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The American University in Cairo
School of Sciences and Engineering
Using Culture Independent Approaches to Gain Insights
Into Human Urinary Tract Microbiome in
Healthy Male and Female individuals
A Thesis Submitted to
Biotechnology graduate program
In partial fulfilment of the requirements for the degree of
Master of Science
By
Sarah Hussein El-Alawi
Under the supervision of
Dr. Hamza El-Dorry
January / 2012
The American University in Cairo
Using Culture Independent Approaches to Gain Insights into Human Urinary Tract
Microbiome in Healthy Male and Female individuals
A Thesis Submitted by
Sarah Hussein El-Alawi
To the Biotechnology Graduate Program
January / 2012
In partial fulfilment of the requirements for
The degree of Master of Science
Has been approved by
Thesis Committee Supervisor/Chair
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Affiliation
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Thesis Committee Reader/Examiner
______________________________________________
Affiliation
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Thesis Committee Reader/Examiner
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Affiliation
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Thesis Committee Reader/External Examiner
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Director
Date
Dean
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Date
DEDICATION
This work is dedicated to my parents and my brother who supported me at all
time of stress and happiness. Without their encouragement, I couldn’t be able
accomplish my work.
_______________
iii
ACKNOWLEDGEMENTS
It is honourable to mention all people who contributed with their guidance and
assistance that was provided during my thesis project. First of all, I would like to express my
deepest gratitude to Prof. Dr. Hamza El-Dorry, the dissertation advisor for his guidance,
expertise and patience that was continuously provided and assisted in broadening my
graduate experience.
A very special thanks to Associate Research Professor, Dr. Ari Jose' Scattone Ferreira
and Mr. Mustafa Adel for their suggestions and efforts in the computational analyses part.
I would like to thank Dr. Ahmed A. Sayed and Mr. Amged Ouf for their efforts in the
sequencing part and their continuous guidance in the Laboratory. Thanks also go to my
colleagues in Biotechnology master program, Rehab Abdallah, Nelly A. ElGhany and Laila
Ziko.
iv
The American University in Cairo
Using Culture Independent Approaches to Gain Insights into Human Urinary Tract
Microbiome in Healthy Male and Female individuals
By Sarah H. El-Alawi
Under the supervision of Dr. Hamza El-Dorry
ABSTRACT
Here we present comprehensive insights into the diverse collection of bacterial communities
that indigenously inhabit the urinary tract of healthy adult male and female individuals using
cultivation independent techniques. Several studies address the importance of uncultured
microbial flora that inhabits the human urinary tract in health and diseases. Thus, a deep and
accurate understanding of the factors influencing this ecological niche and its microbiome is
important to prevent possible infectious diseases.
Genomic DNA was extracted from midstream urine samples collected from 4 adult, healthy
and culture-negative male and female individuals at ages ranging from 18 to 40. Following
PCR amplifications using 63F and 1387R primers for amplification of 16S rRNA genes from
bacteria, 16S rRNA gene libraries were constructed using the amplified DNA fragments.
From each library, we sequenced approximately 60-70 clones’ inserts from both ends. The
generated 16S rRNA gene sequences were compared against RDP II database. Separate
phylogenetic analyses of the two hypervariable regions, V1-V3 and V6-V8, revealed
complex bacterial profiles with predominant taxa of Prevotella, Corynebacterium,
Lactobacillus, Weeksella and Gardnerella. Different bacterial genera that have been
identified in urinary tract overlap the microbial communities that were formerly reported in
superficial skin, gut and vaginal microbiome. Disease causing bacteria were characterized as
a part of the normal flora. Inter-individual variation within the same gender was observed,
and no single characteristic bacterial community was evident. However, significant variations
of microbial signatures between male and female individuals were observed. 16S rRNA gene
sequences
assigned
to
bacterial
genera
of
Streptococcus,
Staphylococcus,
Escherichia/Shigella and others were characterized only in urines of male subjects whereas
the genera of Atopobium, Megashpera and Oligella were identified only in urines of female
subjects. Moreover, the richness and evenness of bacterial flora of the urinary tract was
assessed by means of alpha diversity analysis. The experiments reported in this work
represent the first study of the urinary tract microbiome in healthy Egyptian male and female
v
individuals, and should help in exploring the role of bacterial flora in health and diseases of
both genders.
vi
Table of Contents
DEDICATION ..................................................................................................................... iii
ACKNOWLEDGEMENTS.................................................................................................. iv
ABSTRACT ......................................................................................................................... v
GLOSSARY AND ABREVIATIONS .................................................................................. x
CHAPTER 1: LITERATURE REVIEW ............................................................................... 1
1.1. Human Microbiome Project ............................................................................................ 1
1.1.1: Background ............................................................................................................. 1
1.1.2: Goals and Initiatives of Human Microbiome Project ................................................ 1
1.2. Cultivation dependent and independent methods: ........................................................... 1
1.2.1: Limitations of the culture dependent and independent methods: ............................... 2
1.2.2: Characterization of the human microbiome using culture dependent and independent
methods: ............................................................................................................................ 2
1.2.3: Tools used for characterization of the human urogenital microbiome using culture
independent methods: ........................................................................................................ 3
1.3. Factors affecting the microbiome structure and diversity: ............................................... 4
1.3.1: Female urogenital microbiome and probiotics: ......................................................... 4
1.3.2: Ethnic influences: .................................................................................................... 5
1.3.3: Immunological influences: ....................................................................................... 6
1.4. Female urinary system .................................................................................................... 6
1.4.1: Anatomy of the female urinary system: .................................................................... 6
1.4.2: Antimicrobial defences of the urinary tract:............................................................. 7
1.4.3: Female urinary system and microbiome: .................................................................. 9
1.4.3.1: Establishment of microbiota: ............................................................................. 9
1.4.3.2: The effect of age and hormonal status on the female microbiome: ..................... 9
1.4.3.3: The key members of the female urogenital tract microbiome: .......................... 10
1.4.3.4: Identification of Lactobacillus spp. and its role for the female urogenital health:
.................................................................................................................................... 10
1.4.3.5: Other lactic acid producing bacteria and their role for a healthy urogenital tract:
.................................................................................................................................... 11
1.5. Male urinary system ..................................................................................................... 11
1.5.1: Anatomy of the male urinary system: ..................................................................... 11
1.5.2: Male urinary system and microbiome: ..................... Error! Bookmark not defined.
1.5.2.1: Antimicrobial defences of the urinary tract: ....... Error! Bookmark not defined.
vii
1.5.2.2: The effect of age and circumcision on the male microbiome: ..... Error! Bookmark
not defined.
1.5.2.3: The key members of the male urogenital tract microbiome: .... Error! Bookmark
not defined.
CHAPTER 2: MATERIALS AND METHODS .................... Error! Bookmark not defined.
2.1 Subjects and sample collection ........................................ Error! Bookmark not defined.
2.2 DNA isolation ................................................................. Error! Bookmark not defined.
2.3 16S rRNA PCR amplification .......................................... Error! Bookmark not defined.
2.4 Cloning, 16S rRNA gene library construction and Sequencing ...................................... 15
2.5 Male and Female 16S rRNA urine sequence analyses .................................................... 16
2.5.1: Alpha diversity analysis: ........................................................................................ 16
2.5.2: Phylogenetic analysis of 16S rRNA urine sequences: Error! Bookmark not defined.
CHAPTER 3: RESULTS .................................................................................................... 18
3.1 Processing of the urine samples, PCR amplification, library construction, and sequencing
of the 16S rRNA gene……………………………………………………………………… ..18
3.2 Computational and statistical analysis of 16S rDNA of human urine microbiome .......... 18
3.2.1: Phylogenetic analysis of the female 16S rRNA sequences ...................................... 19
3.2.2: Phylogenetic analysis of the male 16S rRNA sequences ......................................... 21
3.2.3: Estimating the richness and diversity of urine microbial communities using alpha
diversity .......................................................................................................................... 23
3.3 Inter-individual variation ............................................................................................... 24
CHAPTER 4: DISCUSSION .............................................................................................. 25
REFERENCES ................................................................................................................... 31
FIGURES ........................................................................................................................... 41
TABLES ............................................................................................................................. 58
APPENDIX..............................................................................................................................64
viii
LIST OF TABLES
Table 1 Summary of Female urine bacterial communities in 3’ and 5’ sequence datasets ..... 58
Table 2 Summary of Male urine bacterial communities in 3’ and 5’ sequence datasets ........ 59
Table 3 Summary of the number of sequenced clones for each library, length of sequence
obtained from each end and quality of reads ........................................................................ 61
Table 4 Alpha diversity measurements of V6-V8 sequence dataset of male and female 16S
rRNA gene .......................................................................................................................... 62
Table 5 Alpha diversity measurements of V1-V3 sequence dataset of male and female 16S
rRNA gene .......................................................................................................................... 63
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LIST OF FIGURES
Figure 1 Distributions of different bacterial phyla ............................................................... 41
Figure 2 Gel electrophoresis of total genomics DNA from four male urine samples ............ 42
Figure 3 Gel electrophoresis of total genomics DNA from four female urine samples ......... 43
Figure 4 Gel electrophoresis of PCR amplification products of 16S rRNA gene from four
male urine samples .............................................................................................................. 44
Figure 5 Gel electrophoresis of PCR amplification products of 16S rRNA gene from four
male urine samples .............................................................................................................. 45
Figure 6 A phylogenetic tree showing the relationship between various phylotypes based on
analysis of 16S rRNA female urine sequences of V6-V8 dataset ......................................... 46
Figure 7 A phylogenetic tree showing the relationship between various phylotypes based on
analysis of 16S rRNA female urine sequences of V1-V3 dataset ......................................... 47
Figure 8 A phylogenetic tree showing the relationship between various
phylotypes based on analysis of 16S rRNA male urine sequences of V6-V8 dataset ............ 48
Figure 9 A phylogenetic tree showing the relationship between various phylotypes based on
analysis of 16S rRNA male urine sequences of V1-V3 dataset ............................................ 49
Figure 10 Comparison of major taxa taxonomically assigned to V1-V3 and V6-V8 reads of
human female 16S rRNA sequences urine sequences at the genus level............................... 51
Figure 11 Comparison of major taxa taxonomically assigned to V1-V3 and V6-V8 reads of
human male 16S rRNA sequences urine sequences at the genus level.................................. 53
Figure 12 Rarefaction curves plotted to estimate the phylotypes diversity and coverage level
of 16S rRNA urine sequences of 3’ reads from both male and female subjects .................... 54
Figure 13 Rarefaction curves plotted to estimate the phylotypes diversity and coverage level
of 16S rRNA urine sequences of 5’ reads from both male and female subjects .................... 55
Figure 14 The overall distribution of bacterial genera taxonomically assigned to 16S rRNA
urine sequences of V6-V8 dataset........................................................................................ 56
Figure 15 The overall distribution of bacterial genera taxonomically assigned to 16S rRNA
urine sequences of V1-V3 dataset........................................................................................ 57
Supplementary Figure 1 The approval letter by the institutional review board (IRB) of the
American university in Cairo.................................................................................................. 64
Supplementary Figure 2 The Medical history.........................................................................65
x
GLOSSARY AND ABREVIATIONS
ALP
AMPs
APCs
BV
C-section
Defb1
Anti-leukoprotease
Anti microbial peptides
Antigen presenting cells
Bacterial vaginosis
Caesarean section
Defensin beta 1
DSGG
GSLs
HBD
HIMI
HMP
HRT
HUSI-I
IDNS
Ig
IL12
Disialosyl gal-globoside
Glycosphingo lipids
Human beta defensin
Human Intestinal Metagenome Initiative
Human Microbiome Project
Hormonal replacement therapy
Human seminal inhibitor I
SmartGene Integrated Database Network System
Immunoglobulin
Interleukin 12
INRA
IRB
MALDI-TOF
NCBI
NIH
PLA2
rRNA
SGG
SLPI
STDs
Th1
T-RFLPs
UTIs
French National Institute for Agricultural Research
Institutional Review Board
Matrix Assisted Laser Desorption Ionization - Time of Flight
U.S. National Center for Biotechnology Information
National Institute of Health
Phospholipase A2
Ribosomal ribonucleic acid
Sialosyl gal-globoside
Secretory leukocyte protease inhibitor
Sexually transmitted diseases
T-helper 1 cells
Terminal Restriction Fragment Length Polymorphisms
Urinary tract infections
xi
CHAPTER 1: LITERATURE REVIEW
1.1. Human Microbiome Project
1.1.1: Background
The Nobel laureate Joshua Lederberg was the first to define the concept of
microbiome as ‘‘the ecological community of commensal, symbiotic, and pathogenic
microorganisms that literally share our body space’’ [1]. Most of phylogenetic data and
research focuses on bacteria, as they represent most of the microorganisms that inhabit our
bodies. The number of resident microbes in the human body is estimated to be ten times that
of the human somatic and germ cells, majority of which have not been identified or
characterized yet [2].
