Spatiotemporal molecular analysis of cyanobacteria blooms reveals Microcystis--Aphanizomenon interactions
Spatial and temporal variability in cyanobacterial community composition (CCC) within and between eutrophic lakes is not well-described using culture independent molecular methods. We analyzed CCC across twelve locations in four eutrophic lakes and within-lake locations in the Yahara Watershed, WI,...
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description | Spatial and temporal variability in cyanobacterial community composition (CCC) within and between eutrophic lakes is not well-described using culture independent molecular methods. We analyzed CCC across twelve locations in four eutrophic lakes and within-lake locations in the Yahara Watershed, WI, on a weekly basis, for 5 months. Taxa were discriminated by length of MspI-digested cpcB/A intergenic spacer gene sequences and identified by comparison to a PCR-based clone library. CCC across all stations was spatially segregated by depth of sampling locations (ANOSIM R = 0.23, p < 0.001). Accordingly, CCC was correlated with thermal stratification, nitrate and soluble reactive phosphorus (SRP, R = 0.2-0.3). Spatial variability in CCC and temporal trends in taxa abundances were rarely correlative between sampling locations in the same lake indicating significant within lake spatiotemporal heterogeneity. Across all stations, a total of 37 bloom events were observed based on distinct increases in phycocyanin. Out of 97 taxa, a single Microcystis, and two different Aphanizomenon taxa were the dominant cyanobacteria detected during bloom events. The Microcystis and Aphanizomenon taxa rarely bloomed together and were significantly anti-correlated with each other at 9 of 12 stations with Pearson R values of -0.6 to -0.9 (p < 0.001). Of all environmental variables measured, nutrients, especially nitrate were significantly greater during periods of Aphanizomenon dominance while the nitrate+nitrite:SRP ratio was lower. This study shows significant spatial variability in CCC within and between lakes structured by depth of the sampling location. Furthermore, our study reveals specific genotypes involved in bloom formation. More in-depth characterization of these genotypes should lead to a better understanding of factors promoting bloom events in these lakes and more reliable bloom prediction models. |
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We analyzed CCC across twelve locations in four eutrophic lakes and within-lake locations in the Yahara Watershed, WI, on a weekly basis, for 5 months. Taxa were discriminated by length of MspI-digested cpcB/A intergenic spacer gene sequences and identified by comparison to a PCR-based clone library. CCC across all stations was spatially segregated by depth of sampling locations (ANOSIM R = 0.23, p < 0.001). Accordingly, CCC was correlated with thermal stratification, nitrate and soluble reactive phosphorus (SRP, R = 0.2-0.3). Spatial variability in CCC and temporal trends in taxa abundances were rarely correlative between sampling locations in the same lake indicating significant within lake spatiotemporal heterogeneity. Across all stations, a total of 37 bloom events were observed based on distinct increases in phycocyanin. Out of 97 taxa, a single Microcystis, and two different Aphanizomenon taxa were the dominant cyanobacteria detected during bloom events. The Microcystis and Aphanizomenon taxa rarely bloomed together and were significantly anti-correlated with each other at 9 of 12 stations with Pearson R values of -0.6 to -0.9 (p < 0.001). Of all environmental variables measured, nutrients, especially nitrate were significantly greater during periods of Aphanizomenon dominance while the nitrate+nitrite:SRP ratio was lower. This study shows significant spatial variability in CCC within and between lakes structured by depth of the sampling location. Furthermore, our study reveals specific genotypes involved in bloom formation. More in-depth characterization of these genotypes should lead to a better understanding of factors promoting bloom events in these lakes and more reliable bloom prediction models.