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Bacterial and Eukaryotic Small-Subunit Amplicon Data Do Not Provide a Quantitative Picture of Microbial Communities, but They Are Reliable in the Context of Ecological Interpretations
High-throughput sequencing (HTS) of gene amplicons is a preferred method of assessing microbial community composition, because it rapidly provides information from a large number of samples at high taxonomic resolution and low costs. However, mock community studies show that HTS data poorly reflect...
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description | High-throughput sequencing (HTS) of gene amplicons is a preferred method of assessing microbial community composition, because it rapidly provides information from a large number of samples at high taxonomic resolution and low costs. However, mock community studies show that HTS data poorly reflect the actual relative abundances of individual phylotypes, casting doubt on the reliability of subsequent statistical analysis and data interpretation. We investigated how accurately HTS data reflect the variability of bacterial and eukaryotic community composition and their relationship with environmental factors in natural samples. For this, we compared results of HTS from three independent aquatic time series (
= 883) with those from an established, quantitative microscopic method (catalyzed reporter deposition-fluorescence
hybridization [CARD-FISH]). Relative abundances obtained by CARD-FISH and HTS disagreed for most bacterial and eukaryotic phylotypes. Nevertheless, the two methods identified the same environmental drivers to shape bacterial and eukaryotic communities. Our results show that amplicon data do provide reliable information for their ecological interpretations. Yet, when studying specific phylogenetic groups, it is advisable to combine HTS with quantification using microscopy and/or the addition of internal standards.
High-throughput sequencing (HTS) of amplified fragments of rRNA genes provides unprecedented insight into the diversity of prokaryotic and eukaryotic microorganisms. Unfortunately, HTS data are prone to quantitative biases, which may lead to an erroneous picture of microbial community composition and thwart efforts to advance its understanding. These concerns motivated us to investigate how accurately HTS data characterize the variability of microbial communities, the relative abundances of specific phylotypes, and their relationships with environmental factors in comparison to an established microscopy-based method. We compared results obtained by HTS and catalyzed reporter deposition-fluorescence
hybridization (CARD-FISH) from three independent aquatic time series for both prokaryotic and eukaryotic microorganisms (almost 900 data points, the largest obtained with both methods so far). HTS and CARD-FISH data disagree with regard to relative abundances of bacterial and eukaryotic phylotypes but identify similar environmental drivers shaping bacterial and eukaryotic communities. |
doi_str_mv | 10.1128/mSphere.00052-20 |
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= 883) with those from an established, quantitative microscopic method (catalyzed reporter deposition-fluorescence
hybridization [CARD-FISH]). Relative abundances obtained by CARD-FISH and HTS disagreed for most bacterial and eukaryotic phylotypes. Nevertheless, the two methods identified the same environmental drivers to shape bacterial and eukaryotic communities. Our results show that amplicon data do provide reliable information for their ecological interpretations. Yet, when studying specific phylogenetic groups, it is advisable to combine HTS with quantification using microscopy and/or the addition of internal standards.
High-throughput sequencing (HTS) of amplified fragments of rRNA genes provides unprecedented insight into the diversity of prokaryotic and eukaryotic microorganisms. Unfortunately, HTS data are prone to quantitative biases, which may lead to an erroneous picture of microbial community composition and thwart efforts to advance its understanding. These concerns motivated us to investigate how accurately HTS data characterize the variability of microbial communities, the relative abundances of specific phylotypes, and their relationships with environmental factors in comparison to an established microscopy-based method. We compared results obtained by HTS and catalyzed reporter deposition-fluorescence
