The larval gut of Spodoptera frugiperda harbours culturable bacteria with metabolic versatility after insecticide exposure.

IF 2.3 2区 农林科学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Junaid Ali Siddiqui, Ruidong Fan, Yanjiang Liu, Ali Hassan Syed, Yi Benlin, Qingshuai Chu, Zeyang Ding, Muhammad Imran Ghani, Xuemi Liu, Waqas Wakil, Dong-Dong Liu, Xiaoyulong Chen, Tomislav Cernava, Guy Smagghe
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引用次数: 0

Abstract

Spodoptera frugiperda (fall armyworm) poses a substantial risk to crops worldwide, resulting in considerable economic damage. The gut microbiota of insects plays crucial roles in digestion, nutrition, immunity, growth and, sometimes, the degradation of insecticides. The current study examines the effect of synthetic insecticides on the gut microbiome of third instar S. frugiperda larvae using both culture-dependent techniques and 16S rRNA gene sequencing for bacterial community profiling and diversity analysis. In untreated larvae, the sequencing approach revealed a diverse microbiome dominated by the phyla Firmicutes, Proteobacteria and Bacteroidota, with key genera including Bacteroides, Faecalibacterium and Pelomonas. In parallel, 323 bacterial strains were isolated and assigned to the orders Bacillales, Burkholderiales, Enterobacterales, Flavobacteriales, Lactobacillales, Micrococcales, Neisseriaies, Pseudomonadales, Sphingobacteriales and Xanthomonadales. The prevailing culturable species included Serratia marcescens, Klebsiella variicola and Enterobacter quasiroggenkampii. Treatment with sublethal concentrations of three insecticides (broflanilide, spinosad and indoxacarb) caused significant changes in gut microbiome diversity and composition. Treated larvae showed a shift towards increased Proteobacteria abundance and decreased Firmicutes. Specifically, Acinetobacter and Rhodococcus were dominant in treated samples. Functional predictions highlighted significant metabolic versatility involving nutrient processing, immune response, detoxification, xenobiotic metabolism, and stress response, suggesting microbial adaptation to insecticide exposure. Network correlation analysis highlighted disrupted microbial interactions and altered community structures under insecticide treatment. These findings enhance our understanding of how insecticides impact the gut microbiota in S. frugiperda and may inform future strategies for managing pest resistance through microbiome-based approaches.

在杀虫剂暴露后,夜蛾幼虫的肠道中含有具有代谢多样性的可培养细菌。
夜蛾(Spodoptera frugiperda)对世界范围内的作物构成重大威胁,造成相当大的经济损失。昆虫的肠道微生物群在消化、营养、免疫、生长,有时还在杀虫剂的降解中起着至关重要的作用。本研究利用培养依赖技术和16S rRNA基因测序技术,研究了合成杀虫剂对三龄frugiperda幼虫肠道微生物群的影响,并进行了细菌群落分析和多样性分析。在未经处理的幼虫中,测序方法揭示了一个多样化的微生物组,以厚壁菌门,变形菌门和拟杆菌门为主,关键属包括拟杆菌门,Faecalibacterium和Pelomonas。同时,分离出323株细菌,分别属于杆菌门、伯克霍尔德门、肠杆菌门、黄杆菌门、乳酸杆菌门、微球菌门、奈斯球菌门、假单胞菌门、鞘菌门和黄单胞菌门。可培养的主要菌种包括粘质沙雷氏菌、水痘克雷伯菌和拟罗根坎皮肠杆菌。用亚致死浓度的三种杀虫剂(溴氟醚、spinosad和茚虫威)处理导致肠道微生物群多样性和组成发生显著变化。处理后的幼虫表现出向变形菌门丰度增加和厚壁菌门减少的转变。具体来说,不动杆菌和红球菌在处理过的样品中占优势。功能预测强调了显著的代谢多样性,包括营养加工、免疫反应、解毒、异种代谢和应激反应,表明微生物适应杀虫剂暴露。网络相关性分析强调了杀虫剂处理下微生物相互作用的破坏和群落结构的改变。这些发现增强了我们对杀虫剂如何影响S. frugiperda肠道微生物群的理解,并可能通过基于微生物组的方法为未来管理害虫抗性的策略提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Insect Molecular Biology
Insect Molecular Biology 生物-昆虫学
CiteScore
4.80
自引率
3.80%
发文量
68
审稿时长
6-12 weeks
期刊介绍: Insect Molecular Biology has been dedicated to providing researchers with the opportunity to publish high quality original research on topics broadly related to insect molecular biology since 1992. IMB is particularly interested in publishing research in insect genomics/genes and proteomics/proteins. This includes research related to: • insect gene structure • control of gene expression • localisation and function/activity of proteins • interactions of proteins and ligands/substrates • effect of mutations on gene/protein function • evolution of insect genes/genomes, especially where principles relevant to insects in general are established • molecular population genetics where data are used to identify genes (or regions of genomes) involved in specific adaptations • gene mapping using molecular tools • molecular interactions of insects with microorganisms including Wolbachia, symbionts and viruses or other pathogens transmitted by insects Papers can include large data sets e.g.from micro-array or proteomic experiments or analyses of genome sequences done in silico (subject to the data being placed in the context of hypothesis testing).
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