Application of Fluorescence in Situ Hybridization for Visualization and Quantification of Human Gastrointestinal Microbiota

Home , In situ

Application of Fluorescence in situ Hybridization

for Visualization and Quantification of Human

Gastrointestinal Microbiota

A thesis submitted in partial fulfillment of the requirements for

the degree of Master of Science

ALEXANDER MACKENZIE GORDON

B.S. Ohio University, 2012

2015

Wright State University

WRIGHT STATE UNIVERSITY

GRADUATE SCHOOL

August 17, 2015

I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY Alexander Mackenzie Gordon ENTITLED Application of Fluorescence in situ Hybridization for Visualization and Quantification of Human Gastrointestinal Microbiota. BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science.

______Oleg Paliy, Ph.D. Thesis Director

______Barbara Hull, Ph.D., Director Committee on Microbiology and Immunology Program Final Examination College of Science and Mathematics

______Oleg Paliy, Ph.D.

______Barbara Hull, Ph.D.

______Shulin Ju, Ph.D.

______Robert E. W. Fyffe, Ph.D. Vice President for Research and Dean of the Graduate School

Abstract Gordon, Alexander Mackenzie. M.S., Microbiology and Immunology M.S. Program, Wright State University, 2015. Application of Fluorescence in situ Hybridization for Visualization and Quantification of Human Gastrointestinal Microbiota.

The microbiota of the human gastrointestinal tract is the focus of current research due to their role in human health and disease. Modern methods characterize the communities of gut microbiota through the use of culture independent techniques. Technologies such as microarrays and next generation sequencing (NGS) determine microbial profiles by analyzing the pool of 16S ribosomal small subunit RNA genes in the community. These techniques operate through the measurement of genomic content rather than through direct analysis of cells. This approach predisposes the methods to discrepancies and bias. In contrast, the use of fluorescence in situ hybridization (FISH) to analyze the gut microbiota allows for the visualization of the cells as well as determination of relative abundances of target taxa. This work describes the application of FISH to visualize the relative abundances of several different members of human gut microbiota between select samples. The results showed that the abundance data obtained from

FISH are similar to data collected with microarray and NGS techniques. FISH data demonstrated that there is an enrichment of class Bacilli and genus Prevotella in the gastrointestinal tract of Egyptian children, while children from the U.S. show a higher level of genus Bacteroides. This study also showed that the abundances of class Bacteroidia and genus

Bifidobacterium fluctuate in adults undergoing a diet intervention program replacing typical diets with high-protein or high-fat diets. In conclusion, this work illustrates the capabilities of FISH to visualize the members of human gut microbiota and quantify relative abundances of target taxa that are a part of a larger community.

iii Table of Contents • Introduction………………………………………………………………………………1-12 o Microbiota o Microbiota of the gastrointestinal tract o Gastrointestinal microbiota and human health o Microbiota and nutrition o Microbiota and geography o Profiling gut microbiota o Visualization of microbiota o Fluorescence in situ hybridization applied to microbiota o Overview of thesis work

• Methods………………………………………………………………………………….12-19 o Sample collection o Isolation of fecal microbiota o FISH probe design and optimization o Treatment of bacterial cells with lysozyme o Probe hybridization protocol o Slide preparation and microscopy o Image editing and analysis

• Results……………………………………………………………………………………20-31 o Application of fluorescence in situ hybridization to visualize human fecal microbiota isolated from volunteers undergoing shot term diet changes o Design and optimization of fluorescent DNA probes for use in fluorescence in situ hybridization o Application of fluorescence in situ hybridization to visualize human gastrointestinal microbiota isolated from geographically distinct adolescent populations

• Discussion……………………………………..…………………………………………32-34

• References………………………………………………………………………………..35-39

• Appendices………………………………………………………………………………….40

o Table of Abbreviation

List of Figures Figure 2.1: Alignment of probe sequences with 16s RNA gene sequences……………………..16 Figure 2.2: Positive and negative controls of newly designed FISH probes…………………….16 Figure 3.1: aNUT diet comparisons……………………………………………………………...22 Figure 3.2: Bac303 probe FISH images………………………………………………………….23 Figure 3.3: Bif164 probe FISH images…………………………………………………………..23 Figure 3.4: Comparisons of egkHLT and uskHLT samples…………………………….……….28 Figure 3.5: FISH images of probes used in uskHLT-egkHLT project…………………………..29

List of Tables Table 2.1: Volunteer information………………………………………………………………..13 Table 2.2: FISH probe DNA sequences…………………………………………...……………..15 Table 2.3: Probe specificity and accuracy according to RDP……………………………………15 Table 2.4: FISH probe hybridization mixtures…………………………………………………..18 Table 2.5: Wash buffer recipes…………………………………………………………..………18 Table 3.1: aNUT FISH relative abundances with standard error………………………………...21 Table 3.2: aNUT microarray adjusted relative abundances……………………………………...22 Table 3.3: aNUT FISH image cell counts for Bacteroidia……………………………………….24 Table 3.4: aNUT FISH image cell counts for Bifidobacterium………………………………….25 Table 3.5: FISH relative abundances for uskHLT and egkHLT volunteers with standard error...28 Table 3.6: NGS adjusted relative abundances for egkHLT and uskHLT volunteers……………30 Table 3.7: FISH image cell counts for egkHLT samples………………………………………...30 Table 3.8: FISH image cell counts for uskHLT samples………………………………………...31

vi 1. Introduction.

Microbiota

Microbes are the unseen living creatures existing in almost every habitat on Earth

[1]. They live in deep-sea vents, they are inhabitants of the soil, and they form complex communities inside the intestines of multicellular organisms. Their survival and characteristics are dependent on requirements and specifications that are incredibly diverse. Some tolerate oxygen while others are strict anaerobes, some microbes can survive extreme ranges of pH and others only grow in neutral environments, some microbes are benign to a human host under some conditions but become pathogenic when those conditions are disturbed. There is great interest in microscopic organisms as evidenced by the number of diverse fields of study dedicated to them [2-4].

A large focus of the study of microbiology has been the microbes associated with the human body. The niches of the human body include the skin, hair, and the mucosal linings, all of which are inhabited by microbes. A study by Grice et al. (2008) surveyed the microbiota of the different layers of human skin [5]. They determined through the sequencing of the 16S small-subunit ribosomal RNA gene that there were 113 operational taxonomic units (OTUs) associated with the inner elbow across five human subjects. The authors identified the phylum Proteobacteria as the most abundant on all healthy patients and at all sampled skin layers. They also describe that there is as much diversity within an individual’s population as there is between individuals. This particular pattern of diversity is mentioned by the authors to be dissimilar to the patterns of diversity observed in studies of the gut microbiota.

