MTD: a unique pipeline for host and meta-transcriptome joint and integrative analyses of RNA-seq data

Abstract

Ribonucleic acid (RNA)-seq data contain not only host transcriptomes but also nonhost information that comprises transcripts from active microbiota in the host cells. Therefore, joint and integrative analyses of both host and meta-transcriptome can reveal gene expression of the microbial community in a given sample as well as the correlative and interactive dynamics of the host response to the microbiome. However, there are no convenient tools that can systemically analyze host–microbiota interactions through simultaneously quantifying the host and meta-transcriptome in the same sample at the tissue and the single-cell level. This poses a challenge for interested researchers with limited expertise in bioinformatics. Here, we developed a software pipeline that can comprehensively and synergistically analyze and correlate the host and meta-transcriptome in a single sample using bulk and single-cell RNA-seq data. This pipeline, named meta-transcriptome detector (MTD), can extensively identify and quantify microbiome, including viruses, bacteria, protozoa, fungi, plasmids and vectors, in the host cells and correlate the microbiome with the host transcriptome. MTD is easy to install and run, involving only a few lines of simple commands. It offers researchers with unique genomics insights into host responses to microorganisms.

Single-cell analysis identifies conserved features of immune dysfunction in simulated microgravity and spaceflight

“…2A ). Next, because both spaceflight and aging are associated with reactivation of latent viruses, we mined the meta-transcriptome of our single-cell analysis with meta-transcriptome detector (MTD) pipeline 26 . Surprisingly, we saw that as little as 25 hours of simulated microgravity could induce the transcription of latent retroviruses and mycobacteria within human immune cells (Fig.…”

“…Data processing was performed using 10x Genomics Cell Ranger v6.1.2 and MTD 26 pipelines. The “cellranger count” was used to perform transcriptome alignment, filtering, and UMI counting from the FASTQ (raw data) files.…”

“…About 20 million paired-end 150 bp reads per sample were generated from Illumina NovaSeq 6000 Sequencing System. FASTQ raw reads were analyzed using the MTD pipeline 26 . Differential gene expression analysis between groups was done by DESeq2 R package (version 1.36.0) 75 with control for the subject effect.…”

Single-cell multi-ome and immune profiles of the Inspiration4 crew reveal conserved, cell-type, and sex-specific responses to spaceflight

“…FASTQ files were programmatically downloaded from GeneLab ( https://genelab.nasa.gov/ ) and processed using the MTD pipeline 72 . A meta-analysis of the GeneLab data was performed in two steps.…”

The microbiome in the pathogenesis of lung cancer

“…Meta-transcriptomics focuses on mRNA from the microbiome. It involves the high-throughput sequencing of transcripts from all microbial communities in samples collected under specific conditions [108]. This method is used to detect the distributional characteristics and transcriptional functions of active species in microbial communities.…”