Fetal development is a period of unparalleled cellular proliferation, tissue formation, and organ construction within the confines of the womb—a human incubator that surrounds the fetus with amniotic fluid and provides nourishment for growth and protection of vulnerable tissues (Agin, 2009). Although historically the womb and fetus have been considered sterile until birth or rupture of the amniotic sac, recent evidence shows that the womb is host to a diversity of microorganisms that closely resemble the mother’s oral microbial community (Aagaard et al., 2014; DiGiulio et al., 2008). In addition, nutrient exchange that occurs through active and passive transport from the mother’s circulation to the placenta—an organ that acts as a selective maternal–fetal barrier—can also include toxins and microbes that can gain direct entry into fetal circulation. Thus, microbes from the placenta, amniotic fluid, and umbilical cord blood provide a diverse array of exposures to the developing fetus. For this reason, evaluation of the antenatal microbiome (microbial composition at multiple sites during pregnancy) may provide insight into the developmental origins of disease that have not been identified. The purposes of this article are to (a) briefly introduce the microbiome, the antenatal microbiome, and the microbiome and fetal programming; (b) present findings from an integrative review designed to summarize and critically evaluate the current state of knowledge regarding the antenatal microbiome and the health of human offspring; and (c) discuss findings in light of implications for nursing science.
Microbes from the placenta, amniotic fluid, and umbilical cord blood provide a diverse array of exposures to the developing fetus
The microbiome (the community of microorganisms, including bacteria, fungi, and viruses, which reside upon and within the human body) has gained attention as an important modulator of health and disease (Moloney, Desbonnet, Clarke, Dinan, & Cryan, 2014). Researchers have characterized a unique “core” microbiome inhabiting the skin, mouth, gut, urogenital tract, and vagina of adults (The Human Microbiome Project Consortium, 2012), and many associations have been established between microbiota dysbiosis and chronic diseases, such as obesity (Turnbaugh et al., 2009), diabetes (Larsen et al., 2010), and metabolic syndrome (Zhang et al., 2010). Increasingly, investigations are designed to study the microbial composition in relation to specific body sites (e.g., vagina, placenta, gut, skin) because different conditions (e.g., moisture, pH) at each site are ideal for the proliferation of specific types of microbes and may be referred to as microbiota (Cox, Cookson, & Moffatt, 2013). However, there has been less attention given to evaluating the influence of the antenatal microbiome—the plethora of maternal and fetal microbial communities during pregnancy—on the short- and long-term health of the offspring.
Microbes from the placenta, amniotic fluid, and umbilical cord blood provide a diverse array of exposures to the developing fetus
Several emerging areas of investigation concerning the antenatal microbiome support the notion that interactions occur among the maternal microbiome (particularly the womb) and fetus throughout pregnancy. However, precise classifications of dysbiosis—an unhealthy change in microbial composition—by bacterial species, composition, or amount and mechanisms by which dysbiosis leads to altered health outcomes remain enigmatic. Recent advances in the detection of microbes have resulted in support against the longstanding dogma that the fetus develops in a sterile environment (Aagaard et al., 2014; Ardissone et al., 2014; Funkhouser & Bordenstein, 2013). Microbes that gain access to the fetus in utero are primarily thought to be detrimental, for example, TORCH infections (Toxoplasma gondii, other agents like Treponema pallidum, rubella virus, cytomegalovirus, and herpes simplex virus), because of their teratogenic effects. Others have argued that additional pathogens should also be considered related to pregnancy because of their potential for altering short- and long-term outcomes in exposed offspring (Newton, 1999; Waldorf & McAdams, 2013). The 2013 review by Waldorf and McAdams (2013) thoroughly delineates fetal outcomes associated with known pathogens, including fetal death, spontaneous abortion, and residual morbidity in offspring. Given the number of known pathogens that cross the placenta and alter fetal outcomes (at least 22), it is likely that nonpathogenic microbes also cross the placental barrier.
Several recent studies have characterized the vaginal microbiome in women with full-term, uncomplicated pregnancy as having low diversity and high stability of a dominant species, Lactobacillus (Aagaard et al., 2012; Walther-António et al., 2014). While Lactobacillus crispatus promotes stability of the normal vaginal microbiota during pregnancy, Lactobacillus gasseri and/or Lactobacillus iners predispose to the occurrence of abnormal vaginal microbiota (Verstraelen et al., 2009). The impact of abnormal vaginal microbiota on the developing fetus remains unknown. However, evidence suggests that dysbiosis of the vaginal microbiota is associated with adverse pregnancy outcomes and that varied species and compositions of bacteria are present in women that experience preterm labor (Bujold et al., 2008; DiGiulio et al., 2010; Nelson et al., 2009). The type and timing of antimicrobial treatment used to correct vaginal dysbiosis may also be significantly related to birth outcomes. For example, when metronidazole was solely used in the second trimester of pregnancy—as opposed to clindamycin—metronidazole was associated with a greater risk of preterm delivery in high-risk populations (Morency & Bujold, 2007).
It has been reported that preterm infants develop an alternate gut microbiome phenotype characterized by a dominance of Proteobacteria and lack of Bifidobacterium and Lactobacillus, which are two of the main bacterial genera in healthy-term infants (Barrett et al., 2013). This finding may have implications for the developing gut microbiome, as infants who are exclusively breastfed show an enrichment of Bifidobacterium, which aids in the utilization of oligosaccharides found in human milk (Costello, Stagaman, Dethlefsen, Bohannan, & Relman, 2012). Microbiome exposures at birth have also been linked with health outcomes—infants who are delivered by caesarean section instead of vaginally are more likely to have asthma, allergies, and diabetes later in life (Cho & Norman, 2013; Romero & Korzeniewski, 2013). Differences in the composition of microbiota have also been identified between infants born at home versus in the hospital, underscoring that the environment contributes to the initial colonization of the infant (Penders et al., 2006).
