Metatranscriptomics for Gut Microbiota Research

The development of genome sequencing technology, especially the next generation of sequencing technology, has accelerated the study of intestinal flora. Metatranscriptomic shotgun sequencing (RNAseq) allows the whole-genome analysis profiling of active microbial communities under different conditions. Creative Biolabs is a premier provider of customized solutions to live biotherapeutics products (LBP). Most of the potential next-generation probiotics (NGPs) come from the human gut, so we have deep expertise and mature analytical platforms for studying gut microbiota.

Metatranscriptomics for Gut Microbiota

Metatranscriptomics focuses on the global expression of RNA in the microbiome. In general, synthesized clonal DNA (cDNA), followed by RNA extraction from samples, is subjected to high-throughput sequencing. While the transcriptome mirrors a comprehensive set of RNA encoded by the genome of an organism, the metatranscriptome encompasses all transcripts encoded by genes of a group of microbial communities. Since DNA is transcribed into RNA sequences, the regulation of gene expression at the transcriptional level can be studied using metatranscriptomics, which makes it possible to further study the function and metabolic pathways of gut microbiota.

Different sequencing and bioinformatic strategies for human microbiome analysis.Fig.1 Different sequencing and bioinformatic strategies for human microbiome analysis. (Bikel, 2015)

Metatranscriptomic Analysis

A typical metatranscriptomic experiment involves the isolation of the total RNA from the microbiome followed by RNA enrichment depending on the type of RNA to be sequenced (i.e. mRNA, lincRNA, and microRNA). After that, the RNA is fragmented into smaller pieces followed by cDNA synthesis using reverse transcriptase and random hexamers or oligo(dT) primers. Then, as with metagenomic library construction, the 5'and/or 3' ends of the cDNA are repaired and connected to adapters, the library is cleaned, amplified, and quantified, and finally, the library is sequenced. The typical bioinformatics approach to analyzing data obtained from metatranscriptomic experiments is similar to that used in metagenomics and is also divided into two strategies: (1) mapping sequence reads to reference genomes and genes and (2) de novo assembly of new transcriptomes.

A schematic model for omics approaches to study the gut microbiome.Fig.2 A schematic model for omics approaches to study the gut microbiome. (Whon, 2021)

Utilization of Metatranscriptomics in Health and Disease

  • Assessment of microbial activity
  • Assessment of microbiome-immune interactions
  • Studying microbiome antisense RNA
  • Studying microbiome small noncoding RNAs

Obstacles That Limit the Large-scale Application of Metatranscriptomics

Although current metatranscriptomic techniques are promising, there are still some obstacles that limit their large-scale application.

1. Much of the harvested RNA comes from ribosomal RNA, and its dominating abundance can dramatically reduce the coverage of mRNA.

2. mRNA is notoriously unstable, compromising the integrity of the sample before sequencing.

3. Differentiating between host and microbial RNA can be challenging, although commercial enrichment kits are available.

Changes in the microbiome can affect the health of the niche of the environment in which they live. Metatranscriptomics tells us about the genes expressed in the community as a whole, and using functional annotations of expressed genes, it is possible to infer a functional profile of the community under specific conditions. Creative Biolabs has specialized in custom services in LBP development for researchers around the world. If you are interested in our metatranscriptomics services for gut microbiota, please contact us for more information.

References

  1. Bikel, S.; et al. Combining metagenomics, metatranscriptomics, and viromics to explore novel microbial interactions: towards a systems-level understanding of human microbiome. Computational and structural biotechnology journal. 2015, 13: 390-401.
  2. Whon, T.W.; et al. Omics in gut microbiome analysis. Journal of Microbiology. 2021, 59(3): 292-297.

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