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Accurate and Strict Identification of Probiotic Species Based on Coverage of Whole-Metagenome Shotgun Sequencing Data
- Source :
- Frontiers in Microbiology, Frontiers in Microbiology, Vol 10 (2019)
- Publication Year :
- 2018
-
Abstract
- Identifying the microbes present in probiotic products is an important issue in product quality control and public health. The most common methods used to identify genera containing species that produce lactic acid are matrix-assisted laser desorption/ionization–time of flight mass spectrometry (MALDI-TOF MS) and 16S rRNA sequence analysis. However, the high cost of operation, difficulty in distinguishing between similar species, and limitations of the current sequencing technologies have made it difficult to obtain accurate results using these tools. To overcome these problems, a whole-genome shotgun sequencing approach has been developed along with various metagenomic classification tools. Widely used tools include the marker gene and k-mer methods, but their inevitable false-positives (FPs) hampered an accurate analysis. We therefore, designed a coverage-based pipeline to reduce the FP problem and to achieve a more reliable identification of species. The coverage-based pipeline described here not only shows higher accuracy for the detection of species and proportion analysis, based on mapping depth, but can be applied regardless of the sequencing platform. We believe that the coverage-based pipeline described in this study can provide appropriate support for probiotic quality control, addressing current labeling issues.
- Subjects :
- Microbiology (medical)
0303 health sciences
metagenomics
030306 microbiology
Shotgun sequencing
Computer science
lcsh:QR1-502
Computational biology
Pipeline (software)
Microbiology
lcsh:Microbiology
lactic acid bacteria
03 medical and health sciences
Identification (information)
probiotics
16s rrna sequence analysis
Metagenomics
NGS
Methods
mapping coverage
identification
whole genome shotgun sequencing
030304 developmental biology
Subjects
Details
- ISSN :
- 1664302X
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- Frontiers in microbiology
- Accession number :
- edsair.doi.dedup.....d20dd928d58e37d0336120908c9dade2