hybridization (CARD-FISH) from three independent aquatic time series for both prokaryotic and eukaryotic microorganisms (almost 900 data points, the largest obtained with both methods so far). HTS and CARD-FISH data disagree with regard to relative abundances of bacterial and eukaryotic phylotypes but identify similar environmental drivers shaping bacterial and eukaryotic communities.</description><identifier>ISSN: 2379-5042</identifier><identifier>EISSN: 2379-5042</identifier><identifier>DOI: 10.1128/mSphere.00052-20</identifier><identifier>PMID: 32132159</identifier><language>eng</language><publisher>United States: American Society for Microbiology</publisher><subject>Accuracy ; amplicon sequencing ; Applied and Environmental Science ; Aquatic microorganisms ; Bacteria ; Bacteria - classification ; bacterial communities ; bacterial community structure ; bacterial dynamics ; Biomass ; CARD-FISH ; Community composition ; Datasets ; Environmental factors ; Eukaryota - classification ; eukaryotic communities ; Fluorescence in situ hybridization ; Genes ; High-Throughput Nucleotide Sequencing ; Microbiomes ; Microbiota ; Microscopy, Fluorescence ; Models, Statistical ; Next-generation sequencing ; Phylogenetics ; Phylogeny ; Reproducibility of Results ; RNA, Ribosomal, 16S - genetics ; rRNA ; Seawater - microbiology ; Sequence Analysis, DNA ; Statistical analysis</subject><ispartof>mSphere, 2020-03, Vol.5 (2)</ispartof><rights>Copyright © 2020 Piwosz et al.</rights><rights>Copyright © 2020 Piwosz et al. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Copyright © 2020 Piwosz et al. 2020 Piwosz et al.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c537t-2c0007a8ae77868008c2cfeff3863f9153f9495dc9dae3bf4dc863fdc3d359c73</citedby><cites>FETCH-LOGICAL-c537t-2c0007a8ae77868008c2cfeff3863f9153f9495dc9dae3bf4dc863fdc3d359c73</cites><orcidid>0000-0003-4526-3587 ; 0000-0002-7058-9063 ; 0000-0001-5145-3761 ; 0000-0002-3248-3364 ; 0000-0001-7558-909X ; 0000-0003-1063-6523</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2384876828/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2384876828?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,3187,25752,27923,27924,37011,37012,44589,53790,53792,74997</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32132159$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>McMahon, Katherine</contributor><creatorcontrib>Piwosz, Kasia</creatorcontrib><creatorcontrib>Shabarova, Tanja</creatorcontrib><creatorcontrib>Pernthaler, Jakob</creatorcontrib><creatorcontrib>Posch, Thomas</creatorcontrib><creatorcontrib>Šimek, Karel</creatorcontrib><creatorcontrib>Porcal, Petr</creatorcontrib><creatorcontrib>Salcher, Michaela M</creatorcontrib><title>Bacterial and Eukaryotic Small-Subunit Amplicon Data Do Not Provide a Quantitative Picture of Microbial Communities, but They Are Reliable in the Context of Ecological Interpretations</title><title>mSphere</title><addtitle>mSphere</addtitle><description>High-throughput sequencing (HTS) of gene amplicons is a preferred method of assessing microbial community composition, because it rapidly provides information from a large number of samples at high taxonomic resolution and low costs. However, mock community studies show that HTS data poorly reflect the actual relative abundances of individual phylotypes, casting doubt on the reliability of subsequent statistical analysis and data interpretation. We investigated how accurately HTS data reflect the variability of bacterial and eukaryotic community composition and their relationship with environmental factors in natural samples. For this, we compared results of HTS from three independent aquatic time series (
= 883) with those from an established, quantitative microscopic method (catalyzed reporter deposition-fluorescence
hybridization [CARD-FISH]). Relative abundances obtained by CARD-FISH and HTS disagreed for most bacterial and eukaryotic phylotypes. Nevertheless, the two methods identified the same environmental drivers to shape bacterial and eukaryotic communities. Our results show that amplicon data do provide reliable information for their ecological interpretations. Yet, when studying specific phylogenetic groups, it is advisable to combine HTS with quantification using microscopy and/or the addition of internal standards.
High-throughput sequencing (HTS) of amplified fragments of rRNA genes provides unprecedented insight into the diversity of prokaryotic and eukaryotic microorganisms. Unfortunately, HTS data are prone to quantitative biases, which may lead to an erroneous picture of microbial community composition and thwart efforts to advance its understanding. These concerns motivated us to investigate how accurately HTS data characterize the variability of microbial communities, the relative abundances of specific phylotypes, and their relationships with environmental factors in comparison to an established microscopy-based method. We compared results obtained by HTS and catalyzed reporter deposition-fluorescence
