Abstract
Acute respiratory infection (ARI) is the most frequent cause for hospitalization in infants and young children. Using multiplexed nCounter technology to digitally quantify 600 human mRNAs in parallel with 14 virus- and 5 bacterium-specific RNAs, we characterized viral and bacterial presence in nasopharyngeal aspirates (NPA) of 58 children with ARI and determined the corresponding in situ immune profiles. NPA contained different groups of organisms and these were classified into bacterial (n = 27), viral (n = 5), codetection [containing both viral and bacterial transcripts (n = 21), or indeterminate intermediate where microbial load is below threshold (n = 5)]. We then identified differentially expressed immune transcripts (DEITs) comparing NPAs from symptomatic children vs. healthy controls, and comparing children presenting NPAs with detectable microbial load vs. indeterminate. We observed a strong innate immune response in NPAs, due to the presence of evolutionarily conserved type I Interferon (IFN)-stimulated genes (ISG), which was correlated with total bacterial and/or viral load. In comparison with indeterminate NPAs, adaptive immunity transcripts discriminated among viral, bacterial, and codetected microbial profiles. In viral NPAs, B cell transcripts were significantly enriched among DEITs, while only type III IFN was correlated with viral load. In bacterial NPAs, myeloid cells and coinhibitory transcripts were enriched and significantly correlated with bacterial load. In conclusion, digital nCounter transcriptomics provide a microbial and immunological in situ “snapshot” of the nasopharyngeal interface in children with ARI. This enabled discrimination among viral, bacterial, codetection, and indeterminate transcripts in the samples using non-invasive sampling.
Highlights
Acute respiratory infections (ARIs) cause great morbidity and mortality in children across the globe
Microbial Load and Clinical Symptoms of Children With ARI. In this prospective study of 58 randomized nasopharyngeal aspirates (NPA) samples from children diagnosed with ARI, we initially determined the microbial load of the NPAs using custom-designed probes and nCounter digital transcriptomics
Upon examination of correlations among the different microbial targets in NPAs (Figure 1C), H. influenzae is at the center of the network, indicating that it is associated with all other targets detected, S. pneumoniae and M. catarrhalis
Summary
Acute respiratory infections (ARIs) cause great morbidity and mortality in children across the globe. Concomitant viral and bacterial infection, caused mainly by Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis, can lead to the development of acute otitis media (Ruohola et al, 2013) or pneumonia (Nolan et al, 2017) This adds another layer of complexity to the microbial interactions at the respiratory tract. Recent investigations have used blood transcriptomic analysis to identify immune signatures in community-acquired pneumonia (CAP) (Parnell et al, 2012), respiratory syncytial virus (RSV) infection (Mejias et al, 2013), and rhinovirus (RV) infection (Heinonen et al, 2015) Such analyses are robust enough to distinguish bacterial from viral respiratory infection, suggesting that transcriptional profiling can improve diagnosis (Suarez et al, 2015; Sweeney et al, 2016). Systems immunology approaches identified modular communities of immune response genes that are correlated with microbial load, distinguishing microberelated immune signatures
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