New software device makes genetic information analysis simpler

Researchers from Texas Biomedical Research Institute and Tulane University have created a new software device that makes analyzing genetic data about a host and its microbiome at the very same time simpler, quicker, and less expensive.

New software device makes analyzing genetic information simpler
Dr. Binhua “Julie” Ling. Image Credit: Texas Biomedical Research Institute

The “meta-transcriptome detector” (MTD) software can be utilized by a broad range of microbiologists and medication developers, namely those researching diseases like certain cancers, COVID-19, HIV/AIDS, malaria, and a variety of other human health issues associated to microbes. The new research was recently published in the journal Briefings in Bioinformatics.

It is very user-friendly, especially for researchers with little to no background in bioinformatics. You only need to write one line of code to set certain parameters and the software does the rest automatically.”

Binhua “Julie” Ling, PhD, Study Senior Author and Associate Professor, Texas Biomedical Research Institute

Ling also co-leads Texas Biomed’s Host-Pathogen Interactions Research Program.

MTD allows researchers to acquire a complete picture of what microbes are present in the host, including both the “good bacteria” that reside on and within people and animals, as well as dangerous microbes like viruses that cause significant infections. MTD also evaluates gene expression activity, or which genes are switched on or off, in both bacteria and hosts at the same time, enabling researchers to quickly discover correlations between them.

Seeing which genes are functioning in a microbe and in the host, for example, could show that one’s activity is controlled by the other’s, and could point to a future therapeutic target, according to Ling.

We can’t say at this stage if it is cause and effect, but we can use this analysis to pinpoint what genes or pathways we should be investigating—perhaps ones that we never considered before as being related. MTD can help accelerate that process and potentially open new avenues of research and drug development.”

Binhua “Julie” Ling, PhD, Study Senior Author and Associate Professor, Texas Biomedical Research Institute

MTD combines many existing software programs and searches international databases for RNA sequences of over 100,000 bacteria, viruses, fungi, archaea, and protozoa, as well as vector and plasmid sequences. Users can also add certain sequences to the database that they are interested in.

Fei Wu, PhD, and Ling collaborated to investigate how the microbiome changes with age in monkeys infected with the simian immunodeficiency virus (SIV), the monkey counterpart of HIV.

We had to analyze gene expression from the host by one workflow, and the microbiome gene expression by a separate workflow. We wondered why can’t we do both at the same time?”

Fei Wu, PhD, Texas Biomedical Research Institute

Researchers had the time to concentrate on computer-based work as their lab was relocating during the COVID-19 outbreak, and they set out to fix this problem. Wu built and tested the new program with Ling and collaborator Yao-Zhong Liu, PhD, an Associate Professor at Tulane University School of Public Health and Tropical Medicine.

Normally, we are using bioinformatics software to analyze our data, not building it,” Wu says. “It was challenging, but exciting, to branch out and now have something that will not only help us, but also any other researcher doing RNA sequencing of hosts and microbiomes; from humans and monkeys, to mosquitos carrying malaria parasites and snails carrying schistosome parasites.”

MTD has a number of advantages over other tools. It can evaluate RNA sequences from both the host and the microbiota from the same sample, which can be single cells or a bulk tissue sample. This saves time and resources while also revealing fresh information about the interactions between bacteria and their hosts. It does demand some high-performance computing capacity, but it is otherwise broadly available to bioinformatics researchers.

Journal reference:

Wu, F., et al. (2022) MTD: a unique pipeline for host and meta-transcriptome joint and integrative analyses of RNA-seq data. Briefings in Bioinformatics.


The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoLifeSciences.
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