Table 1.

Applications of single-cell microfluidics in virology

Application	Microfluidic technology	Throughput (No. of cells)	Virus of interest	Description	Reference(s)
Viral infection dynamics	Trap array, customized	Up to 700	HIV	Drug-specific patterns of noisy HIV activation dynamics were revealed	[28]
	Microwells, customized	2000~3000	VSV	Interferential effects of defective interfering particles (DIPs) on viral infection were characterized	[30,31]
				Innate immune activation by VSV infection was quantitative profiled	[34]
	Valves, customized	1000~2000	PV	Viral and host factors independently contributed to the cell-to-cell variation of infection outcomes	[35]
		~5000	PV	Single-cell analysis of antiviral therapeutics revealed more than efficacy	[39]
Transcriptome analysis	Microwells, customized	600~700	HPV	Diversity of HPV-18 expression and splicing at the single-cell level was characterized	[43]
	Valves, Fluidigm C1	Up to 800	EhV201	Heterogeneity in viral gene expression was unmasked to map cells into their infection state	[46]
			ZIKV	Expression analysis revealed a candidate ZIKV entry receptor in neural stem cells	[47]
				Neuroepithelial stem cells were characterized to model ZIKV-induced pathogenesis	[48]
			HIV	Cellular markers of HIV permissiveness were revealed by single-cell RNA-sequencing	[49]
				A 134-gene-specific transcriptional signature for the HIV-inducible cell was identified	[50]
	Droplets, Drop-seq (open-source)	Thousands	HSV-1	Activation of anti-viral and developmental programs were revealed in distinct sub-populations	[55]
				In a subpopulation of infected-cell, NRF2 was activated, which restrict HSV-1 infection	[56]
	Droplets, 10X Genomics	Tens of thousands	ZIKV	An immunocompetent mouse model of ZIKV infection was established	[60]
			HIV	Host transcriptional factors associated with HIV downregulation were identified	[61]
			IAV	Extremely wide cell-to-cell variation in viral gene expression was observed	[62]
				Innate immune response to IAV in the respiratory epithelium was investigated at the single-cell level	[63]
				A common pattern of IAV gene expression IAV heterogeneity that governs the antiviral response was revealed	[64]
				Impact of defective virus genomes on host cell responses was evaluated	[65]
				PacBio sequencing was used to assess how viral mutations contribute to the heterogeneity in immune activation	[66]
			IBV	A cell population that can survive IBV infection was found to maintain epithelial barrier function	[67]
			Human CMV	Transcriptional landscape during human CMV latent infection was defined	[68]
				Latently infected cells were driven towards a weaker immune-responsive monocyte state	[69]
				A subpopulation of myeloid cells permissive to human CMV replication was identified	[70]
				CRISPR/Cas9-based screening was used for high-resolution scanning of functional elements in the human CMV genome	[71]
			Murine CMV	Ly49R activation receptor was needed for natural killer cell immunity against murine CMV infection	[72]
			HPV	HPV expression differed between hyperplastic skin lesions	[73]
	Droplets, DART-seq	Tens of thousands	Reovirus	DART-seq enabled amplicon sequ transcriptome profiling technology multiplexed encing and	[74]
Multi-parameter measurements	Valves, customized	Up to 144	HSV-1	A platform was developed for ultra-sensitive quantification of protein and mRNA	[75]
High-throughput screening	Droplets, customized	Thousands to millions	MNV-1	A platform was developed for isolation and analysis of minor alleles in viral quasispecies	[78]
		Hundreds of thousands	HIV	HIV transcriptionally reactivated cells were screened for downstream in-depth characterization	[79]