Effects of Sun Dried Raisins on Gut Microbiota Composition in Healthy Adults

Material Information

Effects of Sun Dried Raisins on Gut Microbiota Composition in Healthy Adults
Wijayabahu, Akemi Thakshila
University of Florida
Publication Date:

Thesis/Dissertation Information

Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Committee Chair:
Committee Co-Chair:
Committee Members:


Subjects / Keywords:


General Note:
Emerging evidence suggests a potential role of gut microbiome in the etiopathogenesis of various diseases. Thus, the maintenance and targeted modification of gut microbiota composition has potential for improving various health parameters. Raisins are rich in phytochemicals that may affect gut microbiota composition. As the association between gut microbiota and raisins has not been investigated in humans the objective of this study is to determine how adding raisins to the diet affects gut microbiota of healthy adults. A 14 day feeding study was conducted with thirteen healthy volunteers between the ages of 18 and 59 years. Participants consumed three servings (one ounce each) of sun dried raisins daily. Fecal samples were collected prior to raisin consumption (baseline) and after addition of raisins to the diet (on day 7 and 14). The composition of fecal microbiota was characterized by sequencing 16S rDNA; sequences were then subjected to quality control and clustered into Operational Taxonomic Units (OTU) at 95% and 98% similarity levels. Overall microbiota diversity was not significantly affected by adding raisins to the diet. An increase of specific OTUs matching Faecalibacterium prausnitzii and Bacteroidetes sp. along with a decrease of OTUs closest to Klebsiella sp., Prevotella sp. and Bifidobacterium spp. correlated with the addition of raisins to the diet. These OTU level changes indicate beneficial changes and a reduced risk for potential pathogen effects such as Klebsiella sp. To better establish benefits of increased raisin intake future studies should target quantifiable health endpoints correlate gut microbiota with improved immune function.

Record Information

Source Institution:
Rights Management:
All applicable rights reserved by the source institution and holding location.
Embargo Date:


This item has the following downloads:

Full Text




2017 Akemi Thakshila Wijayabahu


For my beloved grandmother


4 ACKNOWLEDGMENTS I t hank my supervisory chair Dr. Volker Mai and my supervisory committee member s Dr. Lusine Yaghjyan and Dr. Mattia Prosperi for giving me the opportunity, guidance and support in completing this thesis. I thank Dr. Ma ria Ukhanova, lab manager and S heldon Waugh for the enormous support given for the successful completion of the thesis. I thank University of Florida writing studio, Ms. Betsy Jones and my uncle Mr. Dulip Ranasinha for editing and language help. My gratitude also goes to my family and my colleagues for their support and encouragement.


5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 LIST OF ABBREVIATI ONS ................................ ................................ ............................. 9 ABSTRACT ................................ ................................ ................................ ................... 10 CHAPTER 1 LITERATURE REVIEW ................................ ................................ .......................... 12 The Human Gut Microbiota ................................ ................................ ..................... 12 Human Microbiome Characterization ................................ ................................ ...... 13 Dietary Influences on Gut Microbiota ................................ ................................ ...... 16 Raisins and the Gut Microbiota Composition ................................ .......................... 17 Anti Inflammatory and Pathogen Resistant Properties of Raisins .................... 18 Anti Cancer Properties ................................ ................................ ..................... 19 Overall Benefits of Raisins and Possible Means of Introducing Raisins to Ame rican Diet ................................ ................................ ................................ ...... 20 Strengths and Limitations of Raisins and Gut Microbiome Studies ......................... 21 2 INTRODUCTION ................................ ................................ ................................ .... 22 Research Question ................................ ................................ ................................ 23 Study Hypothesis ................................ ................................ ................................ .... 23 Study Objectives ................................ ................................ ................................ ..... 23 3 MATERIALS AND METHODOLOGY ................................ ................................ ...... 24 Study Population ................................ ................................ ................................ ..... 2 4 Funding Source and Project Approval ................................ ................................ .... 25 Product Information ................................ ................................ ................................ 25 Study Design and Fecal Sample Collection ................................ ............................ 25 DNA Extraction and PCR Amplification ................................ ................................ ... 26 DNA Sequencing and Clustering into Operational Taxonomic Units (OTUs) .......... 26 Statistical Analysis ................................ ................................ ................................ .. 26 4 RESULTS ................................ ................................ ................................ ............... 29 Participant Characteristics ................................ ................................ ...................... 29 Output of 16S rDNA Sequencing ................................ ................................ ............ 29


6 Microbiome Diversity and Richness ................................ ................................ ........ 29 Relative Abundance of Gut Bacteria ................................ ................................ ....... 30 5 DISCUSSION AND CONCLUSION ................................ ................................ ........ 38 APPENDIX A SUPPLEMENTARY FIGURES OF RESULTS SECTION ................................ ....... 44 B DNA EXTRACTION PROTOCOL ................................ ................................ ........... 47 C GAST RO INTESTINAL HEALTH QUESTIONNAIRE SAMPLE .............................. 48 D PARTICIPANT RECRUITMENT POSTER AND SAMPLE COLLECTION FORM .. 49 LIST OF REFERENCES ................................ ................................ ............................... 50 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 58


7 LIST OF TABLES Table page 4 1 Demographic characteristics of study participants ................................ ............. 31 A 1 Primer combination for 16S rRNA gene PCR amplification ............................... 44 A 2 Primer combination for 16S rRNA gene sequencing on Illumina MiSeq ............ 44


8 LIST OF FIGURES Figure page 3 1 Sun dried raisins used in the s tudy. ................................ ................................ .. 27 3 2 Study design.. ................................ ................................ ................................ .... 28 4 1 Chao1 r diversity).. ................................ .......................... 32 4 2 UniFrac beta diversity analysis by study participant. ................................ ........ 33 4 3 Proportion of bacterial OTUs at 95% similarity level grouped by phyla and time points. ................................ ................................ ................................ ........ 34 4 4 Proportion of bacterial OTUs at 95% similarity level grouped by phyla and by participants. ................................ ................................ ................................ ........ 35 4 5 Bacterial OTUs affected by sun dried raisin consumption at 95% similarity level.. ................................ ................................ ................................ .................. 36 4 6 Bacterial OTUs affected by sun dried raisin consumption at 98% similarity level.. ................................ ................................ ................................ .................. 37 A 1 UniFrac beta diversity analysis by feeding time points. ................................ .... 45 A 2 Changes in the proportion of operational taxonomic subunits grouped into four most abundant bacterial phyla. ................................ ................................ .... 46 A 3 Heat map depicting the variations in an OTU closest to Klebsiella spp affected by raisin consumption at 95% similarity level.. ................................ ...... 46


9 LIST OF ABBREVIATIONS BLAST Basic Local Alignment Search Tool BMI Body Mass Index CRC Colorectal Carcinoma IBD Inflammatory Bowel Disease IBS Irritable Bowel Syndrome IL Interleukin. A glycoprotein, a marker of immune response. IL 1 produced by macrophages, B cells, monocytes and dendritic ells, IL 10 produced by monocytes, T helper cells type 2, CD8+ T cells, mast cells, macrophages and B cells. NCBI National Center for Biotechnology Information OTU Operational Taxonomic Unit. Part of a unique sequence that represents a certain taxonomic group or organism. PCNA Proliferative Cell Nuclear Antigen PCR Polymerase Chain Reaction QIIME Quantitative Insight Into Microbial Ecology. An Open source microbiome pipeline SCFA Short Chain Fatty Acid. A fatty acid with equal or less than six carbon atoms. A secondary metabolite of microbial fermentation of fibers.


10 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfill ment of the Requirements for the Degree of Master of Science EFFECTS OF SUN DRIED RAISINS ON GUT MICROBIOTA COMPOSITION IN HEALTHY ADULTS By Akemi Thakshila Wijayabahu M a y 2017 Chair: Volker Mai Major: Epidemiology Emerging evidence suggest s a potential role of gut microbiome in the etiopathogenesis of various diseases. Thus, the m aintenance and targeted modification of gut microbiota composition has potential for improving various health parameters. Raisins are rich in phytochemicals that may a ffect gut microbiota composition As the association between gut microbiota and raisins has not been investigated in humans t he objective of this study is to determine how adding raisins to the diet affects gut microbiota of healthy adults. A 14 day feeding study was conducted with thirteen healthy volunteers between the ages of 18 and 59 years. Participants consumed three servings (one ounce each) of sun dried raisins daily. Fecal samples were collected prior to raisin consumption (baseline) and after addition of raisins to the diet (on day 7 and 14). The composition of fecal microbiota was characterized by sequencing 16S rDNA ; sequences were then subjected to qual ity control and clustered into Operational Taxonomic U nits (OTU) at 95% and 98% similarity levels. Overall microbiota diversity was not significantly affected by adding raisins to the diet. An increase of specific OTUs matching Faecalibacterium prausnitzii and


