The Human Microbiome as a Modifier of Personalized Exposures

Our bodies are made up of trillions of cells and, historically, literature has suggested that each cell in our body (i.e., human cells) is outnumbered 10 to 1 by microbes (i.e., bacterial cells). In more recent history, researchers have proposed a revised ratio, such as with Sender et al. (2016) estimating that the number of bacteria in the body is on the same order as the number of human cells (i.e., 1:1 ratio). Regardless of the ratio, bacterial cells play a significant role in our health and inhabit all parts of the human body. This entire assemblage of microbes is w'hat makes up the human microbiome. In addition, microbes play an integral role in keeping our digestive system running smoothly. However, the microbiome is more than just our partner in digestion—it is also important to boosting immunity, balancing hormone levels, preventing infection, and maintaining optimal brain function.

Passed down from mother to baby, the human microbiome is the collection of all the microorganisms on or in the human body, their genes, and the surrounding environmental conditions. Each body site of the human microbiome has a distinct microbial community. For example, the oral microbiome is recognizably different in composition and function compared to other body site microbiomes. Despite its diversity, the skin microbiome is tiny compared to the massive community inhabiting the gastrointestinal tract (gut) where there is a constant supply of nutrients. Although individually distinct, perturbations in the composition and function of a site microbiome are associated with disease at the affected site, as well as distally (NAS 2018).

The Microbiome of a Baby

The assembly (“colonization”) of the microbiome of an infant is determined by the maternal-offspring exchange of microbiota. In fact, factors such as birth by Caesarean section (C-section), perinatal antibiotics, and dependence on formula feeding can affect this assembly process and lead to increased risk of disease (Mueller et al. 2015). In contrast to the very similar array of bacteria that a baby born vaginally inherits from the mother, the microbiome of a baby born via C-section is likely colonized by a less diverse array, mostly by skin bacteria, in addition to any bacteria picked up from the environment in which the baby is born. This disruption of bacterial transmission resulting from a C-section may increase the risk of disease.

Researchers have observed differences in the specific microbial species between C-section babies and babies delivered vaginally after 1 month, 2years, and even up to 7 years old (Mueller et al. 2015).

The first 1,000days of life is a critical window of early childhood growth and development, particularly for the gut microbiome. From conception to two years of age, this development period is strongly supported and influenced by rapid maturation of metabolic, endocrine, neural, and immune pathways. Adverse environmental insults experienced during this crucial period can negatively affect the trajectory of child growth, leading to malnutrition, either in the form of obesity or as undernutrition (Robertson et al. 2018).

There are two major transitions which occur sometime after delivery that accompany the establishment of stable gut microbiota, with the first occurring soon after birth during lactation and the second during the weaning period with the introduction of solid foods along with continued nursing (Robertson et al. 2018). The first transition creates a gut microbiome abundant with genes specific for the infant’s digestion of milk proteins. A mother’s breastmilk, which contains bacteria and pre- biotic human milk oligosaccharides (HMOs), introduces new microbial communities and stimulates the maturation of the neonatal gut microbiome. In contrast, feeding an infant with formula has been found to impair the development of the neonatal immune system and alter metabolism. Breastfed babies tend to have a stable and relatively uniform gut microbiome w'hen compared to babies fed via formula, even when only small amounts of formula are ingested. Evidence suggests that in addition to delivery via C-section and formula feeding, the use of prenatal antibiotics is another action that can compromise the microbial colonization of the newborn gut. It is suggested that these three actions be practiced prudently and followed by measures to restore the natural composition of the microbiome (Mueller et al. 2015).

The introduction of solid foods in an infant’s diet activates genes in the gut that can break down complex sugars and starches in plants. This transition to solids initiates a rapid increase in the diversity of the infant microbiota and the evolving microbiome begins the resemblance of a more mature, adult-like state. Any disruption of this normal assembly of the gut microbiome may have considerable consequences in the development of autoimmune and metabolic pathologies (Mueller et al. 2015). However, the gut microbiome generally remains stable throughout adulthood in the absence of long-term dietary changes, disease- associated dysbiosis (i.e., gut microbial imbalance or perturbation), or the use of antibiotics (Tanaka and Nakayama 2017).

