Virotrap As a Novel Method to Study Intracellular Complexes Of

Virotrap as a novel method to study intracellular complexes

of inflammatory proteins

Eva Cloots

Verhandeling ingediend tot het verkrijgen van de graad van Master in de Biomedische Wetenschappen

Promotor: Prof. Dr. Sven Eyckerman Vakgroep Biochemie (GE07)

Academiejaar 2013-2014

Virotrap as a novel method to study intracellular complexes

of inflammatory proteins

Eva Cloots

Verhandeling ingediend tot het verkrijgen van de graad van Master in de Biomedische Wetenschappen

Promotor: Prof. Dr. Sven Eyckerman Vakgroep Biochemie (GE07)

Academiejaar 2013-2014

“De auteur en de promotor geven de toelating deze masterproef voor consultatie beschikbaar te stellen en delen ervan te kopiëren voor persoonlijk gebruik. Elk ander gebruik valt onder de beperkingen van het auteursrecht, in het bijzonder met betrekking tot de verplichting uitdrukkelijk de bron te vermelden bij het aanhalen van resultaten uit deze masterproef.”

Datum

(handtekening student) (handtekening promotor)

(naam student) (naam promotor)

ACKNOWLEDGEMENTS This dissertation is the proverbial cherry on top of my education as a Master in Biomedical Sciences. Obviously, I was guided by many people along the way, and in this section I want to take the time to thank them for everything. First and foremost, I want to thank Prof. dr. Sven Eyckerman, my promoter, for all his guidance and for allowing me to explore a wide range of technologies during these past two years. It was truly amazing to be closely involved in the development and exploration of a new cutting edge tool like Virotrap. I could not have wished for a better project and promoter! Prof. dr. Kris Gevaert, thank you for allowing me to be one of the students in your lab and for investing the resources of your lab in our education. I also want to thank Noortje, for her endless patience and guidance to get me started on this project and Delphine, for all her good advice. Thank you to the PhD students Emmy and Giel, for all your advice. Special thanks go out to Giel, for getting me started with CRISPR-Cas. A big thank you also needs to go out to all the mass-spec people, especially Evy, for making sure the samples were all finished in time. I am sure I am forgetting some people, therefore I want to say one big thank you to every single person present at our lab in the past year. It was a pleasure working with all of you!

Freja, Britt and Eva V., it was a pleasure to be a thesis student (or a ‘Very Important Brain’) at the proteomics lab with you guys! I will miss our 'koffiekletskes'. ;-) Katrien, Deborah and Emerald, thank you so much for your friendship and support during our university adventure. Also my fellow students from the Immunology major, thank you guys for making our Master's education so enjoyable. I wish all you guys the best of luck during your forthcoming career as a biomedical scientist!

And last but not least: Mom and the rest of my family. Thank you for continuing to support me through all the weird turns I took during my school career. I could not have done all this without your support!

Thank you all! Eva

SUMMARY ...... 1 NEDERLANDSTALIGE SAMENVATTING ...... 2 1. INTRODUCTION ...... 3 1.1. Protein-protein interactions ...... 3 1.1.1. Methods for binary interaction detection ...... 3 1.1.1.1. Genetic methods ...... 3 1.1.1.1.1. Yeast-two-hybrid (Y2H) ...... 3 1.1.1.1.2. Mammalian protein-protein interaction trap (MAPPIT) ...... 4 1.1.1.2. Biochemical methods: co-immunoprecipitation (co-IP) ...... 4 1.1.2. Methods for co-complex analysis ...... 5 1.1.2.1. Affinity purification-mass spectrometry (AP-MS) and tandem affinity purification (TAP)...... 5 1.1.2.2. Immunoprecipitation-MS (IP-MS) ...... 5 1.1.2.3. Other (biochemical) methods for co-complex analysis ...... 5 1.1.3. Challenges associated with currently available methods ...... 6 1.1.4. Virotrap ...... 7 1.1.4.1. General principle ...... 7 1.1.4.2. Advantages and disadvantages of Virotrap compared to other methods ...... 8 1.2. Signaling cascades in the innate immune system: Toll-like receptors ...... 9 1.2.1. Adaptor proteins ...... 10 1.2.1.1. MyD88 ...... 10 1.2.1.2. Mal ...... 11 1.2.1.3. TRIF ...... 11 1.2.1.4. TRAM ...... 12 1.2.2. Subsequent signaling cascades ...... 12 1.2.2.1. MyD88-dependent ...... 13 1.2.2.2. MyD88-independent ...... 14 1.3. Genome editing with the clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated (Cas) system ...... 15 1.3.1. Basic principles of CRISPR-Cas9 ...... 15 1.3.2. Genome engineering with CRISPR-Cas9 ...... 15 1.4. Objectives of the project ...... 16 1.4.1. Virotrap as a method to study TLR signaling ...... 16 1.4.2. Validation of new MyD88-interacting proteins ...... 16 1.4.3. Expanding Virotrap to other cell types ...... 16 1.4.4. Applying CRISPR-Cas9 to Virotrap as to obtain a cell line capable of supporting increased particle production ...... 17 2. METHODS ...... 18 2.1. Cell culture ...... 18 2.2. Virotrap ...... 18 2.2.1. Constructs ...... 18 2.2.2. Transfections ...... 19 2.2.3. Purification and analysis of VLPs ...... 20 2.2.3.1. MS experiments ...... 20 2.2.3.2. Binary experiments ...... 21 2.2.4. Transfection efficiency in MEF and Jurkat cells ...... 22 2.3. NF-κB luciferase reporter assay ...... 22 2.4. CRISPR-Cas9 genome engineering ...... 23 2.4.1. Construct design ...... 23

2.4.2. Transfections ...... 24 2.4.3. Analysis of mutation efficiency ...... 24 2.5. Validation of newly identified MyD88 interactors ...... 25 2.5.1. Validation of the interactions by MAPPIT and co-IP...... 25 2.5.1.1. Constructs ...... 25 2.5.1.2. MAPPIT ...... 25 2.5.1.3. Co-IP ...... 26 2.5.2. Functional validation of interactions in A549 cells ...... 27 2.5.2.1. siRNA and transfection ...... 27 2.5.2.2. Stimulation and analysis of TLR signaling by RT-qPCR ...... 27 3. RESULTS ...... 29 3.1. MS experiments in HEK293T cells revealed new interaction partners for MyD88 and pitfalls associated with certain bait proteins ...... 29 3.1.1. Unique interactors of MyD88 and MyD88-TIR ...... 29 3.1.2. Additional successful Virotrap screens ...... 30 3.1.3. Some constructs do not lead to detectable particle production, possibly due to activation of immunological pathways ...... 30 3.1.3.1. Bait proteins not resulting in Virotrap particle production ...... 30 3.1.3.2. An NF-κB luciferase assay revealed a link between difficulties with particle production and NF-κB activation ...... 31 3.2. Validation experiments for novel MyD88-TIR and MyD88 interaction partners ...... 32 3.2.1. RNF115, ULK3 and WDR36 interact with MyD88-TIR, and PKP2 interacts with MyD88-TIR and MyD88 in a MAPPIT assay ...... 32 3.2.2. G3BP1 and FAM188A co-precipitate with MyD88 ...... 33 3.2.3. RNF115 may function as a negative regulator in TLR signaling ...... 34 3.3. Generation of a TRIM5 deficient HEK293T cell line and use of these cells in MS experiments ...... 36 3.4. Expanding Virotrap to other cell lines ...... 37 3.4.1. MEF cells are currently not suitable for Virotrap due to inefficient transfection .. 37 3.4.1.1. PEI transfections ...... 37 3.4.1.2. Lipofectamine LTX transfections...... 37 3.4.2. Jurkat cells may be used in Virotrap, but require additional optimization ...... 39 3.4.2.1. Determination of optimal DNA concentration ...... 39 3.4.2.2. Exploration of binary Virotrap with Jurkat cells ...... 39 3.4.2.3. MS experiments with A20 ...... 40 4. DISCUSSION ...... 41 4.1. Virotrap is an exciting novel option for exploring protein-protein interactions in intact mammalian cells ...... 41 4.1.1. Virotrap revealed Rabring7 as a likely novel interaction partner of MyD88 ...... 41 4.1.2. Other bait proteins ...... 42 4.2. Virotrap currently exhibits some limiting factors ...... 43 4.2.1. Interference with particle production ...... 43 4.2.2. Virotrap in other cell lines requires additional optimization ...... 44 5. CONCLUSION ...... 46 6. REFERENCE LIST ...... 47 ANNEXES ...... I A. Supplementary methods ...... I A.I. Background list for MS ...... I

A.II. Overview of DNA mixes used for the NF-κB reporter assay...... II B. Supplementary results ...... III B.I. Additional MS results MyD88 ...... III B.II. Additional MS results MyD88-TIR ...... VIII B.III. Additional co-IP results ...... X C. List of abbreviations ...... XII

SUMMARY Protein-protein interactions (PPIs) are a crucial component of any living cell, and many strategies have been developed to characterize these interactions in great detail. However, the coverage of this entire spectrum of interactions (the ‘interactome’) that can be achieved is currently limited, highlighting the need to develop new complementary techniques for mapping the interactome. Virotrap is a recently developed PPI detection method, based on the intrinsic capability of the Human Immunodeficiency Virus (HIV)-1 Gag protein to form virus-like particles (VLPs). By fusing this Gag protein to a bait protein of interest, the inner shell of the VLP is coated with this bait protein, thereby trapping interactors of the bait protein inside the VLP. As VLPs are secreted into the supernatant in cell culture, purification of these particles and identification of isolated proteins is a straight-forward process. This novel method was applied to toll-like receptor (TLR) signaling components, thereby revealing novel interacting proteins for some of these components. For Myeloid Differentiation Primary Response 88 (MyD88), several possible new interactors were identified, including Ring finger protein (RNF) 115, also called Rab7-interacting RING finger protein (Rabring7). This protein appears to regulate TLR signaling as shown by short interfering (si)RNA knockdown. Validation experiments on the identified interactors also revealed that Virotrap is capable of isolating interactors that remain in the insoluble fraction after lysis of cells, indicating that Virotrap can become an important complementary method to other methods requiring lysis of cells such as affinity purification-mass spectrometry (AP-MS). Interestingly, for certain bait proteins there was significant interference with particle production in Virotrap screens, possibly due to a type of antiviral state. We attempted to resolve this by creating a genetically engineered cell line lacking tripartite motif containing (TRIM)5, encoding the important retroviral restriction factor TRIM5α, which is upregulated by interferon (IFN). Currently, no data for this cell line is available, as problems occurred with the materials required for sample preparation. Because interactions can be cell-type dependent, attempts were also made to use Virotrap in other cell lines. While some success was obtained with Jurkat cells, it is clear Virotrap will require extensive cell-type specific optimization for each cell line.

NEDERLANDSTALIGE SAMENVATTING Eiwit-eiwit interacties staan centraal in elke levende cel. Hoewel er reeds verschillende technieken beschikbaar zijn om deze interacties in kaart te brengen, blijkt de dekking van het gehele interactoom voorlopig beperkt en dit toont aan dat er nog steeds gezocht moet worden naar nieuwe technieken. Virotrap is een nieuwe techniek die gebruik maakt van de natuurlijke partikelvorming van het HIV-1 Gag eiwit. Wanneer een lokaas-eiwit gekoppeld wordt aan het Gag eiwit, worden partikels gevormd die intern bekleed zijn met het eiwit van interesse. Interactoren van dit eiwit worden mee geïncorporeerd in de partikels. Deze techniek werd succesvol toegepast op enkele componenten van de TLR signalisatienetwerken. Hierbij werden voor MyD88 enkele mogelijke nieuwe interactoren gevonden, waarvan RNF115/Rabring7 ook een functionele rol lijkt te hebben in TLR signalisatie. Bij de validatie van deze interactoren bleek dat sommige geïdentificeerde eiwitten niet detecteerbaar zijn in geklaarde lysaten, omdat ze zich in de onoplosbare fractie bevinden. Dit geeft aan dat Virotrap een belangrijke complementaire technologie kan zijn voor lyse-gebaseerde detectiemethoden. Een andere observatie rond Virotrap was dat sommige lokaas-eiwitten niet tot partikelvorming lijken te leiden, mogelijk ten gevolge van een soort algemene antivirale status. TRIM5α, een belangrijke retrovirale restrictiefactor, werd daarom uitgeschakeld via genoom engineering. Voorlopig zijn echter geen resultaten beschikbaar rond deze cellijn, hetgeen waarschijnlijk een gevolg is van problemen met de materialen nodig voor staalvoorbereiding. Verder werd Virotrap deels geoptimaliseerd voor gebruik in andere cellijnen. Hieruit bleek evenwel dat elke cellijn specifieke optimalisatie zal vereisen.

