The Natural Acquisition of the Oral in Childhood: A Cross-Sectional Analysis

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

By

Roma Gandhi, D.M.D, M.P.H.

Graduate Program in Dentistry

The Ohio State University

2016

Thesis Committee:

Ann Griffen, Advisor

Eugene Leys

Erin Gross Copyrighted by

Roma Gandhi

2016 Abstract

This cross-sectional study explored the development of the oral microbiome throughout childhood. Our previous studies of infants up to 1 year of age have shown early presence of exogenous species not commonly found in the oral cavity followed by rapid replacement with a small, shared core set of oral bacterial species. Following this initial colonization, we hypothesize that the complexity of the microbial community will steadily increase with advancing age as the oral cavity develops more intricate environmental niches for bacterial growth, and as children are exposed to new strains of and novel foods.

We sampled 116 children and adolescents ranging from age 1 to 14 years and collected salivary, supragingival and subgingival samples. Bacterial community composition was analyzed at the level of species using rRNA gene amplicon sequencing. This data allowed us to determine commonality among core species and the relationship of age to microbial complexity and community composition. Understanding when the establishment of bacterial communities will occur will help us determine if species are acquired in a specific order and will provide clues as to whether some species require the presence of others to colonize. Taken together, insight will be provided into the reconstruction of the natural acquisition of the human oral microbiome from birth through the establishment of the permanent dentition.

ii Changes in species complexity and the establishment of shared order of the oral have been examined in relation to age and site-specific samples. More specifically, our analyses suggest that the overall oral microbiome remains fairly stable after the first year of life, with very little influence from age, particular oral niches, and caries status.

iii Acknowledgments

I would like to thank my thesis committee for their mentorship and guidance on this

research project. Their dedication in helping me and encouraging intellectual discussions

for my research has been invaluable. I would also like to thank Rosalyn Sulyanto, Zach

Thompson, Cliff Beall, Karmeil Stepter, Priyanka Iyer, and Rami Mikati for their assistance with sample scheduling, study organization and preparation, and statistical analyses.

iv Vita

2007...... B.S., Exercise Science, George Washington

...... University

1970...... M.P.H., Health Policy and Management,

...... Emory University

2014 ...... D.M.D., University of Pennsylvania School

of Dental Medicine

Fields of Study

Major Field: Dentistry

v Table of Contents

Abstract ...... ii

Acknowledgments...... iv

Vita ...... v

Table of Contents ...... vi

List of Tables ...... vii

List of Figures ...... viii

Introduction ...... 1

Hypothesis...... 6

Materials and Methods ...... 7

Results ...... 13

Discussion ...... 15

Tables ...... 19

Figures...... 23

References ...... 34

Appendix A: Exam and Sampling Form ...... 38

Appendix B: Contact Info and History Form ...... 40

vi List of Tables

Table 1. Percent Distribution of Age Cohorts ...... 20

Table 2. Participant Demographic Factors ...... 21

Table 3. Participant Sample Distribution ...... 2 2

vii List of Figures

Figure 1. Abundance Heatmap Reflecting Prevalence of 26 Core Species ...... 24

Figure 2. Linear Mixed Effects Model Reflecting Resolution of Early Chaos ...... 25

Figure 3. Shannon Diversity Index by Age ...... ,...... 26

Figure 4. Species Richness by Age ...... 27

Figure 5. Effects of Age on Community Composition ...... 28

Figure 6. Site-Specific Species Decreasing over Age ...... 29

Figure 7. Effects of Site on Community Composition…………………………………..30

Figure 8. Species, , and Class Abundance Profiles………………………………..31

Figure 9. Effects of Caries Status on Community Composition…………………………32

Figure 10. Effects of dfs/+DFS on Community Composition…………………………...33

viii Introduction

For over a decade, research in genome sciences has aimed to identify a core of similar species within the . If present, a common core set of species would provide insight into identifying key organisms through sequencing studies, and their roles in metabolic activities, immune development, and disease initiation and progression [1]. Complex communities of microbiota exist among specialized niches in the human body such as the gut, skin, vaginal cavity and the oral cavity. The nature of complexity, diversity, and resilience of these bacterial communities are influenced by individual genetics, environment, diet, and microbial exposure. While these communities aid in maintaining equilibrium among biological processes, these complex habitats continue to remain unexplained [2]. Community structure variation exists among each specialized niche with core taxa dominating these habitats [3-6]. Literature has shown that the oral cavity has distinct communities that are markedly diverse among bacterial members and highly variable among individuals with various states of oral and physical health, and there is limited data on how the microbiota evolves from infant communities to adult communities in a healthy individual [7].

Based on infant gut colonization studies, we can hypothesize that bacterial communities colonize the oral cavity in a similar process. The acquisition of the gut microbiome of an infant is initially considered “chaotic.” Based on 16S rRNA gene analysis, phylogenetic diversity of the gut microbiome has slowly increased over time.

While dominant taxa groups experienced shifts in quantity due to external factors such as 1 diet and disease, assembly of the bacterial community has shown to be non-chaotic and distinct stages of bacterial succession have been observed [8]. The initial chaos evident among the gut bacterial community may be due to presence of opportunistic colonizers, which the infant is exposed to from external factors such as the environment or diet.

