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Fecal microbiome inadequately represents gut microbiome

Aug

27

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While fecal sampling is the current standard for representing the whole human gut microbiome, fecal microbiome is insufficient to represent the whole gut microbiome of the GI tract in a recent study of pigs, according to Hindawa Cellular Biology January 17 2023 issue.

For one, stool consistency varies over time. In addition, both gut microbiome composition and phenotypes or diseases of interest help define the nature of one’s health. Researchers then found a significant compositional difference of gut microbiome by specific location along the GI tract. All this calls for greater accuracy than exclusively using stool samples as a means for determining gut health and gut research.

https://www.hindawi.com/journals/cmi/2023/6868417/

Links in relationships also link gut bacteria

Aug

17

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In the last Herbsprout blog, we learned about the interchange of gut microbes between pets and their owners. This blog is taken from Psychology Today. Though lacking the scientific references, one can safely assume what applies to humans and their pets also applies person to person.

We begin with proximity. Proximity to peers plays a role in the microbial content of our gut. Gut microbiome links in family relationships begin at early childhood when the mother’s microbiome influences the gut microbiota of the baby, and continues throughout life, according to an August 09 2023 article in Psychology Today.

People who live with us or are relatively close to us impact the shape of our gut, skin, and oral microbiomes, say the Psychology Today article. This includes family members, friends, and neighbors (1).

Diseases associated with microbiome dysfunction, including obesity, type 2 diabetes, and cognitive disorders, could be influenced by the microbiomes of those around us.

For instance, some diseases that were not previously found communicable have now been considered to be at least partially communicable, such as diabetes or inflammatory bowel disease (1).

The downside of these influences however, include antibiotic resistance that develops in a common community due in part to their micriobial commonalities, as warned by Alexander Fleming in 1945 in his Nobel acceptance speech (2).

1. https://www.psychologytoday.com/intl/blog/the-behavioral-microbiome/202308/microbiome-new-criteria-for-selecting-a-partner?amp

2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4939477/

 

humans and pets exposed to each other’s gut microbiome show improvements to lifelong health

Aug

10

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In a brand new area of research, people exposed to more furry pets and green space early in life have a lower risk of immune and allergic conditions later, according to Curtis Huttenhower, professor of computational biology and bioinformatics at Harvard T.H. Chan School of Public Health in his June 29, 2023 interview. He believes some of those effects are due to the microbiome from their pets. Likewise, pets too can benefit from exposure to the human gut microbiome, adds Huttenhower.

In partnership with the Pet Nutrition Center, because pets maintain consistent food consumption, the Center’s staff along with robotics track the specific types and amounts of food consumed by each individual animal, which includes a consistent diet compared to humans.

Huttenhower explains how the degree to which high-fiber diets help prevent inflammation depends on which gut microbes people have, which is why people respond to the same diet differently. “We all carry vastly different bugs in our microbiomes,” he adds.

The interchange of pet and human microbes presents the opportunity to acquire the “right” microbes at the “right” times leading to better lifelong health.

https://www.hsph.harvard.edu/news/features/gut-microbiome-of-pets-reveals-insights-for-human-health-curtis-huttenhower/

Machine learning of microbiome used to predict cancer

Aug

1

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Technology advances in DNA sequencing and more sophisticated data-analytics tools has led to extensive research on the relationship between the microbiome and diseases. Researchers are developing a machine learning-based approach to distinguish the type of cancer by analyzing the tissue-specific microbial information, according to the July 21, 2023 issue of Nature.com (1).

Random Forest models of five types of cancers from the Cancer Microbiome Atlas database, achieved promising performances when predicting head and neck, stomach, and colon cancer cases, with the latter showing 90% accuracy across the different studies conducted, says the Nature article. The random forest method forms multiple decision trees in machine learning by regression classification task outputs (2).

This research shows the potential of adopting machine learning techniques in predicting disease and cancer.

1. https://www.nature.com/articles/s41598-023-38670-0

2. https://en.m.wikipedia.org/wiki/Random_forest