1. INTRODUCTION 1.1. Protein-protein interactions In recent years, the development of new techniques such as massive parallel sequencing has allowed us to generate large amounts of data regarding the genetic make-up and RNA expression profiles of cells. However, we also know that genes and their transcripts do not necessarily reflect the exact composition of the cell on the protein level (1), and the functionality of proteins is (often transiently) modulated by processes such as post- translational modifications (PTMs) (2). As a result, proteomics has emerged as an important field when studying (protein mediated) cellular functions. Cellular proteins often, though not exclusively, exert their function through interaction with other proteins and knowledge of these PPIs can help us understand protein function to a certain extent (3). The occurrence of PPIs can result in either a stable protein complex or a dynamic system with transient interactions exhibiting a wide range of affinities (2, 4). The dynamics of these interactions can be influenced by factors such as protein abundance or PTMs (4). Due to this dynamic nature it is impossible to map an entire interactome with only one method, and as a result, several approaches have emerged for mapping the interaction profiles of proteins. Currently available methods can generally be categorized as either 'biochemical' or 'genetic' methods (2), and they will either detect direct (‘binary’) interactions or detect larger protein complexes (‘co- complex analysis’). Biochemical approaches usually consist of an affinity-based step, where proteins are isolated from cell lysates, and a detection step, where interacting proteins are identified through antibody-based or mass spectrometry (MS) based approaches (4). Genetic methods, such as yeast two hybrid (Y2H) and mammalian protein-protein interaction trap (MAPPIT), usually rely on expression of a modified bait and prey protein and result in a specific read-out (usually expression of a quantifiable reporter gene or a survival gene) which indicates an interaction between bait and prey occurred. Some examples of powerful methods are described below. Recently, a new method called Virotrap was developed. This thesis project will be focused on the application of this method to TLR signaling (see 1.2.) and on expansion of Virotrap to other cell lines.

1.1.1. Methods for binary interaction detection 1.1.1.1. Genetic methods 1.1.1.1.1. Yeast-two-hybrid (Y2H) Y2H is currently one of the most widely used methods for the study of PPIs. This system relies on the reconstitution of a DNA binding domain (DB) fused to a bait protein and an

activating domain (AD) fused to a collection of prey proteins to form a functional transactivating complex. When the bait and a prey protein interact, the DB can bind to a specific DNA sequence and the AD will initiate transcription of a reporter gene (5). This fairly inexpensive two hybrid method can now also be applied to (semi)automated high throughput screens (HTS), which allows for more elaborate screening (3), even up to the scale of the entire proteome (6).

1.1.1.1.2. Mammalian protein-protein interaction trap (MAPPIT) This method relies on the reconstitution of a disrupted type I cytokine receptor signaling pathway through interaction of a bait and prey protein (7). Type I cytokine receptors are constitutively associated with Janus kinases (JAKs) and upon ligand binding these JAKs phosphorylate tyrosine residues on the receptor. Then, the signal transducer and activator of transcription (STAT) protein family is recruited to the receptor through phosphotyrosine binding Src homology 2 (SH2) domains. These STATs are also phosphorylated by JAKs, leading to STAT dimerization and translocation to the nucleus, where they function as transcription factors (8, 9). In MAPPIT, cells are transfected with a phosphorylation deficient receptor coupled to a bait protein and a gp130-prey fusion protein. In this system, JAKs can still be activated, but no phosphorylation of the receptor can occur. As a result, STATs cannot be recruited. In case of interaction of the bait and prey proteins, gp130 is recruited to the receptor, and as gp130 can be phosphorylated on its tyrosine residues by JAKs, STATs can now be recruited through their SH2 domains, leading to expression of a reporter construct (7). MAPPIT has also successfully been used for HTS of large cDNA panels such as the ORFeome collection (10).

1.1.1.2. Biochemical methods: co-immunoprecipitation (co-IP) Co-IP is an affinity purification method that relies on an antibody specific for an endogenous protein of interest, extraction of the antibody-bound proteins and their interactors from a lysate, and subsequent analysis of the co-precipitated proteins. Co-IP is often used as a confirmation technique after an interaction was identified through other methods, and analysis is generally carried out by Western Blot using specific antibodies for expected prey proteins (11). Co-IP experiments can also be conducted in an overexpressed set-up in which the bait protein or even both bait and prey proteins are overexpressed with an epitope tag for which high-affinity antibodies are available. If expression levels can be kept close to the endogenous protein levels, this may be a valid alternative for endogenous co-IP if no antibodies are

available for the protein of interest, although competition with the endogenous proteins may occur.

1.1.2. Methods for co-complex analysis Generally, methods for co-complex analysis are categorized as biochemical methods only, as these methods do not rely on a specific secondary (genetic) readout.

1.1.2.1. Affinity purification-mass spectrometry (AP-MS) and tandem affinity purification (TAP) AP-MS relies on the isolation of an epitope tagged bait protein from a cell lysate, after which interaction partners are identified by MS (4). This powerful method has several advantages. Firstly, experiments can be carried out in a relevant cell type (which is often not possible in genetic methods). Also, PTMs are usually conserved in AP-MS experiments, so complexes are not destabilized due to the absence of critical PTMs. A last advantage is the possibility to introduce a quantitative component into the experiment, to study the dynamics of an interactome (12). The TAP tag is another strategy for MS coupled affinity purification, where proteins of interest are fused to a ‘tandem tag’ for two separate affinity purifications. In between the two tags a tobacco etch virus (TEV) protease cleavage site is introduced, allowing elution of the protein complexes after the first purification step without using denaturing or other non- physiological conditions that could harm the protein complex. Theoretically, this more stringent purification ensures purification of only true interactors (13). Nowadays, several TAP tags have been designed for use in several organisms under various conditions (4).

1.1.2.2. Immunoprecipitation-MS (IP-MS) IP-MS is essentially a co-complex set-up for co-IP. It is also based on the use of antibodies specific for a bait protein of interest, however, in this co-complex set-up MS is used to study entire endogenous protein complexes, as opposed to identifying a specific previously determined interacting protein. The IP-MS setup has been shown to be successful even on a large scale by Malovannaya et al. (14).

1.1.2.3. Other (biochemical) methods for co-complex analysis Apart from the approaches described above, many other biochemical strategies exist. One such example is size exclusion chromatography (SEC)-stable isotope labeling of amino acids

in cell culture (SILAC). SEC-SILAC introduces a quantitative aspect into chromatographic protein complex purification strategies, which allows a reconstruction of the complexes in the correct stoichiometry with detailed information about their spatiotemporal changes under specific stimuli (15). BioID is another elegant method for characterizing protein complexes. Here, a ‘promiscuous’ biotin ligase is fused to a bait protein of interest, which leads to biotinylation of all proteins in the vicinity of the bait protein (16). Also, crosslinking strategies exist where two proteins (or two regions in one protein) are chemically crosslinked by a covalent bond. After MS identification of the peptides that were linked, conclusions can be drawn on the three dimensional structure of a protein complex (17).

1.1.3. Challenges associated with currently available methods Endogenous co-IP is often seen as a 'gold standard', but one major problem with this method is the availability of high affinity antibodies to precipitate and detect the proteins of interest. Apart from this, all affinity based approaches rely on cell lysis and subsequent protein complex isolation from the lysate. This can be associated with two problems. Firstly, because all cellular compartments are mixed in this process, it is possible that certain interactions are identified even though they are not likely to happen in vivo due to spatial segregation (4). Also, non-specific interactions with for example the used epitope tags can result in non- specific co-purification of proteins (12, 18). As a result, AP-MS datasets can contain a significant amount of contaminants (12). Especially in high throughput datasets the risk of false positives was a concern some years ago (19), though recent efforts have allowed for a more efficient approach of (high throughput) data. For instance, the creation of a contaminant repository for affinity purification (the so-called ‘CRAPome’) allows researchers to score identified protein interactions based on the occurrence of that protein in unrelated AP-MS negative control experiments (18). Another strategy is the use of a more stringent washing protocol or a TAP tag, however, harsh purification strategies can be associated with a second problem: the loss of weak and/or transient interactors during washing steps (4, 12). The aforementioned cross-linking strategies can be employed to preserve weak interactions during purification (17).

With genetic methods there is a risk of identifying interactions that are physicochemically correct, but not biologically relevant due to overexpression of the bait and prey proteins (which can also be a concern with poorly designed AP-MS experiments). Initially, false positive rates in genetic HTS were estimated to reach 60% (20), however, subsequent analysis

with positive and random reference sets has shown that the risk of false positives is most likely small as none of the tested genetic methods appointed more than 5% of the random protein pairs as interacting proteins (21). However, we need to keep in mind that the specific set-up can significantly influence which true or false interactions are detected (as shown for several Y2H set-ups by Chen et al. (22)). Apart from the limited risk of false positives, each method will fail to detect a significant percentage of true interactions. At this moment, it is impossible to cover the entire interactome with the available methods. For example, Venkatesan et al. (23) estimate only ~8% of the 130.000 expected PPIs has currently been identified through large-scale Y2H interactome mapping strategies. This shows it is still useful to develop new strategies.

1.1.4. Virotrap 1.1.4.1. General principle Virotrap is a recently developed technology (Eyckerman et al., submitted), named after its virological origin. In Virotrap, a bait protein is coupled C-terminally to the HIV-1 Gag protein. The HIV-1 Gag protein is a polyprotein which is normally cleaved by a viral protease to form several smaller proteins during maturation of newly produced viral particles. In absence of other proteins and viral RNA, the uncleaved Gag polyprotein is still capable of forming VLPs (24). These empty VLPs will contain a cellular membrane, with directly underneath a layer of Gag proteins (25), anchored to the membrane through an N-terminal myristic acid tail (24). Overexpression of the Gag protein in cell cultures results in efficient production and release of VLPs, containing about 5000 uncleaved Gag proteins each (25). Because a bait protein is C-terminally fused to the Gag protein, the inner surface of the VLPs in a Virotrap experiment will be coated with the bait protein, and relevant interactors are expected to be 'trapped' inside the VLPs (fig. 1). As VLPs have an average diameter of about 145 nm (25), they can theoretically contain even the largest intracellular protein complexes, such as the nuclear pore complex. To enable easy purification of the VLPs, vesicular stomatitis virus glycoprotein (VSV-G) and FLAG-tagged VSV-G are also expressed in the cells. Now the surface of the VLPs will contain trimeric assemblies of VSV-G and FLAG- tagged VSV-G, so they can be purified using an anti-FLAG antibody. Once the secreted VLPs are isolated, the contents of the particles can be analyzed via MS. Virotrap can also be used in a binary setup: in this case a prey protein containing an epitope tag (e.g. E- or Myc-tag) is co-transfected, and the presence of the prey protein in the VLPs is confirmed through Western Blotting with antibodies directed against the tag.

Figure 1. General principle of Virotrap. A Gag-bait fusion protein is expressed in mammalian cells, and this fusion protein picks up interactors during trafficking to the plasma membrane. Once Gag-bait fusions (and interactors) arrive at the plasma membrane, the intrinsic ability of Gag to multimerize comes into play. VLPs bud from the cellular membrane after sufficient Gag-bait fusions have assembled at the cellular membrane. The VLPs are released into the supernatant and can now be purified via a flag-tagged VSV-G protein.

1.1.4.2. Advantages and disadvantages of Virotrap compared to other methods When compared to affinity purification protocols, one big advantage of Virotrap is the preservation of the normal cellular environment: as no lysis is required, cellular proteins can interact under near-physiological conditions. Because the Gag-bait fusion needs to be overexpressed it is currently not possible to maintain the exact physiological state, though efforts to resolve this problem are underway. In binary setups, the bait and prey proteins are both overexpressed, which is associated with the same challenges as the currently available genetic methods. However, Virotrap does seem to complement other genetic methods, as it is capable of detecting a different set of protein interactions when compared to methods such as MAPPIT. This was observed when using a previously validated human reference set of interacting (positive reference set or PRS) and non-interacting proteins (random reference set or RRS). These reference sets have been described by Braun et al. (21). All methods were capable of detecting ~20-35% of known protein interactions and Virotrap showed a limited overlap with other methods (fig. 2), indicating it could be useful for interactions that are not detected by other methods. The instances where Virotrap could not detect interactions that were detected with other methods, could be partly explained by difficulties with expressing some proteins in the Virotrap system.

Figure 2. Comparison of Virotrap, MAPPIT, Y2H, PCA, LUMIER and NAPPA using a PRS. Virotrap shows complementarity with established binary interaction methods, as it was capable of demonstrating known interactions that are not found using other methods. Figure from Eyckerman et al. (submitted).

Currently, the Virotrap protocol is limited to human embryonic kidney (HEK) 293T cells. Such a limitation is also seen in other methods, for example, Y2H screens are obviously carried out in non-mammalian cells. Initially, the HEK293T cell line was chosen for its favorable growth properties and the availability of effective transfection protocols. However, this is a cell line known for its abnormal karyotype and may not be the most relevant experimental system for many protein interactions. Also, TLRs are not normally expressed in HEK293 cells (26), though complementation of these cells with TLR- and co-receptor- expressing vectors enables nuclear factor-kappa B (NF-κB) activation, indicating that all essential intracellular factors in TLR signaling should be present. As part of this project, the Virotrap protocol will also be optimized in other cell lines, more specifically immortalized mouse embryonic fibroblast (MEF) cells and Jurkat cells.