Eventually as the infant grows during the first year, a core set of taxa dominates due to a fitness advantage over changes in the gut environment, diet, and states of health and disease. By the end of the first year, the idiosyncratic microbial ecosystems converge toward a profile characteristic of the adult gastrointestinal tract [9]. In comparison to the oral cavity, colonization occurs similarly where specific bacterial colonies are established within a couple of days of life. By the first year of life, colonization resembles the adult

oral cavity [16]. Our own unpublished studies using 454 sequencing of the 16S rRNA gene have shown that the initial acquisition of the oral microbiome among infants has a specific and orderly assembly of core microbial communities with mitis group showing 100% prevalence within the first 3 months of life. Additional early colonizers are acquired and by the first year of life, 100 % prevalence was noted among

Streptococcus mitis group, Rothia mucilaginosa, and Veillonella atypica [Figure 1]. In

another unpublished study completed by Dr. Ann Griffen and Dr. Roslayn Sulyanto, prior

to age 1, many different minor bacterial communities are acquired possibly under the

influence from external factors such as diet and environment. By the first year of life, a

core set of taxa dominates due to a fitness advantage and results in a distinct succession

of core species [Figure 2].

2 Initial bacteria that colonize the oral cavity in a newborn are likely of maternal origin. The type of the newborn is first exposed to is based on the type of maternal delivery, vaginal or cesarean. Within a few minutes after birth, bacterial communities present in the oral cavity, nasopharyngeal area, epidermis, and intestines are very similar to each other [10]. Over the next few hours and days, the newborn will be exposed to a vast array of bacterial species from breathing, breastfeeding, and human contact. At this point, the process of colonization within the oral cavity ensues.

Within twenty-four hours of life, pioneer microorganisms, such as Streptococcus and Staphylococcus, which are Gram-positive cocci, have already been established in the oral cavity [11-12]. Streptococcus species, S. mitis and S. salivarius, both have the ability to adhere to mucosal cells on the first day of life, and S. sanguis after the eruption of teeth during the first year, which explains the natural distribution of streptococci during infancy [13, 21, 25]. High-sucrose diets appear to cause dominance of S. salivarius suggesting the influence of diet on the intra-oral levels of S. salivarius among infants

[26]. S. mutans, a species most strongly associated with dental caries, may potentially be acquired from mothers through horizontal as well as vertical transmission [23]. The primary route of transmission is through mother-child saliva, which results in the initial acquisition of S. mutans at a time between 6 and 30 months of the child's life, with a higher risk between 18 and 30 months of age, often considered the “window of infectivity” [24, 27, 28]. As the newborn ages, the oral microbiota evolves and by five months of age, a distinct oral microbiota is present from the mother due to various environmental exposures.

3

With early childhood approaching, species are found in higher

proportions in the oral cavity. These species have been known to be associated with early

plaque development on tooth surfaces [14-15], adhering capabilities [16], and co- aggregating properties with other species [17]. Based on older longitudinal studies, A. odontolyticus, has been the primary and frequent colonizer among the Actinomyces genus and has also remained the most prominent on oral mucosal surfaces in infants up to 2

years of age [18, 33]. Lactobacilli are present in low numbers and under 2 years of age,

the species is mostly transient in infants [25]. Other species that have been observed in

infants are Veillonella, Rothia, , Granulicatella, Leptotrichia, ,

Prevotella melaninogenica and catoniae [19-20].

As teeth begin to erupt, there are greater areas of potential niches and attachment sites on hard tooth surfaces and in gingival crevices for further microbial colonization.

Saliva and gingival crevicular fluid affect the oral surfaces, which further alter the oral

microbiota [29]. With a stable core bacterial community already established in a

predentate infant, newer species colonizing oral surfaces leads to an environment of

multiform gram-negative anaerobic microflora in children with primary dentition [31].

The influence of cell-to-cell interactions causing stimulatory or inhibitory affects among

bacterial species, allows for the formation of communities where bacterial inter-

relationships affect composition and stability. Viridans streptococci and

nucleatum, are both influential in this environment [30]. While Porphyromonas

gingivalis colonizes the oral cavity early in childhood possibly through parental salivary

transmission, the species appears to become more stable in the late teenage years as

4 deeper pockets develop [32]. This could potentially indicate a long-term risk factor for

[34].

Throughout the transitional phases of primary, mixed, and permanent dentitions,

the oral microbiota is continuously changing. Based on 454 pyrosequencing, attempts to

define an overall healthy oral microbiome composed of key core bacterial species have

been made. The predominant taxa have been generally described to consist of ,

Proteobacteria, Actinobacteria, and Fusobacteria with an average of 266

"species-level" phylotypes [22]. Other studies have indicated the potential role of P.

catoniae and N. flavescens in association with healthy, caries-free dentitions in young

children [35]. However, due to a small sample sizes and lack of comprehensive microbial

community analyses at the species-level, further research is warranted to understand the

overall acquisition of the microbiome from infancy to adolescents.

The objective of this research is to conduct a cross-sectional study to reveal the

overall prevalence of oral bacterial communities and their natural path of acquisition from after the first year of life up until the age of fourteen. This will allow us to understand community stability, determine how microbiota manipulation can cause or prevent oral disease such as caries, and create an integrative map of the transitioning oral microbiota from primary dentition to permanent dentition. By understanding the oral

microbiome in its most comprehensive state, bacterial agents that contribute to disease

susceptibility may be identified and therapeutic strategies in controlling caries may

further be explored.

