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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.
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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
New techniques to characterise the vaginal microbiome in pregnancy
George L. Mendz
*, Nadeem O. Kaakoush
, Julie A. Quinlivan
School of Medicine, Sydney, The University of Notre Dame Australia, 160 Oxford St,
Darlinghurst, NSW 2010, Australia.
School of Biotechnology and Biomolecular Sciences, The University of New South Wales,
Kensington, NSW, Australia
Institute for Health Research, The University of Notre Dame Australia, Fremantle, WA, Australia.
* Correspondence: E-mail:; 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
AIMS Microbiology Volume 2, Issue 1, 55-68.
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
AIMS Microbiology Volume 2, Issue 1, 55-68.
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.
AIMS Microbiology Volume 2, Issue 1, 55-68.
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 asbacterial 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.
(age in years,
(sequence reads %
supporting the presence
of taxa)
29, G3, P2 26
Campylobacter curvus
(LVS: 1.4%; HVS
parainfluenzae (LVS:
56.1%; HVS: 18.2%)
Mendz et
al., 2014
29, G1, P0 27 HCA Negative
Hafnia spp. (50%)
Bacteroides spp. (32%)
et al.,
38, G2, P1 34
Acinetobacter spp.
et al.,
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.
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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... Culture-independent targeted polymerase chain reaction (PCR) methods were developed to identify species that are not cultivatable in vitro. The methods are based on the analysis of 16S rRNA sequences that allows the identification of a much large number of taxa (MENDZ [59]). 16S rRNA gene belongs to prokaryotic DNA that is found in all bacteria and used to identify bacteria as apart from other type of DNA (animal, plant, fungal). ...
... These approaches are more reliable as they allow to evaluate different microbial communities (including those that cannot be cultivated) and their abundance in various cavities. The most sensitive molecular techniques for investigating the microbiota use non-culture based approaches to study genes or genomes from mixed populations of microbes (MENDZ [59]) and include shotgun analysis (using mass genome sequencing), genomic sequence studies (for phylogenetic analysis) and next generation sequencing technologies (COX [61]). ...
... The best known marker is 16S ribosomal RNA (rRNA) gene (present in all bacteria and Archaea) that is about 1,550 bp and contains nine regions with high variability (hypervariable regions), flanked by conserved regions. Therefore, different bacterial species from a sample can be identified and quantified using NGS that targeted 16S rRNA gene (MENDZ [59]). To eliminate some of the disadvantages of 16S rRNA (multiple number of copies, lack of specificity for some bacterial strains), alternative markers like 23S rRNA and cpn60 were proposed, but incomplete databases have limited their usefulness in practice (TYLER [58]). ...
... Studies based on samples collected from the posterior vaginal fornix, ecto-and endocervix regions to capture the vaginal microbiota have picked out a number of vaginal microbial communities that cannot be recognized by long-established conventional methods but can be revealed using 16S ribosomal RNA (rRNA) gene sequencing [30,31] and enlarged culture techniques [32][33][34]. In this review, we primarily focus on a widespread outline of the strategy that is presently used to study the vaginal microbiota and their combined genomes and talk about the components of experimental blueprint and data analysis. ...
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Background: There is a unique microbial community in the female lower genital tract known as the vaginal microbiota, which varies in composition and density and provides significant benefits during pregnancy, reproductive cyclicity, healthy newborn delivery, protection from preterm birth, infections such as UTIs, bacterial vaginosis, and so on, and improves the efficacy of treatments for vaginal cancers. Methods: It is necessary to know how the vaginal microbiome is composed in order to make an accurate diagnosis of the diseases listed above. A microbiome’s members are difficult to classify, and the way microbial communities function and influence host–pathogen interactions are difficult to understand. More and more metagenomic studies are able to unravel such complexities due to advances in high-throughput sequencing and bioinformatics. When it comes to vaginal microbiota research, we’ll be looking at the use of modern techniques and strategies that can be used to investigate variations in vaginal microbiota in order to detect diseases earlier, better treat vaginal disorders, and boost women’s health. Discussion: The discussed techniques and strategies may improve the treatment of vaginal disorders and may be beneficial for women’s overall health.
... For its development, the interaction between virulence factors and their quantitative domination is necessary. Accordingly, it can be argued that some taxa, depending on certain factors, may act as commensals or pathogens [46]. Moreover, some bacteria, which are also present in BV, e.g., Megasphaera or Atopobium, have the ability to produce lactic acid, which would indicate that it is possible for species other than lactobacilli to protect one against the proliferation of pathogenic bacteria [32]. ...
