Use of untargeted metabolomics to analyse changes in extractable soil organic matter in response to long-term fertilisation

被引:0
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作者
Sheng Tang
Qingxu Ma
Jingjie Zhou
Wankun Pan
David R. Chadwick
Andrew S. Gregory
Lianghuan Wu
Davey L. Jones
机构
[1] Zhejiang University,Ministry of Education Key Lab of Environmental Remediation and Ecosystem Health, Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, College of Environmental and Resource Sciences
[2] Bangor University,School of Natural Sciences
[3] Rothamsted Research,Protecting Crops and the Environment
[4] Murdoch University,SoilsWest, Centre for Sustainable Farming Systems, Food Futures Institute
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关键词
Soil organic matter; Dissolved organic matter; Chemical fertiliser; Farmyard manure; Untargeted metabolomes;
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摘要
This study aimed to explore the soil metabolic response to long-term fertiliser application and the effect of this response on the microbial community by taking advantage of the Woburn Organic Manuring Experiment (UK; operational since 1964). Untargeted metabolomes detected by gas chromatography-time of flight mass spectrometer/mass spectrometry (GC-TOFMS/MS) and ultra-high-pressure liquid chromatography-quadrupole time of flight mass-spectrometer/mass spectrometry (UHPLC-QTOFMS/MS) were used to explore which method better reflected soil microbe-accessible metabolites. Microbial community abundance was detected by high-throughput sequencing. We found that long-term farmyard manure application enhanced the soil’s total and dissolved C and N contents. The metabolite content detected by GC-TOFMS/MS (TOF detector with a cold injection unit) had a negative linear correlation with soil organic matter, extractable organic nitrogen (N), and microbial carbon (C). Conversely, the metabolite content detected by UHPLC-QTOFMS/MS was positively correlated with soil organic matter, indicating that metabolites detected by UHPLC-QTOFMS/MS were the main components of soluble soil organic matter. More positive than negative correlations were observed between metabolites and bacterial (69.5%) and fungal (67.9%) taxa in the co-occurrence network. Among the bacterial taxa in the network, the family Planococcaceae and genus Paenibacillus showed the most correlations with metabolites. The choice of extraction and detection method affects the identity and number of metabolites detected. Therefore, careful consideration is needed when selecting which methods to use. We demonstrated a strong correlation between soil metabolites and microbial community abundance. However, a deeper understanding of soil microbial function and metabolite formation, content, and decomposition is still needed.
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页码:301 / 316
页数:15
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