5 Hypothesis

The establishment of the oral microbial communities has been studied for years

however previous research has focused on limited numbers of intra-oral bacterial species

colonization. With the availability of next generation sequencing, large-scale whole- genome sequencing has become faster and allows for comprehensive microbial community profiling. This novel technology has allowed us to determine the order of acquisition of the oral microbiota. In conjunction, 16S rRNA gene pyrosequencing was used to determine microbial community composition and diversity at the level of species.

These methods have allowed us to understand the core set of oral microbial species among children, its evolution throughout adolescence, and the role in bacterial community inter-relationships. We expect to find an orderly acquisition of the oral microbiota, composed of key core bacterial communities, from infancy to adolescence.

With advancing age leading to tooth eruption, and eventually transitioning from primary to permanent dentition, we expect to see increasing complexity of the oral microbial communities, perhaps due to the availability of different niches for bacterial adherence, exposure to salivary enzymes, environmental factors, and dietary habits.

Hypothesis: The community composition of the oral microbiome among the

supragingival, subgingival, and salivary environments will show increase in species

diversity with advancing age (beginning after age 1).

6 Materials and Methods

Clinical Methods

Subject Recruitment

116 subjects between the ages of 1 through 14 were recruited from the Dental Clinic at

Nationwide Children’s Hospital by the study hygienist under the supervision of Dr. Ann

Griffen. Written permission from parents and an additional assent from children 8 yrs of age or older were both obtained. Subjects were examined and sampled for baseline data.

Participants with missing data for a single timepoint were included in the analysis, but subjects were dropped from the study if two consecutive visits were missed. Our electronic medical record (EPIC with a custom in-house developed pediatric dental module) facilitated tracking and review of dental and medical records and also retaining up-to-date contact information since records are updated if a patient returns to any NCH facility for any services. The hospital provides a million outpatient visits per year with over 33,000 patient visits in the dental clinic, thus providing an ample pool of subjects for our study.

Inclusion/exclusion criteria

Inclusion criteria were ASA status I or II (no serious medical problems) and an English- speaking primary caregiver who accompanied the child to dental visits. Exclusion criteria were ASA status III or greater, chronic disease affecting the immune system or requiring chronic use of antibiotics (including requirement for antibiotic prophylaxis for infective

7 endocarditis), early onset periodontitis (rare and expected to show an altered microbial

profile), and . Sampling was not conducted within 30 days of any antibiotic

therapy, and at times, delayed if necessary. Each age cohort was relatively balanced on

gender and race.

Data Collection

At each visit tooth presence, caries, , plaque levels, presence of visible tongue

, restorations, sealants, orthodontic appliances, and soft tissue lesions were scored

and recorded by the study hygienist under the supervision of Dr. Griffen or the attending

dentist at the clinic. History of antibiotic use, practices, number of persons

residing in household, daycare or school arrangements, fluoride exposure (water and

topical), a simple diet survey focusing on carbohydrate frequency, and tobacco

exposure/use history were collected by interview. Information on breast-feeding and

delivery mode was obtained. For subjects younger than 3 years of age, information on

pacifier, bottle or sippy cup use was recorded as well.

Sampling

Subjects were sampled at least 1 hr after home oral hygiene or consuming food or drink,

and prior to any dental prophylaxis or other dental procedure. Saliva sampling was conducted with a technique that can be uniformly used for children of all ages so that samples were comparable. Saliva was collected by placing a sterile, soft, flocked Copan swab in the right lingual vestibule for a minimum of 30 seconds and then swabbing into

8 both buccal vestibules and finally across the dorsal surface of the tongue. The size of the

swab was adjusted to size of child. The swab was placed in ATL buffer and stored under

refrigeration until being transported to the lab for storage at -20o C and until DNA was

isolated. In addition, both supragingival and subgingival samples were collected. Sterile

microbrushes were used to collect the supragingival plaque from the buccal surfaces of

all teeth in the mandibular right quadrant, and sterile paper points were then inserted into

the mesial sulcus of each of these teeth to obtain subgingival samples. Supra- and

subgingival samples were each pooled separately and stored at -80o.

Laboratory Methods

New Generation Sampling

The relative levels of bacterial species were analyzed using a novel technique. DNA was

isolated followed by 16S rRNA gene amplification and Illumina MiSeq sequencing. 16S

metagenomic sequence library prep was modified to work on the U1 to U3 region of the

16S gene. Sequences were identified at the level of species by blast of the CORE

database with >98% sequence identity (36). Mothur program was used to make contigs

and filter sequence (37). The relationship of age to microbial community composition

was determined using Bray Curtis multidimensional scaling and the EnvFit test, and the

relationship of microbial community complexity to age was analyzed.

Information derived from the following thesis “Sulyanto, Rosalyn. "The Natural History of Oral Bacteria Acquisition in the Developing Infant." Electronic Thesis or Dissertation. Ohio State University, OhioLINK Electronic Theses and Dissertations Center. 17 Jul 9 2016.”