11 Bacteroidetes sp. along with a decrease of OTUs closest to Klebsiella sp. Prevotella sp and Bifidobacterium spp correlated with the addition of raisins to the diet. These OTU level changes indicate beneficial changes and a reduced risk for potential pathogen effects such as Klebsiella sp T o better establish benefits of incr eased raisin intake future studies should target quantifiable health endpoints correlate gut microbiota with improved immune function


12 CHAPTER 1 LITERATURE REVIEW The Human Gut Microbio ta The human gut harbors a diverse and dynamic ecosystem of mostly symbiotic microorganisms frequently referred to as gut microbiota (1 3) G ut microbiota composition and activities have been proposed to correlate with various aspects of human health (1, 4) Mutualistic gut microbiota functions contribute to digestion absorption, excretion as well as immune prote ction S pecific contributions of the gut microbiota include the degradation of insoluble fibers into short cha in fatty acids (SCFA), the de novo synthesis of biomolecules such as vitamins (B12, K) and linoleic acids, biotransformation of phytochemicals and energy conversion ( Butyrate a SCFA is the main energy source of colonocytes), induction of gut motility to a beneficial speed and immune homeostasis (1, 5 8) G ut microbiota in a healthy adult is diverse and fairly stable providing protection from enteric pathogen s (8) D ietary intake can influence the microbial milieu and affect the physiology in the human gut (9, 10) Previous microbiome studies suggest that an increased i ntake of fruits and other plant based foods correlate s with beneficial changes in gut microbiota composition (11 15) However, most of these studies struggle to establish such correlations between fruits and the gut microbiome This chapte r will review potential health benefits of raisins, with an emphasis on microbiota mediated effects as discussed in previous research studies This chapter will also provide information and rationale behind the methodologies used in this study. Intrinsic and extrinsic factors shape the gut microbiota composition. Each individual harbors a unique microbiome that is shaped by maternal inoculati on during


13 birth and then adapts to the person s genetics, age and lifestyle habits such as diet and exercise (16) Bacteria are more abundant in the human gut when than other microorganisms such as euka ryotes and viruses. The bacterial cell count outnumbers the host cell count by a ratio of ten to one (1) Many of these bacteria are obligatory anaerobes contributing to host immune function (7, 17) Many of the microorganisms in the gut cannot be grown by conventional culture method s due to complex growth requirements The a dvancement of high throughput sequencin g has allowed characterization of such complex microbial communities and studies of their associations with human health (18) Human Microbiome Characterization The gut microbiome is the collection of microbial genomes in t he gut. A recent review of current microbiome research reports that a healthy human adult gut has more than 35,000 total bacterial species and over ten million total bacterial genes (19) L arge s of the Human Intestinal (MetaHI T) an Microbiome Project (HMP) have provided insight into host mic robiome signatures as disease diagnostic markers (2, 6, 20) Fecal microbiota DNA extraction the first step in non culture based gut microbiome characterization. Microbial DNA extracted from fecal samples are represent ative of the distal gut microbiota. However, the details of preservation and extraction protocol can potentially have a decisive influence on the yield and quality of DNA (21, 22) The curren t study uses QIAamp DNA stool mini kit to extract DNA, because several studies have shown effectiveness of the protocol in obtain ing a representative gut microbiome sample (23 25) Adding a bead beating step further


14 increases the DNA extractio n efficiency (23, 24) This study use s RNAlater solution to preserve fecal samples to improve stability of DNA and to prevent degradation. A recent study has demonstrated RNAlater to be more effective in terms of both the DNA stability and cost (26) The same study recommends C as the fecal sample storage temperature to prevent any DNA degradation (26) The 16S rDNA microbiome characterization approach Characterization of gut microbiome is challenging because of its diversity and taxonomic complexity. Bacteria dominate the gut microbiome, thus 16S rDNA amplicon sequencing can capture almost all micro o rganisms in the gut that evade conventional culture methods Selected combinations of the hyper variable regions (V1 V9) of 16S rDNA in bacterial genome are amplified using PCR and clustered into Operational Taxonomic Units (OTUs) (27) This study uses the Illumina MiSeq sequencing platform which is an efficient sequencing platform for multiple samples of 16S rDNA (28) The 16S rDNA approach is efficient for analyzing complex microbial communities (27) Identification and classification of sequenced bacterial DNA. Raw sequence data obtained after Illumina sequencing must be clustered and assign ed into biologically meaningful Operational Taxonomic Units (OTUs) t o identify the bacterial co mposition in the fecal samples (29) OTUs are sequence reads t hat are similar to each other at a specified similarity level (95% or 98%). QIIME (Quantitative I nsights I nto M icrobial E cology) is one of the widely used software package s to perform pre processing of raw sequence reads (quality filtering and removal of c himeras), clustering sequences based on a similarity threshold OTU picking, taxonomic assignment and downstream core diversity analys e s (21, 29) The current study uses the UPARSE algorithm with


15 USEARCH greedy clustering approach to generate OTUs The OTU clusters are then matched with greengenes reference database using a 16S rDNA specific microbiome pipeline to assign phylogeny (27, 29 32) Many studies have identified that the clust ering and OTU generation approaches used in the current study are efficient in human gut microbiome research (21, 29, 33) This study uses 95% and 98% similarity levels to cluste r sequences This study expects to ident ify bacterial composition by clustering sample sequences with less stringent and more stringent phylogen etic relatedness. Downstream OTU analysis. Apart from OTU prevalence analysis, changes in d iversity and richness measures overtime can help to determine gut microbiome stability or indicate dysbiosis. The Alpha is OTU diversity within each sample and the beta diversit y is OTU diversity between samples (34) The core diversity analyses in QIIME can produce a Chao1 rarefaction curve, which visualizes the alpha diversity of each sample based on rare OTUs and sequencing depth. Other diversity indices for alpha diversity are (34, 35) QIIME use UniFrac d istance to calculate the beta d iversity; UniFrac distance is based on both the phylogenetic distance as well as the sample composition dissimilarity ( weighted UniFrac distance is a quantitative measure of beta diversity where abundance of sequences are also included and un weighte d Uni Frac distance is a qualitative measure where abundance is not considered ) (32) Targeted 16S rDNA based gut microbiota studies need standardized, cost effecti ve and efficient DNA preservation extraction, upstream and downstream sequence processing and analyzing methods to allow cross comparison between


16 research studies (22, 33) Also to use gut microbial changes as prognostic or disease diagnostic b iomarkers the standardized methods must be sensitive reliable and accurate (22, 33) Direct changes in gut microbiota composition by modified dietary habits have the potential to improve health (36) Currently the extent of the association betwee n diet and human gut microbiota and its correlation to health is not fully understood. Dietary Influences on Gut Microbiota There has been renewed int erest among gut microbiome researchers to understand how dietary manipulations can impact gut microbiota and human health (8, 36, 37) Among factors that can influence the gut microbiota, diet is easily manipulated to allow beneficial changes in the gut microbiota composition Even though the human gut m icrobiota is adapted to l ong term dietary habits, alterations to the diet can change the microbiota composition (9, 38, 39) A diet abundant with fruits vegetables and fibers is recognized as one of the most important preventive factors only second to t obacco cessation in cancer prevention strategies (11, 40 42) Increasing the dietary intake of fruits vegetables and fibers can be suggest ed as an effective means of improving the daily diet. Latest d ietary g uidelines for healthy Americans recommend a n average daily intake of two to two and a half cup equivalents of fruits per 2,000 calorie diet (43 45) According to the dietary evaluations from 2007 2010 National Health and Nutrit ion Examination Survey (NHANES), the dail y intake of fruits by adults is well below the recommended intake (43, 46) .Taking into account the benefit of consuming dried fruits with regard to fulfilling the dietary requirements of fruits, ra isins can contribute to the daily intake of fibers and nourishing with micronutrients (43, 47, 48) Therefore


17 expanding the knowledge on dried fruits such as raisins would have a significant impact on nutrition and pub lic health research. Many of the existing research studies focus on the chemical aspect of fruits and its effect on the gut chemistry and physiology. In order to understand the overall influence of fruits on human gut, more studies should focus on investi gating the effects of specific fruits on the gut microbiome and identify fruits that promote beneficial changes Dietary interventions and epidemiologic studies have documented various effects of fruits on the gut microbiota (8, 49) However, interpreting results based on dietary interventions must be dwelt with caution by considering any confounding e ffects that may be attributed to environmental, lifestyle and individual host factors to ensure reliability of the results Having a be neficial phytochemical profile and the ability of the phytochemicals to influence gut microbiota must be considered when selecting a fruit to test influence on gut microbiota Commonly cultivated, easily accessible and popular fruits with medicinal values could be prioritized to expand the knowledge about specific fruits and its influence on the human gut microbiome Raisins and the Gut Microbiota Composition Raisins are dried grapes ( Vitis vinifera ) a popular dietary constituent used since 120 to 900 BC in European and Mediterranean regions (50, 51) Previous studies have demonstrated various effects of g rape s and grape products (raisins, pomace, wine and seeds) on the gut microbiota (14, 52 56) However, little is known about the effects of raisins on human gut microbiota. Grapes and raisins contain relatively high concentrations of beneficial phytochemicals (47, 57, 58) These phytochemicals include simple sugar s (glucose,