1 Contrary to what was observed on the skin by Grice et al., the primary phyla of the gut microbiota are Firmicutes and Bacteroidetes. The collective number of species in the human gastrointestinal tract (GIT) is estimated to be over 35,000, which vastly outnumbers the diversity of organisms found on the skin [6]. The human colon is estimated to contain approximately 1013 microbial cells with a combined genomic content greater than their host [7,8]. Given its large quantity of cells, diversity, and collective genome, the microbiota of the human GIT has received a large amount attention for its potential involvement in human health.

Microbiota of the gastrointestinal tract

There is a symbiosis between the microbiota of the GIT and the human host. It is a relationship that has developed due to the continual presence of microbial cells in the human gut, and the relationship is evidenced by the lack of a significant immune response towards the microbial community [9]. It is not particularly surprising that there are a greater number of bacterial cells in the human GIT than anywhere else in the human body considering that the primary location of dietary consumption and absorption is in the GIT. The cumulative genetic content of the GIT microbiota produces proteins that enable them to digest a large range of compounds including many polysaccharides such as starches, cellulose and pectin [10-15]. The products formed from the digestion by the

GIT microbiota can then be used by other microbes in the environment or be absorbed by the host and incorporated into human metabolism [16-21]. Microbial metabolism in the

GIT functions on a large scale and is dependent on individual host factors that can have a large impact on shaping microbial communities, which can in turn have an effect on the

2 host. This demonstrates an interesting interdependence between the host’s well being and the communities of the GIT microbiota.

Host factors that can influence the human GIT microbiota range from the age, genetic background, diet, climate, and accessibility of healthcare. An interesting example of how host factors influence the gut microbiota comes from a study by Hehemann et al.

(2010), which showed how host diet and geography provide selective pressure on gut microbes [22]. They found that when comparing populations from Japan and North

America only individuals from Japan hosted microbes in their guts that were capable of digesting porphyran, an indigestible compound in red algae. The authors linked this ability to the high consumption levels of seaweed in the Japanese diet. The study showed that horizontal gene transfer occurred between a marine member of Bacteroidetes,

Zobellia galactanivorans, and a common member of the human GIT microbiota,

Bacteroides plebeius [22,23]. Z. galactanivorans transferred the genes that allows it to digest porphyran. The ability of these microbes to degrade porphyran into secondary metabolites that the host could use effectively allows for the host to digest a typically non-digestible food source by means of the gut microbiota. Not only is this an example of horizontal gene transfer explaining the development of GIT microbiological genome diversity, but also how influential host factors can be on shaping the microbial community.

Another host-microbiota relationship that illustrates the importance of host factors on their microbial composition is the role of Bifidobacterium species in the microbial colonization of the human gut during infancy [24]. Human milk oligosaccharides

(HMOs) provided to a newborn through breast-feeding can only be utilized by specific

3 species of Bifidobacterium. The digestion process of HMOs promotes the growth of these species, and the metabolic end products of HMO processing promote the growth of other microbes that rely on the byproducts. Thus infants that are provided these HMOs through breast-feeding or through other means will have a GIT with different microbial composition than those who are not.

These examples show the significance that the human GIT microbiota has on the human host but also the significance of the human host on the microbiota. This relationship has only begun to be described by the field, but it has already been made clear that there are many factors of the GIT microbiota that influence the host health [25-

28].

Gastrointestinal microbiota and human health

The microbiota of the human intestinal tract has many roles in regards to human health including the ability to degrade specific dietary compounds, the development and stimulation of host immune systems, modulation of gut motility, production of vitamins and short chain fatty acids (SCFA), and protection of the host from transient intestinal pathogens [29-33].

Diseases that have been linked to the gastrointestinal microbiota include irritable bowel syndrome, inflammatory bowel disease, and colorectal cancer [34-36].

Inflammatory bowel disease (IBD) has been associated with a decrease in microbial diversity and a change in composition of gastrointestinal microbiota. Sokol et al. (2009) found that patients with IBD have underrepresented members of class Firmicutes in the

4 gastrointestinal tract, specifically Faecalibacterium prausnitzii [37]. Low relative abundance of F. prausnitzii is related to reduced protection of gut mucosa.

Another critical example of the way the GIT microbiota influences the health of the host is through short chain fatty acid production [38]. SCFAs are produced by microbes as a result of bacterial fermentation in the colon. The major produced SCFAs are acetate, butyrate, and propionate. SCFAs are the end products of microbial digestion in the colon and are absorbed by host colonocytes as their primary energy source. This makes the microbiota a critical component in the efficiency of the host diet by taking ingested food that often cannot be utilized by the host and producing an end product that feeds the colon. The SCFA butyrate may not only provide energy to the host, but studies have shown that butyrate may have a protective effect from developing colon cancer or colon inflammation [39].

Microbiota and nutrition

As seen in the case of Bifidobacterium species with human milk oligosaccharides, and by examining the results of bacterial fermentation, it is unsurprising that nutrition has a large impact on microbiota and therefore also impacts the consequences that diet has for the host. For example, individuals who consume a high protein diet have altered gastrointestinal physiology including a higher production of hydrogen sulfide through the metabolism of amino acids [40]. The increase in hydrogen sulfide can lead to cell cytotoxicity and become a potential risk factor for colorectal cancer. Despite the apparent oncogenic risk of a high protein diet, studies have identified populations that are at low risk for colon carcinoma and associated them with hosts who harbor methanogenic

5 microbiota [41]. The methanogens metabolize amino acids into harmless methane as opposed to the members of genera Clostridium and Bacteroides who are responsible for reducing amino acids into cytotoxic hydrogen sulfide.

Alternatively, a diet composed of high amounts of fat has a different effect on the host versus a diet that is high in protein. A study by Serino et al. (2012) showed that a high fat diet in mice with low carbohydrate content resulted in an increase in gut permeability linked to endotoxaemia when compared to mice on a similar diet supplemented with oligosaccharides [42]. Mice were fed a high fat diet (approximately

72% fat, 28% protein, and <1% carbohydrate) for three months and the bacterial profile of the mice was determined by isolation of bacterial DNA from mouse fecal content and sequencing of16S rRNA genes through pyrosequencing. The authors showed a difference in the bacterial profiles between the mice fed a high fat diet and the mice that were fed a diet supplemented with fiber. Characteristic of the high fat diet was an enrichment of members from the phyla Actinobacteria, Deferribacteres, and Firmicutes.

