New Techniques to characterise the vaginal microbiome in pregnancy

Abstract

Understanding of the vaginal microbiome in health and disease is essential to screen, detect and manage complications in pregnancy. One of the major complications of pregnancy is preterm birth (PTB), which is the leading world-wide cause of death and disability in children under five years of age. The aetiology of PTB is multifactorial, a causal link has been established with infection. Despite the importance of understanding the vaginal microbiome in pregnancy in order to evaluate strategies to prevent and manage PTB, currently used culture based techniques provide limited information as not all pathogens are able to be cultured.
Implementation of culture-independent high-throughput techniques and bioinformatics tools are now advancing our understanding of the vaginal microbiome. New methods employing 16S rRNA and metagenomics analyses make possible a more comprehensive description of the bacteria of the human microbiome. Several studies on the vaginal microbiota of pregnant women have identified a large number of taxa. Studies also suggest reduced diversity of the microbiota in pregnancy compared to non-pregnant women, with a relative enrichment of the overall abundance of Lactobacillus species, and significant differences in the diversity of Lactobacillus spp. A number of advantages and disadvantages of these new techniques are briefly discussed.
The potential clinical importance of the new techniques is illustrated through recent reports where traditional culture-based techniques failed to identify pathogens in high risk complicated pregnancies whose presence subsequently was established using culture-independent, high-throughput analyses.

Full text

AIMS Microbiology, 2(1): 55-68.
DOI: 10.3934/microbiol.2016.1.55
Received: 20 December 2015
Accepted: 01 March 2016
Published: 07 March 2016
http://www.aimspress.com/journal/microbiology
Review
New techniques to characterise the vaginal microbiome in pregnancy
George L. Mendz
1,
*, Nadeem O. Kaakoush
2
, Julie A. Quinlivan
3
1
School of Medicine, Sydney, The University of Notre Dame Australia, 160 Oxford St,
Darlinghurst, NSW 2010, Australia.
2
School of Biotechnology and Biomolecular Sciences, The University of New South Wales,
Kensington, NSW, Australia
3
Institute for Health Research, The University of Notre Dame Australia, Fremantle, WA, Australia.
* Correspondence: E-mail: George.Mendz@nd.edu.au; Tel: +61-2-8204-4457;
Fax: +61-2- 9357-7680
Abstract: Understanding of the vaginal microbiome in health and disease is essential to screen,
detect and manage complications in pregnancy. One of the major complications of pregnancy is
preterm birth, which is the leading world-wide cause of death and disability in children under five
years of age. The aetiology of preterm birth is multifactorial, but a causal link has been established
with infection. Despite the importance of understanding the vaginal microbiome in pregnancy in
order to evaluate strategies to prevent and manage PTB, currently used culture based techniques
provide limited information as not all pathogens are able to be cultured.
The implementation of culture-independent high-throughput techniques and bioinformatics
tools are advancing our understanding of the vaginal microbiome. New methods employing 16S
rRNA and metagenomics analyses make possible a more comprehensive description of the bacteria
of the human microbiome. Several studies on the vaginal microbiota of pregnant women have
identified a large number of taxa. Studies also suggest reduced diversity of the microbiota in
pregnancy compared to non-pregnant women, with a relative enrichment of the overall abundance of
Lactobacillus species, and significant differences in the diversity of Lactobacillus spp. A number of
advantages and disadvantages of these techniques are discussed briefly.
The potential clinical importance of the new techniques is illustrated through recent reports
where traditional culture-based techniques failed to identify pathogens in high risk complicated

