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A Synopsis of the Different Screening Stages Is Represented in Figure 52. Hence, We Decided to Conduct Qpcr Measurements of Mrna

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A Synopsis of the Different Screening Stages Is Represented in Figure 52. Hence, We Decided to Conduct Qpcr Measurements of Mrna II. Results A synopsis of the different screening stages is represented in figure 52. Figure 52 - Schematic representation of the followed screening stages. Hence, we decided to conduct qPCR measurements of mRNA transcripts (fig. 53) and/or to evaluate gene expression at the protein level by WB (fig. 54, 55, 56, 57 and 58) according to antibody availability, for correlation of observed phenotype with gene knockdown level for the twelve mentioned genes. The obtained results are summarized in table 12. 159 II. Results 160 II. Results Figure 53 - mRNA expression as determined by qPCR following infection of BMDCs with lentiviruses expressing shRNAs targeting the indicated genes. Constructs producing best phenotype are boxed. ND - not detectable. * - shRNA targeting 3’ UTR. Data are from one of at least 2 independent experiments. Figure 54 - Protein expression measured by Western Blot for Degs1. Figure 55 - Protein expression measured by Western Blot for β2m. 161 II. Results Figure 56 - Protein expression measured by Western Blot for Rab2. Figure 57 - Protein expression measured by Western Blot for Bet1. Figure 58 - Protein expression measured by Western Blot for Vamp4. Table 12 – Summary for gene knockdown level correlation with phenotype for hit genes (in brackets is indicated shRNA number that provided observed phenotype). Gene symbol Knockdown correlation Bet1 (3, 4, 5) Correlates Degs1 (2, 3, 5) No Correlation Dnm1 (2, 4) No Correlation Rab17 (2, 5) No Correlation Rab19 (1-5) Correlates Rab2 (3, 4) Possible Correlation 162 II. Results Rab40b (1, 2, 4) Possible Correlation Sec24d (1, 3, 4, 5) No Correlation Stx18 (3, 5) Possible Correlation Vamp4 (1-5) Correlates Vti1a (3, 4) Correlates β2m (2, 5) Possible Correlation Taken together, four genes showed a good correlation between knockdown level and phenotype: Vamp4, Rab19, Vti1a and Bet1; four others (Rab40b, Rab2, β2m, Stx18) showed potential correlations, i.e., some of the constructs that produced a phenotype did not produced the lowest mRNA levels, which may be explained by differential lentiviral knockdown efficiencies along different experiments, or additional effects at the translational level. Further validation using immunobloting will be required to clarify if these genes are true hits. Interestingly, constructs targeting the 3’ UTR (indicated with “*” in fig. 53) are in many cases those that either produce one of the best knockdowns or the gene mRNA level is the same (or higher) when compared to control. The observation that some shRNAs used for gene targeting produce higher mRNA levels when compared to the control has been previously described when using this strategy (Oberdoerffer et al., 2008). One possible explanation might be due to a miRNA effect, as there have been reports describing these as transcriptional up-regulators (Vasudevan et al., 2007), although this is speculative in this context. Also, in the case of Vamp4, the Western blot showed that reduced transcript expression was accomplished by all shRNA hairpins, Vamp4 was just depleted at the protein level by construct #II, #III and #V. 163 II. Results At this point, we decided to focus in the gene Vamp4 (vesicle-associated membrane protein 4), which has been suggested to play a role in the trans-Golgi network-to-endosome transport (Tran et al., 2007). The rationale for this decision is based in: 1) the strength of the phenotype and knockdown correlation; 2) when analyzing known and predicted protein-protein interactions databases (Jensen et al., 2009), we could observe that we “hited” another interacting gene, Vti1a, along with the fact that Snap25, Stx1b2, Stx3, Stx6, Stx1b1 and Stx4 also matched the selection criteria for the secondary screening, even though the first four possibly also affect class II presentation as well, and the last two provided inconclusive results. The Vamp4 interacting network is depicted in figure 59. Figure 59 - Known and predicted interactions for Vamp4 protein. From http://string.embl.de (Jensen et al., 2009). As antibodies targeting Snap23 (another of the described interactors of Vamp4, fig. 59) and Stx6 were available, we also decided to investigate their knockdown level by western blot (fig. 60 and fig. 61) using our shRNA lentiviral system, in order to pursue further antigen presentation experiments in the Vamp4 interacting complex. 164 II. Results Figure 60 - Protein expression measured by Western Blot for Snap23. Figure 61 - Protein expression measured by Western Blot for Stx6. As we can observe from figs. 60 and 61, constructs #1 and #5 targeting Snap23 produce lower protein levels when compared to control, while none of the Stx6 shRNA targeting hairpins mediate protein knockdown. The validated candidates are now good candidates for follow-up mechanistic studies (using biochemistry and cell biology tools) and to be tested in an in vivo relevant model of antigen cross-presentation. 