1.2. Signaling cascades in the innate immune system: Toll-like receptors Upon infection, the first component of the immune system that becomes activated is the innate immune system. This innate immune response largely relies on the recognition of pathogen associated molecular patterns (PAMPs) through pattern recognition receptors (PRRs). One such PRR system with a well-known signaling cascade is the TLR family. This receptor family is characterized by the presence of an extracellular domain with leucine rich repeats (LRRs) responsible for PAMP recognition and/or co-receptor interaction (see fig. 3 for examples of recognized PAMPs) and an intracellular Toll/interleukin (IL)-1 receptor (TIR) domain responsible for initiating the signaling cascade (27). In humans and mice respectively, there are 10 and 13 TLRs known (28). When a TLR encounters its ligand, receptor clustering occurs, which allows intracellular molecules to start the signaling cascade (27). Currently, four main activating adaptor proteins are known to initiate this signaling cascade (29), the use of these adaptors by several TLRs is depicted in fig. 3.

Figure 3. Differential use of adaptors by several TLRs. TLR10 is not depicted as this TLR is not expressed in mice, and therefore has not been studied to the same extent. Figure obtained from Kawai & Akira (28).

1.2.1. Adaptor proteins 1.2.1.1. MyD88 MyD88 was the first adaptor protein shown to function in the TLR pathway (30). It consists of an N-terminal death domain (DD), a C-terminal TIR homology domain and a central intermediate domain (ID) (fig. 4) (31). Early on, MyD88 was demonstrated as an essential component in bacterial lipopolysaccharide (LPS) responsiveness in mice, and MyD88 deficient mice were characterized by a delayed activation of NF-κB after TLR stimulation. This defect in the immediate response was the first indication that two pathways exist in TLR signaling: a MyD88 dependent pathway leading to immediate NF-κB activation and cytokine production, and a MyD88 independent pathway leading to IFN production and a delayed NF- κB response (28, 32). We now know that MyD88 does indeed orchestrate a MyD88- dependent pathway in all TLRs, except for TLR3, which solely activates the MyD88- independent pathway. TLR4, which is the receptor for LPS, can activate both a MyD88- dependent and an independent pathway (28), explaining the observations of Kawai and colleagues (32).

Figure 4. Domains of MyD88. Numbers indicate amino acid positions. Figure from O’Neill & Bowie (29).

The structure of MyD88 has been studied extensively, and the major function of all its domains has been determined. The TIR domain is essential for homotypic interaction with the TIR domain of the TLR (or upstream adaptors), while the DD is responsible for connecting

with the downstream signaling protein IL-1 receptor-associated kinase (IRAK)-1, again through homotypic interaction (31, 33). The role for the ID became clear after a series of studies on a splice variant of MyD88 which does not contain this ID: MyD88s. This splice variant, normally induced after prolonged exposure to TLR agonists or pro-inflammatory cytokines, is still capable of binding the downstream signaling molecule IRAK-1 through its DD, but IRAK-4, another kinase required for signaling (also see 1.2.2.1.), can no longer be recruited when the ID is missing (33).

1.2.1.2. Mal TIR Domain Containing Adaptor Protein (TIRAP), more commonly called MyD88 adaptor- like (Mal), is an essential bridging protein between TLR2/4 and MyD88 (1.2.1.1). Through MAPPIT analysis, the TIR domain was shown to be essential in this interaction (34). TLR5, 7, 8, 9 and 11 are able to interact with MyD88 without using Mal as a bridging molecule (28). One interesting feature of Mal is its dependence on phosphorylation of several tyrosine residues by Bruton's tyrosine kinase (BTK) during signaling (fig. 5) (35). Phosphorylation was shown to occur constitutively in overexpressed Mal in HEK293T cells, which induces an activation of the TLR signaling cascade independent of stimulation by TLR ligands (36). In Virotrap, this means the active signaling cascade can probably be studied without co- transfecting a plasmid for a TLR. However, this also means that, when Mal is used as the overexpressed bait protein, the native situation cannot be studied. As a bridging molecule, Mal needs to be targeted to the plasma membrane. This is achieved through an interaction between the phosphatidylinositol-4,5-bisphosphate-binding motif (PIP2) (fig. 4) and the phosphatidylinositol-4,5-bisphosphate containing plasma membrane (29).

Figure 5. Domains of Mal. Numbers indicate amino acid positions. Mal is phosphorylated by BTK at positions 86 and 187. In the TIR domain a Tumor necrosis factor (TNF) receptor associated factor 6 (TRAF6)-binding motif (T6BM) is present, which is responsible for downstream signaling. The PIP2 motif is responsible for targeting Mal to the plasma membrane. Figure obtained from O’Neill & Bowie (29).

1.2.1.3. TRIF TIR-domain-containing adaptor protein inducing IFN-β (TRIF, fig. 6), encoded by the TICAM1 gene, was the first adaptor with a proven function in the MyD88-independent pathway (29). Analysis of TRIF-deficient mice showed that TRIF was involved in signaling in

both TLR3 and -4, though for TLR4 the MyD88-dependent pathway remained intact. This led researchers to the conclusion that TRIF functions in the MyD88-independent pathway (37).

Figure 6. Domains of TRIF. TRIF contains a central TIR domain, an N-terminal domain with a T6BM and a C- terminal domain with a receptor interacting protein (RIP) homotypic interaction motif (RHIM). Both termini contribute to signaling through distinct pathways. Figure obtained from O'Neill & Bowie (29)

1.2.1.4. TRAM TRIF-related adaptor molecule (TRAM) is another TIR domain containing TLR-adaptor (29), encoded by TICAM2 (fig. 7). The generation of TRAM-deficient mice showed a specific role for TRAM in TLR4 signaling only. In these mice, the MyD88-independent pathway of TLR4, but not the function of TLR3 was affected, indicating that TRAM functions exclusively as an adaptor for TLR4 (38). Studies have shown that the role of TRAM might be broader than just its function as an adaptor for TLR4 and TRIF though, as TRAM-deficient cells have more defects in cytokine production than TRIF-deficient cells after LPS stimulation (29). TRAM needs to be recruited to the plasma membrane to function properly, which is achieved by N-terminal myristoylation (fig. 6) (39). This specific localization could be interesting for Virotrap experiments, as the addition of a Gag protein always targets the bait protein to the plasma membrane. This means TRAM can be studied in its normal cellular localization.

Figure 7. Domains of TRAM. Numbers indicate amino acid positions. TRAM contains a C-terminal TIR domain and N-terminal sites for myristoylation (which leads to membrane targeting) and phosphorylation by protein kinase Cε (PKCε). Figure from O’Neill & Bowie (29).

1.2.2. Subsequent signaling cascades Generally, the recruitment of these adaptor proteins allows cells to activate certain transcription factors (TFs) through a series of protein interactions and modifications. The MyD88-dependent pathway classically leads to NF-κB activation, whereas the MyD88- independent pathway mainly leads to IFN responsive factor (IRF) 3 activation and a delayed NF-κB response. Other TFs, such as activating protein (AP)-1, are activated in the MyD88- dependent pathway through mitogen activated protein kinase (MAPK) pathways (28).

1.2.2.1. MyD88-dependent Once MyD88 is recruited to the receptor (either directly, or through Mal) downstream signaling molecules can also be recruited and activated. The first protein family in this subsequent cascade is the IRAK family (40). Four human IRAKs have been identified, and all of them have a DD at their N-terminus and a central kinase domain (KD). It was thought the KD is functional in IRAK-1 and IRAK-4 only, as IRAK-2 and IRAK-3 (also called IRAK-M) have a mutated critical residue in their KD (41). However, later reports concluded that IRAK- 2 does exhibit kinase activity and that this activity is essential for IRAK-2 signaling (42). Once MyD88 has been recruited to the receptor, it will simultaneously bind IRAK-1 and IRAK-4, through its DD and ID respectively. IRAK-4 will now phosphorylate IRAK-1, which also induces kinase activity and autophosphorylation in IRAK-1 (33). However, this autophosphorylation by IRAK-1 is not strictly required for TLR signaling, as cells expressing only a kinase defective IRAK-1 protein can still elicit TLR mediated responses (40). After IRAK-1 is phosphorylated (with or without added autophosphorylation) it dissociates from MyD88/Mal in a complex with IRAK-4, and binds TRAF6 (33, 43). TRAF6 will now associate with both ubiquitin-conjugating enzyme E2 variant 1 (UEV1A) and ubiquitin- conjugating enzyme 13 (UBC13), which leads to TRAF6 ubiquitination (29, 43). Polyubiquitinated TRAF6 recruits a complex containing transforming growth factor (TGF) β- activated protein kinase (TAK1), TAK1-binding protein 2 (TAB2) and TAB3. These last two proteins contain motifs that interact with the TRAF6 polyubiquitin chain. Fig. 8 shows a schematic representation of this signaling cascade. Eventually, this cascade leads to activation of TFs NF-κB and AP-1 (43). The role of IRAK-2 has only recently been elucidated. According to Kawagoe et al. (42), IRAK-2 is activated by IRAK-4 (similarly to IRAK-1) and is responsible for sustained responses to TLR ligands. Whereas IRAK-1 is rapidly degraded after its IRAK-4 mediated autophosphorylation and activation, activated IRAK-2 was present in cells for several hours and mediated the sustained expression of pro-inflammatory cytokines such as TNF-α. Several regulating mechanisms exist in TLR signaling, and two of these will also be studied. The first regulatory factor is IRAK-3, the last IRAK family member. Generally, it is assumed that IRAK-3 prevents dissociation of IRAK family members from MyD88, thereby inhibiting signaling towards TFs such as NF-κB (44). However, a recent report concentrating on the role of IRAK-3 in TLR7 signaling showed that a MyD88-IRAK-4-IRAK-3 complex was still capable of inducing NF-κB activation, though this NF-κB activation only led to transcription of genes that exhibit an overall inhibitory effect on TLR signaling (45). The second regulatory

factor is TNF-α induced protein 3 (TNFAIP3), more commonly known as A20. A20 is responsible for regulating TLR responses by de-ubiquitinating TRAF6, which terminates the downstream signaling capabilities of TRAF6 (46). A20 has been used in Virotrap experiments before, with promising results. Therefore, it would be interesting to repeat this experiment in Jurkat cells.

Figure 8. Schematic representation of TLR signaling. Note that the representation of the TRIF is misleading. No distinction is made between the specific signaling paths of the N- and C-terminal domains of TRIF. Figure from O'Neill et al. (47)

1.2.2.2. MyD88-independent As mentioned earlier, initiation of a signaling cascade by TRIF leads to a delayed NF-κB response with the production of inflammatory cytokines, whereas MyD88 mediates an immediate NF-κB response. This delayed NF-κB response can be mediated by TRIF via both its N-terminal and C-terminal domains (fig. 6). The N-terminal region has been shown to interact with TRAF6, while the C-terminal region is thought to mediate NF-κB activation through interaction with RIP1 (fig. 6 shows the binding motifs for these interactions) (29). Another major function of TRIF is the induction of IFN-β, which is also mediated by the N- terminal region of TRIF, through association with TRAF-family-member-associated NF-κB

activator (TANK)-binding kinase 1 (TBK1) via other proteins such as TRAF3 and NAK- associated protein 1 (NAP1) (39). Fig. 8 shows a schematic representation of these signaling cascades (NAP1 not depicted).

1.3. Genome editing with the clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated (Cas) system 1.3.1. Basic principles of CRISPR-Cas9 CRISPR-Cas is a form of acquired immune system found in prokaryotic cells. CRISPRs are loci in the prokaryotic genome where a series of direct repeats is separated by variable sequences called protospacers, derived from previously encountered exogenous genetic material. The region of alternating protospacers and direct repeats is called the CRISPR RNA (crRNA) array. Such regions are found in close proximity to specific genes, namely Cas genes, which encode proteins such as endonucleases responsible for degrading foreign nucleic acids. The protospacers contain a protospacer adjacent motif (PAM), which is a sequence of a few nucleotides specifically required by a specific Cas enzyme (48, 49). There are three types of CRISPR-Cas systems (I-III) and the CRISPR-Cas system used for genome engineering is a type II system called CRISPR-Cas9 (49). This type II system contains three main elements: the crRNA array, the Cas9 endonuclease, and an auxilliary transactivating crRNA (tracrRNA), which helps processing of the crRNA into separate units containing only one target. After processing, the units contain a partial repeat and a guide sequence of 20 nt, which recognizes foreign DNA through base-pairing. When the guide binds foreign DNA, the Cas9 enzyme is targeted to this foreign DNA and the DNA is cleaved with a double-stranded (ds) break (50).