The Gut Microbiome

Nutritionists continue to assert that a varied and balanced diet is essential for optimal health, and human microbiome researchers emphasize the importance of maintaining the diversity and proper functioning of the gut microbiome. Because the gut microbiota sit on the intersection between diet and host genome, they have important implications for food processing and making nutrients available to the host (programming of host metabolism). Bacteria in the gut are responsible for breaking down many of the complex molecules found in foods; the plant cellulose in fruits, vegetables, and nuts would not even be digestible without the microbiota of the gut. Such bacteria harvest energy for themselves from plant-based foods eaten and also break them down into smaller molecules for easier digestion (Microbiome Institute 2020). Perhaps the saying “you are what you eat” has scientific basis, as bacteria in the gut are somewhat of a reflection of the foods that we eat. For example, the guts of African villagers who eat high-fiber diets are dominated by plant-digesting microbiota, which are much rarer in the guts of Europeans who eat high-fat diets (Yong 2010).

Prebiotics and probiotics are two of the most widely studied elements in the field of gut microbiota, and specialists stress the importance of including both in our diet to help maintain the balance and diversity of the gut microbiome (ESNM 2019; Mayo Clinic 2019). Prebiotics are specialized plant fibers found naturally in fruits and vegetables and in commercial supplements. They are defined as the indigestible ingredients in food that selectively promote the growth and activity of a limited number of autochthonous bacterial species (i.e., indigenous organisms in soil) (ESNM 2019). Because they aren’t digestible, prebiotics pass through the digestive system to become food for bacteria and other microbes (Mayo Clinic 2019). Excessive consumption of prebiotics, however, may lead to discomfort or abdominal bloating in some people, adding to why nutritionists say balance and variety are important. Probiotics come from bacteria traditionally used in biologically active or fermenting food (e.g., yogurt, kombucha, other bacteria-fermented foods, commercial supplements). They, too, provide a range of benefits for the body, to include the maintenance of digestive comfort and the regulation of the immune system. Probiotics can also help balance the gut microbiota when affected by poor diet, infections, some antibiotics treatments, or other external factors such as stress (ESNM 2019).

In addition to its role in the processing of foods and nutrients, the gut microbiome may also have a significant role in metabolizing environmental chemicals to which the host is exposed (Claus et al. 2016). Growing evidence suggests microbial composition of the gut is altered after an exposure. Human exposure to endocrine-disrupting chemicals has been linked to obesity, metabolic syndrome, type 2 diabetes, and others, but it is unclear how the microbiota of the gut interact with environmental chemicals and whether such interactions are relevant for human health (Claus et al. 2016).


Described as what the body does to a drug, pharmacokinetics (PK) is the science of the kinetics of drug absorption, distribution, metabolism, and excretion (ADME) (Ahmed 2015), or simply, the fate and transport of a drug into and throughout the human body. It influences the route of administration for a medication, the amount, and frequency of each dose and dosing interval. Note, however, that principles of PK extend beyond pharmaceuticals (i.e., drugs) and can be used to assess ADME of various chemicals in the body. In this section, we discuss physiologically based pharmacokinetics (PBPK) modeling, its potential benefits to metabolomics, and current shortfalls with respect to using PBPK to address gut microbiome effects.

Absorption, Distribution, Metabolism, and Excretion

After released from its dosage form, drugs are absorbed into the surrounding tissue, the body, or both. Once the gastrointestinal tract is reached, the microbes in the region can alter the disposition, efficacy, and toxicity of the drug (Zimmermann et al. 2019). Drug efficiency is affected both directly and indirectly by microbes. Direct effects on drugs are related to binding, degrading, or other modification of the drug, and indirect effects lead to production of microbial metabolites. A quantitative understanding of the factors that determine gut microbiome contributions to metabolism could help explain interpersonal variability in drug response and provide personalized medicine opportunities (Zimmermann et al. 2019).

