Maternal vaginal and gut microbial populations may influence offspring behavior, physiology, and/or neuropathology. These influences may either be indirect due to changes in maternal behavior or direct due to microbial product exposure. Studies on the sterility of the mammalian placenta and amniotic fluid are controversial. Administration of antibiotics during gestation induces hypo activity, anxiety-like behavior, locomotion and social deficits in offspring. ASD-like mannerisms including social deficits and repetitive behavior in offspring are caused by maternal high fat diets. Cross-fostering offspring with surrogate conventional dams or administration of the probiotic, Lactobacillus reuteri, reverses these mannerisms(Bercik et al. 2011). Maternal microbial metabolites, fermentation products and bacterial structural components like lipopolysaccharides (LPS) and peptidoglycan (PG) can cross the placenta. Fetal brains exposed to PG or LPS present with anxiety-like behaviors and cognitive deficits. Prenatal infections, particularly febrile infections, procure significantly higher risks of schizophrenia and ASD in humans. Offspring of maternal immune activation (MIA) mice models, generated by administration of LPS which induces fever during gestation, display decreased cognitive function and anxiety-like behaviors(Foley et al. 2014). Administration of Bacteroides fragilis lowers intestinal barrier permeability and decreases microbial metabolite concentrations which normalizes these behaviors. Postnatal neurogenesis, including migration, differentiation, apoptosis and synaptic pruning of glial cells, continues over a lifespan(Foley et al. 2014). Hippocampal neurogenesis reduction from long-term antibiotic treatment causes a reduction in novel object recognition. Exercise and the administration of probiotics corrects these anomalies. The gut microbiome mediates gut and brain serotonergic pathways; whereas, serotonin is known to support postnatal neurogenesis(Möhle et al. 2016). Antibiotic treatment augments myelin related transcripts in the prefrontal cortex but cannot be reversed by the transplantation of SPF GM into GF mice(Gacias et al. 2016).

Test 1

Early life microbiome perturbations can have lifelong metabolic, physiological and immunological implications. Vaginal birth ensures that maternal vaginal microbiota species particularly Lactobacillus and Prevotella will colonize offspring which confers protection. Exposure to prenatal stress adversely changes vaginal microbiomes. However, probiotics taken by the mother during gestation can transfer to the offspring during vaginal birth. Infants born by cesarean section have higher risks of autoimmune disease because they are initially colonized by skin residing bacteria, such as Staphylococcus and Corynebacterium . Exposing these neonates to their mother’s vaginal microbiota can partially remedy this mishap. In rats, short-term antibiotic therapy that partially depletes microbiota has no effect on anxious or depressive-like behaviors but visceral hypersensitivity presents in adulthood(Koenig et al. 2011; Jašarević et al. 2015). Short term antibiotic therapy temporarily decreases anxiety-like behavior in adult mice but returns in two weeks after the microbiota resumes their normal composition. Postnatal long-term broad spectrum antibiotic therapy permanently reconstitutes host microbial profiles and functions which then modify brain chemistry and behavior. Specific conditions can be altered, reversed or prevented by transient and/or permanent colonization of probiotics. Probiotics can beneficially reduce repetitive, anxiety and depressive-like behaviors as well as stress in animal models. Probiotics also promote communication, proper cognitive functioning and social behavior in animals. Humans given a probiotic containing fermented milk product twice a day for a month show less reactive emotional responses to images of distressed faces than controls. Microbiota-gut-brain communication is said to be bidirectional. GM can affect their host and a host can affect its GM(Bailey et al. 2011; Gacias et al. 2016). Early life stressors, such as separation from maternal mothers in mice, induce differences in microbial composition which then produce anxiety-like behaviors. Presence of a single bacterial species or microbial consortiums may initiate depressive-like behaviors in their host.
