energy containing fecal 
compounds are volatile in the pH ranges of normal stool and hence may be lost during the 
sample preparation, fecal alkalization will be employed before lyophylization(80). The 
preparation process will be done using up-to-date methods (80,81). After preparation, the energy 
content in stool will be determined by measuring the quantity of heat that is produced upon 
complete combustion of the sample, using bomb calorimetry methodology.  
The microbial flora in stool will be enumerated using 16S rRNA probes that has been 
described previously (46). In brief, 16 S rRNA amplicons will be generated using universal 
bacteria-specific primers that target most enteric bacteria, allowing us to detect a broad, 
unbiased survey of the enteric bacterial population in the study cohort. However, the majority of 
gut microbes are expected to belong to either the Bacteroidetes or the Firmicutes phyla (46). 
The primers that will be used are 8F and 338F. Samples selected for microbiota analyses will be 

 
38 
 
sent to and performed inDr. Peter Turnbaugh’s laboratory at the G.W. Hooper Research 
Institute at University of San Francisco, CA. . Stool for metagenomic analyses will be collected 
throughout the study period with exception of two 24-hour periods in the metabolic chamber and 
the discharge day. The total number of stool samples collected will vary with the defecation 
frequency of the volunteer during the study period.  
 
Block Questionnaire: 
  
Will be administered on admission. The Block Food questionnaire will assess usual 
nutrient intake over the preceding year.  
Blood analyses 
Glucagon-like peptide (GLP-1,2) and leptin measurements 
GLP-1&2 and leptin will be measured using commercial radioimmunoassay kit and will 
be drawn at 6 time points during the study: 
1. Day 5 before start of the first intervention diet (GLP1&2, leptin) 
2. Day 8 after the first 3 day intervention diet  (GLP-1&2, leptin)  
3. Day 11 before the start of the second intervention diet (GLP-1&2, leptin) 
4. Day 14 after the second 3 day intervention diet (GLP-1&2, leptin) 
5. Day 18 before LPL measurment (GLP 1&2, leptin) 

 
39 
 
6. Day 30,  before LPL measurment (GLP 1&2, leptin) 
Blood samples for GLP1&2 will be collected in ice-cooled tubes and will be collected 
using heparin as an anticoagulant (10 IU heparin/ml blood).The appropriate amount of DPP-IV 
inhibitors will be intermediately added for each collection. Tubes will be mixed and stored in an 
ice bath, then centrifuged at 1000 x g for 10 minutes in a refrigerated centrifuge. The specimens 
will be stored at -70°C until analyzed. All blood samples will be taken in the fasting condition. 
 
DATA ANALYSIS 
This is a, cross-over intervention study in volunteers consuming two different caloric 
diets followed by a double blind randomized placebo controlled phase investigating the effect of 
antibiotics . The main outcomes of the study are stool energy content (nutrient absorption) and 
genetic identification of gut microbial communities during over/underfeeding  and during 
antibiotic or placebo intervention. Results of the study will be expressed as kcal/day for energy 
content in stool, % of calories in stool relative to ingested calories and relative abundance of gut 
bacteria. A paired t-test will be used to compare the changes in percent stool calories and 
relative abundance of gut bacteria during the over and underfeeding diets. Pearson or 
Spearman correlation will be used to investigate the association of change in the relative 
abundance of major gut microbiota phyla with stool calorie loss, the association of stool calorie 
loss with gut transit time, and the association of change in relative abundance of the major 
phyla. Student’s t-Test will be applied to determine the difference in the outcomes of stool and 
urine calories between the antibiotic versus placebo groups. Changes in fasting plasma 
glucose, area under the curve for glucose and insulin during the OGTT and lipoprotein lipase 
activity will be compared using paired t-test. In addition, mixed models will be applied to 

 
40 
 
investigate changes in the gut microbiota over time. The defined age range will minimize 
possible differences in ages between the groups. However, if the mean age is significantly 
different between the two groups, general linear regression models accounting for age will be 
used to compare energy loss and relative abundance of gut bacteria in stool between the 
intervention groups 
Sample size 
There will be two primary outcomes for this study. The first will be the difference in 
nutrient absorption between the experimental diets (50% and 150% of WMEN) within the 
groups. The second will be to examine the difference in nutrient absorption in those receiving 
antibiotic versus placebo. In our initial study, we found a significant difference in nutrient 
absorption in lean individuals fed a 2400 kcal/day versus 3400 kcal/day diets of 1.3 ± 1.9%. 
Assuming a similar difference during under versus overfeeding, using a correlation between 
stool calories for each diet as determined in the initial study of r=0.45, with 24 individuals we will 
have a power of 0.86, at an alpha of 0.05 to detect a difference in stool calories. This should be 
considered a conservative estimate as the power may be higher as the difference in calories fed 
during the over/underfeeding will be larger (nearly double) than in the initial study.  
For the comparison between placebo versus antibiotic groups: Murphy et al 
demonstrated that treatment with oral vancomycin resulted in a 16% decrease in Firmicutes. 
Our previous results in humans showed that a 20% decrease in the abundance of Firmicutes 
was associated with a decrease in nutrient absorption of ~150 kcal/d. Based on this, a 16% 
decrease in Firmicutes would be expected to decrease nutrient absorption by 120 kcal/day. 
Even assuming a more modest antibiotic-induced change in the relative abundance of 
Firmicutes by only 10% resulting a 75 kcal per day difference with a standard deviation of 48.9 

 
41 
 
kcal/d, 12 subjects per intervention group (n=24 total) would be sufficient to achieve 95% power 
to detect a difference between intervention groups at a p-value less than 0.05. To account for 
participants who are unable to complete the study protocol, we plan to recruit 40 volunteers. 
 
