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Amplicon sequencing and improved detection of human rhinovirus in respiratory samples.

ABSTRACT: Improved knowledge of the genotypic characteristics of human rhinovirus (HRV) is required, as are nucleic detection assays with the capacity to overcome both the similarities between members of the family Picornaviridae and the wide diversity of different HRV serotypes. The goal of the present study was to investigate the variability and the genotypic diversity of clinical strains circulating in the community. Since most reverse transcription (RT)-PCR assays available cannot differentiate HRV from other members of the family Picornaviridae, we also validated an assay specific for HRV detection. The 5' noncoding regions of 87 different HRV serotypes and clinical isolates were sequenced. On the basis of sequence analysis and phylogenetic determination, we first confirmed that all clinical isolates were HRV. We then validated a real-time RT-PCR assay that was able not only to detect all HRV serotypes and all clinical isolates tested but also to accurately discriminate between rhinovirus and other viruses from the family Picornaviridae. This assay was negative with isolates of coxsackievirus (types A and B), echovirus, enterovirus, parechovirus, and poliovirus, as well as nonpicornaviruses. Among a series of bronchoalveolar lavage specimens, 4% (7 of 161) were positive by culture, whereas 13% (21 of 161) were positive by RT-PCR. In the present study we showed that to specifically identify HRV in clinical specimens, diagnostic assays need to overcome both the diversities and the similarities of picornaviruses. By sequencing the 5' noncoding regions of rhinoviruses recovered from clinical specimens, we designed probes that could specifically detect rhinovirus.

SUBMITTER: Deffernez C

PROVIDER: S-EPMC446277 | biostudies-literature | 2004 Jul

REPOSITORIES: biostudies-literature

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Amplicon sequencing and improved detection of human rhinovirus in respiratory samples.

Deffernez Christelle C Wunderli Werner W Thomas Yves Y Yerly Sabine S Perrin Luc L Kaiser Laurent L

Journal of clinical microbiology 20040701 7

Improved knowledge of the genotypic characteristics of human rhinovirus (HRV) is required, as are nucleic detection assays with the capacity to overcome both the similarities between members of the family Picornaviridae and the wide diversity of different HRV serotypes. The goal of the present study was to investigate the variability and the genotypic diversity of clinical strains circulating in the community. Since most reverse transcription (RT)-PCR assays available cannot differentiate HRV fr ...[more]

PMID: 15243084

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Project description:BACKGROUND:High-throughput sequencing techniques are used to analyse the diversity of the respiratory microbiota in health and disease. Although extensive data are available regarding bacterial respiratory microbiota, its fungal component remains poorly studied. This is partly due to the technical issues associated with fungal metagenomics analyses. In this study, we compared two DNA extraction protocols and two fungal amplification targets for combined bacterial and fungal targeted amplicon sequencing analyses of the respiratory microbiota. METHODS:Six sputa, randomly selected from routine samples in Mondor Hospital (Creteil, France) and treated anonymously, were tested after bacterial and fungal routine culture. Two of which were spiked with Aspergillus Fumigati and Aspergillus Nigri (105 conidia/mL). After mechanical lysis, DNA was extracted using automated QIAsymphony® extraction (AQE) or manual PowerSoil® MoBio extraction (MPE). DNA yield and purity were compared. DNA extracted from spiked sputa was subjected to (i) real-time PCR for Aspergillus DNA detection and (ii) combined metagenomic analyses targeting barcoded primers for fungal ITS1 and ITS2, and bacterial V1-V2 and V3-V4 16S regions. Amplicon libraries were prepared using MiSeq Reagent V3 kit on Illumina platform. Data were analysed using PyroMIC© and SHAMAN software, and compared with culture results. RESULTS:AQE extraction provided a higher yield of DNA (AQE/MPE DNA ratio = 4.5 [1.3-11]) in a shorter time. The yield of Aspergillus DNA detected by qPCR was similar for spiked sputa regardless of extraction protocol. The extraction moderately impacted the diversity or relative abundances of bacterial communities using targeted amplicon sequencing (2/43 taxa impacted). For fungi, the relative abundances of 4/11 major taxa were impacted and AQE results were closer to culture results. The V1-V2 or V3-V4 and ITS1 or ITS2 targets assessed similarly the diversity of bacterial and fungal major taxa, but ITS2 and V3-V4 detected more minor taxa. CONCLUSION:Our results showed the importance of DNA extraction for combined bacterial and fungal targeted metagenomics of respiratory samples. The extraction protocol can affect DNA yield and the relative abundances of few bacterial but more fungal taxa. For fungal analysis, ITS2 allowed the detection of a greater number of minor taxa compared with ITS1.

