最先端技術が人間の代謝の辞書を拡張(Cutting-Edge Technology Expands Dictionary of Human Metabolism)

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2025-06-10 カリフォルニア大学サンディエゴ校 (UCSD)

カリフォルニア大学サンディエゴ校の研究チームは、ヒト代謝に関する知識を大幅に拡張し、851種のN-アシル脂質を同定、そのうち777種はこれまで報告されていなかった新規分子であると発表した。これらの多くは腸内マイクロバイオーム由来と考えられ、食事や疾患(例:糖尿病)によって分布が異なることが示された。さらに、HIV感染者の認知機能との関連も示唆され、腸内細菌が脳機能に影響を及ぼす可能性もある。新手法「リバースメタボロミクス」により、生体内の化学的言語を解読し、微生物と人間の相互作用理解を深化させた。研究成果はCell誌に掲載。

<関連情報>

マイクロバイオームが長鎖脂肪酸から短鎖脂肪酸由来のN-アシル脂質に多様化する The microbiome diversifies long- to short-chain fatty acid-derived N-acyl lipids

Helena Mannochio-Russo ∙ Vincent Charron-Lamoureux ∙ Martijn van Faassen ∙ … ∙ Dionicio Siegel ∙ Rob Knight ∙ Pieter C. Dorrestein
Cell  Published:June 10, 2025
DOI:https://doi.org/10.1016/j.cell.2025.05.015

Graphical abstract

最先端技術が人間の代謝の辞書を拡張(Cutting-Edge Technology Expands Dictionary of Human Metabolism)

Highlights

  • MS/MS data mining enables the creation of an N-acyl lipid spectral library resource
  • Short-chain fatty acid-derived N-acyl lipids are described
  • N-acyl histamines and cadaverines are linked to HIV and neurocognitive impairment
  • N-acyl cadaverines show immunomodulatory effects of T cells

Summary

N-Acyl lipids are important mediators of several biological processes including immune function and stress response. To enhance the detection of N-acyl lipids with untargeted mass spectrometry-based metabolomics, we created a reference spectral library retrieving N-acyl lipid patterns from 2,700 public datasets, identifying 851 N-acyl lipids that were detected 356,542 times. 777 are not documented in lipid structural databases, with 18% of these derived from short-chain fatty acids and found in the digestive tract and other organs. Their levels varied with diet and microbial colonization and in people living with diabetes. We used the library to link microbial N-acyl lipids, including histamine and polyamine conjugates, to HIV status and cognitive impairment. This resource will enhance the annotation of these compounds in future studies to further the understanding of their roles in health and disease and to highlight the value of large-scale untargeted metabolomics data for metabolite discovery.

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