Physiologically Based Pharmacokinetic (PBPK) Modeling

A more complex type of PK model is a PBPK model which uses a system of differential equations that are parameterized using known physiological values representing key tissue groups and organs involved in the ADME of the drug. Essentially, PBPK models describe the relationship between exposure and tissue dose (NRC 2010). PBPK modeling dates back to at least 1937, with the introduction of multi- compartmental modeling by Teorell (Jones and Rowland-Yeo 2013). Compartments represent actual portions of the body and examples include the lungs, bone, liver, kidneys, gut, and slowly perfused tissue. Such compartments are included if they serve roles in the transport, removal, or accumulation of the drug or chemical. Similar tissues are “lumped” together into a single compartment to reduce model complexity (e.g., muscle, skin, and fat lumped together to form a slowly perfused tissue compartment), unless the physiological, physicochemical, or biochemical parameters have noticeably different effects on chemical uptake and disposition (Krishnan and Andersen 2001). Compartments are connected by systemic circulation, represented by arterial and venous blood flow which facilitate distribution. Ordinary differential equations are developed as rate expressions, with a “mass balance” concept followed (i.e., amount of chemical entering the compartment equals the amount leaving or cleared from the compartment plus the amount physically retained within the compartment). Chemical uptake (i.e., amount physically retained) in tissue groups is modeled using applicable rates of diffusion and equilibrium partitioning (NRC 2010). Metabolism occurs in various tissues/organs, including the liver. Excretion represents the elimination of the drug/chemical, often through exhalation, excretion through the kidneys (urine) or liver (bile), with appropriate rate expressions. Subsequently, the system of differential equations is numerically solved via in silico (i.e., computer) to estimate drug (or chemical) concentrations in specific organs or tissues. Further details on PBPK modeling can be found in the literature (Jones and Rowland-Yeo 2013; Krishnan and Andersen 2001; NRC 2010).

Recent advances have led to a better understanding of the diversity and abundance of gut microbial species, which has resulted in a shift in research focus to exploring the effects of an individual’s gut microbiome on metabolism and, more specifically, drug metabolism. It is believed that the gut microbiota and environmental chemicals interact with each other in four distinct ways: (1) upon direct ingestion, the gut microbiota metabolizes the chemical; (2) after it’s conjugated by the liver, the chemical is metabolized by the microbiota; (3) the chemical interferes with the composition of the gut microbiome; or (4) the chemical interferes with the metabolic activity of the gut microbiome (Claus et al. 2016). Despite the mechanistic details captured in PBPK models, the effects of microbial metabolism are not adequately addressed. Moreover, these PBPK models do not facilitate personalization based on dietary, microbial, or genetic data.


The exposure science-related principles explored here, such as metabolomics, the human microbiome and gut microbiome, and PK, stand to be powerful tools for TEH. TEH is a means to integrate and provide occupational, environmental, lifestyle, and clinical exposure-related data to more effectively protect an individual’s health. Employers interested in more complete health assessments stand to gain by implementing exposure science and related principles/tools.


Agin, A., Heintz, D., Ruhland, E., Chao de la Barca, J.M., Zumsteg, J., Moal, V, Guachez, A.S., and I.J. Namer (2016). “Metabolomics - An Overview. From Basic Principles to Potential Biomarkers (Part 1).” Medecine Nucleaire 40(1): 4-10.

Ahmed, T.A. (2015). “Pharmacokinetics of Drugs Following IV Bolus, IV Infusion, and Oral Administration.” Basic Pharmacokinetic Concepts and Some Clinical Applications. doi: 10.5772/61573

Becker, R., Brozena, S„ and D. Smith (2003). “What Is Biomonitoring?” Chemistry Business 26: 1-4.