Other investigators have used an epidemiological approach to evaluate the relationship between maternal stress, smoking, and antibiotic exposure on specific disease outcomes, such as celiac disease in the infant, but have not conclusively determined that such relationships exist (Mårild, Ludvigsson, Sanz, & Ludvigsson, 2014). However, epidemiological studies that are focused on a single type of exposure may fail to identify the influence of synergistic exposures and the associated mechanisms that contribute to future altered health outcomes. Collectively, these findings suggest that there are maternal and fetal microbiome interactions that may affect fetal programming—the epigenetically regulated responses that allow an organism to adapt to environmental signals. Figure 1 summarizes a conceptual model that could be used to test hypotheses regarding the relationships between environmental exposures, maternal and fetal epigenome signatures, and microbiome composition. We propose that maternal antenatal environmental exposures, epigenome signature, and microbiome compositions contribute to birth outcomes and the initial programming (epigenome signature and microbiome) of the offspring. Throughout life, the offspring’s health will continue be influenced by their own environmental exposures, epigenome signature, and microbiome composition. To date, most microbiome studies have been retrospective and/or lack the longitudinal data necessary to make inferences that changes in microbial composition cause disease or to fully decipher the complex relationship among environment, microbiome composition, and health status (Tyler, Smith, & Silverberg, 2014). Although we are far from understanding the precise mechanisms by which these interactions influence health, there is reason to believe that there is a certain degree of plasticity involved in fetal programming that may prove amenable to therapeutic strategies particularly related to environmental influences.
Microbiome and Fetal Programming
Fetal (or prenatal) programming is the influence of endogenous and exogenous exposures during development of the embryo and fetus that impact local fetal cellular environments resulting in changes in the phenotype (Agin, 2009). These changes can potentially impact the construction and function of tissues and organs, including systems that affect behavior, neuroendocrine and immune responses, and metabolic homeostasis, resulting in short- and/or long-term alterations in health. Studies that have evaluated folic acid supplementation during pregnancy have established that nutrition can have a dramatic impact on inheritance not by changing the DNA sequence of a gene or via single nucleotide polymorphisms but by changing the methylation pattern of that gene (Waterland & Jirtle, 2003). The concept of fetal programming and the developmental origins of health and disease arose from studies that followed pregnant mothers and infants who survived the Dutch “Hunger Winter.” David Barker first identified an association with nutrient deprivation of the mother during pregnancy with the development of cardiovascular disease of the offspring who endured undernutrition in utero (Barker, 1995). Subsequently, scientists have also identified other alterations in future health outcomes in offspring exposed to famine in utero, including obesity (Ravelli, van Der Meulen, Osmond, Barker, & Bleker, 1999), perception of health (Roseboom et al., 2003), and clotting factors (Roseboom et al., 2000). Other exposures in utero have also been associated with altered health outcomes offspring, such as type 2 diabetes (Simeoni & Barker, 2009) and alteration in the epigenome signatures in offspring with unknown consequences (Dolinoy, Huang, & Jirtle, 2007; Loke et al., 2013; Pilsner et al., 2009; Vidal et al., 2013).
In addition to the influence of nutrients and diet on fetal health, the microbiome—particularly the gut microbiome of the mother and/or fetus—can contribute to variation in health outcomes. For example, there has also been a significant amount of work investigating the transmission of the human immunodeficiency virus (HIV) from mother to child that is beyond the scope of this review. However, it should be noted that some infants are indeed infected with HIV in utero (Dickover et al., 1994), indicating that HIV virus is also capable of crossing the placental barrier. Furthermore, infants born to HIV-infected mothers who are not infected in utero or during delivery develop different T-cell profiles than children born to uninfected mothers (Lamers et al., 1994), suggesting that maternal infections may contribute to fetal programming even without direct microbial exposure. Furthermore, several microbes can produce substances that are used in various biological pathways involving human health. For example, certain bacterial microorganisms, such as Lactobacillus species, are able to convert nitrate to nitric oxide, a potent regulator of the nervous and immune systems. Bacteria can also generate neurotransmitters and neuromodulators—Lactobacillus species and Bifidobacterium species are known to produce GABA, whereas Bacillus species and Saccharomyces species produce noradrenalin (Cryan & Dinan, 2012). The precise interactions between the maternal and fetal microbiome and the mechanisms that lead to variation in health outcomes have yet to be characterized. However, accumulating evidence suggests that the antenatal microbiome is an important mediator of health outcomes of the offspring and that certain exposures during pregnancy can alter the microbiome and potentially increase vulnerability to the risk of chronic disease.
In order to advance understanding of the influence of the antenatal microbiome on health of the offspring, an integrative review was conducted. Research of microbial communities related to human health has largely increased in recent years because of the improved technology used to identify microbiomes via sequencing methods. Previous culture-based methods were limited because microbial species could only be studied if they could be grown in the laboratory. Currently, sequence-based technologies capitalize on the fact that a small subunit of bacterial ribosomal RNA is highly variable but highly conserved between species and can be used for identification purposes. Table 1 summarizes some terms frequently used in the microbiome literature. Several reviews of microbiome methods have been published and are available for a more detailed description of sequencing methodology (Cox et al., 2013; Sherman, Minnerly, Curtiss, Rangwala, & Kelley, 2014; Tyler et al., 2014). The aims of this integrative review were to summarize and critically evaluate the current state of knowledge regarding the assessment of the antenatal microbiome on the health of human offspring.
An integrative review was conducted to examine human research studies that focused on the relationship between the antenatal (maternal and fetal) microbiome on health outcomes of the offspring. The search of the electronic databases PubMed/MEDLINE and CINAHL from 2004 to the present used key words “microbiome,” “microbiota,” “antenatal period,” “pregnancy,” “offspring,” and “birth outcomes.” Manual searches were also completed using references from previously published studies and literature reviews. Articles that were retrieved via these multiple search methods (n = 254) were reviewed for duplication and for whether they met the following inclusion criteria: (a) research studies that involved human participants with a primary aim of assessing the relationship between the human microbiome during pregnancy and health outcomes of the offspring; (b) studies that reported clear methodologies for measuring the microbiome; and (c) studies written in English within the last 10 years (see Figure 2 for process of the literature selection). A total of 20 articles met the inclusion criteria and are included in this review (Tables 2–4).
Medications Including Antibiotic Exposures
The four studies identified in the literature review were focused on the effect of medications (mostly antibiotics) on the microbiome of premature infants in all of the studies. The studies indicate that premature neonates exposed to antibiotic therapy were more likely to have less diverse gut microbiome composition and a higher risk of infection and mechanical ventilation (Madan et al., 2012; Milisavljevic et al., 2013; Moles et al., 2013; Stewart et al., 2013). No additional studies were identified that assessed medication exposure during pregnancy on the microbiome or health of the fetus later in life.