The mice supplemented with fiber, however, had increased Proteobacteria and

Bacteroidetes, but had a decrease in the phyla present in the high fat diet. Because the high fat diet led to an increase in gut permeability and endotoxaemia but dietary supplementation repaired gut permeability, the authors suggest that there is a relationship between the impact of a high fat diet on the microbiota and the increase in gut permeability and endotoxaemia.

High carbohydrate diets select for a microbiota profile that is suited for degradation of indigestible polysaccharides into SCFAs [43]. There is an increase in the relative abundance of the Prevotella species in individuals with a high carbohydrate diet

6 versus a higher abundance of Bacteroides species in individuals with higher dietary fat and protein intake [44]. Although SCFAs have been attributed to maintaining colon health, other studies have shown that an overabundance of SCFA may be linked to disease states [45-47]. A study by Suez et al. (2014) has shown that the addition of non- caloric artificial sweeteners (NAS) to diets can cause a shift in the microbiota by acting as a prebiotic [48]. The change in microbiota can cause an enhancement in energy harvest through over production of SCFAs which has been previously associated with obesity in mice.

The examples provided illustrate several ways in which the diet consumed by an individual can impact the microbiota of their gastrointestinal tract and consequently influence host physiology. The role of nutrition is key to understanding the relationship that the microbiota shares with the host.

Microbiota and geography

The geography of the human population has been linked to the difference in the

GIT microbiome between individuals [49]. Many potential factors associated with the geographical location of an individual play a role in the shaping of their microbiota. The host diet, accessibility of healthcare, industrialization, and the local climate can all influence the microbiota [50]. A study by Prideaux et al. (2013) found that geographical and ethnic factor influence the host microbiota when they compared microbial profiles between Australian and Chinese patients [51]. De Filippo et al (2010) showed that children for urban France had a lower bacterial diversity than children from Burkina Faso

[52].

7 Another interesting study by Scnhorr et al. (2014) showed that there are unique

GIT microbial characteristics associated with a hunter-gatherer lifestyle that separate it from both an urban and rural lifestyle [53]. The Hadza diet consists of game meat and foods containing a diverse array of plant polysaccharides but very few agricultural products. The Mediterranean diet consumed by the Italians included plenty of starches, olive oil and plant products. The authors characterized the microbiota of the Hadza of

Tanzania and urban Italians through the use of pyrosequencing of the 16S ribosomal

RNA genes. They found that in the Hadza microbiome there was an enrichment of

Proteobacteria and Spirochaetes as well as having a higher Bacteroidetes to Firmicutes ratio. This was contrasted to the Italian profile, which included Actinobacteria, a member almost entirely absent in the Hadza population. The Italians were also different in that they had low amounts of Proteobacteria and Spirochaetes, reflecting the overall lower biodiversity present in the Italian sample. In respect to genus level differences, the

Hadza community showed enrichment in Prevotella, Treponema, and other unlclassified

Bacteroides. These changes reflect how a difference in lifestyle and geography can impact the microbiota.

Profiling gut microbiota

In order to determine the profiles of the gastrointestinal microbiota, researchers have adopted several techniques [54-56]. These include microarrays, quantitative polymerase chain reactions (qPCR), and next generation sequencing (NGS). By taking advantage of differences in the 16S small subunit ribosomal RNA genes of microbiota, these methods can differentiate complex communities according to taxonomy, thus

8 identifying microbial relative abundances. The use of technologies that analyze communities through their genetic differences provides an advantage over older techniques that were dependent on culturing fecal microbiota. This requirement limited the accuracy of distal gut profiling because it would under represent obligate anaerobes, which can be technically demanding and difficult to culture.

Examples of the use of culture independent techniques can be found in the literature and there are advantages and disadvantages for each one [55,57]. Microarrays were one of the first methods used to profile fecal microbiota communities through analysis of member genomes. They quantify the presence of microbiota by comparing

16S small subunit rRNA genes present in the samples against a predetermined library of available sequences on the microarray chip. NGS functions by analyzing the sequences present in the sample and grouping them into operation taxonomic units (OTUs).

Compared to microarray data that relies upon sequence libraries, NGS can provide a wider profile of the microbiota isolated from fecal material because of its ability to identify new OTUs. One of the disadvantages of NGS is that the quantification of microbial profiles provides relative abundances but it does not provide absolute abundance data. Technologies such as microarray and NGS analyze data through molecular genetics rather than through direct quantification of microbial cells.

Visualization of microbiota

The human GIT microbiota is clearly an important area of study for those who want to understand how complex microbial systems can function as well as for those interested in current fields of medicine. The ways that the microbiota can be studied are

9 numerous, but the ability to directly observe microbes through a means of visualization has been a central goal for microbiologist for as long as the field has been around [58-

60].

Numerous microscopy procedures allow visualization of bacteria. They range from basic wet mounts and simple stains that created the foundation for the field of microscopy and are useful for determining basic cellular characteristics such as motility, size, and cellular wall type; the use of modern electron microscopy allows for highly detailed resolution of cells. [61,62]. A major disadvantage of these methods is that they are unable to fully differentiate cells based upon their phylogeny. Through the use of other techniques, such as fluorescence in situ hybridization (FISH) in combination with fluorescent microscopy, microbiota can be visualized in a manner that can differentiate organisms based upon genetic, and therefore taxonomic, differences [63].

Fluorescence in situ hybridization applied to microbiota

Fluorescence in situ hybridization (FISH) is a technique that was developed in the

1980s as a tool for localization of specific nucleic acids within their native cells [64].

The principle behind FISH is that a nucleic acid probe of either RNA or DNA is created to match its complimentary nucleotide sequence inside of a cell. The probe is tagged with a fluorescent dye that when observed under a fluorescent microscope with the specific wavelength of light will fluoresce. When the probe is added to the cell and the cells are under the correct conditions to absorb the probe, the probe will bind to the complimentary sequence if it is present in that cell. When a slide prepared from an environment containing a complex microbial community, such as fecal material, only

10 cells that contain the sequence complementary to the probe bind the probe, and therefore fluoresce.

