Coupling Genomics and Hydraulic Information to Predict the Nitrogen Dynamics in a Channel Confluence
The simulation of nitrogen dynamics in urban channel confluences is essential for the evaluation and improvement of water quality. The omics-based modeling approaches that have been rapidly developed have been increasingly applied to characterize metabolisms of the microbial community and transforma...
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Veröffentlicht in: | Environmental science & technology 2021-04, Vol.55 (8), p.4616-4628 |
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creator | Hui, Cizhang Li, Yi Zhang, Wenlong Yang, Gang Wang, Haolan Gao, Yu Niu, Lihua Wang, Longfei Zhang, Huanjun |
description | The simulation of nitrogen dynamics in urban channel confluences is essential for the evaluation and improvement of water quality. The omics-based modeling approaches that have been rapidly developed have been increasingly applied to characterize metabolisms of the microbial community and transformation of the associated materials. However, the transport of microorganisms and chemicals within and among different phases, which could be the rate-limiting step for the nitrogen dynamics, are always neglected or oversimplified in omics-based models. Therefore, this study proposes a novel simulation system coupling genomic and hydraulic information to simulate transport and transformation processes and provide predictions of nitrogen dynamics in a confluence. The proposed model was able to capture multiphase mass transport, microbial population dynamics, and nitrogen transformation and accurately predict gene abundances and nitrogen concentrations in both water and sediment; the mean relative errors were all lower than 40%. The model emphasized the importance of transport processes, which contributed more than 90% to gene abundances and chemical concentrations. Moreover, the simulation of reaction rates exhibited the specific nitrogen transformation processes in the confluence. The sulfide oxidation and the nitrate reduction and anaerobic ammonium oxidation, with the participation of the genes nap and hzo, respectively, were promoted as the main processes of nitrate and nitrite reduction. |
doi_str_mv | 10.1021/acs.est.0c04018 |
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The omics-based modeling approaches that have been rapidly developed have been increasingly applied to characterize metabolisms of the microbial community and transformation of the associated materials. However, the transport of microorganisms and chemicals within and among different phases, which could be the rate-limiting step for the nitrogen dynamics, are always neglected or oversimplified in omics-based models. Therefore, this study proposes a novel simulation system coupling genomic and hydraulic information to simulate transport and transformation processes and provide predictions of nitrogen dynamics in a confluence. The proposed model was able to capture multiphase mass transport, microbial population dynamics, and nitrogen transformation and accurately predict gene abundances and nitrogen concentrations in both water and sediment; the mean relative errors were all lower than 40%. The model emphasized the importance of transport processes, which contributed more than 90% to gene abundances and chemical concentrations. Moreover, the simulation of reaction rates exhibited the specific nitrogen transformation processes in the confluence. The sulfide oxidation and the nitrate reduction and anaerobic ammonium oxidation, with the participation of the genes nap and hzo, respectively, were promoted as the main processes of nitrate and nitrite reduction.</description><identifier>ISSN: 0013-936X</identifier><identifier>EISSN: 1520-5851</identifier><identifier>DOI: 10.1021/acs.est.0c04018</identifier><identifier>PMID: 33760605</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>Abundance ; Ammonium ; Anaerobiosis ; Contaminants in Aquatic and Terrestrial Environments ; Coupling ; Denitrification ; Dynamics ; Genomics ; Mass transport ; Microorganisms ; Nitrate reduction ; Nitrates ; Nitrites ; Nitrogen ; Oxidation ; Oxidation-Reduction ; Population dynamics ; Reduction ; Simulation ; Sulfides ; Transformations ; Transport processes ; Water quality</subject><ispartof>Environmental science & technology, 2021-04, Vol.55 (8), p.4616-4628</ispartof><rights>2021 American Chemical Society</rights><rights>Copyright