 
 
BENEFITS 
The expected benefits of this study include obtaining valuable knowledge to whether 
gut bacteria are causally related to the development of obesity. Individuals may not directly 
benefit from this study, although each individual will receive a physical examination and 
laboratory testing that may be relevant to their health.

 
42 
 
PROTECTION OF HUMAN SUBJECTS  
Written informed consent 
 
All individuals will be fully informed of the aim, nature, and risks of the study prior to giving 
written informed consent. The study’s informed consent will be obtained by staff of the clinical 
research unit who have reviewed and are familiar with the protocol and compliant with human 
subjects training; these include the principal investigator or other designated qualified protocol  
investigators (listed on the protocol’s face page).  Should we enroll a non-English speaking 
subject, we will obtain IRB approval to use the short form consent process as outline in SOP 12. 
 
Rationale of human selection 
As mentioned previously, there is limited information about energy loss in stool and urine 
in humans. Factors which influence energy loss (such as nutrition, absorption rate, gastrointestinal 
transit time and the gut microbiota) are also affected by several factors i.e., aging (21,23,82) 
ethnicity (36–38), menstrual cycle (39), fluid consumption and food patterns. We will include both 
male and female 18-45 years of age. However we will assess the phase of the menstrual cycle of 
our female volunteers both through medical history and hormone measurements on the day of 
admission. 
Possible risk and hazards 
 
Radiation exposure due to DXA:The DXA scans may take place on one of two comparable 
machines: the GE Lunar Prodigy or the GE Lunar iDXA. The radiation exposure for a 150 mA 
scan in the slow mode using the GE Lunar Prodigy may be as much as 2 mrem, as indicated by a 

 
43 
 
January 1997 internal radiation exposure review. The radiation exposure for a 188 mA scan using 
the GE Lunar iDXA may be as much as 1 mrem as indicated by a January 2014 internal radiation 
exposure review. According to the manufacturer, the exposure at the fast or medium scan speeds 
is likely to result in one-third (fast) to one-half (medium) the radiation exposure of the slow scan 
speed. Typical exposure from this procedure is equivalent to 1.22 (iDXA) to 2.5(Prodigy) days of 
exposure to natural background sources, such as the sun or radioactive materials found naturally 
in the earth’s air and soil. For subjects who move excessively during the scan, a complete or 
partial repeat of the scan procedure may be necessary. Thus, subjects could receive a maximum 
of 2 mrem per procedure for the iDXA (equivalent of 2.5 days of exposure) or 4 mrem per 
procedure for the Prodigy DXA (equivalent to 5 days of exposure from natural sources). In our 
study, only one baseline DXA scan will be performed resulting in a possible maximum exposure of 
4 mrem  if the Prodigy DXA is used for the scan and a repeat is required(equivalent to 5 days of 
exposure from natural sources). This is well within the NIH-Phoenix Radiation Safety Committee’s 
Guidelines for research subjects of 3,000 mrem to any organ or tissue in a 13-week period and 
5,000 mrem per year. The total radiation dose due to the DXA scan in this study, if the iDXA is 
used and a repeat is necessary, will be 2 mrem. The radiation exposure from a DXA scan 
increases the lifetime percentage cancer risk from 25% to 25.00016% for the Prodigy DXA or 
25.00008% for the iDXA. Pregnancy will be excluded using measurement of hCG in urine prior to 
the DXA scan. Oral glucose tolerance test: This test carries the risk of having an indwelling 
catheter in place for three hours. This risk includes hematoma, ecchymoses, and infection. 
 
Twenty-four hour energy expenditure measurement: There is a minimal risk associated 
with this measurement. At anytime, subjects can be in contact visually or by phone with the 
nurses. The nurses also check the temperature in the room as well as the different parameters 
listed on our computer screen every hour. In the case of any discomfort, the volunteer can ask to 
be taken out of the chamber. 

