Dataset Information

Benchmarking and Validation of a Bioinformatics Workflow for Meat Species Identification Using 16S rDNA Metabarcoding.

ABSTRACT: DNA-metabarcoding is becoming more widely used for routine authentication of meat-based food and feed products. Several methods validating species identification methods through amplicon sequencing have already been published. These use a variety of barcodes and analysis workflows, however, no methodical comparison of available algorithms and parameter optimization are published hitherto for meat-based products' authenticity. Additionally, many published methods use very small subsets of the available reference sequences, thereby limiting the potential of the analysis and leading to over-optimistic performance estimates. We here predict and compare the ability of published barcodes to distinguish taxa in the BLAST NT database. We then use a dataset of 79 reference samples, spanning 32 taxa, to benchmark and optimize a metabarcoding analysis workflow for 16S rDNA Illumina sequencing. Furthermore, we provide recommendations as to the parameter choices, sequencing depth, and thresholds that should be used to analyze meat metabarcoding sequencing experiments. The analysis workflow is publicly available, and includes ready-to-use tools for validation and benchmarking.

SUBMITTER: Denay G

PROVIDER: S-EPMC10000984 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

Benchmarking and Validation of a Bioinformatics Workflow for Meat Species Identification Using 16S rDNA Metabarcoding.

Denay Grégoire G Preckel Laura L Petersen Henning H Pietsch Klaus K Wöhlke Anne A Brünen-Nieweler Claudia C

Foods (Basel, Switzerland) 20230224 5

DNA-metabarcoding is becoming more widely used for routine authentication of meat-based food and feed products. Several methods validating species identification methods through amplicon sequencing have already been published. These use a variety of barcodes and analysis workflows, however, no methodical comparison of available algorithms and parameter optimization are published hitherto for meat-based products' authenticity. Additionally, many published methods use very small subsets of the ava ...[more]

PMID: 36900485

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Project description:BackgroundThe 5' region of cytochrome oxidase I (COI) is the standard marker for DNA barcoding. However, COI has proved to be of limited use in identifying some species, and for some taxa, the coding sequence is not efficiently amplified by PCR. These deficiencies lead to uncertainty as to whether COI is the most suitable barcoding fragment for species identification of ticks.MethodsIn this study, we directly compared the relative effectiveness of COI, 16S ribosomal DNA (rDNA), nuclear ribosomal internal transcribed spacer 2 (ITS2) and 12S rDNA for tick species identification. A total of 307 sequences from 84 specimens representing eight tick species were acquired by PCR. Besides the 1,834 published sequences of 189 tick species from GenBank and the Barcode of Life Database, 430 unpublished sequences representing 59 tick species were also successfully screened by Bayesian analyses. Thereafter, the performance of the four DNA markers to identify tick species was evaluated by identification success rates given by these markers using nearest neighbour (NN), BLASTn, liberal tree-based or liberal tree-based (+threshold) methods.ResultsGenetic divergence analyses showed that the intra-specific divergence of each marker was much lower than the inter-specific divergence. Our results indicated that the rates of correct sequence identification for all four markers (COI, 16S rDNA, ITS2, 12S rDNA) were very high (> 96%) when using the NN methodology. We also found that COI was not significantly better than the other markers in terms of its rate of correct sequence identification. Overall, BLASTn and NN methods produced higher rates of correct species identification than that produced by the liberal tree-based methods (+threshold or otherwise).ConclusionsAs the standard DNA barcode, COI should be the first choice for tick species identification, while 16S rDNA, ITS2, and 12S rDNA could be used when COI does not produce reliable results. Besides, NN and BLASTn are efficient methods for species identification of ticks.

Project description:Meat and seafood spoilage ecosystems harbor extensive bacterial genomic diversity that is mainly found within a small number of species but within a large number of strains with different spoilage metabolic potential. To decipher the intraspecies diversity of such microbiota, traditional metagenetic analysis using the 16S rRNA gene is inadequate. We therefore assessed the potential benefit of an alternative genetic marker, gyrB, which encodes the subunit B of DNA gyrase, a type II DNA topoisomerase. A comparison between 16S rDNA-based (V3-V4) amplicon sequencing and gyrB-based amplicon sequencing was carried out in five types of meat and seafood products, with five mock communities serving as quality controls. Our results revealed that bacterial richness in these mock communities and food samples was estimated with higher accuracy using gyrB than using16S rDNA. However, for Firmicutes species, 35% of putative gyrB reads were actually identified as sequences of a gyrB paralog, parE, which encodes subunit B of topoisomerase IV; we therefore constructed a reference database of published sequences of both gyrB and pare for use in all subsequent analyses. Despite this co-amplification, the deviation between relative sequencing quantification and absolute qPCR quantification was comparable to that observed for 16S rDNA for all the tested species. This confirms that gyrB can be used successfully alongside 16S rDNA to determine the species composition (richness and evenness) of food microbiota. The major benefit of gyrB sequencing is its potential for improving taxonomic assignment and for further investigating OTU richness at the subspecies level, thus allowing more accurate discrimination of samples. Indeed, 80% of the reads of the 16S rDNA dataset were represented by thirteen 16S rDNA-based OTUs that could not be assigned at the species-level. Instead, these same clades corresponded to 44 gyrB-based OTUs, which differentiated various lineages down to the subspecies level. The increased ability of gyrB-based analyses to track and trace phylogenetically different groups of strains will generate improved resolution and more reliable results for studies of the strains implicated in food processes.

Dataset Information

Benchmarking and Validation of a Bioinformatics Workflow for Meat Species Identification Using 16S rDNA Metabarcoding.

Publications

Benchmarking and Validation of a Bioinformatics Workflow for Meat Species Identification Using 16S rDNA Metabarcoding.

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