Elucidating a potential role of the infant gut microbiome on the bioavailability of L-tyrosine in phenylketonuria
Mohammadreza Moghimi, Filippo MartinelliiD, Jonas Widder, Tim HenseniD, Luciana HannibaliD, Ute SpiekerkoetteriD, Ines ThieleiD
Abstract
BackgroundPhenylketonuria (PKU) is an inherited metabolic disorder caused by phenylalanine hydroxylase (PAH) deficiency, leading to elevated L-phenylalanine and severe neurological damage if untreated. While phenylalanine-based biomarkers are diagnostic and phenylalanine levels correlate with disease severity, the clinical manifestations of PKU are heterogeneous. ResultsTo identify additional reliable, potentially novel biomarkers, we used germ-free sex-specific, organ-resolved infant whole-body metabolic models (infant-WBMs) to simulate PAH deficiency and predicted elevated L-phenylalanine and its derivatives, alongside reduced L-tyrosine fluxes, as the product of phenylalanine hydroxylation. To test the reliability of these predictions, we combined the infant-WBMs with gut microbiome models from 48 healthy infants. Upon integrating microbiome data, we found that microbial metabolism significantly increased L-tyrosine availability, obscuring its utility as a universal biomarker. In [~]23% of microbiome-PKU models, L-tyrosine fluxes remained low, indicating insufficient microbial compensation. These cases were enriched in Firmicutes and lacked specific Bifidobacterium and Escherichia strains linked to L-tyrosine biosynthesis via the pretyrosine pathway. Shadow price analysis identified microbial species critical for host L-tyrosine metabolism. However, some, such as Bifidobacterium dentium, also contributed to L-phenylalanine synthesis, potentially worsening the PKU phenotype. In contrast, L-phenylalanine, phenylpyruvate, and hydroxyphenylacetic acid remained reliably elevated across all models, validating their diagnostic relevance. ConclusionsOur study demonstrates that microbiome composition can modulate biomarker reliability in PKU, particularly for L-tyrosine. Integrating microbial metabolic models with whole-body physiology enables assessment of biomarker reliability and reveals subpopulations for whom secondary biomarkers or targeted probiotics may be beneficial. This approach offers a powerful framework for refining diagnostics and therapy monitoring in rare metabolic diseases and the development of possible targeted microbiome therapies.
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