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1 THE EFFECT OF INCREASED FUNCTIONAL FIBER CONSUMPTION ON MICROBIOTA COMPOSITION IN INDIVIDUALS WITH CHRONIC KIDNEY DISEASE By JUSTIN JOELL FORDE A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PAR TIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DE GREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2012
2 2012 Justin Joell Forde
3 To Alexis
4 ACKNOWLEDGMENTS I thank my parents, family, friends and mentors They have inspired and encouraged me in all areas of my life. I will continue to use the skills that they have taught me in all of my future endeavors.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 ABSTRACT ................................ ................................ ................................ ..................... 9 CHAPTER 1 LITERATURE REVIEW ................................ ................................ .......................... 11 Kidney Structure and Function ................................ ................................ ................ 11 Chronic Kidney Disease ................................ ................................ .......................... 12 Uremia and Uremic Retention Molecules ................................ ................................ 14 Dietary Therapies for Chronic Kidney Disease ................................ ....................... 16 The Colon and Gut Microflora ................................ ................................ ................. 22 Microbial Activity ................................ ................................ ................................ ..... 25 Molecular Techniques ................................ ................................ ............................. 27 2 PURPOSE ................................ ................................ ................................ .............. 32 3 METHODS ................................ ................................ ................................ .............. 33 Study Design ................................ ................................ ................................ .......... 33 Inclusion/ Exclusion Criteria after Obtaining Consent ................................ ............. 33 Pre Baseline and Baseline ................................ ................................ ...................... 34 Treatment ................................ ................................ ................................ ............... 35 Daily and Weekly Measures ................................ ................................ ................... 35 Collection and Processing of Fecal Samples ................................ .......................... 36 Microbiota Anal yses ................................ ................................ ................................ 36 Statistics ................................ ................................ ................................ ................. 37 4 RESULTS ................................ ................................ ................................ ............... 40 Subject Demographics and Char acteristics ................................ ............................ 40 Diversity and Structure of the Microbiota from DGGE ................................ ............ 40 Analysis of Bifidobacteria and Lactic Acid Bacteria ................................ ................ 41 Diversity and Structure from Sequence Analysis ................................ .................... 42 5 CONCLUSION AND DISCUSSION ................................ ................................ ........ 51 APPENDIX: DOCUMENTS SUBMITTED TO THE IRB ................................ ................ 55
6 LIST OF REFERENCES ................................ ................................ ............................... 67 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 72
7 LIST OF TABLES Table page 3 1 Content and source of fibers in foods provided during weeks 1 and 2 ................ 39 3 2 Content and source of fiber in foods Provided during weeks 3,4, and 5 ............. 39 3 3 Nutrient per serving for control foods ................................ ................................ .. 39 3 4 Nutrient per serving for treatment foods ................................ .............................. 39 4 1 Mean fiber intake by fiber type (g/d) ................................ ................................ .... 44 4 2 Average diversity of control and treatment samples measured by the Shannon index and inverse Simpson in dices and their t test p values. .............. 44
8 LIST OF FIGURES Figure page 3 1 Study timeline. ................................ ................................ ................................ ..... 38 4 1 Flow chart of subject recruitment ................................ ................................ ........ 44 4 2 De ndrogram showing d iversity based on DGGE analysis ................................ ... 45 4 3 Mean Bifidobacteria genome equivalents in baseline and treatment samples .... 46 4 4 Mean lactic acid bacteria genome equivalents in baseline and treatment samples ................................ ................................ ................................ .............. 46 4 5 Average genome equivalents for bifidobacteria in baseline and treatment sam ples as measured by qPCR analysis. ................................ .......................... 47 4 6 Average genome equivalents for lactic acid bacteria in baseline and treatment samples as measured by qPCR analysis. ................................ .......... 47 4 7 Differences in OTU abundance. Heat map of the top ranked OTUs ................... 48 4 8 Unifrac diversity measures. Principal component analysis (PCA) of overall diversity based on Unifrac metric after fiber intervention. ................................ ... 49 4 9 Chao diversity plot. Chao diversity was calculated from sequence distribution after 4 weeks of fiber intervention. ................................ ................................ ...... 50
9 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Re quirements for the Degree of Master of Science THE EFFECT OF INCREASED FUNCTIONAL FIBER CONSUMPTION ON MICROBIOTA COMPOSITION IN INDIVIDUALS WITH CHRONIC KIDNEY DISEASE By Justin Joell Forde May 2012 Chair: Wendy Dahl Major: Food Science and Human Nut rition Twenty six million American adults suffer from chronic kidney disease (CKD) and millions of others are at risk of developing the condition. Many of the symptoms associated with CKD are a direct result of the accumulation of the byproducts of norma l digestive and metabolic processes that occur in the body. In healthy individuals metabolic wastes, such as urea from protein metabolism, are filtered from the blood by the kidney and excreted in the urine. Individuals with CKD have insufficient filtering capacity, leading to the accumulation of waste products in the blood and the accompanying perturbations in body functions. Those toxins that interfere with other metabolic processes are collectively known as uremic retention molecules (URMs). The current dietary method of treating CKD involves consumption of a diet moderate in protein P rotein restriction has some efficacy in reducing the production of nitrogenous wastes, and lowering blood urea nitrogen (BUN) levels, but it may also contribute to malnutri tion, and further the general decline in health associated with CKD. Other therapeutic targets for individuals with CKD should therefore be considered. The gut
10 microbiota may be one such target, as microbial metabolism may modulate blood levels of URMs thr ough fermentation of undigested materials in the colon. The aim of this study was to determine the effects of adding foods fortified with 23 g/d of functional fiber to the diets of patients with chronic kidney disease. Specifically our goal was to deter mine the effect of the fiber on the composition of the gut microbiota of these individuals. Adults (n=14) with a mean age of 64.8 14.7 were recruited and enrolled in a 6 week single blind, crossover design study. Study participants consumed commercially av ailable food products containing no added fiber for a 2 week control period, followed by a 4 week intervention period in which they consumed similar foods with 23 g of added fiber Stool samples for microbiota analysis were collected during the second and sixth weeks of the study. Compliance with food intake was 83% for control, and 78% for treatment. Consuming foods with added fiber had no significant effect on microbial diversity, structure of the microbiota, or the numbers of lactic acid bacteria or bifi dobacteria, but did appear to cause changes in the proportion of individuals containing specific operational taxonomical units within the microbiota In conclusion, high functional fiber intake in individuals with chronic kidney disease causes changes in t he gut microbiota however the physiological effects of these changes are not known
11 CHAPTER 1 LITERATURE REVIEW Kidney Structure and Function The kidneys are a pair of bean shaped organs located near the middle of the back, just below the ribcage, in the retroperitoneum [ 1 ] They have a number of vital functions in mammalian species. Most important is their role in maintaining homeostasis by regulating fluid and electrolyte balance. The kidneys regulate blood volume, pressure, osmolarity, and pH by filtering the blood and selectively excreting or reabsorbing fluid and solutes as they pass through the renal tubules [ 1 3 ] This absorption and excretion is regulated by the hormones aldosterone, antidiuretic hormone, and parathyroid hormone [ 1 ] These hormones act on various structures within the intricate filtration and gradient systems w ithin the kidneys and are released as a result of changes in body such as blood osmolarity, pressure, and pH [ 1 ] This system is essential for the efficient elimination of materials that are produced during the normal breakdown of nutrients and body tissues. The kidney s are composed of three distinct regions, the renal cortex, renal medulla, and renal pelvis [ 1 ] Each of these regions is structurally distinct and houses a differe nt step of the filtration process. The renal cortex is the outermost layer of the kidney, located between the renal capsule and the medulla [ 4 ] The renal cortex is the site where blood filtration begins and is the location of the blood filtration machinery. The next layer is the medulla, located just under the renal cortex. The renal medulla is responsible for m aintaining the osmolarity of the blood [ 4 ] Because the fluid in the renal medulla is hypertonic to the filtr ate, it is here that fluid moves out of the tubule and
12 reenters circulation The renal pelvis is the innermost region of the kidney where urine collects before moving to the bladder [ 4 ] Production of urine requires several complex steps that occur within units called nephrons [ 2 4 ] The nephrons are the functional unit of the kidney and its various structures run thro ugh the three regions of the kidney. There are roughly 1 million nephrons in each kidney and collectively they filter about 189 liters of blood every 24 hours [ 1 ] Filtration of the blood begins in the cortex, where blood is filtered by the [ 4 ] Blood from circulation enters a bundle of capillaries called the glomerulus via the renal artery [ 1 ] S mall molecules such as sodium, chloride, calcium, and potassium ions are pushed through the small fenestrations of the capillaries and out of circulation by blood pressure. Thes capsule, and become filtrate [ 1 ] Large molecu les such as proteins and cells cannot pass through the fenestrations of a healthy nephron and remain in circulation. Materials that the body needs, such as glucose, are reabsorbed as the filtrate passes through semi permeable tubing that composes the ren al tubule. Throughout the renal tubules [ 1 4 ] Water is also removed from the filtrate at specific l ocations by the action s of aldosterone and antidiuretic hormone. These hormones act by different mechanisms, but both function to conserve water in periods of dehydration or low blood volume [ 1 ] Chronic Kidney Disease Chronic kidney disease (CKD), or chronic renal disease, is defined as the gradual and permanent loss of renal function over months or years [ 1 4 ] There are a