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pregnancies whose presence subsequently was established using culture-independent, high-
throughput analyses.
Keywords: Preterm birth; genital infections; vaginal microbiota; high-sequencing throughput;
metagenomics; Lactobacillus
1. Introduction
Understanding the vaginal microbiome in health and disease is essential to screen, detect and
manage complications in pregnancy. A major complication of pregnancy is preterm birth (PTB),
which is the leading world-wide cause of death and disability in children under five years of age [1–
4]. Whilst the aetiology of PTB is multifactorial, a causal link has been established with infection.
The rates of neonatal infectious diseases in mothers with chronic chorioamnionitis who deliver at
term is 20%, and in mothers who deliver prematurely is 50% [5]. Despite the importance of
understanding the vaginal microbiome in pregnancy in order to evaluate strategies to prevent and
manage PTB, currently used culture-based techniques provide clinicians with limited information of
bacterial communities present in the vagina as not all bacteria are able to be cultured.
Pathogens may gain access to the amniotic cavity and fetus by ascending migration of vaginal
microflora, haematogenous dissemination through the placenta, retrograde seeding from the
peritoneal cavity through the Fallopian tubes, or iatrogenic introduction at the time of invasive
procedures [6,7]. Evidence obtained from studies culturing bacteria support the view that the most
common pathway of microbial invasion of the intra-amniotic cavity is the ascending route [8]. Meta-
analyses of antibiotic administration to women with bacterial vaginosis showed a significant
reduction in the incidence of preterm deliveries and low weight babies associated with treatment [9].
A positive association between periodontal disease and uterine infection during pregnancy remains
controversial [10], but a number of oral bacterial species have been identified in the intra-amniotic
space suggesting haematogenous spread [11]. Thus, it is reasonable to hypothesise that preventing
ascending genital tract infections and the initiation of inflammatory cascades in the uterus will
reduce PTB, neonatal fever and other morbidities. Consequently, identification of the bacterial
communities present in the vagina during pregnancy will help to achieve a comprehensive picture of
its microbiota that can be exploited to promote health and prevent/combat disease.
The aim of the study is to provide a description of the vaginal microbiome in health and disease
that has been achieved by specific application of new analytical and bioinformatics tools employed
to investigate generally the human microbiome.
2. Methods
Searches of publications in PubMed performed with the key terms ‘vagina’ and ‘microbiome’
yielded 396 references. Adding the key words ‘sequencing’ or ‘16S rRNA’ or ‘metagenomics’
produced 74, 68 and 19 references, respectively. If instead, the term ‘pregnancy’ was added to the

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original search ‘vagina and microbiome’ the query returned 94 references, and further adding the
term ‘16S rRNA’ reduced this number to 16. An independent search with the key words
‘microbiome’ and ‘new generation sequencing’ returned 111 articles. A check of the articles
retrieved indicated extensive redundancies that allowed purging duplications from the list. All the
articles in the streamlined reference list underwent a preliminary analysis to identify studies that had
primary data on the vaginal microbiome obtained by employing non-cultivation, high-throughput
sequencing methods. The selected articles and references therein were chosen for this review.
The inclusion criteria were studies in English published in the last 15 years that identified
specific taxa in the vaginal microbiome of non-pregnant women or pregnant women, employed
cultivation-independent high-throughput sequencing methods, and demonstrated the power of the
new techniques to contribute to the characterisation of this microbiota. Also included were two older
papers that were seminal for the development of new bioinformatics tools.
3. The Vaginal Microbiome
A growing understanding of the central role played by microbes in human health and disease as
well as advances in techniques to identify microorganisms and bioinformatics tools to analyse very
large data sets have provided the foundation to characterise and investigate the microbial
communities that inhabit the human body: the human microbiome [12]. From a microbiological
perspective the vagina is a complex and dynamic habitat that has a significant impact on the health of
the woman. The changes in the structure of this ecosystem are influenced by many factors including
age, menarche, time of the menstrual cycle, sexual activity, pregnancy, infections, and various habits
and practices [13–17]. The composition of the vaginal microbiota has been investigated for over a
hundred years, and up to 15 years ago, most conclusions about the vaginal microflora of post-
pubertal women were based on methods that used cultivation of microbial populations [18], and
more recently, on culture-independent targeted polymerase chain reaction (PCR) methods [19,20].
These approaches yield biased and incomplete assessments of the structure of microbial communities,
because many members of these communities are not culturable in vitro, and a diverse array of
bacteria other than those identified by targeted PCR may be present, and thus remain undetected. For
instance, in current clinical practice microbiological analyses of the female genital microbiota focus
on a number of species from about 25 genera including Atopobium, Chlamydia, Clostridium,
Escherichia, Gardnerella, Mycoplasma, Neisseria, Prevotella, Staphylococcus, Streptococcus,
Ureaplasma. In more complicated cases searches are conducted for extra genera such as Dialister,
Enterococcus, Fusobacterium, Haemophilus, Leptotrichia, Megasphaera, Mobiluncus,
Peptostreptococcus, and Veillonella.
Cultivation-independent broad-range PCR analyses of 16S rRNA gene sequences from
microbial communities suggest only a small percentage of bacteria in nature have been identified,
even in well-studied environments. Studies of the vaginal microflora employing these methods have
revealed a richer microbiota with a much large number of taxa than those identified employing
culturing methods [21–23] In particular, the identity and diversity of the vaginal bacterial
populations during pregnancy remain largely unknown for various racial backgrounds, health status
and lifestyle. Also, the complex interactions of the various members of the vaginal microflora are not