165 Chapter III Concluding remarks and future perspectives 167 III. Concluding remarks and future perspectives 168 III. Concluding remarks and future perspectives Chapter III – Concluding remarks and future perspectives The work reported here (both for the kinase/phosphatase subset and for the cellular traffic collection of genes) is, to our knowledge, the first systematic screen that aims to identify genes with a role in antigen presentation in primary cells. Particular effort has been made in the recent past to identify genes involved in antigen cross-presentation, in a more restrictive and direct manner (Guermonprez et al., 2003; Jancic et al., 2007; Luckashenak et al., 2008). Recently, (Zou et al., 2009) reported the identification of a new gene (Rab3b/3c) with a role in cross-presentation in dendritic cells, targeting a much smaller collection of genes (57) than the ones reported in this work and by using a murine dendritic cell-line (DC2.4) as APC. Our results suggest that no kinase or phosphatase affects, in a specific manner, cross-presentation, even if I have identified many with a phenotype for both canonical and antigen cross-presentation pathways. Indeed, when considering the role of kinases (major signal transducers) within the endocytic machinery (which is in fact the underlying basis of antigen presentation), one could predict many interaction points between both and specificities. Interestingly enough, when (Liberali et al., 2008) collected all known direct phosphorylation reactions of endocytic machinery components assigned to specific protein kinases from the literature, and annotated those kinases onto the protein kinome tree, they observed that there is not one specific class of kinases that phosphorylates endocytic machinery. Rather, kinases are distributed along the tree, suggesting that the diversity of both has coevolved. In addition, it has to be taken into account that many studies are actually conducted in cancer cells and that the kinases involved in a particular process in transformed cells may be quite different from the ones regulating the same process in primary cells. 169 III. Concluding remarks and future perspectives Currently, there is little to no information on the genes that regulate membrane transport and are critically involved in cross-presentation. Therefore, the identification of 8 novel genes with a specific or predominantly specific role in antigen cross-presentation is of particular relevance. It is particularly exciting the identification of Vamp4, especially because seven of its predicted molecular interactions also give a phenotype when silenced in our screen. Overall, our work has identified ~80 novel genes with a role in antigen presentation and ~8 with a specific role predominantly in antigen cross- presentation. This achievement represents a potential enormous advance to this field as it raises an unprecedented number of molecular leads that have the potential to help the community working in this field to begin to understand the pathways that are specifically involved and required for antigens to be cross- presented. This is however the very beginning! My findings are the starting point for many possible ways in which this project can evolve. No doubt, the first important follow-up study will be to use biochemistry and cell biology tools to understand the fine molecular mechanisms and pathways that are regulated by the identified genes in the context of antigen cross-presentation. The second major axis of research to which my work can give rise is the study of the role of the now identified genes in vivo. Several biologically significant problems or models can be selected, but they should reflect relevant questions in the field including the response to tumors, non-infecting APC virus and against parasites. A good example could be the role of these genes in an in vivo response against Toxoplasma gondii. Interestingly, it has recently been shown that the recruitment of ER is abundant and critical to generate CD8+ T cell responses against this parasite in vitro and in vivo (Goldszmid et al., 2009). There has been a long-standing controversy on the literature about the role of the ER in antigen cross-presentation. Our screen identifies several genes 170 III. Concluding remarks and future perspectives (belonging to the vesicular traffic set) that are known to be involved in ER to other vesicle fusion and that localize to the ER. We are currently exploring this possibility with our collaborators at the Curie Institute (Dr. Sebastian Amigorena’s Group). Our own laboratory is currently working on a technology that will help us to dissect the role of the identified genes in antigen cross-presentation in vivo: using a lentiviral system that can be controlled spatially and temporally, we expect to be able to silence our gene of interest in the relevant cells for antigen presentation (Dendritic Cells) and switch it on and off with the addition or removal of a drug (tetracycline). With this tool in our hands, it will be possible to expand the work to genes for which classical homologous recombination knockouts are not available and also for those that are required for animal viability.
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