If adult hosts maintain steady diets, lifestyles, health and geographical residency, then their microbiome’s diversity and composition remain in relative temporal equilibrium. High microbial diversity is positively correlated with redundant health and the absence of disease(Lloyd-Price et al. 2016). GM are linked to neurodevelopmental and neurodegenerative disorders whereas gastrointestinal comorbidities and food allergies are commonly found in ASD, depressive and elderly patients. GM are also linked to stress related disorders in humans such as IBD. GM are also linked to stress induced anxiety-like behaviors in rodent models(de Theije et al. 2014). ASD patients show consistent variances in species richness and diversity, especially in Clostridia species. The following differences are found in ASD patients versus controls: close associations of Sutterella with intestinal epithelium, absence of the probiotic Prevotella as well as elevations in non-spore forming anaerobes and micro aerophilic bacteria. The following differences are found in schizophrenic patients versus controls: presence of a Lactobacillus specific phage, high abundances of oropharyngeal residing Lactobacillus, as well as high diversity alpha and beta species in the blood(De Angelis et al. 2013). Declines in microglial function associated with brain inflammation often precede depression. The antibacterial minocycline acts as an antidepressant in humans. Minocycline inhibits microglia. Major depressive disorder (MDD) patients have higher abundances of Actinobacteria and lower abundances of Bacteroidetes than controls. GF mice exhibit depressive-like behavior after transplantation of MDD patient GM samples(Molina-Hernández et al. 2008; Miyaoka et al. 2012).
As the ENS degenerates with age, the microbiome loses resilience and reflects shifting bacterial taxa prevailing Firmicutes to dominant Bacteroidetes. Elderly microbiomes, when living in the community, more closely simulate young adults than when living in care facilities. Supplementation of the probiotic, Lactobacillus rhamnosus GG, elevates SCFA levels which tips GM composition towards anti-inflammatory exhibiting taxa(Eloe-Fadrosh et al. 2015).
Patients with neurodegenerative diseases have abnormal microbial populations. AD patients have decreases in Allobaculum and Akkermansia as well as increases in Rikenellaceae compared to controls. PD patients exhibit lower concentrations of Prevotellaceae and SFCA as well as higher concentrations of Lactobacilliaceae and tissue associated Escherichia coli. Tremor dominant PD are distinguished from postural and gate dominant PD patients by lower rates of Enterobacteracea (Harach et al. 2015; Hasegawa et al. 2015). Microglia functioning and neuro-inflammation account for the inhibition and advancement neurodegenerative disease. SFCA produced by microbiota encourages microglial maturation and supports microglial maintenance(Unger et al. 2016). MAMPs that mimic host molecules and enter brain tissue cause low level inflammation. Amyloid pathogenic plaques in AD patients act as brain associated antibacterial agents. The autoimmune condition uveitis occurrs in an immune privileged site and is mediated by auto reactive T cells also capable of recognizing gut associated microbial antigens(Kumar et al. 2016).
Rates of neurophysiological disorders are increasing more than ever. Perhaps microbiomes are being forced to adapt to human and environmental changes at a speed that is nonsynchronous with rates required for symbiotic coevolution. Questions remain regarding the interplay between host associated microorganisms and the brain. Do microbiomes or the host conditions initiate disorders? Are these single or cumulative changes beneficial or pathogenic to the host? Is GM dysbiosis a causative or correlating factor in host dysbiosis? Does GM produce, promote or exacerbate clinical symptoms? Does GM affect the host directly via microbial metabolites or indirectly via immune system modification? Are single bacterial species or accumulations of bacterial consortia responsible for host symptoms?
Data extrapolated from animal models may not be applicable to humans. Population studies may not be relevant to individuals. Collective generations of host genetics, diets, geographical residence, lifestyle furthermore eating, drinking, sleeping and exercising habits accumulate to shape an individual’s microbiome. GM that cause disease in one patient, such as obesity, can be beneficial to a kwashiorkor patient. Full genomic and metabolic analyses of both host and microbiome may be an inexpensive option for patients soon. Future diagnoses may involve a GF mouse and an SPF mouse being treated with the following processes: host fecal transplantation, short-term antibiotic administration, long-term antibiotic treatment and systematic probiotic administration. Future treatments may be customized and tailored to the individual’s personal standards of health.
