Integrated transcriptome and data-independent acquisition proteome analysis of the biosynthesis of Monascus azaphilone pigments and citrinin

  • Yingying Huang*
  • , Yanchun Shao
  • , Chenglong Yang
  • , István Molnár*
  • *Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Monascus azaphilone pigments (MPs) are widely used functional food additives. However, Monascus may simultaneously produce the mycotoxin citrinin (CIT), compromising MPs safety. Here, we used comparative genome, transcriptome, and quantitative data-independent acquisition mass spectrometry (DIA-MS) proteome analyses to compare three representative Monascus purpureus strains: M3 with high MPs and high CIT titers, M34 with high MPs and low CIT titers, and M69 with low titers of both products. Comparative genomic analysis confirmed high similarity among these strains. Differentially expressed genes (DEGs) and differentially abundant proteins (DAPs) were identified by pairwise comparisons among the strains during peak metabolite production, and selected DEGs and DAPs were verified by reverse transcription quantitative polymerase chain reaction and parallel reaction monitoring. An integrated analysis revealed DEG/DAPs correlating with altered MPs and CIT production, providing insights for strain breeding to engineer safer and more efficient MPs production processes in the food, cosmetics and pharmaceutical industries.

Original languageEnglish
Article number108377
JournalFood Bioscience
Volume77
DOIs
Publication statusPublished - Mar 2026
MoE publication typeA1 Journal article-refereed

Funding

This work was financially supported by the National Natural Science Foundation of China ( 31901803 to Y.H.); the Natural Science Foundation of Fujian Province ( 2023J01200 to Y.H.); the Science Foundation for Distinguished Young Scholars of Fujian Academy of Agricultural Science ( JCQN202404 to Y.H.); and VTT Technological Research Centre of Finland (to I.M).

Keywords

  • Comparative genomic analysis
  • DIA proteomics
  • Integrated analysis
  • Polyketide biosynthesis
  • RNA-Seq transcriptomics
  • Secondary metabolism

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