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The physiological microbiota of the vagina is responsible for providing a protective barrier, but Some factors can disturb the balance in its composition. At that time, the amounts of the genus Lactobacillus decrease, which may lead to the development of infection and severe complications during pregnancy. The aim of the study was the analysis of the bacterial composition of the vagina in 32 Caucasian women at each trimester of pregnancy using the next-generation sequencing method and primers targeting V3-V4 regions. In the studied group, the dominant species were Lactobacillus iners, Lactobacillus gasseri, and Lactobacillus plantarum. Statistically significant differences in the quantitative composition between trimesters were observed in relation to Lactobacillus jensenii, Streptococcus agalactiae, Lactobacillus iners, Gardnerella spp. Out of the 32 patients, 20 demonstrated fluctuations within the genus Lactobacillus, and 9 of them, at different stages of pregnancy, exhibited the presence of potentially pathogenic microbiota, among others: Streptococcus agalactiae, Gardnerella spp., Atopobium vaginae, and Enterococcus faecalis. The composition of the vaginal microbiota during pregnancy was subject to partial changes over trimesters. Although in one-third of the studied patients, both the qualitative and quantitative composition of microbiota was relatively constant, in the remaining patients, physiological and potentially pathogenic fluctuations were distinguished.
... Research into the human microbiome and specifically the role in altering the materno-feto-placental microbiome and endogenous concentrations of pro-inflammatory 2-series prostaglandins as measured using new molecular technologies is an emerging field of research for the former intervention. 12,13 However, the development of drugs and obstetric management based upon microbiome and pro-inflammatory markers is still at least a decade from fruition. ...
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Accurate characterization of the vaginal microbiome remains a fundamental goal of the Human Microbiome project (HMP). For over a decade, this goal has been made possible deploying high-throughput next generation sequencing technologies (NGS), which indeed has revolutionized medical research and enabled large-scale genomic studies. The 16S rRNA marker-gene survey is the most commonly explored approach for vaginal microbial community studies. With this approach, prior studies have elucidated substantial variations in the vaginal microbiome of women from different ethnicities. This review provides a comprehensive account of studies that have deployed this approach to describe the vaginal microbiota of African women in health and disease. On the basis of published data, the few studies reported from the African population are mainly in non-pregnant post pubertal women and calls for more detailed studies in pregnant and postnatal cohorts. We provide insight on the use of more sophisticated cutting-edge technologies in characterizing the vaginal microbiome. These technologies offer high-resolution detection of vaginal microbiome variations and community functional capabilities, which can shed light into several discrepancies observed in the vaginal microbiota of African women in an African population versus women of African descent in the diaspora.
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Background This study was designed to explore the profile and potential influencers of the vaginal microbiome (VMB) among asymptomatic pregnant Chinese women and its possible association with pregnancy outcomes. Methods A prospective study was conducted among pregnant Chinese women receiving regular prenatal care at a hospital in Shanghai, China from March 2017 to March 2018. Vaginal swabs were obtained from 113 asymptomatic pregnant women in mid-pregnancy and sequenced by the V3–V4 region of 16S rRNA on an Ion S5™ XL platform. Demographic characteristics and major pregnancy outcomes were collected through questionnaires and electronic medical records. Results The predominant vaginal community state types (CSTs) were CST I (45.1%) and CST III (31.9%). Participants were divided into a lactobacilli-dominant group (LD, CST I/II/III/I–III/V, n = 100, 88.5%) and a less lactobacilli-dominant group (LLD, CST IV-A/B, n = 13, 11.5%). Women in the LLD group showed an increased alpha diversity [median (interquartile range, IQR): 2.41 (1.67, 2.49) vs. 0.30 (0.17, 0.59), P < 0.001], which was related to a lower pre-pregnancy body mass index (BMI) ( P = 0.012), and a greater instance of passive smoking ( P = 0.033). The relative abundance of Lactobacillus was correlated positively with the pre-pregnancy BMI ( r = 0.177, P = 0.041), but negatively with passive smoking ( r = − 0.204, P = 0.030). Conclusion The vaginal flora of asymptomatic pregnant Chinese women was mostly dominated by Lactobacillus crispatus and L. iners . A lower BMI and greater instance of passive smoking may contribute to a less lactobacilli-dominant VMB. However, a larger sample size is needed.
Das intestinale Mikrobiom hat offensichtlich große Auswirkungen auf die Gesundheit der Frau. Es hat Einfluss auf die Ausprägung von postmenopausalen Beschwerden, indem es die Bildung von Phytoöstrogenen aus der Nahrung fördert. Ferner wird Übergewicht entscheidend durch die Zusammensetzung der Darmflora beeinflusst, mit der Nahrung aufgenommene prokarzinogene Stoffe können metabolisiert werden, die zuverlässige Wirksamkeit der oralen Kontrazeption wird erst durch Darmbakterien gewährleistet, die in der Leber entstandene Glukuronkonjugate der Östrogene spalten. Manche Darmkeime schützen den Menschen vor einer manifesten Erkrankung durch C. difficile, indem sie die Gallensäuren degradieren, welche die Sporen der Erreger zum Auskeimen benötigen. Im vaginalen Mikrobiom gibt es mindestens 4 Populationstypen, die jeweils von verschiedenen Lactaobazillenspecies dominiert werden, und einem zusätzlichen Typ, bei dem Laktobazillen fehlen. In der Schwangerschaft ist diese Typenkonstellation aufgehoben und es finden sich ganz überwiegend L. iners, auch in der Postmenopause lässt sich diese Einteilung nicht mehr nachweisen. Das Endometrium ist nicht steril, eine gestörte Bakterienpopulation kann die Implantation der Eizelle behindern. Auch die Plazenta ist nicht steril, dort können Keime eine Frühgeburtlichkeit bedingen. Diese ersten Ergebnisse der neuen Methoden der Mikrobiologie sind noch nicht vollständig verstanden; zu erwarten ist, dass die Zusammenhänge zwischen dem Mikrobiom und der Gesundheit der Frau noch besser erforscht werden.
