Search bioRxivSearch

Biology subjects

Zanini, F.

Publications and source records attributed to Zanini, F..

2 recordsLinked to original sources

Virus-inclusive single cell RNA sequencing reveals molecular signature predictive of progression to severe dengue infection

Dengue virus (DENV) infection can result in severe complications. Yet, the understanding of the molecular correlates of severity is limited, partly due to difficulties in defining the peripheral blood mononuclear cells (PBMCs) that are associated with DENV in vivo. Additionally, there are currently no biomarkers predictive of progression to severe dengue (SD). Bulk transcriptomics data are difficult to interpret because blood consists of multiple cell types that may react differently to infection. Here we applied virus-inclusive single cell RNA-seq approach (viscRNA-Seq) to profile transcriptomes of thousands of single PBMCs derived early in the course of disease from six dengue patients and four healthy controls, and to characterize distinct DENV-associated leukocytes. Multiple genes, particularly interferon response genes, were upregulated in a cell-specific manner prior to progression to SD. Expression of MX2 in naive B cells and CD163 in CD14+ CD16+ monocytes was predictive of SD. The majority of DENV-associated cells in the blood of two patients who progressed to SD were naive IgM B cells expressing the CD69 and CXCR4 receptors and antiviral genes, followed by monocytes. Bystander uninfected B cells also demonstrated immune activation, and plasmablasts from two patients exhibited antibody lineages with convergently hypermutated heavy chain sequences. Lastly, assembly of the DENV genome revealed diversity at unexpected genomic sites. This study presents a multi-faceted molecular elucidation of natural dengue infection in humans and proposes biomarkers for prediction of SD, with implications for profiling any tissue and viral infection, and for the development of a dengue prognostic assay.\n\nSignificanceA fraction of the 400 million people infected with dengue annually progresses to severe dengue (SD). Yet, there are currently no biomarkers to effectively predict disease progression. We profiled the landscape of host transcripts and viral RNA in thousands of single blood cells from dengue patients prior to progressing to SD. We discovered cell-type specific immune activation and candidate predictive biomarkers. We also revealed preferential virus association with specific cell populations, particularly naive B cells and monocytes. We then explored immune activation of bystander cells, clonality and somatic evolution of adaptive immune repertoires, and viral genomics. This multi-faceted approach could advance understanding of pathogenesis of any viral infection, map an atlas of infected cells and promote the development of prognostics.

immunology

Single-cell transcriptional dynamics of flavivirus infection

Dengue and Zika viral infections affect millions of people annually and can be complicated by hemorrhage or neurological manifestations, respectively. However, a thorough understanding of the host response to these viruses is lacking, partly because conventional approaches ignore heterogeneity in virus abundance across cells. We present viscRNA-Seq (virus-inclusive single cell RNA-Seq), an approach to probe the host transcriptome together with intracellular viral RNA at the single cell level. We applied viscRNA-Seq to monitor dengue and Zika virus infection in cultured cells and discovered extreme heterogeneity in virus abundance. We exploited this variation to identify host factors that show complex dynamics and a high degree of specificity for either virus, including proteins involved in the endoplasmic reticulum translocon, signal peptide processing, and membrane trafficking. We validated the viscRNA-Seq hits and discovered novel proviral and antiviral factors. viscRNA-Seq is a powerful approach to assess the genome-wide virus-host dynamics at single cell level.

microbiology