13 number of potential conditions that can cause decline in kidney function. The most common are diabetes mellitus and hypertension [ 3 ] Glomerulonephritis, inherited diseases, malformations, obstructions, and repeated urinary tract infections can also lead to kidney dama ge and CKD [ 1 4 ] These conditions may cause progressive and irreversible damage to the nephrons. As nephrons are damaged, the remaining functioning nephrons adapt to maintain adequate renal function. This adaptation involves accelerated filtering, a process ca lled adaptive hyperfiltration. Initially this hyperfiltration allows individuals with CKD to maintain seemingly normal renal function, but ultimately leads to damage and loss of remaining nephrons [ 5 ] Renal function is determined by the filtering capacity of the kidney, measured as the glomerular filtration rate (GFR). This rate is used to determ ine the progression of CKD and describes the minute. The GFR can be calculated by measuring any chemical that has a steady level in the blood and is easily filtered, but not reabsorbed or secreted by the kidneys. The normal GFR range is similar in men and women and ranges from 100 130 ml/min/1.73m 2 for adults, this value is usually estimated using blood creatinine [ 6 ] In children the GFR is calculated using injected inulin clearance. CKD is classified as having a GFR of less than 60 mL/min/1.73 m 2 for three months regardless of the presence or abse nce of kidney damage [ 7 ] There are five stages of CKD marked by set ranges of GFR. Filtering capacity is diminished with each advancing stage with stage 5 being established renal failure. Stage 5 is also called end stage renal disease and is classified by a G FR of less than 15 mL/min/ 1.73 m 2 these patients do not have adequate renal capacity to maintain life and must therefore undergo dialysis and
14 potentially transplantation [6 ] Due to hyperfiltration, and other adaptive mechanisms, the symptoms of CKD may be mild until the disease is in its later stages. It is reported that symptoms are usually observed when renal capacity is only one tenth of normal [ 6 ] Symptoms may include malaise, poor concentration, anorexia, edema, itching, polyuria, and trouble sleeping or concentrating. Individuals with CKD also have an increased risk of developing hypertension. Cardiovascular events associated with CKD include angina, myocardial infarction, heart failure, stroke, and sudden death [ 8 ] The risk of these events increases with the progress ion of the disease. Longitudinal studies have shown that cardiovascular disease is the leading cause of death in elderly individuals with CKD [ 8 9 ] Uremia and Uremic R etention M olecules As renal function declines, the accumulation of unfiltered metabolites in the blood and tissues increase causing dramatic changes in blood composition. These changes are accompanie d by serious disturbances in body functions including disrupted electrolyte, mineral, and fluid balance as well as anemia, high blood pressure, acidosis, bone disease and other serious complications [ 8 10 ] These metabolites have various origins, but are collectively known as uremic retention molecules (URMs). URMs can be biochemically active, having an e ffect on bioche mical and physiologic functions [ 10 ] explained by derangements in extracellular volume, inorganic ion concentrations, or lack of [ 11 ] It is characterized by the deterior ation of biochemical and physiologic functions leading to a number of complex and variable symptoms. URMs that specifically disturb metabolic processes and lead to the uremic syndrome are known as uremic toxins and include urea, oxalic acid, parathyroid
15 ho rmone (PTH), phenols, and indoles [ 10 11 ] Uremic toxins affect nearly every organ system in the bo dy, but are especially of concern because they contribute to the cardiovascular damage associated with CKD [ 10 ] Each uremic toxin has a distinct origin, is present in different ratios, and has different effects thr oughout the body [ 12 ] URM production can have exogenous, endogenous, or bacterial origins. Exogenous URMs come from the absorption of toxins alread y present in, or created as a byproduct of the digestion or metabolic modification of food products or drugs. Exogenous URMs can be foods or materials added to foods during processing such as pr eservatives, and flavor correctors such as benzoic acid, and pennyroyal oil [ 13 ] Endogenous URMs are those that are produced during metabolic processes, usually endocrine processes [ 7 ] These endogenous URMs are created as a result of the breakdown of body tissues. The third, and often neglected source of URMs, are those that are created during the bacterial fermentation of undigested materials in the colon. These fermentation byproducts build up in the large intestine and are absorbed, contributing to the uremic condition [ 12 14 ] Changes in the intestinal flora or changes in the activity of the microbiota can therefore significantly contribute to increasing serum concentrations of many toxins. There are a number of different URMs, but phenols, indoles, and amines are the principle compounds produced by microbial fermentati on [ 11 ] Phenolic compounds such as phenol, p cresol, and phenylacetic ac id result from the partial breakdown of the amino acids tyrosine and phenylalanine by Lactobacillus, Enterobacter, Bifidobacterium, Clostridium and other obligate or facultative anaerobes. Phenolic compounds accumulate rapidly in the serum of uremic patie nts, even those undergoing dialysis [ 15 ]
16 Phenol and p cresol are usually present in the highest amounts and are associated with uremic co ma and gastrointestinal bleeding at concentrations of about 100 mol/L [ 15 ] Recent data indicates that these phenolic compounds circulate in the body as conjugates such as p cresol sulfate and p cresol glucuronide and that concentrations of these molecules in circulations can be used as a predictor of mortality in patients at different stages of chronic kidney disease [ 10 ] This correlation with morbidity may be a result of the inflammatory properties of these compounds, which contribute to cardiovascular disease, infectious complications, and other uremic symptoms, especially those of the central nervo us system [ 16 ] Indoles are protein bound compou nds that result from microbial fermentation and metabolism of tryptophan. Many enteric microbes, such as E. coli have enzymes called tryptophanases that catalyze the conversion of tryptophan to indoles. The i ndoles are absorbed, along with fluid by the co lon allowing them to enter circulation. Many indoles result from this fermen tation, but the most studied is indoxysulfate, which is conjugated in the liver. Indoxysulfate is believed to cause inflammation, renal fibrosis, and continued loss of kidney func tion [ 13 ] Studies have linked indoxysulfate to endothelial damage, inhibition of endothelial repair, and oxidative stress [ 17 ] Dietary Therapies for Chronic Kidney Disease The goals of dietary therapies for individuals with CKD are to diminish the accumulation of nitrogenous wastes, limit the metabolic disturbances c haracteristic of uremia, to prevent malnutrition, and to slow the progression of renal failure [ 7 ] Protein energy malnutrition is characteristic of CKD and is associated with an increase in mortality, due to inflammation and cardiovascular death risk [ 18 ] It is reported that 40%
17 of individuals w ith CKD are malnourished at the start of chronic hemodialysis treatment O f these individuals 20% to 60% will remain undernourished while on an established hemodialysis routine [ 7 ] Inadequate synthesis of erythropoietin, blood loss, and an iron deficient die t also makes anemia common in CKD patients [ 19 20 ] Disturbances in protein and energy metabolism, horm one levels, loss of appetite, nausea, and vomiting associated with uremia also contribute to poor nutritional status in these individuals. CKD is therefore associated with negative changes in nutritional markers such as decreased serum proteins, decreased body mass, and decreased nutrient intake [ 21 ] Despite the goals of dietary therapies, there is insufficient evidence to suggest that dietary protein restriction slows the progression of CKD [ 7 ] In general, dietary therapies at all stages of CKD involve consumption of a diet low in phosphorous, potassium, calcium, certain vitamins, minerals, and require moderate protein restriction [ 22 ] The moderate protein content of these diets effectively decreases the production of nitrogenous wastes, relieving the symptoms of uremia, but may also decrease health outcomes. Foods exc luded from these diets include dairy products, dried beans, nuts, fruit, starchy vegetables, and whole grains, which contain vital nutrients and are important for maintaining health. Limiting these foods, in addition to factors such as anorexia caused by t he uremic state, altered taste, and limited means or resources may encourage poor diet for CKD patients. The lack of consumption of adequate protein may also be a large contributor in the decline in health. Many CKD patients undergoing dialysis experience consistently low levels of serum proteins, due in part to loss of protein in the urine and through dialysis [ 9 ] This may suggest that protein restriction may be hazardous in individuals with CKD. Individuals who are not properly instructed,
18 do not follow dietary recommendations, or that do not have the means to follow such stringent regimens while maintaining variety in their diets are especially at risk of develo ping protein energy malnutrition. According to the World Health Organization, the daily recommended allowance for protein in adults is 0.8g/kg/d, the minimum daily requirement is 0.6g/kg/d many CKD diets suggest an intake near only 0.3g/kg/d [ 23 ] In heal thy individuals, such dramatic protein restriction would trigger mechanisms such as suppression of amino acid oxidation, suppression of protein degradation, and increased protein synthesis in order to maintain protein balance. Individuals with severe renal insufficiency may be unable to activate these adaptive responses due to inflammation, acidosis, and infection [ 23 ] In addi tion to limiting nutrients, restriction of the consumption of dried beans, fruits, and vegetables in CKD diets may promote low fibe r intake. Furthermore, because these high fiber foods are also naturally low in fat, low fiber diets may encourage increased fat intake [ 24 ] Fiber is the component of carbohydrate that cannot be digested by human enzymes in the small intestine. It provides structure to parts of plant cells and is therefore found mostly in fruits, vegetables, nuts, grains, and legumes [ 25 ] Because it cannot be digested in the small intestine, it is not absorbed by the body and passes through the digestive system where it can have a number of effects. The Institute of Medicine (IOM) definition of dietary fiber incl udes dietary fiber and functional fiber [ 25 ] The Adequate Intake (AI) for total fiber is 38 g/d for men and 25 g/d for women. Median intakes in the United States are significantly lower than this at only 15 g pe r day [ 26 ] Cur rently, food guidelines recommend daily consumption of beans peas, fruits, whole grains, and other foods with naturally occurring fiber [ 26 ] With strict
19 restrictions on their consumption of many of these good sources of fiber, it can be inferred that consumption of fibe r in individuals with CKD is less than adequate. Diets high in fiber are associated with lower serum cholesterol levels, lower risk of coronary heart disease, better glycemic control, reduced blood pressure, reduction in certain cancers, and greater weigh t control [ 24 27 ] In addition to these benefits, fiber may have additional properties that are specifi cally beneficial to individuals with CKD. Individuals with CKD are in an acute and chronic pro inflammatory state that contributes to mortality and morbidity [ 28 ] Studies analyzing data fro m the National Health and Nutrition Examination Survey III, have shown an association between high dietary fiber intake and significant decreases in inflammation, both in the general population and in individuals with CKD, measured by C reactive protein le vels [ 28 ] The decreas es in C reactive protein levels were also significantly different between the groups with and without CKD, with the greatest drop being in the CKD group. These studies also showed an inverse relationship between fiber intake and mortality in individuals with CKD [ 28 ] Fiber sources can be broadly grouped into one of two cate gories; dietary fiber, or functional fiber [ 25 ] Dietary fibers are intact non digestible carbohydrates and lignin that maintain the strength and structure of plants. These plant carbohydrates are most often the polysaccharides that comprise cell walls and the intercellular matrix of the plant [ 29 ] Dietary fib ers are in digestible carboh ydrate found in foods such as fruit s vegetables and beans Dietary fibers include lignin, resistant starch, cellulose, beta glucans, hemicelluloses, pectins, gums, inulin and oligofructose, and associated plant materials [ 25 ] Because they are found intact in their food sources, dietary fibers may be present