Due to the fact that the majority of microbes inhabiting the different environments in
the human body are uncharacterized, the National Institute of Health (NIH) established the
Human Microbiome Project (HMP) in 2007. This project aims to identify the microbial
communities that indigenously reside in different anatomical sites of the human body
including the oral and nasal cavities, gastrointestinal tracts, genitourinary tract and the human
skin [2] (Figure 1). One of the initiatives of the project is to establish the sequences of at least
900 bacterial genomes to later be utilized as a dataset of reference genomes. In addition to
this objetive, samples were collected from the main five body sites of 250 healthy volunteers:
mouth, skin, vagina, the nasal cavity and the gastrointestinal tract. Using metagenomic
approaches including 16S rRNA analysis and whole genome shotgun sequencing (WGS) an
attempt was lunched to characterize and describe the structure of the microbial communities
that reside in these sites [2]. The main goal of the Human Microbiome Project is to determine
and characterize the core microbiome at each site of the human body.
1.1.2: Goals of Human Microbiome Project
The first objective of the Human Microbiome Project aims to define the influences of
age, lifestyle, gender, nutrition and medication on the diversity of the microbial community in
the different sites of the human bodies (Figure 1). This work should help understanding the
relationship between the resident microbial communities and their impact on human health
[3]. The second objective is to create a reference dataset of the microbial genome sequences
and characterize the human microbiota to determine their diversity and complexity. This
1
could be achieved by metagenomic analysis and also through sequencing of cultured
microbial genomes. Sequencing techniques ranging from 16S rRNA and other deep
metagenomic sequencing methods were applied. The vast information and studies collected
are arranged precisely and organized by developing new computational tools [3]. In addition,
HMP aims to design and implement new strategies for manipulation of microbiome in both
healthy and diseased individuals.
1.2. Cultivation dependent and independent methods:
1.2.1: Limitations of the culture dependent and independent methods
Today, culture independent techniques are focused on discovering novel and more
diverse microbes that reside in various sites of the human body. These works reveal slow
growing, uncultivable, and rare bacteria. The most significant culture independent method to
determine the community structure is the molecular approach based on sequencing of
hypervariable regions from the small subunit of the ribosomal RNA gene. Although the
cultivation dependent method is inexpensive and succeeds in identification of various
bacteria, it requires specialized instruments for bacterial identification of anaerobic
microorganisms, and suitable culture medium and specific growth condition for the rare and
slow growing bacteria[4], [5], [6]. However culture independent approach (metagenomics)
cannot substitute the culture-based methods since the phenotypic properties and microbial
interactions with different human environments require isolation of viable microbes.
However, molecular based methods succeeded in providing insight about microbial
functional characteristics of slow and uncultured microbes [7], [8]. In addition, sequencing of
a whole microbial genome using molecular based methods can be achieved [9].
1.2.2: Characterization of the human microbiome using culture dependent and
independent methods
The differences between culture dependent and independent methods were evident in
a study by Ian Kroes and colleges [10] where the bacterial diversity in the subgingival crevice
was determined. The results obtained 56 bacterial isolates by cultivation methods. At the
genus level, 37.5% of those isolates could not be identified, while 55% could not be
identified at the species level. Sequencing of 16S rRNA from the 56 isolates showed 28
unique phylotypes. Sequences obtained by 16S rRNA amplification and cloning revealed
2
higher bacterial diversity than those obtained by cultivation. The uncharacterized sequences
show less than 99% similarity to ARB database of the bacterial 16S rRNA sequences. From
2001 to 2007 about 215 novel bacterial species have been discovered and 29 are novel genera
[4]. In a 5 year study conducted by Peter and colleges [11], they collected bacterial isolates
from urine, faeces, cerebrospinal fluid, respiratory samples and genitourinary tract swabs.
They were subjected to 16S rRNA sequencing and analyzed using NCBI Genbank database
and IDNS (SmartGene Integrated Database Network System). Isolates giving sequence
homology of less than 99% to the corresponding taxa were indicated as novel species and
those with less than 95% of sequence homology were indicated as novel genera [4]. Out of a
total of 1,663 isolates, 60 bacterial isolates were unknown 16S rRNA sequences giving less
than 99% sequence homology on analysis and reported as novel species. After antibiotic
therapy to the susceptible isolate and following the patient’s history and laboratory findings,
10 cases showed that isolates may play a pathogenic role and 8 out of these 10 were reported
as infective agents. One of the novel bacterial species that was identified in the patients’
samples with urinary tract infections were Actinobaculum sp. and Gardnerella sp. During the
study, the numbers of new 16S rRNA sequences in IDNS database increased by a factor of 4
while those in the NCBI Genebank database increased by a factor of 15.
1.2.3: Tools used for characterization of the human urogenital microbiome using
culture independent methods
The techniques are based on analysis of the genetic material of the collected microbial
community to describe the genomic composition, or sequencing of the 16S rRNA clones for
bacterial phylogenetic analysis [12]. The most widely used molecular method is the
sequencing of 16S rRNA clones for many reasons; 1) the approximate size of the 16S rRNA
is 1.5 kb which is sufficient for sequence analysis, 2) the 16S rRNA gene encodes for a part
of the small subunit of ribosome, which is highly conserved in nearly all prokaryotes required
for accurate alignments, 3) the 16S rRNA contains nine hypervariable regions (V1-V9) which
enables the identification of the diversity among different bacterial species due to sequence
divergence along different evolutionary times and 4) pyrosequencing of 16 rRNA
hypervariable regions provides in-depth taxonomic community profiling. Therefore, the
sequencing of 16S rRNA has been applied to demonstrate taxonomical and phylogenetic
relations among various species. The American biologist and physicist, Carl Woese, who
made this technique accessible when he set a proposal to define the tree of life by dividing it
3
into three main domains: Archaea, Bacteria and Eucarya [13]. This tree of life relies on
genetic diversity rather than on morphological similarities.
The hypervariable regions V2, V3 and V6 were the most appropriate targets for
differentiation among various bacterial species while V4, V5, V7 and V8 were the least
appropriate targets for species differentiation [14]. The three hypervariable regions succeeded
in detection of 110 various bacterial species. PCR primers, or known as universal primers,
bind to conserved regions of the 16S rRNA gene and amplify the hypervariable regions. The
forward primer 63F and the reverse primer 1387R were used in a study aimed to evaluate the
efficacy of both primers in identification of diverse bacterial species compared to the
currently used PCR primers. They practically showed higher PCR specificity [15]. They were
successfully able to amplify 16S rRNA genes of various organisms as a novel type of
Proteobacteria (sulphate- and iron- reducing bacteria) and bacteria with high G+C rich
sequences like organisms belonging to Micrococcus genera. However, the primer pair; 27F
and 1392R failed to amplify those 16S rRNA genes [15].
1.3. Factors affecting the microbiome structure and diversity:
There are several unexplored and questionable issues concerns whether the host
genetics, diet, lifestyle, physiological (e.g. pregnancy and menopause) and pathological
factors (e.g. urinary tract infections, sexually transmitted diseases...etc) contribute to the
microbiome structure and diversity of the genitourinary tract of both male and female
individuals. In the following section, we present a literature review regarding these issues.
1.3.1: Female urogenital microbiome and probiotics:
In 1928, the concept of probiotics as beneficial group of bacteria such as lactobilli
artificially administered to restore the unbalanced microflora [16] was first presented by
Stanley Thomas. He performed in-vivo and in-vitro experiments, that resulted in eradication
of Neisseria gonorrhoeae by the addition of a broth of cultured Lactobacillus acidophilus
[17]. The urogenital infections, including urinary tract infections (UTIs), bacterial vaginosis
(BV) and yeast vaginitis, represent a worldwide problem with over 300 million cases per year
[16]. Recurrent infections, bacterial and yeast resistance, and side effects have been the major
obstacles for the usage of antimicrobial agents in treating the urogenital infections [18], [19].
During urogenital infection, the flora is predominated by the infecting pathogen unlike
healthy conditions where the urogenital flora is predominated by the indigenous organisms.
4
The incidence of BV was found to be decreased by four fold in case of vaginal and rectal
colonization by Lactobilli [20]. The strain of lactobacillus and the route of administration
influence the effectiveness of probiotics. Lactobacillus crispatus is one of the prevalent
strains of Lactobilli in the vagina [20], so it is considered to be an optimal choice as a
probiotic agent rather than other strains such as L. fermentum and L. rhamnosus. Both strains
presented poor results as a probiotic agent in the treatment of urogenital infections [21]. In a
study by G. Reid and colleges, they demonstrated that direct instillation of L. rhamnosus GR-1
and L. fermentum B-54 into the vagina reduce the recurrences of urogenital infections [22]. In
2001, it was firstly reported that probiotics could be administered orally with a dose of more
than 108 viable organisms per day [23]. In another study by G. Reid and colleges, they showed
the first clinical evidence that the administration of Lactobacillus rhamnosus GR-1 and
Lactobacillus fermentum RC-14 strains suspended in skimmed milk could be recovered from
the rectum and finally reach the vagina [24]
1.3.2: Ethnic influences:
It has been reported that differences in ethnic groups have an impact on the urogenital
microbiome. For instance, the vaginal microbiome of four different ethnic groups (white,
asian, black, and hispanic) have revealed higher prevalence of Lactobacillus species in Asian
and white women compared to black and hispanic women. The findings were supported by
the median pH values of black and hispanic ethnic groups who revealed higher values in
comparison to the other two ethnicities [25]. There is no well supported explanation for the
differences seen among the ethnic groups. It might be due to genetic differences between the
hosts or immunological differences or a potential outcome of the vaginal secretions and
composition [25]. The data of this study was highly similar to those of Zouh and colleges
(2010) where they characterized the vaginal microbiome of three different ethnic groups;
Japanese, white and black healthy women [26].
In another study by Zouh and colleges (2007), the phylogenetic analysis and profiles of
Terminal restriction fragment length polymorphism (T-RFLPs) of 16S rRNA genes has
proved the significant differences in vaginal bacterial communities of 144 black and
caucasian women from North America [27]. Black women showed higher incidence of
vaginal bacterial communities not dominated by Lactobilli such as Atopobium species and
Clostridiales order compared to Caucasian women. Caucasian women were significantly
dominated by diverse species of Lactobacillus as L.crispatus, L. jensenii and L. gasseri. The
5
differences in ethnic group from the same geographical origin was found to be highly
correlated in determining what strain of Lactobacillus to be dominant in the vaginal milieu
[28]. L.crispatus was the dominant species in the healthy urogenital microflora in most
populations [29], [30]. Those differences in vaginal microflora between various ethnic groups
may account for their susceptibility to BV and sexually transmitted diseases (STDs) [27].