There were three publications that focused on maternal comorbidities, meconium/fecal microbiome, and infant health outcomes. Gosalbes et al. (2013) found that the gut microbiome of infants was less diverse in mothers with atopic eczema, whereas meconium with more lactic acid was associated with respiratory problems in infants. Hu et al. (2013) reported that the most robust predictor of the infant gut microbiome was maternal diabetes status. Pozo-Rubio et al. (2013) found no significant differences in the gut microbiome of infants who had a first-degree relative with celiac disease compared to those who did not; however, infants who were exposed to antibiotics had altered microbiome composition of the gut. These studies suggest that some maternal comorbidities may alter the gut microbiome of the fetus and infant, potentially conferring risk of chronic disease in later life. More data on the specific diagnoses, severity of disease, and treatments used will be necessary to fully understand the influence on health outcomes of the offspring.
Most studies (10/13) to date have evaluated probiotic therapy during the antenatal, prenatal, or postnatal period on health outcomes, ranging from weight/obesity to allergies/eczema. One study set out to determine if fetal ingestion of amniotic fluid resulted in intestinal colonization that would result in inflammation and preterm birth but did not asses long-term health implications for the offspring or diet of the mother per se (Ardissone et al., 2014). Several studies only evaluated the fecal composition of the infant with maternal exposure to probiotics—of these, several did not find any significant changes in the infant fecal microbiome, whereas others did. However, in one of the studies, the administration of probiotics during pregnancy was associated with altered gene expression associated with inflammatory responsiveness in both the placenta and neonatal gut (Rautava, Collado, Salminen, & Isolauri, 2012). The variation in probiotic composition, length, and dose of probiotic therapy make any generalization of the findings very difficult.
The discussion centers on the major findings of the integrative review relative to other microbiome research as well as considerations for future research. Overall, sample sizes for the studies were small (6–160 participants, with one study enrolling 1,223 pregnant women), observational (seven studies) or randomized control trials involving probiotics (10 studies) and contained variable results (12 studies identified significant differences and eight did not).
This review did not find any publications evaluating maternal medication exposures on the health of the offspring beyond those that assessed for the relationship between antibiotic exposure and risk to premature infants. Considering 94% of women will take at least one medication during pregnancy and 50% will take four or more medications, investigation of the impact of medication should be a high research priority (Mitchell et al., 2011). Of the studies that have investigated the short-term implications on the microbiome of the offspring, most have focused on the infant gut microbiome via meconium sampling. Given the study of the microbiome is in its infancy, it may be important to study the impact of the medication on other microbiome sites, because there remains much uncertainty in how different microbiome subcommunities interact with the human system to contribute to or serve as a biomarker for health outcomes. The studies currently presented in the literature have identified that medications will indeed have an impact on microbial compositions (Table 2). However, longitudinal studies with much larger sample sizes are needed to gain insights into interactions between multiple medications and other environmental factors that may influence microbial composition. Considering that the largest sample size we identified in the literature was 55, none of them have enough participants to accurately assess multiple outcomes or variables and, therefore, lack sufficient power to make a conclusive observation of association. Collectively, the studies to date support the need to assess medication exposures during pregnancy and the potential influence on the fetal microbiome when evaluating the relationship between microbiome alterations and health outcomes of the offspring.
Maternal comorbidities appear to have a significant impact on the antenatal microbiome and may confer disease risk to the fetus by presenting the same antecedents or conditions of the disease etiology (Table 3). All three studies that assessed the fetal microbiota in relation to preexisting maternal comorbidities found significant differences based on maternal health status. However, the sample sizes were small (20–55 infants), and the study evaluating infants with a first-degree relative with celiac disease did not have a control group (Pozo-Rubio et al., 2013). To date, a number of health conditions have been associated with variations in microbiome composition in other populations, including psoriasis (Gao, Tseng, Strober, Pei, & Blaser, 2008), gastrointestinal ailments (Garrett et al., 2010; Krisanaprakornkit et al., 2000; Tana et al., 2010), asthma (Chen & Blaser, 2007), cardiovascular disease (Wang et al., 2011), type 2 diabetes (Larsen et al., 2010), and obesity (Turnbaugh et al., 2009). It is likely that the microbial composition of the mother is shared with and influences the development of the offspring’s microbiome composition, and the composition of her microbiota is likely associated with her own health status (Funkhouser & Bordenstein, 2013; Song, Dominguez-Bello, & Knight, 2013). This sharing of microbial communities can result in the offspring developing similar comorbidities that may be modulated by the microbes that colonize them. For example, in animal models when otherwise healthy mice are given a fecal transplant containing feces from overweight mice, they become obese (Turnbaugh et al., 2009). The complexity of determining which compositions may be harmful or beneficial is vast, and because we do not fully understand the interrelationships between microbiome communities and human health, purposely disrupting this balance without knowing the long-term implications could be potentially devastating for future generations.
Stress (Cryan & Dinan, 2012), socioeconomic status (Ding & Schloss, 2014), and environmental exposures (Lozupone, Stombaugh, Gordon, Jansson, & Knight, 2012) are all known to contribute to microbiome variability and possible dysbiosis in humans. However, these factors were not considered in the research studies of the antenatal microbiome reviewed. For example, Ding and Schloss (2014) found that women with a bachelor’s degree or higher were more likely to have a vaginal microbiome associated with high levels of Lactobacillus. In their data set, they did not have the capability to determine which confounding factors associated with advanced education may be contributing to the altered compositions in vaginal microbiomes. One possible explanation is women of different socioeconomic status may have different environmental exposures that alter the microbiome, such as different diets or types of stress. Until additional studies are completed that assess various environmental and socioeconomic variables, it is difficult to hypothesize which factors may contribute synergistically.
Multiple reviews have identified altered microbiome compositions in patients with disease associated with stress (Cryan & Dinan, 2012; Stilling, Dinan, & Cryan, 2014; Wang & Kasper, 2014), although little is known on how the stress of a normal or complicated pregnancy contributes to variations in the antenatal microbiome. In one study investigating heritability of microbes, monozygotic and dizygotic twins appear to have equal similarities in gut microbiome compositions, indicating that a shared environment may be a stronger predictor of microbiome composition than genetic composition (Turnbaugh et al., 2009). Additional twin studies incorporating the use of meticulous biobehavioral measures may help determine how different shared environmental factors associated with different socioeconomic status are linked with various microbial niche communities.