20 in low amounts in CKD diets. Functional fibers consist of non digestible carbohydrates that have been isolated and that have beneficial effects in humans [ 25 ] Because f unctional fibers are not necessarily associated with potassium and phosphate like dietary fibers, they may provide a safe alternative fiber source for individuals with CKD These fibers are extracted from intact fiber sources using a variety of techniques or may be manufactured such as in the case of synthetic resistant starches and oligosaccharides [ 29 ] The category of functional fibers is extensive and includes psyllium, fructooligosaccharides, polydextrose, resistant dextrins, and other isola ted ir synthesized fibers. Fiber can be further classified as soluble or insolubl e, viscous or non viscous, and fermentable or nonfermentable. Each of these fiber classifications exhibits different properties and physiological responses, but some are used interchangeably based on their use. The soluble v ersu s insoluble distinction is a n analytical one based on how readily a fiber disperses in water. Soluble fibers are dispersible in water, while insoluble fibers are not. Soluble fibers include beta glucans, gums, psyllium, some pectins and some hemicelluloses and can be found in the hi ghest levels in oatmeal, lentils, dried peas, beans, and certain fruits and vegetables. Insoluble fibers have a laxative effect because they hold water and bulk the feces L ignin, and some hemicelluloses are also insoluble fibers. Many soluble fibers are a lso viscous Viscous fibers are categorized by their ability to form gels when they are mixed into water. These gels form a matrix that can trap materials in the digestive tract and help reduce cholesterol levels and prevent postprandial spikes in blood su gar by slowing their digestion and absorption [ 31 32 ]
21 Fermentable fibers are those that can be ferment ed by the microbiota in the colon. These fibers are associated with a number of health benefits because their bacterial fermentation results in the formation of short chain fatty acids (SCFA). SCFAs (acetate, butyrate, and propionate) are used as an energy source for colonocytes, the epithelial cells that line the colon. Of the SCFAs produced by bacterial fermentation, butyrate is the preferred energy source for these cells. Butyrate has been shown to have beneficial effects in different colonic diseases an d may be protective against colon cancer and diverticular disease [ 33 ] Butyrate may exhibit these effects by increasing colonic blood flow, regulating colonic motility and by enhancing colonic heal ing [ 32 34 ] Of particular interest are soluble, fermentable fibers called prebiotics. A prebiotic is a nondigestible carbohydrate that beneficially affects the host by selectively stimulating the growth and, or activity of bacteria that are considered beneficial [ 27 ] In order to be categorized as a prebiotic a food material cannot be broken down or absorbed in the upper digestive tract, it must selectively be fermented by beneficial bacteria, and it must therefore help create a mo selectively enhancing the numbers of these bacteria inducing luminal or systemic effects that are beneficial to the host. [ 27 ] In most cases nearly 90% of prebiotic fibers escapes digestion in the intestines and are fermented by bacteria in the colon [ 27 35 ] Prebiotic fibers such as the inulin, and oligofructose, are naturally found in a variety of plants, such as garlic, onions, artichoke, and chicory root. M ost commercially available inulin and oligofructose is synthesized from sucrose or extracted from chicory root by hot water extraction [ 27 ] Oligofructose is obtaine d by treating inulin with hydrolytic enzymes to achieve partial hydrolysis [ 27 ] Structurally these fructooligosaccharides are
22 s hort or medium length chains that cannot be cleaved by mammalian digestive enzymes [ 24 ] Resistant starches are starches that make it al l the way through the small intestine without being degraded by human digestive enzymes. The exact amount of starch that escapes digestion is variable, dependent on factors such as transit time, enzymatic activity, and the interaction of the starch with ot her materials in the digestive tract [ 27 36 ] Like fructooligosaccharides, resistant starches are associ ated with butyrate production, but to a greater degree. Resistant starches may also improve insulin sensitivity, promote satiety, lower cholesterol, increase beneficial bacterial species, and promote bowel regularity [ 36 ] Resistant starches can be grouped into four categories RS1, RS2, RS3, and RS4. RS1 are resistant starches that are inaccessible or digestible, they are found in seeds, legumes, and whole grains that have not b een processed [ 36 ] RS2 resistant starch is granular starch that cannot be digestible by human enzymes. These starches can be found in unripe bananas, high amylose corn, and unco oked potatoes. RS3 starch is the result of cooking and cooling foods that contain resistant starches, such as rice, cornflakes, legumes, and potatoes. RS4 starches are created, or chemically modified to resist digestion [ 36 ] RS 3 and RS 4 are not digested by mammalian intestinal enzymes are largely fermented in the colon. RS 1 and RS 2 are classified as Dietary Fibers while RS 3 and RS 4 may be considered Functional Fibers [ 36 ] The Colon and Gut Microflora The large intestine has a number of important functions, with the principal function being reabsorption of fluid and electrolytes from the feces before d efecation In
23 addition, the colon also houses up to 10 14 bacteria from hundreds of different specie s [ 37 ] In healthy individuals a commensal relationship exists between the bacteria of the colon and the host [ 27 37 ] The host provides a suitable environment and fermentable substrate for these organisms and they in turn produce beneficial materials that can be absorbed and utilized by the host [ 37 ] In re ality, bacterial fermentation in the colon produces a wide range of materials that have both beneficial and harmful effects on the host The balance between the harmful and beneficial compounds produced is determined by a number of factors and can be modul ate d by a number of different factors The large intestine is approximately 150 cm long and is divided into three functional regions called the cecum, colon and the rectum [ 38 ] A steady flux of undigested material and the lar ge number of niches create a suitable environment for a complex and very active community of bacteria. These organisms are mostly obligate anaerobes from the genera Bacteroides, Fusobacterium, Eubacterium, and Bifidobacterium but others exist in high numb ers as well [ 27 39 ] Colonization of the gastrointestinal tract begins during the birth pro cess and over time the colonization pattern begins to resemble that of an adult [ 40 41 ] Factors that influ ence the bacterial species seen are the type of delivery, vaginal or via cesarean, the length of stay in the hospital after birth, whether or not the individual was breastfed and a number of other factors [ 40 41 ] Initially aerobes and facultative anaerobes predominate the colon helping to produce a highly reducing environment that facilitates the growth of s trict anaerobes [ 27 39 ]
24 vagina feces and upper gastrointestinal tract [ 39 41 ] T his process allows a mother to transfer many of the bacteria from her own microbiota to her child This can be positive in cases where the mother has a healthy flora, or detrimental in the converse case. Cesareans, use of antibiotics, and lengthy hospital stays are usually associated with pathogenic bacteria such as C. dificile [ 37 39 41 ] The length of time that it takes for the gut microflora to stabilize can also be influenced by factors such as the type of delive ry [ 40 41 ] The composition of the gut microflora differs significantly between individuals, even members o f the same family [ 42 ] A beneficial bacterial profile has been associated with the inhibition of the growth of harmful bacteria, improved digestion, synthesis of vitamins, and stimulation of immune functi ons [ 43 45 ] Negative bacterial profiles are associated with diarrhea, infections carcinogenesis, and intestinal putrefaction [ 27 37 ] The composition and activities of the colonic bacteria are affected by physiological and structural factors such as substrate avail ability, pH, O 2 levels, and the position of the bacteria in the colon [ 46 ] Physiol ogical factors, such as pH and O 2 levels are largely determined by the presence of absence of other bacteria in the colon. Though the microbiota remains relatively fixed throughout t he lifetime of an individual, slight changes in the structure of the microbiota can have significant affects [ 37 ] Wang and Gibson (1993) showed that when bifidobacteria grown on fructooligosaccharide mediums they reduce the numbers of bacteroides, clostridia, or coliforms [ 47 ] This is thought to be due to a change in the pH, which is unfavorable for these pathogenic bacteria and, potentially by the production of bactericidal substances [ 47 ] This interrelationship between bacteria is why antibiotic use is often associated with diarrhea and secondary infections [ 48 ] Elimination of
25 beneficial bacterial allows for the growth of pathogenic species that lead to illness. Additionally, t he bacteria that make up the microflora have the ability to adapt to conditions in the colon by changing metabolism, utilizing enzymes that allow them to metabolize available substr ates and outcompete other bacteria [ 11 ] Microbial Activity The bacteri a l species that comprise the gut microflora are diverse and have the ability to change their activity based on a number of environmental conditions, especially nutrient availability. Saccharolytic bacterial species preferentially ferment carbohydrates; pro teolytic bacterial species are primarily fermenters of protein [ 27 49 ] The distinction between the two groups is a result of structures or enzymes present in one group that are not present in the other. In the colon the available substrate can be quite large. Fibers, lignins, and other indigestible materials generally make it to the colon intact. Specializ ed structures outside bacterial cells that house enzymes allowing them to digest cellulose and other polysaccharides extracellularly, provide an advantage. These bacteria can then take in the smaller sugars that result and use them for their metabolism th e byproducts of their digestion can also be used by other bacteria This can also be the case with proteolytic enzymes, though proteins generally make it to the colon less intact than carbohydrates because they are degraded and denatured by mammalian pepti dases. Availability of nutrients appears to be the principle factor in determining the modulation of the metabolism of the microbiota [ 27 ] Aside from colonic mucus, fiber is the primary carbohydrate source in the colon because it is resistant to digestion by mammalian enzymes [ 49 ] Bacteria in the colon are able to use this carbohydrate as an
26 energy source, producing hydrogen, meth ane, and short chain fatty acids [ 50 ] Short chain fatty acids are considered to be beneficial to the host, and have been proven to help maintain the integrity of the colonocytes [ 51 ] Under these conditions, nitrogen sources found in the colon are used for growth an d proliferation. In the absence of sufficient carbohydrate, organisms in the colon will begin to ferment protein as an energy source. The fermentation of protein is called putrefaction, and the process requires the hydrolysis of polypeptides into small oli gopeptides and free amino acids that are then fermented and used for bacterial [ 11 ] Many of the products of bacterial fermentation of proteins are toxic such as ammonia, amines, thiols, phenols, and indoles [ 11 ] These materials can build up in the colon and be absorbed by the host, contributing to uremia in individuals with diminished kidney function [ 13 ] CKD and associated changes in dietary habits influence several of the determinants of bacterial fermentation. Despite a reduction in protein intake, the accompanying reduction in fiber intake leads to a low carbohyd rate to protein ratio [ 11 ] This shift is associated wit h increased putrefaction, increased transit time, and a greater numbers of pathogenic bacteria in the microbiota [ 11 ] All of these changes lead to more putrefaction, and the increased production of toxins. Recent research has shown that increasing intake of isolated fibers in individuals with chronic kidney disease can increas e the fecal excretion of nitrogen relative to urinary excretion [ 35 52 ] This suggests that nitrogen is b eing cleared from the blood and shunted into the feces by increased bacterial incorporation. As fiber consumption increases, so does the proliferation of the intestinal bacteria that are able to utilize these materials, increasing the need for other compou nds necessary for growth, such as nitrogen [ 51 ] This