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sufficiently understood to enable this knowledge to be clinically exploited to combat disease. This
study offers a brief discussion of techniques and tools employed to elucidate the vaginal microbiome,
and provides an overview of current knowledge of the vaginal microbiome in late pregnancy. Case
examples highlight potential clinical applications of culture independent techniques.
4. Techniques and Computational Tools to Analyse the Human Microbiome
The advent of high-throughput sequencing (HTS) had a significant impact on disease diagnosis,
particularly of human genetic diseases and cancers [24–27], and to a lesser extent on microbial-
related illnesses. The effectiveness of HTS techniques has been demonstrated by identifying
aetiological agents in samples where traditional bacterial culture techniques failed and in cases where
multiple bacterial agents were involved. Key limitations to a wider use of the HTS techniques are the
lack of ability of diagnostic centres to perform fast sample analyses, and the capacity to analyse the
large datasets generated by such methods. Nonetheless, the potential of HTS is evidenced by the
application of these techniques and subsequent statistical analyses of the data to identify bacterial
species that may be involved in preterm birth. Such work may help refine more targeted clinical
screening approaches. Two important methods for microbial identification and characterisation that
use HTS are sequencing of 16S rRNA and metagenomics.
4.1. Sampling technique
The choice of sampling site of the vagina with swabs should be considered, since there has been
controversy about the microbial diversity in different regions of the vagina. To investigate the
vaginal microbiota, a study of pregnant healthy Chinese women collected three repeated swabs at the
cervix, posterior fornix and vaginal canal and different gestational ages. For each individual woman
there was high vaginal microbiome homogeneity across the three sampling sites. The results revealed
different beta diversity (differences between women) at various gestational ages [28]. In contrast, a
study that included women of several race/ethnic backgrounds with pregnancies both healthy term
and preterm birth found that sampling site was an important variable [29].
4.2. Genomics employing the 16S rRNA gene
The 16S rRNA gene is a universal component of the DNA transcriptional machinery of bacteria
and archaea. This gene has both conserved and hypervariable regions; the former makes universal
amplification possible, and sequencing the latter allows discrimination between different
microorganisms. These characteristics make the 16S rRNA gene well suited as the basis to identify,
classify and quantitate microorganisms in complex biological mixture in samples containing up to
thousands of different species [30].
From the DNA extracted from samples, specific fragments of the 16S rRNA gene are amplified
employing the polymerase chain reaction (PCR) technique in a series of cycles. The amplified gene
segments are then sequenced using HTS developed to sequence in parallel large numbers of
individual DNA fragments.