Although there is very little information regarding how the maternal diet contributes to the antenatal microbiome, we identified multiple studies that have examined the use of probiotics in pregnant women. Several of the probiotic studies identified by this review found that factors, other than probiotics, were associated with changes in the infant gut microbiota (Cabrera-Rubio et al., 2012; Grönlund, Grześkowiak, Isolauri, & Salminen, 2011; Urwin et al., 2014) or that probiotics had no influence on the infant (Grönlund et al., 2011; Ismail et al., 2012; Kukkonen et al., 2007; Shadid et al., 2007). The remaining studies identified some significant difference in microbiota compositions (Lahtinen et al., 2009; Rinne, Kalliomäki, Salminen, & Isolauriet, 2006; Salvini et al., 2011), alterations in gene expression associated with immune function (Rautava et al., 2012), or a decrease in reported eczema up to 3 months of age that did not persist (Niers et al., 2009). The lack of consistency between studies suggests that multiple factors—not just the bacteria administered in the probiotics—contribute to the development of the microbiota composition in neonates and contribute to immune system development. For example, Wu et al. (2011) found that the long-term composition of gut microbiota is clustered by diet and that alterations in diet can significantly change microbial composition within 24 hours, although not enough to change the overall enterotype cluster of the individual. Furthermore, even though communities of microbes in the gut are highly variable between individuals, the functions different microbes carry out in different individuals are the same (Lozupone et al., 2012). Because we do not fully understand how multiple variables work in concert to support certain compositions of bacteria, it may be premature to try to alter them by adding or removing specific types of bacteria and may explain the variability in results of the probiotic studies. However, it is important to note that, when the initial bacterial composition in the gut within an animal model is purposely changed, it is associated with alteration in immune programming and inflammatory response later in life (Olszak et al., 2012). Given intervention studies have already been done, this area of exploration may benefit from longitudinal designs in women with and without probiotic exposure—with examination of the maternal and fetal microbiome and health outcomes over time. Future studies evaluating the actual diets of women, without a probiotic intervention, may be beneficial for improving our understanding of how the microbiome interacts with the host diet and how it contributes to the antenatal microbiome and microbiome of the offspring. In addition, consideration of the chemicals and microbes in the food supply consumed by pregnant women and the influence on the antenatal microbiome and health outcomes of the offspring should be included in future research.
Antenatal Microbiome and Offspring Health
Few studies have assessed for the actual presence of bacteria in utero during healthy pregnancy. The probiotic study by Rautava et al. (2012) assessed for the presence of bacteria in placentas and amniotic fluids of women treated with probiotics during pregnancy and found bacterial DNA present in all placentas and 43% of amniotic fluid obtained during cesarean section. They also found that, when bacteria were present in the amniotic fluid, gene expression related to immune function was altered in the fetal gut. Furthermore, bacteria have been identified in meconium and umbilical cord blood of infants delivered via cesarean section, indicating that there is some passage of bacteria from mother to infant in utero, and it is unknown if these bacteria have any correlation to future health outcomes in the offspring (Gosalbes et al., 2013; Jiménez et al., 2005). The following discussion will include justification for further investigation of the factors affecting the antenatal microbiome and evaluating relationships to the health outcomes of the offspring.
Our understanding of the relationship between mother, offspring, and microbiome development may benefit by closer examination of the fetal compartment for microbes and plausible explanations for how it evolves. For example, dendritic cells may be involved in the process of introducing commensal bacteria to the fetus. Dendritic cells can pick up and hold bacteria and/or antigens from the intestines for a number of days and pull them into the lymphatic system (Macpherson & Uhr, 2004; Rescigno et al., 2001). Mesenteric lymph nodes in pregnant mice are 60% more likely to harbor bacteria than nonpregnant mice (Perez et al., 2007). Commensal bacteria and antigens that are in the lymphatic system may travel to the lymphatic system of the uterus. Lymphatic vessels have been identified in all regions of the placenta, including the area adjacent to the amniotic membrane, and it has been suggested that the abundance of dendritic cells at the maternal–fetal lymphatic interface may exist to present fetal antigens to the mother (Red-Horse, 2008). However, perhaps the converse is true and the dendritic cells are presenting antigens, including microbial antigens, to the fetus to which it will be exposed after birth (i.e., the initial programming of the fetal immune system). Investigations on the mechanisms of maternal transmission of microbes to the fetus and the influence on the health of the offspring are clearly warranted.
In addition, the mechanisms by which pathogens and nonpathogenic microbes influence health outcomes in later life are yet to be elucidated. It is possible that specific microbes differentially contribute to multiple mechanisms or disease pathways, which further add to the complexity of microbiome research. For example, the microbiome subcommunities appear to be unique to each individual, although the overall functional characteristics of microbiome communities are essentially the same (Ding & Schloss, 2014). This means that similar to redundancy seen when multiple DNA codons encode for the same amino acid, multiple species of bacteria can carry out the same functional roles related to microbiome composition. Until the baseline functional qualities of the microbiome are established, it may be difficult to determine which pathways are affected by alterations in composition. Previous studies in animal models and humans suggest that epigenome—specifically DNA methylation (Kellermayer et al., 2011; Olszak et al., 2012)—and hypothalamic–pituitary–adrenocortical axis alterations (Clarke et al., 2013; Diaz Heijtz et al., 2011; Gareau et al., 2011) may be associated with microbiome composition and changes (Figure 1).
Implications for Nursing Research
Advancements in understanding the unique contributions of the microbiome in health and disease provides new avenues to pursue in nursing research, particularly as it related to modulating health risks throughout the lifespan. As a discipline grounded in health promotion and disease prevention, nursing research offers a distinct lens from which to study the impact of the microbiome on person–health–environment interactions. At this stage of the science, many studies have focused on describing the composition of microbiota and detecting dysbiosis that may be associated with disease. However, accumulating evidence on the influence of the maternal microbiome on the epigenome of the developing infant suggests that it may play a significant role in fetal programming and the development of disease later in life. Although empirical evidence is needed to establish precise cause–effect relationships, the potential to mitigate disease risk by enhancing symbiotic conditions during development and in later life has many implications for nursing research.
Investigations focused on characterizing symbiosis and dysbiosis at various sites of the body will be a prerequisite for the development of assessment and monitoring technologies that can be used in practice. Research to understand the interplay between the microbiome, epigenome, and disease will inform nursing interventions that utilize microbiome modification strategies. Studies described in this review point to a wide range of environmental exposures that can alter an individual’s microbiome composition, including medications and diet. Given that the microbiome is modifiable, there is great potential to develop nursing interventions geared toward enhancing the protective capacity of the microbiome in states of health and prevent disease across the lifespan.