18 fructose ), fibers (30% sol uble fibers such as fructo oligosaccharides and inulin and insoluble fibers), tartaric acid, and phenolic compounds (flavonols such as quercetin and kaempferol, phenolic acids such as caftaric and coutaric acids, and proanthocyanidins) (57, 59) Several studies have shown that the production process of raisin s (sun drying and processing) increases the concentration of flavonol, phenolic acid, fructo oligosaccharides ( FOS ), tartaric acid and fiber s not only by condensation (17, 60, 61) Phytochemicals present in raisins has a potential to positively influence the gut microbiota (41, 62, 63) Many in vitro and animal model studies have demonstrated effects of grape phytochemicals on gut microbiota to be beneficial for human healt h (17, 48, 57, 58, 62 65) However, human studies are needed to confirm or strengthen these assumptions based on in vitro and animal studies. Anti I nfl ammatory and Pathogen Resis tant P roperties of Raisins Raisins could potentially influence the epithelial cell integrity Gut epithelial integri ty is essential for absorption of nutrients providing a barrier for pathogens and reduce gut inflammation (1, 8) Yang et al has shown that grape seed s contri bute to better cell integrity in mouse models that mimic inflammatory bowel disease (66) Many phytochemicals present in grape seeds can also be found in raisins Fibers, polyphenolics and SCFA are some of these compounds that are known to exert beneficial effects on gut epithelial integrity (48, 57) Evidence suggests raisins could potentially increase anti pathogenic byproducts of microbiota Gut microbiota can contribute to both active pathogen inhibition (via bacterial metabolites such as SCFA b acteriocins and peroxides ) and by passive inhibition (via bio film barrier formation and competing for resources) (8, 58)


19 Polyphenolic compounds and also fib ers contribute to anti microbial activity (1, 67) Several gut microbiome studies have reported i nhibitory effect of grapes and grape deriva tives on bacterial pathogens such as Escherichia coli, Enterobacter aerogenes, K lebsiella pneumoniae and fungal pathogens such as Penicillium expasum, Candida albicans and Aspergillus niger have been observed (52 54, 68, 69) Phytochemicals in raisins a re suggestive of their ability to potentially reduce chronic inflammation. Many studies report disrupted fermentation process as a predictor of inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), and also pathogen invasion (8, 41, 66, 70, 71) .Phytochemical compounds of raisins could potentially contribute to anti inflammatory activity by modulating the gut microbiota. Spiller et al has demonstrated increased SCFA with raisin consumption, indicating improved fermenta tion process. Di Lorenzo et al has demonstrated the anti inflammatory activity of raisins by suppression of pro inflammatory molecules using an in vitro study on healthy human gastrointestinal epithelial cells (17) Anti Cancer Properties While some gut microbiota are associated with carcinogenesis by prolonged infection exerting pro inflammatory effects, others may contribute to cancer prevention. The phytochemicals that are present in grapes and grape products have shown to be protective against cancers (41) The Yang et al study on mice has demonstrated that grape seeds reduce proliferative cell nuclear antigen (PCNA), indicating a r eduction of hyper proli feration in epithelial cells (66) The Kountouri et al study on colorect al cancer (CRC) cell line (HT29) ha s demonstrated an exposure time depende nt antioxidant and anti inflammatory activity of raisins (42) I ncreased production of butyrate (a SCFA) is associated with reduced risk of ulcerative colitis and CRC (14) Raisins have ample


20 amounts of fibers and tartaric acids that could potentially be converted to SCFA by microbial activity (59) Antioxidants (f lavonoids and phenolic acids ) present in grapes and raisins are also correlated with reduced risk of CRC (17, 41) Camire et al demonstrated the bile acid binding ability of raisins (6 0) Dietary fibers reduce the concentration of bile acids in the colon. Excess fecal bile acids (FBA) are an indicator of increased CRC risk (64) Raisin consumption has shown to decrease FB A in healthy adults (64) F ibers, tartaric acid and SCFA increase bowel movement by reducing the transit time, and subsequent moderate increase of fecal weight contributes to dilution and effe ctive elimination of carcinogens and prevent s constipation (59, 60, 64, 72) Raisins seem to exert protective effect s against colorectal carcinogenesis and some seem to be associated with gut microbiota activity Overall Benefits of Raisins and Possible Means of Introducing Raisins to Amer ican Diet Raisins are beneficial to he alth in many aspects, thus they a re better alternative for commonly used high fat, high sugar snack food R aisins have a low to moderate glycemic index, and a low insulinemic index than other snack food (72, 73) Raisins have more fiber content than any other commonly used snack food, and als o the FOS content of raisins is greater than that of grapes (57, 60) Raisins also seem to correlate with improved total serum cholesterol level (reduced LDL, and triglycerides) and weight loss by regulating appetite (72) Raisins are stable, have a greater shelf life and lesser tendency for spoilage. Few studies have focused on sun dried raisins as a healthier and natural alternative to replace commercial carbohydrate snacks. Rietschier et al has claimed that sun dried


21 raisins appear to be a cost effective source of energy for people doing moderate to high intense exercise in comparison to sports jelly beans or sports chew (58, 74) It is the best and the easiest way to acquire adequate amounts of fibers, micronutrients and beneficial phytochemical s that have the potential to promote immune function and enhance d gut comfort (14, 59, 63, 75) Potential l ong term effects may inc lude the reduced risk of colorectal cancer and prevention of chronic inflammat ion. Strengths and Limitations of Raisins and Gut Microbiome S tudies The Mandalari et al study is the first to describe the correlation between sun dried raisins and the human gu t microbiota using a gastrointestinal digestion model (14) Authors claims that sun dried raisins exhibit immense potential in their capacity t o promote the colonization and proliferation of beneficial bacteria in the human (14) Authors documented a significant increase in Bifidobacterium sp ., Proteobacteria, Actinobacteria, Roseburia sp and decreased in overall B acteroidetes, Faecalibacterium prausnitzii and Ruminococcacea. Although t he authors make inferences based on fecal samples provided by one h ealthy individual artificially digested raisins and a short incubation period (24 hours) they comment on the need for a long term human intervention (1 4) Spiller et a l describe the effects of sun dried raisins on healthy adults (59, 64) Authors measured the amount of SCFA transit time, fecal weight and bile acid binding as markers of gut microbiota activity (59, 60, 64) Although r aisins seem to correlate with gut health via modif ication of microbiota activities their effects on microbiota are not established. In vitro studies cannot fully replicate the real life changes occurring in the human gut influenced by internal and external host factors. Therefor e finding direct effect of raisins on human gut microbiota can contribute to future research.


22 CHAPTER 2 INTRODUCTION The i nterplay of human gut microbiome, diet and health has received m uch attention in the past decade (76) There are many means through which gut microbiota can influence good health; fermentation of dietary fiber to s hort c hain f atty a cids is one such important mechanism (6, 36, 76) Recent research efforts have focused on investigating the effect of dietary patterns, specific foods and individual dietary c ompounds on the gut microbiome (10, 36) The current study investigates the effect of sun dried raisins on gut microbiota composition. The s tudy utilizes a ta rgeted 16S rDNA sequencing approach a recognized method of microbiota characterization (21) to determine the effects of adding raisins to diet on gut microbiota for a two week period Several studies have investigated the influence of either whole raisins or isolated phytochemicals from raisins (42, 57, 59, 64) on the amounts of microbial metabolites produced or the gut microbiota composition using in vitro cell culture or gastric digestion models (14, 59, 60, 64) However, human feeding studies are needed to translate these observations. Maintaining a diverse gut microbiome is associated with an improved immune function (20, 21) The effect of raisins on the overall gut microbiota diversity has not been documented in earlier studies. Thus this study me asures the a lpha and beta diversity to identify the effect s of raisins on gut microbiota diversity Previous studies suggest potential effect of raisins on specific bacterial signatures, thus this study also measures the relative abundance of bacterial signatures before and after raisin consumption (10, 19, 58, 76)


23 Raisins have been shown to reduce the risk of many chronic diseases (38, 58) Investigating the effects of raisins on gut microbiota can potentially determine the means of chronic disease prevention. This research will contribute to the understanding of the benefits of raisin mediated influence on gut micro biota Research Question How can raisin consumption change the human gut microbiota in healthy adults ? Study Hypothesis Sun dried raisins modify the human gut microbiota towards a beneficial composition. Study O bjectives To evaluate the effect of sun dried raisins on the gut microbiome composition in healthy adult s.