Betts, K., and K. Sawyer (2016). Use of Metabolomics to Advance Research on Environmental Exposures and the Human Exposome: Workshop in Brief. Washington, DC: The National Academies Press.

Bradburne, C., Graham, D., Kingston, H.M., Brenner, R., Pamuku, M., and L. Carruth (2015). “Overview of ‘Omics Technologies for Military Occupational Health Surveillance and Medicine.” Military Medicine 180(suppl_10): 34-48.

Claus. S.P.. Guillou, H„ and S. Ellero-Simatos (2016). “The Gut Microbiota: A Major Player in the Toxicity of Environmental Pollutants?” Biofilms and Microbiome 2(1603): 1-12. Centers for Disease Control and Prevention (CDC) (2014). “Exposome and Exposomics.” (accessed 11 Jan 2020).

Dias, D.A., and T. Koal (2016). “Progress in Metabolomics Standardisation and Its Significance in Future Clinical Laboratory Medicine.” The Journal of the International Federation of Clinical Chemistry and Laboratory Medicine 27: 331-343.

DrugBank (2020). DrugBank Webpage, (accessed on 3 Jan 2020). Emwas, A-H.M. (2015). “The Strengths and Weaknesses of NMR Spectroscopy and Mass Spectrometry with Particular Focus on Metabolomics Research.” Methods in Molecular Biology 1277: 161-193.

European Society of Neurogastroenterology & Motility (ESNM) (2019). “Gut Microbiota for Health.” Diet & Gut Microbiota, gut-microbiota-info/about-diet-gut-microbiota/ (accessed 11 Jan 2020).

Goff. P, and R. Hartman (2018). Total Exposure Health Strategic Plan FY19-23. Department of Defense/U.S. Air Force Medical Service, force-medical-service-total-exposure-health-strategic-plan (accessed 2 Apr 2020).

Gowda, G.A., and D. Djukovic (2014). “Overview of Mass Spectrometry-based Metabolomics: Opportunities and Challenges.” Mass Spectrometry in Metabolomics. Methods in Molecular Biology 1198: 3-12.

Human Metabolome Database (HMDB) (2020). (accessed 3 Jan 2020).

Johnson, C.H., and F.J. Gonzalez (2012). “Challenges and Opportunities of Metabolomics.” Journal of Cellular Physiology 227(8): 2975-2981.

Jones, H.M., and K. Rowland-Yeo (2013). “Basic Concepts in Physiologically based Pharmacokinetic Modeling in Drug Discovery and Development.” CPT Pharmacometrics and Systems Pharmacology 2(8): e63.

Krishnan, K., and M.E. Andersen (2001). “Physiologically Based Pharmacokinetic Modeling in Toxicology,” in Principles and Methods of Toxicology (4th ed., pp. 193-241). Philadelphia, PA: Taylor & Francis.

Mayo Clinic (2019). Prebiotics, Probiotics and Your Health, prebiotics-probiotics-and-your-health/art-20390058 (accessed 6 Jun 2019).

Metabolomics Society (2020). (accessed 6 Jan 2020).

Metz, T.O., Baker, E.S., Schymanski, E.L.. Renslow, R.S.. Thomas. D.G., Causon. T.J.. Webb. I.K., Hann, S., Smith, R.D., and J.G. Teeguarden (2017). “Integrating Ion Mobility Spectrometry into Mass Spectrometry-based Exposome Measurements: What Can It Add and How Far Can It Go?” Bioanalysis 9(1): 81—98.

Microbiome Institute (2020). Introduction to the Human Microbiome, 2020. http://www. (accessed 6 Jan 2020).

Mueller. N.T.. Bakacs, E.. Combellick. J.. Grigoryan, Z.. and M.G. Dominguez-Bello. (2015). “The Infant Microbiome Development: Mom Matters.” Trends in Molecular Medicine 21(2): 109-117.

National Academies of Sciences, Engineering and Medicine (NAS) (2018). Environmental Chemicals, the Human Microbiome, and Health Risk: A Research Strategy. Washington, DC: The National Academies Press, doi: 10.17226/24960.

