Use of 16S rRNA gene sequences to identify cyanobacteria that can grow in far‐red light
Although most cyanobacteria use visible light (VL; λ = 400–700 nm) for photosynthesis, some have evolved strategies to use far‐red light (FRL; λ = 700–800 nm). These cyanobacteria are defined as far‐red light‐utilizing cyanobacteria (FRLCyano), including two groups: (1) chlorophyll d‐producing Acary...
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description | Although most cyanobacteria use visible light (VL; λ = 400–700 nm) for photosynthesis, some have evolved strategies to use far‐red light (FRL; λ = 700–800 nm). These cyanobacteria are defined as far‐red light‐utilizing cyanobacteria (FRLCyano), including two groups: (1) chlorophyll d‐producing Acaryochloris spp. and (2) polyphyletic cyanobacteria that produce chlorophylls d and f in response to FRL. Numerous ecological studies examine pigments, such as chlorophylls d and f, to investigate the presence of FRLCyano in the environment. This method is not ideal because it can only detect FRLCyano that have made chlorophylls d or f. Here we develop a new method, far‐red cyanobacteria identification (FRCI), to identify FRLCyano based on 16S rRNA gene sequences. From public databases and published articles, 62 16S rRNA gene sequences of FRLCyano were extracted. Comparing with related lineages, we determined that 97% sequence identity is the optimal cut‐off for distinguishing FRLCyano from other cyanobacteria. To test the method experimentally, we collected samples from 17 sites in Taipei, Taiwan, and conducted VL and FRL enrichments. Our results demonstrate that FRCI can detect FRLCyano during FRL enrichments more sensitively than pigment analysis. FRCI can also resolve the composition of FRLCyano at the genus level, which pigment analysis cannot do. In addition, we applied FRCI to published datasets and discovered putative FRLCyano in diverse environments, including soils, hot springs and deserts. Overall, our results indicate that FRCI is a sensitive and high‐resolution method using 16S rRNA gene sequences to identify FRLCyano. |
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These cyanobacteria are defined as far‐red light‐utilizing cyanobacteria (FRLCyano), including two groups: (1) chlorophyll d‐producing Acaryochloris spp. and (2) polyphyletic cyanobacteria that produce chlorophylls d and f in response to FRL. Numerous ecological studies examine pigments, such as chlorophylls d and f, to investigate the presence of FRLCyano in the environment. This method is not ideal because it can only detect FRLCyano that have made chlorophylls d or f. Here we develop a new method, far‐red cyanobacteria identification (FRCI), to identify FRLCyano based on 16S rRNA gene sequences. From public databases and published articles, 62 16S rRNA gene sequences of FRLCyano were extracted. Comparing with related lineages, we determined that 97% sequence identity is the optimal cut‐off for distinguishing FRLCyano from other cyanobacteria. To test the method experimentally, we collected samples from 17 sites in Taipei, Taiwan, and conducted VL and FRL enrichments. Our results demonstrate that FRCI can detect FRLCyano during FRL enrichments more sensitively than pigment analysis. FRCI can also resolve the composition of FRLCyano at the genus level, which pigment analysis cannot do. In addition, we applied FRCI to published datasets and discovered putative FRLCyano in diverse environments, including soils, hot springs and deserts. Overall, our results indicate that FRCI is a sensitive and high‐resolution method using 16S rRNA gene sequences to identify FRLCyano.</description><identifier>ISSN: 1755-098X</identifier><identifier>EISSN: 1755-0998</identifier><identifier>DOI: 10.1111/1755-0998.13871</identifier><identifier>PMID: 37772760</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>16S rRNA genes ; bacteria ; Chlorophyll ; Cyanobacteria ; DNA sequencing ; Ecological studies ; environmental DNA ; far‐red light ; Gene sequencing ; Hot springs ; metagenomics ; Photosynthesis ; Pigments ; rRNA 16S</subject><ispartof>Molecular ecology resources, 2024-01, Vol.24 (1), p.e13871-n/a</ispartof><rights>2023 John Wiley & Sons Ltd.