24 CHAPTER 3 MATERIALS AND METHODOLOGY Study Population A total of 18 eligible volunteers were recru ited from the area surrounding t he University of Florida, Gai nesville to participate in a two week feeding study. Volunteers were recruited by advertising with flyers Potential participants were screened for eligibility. They were asked to provide information on dietary habits and medical history. Participants with an age between of 18 and 75 years, in general good health and having regular bowel movements (at least three times a week) were included in the study. Exclusion criteria of the study were having underlying gastrointestinal disorders such as ulcers, Irrita ble bowel syn drome and chronic constipation, having diarrhea during the past month (at least three soft o r watery stools within 24 hour period) experiencing a change in body weight of more than 10% in the past three months having a colonoscopy screening within the last two months and using medication that affects bowel function or microbiota such as antibiotics and laxatives during the past month Afte r the written informed consent, participants were asked to complete a demographic questionnaire at baseli ne, a compensation form, a fecal sample collection log and a gastrointestinal health questionnaire during each visit. Participants were given monetary compensation for each fecal sample collect ed Each participant was a ssigned to consume three servings (one ounce per serving ) R aisins 14 days. Participants were considered as their own controls. Thirteen participants completed the feeding study successfully Those participants who complet ed the study were included in the microbiota analysis.


25 Funding Source and Project Approval The g ut microbiota human participant study protocol has been approved by Institutional Review Board University of Florida (IRB 01) with the approval number IRB2015 00607. The current study is funded by Su n Maid growers of California. Product Information Th is study use d sun dried raisins, with no added sugar. A packet of 28.3g (one ounce) Maid contain s 20g of natural sugars (fructo se), 2g of fibers, 1g of protein, 5mg of s odium and micronutrients like iron (47, 77) ( Figure 3 1) Study Design and Fecal Sample Collection For microbiota analysis, a single fecal sample was collected from each of the 13 participants at three time points: day 0 (prior to raisin consumption; baseline), day 7 and day 14 (study design: Figure 3 2 ) Participants were asked to provide the first bowel movement of the day and to fill a short questionnaire using gastrointestinal symptom response scale ( zero to six ; zero having no discomfort at all and six having very severe discomfort) The g astrointestinal health questionnaire included q uestions about stomach ache, acid reflux, hunger pain, rumbling in the stomach, bloating, being bothered by burping, passing gas or flatus, constipation, diarrhea, loose stools, urgent need for bowel movemen t and feeling of inco mplete bowel emptying It also included a section for physical activity (predominantly sedentary, occasionally active, moderately active and vigorously active) (Appendix C ) For Table 4 1 predominantly sedentary and occasionally active was considered as low activity level and the latter two categories was re classified as high activity group. The Demographic questionnaire included age, gender, race, height and weight Participants were asked to collect fecal samples into


26 SIGMA stool collection kit, transfer to sterile plastic collection tubes with RNAlater solution, and C DNA Extraction and PCR Amplification Bacterial genomic DNA was isolated from fecal samples u sing QIAamp DNA Stool mini kit with an initial bead beating step (appendix B) DNA samples were quantified and then amplified using bar coded Illumina primers targeting the V1 and V2 region of the bacterial 16S rDNA Primers used in this study can be found in Appendix A ( Figure A 1) PCR products were purified using the Axygen magnetic separation kit to prepare DNA libraries. DNA S equencing and Clustering into Operational Taxonomic U nits ( OTU s ) DNA library was sequenced on Illumina MiSeq platform ( A ppendix A, Figure A 2) Sequences of low quality (expected error >0.50 quality filter and chimera) or with a length less than 290 nucleotides were removed from the analysis. Using a modified UPARSE pipeline, t he sequences were clustered at si milarity levels of 95% and 98% using the UPARSE algorithm The representative sequences from each OTU are annotated through the G reengenes 16S reference database using a Bayesian RDP classifier Sequences were then binned into OTUs using the USEARCH algori thm resulting in a completed OTU table with OTUs as rows and samples as columns. Statistical Analysis Microbiome diversity analysis Shannon Weaver and Simpson i ndex and species richness were calculated in Microsoft Excel to measure alpha diversity C hao1 rarefaction curve was generated using the Quantitative Insights into Microbial Ecology (QIIME) software package (31) Uni F rac distances and principle component analysis


27 plots were generated using the QIIME software package. The mean UniFrac distance calculations were conducted using Microsoft Excel Relative abundance measures of OTUs Percent relative abundance of bacterial signatures grouped by phyla and genera were calculated OTUs annotated as un classified or classified only up to the k ingdom level by the UPARSE algorithm were manually re aligned using the BLAST tool in NCBI (78) If re aligned sequences matched to sequences belonging to pha ges or vectors and/or if sequence simila rity score and query coverage is less than 95%, then these OTUs were excluded from the analysis The significance of differences in the p roportion of participants showing the presence/absence of s pecific OTUs was ca lculated using z test. Heat maps were generated to include OTUs that reached significance (79) The significance i n mean counts of OTUs was calculated by t test. Figure 3 1. Sun dried raisins used in the study A) nutritional facts label of 1 oz package of raisins and B) the six pack raisins provided for participant s each small package contains one ounce of raisins. Photo Courtesy ( (14) and the author ) A B


28 Figure 3 2. St udy design Red arrow represents the raisin feeding period (day one to day 14). Fecal samples collected before rai sin intake (day 0/baseline) and one week afte r addition of raisins (day 7/ week 1) and two weeks of raisin intake (day 14/ week 2). After informed consent the monetary compensation forms and demographic questionnaire were given at baseline. Gastrointestinal health questionnaire was given at baseline, week one and week two.


29 CHAPTER 4 RESULTS Participant Characteristics Demographic characteristics of the participants are shown in T able 4 1 P articipants did not report any discomfort (overall health, stomach comfort and fecal movement) during the raisin feeding period However, most participants disliked consum ing three one ounce servings of raisins daily Output of 16S rDNA Sequencing S equencing using Illumina MiSeq platform generated a total of 5,533,527 sequence reads from 39 fecal sa mples ( samples from 13 participants each at baseline, week one and week two). After removal of low quality and short length sequences, a total of 4,477,275 sequences were retained, with an average of 106,475 sequences per sample and an average sequence len gth of 322.25 nucleotides. The sequences binned using UPARSE algorithm generated 1,238 and 2,168 unique OTUs at the 95% and 98% similarity level s respectively Microbiome Diversity and Richness Alpha diversity measured using Shannon Weaver index, Simpson index and OTU richness did not show statistically significant difference with raisin intake (data not shown). Also, the Chao 1 rarefaction curve did not differ by time point ( Figure 4 1). The principle coordinate analysis plots based on the UniFrac distanc es show that overall microbiota composition of fecal samples were grouped by participants and not by time points ( Figure 4 2 and A ppendix A, Figure A 1).


30 Relative Abundance of Gut Bacteria In the phylum level analysis, OTUs matching Bacteroidetes and F irm icutes were dominant across all study samples. OTUs matching p hylum Actinobacteria and P roteobacteria were observed to a lesser extent. Relative proportion s of bacterial phyla were not significantly affected by raisin consumption ( Figure 4 3, Figure 4 4 an d A ppendix A, Figure A 2 ) Phylum distribution at 98% similarity level was similar to that of 95%, thus the data plots are not shown for 98% Even thought the effect in raisin consumption on the F irmicutes to B acteroidetes ratio across time points was not significant ( with an average of 2.33 for baseline, 1.56 for week one and 1.60 for week two ) relative proportion of the B acteroidetes seem to increase and the proportion of F irmicutes seem to decrease with raisin consumption ( Figure 4 3 and A ppend ix A, Figure A 2) Genus level e ffect by raisins was also not statistically significant. At 95% similarity level, h eat maps show 16 OTUs that were significantly affected by the first week of raisin consumption, 11 OTUs significantly changed by the second w eek, compared to only 4 OTUs that show significant change when comparing the two feeding period s (week one to week two, Figure 4 5) At 98% similarity level, heat maps show 28 OTUs and 19 OTUs significantly affected by the first and second week of raisin c onsumption respectively, compared to only 13 OTUs changed between the feeding periods ( Figure 4 6 ). OTU matching Klebsiella sp presented in Figure 4 5 was used to generate another heat map with that has an enhanced OTU color separation range (0 to 100) for clear visualization.( Appendix A, Figure A 3 )


31 Table 4 1. Demographic characteristics of study participants Characteristics Range or Percentage (N) Age 18 to 59 years (13) Gender Female 62% (8) Male 38% (5) BMI Normal 46% (6) Overweight 39 % (5) Obese 15% (2) Exercise Low 46% (6) High 54% (7) Race White 46% (6) Black 8% (1) Other 46% (6) Exercise categories: predominantly sedentary and occasionally active categorized as low activity level and the latter two categories re classified as high activity group. Body Mass Index (BMI) categories: BMI between 18.5 to 24.9kgm 2 as normal, 25.0 to 29.9kgm 2 as overweight and 30kgm 2 and above as obese.