Bioinformatics Methods

Sequences were separated by barcodes, trimmed for primers and low quality and filtered

for length using mothur [37]. The sequence reads were used as queries for a blastn search

[38] (parameters: -dust no -gapopen 0 -gapextend 0 -reward 1 -penalty -2 –word_size 10)

of an extended version of the CORE database [39]. The sequence reads were assigned to

species-level OTUs if they matched database sequences at over 98% identity for a region

of greater than 350 bp. Some previously named species have been difficult to

disambiguate based on 16S analysis and those have been indicated with combined names.

Sequences without matches were used to expand the coverage of the database. They were first clustered at 99.5% identity using uclust [40], and non-chimeric clusters were

identified using uchime [41]. Clusters with over 25 members were judged likely to be error free and to represent permanent residents of the oral cavity. Such clusters of pyrosequences were used to search Genbank to identify longer sequences, preferably near full length to add to the database. If there were no long matches ≥ 98% identity, a representative pyrosequence from the cluster was added to the database.

Information derived from the following thesis “Sulyanto, Rosalyn. "The Natural History of Oral Bacteria Acquisition in the Developing Infant." Electronic Thesis or Dissertation. Ohio State University, OhioLINK Electronic Theses and Dissertations Center. 17 Jul 2016.”

10

Statistical Analysis

NMDS of Bray-Curtis dissimilarities between samples and species was performed with

the metaMDS function of the vegan package in R [42]. Dispersion ellipses were

calculated using the ordiellipse function of vegan, and PERMANOVA tests of

differences between groups were calculated with the adonis function [42]. The natural

logarithm base with the diversity function of vegan was calculated using the Shannon

diversity index. Shannon diversity was calculated using R. Measure of levels of bacterial

species over time were analyzed using a linear mixed effects model. False discovery rate

correction for multiple comparisons was made using the Benjamini and Hochberg

procedure. Wilcoxon signed-rank test was used to compare related samples among sites

for each species. In our secondary analysis focused on the effect of caries on overall bacterial composition, caries status was categorized in the following manner: “No caries” was defined as no clinical caries detected during clinical and radiographic exams, “ECC” also known as early childhood caries was defined as caries present in participants under the age of 5, and “Non-ECC” or late-onset caries was defined as caries present in participants over the age of 5. Decayed and filled surfaces (dfs/+DFS) scores were calculated based on the numbers of cavitated lesions and completed restorations.

11 Ethical Considerations

This study was approved by the Institutional Review Boards of Nationwide Children’s

Hospital and the Ohio State University. Signed informed consent from all parents and an additional assent from children 8 yrs of age or older were obtained for the study prior to

enrollment.

12 Results

Study Participants

One hundred and sixteen participants were recruited for this study. Age distribution

varied among the participants with the most participants being around 8 years of age

(12.1%) [Figure 1]. All participants varied among race and were relatively evenly divided

among gender (54.3% females, 45.7% males). About 54.3% of the participants were

Black or African American with the remaining being White (44.8%) or Asian (0.9%).

90.5% were of non-Hispanic or Latino origin [Table 2]. Among the participants, 294 samples were collected with the following site-specific sample distribution: saliva

(89.7%), supragingival (89.7%), and subgingival (74.1%). Lower percentage values for

subgingival samples are due to samples not being sequenced [Table 3].

Effects of Age

Based on the Shannon Diversity Index/Species Richness linear mixed effects model, age

had very little effect on species diversity and species richness in the subgingival,

supragingival, and salivary samples [Figures 3-4]. Site-specific MDS plots showed that

age had no effect on community composition. A very small effect was detected in the

supragingival sample (p=0.015), however due to the small sample size of this study, the

effect was not highly significant [Figure 5]. Multiple bacterial communities were also

13 detected in the samples, however as participants aged these colonies continued to decline

over time [Figure 6]. Streptococcus intermedius, Kingella denitrificans, and

Porphyromonas HF001 showed reduce number of communities in the subgingival

samples. Of note, decreased in the supragingival samples, which

may be due to our small sample size of participants younger than 4 years of age, and

Granulicatella elegans and Porphyromonas HF001 decreased in the salivary samples.

There were no samples that showed significant increase in specific bacterial communities

within the three sites.

Effects of Site

Differences in terms of community composition were detected through site-specific MDS

analysis. Bacterial composition among the supragingival and subgingival niches were

closely related, with communities clustering near each other [Figure 7 ]. Communities in

the salivary sample were relatively distant from the other two sites. This analysis was

driven by species, genus and class of the detected species listed in [Figure 8].

Effects of Caries

A secondary analysis focused on caries status (no caries, early childhood caries (ECC), and non-ECC) and dfs/+DFS (decayed and filled surfaces in primary and mixed dentition) was completed. Site-specific MDS plots showed that decayed surfaces in

14 primary, mixed and permanent dentitions did not effect overall community composition

[Figure 9 and Figure 10].

Discussion

This cross-sectional study focuses on exploring the complexity of the oral microbiome from infancy to adolescence utilizing a novel technique, Illumina MiSeq sequencing. Our findings support our older studies on the infant microbiome complexity as well as highlight prevalence of bacterial communities as children approach adolescence. Understanding the natural acquisition of the oral microbiome can aid in our ability to develop caries preventive strategies.