</rights><rights>Copyright © 2024 John Wiley & Sons Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3711-d69f191cc01f4049f0d7e13fb170fd1eca77cc0551b1897ac62d302ae453c5fc3</citedby><cites>FETCH-LOGICAL-c3711-d69f191cc01f4049f0d7e13fb170fd1eca77cc0551b1897ac62d302ae453c5fc3</cites><orcidid>0000-0002-4961-931X ; 0009-0005-1990-2834 ; 0000-0003-2859-224X ; 0000-0003-1290-0850</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2F1755-0998.13871$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2F1755-0998.13871$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37772760$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ko, Jui‐Tse</creatorcontrib><creatorcontrib>Li, Ying‐Yang</creatorcontrib><creatorcontrib>Chen, Pa‐Yu</creatorcontrib><creatorcontrib>Liu, Po‐Yu</creatorcontrib><creatorcontrib>Ho, Ming‐Yang</creatorcontrib><title>Use of 16S rRNA gene sequences to identify cyanobacteria that can grow in far‐red light</title><title>Molecular ecology resources</title><addtitle>Mol Ecol Resour</addtitle><description>Although most cyanobacteria use visible light (VL; λ = 400–700 nm) for photosynthesis, some have evolved strategies to use far‐red light (FRL; λ = 700–800 nm). These cyanobacteria are defined as far‐red light‐utilizing cyanobacteria (FRLCyano), including two groups: (1) chlorophyll d‐producing Acaryochloris spp. and (2) polyphyletic cyanobacteria that produce chlorophylls d and f in response to FRL. Numerous ecological studies examine pigments, such as chlorophylls d and f, to investigate the presence of FRLCyano in the environment. This method is not ideal because it can only detect FRLCyano that have made chlorophylls d or f. Here we develop a new method, far‐red cyanobacteria identification (FRCI), to identify FRLCyano based on 16S rRNA gene sequences. From public databases and published articles, 62 16S rRNA gene sequences of FRLCyano were extracted. Comparing with related lineages, we determined that 97% sequence identity is the optimal cut‐off for distinguishing FRLCyano from other cyanobacteria. To test the method experimentally, we collected samples from 17 sites in Taipei, Taiwan, and conducted VL and FRL enrichments. Our results demonstrate that FRCI can detect FRLCyano during FRL enrichments more sensitively than pigment analysis. FRCI can also resolve the composition of FRLCyano at the genus level, which pigment analysis cannot do. In addition, we applied FRCI to published datasets and discovered putative FRLCyano in diverse environments, including soils, hot springs and deserts. Overall, our results indicate that FRCI is a sensitive and high‐resolution method using 16S rRNA gene sequences to identify FRLCyano.</description><subject>16S rRNA genes</subject><subject>bacteria</subject><subject>Chlorophyll</subject><subject>Cyanobacteria</subject><subject>DNA sequencing</subject><subject>Ecological studies</subject><subject>environmental DNA</subject><subject>far‐red light</subject><subject>Gene sequencing</subject><subject>Hot springs</subject><subject>metagenomics</subject><subject>Photosynthesis</subject><subject>Pigments</subject><subject>rRNA 16S</subject><issn>1755-098X</issn><issn>1755-0998</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNqFkM1OAjEURhujEUXX7kwTN26A3unMdGZJCP4kiIlKoqumdG5hyDCD7RDCzkfwGX0SiyALN95Nb9rTL18OIRfA2uCnAyKKWixNkzbwRMABOdnfHO735LVBTp2bMRazVITHpMGFEIGI2Ql5GzmklaEQP1P7NOzSCZZIHb4vsdToaF3RPMOyzs2a6rUqq7HSNdpc0XqqaqpVSSe2WtG8pEbZr49Pixkt8sm0PiNHRhUOz3dnk4xu-i-9u9bg8fa-1x20NBcArSxODaSgNQMTsjA1LBMI3IxBMJMBaiWEf4wiGEOSCqXjIOMsUBhGXEdG8ya53uYubOVbu1rOc6exKFSJ1dLJIBFeR8hi4dGrP-isWtrSt5NByiDkXIShpzpbStvKOYtGLmw-V3YtgcmNdbnxKjeO5Y91_-Nyl7sczzHb87-aPRBtgVVe4Pq_PPnQH26DvwEqc4tD</recordid><startdate>202401</startdate><enddate>202401</enddate><creator>Ko, Jui‐Tse</creator><creator>Li, Ying‐Yang</creator><creator>Chen, Pa‐Yu</creator><creator>Liu, Po‐Yu</creator><creator>Ho, Ming‐Yang</creator><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7SS</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-4961-931X</orcidid><orcidid>https://orcid.org/0009-0005-1990-2834</orcidid><orcidid>https://orcid.org/0000-0003-2859-224X</orcidid><orcidid>https://orcid.org/0000-0003-1290-0850</orcidid></search><sort><creationdate>202401</creationdate><title>Use