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Current knowledge about the respiratory microbiome is mainly based on 16S ribosomal RNA gene sequencing. Newer sequencing approaches, such as metatranscriptomics, offer the technical ability to measure the viable microbiome response to environmental conditions such as smoking as well as to explore its functional role by investigating host-microbiome interactions. However, knowledge about its feasibility in respiratory microbiome research, especially in lung biopsies, is still very limited. RNA sequencing was performed in bronchial biopsies from clinically stable smokers (nā€‰=ā€‰5) and ex-smokers (nā€‰=ā€‰6) with COPD not using (inhaled) steroids. The Trinity assembler was used to assemble non-human reads in order to allow unbiased taxonomical and microbial transcriptional analyses. Subsequently, host-microbiome interactions were analyzed based on associations with host transcriptomic data. Ultra-low levels of microbial mass (0.009%) were identified in the RNA-seq data. Overall, no differences were identified in microbiome diversity or transcriptional profiles of microbial communities or individual microbes between COPD smokers and ex-smokers in the initial test dataset as well as a larger replication dataset. We identified an upregulated host gene set, related to the simultaneous presence of Bradyrhizobium, Roseomonas, Brevibacterium.spp., which were related to PERK-mediated unfolded protein response (UPR) and expression of the microRNA-155-5p. Our results show that metatranscriptomic profiling in bronchial biopsy samples from stable COPD patients yields ultra-low levels of microbial mass. Further, this study illustrates the potential of using transcriptional profiling of the host and microbiome to gain more insight into their interaction in the airways.

Citation

B Ditz, J Boekhoudt, N Couto, C A Brandsma, P S Hiemstra, G W Tew, M Neighbors, M A Grimbaldeston, W Timens, H A M Kerstjens, J W A Rossen, V Guryev, M van den Berge, A Faiz. The Microbiome in Bronchial Biopsies from Smokers and Ex-Smokers with Stable COPD - A Metatranscriptomic Approach. COPD. 2022;19(1):81-87

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PMID: 35118915

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