Persistent RNA virus infection is short-lived at the single-cell level but leaves transcriptomic footprints

2021 ◽  
Vol 218 (10) ◽  
Author(s):  
Peter Reuther ◽  
Katrin Martin ◽  
Mario Kreutzfeldt ◽  
Matias Ciancaglini ◽  
Florian Geier ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Persistent Infection ◽  
Rna Virus ◽  
Intrinsic Clearance ◽  
Viral Clearance ◽  
Type I ◽  
Matrix Remodeling ◽  
Single Cell Level ◽  
Cell Level

Several RNA viruses can establish life-long persistent infection in mammalian hosts, but the fate of individual virus-infected cells remains undefined. Here we used Cre recombinase–encoding lymphocytic choriomeningitis virus to establish persistent infection in fluorescent cell fate reporter mice. Virus-infected hepatocytes underwent spontaneous noncytolytic viral clearance independently of type I or type II interferon signaling or adaptive immunity. Viral clearance was accompanied by persistent transcriptomic footprints related to proliferation and extracellular matrix remodeling, immune responses, and metabolism. Substantial overlap with persistent epigenetic alterations in HCV-cured patients suggested a universal RNA virus-induced transcriptomic footprint. Cell-intrinsic clearance occurred in cell culture, too, with sequential infection, reinfection cycles separated by a period of relative refractoriness to infection. Our study reveals that systemic persistence of a prototypic noncytolytic RNA virus depends on continuous spread and reinfection. Yet undefined cell-intrinsic mechanisms prevent viral persistence at the single-cell level but give way to profound transcriptomic alterations in virus-cleared cells.

scholarly journals Single-Cell Transcriptome Analysis as a Promising Tool to Study Pluripotent Stem Cell Reprogramming

2021 ◽  
Vol 22 (11) ◽  
pp. 5988
Author(s):  
Hyun Kyu Kim ◽  
Tae Won Ha ◽  
Man Ryul Lee
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Cell Fate ◽  
Human Cell ◽  
Transcriptome Analysis ◽  
Single Cell Analysis ◽  
Embryonic Stem ◽  
Single Cell Level ◽  
Cell Analysis ◽  
Cell Level

Cells are the basic units of all organisms and are involved in all vital activities, such as proliferation, differentiation, senescence, and apoptosis. A human body consists of more than 30 trillion cells generated through repeated division and differentiation from a single-cell fertilized egg in a highly organized programmatic fashion. Since the recent formation of the Human Cell Atlas consortium, establishing the Human Cell Atlas at the single-cell level has been an ongoing activity with the goal of understanding the mechanisms underlying diseases and vital cellular activities at the level of the single cell. In particular, transcriptome analysis of embryonic stem cells at the single-cell level is of great importance, as these cells are responsible for determining cell fate. Here, we review single-cell analysis techniques that have been actively used in recent years, introduce the single-cell analysis studies currently in progress in pluripotent stem cells and reprogramming, and forecast future studies.

scholarly journals Visualization of phage DNA degradation by a type I CRISPR-Cas system at the single-cell level

2017 ◽  
Vol 5 (1) ◽  
pp. 67-75 ◽  
Author(s):  
Jingwen Guan ◽  
Xu Shi ◽  
Roberto Burgos ◽  
Lanying Zeng
Keyword(s):  
Single Cell ◽  
Dna Degradation ◽  
Type I ◽  
Single Cell Level ◽  
Cell Level ◽  
Phage Dna

T Cell Fate at the Single-Cell Level

2016 ◽  
Vol 34 (1) ◽  
pp. 65-92 ◽  
Author(s):  
Veit R. Buchholz ◽  
Ton N.M. Schumacher ◽  
Dirk H. Busch
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Cell Fate ◽  
Single Cell Level ◽  
Cell Level

In vivo MRI of cancer cell fate at the single-cell level in a mouse model of breast cancer metastasis to the brain

2006 ◽  
Vol 56 (5) ◽  
pp. 1001-1010 ◽  
Author(s):  
Chris Heyn ◽  
John A. Ronald ◽  
Soha S. Ramadan ◽  
Jonatan A. Snir ◽  
Andrea M. Barry ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mouse Model ◽  
Single Cell ◽  
Cell Fate ◽  
Cancer Metastasis ◽  
Breast Cancer Metastasis ◽  
Single Cell Level ◽  
Cell Level ◽  
The Brain

scholarly journals Single cell infection with influenza A virus using drop-based microfluidics

2021 ◽  
Author(s):  
Emma Kate Loveday ◽  
Humberto S. Sanchez ◽  
Mallory M. Thomas ◽  
Connie B. Chang
Keyword(s):  
Single Cell ◽  
Influenza A Virus ◽  
Influenza A ◽  
Single Cell Analysis ◽  
Rna Virus ◽  
Host Cells ◽  
Single Cell Level ◽  
Cell Infection ◽  
Cell Level ◽  
High Genetic Diversity

SummaryInfluenza A virus (IAV) is an RNA virus with high genetic diversity which necessitates the development of new vaccines targeting emerging mutations each year. As IAV exists in genetically heterogeneous populations, current studies focus on understanding population dynamics at the single cell level. These studies include novel methodology that can be used for probing populations at the single cell level, such as single cell sequencing and microfluidics. Here, we introduce a drop-based microfluidics method to study IAV infection at a single cell level by isolating infected host cells in microscale drops. Single human alveolar basal epithelial (A549), Madin-Darby Canine Kidney cells (MDCK) and MDCK + human siat7e gene (Siat7e) cells infected with the pandemic A/California/07/2009 (H1N1) strain were encapsulated within 50 μm radii drops and incubated at 37°C. We demonstrate that drops remain stable over 24 hours, that 75% of cells remain viable, and that IAV virus can propagate within the drops. Drop-based microfluidics therefore enables single cell analysis of viral populations produced from individually infected cells.

scholarly journals Tracking Single Cells Motility on Different Substrates

2020 ◽  
Vol 3 (3) ◽  
pp. 56
Author(s):  
Pooja Sharma ◽  
Van K. Lam ◽  
Christopher B. Raub ◽  
Byung Min Chung
Keyword(s):  
Cell Motility ◽  
Single Cell ◽  
Cancer Metastasis ◽  
Type I Collagen ◽  
Single Cells ◽  
Cost Effective ◽  
Type I ◽  
Single Cell Level ◽  
Cell Level ◽  
Average Cell

Motility is a key property of a cell, required for several physiological processes, including embryonic development, axon guidance, tissue regeneration, gastrulation, immune response, and cancer metastasis. Therefore, the ability to examine cell motility, especially at a single cell level, is important for understanding various biological processes. Several different assays are currently available to examine cell motility. However, studying cell motility at a single cell level can be costly and/or challenging. Here, we describe a method of tracking random cell motility on different substrates such as glass, tissue-culture polystyrene, and type I collagen hydrogels, which can be modified to generate different collagen network microstructures. In this study we tracked MDA-MB-231 breast cancer cells using The CytoSMARTTM System (Lonza Group, Basel, Switzerland) for live cell imaging and assessed the average cell migration speed using ImageJ and wrMTrck plugin. Our cost-effective and easy-to-use method allows studying cell motility at a single cell level on different substrates with varying degrees of stiffness and varied compositions. This procedure can be successfully performed in a highly accessible manner with a simple setup.

scholarly journals Single cell transcriptomics view of cell lineage, cell fate and cellular differentiation

2017 ◽  
Author(s):  
Wenfa Ng
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Fate ◽  
Cellular Differentiation ◽  
Cell Types ◽  
Rna Degradation ◽  
Single Cell Level ◽  
Cell Level ◽  
Single Cell Rna Sequencing ◽  
A Cell