1.3.3: Immunological influences:
The defect of the host immunological response was found to contribute to the host
susceptibility to urinary tract infections. Pirrka and colleges [31] studied the effect of
immunological abnormalities on the susceptibility of women to recurrent urinary tract
infections (UTIs). In this study, they collected urine, blood and vaginal samples from 22
subjects prone to recurrent UTIs in their disease free period and compared them to control
subjects. They observed the enhanced production of IL-12 by antigen presenting cells (APCs)
which are myeloid dendritic cells and peripheral monocytes. However, this was not translated
into T-cell type-1 activation which is known to be responsible for cell mediated immune
response by defence against uropathogens and antibody production [32]. Those findings were
supported by the improper induction of CDC25, which is the T cell activation marker,
compared to control subjects. This suggests that defective translation of APCs into T cell
activation and differentiation into Th1 memory cells might contribute to increased
susceptibility to recurrent UTI.
1.4. Female urinary system
1.4.1: Anatomy of the female urinary system:
The urinary system consists of two kidneys, two ureters, a bladder and a urethra.
Several reasons account for discussing the anatomy of the male and female urinary systems
separately. First, there are differences in the anatomy and physiology of both systems.
Second, the urethra is a part of the reproductive system of male which differs in function
from the female urethra. Finally, the anus is closer to the urethra in female than in male and
the urethra is also close to the vaginal introitus. Both the anus and the vaginal introitus are
heavily colonised with bacterial flora resulting in differences not only in the number and
types of microbiota but also in susceptibility to infections between male and female urinary
systems [33].
6
1.4.2: Antimicrobial defences of the urinary tract:
The antimicrobial defensive mechanisms of the urinary system play a major role in
preventing the viable bacteria entering the lower urinary tract from colonization and then
ascending to its upper part against urinary flow [34]. The flushing action of urine serves in
preventing colonization of microorganisms in the urethra. Consequently, this creates a high
pressure zone preventing the microbial ascent from the urethra to the upper urinary tract.
Several studies demonstrated that there is a relationship between the urine flow rate and the
number of bacterial population [35], [36, 37] . In a study by O’Grady and Cattell, it was
observed that at the normal physiological state of urine flow rate, the bacterial population
reaches the steady state of growth. However, at slower rate as overnight sleep or in cases of
mild dehydration, there was a considerable increase in the number of the bacterial count [36].
Additional factors like urine pH, urine osmolality and urea concentration act as natural
antibacterial activity. The urine pH of a healthy individuals ranges from 5.0 to 6.0. The
acidity of urine is often inhibitory to bacterial growth but in some instances it can be
bactericidal. However, the urea concentration shows greater influence as a defence
mechanism against bacteria than high osmolality [38], [39]. Decreasing urine osmolality but
preserving urea concentration as in dialysis will not affect the bacteriostatic activity of urine.
However, when decreasing the urea concentration and maintaining the urine osmolality, this
will result in reduction of the antibacterial activity [38]. Moreover, the osmotic shock can be
avoided by some uropathogenic bacteria as in case of E. coli [40].
Shedding of the outermost urothelial cells with their adherent uropathogenic bacteria
is considered to be one of the main antibacterial defence features of the urethra. The
exfoliation rate depends to a great extent on the hormonal status of the female. Several
urethral exfoliating cells are abundant in menstruating females and postmenopausal women
on hormonal replacement therapy. On contrary, pre-menstruating girls and postmenopausal
women not on HRT have fewer exfoliating cells [41]. Another defence mechanism is the
mucous secretions of the paraurethral or Skene’s glands which were described in 1948 in a
study by Huffman and colleges [42]. In another study by Hutch and colleges, they theorized
that the paraurethral glands located at the lower end of the urethra produce mucous forming a
layer at the epithelial lining of the urethra. Therefore, this will restrain bacteria from ascent
into the upper urinary tract [43].
7
Several antimicrobial proteins are released into the epithelial lining of the urethra such
as Tamm-Horsfall protein (THP), lactoferrin, and lipocalin. Tamm-Horsfall protein,
Uromodulin, is a glycoprotein secreted by the kidney and is used in preventing
Enterobacteria from adhering to the epithelia by interfering with their fimbrial structures and
binding to adhesin receptors of Escherichia coli [44]. Lactoferin was found to be abundant at
extremely low levels in urine [45]. Its bactericidal activity mainly depends on iron
sequestration, thus reducing the amount of free iron present in urine and reabsorbing it for
later metabolism [34]. Free iron in urine acts as a fertile soil for Gram negative bacteria since
sufficient concentration of iron is required for their nutritional need [45]. Moreover,
antimicrobial peptides (AMPs), such as defensins and cathelicidin, are constitutively secreted
showing bactericidal activity. In case of bacterial infection, AMPs will be inducibly secreted
provoking the innate immune system through the activity of Toll like receptors, cytokines and
chemokines. These receptors will attract more neutrophils and macrophages to the site of
infection, resulting in phagocytosis of the microbes and release of more antimicrobial
proteins and peptides [34]. However, the role of defensins is still not evident; they may act as
an anti-infective agent as suggested by in-vitro studies [46] or serve other purposes. Strong
evidence supports the role of beta defensins, anti-microbial agents, as demonstrated in a study
by Morrison G. and colleges [47]. Using homologous recombination technology, they deleted
the Defb1 gene, an analogous gene to HBD1 constitutively expressed in the collecting and
distal tubules of the kidney [48], occurred to produce genetically engineered mice Defb1−/−
mutants. The data presented 30% of the healthy mutants had Staphylococcus species in their
urine compared to the wild type mutants.
The urinary secretion of immunoglobulins, e.g., IgA and IgG, is one of the
antimicrobial defence mechanisms of the urinary tract [34]. Several studies have found
correlation between the susceptibility to recurrent UTIs and the secretor status of the
individual [49], [50]. Non secretors are individuals who secrete a little or none of their blood
group antigens into the body fluids [51]. The blood group antigens are carbohydrate
determinants located on the surface of erythrocytes, phagocytes, lymphocytes and urothelim
onto which the microbial lectins attach [51], [52]. The blood group antigens are secreted into
body fluids, thus serving as an attachment site of the fimbrial lectins of uropathogenic
bacteria specifically Escherichia coli. Hence, this protects the individual from colonization
by uropathogenic bacteria. The non secretors were observed to be more prone to recurrent
UTIs when compared to the secretors since the composition of the carbohydrate residue is
8
altered in case of the secretors. In a study by Stapleton and colleges, the reason for increased
adherence of E. coli to the urothelium of non secretors was explained. They radiolabelled an
E. coli strain that had been isolated from a patient with UTI and bonded it to two extended
globoseries GSLs, sialosyl gal-globoside (SGG) and disialosyl gal-globoside (DSGG). The
two globoseries GSLs are selectively expressed on vaginal epithelial tissue in non secretors
but not in secretors. It was concluded that sialylation of glycolipids occur in non secretors,
resulting in higher affinity to the adherence of uropathogenic bacteria. However, the
glycolipids are fucosylated in secretors and processed to blood group antigens [53].
1.4.3: Female urinary system and microbiome:
1.4.3.1: Establishment of microbiota:
Upon delivery, the healthy infant born from a sterile or bacteria free environment is
exposed to a wide diversity of microbes after passage through the birth canal [28], [54]. This
microbial community, some provided by the mother, determines the microbial inhabitants of
the different anatomical sites of the healthy adult individual body. The delivery mode
significantly influences the microbial community received by a newborn from its mother
[55]. It was observed that vaginally delivered babies acquire microbiota dominated by
Lactobacillus, Prevotella, or Sneathia spp., resembling most of their mothers’ vaginal
microbiota. Moreover, C-section babies acquired microbiota dominated by Staphylococcus,
Corynebacterium, and Propionibacterium spp., resembling those of the skin surface [55].
Therefore, the delivery mode affects the differentiation of microbiota in various habitats of
the human body and consequently the disease predisposition.
1.4.3.2: The effect of age and hormonal status on the female microbiome:
The microbiome is influenced to a great extent by age and hormonal status of the
female. Bollgren and colleges [56] observed heavy colonization of the periurethral region of
healthy female infant by aerobic flora (Escherichia coli, enterococci and staphylococci)
during the first weeks of life and this starts to diminish till the age of five. Healthy school
children manifested considerably few Gram negative bacteria in their urine samples
suggesting the maturation of a defensive mechanism against facultative anaerobe such as, E.
coli and other bacteria like Enterococci, start to develop from the individual’s early years.
The relationship between the glycogen content of mucosal cells and the hormonal influences
creates a microenvironment that is more diverse and quite different from that of pre9
menarchal girls [57], [58]. The microbial community of the urethra of pre-menarchal and
reproductive women is highly dominated by facultative anaerobe, whereas in postmenopausal women is roughly dominated by obligate anaerobes. Facultative gram negative
bacilli are more frequent in the urethral microbiome of post-menopausal women, however
absent in pre-menarchal and reproductive women [57], [59]. Contradictions aroused between
studies that discussed the dominance of lactobacillus of post-menopausal women microbiome
[59]. The diversity of microbial communities of the female urogenital flora is a direct
consequence of the hormonal influences and age [56], [59].
1.4.3.3: The key members of the female urogenital tract microbiome:
The microbiotas were detected along the whole length of the female urethra; however
they differ in their proportion densities. The prevalent microbiotas that indigenously colonize
the female urogenital tract are Lactobacillus spp. Firmicutes phylum with Bacteriodetes,
Actinobacteria, Fusobacteria, Proteobacteria and Corynebacterium spp.[60], [59], [54].
1.4.3.4: Identification of Lactobacillus spp. and its role for the female urogenital health:
Lactobacillus spp. was firstly discovered by Albert Doderlein in 1982 [61]. He
observed that the in-vitro and in-vivo growth of pathogens was inhibited by a lactic acid
producing organisms. In 1928 [17], it was identified as Lactobacillus acidophilus by Stanley
Thomas and later in 1980 [62]; it was found that Lactobacillus acidophilus represents a group
of organisms that were highly heterogeneous. The acidic vaginal milieu created by
Lactobacillus spp. due to production of lactic acid, inhibits the growth of infective pathogens
and bacteria predisposing to bacterial vaginosis [63]. Hydrogen peroxide (H2O2) [64],
bacteriocins [65] and probiotics [22], [24] are also produced by Lactobilli which cause further
reduction in acquisition of vaginal infections. From a total of 120 different species of
Lactobacillus, only 20 species of Lactobacillus have been identified in the urogenital
microflora. Only one or two of Lactobilli from the four dominant Lactobacillus species, L.
crispatus, L. iners, L. jensenii and Lactobacillus gasseri, are commonly detected in the
healthy female urogenital microflora [66]. However, other species rarely inhabit the vaginal
microflora and tends to be novel phylotypes [67], [29]. This may correlate with the host or
competitive factors that support the growth of one species over another or pre-emptive
colonization by a particular species [30].
10
1.4.3.5: Other lactic acid producing bacteria and their role for a healthy urogenital tract
A significant proportion, 7-33%, of females reflected healthy urogenital state despite
the absence or the occurrence of low numbers of Lactobacillus spp. Several studies
demonstrated that the production of lactic acid and the maintenance of the vaginal acidity by
other bacteria such as Atopobium vaginae, Megasphaera, and Leptotrichia species were
highly correlated with the inhospitality of the urogenital milieu to infectious pathogens [27],
[67], [30]. In several investigations, urine and vaginal samples were collected from healthy
females with no symptoms of urogenital infections or any other clinical problems. They were
either highly dominated by Lactobacillus spp. or had low numbers of Lactobacillus spp. and
exhibited rich microbial communities composing of Atopobium, Gardnerella, Prevotella,
Dialister and Anaerococcus [54]. Consequently, it was concluded that the prevalence of
particular strains of bacteria such as Gardnerella vaginalis does not represent an abnormal
state. This issue was investigated in several studies in which it was noted that Gardnerella
vaginalis was not detected in 70% of healthy female subjects without BV [68]. Moreover, the
concentrations of Gardnerella vaginalis in healthy subjects with no evidence of infection
were detected to be increased during menstruation and decreased after menses. The opposite
was the levels of Lactobacillus spp. which obviously decrease during menses except for L.
iners [69].