hybridization (CARD-FISH) from three independent aquatic time series for both prokaryotic and eukaryotic microorganisms (almost 900 data points, the largest obtained with both methods so far). HTS and CARD-FISH data disagree with regard to relative abundances of bacterial and eukaryotic phylotypes but identify similar environmental drivers shaping bacterial and eukaryotic communities.</description><subject>Accuracy</subject><subject>amplicon sequencing</subject><subject>Applied and Environmental Science</subject><subject>Aquatic microorganisms</subject><subject>Bacteria</subject><subject>Bacteria - classification</subject><subject>bacterial communities</subject><subject>bacterial community structure</subject><subject>bacterial dynamics</subject><subject>Biomass</subject><subject>CARD-FISH</subject><subject>Community composition</subject><subject>Datasets</subject><subject>Environmental factors</subject><subject>Eukaryota - classification</subject><subject>eukaryotic communities</subject><subject>Fluorescence in situ hybridization</subject><subject>Genes</subject><subject>High-Throughput Nucleotide Sequencing</subject><subject>Microbiomes</subject><subject>Microbiota</subject><subject>Microscopy, Fluorescence</subject><subject>Models, Statistical</subject><subject>Next-generation sequencing</subject><subject>Phylogenetics</subject><subject>Phylogeny</subject><subject>Reproducibility of Results</subject><subject>RNA, Ribosomal, 16S - genetics</subject><subject>rRNA</subject><subject>Seawater - microbiology</subject><subject>Sequence Analysis, DNA</subject><subject>Statistical analysis</subject><issn>2379-5042</issn><issn>2379-5042</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdUsFu1DAQjRCIVqV3TsgSFw6kOHYcOxek7XaBlQoUtpwtx57senHixXEq-mX8Hk53qVoky7Zm3nueGb8se1ngs6Ig4l232m0gwBnGmJGc4CfZMaG8zhkuydMH96PsdBi2CVVUpKp49Tw7oqRIi9XH2Z9zpSMEqxxSvUGL8acKtz5ajVadci5fjc3Y24hm3c5Z7Xt0oaJCFx598RFdBX9jDSCFvo2qjzaqaG8AXVkdxwDIt-iz1cE3k_rcd92kZGF4i5oxousN3KJZgn0HZ1XjANkexQ0kZB_hd5zoC-2dX1ud-MsUDLsA0xu-H15kz1rlBjg9nCfZjw-L6_mn_PLrx-V8dplrRnnMiU59cyUUcC4qgbHQRLfQtlRUtK0LlrayZkbXRgFt2tLoKWE0NZTVmtOTbLnXNV5t5S7YLs1HemXlXcCHtVQhjcuBNEy1hWGcEcbLqqGNIAJrLgRWDWXGJK33e63d2HRgNPQxKPdI9HGmtxu59jeSY5ZqL5PAm4NA8L9GGKLs7KDBOdWDHweZvrwQrBTVBH39H3Trx9CnUSWUKAWvUnUJhfeo9EvDEKC9L6bAcjKZPJhM3plMEpworx42cU_4Zyn6F_CQ0es</recordid><startdate>20200304</startdate><enddate>20200304</enddate><creator>Piwosz, Kasia</creator><creator>Shabarova, Tanja</creator><creator>Pernthaler, Jakob</creator><creator>Posch, Thomas</creator><creator>Šimek, Karel</creator><creator>Porcal, Petr</creator><creator>Salcher, Michaela M</creator><general>American Society for Microbiology</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>7X7</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-4526-3587</orcidid><orcidid>https://orcid.org/0000-0002-7058-9063</orcidid><orcidid>https://orcid.org/0000-0001-5145-3761</orcidid><orcidid>https://orcid.org/0000-0002-3248-3364</orcidid><orcidid>https://orcid.org/0000-0001-7558-909X</orcidid><orcidid>https://orcid.org/0000-0003-1063-6523</orcidid></search><sort><creationdate>20200304</creationdate><title>Bacterial and Eukaryotic Small-Subunit Amplicon Data Do Not Provide a Quantitative Picture of Microbial Communities, but They Are Reliable in the Context of Ecological Interpretations</title><author>Piwosz, Kasia ; Shabarova, Tanja ; Pernthaler, Jakob ; Posch, Thomas ; Šimek, Karel ; Porcal, Petr ; Salcher, Michaela M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c537t-2c0007a8ae77868008c2cfeff3863f9153f9495dc9dae3bf4dc863fdc3d359c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Accuracy</topic><topic>amplicon sequencing</topic><topic>Applied and Environmental Science</topic><topic>Aquatic microorganisms</topic><topic>Bacteria</topic><topic>Bacteria - classification</topic><topic>bacterial communities</topic><topic>bacterial community structure</topic><topic>bacterial dynamics</topic><topic>Biomass</topic><topic>CARD-FISH</topic><topic>Community composition</topic><topic>Datasets</topic><topic>Environmental factors</topic><topic>Eukaryota - classification</topic><topic>eukaryotic communities</topic><topic>Fluorescence in situ hybridization</topic><topic>Genes</topic><topic>High-Throughput Nucleotide Sequencing</topic><topic>Microbiomes</topic><topic>Microbiota</topic><topic>Microscopy, Fluorescence</topic><topic>Models, Statistical</topic><topic>Next-generation sequencing</topic><topic>Phylogenetics</topic><topic>Phylogeny</topic><topic>Reproducibility of Results</topic><topic>RNA, Ribosomal, 16S - genetics</topic><topic>rRNA</topic><topic>Seawater - microbiology</topic><topic>Sequence Analysis, DNA</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Piwosz, Kasia</creatorcontrib><creatorcontrib>Shabarova, Tanja</creatorcontrib><creatorcontrib>Pernthaler, Jakob</creatorcontrib><creatorcontrib>Posch, Thomas</creatorcontrib><creatorcontrib>Šimek, Karel</creatorcontrib><creatorcontrib>Porcal, Petr</creatorcontrib><creatorcontrib>Salcher, Michaela