Imputation of single-cell transcriptome data enables the reconstruction of networks predictive of breast cancer metastasis.

Single-cell transcriptome data provide a unique opportunity to explore the gene networks of a particular cell type. However, insufficient capture rate and high dimensionality of single-cell RNA sequencing (scRNA-seq) data challenge cell-type-specific gene network (CGN) reconstruction. Here, we demonstrated that the imputation of scRNA-seq data enables reconstruction of CGNs by effective retrieval of gene functional associations. We reconstructed CGNs for seven primary and nine metastatic breast cancer cell lines using scRNA-seq data with imputation. Key genes for primary or metastatic cell lines were prioritized based on network centrality measures and CGN hub genes that were presumed to be the major determinant of cell type characteristics. To identify novel genes in breast cancer metastasis, we used the average rank difference of centrality between the primary and metastatic cell lines. Genes predicted using CGN centrality analysis were more enriched for known breast cancer metastatic genes than those predicted using differential expression. The molecular chaperone CCT2 was identified as a novel gene for breast metastasis during knockdown assays of several candidate genes. Overall, our study demonstrated an effective CGN reconstruction technique with imputation of scRNA-seq data and the feasibility of identifying key genes for particular cell subsets using single-cell network analysis.

Molecular characterization of human cytomegalovirus infection with single-cell transcriptomics.

Human cytomegalovirus (HCMV) can result in either productive or non-productive infection, with the latter potentially leading to viral latency. The molecular factors dictating these outcomes are poorly understood. Here we used single-cell transcriptomics to analyse HCMV infection progression in monocytes, which are latently infected, and macrophages, considered to be permissive for productive infection. We show that early viral gene expression levels, specifically of those encoding immediate early proteins IE1 and IE2, are a major factor dictating productive infection. We also revealed that intrinsic, not induced, host cell interferon-stimulated gene expression level is a main determinant of infection outcome. Intrinsic interferon-stimulated gene expression is downregulated with monocyte to macrophage differentiation, partially explaining increased macrophage susceptibility to productive HCMV infection. Furthermore, non-productive macrophages could reactivate, making them potential latent virus reservoirs. Overall, we decipher molecular features underlying HCMV infection outcomes and propose macrophages as a potential HCMV reservoir.

Temporal dynamics of HCMV gene expression in lytic and latent infections.

During productive human cytomegalovirus (HCMV) infection, viral genes are expressed in a coordinated cascade that conventionally relies on the dependencies of viral genes on protein synthesis and viral DNA replication. By contrast, the transcriptional landscape of HCMV latency is poorly understood. Here, we examine viral gene expression dynamics during the establishment of both productive and latent HCMV infections. We redefine HCMV gene expression kinetics during productive infection and reveal that viral gene regulation does not represent a simple sequential cascade; many viral genes are regulated by multiple independent modules. Using our improved gene expression classification combined with transcriptome-wide measurements of the effects of a wide array of epigenetic inhibitors on viral gene expression during latency, we show that a defining feature of latency is the unique repression of immediate-early (IE) genes. Altogether, we recharacterize HCMV gene expression kinetics and reveal governing principles of lytic and latent gene expression.

Single cell analysis reveals human cytomegalovirus drives latently infected cells towards an anergic-like monocyte state.

Human cytomegalovirus (HCMV) causes a lifelong infection through establishment of latency. Although reactivation from latency can cause life-threatening disease, our molecular understanding of HCMV latency is incomplete. Here we use single cell RNA-seq analysis to characterize latency in monocytes and hematopoietic stem and progenitor cells (HSPCs). In monocytes, we identify host cell surface markers that enable enrichment of latent cells harboring higher viral transcript levels, which can reactivate more efficiently, and are characterized by reduced intrinsic immune response that is important for viral gene expression. Significantly, in latent HSPCs, viral transcripts could be detected only in monocyte progenitors and were also associated with reduced immune-response. Overall, our work indicates that regardless of the developmental stage in which HCMV infects, HCMV drives hematopoietic cells towards a weaker immune-responsive monocyte state and that this anergic-like state is crucial for the virus ability to express its transcripts and to eventually reactivate.

Most people around the world unknowingly carry the human cytomegalovirus, as this virus can become dormant after infection and hide in small numbers of blood stem cells (which give rise to blood and immune cells). Dormant viruses still make their host cells read their genetic information and create viral proteins ­ a process known as gene expression ­ but they do not use them to quickly multiply. However, it is possible for the cytomegalovirus to reawaken at a later stage and start replicating again, which can be fatal for people with weakened immune systems. It is therefore important to understand exactly how the virus can stay dormant, and how it reactivates. Only certain infected cells allow dormant viruses to later reactivate; in others, it never starts to multiply again. Techniques that can monitor individual cells are therefore needed to understand how the host cells and the viruses interact during dormant infection and reactivation. To investigate this, Shnayder et al. infected blood stem cells in the laboratory and used a method known as single-cell RNA analysis, which highlights all the genes (including viral genes) that are expressed in a cell. This showed that in certain cells, the virus dampens the cell defenses, leading to a higher rate of viral gene expression and, in turn, easier reactivation. Further experiments showed that the blood stem cells that expressed the viral genes were marked to become a type of immune cells known as monocytes. In turn, these infected monocytes were shown to be less able to defend the body against infection, suggesting that latent human cytomegalovirus suppresses the body's innate immune response. The reactivation of human cytomegalovirus is a dangerous issue for patients who have just received an organ or blood stem cells transplant. The study by Shnayder et al. indicates that treatments that boost innate immunity may help to prevent the virus from reawakening, but more work is needed to test this theory.