Project description:BackgroundShort oligonucleotides can be used as markers to tag and track DNA sequences. For example, barcoding techniques (i.e. Multiplex Identifiers or Indexing) use short oligonucleotides to distinguish between reads from different DNA samples pooled for high-throughput sequencing. A similar technique called molecule tagging uses the same principles but is applied to individual DNA template molecules. Each template molecule is tagged with a unique oligonucleotide prior to polymerase chain reaction. The resulting amplicon sequences can be traced back to their original templates by their oligonucleotide tag. Consensus building from sequences sharing the same tag enables inference of original template molecules thereby reducing effects of sequencing error and polymerase chain reaction bias. Several independent groups have developed similar protocols for molecule tagging; however, user-friendly software for build consensus sequences from molecule tagged reads is not readily available or is highly specific for a particular protocol.ResultsMT-Toolbox recognizes oligonucleotide tags in amplicons and infers the correct template sequence. On a set of molecule tagged test reads, MT-Toolbox generates sequences having on average 0.00047 errors per base. MT-Toolbox includes a graphical user interface, command line interface, and options for speed and accuracy maximization. It can be run in serial on a standard personal computer or in parallel on a Load Sharing Facility based cluster system. An optional plugin provides features for common 16S metagenome profiling analysis such as chimera filtering, building operational taxonomic units, contaminant removal, and taxonomy assignments.ConclusionsMT-Toolbox provides an accessible, user-friendly environment for analysis of molecule tagged reads thereby reducing technical errors and polymerase chain reaction bias. These improvements reduce noise and allow for greater precision in single amplicon sequencing experiments.

Project description:To determine the reproducibility and quantitation of the amplicon sequencing-based detection approach for analyzing microbial community structure, a total of 24 microbial communities from a long-term global change experimental site were examined. Genomic DNA obtained from each community was used to amplify 16S rRNA genes with two or three barcode tags as technical replicates in the presence of a small quantity (0.1% wt/wt) of genomic DNA from Shewanella oneidensis MR-1 as the control. The technical reproducibility of the amplicon sequencing-based detection approach is quite low, with an average operational taxonomic unit (OTU) overlap of 17.2%±2.3% between two technical replicates, and 8.2%±2.3% among three technical replicates, which is most likely due to problems associated with random sampling processes. Such variations in technical replicates could have substantial effects on estimating β-diversity but less on α-diversity. A high variation was also observed in the control across different samples (for example, 66.7-fold for the forward primer), suggesting that the amplicon sequencing-based detection approach could not be quantitative. In addition, various strategies were examined to improve the comparability of amplicon sequencing data, such as increasing biological replicates, and removing singleton sequences and less-representative OTUs across biological replicates. Finally, as expected, various statistical analyses with preprocessed experimental data revealed clear differences in the composition and structure of microbial communities between warming and non-warming, or between clipping and non-clipping. Taken together, these results suggest that amplicon sequencing-based detection is useful in analyzing microbial community structure even though it is not reproducible and quantitative. However, great caution should be taken in experimental design and data interpretation when the amplicon sequencing-based detection approach is used for quantitative analysis of the β-diversity of microbial communities.

Dataset Information

Amplicon sequencing and improved detection of human rhinovirus in respiratory samples.

Publications

Amplicon sequencing and improved detection of human rhinovirus in respiratory samples.

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