Back

Recombinant expression, purification, and antifungal activity of the novel antimicrobial peptide TaW662

wang, c.; yang, b.; yang, y.; kang, l.; liu, f.; wang, z.; Feng, D.

2024-04-30 plant biology
10.1101/2024.04.29.591476 bioRxiv
Show abstract

Blumeria graminis f. sp. tritici (Bgt) is a significant wheat fungal pathogen, posing threats to both yield and quality. Antimicrobial peptides, with their broad-spectrum activities, hold promise in combating Bgt-induced wheat fungal diseases.In this study, we identified TaW662, an antifungal peptide gene sourced from the wheat-Thinopyrum intermedium disomic alien addition line SN6306. Through third-generation transcriptome sequencing, we obtained the full-length transcript of TaW662. Notably, TaW662 exhibited upregulated expression in response to powdery mildew infection in SN6306. Subcellular localization analysis revealed TaW662s extracellular secretion, suggesting its role in defense mechanisms. Additionally, the TaW662 protein was expressed in Escherichia coli, and the purified protein could inhibit the growth of Bgt in vitro. Utilizing the online alphafold2 server, we predicted the three-dimensional structure of TaW662, aiding in understanding its fungicidal mechanisms. Analysis of TaW662s physicochemical properties further supported its potential efficacy as a fungicide against Bgt. In conclusion, TaW662 emerges as a promising candidate for combating Bgt-induced wheat fungal diseases, warranting further exploration for agricultural disease management strategies. HighlightsTaW662, a secreted protein homologous to TaWIR1, is induced in wheat by Blumeria graminis f. sp. tritici (Bgt). The expression pattern of TaW662 in wheat under induced by Bgt was analysed using RNA-Seq technology. The three-dimensional structure of TaW662 was predicted using AlphaFold2. The growth of Bgt is inhibited by recombinant TaW662.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.