ArticlePLoS pathogens2019
Unmasking cellular response of a bloom-forming alga to viral infection by resolving expression profiles at a single-cell level.
Article in PLoS pathogens, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 24 citations in OpenAlex.
- Cell-to-cell heterogeneity drives host-virus coexistence in a bloom-forming alga.The ISME journal · 2024Article
- Marine Polymer-Gels' Relevance in the Atmosphere as Aerosols and CCN.Gels (Basel, Switzerland) · 2021Review
- An Emiliania huxleyi pan-transcriptome reveals basal strain specificity in gene expression patterns.Scientific reports · 2021Article
- Modeling poliovirus replication dynamics from live time-lapse single-cell imaging data.Scientific reports · 2021Article
- Visualizing active viral infection reveals diverse cell fates in synchronized algal bloom demise.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Microfluidics in Single-Cell Virology: Technologies and Applications.Trends in biotechnology · 2020Review
- A single-cell view on alga-virus interactions reveals sequential transcriptional programs and infection states.Science advances · 2020Article
- Metabolic and biogeochemical consequences of viral infection in aquatic ecosystems.Nature reviews. Microbiology · 2020Review
- Single Cell Metabolomics: A Future Tool to Unmask Cellular Heterogeneity and Virus-Host Interaction in Context of Emerging Viral Diseases.Frontiers in microbiology · 2020Review
- Single cell ecology.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
- Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
- Morphological switch to a resistant subpopulation in response to viral infection in the bloom-forming coccolithophore Emiliania huxleyi.PLoS pathogens · 2017Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Infection by large dsDNA viruses can lead to a profound alteration of host transcriptome and metabolome in order to provide essential building blocks to support the high metabolic demand for viral assembly and egress. Host response to viral infection can typically lead to diverse phenotypic outcome that include shift in host life cycle and activation of anti-viral defense response. Nevertheless, there is a major bottleneck to discern between viral hijacking strategies and host defense responses when averaging bulk population response. Here we study the interaction between Emiliania huxleyi, a bloom-forming alga, and its specific virus (EhV), an ecologically important host-virus model system in the ocean. We quantified host and virus gene expression on a single-cell resolution during the course of infection, using automatic microfluidic setup that captures individual algal cells and multiplex quantitate PCR. We revealed high heterogeneity in viral gene expression among individual cells. Simultaneous measurements of expression profiles of host and virus genes at a single-cell level allowed mapping of infected cells into newly defined infection states and allowed detection specific host response in a subpopulation of infected cell which otherwise masked by the majority of the infected population. Intriguingly, resistant cells emerged during viral infection, showed unique expression profiles of metabolic genes which can provide the basis for discerning between viral resistant and susceptible cells within heterogeneous populations in the marine environment. We propose that resolving host-virus arms race at a single-cell level will provide important mechanistic insights into viral life cycles and will uncover host defense strategies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.