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0074933</identifier><identifier>PMID: 24086400</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Aphanizomenon ; Aphanizomenon - physiology ; Bacteriology ; Community composition ; Competitive advantage ; Correlation ; Cyanobacteria ; Environmental conditions ; Environmental engineering ; Eutrophic environments ; Eutrophic lakes ; Eutrophication ; Gene sequencing ; Genotypes ; Geography ; Heterogeneity ; Laboratories ; Lakes ; Lakes - chemistry ; Lakes - microbiology ; Microbial Interactions ; Microcystis ; Microcystis - physiology ; Nitrates ; Nitrogen ; Nutrients ; Phosphorus ; Phycocyanin ; Phycocyanin - metabolism ; Planktothrix ; Powell, Jerome ; Prediction models ; Sampling ; Solubility ; Spacer ; Spatial distribution ; Spatial variability ; Spatio-Temporal Analysis ; Stations ; Studies ; Taxa ; Temperature ; Temperature effects ; Temporal variability ; Thermal stratification ; Time Factors ; Variability ; Water quality ; Watershed management ; Watersheds ; Wisconsin</subject><ispartof>PloS one, 2013-09, Vol.8 (9), p.e74933-e74933</ispartof><rights>2013 Miller et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013 Miller et al 2013 Miller et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c526t-fd0da862aa1974f3c58acbd6700a443b4c6996176b3e9cdbb0149d7361e31aec3</citedby><cites>FETCH-LOGICAL-c526t-fd0da862aa1974f3c58acbd6700a443b4c6996176b3e9cdbb0149d7361e31aec3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3785500/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3785500/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79472,79473</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24086400$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Neilan, Brett</contributor><creatorcontrib>Miller, Todd R</creatorcontrib><creatorcontrib>Beversdorf, Lucas</creatorcontrib><creatorcontrib>Chaston, Sheena D</creatorcontrib><creatorcontrib>McMahon, Katherine D</creatorcontrib><title>Spatiotemporal molecular analysis of cyanobacteria blooms reveals Microcystis--Aphanizomenon interactions</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Spatial and temporal variability in cyanobacterial community composition (CCC) within and between eutrophic lakes is not well-described using culture independent molecular methods. We analyzed CCC across twelve locations in four eutrophic lakes and within-lake locations in the Yahara Watershed, WI, on a weekly basis, for 5 months. Taxa were discriminated by length of MspI-digested cpcB/A intergenic spacer gene sequences and identified by comparison to a PCR-based clone library. CCC across all stations was spatially segregated by depth of sampling locations (ANOSIM R = 0.23, p < 0.001). Accordingly, CCC was correlated with thermal stratification, nitrate and soluble reactive phosphorus (SRP, R = 0.2-0.3). Spatial variability in CCC and temporal trends in taxa abundances were rarely correlative between sampling locations in the same lake indicating significant within lake spatiotemporal heterogeneity. Across all stations, a total of 37 bloom events were observed based on distinct increases in phycocyanin. Out of 97 taxa, a single Microcystis, and two different Aphanizomenon taxa were the dominant cyanobacteria detected during bloom events. The Microcystis and Aphanizomenon taxa rarely bloomed together and were significantly anti-correlated with each other at 9 of 12 stations with Pearson R values of -0.6 to -0.9 (p < 0.001). Of all environmental variables measured, nutrients, especially nitrate were significantly greater during periods of Aphanizomenon dominance while the nitrate+nitrite:SRP ratio was lower. This study shows significant spatial variability in CCC within and between lakes structured by depth of the sampling location. Furthermore, our study reveals specific genotypes involved in bloom formation. More in-depth characterization of these genotypes should lead to a better understanding of factors promoting bloom events in these lakes and more reliable bloom prediction models.