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Detecting 16S rRNA sequences of bacteria directly from samples as a phylogenetic marker has
served to discover their presence in environments where they were previously unknown, to identify
new taxa, and to establish phylogenetic relationships between them. In recent years, the use of
cultivation-independent methods based on broad-range PCR analyses of 16S rRNA sequences have
increased the understanding of the composition of vaginal bacterial communities.
The application of 16S rRNA analysis to samples that contain tens or hundreds of bacterial
communities allows deep views into the diversity of these populations. Nonetheless, the method has
limitations. There are three important sources of error. These are: (a) bias towards some species
owing to unequal amplification of different species' 16S rRNA genes; (b) uncertainty in choosing the
hypervariable region that will provide the maximum discriminating power for a given sample, since
no single region is able to distinguish between all bacteria; and (c) complications of 16S rRNA-based
analyses by artifacts such as chimeric sequences caused by PCR amplification and sequencing
errors [31,32].
For example, the potential bias introduced by sample processing, sequencing and taxonomic
classification in 16S rRNA studies was investigated employing samples of a 80 bacterial mock
communities comprised of prescribed proportions of cells from seven vaginally-relevant bacterial
strains, and two additional sets of 80 mock communities by mixing prescribed quantities of DNA
and PCR products. Different DNA extraction kits can produce dramatically different results and the
effects of DNA extraction and PCR amplification for the protocols employed were much larger than
those owing to sequencing and classification. The work concluded that due attention should be given
to sample processing notwithstanding advances in sequencing technology [33].
Another recent study found that the 8F-534R primer pair assigned more sequences to
Lactobacillus spp. (65.5% vs. 25.4%) and less sequences to Sarcina spp. (9.6% vs. 22.1%) compared
to the 968F-1401R primer pair [34]. Other bacterial taxa with inconsistent results across the 8F-534R
and 968F-1401R primer pairs include Bacillus spp., Fusobacterium spp., Lactococcus spp.,
Streptococcus spp., Clostridium spp., Gemella spp., Lachnospira spp., Leuconostoc spp.,
Microbacterium spp., and Weissella spp. [34]. In an attempt to correct these types of errors,
Klindworth and colleagues conducted a comprehensive analysis of overall coverage and phylum
spectrum of 175 primers and 512 primer pairs with respect to the SILVA 16S/18S rRNA non-
redundant reference dataset [35]. In addition to providing a guideline for primer selection based on
application, the authors put forward a selection of primer pairs that are considered optimal for the
amplification of bacterial and archaeal rRNA genes at different sites [35].
4.3. Metagenomics of whole genomes
Metagenomics studies of microorganisms refer to non-culture based approaches for collectively
studying sets of genes or genomes from mixed populations of microbes. These studies are grouped
according to different screening methods: (a) shotgun analysis using mass genome sequencing; (b)
genomic activity-driven studies designed to search for specific microbial functions; (c) genomic
sequence studies using phylogenetic or functional gene expression analysis; and (d) next generation
sequencing technologies for determining whole gene content in environmental samples [36].
To conduct these analyses, DNA or RNA isolated from a sample is randomly sheared, the

