Jacques RavelInstitute for Genome Sciences
Dept. of Microbiology and ImmunologyUniversity of Maryland School of Medicine
The Vaginal Microbiota in Health and Disease
UMD OMICS DAY - May 22, 2012
The Human Microbiota
The importance of the human microbiota in health and disease is now well-established.
Without understanding the interactions between our human and microbial genomes, it is impossible to obtain a complete picture of our biology
Our adult bodies harbor ~10 times more microbial cells than human cells – a significant number of these species have not been successfully grown in culture
The “human genome” is an amalgam of human genes and the genes of our microbial partners
The mechanisms are not well characterized: low pH (≤4.5) lactate other organic acids bacteriocins others
Albert Siegmund Gustav Döderlein, [German obstetrician and gynecologist, 1860–1941],
first described the “Döderlein bacillus” in 1894.
Common wisdom about the human vagina
Lactobacillus spp. are characteristic of vaginal microbiota in “normal” healthy reproductive age women.
Growth of non-indigenous organisms, including pathogens, is restricted.
Taxonomic Marker Genes - 16S rRNA gene
16S rRNA
Microbial identification
16S rRNA gene - Universal
16S rRNA ➙ Bacteria and Archaea
16S rRNA gene nucleotide sequence is phylogenetically informative - One sequence - one species
cpn60 (Chaperonin-60, HSP60, GroEL) or recA are also good alternatives
454 Pyrosequencing
The vaginal microbiota in asymptomatic women
• Four ethnic groups equally represented:
• Caucasian, Black, Hispanic, Asian
• Physician-collected mid-vaginal swabs
• Vaginal pH measurements (Inverness VpH glove)
• Nugent’s Gram stain scores
• Questionnaire (health and sexual history, hygiene...)
• Determine bacterial community composition by 454 pyrosequencing of
barcoded V1-V2 16S rRNA gene
Ravel et al. The vaginal microbiome of reproductive age women. PNAS. 2011. 108 Suppl 1, 4680–4687.Forney LJ, et al. (2010) Comparison of self-collected and physician-collected vaginal swabs for microbiome analysis. J. Clin. Microbiol. 48(5):1741-1748.
Cross sectional study of 410 asymptomatic healthy women
L. inersL. crispatus
L. gasseriL. jenseniiPrevotella
MegasphaeraSneathia
AtopobiumStreptococcus
DialisterLachnospira
AnaerococcusPeptoniphilus
EggerthellaFinegoldia
RhodobacaAnaerotruncus
UreaplasmaMycoplasmaAerococcusParvimonas
StaphylococcusCorynebacterium
VeillonellaL.vaginalis
0 20 40 60 80% abundance
Clusters
pH
Nugent Score
100
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Nugent Score
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pH
A.
B.
C.
D.
E.
F.
Clusters
01
23
4
Shan
non
Div
ersi
ty In
dex
Vaginal community state types (CST)
Ravel et al. The vaginal microbiome of reproductive age women. PNAS. 2011. 108 Suppl 1, 4680–4687.
• Five community state types that differ in their microbial composition and abundance
• Community state type IV lacks significant number of Lactobacillus
IVIIIIII V
Asian (96)
IV
42.7%42.7%
19.8%25%
5.2%
7.3% V
I
II
III
White (97)
26.8%
10.3%
45.4%
8.2%
9.3% IV
V
I
II
III
Black (104)
31.4%
40.4%
22.1%
4.8%
IV
1% V
I
II
III
Hispanic (97)
36.1%
38.1%
14.4%
7.2% IV
4.1% V
I
II
III
Community state types and ethnic groups
Ravel et al. The vaginal microbiome of reproductive age women. PNAS. 2011
The vaginal community space
A plot of principle component analysis (PCA) shows distribution of community states in 3-D space.
