Time-resolved single cell genomics of human cytomegalovirus infection in myeloid cells

• Applicants: Professor Dr. Lars Dölken; Professor Dr. Florian Erhard
• Subject Area: Virology
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 511508753

The human cytomegalovirus (HCMV) persistently infects the majority of the world’s population. While HCMV infection of healthy individuals is usually subclinical, life-threatening HCMV disease is frequent among the immunocompromised. Following entry of the virus into a cell, a decision is made whether this results in lytic, latent or abortive infection. This decision is shaped by the interplay between cell-intrinsic and extrinsic factors. Moreover, HCMV expresses an armory of immune evasins to target host defense mechanisms and promote productive infection. A detailed understanding of the underlying molecular mechanism that define disparate infection outcomes, requires global analyses at single cell level. Furthermore, it has become increasingly clear that the repertoire of viral gene expression in in vitro HCMV latency models is much broader than previously appreciated. These studies have challenged the dogma of a restricted latency-associated transcription program. Here, we aim to exploit the full power of a novel single cell RNA sequencing (scRNA-seq) approach termed single cell SLAM-seq (scSLAM-seq), which we recently developed. Employing metabolic RNA labeling, chemical nucleotide conversion and advance computational analyses (GRAND-SLAM), scSLAM-seq adds a temporal dimension to scRNA-seq and facilitates dose-response analysis at single cell level. Based on time-course scSLAM-seq analysis from HCMV infected primary human macrophages and monocytes from healthy donors, we will exploit the extensive intercellular heterogeneity that is present at single cell level, and utilize novel random barcode reporter viruses to perform combined loss- and gain-of-function screens. We will thereby identify novel host factors and how their interplay in the regulatory network governs the infection outcome in myeloid cells. We will characterize interesting candidates using functional assays and decipher the true latent HCMV transcriptome. In summary, this work will provide a comprehensive functional understanding of HCMV infection outcomes at the single cell level and pioneer exciting new methodology with broad applicability in biomedical sciences.

• DFG Programme: Research Grants