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Background Characterizing microbial communities via next-generation sequencing is subject to a number of pitfalls involving sample processing. The observed community composition can be a severe distortion of the quantities of bacteria actually present in the microbiome, hampering analysis and threatening the validity of conclusions from metagenomic studies. We introduce an experimental protocol using mock communities for quantifying and characterizing bias introduced in the sample processing pipeline. We used 80 bacterial mock communities comprised of prescribed proportions of cells from seven vaginally-relevant bacterial strains to assess the bias introduced in the sample processing pipeline. We created two additional sets of 80 mock communities by mixing prescribed quantities of DNA and PCR product to quantify the relative contribution to bias of (1) DNA extraction, (2) PCR amplification, and (3) sequencing and taxonomic classification for particular choices of protocols for each step. We developed models to predict the “true” composition of environmental samples based on the observed proportions, and applied them to a set of clinical vaginal samples from a single subject during four visits. Results We observed that using different DNA extraction kits can produce dramatically different results but bias is introduced regardless of the choice of kit. We observed error rates from bias of over 85% in some samples, while technical variation was very low at less than 5% for most bacteria. The effects of DNA extraction and PCR amplification for our protocols were much larger than those due to sequencing and classification. The processing steps affected different bacteria in different ways, resulting in amplified and suppressed observed proportions of a community. When predictive models were applied to clinical samples from a subject, the predicted microbiome profiles were better reflections of the physiology and diagnosis of the subject at the visits than the observed community compositions. Conclusions Bias in 16S studies due to DNA extraction and PCR amplification will continue to require attention despite further advances in sequencing technology. Analysis of mock communities can help assess bias and facilitate the interpretation of results from environmental samples. Electronic supplementary material The online version of this article (doi:10.1186/s12866-015-0351-6) contains supplementary material, which is available to authorized users.
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Preterm birth is a major cause of neonatal morbidity and mortality in both developed and developing countries. Preterm birth is a highly complex syndrome that includes distinct clinical subtypes in which many different causes may be involved. The results of epidemiological, molecular, microbiological and animal-model studies support a positive association between maternal periodontal disease and preterm birth. However, the results of intervention studies carried out to determine the effect of periodontal treatment on reducing the risk of preterm birth are controversial. This systematic review critically analyzes the methodological issues of meta-analyses of the studies to determine the effect of periodontal treatment to reduce preterm birth. The quality of the individual randomized clinical trials selected is of highest relevance for a systematic review. This article describes the methodological features that should be identified a priori and assessed individually to determine the quality of a randomized controlled trial performed to evaluate the effect of periodontal treatment on pregnancy outcomes. The AMSTAR and the PRISMA checklist tools were used to assess the quality of the six meta-analyses selected, and the bias domain of the Cochrane Collaboration's Tool was applied to evaluate each of the trials included in the meta-analyses. In addition, the methodological characteristics of each clinical trial were assessed. The majority of the trials included in the meta-analyses have significant methodological flaws that threaten their internal validity. The lack of effect of periodontal treatment on preterm birth rate concluded by four meta-analyses, and the positive effect of treatment for reducing preterm birth risk concluded by the remaining two meta-analyses are not based on consistent scientific evidence. Well-conducted randomized controlled trials using rigorous methodology, including appropriate definition of the exposure, adequate control of confounders for preterm birth and application of effective periodontal interventions to eliminate periodontal infection, are needed to confirm the positive association between periodontal disease and preterm birth.
Screening for asymptomatic bacteriuria is a standard of obstetrical care and is included in most antenatal guidelines. There is good evidence that treatment of asymptomatic bacteriuria will decrease the incidence of pyelonephritis. All pregnant women should be screened for asymptomatic bacteriuria, and there are no new data that would indicate otherwise. Antibiotic treatment of asymptomatic bacteriuria is associated with a decrease in the incidence of preterm delivery or low birth weight, but the methodological quality of the studies means any conclusion about the strength of this association needs to be drawn cautiously. A better understanding of the mechanism by which treatment of asymptomatic bacteriuria could prevent preterm delivery is needed. While several rapid screening tests have been evaluated, none perform adequately to replace urine culture for detecting asymptomatic bacteriuria. Until there are data from well-designed trials that establish the optimal duration of therapy for asymptomatic bacteriuria, standard treatment courses are recommended.