Graphics generated with inVUE (inVUE.sourceforge.net)
CST III(L. iners)
CST I(L. crispatus)
CST V(L. jensenii)
CST II(L. gasseri)
CST IV
• Several microbial community states are found in human vaginas that differ in terms of
bacterial species composition/abundance
• The frequency of each CST differs among women of different ethnicity
• At any given time, about 25% of women are in a non-lactobacillus state.
• How long does this state persist over time? How frequently does the vaginal microbiota
of a women is in this state?
Conclusions
Longitudinal studies of the vaginal microbiota
33 women self-collected vaginal smears and swabs were obtained twice-weekly (1,107 samples total) for 16 weeks
Daily diaries mailed to the lab weekly
Analyze community composition by 454 pyrosequencing of barcoded 16S rRNA genes (V1-V2 region)
Longitudinal studies of the vaginal microbiotaStudy design
1063 samples extracted (out of 1,107)
>3.5 million sequence reads of the V1-V2 region of 16S rRNA gene (avg. 240-316 bp)
Gajer et al. The temporal dynamics of the vaginal microbiota. Science Translational Medicine. 2012. 4(132): 132ra52.
Community State vs. Community State Type
Gajer et al. The temporal dynamics of the vaginal microbiota. Science Translational Medicine. 2012. 4(132): 132ra52.
Profile of Vaginal Community State Types
Profile of vaginal CSTs
Gajer et al. The temporal dynamics of the vaginal microbiota. Science Translational Medicine. 2012. 4(132): 132ra52.
Vaginal Community Classes
LI
LG
LC
DA
DB
Community State Types,9ï$ ,9ï%
Normalized Jensen-Shannondivergence
0.4 0.5 0.6 0.7 0.8 0.9NugentScore
333231302928272625242322212019181716151413121110987654321
0 5 10 15
Time (weeks)
Com
mun
ity
clas
ses
0 2 4 6 8
I II III
Subjects
IIIII
IV!BIV!AI
Proportions of community
state types
a b c d e f
0 20 40 60 80 100
Percent abundance
10
Gajer et al. The temporal dynamics of the vaginal microbiota. Science Translational Medicine. 2012. 4(132): 132ra52.
LI
LG
LC
DA
DB
Community State Types,9ï$ ,9ï%
Normalized Jensen-Shannondivergence
0.4 0.5 0.6 0.7 0.8 0.9NugentScore
333231302928272625242322212019181716151413121110987654321
0 5 10 15
Time (weeks)
Com
mun
ity
clas
ses
0 2 4 6 8
I II III
Subjects
IIIII
IV!BIV!AI
Proportions of community
state types
a b c d e f
0 20 40 60 80 100
Percent abundance
10
LI
LG
LC
DA
DB
Community State Types,9ï$ ,9ï%
Normalized Jensen-Shannondivergence
0.4 0.5 0.6 0.7 0.8 0.9NugentScore
333231302928272625242322212019181716151413121110987654321
0 5 10 15
Time (weeks)
Com
mun
ity
clas
ses
0 2 4 6 8
I II III
Subjects
IIIII
IV!BIV!AI
Proportions of community
state types
a b c d e f
0 20 40 60 80 100
Percent abundance
10
L. gasseriStreptococcusCorynebacteriumStaphylococcusFinegoldiaPrevotellaBifidobacteriumDermabacterMicrobacteriumShigella
Subject 10
0
20
40
60
80
100Phylotypes
L. gasseriStreptococcusCorynebacteriumStaphylococcusFinegoldiaPrevotellaBifidobacteriumDermabacterMicrobacteriumShigella
0.00.10.2
Time (weeks)0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Menses Tampon Douching
Nugent [low,intermediate,high]
Vaginal Intercourse Anal Sex Oral Sex Digital Penetration | | | | | | | | | | | | | | |Sex Toy Lubricant
DJS t6 6
Phyl
otyp
e re
lativ