32 Figure 4 1. diversity). Chao diversity was calculated from sequence distribution at baseline, week 1(one week after raisin starting consumption) and week 2 (two weeks after raisin consumption)


33 Figure 4 2. UniFrac beta diversity analysis by study participant. The principle coordinate plots based on un weighted (A) and weighted (B) UniF rac presents microbiota composition in stool samples measured at baseline, week 1 (one week after starting raisin consumption ) and week 2 (two weeks after raisin consumption) The samples are 16S rDNA MiSeq Illumina sequences obtained from each study participant given with a participant ID 1,2,6,7,8,9,10,12,14,15,16,17 and 18. Each individual has three samples from three time points and each individual was assigned a different color coded circle to visualize intra individual variation before and after the feeding period. A B


34 Figure 4 3 Proportion of bacterial OTUs at 95% similarity level grouped by phyla and time points. The gut microbiota variation based on 16S rDNA abundance at phylum level. Bacteria grouped into four most dominant phyla (Bacteroidetes, Firmicutes, Actinobacteria and Proteobacteria) and other group belongs to those OTUs that had sequence abundance average of le ss than 1.0% at each time point. Cyanobacteria, Fusobacteria, Lentisphaerae, Synergistetes, Tenericutes, TM7 and Verrucomicrobia were combined into other p hyla group Percent relative abundance of baseline, week 1 (one week after raisin consumption) and we ek 2 (two weeks after raisin consumption) samples are shown. Each column shows the bacterial composition of one fecal sample based on the OTU clustering with greengenes reference database. B acterial OTUs classified only up to kingdom were not included in t his analysis (these sequences had a query coverage and similarity of less t han 95% when aligned with BLAST or they belonged to phage DNA used in the sequencing process. All unclassified bacterial sequences were also excluded from the figure as they were al so identified as phages from BLAST analysis).


35 Figure 4 4 Proportion of bacterial OTUs at 95% similarity level grouped by phyla and by participants Illumina Mi S eq sequencing of 16S rDNA for microbial OTUs abundance grouped into dominant phyl a (Bacteroidetes, Firmicutes, Actinobacteria and Proteobacteria) and other. OTUs that had sequence abundance average of less than 1.0% at each time point were grouped as other phyla. This group includes Cyanobacteria, Fusobacteria, Lentisphaerae, Synergist etes, Tenericutes, TM7 and Verrucomicrobia S amples from baseline, week1 (one week after raisin consumption) and week 2 (two weeks after raisin consumption) were grouped by participant ID (1,2,6,7,8,9,10,12,14,15,16,17 and 18) Each column shows the bacter ial composition of one fecal sample based on the OTU clustering with greengenes reference database.


36 Figure 4 5 B acterial OTUs affected by sun dried raisin consumption at 95% similarity level. Left column separator: baseline, middle column separator: week 1 (one week after raisin consumption) and right column separator : week 2 (two weeks after raisin consumption). Each column represents one fecal sample (three samples from each individual with the participant ID no: 1,2,6,7,8,9,10,12,14,16,17,18) and each row shows one OTU with its taxonomic classification of the closes t match to the greengenes microbiota reference database. All samples are significant by z test. Other notations: (*) significant by two sample t test and (!) annotated using BLAST tool. A B C


37 Figure 4 6. Bacterial OTUs affected by sun dried raisin consumption at 98% similarity level Columns show fecal samples and rows show annotated OTUs. All samples are significant by z test. A B C


38 CHAPTER 5 DISCUSSION AND CONCLUSION Increasing the dietary intake of raisins has been suggested to have beneficial effects on human gut microbiota and improved health (14, 58 60, 64) However, the association between raisin intake and gut microbiota has not been investigated among humans. Therefore, this study evaluated the effect of raisins on the o ve rall gut microbiome composition and specific bacterial signatures by including thirteen healthy participants for a two week study Effect of raisins on overall gut microbial diversity has not been investigated before. Raisin intake did not significantly c hange b oth the alpha diversity (within time points) and beta diversity (between time points) ( Figure 4 1 Figure 4 2 and appendix A, Figure A 1). Although raisin intake seem ed to increase the relative abundance of Bacteroidetes and decrease Firmicutes, phy lum level OTU abundance did not differ significantly with raisin consumption ( Figure 4 3, Figure 4 4 and A ppendix A, Figure A 2). Inter individual variation could possibly interfere with the net effect of raisins observed in this study due to differences i n age BMI and possible dietary habits ( Figure 4 2, Table 4 1). Many dietary interventions with fruits have documented similar observations as to overall gut microbiota composition (13, 36, 38) In fact polyphenolic compounds in the grape extract are found to be associated with reshaping gut microbiota towards a homeostatic balance (55, 57) Thus these observations may suggest a possible contributi on of raisins in gut microbial homeostasis in healthy adults. Although the overall microbiome composition seems to remain at homeostatic balance, some specific bacterial signatures significantly correlate with raisin consumption ( Figure 4 5, Figure 4 6). T his study observations suggest that raisins


39 exert complex and selective effects on different groups of gut microbiota, possibly due to the complex nutrient and polyphenolic profile of raisins. Among many OTUs evaluated abundance of several OTUs with kno wn health correlations were influenced with raisin intake, including Faecalibacterium prausnitzii, Klebsiella sp., Prevotella sp., certain Bacteroidetes spp., Bifidobacterium spp. Ruminococcaceae and Lactobacillus sp ( Figure 4 5, Figure 4 6). These observations regarding OTUs must be interpreted carefully because without replicating the study accuracy or the reliability of the observations cannot be confirmed. In contrast to Mandalari et al., who suggested reduced abundance of Faecalibacterium praus nitzi i in human fecal samples after incubation with digested sun dried raisin (human gastrointestinal model) (14) this study observed an increa se of OTUs matching F. prausnitzi i in week one and week two fecal samples obtained after raisin intake ( Figure 4 5). Decrease of F. prausnitzi i in the gut correlates with chronic inflammation, colon polyps and many other diseases (80, 81) Increase of F prausnitzii has been reported with increased intake of Inulin, a common phytochemical present in raisins (82) Higher concentrati on of Inulin or a combination of phytochemicals might have increased the OTUs matching F prausnitzii (57, 82) Future studies can investigate the effect of specific phytochemicals present in raisins on human gut microbiota. Bacterial signatures matching Klebsiella sp. show a significant decrease in the number of OTUs, one week after addition of raisi ns to the diet. This may suggest that increased intake of raisins correlate with reduced risk of enteric inflammation associated with subclinical infection ( Figure 4 5, Figure 4 6 and A ppendix A, Figure A 3). However,


40 t he number of OTU seems to increase sl ightly by the end of the week two Non compliance with the study protocol or adaptation of bacteria to raisins could be two possible explanations. Two studies have suggested inverse association of potential enteric pathogens with sun dried raisin, and the combination of red wine and grape juice extracts, by using human gastr ointestinal models (14) However, the potential pathogen resistant effect of raisins is consistent with many of the in vitro and in vivo grape se ed studies (52, 54, 68) The presence of certain polyphenolics such as flavonoids and proanthocyanidine, gallate esters, and fibers in grape seeds indu ces th e anti pathogenic activity (65, 69) Pathogen resistant compounds similar to that of grape seeds may also be present in raisins (65, 69) This study observed a decrease of OTUs closest to Prevotella sp. with the addition of raisins to the diet. Previous studies ha ve shown an increase in Prevotella sp. with increased intake of fibers and other plant derived food compared to low fiber, high fat, western diet (63, 83) Although many studies correlate Prevotella sp. with improved gut health (84) others state that some species such as Prevotella copri could indica te chronic inflammation, r heumatoid arthritis and cardiovascular disease (83, 85, 86) Four OTU s that are similar to Bacteroidetes sp. including B. uniformis showed an increase with the addition of raisins to the diet. Previous studies have demonstrated that grape derived produ cts have increased B. uniformis (65, 68) Increased number of B. uniformis is associated with stimulation of the adaptive immune function, ameliorating metabolic dysfunction as well as reducing the weight gain in obese animal models (87, 88) B.uniformis may also contribute to the pathogen resistant properties of raisins by


41 converting querectin (flavonol) in raisins to Aglycon; Aglycon has detrimental effects on the growth of Staphylococcus aureus and Helicobacter pylori (65) A significant decrease in OTUs representing Bifidobacterium sp. with the addition of raisins into the diet was observed ( Figure 4 6). In addition, one OTU matching Bifidobacteri um longum show a significant increase after two weeks of raisin consumption compared to week one ( Figure 4 6). Mandalari et al claim that raisins increase Bifidobacterium sp (14) Previous studies have documented that Bifidobacterium sp p are subjected to s elective growth with grape polyphenols based on sensitivity/resistance to anti bacterial grap e polyphenols (52, 68) Bifidobacteri um spp. are also SCFA producers and are associated with be neficial health outcomes and are r ecommended by the World He alth Organization (WHO) as a pro biotic supplement (82, 89) Reduction of certain Bifidobacterium sp. could reduce dietary fermentation and correlate with dysbiosis (89) Increase in B. longum with grape inulin and fructo oligosaccharide has been documented (48, 82) Future studies could target Bifidobacterium sp p. to identify species specific effects with raisin consumption. Raisin consumption has shown diverse effects on bacterial signatures matching Ruminococca ceae. A significant increase in two OTUs matching Ruminococcaeae was observed with raisin consumption while another OTU matching Ruminococcace ae show a decrease only at week two ( Figure 4 6). An OTU matching Lactobacillus sp shows a significant increase in week two compared to week one ( Figure 4 6). Previous studies suggest that the effect on Lactobacillus sp. can vary with different grape products (52, 90) Both Lactobacillus sp. and Ruminococcaceae benefit gut environment by pathogen inhibition, providing essential nutrients and SCFA and immune modulation (8, 52)