27 nitrogen is used in the formatio n of new bacterial proteins. The acidic environment of the colon created by short chain fatty acid production may also cause the conversion of ammonia into ammonium, which is less readily reabsorbed by the body Limitations to this research are that the ac tivity of the gut microflora changes significantly in different regions of the intestines, specifically between the proximal colon, where substrate is high, and the distal colon. The sensitivity of the structure and activity of the microbiota to the availa bility of substrate may provide an important target in developing new, safer therapies for individuals suffering from chronic kidney disease. Molecular T echniques One of the greatest limitations to the s tudy of the microbiota is that many bacteria that co lonize the gut cannot be cultured by conventional methods. Selective enrichment cultures fail to provide adequate conditions for these bacteria to grow and prolifera te For some time t his made rare, slow growing, or uncultivable bacteria difficult or impos sible to identify and characterize, providing an incomplete picture of the intestinal microbiota. M olecular techniques such as polymerase chain r eaction ( PCR ) and high throughput DNA sequencing have allowed the use of 16S rRNA sequences as an effective mea ns of identifying and classifying new bacterial species [ 53 ] The 16S ribosomal RNA of prokaryotes is about 1,500 nucleotides in length and is encoded by genes called 16S rDNA.16S rDNA has highly conserved sites, which can be used for primer binding and targeted amplification of these regions in all species present within a sample using polymerase chain reaction (PCR) [ 53 54 ] C onserved sites flank highly variable regions, V1 V9, that appear to be highly similar within related organisms, specifically those of the sam e genus and species [ 54 55 ] S pecific hypervariable regions are more suited for differentiating betwe en particular types of bacteria For
28 example, Chalravorty et al. (2007) discovered that the V6 region is able to differentiate between most bacteria, except enterobacteriacea, while the V1 best differentiates between Staphylococcus aureus and coagulase neg ative staphylococcus sp p. [ 55 ] Hypervariable regions between different bacteria can therefore be compared to one another as well as to reference sequences for identification and analysis of their relatedness [ 53 54 ] A great deal of information can be gleaned using PCR followed by sequence analysis, however only qualitative information about the microbiota can be obtained using these techniques and species that are present in low numbers are not easily detected [ 53 54 ] electrophoresis (DGGE) and real time quantitative polymerase chain reaction (qPCR) have been used t o qualify and quantify differences in microbiota profiles betwee n different individuals or populations. Denaturing Gradient Gel Electrophoresis is a molecular technique that can be used to quickly compare microbiota composition between many individuals [ 56 ] This comparison is b ased on changes in the electrophoretic mobility of 16s DNA fragments as they migrate through a polyacrylamide gel containing a linear gradient of DNA denaturants, usually urea and formamide. The exact composition of the gel, the gradient, and the amount of time that the gel runs must be optimized based on the melting behavior the sequences being analyzed [ 53 54 ] As the DNA is pulled through the gel by an electric current, there is an increase in the concentration of these denaturants. The stability of these fragments of DNA is based on the strength of the bonding between base pairs present in their sequence. D ifferent fragments will therefore denature at a different concentration of denaturant, and a
29 dif ferent position within a lane. Guanine and cytosine ( GC ) base pairs exhibit more stable bonding than adenine and thymine ( AT ) base pairs allowing GC rich seque nces to migrate further in a gel before becoming denatured [ 54 ] It should be noted that other factors, such as the location of these base pairs in the fragment, also come into play in determining stability. This means that two seq uences with the same ratio of base pairs will still have different stabilities, based on the location of these bases in the sequence. In order to prevent complete dissociation of DNA strands in the gel, DNA sequences for DGGE are amplified using primers th at incorporate a GC clamp at one end of the product [ 53 54 ] The GC rich clamp is a 30 50 string of GC bas e pairs that acts as an anchor, where the fragment will splay and stop migrating, forming a band on the gel. Because fragments from different species differ in their sequence, each band will, in theory, represent a different bacterial species [ 53 54 ] Banding patterns are visualized by staining gels with dyes such as ethidium bromide, or with SYBR green 1, whi ch provides less background staining and may allow for better visualization of less pronounced bands [ 53 ] DGGE is therefore a powerful tool in the comparison o f many different samples at a single time. It is especially useful in studying the behavior of bacterial communities over a given time or as a result of different conditions, such as nutrient availability. DGGE is however limited in its ability to resolve very similar sequences, which often migrate so closely that their bands are superimposed. Vallaeys et al. showed that it is difficult or impossible to resolve 16S fragments with a very small amount of sequence variation [ 57 ] Additionally, DGGE only gives a relative idea of the numbers of the bacteria present through the intensity of the bands present. Techniques
30 such as qPCR must be utilized in order to quantify bacteria of interest in an initial sa mple. qPCR Is a method used to detect the relative or absolute abundance of specific sequence during amplification [ 58 ] While PCR uses universal primers, qPCR uses primers specific to a sequences o f interest in the genome. qPCR is one of the most widely used techniques for culture independent quantification of bacteria in the feces and has been shown to be about 10 100 fold more sensitive than culture and fluorescence in situ hybridization [ 58 ] qPCR is especially efficient when quantifying small amounts of DNA. qPCR follows the same scheme as PCR, but has the added feature of allowing DNA to be quantified in real time as it is being amplified. This is made possible by the use of dyes such as non specific dyes that stain any double stranded DNA formed or sequence specific DNA probes labeled with a fluorescent reporter that will permit detection only after hybridization [ 56 ] Initially the quantity of sample will be too low to quantify, but there will reach a point at which a threshold value is reached. Quantification of DNA is based on the number of cycles required to reach this threshold intensity, denote d C t The greater the amount of initial product, the sooner this threshold value will be reached. If it is assumed that each sequence is present in the genome in only a single copy then the copy number will approximate the number of bacterial genomes prese nt in the initial sample [ 56 ] Together, these techniques can be used to develop a good picture of the microbiota, but they are still limited. Each one of these techniques introduces a unique potential bias. Rochel le et al. demonstrated that variations in the handling of marine sediment samples, prior to DNA extraction, lead to differences in the types and the
31 diversity of sequences observed via 16S rRNA sequence analysis [ 59 ] The DNA extraction process itself can introduce bias. This occurs as a result of problems with effective disruption of all bacterial cel ls present in each sample and also with removal of inhibitors of the PCR reaction [ 54 ] PCR can be a significant source of errors as well. There may be differential or preferential amplification of genes due to template strands rea nnealing to one another, rather than annealing to primer [ 59 ] Despite the limitations of the molecu lar techniques used, analysis of the 16S rDNA appears to be an effective means of studying the microbiota.
32 CHAPTER 2 PURPOSE There are little data regarding the intakes of fiber in individuals with chronic kidney disease. These individuals may have red uced fiber intakes from whole grains, fruits, vegetables and legumes due poor appetite and dietary restrictions. Evidence suggests that increased fiber intake is associated with lowered blood urea nitrogen levels in individuals with compromised renal funct io n this may be associated with changes in the activity and composition of the microbiota. There have been no studies that use modern molecular tools to assess the changes in the microbiota as a result of fiber supplementation in individuals with chronic kidney disease. The overall objective of this study is to use these molecular tools to determine whether increasing intake of functional fiber in individuals with chronic kidney disease will lead to an increase in bacteria associated with health benefits specifically lactic acid bacteria and bifidobacteria. We also wanted to determine what overall changes in diversity and composition would occur in these individuals as a result of increased functional fiber consumption.
33 CHAPTER 3 METHODS Study Design A six week, single blind, crossover study was carried out with 14 adults having a mean age of 64.8 + 14.7 years all having chronic kidney disease. The study took part in two phases; a two week control period, followed by a four week treatment period. Partici pants were provided 4 servings/d of commercially available food products containing low fiber during the control period, and containing added fiber during the treatment period. These foods were removed from their packaging and repackaged to prevent identif ication by study participants. Study foods included snack bars, cookies, and cereal containing added fiber and no added fiber. High f iber and low fiber foods were matched as closely as possible in taste and appearance. Participants provided two fecal sampl es throughout the study, during the second and sixth weeks of the study. C ompliance was measured using daily diaries and confirmed by weighing leftover food returned upon completion of the study. Approval was obtained from the Institutional Review Board at the University of Florida, IRB 01. Informed consent was obtained from all the study participants. Inclusion/ Exclusion Criteria after Obtaining Consent Participants were included if they were 18 years of age and had chronic kidney disease, but were not on dialysis, and were willing to consume four different study foods each day for six weeks. Participants were excluded if they i) had been diagnosed with acute kidney injury, glomerulonephritis, or acute renal failure (ARF) over the past 3 months. ii) were s cheduled to have a renal transplant or dialysis within 3 months of the study initiation, had a history of liver disease, dialysis, or had undergone renal
34 transplantation. ii) were on motility stimulating drugs, steroids, immunosuppressant medication, or we re unwilling to discontinue taking any prebiotics, fiber supplements, or laxatives iv) were pregnant, lactating, or had active gastrointestinal bleeding. Pre Baseline and Baseline During the first study visit, participants were given a two week supply of study food, and were taught to use the stool collection apparatus. Study food was packaged in plastic bags labeled with the day that food should be consumed. Participants were asked to return any leftover food in these plastic bags during their next study visit. Participants were also given a small Styrofoam cooler containing a stool collection kit and instructions for its use. Study personnel then gave a brief tutorial to each study participant, demonstrating how to assemble and use the kit. Participants were asked to call the study coordinator as soon as possible after providing a sample so that study personnel could retrieve it within four hours of defecation. Participants were informed that all samples should be kept on ice, but not frozen while waiting for pickup. During the first few days of the second week of the study, study coordinators made reminder calls to all participants asking that they provide a sample within the last three days of that week. This procedure was repeated for the treatment feca l samples. Participants were given anoth er brief orientation during their penultimate study visit reminding them how to use the stool collection apparatus. Participants were also called during the early part of week six, reminding them to provide a fecal sample at the end of that week. All samples were collected, homogenized, put into three separate tubes, and frozen at 70 C within 6 hours of defecation.
