Iranian
Biomedical Journal
Volume 29, Issue 1 And 2 (1-2025)
IBJ 2025, 29(1 And 2): 68-81 |
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Ethics code: IR.PII.REC.1400.0.56
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Aminzadeh M, Bahrami F, Piryaei Z, Vasighi M, Kalantari Z, Arjmand* M et al . Unraveling Leishmania major Metacyclogenesis: A Comprehensive Analysis of Transcriptomic and Metabolomic Profiles. IBJ 2025; 29 (1 and 2) :68-81
URL: http://ibj.pasteur.ac.ir/article-1-4899-en.html
URL: http://ibj.pasteur.ac.ir/article-1-4899-en.html
Mansour Aminzadeh 
, Fariborz Bahrami , Zeynab Piryaei , Mahdi Vasighi , Zahra Kalantari , Mohammad Arjmand* , Soheila Ajdary *
, Fariborz Bahrami , Zeynab Piryaei , Mahdi Vasighi , Zahra Kalantari , Mohammad Arjmand* , Soheila Ajdary *
Abstract:
Background: Metacyclogenesis, a key process in the Leishmania (L.) life cycle, involves the transformation of non-infective procyclic promastigotes into infective metacyclic forms. This transition is driven by metabolic adaptations essential for parasite survival and infectivity. This study integrates metabolomics and transcriptomics to elucidate the molecular mechanisms underlying L. major metacyclogenesis.
Methods: Metabolic profiles of procyclic and metacyclic forms were analyzed using ¹H-NMR spectroscopy, followed by multivariate statistical analysis to identify differential metabolites. Pathway analysis utilized the KEGG database to pinpoint altered metabolic pathways. Besides, transcriptomic data from public repositories were analyzed for differential gene expression and pathway enrichment.
Results: Multivariate statistical analysis revealed 44 significantly different metabolites and ten altered pathways between the two forms. Transcriptomics showed 238 upregulated and 49 downregulated genes during metacyclogenesis. Upregulated genes were associated with protein phosphorylation, ion transport, and signal transduction, while several GO categories were downregulated. Integrated omics data highlighted seven significantly altered KEGG pathways, including fructose/mannose, galactose, arginine/proline, histidine, inositol phosphate, and pyruvate metabolism.
Conclusion: The transition from procyclic to metacyclic forms involves distinct metabolic and gene expression changes. Integrating metabolomics and transcriptomics identified key altered pathways and potential biomarkers, providing deeper insights into the mechanisms of metacyclogenesis and highlighting targets for therapeutic intervention.
Methods: Metabolic profiles of procyclic and metacyclic forms were analyzed using ¹H-NMR spectroscopy, followed by multivariate statistical analysis to identify differential metabolites. Pathway analysis utilized the KEGG database to pinpoint altered metabolic pathways. Besides, transcriptomic data from public repositories were analyzed for differential gene expression and pathway enrichment.
Results: Multivariate statistical analysis revealed 44 significantly different metabolites and ten altered pathways between the two forms. Transcriptomics showed 238 upregulated and 49 downregulated genes during metacyclogenesis. Upregulated genes were associated with protein phosphorylation, ion transport, and signal transduction, while several GO categories were downregulated. Integrated omics data highlighted seven significantly altered KEGG pathways, including fructose/mannose, galactose, arginine/proline, histidine, inositol phosphate, and pyruvate metabolism.
Conclusion: The transition from procyclic to metacyclic forms involves distinct metabolic and gene expression changes. Integrating metabolomics and transcriptomics identified key altered pathways and potential biomarkers, providing deeper insights into the mechanisms of metacyclogenesis and highlighting targets for therapeutic intervention.
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