1.3.2. Genome engineering with CRISPR-Cas9 CRISPR-Cas9 has been adapted for use as a fairly straight-forward genome engineering tool in cells. In this setup, a human codon-optimized Cas9 is transfected into cells together with so-called single-guide RNAs (sgRNAs), which are based on the crRNA structure and target a specific sequence in the genome of the cell (fig. 9) (49).

There are two possible setups with Cas9: in one setup, wild-type Cas9 is used, which induces ds breaks, causing a significant risk of inducing premature stopcodons after repair. In another setup, a nicking variant of Cas9 (Cas9n) is used which induces breaks in one strand. When this system is used with two separate sgRNAs, it still leads to ds breaks. However, as the number of nucleotides that needs to match before a ds break can be introduced is effectively

doubled, this system shows a significantly lower number of off-target effects (51). For the Cas9n approach, sgRNAs are designed in such a way that 5' overhangs are created after double nicking.

Figure 9. Structure of the sgRNA. A genomic target is chosen and a 20 nt portion of the sgRNA (blue) is based on this target sequence, thus targeting the Cas9 to the correct location. The rest of the sgRNA (red) is called the scaffold and has an auxiliary function. Figure from Ran et al. (49).

1.4. Objectives of the project 1.4.1. Virotrap as a method to study TLR signaling One aspect of this thesis project mainly consists of Virotrap experiments in HEK293T cells with various adaptor and signaling molecules from the TLR signaling cascade as baits. This not only contributes to the validation and implementation of Virotrap as a method for studying PPIs in dynamic signaling cascades, but also the discovery of any new interaction partners contributes to the ever expanding knowledge on TLR signaling and regulation.

1.4.2. Validation of new MyD88-interacting proteins Previously unknown interactors of MyD88 identified through Virotrap will be validated with other methods. The interaction itself will be retested in MAPPIT and by overexpression co-IP, while the functional relevance of top candidates will be assessed further by knocking down these proteins by siRNA, and performing quantitative reverse transcriptase (qRT)-polymerase chain reaction (PCR) on TLR responsive genes in A549 cells, an adenocarcinoma cell line endogenously expressing TLRs, mainly TLRs 2-6 (52).

1.4.3. Expanding Virotrap to other cell types A second objective of this project is to expand Virotrap to other cell lines, more specifically immortalized MEF cells and Jurkat cells. Both cell types are relatively difficult to transfect, though high transfection efficiency can be obtained with commercial reagents and

nucleofection systems. TLR expression has been observed for both MEF and Jurkat cells, though sensitivity to the respective ligands can vary (53, 54). Jurkat cells are often used in HIV-1 research, which makes them an interesting cell type for Virotrap particle production. If Virotrap can be used in a wider array of cell types, it will become possible to use Virotrap as a method to study pathways and mechanisms that might be difficult to study in HEK293T cells. Also, if Virotrap can be used in other species (e.g. MEF cells), it can also be used to study protein complexes that have not been identified in humans or for which no expression constructs can be obtained. This would make Virotrap a powerful tool for characterizing protein complexes in their natural environment.

1.4.4. Applying CRISPR-Cas9 to Virotrap as to obtain a cell line capable of supporting increased particle production Some bait proteins involved in innate immune pathways do not lead to efficient particle production. One protein possibly involved in this inhibition is TRIM5α. TRIM5α is a cytosolic protein well-known for its anti-retroviral properties. It functions as a cytosolic PRR capable of recognizing retrovirus capsid proteins, leading to activation of transcription factors through activation of TAK1. TRIM5α has also been shown to be directly responsible for inefficient particle production for several retroviruses (55). The expression of TRIM5α is inducible by IFN in several cell lines (56), which makes it an important gene in our experiments with components of the TLR pathway, as there are both MyD88-dependent and independent pathways capable of inducing IFN production (fig. 3). We postulated the inefficient particle production seen for some baits (for example TAK1) could be caused by the activity of TRIM5α and its subsequent interference with particle assembly. To investigate this, a TRIM5 deficient cell line was created with the CRISPR-Cas9 technology. For use in Virotrap, this means a TRIM5-/- HEK293T cell line is created with the CRISPR-Cas9 system. To obtain a full knock-out, three genomic copies of this gene need to be eliminated, as HEK293T cells have three full copies of this gene (http://bioit.dmbr.ugent.be/hek293/) (Callewaert et al., under review).

2. METHODS 2.1. Cell culture HEK293T cells, immortalized MEF cells and A549 cells were cultured in High glucose Dulbecco's Modified Eagle Medium (DMEM) with GlutaMAXTM (Gibco), supplemented with 10% HyCloneTM fetal bovine serum (FBS, Thermo Scientific), 50U/ml penicillin and 50 µg/ml streptomycin (Gibco). For HEK293T cells medium also contained 10 mM HEPES

(Gibco). HEK293T and MEF cells were incubated at 37°C with 8% CO2, A549 cells with 5%

CO2. Jurkat cells were cultured in standard Roswell Park Memorial Institute 1640 (RPMI 1640) Medium (Gibco), with 10% FBS, 50U/ml penicillin and 50 µg/ml streptomycin. Cells were incubated at 37°C with 5% CO2. After nucleofection, Jurkat cells were kept in RPMI 1640 with 10% FBS or Opti-MEM (Gibco) with 2% FBS, without antibiotics until harvest.

2.2. Virotrap 2.2.1. Constructs Transfections were carried out with pMET7-Gag-bait expression vectors containing a strong SRα promoter for high expression of the Gag-bait fusions (table 1). Prey constructs for binary setups had the same pMET7 backbone as the bait constructs, but with an N-terminal Myc tag. For MS experiments a non-relevant construct (pSVsport) instead of a prey construct was added to maintain standard DNA ratios, as no tagged prey is required for these experiments.

Table 1. Overview of Virotrap bait constructs Coding protein Construct MyD88 pMET7-Gag-SP1-MyD88* MyD88 TIR domain pMET7-Gag-SP1-MyD88TIR* Mal (TIRAP) pMET7-Gag-TIRAP PYCARD pMET7-Gag-Pycard Trif (TICAM1) pMET7-Gag-TICAM1 Tram (TICAM2) pMET7-Gag-TICAM2* TLR4 intracellular domain pMET7-Gag-SP1-20xGGS-TLR4IC TLR2 intracellular domain pMET7-Gag-SP1-20xGGS-TLR2IC IRAK-1 pMET7-Gag-IRAK-1* IRAK-2 pMET7-Gag-SP1-IRAK-2 IRAK-3 pMET7-Gag-SP1-IRAK-3 IRAK-4 pMET7-Gag-IRAK-4* A20 (TNFAIP3) pMET7-Gag-TNFAIP3* Constructs marked with an asterisk (*) were already present in the Virotrap expression vector collection. Note some constructs contain a spacer sequence or ‘smart peptide’ (Eyckerman et al., unpublished), which theoretically allows the bait to move more freely to interact with other proteins.

A 2:1 ratio of a FLAG tagged VSV-G construct (pcDNA3-FLAG-VSV-G) and a regular VSV- G construct (pMD2.G) were co-transfected in all experiments, to allow purification of the resulting VLPs through the FLAG tag presented on the VLP surface.

Coding sequences for the constructs were provided by the Cytokine Receptor Lab of Prof. J. Tavernier. Wild-type sequences were mostly available through their Gateway compatible hORFeome v8.1 entry clone collection, which is an ongoing effort to create a collection of all human open reading frames (ORFs). hORFeome v8.1 currently contains 11.149 human ORFs (http://horfdb.dfci.harvard.edu/). The sequences were cloned into Gateway compatible Virotrap expression vectors using LR clonase (Invitrogen). ORFs not available in the hORFeome v8.1 collection were obtained from available MAPPIT vectors through classical cloning strategies with restriction enzymes (all from New England Biolabs).

After cloning, competent DH10B Escherichia coli cells were transformed with the constructs by heat shock transformation in S.O.C. Medium (Invitrogen). Bacteria were plated on LB agar plates (10 g BactoTM Tryptone (BD Biosciences), 5g BactoTM yeast extract (BD TM Biosciences), 10g NaCl, 15 g Bacto Agar (BD Biosciences) in 1 L H2O) containing ampicillin, suitable colonies were picked and grown in liquid LB medium also containing ampicillin. Nucleobond miniprep kits (Machery-Nagel) were used to purify the plasmid DNA from the bacteria. A restriction digest was performed to confirm that the correct insert was cloned into the vector. For Gateway constructs this was done by BsrGI digest, while for constructs obtained through classical cloning strategies suitable restriction enzymes were identified through restriction site analysis of the construct with CLC Workbench (CLC Bio). Constructs made by classical cloning strategies were also sequenced by the VIB Genetic Service Facility to verify the correct insert. For larger scale plasmid production bacteria were cultured overnight in LB medium with antibiotic selection and plasmid purification was carried out according to the manufacturer's protocol with Nucleobond midi, midi extra and maxiprep kits (Machery-Nagel), depending on the amount of plasmid DNA needed.

2.2.2. Transfections HEK293T cells were transfected with 25K linear polyethyleneimine (PEI) reagent (Polysciences, Inc.). In MS experiments, 4 T75 flasks were seeded for each bait in the morning on day 1 with 8,5.106 cells for transfection on day 2, or 3,6.106 cells for transfections on day 3. For each T75 flask the following mix of plasmid DNA was prepared in DMEM media without additives: 3,75 µg bait construct and 3,75 µg mock DNA/FLAG-VSV-G/VSV- G mix with a ratio of 15:4:2. In a separate tube, PEI was added to DMEM without additives in a 5:1 PEI:DNA ratio. PEI and DNA were combined and were added to the cell cultures after

10 minutes incubation at room temperature. Then, cell cultures were allowed to take up the plasmid DNA in DMEM containing 2% FBS for several hours, after which media was replaced with standard DMEM media containing 10% FBS, antibiotics and HEPES. Later, the protocol was adjusted to be carried out in 2 T175 flasks per bait. The ratios of all used products to the seeded surface area were maintained.

For Virotrap optimization in MEF cells, cells were seeded in 6 well plates at ~80% confluency at the time of transfection. For PEI transfections, 25K linear PEI was used in several PEI:DNA ratios. As only very limited transfection efficiency could be obtained with PEI, transfections were further optimized with Lipofectamine LTX with Plus reagent (Invitrogen). These transfections were carried out according to the manufacturers optimization instructions, though in a smaller plating volume (1 ml instead of 2 ml) to concentrate the VLPs. Gag- bait/Myc-prey/FLAG-VSV-G/VSV-G were added with a ratio of 25:6:10:5. These ratios of DNA were derived from the binary Virotrap standard protocol in HEK293T cells.

For Jurkat cells the Neon® nucleofection system (Thermo Scientific) was used according to the manufacturer's protocol. Jurkat cells were resuspended at a density of 2.107 cells/ml in resuspension buffer R, DNA was added and experiments were carried out with 10 µl Neon pipette tips for DNA/cell ratio determination, and 100 µl Neon pipette tips for binary and MS protocols. For binary experiments one pipette tip was used twice per bait-prey combination as to nucleofect 4.106 cells, and cells were plated in 10 ml media containing 10% FBS without antibiotics. For MS experiments two tips were used twice per bait construct as to nucleofect 8.106 cells, and cells were plated in 20 ml media containing 10% FBS without antibiotics. Because normal DNA ratios for MS experiments were insufficient for detectable particle production, the non-relevant pSVsport construct was substituted for additional bait-construct. 15 µg of total DNA was used per 100 µl cell suspension. DNA ratios for binary experiments were the same as in HEK293T and MEF cells.

2.2.3. Purification and analysis of VLPs 2.2.3.1. MS experiments Supernatant was harvested from the cell culture flasks, spun down for 3-5 minutes at 1750g to remove cells and/or cellular debris, and filtered over 0.45 µm filters (Merck Millipore). In ~10 ml increments, VLPs in the supernatant were allowed to bind for 1.5-2 hours with 100 µl Dynabeads MyOne Streptavidin T1 paramagnetic beads (Invitrogen) that were pre-bound

with biotin labeled monoclonal mouse anti-FLAG antibody (BioM2, Sigma-Aldrich). After full processing of the supernatant, the beads were transferred to a low protein binding eppendorf tube and the VLPs were eluted from the beads using an excess (200 µg/ml) of FLAG peptide (Sigma-Aldrich). Sodium dodecyl sulfate (SDS) was added to the supernatant in a final concentration of 0.1%. SDS was removed using HiPPR detergent removal spin columns (Thermo Scientific) according to the manufacturer's protocol, with 20 mM TRIS HCl pH 7.5 (no salt) as the equilibration buffer for the columns. The detergent-free sample was boiled for 5 minutes at 95°C, chilled and 1 µg trypsin was added for overnight digest at 37°C. Trifluoroacetic acid (TFA) was added to a final concentration of 0,1% and samples were subsequently analyzed using a Q ExactiveTM Hybrid Quadrupole-Orbitrap MS (Thermo Scientific).