1.5. Male urinary system
1.5.1: Anatomy of the male urinary system:
The anatomy of the male urethra differs from the female urinary system since it
constitutes a part of the male urinary system as well as its reproductive system. Therefore, it
is responsible for excretion of urine and ejaculation of semen. The urethra consists of three
main regions: the prostatic, the penile and the membranous urethra. The male urethra is five
times longer than that of the female. This elucidates the cause of the frequent UTIs by
ascending pathogens in the females compared to the males [33].
1.5.2: Male urinary system and microbiome:
1.5.2.1: Antimicrobial defences of the urinary tract:
The majority of the antimicrobial defense mechanisms in the female urinary system
resemble those of the male, including urinary flow, epithelial desquamation and the release of
antimicrobial peptides and proteins. The high zinc concentration in the prostatic tissue,
11
compared to other human tissue [70] and its secretion into prostatic fluid, represents one of
the main antibacterial defense mechanisms of the male genitourinary tract [71]. Several
compounds, such as lysozyme, lactoferrin [71], phospholipase A2 and secretory leukocyte
protease inhibitor (SLPI), have been identified in the prostatic fluid and were observed to
protect the male genitourinary tract from infectious agents. When lysozyme concentrations in
healthy male individuals were compared to patients with chronic prostatitis, the
concentrations were noticeably higher. Patients that were investigated with an initial
remarkably reduced concentration of lysozyme, experienced recurrences after antibiotic
treatment [72]. SLPI is a proteinase inhibitor secreted by the epithelial lining of the seminal
fluid and also known as human seminal inhibitor I (HUSI-I) or anti-leukoprotease (ALP)
[73]. The first NH2 terminal domain of SLPI showed anti bacterial activity against
Escherichia coli and Staphylococcus aureus in vitro, but lesser activity when compared to
lysozyme and defensins [75]. Phospholipase A2 (GIIA PLA2) shows potent antibacterial
activity against Gram-positive bacteria [76], its concentration in the human seminal plasma is
high, approximately 1000 times compared to the human blood plasma [77]. The positive
charge on PLA2 attacks the peptidoglycan layer of the bacterial cell wall, facilitating
penetration of the phosphobilipid layer [76].
In an immunohistochemical study by Jeffrey Pudney and Deborah J. Anderson [78], it
was demonstrated that the uroepithelial lining of the male penile urethra expresses the
secretory component of the polymeric IgA, IgM and to lesser extent IgG transport molecules.
The immunoglobulins represent the first line of immune defense against bacterial pathogens.
The glands of Littre’ secrete a mucoidal layer containing the secretory IgA abundant in the
epithelium lining the fossa navicularis and meatus. This shows similarity to the mucous
secretions of the cervical gland of the female genital system which is rich in secretory
immunoglobulins and acts as an immune barrier [78], [79]. The seminal fluid contains high
levels of IgG and IgA and low levels of IgM [80].
1.5.2.2: The effect of age and circumcision on the male microbiome:
The relationship between age and the establishment of microbiome in healthy boys is
correspondent to that previously mentioned in healthy girls [57]. Circumcision was found to
be an additional factor that influences the establishment of microbiome and later the pattern
of bacteria causing UTIs during the first years of life. Definite types of uropathogens such as
Klebsiella-enterobacter, Proteus mirabilis, and Pseudomonas aeruginosa was observed to be
12
significantly higher in the urethra of uncircumcised boys. Moreover, there was a higher
colony count for Gram negative uropathogens and E. coli isolated from the urethra of
uncircumcised boys [74], [75]. This supports the idea that there is a direct correlation
between periurethral bacterial colonization and pathogenesis with urinary tract infections.
1.5.2.3: The key members of the male urogenital tract microbiome:
The male urethra is approximately 20 cm in length, where various microbial
communities are expected to exist in differently in various regions. It was found that the last
6 cm of the male urethral orifice is solely colonized by highly complex and variable strains of
bacterial communities. Travelling further into the male urethra, the bacterial concentration
and their complexity becomes less and even undetectable [76]. Several factors result in the
differences in complexity and diversity of microbial strains between various individuals:
sexual activity, age, gender, level of hygiene and circumcision. Several investigations
observed that the indigenous microbiota of sexually active individuals were significantly
more complex than that of non-sexually active individuals [77], [78]. Moreover, several
organisms isolated from the vagina and cervixes of females were abundant in sexually active
males. However, the conditions, specifically the pH, found in the penile urethra differ from
those of the female vagina. Therefore, the isolation of bacterial species, such as Lactobacillus
spp. that predominate the vaginal flora of healthy female, were not increased in sexually
active men [79]. The most detectable microbiotas in the urethral orifice were Staphylococcus,
Streptococcus, Corynebacterium, Pseudomonas and Enterococcus species [76], [80]. The
microbiotas isolated from urine samples of older men might be less representative of the
penile urethra due to the higher incidences of renal and prostatic disorders [84].
Two specific aims will be addressed in this thesis work. First, this work will focus on
the application of cultivation independent approach, 16S rRNA analysis, in order to define
the structure and diversity of the urinary tract microbiomes investigated in four healthy and
culture negative male and female individuals. The results showed diverse bacterial profiles in
both genders. Second, 16S rRNA gene libraries were constructed and 16S rRNA phylogenies
of two different hypervariable regions, V1-V3 and V6-V8, were done. Comparing the results
of the two regions demonstrated wider range of taxonomical classification of V1-V3
sequence dataset. Therefore, this thesis provides comparable taxonomical classification of
bacterial genera diversity between male and female individuals.
13
CHAPTER 2: MATERIALS AND METHODS
2.1 Subjects and sample collection
Mid-stream urine samples, 100 ml, were collected from eight healthy adult volunteers,
4 male and 4 female individuals, in a sterile collection cup. All male subjects were
circumcised. None of the female subjects reported taking vaginal douches, genital wipes
and/or vaginal medications. They were all regularly menstruating (25-35 days menstrual
cycles), at reproductive age and with no history of sexual experience. Urine samples were
collected from female individuals who were not menstruating. All the subjects were provided
with a written informed consent which was approved by the institutional review board (IRB)
of the American university in Cairo (Appendix 1). The subjects’ age range between 18- 40
years old. All enrolled subjects were asked to fill a written medical history form to make sure
of the overall general health (Appendix 2). The urine samples of all subjects have been tested
for any urinary tract infections. Urine was also tested for sexually transmitted pathogens as
Chlamydia trachomatis and Neisseria gonorrhoeae [81]. None of the involved subjects in the
study has reported taking an antibiotic for at least the last three months. All the previously
mentioned tests in addition to the urine culture and sensitivity tests for the infected pathogens
were carried out in El-Borg clinical laboratory. El-Borg is the first medical laboratory in
Egypt accredited by the Swedish Board for Accreditation and Conformity Assessment
(SWEDAC).
2.2 DNA isolation
Urine samples were centrifuged at 4,000 xg for 15 minutes at 4°C. The supernatant
was discarded and the cell pellet was stored at -80°C until DNA isolation [82]. DNA was
extracted from the cell pellet by using QIAmp DNA blood mini kit (QIAGEN, Valencia,
CA), according to the manufacturer’s instructions. Genomic DNA was resuspended in 30 ml
of buffer AE and stored at -20°C until 16S rRNA PCR amplification and sequencing
analyses.
2.3 PCR amplification 16S rRNA gene
All PCR reactions were performed using thermocycler (Applied Biosystems
GeneAmp PCR 9700). The two universal primers used for PCR amplification of 1,300 bp of
the consensus 16S rRNA gene were forward primer 63F (5`-CAGGCC TAA CAC ATG
14
CAA GTC-3`) and reverse primer 1387R (5`-GGG CGG WGT GTA CAA GGC-3`) [15].
The PCR approach was performed in a total volume of 25μL containing 50 ng of the template
DNA (3μL), 100 mM of dNTP, 20 pmol of each primer, 10X DreamTaq reaction buffer and
5U / μL of DreamTaq DNA polymerase (Fermentas, Burlington, CA). The reaction
conditions were initial DNA denaturation at 94°C for 10 min followed by 25 cycles of
denaturation at 94°C for 40 sec, annealing at 56°C for 40 sec and elongation at 72°C for 1
min, and a final extension at 72°C for 7 min. To confirm the presence of amplicon, it was
electrophoresed on 1% agarose gel, stained with ethidium bromide and visualized using short
wavelength ultraviolet light.
2.4 Cloning, 16S rRNA gene library construction, and Sequencing
PCR products were purified using QIAquick PCR Purification Kit (QIAGEN,
Valencia, CA) according to the manufacturer’s instructions. The purified DNA was cloned
into pGEM®-T Easy Vector (Promega, USA) using a vector/insert ratio of 1:3 and performed
according to the manufacturer’s instructions. The ligation mixtures were transformed using
high efficiency competent E.coli TOP 10 cells using Micropulser electroporation device (BioRad, Hercules, CA) according to the manufacturer’s instructions and plated on Luria-Bertani
agar plates containing 100 μg/ml ampicillin followed by incubation overnight at 37°C.
Approximately 100 white colonies were selected from each library and inoculated into 96well microtitre plate containing 150 μL of Luria-Bertani broth supplemented with 100 μg/ml
ampicillin followed by incubation overnight at 37°C. 15% glycerol stock was prepared for
further use and stored at -80°C. Colony PCR was performed to confirm the 1.3 kb insert size.
Bacterial cultures were reinoculated into 96-well block containing 1300μL of Luria-Bertani
broth (supplemented with 100 μg/ml ampicillin) followed by incubation overnight at 37°C
with shaking. Plasmid DNAs were isolated using R.E.A.L. Prep 96 Plasmid Kit (QIAGEN,
Valencia, CA) and stored at -20°C. The isolated plasmids with their cloned inserts were
sequenced from both ends with universal primers equivalent to the plasmid vector sequences
M13F 5’- TGTAAAACGACGGCCAGT- 3’ and M13R 5’- CAGGAAACAGCTATGACC3’. Cycle sequencing was performed using Applied Biosystems Big Dye terminator chemistry
and the sequences were resolved on the 96-capillary Applied Biosystems 3730XL DNA
Analyzer.
15
2.5 Male and Female 16S rRNA urine sequence analyses
2.5.1: Alpha diversity analysis:
Mothur v.1.18.1 pipeline’s alpha diversity analyses package [83] was used for
estimating the richness, evenness and overall diversity of the bacterial communities of male
and female urinary tract. Plotting rarefaction curves and calculating the three non-parametric
estimators of alpha diversity (Chao1, Shannon and Simpson indices) were executed to
measure the overall coverage of the tested urine samples.
2.5.2: Phylogenetic analysis of 16S rRNA urine sequences:
Sequences were processed by trimming the plasmid vector bases with cross match and
discarding low quality sequences < 300 bp in length and/or had average PHRED quality
score of Q= < 20 using “Codoncode Aligner” (Codoncode Corporation, Dedham, MA). The
3’ and 5’ reads could not be assembled and therefore the phylogenetic approach was based
upon separate analysis for the 3’ and 5’ reads of both male and female samples. BLASTN of
the 16S rRNA sequences generated from libraries of both male and female urine samples
were conducted against RDP II database [83]. The database is already installed in our local
server maintaining the sequences with the best two blast hits and E-value threshold 10-5. On
each of the four sequence sets “5’males, 5’ females, 3’ males, 3’ females” chimera detection
was performed, that can arise during PCR.
