Recent dual RNA-seq database measures gene activity in bacteria and their human hosts

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Enhanced monitoring and identification have led to the investigation of previously overlooked bacteria, such as serious pathogens. In contrast, human population growth, globalization and increasing travel have added to the proliferation of new pathogens and evolving trends of infectious diseases. The biology of overlooked and evolving pathogens is frequently confused but important to creating therapeutic and preventive strategies. Obligate intracellular pathogens pose additional difficulties, as many trigger diseases that are challenging to detect and difficult to control experimentally.

The database, DualSeqDB, can also be utilized to determine when different groups of bacteria use identical genes to infect humans and other animals, indicating potential therapeutic targets for new antibiotics production.

 Researchers and health researchers help from the database classify potential new drug targets by analyzing how infection mechanisms function through unrelated bacterial organisms. Researchers may also link their databases to DualSeqDB to make it easier for other researchers worldwide to view and use them.

According to Dr Lang, the public health consequences of possible abiotic possible treatments are serious, particularly, when multi-resistant strains of common pathogens emerge in clinics around the globe. Studying gene activation during sequencing infection cycles is one of the most cost-effective ways of finding new drug targets.

DualSeqDB was developed by defining and merging existing databases. Using a well-defined pipeline, the teams standardized data on gene expression from various sources to make it directly comparative (RNA-Seq Blog, 2020).

In a standard dual RNA-seq assay, either animal is immunized with a given bacterial load (in vivo). The related cell culture models are inoculated with bacteria at a specified multiplicity of infections (in vitro). After inoculation, samples are collected over time to assess the reaction time. At each stage, contaminated cells are lysed, RNA is separated, and the cDNA library is processed and sequenced using high-throughput sequencing technologies that produce large quantities of data. RNA-seq results for the mock-infected host cells and the original bacterial cultures are used as a control group for gene expression. 

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Dual RNA-seq studies have many technical challenges, including the varying structure and quality of RNA among bacteria and eukaryotic cells, the greater proportion of RNA in eukaryotic cells, and the need to compensate for its host in prevalence rRNA transcripts and the unpredictable rate of disease.

Typically, such drawbacks can be overcome by high-profile sequencing, pathogen and host rRNA depletion, and enriching samples for contaminated host cells by fluorescence-activated cell sorting (Rendon et al., 2021)

How does it work?

Dual RNA-seq assesses intracellular pathogen and host cell transcription of RNA in a unified experiment 14, 15 and can give insight into both the host and pathogen response to an infection. For example, dual RNA-seq was used to research compulsory intracellular Chlamydia trachomatis16, which showed the resetting of Chlamydia metabolism during the onset of human epithelial cell infection.

During infection, pathogens activate the expression of specific genes that enable them to reproduce within the host and ensure their longevity. The host, in essence, stimulates complex pathways to detect and destroy pathogens (Mika-Gospodorz et al., 2020).

Researchers will monitor this arms race while the infection process by sequencing data from RNA transcripts obtained concurrently from both the bacteria and the host. This ‘dual RNA-seq’ helps researchers to classify novel molecular features that would otherwise remain unseen.

Development of Dual Sequence Database

DualSeqDB was developed by Gian Tartaglia and Benjamin Lang at the Center for Genomic Control (CRG) and Javier Macho Rendón, Marc Ramos Llorens and Marc Torrent at the Universitat Autònoma de Barcelona (UAB).

Given the current acceleration of sequencing technology in science and clinics, this database is  expected to expand continuously and become a robust repository that will support in the battle against infectious diseases (RNA-Seq Blog, 2020)

It was supposed to shed by using this technology light, particularly on the dedication of non-protein encoding transcripts to virulence, as such classes have largely skipped prior infection trials due to lack of effective techniques. Dual RNA-seq output was assessed in an in vitro infection model focused on the essential optional intracellular pathogen Salmonella enterica serovar Typhimurium and separated human cell lines. Dual RNA-seq was proven to be capable of catching all big bacteria and individual transcript types and found to be reproducible. During these tests, a previously mostly undescribed bacterial small non-coding RNA (sRNA), known as STnc440, was established as one of the most highly mediated genes in intracellular Salmonella. 

 

References

Mika-Gospodorz, B., Giengkam, S., Westerman, A. J., Wongsantichon, J., Kion-Crobsy, W., Chuenklin, S., Wang, L. C., Sunyakumthorn, P., Sobota, R. M., Subbian, S., Vogel, J., Barquist, L., & Salje, J. (2020, July 3). Dual RNA-seq of Orientia tsutsugamushi informs on host-pathogen interactions for this neglected intracellular human pathogen. Nature Communications, (11). Nature Communications. https://doi.org/10.1038/s41467-020-17094-8

Rendon, J. M., Lang, B., Llorens, M. R., Tartagila, G. G., & Burgas, M. T. (2021, January 8). DualSeqDB: the host–pathogen dual RNA sequencing database for infection processes. Nucleic Acids Research, 49(D1). Nucleic Acids Research. https://doi.org/10.1093/nar/gkaa890

RNA-Seq Blog. (2020, November 10). New dual RNA-seq database measures gene activity in bacteria and their human hosts. RNA-Seq Blog. https://rna-seqblog.com/new-dual-rna-seq-database-measures-gene-activity-in-bacteria-and-their-human-hosts/

Westermann, A. J. (2014, December). Dual RNA-seq of pathogen and host. the Graduate School of Life Sciences (GSLS).

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