Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy Databases
Taxonomic classification using metabarcoding is a commonly used method in microbiological studies of environmental samples and during monitoring of biotechnological processes. However, it is difficult to compare results from different laboratories, due to the variety of bioinformatics tools that hav...
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MDPI AG
2024-03-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/25/6/3508 |
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| author | Wiktor Babis Jan P. Jastrzebski Slawomir Ciesielski |
| author_facet | Wiktor Babis Jan P. Jastrzebski Slawomir Ciesielski |
| author_sort | Wiktor Babis |
| collection | DOAJ |
| description | Taxonomic classification using metabarcoding is a commonly used method in microbiological studies of environmental samples and during monitoring of biotechnological processes. However, it is difficult to compare results from different laboratories, due to the variety of bioinformatics tools that have been developed and used for data analysis. This problem is compounded by different choices regarding which variable region of the <i>16S rRNA</i> gene and which database is used for taxonomic identification. Therefore, this study employed the DADA2 algorithm to optimize the preprocessing of raw data obtained from the sequencing of activated sludge samples, using simultaneous analysis of three frequently used regions of <i>16S rRNA</i> (V1–V3, V3–V4, V4–V5). Additionally, the study evaluated which variable region and which of the frequently used microbial databases for taxonomic classification (Greengenes2, Silva, RefSeq) more accurately classify OTUs into taxa. Adjusting the values of selected parameters of the DADA2 algorithm, we obtained the highest possible numbers of OTUs for each region. Regarding biodiversity within regions, the V3–V4 region had the highest Simpson and Shannon indexes, and the Chao1 index was similar to that of the V1–V3 region. Beta-biodiversity analysis revealed statistically significant differences between regions. When comparing databases for each of the regions studied, the highest numbers of taxonomic groups were obtained using the SILVA database. These results suggest that standardization of metabarcoding of short amplicons may be possible. |
| first_indexed | 2024-04-24T18:11:12Z |
| format | Article |
| id | doaj.art-4b27f66c1cf74c4fa2cdd0ba5a8ab7b7 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-04-24T18:11:12Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-4b27f66c1cf74c4fa2cdd0ba5a8ab7b72024-03-27T13:46:19ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672024-03-01256350810.3390/ijms25063508Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy DatabasesWiktor Babis0Jan P. Jastrzebski1Slawomir Ciesielski2Department of Plant Physiology, Genetics and Biotechnology, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, PolandDepartment of Plant Physiology, Genetics and Biotechnology, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, PolandDepartment of Environmental Biotechnology, University of Warmia and Mazury in Olsztyn, 11-709 Olsztyn, PolandTaxonomic classification using metabarcoding is a commonly used method in microbiological studies of environmental samples and during monitoring of biotechnological processes. However, it is difficult to compare results from different laboratories, due to the variety of bioinformatics tools that have been developed and used for data analysis. This problem is compounded by different choices regarding which variable region of the <i>16S rRNA</i> gene and which database is used for taxonomic identification. Therefore, this study employed the DADA2 algorithm to optimize the preprocessing of raw data obtained from the sequencing of activated sludge samples, using simultaneous analysis of three frequently used regions of <i>16S rRNA</i> (V1–V3, V3–V4, V4–V5). Additionally, the study evaluated which variable region and which of the frequently used microbial databases for taxonomic classification (Greengenes2, Silva, RefSeq) more accurately classify OTUs into taxa. Adjusting the values of selected parameters of the DADA2 algorithm, we obtained the highest possible numbers of OTUs for each region. Regarding biodiversity within regions, the V3–V4 region had the highest Simpson and Shannon indexes, and the Chao1 index was similar to that of the V1–V3 region. Beta-biodiversity analysis revealed statistically significant differences between regions. When comparing databases for each of the regions studied, the highest numbers of taxonomic groups were obtained using the SILVA database. These results suggest that standardization of metabarcoding of short amplicons may be possible.https://www.mdpi.com/1422-0067/25/6/3508<i>16S rRNA</i> geneactivated sludgebiodiversityDADA2metabarcodingOTUs |
| spellingShingle | Wiktor Babis Jan P. Jastrzebski Slawomir Ciesielski Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy Databases International Journal of Molecular Sciences <i>16S rRNA</i> gene activated sludge biodiversity DADA2 metabarcoding OTUs |
| title | Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy Databases |
| title_full | Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy Databases |
| title_fullStr | Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy Databases |
| title_full_unstemmed | Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy Databases |
| title_short | Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy Databases |
| title_sort | fine tuning of dada2 parameters for multiregional metabarcoding analysis of 16s rrna genes from activated sludge and comparison of taxonomy classification power and taxonomy databases |
| topic | <i>16S rRNA</i> gene activated sludge biodiversity DADA2 metabarcoding OTUs |
| url | https://www.mdpi.com/1422-0067/25/6/3508 |
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