 
44 
 
 
Oral antibiotic treatment: Oral Vancomycin is an approved antibiotic which is used for 
Clostridia Difficile diarrhea and Staphylococcal enterocolitis. Vancomycin inhibits bacterial cell wall 
synthesis and is bactericidal against a number of aerobic and anaerobic bacteria.  Potential 
adverse events, which are predominantly associated with the intravenous form of vancomycin 
include hypokalemia (13%) and abdominal pain (15%), diarrhea (9%), nausea (17%) and vomiting 
(9%). There is also risk of nephrotoxicity (5%) (67).   Intravenous vancomycin is also associated 
with “red man syndrome”. Oral vancomycin, in the absence of ongoing enterocolitis, is very poorly 
absorbed with only 0.76% appearing in the urine (67). Contraindications to oral vancomycin are 
hypersensitivity to previous vancomycin use. Given the poor oral absorption potential side effects 
are expected to be minimized in these otherwise healthy volunteers. Volunteers will all be on the 
inpatient unit during vancomycin administration and will be closely observed. In addition, a 
chemistry panel including measurement of serum potassium and serum creatinine will be 
performed on admission, and on day #13 (prior to starting vancomycin) and day # 24. The long-
term effect of Vancomycin on the gut microbiota is unclear. There are several studies showing 
that oral antibiotic treatment can lead to changes in the gut microbiota that can persist for 
months(83). One study showed an increased risk of developing obesity after treatment with 
intravenous Vancomycin compared to other antibiotic treatments(55) however oral and not 
intravenous Vancomycin will be used in this study. However, specifically whether oral vancomycin 
has a persistent effect on gut microbiota is not clear.  
 
Intravenous heparin boli: Contraindication to intravenous heparin injections are active or 
uncontrollable bleeding, severe thrombocytopenia, known allergies to heparin or a history of 
heparin-induced thrombocytopenia. Common adverse events of heparin injections are local skin 
irritation, erythema, hematoma, increased liver aminotransferase levels, transient  
thrombocytopenia defined as a platelet count < 150,000/ml which occurs in up to 30% of patients 
that received heparin, and heparin induced thrombocytopenia requiring treatment with an 

 
45 
 
alternative anticoagulant (1-10%). Severe adverse events are hemorrhage, heparin-induced 
thrombocytopenia with thrombosis (less than 1%), and anaphylaxis or increased immune 
hypersensitivity reaction (84). The anti-coagulation effect half-life is 1.5 hours and plasma half-life 
0.687 to 2.478 hours dependent on heparin dose.1 Day and 7 days after the heparin injection we 
will check platelet count to look for signs of heparin induced thrombocytopenia as described by 
Warkentin et al(85). Throughout the treatment period tests for occult blood in stool will additionally 
be performed to periodically check for occult GI bleedings. Of note the dose we are using (75 
IU/kg) is within the recommendations for heparin bolus for clinical use which is 80 IU/kg(86).  
 
Twenty-four hour stool and urinary collection for energy and bacterial content: There are 
minimal risks related to this procedure but it is inconvenient. The volunteer will be trained all the 
necessary skills and equipped with collection devices, storage bags and gloves.  
 
Digestion of dye marker: There are minimal risks associated with this procedure.  
Individuals may feel uncomfortable by the changes in color of their feces. These dyes have 
proven to be excellent indicators, creating sharp color demarcations (73). 
Disclosure of medical conditions 
 The participants will be informed of any medical conditions uncovered by the screening 
blood work performed and referred to their primary care provider. The information will also be 
entered into their medical records and at the patient’s request, sent to their physicians. All 
information from the study will be made available to the patients and their physicians at the 
patient’s request. Information will be treated with the same protection and confidentiality as all 
other medical records. All information from the study may be made available to insurance 
companies if the information is requested by the insurance company and the subject signs a 
release of information. This could affect future insurability and employment opportunities. 

 
46 
 
 
Data and safety monitoring 
Except for abdominal discomfort, nausea and headache, potential adverse effects from this 
study are expected to be infrequent. This is, in part, a randomized double blind placebo controlled 
study. Oral vancomycin is an approved FDA medication but its’ use in this study (to promote 
changes in the gut microbiota) is off-label.  Participants will be on oral vancomycin for only 12 
days and during this time, they will be observed on the inpatient clinical research unit. Therefore 
the principal investigator will act as the data and safety monitor for this study. Should an serious 
unanticipated problem occur (defined below), the principal investigator (PI) will have access to the 
randomization code. The PI will report all serious unanticipated problems in writing as soon as 
possible, but within seven calendar days of learning of the event.  Not serious unanticipated 
problems will be reported within 14 days after the PI learns of the event to the NIDDK IRB.  
All AEs reported spontaneously by the subject, as well as those noted by the investigator or study 
site staff, will be recorded. In order to avoid vague, ambiguous, or colloquial expressions, the AE 
term should be recorded using standard medical terminology rather than the subject's own words. 
Every attempt will be made to describe the AE in terms of a diagnosis. Whenever the investigators 
are confident in making a unifying diagnosis, all related signs, symptoms and abnormal test 
results will be grouped together and recorded as a single AE. 
All subjects who have AEs, whether or not the AEs are considered associated with the use of the 
study medication, will be monitored until the AE resolves, stabilizes or becomes chronic. The 
clinical course of the AE will be followed according to accepted standards of medical practice, 
even after the end of the observation period, until a satisfactory explanation for the AE is found or 
the investigator considers it medically justifiable to terminate follow-up.  

 
47 
 
All AEs will be evaluated for intensity and causal relationship with use of the study medication or 
study procedures by the investigator.  
Study procedures will be subject to audits and/or monitoring visits to ensure compliance with the 
protocol and applicable regulatory requirements consistent with the NIDDK quality assurance 
program plan. Audit and/or monitoring visit results will be reported to the Principal Investigator for 
further reporting as appropriate. Study documents and pertinent hospital or clinical records will be 
reviewed to verify that the conduct of the study is consistent with the protocol plan. 
 