of 16S rRNA gene sequences to identify cyanobacteria that can grow in far‐red light</title><author>Ko, Jui‐Tse ; Li, Ying‐Yang ; Chen, Pa‐Yu ; Liu, Po‐Yu ; Ho, Ming‐Yang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3711-d69f191cc01f4049f0d7e13fb170fd1eca77cc0551b1897ac62d302ae453c5fc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>16S rRNA genes</topic><topic>bacteria</topic><topic>Chlorophyll</topic><topic>Cyanobacteria</topic><topic>DNA sequencing</topic><topic>Ecological studies</topic><topic>environmental DNA</topic><topic>far‐red light</topic><topic>Gene sequencing</topic><topic>Hot springs</topic><topic>metagenomics</topic><topic>Photosynthesis</topic><topic>Pigments</topic><topic>rRNA 16S</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ko, Jui‐Tse</creatorcontrib><creatorcontrib>Li, Ying‐Yang</creatorcontrib><creatorcontrib>Chen, Pa‐Yu</creatorcontrib><creatorcontrib>Liu, Po‐Yu</creatorcontrib><creatorcontrib>Ho, Ming‐Yang</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Molecular ecology resources</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ko, Jui‐Tse</au><au>Li, Ying‐Yang</au><au>Chen, Pa‐Yu</au><au>Liu, Po‐Yu</au><au>Ho, Ming‐Yang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Use of 16S rRNA gene sequences to identify cyanobacteria that can grow in far‐red light</atitle><jtitle>Molecular ecology resources</jtitle><addtitle>Mol Ecol Resour</addtitle><date>2024-01</date><risdate>2024</risdate><volume>24</volume><issue>1</issue><spage>e13871</spage><epage>n/a</epage><pages>e13871-n/a</pages><issn>1755-098X</issn><eissn>1755-0998</eissn><abstract>Although most cyanobacteria use visible light (VL; λ = 400–700 nm) for photosynthesis, some have evolved strategies to use far‐red light (FRL; λ = 700–800 nm). These cyanobacteria are defined as far‐red light‐utilizing cyanobacteria (FRLCyano), including two groups: (1) chlorophyll d‐producing Acaryochloris spp. and (2) polyphyletic cyanobacteria that produce chlorophylls d and f in response to FRL. Numerous ecological studies examine pigments, such as chlorophylls d and f, to investigate the presence of FRLCyano in the environment. This method is not ideal because it can only detect FRLCyano that have made chlorophylls d or f. Here we develop a new method, far‐red cyanobacteria identification (FRCI), to identify FRLCyano based on 16S rRNA gene sequences. From public databases and published articles, 62 16S rRNA gene sequences of FRLCyano were extracted. Comparing with related lineages, we determined that 97% sequence identity is the optimal cut‐off for distinguishing FRLCyano from other cyanobacteria. To test the method experimentally, we collected samples from 17 sites in Taipei, Taiwan, and conducted VL and FRL enrichments. Our results demonstrate that FRCI can detect FRLCyano during FRL enrichments more sensitively than pigment analysis. FRCI can also resolve the composition of FRLCyano at the genus level, which pigment analysis cannot do. In addition, we applied FRCI to published datasets and discovered putative FRLCyano in diverse environments, including soils, hot springs and deserts. Overall, our results indicate that FRCI is a sensitive and high‐resolution method using 16S rRNA gene sequences to identify FRLCyano.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>37772760</pmid><doi>10.1111/1755-0998.13871</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-4961-931X</orcidid><orcidid>https://orcid.org/0009-0005-1990-2834</orcidid><orcidid>https://orcid.org/0000-0003-2859-224X</orcidid><orcidid>https://orcid.org/0000-0003-1290-0850</orcidid></addata></record> |
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subjects | 16S rRNA genes bacteria Chlorophyll Cyanobacteria DNA sequencing Ecological studies environmental DNA far‐red light Gene sequencing Hot springs metagenomics Photosynthesis Pigments rRNA 16S |
title | Use of 16S rRNA gene sequences to identify cyanobacteria that can grow in far‐red light |
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