Murata, T. — Page 2 | bioRxiv Science

bioRxiv2020

Direct evidence of abortive lytic infection-mediated establishment of Epstein-Barr virus latency during B-cell infection

Viral infection induces dynamic changes in transcriptional profiles. Virus-induced and anti-viral responses are intertwined during the infection. Epstein-Barr virus (EBV) is a human gammaherpesvirus that provides a model of herpesvirus latency. To measure the transcriptome changes during the establishment of EBV latency, EBV-negative Akata cells were infected with EBV-EGFP and observed by transcriptome sequencing (RNA-seq) at 0, 2, 4, 7, 10, and 14 days after infection. We found transient downregulation of mitotic division-related genes, reflecting reprograming of cell growth by EBV. Moreover, a burst of viral lytic gene expression was detected in the early phase of infection. Experimental and mathematical investigations demonstrated that infectious virions were not produced in the pre-latent phase, suggesting the presence of an abortive lytic infection. Finally, we conducted fate mapping using recombinant EBV, enabling the noninvasive, continuous observation of infected cells during EBV infection. Our tracking analysis provided direct evidence that the abortive lytic infection in the pre-latent phase converges to latent infection during EBV infection of B-cells, shedding light on novel roles of viral lytic gene(s) in establishing latency. Author summaryViral infection is a complex process that activates both virus-triggered and host anti-viral responses. This process has classically been studied by snapshot analysis such as microarray and RNA-seq at discrete time points as population averages. Snapshot data lead to invaluable findings in host-pathogen interactions. However, these "snapshot" omics, even from a single cell, lack temporal resolution. Because the behavior of infected cells is highly dynamic and heterogenous, continuous analysis is required for deciphering the fate of infected cells during viral infection. Here, we exploited fate mapping techniques with recombinant Epstein-Barr virus (EBV) to track the infected cells and recorded a log of lytic gene expression during EBV infection. Our continuous observation of infected cells revealed that EBV established latency in B-cells via an abortive lytic infection in the pre-latent phase.

microbiology↗

bioRxiv2018

Single-cell transcriptome analysis of Physcomitrella leaf cells during reprogramming using microcapillary manipulation

BackgroundNext-generation sequencing technologies have made it possible to carry out transcriptome analysis at the single-cell level. Single-cell RNA-sequencing (scRNA-seq) data provide insights into cellular dynamics, including intercellular heterogeneity as well as inter- and intra-cellular fluctuations in gene expression that cannot be studied using populations of cells. The utilization of scRNA-seq is, however, restricted to specific types of cells that can be isolated from their original tissues, and it can be difficult to obtain precise positional information for these cells in situ.\n\nResultsHere, we established single cell-digital gene expression (1cell-DGE), a method of scRNA-seq that uses micromanipulation to extract the contents of individual living cells in intact tissue while recording their positional information. Furthermore, we employed a unique molecular identifier to reduce amplification bias in the cDNA libraries. With 1cell-DGE, we could detect differentially expressed genes (DEGs) during the reprogramming of leaf cells into stem cells in excised tissues of the moss Physcomitrella patens, identifying 6,382 DEGs between cells at 0 h and 24 h after excision. We found substantial variations in both the transcript levels of previously reported reprogramming factors and the overall expression profiles between cells, which appeared to be related to their different reprogramming abilities or the estimated states of the cells according to the pseudotime based on the transcript profiles.\n\nConclusionsWe developed 1cell-DGE with microcapillary manipulation, a technique that can be used to analyze the gene expression of individual cells without detaching them from their tightly associated tissues, enabling us to retain positional information and investigate cell-cell interactions.

plant biology↗