Institute for Systems Biology (ISB) researchers have simulated
personalized, microbiome-mediated responses to diet and predict
individual-specific short-chain fatty acid production rates in
response to different dietary, prebiotic, and probiotic inputs.
Short-chain fatty acids (SCFAs) are beneficial molecules created
by the bacteria residing in our gut that are closely tied to
improved host metabolism, lower systemic inflammation, better
cardiovascular health, lower cancer risk, and more. However, SCFA
profiles can vary widely between individuals consuming the same
exact diet and we currently lack tools for predicting this
inter-individual variation.
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Researchers at the Institute for Systems Biology (ISB) have
developed a novel way to simulate personalized, microbiome-mediated
responses to diet. They use a microbial community-scale metabolic
modeling (MCMM) approach to predict individual-specific SCFA
production rates in response to different dietary, prebiotic, and
probiotic inputs.
In other words, ISB scientists can build a “digital twin” of gut
microbiome metabolism that can simulate personalized responses to
diet, using gut microbiome sequencing data and information on
dietary intake to constrain each individual-specific model. They
detailed their results in a paper published in Nature
Microbiology.
“To a first approximation, the gut microbiome is a bioreactor
that converts dietary fibers into these SCFAs,” said Dr. Sean
Gibbons, ISB associate professor and co-senior author.
“Understanding how the ecology of the gut and dietary intake can be
quantitatively mapped to SCFA outputs will represent a major
advance in translating microbiome science into the clinic.”
Unlike black-box machine learning approaches to prediction,
MCMMs are transparent and mechanistic, with tens of thousands of
metabolites and enzymes across dozens of organisms providing a high
degree of knowledge about the specific microbes, dietary
components, and metabolic pathways that contribute to SCFA
production. Despite this transparency, the complexity of these
models makes them difficult to experimentally validate.
One approach is to measure SCFA production rates for an entire
ecosystem, and then compare these ecosystem-scale measures to their
cognate model predictions. However, measuring SCFAs in the wild is
tricky because the body rapidly consumes them after they are
created. In order to overcome this challenge, the authors measured
SCFA production rates from in vitro (i.e., test tube) communities
of random mixtures of human gut bacterial isolates and from ex vivo
(i.e., outside the body) stool homogenates from different humans
incubated in an anaerobic chamber with a variety of dietary
fibers.
By isolating microbiota-driven SCFA production from host
absorption, ISB scientists were able to show that MCMM predictions
were significantly correlated with measured production rates across
a range of fibers for both butyrate and propionate, two of the most
abundant and physiologically potent SCFAs.
While in vivo (i.e., in the body) measurements of butyrate and
propionate production were not feasible, the authors were able to
use indirect associations between SCFA production rates and
blood-based health markers to validate the physiological effects of
inter-individual differences of production. First, they showed that
MCMM predictions could differentiate between individuals from a
high-fiber feeding study who showed divergent immune responses:
most individuals showed a reduction in systemic markers of
inflammation, but a subset of people showed an increase in
inflammation on a high-fiber diet. Individuals in the
high-inflammation response group showed a significantly reduced
capacity for producing propionate, according to MCMM predictions.
Next, the authors showed that butyrate predictions were
significantly associated with blood markers of cardiometabolic and
immune health in a population of over 2,000 individuals.
Specifically, higher MCMM-predicted butyrate production was
significantly associated with lower LDL cholesterol, lower
triglycerides, improved insulin sensitivity, lower systemic
inflammation, and lower blood pressure.
“The predictive accuracy of MCMMs in vitro, coupled with the
significant associations between SCFA predictions and health
markers in human cohorts, gives us confidence in the utility of
these models for precision nutrition,” said lead author Dr. Nick
Quinn-Bohmann, a University of Washington graduate student at ISB
who recently defended his dissertation.
After validating MCMM predictions in a variety of ways, the
authors then demonstrated the potential of this approach for
designing personalized prebiotic, probiotic, and dietary
interventions that optimize SCFA production profiles. They
simulated butyrate production rates for two different diets – the
standard Austrian diet (i.e., standard European diet) and a vegan
high-fiber diet – across a cohort of over 2,000 individuals from
the Pacific West of the US. They found that a small subset of
individuals showed almost no increase in butyrate production when
switched to the high-fiber diet (termed “non-responders”) and
another subset actually saw a small drop in butyrate production on
the high-fiber diet (termed “regressors”). Next, they simulated
three simple co-interventions on both background diets to try and
augment butyrate production in the non-responders and the
regressors: adding the prebiotic fiber inulin, adding the prebiotic
fiber pectin, or adding a butyrate-producing probiotic
(Faecalibacterium). The results showed that no single combinatorial
intervention was optimal across all individuals: some benefited
most from adding a prebiotic fiber, while others appeared to
require the addition of a butyrate-producing probiotic to their
microbiota.
“Together, these results represent an important proof of concept
for a novel path forward in microbiome-mediated precision
nutrition,” said Dr. Christian Diener, co-senior author and
assistant professor at the Medical University of Graz in Austria.
“But, of course, there is more work to do to validate the
predictive capacity of these models in prospective human trials
before they can enter clinical practice.”
About ISB
Institute for Systems Biology (ISB) is a collaborative and
cross-disciplinary non-profit biomedical research organization
based in Seattle. We focus on some of the most pressing issues in
human health, including aging, brain health, cancer, COVID-19, as
well as many infectious diseases. Our science is translational, and
we champion sound scientific research that results in real-world
clinical impacts. ISB is an affiliate of Providence, one of the
largest not-for-profit health care systems in the United States.
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Joe Myxter Director of Communications, ISB
jmyxter@isbscience.org