Applying predictive models to decipher rhizobacterial modifications in common reed die-back affected populations
The microbiota inhabiting the soil, as well as the rhizosphere, represents a key determinant of several plant functions. Like for humans, dysbiosis of the plant-associated microbiota may be a co-causal agent in disease with still obscure eziology. In the last decades, the common reed Phragmites aust...
Gespeichert in:
Veröffentlicht in: | The Science of the total environment 2018-11, Vol.642, p.708-722 |
---|---|
Hauptverfasser: | , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 722 |
---|---|
container_issue | |
container_start_page | 708 |
container_title | The Science of the total environment |
container_volume | 642 |
creator | Bacci, Giovanni Cerri, Martina Lastrucci, Lorenzo Ferranti, Francesco Ferri, Valentina Foggi, Bruno Gigante, Daniela Venanzoni, Roberto Viciani, Daniele Mengoni, Alessio Reale, Lara Coppi, Andrea |
description | The microbiota inhabiting the soil, as well as the rhizosphere, represents a key determinant of several plant functions. Like for humans, dysbiosis of the plant-associated microbiota may be a co-causal agent in disease with still obscure eziology. In the last decades, the common reed Phragmites australis has been deeply studied for its disappearance from natural stands, but no clear causative agents have been identified and no laboratory models of such “reed die-back syndrome” (RDBS) have been developed. In this study, we try to shed light on the RDBS, by comparing the rhizosphere microbiota of five Italian P. australis populations with different degrees of decline. Results obtained showed a biogeographical meaningful pattern of rhizosphere microbiota, coupled with an impact of RDBS. Obtained data allowed to construct a two-steps predictive model which enabled the prediction of the plant health status from the microbiota taxonomic composition, independently from their geographic location. In conclusion, this study represents one of the first overviews that statistically links RDBS to alteration of rhizosphere microbiota and suggests a model for the analysis of plant-bacteria relationships in nature.
[Display omitted]
•Die-back of Phragmites australis is a still obscure syndrome.•Root microbiota composition was shown to be affected by both sites and health status.•A plant health status x site x microbiota interaction was defined.•Root microbiota composition was shown to be predictable from plant health status. |
doi_str_mv | 10.1016/j.scitotenv.2018.06.066 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2057127860</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0048969718321375</els_id><sourcerecordid>2057127860</sourcerecordid><originalsourceid>FETCH-LOGICAL-c371t-d6c9ce81fdb0c514b6e7024bfc3d0ecf59b48ec84999f335d273c1731bb9bb93</originalsourceid><addsrcrecordid>eNqFkMFqGzEQhkVpaJykr9Dq2Ms60motrY7GtE0gkEvuYnc0SuTurlRpbXCfPjJ2fc3ww1y-fwY-Qr5ztuSMy_vtMoOfw4zTflkz3i6ZLJGfyIK3Slec1fIzWTDWtJWWWl2Tm5y3rIxq-RdyXWvNhZByQeI6xuHgp1caE1oPs98jHYPFIdM5UIvg4xsmmt78v9B3MGPy3XAkvPPQzT5MmfqJQhjHMNGEaKn1WBX0D-2cw9KwNIa4G07wHbly3ZDx63nfkpdfP182D9XT8-_HzfqpAqH4XFkJGrDlzvYMVrzpJSpWN70DYRmCW-m-aRHaRmvthFjZWgngSvC-1yXilvw4nY0p_N1hns3oM-AwdBOGXTY1Wyleq1aygqoTCinknNCZmPzYpYPhzBxtm6252DZH24bJElma385Pdv2I9tL7r7cA6xNQdOLeYzoewgmK6VTMGBv8h0_eAcJOmNE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2057127860</pqid></control><display><type>article</type><title>Applying predictive models to decipher rhizobacterial modifications in common reed die-back affected populations</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals</source><creator>Bacci, Giovanni ; Cerri, Martina ; Lastrucci, Lorenzo ; Ferranti, Francesco ; Ferri, Valentina ; Foggi, Bruno ; Gigante, Daniela ; Venanzoni, Roberto ; Viciani, Daniele ; Mengoni, Alessio ; Reale, Lara ; Coppi, Andrea</creator><creatorcontrib>Bacci, Giovanni ; Cerri, Martina ; Lastrucci, Lorenzo ; Ferranti, Francesco ; Ferri, Valentina ; Foggi, Bruno ; Gigante, Daniela ; Venanzoni, Roberto ; Viciani, Daniele ; Mengoni, Alessio ; Reale, Lara ; Coppi, Andrea</creatorcontrib><description>The microbiota inhabiting the soil, as well as the rhizosphere, represents a key determinant of several plant functions. Like for humans, dysbiosis of the plant-associated microbiota may be a co-causal agent in disease with still obscure eziology. In the last