The infernal 1.0 software [84] was used to create a single multiple sequence
alignments (MSA) of all 16S rRNA sequences of the male and female urine samples. It is a
fast sensitive tool that builds a consensus RNA secondary structure profiles called covariance
models where MSA of each final set together with reference reads already identified in
previous blastn search on RDP database was done. Therefore, two alignments were created;
the 3’ sequence alignment (including reads ending with the reverse complement of the 1387R
primer sequence) and the 5’ sequence alignment (including reads ending with the 63F primer
sequence). For purposes of phylogenetic deduction, further refinement to remove uncertainty
in MSA was accomplished using ZORRO masking program [85] which assigns confidence
scores to each alignment column ranging from 0-1, where 1 represents the most reliable
match and 0 represents the ambiguous match. This program was applied in order to minimize
errors resulting from manual trimming of MSA columns for the removal of poorly aligned
columns and highly divergent alignments. For taxonomy assignments, a maximum likelihood
16
phylogenetic tree of the refined alignment was generated using phyML [86]. Several
taxonomic assignments that have bootstrap values of < 70% at the species level were not
considered and removed as most investigators agree that the phylogenetic clade is strongly
supported at bootstrap value of > 70% [87].
17
CHAPTER 3: RESULTS
3.1 Processing of the urine samples, PCR amplification, library
construction, and sequencing of the 16S rRNA gene
Multiple reports have investigated that either urine or urethral swabs can be used
similarly in the detection of urethral microbiomes of males [81]. In this study, urine samples
were used as a representative for sampling in males since urethral swabs cause discomfort
particularly in case of multiple sampling.
After sample collection and DNA extraction, agarose gel electrophoreses of extracted
DNAs show high molecular weight with good quality, figures (2 and 3). Using universal
primers, 63F and 1387R, the entire 16S rRNA gene was amplified. Figures 4 and 5 showed
that the amplified DNA fragments for the four males and females have the expected size of
around 1,300 bp. Amplified DNAs were ligated into pGEM®-T Easy Vector (Promega,
USA) and used to transform competent E. coli cells. For each individual transformant sample,
library of 96 random individual colonies was grown in 96-well plates. Recombinant plasmids
from each of the eight plates-representing four males and four females-were sequenced from
both ends of the inserts (here called 3’ and 5’ ends) using the Sanger chain termination
approach and analyzed on ABI 3730XL DNA analyzer. Tables (1 and 2) show a summary of
the sequenced samples. The average length of sequenced DNA was 478 bp with at least 20 of
PHRED quality score. The number of reads for each individual (forward plus reverse) varied
from a minimum of 76 (male 3) to a maximum 157 (female 3). It is important to note that our
inserts have size of around 1300 bp, and the maximum read length obtained from the 5’ and
the 3’ of the inserts did not permit overlapping of the sequences from both ends of the
recombinant plasmids as shown in Table 3. Therefore, the phylogenetic analysis was based
upon separate analysis for the 3’ and 5’ reads of both male and female samples. Table (3)
summarizes the number of sequenced clones for each library, length of sequence obtained
from each end and quality of reads.
3.2 Computational and statistical analysis
To identify microbial communities that coexist in the urinary tract of male and female
individuals, the 16S rRNA sequences were classified using the RDP II database [88] keeping
18
the E-value cutoff 10-5. For taxonomy assignments, the phylogenetic tree was constructed at
bootstrap values of > 70% at the species level.
3.2.1: Phylogenetic analysis of the female 16S rRNA sequences
The core microbiome of the female urinary tract was better characterized by sorting
the 16S rRNA sequences at the genus level. The phylogenetic analysis of the two different
regions of the 16S rRNA amplicon revealed diverse bacterial genera (Figure 6 and 7). Out of
a total of 15 bacterial genera identified in all female urine specimens, 4 different genera were
detected in both 3’ and 5’ reads. The 3’ reads of V6-V8 regions of the urine 16S rRNA
sequences were approximately 50% dominated by bacterial phylotypes that were
phylogenetically related to Prevotella, Corynebacterium, Gardnerella and Weeksella spp.
The 16S rRNA sequences belonging to Lactobacillus, Unclassified Flavobacteriaceae family,
Sneathia, Atopobium and Oligella spp were less abundant while the remaining genera
represent approximately less than 1%. Likewise, The 5’ reads of V1-V3 regions of the urine
16S rRNA sequences were approximately 50% consisting of the same bacterial phylotypes
that were previously identified in the V6-V8 regions. Facklamia spp. was the only bacterial
genus being identified in the V1-V3 reads but not in the V6-V8 reads. Most reads for the
female subject1 detected bacterial phylotypes belonging to Gardnerella and uncultured taxa.
Coincidence was revealed in case of Atopobium vaginae and Megasphaera spp, each one
being present only when the other one being found.
At the order level, the results of phylogenetic analysis data of the female urine 16S
rRNA sequences identified 9 different orders in both sequence datasets, V1-V3 and V6-V8.
The most abundant orders of the 16S rRNA sequences were Actinomycetales,
Bifidobacteriales, Flavobacteriales and Bacteriodales. Actinomycetales and Flavobacteriales
were present in 3 / 4 urine samples. In contrast, Bifidobacteriales was only detected in 1 / 4
urine samples however it accounted for significant proportion of sequences. All bacterial
genera and orders being identified in the female urine flora are summarized in Table 1.
Actinomycetales comprised approximately 40 sequences and contains 3 genera,
mainly represented by the genus Corynebacterium and to a lesser extent, the genera
Arthrobacter (A. albus and A. cumminsii) and Zimmermannella (Pseudoclavibacter timone
and uncultured taxa). Corynebacterium spp contain diverse species (C. coyleae, C.
19
tuscaniense, C. riegelii and uncultured taxa) and has been identified as a member of the
superficial skin flora [89]. Flavobacteriales comprised approximately 40% of sequences and
it contains 3 genera, (Planobacterium, Weeksella and uncultured taxa), represented at various
relative abundances. Unclassified Flavobacteriaceae family was represented by a single
clade containing high numbers of clones assigned to uncultured bacteria (at > 90% 16S rRNA
sequences similarity). Closest RDP matches of all Weeksella sequences, represented as one of
the dominant genera of the female urinary microbiome, were assigned to W. virosa spp.
Numerous clones from female subjects 2 and 4 of the V1-V3 reads were taxonomically
related (at different percent similarity, mostly greater than 70%) to 16S rRNA sequences of
Weeksella virosa. While numerous clones representing the female subjects 1 and 3 showed
100% similarity to the 16S rRNA sequences of V6-V8 reads of Weeksella virosa. Closest
RDP matches of all Bacteriodales and Bifidobacteriodales sequences were assigned to the
genera Prevotella and Gardnerella respectively. The genus Prevotella contains diverse
species (P. disiens, P. buccalis, P. timonensis, P. amnii and mainly uncultured taxa) while the
genus Gardnerella was mostly assigned as G.vaginalis and both comprised approximately
half of the female urinary 16S rRNA sequences. Lactobacillus and Facklamia spp. (only
detected in female urine 16S rRNA sequences of V6-V8 reads) were the main representative
genera of the order Lactobacillales.
Other bacterial orders: In addition to bacterial phylotypes that were previously
discussed, 4 orders representing 6 bacterial genera were abundant at low proportions. The
bacterial genera represent approximately less than 1% of the female urine microbiome. For
instance, the Coriobacteriales (genus Atopobium), the Selenomondales (including the
following genera Megasphera and Dialister spp.) and the Fusobacteriales (genus Sneathia)
were known to be directly correlated with the female urogenital flora [25], [54], [30]. It
should be noted that those bacterial genera were entirely abundant in female subject 3. The
abundance of diverse bacterial communities in female subject 3 might be attributed to the
high number of clones recovered allowing examination of additional bacterial phylotypes in
the female urine flora. The most dominant bacterial phylotype of the Burkholderiales order,
the genus Oligella (mostly assigned to O. urethralis), coexists in female urine subjects 2 and
4. Oligella urethralis was previously classified as Moraxella urethralis [90] which is a small
aerobic and Gram negative bacterium usually isolated from human urine.
20
At the phylum level, a total of 5 phyla have been identified. The most frequently
detected sequences corresponding to 4 bacterial phyla were Firmicutes, Actinobacteria,
Fusobacteria and Bacteroidetes while Proteobacteria phylum was less frequently observed.
3.2.2: Phylogenetic analysis of the male 16S rRNA sequences
The 16S rRNA sequences of the male urine samples were similarly sorted at the genus
level to characterize the core microbiome of the male urinary tract. Likewise, the
phylogenetic analysis of the two different regions of the 16S rRNA amplicons revealed
various bacterial genera (Figure 8 and 9). Out of 39 bacterial genera being identified in all
male urine samples, 19 different genera were solely detected in both reads. The 3’ reads of
V6-V8 regions of the urine 16S rRNA sequences were approximately 50% dominated by
bacterial phylotypes that were phylogenetically related to Prevotella, Escherichia/Shigella,
lactobacillus and Corynebacterium. 16S rRNA sequences belonging to Bacteroides,
Fecalibacterium,
Acinetobacter,
Anaerococcus,
unclassified
Lachnospiraceae
and
Flavobacteriaceae families were less abundant while the other genera represents considerable
low proportions of the whole bacterial community. The 5’ reads of V1-V3 regions of the
urine 16S rRNA sequences were approximately 50% consisting of the same bacterial
phylotypes that were previously identified in the V6-V8 regions. Other microbial
communities were only observed in the V1-V3 reads; Peptoniphilus, Ruminococcus,
Coprococcus, Sphingomonas, Alistipes, Empedobacter, Sphingomonas, pseudoxanthomonas,
Kocuria and Cupriavidus spp. However, Arthrobacter, Negativicoccus, Salmonella,
Weeksella and Veilonella spp were only identified in the V6-V8 reads. Unlike the 16S rRNA
sequences of the female urine specimens, uniqueness of a single bacterial genus to a specific
male subject was not observed. Distinct differences between kinds of bacterial communities
of the urinary tract of the female and male individuals were significantly observed as shown
in Figures 10 and 11.
At the order level, the two sequence datasets revealed a total of different 17 orders
being identified. The most abundant orders of the 16S rRNA sequences were
Actinomycetales, Lactobacillales, Enterobacteriales, Bacteriodales and Clostridiales.
Sphingomonadales, xanthomonadales and Burkholderiales were only identified in the V6-V8
reads while virtually no order was specifically identified in the V6-V8 reads. All bacterial
genera and orders being identified in the male urine flora were summarized in Table 2.
21
Actinomycetales comprised approximately 50 sequences and contains 3 genera,
mainly represented by the genus Corynebacterium and to a lesser extent, the genera
Arthrobacter (A. albus and A. cumminsii) and Kocuria. Corynebacterium spp contains
diverse species (C. riegelii and mostly uncultured taxa). Flavobacteriales comprised nearly
25 sequences and contains 3 genera, (Flavobacterium and the genus Weeksella that was
recovered from the 16S rRNA sequences of V6-V8 reads of male subjects 3 and 4). The
Flavobacteriales order was represented at various relative abundance rates. Unclassified
Flavobacteriaceae family was represented by a single clade containing high numbers of
clones mainly assigned to uncultured bacteria (at > 90% 16S rRNA sequences similarity).
Similarly, the closest RDP matches of all Weeksella sequences were assigned to W. virosa
spp. Unlike the female urine 16S rRNA sequence similarity, the Bacteriodales order is
represented by 5 different genera, Prevotella, Bacteroides, Porphyromonas, and the genera
Alistipes and Barnesiella that were detected only in V1-V3 reads, constituting approximately
25% of 16S rRNA sequences of the phylogenetic tree. The genus Prevotella contains diverse
species (P.melaninogenica which was recently classified as Bacteroides melaninogenicus
[91], B. buccalis and mostly uncultured taxa). Bacteroides spp. is a host member of the
vaginal and the gastrointestinal tract flora [92]. Enterobacteriales contains 3 genera, mainly
represented by the genus Escherichia/Shigella. However the remaining genera (Enterobacter
aerogenes and Salmonella) accounted for a considerable small proportion of the
Enterobacteriales order where they have been identified as members of the gastrointestinal
flora. The genus Escherichia/Shigella accounted for significant proportions of male urine
sample 1 indicating a possible urinary tract infection. The Clostridiales order comprises
nearly 30 sequences of 16S rRNA sequences of V1-V3 dataset and contains more diverse
bacterial phylotypes than those of V6-V8 sequence dataset. Unclassified Lachnospiraceae
family was represented by several clades containing high numbers of clones assigned to
uncultured bacteria (at > 97% 16S rRNA sequences similarity). Closest RDP matches of all
Caulobacteriales and Pseudomonadales sequences were assigned to the genera Acinetobacter
and Brevundimonas respectively. High number of clones of V1-V3 and V6-V8 datasets were
assigned to Acinetobacter spp which is an environmentally widespread aerobic Gramnegative bacterium predominately found in moist regions of the skin [33].
