These new findings may affect how microbiology labs and physicians diagnose and treat several gastrointestinal conditions
Once again, a research effort has teased out new insights into the role the human microbiome plays in our digestive processes. Microbiologist and medical laboratory managers will be interested to learn that, according to the study team, specific microbes have a role in regulating how fast food moves through the digestive tract.
Researchers at the Dey Laboratory in Seattle recently examined the function of microbial bile acid metabolism in gut motility. They determined that “metabolites generated by the gut microbiome regulate gut transit,” according to a new paper published by the Fred Hutchinson Cancer Research Center (Fred Hutch).
“These findings have potential implications for the treatment of gastrointestinal conditions,” noted a Fred Hutch news release. This may mean new clinical laboratory tests to identify these strains of bacteria, along with new therapies for treating patients.
Gut motility (aka, Peristalsis) is the term used to describe the movement of food from the time it enters via the mouth until it leaves the body. This movement, the researchers found, is regulated by interactions between diet, the enteric nervous system (ENS) and the gut microbiota via processes that include bile acid metabolism.
Sex, Diet, and Lifestyle All Affect Treatment for Gastrointestinal Diseases
The Dey Laboratory researchers also discovered that sex was a significant variable in determining transit times with males having larger pro-motility effects.
“Our results suggest that strategies for treating or preventing gastrointestinal diseases may need to be tailored to sex and to biogeography of the gut,” they wrote. “While targeting the microbiome and the ENS is justified, our observation of significant transcriptional responses to defined interventions in a highly controlled gnotobiotic setting also highlights challenges to clinical translation.”
The researchers concluded that:
Gut microbiome-generated bile acids regulate colonic transit via TGR5 protein.
Bile acids exert sex-biased effects on gut transit times.
Enteric nervous system (ENS) transcriptional responses are regional- and microbiome-specific.
“The human experience—which reflects the aggregate effects of the innumerable dietary ingredients that we consume daily, the hugely diverse metabolically dynamic microbes that inhabit our guts, our own digestive processes, and the interactions of all of the above that result in thousands of gut metabolites—entails significantly more complex and variable transcriptional responses to environmental cues,” the Dey Laboratory scientists concluded.
To perform their research, the scientists developed both high and low BSH (bile salt hydrolase) bacterial communities for germ-free mice, which are known to exhibit slower gut motility and less complex bile acid profiles than colonized animals. (See graphic above taken from the Dey Laboratory published paper.)
The spice turmeric and dyes were added to the diets of the mice to track gut motility. The mice that were given the BSH-high microbiota had higher fecal concentrations of unconjugated bile acids than those given the BSH-low form of the microbiota. The mice given the BSH-high version also experienced faster transit times, according to the researchers’ iScience paper.
The researchers also concluded that the BSH-high group had greater fecal concentrations of lithocholic acid (LCA) which indicates variations in bile acid metabolism might affect gut transit.
When the scientists infused bile acids directly into mouse colons, variable acids reacted differently with LCA having the fastest transit times. The researchers hypothesized that LCA might signal through a bile receptor known as TGR5 which blocked the effects of LCA on colonic transit times. TGR5, also called G protein-coupled bile acid receptor, functions as a cell surface receptor for bile acids.
The Dey Laboratory team developed a method to measure expression changes in ENS genes and found that neither BSH activity nor gut transit phenotypes were major drivers of gene expression changes. They found that the location of the gut segment, or biogeography, was the leading contributor to ENS signature variance between samples.
The scientists “identified consortium-specific transcriptional changes in genes involved in ENS signaling, development, maintenance, and bile acid metabolism, and these differed across regions of the GI tract. Together these findings indicate that ENS transcriptional responses are regional and microbiome-specific,” according to the Fred Hutch press release.
“This remains a confusing part of the story for us—how is it that we can see predictable host motility responses when colonizing the guts of gnotobiotic mice with phenotypically defined communities, but the middle-man (the host enteric nervous system) appears to have such varied responses?” the Dey Laboratory researchers noted in the press release.
“It suggests that gut motility phenotypes that appear similar may in fact represent (when we look under the hood) diverse host physiologic phenotypes that we are just beginning to understand,” they added.
The results of this study could have potential implications for the precision medicine diagnosis and treatment of gastrointestinal illnesses.
Blue Poop Challenge
Earlier this year, people were encouraged to participate in the “blue poop challenge” conducted by research company ZOE Global Limited (ZOE) to determine how long it takes food to travel through the body.
For the Blue Poop Challenge, individuals are asked to eat blue muffins and then report on the company’s website as to how long it took for the blue dye to appear in their stools.
The purpose of this ongoing study is to reveal pertinent information about an individual’s gut health and microbiome.