decades, the common reed Phragmites australis has been deeply studied for its disappearance from natural stands, but no clear causative agents have been identified and no laboratory models of such “reed die-back syndrome” (RDBS) have been developed. In this study, we try to shed light on the RDBS, by comparing the rhizosphere microbiota of five Italian P. australis populations with different degrees of decline. Results obtained showed a biogeographical meaningful pattern of rhizosphere microbiota, coupled with an impact of RDBS. Obtained data allowed to construct a two-steps predictive model which enabled the prediction of the plant health status from the microbiota taxonomic composition, independently from their geographic location. In conclusion, this study represents one of the first overviews that statistically links RDBS to alteration of rhizosphere microbiota and suggests a model for the analysis of plant-bacteria relationships in nature.
[Display omitted]
•Die-back of Phragmites australis is a still obscure syndrome.•Root microbiota composition was shown to be affected by both sites and health status.•A plant health status x site x microbiota interaction was defined.•Root microbiota composition was shown to be predictable from plant health status.</description><identifier>ISSN: 0048-9697</identifier><identifier>EISSN: 1879-1026</identifier><identifier>DOI: 10.1016/j.scitotenv.2018.06.066</identifier><identifier>PMID: 29913366</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Ecology ; Italy ; Microbiota ; Models, Theoretical ; Phragmites australis ; Plant Roots ; Poaceae ; Predictive models ; Reed die-back ; Rhizosphere ; Soil Microbiology</subject><ispartof>The Science of the total environment, 2018-11, Vol.642, p.708-722</ispartof><rights>2018 Elsevier B.V.</rights><rights>Copyright © 2018 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c371t-d6c9ce81fdb0c514b6e7024bfc3d0ecf59b48ec84999f335d273c1731bb9bb93</citedby><cites>FETCH-LOGICAL-c371t-d6c9ce81fdb0c514b6e7024bfc3d0ecf59b48ec84999f335d273c1731bb9bb93</cites><orcidid>0000-0003-4760-8403 ; 0000-0002-1265-8251 ; 0000-0003-4406-7816</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.scitotenv.2018.06.066$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,45974</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29913366$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bacci, Giovanni</creatorcontrib><creatorcontrib>Cerri, Martina</creatorcontrib><creatorcontrib>Lastrucci, Lorenzo</creatorcontrib><creatorcontrib>Ferranti, Francesco</creatorcontrib><creatorcontrib>Ferri, Valentina</creatorcontrib><creatorcontrib>Foggi, Bruno</creatorcontrib><creatorcontrib>Gigante, Daniela</creatorcontrib><creatorcontrib>Venanzoni, Roberto</creatorcontrib><creatorcontrib>Viciani, Daniele</creatorcontrib><creatorcontrib>Mengoni, Alessio</creatorcontrib><creatorcontrib>Reale, Lara</creatorcontrib><creatorcontrib>Coppi, Andrea</creatorcontrib><title>Applying predictive models to decipher rhizobacterial modifications in common reed die-back affected populations</title><title>The Science of the total environment</title><addtitle>Sci Total Environ</addtitle><description>The microbiota inhabiting the soil, as well as the rhizosphere, represents a key determinant of several plant functions. Like for humans, dysbiosis of the plant-associated microbiota may be a co-causal agent in disease with still obscure eziology. In the last decades, the common reed Phragmites australis has been deeply studied for its disappearance from natural stands, but no clear causative agents have been identified and no laboratory models of such “reed die-back syndrome” (RDBS) have been developed. In this study, we try to shed light on the RDBS, by comparing the rhizosphere microbiota of five Italian P. australis populations with different degrees of decline. Results obtained showed a biogeographical meaningful pattern of rhizosphere microbiota, coupled with an impact of RDBS. Obtained data allowed to construct a two-steps predictive model which enabled the prediction of the plant health status from the microbiota taxonomic composition, independently from their geographic location. In conclusion, this study represents one of the first overviews that statistically links RDBS to alteration of rhizosphere microbiota and suggests a model for the analysis of plant-bacteria relationships in nature.
