Zekeng, E
(2018)
Evaluating models of Influenza A virus
Infection.
PhD thesis, University of Liverpool.
|
Text
200651781_March2019.pdf - Unspecified Download (6MB) | Preview |
Abstract
High throughput proteomics and transcriptomics has provided a platform to further understand viral – host interaction. This provides a window into the host proteome and transcriptome with and without infection. This leads to identification of potential biomarkers, understanding IAV pathogenesis and also drawing a comparison of how hosts respond to viral infection. This thesis used two independent high throughput approaches to explore the proteome and transcriptome of samples from hosts (in vitro and in vivo) infected with influenza A virus (IAV) compared to samples from hosts (in vitro and in vivo) non-infected with IAV. The independent high throughput approaches used were; proteomics on a Q-Exactive platform and transcriptomics on a MinION sequencer. These approaches were used to further understand IAV infection in these different hosts and secondly to explore and search further for a potential biomarker for the diagnosis of IAV and potential drug targets. To our knowledge, this is the first study that has used high throughput approaches to analyses samples from different hosts. This allowed for comparison across hosts but also provides vast amounts of data that are reliable and consistent. A549 cells that were mock-infected and IAV- infected were subjected to the Q-Exactive platform and MinION sequencing. This provided insight into the in vitro host-viral interaction on a cellular level. For the first time, showed the potential of MinION sequencing as a method for understanding the viral-host interaction of IAV infected cells and identifying potential biomarkers. This highlighted transcripts such as NUP54, RBM42, HPGD, GCLC, ANPEP, AKAP13, RACGAP1, CREB1, MAN2B1 and PRKCI. These transcripts were identified by bioinformatic analysis as host factors that play a crucial role in replication of IAV in the host. The corresponding proteins to these transcripts were also identified by proteomics. To better understand IAV in hosts, in vivo, Non-human primates (NHP) were infected with IAV and the broncho-alveolar fluid (BALF) was collected and compared to BALF from naïve NHP. After analysis on the Q-Exactive platform, the results obtained drew parallels on a cellular level to that observed in vitro models. Proteins such as; DDX58, EIF3A, HSP90AA1, MAPK1, MX1 and STAT1 involved in the “replication of IAV” were highlighted. In addition to the cellular changes, the NHP studies provided insight into an immune response similar to that observed in humans following IAV infection. This provided an added dimension in understanding IAV infection. Finally, nasopharyngeal aspirates (NAs) from humans IAV- infected and IAV non-infected from three different cohorts (Alder Hey Children’s hospital (AHCH), Liverpool, Great Ormond Street Hospital (GOSH), London and Institute Pasteur Dakar (IPD)) were analysed on the Q-Exactive platform. This provided a full circle loop to compare if the changes observed in vitro model – A549 cells and in vivo model-NHP were relatable back to humans. Proteins identified in vitro and in vivo studies were concordant with proteins identified in the human NAs. These proteins include; COPA, STAT1, TUBB and HSPB1. Additionally, three proteins were identified in human NAs across all three cohorts; BPIFA1/SPLUNC1, Lactotransferrin and Fibrinogen A, B and G. These proteins play crucial roles in elucidating IAV infection in the host. This study presents the first time these proteins have been highlighted using label-free Mass spectrometry in human NAs across three cohorts from different geographical locations. This thesis illustrates how proteomic analysis of IAV-infected samples compared to non-infected samples can be used to identify markers that may serve as potential diagnostic indicators for IAV infection.
| Item Type: | Thesis (PhD) |
|---|---|
| Divisions: | Faculty of Health and Life Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 28 Jun 2019 09:50 |
| Last Modified: | 19 Jan 2023 00:43 |
| DOI: | 10.17638/03042661 |
| Supervisors: |
|
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3042661 |
Dimensions
Dimensions