Our study participants varied over race and ethnicity while gender remained balanced. All subjects were recruited during hygiene appointments to ensure random distribution of low caries risk and high caries risk patients. Patients on recent antibacterial therapy (<30 days of sampling appointment) were not sampled due to alterations of the oral microbiome. To determine variability in microbial complexity, sampling was obtained from three environmental niches: saliva, subgingival and supragingival. In particular, we were interested in seeing if tooth eruption and further development of subgingival and supragingival areas altered oral microbial composition over time.

Our analysis showed that age (after the first year of life through 14 years) appeared to have little effect on species diversity and community composition in salivary,

15 supragingival, and subgingival samples. Particular site-specific bacterial taxa decreased

over time. Within the subgingival environments, gram-positive Streptococcus

intermedius and gram-negative Kingella denitrificans and Porphyromonas HF001 communities decreased over time. Studies have shown that Streptococcus intermedius is

the dominant species found in subgingival plaque and known to cause abscesses [43]. In

the supragingival environment, gram-positive Streptococcus mutans decreased over time,

which was not a significant finding. Based on our MDS plot analysis, a very small effect

was detected in the supragingival samples in terms of community composition however

this was also not significant. This is mainly due to our small sample size of participants younger than 4 years of age. The salivary environment showed decreased communities of

gram-positive Granulicatella elegans and Porphyromonas HF001. It is important to note

that the decline of Porphyromonas HF001 colonies is unusual as over time, the species

becomes more stable and may possibly be indicative as a risk factor for periodontal

disease. [32, 34].

In addition, site-specific community composition differences were driven by

rank. Based on differences in species, genus and class, supragingival and subgingival

communities were similar. This is likely due to the presence of plaque surrounding these

environments. The composition of the oral microbiome among these sites may be

influenced by type and frequency of food intake, as well as capabilities of bacterial

adherence at teeth erupt [20, 23].

Our secondary analysis involving caries status and dfs/+DFS showed no impact

on community composition or age. We sampled directly into three specific niches:

16 salivary biofilm against the buccal mucosa, supragingival margin, and subgingival sulcus.

While these areas harbor small communities of Streptococcus mutans, sufficient quantities of colonies were not detected in the overall microbiome due to sampling not being performed in large cavitated lesions, which contain larger quantities.

Taken together, our results demonstrated that the acquisition of the oral microbiome appears to be seen during the first 12 months of life with no significant changes detected after the first year of life. The oral microbiome may not be altered until much later on possibly during the late teen years. Further long-term monitoring during will allow us to understand community stability, determine how microbiota manipulation can cause or prevent oral disease such as caries. This will allow us to create an integrative map of the transitioning oral microbiota from primary dentition to permanent dentition.

Limitations and Future Directions

Our primary limitation in this study was our small sample size. This limited the statistical power in many of our analyses. Another major limitation was the inability to control for confounding factors from our participants due to our study being a cross- sectional analysis. In addition, further sequencing is required on the DNA samples that were collected during subgingival sampling. Further focus on recruitment of healthy young (<4 years of age) and older (>8 years of age) patients and maintenance of balance among ethnicity, race and gender is needed. We should also consider targeting late teenagers and young adults to assess when the introduction of the adult microbiome occurs in a new study. The future direction of this cross-sectional study is focused on

17 longitudinal monitoring with six-month recalls over the span of 3 years and understanding the stability of the oral microbiome from after the first year of life through

14 years.

18

Tables

19

13 12 11 10 9 8 7 12.1 6 9.5 5 8.6 8.6 8.6 8.6 8.6 7.8 4 6.9 6.9 3 5.2 5.2 2 1 1.7 1.7 1 yr 2 yr 3 yr 4 yr 5 yr 6 yr 7 yr 8 yr 9 yr 10 yr 11 yr 12 yr 13 yr 14 yr

Table 1. Percent Distribution of Age Cohorts

20

Table 2. Participant Demographic Factors

21

Table 3. Participant Sample Distribution

22

Figures

23

% prevalence Species 0‐3 mo 4‐6 mo 7‐9 mo 10‐12 mo Streptococcus mitis group 100 100 100 100 Rothia mucilaginosa 88 94 100 100 Veillonella atypica dispar parvula 71 88 100 100 Streptococcus salivarius group 94 94 100 93 Gemella haemolysans 88 88 88 93 Colonizers Veillonella HB016 71 82 82 87 Prevotella melaninogenica 53 76 94 87 Early 47 71 82 80 Streptococcus parasanguinis 41 53 94 100 Granulicatella adiacens 47 41 100 93 Granulicatella elegans 41 47 82 93 Actinomyces odontolyticus lingnae 41 65 88 80 Porphyromonas catoniae 35 29 71 73 Streptococcus australis 24 65 76 67 Porphyromonas HF001* 35 35 65 93 Neisseria flavescens 35 29 59 87 Leptotrichia FP036* 12 29 41 80 Colonizers TM7 B350‐25* 24 29 53 73 Gemella sanguinis 12 24 47 73 Late Streptococcus VG051 41 12 35 73 Streptococcus cristatus 41 41 65 67 polysaccharea 18 24 41 67 Prevotella oral taxon 299 18 24 41 67 Neisseria flava mucosa pharyngis 35 6 18 67 * not yet cultivated Figure 1. Abundance Heatmap Reflecting Prevalence of 26 Core Species

