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Comparative study of multiple approaches for identifying cultivable microalgae population diversity from freshwater samples
The vast diversity of microalgae imposes the challenge of identifying them through the most common and economical identification method, morphological identification, or through using the more recent molecular-level identification tools. Here we report an approach combining enrichment and metagenomi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10328328/ https://www.ncbi.nlm.nih.gov/pubmed/37418475 http://dx.doi.org/10.1371/journal.pone.0285913 |
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author | Badr, Amal A. Fouad, Walid M. |
author_facet | Badr, Amal A. Fouad, Walid M. |
author_sort | Badr, Amal A. |
collection | PubMed |
description | The vast diversity of microalgae imposes the challenge of identifying them through the most common and economical identification method, morphological identification, or through using the more recent molecular-level identification tools. Here we report an approach combining enrichment and metagenomic molecular techniques to enhance microalgae identification and identify microalgae diversity from environmental water samples. From this perspective, we aimed to identify the most suitable culturing media and molecular approach (using different primer sets and reference databases) for detecting microalgae diversity. Using this approach, we have analyzed three water samples collected from the River Nile on several enrichment media. A total of 37 microalgae were identified morphologically to the genus level. While sequencing the three-primer sets (16S rRNA V1-V3 and V4-V5 and 18S rRNA V4 region) and aligning them to three reference databases (GG, SILVA, and PR(2)), a total of 87 microalgae were identified to the genus level. The highest eukaryotic microalgae diversity was identified using the 18S rRNA V4 region and alignment to the SILVA database (43 genera). The two 16S rRNA regions sequenced added to the eukaryotic microalgae identification, 26 eukaryotic microalgae. Cyanobacteria were identified through the two sequenced 16S rRNA regions. Alignment to the SILVA database served to identify 14 cyanobacteria to the genera level, followed by Greengenes, 11 cyanobacteria genera. Our multiple-media, primer, and reference database approach revealed a high microalgae diversity that would have been overlooked if a single approach had been used over the other. |
format | Online Article Text |
id | pubmed-10328328 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-103283282023-07-08 Comparative study of multiple approaches for identifying cultivable microalgae population diversity from freshwater samples Badr, Amal A. Fouad, Walid M. PLoS One Research Article The vast diversity of microalgae imposes the challenge of identifying them through the most common and economical identification method, morphological identification, or through using the more recent molecular-level identification tools. Here we report an approach combining enrichment and metagenomic molecular techniques to enhance microalgae identification and identify microalgae diversity from environmental water samples. From this perspective, we aimed to identify the most suitable culturing media and molecular approach (using different primer sets and reference databases) for detecting microalgae diversity. Using this approach, we have analyzed three water samples collected from the River Nile on several enrichment media. A total of 37 microalgae were identified morphologically to the genus level. While sequencing the three-primer sets (16S rRNA V1-V3 and V4-V5 and 18S rRNA V4 region) and aligning them to three reference databases (GG, SILVA, and PR(2)), a total of 87 microalgae were identified to the genus level. The highest eukaryotic microalgae diversity was identified using the 18S rRNA V4 region and alignment to the SILVA database (43 genera). The two 16S rRNA regions sequenced added to the eukaryotic microalgae identification, 26 eukaryotic microalgae. Cyanobacteria were identified through the two sequenced 16S rRNA regions. Alignment to the SILVA database served to identify 14 cyanobacteria to the genera level, followed by Greengenes, 11 cyanobacteria genera. Our multiple-media, primer, and reference database approach revealed a high microalgae diversity that would have been overlooked if a single approach had been used over the other. Public Library of Science 2023-07-07 /pmc/articles/PMC10328328/ /pubmed/37418475 http://dx.doi.org/10.1371/journal.pone.0285913 Text en © 2023 Badr, Fouad https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Badr, Amal A. Fouad, Walid M. Comparative study of multiple approaches for identifying cultivable microalgae population diversity from freshwater samples |
title | Comparative study of multiple approaches for identifying cultivable microalgae population diversity from freshwater samples |
title_full | Comparative study of multiple approaches for identifying cultivable microalgae population diversity from freshwater samples |
title_fullStr | Comparative study of multiple approaches for identifying cultivable microalgae population diversity from freshwater samples |
title_full_unstemmed | Comparative study of multiple approaches for identifying cultivable microalgae population diversity from freshwater samples |
title_short | Comparative study of multiple approaches for identifying cultivable microalgae population diversity from freshwater samples |
title_sort | comparative study of multiple approaches for identifying cultivable microalgae population diversity from freshwater samples |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10328328/ https://www.ncbi.nlm.nih.gov/pubmed/37418475 http://dx.doi.org/10.1371/journal.pone.0285913 |
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