 
Event Characterization and Reporting to the IRB and Clinical Director (CD)  
 
Adverse events, protocol deviations, unanticipated problems (UP), Unanticipated 
Adverse Events (UADEs), serious adverse events, and serious are defined as described 
in NIH HRPP SOP 16 (“Reporting Requirements for Unanticipated Problems, Adverse 
Events and Protocol Deviations”).  All adverse events occurring during the study, 
including those observed by or reported to the research team, will be recorded. Serious 
unanticipated problems, Unanticipated Adverse Device Effects and serious protocol 
deviations, will be reported to the IRB and CD as soon as possible but not more than 7 
days after the PI first learns of the event. Not serious unanticipated problems will be 
reported to the IRB and CD as soon as possible but not more than 14 days after the PI 
first learns of the event. Not serious protocol deviations will only be reported to the IRB 
(within 14 days after the PI first learns of the event) if they represent a departure from NIH 
policies for the conduct of human subjects research, adversely affect the health care of the 

 
48 
 
subject(s) or compromise the interpretation or integrity of the research. Non-serious 
protocol deviations that result from normal subject scheduling variations or technical 
issues associated with sampling that does not impact the health of the subject or the 
interpretation of the study data will not be reported. 
 
Deaths will be reported to the NIDDK IRB and the Clinical Director within 7 days after the 
PI first learns of the event.

 
49 
 
Research Use of Stored Human Samples, Specimens or Data 
Blood (stored as plasma or serum), urine and stool samples not immediately used for study 
purposes will be stored for future measurements. Some of these samples will be sent to a 
commercial laboratory to measure GLP-1, GLP-2, leptin (plasma samples). Stool samples 
selected for analyses of the gut microbiota will be sent to Dr.Peter Turnbaugh at G.W. Hooper 
Research Foundation at University of San Francisco, CA. , as specified in the study. Blood 
received before and after the heparin boli will be sent to Dr. Gloria Vega at the UT Southwestern 
Medical Center in Dallas for measurement of lipoprotein lipase activity. Blood (stored as plasma 
or serum), urine, and stool samples not immediately used for study purposes will be stored for 
future measurements. All samples will be stored in freezers located on the premises at the NIH 
in Phoenix. 
Stored samples and specimens will be used only to measure factors that relate to diabetes, 
obesity and their complications. Stored samples, specimens or data may be sent to 
collaborators for specific measurements or analyses. All stored samples, specimens, and data 
will be coded so that when sent for measurements the identity of the volunteer remains 
confidential. Identification of coded samples will be kept in a secure password protected 
database accessible only to investigators, but will be identifiable in case specific tests yield 
clinical information of importance to a particular volunteer or samples can be destroyed per 
volunteer request (see below). Samples will be used only for research and not for commercial 
purposes. Research volunteers will not be informed of individual results from analyses 
performed specifically for research purposes, unless there is clear evidence accepted by the 
medical community that these results will impact the volunteer’s individual medical care or future 
health. Samples will be stored until used unless the volunteer requests in writing that the 

 
50 
 
samples be destroyed. All samples lost or destroyed secondary to volunteer request will be 
included in the annual renewal report. 
 
 
 
COMPENSATION 
 
Subjects will be receiving a total amount of $2635 if they complete the clinical part of the study. 
The amount is calculated as stated in the table below. For each follow-up visit subjects will 
receive another $25 per visit for a total of 75 dollars. If subjects are discharged prior to 
completion of the inpatient portion of the study for any reason including ineligibility based on 
initial testing,  side effects of the used treatments, inability to perform testing on the unit (for 
instance due to non-operational equipment) or personal reasons they will receive a rate of $20 
per day completed. These are the standard compensation rules for all studies on our unit.   
 
Daily payment @ $35.00/d x 31 days 
$1085.00 
One inconvenience unit for the OGTT x 3 
$75.00 
Three inconvenience units for the respiratory chamber for 23.5 hours x 2 
$150.00 
One inconvenience unit for fasting blood collection/CBC  x 6 
$150.00 
One inconvenience unit for intake of study medication daily x 12 
$300.00 
One inconvenience unit per day of 24h-urine and/or stool collection x 31  
$775.00 

 
51 
 
Two inconvenience units for intravenous heparin injection x 2 
$100.00 
Total  
$2635.00 
Follow up: 
 
One inconvenience unit will be paid for each stool sample for follow up x 3 
 
$ 75.00 

 
52 
 
 
Appendix A: 
 
Participants enrolled in a related study of nutrient absorption at the Children’s Hospital of 
Philadelphia (CHOP). This study entitled “Diagnosing Pancreatic-Based Malabsorption in 
Patients with Chronic Pancreatitis CHOP IRB# 16-013001” has been reviewed and approved by 
the CHOP Institutional Review Board. Dr. Virginia Stallings is the principal investigator. In this 
study, participants with chronic pancreatitis and controls collect stool over 72 hours as part of a 
study to investigate the alterations in nutrient absorption in participants with chronic pancreatitis. 
These stool samples will be assessed for both amount of fecal fat and calories/gram of stool. To 
measure stool calories, approximately 50 grams of stool will be sent to our clinical research unit. 
We expect to receive approximately 72 samples from 48 participants (24 with chronic 
pancreatitis and 24 controls). We will then freeze dry and make one gram pellets and perform 
bomb calorimetry on these samples for measurement of calories/gram. 
 
