High-dimensional CyTOF analysis of dengue virus–infected human DCs reveals distinct viral signatures

Hamlin, Rebecca E.; Rahman, Adeeb; Pak, Theodore R.; Maringer, Kevin; Mena, Ignacio; Bernal-Rubio, Dabeiba; Potla, Uma; Fredericks, Anthony C.; Amir, El-ad David; Kasarskis, Andrew; Ramos, Irene; Mérad, Miriam; Fernández-Sesma, Ana

doi:10.1172/jci.insight.92424

Cited by 31 publications

(30 citation statements)

References 75 publications

(105 reference statements)

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“…Genotype II is the predominant genotype in Indonesia and the only genotype of DENV‐4 that appears to be currently circulating (Figure ). Genotype III of DENV‐4 was sampled between 1976 and 1977 and had not been reported in Indonesia subsequently until a recent study sampled a virus of this genotype from patient plasma collected in 2009 from Jakarta …”

Section: Resultsmentioning

confidence: 99%

Dengue viruses circulating in Indonesia: A systematic review and phylogenetic analysis of data from five decades

Harapan

Michie

Yohan

et al. 2019

Reviews in Medical Virology

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Although epidemiological and molecular epidemiological (serotype, genotype, and lineage information) data are available for several major cities in Indonesia, there is yet to be a comprehensive national study of dengue in Indonesia over time. This study was conducted to provide a comprehensive epidemiology of circulating dengue viruses (DENV) in Indonesia between 1973 and 2016. This was conducted through a systematic review of the literature and phylogenetic analysis of available DENV sequences. Available data from National Disease Surveillance System have indicated an increasing trend of dengue incidence in Indonesia over the past 50 years. Incidence rates appear to be cyclic, peaking approximately every 6 to 8 years. In contrast, the case fatality rate has decreased approximately by half with each decade since 1980.Over this 50-year time span, serotype shifts, genotype displacement within DENV-1 and DENV-2, and introduction of DENV-1 and DENV-3 genotype from other countries occurred. These events were associated with increased incidence of dengue cases. Our study also provides a valuable national snapshot of DENV genetic diversity in Indonesia that may contribute to development of more effective dengue vaccine compositions for the region.

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Section: Resultsmentioning

confidence: 99%

Dengue viruses circulating in Indonesia: A systematic review and phylogenetic analysis of data from five decades

Harapan

Michie

Yohan

et al. 2019

Reviews in Medical Virology

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“…Findings with influenza virus, poliovirus, dengue virus (DENV) and Zika virus (ZIKV) have revealed extensive variation in viral RNA abundance within single cells (29–31). Using high dimensional mass cytometry by time-of-flight (CyTOF) analysis, others have described differences in IFN-induced and pro-inflammatory cytokine production in infected and bystander human dendritic cells following DENV infection (32). Studies examining IFN-I induction at the single-cell level have used fluorescently-tagged cells, single-mRNA molecule in situ hybridization, single-cell quantitative PCR (qPCR), and single-cell RNA sequencing (scRNA-seq) (16–19, 27, 33).…”

Section: Introductionmentioning

confidence: 99%

West Nile virus-inclusive single-cell RNA sequencing reveals heterogeneity in the type I interferon response within single cells

