Dataset Information

Coverage evaluation of universal bacterial primers using the metagenomic datasets.

ABSTRACT: BACKGROUND: The coverage of universal primers for the bacterial 16S rRNA gene plays a crucial role in the correct understanding of microbial community structure. However, existing studies on primer coverage are limited by the lack of appropriate databases and are restricted to the domain level. Additionally, most studies do not account for the positional effect of single primer-template mismatches. In this study, we used 7 metagenomic datasets as well as the Ribosomal Database Project (RDP) to assess the coverage of 8 widely used bacterial primers. RESULTS: The coverage rates for bacterial primers were found to be overestimated by previous studies that only investigated the RDP because of PCR amplification bias in the sequence composition of the dataset. In the RDP, the non-coverage rates for all primers except 27F were ?6%, while in the metagenomic datasets, most were ?10%. If one considers that a single mismatch near the 3' end of the primer might greatly reduce PCR efficiency, then some phylum non-coverage rates would change by more than 20%. Primer binding-site sequence variants that could not pair with their corresponding primers are discussed. CONCLUSIONS: Our study revealed the potential bias introduced by the use of universal bacterial primers in the assessment of microbial communities. With the development of high-throughput, next-generation sequencing techniques, it will become feasible to sequence more of the hypervariable regions of the bacterial 16S rRNA gene. This, in turn, will lead to the more frequent use of the primers discussed here.

SUBMITTER: Mao DP

PROVIDER: S-EPMC3445835 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Coverage evaluation of universal bacterial primers using the metagenomic datasets.

Mao Dan-Ping DP Zhou Quan Q Chen Chong-Yu CY Quan Zhe-Xue ZX

BMC microbiology 20120503

<h4>Background</h4>The coverage of universal primers for the bacterial 16S rRNA gene plays a crucial role in the correct understanding of microbial community structure. However, existing studies on primer coverage are limited by the lack of appropriate databases and are restricted to the domain level. Additionally, most studies do not account for the positional effect of single primer-template mismatches. In this study, we used 7 metagenomic datasets as well as the Ribosomal Database Project (RD ...[more]

PMID: 22554309

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Project description:BackgroundMass distribution of insecticide-treated nets (ITNs) is a cost-effective way to achieve universal coverage, but maintaining this coverage is more difficult. In addition to commonly used indicators, evaluation of universal coverage should include coverage of effective nets and changes in coverage over time.MethodsLongitudinal and cross-sectional household ITN surveys were carried out from 2010 to 2013 in six locations representing a variety of settings across western Kenya. Five indicators were used to evaluate the current status of universal coverage: 1) ITN ownership--proportion of households that own at least one ITN, 2) access index--ratio of the number of family members over the number of ITNs owned by that household, 3) operational coverage--proportion of the at-risk population potentially covered by ITNs, assuming one ITN for every two people, 4) effective coverage--population coverage of effective ITNs, and 5) usage--proportion of the population that used ITNs the previous night.ResultsITN ownership and operational coverage increased substantially from 2010 to 2013, but this increase was mostly due to the 2011 mass distribution campaign. In 2013, household ITN ownership was on average 84.4% (95% CI [78.4, 90.5]) across the six study areas, and operational coverage was 83.2% (95% CI [72.5, 93.8]). The ITN access rate was 59.1% (95% CI [56.6, 61.7]), and 40.8% (95% CI [38.3, 43.4]) of the people at risk needed more nets to achieve universal coverage. About 88.5% (95% CI [86.1, 90.9]) of the ITNs were below three years old and 16.5% (95% CI [12.1, 20.9]) of the ITNs had hole(s). The estimated effective long-lasting insecticide-treated net (LLIN) coverage was 70.5% (95 CI [58.7, 82.3]). Approximately 18.4% (95% CI [15.5, 21.4]) of the ITNs were shared by more than three persons, and the population ITN usage rate was about 75-87%. The reason for not using ITNs was almost exclusively "net not available".ConclusionCurrent methods of delivering ITNs, i.e., one mass campaign every five years and regular distribution of ITNs from health center can barely maintain the current effective coverage. Inaccessibility and loss of physical integrity of ITNs are major hindrances to achieving and maintaining universal coverage.

Project description:BackgroundLong-read shotgun metagenomic sequencing is gaining in popularity and offers many advantages over short-read sequencing. The higher information content in long reads is useful for a variety of metagenomics analyses, including taxonomic classification and profiling. The development of long-read specific tools for taxonomic classification is accelerating, yet there is a lack of information regarding their relative performance. Here, we perform a critical benchmarking study using 11 methods, including five methods designed specifically for long reads. We applied these tools to several mock community datasets generated using Pacific Biosciences (PacBio) HiFi or Oxford Nanopore Technology sequencing, and evaluated their performance based on read utilization, detection metrics, and relative abundance estimates.ResultsOur results show that long-read classifiers generally performed best. Several short-read classification and profiling methods produced many false positives (particularly at lower abundances), required heavy filtering to achieve acceptable precision (at the cost of reduced recall), and produced inaccurate abundance estimates. By contrast, two long-read methods (BugSeq, MEGAN-LR & DIAMOND) and one generalized method (sourmash) displayed high precision and recall without any filtering required. Furthermore, in the PacBio HiFi datasets these methods detected all species down to the 0.1% abundance level with high precision. Some long-read methods, such as MetaMaps and MMseqs2, required moderate filtering to reduce false positives to resemble the precision and recall of the top-performing methods. We found read quality affected performance for methods relying on protein prediction or exact k-mer matching, and these methods performed better with PacBio HiFi datasets. We also found that long-read datasets with a large proportion of shorter reads (< 2 kb length) resulted in lower precision and worse abundance estimates, relative to length-filtered datasets. Finally, for classification methods, we found that the long-read datasets produced significantly better results than short-read datasets, demonstrating clear advantages for long-read metagenomic sequencing.ConclusionsOur critical assessment of available methods provides best-practice recommendations for current research using long reads and establishes a baseline for future benchmarking studies.

Dataset Information

Coverage evaluation of universal bacterial primers using the metagenomic datasets.

Publications

Coverage evaluation of universal bacterial primers using the metagenomic datasets.

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