</description><subject>Aphanizomenon</subject><subject>Aphanizomenon - physiology</subject><subject>Bacteriology</subject><subject>Community composition</subject><subject>Competitive advantage</subject><subject>Correlation</subject><subject>Cyanobacteria</subject><subject>Environmental conditions</subject><subject>Environmental engineering</subject><subject>Eutrophic environments</subject><subject>Eutrophic lakes</subject><subject>Eutrophication</subject><subject>Gene sequencing</subject><subject>Genotypes</subject><subject>Geography</subject><subject>Heterogeneity</subject><subject>Laboratories</subject><subject>Lakes</subject><subject>Lakes - chemistry</subject><subject>Lakes - microbiology</subject><subject>Microbial Interactions</subject><subject>Microcystis</subject><subject>Microcystis - physiology</subject><subject>Nitrates</subject><subject>Nitrogen</subject><subject>Nutrients</subject><subject>Phosphorus</subject><subject>Phycocyanin</subject><subject>Phycocyanin - metabolism</subject><subject>Planktothrix</subject><subject>Powell, Jerome</subject><subject>Prediction models</subject><subject>Sampling</subject><subject>Solubility</subject><subject>Spacer</subject><subject>Spatial distribution</subject><subject>Spatial variability</subject><subject>Spatio-Temporal Analysis</subject><subject>Stations</subject><subject>Studies</subject><subject>Taxa</subject><subject>Temperature</subject><subject>Temperature effects</subject><subject>Temporal variability</subject><subject>Thermal stratification</subject><subject>Time Factors</subject><subject>Variability</subject><subject>Water quality</subject><subject>Watershed management</subject><subject>Watersheds</subject><subject>Wisconsin</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNptkktv1DAUhSMEoqXwDxBE6oZNBjt-xRukqmqhUhELYG1dP9J65NjBTioNv54Mk1YtYmXLPufzvdenqt5itMFE4I_bNOcIYTOm6DYICSoJeVYdY0nahreIPH-0P6pelbJFiJGO85fVUUtRxylCx5X_PsLk0-SGMWUI9ZCCM3OAXMMC3xVf6tTXZgcxaTCTyx5qHVIaSp3dnYNQ6q_e5GR2ZfKlac7GW4j-dxpcTLH2cXEsNp9ieV296Be5e7OuJ9XPy4sf51-a62-fr87PrhvDWj41vUUWOt4CYCloTwzrwGjLBUJAKdHUcCk5FlwTJ43VGmEqrSAcO4LBGXJSvT9wx5CKWqdUFKZEYsxYJxfF1UFhE2zVmP0AeacSePX3IOUbBXnyJjjVg-0sdcIJMJQBdD3nUjONrWU9M2hhfVpfm_XgrHFxWsb4BPr0JvpbdZPuFBEdY2gP-LACcvo1uzKpwRfjQoDo0ryvmxKKhGR0kZ7-I_1_d_SgWn6llOz6h2IwUvvk3LvUPjlqTc5ie_e4kQfTfVTIH8UGxco</recordid><startdate>20130927</startdate><enddate>20130927</enddate><creator>Miller, Todd R</creator><creator>Beversdorf, Lucas</creator><creator>Chaston, Sheena D</creator><creator>McMahon, Katherine D</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20130927</creationdate><title>Spatiotemporal molecular analysis of cyanobacteria blooms reveals Microcystis--Aphanizomenon interactions</title><author>Miller, Todd R ; Beversdorf, Lucas ; Chaston, Sheena D ; McMahon, Katherine D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c526t-fd0da862aa1974f3c58acbd6700a443b4c6996176b3e9cdbb0149d7361e31aec3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Aphanizomenon</topic><topic>Aphanizomenon - physiology</topic><topic>Bacteriology</topic><topic>Community composition</topic><topic>Competitive advantage</topic><topic>Correlation</topic><topic>Cyanobacteria</topic><topic>Environmental conditions</topic><topic>Environmental engineering</topic><topic>Eutrophic environments</topic><topic>Eutrophic lakes</topic><topic>Eutrophication</topic><topic>Gene sequencing</topic><topic>Genotypes</topic><topic>Geography</topic><topic>Heterogeneity</topic><topic>Laboratories</topic><topic>Lakes</topic><topic>Lakes - chemistry</topic><topic>Lakes - microbiology</topic><topic>Microbial Interactions</topic><topic>Microcystis</topic><topic>Microcystis - physiology</topic><topic>Nitrates</topic><topic>Nitrogen</topic><topic>Nutrients</topic><topic>Phosphorus</topic><topic>Phycocyanin</topic><topic>Phycocyanin - metabolism</topic><topic>Planktothrix</topic><topic>Powell, Jerome</topic><topic>Prediction models</topic><topic>Sampling</topic><topic>Solubility</topic><topic>Spacer</topic><topic>Spatial distribution</topic><topic>Spatial variability</topic><topic>Spatio-Temporal Analysis</topic><topic>Stations</topic><topic>Studies</topic><topic>Taxa</topic><topic>Temperature</topic><topic>Temperature effects</topic><topic>Temporal