Identification of peptides and storage of data was done using Mascot Daemon (Matrix Science) and an in-house MS laboratory information management system (MS lims) (57). Data analysis was conducted with a workflow in KNIME (Knime.com AG) created specifically for Virotrap, and this generated lists with either all identified proteins, or all proteins that were identified by at least two different peptides. When using the KNIME workflow for generating the lists with all found proteins for a certain bait, a representative background list of 19 unrelated Virotrap experiments was included (see Annex A.I.). These experiments were carried out with unrelated bait-proteins, and they were selected based on the number of Gag peptides found. The use of such a background list enables filtering out of background data (i.e. all proteins that were also found with at least one peptide in the 19 background experiments), thus only retaining the interactors that associated specifically with the bait, and not, for example, with Gag.

2.2.3.2. Binary experiments Supernatant was harvested after spinning down cells and/or any remaining cellular debris. Next, supernatant was incubated with 10 µl Dynabeads MyOne Streptavidin T1, loaded with BioM2 anti-FLAG-antibody for 2 hours to purify the VLPs (for experiments with Jurkats 20 µl beads were used). The beads containing VLPs were then washed, and the VLPs were eluted and opened by adding XT loading buffer and reducing agent (RA) (Bio-rad). For cell lysates, cell pellets or 6-well plates containing adherent cells were washed with ice cold PBS and lysed with 100 µl lysis buffer (50mM HEPES pH7.4, 100mM NaCl, 0.8% CHAPS, Complete protease inhibitor cocktail (Roche)). Cellular debris was spun down at

15.000g, and XT buffer and RA were added to the cleared lysate. Samples containing XT buffer and RA were boiled and loaded onto a Criterion XT Bis-Tris 4%-12% precast gel (Bio- Rad), and blotted overnight to a PVDF transfer membrane (Millipore) optimized for fluorescent detection. To detect the presence of prey protein in supernatant and lysates, blots were incubated with monoclonal mouse anti-Myc antibody (clone 9E10, produced in-house). For lysates, rabbit anti-actin antibody (Sigma-Aldrich) is used as a positive control. Both signals are visualized using secondary antibodies containing different infrared signals for the Odyssey imaging system (Li-cor). Afterward, all bound antibodies were removed with mild stripping buffer (7.5 g glycine, 0.5 g SDS, 5 mL Tween20, pH2.2, brought up to 0.5 L with water), and a mouse monoclonal anti-HIV1 p24 (Gag) antibody (Abcam) was added and visualized with anti- mouse infrared antibody to visualize particle production efficiency.

2.2.4. Transfection efficiency in MEF and Jurkat cells Initial experiments in MEF and Jurkat cells were carried out with Gag-eGFP constructs. The percentage of eGFP positive cells was determined 48h after transfection using a FACScalibur flow cytometer and CellQuest Pro (BD Bioscienes). Cells were stained with propidium iodide to verify cell viability.

2.3. NF-κB luciferase reporter assay To identify constructs that activated NF-κB signaling pathways, an NF-κB luciferase reporter assay was conducted using all the bait constructs. For this assay 2,5.103 HEK293T cells were plated in 100 µl in a 96 well plate 48h before transfection. The used DNA mixtures are described in Annex A.II. The DNA was transfected using a standard calciumphosphate (CaP) protocol. The DNA was diluted in 50 µl sterile water and 5 µl 2.5 M CaCl2 was added. The DNA-CaCl2 mixture was then added to 50 µl 2x HEPES-buffered saline (HeBS) and the mixture was vortexed for 1 min. The DNA-CaP mix was then added dropwise to the cells. Cells were incubated for one day at 37°C and 8% CO2, after which bacterial LPS was added at a concentration of 100 ng/ml to the positive control wells. The cells were incubated again at 37°C and 8% CO2, and after 24 hours luciferase activity was assayed. This was done by lysing the cells with 50 µl cell culture lysis reagent buffer (25 mM Tris-phosphate pH 7.8, 10 mM DTT, 10 mM 1,2-diaminocyclohexane- N,N,N',N'-tetraacetic acid, 50% glycerol, 5% Triton X-100), after which 35 µl of luciferase substrate buffer (40 mM Tricine, 2.14 mM (MgCO3)4Mg(OH)2·5H2O, 5.34 mM

MgSO4·7H2O, 66.6 mM DTT, 0.2 mM EDTA, 270 μM coenzyme A (Sigma), 530 μM ATP (Sigma), 470 μM luciferin (Duchefa)) was added and the signal was read with an EnVision 2101 multilabel reader (PerkinElmer). Each condition was assayed in triplicate.

2.4. CRISPR-Cas9 genome engineering 2.4.1. Construct design For inactivation of the TRIM5 gene with the CRISPR-Cas9 genome editing technology, two sets of sgRNAs were created using the online CRISPR design module (http://crispr.mit.edu/), the genomic target sequences of these sgRNA pairs are shown in table 2. The sgRNAs were used both separately and as pairs with the Cas9 enzyme that creates double stranded breaks, and as pairs in the Cas9 nicking variant (Cas9n), where two nicks lead to a double stranded break. The sgRNA pairs are positioned in such a way that 5' overhangs are created after two nicks are introduced in Cas9n strategies (51).

Table 2. Genomic target sequences the sgRNA pairs are based on 3' sgRNA target 5' sgRNA target Offset sgRNA pair 1 CCTGACACAACCCCTGAGCC TGG CCTCCTCCTTTACATTAACC AGG 17 sgRNA pair 2 TGGAATCCTGGTTAATGTAA AGG TCCACTGCTCCTGCCTGTCC TGG 25 Target sequences for CRISPR-Cas9 are 20bp sequences, followed by the 3bp PAM-sequence (bold) required by Cas9 for recognition of the site. The 3' sgRNA of a pair corresponds to the forward strand of the genomic DNA (thus binding to and nicking the reverse strand), while the 5’ sequence of the pair corresponds to the reverse strand of the genomic DNA. The last column shows the offset between the two sgRNAs in one pair, this offset needs to be kept as small as possible for Cas9n strategies, because larger offsets decrease efficiency.

All four sgRNA oligo's and their complementary strands were synthesized (Integrated DNA Technologies) with additional nucleotides in such a way that after annealing a fragment was obtained with suitable overhangs for cloning into an BbsI opened CRISPR-Cas9 vector (table 3.). The CRISPR-Cas9 vectors used for this strategy were pSpCas9(BB)-2A-Puro and pSpCas9n(BB)-2A-Puro (Addgene).

Table 3. Annealed oligo's ready for cloning into the BbsI opened Cas9/Cas9n vector 3' sgRNA 5' sgRNA sgRNA pair 1 CACCGCCTGACACAACCCCTGAGCC CACCGCCTCCTCCTTTACATTAACC CGGACTGTGTTGGGGACTCGGCAAA CGGAGGAGGAAATGTAATTGGCAAA sgRNA pair 2 CACCGTGGAATCCTGGTTAATGTAA CACCGTCCACTGCTCCTGCCTGTCC CACCTTAGGACCAATTACATTCAAA CAGGTGACGAGGACGGACAGGCAAA Note the oligo's themselves do not contain the 3 nt PAM sequence, this sequence is required to be present in the genomic sequence itself for efficient Cas9 targeting and not in the guide sequence.

After ligation of the sgRNA oligo's into the BbsI opened vectors, plasmids were produced in competent DH10B cells as described earlier (2.2.1.). To verify the correct oligo was inserted 23

into the plasmid two strategies were used. First, the vector was cut using NdeI and BbsI, which leads to a 418 nt fragment if an oligo was inserted due to the loss of the BbsI cutting site, and a 329 nt fragment if no oligo was inserted and the BbsI cutting sites were maintained. Additionally, if the fragment had the correct length the construct was sequenced to verify the correct insert, this was done using a primer targeting the U6 promotor in the vector as described by Ran et al. (49).

2.4.2. Transfections HEK293T cells were transfected with PEI in a 24 well format, for which 2.105 cells were seeded per well 20h before transfection. In total, 500ng of CRISPR-Cas9 plasmid was transfected per well with 3 µg PEI. After 24 hours, transfected cells were kept in medium containing 2 µg/m of puromycin for selection of transfected cells. Puromycin selection was carried out until all control cells died (~70 hours), after which the cells were washed, transferred to 6-well plates and allowed to expand.

2.4.3. Analysis of mutation efficiency Analysis of the introduced mutations was conducted by isolating genomic DNA with QuickExtract DNA extraction solution (Epicentre) using ~200.000 to 250.000 cells in 0.5 ml of QuickExtract. Genomic DNA concentration was determined to be in the 50-70 ng/µl range with a Nanodrop ND-1000 spectrophotometer (Thermo Scientific). For amplification of the targeted region of TRIM5, PCR was carried out with primers amplifying a 547 nt fragment of the N-terminal region of TRIM5 (Fwd 5'-ACCAATGCACAGATAAGAACAGA-3' & Rev 5'- ACTTGACCTCCCTGAGCTTC-3'). First, the PCR was optimized by using either 2 µl or 5 µl of genomic DNA in both a standard and a touchdown PCR protocol (fig. 10) with Herculase II fusion DNA polymerase (Agilent technologies). In the optimized protocol, 5 µl of genomic DNA was used with the touchdown PCR program. The PCR product was visualized on a 1% agarose gel, the amplicon band was cut out and the amplicon was purified using a NucleoSpin Gel and PCR clean-up kit (Machery-Nagel). The purified PCR product was analyzed using the Surveyor mutation detection kit for standard gel electrophoresis (Transgenomic), according to the manufacturer's protocol. In short, the heterogenous DNA was denatured and allowed to rehybridize with itself. After this process, a mixture of correctly matched and mismatched double stranded DNA fragments was obtained, which was treated with a mismatch-specific nuclease of celery. The samples were then loaded on a 2% agarose gel to visualize the fragments.

Figure 10. PCR protocols tested for amplification of a 547 nt region in the genomic TRIM5 sequence. On the left, the standard PCR protocol as described by Ran et al. (49) is represented. On the right our touchdown PCR protocol is shown. During 14 cycles, annealing temperature is lowered from 68°C to 55°C at a rate of -1°C per cycle. After this, the PCR continues with 21 cycles of amplification with an annealing temperature of 54°C.

2.5. Validation of newly identified MyD88 interactors 2.5.1. Validation of the interactions by MAPPIT and co-IP 2.5.1.1. Constructs MAPPIT bait vectors for MyD88 (pCLG-20xGGS-MyD88) and MyD88-TIR (pCLL-MyD88- TIR) were already available through the Cytokine Receptor Lab of Prof. J. Tavernier. MyD88 interactors Rabring7, FAM188A, ULK3, TRMT6, G3BP1, WDR36 and PKP2 were available through the hORFeome v8.1 collection and were cloned into pMG1 prey vectors with the Gateway cloning technology. For co-IP experiments N-terminal tagging sequences were added to bait and preys. To this end, MyD88 was cloned into a pMET7-FLAG-SP1 vector and interactors were cloned into a pMET7-Myc-SP2 vector, again through Gateway cloning.

2.5.1.2. MAPPIT For MAPPIT, HEK293T cells were seeded at a density of 10.000 cells/well 18-24h prior to transfection and cells were transfected by CaP transfection. In total, approximately 500 ng of DNA was prepared (250 ng bait, 150-250 ng prey, 50 ng reporter) in 100 µl total volume according to the protocol described in 2.4 (adding 2x HeBS was now done while vortexing). For each well, 10 µl of this mix was added to the cells and 6 wells were transfected per condition. As a positive control a pMG2-Mal prey vector and a pMG1-EFHA1 prey vector were used. As a negative control an empty pMG1 vector was used. After 24h three wells per condition were stimulated with 100 ng/ml leptin, while the other

three wells functioned as unstimulated controls. Reporter activity was measured 24h after stimulation, in the same manner as the NF-κB luciferase assay (see 2.4.). Luciferase activity was calculated and reported as a fold induction (the mean of stimulated wells divided by the mean of the unstimulated wells).

2.5.1.3. Co-IP For co-IP 5.106 HEK293T cells were seeded in 10 cm petri dishes 24h prior to transfection. Transfections were carried out according to the standard Virotrap transfection protocol (see 2.2.2.) using 2,5 µg FLAG-tagged MyD88 and 2,5 µg Myc-tagged bait construct (table 4) with 25 µg PEI, in µl DMEM without additives. For each prey combination, two petri dishes were seeded, one of which served as a bead control (beads without antibody).

