JOURNAL ARTICLE

Molecular phylogenetics of the Umbelopsis genus—identification of new species and evaluation of their oil application value.

  • Published In: Journal of Applied Microbiology, 2024, v. 135, n. 4. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Hou, Donghai; Tang, Dexiang; Wang, Yao; Zhu, Juye; Luo, Run; Liu, Zuoheng; Lu, Yingling; Sun, Tao; Ma, Yanhong; Zhang, Yuyao; Yu, Hong 3 of 3

Abstract

This article focuses on the taxonomic reconstruction and lipid characterization of the fungal genus Umbelopsis, including the description of a new species, Umbelopsis ophiocordycipiticola. Using morphological traits and multilocus phylogenetic analysis of ITS, LSU, and ACT genes, the study identified three Umbelopsis species and established U. ophiocordycipiticola as a novel species distinguished by its sporangia and sporangiospore morphology. Gas chromatography–mass spectrometry revealed that U. ophiocordycipiticola has a notably high oil content (up to 50.89% dry cell weight) with a substantial proportion of polyunsaturated fatty acids (PUFAs), including γ-linolenic acid, arachidonic acid, eicosapentaenoic acid, and docosahexaenoic acid. All three species demonstrated fatty acid profiles suitable for biodiesel production, meeting standards set by the American Association for Testing and Materials (ASTM 6751) and the Brazilian National Petroleum Agency (ANP 255), with U. ophiocordycipiticola showing particular promise for both biofuel and nutraceutical applications.

Additional Information

  • Source:Journal of Applied Microbiology. 2024/04, Vol. 135, Issue 4, p1
  • Document Type:Article
  • Subject Area:Nutrition and Dietetics
  • Publication Date:2024
  • ISSN:1364-5072
  • DOI:10.1093/jambio/lxae065
  • Accession Number:177016892
  • Copyright Statement:Copyright of Journal of Applied Microbiology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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