tetano
Editor, Senior Moderator
J Clin Microbiol. 2015 May 13. pii: JCM.02495-14. [Epub ahead of print]
[h=1]Evaluation of unbiased RNAseq as a diagnostic method in influenza virus positive respiratory samples.[/h] Fischer N[SUP]1[/SUP], Indenbirken D[SUP]2[/SUP], Meyer T[SUP]3[/SUP], L?tgehetmann M[SUP]3[/SUP], Lellek H[SUP]4[/SUP], Spohn M[SUP]2[/SUP], Aepfelbacher M[SUP]3[/SUP], Alawi M[SUP]5[/SUP], Grundhoff A[SUP]6[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Unbiased, non-targeted metagenomic RNA sequencing (UMERS) has the advantage to detect known as well as unknown pathogens and thus can significantly improve the detection of viral, bacterial, parasitic and fungal sequences in public health settings. In particular, in only 30-40% of respiratory specimen from patients with acute respiratory illness conventional diagnostic methods successfully identify the putative pathogenic agent. We here apply UMERS to 24 diagnostic respiratory specimens (bronchoalveolar lavage (BAL), sputum and swab) from patients with seasonal influenza infection and 5 BAL samples from patients with pneumonia tested negative for influenza to validate RNA sequencing as an unbiased, diagnostic tool in comparison to conventional diagnostic methods. In addition to our comparison to PCR we evaluate i) the potential to retrieve comprehensive influenza virus genomic information and ii) capability to detect known superinfecting pathogens. When compared to quantitative RT-PCR for influenza virus sequences, UMERS detected influenza viral sequences in 18/24 samples. Complete influenza virus genomes could be assembled from 8 samples. Furthermore, in 3/24 influenza positive samples additional viral pathogens could be detected and 2/24 samples showed significantly increased abundance of individual bacterial species known to cause superinfections during influenza virus infection. Thus, analysis of respiratory samples from known or suspected influenza patients by UMERS provides valuable information that is relevant for clinical investigation.
Copyright ? 2015, American Society for Microbiology. All Rights Reserved.
PMID: 25972420 [PubMed - as supplied by publisher]
[h=1]Evaluation of unbiased RNAseq as a diagnostic method in influenza virus positive respiratory samples.[/h] Fischer N[SUP]1[/SUP], Indenbirken D[SUP]2[/SUP], Meyer T[SUP]3[/SUP], L?tgehetmann M[SUP]3[/SUP], Lellek H[SUP]4[/SUP], Spohn M[SUP]2[/SUP], Aepfelbacher M[SUP]3[/SUP], Alawi M[SUP]5[/SUP], Grundhoff A[SUP]6[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Unbiased, non-targeted metagenomic RNA sequencing (UMERS) has the advantage to detect known as well as unknown pathogens and thus can significantly improve the detection of viral, bacterial, parasitic and fungal sequences in public health settings. In particular, in only 30-40% of respiratory specimen from patients with acute respiratory illness conventional diagnostic methods successfully identify the putative pathogenic agent. We here apply UMERS to 24 diagnostic respiratory specimens (bronchoalveolar lavage (BAL), sputum and swab) from patients with seasonal influenza infection and 5 BAL samples from patients with pneumonia tested negative for influenza to validate RNA sequencing as an unbiased, diagnostic tool in comparison to conventional diagnostic methods. In addition to our comparison to PCR we evaluate i) the potential to retrieve comprehensive influenza virus genomic information and ii) capability to detect known superinfecting pathogens. When compared to quantitative RT-PCR for influenza virus sequences, UMERS detected influenza viral sequences in 18/24 samples. Complete influenza virus genomes could be assembled from 8 samples. Furthermore, in 3/24 influenza positive samples additional viral pathogens could be detected and 2/24 samples showed significantly increased abundance of individual bacterial species known to cause superinfections during influenza virus infection. Thus, analysis of respiratory samples from known or suspected influenza patients by UMERS provides valuable information that is relevant for clinical investigation.
Copyright ? 2015, American Society for Microbiology. All Rights Reserved.
PMID: 25972420 [PubMed - as supplied by publisher]