Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites
Abstract Accurate species identification and abundance estimation are critical for the interpretation of whole metagenome sequencing (WMS) data. Yet, existing metagenomic profilers suffer from false-positive identifications, which can account for more than 90% of total identified species. Here, by l...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-09-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-41099-8 |
| _version_ | 1797558677753823232 |
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| author | Zheng Sun Jiang Liu Meng Zhang Tong Wang Shi Huang Scott T. Weiss Yang-Yu Liu |
| author_facet | Zheng Sun Jiang Liu Meng Zhang Tong Wang Shi Huang Scott T. Weiss Yang-Yu Liu |
| author_sort | Zheng Sun |
| collection | DOAJ |
| description | Abstract Accurate species identification and abundance estimation are critical for the interpretation of whole metagenome sequencing (WMS) data. Yet, existing metagenomic profilers suffer from false-positive identifications, which can account for more than 90% of total identified species. Here, by leveraging species-specific Type IIB restriction endonuclease digestion sites as reference instead of universal markers or whole microbial genomes, we present a metagenomic profiler, MAP2B (MetAgenomic Profiler based on type IIB restriction sites), to resolve those issues. We first illustrate the pitfalls of using relative abundance as the only feature in determining false positives. We then propose a feature set to distinguish false positives from true positives, and using simulated metagenomes from CAMI2, we establish a false-positive recognition model. By benchmarking the performance in metagenomic profiling using a simulation dataset with varying sequencing depth and species richness, we illustrate the superior performance of MAP2B over existing metagenomic profilers in species identification. We further test the performance of MAP2B using real WMS data from an ATCC mock community, confirming its superior precision against sequencing depth. Finally, by leveraging WMS data from an IBD cohort, we demonstrate the taxonomic features generated by MAP2B can better discriminate IBD and predict metabolomic profiles. |
| first_indexed | 2024-03-10T17:34:33Z |
| format | Article |
| id | doaj.art-b736b1a77338408e8d70c8868c613de4 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-10T17:34:33Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-b736b1a77338408e8d70c8868c613de42023-11-20T09:54:50ZengNature PortfolioNature Communications2041-17232023-09-0114111210.1038/s41467-023-41099-8Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sitesZheng Sun0Jiang Liu1Meng Zhang2Tong Wang3Shi Huang4Scott T. Weiss5Yang-Yu Liu6Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical SchoolQingdao OE Biotechnology Company LimitedKey Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, Inner Mongolia Agricultural UniversityChanning Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical SchoolFaculty of Dentistry, The University of Hong KongChanning Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical SchoolChanning Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical SchoolAbstract Accurate species identification and abundance estimation are critical for the interpretation of whole metagenome sequencing (WMS) data. Yet, existing metagenomic profilers suffer from false-positive identifications, which can account for more than 90% of total identified species. Here, by leveraging species-specific Type IIB restriction endonuclease digestion sites as reference instead of universal markers or whole microbial genomes, we present a metagenomic profiler, MAP2B (MetAgenomic Profiler based on type IIB restriction sites), to resolve those issues. We first illustrate the pitfalls of using relative abundance as the only feature in determining false positives. We then propose a feature set to distinguish false positives from true positives, and using simulated metagenomes from CAMI2, we establish a false-positive recognition model. By benchmarking the performance in metagenomic profiling using a simulation dataset with varying sequencing depth and species richness, we illustrate the superior performance of MAP2B over existing metagenomic profilers in species identification. We further test the performance of MAP2B using real WMS data from an ATCC mock community, confirming its superior precision against sequencing depth. Finally, by leveraging WMS data from an IBD cohort, we demonstrate the taxonomic features generated by MAP2B can better discriminate IBD and predict metabolomic profiles.https://doi.org/10.1038/s41467-023-41099-8 |
| spellingShingle | Zheng Sun Jiang Liu Meng Zhang Tong Wang Shi Huang Scott T. Weiss Yang-Yu Liu Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites Nature Communications |
| title | Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites |
| title_full | Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites |
| title_fullStr | Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites |
| title_full_unstemmed | Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites |
| title_short | Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites |
| title_sort | removal of false positives in metagenomics based taxonomy profiling via targeting type iib restriction sites |
| url | https://doi.org/10.1038/s41467-023-41099-8 |
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