35 Treatment Study participants were asked to consume two small cookies, a cereal bar, and two servings o f cereal each day During the intervention period study foods provided 23 grams per day of functional fiber, pea hull, inulin, and soluble corn fiber. During both the control and intervention weeks, food was packaged and labeled by date, to control serving size and prevent confusion. At each study visit, every two weeks starting at baseline, participants were provided with a two week supply of packaged food. During Corn Pops Publix Chocolate chip cookies, Special K bars. Each of these foods provided less than 1 gram with fiber Weight Watchers chocolate chip cookies, and Fiber One bars The f iber sources in each of the st udy foods can be found in tables 3 1 and 3 2 and the nutrient in each serving can be found in tables 3 3 a nd 3 4. Each day participants filled out surveys of compliance, listing which foods were consumed or omitted. Participants were also asked to return a ny food that was not consumed, as a check of self reported compliance. Study personnel called all study participants weekly to maintain contact, even during weeks between study visits. Daily and Weekly Measures Participants were given daily diaries in wh ich they answered brief questions about compliance and gastrointestinal symptoms. Participants were also asked to report their food intake for three days, four times throughout the study period. Daily diaries had perforated pages to allow participants to l eave pages with study personnel during each visit.
36 Collection and Processing of Fecal Samples Collection of two full defecations for microbial analysis occurred during the second and sixth weeks of the study. Samples were collected at home by study partic ipants using a stool collection apparatus provided to them during their study visit. Samples were stored in a cooler of ice until processing. Study personnel retrieved and processed samples within six hours of defecation in order to ensure that handling of all samples was as standardized as possible. Prior to freezing, all samples were homogenized thoroughly. After processing, samples were frozen at 70 C until analysis. Microbiota Analys e s Bacterial DNA was extracted from 200 300 mg fecal samples using a Quiagen stool DNA extraction kit. The protocol was modified to include a three minute bead beating step. PCR using universal primers was then used to amplify a 457 bp fragment from the V6 to V8 hypervariable region of the 16S ribosomal DNA. The PCR product was then analyzed by denaturing gradient gel electrophoresis, using an 8% (weight/volume) polyacrylamide gel with a denaturing gradient that increased from 40% at the top of the gel to 50% at the bottom ( A 100% denaturing solution contain s 40% (vol/vol) f ormamide and 7 M urea. ). Samples were run at a constant voltage of 65 volts for 960 minutes at 60 o C. Gels were then stained with SYBR Gold and were scanned with Quantity One then analyzed with Diversity Database software. Diversity of the bacterial popu lations, a measure of species richness and composition, was determined from DGGE analysis using the Shannon Wiener and Inverse Simpson diversity indices. Diversity indices increase when the number of
37 species in a population increases reach ing maximum valu es when all of the species within a population have the same number of individuals. Bifidobacterium spp. genus, and Lactobacillus spp genus were quantified using quantitative real time polymerase chain reaction (qPCR). Specific primers for Bifidobacteriu m spp. genus and Lactobacillus spp genus were used qPCR analysis was performed in duplicate and 0.2 M primers. qPCR conditions used were: 10 min at 95C followed by 40 cycles of 95C for 30 s, annealing for 1 min and extension at 72C for 30 s. Proportio ns of lactic acid and bifidobacteria were obtained by dividing the number positive for the primer by the total number of bacteria, obtained using the universal V3 primer set. Lastly, DNA was amplified for sequencing using barcoded primers. PCR products wer e cleaned, pooled into equimolar amounts and submitted for sequencing. The resultant sequences were analyzed using the Ribosomal Database Project (RDP). Sequences were then grouped, or binned into operational taxonomic units (OTUs) by degrees of similarit y. Using this binned sequence data, the structure and the diversity of the microbiota were analyzed using microbial ecology tools available in the Quantitative insights into M icrobial E cology (QIME) package. Statistics A paired t test was used to calculate means and variation and for establishing two sided significance levels (p < 0.05). The QIME package was used to calculate p values for differences in UniFrac distances.
38 Figure 3 1 Study timeline
39 Table 3 1. Content and source of fibers in f oods prov ided during weeks 1 and 2 Food Servings Provided Fiber Content Fiber source Corn Pops 2 0g N/A Publix Chocolate Chip Cookies 2 0g N/A Special K Bars 1 <1g N/A Table 3 2 Content and source of fiber in f oods Provided dur ing weeks 3,4, and 5 Food Servings Provided Fiber Content Fiber source Kelloggs Corn Pops with Fiber 2 3g Corn dextrin Weight Watchers Chocolate Chip Cookies 2 4g Pea hull fiber Fiber One bars 1 9g Chicory root Table 3 3 Nutrient per serving for control foods Food Calories Total fat Protein C arbohydrate Corn Pops 110 0g 1g 26g Publix Chocolate Chip Cookies 110 4g <1g 8.5g Special K Bars 90 1.5g 1g 17g Table 3 4 Nutrient per servi ng for treatment foods Food Calories Total fat Protein C arbohydrate Kelloggs Corn Pops with Fiber 120 0g 1g 29g Weight Watchers Chocolate Chip Cookies 180 5g 2g 18g Fiber One bars 140 4g 2g 29g
40 CHAPTER 4 RESULTS Subject D em ographics and Characteristics From a n unknown population of individuals with chronic kidney disease being treated at Shands hospital in Gainesville, Florida 270 were screened, 203 did not fit the inclusion criteria or declined contact. The 67 remaining i ndividuals were contacted and 50 were excluded with secondary exclusion criteria or declined participation. Ultimately, 17 individuals were consented, and enrolled in the study but only 14 provided the two fecal samples necessary for analysis. The other t wo were unable to produce samples within the necessary time frame and were therefore excluded. Of these 14 study participants, 9 were female and 6 were male; their mean age was 64.8 + 17.4 In the preliminary surveys, 11 participants reported white as their race, 7 of which non Hispanic. The remaining 3 participants identified as black and non Hispanic. Seven of the 14 participants who completed the study also had diabetes. Compliance was measured using self reported information from daily diaries and also fr om the measure of leftover food returned by participants at each study visit. Compliance was 83% for the control period, and 78% for the treatment period. Self reported data from 3 day food records filled out by participants throughout the study (data not included) indicated that mean fiber intake increased from 11.83.2 to 22.47.0 g/d (p<0.001) with no change in energy or protein intake. Diversity and Structure of the Microbiota from DGGE Comparisons of the baseline and treatment samples by qualitative DGGE profiling revealed that there were no significant changes in diversity between the two time points, as measured by the mean Shannon Wiener diversity and inverse Simpson
41 Indices ( Table 4 2 ). The average Shannon index for baseline samples, taken just pr ior to fiber supplementation, was 2.71 with a range of 2.48 to 2.94 while the average Shannon index at week six, after four weeks of consumption of fiber foods, was 2.64, with a range of 2.00 to 3.09. The p value for the t test between these two averages w as 0.44, indicating no significant difference. Next, the average inverse Simpson Index was calculated for baseline and treatment samples. The average inverse Simpson index at baseline was 13.6 with a range of 11.9 to 18.7, while the value at treatment was 14.3 with a range of 9.9 to 27.7. This also showed no significance, with a t test p value of 0.611. The dendrogram in F igure 4 2 is a graphical representation of the similarity coefficients between individuals. These values are obtained using software tha t measures the number and intensity of DGGE bands for each individual before and after treatment. Individuals with fewer nodes and shorter branch lengths between them are considered more closely related. Overall t he dendrogram does not show a strong group ing of participants based on treatment group. While some p articipants are more closely related to themselves before and after treatment than they are to participants of the same treatment group others seem to differ significantly, making the results incon clusive. Analysis of Bifido bacteria and Lactic Acid Bacteria qPCR analysis at the two time points revealed that the mean number of genome equivalents at baseline was 63,100, while at treatment it was 127,682 Figure 4 5 The t test p value for this chan ge did not reach significance (p = 0.36). The mean genome equivalents for the lactic acid bacteria decreased from 169 000 to 31 722 from baseline
42 to treatment (Figure 4 6 ) but also failed to reach significance with a t test p value of 0.39. These values w ere standardized against the total number of sequences to get the mean proportions of baseline genome equivalents. The Baseline mean proportions of genome equivalents for the bifidobacteria increased from 0.03 to 0.07 and also failed to reach significance (p = 0.29). Mean proportions of genome equivalents for lactic acid bacteria decreased from 0.035 to 0.013 (p = 0.39). These results indicate that there was no significant change in the lactic acid bacteria or bifidobacteria due to treatment. Des pite the lack of overall significance, 6 of our 14 study participant s experienced a notable increase in the mean genome equivalents for Bifidobacteria due to fiber intervention defined as a two or greater fold change Of the remaining 8 study participants 6 experienced a notable decrease in the Bifidobacteria genome equivalents and two experienced no change Eight of the study participants experienced a notable increase in the genome equivalence of lactic acid bacteria, and 3 experienced a decrease. Three of the study participants experienced no change in lactic acid bacteria Figure 4 3 and Figure 4 4 show the individual average genome equivalents for bifidobacteria and lactic acid respectively. Diversity and Structure from Sequence Analysis The total n umbers of OTUs present as estimated using Chao1 based diversity plot curves did not differ between control and treatment time points shown in Fig 4 7 This can be seen by the overlap of the two curves, indicating that diversity was not significantly dif ferent between the two time points. Further analysis was done using the unique fraction metric (UniFrac) which computes differences between microbial communities based on phylogenetic differences between them, identified from 16S
43 sequences. This analysis a lso detected no change in diversity between the two time points. Based on the clustering and distribution of the control and treatment samples in principal component analysis In Fig 4 6 it can be seen that populations do not appear to differentiate based on intervention. Comparison of the distribution of OTUs between control and treatment samples revealed no trend in the change in the structure due to treatmen t. F igure 4 5 it indicates that there were however changes in the proportions of participants po ssessing specific OTUs
44 Figure 4 1 Flow chart of subject recruitment Table 4 1. Mean fiber intake by fiber type (g/d) Corn dextrin Pea hull fiber Fructooligosaccharide 3.8 6.2 7.0 Table 4 2 Average diversity of control and treatment s amples measured by the Shannon index and inverse Simpson indices and their t test p values. Statistical test Control Treatment t test p value Average Shannon index 2.71 2.64 0.44 Average inverse Simpson index 13.63 14.29 0.61
45 Figure 4 2 Dendrogram showing diversity based on DGGE analysis. C denotes control period and T denotes treatment, with the number corresponding to subject number. The similarity of samples is determined by the number of nodes between them and branch length, with fewer nodes signifying more similar diversity values.
