Next-Generation Sequencing Analysis of Cellular Response to Influenza B Virus Infection

Abstract

Influenza B virus (IBV) is a respiratory pathogen that infects humans and causes seasonal influenza epidemics. However, cellular response to IBV infection in humans and mechanisms of host-mediated restriction of IBV replication are not thoroughly understood. In this study, we used next-generation sequencing (NGS) to perform transcriptome profiling of IBV-infected human lung epithelial A549 cells at 0, 6, 12, and 24 h post infection (hpi) and characterized the cellular gene expression dynamics. We observed that more than 4000 host genes were differentially regulated during the study period, which included up regulation of genes encoding proteins, having a role in the innate antiviral immune responses, immune activation, cellular metabolism, autophagy, and apoptosis, as well as down regulation of genes involved in mitosis and cell proliferation. Further analysis of RNA-Seq data coupled with RT-qPCR validation collectively showed that double-strand RNA recognition pathways, including retinoic acid-inducible gene I (RIG-I) and Toll-like receptor 3 (TLR3), were substantially activated following IBV infection. Taken together, these results provide important initial insights into the intimate interaction between IBV and lung epithelial cells, which can be further explored towards elucidation of the cellular mechanisms in restriction or elimination of IBV infections in humans.

Influenza B infections in children: A review

“…Several different approaches are currently available for the diagnosis of influenza infections in children[ 23 - 25 ]. These include nucleic acid amplification tests (NAT), immunochromatography-based rapid diagnostic tests, immunofluorescence assays and viral isolation in cell culture[ 23 ].…”

“…Samples positive for IFB are further characterized by genotyping analysis to identify the subtype; the B/Yamagata/16/88 and B/Victoria/2/87 lineages. Different primers are used to identify the Victoria lineage and Yamagata lineage[ 23 - 25 ].…”

Interactomics: Dozens of Viruses, Co-evolving With Humans, Including the Influenza A Virus, may Actively Distort Human Aging

“…Moreover, we used published transcriptomic data to further investigate the potential of several top age-distorter candidates to interfere with cellular senescence. We took advantage of the recent demonstration that human cellular senescence can be empirically deduced from transcriptomes through differential expression of a set of 125 biomarker genes, known as SenMayo biomarkers ( Saul et al 2022 ), to search for evidence of an alteration of cellular senescence associated with various viral infection ( Kaczkowski et al 2012 ; Jagya et al 2014 ; Peng et al 2014 ; Bercovich-Kinori et al 2016 ; Devadas et al 2016 ; Hu et al 2016 ; Tang et al 2016 ; Zhang et al 2016 ; Boldanova et al 2017 ; Deshiere et al 2017 ; Harden et al 2017 ; Hojka-Osinska et al 2017 ; Klymenko et al 2017 ; McGrath et al 2017 ; Oberstein and Shenk 2017 ; Oh et al 2017 ; Razooky et al 2017 ; Viollet et al 2017 ; Zhu et al 2017 ; Journo et al 2018 ; Tso et al 2018 ; Golumbeanu et al 2019 ; Mrozek-Gorska et al 2019 ; Wang et al 2019 ; Blanco-Melo et al 2020 ; Dissanayake et al 2020 ; Li et al 2020 ; Seelbinder et al 2020 ; Sen et al 2020 ; Sheng et al 2020 ; Thompson et al 2020 ; Winer et al 2020 ; Zhuravlev et al 2020 ; Bauby et al 2021 ; Chandrashekar et al 2021 ; Chow et al 2021 ; Coelho et al 2021 ; Dapat et al 2021 ; van der Heijden et al 2021 ; Hong et al 2021 ; Tegtmeyer et al 2021 ; Tsalik et al 2021 ; Yanagi et al 2021 ; Yuan et a...…”

“…Samples sources are: (1) Alberts et al (2022) ; (2) Park et al (2022) ; (3) van Solingen et al (2022) ; (4) Chandrashekar et al (2021) ; (5) Chow et al (2021) ; (6) Blanco-Melo et al (2020) ; (7) Deshiere et al (2017) ; (8) Golumbeanu et al (2019) ; (9) van der Heijden et al (2021) ; (10) Bauby et al (2021) ; (11) GSE53993; (12) Coelho et al (2021) ; (13, 14) Devadas et al (2016) ; (15) Bell et al (2022) ; (16) GSE186908; (17) GSE192528; (18) Thompson et al (2020) ; (19, 63–65) Tsalik et al (2021) ; (20, 28, 62) Dissanayake et al (2020) ; . (21) Zhuravlev et al (2020) ; (22) GSE97672; (23, 27) GSE89008; (24) GSE82232; (25) GSE101760; (26) GSE97672; (29) Sheng et al (2020) ; (30) Hong et al (2021) ; (31) Mrozek-Gorska et al (2019) ; (32) Wang et al (2019) ; (33) Yanagi et al (2021) ; (34) GSE84897; (35) Tso et al (2018) ; (36) Journo et al (2018) ; (37) GSE79032; (38) Seelbinder et al (2020) ; (39) Oberstein and Shenk (2017) ; (40–42) Sen et al (2020) ; (43) Zhang et al (2016) ; (44, 49) Jagya et al (2014) ; (45) Yuan et al (2021) ; (46) GSE194179; (47) Zai et al (2022) ; (48) Winer et al (2020) ; (50) Montanari et al (2022) ; (51) Tegtmeyer et al (2021) ; (52) Hojka-Osinska et al (2017) ; (53) Li et al (2020) ; (54) GSE84346; (55) Hu et al (2016) ; (56, 59, 60) Kaczkowski et al (2012) ; (57) Klymenko et al (2017) ; (58) GSE92496; (61) Dapat et al (2021) ; (66) GSE102924; (67) GSE93385; (68) GSE78711; (69) GSE87750. Each column represents a condition of infection, for example, by a given virus in a given human tissue, or successive ti...…”