In addition to the previously mentioned bacterial phylotypes, other 9 orders
representing 12 bacterial genera were represented by approximately less than 1% of the
female urine microbiome. For instance, bacterial communities of the Selenomondales order
22
(including the following genera Phascolarctobacterium, Veillonella and Negativicoccus
succinicivorans spp.) have been identified before as indigenous members of the microbiota of
the human gut [93], female urogenital tract [60], [30] and the skin [94]. Closest RDP matches
of all Bacillales sequences were assigned to the genus Streptococcus (mainly represented by
the species of S. agalactiae).
At the phylum level, a total of 5 phyla have been identified. The most frequently
detected sequences corresponding to 4 bacterial phyla were Firmicutes, Actinobacteria,
Proteobacteria and Bacteroidetes while Fusobacteria phylum was less frequently observed.
3.2.3: Estimating the richness and diversity of urine microbial communities
using alpha diversity
Mothur v.1.18.1 pipeline’s alpha diversity analyses package [83] was performed for
estimating the richness, evenness and overall diversity of microbial communities for all urine
host samples under study. Rarefaction curves, Chao1, Shannon and Simpson indices
estimations were measured to determine the different depths of sampling and the overall
richness and diversity of the host communities. Rarefaction curves have been plotted for both
the 3’ and 5’ reads of the male and female samples at a 1% genetic difference level. The
number of OTUs range from 2 to 31 and 12 to 53 OTUs of 3’ and 5’ sequence reads
respectively. The results of rarefaction curves are shown in Figures 12 and 13.
Chao1 is one of the three non parametric estimators extrapolated from data to explore
the true species richness by using an equation to identify the undiscovered species in the
sample. Additionally, Simpson and Shannon indices were calculated to estimate the richness
of the sample by measuring the species diversity and the relative abundance of each species
taking into account the whole community (evenness). Both Shannon and Simpson indices
showed high species diversity in all samples. The least diverse sample was observed only in
the female subject1 as it was the only specimen that reached asymptote phase and its
Shannon and Simpson estimations showed complete evenness. Interestingly, the 5’ reads
were more diverse when compared to the 3’ reads. However, both require sufficient coverage
and the communities need more sampling in order to reach completion. The overall results of
the three non parametric estimators are listed in Tables 4 and 5.
23
3.3 Inter-individual variation
The female and male urine samples revealed remarkable differences in the
distribution of various taxa at the genus level as shown in figures 14 and 15. Species of
Gardnerella and Prevotella were the dominant bacterial population recovered from different
3/4 female urine specimens. In case of the male urine 16S rRNA sequences, species of
Prevotella, Corynebcaterium and Escherichia/Shigella were the dominant bacterial
population recovered from all male urine specimens. Although Lactobacillus spp. represents
one of the most abundant bacterial genera, its reads have been identified in only 2/4 of the
urine samples of both sequences reads. However, the bacterial species composition and
evenness varied between different subjects. Species of Megasphaera, Dialister and Sneathia
were detected once in subject 3, Arthrobacter and Facklamia spp. in female subject 4, and
Zimmermannella spp. in female subject 2. Female subject 3 show the highest diversity and
species richness in the 16S rRNA sequence dataset of the V6-V8 reads. In contrast, female
subjects 1, 2 and 4 have nearly the same species diversity and evenness.
When examining V6-V8 reads of the 16S rRNA sequences of the male urine
microbiome, reads assigned to Arthrobacter, Phascolarctobacterium, Negativicoccus and
Succinivibrio spp. were detected once in sample 4. Species of Roseburia and Oscillibacter
spp., Sneathia and Flavobacterium spp. were identified once in samples 1 and 3 respectively.
When examining V6-V8 reads of the 16S rRNA sequences of the male urine microbiome,
reads assigned to Sphingomonas, Pseudoxanthomonas, Cupriavidus, Barnesiella and kocuria
were observed once in urine subject 4. Species of Alistipes, Ruminococcus and Coprococcus
were detected once in sample 1, and Brevundimonas spp in male subject2.
When examining the 16S rRNA sequences of both the V1-V3 and V6-V8 reads, the
results uncovered noteworthy differences in distribution of bacterial phyla in all urine
specimens. Actinobacteria was present in all female urine samples. Fusobacteria and
Bacteroidetes were observed in 3/4 urine samples. Firmicutes and Proteobacteria were
detected in only two samples 3, 4 and 2, 4 respectively. Additionally, Fusobacteria was the
only bacterial phylum that was detected once in male urine subject 3 while the remaining
phyla were present in all male urine samples. This reveals that the inter-individual variation
was even noticeable at the phylum level.
24
CHAPTER 4: DISCUSSION
In this work, mid-stream urine samples were collected from 8 healthy volunteers
(n=8), 4 healthy male and female individuals, into sterile containers. Then, PCR
amplification was performed using forward and reverse 16S universal primers yielding
amplicons with the expected length of 1300 bp. Following library construction, M13 vector
primers were used for Sanger sequencing of ends of the inserts. As previously mentioned in
the results, the 16S rRNA gene was not fully sequenced. Thus, two different hypervariable
regions, V1-V3 (represents the 5’ end) and V6-V8 (represent the 3’ end), of 16S rRNA
sequences were sequenced because they were more suitable to distinguish between various
bacteria at the genus level when compared to V4 and V5. Both V4 and V5 manifested more
sequence conservation, therefore they were not suitable targets for species identification [14].
V1-V3 reads were noticeably more appropriate for enduringness of taxonomical classification
while V6-V8 reads were more appropriate for studying the microbial diversity [95], [96]. At
the phylum and the order level, similar bacterial groups were observed in V1-V3 and V6-V8
reads respectively. While considerable differences were detected at the genus and the species
level.
The first glimpse on the results of the 16S rRNA sequences obtained from both
human female and male urine samples showed that the female urine microbiome consists of
major five bacterial phyla; Firmicutes, Actinobacteria, Fusobacteria, Bacteroidetes and
Proteobacteria. The results of the female 16S rRNA urine sequences were comparable with
previously identified 16S rRNA sequences of former studies describing the female urogenital
microbiota [25], [54], [30]. Prevotella, Corynebacterium, Gardnerella and Weeksella spp.
represents the most dominant bacterial genera. Weeksella virosa was first isolated from the
human urine by Tatum and colleges (1974) [97] and was detected as dominant genus of the
female genital tract by Holmes and colleges (1986) [98] with no clear pathogenicity. While
Prevotella, Escherichia/Shigella, lactobacillus and Corynebacterium represent the most
dominant bacterial genera of the male urine microbiome. Similar results on the male urine
microbiome were previously observed in studies conducted by Nelson and colleges (2010),
(2012) [79], [99] and Dong and colleges (2011) [81]. Although Gardnerella spp. has been
assigned as one of the dominant genera of the female urogenital microbiota, the three studies
on the male urine did not display similar results. However, there is no characteristic
25
identification of the types of microbial communities of either male or female urine core
microbiota of all individuals.
Multiple bacterial species such as, A. vaginae, Megasphaera and Sneathia spp. were
identified using culture independent methods, 16S rRNA sequencing of gene libraries, which
was inapplicable using cultivation methods since they are slow growing, strict anaerobes and
difficult to grow on selective media. Specific media as MRS and Rogosa media were applied
to support the growth of Lactobacillus but not of L.iners [100]. The identification of
uncultured bacterial species as members of the healthy female urine microbiome further
assesses the limitations of cultivation dependent methods.
Lactobacillus spp. is the dominant bacteria of the female urogenital tract [54], [30],
[25] which was similarly observed here but to a lesser extent. The majority of the clones of
Lactobacillus recovered from the 16S female urine sequences were phylogenetically related
to the following species, L.crispatus and L.iners. They represent two of the four most
commonly found species in the human female vagina. The results of phylogenetic analyses
were quite similar to the 16S rRNA phylogeny results discussed in several studies [54], [27],
[25]. In 3/4 of the female urine samples, Lactobacillus spp. coexisted either at significantly
low abundance rates or even undetectable. In both cases, it was noted that other lactic acid
producing bacteria such as Atopobium vaginae, Megasphaera, and Leptotrichia spp.
compensate for the low proportions of lactobacillus spp. They are well known for their
ability to conserve the low pH and lactic acid production for a healthy vagina. Accordingly,
the coexistence of bacterial species as Prevotella disiens and Gardnerella vaginalis as
potential members of the female core microbiome does not represent an abnormal state as in
case of bacterial vaginosis [21], [60]. Bacterial vaginosis [18] is defined as: a medical
condition in which a considerable decrease in the number of lactic acid producing bacteria
specifically Lactobacillus spp. and a concomitant increase in other facultative or anaerobic
bacteria is observed resulting in a change in the composition of vaginal flora. It is noteworthy
that the growth of G. vaginalis is positively influenced by the abundance of Prevotella spp.
Prevotella spp. provides Gardnerella spp. with the key nutrients of amino acids and ammonia
[25]. Prevotella disiens is well known for its key role in predisposition to female genital tract
infections [60]. Corynebacterium riegelii was discovered as a novel species in female
patients with UTIs [101]. Gardnerella vaginalis strains are one of the pathogenetic factors of
BV [102].
26
The bacterial microbiota found in healthy men are quite similar in both urethral
swabs and urine specimens [81]. Thus, both samples can be applied for taxonomical and
phylogenetic analysis of the male core microbiome. Interestingly, the phylogenetic results
were strongly correlated with studies [99], [81] that previously discussed the abundance of
vaginal flora of healthy women and BV associated taxa in the urine specimens of healthy
men. Lactobacillus, Prevotella, Gardnerella, Veillonella (detected in V6-V8 reads) and
Sneathia spp. (detected in V1-V3 reads) were abundant in male urine sample 3 who
previously reported sexual experience. Therefore, vaginal sexual exposure may result in
broader exchange of urogenital microbiota. The Lactobacillales, genus Lactobacillus,
coexists in 2/4 of the male individuals primarily in urine sample 3. Lactobacillus contains
diverse species (L. crispatus and mostly represented as L. iners and uncultured taxa) and
comprised approximately 20 sequences. A study by Rachel R. and Cindy A. proposed that
the vaginal Lactobacillus plays a key role in reducing the incidence of sexually transmitted
infections (STIs) following exposure to STI pathogens [103]. A study by Nelson and colleges
[99] reported the abundance of bacterial genera, isolated from the vaginal flora, in urine and
coronal sulcus specimens of participants with no history of sexual experience except for
Sneathia spp. Based on the study observations, the similarity of both male and female genital
tracts micobiome supports the assumption that a few microbial communities could survive
during sexual transfer.
Multiple bacterial genera were previously identified as water- borne bacteria
suggesting that they could be a tap water contaminant or a potential member of the bacterial
community of the female and male urinary tract. For instance, the genus Planobacterium
[104] which was observed in the 16S rRNA sequence phylogeny of female subject 3 and the
genera Sphingomonas, Cupriavidus and Pseudoxanthomonas spp. which were observed in the
16S rRNA sequence phylogeny of male urine sample 4 (with > 97% sequence similarity).
Likewise, the former observation was in concordance with the results of a study by
Riemersma and colleges [80].
It is noteworthy that several abundant taxa detected in urine samples were previously
classified as residents of the human gut microbiome [105] as Ruminococcus,
Faecalibacterium,
Coprococcus,
Roseburia,
Clostridiale
and
Oscillibacter
while
Peptoniphilus spp. as a member of indigenous microbiota of the skin respectively [33].