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fragments are clonally amplified employing PCR, and then sequenced using one of the various HTS
developed to sequence in parallel large numbers of individual DNA or RNA fragments. The
sequence data are then processed for assembly using one of the two strategies, either reference-based
assembly (co-assembly) or de novo assembly. The information on DNA sequences is sorted into
taxonomic groups that may represent individual or closely related genomes. Generally, metagenomic
sequences are annotated in two steps: (a) feature prediction is performed by identifying
characteristics of interest within genes; and (b) functional annotation is performed by assigning
putative gene functions and taxonomic neighbours.
4.4. Some computational tools to analyse large sequencing data sets
To analyse large raw reads data sets generated by HTS of universal genes, several
computational tools have been developed that can be employed as barcodes to classify microbes (e.g.
16S rRNA gene and hsp60). Two of the most commonly used tools to classify reads into operational
taxonomic units (OTU) are MOTHUR [37] and Quantitative Insights Into Microbial Ecology
(QIIME) [38] MOTHUR integrates and streamlines a number of algorithms employed for microbial
classification (e.g. NAST, PyroNoise, Classifier and UChime) into an open-source stand-alone
program, while QIIME acts as an interface that connects a number of programs used for microbial
classification (e.g. pynast and uclust). More recently, the algorithm UPARSE [39] was developed to
improve the accuracy of OTU clustering; both MOTHUR and QIIME are able to run UPARSE to
classify OTU. Furthermore, the software package microbial Profiling Using Metagenomic Assembly
(mPUMA) [40] utilises de novo assembly of OTU to enable the analysis of microbial communities.
A new method called STIRRUPS employs the USEARCH algorithm with a curated reference
that can be used for rapid species-level classification of 16S rRNA partial sequences. It was
developed to construct a vaginal 16S rRNA sequences reference database for bacterial taxa likely to
be associated with vaginal health. The method and database provide accurate species-level
classifications of metagenomics 16S rRNA sequence reads that will be useful for analysis and
comparison of microbiome profiles from vaginal samples [41].
Other tools have been designed as pipelines for more complex data sets arising from whole
genome sequencing approaches (metagenome analysis) such as MetaGenome Rapid Annotation
using Subsystem Technology (MG-RAST) [42], QIIME [38], Metagenomics Platform for Sequence
Analysis and Management System (MetaSAMS) [40], and EBI Metagenomics [44].
The statistical analyses of sequence data sets requires both simple and multivariate statistical
techniques including Principal Component Analysis (PCA), non-metric Multi-dimensional Scaling
(MDS) and Permutational Multivariate Analysis of Variance (PERMANOVA) [44,46]. Principal
Component Analysis can determine if a sample clusters with or away from others, and identify what
microbial taxa contribute to differences in microbial composition. Multi-dimensional Scaling is an
alternative ordination method to PCA. The relative abundance of bacterial taxa can be compared
with PERMANOVA using a Bray-Curtis similarity measure to construct distance matrices. This
procedure is a multivariate analogue of ANOVA except that pairwise distances/similarities between
sampling units (in this case using the Bray-Curtis similarity coefficient) are used to calculate
multivariate averages (centroids) and test statistics (pseudo-F). Probabilities are obtained by

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comparing the pseudo-F value to a distribution of test statistics generated by random permutations of
the data.
5. The Vaginal Microbiome of Pregnant Women
5.1. Comparison of the vaginal microbiome of healthy non-pregnant and pregnant women
Fewer bacterial species inhabit the vagina in comparison with the gastrointestinal tract, although
DNA sequences from more than 80 bacterial genera corresponding to more than 950 taxa have been
identified [23]. Many vaginal bacterial taxa are yet to be characterised [41].
Bacteria of the genus Lactobacillus are the most abundant colonisers of the vagina of healthy
women. A culture-independent, universal PCR amplification of the 16S rRNA gene investigation of
the microbiome of 396 reproductive-age asymptomatic women found their vaginal bacterial
communities clustered into five vaginal groups (VG). Four of these groups were dominated by
Lactobacillus spp.: L. crispatus, L. gasseri, L. iners, or L. jensenii, albeit they co-inhabited with
other bacterial taxa [21]. The fifth group was characterised by a greater abundance of other bacteria.
In healthy pregnancy, there is a decrease in the diversity of bacterial taxa in the vagina [47,48]
and in the dominance of some VG.
Figure 1. Frequencies of bacterial communities in non-pregnant women (light grey) and
pregnant women (dark grey). The groups are dominated by L. crispatus (I), L. gasseri (II),
L. iners (III), other bacteria (IV), and L. jensenni (V).
In a study of 24 pregnant women with uncomplicated pregnancy at term compared to a cohort
of non-pregnant subject, differences were observed. There was a reduction in diversity, and an
absence of specific taxa, as well as a relative enrichment of Lactobacillus species including L.
Frequency (%)
Bacterial Community Groups