46 Figure 4 3 Mean Bifidobacteria genome equivalents in baseline and treatment samples Figure 4 4 Mean l actic acid bacteria genome equivalents in baseline and treatment samples 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05 1.E+06 1 2 3 4 5 7 8 9 10 11 12 13 16 17 Average Genome Equivalents Subject Number Baseline Treatment 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05 1.E+06 1.E+07 1 2 3 4 5 7 8 9 10 11 12 13 16 17 Average Genome Equivalents Subject Number Baseline Treatment
47 Figure 4 5 Average genome equivalents for bifidobacteria in baseline and treatment samples as measured by qPCR analysis. Figure 4 6 Average genome equival ents for lactic acid bacteria in baseline and treatment samples as measured by qPCR analysis. Baseline 63100 Treatment 127682 0 20000 40000 60000 80000 100000 120000 140000 Average Genome Equivalents Baseline 169000 Treatment 31,722 0 20000 40000 60000 80000 100000 120000 140000 160000 180000 Average Genome Equivalents
48 A B Figure 4 7 Differences in OTU abundance. Heat map of the top ranked OTUs for the 95% a) and 98% b) Rows denote subject number and columns denote OTUs, labeled with taxonomical abbreviations and percentage that the representative sequence matches to a database reference sequence Colored squares denote the number of sequences within each bin separated by subject and time point. B denotes before fi ber and A denotes after.
49 Figure 4 8 Unifrac diversity measures. Principal component analysis (PCA) of overall diversity based on Unifrac metric after fiber intervention. Blue circles represent baseline samples and red squares represent treatment sample s.
50 Figure 4 9 Chao diversity plot Chao diversity was calculated from sequence distribution after 4 weeks of fiber intervention. Blue line represents baseline diversity and the green line indicates diversity for treatment samples.
51 CHAPTER 5 CON CLUSION AND DISCUSSI ON In this study, individuals with CKD consume d an average of 16.5 grams /d of functional fiber in commercially available food products for 4 weeks. Fecal samples were taken for microbiota a nalysis at baseline and at the end of the 4 we ek intervention period. As expected, average fiber consumption at baseline was lower than recommendations in thi s population. B ased on self reported data t otal fiber I ntake increased significantly in these individuals during the treatment period from 11.8 + 3.2 to 22.4 + 7g/d (p<0.001) This change was not associated with changes i n the consumption of energy or protein. Despite the significant increase in fiber intake in our study participants, the richness and distribution of the species in their microbi ota did not change. This was measured both by DGGE and DNA sequence analysis. Inc reased functional fiber intake also had no significant impact on the overall levels of lactic acid bacteria or bifido bacteria in our study population as measured by qPCR anal ysis. Despite these overall negative results, there were changes in the proportions of participants possessing specific OTUs as a result of fiber intake These ch anges could not be characterized into intervention specific changes and did not include bacter ia that are well known for their beneficial or detrimental properties Study participants also experienced changes in bifidobacteria and lactic acid bacteria genome equivalents as a result of fiber intervention While some participants experienced increas es in mean genome equivalents of lactic acid bacteria and bifido bacteria others experienced decreases. There was no overall change seen across all study participants and changes across individuals did not appear to be related to the
52 significant decrease s i n BUN seen in the larger study by Salmean et al. Small sample size may have prevented accurate analysis of the correlation between changes in g enome equivalents for these bacteria and changes in blood urea nitrogen levels. When considering these findings it is important to keep in mind that the microbiota is not well understood and that the relationship between changes in the microbiota and dietary intake is both complex and dynamic. Our results may also have been complicated by a number of issues with t he study design. Issues with fiber sources, compliance, and the limitations of the molecular tools used may limit our analysis. One of the major complicating factor s in the analysis of these findings was the use of multiple fiber sources. Different fibers can selectively enhance the growth of particu lar bacteria in the microflora. O ligo fructose derived from chicory root present in the Fiber O ne bars, selectively stimulates the growth and activity of bifidobacteria Corn dextrin, present in the Kellogg s Corn Pops would be expected to stimulate lactic acid bacteria growth The insoluble pea hull fiber present in the Weight Watchers Chocolate Chip C ookies is thought to be resistant to fermentation by the microbiota, but may decrease transit time, which ma y impact fermentation Examina tion of the compliance of each individual f iber provided during the treatment periods reveals that compliance was not uniform for all fiber sources. Average consumption of corn dextrin was only 3.8 g/d, likely insufficient t o cause a significant increase in lactic acid bacteria. Alternatively, c onsumption of fructooligosaccharide and pea hull fiber was 7 and 6 g/d respectively. In a study by Bouhnik et al it was shown that the ideal oligofructose consumption for increased bif idobacteria coun ts, without side effects was 10 grams per day [ 60 ] The d ifferences in compliance between the different
53 fiber sources may be attributed to vol ume of food that was provided to study participants for daily consumption. Issues with appetite and changes in taste are common in the later stages of CKD. This may have made it difficult for our participants to fit the required servings of food into thei r diet. The length of the study, which was prolonged by the two week control period, may have also caused fatigue as our study food stayed relatively consistent for the entire 6 weeks of the study Additionally, restrictions on dairy product consumption fo r individuals with chronic kidney disease requires the use of milk alternatives that may be displeasing in taste, perhaps adding to poor cereal compliance R ice milk was provided during this study though all study participants did not use it Half of the study participants had a diagnosis of diabetes making it difficult to fit carbohydrate rich foods into their already limited diet. Furthermore, the molecular techniques used in this study do not measure changes in microbial activity. This limits our view of the changes in the microbiota to presence or absence of bacterial sequences, exclusively. This is an important concept because metabolism in the colon is dependent on multiple bacterial species working with a number of saccharolytic enzymes. B acteria c an be classified as primary fermenters of carbohydrate or protein, but in reality their activity will vary based on available substrate. This makes categorizing bacteria as beneficial or detrimental largely speculative. This study shows that the microbiot a of individuals with chronic kidney can be changed with increased fiber consumption. However, the provision of mixed fiber sources, limited number of fecal samples collected, and issues with compliance make it difficult to characterize these changes. Futu re research should be done with this
54 population to determine how a single fiber source may impact the microbiota, and to determine whether a disease specific CKD microbiota profile exists.
55 APPENDIX A DOCUMENTS SUBMITTED TO THE IRB I NFORMED C ONSENT F ORM to Participate in Research, and A UTHORIZATION to Collect, Use, and Disclose Protected Health Information (PHI) I NTRODUCTION Name of person seeking your consent: Place of employment and position: This is a research study of: the effects of fiber intake on gastrointestinal symptoms and quality of life in individuals with chronic kidney disease. Could participating in this study offer any direct benefits to you? Yes as described on page 5 Could participating cause you any discomforts or are there any risks to you? Yes as described on pag e 4 Please read this form which describes the study in some detail. I or one of my co workers will also describe this study to you and answer all of your questions. Your participation is entirely voluntary If you choose to participate you can change y our mind at any time and withdraw from the study. Y ou will not be penalized in any way or lose any benefits to which you would otherwise be entitled i f you choose not to participate in this study or to withdraw If you have questions about your rights as a research subject, please call the University of Florida Institutional Review Board (IRB) office at (352) 846 1494. If you decide to take part in this study, please sign this form on page 10. G ENERAL I NFORMATION ABOUT THI S S TUDY 1. Name of Participan t ("Study Subject") ___________________________________________________________________ 2. What is the Title of this research study ?
56 An investigation into pulse fibre fermentation and nitrogen excretion in patients with chronic renal failure. 3. Who do you cal l if you have questions about this rese arch study? Dr. Wendy Dahl Dr. Bobbi Langkamp Henken work: 352 392 1991 ext. 224 work: 352 392 1991 ext. 205 cell: 352 226 1773 cell: 352 642 3669 home: 352 374 7798 home: 352 372 5434 email: email@example.com email: firstname.lastname@example.org 4. Who is paying for this research study? The sponsor of this stu dy is Saskatche wan Pulse Growers, a Canadian commodity organization that promotes the sale of Saskatchewan (Canada) grown beans, peas and lentils. 5. Why is this research study being done ? The purpose of this research study is to determine if consuming fiber fortified baked goo ds and cereal will improve the quality of life, gastrointestinal symptoms, appetite, blood values and other outcomes in individuals with chronic kidney disease. You are being asked to be in this research study because you are a chronic kidney disease patie W HAT C AN YOU E XPECT IF YOU P ARTICIPATE IN THIS S TUDY ? 6. What w ill be done as part of your normal clinical care (even if you did not participate in this research study )? This study is not related to your normal clinical care. Your nephrologist will not be informed that you are taking part in this study. 7. What will be done only because you are in this research study ? If you decide to take part in this study, you will be rand omly assigned (much like the flip of a coin) to receive either baked goods and cereal fortified with fiber (experimental foods) or baked goods and cereal without fiber fortification (control foods). All participants will consume the unfortified foods for a two week baseline period. The control is a food that looks similar and is given in the same way as an experimental food but contains no fiber fortification. A control is used in nutrition research studies to show what effect a treatment has compared with taking nothing at all. If you are assigned to receive the control you will not receive the b enefits of the fiber fortified foods but will still receive similar nutrients and calories found in regular baked goods and cereal. Both groups are exposed to th e same risks, which are described below under "What are the possible discomforts and risks?" Y ou will not be told whether you are receiv ing control (regular baked goods and cereal) or the fiber fortified foods, but that information is available if it is n eeded. Also, y ou will have a 50% chance of receiv ing the control foods and a 50% chance of receiving the fiber fortified foods In the remainder of the description of what will be done, both the control and the fiber fortified foods will be called "study f oods
57 1. At the beginning of the study, you will have a study visit to the Food Science and Human Nutrition Clinical lab at the Food Science Human Nutrition building at the University of Florida. You will be asked to return for a study visit in weeks 2, 4 an d the final week, week 6. During each study visit: 2. A licensed phlebotomist will obtain 2 tsp. venous blood from you for assessment of BUN (blood urea nitrogen a measurement of nitrogen wastes in your blood), creatinine (a measurement of kidney function), fasting blood glucose (blood sugar), and a cholesterol profile. This component of the study will take approximately 15 minutes to complete. You are required to fast a minimum of 6 hours prior to the blood draw and it is preferable if you fast overnight. T he blood draw will take place in the blood draw room of the Food Science and Human Nutrition Clinical Laboratory 3. You will be asked to complete three questionnaires. A Simplified Nutritional Appetite Questionnaire (SNAQ), GSRS (Gastrointestinal Symptom Que Your Health and Well Being 36) 4. Body weight and height will be assessed on the first day of the study and at your final study visit. These procedures will take le ss than 10 minutes. 5. You will be given and aske d to consume 3 5 servings of these foods e ach day for 6 weeks. At home: 6. You will be given a study diary and asked to answer questions about medication, intake of the stu dy foods and gastrointestinal function each day You will also receive pre dated bags to safe any left over study foods. 7. You will be asked to complete a 3 day food record in week 1 of the study and during week 6 of the study. 8. A study coordinator will visit you at your home during week 2, 3 and 5 of the questionnaire. Study coordinator will also pick up any left over study foods. 9. During week 1 and week 6, you will be asked to colle ct two stool samples each week. You will be provided with a collection container specially designed for stool collections. When collection is made, you will be required to call the study cell phone and a laboratory technician will pick up your sample from your home. If you have any questions now or at any time during the study, please contact
