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Kitagawa, K.

Publications and source records attributed to Kitagawa, K..

2 recordsLinked to original sources

Two strategies underlying the trade-off of hepatitis C virus proliferation: stay-at-home or leaving-home?

Viruses proliferate through both genome replication inside infected cells and transmission to new target cells or to new hosts. Each viral genome molecule in infected cells is used either for amplifying the intracellular genome as a template (\"stay-at-home strategy\") or for packaging into progeny virions to be released extracellularly (\"leaving-home strategy\"). The balance between these strategies is important for both initial growth and transmission of viruses. In this study, we used hepatitis C virus (HCV) as a model system to study the functions of viral genomic RNA in both RNA replication in cells and in progeny virus assembly and release. Using viral infection assays combined with mathematical modelling, we characterized the dynamics of two different HCV strains (JFH-1, a clinical isolate, and Jc1-n, a laboratory strain), which have different viral assembly and release characteristics. We found that 1.27% and 3.28% of JFH-1 and Jc1-n intracellular viral RNAs, respectively, are used for producing and releasing progeny virions. Analysis of the Malthusian parameter of the HCV genome (i.e., initial growth rate) and the number of de novo infections (i.e., initial transmissibility) suggests that the leaving-home strategy provides a higher level of initial transmission for Jc1-n, while, in contrast, the stay-at-home strategy provides a higher initial growth rate for JFH-1. Thus, theoretical-experimental analysis of viral dynamics enables us to better understand the proliferation strategies of viruses. Ours is the first study to analyze stay-leave trade-offs during the viral life cycle and their significance for viral proliferation.

evolutionary biology

Single-cell RNA Profiling Identifies Diverse Cellular Responses to EWSR1-FLI1 Down-regulation in Ewing Sarcoma

Single-cell analyses provide insight into time dependent behaviors in response to dynamic changes of oncogene expression. We developed an unbiased approach to study gene expression variation using a model of cellular dormancy induced via EWSR1-FLI1 down-regulation in Ewing sarcoma (EWS) cells. We propose that variation in the expression of EWSR1-FLI1 over time determines cellular responses. Cell state and functions were assigned using random forest feature selection in combination with machine learning. Notably, three distinct expression profiles were uncovered contributing to Ewing sarcoma cell heterogeneity. Our predictive model identified [~]1% cells in a dormant-like state and [~]2-4% with higher stem-like and neural stem-like features in an exponentially proliferating EWS cell line and EWS xenografts. Following oncogene knockdown, cells re-entering the proliferative cycle have greater stem-like properties, whereas for those remaining quiescent, FAM134B-dependent dormancy provides a survival mechanism. We also show cell cycle heterogeneity related to EWSR1-FLI1 expression as an independent feature driving cancer heterogeneity, and drug resistance.\n\nSIGNIFICANCEWe show that time-dependent changes induced by suppression of oncogenic EWSR1-FLI1 induces dormancy, with different subpopulation dynamics, including stem-like characteristics and prolonged dormancy. Cells with these characteristics are identified in exponentially growing cell populations and confer drug resistance, and could potentially contribute to metastasis or late recurrence in patients.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC=\"FIGDIR/small/750539v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (24K):\norg.highwire.dtl.DTLVardef@6a5449org.highwire.dtl.DTLVardef@c39124org.highwire.dtl.DTLVardef@16e0a45org.highwire.dtl.DTLVardef@1644614_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology