Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification
ABSTRACT Accurate metagenomic classification relies on comprehensive, up-to-date, and validated reference databases. While the NCBI BLAST Nucleotide (nt) database, encompassing a vast collection of sequences from all domains of life, represents an invaluable resource, its massive size—currently exce...
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| Format: | Article |
| Language: | English |
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American Society for Microbiology
2025-04-01
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| Series: | mSystems |
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| Online Access: | https://journals.asm.org/doi/10.1128/msystems.01239-24 |
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| author | Jose Manuel Martí Car Reen Kok James B. Thissen Nisha J. Mulakken Aram Avila-Herrera Crystal J. Jaing Jonathan E. Allen Nicholas A. Be |
| author_facet | Jose Manuel Martí Car Reen Kok James B. Thissen Nisha J. Mulakken Aram Avila-Herrera Crystal J. Jaing Jonathan E. Allen Nicholas A. Be |
| author_sort | Jose Manuel Martí |
| collection | DOAJ |
| description | ABSTRACT Accurate metagenomic classification relies on comprehensive, up-to-date, and validated reference databases. While the NCBI BLAST Nucleotide (nt) database, encompassing a vast collection of sequences from all domains of life, represents an invaluable resource, its massive size—currently exceeding 1012 nucleotides—and exponential growth pose significant challenges for researchers seeking to maintain current nt-based indices for metagenomic classification. Recognizing that no current nt-based indices exist for the widely used Centrifuge classifier, and the last public version currently available was released in 2018, we addressed this critical gap by leveraging advanced high-performance computing resources. We present new Centrifuge-compatible nt databases, meticulously constructed using a novel pipeline incorporating different quality control measures, including reference decontamination and filtering. These measures demonstrably reduce spurious classifications, as shown through our reanalysis of published metagenomic data where Plasmodium annotations were dramatically reduced using our decontaminated database, highlighting how database quality can significantly impact research conclusions. Through temporal comparisons, we also reveal how our approach minimizes inconsistencies in taxonomic assignments stemming from asynchronous updates between public sequence and taxonomy databases. These discrepancies are particularly evident in taxa such as Listeria monocytogenes and Naegleria fowleri, where classification accuracy varied significantly across database versions. These new databases, made available as pre-built Centrifuge indexes, respond to the need for an open, robust, nt-based pipeline for taxonomic classification in metagenomics. Applications such as environmental metagenomics, forensics, and clinical metagenomics, which require comprehensive taxonomic coverage, will benefit from this resource. Our work highlights the importance of treating reference databases as dynamic entities, subject to ongoing quality control and validation akin to software development best practices. This approach is crucial for ensuring accuracy and reliability of metagenomic analysis, especially as databases continue to expand in size and complexity.IMPORTANCEAccurately identifying the diverse microbes present in a sample, whether from the human gut, a soil sample, or a crime scene, is crucial for fields ranging from medicine to environmental science. Researchers rely on comprehensive DNA databases to match sequenced DNA fragments to known microbial species. However, the widely used NCBI nt database, while vast, poses significant challenges. Its massive size makes it difficult for many researchers to use effectively with taxonomic classifiers, and inconsistencies and contamination within the database can impact the accuracy of microbial identification. This work addresses these challenges by providing cleaned, updated, and validated nt-based databases specifically optimized for the widely used Centrifuge classification tool. This new resource demonstrably reduces errors and improves the reliability of microbial identification across diverse taxonomic groups. Moreover, by providing readily usable indexes, we overcome the size barrier, enabling researchers to leverage the full potential of the nt database for metagenomic analysis. Our findings underscore the need to treat reference databases as dynamic entities, emphasizing continuous quality control and versioning as essential practices for robust and reproducible metagenomics research. |
| format | Article |
| id | doaj-art-2d48da487a27459bb1fa39a34a2e4ee5 |
| institution | OA Journals |
| issn | 2379-5077 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | American Society for Microbiology |
| record_format | Article |
| series | mSystems |