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crispatus, L. iners, L. jensenii and L. johnsonii. [11]. The dominant orders during pregnancy were
Lactobacillales, Clostridiales, Bacteroidales and Actinomycetales. Differences in the microbiome
composition between pregnant and non-pregnant women were also observed in a retrospective case-
control longitudinal study of 32 non-pregnant and 22 pregnant women. Lactobacillus spp. were the
predominant members of the microbial community in normal pregnancies [49]. Figure 1 summarises
the frequency of the five VG from three studies comprising 589 healthy non-pregnant women
[21,22,44] compared to frequencies from 251 healthy pregnant women [29,49–51]. The frequencies
in the groups dominated by L. crispatus and L. iners are different.
Current data suggest normal pregnancy induces changes in vaginal bacterial populations to a
microbiome of low diversity. Lactobacillus species strongly dominate the vaginal environment
during pregnancy, but changes also occur also in other colonising taxa.
5.2. The microbiome of pregnant women with vaginal infections
Ascending vaginal infections in pregnancy may lead to chorioamnionitis, PTB and adverse
pregnancy outcomes [52]. These infections are postulated to arise predominantly through ascending
pathways from the vagina, through the cervix and across the placental barrier. They contribute to
25% of cases of PTB [53].
New techniques have added to our understanding of these pathogenic pathways and their
potential causative agents. The use of 16S rRNA gene sequence-based analyses have revealed the
presence of anaerobic taxa not previously detected by culture. An increase in the abundance and
diversity of some anaerobic taxa have been linked with vaginal infection [54]. The commonest taxa
identified are from genera such as Gardnerella, Megasphaera, Prevotella, etc., as well as
taxonomically “undetermined” taxa such as “bacterial vaginosis associated bacteria (BVAB)” [55].
Two studies [21,56] reported changes in the relative abundances of L.iners, the Lactobacillus
found most commonly in healthy pregnancies, and in three anaerobic taxa associated with vaginal
infections (Figure 2). In another study of 374 pregnant women, the presence of specific vaginal
bacterial taxa was correlated against the risk of preterm birth. Culture-independent targeted PCR of
the 16S rRNA gene of 12 bacterial taxa was carried out on fluid collected from the upper vagina.
Among African-american and Hispanic women, even after controlling for selected maternal
behavioural and biological characteristics, the bacterial community in the vagina in the second
trimester of pregnancy was an independent correlation with adverse pregnancy outcome.
Mycoplasma taxa were positively associated with PTB in both these groups of participants. However,
the association was not observed in Caucasian participants. Surprisingly, a specific Group B
Streptococcus taxon associated with bacterial vaginosis showed a negative association with PTB [20].
Another study of 88 women from five racial groups using universal 16S rRNA amplification found
vaginal microbiome diversity in human pregnancy correlated with PTB. Race, ethnicity and
sampling site were also important variables. The abundance of Lactobacillus spp. was higher among
women at low risk of PTB relative to those at high risk, but there was no correlation between
Lactobacillus abundance and PTB [29].