The application of FISH for the visualization of microbiota follows the same principle [64]. The probe used in FISH can be specifically designed to a complimentary sequence unique to a particular taxon of bacteria. The 16S ribosomal RNA gene is useful for choosing probe targets as it has both conserved regions as well as taxon specific variable regions [63]. By creating probes for taxon specific regions of the 16S ribosomal

RNA gene, only cells of that taxon will be fluorescent. If a fluorescent stain such as 4’,6- diamidino-2-phenylindole (DAPI) is used as a background stain that will bind to AT rich regions of DNA causing the fluorescence of all cells in a sample, then a composite image can be created. This can be used to determine the relative abundance of the probe’s target taxon because under the wavelength specific to the probe the number of cells can be counted and compared to the total number of cells present as counted when the wavelength is changed to that of the background stain. This protocol can be repeated using a multichannel fluorescent microscope as long as there is an assigned wavelength for each probe used, or several probes can be used with the same tag repeating the same sample with a different probe.

Overview of thesis research

The work detailed in this thesis involves the utilization of fluorescence in situ hybridization paired with fluorescent microscopy to visualize microbiota from two separate projects from the same laboratory. The first project is a study of the human microbiota exposed to a series of short term intervention diets that transition volunteers

11 from western diets to diets that are high in either protein or fat. Patient bacterial profiles used to compare against FISH results were determined through the use of a microarray that identifies operational taxonomic units through their16S ribosomal RNA genes. The second project is a study that compares the profile of fecal bacteria between healthy children from the United States and healthy Egyptian children. The profiles of this project were determined through next generational sequencing of the 16S ribosomal RNA genes.

This project uses nucleic acid probes for FISH that have been adopted from previous work as well as probes newly created and used for the first time in these experiments.

2. Methods

Sample collection

For both projects, fresh fecal samples were obtained from volunteers. For the diet intervention project studying adult nutrition (aNUT), samples were taken from two patients at three collection points; the first was while the patients consumed their normal diets (aNUT-W), another sample was taken on the seventh day of a week long high protein diet (aNUT-P), and the final sample was taken on day seven of a week long high fat diet (aNUT-F). The use of human fecal samples was approved by Wright State

Institutional Review Board (PI: Dr. Oleg Paliy, protocol # SC3746). The second project collected fecal samples from four adolescents, two from Egypt (egkHLT) and two from the United States (uskHLT). All samples from both projects were collected from volunteers who defecated into sterile sample collection containers that were stored at -

80˚C immediately following collection. Table 2.1 details the age and gender of the volunteers used in both studies.

12 Table 2.1 Volunteer Information Sample Age Gender aNUT 1 29 F aNUT 2 24 F egkHLT 1 14 M egkHLT 2 15 M uskHLT 1 10 M uskHLT 2 9 M

Isolation of fecal microbiota

Microbes were isolated from fecal material using the following protocol [63]. a) 100mg of stool was added to a 2ml eppendorf tube followed by addition of 1ml

phosphate buffered saline (PBS) with 0.1% sodium dodecyl sulfate (SDS). b) Eppendorf tube was vortexed at maximum speed until stool sample was well

homogenized. c) Sample tube was centrifuged for 15 minutes at 200rpm so that large particles would

move to the bottom, while generating two separate supernatant layers. d) The uppermost supernatant layer was removed and moved to a new eppendorf tube

and what remained of the original sample tube was discarded. e) The new sample tube was centrifuged for 15 seconds at 4000g and the upper

supernatant was again separated and kept in a new 2ml sample tube while the

remainder was discarded. f) 500µl of the sample was combined with 1.5ml of 4% paraformaldehyde in PBS and

then incubated overnight at 4˚C. g) After incubation, the samples were spun down for 3 minutes at 13000g and the

supernatant was discarded.

13 h) The resulting cell pellet remaining was washed 3 times with 1ml of PBS using a

centrifugation step identical to step (g) to pellet cells between washes. i) The final pellet was resuspended in 2ml of 1:1 ethanol/PBS solution and stored at -

20˚C for future use.

FISH probe design and optimization

In this work, five probes were used. Three of the probes have been adapted for this study from previous work [65,66]. The remaining two probes (Bfra602 and Prev743) were designed and optimized for this project. Table 2.2 provides a list of the probe sequences. Probes were created by comparing 16S ribosomal subunit RNA genes of target taxa against the 16S ribosomal subunit RNA genes of closely related taxa using

Clustal Omega alignment tool.16S ribosomal subunit RNA genes were acquired from

NCBI nucleotide database (Figure 2.1). By comparing these two groups of sequences, regions of consensus in members of the target taxa but not in closely related taxa could be considered candidate sequences for probe construction. These candidates were run through the probe match function on the Ribosomal Database Project (RDP) accounting for three mismatches. Only candidate sequence probes that showed high specificity and accuracy for their target taxon were used in this project. Refer to Table 2.3 for details on all probe specificity (the percent of target OTUs that the probe binds) and accuracy (the percent of probe matches that are specific to the target taxon). A lower specificity is not necessarily a cause for excluding a probe; it only indicates that the probe could not bind to all the available target sequences listed in RDP. As long as the fraction of sequences that the probe can bind to are represented equally amongst samples being compared then

14 the probe is still suitable for comparing relative abundances of microbes. The need for a high amount of probe accuracy is more critical.

Table 2.2 FISH robe DNA sequence Probe Sequence Bac303 CCAATGTGGGGGACCTT Bfra602 GAGCCGCAAACTTTCACAA Bif164 CATCCGGCATTACCACCC Lacto722 YCACCGCTACACATGRAGTTCCACT Prev743 AATCCTGTTCGATACCCGCA

Table 2.3 Probe specificity and accuracy according to RDP Probe Target Specificity Accuracy Bac303 class Bacteroidia 60.48% 99.27% Bfra602 genus Bacteroides 85.98% 99.54% Bif164 genus Bifidobacterium 91.20% 98.44% Lacto722 class Bacilli 9.43% 99.61% Prev743 genus Prevotella 69.98% 90.89%

The in-situ performance of FISH probes is heavily dependent on optimization of the hybridization conditions, specifically the hybridization buffer and the concentration of formamide. In order to determine these parameters a series of hybridizations with differing concentrations of formamide were carried out with each probe and a pure microbial culture of their target (intervals of 10%, from 0-60%). Finally, each probe was tested against a pure culture of both a target and a non-target taxon as positive and negative controls (Figure 2.2).