Barnesiella spp. was also known to inhabit the human distal gut flora [106]. Furthermore, it
27
has been detected in the conjunctival microbiota of neonates delivered vaginally [33].
Alistipes spp. has been detected in few studies done on paediatric patients suffering from
irritable bowel syndrome [107]; however it has not been identified as a genuine member of
the male urine microbiota. Here, it was observed as a potential member of the male urine
flora. Most of the taxonomically assigned bacterial phylotypes of the Clostridiales order have
been identified in the vaginal flora of healthy women. They are well known for their clinical
diagnosis of BV as they metabolize carbohydrates and amino acids producing stinking
compounds such as thiols, amines and organic acids [108]. The stinking odour is one of the
main diagnostic features of BV. They include strict anaerobes such as: Anaerococcus,
Peptoniphilus and unclassified Lachnospiraceae family that was recovered using cultivation
independent methods. They represent considerable proportion of the indigenous microbiota
of the male urogenital tract. Therefore, more efforts should be done to better characterize the
roles of these microbial communities in the urinary flora.
Similarly, several abundant taxa detected in urine samples were previously classified
as residents of the human skin microbiome. In a study by Helene Marchandin and colleges
(2010), the anaerobic and Gram negative coccus, Negativicoccus succinicivorans, was firstly
identified in clinical isolates from the human skin and soft tissues as a novel genus using 16S
rRNA phylogeny with 99.9% identity. Several microbiotas were solely detected in urine like
the species of Lactobacillus, Veillonella and Gardnerella which were similar to bacterial
species detected in the mucosal surfaces [99].
In order to assess the diversity of 16S rRNA sequences of bacterial phylotypes that
indigenously coexist in the urinary tract of both male and female individuals, alpha diversity
analyses were performed using mothur pipeline. Based on a 0.01 phylogenetic distance,
rarefaction curves were plotted for both V1-V3 and V6-V8 sequence datasets. Expectedly,
neither 5’ nor 3’ reads showed good coverage as both did not reach the plateau phase
indicating that more sequences needed to be sequenced in order to reach the predicted
maximum richness. Those findings may be attributed to the fact that the numbers of analyzed
clones are small. Interestingly, the female subject 1 solely reached the plateau phase in V6V8 reads. Unlikewise, the coverage of the same urine sample of its V1-V3 reads was
incomplete and thus, more phylotypes remain to be identified. In addition, Chao1, Simpson
and Shannon alpha diversity indices estimations were performed. Chao1 is a non-parametric
estimate that measures the total number of phylotypes that are expected to exist and might not
28
be detected in each sample. For both sequence reads of male and female urine samples,
Chao1 values were significantly exceeding the actual number of phylotypes present in each
sample. Simpson and Shannon indices measure the species diversity which reflects the
species richness and evenness. However, the sensitivity of Simpson index towards species
evenness is higher than its richness while the sensitivity of Shannon index towards species
richness is in turn higher than its evenness [109]. Simpson index values range from 0 (low
diversity) to 1 (high diversity) while Shannon index values range from 1 (low diversity) to 5
(high diversity).
Based on the previous observations, our data implies a phylogenetic view of the
urinary microbial communities in male and female individuals. First, our findings support
that the bacterial communities of the urinary tract are complex and polymicrobial. Interindividual variation was observed in all analyzed samples confirming that no single
characteristic bacterial community was evident. Those results coincide with previous studies
on male and female urogenital flora [79], [60]. Diverse bacterial genera identified in the
urinary tract were highly similar to microbial communities that were formerly reported in
superficial skin [105], [94], gut [33], [93], and vaginal microbiome [54], [26], [21]. In
addition, the interpretations of phylogenetic analysis results of male 16S rRNA urine
sequences suggest that there are evident differences in the composition of microbial
communities of urine and penile coronal sulcus (CS). Coronal sulcus specimens are
dominated by 16S rRNA sequences assigned to the family Pseudomonadaceae spp. [110]
which was apparently rare in urine. Obligate and/or facultative anaerobes such as
Streptococcus, Lactobacillus, Gardnerella and Veillonella were commonly detected in 16S
urine sequences whereas they were rare in CS sequences [99]. Second, several BV associated
taxa such as Prevotella, Gardnerella, A.vaginae and Sneathia spp. are suggested to be
genuine members of both healthy male and female urinary microbiome. Some of them are
lactic acid producing bacteria that compensate for the undetectable abundance of
Lactobacillus spp. in female urine samples. Thus, additional future studies should be
performed in order to clear out this issue as numerous cases of healthy women having normal
urogenital microbiome could be misdiagnosed with BV. Finally, considerable differences
between male and female urine microbiome were detected. Common bacterial taxa exist in
high proportions in urine sequences of both genders as Prevotella, Corynebacterium,
Weeksella and Lactobacillus. Few bacteria as Gardnerella spp., predominantly found in urine
samples of female individuals, was apparently identified as minor representatives of male
29
urine samples. 16S rRNA sequences assigned to bacterial genera of Streptococcus,
Staphylococcus, Escherichia/Shigella, Acinetobacter and others were abundant in male urine
samples whereas sequences assigned to these genera were not detected in urines of female
subjects. This was similarly observed in phylogenetic analysis of female urine sequences
such as 16S sequences assigned to O. urethralis, A. vaginae, Dialister and other bacterial
flora not identified in urines of male subjects.
It is noteworthy to mention the pitfalls of this thesis work which needs further
investigation. First, the overall results of alpha diversity agree on implying that both male and
female urine samples are highly diverse and more coverage is required to give better insight
into the urine microbiome. This might be attributed to the small number of clones analyzed in
each individual urine sample which was reflected on the results of the three non-parametric
estimators of alpha diversity analysis. Therefore, repeated sampling of each individual will be
necessary to validate the confidence of our results. Second, primer walking is required to
ensure complete coverage of the whole 16S rRNA gene. This will broaden our perception on
the diversity of the male and female urine microbiota and adds further level of complexity for
data analysis at the bacterial species level. Finally, the inadequate number of male and female
individuals under study needs further investigation in the future.
In conclusion, enhanced resolution obtained by 16S rRNA Sanger sequencing
manifests the advantages of cultivation independent methods over independent ones in
exploring the indigenous microbiome of urinary tract of healthy adult individuals. The study
of phylogenetic profiles of 16S rRNA sequences of urine phylotypes shed the light on the
occurrence of wide range of bacteria including many associated with disease causing bacteria
as a part of the healthy male and female urine microbiome. Thus, additional future studies
should uncover the relationship between the human urinary tract microbiota and their impact
on human health upon study of various disease states particularly those resistant to traditional
treatment methods.
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Figures
Figure 1 Distributions of different bacterial phyla
This figure illustrates the relative abundances of different bacterial phyla at
various anatomical sites of the human body including the skin, gut, male and female
urogenital tracts. This figure is modified from (Dethlefsen et al.2007) [110].
41
Figure 2 Gel electrophoresis of total genomics DNA from four male urine
samples
DNAs extracted from microbial community collected from urine of four healthy adult
male individuals were examined on 1% gel electrophoresis. MW: 1kb DNA marker ladder
(Invitrogen, Carlsbad, CA).
42
Figure 3 Gel electrophoresis of total genomics DNA from four female urine
samples
DNAs extracted from microbial community collected from urine of four healthy adult
female individuals were examined on 1% gel electrophoresis. MW: 1kb DNA marker ladder
(Invitrogen, Carlsbad, CA).
43
Figure 4 Gel electrophoresis of PCR amplification products of 16S rRNA
gene from four male urine samples
DNA isolated from four urine males shown in Figure 2 were used to amplifiy the 16S
rRNA gene. The PCR reactions were performed using the universal primers 63F and 1387
(details in Material and Methods). The products of the amplifications were analyzed on 1%
gel electrophorasis. MW: 1kb DNA marker ladder (Invitrogen, Carlsbad, CA). A purified E.
coli genomic DNA was used as PCR positive (+ ve) control and no added genomic DNA as
PCR negative (-ve) control. All 16S rRNA amplicons had the expected length of 1.3 kb.
44
Figure 5 Gel electrophoresis of PCR amplification products of 16S rRNA
gene from four male urine samples
DNA isolated from four urine females shown in Figure 2 were used to amplifiy the
16S rRNA gene. The PCR reactions were performed using the universal primers 63F and
1387 (details in Material and Methods). The products of the amplifications were analyzed on
1% gel electrophorasis. MW: 1kb DNA marker ladder (Invitrogen, Carlsbad, CA). A purified
E. coli genomic DNA was used as PCR positive (+ ve) control and no added genomic DNA as
PCR negative (-ve) control. All 16S rRNA amplicons had the expected length of 1.3 kb.
45
Figure 6 A phylogenetic tree showing the relationship between various
phylotypes based on analysis of 16S rRNA female urine sequences of V6-V8
dataset
The phylogenetic tree was constructed using a maximum - likelihood algorithm based
on analysis of 16S rRNA gene sequences of V6-V8 dataset recovered from urine samples of
four healthy female subjects. It also demonstrates the relationship between various bacterial
phylotypes that were evolutionary compared to closely related organisms retrieved from RDP
II database. For taxonomy assignments, the phylogenetic tree was constructed at bootstrap
values of > 70% at the species level.
46
Figure 7 A phylogenetic tree showing the relationship between various
phylotypes based on analysis of 16S rRNA female urine sequences of V1-V3
dataset
The phylogenetic tree was constructed using a maximum -likelihood algorithm based
on analysis of 16S rRNA gene sequences of V1-V3 dataset recovered from urine samples of
four healthy female subjects. It also demonstrates the relationship between various bacterial
phylotypes that were evolutionary compared to closely related organisms retrieved from RDP
II database. For taxonomy assignments, the phylogenetic tree was constructed at bootstrap
values of > 70% at the species level.
47
Figure 8 A phylogenetic tree showing the relationship between various
phylotypes based on analysis of 16S rRNA male urine sequences of V6-V8
dataset
The phylogenetic tree was constructed using a maximum - likelihood algorithm based
on analysis of 16S rRNA gene sequences of V6-V8 dataset recovered from urine samples of
four healthy male subjects. It also demonstrates the relationship between various bacterial
phylotypes that were evolutionary compared to closely related organisms retrieved from RDP
II database. For taxonomy assignments, the phylogenetic tree was constructed at bootstrap
values of > 70% at the species level.
48
Figure 9 A phylogenetic tree showing the relationship between various
phylotypes based on analysis of 16S rRNA male urine sequences of V1-V3
dataset
The phylogenetic tree was constructed using a maximum - likelihood algorithm based
on analysis of 16S rRNA gene sequences of V1-V3 dataset recovered from urine samples of
four healthy male subjects. It also demonstrates the relationship between various bacterial
phylotypes that were evolutionary compared to closely related organisms retrieved from RDP
II database. For taxonomy assignments, the phylogenetic tree was constructed at bootstrap
values of > 70% at the species level.
49
50
Figure 10 Comparison of major taxa taxonomically assigned to V1-V3 and
V6-V8 reads of human female 16S rRNA sequences urine sequences at the
genus level
This illustration depicts the bacterial communities that indigenously inhabit the
female urinary tract by sorting the 16S rRNA sequences at the genus level. Out of 17
bacterial genera being identified in all female urine specimens, 4 different genera were
unique for both of the two reads. The 3’ reads representing V6-V8 regions of the urine 16S
rRNA sequences were predominantly assigned to Prevotella, Corynebacterium, Gardnerella
and Weeksella spp. While the 5’ reads representing V1-V3 regions of the urine 16S rRNA
sequences were predominantly assigned to the same bacterial taxa. Other microbial
communities were only observed in the V1-V3 reads; Empedobacter, Facklamia and
Flavobacterium spp.