58 day. Total study time, not including travel to and from study visits is expected to be less than 20 hrs not including time taken to consume study foods. 9 How many people are expected to take part in this research study ? Twenty people will be participating in this research study W HAT ARE THE R ISKS AND B ENEFITS OF TH IS S TUDY AND W HAT ARE Y OUR O PTIONS ? 10 What are the possible discomforts and risks from taking part in this research study ? The risks of drawing blood from a vein include discomfort at the site of puncture; possible bruising and swelling around the pu ncture site; rarely an infection; and, uncommonly, faintness from the procedure. An overnight fast is required and may cause physical discomfort. Some people may feel uncomfortable when body weight is measured. Certain questions on the questionnaires may be personal and thus, may be upsetting. You may choose not to answer any of the questions. Consuming fiber fortified foods may result in bloating, gas (flatulence) and abdominal discomfort. Other p ossible risks to you may include: This study may include risks that are unknown at this time. Participation in more than one research study or project may further increase the risks to you. If you are already enrolled in another research study, p lease inform
59 11c. How could the researchers benefit from this study? In general, presenting research results helps the career of a scientist. Therefore,
60 If you are paid for taking part in this study, your name and social security number will be reported to the appropriate University employees for purposes of making and recording the payment. You are responsible for paying income taxes on any payments provided by the study. If the payments total $600 or more, the University must report the amount you received to the Internal Revenue Service (IRS). 1 6 What if you are injured because of the study? If you are injured as a direct result of your participation in this study, the Sponsor will pay for all reasonable and necessary medical expenses required to treat your injury, as long as: 1. The injury occurs during the study and results di rectly from the Study related procedures which you would not have received as part of your routine medical care; 2. The injury is not listed in question 10 above; 3. The injury is not the result of the natural course of your disease or some other underlying con dition and; 4. Your insurance company denies payment for the medical services. The Sponsor and the Principle Investigator will determine whether your injury is related to your participation in this study. The Principle Investigator and others involved in this study may be University of Florida employees. As employees of the university, they are protected under state law, which limits financial recovery for negligence. Please contact the Principal Investigator listed in question 3 of this form if you experience an injury or have questions about any discomforts that you experience while participating in this study. 17. How will your health informati on be collected, used and shared? If you agree to participate in this study, the Principal Investigator will create, collect, and use private information about you and your health This information is called protected health information or PHI In order to do this, the Principal Investigator needs your authorization. The following section describes what PHI will be collected, used and shared, how it will be collected, used, and shared, who will collect, use or share it, who will have access to it, how it w ill be secured, and what your rights are to revoke this authorization. Your protected health information may be collected, used, and shared with others to determine if you can participate in the study, and then as part of yo ur participation in the study. This information can be gathered from you or your past, current or future health records, from procedures such as physical examinations, x rays, blood or urine tests or f rom other procedures or tests. This information will be created by receiving study tr eatments or participating in study procedures, or from your study visits and telephone calls. More specifically, the following information may be collected, used, and shared with others: Your social security number for compensation purposes
61 Bo dy weight, height age, sex, race and ethnicity Blood urea nitrogen, creatinine, fasting blood glucose, cholesterol profile Dietary intake Gastrointestinal function and symptoms Stool microbiota data A Simplified Nutritional Appetite Questionnaire (SNAQ) GSRS (Gastrointestinal Symptom Questionnaire Your Health and Well Being Kidney Disease and Quality of Life 36). This informatio n will be stored in locked filing cabinets or on computer servers with secure passwords, or encrypted electronic storage devices. S ome of the information collected could be included in a "limited data set" to be use d for other research purposes. If so, th e limited data set will only include information that does not directly identify you. For example, the limited data set cannot include your name, address, telephone number, social security number, photographs, or other codes that link you to the informatio n in the limited data set. If limited data sets are created and used, agreements between the parties creating and receiving the limited data set are required in order to protect your identity and confidentiality and privacy. 18. For what study related pur poses will your protected health information be collected, used, and shared with others? Your PHI may be collected, used, and shared with others to make sure you can participate in the research, through your participation in the research, and to evaluate the results of the research study. More specifically, your PHI may be collected, used, and shared with others for the following study related purpose(s): to examine the effects of consuming fiber fortification on quality of life and wellness of individual s with chronic kidney disease. Once this information is collected, it becomes part of the research record for this study. 19. Who will be allowed to collect, use, and share your protected health information? Only certain people have the legal right to collect, use and share your research records, and they will protect the privacy and security of these records to the extent the law a llows. These people include the: the study Principal Investigator s,
62 United States and foreign governmental agencies who are responsible for overseeing research, such as the Food and Drug Ad ministration, the Department of Health and Human Services, and the Office of Human Research Protections Government agencies who are responsible for overseeing public health concerns such as the Centers for Disease Control and f ederal, s tate and local heal th departments Otherwise, your research records will not be released without your permission unless required by law or a court order. It is possible that once this information is shared with authorized persons, it could be shared by the persons or agencies who receive it and it would no longer be prote cted by the federal medical privacy law. 21. If you agree to take part in this research study, how long will your protected health information be used and shared with others? Your PHI will be used and shared with others for one year following the com pletion of the study. You are not required to sign this consent and authorization or allow researchers to collect, use and share your PHI. Y our refusal to sign will not affect your treatment, payment, enrollment, or eli gibility for any benefits outside this research study. However, you cannot participate in this research unless you allow the collection, use and sharing of your protected health information by signing this consen t and authorization. You have the right to r eview and copy your protected health information. However, we can make this available only after the study is finished. You can revoke your authorization at any time before, during, or after your participation in th is study. If you revoke it no new infor mation will be collected about you. However, information that was already collected may still be used and shared with others if the researchers have relied on it to complete the research. You can revoke your authorization by giving a written request with your signature on it to the Principal Investigator.
63 S IGNATURES As a representative I have explained to the participant the purpose, th e procedures, the possible benefits, and the risks of this research study; the alternative information will be collected, used, and shared with others: Signature of Person Obtaining Consent and Authorization Date risks; the alternatives to being in the study; and how your protected health information will be collected, used and shared with othe rs. You have received a copy of this Form. You have been given the opportunity to ask questions before you sign, and you have been told that you can ask questions at any time. You voluntarily agree to participate in this study. You hereby authorize the collection, use and sharing of your protected health information as described in section s 17 21 above. By signing this form, you are not waiving any of your legal rights. Signature of Person Consenting and Authorizing Date
64 Appendix A Daily Diary Date:_________________ Study #___________ 1. How many bowel movements did you have today? 0 1 2 3 4 5 >6 2. Did you experience diarrhea today? yes no 3. Did you take laxative today? yes no 4. Are you currently taki ng antibiotics? yes no 5. Did your medication change? yes no 6. How many servings of study foods did you consume today? 0 1 2 3 4 5 >6 g 7. Did you consume a fiber supplement today? If so, what did you take?
65 Telephone Script Hello, my name is___________ with the fiber study. (Potential participant indicates they are calling about the study) G reat. I would be happy to give you more information about the study. The purpose of this study is to determine whether the providing adequate fiber to patients with CKD will result in improved gastrointestinal function and quality of life. If you qualify and decide to participate, you will be randomly assigned to a treatment or control group, but you will not be told which group you ar e in until completion of the study. Both groups will be given cookies, cereal bars and breakfast cereal and to consume daily for a period of 6 weeks (42 days), with the treatment group receiving high fiber food. During the course of the study you would b e asked to come in our clinical lab on four separate occasions to have your blood drawn and fill out questionnaires. These appointments should take no more than an hour. The questionnaires will ask questions regarding your quality of life, appetite, and gastrointestinal symptoms. Participants will also be asked to provide three stool samples during the study. Foods provided to participants provide nutrients and energy to all participants. Individuals selected for the fiber fortification group may expe rience improved gastrointestinal function and quality of life due to the fiber Does this sound like something you would be interested in doing? (Responds Yes) Great, now I will read the inclusion/exclusion criteria for the study to make sure you qualify. Please wait until I finish reading through this list, then you can let me know if you are still interested. (Read inclusion/exclusion criteria without pausing) Does this still sound like something you would like to take part in? (Responds Yes) Great, th en we can schedule an initial appointment for you to receive more detailed information on the study and review a consent form. Is there a date and time that works best for you? (Schedule appointment and obtain best way to contact patient)
66 Inclusion Cri teria Participants Must: Be 18 years of age or older H ave GFR of 29 mL/min/1.73 m 2 (stage 4 and 5 but who are not on dialysis) Exclusion Criteria Have you been diagnosed wi th acute kidney injury (AKI) Have you been diagnosed with glumerulonephritis (GN) ? Are you on immunosuppressant /steroid medications ? Are you taking a probiotic supplement and refuse to discontinue it? Are you scheduled for dialysis within 3 months of study initiation? Do you have a history of liver disease? Have you been on dialysis ? H ave you undergone renal transplantation? Are you breastfeeding? Do you have active gastrointestinal bleeding ? Have a change in medications over the past 4 weeks ? part in the study. Are you still interested in taking part in the study?