Because of the general sparsity of data in this area, there has been support from federal research agencies to improve our understanding of how the antenatal microbiome contributes to health outcomes. There are currently 34 studies funded by the National Institutes of Health listed in the National Institutes of Health RePORTer system (http://projectreporter.nih.gov/reporter.cfm) when “microbiome” and “pregnancy” are used as search terms. Of the 34 studies, four studies have been (Table 5) funded by the National Institute of Nursing Research, and multiple institutes continue to issue grant funding for this area of research (Table 6). Conducting interdisciplinary, clinically relevant research investigating the antenatal microbiome mirrors the National Institute of Nursing Research’s mission to incorporate new biological and behavioral science technologies into nursing science to promote and improve health. Enhancing our understanding of how the antenatal microbiome contributes to health outcomes in the offspring of pregnant women will provide a foundation for future development of preventative interventions and policy to protect the health of future generations. Investigations into this area of inquiry will likely require an innovative approach to protect the health of both mother and offspring. For example, observational studies investigating several simultaneous influences (e.g., stress, medications, microbiome, genetic sequence) with bioinformatics support to identify factors associated with disease risk may be preferred over intervention studies.
A deeper understanding of the influence of the antenatal microbiome on the health of the offspring may provide new insight on the origins of chronic disease as well as inform practice and healthcare decision-making. As shown in this review of the literature, multiple factors (maternal transmission of microbes, comorbidities, and diet) have been shown to be associated with alterations in the fetal environment during pregnancy with documented changes in fetal microbiome composition and disease risk in the offspring. Less attention has been focused on investigating the influence of medication exposures (including antibiotics) on the antenatal microbiome and the long-term implications on health outcomes of the offspring. Other areas that warrant further research were identified in the literature review. In particular, investigations that provide data on the antenatal microbiome composition over the course of pregnancy and incorporate mechanisms of fetal programming (epigenomics) have potential to greatly advance this area of research.
Aagaard K., Ma J., Antony K. M., Ganu R., Petrosino J., Versalovic J. (2014). The placenta harbors a unique microbiome. Science Translational Medicine
, 6, 237ra65. doi:10.1126/scitranslmed.3008599
Aagaard K., Riehle K., Ma J., Segata N., Mistretta T. A., Coarfa C., Versalovic J. ( 2012). A metagenomic approach to characterization of the vaginal micriobiome signature in pregnancy. PLOS ONE
, e36466. doi:10.1371/journal.pone.0036466
Agin D. ( 2009). More than genes: What science can tell us about toxic chemicals, development and the risk to our children
. Oxford, England: Oxford University Press.
Ardissone A. N., de la Cruz D. M., Davis-Richardson A. G., Rechcigl K. T., Li N., Drew J. C., Neu J. ( 2014). Meconium microbiome analysis identifies bacteria correlated with premature birth. PLOS ONE
, 9, e90784. doi:10.1371/journal.pone.0090784
Barker D. J. ( 1995). Fetal origins of coronary heart disease. BMJ (Clinical Research Ed.)
, 311, 171–174. doi:10.1136/bmj.311.6998.171
Barrett E., Kerr C., Murphy K., O’Sullivan O., Ryan C. A., Dempsey E. M., Stanton C. ( 2013). The individual-specific and diverse nature of the preterm infant microbiota. Archives of Disease in Childhood. Fetal and Neonatal Edition
, 98, F334–F340. doi:10.1136/archdischild-2012-303035
Bujold E., Morency A. M., Rallu F., Ferland S., Tétu A., Duperron L., Laferrière C. ( 2008). Bacteriology of amniotic fluid in women with suspected cervical insufficiency. Journal of Obstetrics and Gynaecology Canada
, 30, 882–887.
Cabrera-Rubio R., Collado M. C., Laitinen K., Salminen S., Isolauri E., Mira A. ( 2012). The human milk microbiome changes over lactation and is shaped by maternal weight and mode of delivery. America Journal of Clinical Nutrition
, 96, 544–551. doi:10.3945/[ZERO WIDTH SPACE]ajcn.112.037382
Chen Y., Blaser M. J. ( 2007). Inverse associations of Helicobacter pylori
with asthma and allergy. Archives of Internal Medicine
, 167, 821–827. doi:10.1001/archinte.167.8.821
Cho C. E., Norman M. ( 2013). Cesarean section and development of the immune system in the offspring. American Journal of Obstetrics and Gynecology
, 208, 249–254. doi:10.1016/j.ajog.2012.08.009
Clarke G., Grenham S., Scully P., Fitzgerald P., Moloney R. D., Shanahan F., Cryan J. F. ( 2013). The microbiome–gut–brain axis during early life regulates the hippocampal serotonergic system in a sex-dependent manner. Molecular Psychiatry
, 18, 666–673. doi:10.1038/mp.2012.77
Costello E. K., Stagaman K., Dethlefsen L., Bohannan B. J., Relman D. A. ( 2012). The application of ecological theory toward an understanding of the human microbiome. Science
, 336, 1255–1262. doi:10.1126/science.1224203
Cox M. J., Cookson W. O., Moffatt M. F. ( 2013). Sequencing the human microbiome in health and disease. Human Molecular Genetics