42 This is the first human feeding study to evaluate the influence of sun dried raisins on gut microbiota Mandalari et al was t he first to evaluate short term effects of raisins on gut microbiota (less than one hour to 24 hours) using a gut stimulator mimicking the human gut (14) However, their choice of comparison group, duration of the study, use of in vitro model and different analytical methods restrict inferences regarding the effect of raisins on human gut microbiota and also limit direct comparison with this study (14) Although study findings are consistent with the hypothesis that raisin intake contribute s to beneficial changes in the human gut microbiota composition, further research needs to be conducted with controlled inter individual parameters such as age, gender, race, BMI and other dietary habits or a representative sample from the US population with more study participants Because t here were no previous human studies on raisins and gut microbiota interaction, the effect size could not be determined to calculate an ideal sample size. However, many small scale dietary interventions with fruits have found significant observations in gut microbiota indicating that the sample size used in this study is sufficient to observe a significant change (82, 84, 91) The n umber of OTUs significantly affected by raisin intake is greater in week one compared to week two. Raisins seem to exert a str onger effect during week one or it could be that the participants did not fully meet the required raisin intake even though the reported compliance to the study protocol was high Participants continuous consumption of raisins suggests the need for reduced number of servings (three ) or feeding frequency (less than daily). Incorporating raisins to other food products such as yogurt or meals such as salads could be suggested to improve compliance.


43 To provide support to observed changes in microbi ota due to raisin intake future studies could incorporate measures of SCFA and bile acid concentration, fecal weight, B ristol stool measurements and a food log or conduct a metabolomics analysis of fecal microbiota (60, 64) .A prospective epidemiologic study could determine potential long term e ffects of raisins on gut microbiota and health in the general population. Carefully controlled dietary interventions could identify specific contributions of raisins to human health. Conclusion. Adding sun dried raisins to the diet seem s to in duce beneficial changes in several bacterial OTUs including the increase of OTUs matching Faecalibacterium prausnitzii and Bacteroidetes sp and the decrease of a bacterial OTU matching enteric pathogen Klebsiella sp.


44 APPENDIX A SUPPLE MENTARY FIGU RES OF RESULTS SECTION Table A 1. Primer combination for 16S rRNA gene PCR amplification Primer Primer sequence 27F Forward Primer AATGATACGGCGACCACCGAGATCTACAC TATGGTAATT CC 338R Reverse Primer CAAGCAGAAGACGGCATACGAGAT TCCCTTGTCTCC AGTCAGTCAG AA mer: er, *Primers contain a linker sequence that bind to the flow cell. Specific bar code to identify different samples, adapters provide sticky ends to attach to the flow cell. Length of the PCR product is 250 base pairs. Table A 2. Primer combination for 16S rRNA gene sequencing on Illumina MiSeq MiSeq custom sequence primers Primer sequence Read 1 Read 2 Index Index sequence allows 96 different samples to be sequenced on one flow cell, thus increasing the throughput. Read 1 and Read 2 allow accurate sequence alignment, detect insertions or deletions and PCR duplicates


45 Figure A 1 UniFrac beta diversity analysis by feeding time point s Un weighted UniFrac analysis based on 16S rDNA MiSeq sequences from stool samples (circles), measured before, during and after the raisin feeding period (baseline/day0, week1/day 7 and week2/day14 respectively ) All the samples from each time point were assigned a different color code (Baseline: blue, week 1: red and week 2: green) to visualize the microbial diversity variation at each time point. A single circle represent s a single sample from one of thirteen healthy volunteers (total sample size 39 ).


46 Figure A 2 Changes in the proportion of operational taxonomic subunits grouped into four most abundant bacterial phyla. Based on 16S rDNA similarity, individual sequence reads were matched to the closest reference sequence in greengenes database at 95% similarity level. OTUs were grouped into phylum level at each time point. Stool samples of 13 participants were analyzed at baseline (before raisin consumption), week 1 (du ring raisin consumption at day 7) and week 2 (after raisin consumption at day 14). Phyla with less than 1% prevalence at all three time points were grouped as other phyla Figure A 3. Heat map depicting the variations in an OTU closest to Klebsiella spp affected by raisin consumption at 95% similarity level. The OTU matching Klebsiella spp taken fro m figure 4 8 with an OTU count color separation rage of 0 to 5, B: same OTU with a enhanced color separation range of 0 to 100 as indicated in th e top left color intensity bar.


47 APPENDIX B DNA EXTRACTION PROTOCOL Pre processing of fecal samples Fecal samples were collected and stored at 8 0 C in RNAlater solution. Stock samples were thawed once, homogenized and half a pea ( 200 300 mg ) sized solid stool or 300 500 L loose stoo l were measure into separate 2mL micro centrifuge tubes (stored in 4 C or used immediately without storage). Three glass beads were added to the stool sample tubes along with 1 m L 0.05 M phosphate buffer and vortex ed until the stool was thoroughly homogenized. Thereafter the sam ples were centrifuged at maximum speed ( Table centrifuge >10.000 rpm) and pellet s were saved Washing of the samples were carried out again using 1 m L 0.05 M phosphate buffer similar t o previous step DNA extraction DNA isolation was conducted using QIAamp stool mini DNA kit (25) Few changes to the original protocol have been made. After hea ting the fecal sample and ASL buffer suspension, 0.3 g of zirconia beads were added to each tube and bead beating was performed for 3 min. In this protocol after incubation with InhibitEX tablet and centrifugation, 1.2 m L of the supernatant was used for th e next step. Volumes of chemical solutions used in this study slightly differ from the original protocol : 25 L Proteinase K 400 L AL buffer and a 400 L of 200proof ethanol After applying the lysate and completing the washing steps as in the original protocol, pre heated 100 L of AE buffer (heated at 65 C for 5 10 min ute ) was transferred to the QIAamp spin column with a new labeled 1.5 m L micro centrifuge tube Tubes were i ncubate d at room temperature for 5 min ute and then centrifu ge d at full speed for 1 min ute to elute DNA.






50 LIST OF REFERENCES 1. Sekirov I, Finlay BB. The role of the intestinal microbiota in enteric infection. J Physiol 2009;587(17):4159 67. [PubMed:19491248] 2. Turnbaugh PJ, Ley RE, Hamady M, Fraser Liggett C, Knight R, Gordon JI. The Human Microbiome Project. Nature 2007;449(7164):804 10. [ PubMed:17943116] 3. Gibbons SM, Kearney SM, Smillie CS, Alm EJ. Two dynamic regimes in the human gut microbi ome. PLOS Comput Biol 2017;13(2):e1005364. [PubMed:28222117] 4. D'Argenio V, Salvatore F. The role of the gut microbiome in the healthy adult status Clin Chim Acta 2015;45 :97 102. [PubMed:25584460] 5. LeBlanc JG, Milani C, de Giori GS, Sesma F, Van Sinderen D, Ventura M. Bacteria as vitamin suppliers to their host: a gut m icrobiota perspective. Curr O pin B i otechnol 2013;24(2):160 8. [PubMed:22940212] 6. Kau AL, Ahern PP, Griffin NW, Goodman AL, Gordon JI. Human nutrition, the gut microbiome and the immune system. Nature 2011;474:327 36. [PubMed:21677749] 7. Maier E, Anderson RC, Roy NC. Understanding How Commensal Obligate Anaerobic Bacteria Regulate Immune Functions in the Large Intestine. Nutrients 2015;7(1):45 73. [PubMed:25545102] 8. Arnolds KL, Lozupone CA. Striking a Balance with Help from our Little Friends ; How the Gut Microbiota Contributes to Immune Homeostasis. Yale J Biol Med 2016;89(3):389 95. [PubMed:27698623] 9. Flint HJ, Scott KP, Louis P, Duncan SH. The role of the gut microbiota in nutrition and health. Nat Rev Gastroenterol Hepatol 2012;9(10):577 89. [PubMed:22945443] 10. De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB Massart S, et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Nat l Acad Sci 2010;107(33):14691 6. [PubMed:20679230] 11. Klinder A, Shen Q, Heppel S, Lovegrove JA, Rowland I, Tuoh y KM. Impact of increasing fruit and vegetables and flavonoid intake on the human gut microbiota. Food Funct 2016;7(4):1788 96. [PubMed:26757793] 12. Ukhanova M, Wang X, Baer DJ, Novotny JA, Fredborg M, Mai V. Effects of almond and pistachio consumption on gut microbiota composition in a randomised cross over human feeding study. Br J Nutr 2014;111(12):2146 52. [PubMed:24642201]