24

Figure 2. Resolution of Early Chaos

25

p = 0.9 Beta est. : -0.0031

div

2.02.53.03.5 Subgingival

123567891011121314

p = 0.7 Beta est. : -0.0063

div

2.0 2.5 3.0 3.5 Supragingival

1234567891011121314

p = 0.8 Beta est. : 0.0071

div

1.5 2.0 2.5 3.0 3.5 Saliva

1234567891011121314

Figure 3. Shannon Diversity Index by Age

26

p = 0.6 Beta est. : 0.21

div

Subgingival

20 25 30 35 40 45 50

123567891011121314

p = 1 Beta est. : -0.012

div

Supragingival

20 25 30 35 40 45 50 1234567891011121314

p = 0.3 Beta est. : 0.37

div

15 20 25 30 35 40 45 Saliva

1234567891011121314

Figure 4. Species Richness by Age

27

NA: Mean Levels:Species NA: Mean Levels:Species NA: Mean Levels:Species EnvFit p = 0.662 EnvFit p = 0.015 * EnvFit p = 0.181

1 1 1 14 14 14 MDS2 MDS2 MDS2 -0.2 0.0 0.2 0.4 -0.4 -0.2 0.0 0.2 0.4 -0.4 -0.2 0.0 0.2 0.4 -0.4 -0.2 0.0 0.2 0.4 -0.4 -0.2 0.0 0.2 0.4 -0.4 -0.2 0.0 0.2 0.4 MDS1 MDS1 MDS1

Figure 5. Effects of Age on Community Composition

28

Figure 6. Presence of Site Specific Species Decreasing Over Age

29

Saliva vs Supragingival vs Subgingival: Mean Levels:Species Permanova p = 0.000999 *** Beta-dispersion p = 0.798

