Challenges of Comparing Marine Microbiome Community Composition Data Provided by Different Commercial Laboratories and Classification Databases
In the high-throughput sequencing (HTS) era, a metabarcoding technique based on the bacterial V3–V4 hypervariable region of 16S rRNA analysis requires sophisticated bioinformatics pipelines and validated methods that allow researchers to compare their data with confidence. Many commercial laboratori...
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MDPI AG
2022-11-01
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| author | Monika Mioduchowska Anna Iglikowska Jan P. Jastrzębski Anna-Karina Kaczorowska Ewa Kotlarska Artur Trzebny Agata Weydmann-Zwolicka |
| author_facet | Monika Mioduchowska Anna Iglikowska Jan P. Jastrzębski Anna-Karina Kaczorowska Ewa Kotlarska Artur Trzebny Agata Weydmann-Zwolicka |
| author_sort | Monika Mioduchowska |
| collection | DOAJ |
| description | In the high-throughput sequencing (HTS) era, a metabarcoding technique based on the bacterial V3–V4 hypervariable region of 16S rRNA analysis requires sophisticated bioinformatics pipelines and validated methods that allow researchers to compare their data with confidence. Many commercial laboratories conduct extensive HTS analyses; however, there is no available information on whether the results generated by these vendors are consistent. In our study, we compared the sequencing data obtained for the same marine microbiome community sample generated by three commercial laboratories. Additionally, as a sequencing control to determine differences between commercial laboratories and two 16S rRNA databases, we also performed a “mock community” analysis of a defined number of microbial species. We also assessed the impact of the choice of two commonly used 16S rRNA databases, i.e., Greengenes and SILVA, on downstream data analysis, including taxonomic classification assignment. We demonstrated that the final results depend on the choice of the laboratory conducting the HTS and the reference database of ribosomal sequences. Our findings showed that the number of produced ASVs (amplicon sequence variants) ranged from 137 to 564. Different putative bacterial endosymbionts could be identified, and these differences correspond to the applied 16S rRNA database. The results presented might be of particular interest to researchers who plan to perform microbiome community analysis using the 16S rRNA marker gene, including the identification of putative bacterial endosymbionts, and serve as a guide for choosing the optimum pipeline to obtain the most accurate and reproducible data. |
| first_indexed | 2024-03-09T17:27:37Z |
| format | Article |
| id | doaj.art-21350bfa65bf43fbb9c201d214298ba2 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-09T17:27:37Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-21350bfa65bf43fbb9c201d214298ba22023-11-24T12:32:19ZengMDPI AGWater2073-44412022-11-011423385510.3390/w14233855Challenges of Comparing Marine Microbiome Community Composition Data Provided by Different Commercial Laboratories and Classification DatabasesMonika Mioduchowska0Anna Iglikowska1Jan P. Jastrzębski2Anna-Karina Kaczorowska3Ewa Kotlarska4Artur Trzebny5Agata Weydmann-Zwolicka6Department of Evolutionary Genetics and Biosystematics, Faculty of Biology, University of Gdansk, 80-308 Gdansk, PolandDepartment of Evolutionary Genetics and Biosystematics, Faculty of Biology, University of Gdansk, 80-308 Gdansk, PolandBioinformatics Core Facility, University of Warmia and Mazury in Olsztyn, Kortowo, 10-719 Olsztyn, PolandCollection of Plasmids and Microorganisms (KPD), Faculty of Biology, University of Gdansk, 80-308 Gdansk, PolandMolecular Biology Laboratory, Genetics and Marine Biotechnology Department, Institute of Oceanology of the Polish Academy of Sciences, 81-712 Sopot, PolandMolecular Biology Techniques Laboratory, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, PolandDepartment of Marine Plankton Research, Institute of Oceanography, University of Gdansk, 81-378 Gdynia, PolandIn the high-throughput sequencing (HTS) era, a metabarcoding technique based on the bacterial V3–V4 hypervariable region of 16S rRNA analysis requires sophisticated bioinformatics pipelines and validated methods that allow researchers to compare their data with confidence. Many commercial laboratories conduct extensive HTS analyses; however, there is no available information on whether the results generated by these vendors are consistent. In our study, we compared the sequencing data obtained for the same marine microbiome community sample generated by three commercial laboratories. Additionally, as a sequencing control to determine differences between commercial laboratories and two 16S rRNA databases, we also performed a “mock community” analysis of a defined number of microbial species. We also assessed the impact of the choice of two commonly used 16S rRNA databases, i.e., Greengenes and SILVA, on downstream data analysis, including taxonomic classification assignment. We demonstrated that the final results depend on the choice of the laboratory conducting the HTS and the reference database of ribosomal sequences. Our findings showed that the number of produced ASVs (amplicon sequence variants) ranged from 137 to 564. Different putative bacterial endosymbionts could be identified, and these differences correspond to the applied 16S rRNA database. The results presented might be of particular interest to researchers who plan to perform microbiome community analysis using the 16S rRNA marker gene, including the identification of putative bacterial endosymbionts, and serve as a guide for choosing the optimum pipeline to obtain the most accurate and reproducible data.https://www.mdpi.com/2073-4441/14/23/3855amplicon sequencingASV assignmentHTSmarine microorganismsmetagenetics“mock community” |
| spellingShingle | Monika Mioduchowska Anna Iglikowska Jan P. Jastrzębski Anna-Karina Kaczorowska Ewa Kotlarska Artur Trzebny Agata Weydmann-Zwolicka Challenges of Comparing Marine Microbiome Community Composition Data Provided by Different Commercial Laboratories and Classification Databases Water amplicon sequencing ASV assignment HTS marine microorganisms metagenetics “mock community” |
| title | Challenges of Comparing Marine Microbiome Community Composition Data Provided by Different Commercial Laboratories and Classification Databases |
| title_full | Challenges of Comparing Marine Microbiome Community Composition Data Provided by Different Commercial Laboratories and Classification Databases |
| title_fullStr | Challenges of Comparing Marine Microbiome Community Composition Data Provided by Different Commercial Laboratories and Classification Databases |
| title_full_unstemmed | Challenges of Comparing Marine Microbiome Community Composition Data Provided by Different Commercial Laboratories and Classification Databases |
| title_short | Challenges of Comparing Marine Microbiome Community Composition Data Provided by Different Commercial Laboratories and Classification Databases |
| title_sort | challenges of comparing marine microbiome community composition data provided by different commercial laboratories and classification databases |
| topic | amplicon sequencing ASV assignment HTS marine microorganisms metagenetics “mock community” |
| url | https://www.mdpi.com/2073-4441/14/23/3855 |
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