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Meta Analysis ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 1 ? Systematic review or meta-analysis. Synthesizes findings across many studies. Strongest evidence. Gut & Microbiome Marine & Wildlife Sign in to save

Exploring the Potential of Metatranscriptomics to Describe Microbial Communities and Their Effects in Molluscs

International Journal of Molecular Sciences 2022 11 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 45 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Cristian Gallardo‐Escárate, Magalí Rey-Campos, Magalí Rey-Campos, Cristian Gallardo‐Escárate, Raquel Ríos-Castro, Cristian Gallardo‐Escárate, Cristian Gallardo‐Escárate, Beatriz Novoa, Cristian Gallardo‐Escárate, Beatriz Novoa, Beatriz Novoa, Cristian Gallardo‐Escárate, Beatriz Novoa, Beatriz Novoa, António Figueras António Figueras António Figueras Beatriz Novoa, António Figueras António Figueras António Figueras Beatriz Novoa, António Figueras Beatriz Novoa, Beatriz Novoa, António Figueras António Figueras

Summary

Metatranscriptomics revealed a more complete picture of mussel microbiomes — including bacteria, viruses, fungi, and protozoans — than traditional 16S sequencing alone. The approach also identified host genes whose expression changed with pathogen load, providing new insights into how molluscs respond to microbial infections.

Study Type Review

Metatranscriptomics has emerged as a very useful technology for the study of microbiomes from RNA-seq reads. This method provides additional information compared to the sequencing of ribosomal genes because the gene expression can also be analysed. In this work, we used the metatranscriptomic approach to study the whole microbiome of mussels, including bacteria, viruses, fungi, and protozoans, by mapping the RNA-seq reads to custom assembly databases (including the genomes of microorganisms publicly available). This strategy allowed us not only to describe the diversity of microorganisms but also to relate the host transcriptome and microbiome, finding the genes more affected by the pathogen load. Although some bacteria abundant in the metatranscriptomic analysis were undetectable by 16S rRNA sequencing, a common core of the taxa was detected by both methodologies (62% of the metatranscriptomic detections were also identified by 16S rRNA sequencing, the Oceanospirillales, Flavobacteriales and Vibrionales orders being the most relevant). However, the differences in the microbiome composition were observed among different tissues of <i>Mytilus galloprovincialis</i>, with the fungal kingdom being especially diverse, or among molluscan species. These results confirm the potential of a meta-analysis of transcriptome data to obtain new information on the molluscs' microbiome.

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