Figure 2.1 Alignment of probe sequences with 16s RNA gene sequences. 16S ribosomal RNA gene sequences of target taxa were aligned to non-target sequences to identify regions of consensus amongst a target that were not a match to the non-target sequence. These regions were used as candidate probes that were tested against the RDP database for accuracy and specificity.

Figure 2.2 Positive and negative controls of newly designed FISH probes. In negative control images the only visible fluorescence is from the background DAPI staining indicating that there is no hybridization. In positive control images all cells appear a shade of violet, which is the combination of the blue DAPI staining as well as the red hybridization of the probe to the cell.

16 Treatment of bacterial cells with lysozyme

The protocol for FISH has been developed previously [63]. Before microbiota could undergo the hybridization, microbial cells were treated with lysozyme. Once treated with lysozyme, DNA probes tagged with fluorescent labels are added to the cells to hybridize overnight. Excess probe is washed off and background DAPI is added before viewing under microscope.

Lysozyme treatment protocol.

a) 200µl of 1:1 ethanol/PBS cell suspension was placed in a 500µl eppendorf tube.

b) Sample was centrifuged for 3 minutes at 13000g and supernatant was discarded

leaving cell pellet.

c) The resulting pellet was suspended in 200µl of lysozyme wash buffer containing

100mM Tris-HCl, 50mM EDTA, with a pH of 8.

d) Sample was centrifuged for 3 minutes at 13000g and supernatant was discarded.

e) 0.2mg of lysozyme was mixed with 200µl of lysozyme wash buffer and then

added to suspend the cell pellet.

f) Sample was incubated at room temperature for 15 minutes.

g) Sample was centrifuged for 3 minutes at 13000g and supernatant was discarded.

h) The cell pellet was washed with 400µl of PBS and centrifuged under same

conditions as step (g).

i) Cells were suspended in 60µl of PBS and then immediately used in the

hybridization procedure for FISH.

17 Probe hybridization protocol

Hybridization of fluorescent DNA probes into bacterial cell samples occured over

16 hours at 46˚C. 80µl of pre-warmed, 46˚C hybridization buffer was added to a 500µl eppendorf tube. The hybridization buffer was made of 900mM NaCl, 20mM Tris-HCl, pH 7.5, and 0.01% SDS. Hybridization conditions are unique to each probe and can be found in Table 2.4 [65-70]. The hybridization mixture was prepared and then 10µl of lysozyme treated cells were added to the reaction tube. The hybridization mixture was incubated for 16 hours protected from light.

Table 2.4 FISH probe hybridization mixtures Probe DNase/RNase Free Water Formamide Bac303 100µl 0µl Bfra602 60µl 40µl Bif164 60µl 40µl Lacto722 50µl 50µl Prev743 80µl 20µl

After the overnight incubation was completed, cells were pelleted via centrifugation for 3 minutes at 13000g. Cells were suspended in a wash solution specific to each probe, and incubated at 48˚C for 20 minutes. Recipes for each wash solution can be found in Table 2.5. After wash incubation, cells were centrifuged once again for 3 minutes at 13000g. Cells were finally suspended in 15µl of PBS.

Table 2.5 Wash buffer recipes Probe Recipe Bac303 160µl hybridization buffer, 240µl Dnase/Rnase free water Bfra602 425mM NaCl, 20mM Tric-HCl, pH 7.5, 0.01% SDS Bif164 250mM NaCl, 20mM Tris-HCl, pH7.5, 0.01% SDS Lacto722 170mM NaCl, 20mM Tris-HCl, pH7.5, 0.01% SDS Prev743 425mM NaCl, 20mM Tric-HCl, pH 7.5, 0.01% SDS

18 Slide preparation and microscopy

Hybridized cells were prepared on slides by adding 10µl of the 15µl of hybridized cells suspended in PBS and spreading the suspension evenly across the area of a slide proportional to the size of a coverslip. The slides were left to dry for twenty minutes in the dark before a coverslip with 10µl of Vectashield mounting media containing DAPI was added on top of the slide.

Microscopy was performed on a Leica DMI6000B inverted fluorescent microscope. Images were taken at 1000x for every field under both ultraviolet light for analysis of DAPI stained cells and light at wavelength (495-519nm) for analysis of 6-

FAM tagged probe hybridized cells. Images from both light sources were overlaid to form a composite image in Image Pro 6.2 software.

Image editing and analysis

All images used in this project were edited through Adobe Photoshop in order to remove bleed-through DAPI fluorescent signaling. Eight images from every sample were taken and all cells were counted. The average of the hybridized cells was compared against the average number of DAPI stained cells in order to determine the average relative abundance of the probe target cells in the sample. Relative abundances were compared to the microarray and NGS data.

19 3. Results

Application of fluorescence in situ hybridization to visualize human fecal microbiota isolated from volunteers undergoing short-term diet changes

This study was designed and carried out in order to visualize the human gastrointestinal microbiota through the use of fluorescence in situ hybridization (FISH) and to quantify the relative abundances of target taxa. The first project that FISH was applied to was a short-term diet intervention study. Adult participants donated fecal samples while consuming their typical western diet before switching to a diet either high in fat (13% protein, 20% carbohydrate, 67% fat) or high in protein (52% protein, 23% carbohydrate, 25% fat) and donating another sample on day 7 of the new diet. Donors had not taken antibiotics within three months of the start of the study and were all in relative good health.

Work previously done in the laboratory analyzed the composition of the donor fecal microbiota using a microarray technique. For this study, samples from two patients for all three diets were visualized using FISH with two different probes. One probe targets the class Bacteroidia (Bac303) and the second probe targets the genus

Bifidobacterium (Bif164). These probes bind to sequences in the 16S ribosomal subunit

RNA gene that is often used to distinguish organisms according to their taxa. These probes and their targets were chosen to show that FISH probes could be used to target variable levels of taxa ranging from higher-level classes to lower level genera. These targets were also selected because the relative abundances of these taxa change with the various diets the volunteers consumed.