Since 2010, Dark Daily has reported on dozens of research studies and innovative developments involving human microbiome and gut bacteria and their critical importance in the development of clinical laboratory testing, drug therapies, and precision medicine.
These studies’ findings could lead to improved immune system therapeutics and associated clinical laboratory tests.
“All of this suggests the potential in the future for clinical laboratories and microbiologists to do microbiome testing in support of clinical care,” said Robert Michel, Editor-in-Chief of Dark Daily and its sister publication The Dark Report.
More research is needed in these areas. But gut bacteria and the human microbiome are an integral part of our health and wellbeing. It is worth keeping an eye on new developments in those fields of study.
The KCL researchers’ new models for predicting which patients will need hospitalization and breathing support may be useful for pathologists and clinical laboratory scientists
One more window into understanding the SARS-CoV-2 coronavirus may have just opened. A British study identified six distinct “clusters” of symptoms that the research scientists believe may help predict which patients diagnosed with COVID-19 will require hospitalization and respiratory support. If further research confirms these early findings, pathologists and medical laboratory managers may gain new tools to diagnose infections faster and more accurately.
Launched in March in the United Kingdom and extended to the United States and Sweden, the app has attracted more than four million users who track their health and potential COVID symptoms on a daily basis.
Increased Accuracy in Predicting COVID-19 Hospitalizations
KCL researchers identified six distinct “types” of COVID-19, each distinguished by a particular cluster of symptoms. They include headaches, muscle pains, fatigue, diarrhea, confusion, loss of appetite, shortness of breath, and more. The researchers also found that COVID-19 disease progression and outcome also vary significantly between people, ranging from mild flu-like symptoms or a simple rash to severe or fatal conditions.
Using app data logged by 1,600 users in March and April, the researchers developed an algorithm that combined information on age, gender, body mass index (BMI), and pre-existing conditions with recorded symptoms from the onset of the illness through the first five days. The researchers then tested the algorithm using a second independent dataset of 1,000 users, logged in May.
In a news release, the KCL researchers identified the six clusters of symptoms as:
Flu-like with No Fever: Headache, loss of smell, muscle pains, cough, sore throat, chest pain, no fever.
Flu-like with Fever: Headache, loss of smell, cough, sore throat, hoarseness, fever, loss of appetite.
Gastrointestinal: Headache, loss of smell, loss of appetite, diarrhea, sore throat, chest pain, no cough.
Severe Level One, Fatigue: Headache, loss of smell, cough, fever, hoarseness, chest pain, fatigue.
Severe Level Two, Confusion: Headache, loss of smell, loss of appetite, cough, fever, hoarseness, sore throat, chest pain, fatigue, confusion, muscle pain.
Severe Level Three, Abdominal and Respiratory: Headache, loss of smell, loss of appetite, cough, fever, hoarseness, sore throat, chest pain, fatigue, confusion, muscle pain, shortness of breath, diarrhea, abdominal pain.
Using the data, the researchers were able to more accurately predict—78.8% versus 69.5%—which of the six symptom clusters placed patients at higher risk of requiring hospitalization and breathing support (ventilation or additional oxygen) than with prediction models based on personal characteristics alone. For example, nearly 50% of the patients in cluster six (Severe Level Three, Abdominal and Respiratory) ended up in the hospital, compared with 16% of those in cluster one (Flu-like with No Fever).
According to the Zoe website, the ongoing research is led by:
Prof. Tim Spector, FMedSci, Professor of Genetic Epidemiology at King’s College London and Director of TwinsUK, an adult registry of twins in the United Kingdom;
Andrew Chan, MD, Professor of Medicine at Harvard Medical School, Professor of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health and Chief of the Clinical and Translational Epidemiology Unit, CTEU Massachusetts General Hospital; and
Encouraging Everyone to Use the COVID-Symptom Study App
The study points out that—broadly speaking—people with cluster four, five, or six COVID-19 symptoms tended to be older and frailer and were more likely to be overweight and have pre-existing conditions, such as diabetes or lung disease, than those with cluster one, two, or three symptoms.
Tim Spector, FMedSci, Head of the Department of Twin Research and Genetic Epidemiology, and Professor of Genetic Epidemiology at King’s College London, encourages everyone to download the COVID Symptom Study app and help increase the data available to researchers.
“Data is our most powerful tool in the fight against COVID-19,” Spector said in the KCL news release. “We urge everyone to get in the habit of using the app daily to log their health over the coming months, helping us to stay ahead of any local hotspots or a second wave of infections.”
As the body of knowledge surrounding COVID-19 grows, clinical laboratory professionals would be well advised to remain informed on further research regarding not only the potential for COVID-19 variants to exist, but also the evolving guidance on infection prevention and testing.