I NTEGRALES QUE CONTIENEN PRODUCTOS DE LAS FUNCIONES SENO Y COSENO

Cell Type Variability

IFN responses are well documented as being context dependent. Different cell types have constitutive expression of varying components of the IFN signalling pathway, or different basal levels of these proteins. In some cells, priming with other cytokines is able to modify the IFN response; for example priming with IFN increases the concentration of the ISGF3 components, and in monocytes and DCs it induces expression of STAT4. There are differences in activation of STAT proteins between cell types, and varying induction of the STAT independent signalling pathways. Differential activation of STAT1, STAT3 and STAT5 was previously observed across T cells, B cells and monocytes by IFN. For example, increased activation of STAT3 and STAT5 was observed in B cells and CD4+ T cells compared to monocytes, and very little activation of STAT1 was seen in B cells (van Boxel-Dezaire et al, 2006, 2010). In NK cells, STAT4 is initially activated, leading to production of IFN. As levels of STAT1 increase, this becomes predominant, and IFN production is replaced by NK cell killing (Mack et al, 2011).

Primary Monocytes and CD4+ T cells

Given the variability in IFN response between cell types, it was necessary to focus this investigation on particular cells, and primary monocytes and CD4+ T cells were chosen. These leukocytes both originate from hematopoietic stem cells in the bone marrow, which differentiate into myeloid or lymphoid precursors. The myeloid precursor goes on to further differentiate into various cell types, including monocytes and neutrophils, whilst the lymphoid precursors differentiate into B cells, T cells and NK cells (Figure 1.2).

Monocytes have several roles in the immune system, including phagocytosis of pathogens, antigen presentation and production of cytokines. They can be classified into classical (CD14++, CD16-), intermediate (CD14++, CD16+) and non-classical (CD14+, CD16++) subsets, with ~85% of the population consisting of classical monocytes. Whilst all subsets differentiate into macrophages, classical monocytes provide the principal source of monocyte-derived DCs. They also demonstrate the greatest phagocytic activity

and secretion of cytokines (Ziegler-Heitbrock et al, 2010; Boyette et al, 2017; Ravenhill

et al, 2020).

T cells are derived from the lymphoid precursor, maturing in the thymus into CD4+ helper T cells, or CD8+ cytotoxic T cells. These are activated by interaction with an antigen presenting cell (APC) expressing a co-stimulatory protein, and foreign antigen bound to major histocompatibility complex (MHC). Activation of CD8+ T cells leads to target cell killing, whilst naïve CD4+ T cells go on to differentiate into further subsets of effector T cells, which secrete cytokines and activate other innate and adaptive immune cells. Helper T cells activate B cells for antibody secretion, macrophages for phagocytosis, and naïve CD8+ T cells to become effector cells, as well as developing into memory T cells (Lanzavecchia & Sallusto, 2000; Alberts, 2015).

These cell types were chosen as they provide accessible primary cells with relevance in viral infection, and they respond to IFN, though there is little previous information on the IFN-induced effects at the cell surface. Analysis of primary cells is important in this context, as not all cultured cell lines express the same restriction factors. This is demonstrated by the HIV accessory proteins, which may be dispensable in cultured systems, but are important for in vivo replication (Malim & Emerman, 2008). The search for BST2 demonstrated the effect of expression of different ARFs between cell types, with Vpu being required for viral release in HeLa cells, but not in in 293T and HT1080 cells unless they had been stimulated with IFN (Neil et al, 2008). Additionally, isolation from peripheral blood makes monocytes and T cells easily accessible, so it is feasible to investigate multiple donors.

Monocytes and CD4+ T cells play a critical role in the immune response, and are valuable cell types to examine for ARFs due to their relevance in viral infection. HCMV establishes a latent infection in monocytes, providing a major site of persistent infection in the host. Differentiation of monocytes into macrophages or DCs promotes reactivation (Taylor-Wiedeman et al, 1991; Reeves & Sinclair, 2013; Poole et al, 2015). HIV is able to infect both monocytes and CD4+ T cells, due to expression of CD4 and viral co- receptors. HIV predominantly infects CD4+ T cells, but monocytes may also play an important role in infection, possibly acting as a viral reservoir (Campbell et al, 2014).