Saliva Supragingival Subgingival MDS2 -0.2 0.0 0.2 0.4

-0.4 -0.2 0.0 0.2 0.4

MDS1

Figure 7. Effects of Site on Community Composition

30

Streptococcus mitis pneumoniae infantis oralis **** Streptococcus **** **** Rothia mucilaginosa **** Streptococcus vestibularis salivarius **** Streptococcus parasanguinis **** Gemella haemolysans **** Rothia **** parainfluenzae **** Prevotella melaninogenica **** Neisseria flavescens **** Haemophilus **** Streptococcus VG051 **** Granulicatella adiacens **** Actinomyces odontolyticus lingnae **** Granulicatella **** Streptococcus australis **** Prevotella histicola **** Geme lla sa ngu in is **** Streptococcus ET G 4d04 **** Gemella **** *** Oribacterium sinus **** Streptococcus oral taxon 066 **** Haemophilus 3A01 **** Oribacterium **** Haemophilus parahaemolyticus *** Haemophilus oral taxon 036 **** Prevotella oral taxon 299 **** Atopobium **** Atopobium parvulum **** DO039 **** Actinomyces graevenitzii **** Streptococcus peroris **** Stomatobaculum *** Bergeyella JF233961 *** Prevotella oral taxon 306 **** Lachnoanaerobaculum orale **** Megasphaera **** TM7 oral taxon 352 **** Haemophilus nbw161b08c1 **** Coriobacteridae *** Stomatobaculum longum *** Solobacterium **** Megasphaera micronuciformis **** Solobacterium moorei **** Prevotella scopos **** Bergeyella ncd1730f01c1 *** Mogibacterium *** Prevotella shahii **** Eubacterium sulci infirmum **** Corynebacterium argentoratense *** Microbacterium **** Neisseria sicca **** Streptococcus GM006 **** Mogibacterium neglectum vescum *** Propionivibrio *** **** Catonella GI038 **** Neisseria FJ557362 **** Erysipelotrichi **** Prevotella pallens **** Brachybacterium **** Catonella GQ106843 **** TM7 Novel GBNMMOK01C81NC **** Propionibacterium acnes **** Brevundimonas *** Selenomonas dianae **** maltophilum *** Selenomonas oral taxon E97 *** Centipeda **** Propionivibrio HE018 *** Brachybacterium rhamnosum **** Brevundimonas HINF004 *** Selenomonas flueggei **** GN02 **** GN02 JF214631 **** Capnocytophaga FJ773364 *** Selenomonas 201B03 **** Arthrobacter **** GN02 **** Centipeda periodontii **** Arthrobacter woluwensis **** Kingella oral taxon 012 **** unclassified Comamonadaceae **** Veillonellaceae oral taxon 135 145 148 155 *** Capnocytophaga X066 **** Leptotrichia EI022 *** Comamonadaceae FX006 *** Olsenella **** Actinobaculum oral taxon 848 **** Olsenella F0004 **** oral taxon 167 *** unclassified Veillonellaceae **** Prevotella nigrescens **** SR1 ncd2777g11c1 **** Actinomyces israelii **** unclassified Clostridiales C *** Selenomonas GU413405 **** **** Prevotella micans *** Streptococcus AY020 **** Capnocytophaga U41352 **** Johnsonella *** TM7 oral taxon 347 **** Capnocytophaga P4G_35 P4 **** Selenomonas 403445 **** Catonella **** Prevotella BR014 **** Alloprevotella 601F05 **** Selenomonas DY027 **** Peptococcus **** Treponema socranskii subsp. buccale paredis socranskii **** Atopobium rimae **** Eubacterium brachy **** Selenomonas AA024 **** Eikenella **** Streptococcus anginosus **** **** Aggregatibacter segnis **** Selenomonas 502C12 **** Lautropia **** valvarum **** Actinomyces dentalis **** Bergeyella FJ976204 **** Abiotrophia **** Prevotella maculosa **** Actinomyces georgiae **** Johnsonella ignava *** Capnocytophaga X089 **** Bergeyella **** Aggregatibacter DQ003635 **** Peptococcus oral taxon 075 **** Neisseria oralis *** unclassified Peptostreptococcaceae **** Aggregatibacter AY349380 **** Lachnoanaerobaculum umeaense *** **** Capnocytophaga DS022 *** Dialister **** Catonella morbi **** Aggregatibacter aphrophilus **** Prevotella saccharolytica **** Leptotrichia trevisanii **** Actinobaculum **** Kingella denitrificans **** Lachnospiraceae 502G12 **** **** Cardiobacterium **** Treponema vincentii medium **** TM7 oral taxon 349 **** Selenomonas artemidis **** unclassified E **** Prevotella oulorum **** Leptotrichia goodfellowii **** Lautropia mirabilis **** Abiotrophia defectiva **** Treponema **** TM7 **** Selenomonas infelix **** Lachnospiraceae oral taxon 100 **** **** Porphyromonas *** Streptococcus cristatus **** D ialist er in visus **** Leptotrichia hofstadii **** Tannerella **** Eubacterium yurii **** Actinobaculum 12B759 **** Bergeyella 602D02 **** Neisseria elongata **** Parvimonas **** Capnocytophaga granulosa **** Lachnoanaerobaculum saburreum **** Selenomonas sputigena **** Aggregatibacter **** TM7 nbw1037h06c1 **** **** Capnocytophaga ochracea **** Campylobacter showae **** unclassified Lachnospiraceae A **** Actinomyces massiliensis **** Capnocytophaga ChDC OS44 **** Alloprevotella tannerae *** Actinomyces gerencseriae **** Kingella **** Leptotrichia hongkongensis **** Corynebacterium durum **** Tannerella BU063 **** Propionibacterium **** **** Bacteroidales oral taxon 274 **** Actinomyces johnsonii **** Neisseria *** Fusobacterium nucleatum subsp. nucleatum **** Kingella oralis **** Bacteroidia **** Capnocytophaga gingivalis **** TM7 oral taxon 348 **** Campylobacter **** Leptotrichia oral taxon 225 **** Gemella morbillorum **** Selenomonas noxia **** Prevotella *** Parvimonas micra **** Propionibacterium propionicus **** Campylobacter gracilis **** TM7 **** TM7 401H12 **** Leptotrichia BU064 **** Leptotrichia shahii **** Leptotrichia wadei **** Selenomonas **** Rothia aeria **** Streptococcus gordonii **** Flavobacteria **** Capnocytophaga sputigena **** Actinomyces **** Prevotella oris **** Leptotrichia buccalis **** Capnocytophaga leadbetteri **** Corynebacterium **** Porphyromonas catoniae **** Streptococcus intermedius constellatus **** Neisseria flava mucosa pharyngis **** Prevotella loescheii **** Capnocytophaga **** Actinomyces viscosus naeslundii oris **** Fusobacterium nucleatum subsp. animalis **** Fusobacterium nucleatum subsp. fusiforme **** Leptotrichia **** Fusobacterium nucleatum subsp. polymorphum **** **** Corynebacterium matruchotii **** Fusobacterium **** Fusobacteria ****

1e-17 1e-15 1e-13 1e-11 1e-09 1e-07 1e-05 0.001 0.1 1e-17 1e-15 1e-13 1e-11 1e-09 1e-07 1e-05 0.001 0.1 1e-09 1e-08 1e-07 1e-06 1e-05 1e-04 0.001 0.01 0.1

Figure 8. Species, Genus and Class Abundance Profiles

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Figure 9. Effects of Caries Status on Community Composition

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Figure 10. Effects of dfs/+DFS on Community Composition

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References

1. Turnbaugh. P.J. et al. The . Nature. 2007; 449:804– 810.

2. Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207-214 (2012).

3. Turnbaugh, P. J. et al. A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009).

4. Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010).

5. Grice, E. A. et al. Topographical and temporal diversity of the human skin microbiome. Science 324, 1190–1192 (2009).

6. Ravel, J. et al. Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci USA 108 (Suppl 1). 4680–4687 (2011).

7. Costello, E. K. et al. Bacterial community variation in human body habitats across space and time. Science 326, 1694–1697 (2009).

8. Koenig J. E. et al. Succession of microbial consortia in the developing infant gut microbiome. Proc Natl Acad Sci USA 108 Suppl 1: 4578-4585 (2011).

9. Palmer C. et al. Development of the human infant intestinal microbiota. PLoS Biol 5: e177 (2007).

10. Hill G. B. Preterm birth: Associations with genital and possibly oral microflora. Ann Periodontol 3, 222–32 (1998).

11. Offenbacher S. et al. Periodontal infection as a possible risk factor for preterm low birth weight. J Periodontol. 67(10 Suppl): 1103–13 (1996).

12. Mold J. E. et al. Maternal alloantigens promote the development of tolerogenic fetal regulatory T cells in utero. Science 322:1562–5 (2008).

