The human body is composed of various systems at different sizes and levels of complexity, at the cellular level, it can be understood that a plethora of microbiota contribute to the functioning of those systems (Kim & Benayoun, 2020).

The role of the microbiota in the development of human health and fitness has been demonstrated in a wide range of diseases including cancer, Alzheimer’s, diabetes, heart disease, obesity, Parkinson’s, and Alzheimer’s.

For example, age – which depends on insulin resistance – has been linked to an increase in the presence of highly virulent bacteria such as E. coli and Pseudomonas aeruginosa and the development of diabetes.

Like other parts of the human biological experience, the human microbiome changes with age over time, its maintenance is a part of retaining stable microenvironments, and therefore overall health (Kim & Jazwinski, 2018). Bacteria and other biological actors, including many viruses, are important to the body maintaining its state (Barrera-Vázquez & Gomez-Verjan, 2019).

Exercise, environment, and nutrition can influence the microbial composition and function of the host’s own microbiome as well as the microbiota of other animals and humans (Mills et al., 2019). As with other processes in the human body, even with good habits, these things cannot maintain homeostasis forever, as the body ages and systems break down, the human microbiome changes and contributes to further speeding up the aging process (Lozupone & Turnbaugh, 2019).

In the context of gene therapy, the microbiome can be influenced in two ways, indirectly, through altering the human genome with gene therapy as well as more conventional medicine, or instead, the microbiota could be altered directly (Madhusoodanan, 2020). The genes of microscopic organisms which have their own genomes, but in their own way function as a part of the human body, could themselves be altered through a process similar to the one used to deliver gene therapies to humans.  This is one-way microbiota could be influenced in the human body in a similar manner to the way wheat or corn are prepared for civilizations.

At some point in the development of medicine, to truly have healthcare instead of sick care, we will have to curate the foreign bodies which enter the body with care, with a clear vision as to what which species of microbes are going to do.

This is a daunting challenge, as the effects of such organisms on microenvironments, and by extent the human body overall, are not fully understood, but with breakthroughs in data analyses, such as the creation of specific processes.

One of the most common problem which occurs in the microbiome associated with age is something called gut dysbiosis, which is caused by the gut losing biodiversity, resulting in a decreased ability to digest. This is an important contributing reason why senior citizens more often experience problems such as constipation or inflammation due to eating the wrong thing.

There are some things which can be done in order to maintain this diversity, a varied diet, ideally one rich in fiber, helps, but this can be a vicious cycle, at a certain point what prevents people from maintaining a varied diet are things like a damaged gut, even if that gut has generally been taken good care of, it will lose some of its ability to process food eventually.

While the role of the microbiome is best studied as it relates to the gut and the influence of bacteria, all parts of the body are influenced by microbial organisms in a way which are not as fully understood.

The impact of these many organisms is not fully understood by the science, and the diversity of microorganisms is so numerous that isolating each one’s specific role or roles is a difficult task.

The world of microbial lifeforms remains uncharted territory in the realm of science and medicine, but one which will become less mysterious as machine learning allows researchers to parse through much more data (Barrera-Vázquez & Gomez-Verjan, 2019) (Cammarota et al., 2020) (Topçuoğlu, Lesniak, Ruffin, Wiens, & Schloss, 2019). The day may come when there is not much we do not understand about processes of the human body, large or small, but it will be a long road.

References and Further Reading

Barrera-Vázquez, O. S., & Gomez-Verjan, J. C. (2019). The Unexplored World of Human Virome, Mycobiome, and Archaeome in Aging. The Journals of Gerontology: Series A, 75(10), 1834-1837. doi:10.1093/gerona/glz274

Behrouzi, A., Nafari, A. H., & Siadat, S. D. (2019). The significance of microbiome in

personalized medicine. Clinical and translational medicine, 8(1), 16.

Cammarota, G., Ianiro, G., Ahern, A., Carbone, C., Temko, A., Claesson, M. J., . . . Tortora, G. (2020). Gut microbiome, big data and machine learning to promote precision medicine for cancer. Nature Reviews Gastroenterology & Hepatology, 17(10), 635-648. doi:10.1038/s41575-020-0327-3

DeGruttola, A. K., Low, D., Mizoguchi, A., & Mizoguchi, E. (2016). Current

Understanding of Dysbiosis in Disease in Human and Animal Models. Inflammatory bowel diseases, 22(5), 1137–1150.

Deng, F., Li, Y., & Zhao, J. (2019). The gut microbiome of healthy long-living people.

Aging, 11(2), 289–290.

Kim, M., & Benayoun, B. A. (2020). The microbiome: An emerging key player in

aging and longevity. Translational Medicine of Aging, 4, 103-116. doi:10.1016/j.tma.2020.07.004

Kim, S., & Jazwinski, S. (2018). The Gut Microbiota and Healthy Aging: A Mini-Review. Gerontology, 64(6), 513-520. doi:10.1159/000490615

Lozupone, C. A., & Turnbaugh, P. (2019). Decision letter: Adjusting for age improves identification of gut microbiome alterations in multiple diseases. doi:10.7554/elife.50240.sa1

Madhusoodanan, J. (2020). News Feature: Editing the microbiome. Proceedings of the National Academy of Sciences, 117(7), 3345-3348. doi:10.1073/pnas.2000108117

Mills, J. G., Brookes, J. D., Gellie, N. J., Liddicoat, C., Lowe, A. J., Sydnor, H. R., . . .

Breed, M. F. (2019). Relating Urban Biodiversity to Human Health With the ‘Holobiont’ Concept. Frontiers in Microbiology, 10. doi:10.3389/fmicb.2019.00550

Santoro, A., Ostan, R., Candela, M., Biagi, E., Brigidi, P., Capri, M., & Franceschi, C.

(2018). Gut microbiota changes in the extreme decades of human life: a focus on centenarians. Cellular and molecular life sciences : CMLS, 75(1), 129–148.

Topçuoğlu, B. D., Lesniak, N. A., Ruffin, M., Wiens, J., & Schloss, P. D. (2019). A

framework for effective application of machine learning to microbiome-based classification problems. doi:10.1101/816090

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