FISH results showed that for both of the volunteers, the relative abundance of

20 genus Bifidobacterium is reduced when volunteers switch from their original diet to either the high-fat or high-protein diet. For aNUT1samples the relative abundance changes from 3.0% in western diet to 2.5% or 2.2% for high-protein diet or high-fat diet respectively. aNUT2 samples decreased from 5.6% to 2.4% or 3.5%. This trend follows what is observed in the microarray data, and this is consistent with what would be expected given Bifidobacterium species reputation for carbohydrate digestion [10,16,24].

As the availability of carbohydrates decreases so does the abundance of carbohydrate degrader.

The microarray data for class Bacteroidia showed enrichment when volunteers switched from their western diets to the high protein or high fat diet. This was matched by the FISH data for this target taxon. aNUT1 Bacteroidia abundances increased from

1.9% in the western diet to 9.8% or 9.3% for high-protein or high-fat diets respectively. aNUT2 changed from 3.7% to either 13.1% or 10.5%. The FISH data and microarray data for both Bifidobacterium and Bacteroidia are compared in Figure 3.1, and the results for FISH relative abundances can be found in Table 3.1 while the results for the adjusted microarray are in Table 3.2. Representative images for both the Bac303 and Bif164 hybridizations can be found in Figure 3.2 and 3.3. The cell counts for every image taken for either Bacteroidia or Bifidobacterium can be found in Table 3.3 and 3.4 respectively.

Table 3.1 aNUT FISH relative abundances, data are shown as mean ± standard error Sample Bacteroidia Bifidobacterium aNUT-W1 1.9 ±< 0.1% 3.0 ± <0.1% aNUT-P1 9.8 ± <0.1% 2.5 ± <0.1% aNUT-F1 9.3 ± <0.1% 2.2 ± <0.1% aNUT-W2 3.7 ± <0.1% 5.6 ±<0.1% aNUT-P2 13.1 ± <0.1% 2.4 ± <0.1% aNUT-F2 10.5 ± <0.1% 3.5 ± <0.1%

21 Table 3.2 aNUT microarray adjusted relative abundances Sample Bacteroidia Bifidobacterium aNUT-W1 4.5% 4.4% aNUT-P1 8.0% 2.6% aNUT-F1 10.8% 3.0% aNUT-W2 4.4% 7.3% aNUT-P2 13.0% 4.5% aNUT-F2 12.1% 6.1%

Figure 3.1 aNUT diet comparisons. Genus Bifidobacterium shows a decrease in relative abundance when volunteers switched from a western diet to either a high protein or a high fat diet. Class Bacteroidia shows an increase in relative abundance when volunteers switched from a western diet to a diet high in protein or high in fat.

22 Figure 3.2: Bac303 probe FISH images

Figure 3.3 Bif164 probe FISH images

Figures 3.2 and 3.3. A selection of FISH images from adult nutrition project. All cells were stained with a background DAPI stain (blue) and cells of target taxa are visible (violet) after hybridization with probe. Relative abundances presented in images are representative of data available in Figure 3.2.

23 Table 3.3 aNUT FISH image cell counts for Bacteroidia

aNUT 1 aNUT 2 DAPI FITC DAPI FITC stained hybridized stained hybridized Image cells cells %Hybridization Image cells cells %Hybridization Western 1 254 2 0.8% 1 202 6 3.0% diet 2 96 4 4.2% 2 216 4 1.9% 3 154 3 1.9% 3 196 7 3.6% 4 85 0 0.0% 4 150 5 3.3% 5 95 1 1.1% 5 103 5 4.9% 6 145 4 2.8% 6 123 7 5.7% 7 141 6 4.3% 7 158 8 5.1% 8 70 0 0.0% 8 72 3 4.2% AVG 130 2.5 1.9% AVG 152.5 5.625 3.7% High 1 16 1 6.3% 1 53 7 13.2% protein 2 30 2 6.7% 2 57 7 12.3% diet 3 48 6 12.5% 3 54 12 22.2% 4 41 4 9.8% 4 78 10 12.8% 5 52 5 9.6% 5 43 2 4.7% 6 39 4 10.3% 6 49 9 18.4% 7 33 3 9.1% 7 61 9 14.8% 8 48 5 10.4% 8 80 6 7.5% AVG 38.375 3.75 9.8% AVG 59.375 7.75 13.1% High fat 1 46 7 15.2% 1 77 8 10.4% diet 2 82 10 12.2% 2 96 10 10.4% 3 56 2 3.6% 3 85 5 5.9% 4 48 6 12.5% 4 65 11 16.9% 5 62 3 4.8% 5 58 4 6.9% 6 63 6 9.5% 6 73 7 9.6% 7 77 6 7.8% 7 100 10 10.0% 8 69 7 10.1% 8 106 14 13.2% AVG 62.875 5.875 9.3% AVG 82.5 8.625 10.5%

24 Table 3.4 aNUT FISH image cell counts for Bifidobacterium

aNUT 1 aNUT 2 DAPI FITC DAPI FITC stained hybridized stained hybridized Image cells cells %Hybridization Image cells cells %Hybridization Western 1 46 2 4.3% 1 194 12 6.2% diet 2 32 1 3.1% 2 146 9 6.2% 3 41 1 2.4% 3 91 4 4.4% 4 53 1 1.9% 4 103 4 3.9% 5 61 3 4.9% 5 143 10 7.0% 6 45 1 2.2% 6 177 11 6.2% 7 40 1 2.5% 7 130 8 6.2% 8 52 1 1.9% 8 186 8 4.3% AVG 46.25 1.375 3.0% AVG 146.25 8.25 5.6% High 1 36 1 2.8% 1 47 0 0.0% protein 2 27 1 3.7% 2 40 1 2.5% diet 3 40 1 2.5% 3 52 3 5.8% 4 39 3 7.7% 4 51 0 0.0% 5 28 0 0.0% 5 44 0 0.0% 6 51 0 0.0% 6 56 2 3.6% 7 25 0 0.0% 7 52 2 3.8% 8 35 1 2.9% 8 28 1 3.6% AVG 35.125 0.875 2.5% AVG 46.25 1.125 2.4% High fat 1 96 1 1.0% 1 65 5 7.7% diet 2 33 1 3.0% 2 149 3 2.0% 3 102 2 2.0% 3 72 2 2.8% 4 71 0 0.0% 4 75 3 4.0% 5 95 5 5.3% 5 40 0 0.0% 6 102 3 2.9% 6 47 1 2.1% 7 120 2 1.7% 7 83 3 3.6% 8 106 2 1.9% 8 64 4 6.3% AVG 90.625 2 2.2% AVG 74.375 2.625 3.5%

25 Design and optimization of fluorescent DNA probes for use in fluorescence in situ hybridization

This study outlines the creation of two new probes so that FISH could be accurately performed on the egkHLT-uskHLT project. This project previously demonstrated an inverse relationship between the high levels of genus Prevotella in egkHLT samples and the high levels of genus Bacteroides in uskHLT samples. Because these two genera are closely related and there were previously no probes specific to these targets, probes were designed for each one de novo in this project.

