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Uncovering Nematicidal Natural Products from Xenorhabdus Bacteria.

ABSTRACT: Parasitic nematodes infect different species of animals and plants. Root-knot nematodes are members of the genus Meloidogyne, which is distributed worldwide and parasitizes numerous plants, including vegetables, fruits, and crops. To reduce the global burden of nematode infections, only a few chemical therapeutic classes are currently available. The majority of nematicides are prohibited due to their harmful effects on the environment and public health. This study was intended to identify new nematicidal natural products (NPs) from the bacterial genus Xenorhabdus, which exists in symbiosis with Steinernema nematodes. Cell-free culture supernatants of Xenorhabdus bacteria were used for nematicidal bioassay, and high mortality rates for Caenorhabditis elegans and Meloidogyne javanica were observed. Promoter exchange mutants of biosynthetic gene clusters encoding nonribosomal peptide synthetases (NRPS) or NRPS-polyketide synthase hybrids in Xenorhabdus bacteria carrying additionally a hfq deletion produce a single NP class, which have been tested for their bioactivity. Among the NPs tested, fabclavines, rhabdopeptides, and xenocoumacins were highly toxic to nematodes and resulted in mortalities of 95.3, 74.6, and 72.6% to C. elegans and 82.0, 90.0, and 85.3% to M. javanica, respectively. The findings of such nematicidal NPs can provide templates for uncovering effective and environmentally safe alternatives to commercially available nematicides.

SUBMITTER: Abebew D

PROVIDER: S-EPMC8778618 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objective: Ferroptosis, a novel form of cell death, is closely associated with excessive iron accumulated within the substantia nigra in Parkinson's disease (PD). Despite extensive research, the underlying molecular mechanisms driving ferroptosis in PD remain elusive. Here, we employed a bioinformatics and machine learning approach to predict the genes associated with ferroptosis in PD and investigate the interactions between natural products and their active ingredients with these genes. Methods: We comprehensively analyzed differentially expressed genes (DEGs) for ferroptosis associated with PD (PDFerDEGs) by pairing 3 datasets (GSE7621, GSE20146, and GSE202665) from the NCBI GEO database and the FerrDb V2 database. A machine learning approach was then used to screen PDFerDEGs for signature genes. We mined the interacted natural product components based on screened signature genes. Finally, we mapped a network combined with ingredients and signature genes, then carried out molecular docking validation of core ingredients and targets to uncover potential therapeutic targets and ingredients for PD. Results: We identified 109 PDFerDEGs that were significantly enriched in biological processes and KEGG pathways associated with ferroptosis (including iron ion homeostasis, iron ion transport and ferroptosis, etc.). We obtained 29 overlapping genes and identified 6 hub genes (TLR4, IL6, ADIPOQ, PTGS2, ATG7, and FADS2) by screening with two machine learning algorithms. Based on this, we screened 263 natural product components and subsequently mapped the "Overlapping Genes-Ingredients" network. According to the network, top 5 core active ingredients (quercetin, 17-beta-estradiol, glycerin, trans-resveratrol, and tocopherol) were molecularly docked to hub genes to reveal their potential role in the treatment of ferroptosis in PD. Conclusion: Our findings suggested that PDFerDEGs are associated with ferroptosis and play a role in the progression of PD. Taken together, core ingredients (quercetin, 17-beta-estradiol, glycerin, trans-resveratrol, and tocopherol) bind well to hub genes (TLR4, IL6, ADIPOQ, PTGS2, ATG7, and FADS2), highlighting novel biomarkers for PD.

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Uncovering Nematicidal Natural Products from Xenorhabdus Bacteria.

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