e ab
unda
nce
(%)
L. crispatusL. inersL. jenseniiStaphylococcusL.unclassifiedL. gasseriLactobacillales.3ClostridiumCorynebacteriumL.otu2
Subject 8
0
20
40
60
80
100PhylotypesL. crispatusL. inersL. jenseniiStaphylococcusL. unclassifiedL. gasseriLactobacillales.3ClostridiumCorynebacteriumL.otu2
0.00.10.2
Time (weeks)0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Menses Tampon Douching
Nugent [low,intermediate,high]
Vaginal Intercourse Anal Sex Oral Sex Digital Penetration | | | | | | | | | | | | | | | |Sex Toy % % % % %Lubricant
DJS t6 6
Phyl
otyp
e re
lativ
e ab
unda
nce
(%)
L. inersStreptococcusCorynebacteriumFinegoldiaL.unclassifiedL. crispatusAtopobiumPrevotellaPeptoniphilusAnaerococcus
Subject 32
0
20
40
60
80
100PhylotypesL. inersStreptococcusCorynebacteriumFinegoldiaL.unclassifiedL. crispatusAtopobiumPrevotellaPeptoniphilusAnaerococcus
0.000.040.08
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Menses Tampon Douching
Nugent [low,intermediate,high]
Vaginal Intercourse Anal Sex Oral Sex Digital Penetration Sex Toy Lubricant
Time (weeks)
Phyl
otyp
e re
lativ
e ab
unda
nce
(%)
DJS t6 6
L. inersL. jenseniiL. gasseriL.unclassifiedUreaplasmaLactobacillales.7L.otu7CorynebacteriumLactobacillales.2Staphylococcus
Subject 33
0
20
40
60
80
100Phylotypes
L. inersL.jenseniiL.gasseriL.unclassifiedUreaplasmaLactobacillales.7L.otu7CorynebacteriumLactobacillales.2Staphylococcus
0.00
0.01
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Menses Tampon Douching
Nugent [low,intermediate,high]
Vaginal Intercourse Anal Sex Oral Sex Digital Penetration | | |Sex Toy Lubricant
Time (weeks)
Phyl
otyp
e re
lativ
e ab
unda
nce
(%)
DJS t6 6
Longitudinal profiles - relative high stability
LI LI LC
LG
Atopobium
Sneathia
Ruminococcaceae.1
L.iners
Gardnerella
Prevotella
Megasphaera
Aerococcus
Eggerthella
Gemella
Subject 11
0
20
40
60
80
100 PhylotypeAtopobiumSneathiaRuminococcaceae.1L.inersGardnerellaPrevotellaMegasphaeraAerococcusEggerthellaGemella
0.000.040.080.12 6DJS 6t
weeks0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Menses Tampon Douching
Nugent [low,intermediate,high]
Vaginal Intercourse Anal Sex Oral Sex Digital Penetration Sex Toy % % %Lubricant
IV-B
L. crispatusStreptococcusL.otu5BifidobacteriumAnaerococcusPrevotellaFinegoldiaPeptostreptococcusScardoviaLachnospiraceae.8Shigella
Subject 5
0
20
40
60
80
100Phylotypes
L. crispatusStreptococcusL.otu5BifidobacteriumAnaerococcusPrevotellaFinegoldiaPeptostreptococcusScardoviaLachnospiraceae.8Shigella
0.0
0.1
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Menses Tampon Douching
Nugent [low,intermediate,high]
Vaginal Intercourse Anal Sex Oral Sex Digital Penetration | | | | | | | | |Sex Toy Lubricant
Time (weeks)
Phyl
otyp
e re
lativ
e ab
unda
nce
(%)
DJS t6 6
CorynebacteriumL.crispatusL.inersAnaerococcusPeptoniphilusPrevotellaL.gasseriFinegoldiaCampylobacterFacklamiaStreptococcusAurantimonadaceae.1
Subject 3
0
20
40
60
80
100 PhylotypeCorynebacteriumL.crispatusL.inersAnaerococcusPeptoniphilusPrevotellaL.gasseriFinegoldiaCampylobacterFacklamiaStreptococcusAurantimonadaceae.1
0.000.040.080.12
6DJS 6t
weeks0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Menses Tampon Douching