De Angelis, M. et al., 2013. Fecal Microbiota and Metabolome of Children with Autism and Pervasive Developmental Disorder Not Otherwise Specified M. M. Heimesaat, ed. PLoS ONE, 8(10), p.e76993. Available at: http://dx.plos.org/10.1371/journal.pone.0076993 [Accessed June 6, 2017].
Bailey, M.T. et al., 2011. Exposure to a social stressor alters the structure of the intestinal microbiota: Implications for stressor-induced immunomodulation. Brain, Behavior, and Immunity, 25(3), pp.397–407. Available at: http://www.sciencedirect.com/science/article/pii/S0889159110005295 [Accessed June 6, 2017].
Bercik, P. et al., 2011. The intestinal microbiota affect central levels of brain-derived neurotropic factor and behavior in mice. Gastroenterology , 141(2), pp.599–609, 609–3. Available at: http://linkinghub.elsevier.com/retrieve/pii/S001650851100607X [Accessed June 6, 2017].
Chang, C.-Y., Ke, D.-S. & Chen, J.-Y., 2009. Essential fatty acids and human brain. Acta neurologica Taiwanica, 18(4), pp.231–41. Available at: http://www.ncbi.nlm.nih.gov/pubmed/20329590 [Accessed June 6, 2017].
Clarke, G. et al., 2013. The microbiome-gut-brain axis during early life regulates the hippocampal serotonergic system in a sex-dependent manner. Molecular Psychiatry , 18(6), pp.666–673. Available at: http://www.nature.com/doifinder/10.1038/mp.2012.77 [Accessed June 6, 2017].
Eloe-Fadrosh, E.A. et al., 2015. Functional dynamics of the gut microbiome in elderly people during probiotic consumption. mBio, 6(2), pp.e00231-15. Available at: http://mbio.asm.org/lookup/doi/10.1128/mBio.00231-15 [Accessed June 6, 2017].
Erny, D. et al., 2015. Host microbiota constantly control maturation and function of microglia in the CNS. Nature neuroscience, 18(7), pp.965–77. Available at: http://www.nature.com/doifinder/10.1038/nn.4030 [Accessed June 6, 2017].
Foley, K.A. et al., 2014. Pre- and Neonatal Exposure to Lipopolysaccharide or the Enteric Metabolite, Propionic Acid, Alters Development and Behavior in Adolescent Rats in a Sexually Dimorphic Manner K. Hashimoto, ed. PLoS ONE, 9(1), p.e87072. Available at: http://dx.plos.org/10.1371/journal.pone.0087072 [Accessed June 6, 2017].
Foster, J.A. & McVey Neufeld, K.-A., 2013. Gut–brain axis: how the microbiome influences anxiety and depression. Trends in Neurosciences, 36(5), pp.305–312. Available at: http://www.ncbi.nlm.nih.gov/pubmed/23384445 [Accessed June 6, 2017].
Gacias, M. et al., 2016. Microbiota-driven transcriptional changes in prefrontal cortex override genetic differences in social behavior. eLife , 5. Available at: http://elifesciences.org/lookup/doi/10.7554/eLife.13442 [Accessed June 6, 2017].
Harach, T. et al., 2015. Reduction of Alzheimer’s disease beta-amyloid pathology in the absence of gut microbiota. Available at: http://arxiv.org/abs/1509.02273 [Accessed June 6, 2017].
Hasegawa, S. et al., 2015. Intestinal Dysbiosis and Lowered Serum Lipopolysaccharide-Binding Protein in Parkinson’s Disease P. J. Kahle, ed. PLOS ONE, 10(11), p.e0142164. Available at: http://dx.plos.org/10.1371/journal.pone.0142164 [Accessed June 6, 2017].
Hoban, A.E. et al., 2016. Regulation of prefrontal cortex myelination by the microbiota. Translational Psychiatry, 6(4), p.e774. Available at: http://www.nature.com/doifinder/10.1038/tp.2016.42 [Accessed June 6, 2017].
Jašarević, E. et al., 2015. Alterations in the Vaginal Microbiome by Maternal Stress Are Associated With Metabolic Reprogramming of the Offspring Gut and Brain. Endocrinology, 156(9), pp.3265–3276. Available at: https://academic.oup.com/endo/article-lookup/doi/10.1210/en.2015-1177 [Accessed June 6, 2017].