, 22, R88–R94. doi:10.1093/hmg/ddt398
Cryan J. F., Dinan T. G. ( 2012). Mind-altering microorganisms: The impact of the gut microbiota on brain and behaviour. Nature Reviews. Neuroscience
, 13, 701–712. doi:10.1038/nrn3346
Diaz Heijtz R., Wang S., Anuar F., Qian Y., Björkholm B., Samuelsson A., Pettersson S. ( 2011). Normal gut microbiota modulates brain development and behavior. Proceedings of the National Academy of Sciences of the United States of America
, 108, 3047–3052. doi:10.1073/pnas.1010529108
Dickover R. E., Dillon M., Gillette S. G., Deveikis A., Keller M., Plaeger-Marshall S., Bryson Y. ( 1994). Rapid increases in load of human immunodeficiency virus correlate with early disease progression and loss of CD4 cells in vertically infected infants. Journal of Infectious Diseases
, 170, 1279–1284. doi:10.1093/infdis/170.5.1279
DiGiulio D. B., Romero R., Amogan H. P., Kusanovic J. P., Bik E. M., Gotsch F., Relman D. A. ( 2008). Microbial prevalence, diversity and abundance in amniotic fluid during preterm labor: A molecular and culture-based investigation. PLOS ONE
, 3, e3056. doi:10.1371/journal.pone.0003056
DiGiulio D. B., Romero R., Kusanovic J. P., Gómez R., Kim C. J., Seok K. S., Relman D. A. ( 2010). Prevalence and diversity of microbes in the amniotic fluid, the fetal inflammatory response, and pregnancy outcome in women with preterm pre-labor rupture of membranes. American Journal of Reproductive Immunology
, 64, 38–57. doi:10.1111/j.1600-0897.2010.00830.x
Ding T., Schloss P. D. ( 2014). Dynamics and associations of microbial community types across the human body. Nature
, 509, 357–360. doi:10.1038/nature13178
Dolinoy D. C., Huang D., Jirtle R. L. ( 2007). Maternal nutrient supplementation counteracts bisphenol A-induced DNA hypomethylation in early development. Proceedings of the National Academy of Sciences of the United States of America
, 104, 13056–13061. doi:10.1073/pnas.0703739104
Funkhouser L. J., Bordenstein S. R. ( 2013). Mom knows best: The universality of maternal microbial transmission. PLOS Biology
, 11. doi:10.1371/journal.pbio.1001631
Gao Z., Tseng C. H., Strober B. E., Pei Z., Blaser M. J. ( 2008). Substantial alterations of the cutaneous bacterial biota in psoriatic lesions. PLOS ONE
, 3, e2719. doi:10.1371/journal.pone.0002719
Gareau M. G., Wine E., Rodrigues D. M., Cho J. H., Whary M. T., Philpott D. J., Sherman P. M. ( 2011). Bacterial infection causes stress-induced memory dysfunction in mice. Gut
, 60, 307–317. doi:10.1136/gut.2009.202515
Garrett W. S., Gallini C. A., Yatsunenko T., Michaud M., DuBois A., Delaney M. L., Glimcher L. H. ( 2010). Enterobacteriaceae act in concert with the gut microbiota to induce spontaneous and maternally transmitted colitis. Cell Host & Microbe
, 8, 292–300. doi:10.1016/j.chom.2010.08.004
Gosalbes M. J., Llop S., Vallès Y., Moya A., Ballester F., Francino M. P. ( 2013). Meconium microbiota types dominated by lactic acid or enteric bacteria are differentially associated with maternal eczema and respiratory problems in infants. Clinical and Experimental Allergy
, 43, 198–211. doi:10.1111/cea.12063
Grönlund M. M., Grześkowiak Ł., Isolauri E., Salminen S. ( 2011). Influence of mother’s intestinal microbiota on gut colonization in the infant. Gut Microbes
, 2, 227–233.
Hu J., Nomura Y., Bashir A., Fernandez-Hernandez H., Itzkowitz S., Pei Z., Peter I. ( 2013). Diversified microbiota of meconium is affected by maternal diabetes status. PLOS ONE
, 8, e78257. doi:10.1371/journal.pone.0078257
Ismail I. H., Oppedisano F., Joseph S. J., Boyle R. J., Robins-Browne R. M., Tang M. L. K. ( 2012). Prenatal administration of Lactobacillus rhamnosus
has no effect on the diversity of the early infant gut microbiota. Pediatric Allergy and Immunology
, 23, 255–258. doi:10.1111/j.1399-3038.2011.01239.x
Jiménez E., Fernández L., Marín M. L., Martín R., Odriozola J. M., Nueno-Palop C., Rodríguez J. M. ( 2005). Isolation of commensal bacteria from umbilical cord blood of healthy neonates born by cesarean section. Current Microbiology
, 51, 270–274. doi:10.1007/s00284-005-0020-3
Kellermayer R., Dowd S. E., Harris R. A., Balasa A., Schaible T. D., Wolcott R. D., Smith C. W. ( 2011). Colonic mucosal DNA methylation, immune response, and microbiome patterns in Toll-like receptor 2-knockout mice. FASEB Journal
, 25, 1449–1460. doi:10.1096/fj.10-172205
Krisanaprakornkit S., Kimball J. R., Weinberg A., Darveau R. P., Bainbridge B. W., Dale B. A. ( 2000). Inducible expression of human beta-defensin 2 by Fusobacterium nucleatum in oral epithelial cells: Multiple signaling pathways and role of commensal bacteria in innate immunity and the epithelial barrier. Infection and Immunity
, 68, 2907–2915. doi:10.1096/fj.10-172205
Kukkonen K., Savilahti E., Haahtela T., Juntunen-Backman K., Korpela R., Poussa T., Kuitunen M. ( 2007). Probiotics and prebiotic galacto-oligosaccharides in the prevention of allergic diseases: A randomized, double-blind, placebo-controlled trial. The Journal of Allergy and Clinical Immunology
, 119, 192–198. doi:10.1016/j.jaci.2006.09.009
Lahtinen S. J., Boyle R. J., Kivivuori S., Oppedisano F., Smith K. R., Robins-Browne R., Tang M. L. ( 2009). Prenatal probiotic administration can influence Bifidobacterium microbiota development in infants at high risk of allergy. The Journal of Allergy and Clinical Immunology
, 123, 499–501.
