Bacterial Community Structure and Diversity in the Aqueous Environment of Shihou Lake and its Relationship with Environmental Factors
Abstract Microorganisms are sensitive to changes in the external environment and are often used as indicators to monitor and reflect water quality. Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key...
Ausführliche Beschreibung
Autor*in: |
Deng, Ru [verfasserIn] Chen, Xi [verfasserIn] Qiu, Li-Ping [verfasserIn] Chen, Jia-Zhang [verfasserIn] Meng, Shun-Long [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2021 |
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Schlagwörter: |
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Anmerkung: |
© Association of Microbiologists of India 2021 |
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Übergeordnetes Werk: |
Enthalten in: Indian journal of microbiology - Poona [u.a.], 2007, 61(2021), 4 vom: 23. Aug., Seite 475-486 |
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Übergeordnetes Werk: |
volume:61 ; year:2021 ; number:4 ; day:23 ; month:08 ; pages:475-486 |
Links: |
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DOI / URN: |
10.1007/s12088-021-00974-y |
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Katalog-ID: |
SPR045381135 |
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520 | |a Abstract Microorganisms are sensitive to changes in the external environment and are often used as indicators to monitor and reflect water quality. Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key environmental factors affecting the bacterial community were identified. The microbial community diversity in Shihou Lake water was rich and showed significant differences over time. The main bacterial phyla were the Cyanobacteria, Proteobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, Firmicutes, Chlorobi, WS6 and Saccharibacteria. The relative abundance of these major phyla in the sample accounted for 97.83%–99.07% of the total abundance; Cyanobacteria had the highest relative abundance, accounting for 13.07%–44.61% of the total, and the abundance of each dominant phylum was significantly different at different time points. The Shannon and Simpson indexes showed that the diversity of each month was as follows: August > October > July > September > November. The Chao1 and Ace indexes indicated that the order of richness was: November > October > July > August > September. Beta diversity analysis found significant differences in the samples from month to month. Environmental factors such as temperature, total nitrogen, chlorophyll-a, permanganate index, nitrite, pH and ammonia nitrogen had significant effects on microbial community structure. | ||
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10.1007/s12088-021-00974-y doi (DE-627)SPR045381135 (SPR)s12088-021-00974-y-e DE-627 ger DE-627 rakwb eng 570 ASE Deng, Ru verfasserin aut Bacterial Community Structure and Diversity in the Aqueous Environment of Shihou Lake and its Relationship with Environmental Factors 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Association of Microbiologists of India 2021 Abstract Microorganisms are sensitive to changes in the external environment and are often used as indicators to monitor and reflect water quality. Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key environmental factors affecting the bacterial community were identified. The microbial community diversity in Shihou Lake water was rich and showed significant differences over time. The main bacterial phyla were the Cyanobacteria, Proteobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, Firmicutes, Chlorobi, WS6 and Saccharibacteria. The relative abundance of these major phyla in the sample accounted for 97.83%–99.07% of the total abundance; Cyanobacteria had the highest relative abundance, accounting for 13.07%–44.61% of the total, and the abundance of each dominant phylum was significantly different at different time points. The Shannon and Simpson indexes showed that the diversity of each month was as follows: August > October > July > September > November. The Chao1 and Ace indexes indicated that the order of richness was: November > October > July > August > September. Beta diversity analysis found significant differences in the samples from month to month. Environmental factors such as temperature, total nitrogen, chlorophyll-a, permanganate index, nitrite, pH and ammonia nitrogen had significant effects on microbial community structure. Illumina MiSeq sequencing (dpeaa)DE-He213 Bacterial community (dpeaa)DE-He213 Environmental factors (dpeaa)DE-He213 Planktonic bacteria (dpeaa)DE-He213 Chen, Xi verfasserin aut Qiu, Li-Ping verfasserin aut Chen, Jia-Zhang verfasserin aut Meng, Shun-Long verfasserin aut Enthalten in Indian journal of microbiology Poona [u.a.], 2007 61(2021), 4 vom: 23. Aug., Seite 475-486 (DE-627)588782432 (DE-600)2471820-8 0973-7715 nnns volume:61 year:2021 number:4 day:23 month:08 pages:475-486 https://dx.doi.org/10.1007/s12088-021-00974-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 61 2021 4 23 08 475-486 |
spelling |
