Project description:To study expression pattern of small nucleolar RNAs (snoRNAs) during influenza A viral infection, human cells A549 were infected with influenza A/Puerto Rico/8/1934 (H1N1) virus. Small RNA-seq analysis of infected cells after 24 h or 48 h incubation was performed on an Illumina NextSeq 500 platform. The same mock-infected cells were used as control. Small RNA fractions (<200 nucleotide length) was used for constructing of cDNA libraries. Differential expressed non-coding RNAs were identified using R package DESeq2.
Project description:In this study monoclonal cell lines carrying mutations in IFITM3 gene were obtained based on WI-38 VA13 cells. To research the involvement of the IFITM3 gene in cellular response to Influenza A virus infection, original WI-38 VA13 cells and the clones with depressed IFITM3 gene activity (F3, F5, Е12) were infected with influenza A/Puerto Rico/8/1934 (H1N1) virus. RNA-seq analysis of infected cell lines after 24 h was performed on an Illumina NextSeq 500 platform. The same mock-infected cells were used as controls (0 hpi). PolyA RNA-enriched fraction was used for constructing of cDNA libraries. Differential expressed genes were identified using R package DESeq2.
Project description:To study genes involved in cellular response to Influenza A virus infection, human cells MRC5, WI-38 VA-13, A549 and HEK293FT were infected with influenza A/Puerto Rico/8/1934 (H1N1) virus. RNA-seq analysis of infected cell lines after 48 h was performed on an Illumina NextSeq 500 platform. The same mock-infected cells were used as controls. PolyA RNA-enriched fraction was used for constructing of cDNA libraries. Differential expressed genes were identified using R package DESeq2.
Project description:Human influenza remains a serious public health problem. This data article reports the transcriptome analysis data of human cell lines infected with influenza A/Puerto Rico/8/1934 (H1N1) virus. Mock-infected cells were included as controls. Human embryonic fibroblasts (MRC-5) and immortalized cell lines (A549, HEK293FT, WI-38 VA-13) were selected for RNA sequencing using Illumina NextSeq500 platform. Raw data were applied to the bioinformatic pipeline, which includes quality control with FastQC and MultiQC, adapter and quality trimming with Cutadapt, filtering to the genome of influenza A with STAR, transcript quantification with Salmon tool (GRCh38_RefSeq_Transcripts). Differential expressed genes were identified using R package DESeq2 with FDR-adjusted p-value < 0.001 and absolute value of log2(FC) > 1. Lists of differentially expressed genes is provided. The raw and processed RNA-seq data presented in this article were deposited to the European Nucleotide Archive via the ArrayExpress partner repository with the dataset accession number E-MTAB-9511 .
Project description:The ultimate success of a viral infection at the cellular level is determined by the number of progeny virions produced. However, most single-cell studies of infection quantify the expression of viral transcripts and proteins, rather than the amount of progeny virions released from infected cells. Here we overcome this limitation by simultaneously measuring transcription and progeny production from single influenza-virus-infected cells by embedding nucleotide barcodes in the viral genome. We find that viral transcription and progeny production are poorly correlated in single cells. The cells that transcribe the most viral mRNA do not produce the most viral progeny, and often represent aberrant infections that fail to express the influenza NS gene. However, only some of the discrepancy between transcription and progeny production can be explained by viral gene absence or mutations: there is also a wide range of progeny production among cells infected by complete unmutated virions. Overall, our results show that viral transcription is a relatively poor predictor of an infected cell’s contribution to the progeny population.
Project description:The objective of this study was to identify the viral transcripts packaged into the virion particles produced from BCBL1 cells as well as virions from 293L cells containing BAC36 BACs RNA from virions were extracted and analyzed by RNA sequencing
Project description:The outcome of viral infection is extremely heterogeneous at the cellular level, and infected cells only sometimes activate innate immunity. Here we assess how the genetic variation inherent in viral populations contributes to this heterogeneity. We do this by developing a new approach to determine both the cellular transcriptome and full-length sequences of all viral genes in single influenza-infected cells. Infections that activate an innate-immune response in single cells are associated with viral defects that include amino-acid mutations, internal deletions, and failure to express key genes. However, immune activation remains stochastic in cells infected by virions with these defects, and sometimes occurs even in cells infected by virions that express unmutated copies of all genes. Our work shows that the genetic variation present in influenza virus populations substantially contributes to but does not fully explain the heterogeneity in infection outcome and immune activation in single infected cells.