American Chemical Society Apr 20, 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a361t-9092188f5b3aa93391bc2b27cd2662de43bc13bafa8e89d908b3c0b7768284f73</citedby><cites>FETCH-LOGICAL-a361t-9092188f5b3aa93391bc2b27cd2662de43bc13bafa8e89d908b3c0b7768284f73</cites><orcidid>0000-0002-4300-690X ; 0000-0001-8136-7370</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/acs.est.0c04018$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/acs.est.0c04018$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>314,776,780,2752,27053,27901,27902,56713,56763</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33760605$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hui, Cizhang</creatorcontrib><creatorcontrib>Li, Yi</creatorcontrib><creatorcontrib>Zhang, Wenlong</creatorcontrib><creatorcontrib>Yang, Gang</creatorcontrib><creatorcontrib>Wang, Haolan</creatorcontrib><creatorcontrib>Gao, Yu</creatorcontrib><creatorcontrib>Niu, Lihua</creatorcontrib><creatorcontrib>Wang, Longfei</creatorcontrib><creatorcontrib>Zhang, Huanjun</creatorcontrib><title>Coupling Genomics and Hydraulic Information to Predict the Nitrogen Dynamics in a Channel Confluence</title><title>Environmental science & technology</title><addtitle>Environ. Sci. Technol</addtitle><description>The simulation of nitrogen dynamics in urban channel confluences is essential for the evaluation and improvement of water quality. The omics-based modeling approaches that have been rapidly developed have been increasingly applied to characterize metabolisms of the microbial community and transformation of the associated materials. However, the transport of microorganisms and chemicals within and among different phases, which could be the rate-limiting step for the nitrogen dynamics, are always neglected or oversimplified in omics-based models. Therefore, this study proposes a novel simulation system coupling genomic and hydraulic information to simulate transport and transformation processes and provide predictions of nitrogen dynamics in a confluence. The proposed model was able to capture multiphase mass transport, microbial population dynamics, and nitrogen transformation and accurately predict gene abundances and nitrogen concentrations in both water and sediment; the mean relative errors were all lower than 40%. The model emphasized the importance of transport processes, which contributed more than 90% to gene abundances and chemical concentrations. Moreover, the simulation of reaction rates exhibited the specific nitrogen transformation processes in the confluence. The sulfide oxidation and the nitrate reduction and anaerobic ammonium oxidation, with the participation of the genes nap and hzo, respectively, were promoted as the main processes of nitrate and nitrite reduction.</description><subject>Abundance</subject><subject>Ammonium</subject><subject>Anaerobiosis</subject><subject>Contaminants in Aquatic and Terrestrial Environments</subject><subject>Coupling</subject><subject>Denitrification</subject><subject>Dynamics</subject><subject>Genomics</subject><subject>Mass transport</subject><subject>Microorganisms</subject><subject>Nitrate reduction</subject><subject>Nitrates</subject><subject>Nitrites</subject><subject>Nitrogen</subject><subject>Oxidation</subject><subject>Oxidation-Reduction</subject><subject>Population dynamics</subject><subject>Reduction</subject><subject>Simulation</subject><subject>Sulfides</subject><subject>Transformations</subject><subject>Transport processes</subject><subject>Water quality</subject><issn>0013-936X</issn><issn>1520-5851</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kTFPwzAQRi0EoqUwsyFLLEgo5Ww3jjOiAKUSAgaQ2CLHcairxC52MvTfk9DSAYnplve-O92H0DmBKQFKbqQKUx3aKSiYAREHaExiClEsYnKIxgCERSnjHyN0EsIKACgDcYxGjCUcOMRjVGauW9fGfuK5tq4xKmBpS_y4Kb3saqPwwlbON7I1zuLW4VevS6Na3C41fjatd5_a4ruNlT-qsVjibCmt1TXOnK3qTlulT9FRJeugz3Zzgt4f7t-yx-jpZb7Ibp8iyThpoxRSSoSo4oJJmTKWkkLRgiaqpJzTUs9YoQgrZCWFFmmZgiiYgiJJuKBiViVsgq62uWvvvrr-L3ljgtJ1La12XchpDDHjnBPao5d_0JXrvO2v6ykiZhSoGAJvtpTyLgSvq3ztTSP9JieQDwXkfQH5YO8K6I2LXW5XNLrc878f74HrLTCY-53_xX0DwtGQNA</recordid><startdate>20210420</startdate><enddate>20210420</enddate><creator>Hui, Cizhang</creator><creator>Li, Yi</creator><creator>Zhang, Wenlong</creator><creator>Yang, Gang</creator><creator>Wang, Haolan</creator><creator>Gao, Yu</creator><creator>Niu, Lihua</creator><creator>Wang, Longfei</creator><creator>Zhang, Huanjun</creator><general>American Chemical