Bacteroides probe Bfra602 was created by comparing sequences of the 16S ribosomal subunit RNA gene of several Bacteroides species to find segments of the genes that were identical. These sequences were aligned against 16S RNA genes of closely related Prevotella species to ensure probe specificity and confirm the absence of cross hybridization. The procedure was repeated in order to generate probe sequences for the

Prevotella probe Prev743. Candidate probe sequences were submitted to the Probe

Match feature of RDP in order to determine probe specificity (measures the percent of target OTUs that the probe binds) and accuracy (measures the percent of probe matches specific to the target). Probes maintained specificity to their respective targets even with three mismatches allowed.

Application of fluorescence in situ hybridization to visualize human GIT microbiota isolated from geographically distinct adolescent populations

The second project that FISH has been applied to was a study that compared the microbiota of children living in the United States with children living in Egypt. Two

26 volunteers from each group donated fecal material, which were collected and frozen immediately. All participants were healthy individuals and had not taken antibiotics within 3 months prior to sample collection.

The GIT microbiota was characterized previously through next generation sequencing. Samples from this study were visualized using FISH with target probes for class Bacilli (Lacto722), as well as for the genera Bacteroides (Bfra602) and Prevotella

(Prev743). Again, targets were selected to demonstrate the utility of FISH to quantify the relative abundances of targets of differing taxonomic levels, but the two genera were selected because of the interesting inverse relationship that was observed in the NGS results. The work done before showed that in Egyptian children the amount of Prevotella was greater than the amount of closely related Bacteroides, this relationship was reversed in children from the United States.

The FISH results showed a higher level of genus Bacteroides and a lower amount of genus Prevotella in U.S. children with the opposite trend in Egyptian children. The data also showed that the levels of class Bacilli was more abundant in the volunteers from

Egypt versus U.S. adolescents. All FISH data used in this project can be found in Table

3.5, the adjusted NGS results used in this project are available in Table 3.6, and the cell counts used to determine FISH averages for both egkHLT and uskHLT are located in

Table 3.7 and 3.8 respectively. FISH and NGS data are compared in Figure 3.4.

Representative images are provided for each probe used in this project, they can be found in Figure 3.5.

27 Table 3.5 FISH relative abundances for uskHLT and egkHLT volunteers, data are shown as mean ± standard error Sample Bacilli Bacteroides Prevotella egkHLT1 3.4 ± <0.1% 1.8 ± <0.1% 10.7 ± <0.1% egkHLT2 3.9 ± <0.1% 1.5 ± <0.1% 16.3 ± <0.1% uskHLT1 0.7 ± <0.1% 18.8 ± <0.1% 5.2 ± <0.1% uskHLT2 1.2 ± <0.1% 15.4 ± <0.1% 7.8 ± <0.1%

Figure 3.4 Comparisons of egkHLT and uskHLT samples. Class Bacilli has a higher relative abundance in Egyptian children compared to U.S. children. Genus Bacteroides and Prevotella share an inverse relationship with Bacteroides being present in a higher relative abundance in U.S. children than in Egyptian children while the reverse is true of Prevotella.

Figure 3.5 FISH images of probes used in uskHLT-egkHLT project. A selection of FISH images from uskHLT-egkHLT project. All cells were stained with a background DAPI stain (blue) and cells of target taxa are visible (violet) after hybridization with probe. Relative abundances presented in images are representative of data available in Figure 3.4.

29 Table 3.6 NGS adjusted relative abundances for egkHLT and uskHLT volunteers Sample Bacilli Bacteroides Prevotella egkHLT1 2.1% 2.5% 14.7% egkHLT2 4.6% 2.0% 16.0% uskHLT1 1.1% 12.4% 4.6% uskHLT2 1.2% 12.0% 4.6%

Table 3.7 FISH image cell counts for egkHLT samples

egkHLT 1 egkHLT 2 DAPI FITC DAPI FITC stained hybridized stained hybridized Image cells cells %Hybridization Image cells cells %Hybridization Bacilli 1 43 2 4.7% 1 84 2 2.4% 2 65 1 1.5% 2 61 3 4.9% 3 39 1 2.6% 3 66 5 7.6% 4 46 1 2.2% 4 83 1 1.2% 5 36 2 5.6% 5 89 2 2.2% 6 48 2 4.2% 6 101 6 5.9% 7 34 1 2.9% 7 108 6 5.6% 8 47 2 4.3% 8 122 3 2.5% AVG 44.75 1.5 3.4% AVG 89.25 3.5 3.9% Bacteroides 1 37 1 2.7% 1 83 0 0.0% 2 55 0 0.0% 2 59 0 0.0% 3 68 0 0.0% 3 90 1 1.1% 4 44 1 2.3% 4 97 1 1.0% 5 46 0 0.0% 5 103 2 1.9% 6 44 0 0.0% 6 100 5 5.0% 7 48 1 2.1% 7 62 1 1.6% 8 41 4 9.8% 8 87 0 0.0% AVG 47.875 0.875 1.8% AVG 85.125 1.25 1.5% Prevotella 1 94 6 6.4% 1 130 25 19.2% 2 55 4 7.3% 2 120 8 6.7% 3 70 10 14.3% 3 103 22 21.4% 4 68 8 11.8% 4 57 7 12.3% 5 77 9 11.7% 5 39 7 17.9% 6 94 9 9.6% 6 71 11 15.5% 7 77 9 11.7% 7 31 6 19.4% 8 75 10 13.3% 8 76 16 21.1% AVG 76.25 8.125 10.7% AVG 78.375 12.75 16.3%