Table 4. Protein partners tested by co-IP Partner 1 Partner 2 pMET7-FLAG-SP1-MyD88 pMET7-MYC-SP2-ULK3 pMET7-FLAG-SP1-MyD88 pMET7-MYC-SP2-FAM188A pMET7-FLAG-SP1-MyD88 pMET7-MYC-SP2-WDR36 pMET7-FLAG-SP1-MyD88 pMET7-MYC-SP2-RNF115 pMET7-FLAG-SP1-MyD88 pMET7-MYC-SP2-PKP2 pMET7-FLAG-SP1-MyD88 pMET7-MYC-SP2-G3BP1 pMET7-FLAG-SP1-MyD88 pMET7-MYC-SP2-TRMT6 pMET7-FLAG-SP1-MyD88 pMET7-MYC-SP2-MAL

After 48h cells were washed with ice cold PBS and lysed on ice with mild lysis buffer (10 mM TRIS-HCl pH 8.0, 150 mM NaCl, 1% NP-40, 10% glycerol, 5 mM ZnCl2, Complete protease inhibitor cocktail (Roche) and phosphatase inhibitors Na3VO4, NaF and β- glycerophosphate) or radioimmunoprecipitation assay (RIPA) buffer (50 mM TRIS-HCl pH 8.0, 200 mM NaCl, 2 mM EDTA, 1% NP-40, 0.5% DOC, 0.05% SDS, Complete protease inhibitor cocktail and phosphatase inhibitors). After spinning down cellular debris, an aliquot of the lysate was kept separately as a control sample to verify efficient expression of bait and prey. The rest of the lysate was incubated for 2 hours with BioM2 anti-FLAG antibody prebound Dynabeads MyOne Streptavidin T1. Beads were captured on a magnet and supernatant was discarded after taking out an aliquot as a depleted control. After washing, beads were eluted directly in loading buffer for SDS-polyacrylamide gel electrophoresis (PAGE). Samples were loaded on a Criterion XT Bis-Tris 4%-12% gel (Bio-Rad) and proteins were blotted to a PVDF membrane overnight. Presence of the prey protein was detected by anti-Myc antibody (monoclonal mouse or polyclonal rabbit (Abcam)), and visualized with 26

infrared antibody. When rabbit anti-Myc was used, monoclonal mouse anti-Flag (Sigma- Aldrich) and anti-mouse infrared antibody were used to visualize presence of the bait protein.

2.5.2. Functional validation of interactions in A549 cells To investigate the functional significance of previously unidentified MyD88 interactors, we knocked down a selection of these interactors and studied the effect on LPS signaling through qRT-PCR on TLR4 target genes CCL5, IFNB1, TFNA and IL1B.

2.5.2.1. siRNA and transfection For efficient knock-down, siGENOME siRNA pools (Thermo Scientific) consisting of 4 different siRNAs were obtained for FAM115A, FAM188A and Rabring7. Resuspended siRNA was kept as a 20µM stock at -20°C. Knock-down experiments were carried out by seeding 100.000 A549 cells in 24 well plates 24h before transfection in 500 µl DMEM with 10% FCS and antibiotics. siRNA was transfected into A549 cells with DharmaFECT 1 transfection reagent (Thermo Scientific), according to the manufacturer's standard protocol. In short, 25 µl 2 µM siRNA was diluted in 25 µl DMEM without additives, in a separate tube 2 µl DharmaFECT reagent is diluted in 48 µl DMEM without additives. Both tubes are added together and after 20 min incubation, the transfection mix was added up to 500 µl with DMEM without antibiotics, resulting in a final concentration of 100 nM siRNA. Medium on the cells was replaced with 500 µl transfection mix. Apart from the siRNAs for Rabring7, FAM188A and FAM115A, appropriate control experiments were included. As a negative control an ON-TARGETplus non-targeting siRNA was used (Thermo Scientific), also a mock transfection was carried out and completely untreated wells were included. A polo-like kinase (PLK)-1 siRNA (Thermo Scientific) was included to check for transfection efficiency, as knock-down of this protein causes a defect in cell-growth and increased apoptosis. For each condition two wells were seeded to obtain one LPS-stimulated and one unstimulated well.

2.5.2.2. Stimulation and analysis of TLR signaling by RT-qPCR To analyze mRNA expression of TLR4 signaling targets CCL5, IFNB1, ISG15, TNFA and IL1B, cells were either left untreated or stimulated with 100 ng/ml LPS 48h after siRNA transfection. After 3h, cells were lysed with RLT buffer (Qiagen) containing β- mercaptoethanol. Total RNA was isolated from the cells with a Nucleospin RNA kit (Macherey-Nagel). RNA concentration was measured with a Nanodrop ND-1000. To obtain cDNA suitable for PCR amplification the PrimeScript reverse transcriptase kit (Takara) was

used. For qPCR, every sample was quantified four times per gene in a 384 well format. Apart from the five TLR4 target genes, expression of housekeeping genes GAPDH, PPARA and ACTB was monitored to normalize expression levels. The primers used for qPCR are shown in table 5. qPCR was carried out using the LightCycler 480 SYBR Green I Master kit (Roche). Per well, the following mix was prepared: 5 µl 2x SYBR Green I Master, 0.5 µl Fwd primer (10 µM) and 0.5 µl Rev primer (10 µM). The mix was transferred to the 384 well plate and 4 µl of 1/20 diluted cDNA was added. As a negative control, cDNA was substituted for

PCR grade H2O. Plates were measured using the LightCycler 480 instrument II (Roche).

Table 5. Primer sequences for qRT-PCR

Gene Forward Reverse CCL5 TGCCCACATCAAGGAGTATTT CTTTCGGGTGACAAAGACG IFNB1 CTTTGCTATTTTCAGACAAGATTCA GCCAGGAGGTTCTCAACAAT IL1B GAGCTACGAATCTCCGACCAC GGCAGGGAACCAGCATCTTC TNFA GAGGCCAAGCCCTGGTATG CGGGCCGATTGATCTCAGC GAPDH TGCACCACCAACTGCTTAGC GGCATGGACTGTGGTCATGAG PPARA GGTGGACACGGAAAGCCCAC GGACCACAGGATAAGTCACC ACTB CCAACCGCGAGAAGATGA CCAGAGGCGTACAGGGATAG

Analysis of qPCR data was carried out using Qbase+ (Biogazelle). Using this program, relative expression levels of TLR target genes were normalized to the housekeeping genes and represented as such in the results section.

3. RESULTS 3.1. MS experiments in HEK293T cells revealed new interaction partners for MyD88 and pitfalls associated with certain bait proteins 3.1.1. Unique interactors of MyD88 and MyD88-TIR Both MyD88 constructs (full-length MyD88 and MyD88-TIR) led to the identification of several unique interactors. A first observation during the experiment was that full length MyD88 induced a high amount of cell death in HEK293T cells. MyD88-TIR did not cause cell death, indicating that the toxicity was caused either specifically by the MyD88 construct, or downstream signaling through full length MyD88. The full length MyD88 indeed allowed reconstitution of part of the MyD88 dependent pathway: both IRAK-1 and IRAK-4 were identified by MS. However, due to our stringent analysis criteria, IRAK-4 was not retained as it was only identified by one single peptide in all three experiments. Not surprisingly, no IRAKs were identified in the sample when using MyD88-TIR, as this construct lacks the domains known for interacting with IRAKs. Both MyD88 constructs should be able to allow interaction with the upstream adaptor Mal, however, this protein was not recurrently identified in the samples with either MyD88 or MyD88-TIR. Mal was however present with a single peptide in one MyD88-TIR experiment. In total, 2786 proteins were identified in the three experiments using MyD88, while MyD88-TIR yielded 2466 identified proteins. After analysis, 314 and 86 proteins were retained as unique interacting proteins for MyD88 and MyD88-TIR respectively. Table 6 shows the proteins that were retained after subtracting the background proteins, and that were recurrently identified (i.e. at least twice for one bait, or at least once in both MyD88 and MyD88-TIR) by more than one peptide. The full list of unique proteins identified by MS, including proteins that were identified only by one single peptide, can be found in Annex B.I. and B.II.

All obtained MS spectra were also challenged against a reverse database, to generate a global score that indicates how many false positives can be expected in the identifications for a certain experiment. Here, all sequences in the reference protein database are reversed, and the number of positive matches between the MS spectra and the reverse database is calculated. The ratio of the spectra identified with the reverse database and the total number of spectra identified is called the false discovery rate (FDR). A low FDR indicates that the identifications are most likely true identifications, and not random matches. For MyD88 FDRs were 0%, 0.06%, 0.07%, and for MyD88-TIR FDRs were 0%, 0.03% and 0.12%.

Several proteins were selected for further validation based on their recurrence, functional annotation and/or availability through hORFeome v8.1. hORFeome clones were available for Rabring7, FAM188A, ULK3, WDR36, TRMT6, PKP2 an G3BP1, so these proteins were further tested in MAPPIT and co-IP setups. Rabring7, FAM188A and FAM115A were selected for further validation with siRNA, as they were all identified in several experiments for both baits.

Table 6. Results for MyD88 and MyD88-TIR MyD88 MyD88 TIR Identified protein (gene name) N° of exp. Identified protein (gene name) N° of exp. G3BP1 3 (3) SEPSECS 3 (3) PKP2 3 (3) Rabring7/RNF115 2 (3) FAM115A 3 (3) FAM115A 1 (1) HDLBP 3 (3) FAM188A 1 (3)

ULK3 2 (2) IRAK1 2 (3) Rabring7/RNF115 2 (2) TRMT6 2 (3) RAD50 2 (3) RPA1 2 (3) WDR36 2 (2) PIP4K2C 2 (3) FAM188A 1 (3)

Three experiments were carried out with each bait protein, numbers in the table indicate in how many of these experiments the interactor was identified by more than one peptide. Numbers in brackets indicate how often the protein was identified by at least one peptide. Full names of the proteins can be found in Annex B.I. and B.II.

3.1.2. Additional successful Virotrap screens Apart from MyD88, several signaling molecules from TLR pathways were screened using Virotrap. MS analysis revealed a limited set of interactors for IRAK-3 and PYCARD (data not shown). It should be noted PYCARD is not an actual TLR signaling component, but it was included because adaptor proteins generally work fairly well in Virotrap. TRAM, IRAK- 1 and -2 also resulted in some Virotrap particle production, however, after analysis there was no overlap of interacting proteins between different experiments (data not shown).

3.1.3. Some constructs do not lead to detectable particle production, possibly due to activation of immunological pathways 3.1.3.1. Bait proteins not resulting in Virotrap particle production Some constructs proved to be far more challenging as bait proteins in Virotrap. When using Mal as the bait protein, no particle formation was observed whatsoever (e.g. no Gag, bait or

VSV-G was found). The same problem was seen for IRAK-4 and to a lesser extent TRIF. Interestingly, the intracellular domains of TLR2 and -4 also gave rise to similar problems: TLR2-IC showed no discernible particle formation either, while TLR4-IC did form particles, though without interacting with any of its main adaptors (Mal, MyD88, TRAM or TRIF), which can be explained if the structure of the VLP does not allow the TLR fragments to associate in such a way that activation follows. One possible explanation for the defective particle formation for certain bait constructs, would simply be the activation of anti-viral pathways by the bait components, which interfere with Gag assembly (see also 1.4.4.). This explanation stems from another experiment conducted by the research group, where TAK1 (also see fig. 8) was used as the bait and also did not lead to any particle formation. From literature, it is well-known that an association between TAK1 and the anti-viral protein TRIM5α exists. We postulated it was possible that some constructs activated pathways involving TAK1 and TRIM5α, thus inducing the antiviral properties of TRIM5α.

3.1.3.2. An NF-κB luciferase assay revealed a link between difficulties with particle production and NF-κB activation To assess which constructs led to functional signaling and thereby possibly led to particle inhibition, an NF-κB reporter assay was used on all constructs as described in the methods section. Fig. 11 shows a plot with the average read-out values of this assay for each construct.

Figure 11. Average values of the NF-κB reporter assay. The X-axis shows the Gag-bait constructs that were assayed, NR signifies the addition of non-relevant pSVsport construct (see also annex A.II.) The y-axis shows the average read-out value for a given construct. Two separate charts were made due to the large differences in read-out values for the constructs. Error bars show + and - one standard deviation.

The positive control showed no increase in read-out value when compared to the negative

control, an observation that might be explained by the fact that the DNA used was not specifically endotoxin-free or the fact that HEK293T cells were used, which do give an increased background signal in TLR4 pathway reconstitution experiments when compared to HEK293 cells, therefore possibly masking the signal normally induced by LPS (F. Peelman, personal communication). As no fold induction could be deducted for LPS, it is impossible to indicate how strong a construct activated the NF-κB pathway compared to LPS stimulation. However, a definite trend can be seen in the read-outs of other constructs when compared to the negative controls. First and foremost, PYCARD did not induce an increased reporter expression, which is consistent with reports that PYCARD does not elicit but rather inhibits NF-κB activation (58). TLR2 and -4 also did not induce a high increase in reporter expression. From this, it may be assumed that overexpressed TLR2 and -4 do not necessarily associate to form an active signaling platform, therefore explaining our lack of results with these constructs. As expected due to the toxicity seen with MyD88, MyD88 did induce activation of the signaling cascade. Interestingly, MyD88-TIR in a low dose did not activate NF-κB, while a high dose did induce some NF-κB activation. This is unexpected, as MyD88-TIR should be deficient for downstream signaling due to the missing DD for interaction with IRAKs. However, this does illustrate the unnatural situation created by forced overexpression of proteins. One possible explanation for this observation could be that MyD88-TIR simply engages endogenous full-length MyD88 to form active signaling complexes. The results for the constructs that did not lead to efficient particle formation are interesting, as Mal, TRIF, IRAK-2 and high-dose IRAK-4 show very high induction of NF-κB. This indicated our theory of activation of antiviral mechanisms could indeed be a possibility. The most remarkable observation is probably the extremely high induction of NF-κB by IRAK-3, a protein known for its inhibitory role in TLR signaling. However, as mentioned before (1.2.2.1.), IRAK-3 does indeed induce NF-κB signaling, only with a repressive transcriptional program as a result. As such, simply looking at NF-κB activation does not necessarily indicate which baits might prove to be difficult, however, it did give us some indication as to why some baits might not have worked in the current Virotrap set-up.