| spelling | doaj-art-2d48da487a27459bb1fa39a34a2e4ee52025-08-20T02:12:20ZengAmerican Society for MicrobiologymSystems2379-50772025-04-0110410.1128/msystems.01239-24Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classificationJose Manuel Martí0Car Reen Kok1James B. Thissen2Nisha J. Mulakken3Aram Avila-Herrera4Crystal J. Jaing5Jonathan E. Allen6Nicholas A. Be7Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, California, USABiosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, California, USABiosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, California, USAGlobal Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, California, USAGlobal Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, California, USABiosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, California, USAGlobal Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, California, USABiosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, California, USAABSTRACT Accurate metagenomic classification relies on comprehensive, up-to-date, and validated reference databases. While the NCBI BLAST Nucleotide (nt) database, encompassing a vast collection of sequences from all domains of life, represents an invaluable resource, its massive size—currently exceeding 1012 nucleotides—and exponential growth pose significant challenges for researchers seeking to maintain current nt-based indices for metagenomic classification. Recognizing that no current nt-based indices exist for the widely used Centrifuge classifier, and the last public version currently available was released in 2018, we addressed this critical gap by leveraging advanced high-performance computing resources. We present new Centrifuge-compatible nt databases, meticulously constructed using a novel pipeline incorporating different quality control measures, including reference decontamination and filtering. These measures demonstrably reduce spurious classifications, as shown through our reanalysis of published metagenomic data where Plasmodium annotations were dramatically reduced using our decontaminated database, highlighting how database quality can significantly impact research conclusions. Through temporal comparisons, we also reveal how our approach minimizes inconsistencies in taxonomic assignments stemming from asynchronous updates between public sequence and taxonomy databases. These discrepancies are particularly evident in taxa such as Listeria monocytogenes and Naegleria fowleri, where classification accuracy varied significantly across database versions. These new databases, made available as pre-built Centrifuge indexes, respond to the need for an open, robust, nt-based pipeline for taxonomic classification in metagenomics. Applications such as environmental metagenomics, forensics, and clinical metagenomics, which require comprehensive taxonomic coverage, will benefit from this resource. Our work highlights the importance of treating reference databases as dynamic entities, subject to ongoing quality control and validation akin to software development best practices. This approach is crucial for ensuring accuracy and reliability of metagenomic analysis, especially as databases continue to expand in size and complexity.IMPORTANCEAccurately identifying the diverse microbes present in a sample, whether from the human gut, a soil sample, or a crime scene, is crucial for fields ranging from medicine to environmental science. Researchers rely on comprehensive DNA databases to match sequenced DNA fragments to known microbial species. However, the widely used NCBI nt database, while vast, poses significant challenges. Its massive size makes it difficult for many researchers to use effectively with taxonomic classifiers, and inconsistencies and contamination within the database can impact the accuracy of microbial identification. This work addresses these challenges by providing cleaned, updated, and validated nt-based databases specifically optimized for the widely used Centrifuge classification tool. This new resource demonstrably reduces errors and improves the reliability of microbial identification across diverse taxonomic groups. Moreover, by providing readily usable indexes, we overcome the size barrier, enabling researchers to leverage the full potential of the nt database for metagenomic analysis. Our findings underscore the need to treat reference databases as dynamic entities, emphasizing continuous quality control and versioning as essential practices for robust and reproducible metagenomics research.https://journals.asm.org/doi/10.1128/msystems.01239-24metagenomicstaxonomic classificationreference databaseNCBI BLAST ntCentrifugeRecentrifuge |
| spellingShingle | Jose Manuel Martí Car Reen Kok James B. Thissen Nisha J. Mulakken Aram Avila-Herrera Crystal J. Jaing Jonathan E. Allen Nicholas A. Be Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification mSystems metagenomics taxonomic classification reference database NCBI BLAST nt Centrifuge Recentrifuge |
| title | Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification |
| title_full | Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification |
| title_fullStr | Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification |
| title_full_unstemmed | Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification |
| title_short | Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification |
| title_sort | addressing the dynamic nature of reference data a new nucleotide database for robust metagenomic classification |
| topic | metagenomics taxonomic classification reference database NCBI BLAST nt Centrifuge Recentrifuge |
| url | https://journals.asm.org/doi/10.1128/msystems.01239-24 |
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