Single cell studies increasing reveal myriad cellular subtypes beyond those postulated or observed through optical and fluorescence microscopy as well as DNA sequencing studies. While gene sequencing at the single cell level offer a path towards illuminating, in totality, the different subtypes of cells present, the technique nevertheless does not offer answers concerning the functional repertoire of the cell, which is defined by the collection of RNA transcribed from the genome. Known as the transcriptome, transcribed RNA defines the function of the cell as proteins or effector RNA molecules, while the genome is the collection of all information endowed in the cell type, expressed or not. Thus, a particular cell state, lineage, cell fate or cellular differentiation is more fully depicted by transcriptomic analysis compared to delineating the genomic context at the single cell level. While conceptually sound and could be analysed by contemporary single cell RNA sequencing technology and data analysis pipelines, the relative instability of RNA in view of RNase in the environment would make sample preparation particularly challenging, where degradation of cellular RNA by extraneous factors could provide a misinterpretation of specific functions available to a cell type. Hence, RNA as the de facto functional molecule of the cell defining the proteomics landscape as well as effector RNA repertoire, meant that RNA transcriptomics at the single cell level is the way forward if the goal is to understand all available cell types, lineage, cell fate and cellular differentiation. Given that a cell state is defined by the functions encoded by functional molecules such as proteins and RNA, single cell RNA sequencing offers a larger contextual basis for understanding cellular decision making and functions, for example, proteins are increasingly known to work in concert with RNA effector molecules in enabling a function. Hence, providing a view of the diverse cell types and lineages present in a body, single cell RNA sequencing is only hampered by the high sensitivity required to analyse the small amount of RNA available in single cells, as well as the perennial problem of RNA studies: how to prevent or reduce RNA degradation by environmental RNase enzymes. Ability to reduce RNA degradation would provide the cell biologist a unique view of the functional landscape of different cells in the body through the language of RNA.

scholarly journals Single cell transcriptomics view of cell lineage, cell fate and cellular differentiation

2017 ◽  
Author(s):  
Wenfa Ng
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Fate ◽  
Cellular Differentiation ◽  
Cell Types ◽  
Rna Degradation ◽  
Single Cell Level ◽  
Cell Level ◽  
Single Cell Rna Sequencing ◽  
A Cell

Single cell studies increasing reveal myriad cellular subtypes beyond those postulated or observed through optical and fluorescence microscopy as well as DNA sequencing studies. While gene sequencing at the single cell level offer a path towards illuminating, in totality, the different subtypes of cells present, the technique nevertheless does not offer answers concerning the functional repertoire of the cell, which is defined by the collection of RNA transcribed from the genome. Known as the transcriptome, transcribed RNA defines the function of the cell as proteins or effector RNA molecules, while the genome is the collection of all information endowed in the cell type, expressed or not. Thus, a particular cell state, lineage, cell fate or cellular differentiation is more fully depicted by transcriptomic analysis compared to delineating the genomic context at the single cell level. While conceptually sound and could be analysed by contemporary single cell RNA sequencing technology and data analysis pipelines, the relative instability of RNA in view of RNase in the environment would make sample preparation particularly challenging, where degradation of cellular RNA by extraneous factors could provide a misinterpretation of specific functions available to a cell type. Hence, RNA as the de facto functional molecule of the cell defining the proteomics landscape as well as effector RNA repertoire, meant that RNA transcriptomics at the single cell level is the way forward if the goal is to understand all available cell types, lineage, cell fate and cellular differentiation. Given that a cell state is defined by the functions encoded by functional molecules such as proteins and RNA, single cell RNA sequencing offers a larger contextual basis for understanding cellular decision making and functions, for example, proteins are increasingly known to work in concert with RNA effector molecules in enabling a function. Hence, providing a view of the diverse cell types and lineages present in a body, single cell RNA sequencing is only hampered by the high sensitivity required to analyse the small amount of RNA available in single cells, as well as the perennial problem of RNA studies: how to prevent or reduce RNA degradation by environmental RNase enzymes. Ability to reduce RNA degradation would provide the cell biologist a unique view of the functional landscape of different cells in the body through the language of RNA.

scholarly journals Mechanistic models of signaling pathways deconvolute the glioblastoma single-cell functional landscape