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Abundance (%)
Figure 2. The relative abundances of L. iners, Gardnerella vaginalis, Megasphaera 1,
Prevotella spp. and BVAB1 in healthy women (light grey) and in women with vaginal
infection (dark grey) [21,56].
In a case-control study, pyrosequencing of 16S rRNA genes was used to investigate differences
in the vaginal microbiome of women giving birth at term or preterm. It comprised 18 women with
pregnancy complicated by spontaneous preterm labour and 72 controls with uncomplicated
pregnancy. No differences were found in the relative abundance of microbial phylotypes, and there
were no differences in the frequency of the vaginal community states between groups [49].
The results to date suggest the vaginal microbiota in pregnancy is more complex in the presence
of infection, and an increase in the abundance of anaerobic species is linked to adverse pregnancy
outcomes. Larger studies involving women with geographic, racial and ethnic diversity are required
to tease out key associations [47].
6. Clinical Applications of New Technologies
Employing HTS of the 16S rRNA gene and statistical analyses on DNA extracted from vaginal
swabs, bacterial taxa can be identified in the vagina of women with a complicated pregnancy. Recent
cases report that taxa belonging to the genera Acinetobacter, Bacteroides, and Hafnia, and the
species Campylobacter curvus and Haemophilus parainfluenzae were potentially involved in
preterm, very preterm and extremely preterm births [57–59]; Table 1 summarises data from these
reports. Of note is that none of the taxa identified by 16S rRNA techniques, nor any other pathogens,
including Group B Streptococcus, were found employing standard hospital cultures of vaginal swabs.
These examples demonstrate how current culture-based methods of detection of bacterial
infections do not reveal the entire microflora present in the female genital tract, even when they may
dominate the microbiome in disease states diagnosed with histological clinical chorioamnionitis.

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Cultivation-independent universal PCR analyses can detect potentially pathogenic species in cases
when standard culture-based techniques are negative. The cases in Table 1 provide also new insights
into pathogenic taxa in the vaginal microbiome of pregnant women, and demonstrate the need to
review clinical practices employed to identify pathogens in maternal infections.
Table 1. Predominant bacterial communities in three premature births.
Mother
(age in years,
gravidity,
parity)
Gestational
Age
(weeks)
Diagnosis
Hospital
Microbiology
Taxa
(sequence reads %
supporting the presence
of taxa)
Reference
29, G3, P2 26
PPROM,
HCA
Negative
Campylobacter curvus
(LVS: 1.4%; HVS
61.3%)
Haemophilus
parainfluenzae (LVS:
56.1%; HVS: 18.2%)
Mendz et
al., 2014
29, G1, P0 27 HCA Negative
Hafnia spp. (50%)
Bacteroides spp. (32%)
Kaakoush
et al.,
2014
38, G2, P1 34
HCA,
Vasculitis
Negative
Acinetobacter spp.
(68.2%)
Quinlivan
et al.,
2014
PPROM: pre-partum rupture of membranes; HCA: chorioamnionitis demonstrated by histopathology of the
placenta; vasculitis of the umbilical cord. LVS: low vaginal swab; HVS: high vaginal swab.
7. Conclusion
The use of new technologies has advanced out understanding of the vaginal microbiome. Key
findings are that: (1) species diversity is reduced during pregnancy; (2) patterns of vaginal
populations are different in pregnant and non-pregnant women; (3) Lactobacillus spp. dominate the
vaginal microbiome of healthy pregnant women, with varying relative abundances of different
species, and with L. iners as the most frequent predominant species; and (4) accumulating evidence
supports a role for alteration in the vaginal microbiome in PTB.
Sequence-based analyses of the 16S rRNA gene revealed also the presence of anaerobic species
in the vagina not previously detected by culture [55], and allowed associations to be made between
specific taxa and PTB.
Considering the limitations of studies to date to reveal all the microflora present in the genital
tract of pregnant women, more work is required to understand what are the differences in the
microbiome of women owing to race, age and lifestyle. Research employing non-culturing methods
and state-of-the-art sequencing analyses will be needed to delineate the “entire picture” of the
vaginal and uterine microbiomes and to determine their relationships.
A comprehensive view of the genital microflora will serve also to identify new bacterial taxa

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involved in urogenital infections, and to elucidate whether colonisation of the uterus is primarily via
ascending infection, and the role or other routes of access to the amniotic cavity.
Future efforts to reduce PTB depend upon a better knowledge of the taxa found in pregnant
women in health and disease. This information will underpin the development of earlier and more
specific methods to diagnose maternal genital infections, and to reduce mortality and morbidity in
fetuses and neonates.
Acknowledgements
The study was supported by a grant from the Research Foundation of the Cerebral Palsy
Alliance of Australia.
Conflicts of interest
All authors declare no conflicts of interest in this study.
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