Samples will be coded and without any personal identifiers. Participants are aware that coded 
samples will be sent to our facility for these measurements. Once the measurements are made, 
we will send the researchers at CHOP the results. Remaining sample will not be returned, and 
will be destroyed once the measurements are made and reviewed. Researchers at CHOP will 
use this data for research analysis only, and results will not be communicated to the 
participants.   
REFERENCE LIST 
1.  
Obesity: preventing and managing the global epidemic. Report of a WHO consultation. 
World Health Organ Tech Rep Ser. 2000;894:i–xii, 1–253.  
2.  
Yanovski SZ, Yanovski JA. Obesity. N Engl J Med. 2002;346:591–602.  
3.  
Weststrate JA, Dekker J, Stoel M, Begheijn L, Deurenberg P, Hautvast JG. Resting energy 
expenditure in women: impact of obesity and body-fat distribution. Metabolism. 
1990;39:11–7.  

 
53 
 
4.  
Segal KR, Dunaif A. Resting metabolic rate and postprandial thermogenesis in polycystic 
ovarian syndrome. Int J Obes. 1990;14:559–67.  
5.  
Vansant G, Van Gaal L, De Leeuw I. Impact of obesity on resting metabolic rate and 
glucose-induced thermogenesis in non-insulin dependent diabetes mellitus. Int J Obes 
Relat Metab Disord. 1992;16:817–23.  
6.  
Gougeon R, Pencharz PB, Marliss EB. Effect of NIDDM on the kinetics of whole-body 
protein metabolism. Diabetes. 1994;43:318–28.  
7.  
Schoeller DA. Balancing energy expenditure and body weight. Am J Clin Nutr. 
1998;68:956S–961S.  
8.  
Menozzi R, Bondi M, Baldini A, Venneri MG, Velardo A, Del Rio G. Resting metabolic rate, 
fat-free mass and catecholamine excretion during weight loss in female obese patients. Br 
J Nutr. 2000;84:515–20.  
9.  
Blundell JE, Cooling J. Routes to obesity: phenotypes, food choices and activity. Br J Nutr. 
2000;83 Suppl 1:S33–8.  
10.  Huang KC, Kormas N, Steinbeck K, Loughnan G, Caterson ID. Resting metabolic rate in 
severely obese diabetic and nondiabetic subjects. Obes Res. 2004;12:840–5.  
11.  Fontvieille AM, Dwyer J, Ravussin E. Resting metabolic rate and body composition of Pima 
Indian and Caucasian children. Int J Obes Relat Metab Disord. 1992;16:535–42.  
12.  Ravussin E. Energy metabolism in obesity. Studies in the Pima Indians. Diabetes Care. 
1993;16:232–8.  
13.  Albu J, Shur M, Curi M, Murphy L, Heymsfield SB, Pi-Sunyer FX. Resting metabolic rate in 
obese, premenopausal black women. Am J Clin Nutr. 1997;66:531–8.  
14.  Sharp TA, Bell ML, Grunwald GK, Schmitz KH, Sidney S, Lewis CE, et al. Differences in 
resting metabolic rate between white and African-American young adults. Obes Res. 
2002;10:726–32.  
15.  Tataranni PA, Harper IT, Snitker S, Del Parigi A, Vozarova B, Bunt J, et al. Body weight 
gain in free-living Pima Indians: effect of energy intake vs expenditure. Int J Obes Relat 
Metab Disord. 2003;27:1578–83.  
16.  Atwater W, Rosa E. Description of a new respiration calorimeter and experiments on the 
conservation of energy in the human body. Washington: Government Printing House, 
1899.  
17.  Woolf GM, Miller C, Kurian R, Jeejeebhoy KN. Diet for patients with a short bowel: high fat 
or high carbohydrate? Gastroenterology. 1983;84:823–8.  