3.2. Validation experiments for novel MyD88-TIR and MyD88 interaction partners 3.2.1. RNF115, ULK3 and WDR36 interact with MyD88-TIR, and PKP2 interacts with MyD88-TIR and MyD88 in a MAPPIT assay MyD88 and MyD88-TIR were tested as a bait with several prey construct. Results are shown in fig. 12. Of the 7 possible MyD88(TIR) interactors, 4 could be confirmed by MAPPIT to

some extent. Rabring7 (called RNF115 in fig. 12), which was identified in Virotrap with both MyD88 and MyD88-TIR, was confirmed convincingly in MAPPIT for MyD88-TIR and showed the highest signal of all tested novel interactors. PKP2 was identified in Virotrap for MyD88, though an interaction was seen for both MyD88 and MyD88-TIR in MAPPIT. ULK3 and WDR36 were originally identified in Virotrap with MyD88 as the bait protein, though in MAPPIT the interactions were reproduced with MyD88-TIR only and the signal was limited.

Figure 12. Results of a MAPPIT assay using MyD88-TIR and MyD88 as a bait. All new MyD88 interacting protein were assayed twice in a MAPPIT assay, every assayed 96 well plate included the controls EFHA1, Mal and the empty prey vector. Results shown in the graph are representative results from all assayed plates. It should be noted that for Mal, several plates did not show any induction after stimulation. However, as these plates also included an EFHA1 control that did show induction, these plates were retained for analysis. The figure shows a representative value only for those plates were Mal led to a signal.

3.2.2. G3BP1 and FAM188A co-precipitate with MyD88 All prey construct were also tested in a co-precipitation assay with full-length MyD88. Initially, co-precipitation could be confirmed for G3BP1, TRMT6, FAM188A and the positive control Mal, however, these proteins were also clearly visible in the bead control samples (Annex B.III.). Rabring7, WDR36, PKP2 and ULK3 were not visible on initial WB analysis (Annex B.III.), both in the immunoprecipitated supernatant and in cell lysates, leading us to investigate whether these proteins are associated with the insoluble fraction during lysis. For Rabring7 and PKP2 this could indeed be confirmed (Annex B.III.). To reduce the background signals seen in the bead controls, the experiment was repeated using the more stringent RIPA buffer. In this experiment (fig. 13) G3BP1 and FAM188A again co-

precipitated with MyD88, and the signal now indeed was greatly enriched compared to the bead control, indicating a true interaction. For TRMT6, the signal for the co-IP was not greatly enriched compared to the bead control, indicating this was most likely a non-specific interaction. Interestingly, PKP2 was now visible on lysates, however, no co-precipitation was seen. It should be noted that expression of MyD88 also seemed decreased in the samples with PKP2. A possibility would be that PKP2 is still partially retained in the insoluble fraction, and that MyD88 is also retained due to interaction with PKP2. Rabring7, WDR36 and ULK3 however, were still not visible in the lysates (data not shown).

Figure 13. Co-IP using MyD88 as a bait protein. The top two rows show the signal obtained with an anti-Myc polyclonal antibody, indicating presence of the prey proteins. The second row shows signal obtained with anti- FLAG, indicating presence of the bait protein MyD88. For the bead control (‘bead ctrl’) condition, supernatant was incubated with beads without any bound antibody. For clarity, signals shown here were enhanced, however, a sample and its bead control were consistently enhanced in the exact same manner. The original blots are included in Annex B.III.

3.2.3. RNF115 may function as a negative regulator in TLR signaling A549 were transfected with siRNAs targeting Rabring7, FAM115A, FAM188A. Non- targeting siRNA was used as a negative control, and PLK1-siRNA functioned as a positive control (fig. 14). The increase in apoptosis in PLK1-siRNA transfected cells shows transfection was efficient, as PLK1 knockdown has been shown to increase apoptosis approximately threefold in A549 cells (59).

Figure 14. Condition of A549 cells 48 hours post-transfection. A. Untransfected controls; B. Mock transfection; C. PLK1 siRNA; D. non-targeting siRNA; E. RNF115; F. FAM115A; G. FAM188A.

qRT-PCR analysis was carried out on mRNA for several TLR signaling targets. The results are shown in fig. 15. Most importantly, there is no real difference between the unstimulated and LPS stimulated non-transfected control samples, indicating that either our specific batch of A549 cells is not sufficiently responsive to LPS, or that the LPS itself did not elicit a response. As a result, it is impossible to make definitive conclusions based on these results.

Figure 15. qPCR analysis of four TLR target genes in control and siRNA transfected cells, both with and without LPS. The X-axis signifies the tested siRNAs and controls. Values on the y-axis are calibrated normalized relative quantities (CNRQs) as calculated with Qbase+.

However, when only comparing gene expression in the different unstimulated conditions (fig. 16), the results do suggest that Rabring7 may indeed have an influence on TLR signaling: basal levels of TLR target genes seem to be elevated when Rabring7 is knocked down, indicating that this protein may have a function in inhibiting basal activity. What the exact function of Rabring7 is in the activated pathway cannot be determined from this experiment.

Figure 16. Comparison of gene expression in several unstimulated conditions. The X-axis signifies the tested siRNAs and controls. Values on the y-axis are CNRQs as calculated with Qbase+.

3.3. Generation of a TRIM5 deficient HEK293T cell line and use of these cells in MS experiments In an attempt to circumvent any possible interference in particle formation by TRIM5α, we set out to create a TRIM5 deficient HEK293T cell line with CRISPR-Cas9. SgRNAs were used in several combinations, leading to 8 different knock-out conditions. After SURVEYOR nuclease digest, we selected three conditions where genome editing was most successful, based on the intensity of the full length and cut bands present on agarose gel electrophoresis (fig. 17, lanes 5, 6 and 11). Interestingly, as can be seen in lane 4, wild-type HEK293T cells also show cut bands, indicating wild-type HEK293T cells have heterogenous DNA at the TRIM5 locus. The presence of a SNP could indeed be verified with the large-scale HEK293 sequencing effort by Callewaert et al. (under review).

Figure 17. Analysis of SURVEYOR fragments. Lane 1: SmartLadder; lane 2: SURVEYOR negative control; lane 3: SURVEYOR positive control; lane 4: wild-type HEK293T cells; lane 5: Cas9 + pair 1 5' sgRNA; lane 6: Cas9 + 3' sgRNA; lane 7: Cas9 + pair 2 5' sgRNA; lane 8: Cas9 + pair 2 3' sgRNA; lane 9: Cas9 + full pair 1; lane 10: Cas9 + full pair 2 ; lane 11: Cas9n + full pair 1 ; lane 12: Cas9n + full pair 2.

To assay whether disabling the TRIM5 gene was sufficient to restore particle production for certain baits, a pilot experiment was carried out with the Cas9/pair 1 5’ sgRNA cells, with TAK1 as a bait protein, as this is the protein that is most closely linked to TRIM5α. However, MS results of this experiments did not reveal high particle production, as only some VSV-G peptides, but no Gag or TAK1 peptides were identified. It should be noted that the MS profile showed a high concentration of peptides or proteins eluting at the end of the nano-LC run, which may indicate a problem during trypsin digest.

3.4. Expanding Virotrap to other cell lines 3.4.1. MEF cells are currently not suitable for Virotrap due to inefficient transfection 3.4.1.1. PEI transfections PEI transfections in MEF cells proved to be suboptimal, as only low transfection efficiency (as measured by eGFP expression) was observed, combined with high toxicity. In a first experiment, PEI:DNA ratios of 2:1, 3:1 and 5:1 were tested both with low (~1 µg) and high (~2,75 µg) amounts of DNA. Visual inspection showed the 5:1 ratio was the most efficient, though high PEI/DNA concentrations led to toxicity (data not shown). Fig. 18 shows eGFP expression of a second PEI optimization experiment, using a range of total PEI amounts in a 5:1 ratio with the DNA. One condition with Lipofectamine LTX was already included here, as high efficiency had been obtained previously in the lab when using 20 µl Lipofectamine LTX with 2.5 µg DNA.

Figure 18. Flow cytometry of several PEI transfection conditions in MEF cells. The FL1-H channel shows the eGFP signal. In all experiments, the M1 gate was chosen in such a way that virtually no positive counts were assigned to the control sample. Numbers in the right upper corner indicate the percentage of cells in the M1 gate.

3.4.1.2. Lipofectamine LTX transfections While Lipofectamine is generally the best class of reagents for MEF cells, eGFP expression was not consistent and only reached a high efficiency in one specific experiment. Several experiments were carried out with varying conditions of amount of DNA and Lipofectamine LTX, shown in fig. 19.

Figure 19. Transfection efficiencies in MF cells under several conditions. The first row shows an experiment using several amounts of LTX, as indicated in the manufacturer’s optimization instructions. The best conditions were assayed with several amounts of DNA in rows 2 and 3, as lower DNA amount can improve tolerability. This experiment was also repeated with a new Lipofectamine LTX batch (rows 4 and 5).

As can be seen in fig. 19, the transfection efficiency was not consistent. For example, the condition using 15 µl Lipofectamine LTX with 2,5 µg DNA resulted in 79.17% and 52.80% transfection efficiency in the first and second optimization experiment respectively. When a new batch of Lipofectamine LTX was started, efficiency dropped even lower (30.7%), indicating inconsistency may even be an intrinsic factor of the reagent. At the lab of Prof. J. Tavernier, results higher than 90% efficiency have been observed. Therefore, new MEF cells were obtained from their liquid nitrogen stock and the optimization 38

experiments were repeated one last time, to check whether the insufficient efficiency could be related to our specific cells (fig. 20). However, for these new MEFs, transfection efficiency was even lower than in our previous experiments. As Virotrap requires high and consistent transfection efficiency, the experiments in MEF cells were discontinued at this point.

Figure 20. Transfection efficiency of two different MEF cell lines. The top row shows eGFP expression in the MEF cells that were used in previous experiments, while the bottom rown shows MEF cells obtained from the lab of Prof. J. Tavernier.

3.4.2. Jurkat cells may be used in Virotrap, but require additional optimization 3.4.2.1. Determination of optimal DNA concentration As the Neon protocol recommends optimizing the amount of DNA used per nucleofection, a pilot experiment was carried out with 1, 2 and 3 µg total DNA per 10 µl cells, using eGFP as a bait protein. Transfection efficiencies as measured by flow cytometry are shown in fig. 20. Transfection efficiency was similar in transfections with 1 and 2 µg DNA, though there appeared to be more toxicity when 2 µg DNA was used (data not shown). Further experiments were carried out with 1.5 µg DNA per 10 µl cells based on these results.

Figure 21. Flow cytometry of eGFP transfected Jurkats. The FL1-H channel shows the eGFP signal. The M1 gate was again chosen in such a way that virtually no positive counts were assigned to the control sample. Numbers in the right upper corner indicate the percentage of cells in the M1 gate.

3.4.2.2. Exploration of binary Virotrap with Jurkat cells One pilot experiment was carried out using a standard set of binary interactions that give well-characterized results in HEK293T cells, namely MyD88-TIR-Mal (positive control),

eGFP-Mal (transfection control) and MyD88-TIR-FADD (negative control). Visual inspection showed transfection efficiency was in the expected range. No Myc-signal was detected for the positive control in the supernatant, and no clear signal could be obtained for Gag either, indicating particle formation was not optimal in this set-up (data not shown). Further experiments were carried out using MS, as this is the main Virotrap set-up for exploring interactions on a larger scale.

3.4.2.3. MS experiments with A20 The first Jurkat Virotrap experiment with A20 resulted in a large amount of purified proteins, however, the main components of the VLP (Gag, A20, VSV-G) were not identified in the sample by MS. We repeated this experiment a second time, substituting the non-relevant DNA for additional Gag-bait construct to increase the expression. In this experiment, Gag, A20 and VSV-G were identified by MS, however, their intensity was still overshadowed by a high amount of background proteins. For this reason, we repeated the experiment and substituted the RPMI + 10% FBS plating medium for Opti-MEM + 2% FBS, as survival of Jurkat cells under these conditions was still favorable (table 7).