13. Long S.S. et al. Determinants of the developing oral flora in normal newborns. Appl Environ Microbiol 32: 494-497 (1976).

14. Nyvad B, Kilian M (1987). of the early colonization of human enamel and root surfaces in vivo. Scand J Dent Res 95:369-380. 34

15. Alaluusua S, Asikainen S (1988) Detection and distribution of actinomycetemcomitans in the primary dentition. J Periodontol 59: 504-507.

16. Ellen RP, Sivendra R (1985). In vitro attachment, salivary agglutination, and surface fibril density of fresh Actinomyces isolates from two distinct oral surfaces. JDent Res 64:799-803.

17. Kolenbrander PE, Celesk RA (1983). Coaggregation of human oral Cytophaga species and Actinomyces israelii. Infect Immun 40:1178-1185.

18. Sarkonen N. et al. Oral colonization with Actinomyces species in infants by two years of age. J Dent Res 79: 864-867 (2000).

19. Kononen E. et al. Establishment of oral anaerobes during the first year of life. J Dent Res 78: 1634-1639 (1999).

20. Cephas K. D. et al. Comparative analysis of salivary bacterial microbiome diversity in edentulous infants and their mothers or primary care givers using pyrosequencing. PLoS One 6: e23503 (2011).

21. Caufield P. W. et al. Natural history of Streptococcus sanguinis in the oral cavity of infants: evidence for a discrete window of infectivity. Infect Immun 68: 4018- 4023 (2000).

22. Zaura E, Keijser BJ, Huse SM, Crielaard W (2009) Defining the healthy "core microbiome" of oral microbial communities. BMC Microbiol 9: 259.

23. Berkowitz RJ (2006) Mutans streptococci: acquisition and transmission. Pediatr Dent 28: 106-109; discussion 192-108.

24. Carletto Korber FP, Cornejo LS, Gimenez MG (2005) Early acquisition of Streptococcus mutans for children. Acta Odontol Latinoam 18: 69-74.

25. Carlsson J, Grahnen H, Jonsson G (1975) Lactobacilli and streptococci in the mouth of children. Caries Research 9: 333-339.

26. Carlsson J, Grahnen H, Jonsson G, Wikner S (1970) Early establishment of Streptococcus salivarius in the mouth of infants. Journal of Dental Research 49: 415-418.

27. Caufield PW, Cutter GR, Dasanayake AP (1993) Initial acquisition of mutans streptococci by infants: evidence for a discrete window of infectivity. Journal of Dental Research 72: 37-45. 35

28. Florio FM, Klein MI, Pereira AC, Goncalves BR (2004) Time of initial acquisition of mutans streptococci by human infants. J Clin Pediatr Dent 28: 303- 308.

29. Kononen E (1999) Oral colonization by anaerobic bacteria during childhood: role in health and disease. Oral Dis 5: 278-285.

30. Kononen E (2000) Development of oral bacterial flora in young children. Ann Med 32: 107-112.

31. Kononen E, Asikainen S, Saarela M, Karjalainen J, Jousimies-Somer H (1994) The oral gram-negative anaerobic microflora in young children: longitudinal changes from edentulous to dentate mouth. & Immunology 9: 136-141.

32. Lamell CW, Griffen AL, McClellan DL, Leys EJ (2000) Acquisition and colonization stability of Actinobacillus actinomycetemcomitans and in children. Journal of clinical microbiology 38: 1196- 1199.

33. McClellan DL, Griffen AL, Leys EJ (1995) Age and prevalence of Actinobacillus actinomycetemcomitans in children. Journal of Dental Research 74: 587.

34. McClellan DL, Griffen AL, Leys EJ (1996) Age and prevalence of Porphyromonas gingivalis in children. J Clin Microbiol 34: 2017-2019.

35. Crielaard W, Zaura E, Schuller AA, Huse SM, Montijn RC, et al. (2011) Exploring the oral microbiota of children at various developmental stages of their dentition in the relation to their oral health. BMC Med Genomics 4: 22.

36. Haas BJ, Gevers D, Earl AM, Feldgarden M, Ward DV, Giannoukos G, Ciulla D, Tabbaa D, Highlander SK, Sodergren E, Methe B, DeSantis TZ, Petrosino JF, Knight R, Birren BW (2011) Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome research 21: 494-504.

37. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and environmental microbiology 75: 7537-7541.

36

38. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. Journal of Molecular Biology 215:403–410.

39. Griffen AL, Beall CJ, Firestone ND, Gross EL, Difranco JM, Hardman JH, Vriesendorp B, Faust RA, Janies DA, Leys EJ (2011) CORE: a phylogenetically- curated 16S rDNA database of the core oral microbiome. PLoS ONE 6:e19051.

40. Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461.

41. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200.

42. Oksanen J, Blanchet FG, Kindt R, Legendre P (2013) Package “vegan.” R Packag …

43. Whiley, RA, Freemantle, L, Beighton, D, Radford, JR, Hardie, JM, Tillotsen, G (1993). , identification and prevalence of Streptococcus anginosus, S. intermedius and S. constellatus from the human mouth. in Health and Disease 6: 285 – 291.

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Appendix A: Exam and Sampling Form

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Appendix B: Contact Info and History Form

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