Triple RNA-Seq Reveals Synergy in a Human Virus-Fungus Co-infection Model.

Seelbinder B, Wallstabe J, Marischen L, Weiss E, Wurster S, Page L, Löffler C, Bussemer L, Schmitt AL, Wolf T, Linde J, Cicin-Sain L, Becker J, Kalinke U, Vogel J, Panagiotou G, Einsele H, Westermann AJ, Schäuble S, Loeffler J (2020) Triple RNA-Seq Reveals Synergy in a Human Virus-Fungus Co-infection Model. Cell Rep 33(7), 108389. PubMed

ILRS Authors

Bastian Seelbinder

Projects

From Data to Science: A multi-Omics Analysis of the Pathobiome
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Abstract

High-throughput RNA sequencing (RNA-seq) is routinely applied to study diverse biological processes; however, when performed separately on interacting organisms, systemic noise intrinsic to RNA extraction, library preparation, and sequencing hampers the identification of cross-species interaction nodes. Here, we develop triple RNA-seq to simultaneously detect transcriptomes of monocyte-derived dendritic cells (moDCs) infected with the frequently co-occurring pulmonary pathogens Aspergillus fumigatus and human cytomegalovirus (CMV). Comparing expression patterns after co-infection with those after single infections, our data reveal synergistic effects and mutual interferences between host responses to the two pathogens. For example, CMV attenuates the fungus-mediated activation of pro-inflammatory cytokines through NF-κB (nuclear factor κB) and NFAT (nuclear factor of activated T cells) cascades, while A. fumigatus impairs viral clearance by counteracting viral nucleic acid-induced activation of type I interferon signaling. Together, the analytical power of triple RNA-seq proposes molecular hubs in the differential moDC response to fungal/viral single infection or co-infection that contribute to our understanding of the etiology and, potentially, clearance of post-transplant infections.

Identifier

doi: S2211-1247(20)31378-4 PMID: 33207195

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