English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The inhibitory properties of novel antimicrobial proteins against food-borne pathogens such as  Listeria monocytogenes  offer extensive benefits to the food and medical industries. In this study, we have identified antimicrobial proteins from a milk curd–derived bacterial isolate that exhibits antilisterial activity using genome mining and mass spectrometry analysis. The analysis of the draft genome sequence identified the isolate as  Paenibacillus polymyxa  Kp10, and predicted the presence of antimicrobial paenibacillin, paenilan, paeninodin, sactipeptides, thiazole-oxazole modified microcin, and histone-like DNA binding protein HU encoded in its genome. Interestingly, nanoLC-MS/MS analysis identified two histone-like DNA binding proteins HU as predicted  in silico  earlier, exhibiting antilisterial activity. Additionally, translation initiation factor IF-1 and 50S ribosomal protein L29 were also discovered by the mass spectrometry in the active fractions. The antilisterial activity of the four proteins was verified through heterologous protein expression and antimicrobial activity assay  in vitro . This study has identified structural regulatory proteins from  Paenibacillus  possessing antilisterial activity with potential future application in the food and medical industries.

The Discovery of New Antilisterial Proteins From Paenibacillus polymyxa Kp10 via Genome Mining and Mass Spectrometry