Table 3.8 FISH image cell counts for uskHLT samples

uskHLT 1 uskHLT 2 DAPI FITC DAPI FITC stained hybridized stained hybridized Image cells cells %Hybridization Image cells cells %Hybridization Bacilli 1 75 2 2.7% 1 101 2 2.0% 2 41 0 0.0% 2 86 2 2.3% 3 49 2 4.1% 3 157 3 1.9% 4 97 0 0.0% 4 103 3 2.9% 5 58 0 0.0% 5 112 1 0.9% 6 70 0 0.0% 6 264 1 0.4% 7 81 0 0.0% 7 120 1 0.8% 8 85 0 0.0% 8 114 0 0.0% AVG 69.5 0.5 0.7% AVG 132.125 1.625 1.2% Bacteroides 1 64 17 26.6% 1 104 20 19.2% 2 74 7 9.5% 2 110 7 6.4% 3 35 8 22.9% 3 102 17 16.7% 4 72 7 9.7% 4 76 14 18.4% 5 64 16 25.0% 5 70 15 21.4% 6 78 16 20.5% 6 73 10 13.7% 7 87 12 13.8% 7 89 13 14.6% 8 80 21 26.3% 8 98 15 15.3% AVG 69.25 13 18.8% AVG 90.25 13.875 15.4% Prevotella 1 103 5 4.9% 1 35 2 5.7% 2 108 6 5.6% 2 52 3 5.8% 3 84 5 6.0% 3 34 4 11.8% 4 44 2 4.5% 4 37 3 8.1% 5 78 4 5.1% 5 39 1 2.6% 6 74 4 5.4% 6 30 2 6.7% 7 56 1 1.8% 7 41 3 7.3% 8 65 5 7.7% 8 39 6 15.4% AVG 76.5 4 5.2% AVG 38.375 3 7.8%

31 4. Discussion

The application of fluorescence in situ hybridization has proved useful to many fields of biology for its ability to visualize and distinguish cells based upon the presence of specific nucleic acid sequences. When FISH is used to visualize bacterial samples containing more than one phylotype, this ability allows for the distinction of cells according to their taxonomic classification [64]. Here FISH was used to visualize the microbiota of individuals from two projects currently under investigation in the laboratory; one examining the role of nutrition in influencing the GIT microbiota and the other, the impact of geographical differences.

The use of FISH for the visualization of microbiota in an adult diet intervention study was in general concordance with the results obtained previously through the use of microarray. The microbial profile of both volunteers followed the same trend as the microarray data showing levels of the genus Bifidobacterium decrease when switching from a western diet to both high protein and high fat diets. As mentioned previously, this trend is expected considering the current knowledge about Bifidobacterium species

[10,16,24]. Members of genus Bifidobacterium are known to be dependent on the presence of complex polysaccharides and oligosaccharides that the host cannot digest.

By reducing the amount of carbohydrates in host diets selective pressure on the microbial community will reduce the amount of carbohydrate utilizers that the community can support. FISH results for both volunteers also had levels of class Bacteroidia that matched the trends seen in the microarray data; demonstrating that FISH probes can target higher taxonomic levels. When volunteers switched to a high-fat or high-protein diet, the abundance of class Bacteroidia increased.

32 For the next project an interesting pattern emerged when comparing the GIT microbiota of U.S. children and Egyptian children. NGS data that was analyzed previously in the lab revealed that children from Egypt had a higher level of the genus

Prevotella and a lower level of genus Bacteroides, while U.S. children showed the opposite pattern. Although both of these organisms belong to the order Bacteroidales, species of Prevotella have genes dedicated to degrading complex carbohydrates, while members of Bacteroides have been noted as generalists capable of utilizing a wide range of dietary substrates such as protein and fat [44]. The inverse relationship is likely due to the diet differences between the two groups, with U.S. children consuming a diet higher in animal products and simple sugars and Egyptian children consuming more plant byproducts containing more indigestible complex carbohydrates. This pattern has been previously observed in the literature and has been explained with similar rationale [44].

Since this data was of interest and showed biological relevance, it was desirable to observe the pattern through a visualization technique.

Probes that have been claimed in previous studies to target genus Bacteroides are in fact not typically specific to only Bacteroides but often times are inclusive to members from all of class Bacteroidia [65]. Since Prevotella and Bacteroides are closely related, specific probes had to be created in order to distinguish between the two genera. Probes

Prev743 and Bfra642 were created and used here in this work for the first time for the purposes of quantifying Prevotella and Bacteroides seperately. Future studies that wish to pursue FISH for the visualization of microbiota should give consideration to the specificity and accuracy of the probes being used, and in situations that require it; probes should be customized for the desired target.

33 The egkHLT-uskHLT project generated FISH data that was in agreement with the

NGS data that has been produced by the laboratory. The FISH values were not exact matches to the NGS data, but when the NGS data reported a taxon higher or lower in either group, the FISH data had the same trend. Similar to the diet intervention project, the targets were picked so that at least one target was a lower level taxon and one higher- level taxon. In this project the higher-level taxon was selected to be the class Bacilli because this class has a higher abundance in egkHLT samples compared to the kHLT samples.

The work done here demonstrates the ability of fluorescence in situ hybridization to visualize the microbiota of the gastrointestinal tract, albeit only one or a few targets at a time. These results also show that FISH provides relative abundance data that is in agreement with both microarray and NGS. This thesis illustrates the importance of evaluating probes based upon their accuracy and specificity to their intended targets, maintaining the reliability and reproducibility of the quantitative data acquired through

FISH. This study outlines a procedure to assess current probes as well as provides a method to create new ones. As the libraries of bacterial 16S ribosomal RNA genes get more thorough, and as the ability to analyze sequence information becomes easier, the accuracy and specificity of probes should increase, creating probes that are more accurate and can better meet the needs of researchers who wish to apply FISH to their current projects.

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39 Appendices

Table of Abbreviations Abbreviation Definition aNUT Adult nutrition (project/samples) aNUT-F Adult nutrition samples from volunteers on a high fat diet aNUT-P Adult nutrition samples from volunteers on a high protein diet aNUT-W Adult nutrition samples from volunteers on a normal diet DAPI 4’,6-diamidino-2-phenylindole egkHLT Samples from adolescent volunteers in Egypt FISH Fluorescence in situ hybridization GIT Gastrointestinal tract HMO Human milk oligosaccharide IBD Inflammatory bowel disease NAS Non-caloric artificial sweetener NGS Next generation sequencing OTU Operational taxonomic units PBS Phosphate buffered saline qPCR Quantitative polymerase chain reaction RDP Ribosomal database project SCFA Short chain fatty acid SDS Sodium dodecyl sulfate uskHLT Samples from adolescent volunteers in the United States