Identification and functional assessment of a bioactive peptide from the Tiannan odorous frog, Odorrana tiannanensis

Abstract

Amphibian skin secretions serve as chemical defence mechanisms to protect against predators in their natural habitats. Among the diverse classes of compounds present in these secretions, peptides exhibiting a range of bioactivities, such as antimicrobial and pharmacological properties, are typically the most abundant. These peptides may hold significant therapeutic potential. Notably, antimicrobial peptides (AMPs) offer distinct advantages over conventional clinical antibiotics. As the issue of antibiotic resistance becomes increasingly severe, the urgency to discover novel antimicrobial molecules has intensified. AMPs derived from amphibian defensive skin secretions have demonstrated exceptional bioactivities, positioning them as one of the most promising groups of molecules for potential therapeutic applications.

In this study, a cDNA containing coding information for peptide QUB-2051 was identified from the skin secretion of Odorrana tiannanensis using ‘shotgun’ cloning and its encoded mature peptide, sequenced as SILSGIFGVGKKIVCGLSGLC, was synthesised by solid-phase peptide synthesis. The synthetic peptide was characterised by matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) mass spectrometry and purified by reverse-phase high performance liquid chromatography (RP-HPLC). The purified peptide was screened for antimicrobial and anti-lung cancer activities. The results revealed that QUB-2051 exhibited antimicrobial activity against S. aureus (MIC = 4 µM), E. coli (MIC = 8 µM), and C. albicans (MIC = 2 µM). The anticancer activity of the peptide on lung cancer cell proliferation was evident with concentrations of 50 µM or more. Based on these findings, QUB-2051 has potential as a promising therapeutic drug candidate for future study.

Thesis is embargoed until 31st December 2029.

Date of Award	Dec 2024
Original language	English
Awarding Institution	Queen's University Belfast
Supervisor	Lei Wang (Supervisor), Tianbao Chen (Supervisor) & Mei Zhou (Supervisor)