51 13. Eid N, Osmanova H, Natchez C, Walton G, Costabile A, Gibson G, et al. Impact of palm date consumption on microbiota growth and large intestinal health: a randomised, controlled, cross over, human intervention study. Br J Nutr 2015;114(8):1226 36. [PubMed:26428278] 14. Mandalari G, Chessa S, Bisignano C, Chan L, Carughi A. The effect of sun dried raisins (Vitis vinifera L.) on the in vitro composition of the gut microbiota. Food Funct 2016 ; 7(9):4048 4060 [PubMed:27713974] 15. Puupponen PR, Seppnen L T, Kankainen M, Maukonen J, Trrnen R, Kolehmainen M, et al. Effects of ellagitannin rich berries on blood lipids, gut microbiota, and urolithin production in human subjects with symptoms of metabolic syndrome. Mol Nutr Food Res 2017;57(12):2258 63. [PubMed:23934737] 16. Rodrguez JM, Murphy K, Stanton C, Ross RP, Kober OI, Juge N, et al. The composition of the gut microbiota througho ut life, with an emphasis on early life. Microb Ecol Health D is 2015; 26: 26050 [PubMed:25651996] 17. Di Lorenzo C, Sangiovanni E, Fumagalli M, Colombo E, Frigerio G, Colombo F, et al. Evaluation of the Anti Inflammatory Activity of Raisins (Vitis vinife ra L.) in Human Gastric Epithelial Cells: A Comparative Study. Int J Mol Sci 2016;17(7):1156. [PubMed:27447609] 18. Chatelier EL, Nielsen T, Qin J, Prifti E, Hildebrand F, Falony G, et al. Richness of human gut microbiome correlates with metabolic markers. Nature 2013;500:541 6. [PubMed:23985870] 19. Jandhyala SM, Talukdar R, Subramanyam C, Vuyyuru H, Sasikala M, Reddy DN. Role of the normal gut mi crobiota. World J Gastroenterol 2015;21(29):8787 803. [PubMed:26269668] 20. Lozupone CA, Stombaugh JI, Gordon J I, Jansson JK, Knight R. Diversity, stability and resilience of the human gut microbiota. Nature 2012;489:220 30. [PubMed:22972295] 21. Goodrich JK, Di Rienzi SC, Poole AC, Koren O, Walters WA, Caporaso JG, et al. Conducting a Microbiome Study. Cell 2014;1 58(2):250 62. [PubMed: 25036628 ] 22. Mai V, Ukhanova M, Baer DJ. Understanding the Extent and Sources of Variation in Gut Microbiota Studies; a Prerequisite for Establishing Associations with Disease. Diversity 2010;2(9):1085 96. 23. McOrist AL, Jackson M, Bird AR. A comparison of five methods for extraction of bacterial DNA fr om human faecal samples. J Microbiol Methods 2002;50(2):131 9. [PubMed: 11997164 ]


52 24. Li M, Gong J, Cottrill M, Yu H, de Lange C, Burton J, et al. Evaluation of QIAamp DNA Stool Mini Kit for ecological studies of gut microbiota. J Microbiol Methods 2003;54(1):13 20. [PubMed: 12732417 ] 25. QIAG EN. QIAamp DNA Stool Handbook 2:[Available from: ] 26. Song SJ, Amir A, Metcalf JL, Am ato KR, Xu ZZ, Humphrey G, et al. Preservation Methods Differ in Fecal Microbiome Stability, Affecting Suitability for Field Studies. mSystems 2016;1(3):e00021 16. [PubMed:27822526] 27. Westcott SL, Schloss PD. De novo clustering methods outperform referen ce based methods for assigning 16S rRNA gene sequences to operational taxonomic units. PeerJ 2015;3:e1487. [PubMed:26664811] 28. Shokralla S, Spall JL, Gibson JF, Hajibabaei M. Next generation sequencing technologies for environmental DNA research. Mol Eco l 2016;21(8):1794 805. [PubMed:22486820] 29. Edgar RC. UCLUST algorithm: Drive5; 2016 [Available from: ] 30. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. Greengenes, a chimera checked 16S rRNA gene database and workbe nch compatible with ARB. Appl and Environ Microbiol 2006;72(7):5069 72. [PubMed:16820507] 31. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high throughput community sequencing data. Nature Methods 2010;7(5):335 6. [PubMed:20383131] 32. Kuczynski J, Stombaugh J, Walters WA, Gonzlez A, Caporaso JG, Knight R. Using QIIME to analyze 16S rR NA gene sequences from Microbial Communities. Curr Protoc Bioinformatics 2011; 10. [PubMed:226161565] 33. Hiergeist A, Reischl U, Gessner A. Multicenter quality assessment of 16S ribosomal DNA sequencing for microbiome analyses reveals high inter c enter var iability. Int J Med Microbiol 2016;306(5):334 42. [PubMed:27052158] 34. Magurran AE, McGill BJ. Biological diversity: frontiers in measurement and assessment: Oxford University Press; 2011. ] 35. COLLOS. 2.2.4. Alpha diversity COLOSS 2013. [ Available fro m: symbionts/2/2/4 ] 36. Graf D, Cagno RD, Fk F, Flint HJ, Nyman M, Saarela M, et al. Contribution of diet to the composition of the human gut microbiota Microb Ecol Health Dis 2015;26. [PubMed:25656825]


53 37. Mai V, Draganov PV. Recent advances and remaining gaps in our knowledge of associations between gut microbiota and human health. World J Gastroenterol 2009;15(1):81 5. [PubMed:27052158] 38. Eicher Miller H, Boushey C. How Often and How Much? Differences in Dietary Intake by Frequency and Energy Contribution Vary among U.S. Adults in NHANES 2007 2012. Nutrients 2017;9(1):86. [PubMed:19115471] 39. Iqbal S, Quigley EM. Progress in Our Understand ing of the Gut Microbiome: Implications for the Clinician. Curr Gastroenterol Rep 2016;18(9):49. [PubMed:27448618] 40. Key TJ, Schatzkin A, Willett WC, Allen NE, Spencer EA, Travis RC. Diet, nutrition and the prevention of cancer. Public Health Nutr 2004;7 (1):187 200. [PubMed:14972060] 41. Eid N, Walton G, Costabile A, Kuhnle GG, Spencer JP. Polyphenols, glucosinolates, dietary fibre and colon cancer: Understanding the potential of specific types of fruit and vegetables to reduce bowel cancer pr ogression IOS Press. Nutr Aging 2014;2(1):45 67. 42. Kountouri AM, Gioxari A, Karvela E, Kaliora AC, Karvelas M, Karathanos VT. Chemopreventive properties of raisins originating from Greece in col on cancer cells. Food Funct 2013;4(3):366 72. [PubMed:23211994] 43. R eicks M, Jonnalagadda S, Albertson AM, Joshi N. Total dietary fiber intakes in the US population are related to whole grain consumption: results from the National Health and Nutrition Examination Survey 2009 to 2010 2014;34(3):226 34. [PubMed:24655489] 44 Kushi LH, Doyle C, McCullough M, Rock CL, Demark WW, Bandera EV, et al. American Cancer Society guidelines on nutrition and physical activi ty for cancer prevention. CA J Clin 2012;62(1):30 67. [PubMed:22237782] 45. U.S. Departmen t of Health and Human Ser vices: US D epartment o f A griculture Dietary guidelines for Americans 2015 2020. 6 e d. Washington, DC: U.S. Government Printing Office; 2015. 46. Moore LV, Thompson FE. Adults meeting fruit and vegetable intake recommendations Uni ted States, 2013. 2015; 6 4(26): 709 13. [ Available from: ] 47. U. S. Department of Agriculture Agricultural Research Service. USDA Branded Food Products Datab ase, 45086068, Sun Maid N atural California Raisins UPC: 041143124604 2017 [Available from: ]


54 48 De la Cerda Carrasco A, Lopez SR, Nunez K H, Pena NA, Obreque S E. Phenolic composition and antioxidant capacity of pomaces from four grape varieties (Vitis vinifera L.). J Sci Food Agric 2015;95(7):1521 7. [PubMed:25082193] 49. Firmicutes/Bacteroi detes ratio of the human microbiota ch anges with age. BMC microbiol 2009;9(1):1. [PubMed:19508720] 50. Reisch BI, Owens CL, Cousins PS. Fruit Breeding: Springer US; 2016. [ Available from: 1 4419 0763 9_7/fulltext.html ] 51. California Raisin Marketing Board. Raisins in Ancient times. 2016 [Available from: raisin industry/history/ ] 52. Quintela A, Milagro FI, Aguirre L, Martnez JA, Portillo MP. Impact of Polyphenols and Polyphenol Rich Dietary Sources on Gut Microbiota Composition. J Agric F ood chem 2013;61(40):9517 33. [PubMed:14972060] 53. Yadav D, Kumar A, Kumar P, Mishra D. Antimicrobial properties of black grape (Vitis vinifera L.) peel extracts against antibiotic resistant pathogenic bacteria and toxin prod ucing molds. Indian J P harmacol 2015;47 (6):663. [PubMed:26729960] 54. activities of grape (Vitis vinifera L.) extracts. 2004;15(5):335 9. 55. Viveros A, Chamorro S, Pizarro M, Arija I, Centeno C, Brenes A. Effects of dietar y polyphenol rich grape products on intestinal microflora and gut morphology in broiler chicks. Poult Sci 2011;90(3):566 78. [PubMed:21325227] 56. Kafantaris I, Kotsampasi B, Christodoulou V, Kokka E, Kouka P, Terzopoulou Z, et al. Grape pomace improves an tioxidant capacity and faecal microflora of lambs. J Anim Physiol Anim Nu tr 2016. [PubMed:27753147] 57. Impei S, Gismondi A, Canuti L, Canini A. Metabolic and biological profile of autochthonous Vitis vinifera L. ecotypes. Food Funct 2015;6(5):1526 38. [Pu bMed:25820686] 58. Raisins in human health: A review. BIO Web of Conferences. 2017;7:04005. 59. Spiller GA, Story JA, Furumoto EJ, Chezem JC, Spiller M. Effect of tartaric acid and dietary fibre from sun dried raisins on colonic function and on bile acid and volatile fatty acid excretion in healthy adults. Br J Nutr 2003;90(4):803 7. [PubMed:13129449] 60. Camire ME, Dougherty MP. Raisin Dietary Fiber Composition and in Vitr o Bile Acid Binding. J Agric Food Chem 2003;51(3):834 7. [PubMed:12537466]