NAR Cancer ◽  
2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Matías M Falco ◽  
María Peña-Chilet ◽  
Carlos Loucera ◽  
Marta R Hidalgo ◽  
Joaquín Dopazo
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Large Degree ◽  
Mechanistic Modeling ◽  
Therapeutic Interventions ◽  
Single Cell Level ◽  
Cell Level ◽  
Cell Fate Decisions ◽  
Cancer Hallmarks ◽  
Definition Of

Abstract Single-cell RNA sequencing is revealing an unexpectedly large degree of heterogeneity in gene expression levels across cell populations. However, little is known on the functional consequences of this heterogeneity and the contribution of individual cell fate decisions to the collective behavior of the tissues these cells are part of. Here, we use mechanistic modeling of signaling circuits, which reveals a complex functional landscape at single-cell level. Different clusters of neoplastic glioblastoma cells have been defined according to their differences in signaling circuit activity profiles triggering specific cancer hallmarks, which suggest different functional strategies with distinct degrees of aggressiveness. Moreover, mechanistic modeling of effects of targeted drug inhibitions at single-cell level revealed, how in some cells, the substitution of VEGFA, the target of bevacizumab, by other expressed proteins, like PDGFD, KITLG and FGF2, keeps the VEGF pathway active, insensitive to the VEGFA inhibition by the drug. Here, we describe for the first time mechanisms that individual cells use to avoid the effect of a targeted therapy, providing an explanation for the innate resistance to the treatment displayed by some cells. Our results suggest that mechanistic modeling could become an important asset for the definition of personalized therapeutic interventions.

scholarly journals Single-Cell RNA Sequencing Reveals the Heterogeneity of Tumor-Associated Macrophage in Non-Small Cell Lung Cancer and Differences Between Sexes

2021 ◽  
Vol 12 ◽  
Author(s):  
Qi Yang ◽  
Hongman Zhang ◽  
Ting Wei ◽  
Anqi Lin ◽  
Yueqin Sun ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Single Cell ◽  
Cell Lung Cancer ◽  
Early Stage ◽  
Small Cell ◽  
Matrix Remodeling ◽  
Single Cell Level ◽  
Small Cell Lung ◽  
Cell Level

Non-Small Cell Lung Cancer (NSCLC) is a disease with high morbidity and mortality, which has sex-related differences in prognosis and immunotherapy efficacy. However, the difference in the mechanisms remains unclear. Macrophages, characterized by high plasticity and heterogeneity, act as one of the key cells that exert anti-tumor effects in the tumor microenvironment (TME) and play a complicated role in the process of tumor progression. To elucidate the subtype composition and functional heterogeneity of tumor-associated macrophages (TAMs) in NSCLC and further compare the sex-mediated differences, we conducted a single-cell level analysis in early-stage smoking NSCLC patients, combined with ssGSEA analysis, pseudotime ordering, and SCENIC analysis. We found two universally presented immune-suppressive TAMs with different functional and metabolic characteristics in the TME of NSCLC. Specifically, CCL18+ macrophages exerted immune-suppressive effects by inhibiting the production of inflammatory factors and manifested high levels of fatty acid oxidative phosphorylation metabolism. Conversely, the main metabolism pathway for SPP1+ macrophage was glycolysis which contributed to tumor metastasis by promoting angiogenesis and matrix remodeling. In terms of the differentially expressed genes, the complement gene C1QC and the matrix remodeling relevant genes FN1 and SPP1 were differentially expressed in the TAMs between sexes, of which the male upregulated SPP1 showed the potential as an ideal target for adjuvant immunotherapy and improving the efficacy of immunotherapy. According to the early-stage TCGA-NSCLC cohort, high expression of the above three genes in immune cells were associated with poor prognosis and acted as independent prognostic factors. Moreover, through verification at the transcription factor, transcriptome, and protein levels, we found that TAMs from women showed stronger immunogenicity with higher interferon-producing and antigen-presenting ability, while men-derived TAMs upregulated the PPARs and matrix remodeling related pathways, thus were more inclined to be immunosuppressive. Deconstruction of the TAMs at the single-cell level deepens our understanding of the mechanism for tumor occurrence and progress, which could be helpful to achieve the precise sex-specific tumor treatment sooner.

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