 
54 
 
18.  Van den Neucker AM, Forget PP, van Kreel B. Lipid, nitrogen, water and energy content of 
a single stool sample in healthy children and children with cystic fibrosis. Eur J Pediatr. 
2003;162:764–6.  
19.  Murphy JL, Wootton SA, Bond SA, Jackson AA. Energy content of stools in normal healthy 
controls and patients with cystic fibrosis. Arch Dis Child. 1991;66:495–500.  
20.  Cohen JR, Schall JI, Ittenbach RF, Zemel BS, Stallings VA. Fecal elastase: pancreatic 
status verification and influence on nutritional status in children with cystic fibrosis. J 
Pediatr Gastroenterol Nutr. 2005;40:438–44.  
21.  Van Es AJ, Vogt JE, Niessen C, Veth J, Rodenburg L, Teeuwse V, et al. Human energy 
metabolism below, near and above energy equilibrium. Br J Nutr. 1984;52:429–42.  
22.  Southgate DA, Durnin JV. Calorie conversion factors. An experimental reassessment of 
the factors used in the calculation of the energy value of human diets. Br J Nutr. 
1970;24:517–35.  
23.  Kruskall LJ, Campbell WW, Evans WJ. The Atwater energy equivalents overestimate 
metabolizable energy intake in older humans: results from a 96-day strictly controlled 
feeding study. J Nutr. 2003;133:2581–4.  
24.  Southgate DA. Fibre and the other unavailable carbohydrates and their effects on the 
energy value of the diet. Proc Nutr Soc. 1973;32:131–6.  
25.  Shetty PS, Kurpad AV. Increasing starch intake in the human diet increases fecal bulking. 
Am J Clin Nutr. 1986;43:210–2.  
26.  Beyer PL, Flynn MA. Effects of high- and low-fiber diets on human feces. J Am Diet Assoc. 
1978;72:271–7.  
27.  Miles CW, Kelsay JL, Wong NP. Effect of dietary fiber on the metabolizable energy of 
human diets. J Nutr. 1988;118:1075–81.  
28.  Wisker E, Maltz A, Feldheim W. Metabolizable energy of diets low or high in dietary fiber 
from cereals when eaten by humans. J Nutr. 1988;118:945–52.  
29.  Webb P. The exchange of matter and energy in lean and overweight men and women: a 
calorimetric study of overeating, balanced intake and undereating. Int J Obes. 1985;9 
Suppl 2:139–45.  
30.  Castiglia-Delavaud C, Verdier E, Besle JM, Vernet J, Boirie Y, Beaufrere B, et al. Net 
energy value of non-starch polysaccharide isolates (sugarbeet fibre and commercial inulin) 
and their impact on nutrient digestive utilization in healthy human subjects. Br J Nutr. 
1998;80:343–52.  
31.  Denke MA, Fox MM, Schulte MC. Short-term dietary calcium fortification increases fecal 
saturated fat content and reduces serum lipids in men. J Nutr. 1993;123:1047–53.  

 
55 
 
32.  Glatz JF, Katan MB. Dietary saturated fatty acids increase cholesterol synthesis and fecal 
steroid excretion in healthy men and women. Eur J Clin Invest. 1993;23:648–55.  
33.  Jacobsen R, Lorenzen JK, Toubro S, Krog-Mikkelsen I, Astrup A. Effect of short-term high 
dietary calcium intake on 24-h energy expenditure, fat oxidation, and fecal fat excretion. Int 
J Obes (Lond). 2005;29:292–301.  
34.  McCargar LJ, Clandinin MT, Belcastro AN, Walker K. Dietary carbohydrate-to-fat ratio: 
influence on whole-body nitrogen retention, substrate utilization, and hormone response in 
healthy male subjects. Am J Clin Nutr. 1989;49:1169–78.  
35.  Jumpertz R, Le DS, Turnbaugh PJ, Trinidad C, Bogardus C, Gordon JI, et al. Energy-
balance studies reveal associations between gut microbes, caloric load, and nutrient 
absorption in humans. Am J Clin Nutr. 2011;94:58–65.  
36.  Metcalf AM, Phillips SF, Zinsmeister AR, MacCarty RL, Beart RW, Wolff BG. Simplified 
assessment of segmental colonic transit. Gastroenterology. 1987;92:40–7.  
37.  Martelli H, Devroede G, Arhan P, Duguay C, Dornic C, Faverdin C. Some parameters of 
large bowel motility in normal man. Gastroenterology. 1978;75:612.  
38.  Chan YK, Kwan AC, Yuen H, Yeung YW, Lai KC, Wu J, et al. Normal colon transit time in 
healthy Chinese adults in Hong Kong. J Gastroenterol Hepatol. 2004;19:1270–5.  
39.  Jung HK, Kim DY, Moon IH. Effects of gender and menstrual cycle on colonic transit time 
in healthy subjects. Korean J Intern Med. 2003;18:181–6.  
40.  Madsen JL. Effects of gender, age, and body mass index on gastrointestinal transit times. 
Dig Dis Sci. 1992;37:1548–53.  
41.  Webb P, Annis JF. Adaptation to overeating in lean and overweight men and women. Hum 
Nutr Clin Nutr. 1983;37:117–31.  
42.  Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, et al. A core 
gut microbiome in obese and lean twins. Nature. 2009;457:480–4.  
43.  Turnbaugh PJ, Ridaura VK, Faith JJ, Rey FE, Knight R, Gordon JI. The effect of diet on 
the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci 
Transl Med. 2009;1:6ra14.  
44.  Turnbaugh PJ, Backhed F, Fulton L, Gordon JI. Diet-induced obesity is linked to marked 
but reversible alterations in the mouse distal gut microbiome. Cell Host Microbe. 
2008;3:213–23.  
45.  Hildebrandt MA, Hoffmann C, Sherrill-Mix SA, Keilbaugh SA, Hamady M, Chen YY, et al. 
High-fat diet determines the composition of the murine gut microbiome independently of 
obesity. Gastroenterology. 2009;137:1716–24 e1–2.  

