Transcriptome Analysis Reveals Dynamic Changes in Coxsackievirus A16 - - PowerPoint PPT Presentation

Transcriptome Analysis Reveals Dynamic Changes in Coxsackievirus A16 Infected HEK 293T Cells

Wenwen Dai Jilin University China

Clinical manifestations of Hand, Foot and Mouth Disease

death Acute flaccids Aseptic meningitis and brainstem meningitis Vesicular eruptions on skins of hand feet and oral cavity

HFMD primarily affects children younger than 5 years old and displays a wide range of clinical manifestations

Epidemiology of Hand, Foot and Mouth Disease

2millions of infections hundreds

• f deaths

Asia-Pacific region

HFMD have been a great public health concern so far

Pathogens of HFMD, co-infection and recombination

HFMD

EV71 Acute central nervous system syndromes CV A16 mild and self-limiting syndromes

Greater attention should be paid to investigations of CVA16 infection mechanisms

HFMD is caused by Enterovirus. Among them, EV71 and CV A16 are the most prevalent

Coinfection Recombination

large outbreaks and evolution of both viruses

Has contributed to majority of HFMD cases for decades

Structure of CVA16

Life cycle of CVA16 CVA16 life cycle

attach to cellular receptors and enter via endocytosis Viral RNA translates into a polyprotein Proteins induce membranous structures for RNA replication New RNAs are packaged into progeny virions release through cellular exit route Graphical overview of CV A16 life cycle Polyprotein is processed to 11 individual proteins

Transcriptome study

Transcriptome

miRNA expression profile

how CVA16 infection affects the function of a cell and the related regulatory mechanisms

mRNA expression profile CV A16 infected cell Uninfected cell

markers of EV71-related clinical symptoms in different tissues or cells transcriptome profile of CVA16 infected cells is still largely unknown

Next-generation sequencing of mRNA / miRNA and data processing

CVA16 15h supernatant Mock 293T cell lysates

Next generation sequencing

gene density

Illuminna Hiseq 2000

mRNA-seq Differentially expressed gene

mapped identify

human reference genome sequences ENSEMBL62/GRCh37 DEGseq

miRNA-seq clean short reads

SHRiMP2 software

mapped

human pre-miRNA

gene density

identify

DEGseq

Differentially expressed miRNA

predict

Differentially expressed gene targeted by miRNAs

RNAhybrid 2.1 and miRanda3.3 algorithms Burrows-Wheeler Aligner (BWA)

Differentially expressed mRNA and miRNA, as well as target genes would be identified

mRNA and miRNA expression profiles

Top 10 differentially expressed

mRNA profile miRNA profile

1954 differentially expressed mRNA 51 differentially expressed miRNA

SCARB2 gene was the most differentially expressed target gene

1825up-regulated 129 down-regulated 29up-regulated 22 down-regulated

Red: infected Blue: uninfected

The expression regulation of SCARB2 in CVA16-infected cells

Up-regulation of SCARB2 may increase the chance of co-infection ,which would partly explain the co-circulation and genetic recombination of EV71 and CVA16

SCARB2 mRNA copies SCARB2 protein levels SCARB2 is ubiquitously distributed and is a common receptor for all clinically isolated CVA16 and EV71.

and CVA16

human scavenger receptor class B member 2 hsa-miR-3605-5p

Function analysis of differentially expressed mRNA target genes

Differentially expressed mRNA target gene functional categories identify

Gene ontology from DA VID database

Function analysis of differentially expressed mRNA target genes

Differentially expressed genes were enriched in the regulation of cellular processes, cellular macromolecule metabolic processes and regulation of metabolic processes.

Function analysis of differentially expressed miRNA target genes

Differentially expressed target gene

Differentially expressed target genes were clustered into four functional pathways, especially the ECM-receptor interaction and the Circadian rhythm pathways

KEGG pathway from DA VID database

ECM-receptor interaction and circadian rhythm pathways

• ral ulcers of

Behcet’s disease inflammation of the airway cardiac pathology symptoms of CVA16 Sleeping sickness of meningitis ECM-receptor interaction circadian rhythm pathways

ECM-receptor interaction and circadian rhythm pathways may be involved with the pathogenicity of CVA16

NR1D1 CSNK1D CLOCK PER1 PER2 hsa-miR-106a-5p hsa-miR-1294 hsa-miR-3614-3p hsa-miR-331-3p hsa-miR-149-3p hsa-miR-148b-5p hsa-miR-378g hsa-miR-378c hsa-miR-423-5p hsa-miR-589-3p hsa-miR-5010-5p hsa-miR-5001-5p hsa-miR-4510

Regulation relation networks between the differentially expressed genes and miRNAs

ITGA3 CHAD AGRN COL5A1 COL5A2 HSPG2 LAMA3 LAMA5 TNXB COL11A2 ITGA2 LAMA4 ITGA7 GP1BA hsa-miR-100-5p hsa-miR-146a-3p hsa-miR-1294 hsa-miR-1273g-3p hsa-miR-1248 hsa-miR-106a-5p hsa-miR-148b-5p hsa-miR-3126-5p hsa-miR-2277-5p hsa-miR-193b-5p hsa-miR-187-3p hsa-miR-149-3p hsa-miR-3127-3p hsa-miR-3605-5p hsa-miR-331-3p hsa-miR-3187-3p hsa-miR-3607-3p hsa-miR-378d hsa-miR-378c hsa-miR-3660 hsa-miR-362-5p hsa-miR-3614-3p hsa-miR-378f hsa-miR-5001-5p hsa-miR-4510 hsa-miR-4259 hsa-miR-423-5p hsa-miR-378g hsa-miR-5096 hsa-miR-92b-5p hsa-miR-7-5p hsa-miR-665 hsa-miR-3607-5p

ECM-receptor interaction and circadian rhythm pathways

most of the differently expressed genes in the two pathways were modulated by miRNAs hsa-miR- 149-3p and hsa-miR-5001-5p The down-regulation of two miRNAs results in up-regulation of genes in ECM-receptor interaction and circadian rhythm pathways and are related to clinical symptoms of patients infected with CVA16

Green: down -regulation Yellow: up-regulation

Provide novel insight into the pathogenesis of HFMD induced by CVA16 infection Up-regulated SCARB2 and genes in ECM-receptor interaction and circadian rhythm pathways Elucidated the changes in cells upon CVA16 infection at transcriptome level

Conclusions

Acknowledgement

National Engineering Laboratory for AIDS Vaccine of School of Life Sciences in Jilin University BIG Data Center of Beijing Institute of Genomics in Chinese Academy of Sciences

• Prof. Jiang Chunlai（姜春来）
• Prof. Su Weiheng（苏维恒）
• Prof. Xiao Jingfa（肖景发）
• Prof. Li Rujiao （李茹姣）