Koenig, J.E. et al., 2011. Succession of microbial consortia in the developing infant gut microbiome. Proceedings of the National Academy of Sciences of the United States of America, (Supplement 1), pp.4578–85. Available at: http://www.ncbi.nlm.nih.gov/pubmed/20668239 [Accessed June 6, 2017].
Krajmalnik-Brown, R. et al., 2015. Gut bacteria in children with autism spectrum disorders: challenges and promise of studying how a complex community influences a complex disease. Microbial Ecology in Health & Disease, 26(0). Available at: http://www.microbecolhealthdis.net/index.php/mehd/article/view/26914 [Accessed June 6, 2017].
Kumar, D.K.V. et al., 2016. Amyloid-β peptide protects against microbial infection in mouse and worm models of Alzheimer’s disease. Science Translational Medicine, 8(340). Available at: http://stm.sciencemag.org/content/8/340/340ra72 [Accessed June 6, 2017].
Lloyd-Price, J., Abu-Ali, G. & Huttenhower, C., 2016. The healthy human microbiome. Genome Medicine, 8(1), p.51. Available at: http://genomemedicine.biomedcentral.com/articles/10.1186/s13073-016-0307-y [Accessed June 6, 2017].
Luczynski, P. et al., 2016. Adult microbiota-deficient mice have distinct dendritic morphological changes: differential effects in the amygdala and hippocampus P. Gaspar, ed. European Journal of Neuroscience, 44(9), pp.2654–2666. Available at: http://doi.wiley.com/10.1111/ejn.13291 [Accessed June 6, 2017].
Miyaoka, T. et al., 2012. Minocycline as adjunctive therapy for patients with unipolar psychotic depression: An open-label study. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 37(2), pp.222–226. Available at: http://www.sciencedirect.com/science/article/pii/S0278584612000243 [Accessed June 6, 2017].
Möhle, L. et al., 2016. Ly6Chi Monocytes Provide a Link between Antibiotic-Induced Changes in Gut Microbiota and Adult Hippocampal Neurogenesis. Cell Reports, 15(9), pp.1945–1956. Available at: http://linkinghub.elsevier.com/retrieve/pii/S2211124716305186 [Accessed June 6, 2017].
Molina-Hernández, M. et al., 2008. Antidepressant-like actions of minocycline combined with several glutamate antagonists. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 32(2), pp.380–386. Available at: http://www.sciencedirect.com/science/article/pii/S0278584607003338 [Accessed June 6, 2017].
Ogbonnaya, E.S. et al., 2015. Adult Hippocampal Neurogenesis Is Regulated by the Microbiome. Biological psychiatry, 78(4), pp.e7-9. Available at: http://www.ncbi.nlm.nih.gov/pubmed/25700599 [Accessed June 6, 2017].
Round, J.L. & Mazmanian, S.K., 2009. The gut microbiota shapes intestinal immune responses during health and disease. Nature Reviews Immunology, 9(5), pp.313–323. Available at: http://www.nature.com/doifinder/10.1038/nri2515 [Accessed June 6, 2017].
de Theije, C.G.M. et al., 2014. Food allergy and food-based therapies in neurodevelopmental disorders. Pediatric Allergy and Immunology, 25(3), pp.218–226. Available at: http://doi.wiley.com/10.1111/pai.12149 [Accessed June 6, 2017].
Unger, M.M. et al., 2016. Short chain fatty acids and gut microbiota differ between patients with Parkinson’s disease and age-matched controls. Parkinsonism & Related Disorders, 32, pp.66–72. Available at: http://linkinghub.elsevier.com/retrieve/pii/S1353802016303236 [Accessed June 6, 2017].
Zoetendal, E.G., Rajilic-Stojanovic, M. & de Vos, W.M., 2008. High-throughput diversity and functionality analysis of the gastrointestinal tract microbiota. Gut, 57(11), pp.1605–1615. Available at: http://www.ncbi.nlm.nih.gov/pubmed/18941009 [Accessed June 6, 2017].