Integrative analysis of microbiota and metabolomics in chromium-exposed silkworm (Bombyx mori) midguts based on 16S rDNA sequencing and LC/MS metabolomics

被引:1
|
作者
Chen, Ya-Zhen [1 ,2 ]
Rong, Wan-Tao [1 ,2 ]
Qin, Ying-Can [1 ,2 ]
Lu, Lin-Yuan [1 ,2 ]
Liu, Jing [1 ,2 ]
Li, Ming-Jie [1 ,2 ]
Xin, Lei [1 ,2 ]
Li, Xiao-Dong [1 ,2 ]
Guan, De-Long [1 ,2 ]
机构
[1] Hechi Univ, Guangxi Key Lab Sericulture Ecol & Appl Intelligen, Hechi, Peoples R China
[2] Hechi Univ, Guangxi Collaborat Innovat Ctr Modern Sericulture, Hechi, Peoples R China
关键词
chromium exposure; silkworms; gut microbiota; metabolomics; multi-omics; BACILLUS; SOFTWARE; CADMIUM; PROTEIN; HEALTH; FAMILY;
D O I
10.3389/fmicb.2023.1278271
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
The gut microbiota, a complex ecosystem integral to host wellbeing, is modulated by environmental triggers, including exposure to heavy metals such as chromium. This study aims to comprehensively explore chromium-induced gut microbiota and metabolomic shifts in the quintessential lepidopteran model organism, the silkworm (Bombyx mori). The research deployed 16S rDNA sequence analysis and LC/MS metabolomics in its experimental design, encompassing a control group alongside low (12 g/kg) and high (24 g/kg) feeding chromium dosing regimens. Considerable heterogeneity in microbial diversity resulted between groups. Weissella emerged as potentially resilient to chromium stress, while elevated Propionibacterium was noted in the high chromium treatment group. Differential analysis tools LEfSe and random forest estimation identified key species like like Cupriavidus and unspecified Myxococcales, offering potential avenues for bioremediation. An examination of gut functionality revealed alterations in the KEGG pathways correlated with biosynthesis and degradation, suggesting an adaptive metabolic response to chromium-mediated stress. Further results indicated consequential fallout in the context of metabolomic alterations. These included an uptick in histidine and dihydropyrimidine levels under moderate-dose exposure and a surge of gentisic acid with high-dose chromium exposure. These are critical players in diverse biological processes ranging from energy metabolism and stress response to immune regulation and antioxidative mechanisms. Correlative analyses between bacterial abundance and metabolites mapped noteworthy relationships between marker bacterial species, such as Weissella and Pelomonas, and specific metabolites, emphasizing their roles in enzyme regulation, synaptic processes, and lipid metabolism. Probiotic bacteria showed robust correlations with metabolites implicated in stress response, lipid metabolism, and antioxidant processes. Our study reaffirms the intricate ties between gut microbiota and metabolite profiles and decodes some systemic adaptations under heavy-metal stress. It provides valuable insights into ecological and toxicological aspects of chromium exposure that can potentially influence silkworm resilience.
引用
收藏
页数:16
相关论文
共 44 条
  • [1] Integrative analysis of the gut microbiota and metabolome in rats treated with rice straw biochar by 16S rRNA gene sequencing and LC/MS-based metabolomics
    Jie Han
    Jun Meng
    Shuya Chen
    Chuang Li
    Scientific Reports, 9
  • [2] Integrative analysis of the gut microbiota and metabolome in rats treated with rice straw biochar by 16S rRNA gene sequencing and LC/MS-based metabolomics
    Han, Jie
    Meng, Jun
    Chen, Shuya
    Li, Chuang
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [3] Integrative Analysis of Vaginal Microorganisms and Serum Metabolomics in Rats With Estrous Cycle Disorder Induced by Long-Term Heat Exposure Based on 16S rDNA Gene Sequencing and LC/MS-Based Metabolomics
    An, GaiHong
    Zhang, Yu
    Fan, LiJun
    Chen, JiaJun
    Wei, MengFan
    Li, Chao
    Chen, XueWei
    Zhang, Li
    Yang, DanFeng
    Wang, Jing
    FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY, 2021, 11
  • [4] Investigating the modulatory effects of lactoferrin on depressed rats through 16S rDNA gene sequencing and LC-MS metabolomics analysis
    Zhang, Jing
    Xin, Hongmei
    Wang, Wuji
    Li, Yanyi
    Wu, Riga
    Wei, Lisi
    Su, Si
    Wang, Xiaohong
    Wang, Xiujuan
    Wang, Xiaojuan
    Li, Li
    Hu, Rilebagen
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [5] Variations in gut microbiota and fecal metabolic phenotype associated with depression by 16S rRNA gene sequencing and LC/MS-based metabolomics
    Yu, Meng
    Jia, Hongmei
    Zhou, Chao
    Yang, Yong
    Zhao, Yang
    Yang, Maohua
    Zou, Zhongmei
    JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS, 2017, 138 : 231 - 239
  • [6] Comprehensive Analysis of the Relationships Between the Gut Microbiota and Fecal Metabolome in Individuals With Primary Sjogren's Syndrome by 16S rRNA Sequencing and LC-MS-Based Metabolomics
    Yang, Li
    Xiang, Zhao
    Zou, Jinmei
    Zhang, Yu
    Ni, Yuanpiao
    Yang, Jing
    FRONTIERS IN IMMUNOLOGY, 2022, 13
  • [7] Effect of in vitro cultivation on human gut microbiota composition using 16S rDNA amplicon sequencing and metabolomics approach
    Srednicka, Paulina
    Roszko, Marek Lukasz
    Popowski, Dominik
    Kowalczyk, Monika
    Wojcicki, Michal
    Emanowicz, Paulina
    Szczepanska, Magdalena
    Kotyrba, Danuta
    Juszczuk-Kubiak, Edyta
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [8] Effect of in vitro cultivation on human gut microbiota composition using 16S rDNA amplicon sequencing and metabolomics approach
    Paulina Średnicka
    Marek Łukasz Roszko
    Dominik Popowski
    Monika Kowalczyk
    Michał Wójcicki
    Paulina Emanowicz
    Magdalena Szczepańska
    Danuta Kotyrba
    Edyta Juszczuk-Kubiak
    Scientific Reports, 13
  • [9] Investigating the modulatory effects of lactoferrin on depressed rats through 16S rDNA gene sequencing and LC-MS metabolomics analysis (vol 14, 22111, 2024)
    Zhang, Jing
    Xin, Hongmei
    Wang, Wuji
    Li, Yanyi
    Wu, Riga
    Wei, Lisi
    Su, Si
    Wang, Xiaohong
    Wang, Xiujuan
    Wang, Xiaojuan
    Li, Li
    Hu, Rilebagen
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [10] Combined analysis of 16S rDNA sequencing and metabolomics to find biomarkers of drug-induced liver injury
    Kaini He
    Mimi Liu
    Qian Wang
    Sijie Chen
    Xiaoyan Guo
    Scientific Reports, 13