Figure 1.2 Blood lineages derived from hematopoietic stem cells

Multipotent stem cells differentiate into common myeloid or lymphoid precursors, and progenitor cells become increasingly specialised at each level of differentiation. Monocytes and T cells are derived from the myeloid and lymphoid lineages respectively. Figure is adapted from (Häggström, 2014), which was released under the Attribution- Share Alike 3.0 Unported license.

Published ‘Omics Data on IFN Stimulation of Primary Monocytes and CD4+ T Cells

There is a wealth of previous ‘omics data regarding IFN stimulation on a variety of cultured and primary cell lines, however the majority of this is transcriptomic. Much of this is deposited in the Interferome, a large database of IFN responsive genes, curated from various genome-wide microarray based studies (Rusinova et al, 2013). It includes data for type I, II and III IFNs and allows filtering based on the type of IFN and the cell types examined amongst other parameters. To date, it includes 40 experiments with type I IFNs, encompassing 107 datasets.

Searching for IFN stimulation of primary monocytes yielded just one dataset in the Interferome (dataset 306) (Smiljanovic et al, 2012). This study used microarrays to compare expression profiles in patients with rheumatoid arthritis (RA) or SLE with healthy donors. They also looked at in vitro stimulation of primary monocytes pooled from a number of donors, with a range of cytokines (IFN2a, IFN and tumour necrosis factor (TNF)-) in order to generate profiles that could be matched to the disease

signatures. They determined that gene expression in SLE patients was predominantly driven by IFN, whilst TNF was dominant for RA, with disease dependent responses to each cytokine adding further complexity. The focus of the work was therefore on the disease aspects with little analysis of the IFN data, but it provides some data on IFN stimulation of primary monocytes.

Another major investigation of IFN stimulation of primary leukocytes at the transcriptomic level was by Schlaak et al (2002). In this study, four cell lines alongside primary PBMCs, T cells and DCs were stimulated with IFN2a, before analysis of the expression of 150 known ISGs and genes of interest on a complementary DNA (cDNA) ‘macroarray’. Only seven genes were induced across all cell types in all experiments, and multiple genes were only substantially induced in the primary cells. IRF7 was induced exclusively in the hematopoietic cells. Three donors were used for DCs, and five for T cells, allowing donor specific variation to be investigated. Multiple replicates of the experiment on cell lines generated similar results each time, suggesting a reproducible response to IFN, and a robust technique. However, much greater variation was observed amongst the primary cells from different donors. In the T cells, 45 genes were induced more than 2 fold in at least 1 donor, whilst just 10 genes were induced in all 5 donors. DCs also showed donor-specific responses, though with slightly less extreme variation between donors than in the T cells. This study was limited to only investigating a predetermined set of genes, predominantly decided based on previous studies of IFN stimulation of fibrosarcoma cells. The methodology therefore doesn’t allow identification of novel ISGs, and even greater differences between the cell types may be expected in a broader study including more immune cell specific ISGs.

These transcriptomic studies provide valuable datasets, however the correlation between transcript and protein levels is often quite poor (Haider & Pal, 2013; Liu et al, 2016), and proteomic investigations are likely to reveal novel data, particularly given the ability to examine specific subcellular compartments such as the cell surface. One previous proteomic study utilised 2-dimensional gel electrophoresis (2DE) to investigate IFN stimulation of activated CD4+ T cells. The technique is known to underperform in the detection of membrane proteins and identified a very limited number of proteins; there were 11 ‘spots’ of differentially expressed proteins between the IFN-stimulated and

unstimulated cells, corresponding to 7 proteins (Rosengren et al, 2005). The project presented here therefore substantially furthers these studies.