Partial restoration of the microbiota of cesarean-born infants via vaginal microbial transfer

Maria G Dominguez-Bello, Kassandra M De Jesus-Laboy, Nan Shen, Laura M Cox, Amnon Amir, Antonio Gonzalez, Nicholas A Bokulich, Se Jin Song, Marina Hoashi, Juana I Rivera-Vinas, Keimari Mendez, Rob Knight, Jose C Clemente, Maria G Dominguez-Bello, Kassandra M De Jesus-Laboy, Nan Shen, Laura M Cox, Amnon Amir, Antonio Gonzalez, Nicholas A Bokulich, Se Jin Song, Marina Hoashi, Juana I Rivera-Vinas, Keimari Mendez, Rob Knight, Jose C Clemente

Abstract

Exposure of newborns to the maternal vaginal microbiota is interrupted with cesarean birthing. Babies delivered by cesarean section (C-section) acquire a microbiota that differs from that of vaginally delivered infants, and C-section delivery has been associated with increased risk for immune and metabolic disorders. Here we conducted a pilot study in which infants delivered by C-section were exposed to maternal vaginal fluids at birth. Similarly to vaginally delivered babies, the gut, oral and skin bacterial communities of these newborns during the first 30 d of life was enriched in vaginal bacteria--which were underrepresented in unexposed C-section-delivered infants--and the microbiome similarity to those of vaginally delivered infants was greater in oral and skin samples than in anal samples. Although the long-term health consequences of restoring the microbiota of C-section-delivered infants remain unclear, our results demonstrate that vaginal microbes can be partially restored at birth in C-section-delivered babies.

Figures

Figure 1. Restoring the maternal microbiota in…
Figure 1. Restoring the maternal microbiota in infants born by C-section
(a) Infants born by C-section were swabbed with a gauze that was incubated in the maternal vagina 30–60 min prior to the C-section. All mothers delivering by C-section received antibiotics (ABX) as part of standard of care. The gauze was extracted prior to the procedure, kept in a sterile container, and used to swab the newborn within the first one to three minutes after birth, starting with the mouth, face, and rest of the body. (b) Proportion of each sample estimated to originate from different maternal sources (using bacterial sourcetracking) of anal (top row), oral (middle), and skin (bottom) samples in infants delivered either vaginally (left column, n = 7 subjects sampled at six time points), by C-section (unexposed) (right, n = 8 × 6), or by C-section and exposed to vaginal fluids (middle, n = 4 × 6). (c) Bacterial community distances in anal (left), oral (middle), and skin (right) samples between vaginally delivered and C-section-delivered exposed (I-V) or not exposed (C-V) to the vaginal gauze, during the first month of life (Unweighted UniFrac distances). Bars indicate standard deviation from the mean. Distances between vaginal and exposed C-section infants were significantly smaller than from unexposed C-section infants (ANOVA and Tukey’s honest significant difference test. * P < 0.01) (d) Representative bacterial taxa enriched in infants with perinatal exposure to vaginal fluids during the first month of life. Bars indicate standard deviation from the mean.
Figure 2. Transmission of maternal vaginal microbes…
Figure 2. Transmission of maternal vaginal microbes to the gauze
(a) Principal coordinate analysis of unweighted UniFrac community distances for maternal anal, oral, skin, and vaginal microbiota (n = 95 samples) and gauze (n = 4) microbiota at day one. Vaginal gauze bacteria resemble vaginal communities. Arrows indicate vaginal samples from mothers exposed to antibiotics. (b) Bacterial community distances between gauzes and each maternal body site at day one. Bars indicate standard deviation from the mean. (c) Proportion of gauze samples estimated to originate from different maternal sources using bacterial sourcetracking. Each stacked bar represents a gauze sample from a different mother. Oral samples were not found to be a potential source for any gauze and are not indicated in the legend. (d) Bacterial diversity (Faith’s phylogenetic diversity) of maternal vaginal microbiota in mothers that received (n = 13) or did not receive (n = 5) antibiotics prior to vaginal sampling before delivery. (e) Relative abundance of bacterial genera in the vaginal microbiota in mothers that received (n = 13) or did not receive (n = 5) antibiotics prior to vaginal sampling before delivery.