M</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>ProQuest - Health & Medical Complete保健、医学与药学数据库</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech 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>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Biological Science Database</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>mSphere</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Piwosz, Kasia</au><au>Shabarova, Tanja</au><au>Pernthaler, Jakob</au><au>Posch, Thomas</au><au>Šimek, Karel</au><au>Porcal, Petr</au><au>Salcher, Michaela M</au><au>McMahon, Katherine</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bacterial and Eukaryotic Small-Subunit Amplicon Data Do Not Provide a Quantitative Picture of Microbial Communities, but They Are Reliable in the Context of Ecological Interpretations</atitle><jtitle>mSphere</jtitle><addtitle>mSphere</addtitle><date>2020-03-04</date><risdate>2020</risdate><volume>5</volume><issue>2</issue><issn>2379-5042</issn><eissn>2379-5042</eissn><abstract>High-throughput sequencing (HTS) of gene amplicons is a preferred method of assessing microbial community composition, because it rapidly provides information from a large number of samples at high taxonomic resolution and low costs. However, mock community studies show that HTS data poorly reflect the actual relative abundances of individual phylotypes, casting doubt on the reliability of subsequent statistical analysis and data interpretation. We investigated how accurately HTS data reflect the variability of bacterial and eukaryotic community composition and their relationship with environmental factors in natural samples. For this, we compared results of HTS from three independent aquatic time series (
= 883) with those from an established, quantitative microscopic method (catalyzed reporter deposition-fluorescence
hybridization [CARD-FISH]). Relative abundances obtained by CARD-FISH and HTS disagreed for most bacterial and eukaryotic phylotypes. Nevertheless, the two methods identified the same environmental drivers to shape bacterial and eukaryotic communities. Our results show that amplicon data do provide reliable information for their ecological interpretations. Yet, when studying specific phylogenetic groups, it is advisable to combine HTS with quantification using microscopy and/or the addition of internal standards.
High-throughput sequencing (HTS) of amplified fragments of rRNA genes provides unprecedented insight into the diversity of prokaryotic and eukaryotic microorganisms. Unfortunately, HTS data are prone to quantitative biases, which may lead to an erroneous picture of microbial community composition and thwart efforts to advance its understanding. These concerns motivated us to investigate how accurately HTS data characterize the variability of microbial communities, the relative abundances of specific phylotypes, and their relationships with environmental factors in comparison to an established microscopy-based method. We compared results obtained by HTS and catalyzed reporter deposition-fluorescence
hybridization (CARD-FISH) from three independent aquatic time series for both prokaryotic and eukaryotic microorganisms (almost 900 data points, the largest obtained with both methods so far). HTS and CARD-FISH data disagree with regard to relative abundances of bacterial and eukaryotic phylotypes but identify similar environmental drivers shaping bacterial and eukaryotic communities.</abstract><cop>United States</cop><pub>American Society for Microbiology</pub><pmid>32132159</pmid><doi>10.1128/mSphere.00052-20</doi><orcidid>https://orcid.org/0000-0003-4526-3587</orcidid><orcidid>https://orcid.org/0000-0002-7058-9063</orcidid><orcidid>https://orcid.org/0000-0001-5145-3761</orcidid><orcidid>https://orcid.org/0000-0002-3248-3364</orcidid><orcidid>https://orcid.org/0000-0001-7558-909X</orcidid><orcidid>https://orcid.org/0000-0003-1063-6523</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy amplicon sequencing Applied and Environmental Science Aquatic microorganisms Bacteria Bacteria - classification bacterial communities bacterial community structure bacterial dynamics Biomass CARD-FISH Community composition Datasets Environmental factors Eukaryota - classification eukaryotic communities Fluorescence in situ hybridization Genes High-Throughput Nucleotide Sequencing Microbiomes Microbiota Microscopy, Fluorescence Models, Statistical Next-generation sequencing Phylogenetics Phylogeny Reproducibility of Results RNA, Ribosomal, 16S - genetics rRNA Seawater - microbiology Sequence Analysis, DNA Statistical analysis |
title | Bacterial and Eukaryotic Small-Subunit Amplicon Data Do Not Provide a Quantitative Picture of Microbial Communities, but They Are Reliable in the Context of Ecological Interpretations |
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