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Pyrroloquinoline quinone production defines the ability of Devosia species to degrade deoxynivalenol.

Chongwen GuoJikai WenYu SunGuoqiang LiangZijiao WangLulu PanJiarun HuangYuanxin LiaoZeyuan WangQingmei ChenPeiqiang MuYiqun Deng
Published in: Food & function (2024)
Deoxynivalenol (DON) is a prevalent mycotoxin that primarily contaminates cereal crops and animal feed, posing a significant risk to human and animal health. In recent years, an increasing number of Devosia strains have been identified as DON degradation bacteria, and significant efforts have been made to explore their potential applications in the food and animal feed industries. However, the characteristics and mechanisms of DON degradation in Devosia strains are still unclear. In this study, we identified a novel DON degrading bacterium, Devosia sp. D-G15 (D-G15), from soil samples. The major degradation products of DON in D-G15 were 3-keto-DON, 3- epi -DON and an unidentified product, compound C. The cell viability assay showed that the DON degradation product of D-G15 revealed significantly reduced toxicity to HEK293T cells compared to DON. Three enzymes for DON degradation were further identified, with G15-DDH converting DON to 3-keto-DON and G15-AKR1/G15-AKR6 reducing 3-keto-DON to 3- epi -DON. Interestingly, genome comparison of Devosia strains showed that the pyrroloquinoline quinone (PQQ) synthesis gene cluster is a unique feature of DON degradation strains. Subsequently, adding PQQ to the cultural media of Devosia strains without PQQ synthesis genes endowed them with DON degradation activity. Furthermore, a novel DON-degrading enzyme G13-DDH (<30% homology with known DON dehydrogenase) was identified from a Devosia strain that lacks PQQ synthesis ability. In summary, a novel DON degrading Devosia strain and its key enzymes were identified, and PQQ production was found as a distinct feature among Devosia strains with DON degradation activity, which is important for developing Devosia strain-based technology in DON detoxification.
Keyphrases
  • escherichia coli
  • public health
  • machine learning
  • genome wide
  • endothelial cells
  • deep learning
  • high throughput
  • plant growth