51
52
Figure 11 Comparison of major taxa taxonomically assigned to V1-V3 and
V6-V8 reads of human male 16S rRNA sequences urine sequences at the
genus level
This illustration depicts the bacterial communities that indigenously inhabit the male
urinary tract by sorting the 16S rRNA sequences at the genus level. Out of 41 bacterial
genera being identified, 19 different genera were unique for both of the two reads. The 3’
reads
representing
V6-V8
regions
were
predominantly
assigned
to
Prevotella,
Escherichia/Shigella, lactobacillus and Corynebacterium. Similarly, the taxonomical
assignments of 16S rRNA sequences of 5’ reads to the major bacterial were dominantly
observed. Other microbial communities were only observed in the V1-V3 reads as
Ruminicoccus, Coprococcus, Sphingomonas, Pseudoxanthomonas, Kocuria and Cupriavidus
spp. However, Negativicoccus, Oscillibacter, Brucella, Salmonella, Weeksella and Alistipes
spp were only identified in the V6-V8 reads.
53
3' 16S rDNA libraries
35
30
25
female1
female2
20
female3
Phylotypes
female4
15
male1
male2
10
male3
mlae4
5
0
1
10
20
30
40
50
60
68
78
Number of clones
Figure 12 Rarefaction curves plotted to estimate the phylotypes diversity
and coverage level of 16S rRNA urine sequences of 3’ reads from both male
and female subjects
This graph was plotted to assess the diversity of 16S rRNA sequences of bacterial
phylotypes that indigenously inhabit the urinary tract both male and female individuals.
Based on a 0.01 phylogenetic distance, rarefaction curve was plotted for 3’ reads representing
V6-V8 sequence dataset. The graph also demonstrates that neither male nor female bacterial
phylotypes showed good coverage as both expectedly failed to reach the plateau phase. The
only exception was female subject 1.
54
5' 16S rDNA libraries
50
45
40
female1
35
female2
30
female3
Phylotypes 25
female4
20
male1
15
male2
10
male3
5
male4
0
1
10
20
30
40
50
60
70
79
Number of clones
Figure 13 Rarefaction curves plotted to estimate the phylotypes diversity
and coverage level of 16S rRNA urine sequences of 5’ reads from both male
and female subjects
This graph was plotted to assess the diversity of 16S rRNA sequences of bacterial
phylotypes that indigenously inhabit the urinary tract both male and female individuals.
Based on a 0.01 phylogenetic distance, rarefaction curve was plotted for 5’ reads representing
V1-V3 sequence dataset. The graph also demonstrates that neither male nor female bacterial
phylotypes, specifically female subject 1, showed good coverage as both expectedly failed to
reach the plateau phase.
55
80
75
70
65
60
55
50
45
40
35
30
Female
25
Male
20
15
10
5
0
Figure 14 The overall distribution of bacterial genera taxonomically
assigned to 16S rRNA urine sequences of V6-V8 dataset
This graph demonstrates the overall composition of 16S rRNA sequences of V6-V8
dataset being recovered from 16S libraries of male and female urine samples according to
sequence similarity against RDP database. Nine bacterial taxa have been identified in both
male and female subjects in different proportions. It also represents the relation between the
number of sequence reads and their composition of bacterial communities in both subjects.
56
100
95
90
85
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
Female
Male
Figure 15 The overall distribution of bacterial genera taxonomically
assigned to 16S rRNA urine sequences of V1-V3 dataset
This graph demonstrates the overall composition of 16S rRNA sequences of V1-V3
dataset being recovered from 16S libraries of male and female urine samples according to
sequence similarity against RDP database. Eight bacterial taxa have been identified in both
male and female subjects in different proportions. It also represents the relation between the
number of sequence reads and their composition of bacterial communities in both subjects .
57
TABLES
Table 1 Summary of Female urine bacterial communities in 3’ and 5’
sequence datasets
Bootstrap
value of
phylogeneti
c clade
Total
number of
sequences
of 3'reads
Bootsrap
value of
phylogenetic
clade
Total
number of
sequences
of 5' reads
Order
Genus
Bifidobacteriales
Gardnerella
99
97
100
73
Coriobacteriales
Atopobium
99
13
98
13
Actinomycetales
Zimmermannella
100
4
99
4
Arthrobacter
88
3
99
3
Corynebacterium
95
30
99
42
Burkholderiales
Oligella
99
10
100
16
Lactobacillales
Lactobacillus
83
18
99
22
98
3
71
92
81
55
100
53
100
3
100
3
96
10
< 94
9
Facklamia
Bacteriodales
Prevotella
Flavobacteriales
Weeksella
100
< 92
Planobacterium
Unclassified taxa
Fusobacteriales
Sneathia
100
13
100
16
Selenomondales
Dialister
93
6
100
7
Megasphaera
98
5
89
8
The table represents all bacterial communities being identified in female urinary tract by
comparing their 16S rRNA gene sequences to known organisms in the RDP database. This
table demonstrates the dominant bacterial genera, Prevotella, Weeksella, Corynebacterium
and Gardnerella, in both V1-V3 and V6-V8 sequence reads [dark orange colour]. It also
verifies the results of phylogenetic analyses where higher taxonomical range and improved
resolution of bootstrap value of phylogenetic clade were observed in V1-V3 dataset. Few
bacterial genera showed lesser resolution in 5’ reads [light orange colour].
58
Table 2 Summary of Male urine bacterial communities in 3’ and 5’ sequence
datasets
Order
Genus
Actinomycetales
Corynebacterium
Bifidobacteriales
Lactobacillales
Arthrobacter
Kocuria
Gardnerella
Streptococcus
Bootsrap
value of
phylogenetic
clade
Fusobacteriales
Bacillales
Clostridiales
Caulobacterilaes
Rhizobiales
Pseudomonadales
Aeromonadales
Sneathia
Staphylococcus
Anaerococcus
Roseburia
Unclassified
Lachnospiraceae
family
Oscillibacter
Unclassified
Ruminococcaceae
Ruminococcus
Fecalibacterium
Peptoniphilus
Unclassified Clostridiales
Coprococcus
Phascolarctobacterium
Veilonella
Negativicoccus
Brevundimonas
Ochrobactrum
Acinetobacter
Succinivibrio
Enterobacterilaes
Eischerichia/Shigella
Selenomondales
40
92
3
Bootstrap
value of
phylogenetic
clade
Total
number of
sequences
of 5' reads
99
52
96
3
3
6
3
6
10
9
100
100
99
100
95
99
90
100
100
15
3
94
99
3
3
99
3
99
99
16
99
98
3
3
11
4
3
3
99
6
97
97
99
100
3
3
4
7
4
16
4
98
97
99
97
11
5
36
14
98
56
99
51
82
2
3
100
95
97
100
6
8
5
40
99
96
100
97
99
99
Salmonella
Enterobacter
Bacteriodales
100
100
98
95
100
98
91
95
Lactobacillus
Total
number of
sequences
of 3' reads
100
98
87
100
Prevotella
Bacteroides
Porphyromonas
59
3
62
17
6
99
46
3
6
9
6
79
23
8
Flavobacteriales
Sphingomonadales
Xanthomonadales
Burkholderiales
Barnesiella
Alistipes
Weeksella
Flavobacterium
Unclassified
Flavobacteriaceae
Sphingomonas
Pseudoxanthomonas
Cupriavidus
99
99
3
3
78
10
3
100
3
99
16
90
14
3
3
3
75
99
97
99
The table represents all bacterial communities being identified in female urinary tract by
comparing their 16S rRNA gene sequences to known organisms in the RDP database. This
table demonstrates the dominant bacterial genera, Prevotella, Eischerichia/Shigella,
Corynebacterium and Lactobacillus, in both V1-V3 and V6-V8 sequence reads [dark orange
colour]. It also verifies the results of phylogenetic analyses where higher taxonomical range
and improved resolution of bootstrap value of phylogenetic clade were observed in V1-V3
dataset. Few bacterial genera showed lesser resolution in 5’ reads [light orange colour].
60
Table 3 Summary of the number of sequenced clones for each library,
length of sequence obtained from each end and quality of reads
Female
1
Female
2
Female
3
Female
4
Male
1
Male
2
Male
3
Male
4
50
67
77
43
52
49
45
72
63
63
80
36
48
33
31
27
40
56
70
30
39
17
20
20
Average Length
of reads (bps)
Minimum Length
of reads (bps)
Maximum
Length of reads
(bps)
530
497
524
433
470
478
429
468
376
302
329
300
309
303
315
308
620
619
644
583
589
639
612
617
Minimum
Quality of reads
20
20
20
20
20
20
20
20
Number of reads
(using 63F
primer)
Number of reads
(using 1387R
primer)
Number of reads
in both forward
and reverse
sequences
The table represents the number of sequenced clones for each library, length of
sequence obtained from each end and quality of reads. The number of reads for each
individual (forward plus reverse) varied from a minimum of 76 (male 3) to a maximum 157
(female 3). Sequences were processed by trimming the plasmid vector bases with cross match
and discarding low quality sequences < 300 bp in length and/or had average PHRED quality
score of Q= < 20. Therefore, the minimum length of reads is 302 (female 2) and varied up to
a maximum of 644 (female 3). This explains why the reads obtained from the 5’ and the 3’ of
the inserts did not permit overlapping of the sequences from both ends of the recombinant
plasmids.
61
Table 4 Alpha diversity measurements of V6-V8 sequence dataset of male
and female 16S rRNA gene
Library
Number of
Sequences
3’_plate1_female 58
Number of
OTUs
Chao1
Shannon
index
Simpson
index
2
2
0.08365
0.967213
3’_plate2_female 59
22
44.75
2.52451
0.111864
3’_plate3_female 76
31
69
2.897021
0.080253
3’_plate4_female 62
20
98
2.217736
0.191396
3’_plate1_male
55
30
205.5
2.613783
0.168831
3’_plate2_male
61
25
110.5
2.521391
0.136201
3’_plate3_male
43
24
87.33333
2.480538
0.170048
3’_plate4_male
45
24
45
2.927935
0.047343
All the table calculations were performed using mothur software [9] for 3’reads of both male
and female 16S rRNA sequences at a 1% divergence threshold. The number of observed
OTUs range from 2 to 31. The results coincide with the plotted rarefaction curves where the
Chao1 values of all urine samples, with exception of female subject1, were significantly
exceeding the actual number of phylotypes present in each sample. Chao1, Shannon and
Simpson indices were calculated for estimating the richness, evenness and overall diversity of
microbial communities for urine samples under study.
62
Table 5 Alpha diversity measurements of V1-V3 sequence dataset of male
and female 16S rRNA gene
Library
Number of
clones
5’_plate1_female 44
Number of
OTUs
Chao1
34.5
Shannon
index
1.136917
Simpson
index
0.567177
12
5’_plate2_female 70
40
82
3.349299
0.041408
5’_plate3_female 79
43
88.11111 3.42104
0.037975
5’_plate4_female 59
41
115.3333 2.987554
0.068747
5’_plate1_male
43
24
58
2.869584
0.057082
5’_plate2_male
63
44
137.5
3.596609
0.020337
5’_plate3_male
46
23
53
2.662995
0.100177
5’_plate4_male
72
53
289.5
3.812269
0.013693
All the table calculations were performed using mothur software [9] for 5’reads of both male
and female 16S rRNA sequences at a 1% divergence threshold. The number of observed
OTUs range from 12 to 53. The results coincide with the plotted rarefaction curves where the
Chao1 values of all urine samples were significantly exceeding the actual number of
phylotypes present in each sample. Unlike wise, the coverage of V1-V3 reads of female urine
sample 1 was incomplete and thus, more phylotypes remain to be identified. Chao1, Shannon
and Simpson indices were calculated for estimating the richness, evenness and overall
diversity of microbial communities for urine samples under study.
63
APPENDIX
Supplementary Figure 1 The approval letter by the institutional review
board (IRB) of the American university in Cairo
All the subjects under the study were provided with a written informed consent which
was approved by the institutional review board (IRB) of the American university in Cairo.
64
Supplementary Figure 2 The medical history
All enrolled subjects were asked to fill a written medical history form to make sure of
the overall general health.
65