References

    1. Dominguez-Bello MG, et al. Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns. Proc Natl Acad Sci U S A. 2010;107:11971–11975.
    1. Olszak T, et al. Microbial exposure during early life has persistent effects on natural killer T cell function. Science. 2012;336:489–493.
    1. Cox LM, et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell. 2014;158:705–721.
    1. Thavagnanam S, Fleming J, Bromley A, Shields MD, Cardwell CR. A meta-analysis of the association between Caesarean section and childhood asthma. Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology. 2008;38:629–633.
    1. Pistiner M, Gold DR, Abdulkerim H, Hoffman E, Celedon JC. Birth by cesarean section, allergic rhinitis, and allergic sensitization among children with a parental history of atopy. J Allergy Clin Immunol. 2008;122:274–279.
    1. Huh SY, et al. Delivery by caesarean section and risk of obesity in preschool age children: a prospective cohort study. Archives of disease in childhood. 2012;97:610–616.
    1. Sevelsted A, Stokholm J, Bonnelykke K, Bisgaard H. Cesarean section and chronic immune disorders. Pediatrics. 2015;135:e92–e98.
    1. Gibbons L, et al. The Global Numbers and Costs of Additionally Needed and Unnecessary Caesarean Sections Performed per Year: Overuse as a Barrier to Universal Coverage. World Health Report. 2010;30
    1. Finger C. Caesarean section rates skyrocket in Brazil. Many women are opting for caesareans in the belief that it is a practical solution. Lancet. 2003;362:628.
    1. Barber EL, et al. Indications contributing to the increasing cesarean delivery rate. Obstetrics and gynecology. 2011;118:29–38.
    1. Appropriate technology for birth. Lancet. 1985;2:436–437.
    1. Clemente JC, et al. The microbiome of uncontacted Amerindians. Science Advances. 2015;1
    1. Knights D, et al. Bayesian community-wide culture-independent microbial source tracking. Nat Methods. 2011;8:761–763.
    1. Knights D, Parfrey LW, Zaneveld J, Lozupone C, Knight R. Human-associated microbial signatures: examining their predictive value. Cell Host Microbe. 2011;10:292–296.
    1. Backhed F, et al. Dynamics and Stabilization of the Human Gut Microbiome during the First Year of Life. Cell Host Microbe. 2015;17:690–703.
    1. Yatsunenko T, et al. Human gut microbiome viewed across age and geography. Nature. 2012;486:222–227.
    1. Pantoja-Feliciano IG, et al. Biphasic assembly of the murine intestinal microbiota during early development. Isme J. 2013;7:1112–1115.
    1. Fardini Y, Chung P, Dumm R, Joshi N, Han YW. Transmission of diverse oral bacteria to murine placenta: evidence for the oral microbiome as a potential source of intrauterine infection. Infection and immunity. 2010;78:1789–1796.
    1. Aagaard K, et al. The placenta harbors a unique microbiome. Science translational medicine. 2014;6:237ra265.
    1. Caporaso JG, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335–336.
    1. Rideout JR, et al. Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences. Peer J. 2014;2:e545.
    1. McDonald D, et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. Isme J. 2012;6:610–618.
    1. Faith DP, Baker AM. Phylogenetic diversity (PD) and biodiversity conservation: some bioinformatics challenges. Evolutionary bioinformatics online. 2006;2:121–128.
    1. Lozupone C, Knight R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol. 2005;71:8228–8235.
    1. Langille MG, et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol. 2013;31:814–821.
    1. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Molecular biology and evolution. 2013;30:772–780.

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