Worms as models for personalized medicine

Tailoring a person’s diet or medications based on their genome has been a goal of the medical community for decades, but the strategy has not been widely successful because people metabolize chemicals differently. A drug may work differently for two patients because they have different metabolisms, which may be due to genetic, environmental, or microbial differences.

Researchers in the BTI laboratory of Professor Frank Schroeder and colleagues have used a simple roundworm, Caenorhabditis elegans, as an experimental model that could link genomic differences to differences in metabolism. The work was published in Nature on July 6.

“Individuals have different metabolisms, and that’s important for how different diets, diseases, and medications affect us,” said Schroeder, one of the paper’s authors. “You need to find ways to tailor biomedical recommendations for different people based on their individual metabolism.”

Understanding a person’s metabolism based on their genome is particularly difficult because human studies can never really be replicated to confirm or refute the results, said Schroeder, who is also a professor in the Department of Chemistry and Chemical Biology at Cornell University.

“If you collect data from one person, you never get a chance to sample another individual with the same genetic background, age, microbiome and environmental exposure,” Schroeder said. “This makes it very difficult to unravel the genetic traits responsible for the different metabolic variants.”

The roundworms C. elegans are well-suited for the job because their metabolism is surprisingly similar to that of humans, and they are self-fertilizing hermaphrodites, allowing researchers to obtain thousands of worms that share identical genomes.

“Each strain of C. elegans can be considered a unique individual,” said Bennett Fox, a postdoctoral scientist in Schroeder’s laboratory and first author of the paper. “Another major advantage is the ease of genome editing in C. elegans, which allowed us to experiment directly with gene-edited strains and test our hypotheses in live animals.”

The researchers looked at four “individual” worm strains: a standard laboratory strain, two wild strains from Hawaii and one wild strain from Taiwan. The animals grow under standard conditions at the same stage of development.

“We performed an untargeted analysis using high-resolution mass spectrometry and observed more than 20,000 unique metabolites, most of which remain unknown,” Fox said. “It was interesting to find strain-specific metabolites, compounds that were highly enriched or depleted in one strain relative to the other three strains.”

The researchers focused their efforts on a previously unidentified group of compounds described as conjugates between 3-hydroxypropionate (3HP) and several amino acids (3HP-AA). 3HP is toxic at high levels, and is normally metabolized by an enzyme called HPHD-1.

In one wild strain of C. elegans, the team found a mutation in the gene encoding HPHD-1 that produces an enzyme with reduced function. In response to the function-reducing mutation, this strain increased the production of 3HP-AA, which the researchers hypothesized to represent a detoxification mechanism.

“We’ve shown one way that genetic variants can manifest in metabolic differences,” said Schroeder. “And now we can look for similar variants or analogues in humans.”

“We show how to uncover the genetic basis of inter-individual metabolic variation, and this could help the field of personalized medicine fulfill its promise,” added Schroeder.

Schroeder’s lab, which specializes in biochemistry and identification of unknown metabolites, works closely with the Walhout lab (systems biology, metabolism) at the University of Massachusetts Chan Medical School and the Andersen lab (natural variation, quantitative genetics) at Northwestern University. The unique synergy and complementary interests of the three labs together resulted in this important step forward for modeling metabolism in different individuals.

This research was supported by a grant from the National Institutes of Health (DK115690).

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