Spatial-temporal Changes and Driving Factors of Soil Microbial Communities in a Typical City of North China Plain
The structure and function of microbial communities are affected by several environmental factors. To clarify the spatial-temporal changes and main influencing factors of soil microbial communities in a typical pharmaceutical city, it is urgent to study the spatial-temporal changes in microbial communities in soils for typical cities. Shijiazhuang City was selected as the study area, and 12 sampling sites were selected. The topsoil was collected in June (summer) and September (autumn) of 2021. The 16S rRNA high-throughput sequencing technology was used to study the structure and function of microbial communities in the soil and explore their spatial-temporal changes. Concurrently, Pearson correlation analysis was applied to establish the correlation between the microbial community and environmental factors, and identify the main driving factors of temporal and spatial changes in the microbial community. The results showed that:① Actinobaciota and Proteobateria were the main dominant bacteria in the surface soil of Shijiazhuang City; at the phylum level, the relative abundance of Actinobacteria and Proteobateria decreased from summer to autumn; at the genus level, the dominant genera were Arthrobacter and unknown genera in summer and Arthrobacter and Candidatus_Nitrocosmicus in autumn, which showed significant seasonal differences (P<0.05). ② For seasonal variation, the mean values of the Simpson, Ace, and Chao indices increased, whereas the mean values of OTU decreased; for spatial variation, the Shannon and Simpson indices showed significant spatial difference (P<0.01 and P<0.05). ③ There were no significant spatial-temporal differences in various functional genes; thereinto, the relative abundances of energy production and transformation functional genes were the highest (24.06%-24.84% in summer and 24.63%-25.98% in autumn, respectively). ④ The compositions of microbial community, diversity index, and functional genes were significantly correlated with quinolone antibiotics (QNs), total phosphorus (TP), and nitrate nitrogen (NO3--N), most significantly correlated with QNs (|r|>0.900), which indicated that antibiotics were the main driving factor of soil microbial communities. Therefore, to ensure the stability of microbial community structure and function in urban soil, the comprehensive management and control of antibiotic pollution in soil should be further strengthened.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:44 |
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| Enthalten in: |
Huan jing ke xue= Huanjing kexue - 44(2023), 9 vom: 08. Sept., Seite 5164-5175 |
| Sprache: |
Chinesisch |
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| Beteiligte Personen: |
Zhao, Xin-Yu [VerfasserIn] |
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| Links: |
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| Themen: |
Anti-Bacterial Agents |
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| Anmerkungen: |
Date Completed 14.09.2023 Date Revised 14.09.2023 published: Print Citation Status MEDLINE |
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| doi: |
10.13227/j.hjkx.202210090 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM361971761 |
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| 245 | 1 | 0 | |a Spatial-temporal Changes and Driving Factors of Soil Microbial Communities in a Typical City of North China Plain |
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| 500 | |a Citation Status MEDLINE | ||
| 520 | |a The structure and function of microbial communities are affected by several environmental factors. To clarify the spatial-temporal changes and main influencing factors of soil microbial communities in a typical pharmaceutical city, it is urgent to study the spatial-temporal changes in microbial communities in soils for typical cities. Shijiazhuang City was selected as the study area, and 12 sampling sites were selected. The topsoil was collected in June (summer) and September (autumn) of 2021. The 16S rRNA high-throughput sequencing technology was used to study the structure and function of microbial communities in the soil and explore their spatial-temporal changes. Concurrently, Pearson correlation analysis was applied to establish the correlation between the microbial community and environmental factors, and identify the main driving factors of temporal and spatial changes in the microbial community. The results showed that:① Actinobaciota and Proteobateria were the main dominant bacteria in the surface soil of Shijiazhuang City; at the phylum level, the relative abundance of Actinobacteria and Proteobateria decreased from summer to autumn; at the genus level, the dominant genera were Arthrobacter and unknown genera in summer and Arthrobacter and Candidatus_Nitrocosmicus in autumn, which showed significant seasonal differences (P<0.05). ② For seasonal variation, the mean values of the Simpson, Ace, and Chao indices increased, whereas the mean values of OTU decreased; for spatial variation, the Shannon and Simpson indices showed significant spatial difference (P<0.01 and P<0.05). ③ There were no significant spatial-temporal differences in various functional genes; thereinto, the relative abundances of energy production and transformation functional genes were the highest (24.06%-24.84% in summer and 24.63%-25.98% in autumn, respectively). ④ The compositions of microbial community, diversity index, and functional genes were significantly correlated with quinolone antibiotics (QNs), total phosphorus (TP), and nitrate nitrogen (NO3--N), most significantly correlated with QNs (|r|>0.900), which indicated that antibiotics were the main driving factor of soil microbial communities. Therefore, to ensure the stability of microbial community structure and function in urban soil, the comprehensive management and control of antibiotic pollution in soil should be further strengthened | ||
| 650 | 4 | |a English Abstract | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a diversity index | |
| 650 | 4 | |a driving factors | |
| 650 | 4 | |a functional genes | |
| 650 | 4 | |a microbial community | |
| 650 | 4 | |a soil | |
| 650 | 4 | |a temporal and spatial distribution | |
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| 650 | 7 | |a Anti-Bacterial Agents |2 NLM | |
| 700 | 1 | |a Chen, Hui |e verfasserin |4 aut | |
| 700 | 1 | |a Chang, Shuai |e verfasserin |4 aut | |
| 700 | 1 | |a Song, Yuan-Meng |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Bo |e verfasserin |4 aut | |
| 700 | 1 | |a Lu, Meng-Qi |e verfasserin |4 aut | |
| 700 | 1 | |a Cui, Jian-Sheng |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Lu-Lu |e verfasserin |4 aut | |
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