Lamers S. L., Sleasman J. W., She J. X., Barrie K. A., Pomeroy S. M., Barrett D. J., Goodenow M. M. ( 1994). Persistence of multiple maternal genotypes of human immunodeficiency virus type I in infants infected by vertical transmission. Journal of Clinical Investigation
, 93, 380–390. doi:10.1172/JCI116970
Larsen N., Vogensen F. K., van den Berg F. W. J., Nielsen D. S., Andreasen A. S., Pedersen B. K., Jakobsen M. ( 2010). Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLOS ONE
, 5, e9085. doi:10.1371/journal.pone.0009085
Loke Y. J., Novakovic B., Ollikainen M., Wallace E. M., Umstad M. P., Permezel M., Craig J. M. ( 2013). The peri/postnatal epigenetic twins study (PETS). Twin Research and Human Genetics
, 16, 13–20. doi:10.1017/thg.2012.114
Lozupone C. A., Stombaugh J. I., Gordon J. I., Jansson J. K., Knight R. ( 2012). Diversity, stability and resilience of the human gut microbiota. Nature
, 489, 220–230. doi:10.1038/nature11550
Macpherson A. J., Uhr T. ( 2004). Induction of protective IgA by intestinal dendritic cells. Science
, 303, 1662–1665. doi:10.1126/science.1091334
Madan J. C., Salari R. C., Saxena D., Davidson L., O’Toole G. A., Moore J. H., Hibberd P. L. ( 2012). Gut microbial colonisation in premature neonates predicts neonatal sepsis. Archives of Disease in Childhood. Fetal and Neonatal Edition
, 97, F456–F462. doi:10.1136/fetalneonatal-2011-301373
Mårild K., Ludvigsson J., Sanz Y., Ludvigsson J. F. ( 2014). Antibiotic exposure in pregnancy and risk of coeliac disease in offspring: A cohort study. BMC Gastroenterology
, 14, 75. doi:10.1186/1471-230X-14-75
Milisavljevic V., Garg M., Vuletic I., Miller J. F., Kim L., Cunningham T. D., Schröder I. ( 2013). Prospective assessment of the gastroesophageal microbiome in VLBW neonates. BMC Pediatrics
, 13, 49. doi:10.1186/1471-2431-13-49
Mitchell A. A., Gilboa S. M., Werler M. M., Kelley K. E., Louik C., Hernández-Díaz S. ( 2011). Medication use during pregnancy, with particular focus on prescription drugs: 1976–2008. American Journal of Obstetrics and Gynecology
, 205, 51.e1–51.e8.e8. doi:10.1016/j.ajog.2011.02.029
Moles L., Gómez M., Heilig H., Bustos G., Fuentes S., de Vos W., Jimenéz E. ( 2013). Bacterial diversity in meconium of preterm neonates and evolution of their fecal microbiota during the first month of life. PLOS ONE
, 8, e66986. doi:10.1371/journal.pone.0066986
Moloney R. D., Desbonnet L., Clarke G., Dinan T. G., Cryan J. F. ( 2014). The microbiome: Stress, health and disease. Mammalian Genome
, 25, 49–74. doi:10.1007/s00335-013-9488-5
Morency A.-M., Bujold E. ( 2007). The effect of second-trimester antibiotic therapy on the rate of preterm birth. Journal of Obstetrics and Gynaecology Canada
, 29, 35–44. http://jogc.org/abstracts/full/200701_Obstetrics_2.pdf
Nelson D. B., Hanlon A., Hassan S., Britto J., Geifman-Holtzman O., Haggerty C., Fredricks D. N. ( 2009). Preterm labor and bacterial vaginosis-associated bacteria among urban women. Journal of Perinatal Medicine
, 37, 130–134. doi:10.1515/JPM.2009.026.Preterm
Newton E. R. ( 1999). Diagnosis of perinatal TORCH infections. Clinical Obstetrics and Gynecology
, 42, 59–70.
Niers L., Martin R., Rijkers G., Sengers F., Timmerman H., van Uden N., Hoekstra M. ( 2009). The effects of selected probiotic strains on the development of eczema (the PandA study). Allergy
, 64, 1349–1358. doi:10.1111/j.1398-9995.2009.02021.x
Olszak T., An D., Zeissig S., Vera M. P., Richter J., Franke A., Blumberg R. S. ( 2012). Microbial exposure during early life has persistent effects on natural killer T cell function. Science
, 336, 489–493. doi:10.1126/science.1219328
Penders J., Thijs C., Vink C., Stelma F. F., Snijders B., Kummeling I., Stobberingh E. E. ( 2006). Factors influencing the composition of the intestinal microbiota in early infancy. Pediatrics
, 118, 511–521. doi:10.1542/peds.2005-2824
Perez P. F., Doré J., Leclerc M., Levenez F., Benyacoub J., Serrant P., Donnet-Hughes A. ( 2007). Bacterial imprinting of the neonatal immune system: Lessons from maternal cells? Pediatrics
, 119, e724–e732. doi:10.1542/peds.2006-1649
Pilsner R., Hu H., Ettinger A., Sánchez B., Wright R., Cantonwine D., Hernández-Avila M. ( 2009). Influence of prenatal lead exposure on genomic methylation of cord blood DNA. Environmental Health Perspectives
, 117, 1466–1471. doi:10.1289/ehp.0800497
Pozo-Rubio T., de Palma G., Mujico J. R., Olivares M., Marcos A., Acuña M. D., Nova E. ( 2013). Influence of early environmental factors on lymphocyte subsets and gut microbiota in infants at risk of celiac disease; the PROFICEL study. Nutrición Hospitalaria
, 28, 464–473. doi:10.3305/nh.2013.28.2.6310
Rautava S., Collado M. C., Salminen S., Isolauri E. ( 2012). Probiotics modulate host-microbe interaction in the placenta and fetal gut: A randomized, double-blind, placebo-controlled trial. Neonatology
, 102, 178–184. doi:10.1159/000339182
Ravelli A. C. J., van der Meulen J. H. P., Osmond C., Barker D. J. P., Bleker O. P. ( 1999). Obesity at the age of 50 y in men and women exposed to famine prenatally. American Journal of Clinical Nutrition
, 70, 811–816.
Red-Horse K. ( 2008). Lymphatic vessel dynamics in the uterine wall. Placenta
, 29, S55–S59. doi:10.1016/j.placenta.2007.11.011
Rescigno M., Urbano M., Valzasina B., Francolini M., Rotta G., Bonasio R., Ricciardi-Castagnoli P. ( 2001). Dendritic cells express tight junction proteins and penetrate gut epithelial monolayers to sample bacteria. Nature Immunology
, 2, 361–367. doi:10.1038/86373
Rinne M., Kalliomäki M., Salminen S., Isolauri E. ( 2006). Probiotic intervention in the first months of life: Short-term effects on gastrointestinal symptoms and long-term effects on gut microbiota. Journal of Pediatric Gastroenterology and Nutrition
, 43, 200–205. doi:10.1097/01.mpg.0000228106.91240.5b
Romero R., Korzeniewski S. J. ( 2013). Are infants born by elective cesarean delivery without labor at risk for developing immune disorders later in life? American Journal of Obstetrics and Gynecology
, 208, 243–246. doi:10.1016/j.ajog.2012.12.026
Roseboom T. J., Van Der Meulen J. H. P., Ravelli A. C. J., Osmond C., Barker D. J. P., Bleker O. P. ( 2000). Plasma fibrinogen and factor VII concentrations in adults after prenatal exposure to famine. British Journal of Haematology
, 111, 112–117. doi:10.1111/j.1365-2141.2000.02268.x
Roseboom T. J., Van Der Meulen J. H., Ravelli A. C., Osmond C., Barker D. J., Bleker O. P. ( 2003). Perceived health of adults after prenatal exposure to the Dutch famine. Paediatric and Perinatal Epidemiology
, 17, 391–397. doi:10.1046/j.1365-3016.2003.00516.x
Salvini F., Riva E., Salvatici E., Boehm G., Jelinek J., Banderali G., Giovannini M. ( 2011). A specific prebiotic mixture added to starting infant formula has long-lasting bifidogenic effects. Journal of Nutrition
, 141, 1335–1339. doi:10.3945/[ZERO WIDTH SPACE]jn.110.136747
Shadid R., Haarman M., Knol J., Theis W., Beermann C., Rjosk-Dendorfer D., Krauss-Etschmann S. ( 2007). Effects of galactooligosaccharide and long-chain fructooligosaccharide supplementation during pregnancy on maternal and neonatal microbiota and immunity—A randomized, double-blind, placebo-controlled study. American Journal of Clinical Nutrition
, 86, 1426–1437.
