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Reduced fecal concentrations of short- and branched-chain fatty acids, secondary bile acids, and tryptophan metabolites were associated with compositional microbiome dysbiosis and risk of postoperative infection.
Fecal metabolite profiling may be a viable tool for predicting postoperative infections in patients who received liver transplants, according to findings from a recent study published in Cell Host & Microbe.
Fecal metabolites were quantified for more than 100 patients undergoing liver transplantation and correlated with fecal microbiome compositions, pathobiont expansion, and postoperative infections, demonstrating reduced fecal concentrations of short- and branched-chain fatty acids, secondary bile acids, and tryptophan metabolites were associated with compositional microbiome dysbiosis and the relative risk of postoperative infection.1
Antimicrobial resistance and the development of drug-resistant pathogens make infections harder to treat and make other medical procedures and treatments much riskier. Infection is a major complication of liver transplantation, with risk further increased by the use of immunosuppressive anti-rejection medications. Given the heightened risk of infection in this patient population, understanding the microbiome’s role in this process is essential.2,3
“Antibiotic resistance is growing every year and getting worse. Without antibiotics that work, we can't do things like perform surgeries, protect premature infants or treat cancer,” said Christopher Lehmann, MD, assistant professor of medicine at the University of Chicago, in a press release.4 “It turns out the human microbiome, particularly the gut microbiome, has adapted to fight off drug-resistant bacteria over the course of history. We need to try to understand how that works to fight off these drug-resistant infections.”
Metabolites produced by the intestinal microbiome play an important role in modulating mucosal immune defenses and optimizing epithelial barrier function. The loss of microbiome diversity and expansion of antibiotic resistance is signaled by changes in fecal metabolite concentrations and more frequent systemic infection, but lab tests for quantifying this dybiosis have not yet been implemented in clinical practice, nor has its impact on clinical outcomes in liver transplantation been explored.1
To correlate metabolite concentrations with fecal microbiota compositions, multidrug-resistant organism expansion, and invasive infection, Lehmann and a team of investigators performed a prospective surveillance study in liver transplant recipients admitted to the University of Chicago Medical Center for liver transplantation. Among the 158 patients enrolled in the study, 107 underwent transplantation and provided a fecal sample for metabolite quantification and correlation.1
Upon analysis, short-chain fatty acids, secondary bile acid, B vitamins, and other metabolite concentrations successfully identified patients with preserved fecal microbiome diversity, reduced colonization density with pathobionts, and reduced rates of postoperative infection. Investigators pointed out reduced fecal concentrations of short- and branched-chain fatty acids, secondary bile acids, and tryptophan metabolites correlated with compositional microbiome dysbiosis and the relative risk of postoperative infection in this patient population.1
Rather than sequencing genomes to identify specific bacterial species, investigators examined fecal metabolites alone to see if those molecules offered the same predictive value. Along with distinguishing healthy microbiomes from unhealthy microbiomes, investigators found metabolites could also predict future infection and noted the amount of drug-resistant pathogens in the microbiome predicted postoperative infections with an accuracy they would expect from a clinical test, highlighting the strong predictive value of fecal metabolite profiling.1
“We can go straight from metabolites to predicting a clinical outcome. This is important because metabolomic analysis can be performed very quickly, whereas sequencing is relatively slow,” Lehmann concluded.4 “The next step of this course of research will be investigating whether we can use these findings to correct people’s microbiomes.”