JOURNAL ARTICLE

Correlation between sporogenesis and lipopeptide production in Paenibacillus elgii.

  • Published In: Letters in Applied Microbiology, 2024, v. 77, n. 9. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: da Costa, Rosiane Andrade; Andrade, Isadora Emanoela Pereira Costa; de Araújo, Thiago Fellipe; Fulgêncio, Débora Luiza Albano; Mendonça, Marise Leite; Rocha, Gabriel Iudy Yamaguchi; dos Santos, Raiana Moreira; Barreto, Cristine Chaves 3 of 3

Abstract

This article focuses on optimizing the production of antimicrobial lipopeptides pelgipeptins and tridecaptins by the bacterium *Paenibacillus elgii* AC13 using chemically defined media. The study found that removing calcium ions (Ca²⁺) from the culture medium interrupted sporogenesis (spore formation) in *P. elgii* AC13 and significantly increased pelgipeptin yield in both the supernatant and cell fraction, while tridecaptin production remained largely cell-associated and unaffected by calcium absence. These findings suggest that pelgipeptin production is inversely related to spore formation, enhancing its potential for commercial antimicrobial applications, whereas tridecaptins may be degraded or bound to cell debris, complicating their recovery. The use of chemically defined media with specific nutrient modifications improved pelgipeptin yields compared to complex media, offering a more efficient approach for biotechnological exploitation of these antimicrobial peptides.

Additional Information

  • Source:Letters in Applied Microbiology. 2024/09, Vol. 77, Issue 9, p1
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2024
  • ISSN:0266-8254
  • DOI:10.1093/lambio/ovae079
  • Accession Number:180267948
  • Copyright Statement:Copyright of Letters in 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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