Sherman M. P., Minnerly J., Curtiss W., Rangwala S., Kelley S. T. ( 2014). Research on neonatal microbiomes: What neonatologists need to know. Neonatology
, 105, 14–24. doi:10.1159/000354944
Simeoni U., Barker D. J. ( 2009). Offspring of diabetic pregnancy: Long-term outcomes. Seminars in Fetal & Neonatal Medicine
, 14, 119–124. doi:10.1016/j.siny.2009.01.002
Song S. J., Dominguez-Bello M. G., Knight R. ( 2013). How delivery mode and feeding can shape the bacterial community in the infant gut. Canadian Medical Association Journal
, 185, 373–374. doi:10.1503/cmaj.130147
Stewart C. J., Marrs E. C., Nelson A., Lanyon C., Perry J. D., Embleton N. D., Berrington J. E. ( 2013). Development of the preterm gut microbiome in twins at risk of necrotizing enterocolitis and sepsis. PLOS ONE
, 8. doi:10.1371/journal.pone.0073465
Stilling R. M., Dinan T. G., Cryan J. F. ( 2014). Microbial genes, brain & behaviour—epigenetic regulation of the gut–brain axis. Genes, Brain, and Behavior
, 13, 69–86. doi:10.1111/gbb.12109
Tana C., Umesaki Y., Imaoka A., Handa T., Kanazawa M., Fukudo S. ( 2010). Altered profiles of intestinal microbiota and organic acids may be the origin of symptoms in irritable bowel syndrome. Neurogastroenterology & Motility
, 22, 512–519. e114–e115. doi:10.1111/j.1365-2982.2009.01427.x
The Human Microbiome Project Consortium. ( 2012). Structure, function and diversity of the healthy human microbiome. Nature
, 486, 207–214. doi: 10.1038/nature11234
Turnbaugh P. J., Hamady M., Yatsunenko T., Cantarel B. L., Duncan A., Ley R. E., Gordon J. I. ( 2009). A core gut microbiome in obese and lean twins. Nature
, 457, 480–484. doi:10.1038/nature07540
Tyler A. D., Smith M. I., Silverberg M. S. ( 2014). Analyzing the human microbiome: A “how to” guide for physicians. American Journal of Gastroenterology
, 109, 983–993. doi:10.1038/ajg.2014.73
Urwin H. J., Miles E. A., Noakes P. S., Kremmyda L. S., Vlachava M., Diaper N. D., Yagoob P. ( 2014). Effect of salmon consumption during pregnancy on maternal and infant faecal microbiota, secretory IgA and calprotection. British Journal of Nutrition
, 111, 773–784. doi:10.1017/S0007114513003097
Verstraelen H., Verhelst R., Claeys G., De Backer E., Temmerman M., Vaneechoutte M. ( 2009). Longitudinal analysis of the vaginal microflora in pregnancy suggests that L. cripatus
promotes the stability of the normal vaginal microflora and that L. gasseri
and/or L. iners
are more conducive to the occurrence of abnormal vaginal microflora. BMC Microbiology
, 9, 116. doi:10.1186/1471-2180-9-116
Vidal A. C., Murphy S. K., Murtha A. P., Schildkraut J. M., Soubry A., Huang Z., Hoyo C. ( 2013). Associations between antibiotic exposure during pregnancy, birth weight and aberrant methylation at imprinted genes among offspring. International Journal of Obesity
, 37, 907–913. doi:10.1038/ijo.2013.47
Vitali B., Cruciani F., Baldassarre M. E., Capursi T., Spisni E., Valerii M. C., Brigidi P. ( 2012). Dietary supplementation with probiotics during late pregnancy: Outcome on vaginal microbiota and cytokine secretion. BMC Microbiology
, 12, 236. doi:10.1186/1471-2180-12-236
Waldorf K. M. A., McAdams R. M. ( 2013). Influence of infection during pregnancy on fetal development. Reproduction
, 146, R151–R162. doi:10.1530/REP-13-0232
Walther-António M. R. S., Jeraldo P., Breg Miller M. E., Yeoman C. J., Nelson K. E., Wilson B. A., Creedon D. J. ( 2014). Pregnancy’s stronghold on the vaginal microbiome. PLOS ONE
, 9. doi: 10.1371/journal.pone.0098514
Wang Y., Kasper L. H. ( 2014). The role of microbiome in central nervous system disorders. Brain, Behavior, and Immunity
, 38, 1–12. doi:10.1016/j.bbi.2013.12.015
Wang Z., Klipfell E., Bennett B. J., Koeth R., Levison B. S., DuGar B., Hazen S. L. ( 2011). Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature
, 472, 57–63. doi:10.1038/nature09922
Waterland R. A., Jirtle R. L. ( 2003). Transposable elements: Targets for early nutritional effects on epigenetic gene regulation. Molecular and Cellular Biology
, 23, 5293–5300. doi:10.1128/MCB.23.15.5293-5300.2003
Wu G. D., Chen J., Hoffmann C., Bittinger K., Chen Y.-Y., Keilbaugh S. A., Lewis J. D. ( 2011). Linking long-term dietary patterns with gut microbial enterotypes. Science
, 334, 105–108. doi:10.1126/science.1208344
Zhang C., Zhang M., Wang S., Han R., Cao Y., Hua W., Zhao L. ( 2010). Interactions between gut microbiota, host genetics and diet relevant to development of metabolic syndromes in mice. ISME Journal
, 4, 232–241. doi:10.1038/ismej.2009.112