A novel family of non-secreted tridecaptin lipopeptide produced by Paenibacillus elgii.
Rosiane Andrade da CostaIsadora Emanoela Pereira Costa AndradeOtávio Henrique Bezerra PintoBeatriz Blenda Pinheiro de SouzaDébora Luíza Albano FulgêncioMarise Leite MendonçaAdriane Silva KurokawaDaniel Barros OrtegaLucas Silva CarvalhoRicardo Henrique KrügerMarcelo Henrique Soller RamadaCristine Chaves BarretoPublished in: Amino acids (2022)
Bacteria from the genus Paenibacillus make a variety of antimicrobial compounds, including lipopeptides produced by a non-ribosomal synthesis mechanism (NRPS). In the present study, we show the genomic and phenotypical characterization of Paenibacillus elgii AC13 which makes three groups of small molecules: the antimicrobial pelgipeptins and two other families of peptides that have not been described in P. elgii. A family of lipopeptides with [M + H] + 1664, 1678, 1702, and 1717 m/z was purified from the culture cell fraction. Partial characterization revealed that they are similar to tridecaptin from P. terrae. However, they present amino acid chain modifications in positions 3, 7, and 10. These new variants were named tridecaptin G1, G2, G3, and G4. Furthermore, a gene cluster was identified in P. elgii AC13 genome, revealing high similarity to the tridecaptin-NRPS gene cluster from P. terrae. Tridecaptin G1 and G2 showed in vitro antimicrobial activity against Escherichia coli, Klebsiella pneumonia (including a multidrug-resistant strain), Staphylococcus aureus, and Candida albicans. Tri G3 did not show antimicrobial activity against S. aureus and C. albicans at all tested concentrations. An intriguing feature of this family of lipopeptides is that it was only observed in the cell fraction of the P. elgii AC13 culture, which could be a result of the amino acid sequence modifications presented in these variants.
Keyphrases
- amino acid
- candida albicans
- copy number
- staphylococcus aureus
- biofilm formation
- single cell
- multidrug resistant
- escherichia coli
- genome wide
- cell therapy
- machine learning
- stem cells
- klebsiella pneumoniae
- genome wide identification
- drug resistant
- gram negative
- deep learning
- pseudomonas aeruginosa
- cystic fibrosis
- gene expression
- acute respiratory distress syndrome
- mechanical ventilation