variability</topic><topic>Thermal stratification</topic><topic>Time Factors</topic><topic>Variability</topic><topic>Water quality</topic><topic>Watershed management</topic><topic>Watersheds</topic><topic>Wisconsin</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Miller, Todd R</creatorcontrib><creatorcontrib>Beversdorf, Lucas</creatorcontrib><creatorcontrib>Chaston, Sheena D</creatorcontrib><creatorcontrib>McMahon, Katherine D</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>ProQuest Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Miller, Todd R</au><au>Beversdorf, Lucas</au><au>Chaston, Sheena D</au><au>McMahon, Katherine D</au><au>Neilan, Brett</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatiotemporal molecular analysis of cyanobacteria blooms reveals Microcystis--Aphanizomenon interactions</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2013-09-27</date><risdate>2013</risdate><volume>8</volume><issue>9</issue><spage>e74933</spage><epage>e74933</epage><pages>e74933-e74933</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Spatial and temporal variability in cyanobacterial community composition (CCC) within and between eutrophic lakes is not well-described using culture independent molecular methods. We analyzed CCC across twelve locations in four eutrophic lakes and within-lake locations in the Yahara Watershed, WI, on a weekly basis, for 5 months. Taxa were discriminated by length of MspI-digested cpcB/A intergenic spacer gene sequences and identified by comparison to a PCR-based clone library. CCC across all stations was spatially segregated by depth of sampling locations (ANOSIM R = 0.23, p < 0.001). Accordingly, CCC was correlated with thermal stratification, nitrate and soluble reactive phosphorus (SRP, R = 0.2-0.3). Spatial variability in CCC and temporal trends in taxa abundances were rarely correlative between sampling locations in the same lake indicating significant within lake spatiotemporal heterogeneity. Across all stations, a total of 37 bloom events were observed based on distinct increases in phycocyanin. Out of 97 taxa, a single Microcystis, and two different Aphanizomenon taxa were the dominant cyanobacteria detected during bloom events. The Microcystis and Aphanizomenon taxa rarely bloomed together and were significantly anti-correlated with each other at 9 of 12 stations with Pearson R values of -0.6 to -0.9 (p < 0.001). Of all environmental variables measured, nutrients, especially nitrate were significantly greater during periods of Aphanizomenon dominance while the nitrate+nitrite:SRP ratio was lower. This study shows significant spatial variability in CCC within and between lakes structured by depth of the sampling location. Furthermore, our study reveals specific genotypes involved in bloom formation. More in-depth characterization of these genotypes should lead to a better understanding of factors promoting bloom events in these lakes and more reliable bloom prediction models.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24086400</pmid><doi>10.1371/journal.pone.0074933</doi><oa>free_for_read</oa></addata></record> |
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subjects | Aphanizomenon Aphanizomenon - physiology Bacteriology Community composition Competitive advantage Correlation Cyanobacteria Environmental conditions Environmental engineering Eutrophic environments Eutrophic lakes Eutrophication Gene sequencing Genotypes Geography Heterogeneity Laboratories Lakes Lakes - chemistry Lakes - microbiology Microbial Interactions Microcystis Microcystis - physiology Nitrates Nitrogen Nutrients Phosphorus Phycocyanin Phycocyanin - metabolism Planktothrix Powell, Jerome Prediction models Sampling Solubility Spacer Spatial distribution Spatial variability Spatio-Temporal Analysis Stations Studies Taxa Temperature Temperature effects Temporal variability Thermal stratification Time Factors Variability Water quality Watershed management Watersheds Wisconsin |
title | Spatiotemporal molecular analysis of cyanobacteria blooms reveals Microcystis--Aphanizomenon interactions |
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