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Comparison of metatranscriptomics and targeted-sequencing methods for integrative analysis of the whole microbiome

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Abstract Background: Targeted-sequencing sequencing methods, such as 16S-rRNA profiling, viral metagenomics, and human mRNA sequencing are mainly used for the exploration of the microbiome, yet their combination can be expensive and time-consuming. Metatranscriptomics snapshots the entire active microbiome trough bulk RNA sequencing in one test, but lacks adequate comparisons with targeted-sequencing approaches. Results: We compared metatranscriptomics and targeted sequencing methods for bacterial, viral, and human components, using 20 nasopharyngeal aspirates from infants under 1 year old and hospitalized for bronchiolitis at the Hospices Civils de Lyon.RNA microbiome concordance reached 86% and 78% for RNA viruses and human coding genes, respectively. Patient clustering was similar using 2650 host transcripts sequenced with metatranscriptomics and mRNA-Seq. Metatranscriptomics detected RNA of eukaryotic and prokaryotic DNA viruses, indicating potential for discerning replicative from latent DNA microbiome. Transcriptionally active bacteriome corresponded to 82% of bacteria exceeding 0.5% relative abundance, showing different transcriptional profiles depending on bacterial species. Conclusion: Multi-omics technologies enhance epidemiology, investigate trans-kingdom interactions, and provide opportunities to establish microbiome biomarkers. With sufficient depth of sequencing, metatranscriptomics complements and aligns with various aspects of targeted-sequencing approaches. Further clinical studies are essential to position metatranscriptomics in critical acute situations and cases of diagnostic uncertainty.
Title: Comparison of metatranscriptomics and targeted-sequencing methods for integrative analysis of the whole microbiome
Description:
Abstract Background: Targeted-sequencing sequencing methods, such as 16S-rRNA profiling, viral metagenomics, and human mRNA sequencing are mainly used for the exploration of the microbiome, yet their combination can be expensive and time-consuming.
Metatranscriptomics snapshots the entire active microbiome trough bulk RNA sequencing in one test, but lacks adequate comparisons with targeted-sequencing approaches.
Results: We compared metatranscriptomics and targeted sequencing methods for bacterial, viral, and human components, using 20 nasopharyngeal aspirates from infants under 1 year old and hospitalized for bronchiolitis at the Hospices Civils de Lyon.
RNA microbiome concordance reached 86% and 78% for RNA viruses and human coding genes, respectively.
Patient clustering was similar using 2650 host transcripts sequenced with metatranscriptomics and mRNA-Seq.
Metatranscriptomics detected RNA of eukaryotic and prokaryotic DNA viruses, indicating potential for discerning replicative from latent DNA microbiome.
Transcriptionally active bacteriome corresponded to 82% of bacteria exceeding 0.
5% relative abundance, showing different transcriptional profiles depending on bacterial species.
Conclusion: Multi-omics technologies enhance epidemiology, investigate trans-kingdom interactions, and provide opportunities to establish microbiome biomarkers.
With sufficient depth of sequencing, metatranscriptomics complements and aligns with various aspects of targeted-sequencing approaches.
Further clinical studies are essential to position metatranscriptomics in critical acute situations and cases of diagnostic uncertainty.

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