10.1007/s12088-021-00974-y doi (DE-627)SPR045381135 (SPR)s12088-021-00974-y-e DE-627 ger DE-627 rakwb eng 570 ASE Deng, Ru verfasserin aut Bacterial Community Structure and Diversity in the Aqueous Environment of Shihou Lake and its Relationship with Environmental Factors 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Association of Microbiologists of India 2021 Abstract Microorganisms are sensitive to changes in the external environment and are often used as indicators to monitor and reflect water quality. Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key environmental factors affecting the bacterial community were identified. The microbial community diversity in Shihou Lake water was rich and showed significant differences over time. The main bacterial phyla were the Cyanobacteria, Proteobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, Firmicutes, Chlorobi, WS6 and Saccharibacteria. The relative abundance of these major phyla in the sample accounted for 97.83%–99.07% of the total abundance; Cyanobacteria had the highest relative abundance, accounting for 13.07%–44.61% of the total, and the abundance of each dominant phylum was significantly different at different time points. The Shannon and Simpson indexes showed that the diversity of each month was as follows: August > October > July > September > November. The Chao1 and Ace indexes indicated that the order of richness was: November > October > July > August > September. Beta diversity analysis found significant differences in the samples from month to month. Environmental factors such as temperature, total nitrogen, chlorophyll-a, permanganate index, nitrite, pH and ammonia nitrogen had significant effects on microbial community structure. Illumina MiSeq sequencing (dpeaa)DE-He213 Bacterial community (dpeaa)DE-He213 Environmental factors (dpeaa)DE-He213 Planktonic bacteria (dpeaa)DE-He213 Chen, Xi verfasserin aut Qiu, Li-Ping verfasserin aut Chen, Jia-Zhang verfasserin aut Meng, Shun-Long verfasserin aut Enthalten in Indian journal of microbiology Poona [u.a.], 2007 61(2021), 4 vom: 23. Aug., Seite 475-486 (DE-627)588782432 (DE-600)2471820-8 0973-7715 nnns volume:61 year:2021 number:4 day:23 month:08 pages:475-486 https://dx.doi.org/10.1007/s12088-021-00974-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 61 2021 4 23 08 475-486 |
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10.1007/s12088-021-00974-y doi (DE-627)SPR045381135 (SPR)s12088-021-00974-y-e DE-627 ger DE-627 rakwb eng 570 ASE Deng, Ru verfasserin aut Bacterial Community Structure and Diversity in the Aqueous Environment of Shihou Lake and its Relationship with Environmental Factors 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Association of Microbiologists of India 2021 Abstract Microorganisms are sensitive to changes in the external environment and are often used as indicators to monitor and reflect water quality. Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key environmental factors affecting the bacterial community were identified. The microbial community diversity in Shihou Lake water was rich and showed significant differences over time. The main bacterial phyla were the Cyanobacteria, Proteobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, Firmicutes, Chlorobi, WS6 and Saccharibacteria. The relative abundance of these major phyla in the sample accounted for 97.83%–99.07% of the total abundance; Cyanobacteria had the highest relative abundance, accounting for 13.07%–44.61% of the total, and the abundance of each dominant phylum was significantly different at different time points. The Shannon and Simpson indexes showed that the diversity of each month was as follows: August > October > July > September > November. The Chao1 and Ace indexes indicated that the order of richness was: November > October > July > August > September. Beta diversity analysis found significant differences in the samples from month to month. Environmental factors such as temperature, total nitrogen, chlorophyll-a, permanganate index, nitrite, pH and ammonia nitrogen had significant effects on microbial community structure. Illumina MiSeq sequencing (dpeaa)DE-He213 Bacterial community (dpeaa)DE-He213 Environmental factors (dpeaa)DE-He213 Planktonic bacteria (dpeaa)DE-He213 Chen, Xi verfasserin aut Qiu, Li-Ping verfasserin aut Chen, Jia-Zhang verfasserin aut Meng, Shun-Long verfasserin aut Enthalten in Indian journal of microbiology Poona [u.a.], 2007 61(2021), 4 vom: 23. Aug., Seite 475-486 (DE-627)588782432 (DE-600)2471820-8 0973-7715 nnns volume:61 year:2021 number:4 day:23 month:08 pages:475-486 https://dx.doi.org/10.1007/s12088-021-00974-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 61 2021 4 23 08 475-486 |
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10.1007/s12088-021-00974-y doi (DE-627)SPR045381135 (SPR)s12088-021-00974-y-e DE-627 ger DE-627 rakwb eng 570 ASE Deng, Ru verfasserin aut Bacterial Community Structure and Diversity in the Aqueous Environment of Shihou Lake and its Relationship with Environmental Factors 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Association of Microbiologists of India 2021 Abstract Microorganisms are sensitive to changes in the external environment and are often used as indicators to monitor and reflect water quality. Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key environmental factors affecting the bacterial community were identified. The microbial community diversity in Shihou Lake water was rich and showed significant differences over time. The main bacterial phyla were the Cyanobacteria, Proteobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, Firmicutes, Chlorobi, WS6 and Saccharibacteria. The relative abundance of these major phyla in the sample accounted for 97.83%–99.07% of the total abundance; Cyanobacteria had the highest relative abundance, accounting for 13.07%–44.61% of the total, and the abundance of each dominant phylum was significantly different at different time points. The Shannon and Simpson indexes showed that the diversity of each month was as follows: August > October > July > September > November. The Chao1 and Ace indexes indicated that the order of richness was: November > October > July > August > September. Beta diversity analysis found significant differences in the samples from month to month. Environmental factors such as temperature, total nitrogen, chlorophyll-a, permanganate index, nitrite, pH and ammonia nitrogen had significant effects on microbial community structure. Illumina MiSeq sequencing (dpeaa)DE-He213 Bacterial community (dpeaa)DE-He213 Environmental factors (dpeaa)DE-He213 Planktonic bacteria (dpeaa)DE-He213 Chen, Xi verfasserin aut Qiu, Li-Ping verfasserin aut Chen, Jia-Zhang verfasserin aut Meng, Shun-Long verfasserin aut Enthalten in Indian journal of microbiology Poona [u.a.], 2007 61(2021), 4 vom: 23. Aug., Seite 475-486 (DE-627)588782432 (DE-600)2471820-8 0973-7715 nnns volume:61 year:2021 number:4 day:23 month:08 pages:475-486 https://dx.doi.org/10.1007/s12088-021-00974-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 61 2021 4 23 08 475-486 |
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10.1007/s12088-021-00974-y doi (DE-627)SPR045381135 (SPR)s12088-021-00974-y-e DE-627 ger DE-627 rakwb eng 570 ASE Deng, Ru verfasserin aut Bacterial Community Structure and Diversity in the Aqueous Environment of Shihou Lake and its Relationship with Environmental Factors 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Association of Microbiologists of India 2021 Abstract Microorganisms are sensitive to changes in the external environment and are often used as indicators to monitor and reflect water quality. Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key environmental factors affecting the bacterial community were identified. The microbial community diversity in Shihou Lake water was rich and showed significant differences over time. The main bacterial phyla were the Cyanobacteria, Proteobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, Firmicutes, Chlorobi, WS6 and Saccharibacteria. The relative abundance of these major phyla in the sample accounted for 97.83%–99.07% of the total abundance; Cyanobacteria had the highest relative abundance, accounting for 13.07%–44.61% of the total, and the abundance of each dominant phylum was significantly different at different time points. The Shannon and Simpson indexes showed that the diversity of each month was as follows: August > October > July > September > November. The Chao1 and Ace indexes indicated that the order of richness was: November > October > July > August > September. Beta diversity analysis found significant differences in the samples from month to month. Environmental factors such as temperature, total nitrogen, chlorophyll-a, permanganate index, nitrite, pH and ammonia nitrogen had significant effects on microbial community structure. Illumina MiSeq sequencing (dpeaa)DE-He213 Bacterial community (dpeaa)DE-He213 Environmental factors (dpeaa)DE-He213 Planktonic bacteria (dpeaa)DE-He213 Chen, Xi verfasserin aut Qiu, Li-Ping verfasserin aut Chen, Jia-Zhang verfasserin aut Meng, Shun-Long verfasserin aut Enthalten in Indian journal of microbiology Poona [u.a.], 2007 61(2021), 4 vom: 23. Aug., Seite 475-486 (DE-627)588782432 (DE-600)2471820-8 0973-7715 nnns volume:61 year:2021 number:4 day:23 month:08 pages:475-486 https://dx.doi.org/10.1007/s12088-021-00974-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 61 2021 4 23 08 475-486 |
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Enthalten in Indian journal of microbiology 61(2021), 4 vom: 23. Aug., Seite 475-486 volume:61 year:2021 number:4 day:23 month:08 pages:475-486 |
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Indian journal of microbiology |
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Deng, Ru @@aut@@ Chen, Xi @@aut@@ Qiu, Li-Ping @@aut@@ Chen, Jia-Zhang @@aut@@ Meng, Shun-Long @@aut@@ |
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Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key environmental factors affecting the bacterial community were identified. The microbial community diversity in Shihou Lake water was rich and showed significant differences over time. The main bacterial phyla were the Cyanobacteria, Proteobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, Firmicutes, Chlorobi, WS6 and Saccharibacteria. The relative abundance of these major phyla in the sample accounted for 97.83%–99.07% of the total abundance; Cyanobacteria had the highest relative abundance, accounting for 13.07%–44.61% of the total, and the abundance of each dominant phylum was significantly different at different time points. The Shannon and Simpson indexes showed that the diversity of each month was as follows: August > October > July > September > November. 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Deng, Ru |
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Bacterial Community Structure and Diversity in the Aqueous Environment of Shihou Lake and its Relationship with Environmental Factors |