[Display omitted]
•Die-back of Phragmites australis is a still obscure syndrome.•Root microbiota composition was shown to be affected by both sites and health status.•A plant health status x site x microbiota interaction was defined.•Root microbiota composition was shown to be predictable from plant health status.</description><subject>Ecology</subject><subject>Italy</subject><subject>Microbiota</subject><subject>Models, Theoretical</subject><subject>Phragmites australis</subject><subject>Plant Roots</subject><subject>Poaceae</subject><subject>Predictive models</subject><subject>Reed die-back</subject><subject>Rhizosphere</subject><subject>Soil Microbiology</subject><issn>0048-9697</issn><issn>1879-1026</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkMFqGzEQhkVpaJykr9Dq2Ms60motrY7GtE0gkEvuYnc0SuTurlRpbXCfPjJ2fc3ww1y-fwY-Qr5ztuSMy_vtMoOfw4zTflkz3i6ZLJGfyIK3Slec1fIzWTDWtJWWWl2Tm5y3rIxq-RdyXWvNhZByQeI6xuHgp1caE1oPs98jHYPFIdM5UIvg4xsmmt78v9B3MGPy3XAkvPPQzT5MmfqJQhjHMNGEaKn1WBX0D-2cw9KwNIa4G07wHbly3ZDx63nfkpdfP182D9XT8-_HzfqpAqH4XFkJGrDlzvYMVrzpJSpWN70DYRmCW-m-aRHaRmvthFjZWgngSvC-1yXilvw4nY0p_N1hns3oM-AwdBOGXTY1Wyleq1aygqoTCinknNCZmPzYpYPhzBxtm6252DZH24bJElma385Pdv2I9tL7r7cA6xNQdOLeYzoewgmK6VTMGBv8h0_eAcJOmNE</recordid><startdate>20181115</startdate><enddate>20181115</enddate><creator>Bacci, Giovanni</creator><creator>Cerri, Martina</creator><creator>Lastrucci, Lorenzo</creator><creator>Ferranti, Francesco</creator><creator>Ferri, Valentina</creator><creator>Foggi, Bruno</creator><creator>Gigante, Daniela</creator><creator>Venanzoni, Roberto</creator><creator>Viciani, Daniele</creator><creator>Mengoni, Alessio</creator><creator>Reale, Lara</creator><creator>Coppi, Andrea</creator><general>Elsevier B.V</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>7X8</scope><orcidid>https://orcid.org/0000-0003-4760-8403</orcidid><orcidid>https://orcid.org/0000-0002-1265-8251</orcidid><orcidid>https://orcid.org/0000-0003-4406-7816</orcidid></search><sort><creationdate>20181115</creationdate><title>Applying predictive models to decipher rhizobacterial modifications in common reed die-back affected populations</title><author>Bacci, Giovanni ; Cerri, Martina ; Lastrucci, Lorenzo ; Ferranti, Francesco ; Ferri, Valentina ; Foggi, Bruno ; Gigante, Daniela ; Venanzoni, Roberto ; Viciani, Daniele ; Mengoni, Alessio ; Reale, Lara ; Coppi, Andrea</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c371t-d6c9ce81fdb0c514b6e7024bfc3d0ecf59b48ec84999f335d273c1731bb9bb93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Ecology</topic><topic>Italy</topic><topic>Microbiota</topic><topic>Models, Theoretical</topic><topic>Phragmites australis</topic><topic>Plant Roots</topic><topic>Poaceae</topic><topic>Predictive models</topic><topic>Reed die-back</topic><topic>Rhizosphere</topic><topic>Soil Microbiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bacci, Giovanni</creatorcontrib><creatorcontrib>Cerri, Martina</creatorcontrib><creatorcontrib>Lastrucci, Lorenzo</creatorcontrib><creatorcontrib>Ferranti, Francesco</creatorcontrib><creatorcontrib>Ferri, Valentina</creatorcontrib><creatorcontrib>Foggi, Bruno</creatorcontrib><creatorcontrib>Gigante, Daniela</creatorcontrib><creatorcontrib>Venanzoni, Roberto</creatorcontrib><creatorcontrib>Viciani, Daniele</creatorcontrib><creatorcontrib>Mengoni, Alessio</creatorcontrib><creatorcontrib>Reale, Lara</creatorcontrib><creatorcontrib>Coppi, Andrea</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>The Science of the total environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bacci, Giovanni</au><au>Cerri, Martina</au><au>Lastrucci, Lorenzo</au><au>Ferranti, Francesco</au><au>Ferri, Valentina</au><au>Foggi, Bruno</au><au>Gigante, Daniela</au><au>Venanzoni, Roberto</au><au>Viciani, Daniele</au><au>Mengoni, Alessio</au><au>Reale, Lara</au><au>Coppi, Andrea</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Applying predictive models to decipher rhizobacterial modifications in common reed die-back affected populations</atitle><jtitle>The Science of the total environment</jtitle><addtitle>Sci Total Environ</addtitle><date>2018-11-15</date><risdate>2018</risdate><volume>642</volume><spage>708</spage><epage>722</epage><pages>708-722</pages><issn>0048-9697</issn><eissn>1879-1026</eissn><abstract>The microbiota inhabiting the soil, as well as the rhizosphere, represents a key determinant of several plant functions. Like for humans, dysbiosis of the plant-associated microbiota may be a co-causal agent in disease with still obscure eziology. In the last decades, the common reed Phragmites australis has been deeply studied for its disappearance from natural stands, but no clear causative agents have been identified and no laboratory models of such “reed die-back syndrome” (RDBS) have been developed. In this study, we try to shed light on the RDBS, by comparing the rhizosphere microbiota of five Italian P. australis populations with different degrees of decline. Results obtained showed a biogeographical meaningful pattern of rhizosphere microbiota, coupled with an impact of RDBS. Obtained data allowed to construct a two-steps predictive model which enabled the prediction of the plant health status from the microbiota taxonomic composition, independently from their geographic location. In conclusion, this study represents one of the first overviews that statistically links RDBS to alteration of rhizosphere microbiota and suggests a model for the analysis of plant-bacteria relationships in nature.
[Display omitted]
•Die-back of Phragmites australis is a still obscure syndrome.•Root microbiota composition was shown to be affected by both sites and health status.•A plant health status x site x microbiota interaction was defined.•Root microbiota composition was shown to be predictable from plant health status.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>29913366</pmid><doi>10.1016/j.scitotenv.2018.06.066</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0003-4760-8403</orcidid><orcidid>https://orcid.org/0000-0002-1265-8251</orcidid><orcidid>https://orcid.org/0000-0003-4406-7816</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0048-9697 |
ispartof | The Science of the total environment, 2018-11, Vol.642, p.708-722 |
issn | 0048-9697 1879-1026 |
language | eng |
recordid | cdi_proquest_miscellaneous_2057127860 |
source | MEDLINE; Elsevier ScienceDirect Journals |
subjects | Ecology Italy Microbiota Models, Theoretical Phragmites australis Plant Roots Poaceae Predictive models Reed die-back Rhizosphere Soil Microbiology |
title | Applying predictive models to decipher rhizobacterial modifications in common reed die-back affected populations |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-22T05%3A02%3A56IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Applying%20predictive%20models%20to%20decipher%20rhizobacterial%20modifications%20in%20common%20reed%20die-back%20affected%20populations&rft.jtitle=The%20Science%20of%20the%20total%20environment&rft.au=Bacci,%20Giovanni&rft.date=2018-11-15&rft.volume=642&rft.spage=708&rft.epage=722&rft.pages=708-722&rft.issn=0048-9697&rft.eissn=1879-1026&rft_id=info:doi/10.1016/j.scitotenv.2018.06.066&rft_dat=%3Cproquest_cross%3E2057127860%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2057127860&rft_id=info:pmid/29913366&rft_els_id=S0048969718321375&rfr_iscdi=true |