O’Neal

Upadhyay

Wolabaugh

et al. 2018

Preprint

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232 words; Importance: 122 words; and Text: 4,850 words. 22 ABSTRACT 23West Nile virus (WNV) is a neurotropic mosquito-borne flavivirus of global importance. 24Neuroinvasive WNV infection results in encephalitis and can lead to prolonged 25 neurological impairment or death. Type I interferon (IFN-I) is crucial for promoting 26 antiviral defenses through the induction of antiviral effectors, which function to restrict 27 viral replication and spread. However, our understanding of the antiviral response to 28 WNV infection is mostly derived from analysis of bulk cell populations. It is becoming 29 increasingly apparent that substantial heterogeneity in cellular processes exists among 30 individual cells, even within a seemingly homogenous cell population. Here, we present 31 WNV-inclusive single-cell RNA sequencing (scRNA-seq), an approach to examine the 32 transcriptional variation and viral RNA burden across single cells. We observed that 33 only a few cells within the bulk population displayed robust transcription of IFN-β mRNA, 34 and this did not appear to depend on viral RNA abundance within the same cell. 35 Furthermore, we observed considerable transcriptional heterogeneity in the IFN-I 36 response, with genes displaying high unimodal and bimodal expression patterns. 37 Broadly, IFN-stimulated genes negatively correlated with viral RNA abundance, 38 corresponding with a precipitous decline in expression in cells with high viral RNA levels. 39 Altogether, we demonstrated the feasibility and utility of WNV-inclusive scRNA-seq as a 40 high-throughput technique for single-cell transcriptomics and WNV RNA detection. This 41 approach can be implemented in other models to provide insights into the cellular 42 features of protective immunity and identify novel therapeutic targets. 43 44 45 IMPORTANCE 46 West Nile virus (WNV) is a clinically relevant pathogen responsible for recurrent 47 epidemics of neuroinvasive disease. Type I interferon is essential for promoting an 48 antiviral response against WNV infection; however, it is unclear how heterogeneity in 49 the antiviral response at the single-cell level impacts viral control. Specifically, 50 conventional approaches lack the ability to distinguish differences across cells with 51 varying viral abundance. The significance of our research is to demonstrate a new 52 technique for studying WNV infection at the single-cell level. We discovered extensive 53 variation in antiviral gene expression and viral abundance across cells. This protocol 54 can be applied to primary cells or in vivo models to better understand the underlying 55 cellular heterogeneity following WNV infection for the development of targeted 56 therapeutic strategies. 57 58 59 60 61

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“…In recent years, we witnessed an exponential growth in high‐dimensional (HD) technologies, which resulted in a wide range of medical and biological applications. HD cytometers such as mass cytometry (Cytometry by time of flight, CyTOF) and flow cytometry (hereafter termed HDcyto) can detect more than 40 parameters (with the promise for detection of up to 100 parameters) with single‐cell resolution.…”

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confidence: 99%

The end of omics? High dimensional single cell analysis in precision medicine

et al. 2019

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High-dimensional single-cell (HDcyto) technologies, such as mass cytometry (CyTOF) and flow cytometry, are the key techniques that hold a great promise for deciphering complex biological processes. During the last decade, we witnessed an exponential increase of novel HDcyto technologies that are able to deliver an in-depth profiling in different settings, such as various autoimmune diseases and cancer. The concurrent advance of custom data-mining algorithms has provided a rich substrate for the development of novel tools in translational medicine research. HDcyto technologies have been successfully used to investigate cellular cues driving pathophysiological conditions, and to identify disease-specific signatures that may serve as diagnostic biomarkers or therapeutic targets. These technologies now also offer the possibility to describe a complete cellular environment, providing unanticipated insights into human biology. In this review, we present an update on the current cutting-edge HDcyto technologies and their applications, which are going to be fundamental in providing further insights into human immunology and pathophysiology of various diseases. Importantly, we further provide an overview of the main algorithms currently available for data mining, together with the conceptual workflow for high-dimensional cytometric data handling and analysis. Overall, this review aims to be a handy overview for immunologists on how to design, develop and read HDcyto data.Keywords: bioinformatic tools r diagnostic biomarkers r flow cytometry r mass cytometry (CyTOF) r single cell analysisIn recent years, we witnessed an exponential growth in highdimensional (HD) technologies, which resulted in a wide range of medical [1][2][3][4][5][6][7][8][9][10][11] and biological [12][13][14] applications. HD cytometers such as mass cytometry (Cytometry by time of flight, CyTOF) and flow cytometry (hereafter termed HDcyto) can detect more than 40 parameters (with the promise for detection of up to 100 parameters) with single-cell resolution. The data produced by HDcyto techniques together with appropriate computational methods of analysis have initiated a new era for translational medicine, enabling the unsupervised discovery of new cell pop-

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High-dimensional CyTOF analysis of dengue virus–infected human DCs reveals distinct viral signatures

Cited by 31 publications

References 75 publications

Dengue viruses circulating in Indonesia: A systematic review and phylogenetic analysis of data from five decades

Dengue viruses circulating in Indonesia: A systematic review and phylogenetic analysis of data from five decades

West Nile virus-inclusive single-cell RNA sequencing reveals heterogeneity in the type I interferon response within single cells

The end of omics? High dimensional single cell analysis in precision medicine

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