 
56 
 
46.  Ley RE, Backhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut 
microbial ecology. Proc Natl Acad Sci U S A. 2005;102:11070–5.  
47.  Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-
associated gut microbiome with increased capacity for energy harvest. Nature. 
2006;444:1027–31.  
48.  Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes 
associated with obesity. Nature. 2006 Dec 21;444(7122):1022–3.  
49.  Flint HJ. Obesity and the gut microbiota. J Clin Gastroenterol. 2011 Nov;45 Suppl:S128–
132.  
50.  Antonopoulos DA, Huse SM, Morrison HG, Schmidt TM, Sogin ML, Young VB. 
Reproducible community dynamics of the gastrointestinal microbiota following antibiotic 
perturbation. Infect Immun. 2009;77:2367–75.  
51.  Dethlefsen L, Huse S, Sogin ML, Relman DA. The pervasive effects of an antibiotic on the 
human gut microbiota, as revealed by deep 16S rRNA sequencing. PLoS Biol. 2008 Nov 
18;6(11):e280.  
52.  Rea MC, Dobson A, O’Sullivan O, Crispie F, Fouhy F, Cotter PD, et al. Effect of broad- and 
narrow-spectrum antimicrobials on Clostridium difficile and microbial diversity in a model of 
the distal colon. Proc Natl Acad Sci USA. 2011 Mar 15;108 Suppl 1:4639–44.  
53.  Murphy EF, Cotter PD, Hogan A, O’Sullivan O, Joyce A, Fouhy F, et al. Divergent 
metabolic outcomes arising from targeted manipulation of the gut microbiota in diet-
induced obesity. Gut [Internet]. 2012 Feb 16 [cited 2012 Apr 17]; Available from: 
http://www.ncbi.nlm.nih.gov/pubmed/22345653 
54.  Yap IKS, Li JV, Saric J, Martin F-P, Davies H, Wang Y, et al. Metabonomic and 
microbiological analysis of the dynamic effect of vancomycin-induced gut microbiota 
modification in the mouse. J Proteome Res. 2008 Sep;7(9):3718–28.  
55.  Thuny F, Richet H, Casalta J-P, Angelakis E, Habib G, Raoult D. Vancomycin treatment of 
infective endocarditis is linked with recently acquired obesity. PLoS ONE. 2010;5(2):e9074.  
56.  Cani PD, Amar J, Iglesias MA, Poggi M, Knauf C, Bastelica D, et al. Metabolic 
endotoxemia initiates obesity and insulin resistance. Diabetes. 2007 Jul;56(7):1761–72.  
57.  Membrez M, Blancher F, Jaquet M, Bibiloni R, Cani PD, Burcelin RG, et al. Gut microbiota 
modulation with norfloxacin and ampicillin enhances glucose tolerance in mice. FASEB J. 
2008 Jul 1;22(7):2416–26.  
58.  Bäckhed F, Ding H, Wang T, Hooper LV, Koh GY, Nagy A, et al. The Gut Microbiota as an 
Environmental Factor That Regulates Fat Storage. PNAS. 2004 Nov 2;101(44):15718–23.  

 
57 
 
59.  Mandard S, Zandbergen F, van Straten E, Wahli W, Kuipers F, Müller M, et al. The fasting-
induced adipose factor/angiopoietin-like protein 4 is physically associated with lipoproteins 
and governs plasma lipid levels and adiposity. J Biol Chem. 2006 Jan 13;281(2):934–44.  
60.  Aronsson L, Huang Y, Parini P, Korach-André M, Håkansson J, Gustafsson J-Å, et al. 
Decreased fat storage by Lactobacillus paracasei is associated with increased levels of 
angiopoietin-like 4 protein (ANGPTL4). PLoS ONE [Internet]. 2010 [cited 2012 Jun 
25];5(9). Available from: http://www.ncbi.nlm.nih.gov/pubmed/20927337 
61.  Harmsen H, Gibson G, Elfferich P, Raangs G, Wildeboer‐Veloo A, Argaiz A, et al. 
Comparison of viable cell counts and fluorescence in situ hybridization using specific 
rRNA‐based probes for the quantification of human fecal bacteria. FEMS microbiology 
letters. 2000;183:125–9.  
62.  Horner-Devine MC, Carney KM, Bohannan BJ. An ecological perspective on bacterial 
biodiversity. Proc Biol Sci. 2004;271:113–22.  
63.  Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, et al. Diversity of 
the human intestinal microbial flora. Science. 2005;308:1635–8.  
64.  Qin X, Shen H, Liu M, Yang Q, Zheng S, Sabo M, et al. GLP-1 reduces intestinal lymph 
flow, triglyceride absorption, and apolipoprotein production in rats. Am J Physiol 
Gastrointest Liver Physiol. 2005;288:G943–9.  
65.  Drucker DJ. Glucagon-like peptide 2. J Clin Endocrinol Metab. 2001;86:1759–64.  
66.  Guilmeau S, Buyse M, Bado A. Gastric leptin: a new manager of gastrointestinal function. 
Curr Opin Pharmacol. 2004;4:561–6.  
67.  Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its 
complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of 
a WHO consultation. Diabet Med. 1998;15:539–53.  
68.  1999 World Health Organization-International Society of Hypertension Guidelines for the 
Management of Hypertension. Guidelines Subcommittee. J Hypertens. 1999;17:151–83.  
69.  Giannini EG, Testa R, Savarino V. Liver enzyme alteration: a guide for clinicians. CMAJ. 
2005 Feb 1;172(3):367–79.  
70.  Levey AS, Coresh J, Balk E, Kausz AT, Levin A, Steffes MW, et al. National Kidney 
Foundation Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and 
Stratification. Ann Intern Med. 2003 Jul 15;139(2):137–47.  
71.  Block G. A review of validations of dietary assessment methods. Am J Epidemiol. 1982 
Apr;115(4):492–505.  
72.  Ferraro R, Boyce VL, Swinburn B, De Gregorio M, Ravussin E. Energy cost of physical 
activity on a metabolic ward in relationship to obesity. Am J Clin Nutr. 1991;53:1368–71.  

