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A universal method for species identification of mammals utilizing next generation sequencing for the analysis of DNA mixtures.

ABSTRACT: Species identification can be interesting in a wide range of areas, for example, in forensic applications, food monitoring and in archeology. The vast majority of existing DNA typing methods developed for species determination, mainly focuses on a single species source. There are, however, many instances where all species from mixed sources need to be determined, even when the species in minority constitutes less than 1 % of the sample. The introduction of next generation sequencing opens new possibilities for such challenging samples. In this study we present a universal deep sequencing method using 454 GS Junior sequencing of a target on the mitochondrial gene 16S rRNA. The method was designed through phylogenetic analyses of DNA reference sequences from more than 300 mammal species. Experiments were performed on artificial species-species mixture samples in order to verify the method's robustness and its ability to detect all species within a mixture. The method was also tested on samples from authentic forensic casework. The results showed to be promising, discriminating over 99.9 % of mammal species and the ability to detect multiple donors within a mixture and also to detect minor components as low as 1 % of a mixed sample.

SUBMITTER: Tillmar AO

PROVIDER: S-EPMC3865308 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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A universal method for species identification of mammals utilizing next generation sequencing for the analysis of DNA mixtures.

Tillmar Andreas O AO Dell'Amico Barbara B Welander Jenny J Holmlund Gunilla G

PloS one 20131216 12

Species identification can be interesting in a wide range of areas, for example, in forensic applications, food monitoring and in archeology. The vast majority of existing DNA typing methods developed for species determination, mainly focuses on a single species source. There are, however, many instances where all species from mixed sources need to be determined, even when the species in minority constitutes less than 1 % of the sample. The introduction of next generation sequencing opens new po ...[more]

PMID: 24358309

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Project description:INTRODUCTION:Invertebrate communities are central to many environmental monitoring programs. In freshwater ecosystems, aquatic macroinvertebrates are collected, identified and then used to infer ecosystem condition. Yet the key step of species identification is often not taken, as it requires a high level of taxonomic expertise, which is lacking in most organizations, or species cannot be identified as they are morphologically cryptic or represent little known groups. Identifying species using DNA sequences can overcome many of these issues; with the power of next generation sequencing (NGS), using DNA sequences for routine monitoring becomes feasible. RESULTS:In this study, we test if NGS can be used to identify species from field-collected samples in an important bioindicator group, the Chironomidae. We show that Cytochrome oxidase I (COI) and Cytochrome B (CytB) sequences provide accurate DNA barcodes for chironomid species. We then develop a NGS analysis pipeline to identifying species using megablast searches of high quality sequences generated using 454 pyrosequencing against comprehensive reference libraries of Sanger-sequenced voucher specimens. We find that 454 generated COI sequences successfully identified up to 96% of species in samples, but this increased up to 99% when combined with CytB sequences. Accurate identification depends on having at least five sequences for a species; below this level species not expected in samples were detected. Incorrect incorporation of some multiplex identifiers (MID's) used to tag samples was a likely cause, and most errors could be detected when using MID tags on forward and reverse primers. We also found a strong quantitative relationship between the number of 454 sequences and individuals showing that it may be possible to estimate the abundance of species from 454 pyrosequencing data. CONCLUSIONS:Next generation sequencing using two genes was successful for identifying chironomid species. However, when detecting species from 454 pyrosequencing data sets it was critical to include known individuals for quality control and to establish thresholds for detecting species. The NGS approach developed here can lead to routine species-level diagnostic monitoring of aquatic ecosystems.

Project description:BackgroundThe cerebrospinal fluid (CSF) culture is a widely used method for the diagnosis of meningitis, but its detection sensitivity is low. Several new methods have been developed for pathogen detection, including metagenomic next-generation sequencing (mNGS) and pathogen-targeted NGS (ptNGS). In this study, we aimed to evaluate the performance of ptNGS in pathogen detection in CSF.MethodsCSF specimens were acquired from 38 patients with meningitis who were diagnosed at Xuanwu Hospital, Capital Medical University between October 2020 and February 2021. DNA was extracted from the CSF samples, and pathogens were identified using both ptNGS and mNGS. SPSS 22.0 software was used to compare the pathogen detection performance of ptNGS and mNGS in CSF.ResultsAmong the 38 patients with meningitis, 14 had a non-infectious disease (NID) and 24 had an infectious disease (ID). Of the 38 samples, both ptNGS and mNGS detected 9 (23.7%) positive samples, and 12 (31.6%) negative samples. Thirteen (34.2%) samples were detected to be positive by ptNGS only, and 4 (10.5%) were detected to be positive by mNGS only. The positivity rate detected by ptNGS for the ID group was higher than that detected by mNGS (P=0.080), and the positivity rates detected by ptNGS and mNGS for the NID group were comparable. The positive predictive value (PPV) and negative predictive value (NPV) of diagnosing an ID by ptNGS were 77.3% and 56.3%, respectively. While, the PPV and NPV of diagnosing an ID by mNGS were 76.9% and 44.0%, respectively. ptNGS increased the sensitivity rate by approximately 70%. The sensitivity rate of ptNGS was higher than that of mNGS (70.8% vs. 41.7%), while the specificity rate of mNGS was higher than that of ptNGS (78.6% vs. 64.3%). Additionally, ptNGS required a shorter time for pathogen diagnosis (15 vs. 24 hrs) and had lower costs than mNGS.ConclusionsptNGS has a number of advantages over mNGS, including its sensitivity, timeliness, and economy, all factors that are important considerations in clinical use.

Dataset Information

A universal method for species identification of mammals utilizing next generation sequencing for the analysis of DNA mixtures.

Publications

A universal method for species identification of mammals utilizing next generation sequencing for the analysis of DNA mixtures.

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