Author: Li, Ci-Xiu; Li, Wei; Zhou, Jun; Zhang, Bing; Feng, Yan; Xu, Chang-Ping; Lu, Yi-Yu; Holmes, Edward C.; Shi, Mang
Title: High resolution metagenomic characterization of complex infectomes in paediatric acute respiratory infection Cord-id: aa4s7b21 Document date: 2020_3_3
ID: aa4s7b21
Snippet: The diversity of pathogens associated with acute respiratory infection (ARI) makes diagnosis challenging. Traditional pathogen screening tests have a limited detection range and provide little additional information. We used total RNA sequencing (“meta-transcriptomicsâ€) to reveal the full spectrum of microbes associated with paediatric ARI. Throat swabs were collected from 48 paediatric ARI patients and 7 healthy controls. Samples were subjected to meta-transcriptomics to determine the prese
Document: The diversity of pathogens associated with acute respiratory infection (ARI) makes diagnosis challenging. Traditional pathogen screening tests have a limited detection range and provide little additional information. We used total RNA sequencing (“meta-transcriptomicsâ€) to reveal the full spectrum of microbes associated with paediatric ARI. Throat swabs were collected from 48 paediatric ARI patients and 7 healthy controls. Samples were subjected to meta-transcriptomics to determine the presence and abundance of viral, bacterial, and eukaryotic pathogens, and to reveal mixed infections, pathogen genotypes/subtypes, evolutionary origins, epidemiological history, and antimicrobial resistance. We identified 11 RNA viruses, 4 DNA viruses, 4 species of bacteria, and 1 fungus. While most are known to cause ARIs, others, such as echovirus 6, are rarely associated with respiratory disease. Co-infection of viruses and bacteria and of multiple viruses were commonplace (9/48), with one patient harboring 5 different pathogens, and genome sequence data revealed large intra-species diversity. Expressed resistance against eight classes of antibiotic was detected, with those for MLS, Bla, Tet, Phe at relatively high abundance. In summary, we used a simple total RNA sequencing approach to reveal the complex polymicrobial infectome in ARI. This provided comprehensive and clinically informative information relevant to understanding respiratory disease.
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