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Bacterial Community Structure and Diversity in the Aqueous Environment of Shihou Lake and its Relationship with Environmental Factors |
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bacterial community structure and diversity in the aqueous environment of shihou lake and its relationship with environmental factors |
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Bacterial Community Structure and Diversity in the Aqueous Environment of Shihou Lake and its Relationship with Environmental Factors |
abstract |
Abstract Microorganisms are sensitive to changes in the external environment and are often used as indicators to monitor and reflect water quality. Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key environmental factors affecting the bacterial community were identified. The microbial community diversity in Shihou Lake water was rich and showed significant differences over time. The main bacterial phyla were the Cyanobacteria, Proteobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, Firmicutes, Chlorobi, WS6 and Saccharibacteria. The relative abundance of these major phyla in the sample accounted for 97.83%–99.07% of the total abundance; Cyanobacteria had the highest relative abundance, accounting for 13.07%–44.61% of the total, and the abundance of each dominant phylum was significantly different at different time points. The Shannon and Simpson indexes showed that the diversity of each month was as follows: August > October > July > September > November. The Chao1 and Ace indexes indicated that the order of richness was: November > October > July > August > September. Beta diversity analysis found significant differences in the samples from month to month. Environmental factors such as temperature, total nitrogen, chlorophyll-a, permanganate index, nitrite, pH and ammonia nitrogen had significant effects on microbial community structure. © Association of Microbiologists of India 2021 |
abstractGer |
Abstract Microorganisms are sensitive to changes in the external environment and are often used as indicators to monitor and reflect water quality. Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key environmental factors affecting the bacterial community were identified. The microbial community diversity in Shihou Lake water was rich and showed significant differences over time. The main bacterial phyla were the Cyanobacteria, Proteobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, Firmicutes, Chlorobi, WS6 and Saccharibacteria. The relative abundance of these major phyla in the sample accounted for 97.83%–99.07% of the total abundance; Cyanobacteria had the highest relative abundance, accounting for 13.07%–44.61% of the total, and the abundance of each dominant phylum was significantly different at different time points. The Shannon and Simpson indexes showed that the diversity of each month was as follows: August > October > July > September > November. The Chao1 and Ace indexes indicated that the order of richness was: November > October > July > August > September. Beta diversity analysis found significant differences in the samples from month to month. Environmental factors such as temperature, total nitrogen, chlorophyll-a, permanganate index, nitrite, pH and ammonia nitrogen had significant effects on microbial community structure. © Association of Microbiologists of India 2021 |
abstract_unstemmed |
Abstract Microorganisms are sensitive to changes in the external environment and are often used as indicators to monitor and reflect water quality. Using Illumina MiSeq sequencing, the characteristics of the microbial community in Shihou Lake water at different time points were analyzed and the key environmental factors affecting the bacterial community were identified. The microbial community diversity in Shihou Lake water was rich and showed significant differences over time. The main bacterial phyla were the Cyanobacteria, Proteobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, Firmicutes, Chlorobi, WS6 and Saccharibacteria. The relative abundance of these major phyla in the sample accounted for 97.83%–99.07% of the total abundance; Cyanobacteria had the highest relative abundance, accounting for 13.07%–44.61% of the total, and the abundance of each dominant phylum was significantly different at different time points. The Shannon and Simpson indexes showed that the diversity of each month was as follows: August > October > July > September > November. The Chao1 and Ace indexes indicated that the order of richness was: November > October > July > August > September. Beta diversity analysis found significant differences in the samples from month to month. Environmental factors such as temperature, total nitrogen, chlorophyll-a, permanganate index, nitrite, pH and ammonia nitrogen had significant effects on microbial community structure. © Association of Microbiologists of India 2021 |
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title_short |
Bacterial Community Structure and Diversity in the Aqueous Environment of Shihou Lake and its Relationship with Environmental Factors |
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https://dx.doi.org/10.1007/s12088-021-00974-y |
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Chen, Xi Qiu, Li-Ping Chen, Jia-Zhang Meng, Shun-Long |
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2024-07-03T15:37:27.279Z |
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score |
7.4006405 |