Search bioRxiv⌕ Search

Biology subjects

Moghimi, M.

Publications and source records attributed to Moghimi, M..

2 recordsLinked to original sources

Elucidating a potential role of the infant gut microbiome on the bioavailability of L-tyrosine in phenylketonuria

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.

systems biology↗

CHROMAS: A Computational Pipeline to Track Chromatophores and Analyze their Dynamics

Cephalopod chromatophores are small dermal neuromuscular organs, each consisting of a pigment-containing cell and 10-20 surrounding radial muscles. Their expansions and contractions, controlled and coordinated by the brain, are used to modify the animals appearance during camouflaging and signaling. Building up on tools developed by this lab, we propose a flexible computational pipeline to track and analyse chromatophore dynamics from high-resolution videos of behaving cephalopods. This suite of functions, which we call CHROMAS, segments and classifies individual chromatophores, compensates for animal movements and skin deformations, thus enabling precise and parallel measurements of chromatophore dynamics and long-term tracking over development. A high-resolution tool for the analysis of chromatophore deformations during behavior reveals details of their motor control and thus, their likely innervation. When applied to many chromatophores simultaneously and combined with statistical and clustering tools, this analysis reveals the complex and distributed nature of the chromatophore motor units. We apply CHROMAS to the skins of the bobtail squid Euprymna berryi and the European cuttlefish Sepia officinalis, illustrating its performance with species with widely different chromatophore densities and patterning behaviors. More generally, CHROMAS offers many flexible and easily reconfigured tools to quantify the dynamics of pixelated biological patterns.

animal behavior and cognition↗