 
58 
 
73.  Lutwak L, BURTON BT. FECAL DYE MARKERS IN METABOLIC BALANCE STUDIES. 
THE USE OF BRILLIANT BLUE AND METHYLCELLULOSE FOR ACCURATE 
SEPARATION OF STOOL PERIODS. Am J Clin Nutr. 1964;14:109.  
74.  Tataranni PA, Ravussin E. Use of dual-energy X-ray absorptiometry in obese individuals. 
Am J Clin Nutr. 1995;62:730.  
75.  Young SG, Zechner R. Biochemistry and pathophysiology of intravascular and intracellular 
lipolysis. Genes Dev. 2013 Mar 1;27(5):459–84.  
76.  Sumner AE, Vega GL, Genovese DJ, Finley KB, Bergman RN, Boston RC. Normal 
triglyceride levels despite insulin resistance in African Americans: role of lipoprotein lipase. 
Metabolism. 2005 Jul;54(7):902–9.  
77.  Tato F, Vega GL, Grundy SM. Determinants of Plasma HDL-Cholesterol in 
Hypertriglyceridemic Patients Role of Cholesterol-Ester Transfer Protein and Lecithin 
Cholesteryl Acyl Transferase. Arterioscler Thromb Vasc Biol. 1997 Jan 1;17(1):56–63.  
78.  Blades B, Vega GL, Grundy SM. Activities of lipoprotein lipase and hepatic triglyceride 
lipase in postheparin plasma of patients with low concentrations of HDL cholesterol. 
Arterioscler Thromb Vasc Biol. 1993 Aug 1;13(8):1227–35.  
79.  Hill JS, Yang D, Nikazy J, Curtiss LK, Sparrow JT, Wong H. Subdomain chimeras of 
hepatic lipase and lipoprotein lipase. Localization of heparin and cofactor binding. J Biol 
Chem. 1998;273:30979–84.  
80.  Zarling EJ, Ruchim MA, Makino D. Improved technique for measuring fecal energy loss in 
normal and malabsorbing humans. J Lab Clin Med. 1986;107:5–9.  
81.  Lovelady HG, Stork EJ. An improved method for preparation of feces for bomb calorimetry. 
Clin Chem. 1970;16:253–4.  
82.  Southgate D, Durnin J. Calorie conversion factors. An experimental reassessment of the 
factors used in the calculation of the energy value of human diets. British Journal of 
Nutrition. 1970;24:517–35.  
83.  Dethlefsen L, Relman DA. Incomplete recovery and individualized responses of the human 
distal gut microbiota to repeated antibiotic perturbation. Proc Natl Acad Sci USA. 2011 Mar 
15;108 Suppl 1:4554–61.  
84.  Micromedex® 1.0 Database including DUGDEX®.  2010.  
85.  Warkentin TE, Heddle NM. Laboratory diagnosis of immune heparin-induced 
thrombocytopenia. Curr Hematol Rep. 2003 Mar;2(2):148–57.  
86.  Guyatt GH, Akl EA, Crowther M, Gutterman DD, Schuünemann HJ, American College of 
Chest Physicians Antithrombotic Therapy and Prevention of Thrombosis Panel. Executive 
summary: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American 

 
59 
 
College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012 
Feb;141(2 Suppl):7S–47S.  
 

 
60 
 
SCHEDULE OF PROCEDURES 
 
 
 
 

 
61 
 
Blood Drawing 
1) 
Screening lab work  
 
 
  
 
 
 
 
 
 
32 ml 
2)  
CBC x 2  
 
 
 
 
 
 
 
 
 
 
  10 ml 
2) 
OGTT (fasting, 2h) 
 
 
 
 
 
 
 
 
 
  3 ml 
3) 
OGTT (3-hr) x 2  
 
 
 
  
 
 
 
 
 
90 ml  
4) 
Fasting blood samples x 6 
 
 
 
 
             
 
            180 ml 
5)            LPL measurements  
               
 
             82 ml 
           
TOTAL for study 
 
 
 
 
 
 
        
 
 
         397 ml