Nugent [low,intermediate,high]
Vaginal Intercourse Anal Sex Oral Sex Digital Penetration Sex Toy %Lubricant
Atopobium
L.iners
Gardnerella
Aerococcus
Prevotella
Megasphaera
Mobiluncus
Eggerthella
Parvimonas
Peptoniphilus
Subject 17
0
20
40
60
80
100 PhylotypeAtopobiumL.inersGardnerellaAerococcusPrevotellaMegasphaeraMobiluncusEggerthellaParvimonasPeptoniphilus
0.05
0.156DJS 6t
weeks0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Menses Tampon Douching
Nugent [low,intermediate,high]
Vaginal Intercourse Anal Sex Oral Sex Digital Penetration | | | | | |Sex Toy Lubricant
L.inersPrevotellaFinegoldiaL.gasseriAtopobiumPeptoniphilusL.unclassifiedAnaerococcusAerococcusGardnerellaStreptococcusPorphyromonas
Subject 29
0
20
40
60
80
100 PhylotypeL.inersPrevotellaFinegoldiaL.gasseriAtopobiumPeptoniphilusL.unclassifiedAnaerococcusAerococcusGardnerellaStreptococcusPorphyromonas
0.00.10.20.3
6DJS 6t
weeks0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Menses Tampon Douching
Nugent [low,intermediate,high]
Vaginal Intercourse Anal Sex Oral Sex Digital Penetration | |Sex Toy % %Lubricant
Longitudinal profiles - low stability
IV-A IV-B IV-B
LI LC
AtopobiumL. inersLachnospiraceae.2SneathiaRuminococcaceae.1Proteobacteria.21PrevotellaRuminococcaceae.2GardnerellaL.crispatusMegasphaeraRuminococcaceae.5MoryellaMycoplasma
Subject 18
0
20
40
60
80
100Phylotypes
AtopobiumL. inersLachnospiraceae.2SneathiaRuminococcaceae.1Proteobacteria.21PrevotellaRuminococcaceae.2GardnerellaL.crispatusMegasphaeraRuminococcaceae.5MoryellaMycoplasma
0.00.20.4
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Menses Tampon Douching
Nugent [low,intermediate,high]
Vaginal Intercourse Anal Sex Oral Sex Digital Penetration Sex Toy Lubricant
Time (weeks)
DJS t6 6
Phyl
otyp
e re
lativ
e ab
unda
nce
(%)
Vaginal community dynamicsL. crispatus to L. iners to diverse group transition
Menstrual cycle (days)
log(6
DJS
6t)
0 7 14 21 28
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Modeling Community Stability
Menstrual cycle (days)
log(6
DJS
6t)
0 7 14 21 28
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Estrogen
Progesterone
Gajer et al. The temporal dynamics of the vaginal microbiota. Science Translational Medicine. 2012. 4(132): 132ra52.
Conclusions - Implications
Microbiome is somewhat unique/personalized to a women (or group of women)
Different women, different kinds of communities
Different women, different changes over time
Understanding these changes has major implications in increasing diagnosis accuracies, hence decrease disease prevalence, as well as predicting susceptibility and risk to infections.
Might have to rethink women’s health and treatments
Future: personalized treatment - use prior information and prescribe treatment
Acknowledgments
Larry Forney
National Institutes of Health NIAID U01 - AI070921- R03-AI061131NIAID UH2 - AI083264
Pawel Gajer
Sara KoenigStacey McCulle
Guoyun Bai
Li Fu
Rebecca Brotman
Zaid Abdo
Maria Schneider
Xia Zhou
Joyce Sakamoto
Melissa Nandy
Hongqiu YangXue Zhong
Bishoy Michael
Bing Ma
Doug Fadrosh
Arthur Brady
Owen White
Elliot Drabek
Anup Mahurkar
Ursel Shütte
Jonathan Crabtree
Kevin AultShara Karlebach
Ligia Peralta Reshma Gorle
Matt Settles
Roxana Hickey