National Institute for Occupational Safety and Health (NIOSH) (2019). Exposome and Exposomics. (accessed 2 Jan 2020).

National Institutes of Health (NIH) (2012). NIH Announces New Program in Metabolomics. Retrieved January 6, 2020, from nih-announces-new-program-metabolomics.

National Research Council (NRC) (2010). Committee on Acute Exposure Guideline Levels. Acute Exposure Guideline Levels for Selected Airborne Chemicals: Volume 9. Washington (DC): National Academies Press (US): 7, PBPK Modeling White Paper: Addressing the Use of PBPK Models to Support Derivation of Acute Exposure Guideline Levels.

National Research Council (NRC) (2012). Exposure Science in the 21st Century: a Vision and a Strategy. Washington, DC: National Academies Press.

Pacific Northwest National Lab (2017). “Biological Sciences Research Highlights.” For Robust SLIM, an R&D 'Oscar', asp?id=4786 (accessed 11 Jan 2020).

Pacific Northwest National Lab (2020). High-Throughput and Ultra-sensitive Multidimensional Analytical Platform Based on Multiplexed Ion Mobility Spectrometry/Mass Spectrometry. (accessed 3 Jan 2020).

Patti, G.J., Yanes, O., and G. Siuzdak (2013). “Metabolomics: The Apogee of the Omic Triology.” Nature Reviews Molecular Cell Biology 13(4): 263-269.

Robertson, R.C., Manges, A.R., Finlay, B.B., and A.J. Prendergast (2018). “The Human Microbiome and Child Growth - First 1000 Days and Beyond.” Trends in Microbiology 27(2): 131-147.

Schrirnpe-Rutledge, A.C., Codreanu, S.G., Sherrod, S.D., and J.A. McLean (2016). “Untargeted Metabolomics Strategies - Challenges and Emerging Directions.” Journal of the American Society for Mass Spectrometry 27(12): 1897-1905.

Sender, R., Fuchs, S., and R. Milo (2016). “Revised Estimates for the Number of Human and Bacteria Cells in the Body.” PLoS Biol 14(8): 1-14.

Swanson, H.I. (2015). “Drug Metabolism by the Host and Gut Microbiota: A Partnership or Rivalry?” Drug Metabolism and Disposition 43(10): 1499-1504.

Tanaka, M., and J. Nakayama (2017). “Development of the Gut Microbiota in Infancy and Its Impact on Health in Later Life.” Allergology International 66(4): 515-522.

Teeguarden, J.G., Tan, Y.M., Edwards, S.W., Leonard, J.A., Anderson, K.A., Corley, R.A., Kile, M.L., Simonich, S.M., Stone, D., Tanguay, R.L., Waters, K.M., Harper, S.L., and D.E. Williams. (2016). Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework. Washington, DC: ACS Publications.

Toxic Exposome Database (2020). The Metabolomics Innovation Centre (TMIC). http:// (accessed 3 Jan 2020).

Trivedi, D.K., Hollywood, K.A., and R. Goodacre (2017). “Metabolomics for the Masses: The Future of Metabolomics in a Personalized World.” New Horizons in Translational Medicine 3(6):294-305.

Wild, C.P. (2005). “Complementing the Genome with an “Exposome”: The Outstanding Challenge of Environmental Exposure Measurement in Molecular Epidemiology.” Cancer Epidemiology Biomarkers & Prevention 14(8): 1847-1850.

Wild, C.P. (2012). “The Exposome: From Concept to Utility.” International Journal of Epidemiology 41(1): 24-32.

Yong, E. (2010). An Introduction to the Microbiome. National Geographic. https://www. nationalgeographic.corn/science/phenomena/2010/08/08/an-introduction-to-the- microbiome (accessed 8 Nov 2018).

Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R., and A.L. Goodman (2019). “Separating Host and Microbiome Contributions to Drug Pharmacokinetics and Toxicity.” Science 363(6473).

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