55 61. phenolic compounds Int J Food Sci Nutr 200 1 [PubMed: 11570016 ] 62. Reis GM, Faccin H, Viana C, Rosa MB, de Ca rvalho LM. Vitis vinifera L. cv Pinot noir pomace and lees as potential sources of bioactive compounds. Int J Food Sci Nutr 2016;67(7):789 96. [PubMed:27381473] 63. Selma MV, Espin JC, Tomas Barberan FA. Interaction between phenolics and gut microbiota: ro le in human health. J Agric Food Chem 2009;57(15):6485 501. [PubMed:19580283] 64. Spiller GA, Story JA, Lodics TA, Pollack M, Monyan S, Butterfield G, et al. Effect of Sun Dried Raisins on Bile Acid Excretion, Intestinal Transit Time, and Fecal Weight: A D ose Response Study. J Med Food 2 003;6(2):87 91 [PubMed:12935318] 65. Williamson G, Carughi A. Polyphenol content and health benefits of raisins. Nutr Res 2010;30(8):511 9. [PubMed:20851304] 66. Yang G, Wang H, Kang Y, Zhu MJ. Grape seed extract improves epithelial structure and suppresses inflammation in ileum of IL 10 deficient mice. Food F unct 2014;5(10):2558 63. [PubMed:25137131] 67. Bull MJ, Plummer NT. Part 1: The Human Gut Mic robiome in Hea lth and Disease. Int egr Med 2014; 13(6): 17 22. [PubMed:26770121] 68. Kemperman RA GG, Mondot S, Possemiers, S., Marzorati M, Van de Wiele T, Dor J, Vaughan EE. Impact of polyphenols from black tea and red wine/grape juice on a gut model microbi ome. Food R es Int 2013;53(2):659 69. 69. Yi NN. Antimicrobial Activity and Health Benefits of Red Wine from Grap e. Univ Res J 2011;4(3):153 65. 70. O'Hara AM, Shanahan F. The gut flora as a forgotten organ. EMBO Rep 2006;7(7):688 93. [PubMed:16819463] 71. Yang JY, Zh ang HJ, Wang J, Wu SG, Yue HY, Jiang XR, et al. Effects of dietary grape proanthocyanidins on the growth performance, jejunum morphology and plasma biochemical indices of broiler chicks. Animal 2016:1 9. [PubMed:27774930] 72. Anderson JW, Waters AR. Raisin Consumption by Humans: Effects on Glycemia and Insulinemia and Cardiova scular Risk Factors. J Food Sci 2013;78(s1). [PubMed: 23789931 ] 73. Esfahani A, Lam J, Kendall CWC. Acute effects of raisin consumption on glucose and insulin reponses in healthy indivi duals. J Nutr Sci 2014;3. [PubMed: 25191601 ]


56 74. Rietschier HL, Henagan TM, Earnest CP, Baker BL, Cortez CC, Stewart LK. Sun dried raisins are a cost effective alternative to Sports Jelly Beans in prolonged cycling. J Strength Cond Res 2011;25(11):3150 6. [ PubMed:21881533] 75. Kasubuchi M, Hasegawa S, Hiramatsu T, Ichimura A, Kimura I. Dietary gut microbial metabolites, short chain fatty acids, and host metabolic regulation. Nutrients 2015;7(4):2839 49. [PubMed:25875123] 76. Maslowski KM, Mackay CR. Diet, gu t microbiota and imm une responses. Nat Immunol 2011;12(1):5 9. [PubMed:21169997] 77. California S un M aid Growers. Sun Maid California. 2016 [Available from: ] 78. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local a lignment search tool. J Mol Biol 1990;215(3):403 10. [PubMed:2231712] 79. Pavlidis P, Noble WS. Matrix2png: a utility for visualizing matrix data. Bioinformatics 2003;19(2):295 6. [PubMed:12538257] 80. Miquel S, Martin R, Rossi O, Bermudez Humaran LG, Chatel JM, Sokol H, et al. Faecalibacterium prausnitzii and human intestinal health. Curr O pin M icrobiol 2013;16(3):255 61. [PubMed:23831042] 81. Eppinga H, Sperna Weiland CJ, Thio HB, van der Woude CJ, Nijsten TE, Peppelenbos ch MP, et al. Similar Depletion of Protective Faecalibacterium prausnitzii in Psoriasis and Inflammatory Bowel Disease, but not in Hidradenitis Suppurativa. J Crohns Colitis 2016;10(9):1067 75. [PubMed:26971052] 82. Ramirez Farias C, Slezak K, Fuller Z, Duncan A, Holtrop G, Louis P. Effect of inulin on the human gut microbiota: stimulation of Bifidobacterium adolescentis and Faecalibacterium prausnitzii. Br J Nutr. 2009;101(4):541 50. [PubMed:18590586] 83. Ley RE. Gut microbiota in 2015: Prevotella in the gut: choose carefully. Nat Rev Gastroenterol Hepatol 2016;13:69 70. [PubMed:26828918] 84. Queipo Ortuno MI, Boto Ordonez M, Murri M, Gomez Zumaquero JM, Clemente Postigo M, Estruch R, et al. Influence of red wine polyphenols and ethanol on the gut microbi ota ecology and biochemical biomarkers. Am J Clin Nutr. 2012;95(6):1323 34. [PubMed:22552027] 85. Scher JU, Sczesnak A, Longman RS, Segata N, Ubeda C, Bielski C, et al. Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to art hrit is. Elife 2013;e01202. [PubMed:24192039]


57 86. Brusca SB, Abramson SB, Scher JU. Microbiome and mucosal inflammation as extra articular triggers for rheumatoid arthritis and autoimmunity. Curr Opin Rheumatol 2014;26(1):101 7. [PubMed: 24247114 ] 87. Gauffi n CP, Santacruz A, Moya A, Sanz Y. Bacteroides uniformis CECT 7771 ameliorates metabolic and immunological dysfunction in mice with high fat diet induced obesity. PLoS One 2012;7(7):e41079. [PubMed: 22844426 ] 88. Kim H, Kim DH, Seo KH, Chon JW, Nah SY, Bart ley GE, et al. Modulation of the Intestinal Microbiota Is Associated with Lower Plasma Cholesterol and Weight Gain in Hamsters Fed Chardonnay Grape Seed Flour. J Agric Food Chem 2015;63(5):1460 7. [PubMed: 25598538 ] 89. O'Callaghan A, van Sinderen D. Bifido bacteria and Their Role as Members of the Human Gut Microbiota. Front Microbiol 2016;7. [PubMed: 27379055 ] 90. Hidalgo M, Oruna Concha MJ, Kolida S, Walton GE, Kallithraka S, Spencer JP, et al. Metabolism of anthocyanins by human gut microflora and their in fluence on gut bacterial growth. J Agric Food Chem 2012;60(15):3882 90. [PubMed: 22439618 ] 91. David LA, Materna AC, Friedman J, Campos Baptista MI, Blackburn MC, Perrotta A, et al. Host lifestyle affects human m icrobiota on daily timescales. Genome Biol 15 2014. [PubMed: 25146375 ]


58 BIOGRAPHICAL SKETCH Akemi Thakshila Wijayabahu was born in Kandy, Sri Lanka. She completed her undergraduate education at the University of Peradeniya, Sri Lanka with a first class honors in molecular biology and biotechnology special degree in January, 2008. Akemi received h er Master of Science i n E pidemiology from The University of Florida. While simultaneously working for the Department of Epidemiology and at Emerging Pathogen Throughout her graduate studies at the University of Florida, Akemi was involved with the HIV and Alcohol Research C onsortium (SHARC) had contributed as a research assistant at D epartm ent of Epidemiology and E merging Pathogen I nstitute, and worked as a graduate teaching assistant, teach ing Healthcare leade rship for undergraduates under Bachelor of H ealth S cience program, University of Florida.