67 LIST OF REFERENCES 1. Smith H: The Kidney: Structure and Function in Health and Disease Oxford medical publications 1951. 2. Avner E, Harmon W, Niaudet P, Yoshi kawa N: Pediatric Nephrology Springer Verlag Berlin Heidelberg 2009. 3. Cummings DM, Larsen LC, Doherty L, Lea CS, Holbert D: Glycemic control patterns and kidney disease progression among primary care patients with diabetes mellitus J Am Board Fam Med 2 011, 24 (4):391 398. 4. Vize PD: The kidney: from normal development to congentital disease Orlando: Academic Press 2003. 5. Brenner BM, Lawler EV, Mackenzie HS: The hyperfiltration theory: a paradigm shift in nephrology Kidney Int 1996, 49 (6):1774 1777 6. K/DOQI clinical practice guidelines for bone metabolism and disease in chronic kidney disease Am J Kidney Dis 2003, 42 (4 Suppl 3):S1 201. 7. Wilcox C, Berl T, Himmerlfarb J, Murphy B, Salant D, Yu A, Druml W, Mitch W: Nutritional Management of Acut e Renal Failure In: Therapy in nephrology and hypertension: A companion to Brenner and Rector's The Kidney, Third Edition. Saunders Elsevier 2008: 96 106. 8. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY: Chronic kidney disease and the risks of death, ca rdiovascular events, and hospitalization N Engl J Med 2004, 351 (13):1296 1305. 9. Keith DS, Nichols GA, Gullion CM, Brown JB, Smith DH: Longitudinal follow up and outcomes among a population with chronic kidney disease in a large managed care organizatio n Arch Intern Med 2004, 164 (6):659 663. 10. Vanholder R, Van Laecke S, Glorieux G: What is new in uremic toxicity? Pediatr Nephrol 2008, 23 (8):1211 1221. 11. Evenepoel P, Meijers BK, Bammens BR, Verbeke K: Uremic toxins originating from colonic microbia l metabolism Kidney Int Suppl 2009(114):S12 19. 12. Vanholder R, De Smet R: Pathophysiologic effects of uremic retention solutes J Am Soc Nephrol 1999, 10 (8):1815 1823. 13. Schepers E, Glorieux G, Vanholder R: The gut: the forgotten organ in uremia? Bl ood Purif 2010, 29 (2):130 136.
68 14. Meyer TW, Hostetter TH: Uremia N Engl J Med 2007, 357 (13):1316 1325. 15. Niwa T: Phenol and p cresol accumulated in uremic serum measured by HPLC with fluorescence detection Clin Chem 1993, 39 (1):108 111. 16. Record N B, Prichard JW, Gallagher BB, Seligson D: Phenolic acids in experimental uremia. I. Potential role of phenolic acids in the neurological manifestations of uremia Arch Neurol 1969, 21 (4):387 394. 17. Dou L, Jourde Chiche N, Faure V, Cerini C, Berland Y, D ignat George F, Brunet P: The uremic solute indoxyl sulfate induces oxidative stress in endothelial cells J Thromb Haemost 2007, 5 (6):1302 1308. 18. Kalantar Zadeh K, Block G, Humphreys MH, Kopple JD: Reverse epidemiology of cardiovascular risk factors i n maintenance dialysis patients Kidney Int 2003, 63 (3):793 808. 19. Abboud H, Henrich WL: Clinical practice. Stage IV chronic kidney disease N Engl J Med 2010, 362 (1):56 65. 20. Brouhard BH, LaGrone L: Effect of dietary protein restriction on functiona l renal reserve in diabetic nephropathy Am J Med 1990, 89 (4):427 431. 21. Zeller K, Whittaker E, Sullivan L, Raskin P, Jacobson HR: Effect of restricting dietary protein on the progression of renal failure in patients with insulin dependent diabetes mell itus N Engl J Med 1991, 324 (2):78 84. 22. Nutrition and Kidney Failure (Stage 5) Are You Getting What You Need? In Edited by Foundation NK; 2010. 23. Druml W: Acute renal failure is not a "cute" renal failure! Intensive Care Med 2004, 30 (10):1886 1890. 24. Anderson JW, Smith BM, Gustafson NJ: Health benefits and practical aspects of high fiber diets Am J Clin Nutr 1994, 59 (5 Suppl):1242S 1247S. 25. Medicine Io: Dietary, Functional, and Total Fiber In: Dietary Reference Intakes for Energy, Carbohydrate Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids District of Colombia 2005: 339 421. 26. Services USDoAaUSDoHaH: Dietary Guidelines for Americans In 7th edition edn. Washington, D.C. : Government Printing Office 2010. 27. Gibson GR, Rob erfroid MB: Dietary modulation of the human colonic microbiota: introducing the concept of prebiotics J Nutr 1995, 125 (6):1401 1412.
69 28. Krishnamurthy VM, Wei G, Baird BC, Murtaugh M, Chonchol MB, Raphael KL, Greene T, Beddhu S: High dietary fiber intake is associated with decreased inflammation and all cause mortality in patients with chronic kidney disease Kidney Int 2011. 29. Van Soest PJ, Robertson JB, Lewis BA: Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in rela tion to animal nutrition J Dairy Sci 1991, 74 (10):3583 3597. 30. Marlett JA, McBurney MI, Slavin JL: Position of the American Dietetic Association: health implications of dietary fiber J Am Diet Assoc 2002, 102 (7):993 1000. 31. Jenkins DJ, Kendall CW, Vuksan V: Viscous fibers, health claims, and strategies to reduce cardiovascular disease risk Am J Clin Nutr 2000, 71 (2):401 402. 32. Wursch P, Pi Sunyer FX: The role of viscous soluble fiber in the metabolic control of diabetes. A review with special em phasis on cereals rich in beta glucan Diabetes Care 1997, 20 (11):1774 1780. 33. Velazquez OC, Lederer HM, Rombeau JL: Butyrate and the colonocyte. Production, absorption, metabolism, and therapeutic implications Adv Exp Med Biol 1997, 427 :123 134. 34. Archer S, Meng S, Wu J, Johnson J, Tang R, Hodin R: Butyrate inhibits colon carcinoma cell growth through two distinct pathways Surgery 1998, 124 (2):248 253. 35. Meijers BK, De Preter V, Verbeke K, Vanrenterghem Y, Evenepoel P: p Cresyl sulfate serum con centrations in haemodialysis patients are reduced by the prebiotic oligofructose enriched inulin Nephrol Dial Transplant 2010, 25 (1):219 224. 36. Annison G, Topping DL: Nutritional role of resistant starch: chemical structure vs physiological function A nnu Rev Nutr 1994, 14 :297 320. 37. Sobhani I, Tap J, Roudot Thoraval F, Roperch JP, Letulle S, Langella P, Corthier G, Tran Van Nhieu J, Furet JP: Microbial dysbiosis in colorectal cancer (CRC) patients PLoS One 2011, 6 (1):e16393. 38. Porrett T, McGrath A: Stoma care Oxford, OX ; Malden, MA: Blackwell Pub.; 2005.
70 39. Gaskins HR, Croix JA, Nakamura N, Nava GM: Impact of the intestinal microbiota on the development of mucosal defense Clin Infect Dis 2008, 46 Suppl 2 :S80 86; discussion S144 151. 40. Mac kie RI, Sghir A, Gaskins HR: Developmental microbial ecology of the neonatal gastrointestinal tract Am J Clin Nutr 1999, 69 (5):1035S 1045S. 41. Palmer C, Bik EM, DiGiulio DB, Relman DA, Brown PO: Development of the human infant intestinal microbiota PLo S Biol 2007, 5 (7):e177. 42. Spor A, Koren O, Ley R: Unravelling the effects of the environment and host genotype on the gut microbiome Nat Rev Microbiol 2011, 9 (4):279 290. 43. Round JL, Mazmanian SK: The gut microbiota shapes intestinal immune response s during health and disease Nat Rev Immunol 2009, 9 (5):313 323. 44. Bourlioux P, Koletzko B, Guarner F, Braesco V: The intestine and its microflora are partners for the protection of the host: report on the Danone Symposium "The Intelligent Intestine," h eld in Paris, June 14, 2002 Am J Clin Nutr 2003, 78 (4):675 683. 45. Guarner F, Malagelada JR: Gut flora in health and disease Lancet 2003, 361 (9356):512 519. 46. Duncan SH, Louis P, Thomson JM, Flint HJ: The role of pH in determining the species compos ition of the human colonic microbiota Environ Microbiol 2009, 11 (8):2112 2122. 47. Wang X, Gibson GR: Effects of the in vitro fermentation of oligofructose and inulin by bacteria growing in the human large intestine J Appl Bacteriol 1993, 75 (4):373 380. 48. Bartlett JG: Clinical practice. Antibiotic associated diarrhea N Engl J Med 2002, 346 (5):334 339. 49. Pearson JP, Brownlee IA: The interaction of large bowel microflora with the colonic mucus barrier Int J Inflam 2010, 2010 :321426. 50. Wong JJ, H awkins NJ, Ward RL: Colorectal cancer: a model for epigenetic tumorigenesis Gut 2007, 56 (1):140 148. 51. Topping DL, Clifton PM: Short chain fatty acids and human colonic function: roles of resistant starch and nonstarch polysaccharides Physiol Rev 2001 81 (3):1031 1064.
71 52. Bliss DZ, Stein TP, Schleifer CR, Settle RG: Supplementation with gum arabic fiber increases fecal nitrogen excretion and lowers serum urea nitrogen concentration in chronic renal failure patients consuming a low protein diet Am J Clin Nutr 1996, 63 (3):392 398. 53. Muyzer G, de Waal EC, Uitterlinden AG: Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction amplified genes coding for 16S rRNA Appl Environ Microbi ol 1993, 59 (3):695 700. 54. Muyzer G, Smalla K: Application of denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE) in microbial ecology Antonie Van Leeuwenhoek 1998, 73 (1):127 141. 55. Chakravorty S, Helb D Burday M, Connell N, Alland D: A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria J Microbiol Methods 2007, 69 (2):330 339. 56. McBurney W, Mangold M, Munro K, Schultz M, Rath HC, Tannock GW: PCR/DGGE and 16S rRNA gene library analysis of the colonic microbiota of HLA B27/beta2 microglobulin transgenic rats Lett Appl Microbiol 2006, 42 (2):165 171. 57. Sigler V, Pasutti L: Evaluation of denaturing gradient gel electrophoresis to differentiate Escherichia coli populations in secondary environments Environ Microbiol 2006, 8 (10):1703 1711. 58. Mathys S, Lacroix C, Mini R, Meile L: PCR and real time PCR primers developed for detection and identification of Bifidobacterium thermophilum in faeces BMC Microbiol 20 08, 8 :179. 59. Rochelle PA, Cragg BA, Fry JC, Parkes RJ, Weightman AJ: Effect of Sample Handling on Estimation of Bacterial Diversity in Marine Sediments by 16s Ribosomal Rna Gene Sequence Analysis Fems Microbiol Ecol 1994, 15 (1 2):215 225. 60. Bouhnik Y, Vahedi K, Achour L, Attar A, Salfati J, Pochart P, Marteau P, Flourie B, Bornet F, Rambaud JC: Short chain fructo oligosaccharide administration dose dependently increases fecal bifidobacteria in healthy humans J Nutr 1999, 129 (1):113 116.
72 BIOGRAPH ICAL SKETCH Justin Forde was born and raised in Miami, FL where his family currently resides. he received his B achelor of S cience degree at the University of Florida in Gainesville, FL in 2009. He graduated with his Master of Science degree at the University of Florida in Gainesville, FL in the spring of 2012