Society</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7ST</scope><scope>7T7</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>SOI</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-4300-690X</orcidid><orcidid>https://orcid.org/0000-0001-8136-7370</orcidid></search><sort><creationdate>20210420</creationdate><title>Coupling Genomics and Hydraulic Information to Predict the Nitrogen Dynamics in a Channel Confluence</title><author>Hui, Cizhang ; Li, Yi ; Zhang, Wenlong ; Yang, Gang ; Wang, Haolan ; Gao, Yu ; Niu, Lihua ; Wang, Longfei ; Zhang, Huanjun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a361t-9092188f5b3aa93391bc2b27cd2662de43bc13bafa8e89d908b3c0b7768284f73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Abundance</topic><topic>Ammonium</topic><topic>Anaerobiosis</topic><topic>Contaminants in Aquatic and Terrestrial Environments</topic><topic>Coupling</topic><topic>Denitrification</topic><topic>Dynamics</topic><topic>Genomics</topic><topic>Mass transport</topic><topic>Microorganisms</topic><topic>Nitrate reduction</topic><topic>Nitrates</topic><topic>Nitrites</topic><topic>Nitrogen</topic><topic>Oxidation</topic><topic>Oxidation-Reduction</topic><topic>Population dynamics</topic><topic>Reduction</topic><topic>Simulation</topic><topic>Sulfides</topic><topic>Transformations</topic><topic>Transport processes</topic><topic>Water quality</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hui, Cizhang</creatorcontrib><creatorcontrib>Li, Yi</creatorcontrib><creatorcontrib>Zhang, Wenlong</creatorcontrib><creatorcontrib>Yang, Gang</creatorcontrib><creatorcontrib>Wang, Haolan</creatorcontrib><creatorcontrib>Gao, Yu</creatorcontrib><creatorcontrib>Niu, Lihua</creatorcontrib><creatorcontrib>Wang, Longfei</creatorcontrib><creatorcontrib>Zhang, Huanjun</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environment Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Environmental science & technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hui, Cizhang</au><au>Li, Yi</au><au>Zhang, Wenlong</au><au>Yang, Gang</au><au>Wang, Haolan</au><au>Gao, Yu</au><au>Niu, Lihua</au><au>Wang, Longfei</au><au>Zhang, Huanjun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Coupling Genomics and Hydraulic Information to Predict the Nitrogen Dynamics in a Channel Confluence</atitle><jtitle>Environmental science & technology</jtitle><addtitle>Environ. Sci. Technol</addtitle><date>2021-04-20</date><risdate>2021</risdate><volume>55</volume><issue>8</issue><spage>4616</spage><epage>4628</epage><pages>4616-4628</pages><issn>0013-936X</issn><eissn>1520-5851</eissn><abstract>The simulation of nitrogen dynamics in urban channel confluences is essential for the evaluation and improvement of water quality. The omics-based modeling approaches that have been rapidly developed have been increasingly applied to characterize metabolisms of the microbial community and transformation of the associated materials. However, the transport of microorganisms and chemicals within and among different phases, which could be the rate-limiting step for the nitrogen dynamics, are always neglected or oversimplified in omics-based models. Therefore, this study proposes a novel simulation system coupling genomic and hydraulic information to simulate transport and transformation processes and provide predictions of nitrogen dynamics in a confluence. The proposed model was able to capture multiphase mass transport, microbial population dynamics, and nitrogen transformation and accurately predict gene abundances and nitrogen concentrations in both water and sediment; the mean relative errors were all lower than 40%. The model emphasized the importance of transport processes, which contributed more than 90% to gene abundances and chemical concentrations. Moreover, the simulation of reaction rates exhibited the specific nitrogen transformation processes in the confluence. 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subjects | Abundance Ammonium Anaerobiosis Contaminants in Aquatic and Terrestrial Environments Coupling Denitrification Dynamics Genomics Mass transport Microorganisms Nitrate reduction Nitrates Nitrites Nitrogen Oxidation Oxidation-Reduction Population dynamics Reduction Simulation Sulfides Transformations Transport processes Water quality |
title | Coupling Genomics and Hydraulic Information to Predict the Nitrogen Dynamics in a Channel Confluence |
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