Table 7. Survival of Jurkat cells in Opti-MEM medium 0% FBS 1% FBS 2% FBS 5% FBS 10% FBS Cell viability 90% 89% 94% 99% 99% 5 5 5 5 5 Cell number 2,5.10 3,1.10 4,9.10 5,3.10 4,8.10 An equal number of Jurkat cells was kept in Opti-MEM medium with the indicated amounts of FBS for 48h. Survival and cell number of the 5% and 2% conditions were comparable to the 10% FBS condition..

In this experiment with reduced background, signals were still in the same range as in the previous experiments, and VSV-G was not detected at all, leading us to believe to VSV-G to Gag ratio was not optimal. One last experiment was carried out, scaling up the amount of VSV-G mix (4,29 µg VSV-G mix and 10,71 µg Gag-A20 per 100 µl cells), which did result in the identification of VSV-G, but still with a very low Mascot score. A20 and Gag were also identified, with scores comparable to previous experiments.

4. DISCUSSION 4.1. Virotrap is an exciting novel option for exploring protein-protein interactions in intact mammalian cells 4.1.1. Virotrap revealed Rabring7 as a likely novel interaction partner of MyD88 MyD88 interacted with two known partners, IRAK-1 and IRAK-4, along with a number of novel interacting proteins previously not identified. IRAK-4 was not retained in the analysis, as it was only identified by one specific peptide by MS, indicating that the stringency of analysis still eliminates true interactors. It should be noted that this is a feature shared by almost all technologies for studying protein interactions. Some of the novel interactions were firstly validated through MAPPIT and co-IP in HEK293T cells to evaluate the interactions themselves, independent of their functional relevance. Interactions could be reproduced in MAPPIT for Rabring7, PKP2, WDR36 and very weakly for ULK3, while co-IP confirmed FAM188A and TRMT6, though co-IP results should be treated with caution, as there was still a certain amount of background in these experiments, even with a stringent buffer. A negative result in one of these confirmation experiments does not automatically mean that the interaction identified by Virotrap is a false positive. As discussed earlier, most PPI methods are only capable of detecting a limited percentage of all interactions in a cell and Virotrap may detect true interactions that simply cannot be identified through other methods. The most striking example of such a situation is Rabring7. This protein was detected with both MyD88 and MyD88-TIR in Virotrap, and could be confirmed using a MAPPIT assay with MyD88- TIR. The reporter gene induction was even in the same range as that of the MyD88-TIR-Mal interaction. However, when a co-IP experiment was attempted using Rabring7 as a prey protein, Rabring7 could not be detected in control lysates. After examination of the insoluble fraction, it could be concluded that Rabring7 is associated with the insoluble fraction, and as such can not be detected in experiments relying on protocols which require cellular lysis. This could be an indication as to why Rabring7 has remained unidentified as a MyD88 interactor, since large scale experiments are often conducted with affinity based protocols requiring lysis. This also illustrates how Virotrap can become a complimentary method to currently available co-complex analysis approaches such as AP-MS, thereby bringing us one step closer to full coverage of the interactome.

Three MyD88 interactors were also tested in a functional assay using siRNA knockdown, which revealed a possible functional role for Rabring7 in TLR signaling. Basal transcription levels of TLR target genes CCL5 and TNFA were increased when Rabring7 was knocked

down using siRNA, indicating an influence of Rabring7 on both MyD88-dependent and independent pathways. As LPS did not induce increased TLR target gene expression in our A549 cells, we could not investigate whether Rabring7 only had an influence on basal levels of gene expression, or also on negative regulation of the activated TLR signaling pathways. A549 cells have previously been reported to be insensitive to LPS mediated TLR4 activation if no normal human serum (NHS) containing soluble CD14 is added (60), however, A549 cells have been used successfully to study TLR signaling by T. Van Acker at the lab of Prof. F. Peelman (personal communication). This indicates that the response of A549 cells to LPS may differ between batches of this cell line. A possible next step would be to repeat the experiment in the presence of NHS, or in a cell line that is consistently responsive to LPS without the need for the addition of co-receptors. In any case, it will be interesting to further study the role of Rabring7 on TLR signaling, as Rabring7 is phosphorylated and subsequently stabilized by the kinase Akt (61), a protein that has been implicated in negative regulation of TLR signaling (62, 63), though the exact mechanisms of this are still controversial. However, one other observation does argue against a role for Rabring7 as an inhibitor of innate immune signaling: Rabring7 has also been shown to promote restriction of HIV-1 particle release by co-operating with the antiviral restriction factor tetherin (64). This suggests Rabring7 promotes antiviral activity, while our results suggest a more anti-inflammatory function. From this, it is clear that additional research is necessary to elucidate the exact role of Rabring7 in TLR signaling.

4.1.2. Other bait proteins With other bait proteins some interacting proteins were also identified. Interestingly, an entire complex was isolated with IRAK-3 as a bait, none of which were previously known interaction partners (data not shown). While this gives a lot of information about possible larger protein complexes, it also illustrates one difficulty for interpretation of co-complex analyses: it is nearly impossible to determine which interactions were direct interactions with the bait. During these experiments, it also became clear that sensitivity of the MS runs was decreased for several of these experiments. Several factors could be causing a drop in sensitivity, and currently it is being investigated which factor is responsible. The most likely possibility is a less efficient batch of HiPPR detergent removal columns: if SDS is not completely removed this can interfere with the trypsin digest, thus leading to less identifiable peptides.

4.2. Virotrap currently exhibits some limiting factors 4.2.1. Interference with particle production There were a few bait proteins that did not result in detectable particle production. As these constructs were generally capable of inducing a high signal in an NF-κB activation assay, it is suspected these constructs lead to the activation of some immunological pathway interfering with viral particle production. As TRIM5α is a retroviral restriction factor functioning via TAK1, the first bait that was noticed to have this problem, it was attempted to resolve this issue by knocking out TRIM5 in HEK293T cells using CRISPR-Cas9. No increase in particle production was observed when TAK1 was used as a bait with these genetically engineered cells, which could be explained by several factors. First, the nano-LC MS profile of this experiment showed a high amount of molecules eluting very late in the run, which again may indicate a problem during trypsin digestion of the sample. As discussed in 4.1.2., this could be due to a problem with the HiPPR detergent removal columns. Second, HEK293T cells have three copies of the TRIM5 gene (Callewaert et al., submitted). As CRISPR-Cas9 genome engineering does not automatically result in homozygous cell lines, residual TRIM5α may have been present in the cells if one of the copies remained functional. In future experiments, it is advisable to isolate clonal cell lines from the engineered cell culture, followed by targeted sequencing to verify perturbation of all three functional copies of the gene. A third option is simply that either TRIM5α is not actually responsible for the interference with particle production, or that TRIM5α is not the only viral restriction factor involved in this process. Mammalian cells use a wide array of antiviral mechanisms, that are often perturbed by accessory proteins of the infectious virus (65). Because the Virotrap system does not use an entire functional virus, it is not impossible some of these antiviral mechanisms can interfere with Virotrap. One example of an antiviral defense mechanisms that can theoretically interfere with Virotrap is the host transmembrane protein tetherin. This IFN-inducible protein is incorporated into viral particles and subsequently traps the secreted virions onto the cellular membrane, resulting in the inhibition of particle release (66). In cells expressing tetherin, this process is antagonized by the HIV-1 accessory protein Vpu (67). Note that the antiviral strategies mentioned here rely on factors normally induced by IFN, while an NF-κB assay showed the more challenging constructs induced high NF-κB activation. This seems counterintuitive, but TLR pathways inducing NF-κB (such as TLR4) and IRF (such as TLR7, -8 and -9) do share several signaling proteins, including MyD88, IRAK-1 and -4 (29), indicating it is still possible the interference seen with some of these constructs is indeed (partly) IRF or IFN-dependent. Interestingly, tetherin is indeed strongly upregulated in

HEK293T cells after IFN treatment (67). Which factors are responsible for interference may even be cell-type dependent, as cells can generally exhibit a range of responses to certain stimuli. Therefore, it may be interesting to directly study the effect of Gag-bait construct overexpression on the transcription of known host restriction factors such as TRIM5α and tetherin in cell lines of interest. This will clearly show which factors are responsible for inhibiting particle production and/or release, independent of the pathway they are induced by. If the precise factors involved can be identified, they are relatively easy to disable using genome engineering technologies such as CRISPR-Cas9. Therefore, we can be confident the limitations seen when using certain baits that may activate immunological defense mechanisms, can be resolved in the future.

4.2.2. Virotrap in other cell lines requires additional optimization When we attempted to expand Virotrap to MEF cells, it quickly became clear that Virotrap will be limited to cells that can be transfected with high efficiency. As we did not obtain consistent high transfection efficiency in MEF cells, Virotrap currently can not be used in these cells. In the future, attempts to use Virotrap in MEF cells may be undertaken again. For example, while PEI transfections were not highly efficient, extensive optimization may increase efficiency to an acceptable level. A first option would be to assess other types of PEI transfection reagent, as this polymer is available in both linear and branched forms, with several molecular weights. Extensive protocols are available, even for primary cells, where additional parameters such as salt concentration and even culturing conditions are optimized (68). With cost-effective reagents such as PEI, it would not be a major obstacle if 20-30% extra cells have to be transfected to obtain the same total number of transfected cells as with HEK293T cells. Also, other commercial reagents can be tested for transfection efficiency and consistency in MEF cells, though cost then becomes an important consideration.

For Jurkat cells, the availability of a good transfection protocol with the Neon system does facilitate the expansion of Virotrap to these cells. At the end of this project, it was possible to produce particles in Jurkat cells, however, efficiency is not optimal yet: not enough particles are produced to identify interacting proteins by MS. Several steps can still be taken to optimize this. First, the standard concentration for DNA stocks at the lab is 1 µg/µl, though this means DNA takes up a large volume in the mix that is used for nucleofection with the Neon system. Using a higher DNA concentration will result in decreased dilution of the Neon buffers, which may further increase efficiency of the system. A second option would be to

scale up the entire experiment, however, as the Neon system is expensive, this would mean Virotrap will be reserved for very specific experiments in Jurkat cells, not for general screens. Also note that antiviral mechanisms mentioned earlier may also come into play in Jurkat cells. In any case, the experiments with Jurkat cells do show that when sufficiently high transfection efficiency can be obtained, the production of particles starts. This indicates Virotrap may also be expandable to other cell types, as long as there are efficient transfection options available, that are still cost-effective enough to be carried out on a large scale.

5. CONCLUSION Virotrap has proven to be a powerful new method for protein complex analysis. Several possible new interactors were identified for the central TLR signaling protein MyD88, though additional experiments need to be carried out to determine whether all these identified protein are not only true interactors, but also have functional relevance in TLR signaling. For Rabring7 a possible functional relevance was already shown through siRNA knock-down, though the exact mechanisms and magnitude of the influence remain to be determined. The observation that for some bait proteins particle formation was unsuccessful exposed a possible weakness of the Virotrap system. As this method is based on production of viral structures, the induction of any kind of generalized antiviral state (e.g. due to expression of inflammatory proteins) will interfere with the process. The viral restriction factor TRIM5α was eliminated from HEK293T cells to test whether this could be the factor responsible for inhibiting particle production, as this factor is closely associated with some of the bait proteins that failed to produce detectable particles. When this TRIM5 deficient cell line was used for Virotrap with TAK1, no direct effect was observed, however, we identified some other factors that could explain this problem. Therefore, it is still an interesting area to optimize further, and the research group will continue to explore this. In theory, other factors besides TRIM5 may be involved as well, indicating an in-depth characterization of antiviral strategies activated by the Virotrap system would be highly relevant to further improve the system. To increase versatility of the Virotrap system, we have attempted to expand the technology to other cell lines. In MEF cells this was greatly hindered by a lack of efficient and reproducible transfection methods. For Jurkat cells a certain degree of success was achieved, as MS experiments revealed particle production to some extent. However, particle production was limited and thus insufficient to detect novel interaction partners. In any case, this does show Virotrap has the potential to be expanded to other cell lines, though requiring efficient transfection methods and cell-specific optimization. Also, restriction factors that are possibly induced by active immune signaling in HEK293T cells, may even be constitutively active in other cell types, which means cell type-specific optimization may also need to include a characterization of restriction factors active in the cell type of interest.

6. REFERENCE LIST 1. Vogel C & Marcotte EM (2012) Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet 13(4):227-232. 2. Lievens S, Eyckerman S, Lemmens I, & Tavernier J (2010) Large-scale protein interactome mapping: strategies and opportunities. Expert Rev Proteomics 7(5):679-690. 3. Walhout AJ & Vidal M (2001) High-throughput yeast two-hybrid assays for large-scale protein interaction mapping. Methods 24(3):297-306. 4. Oeffinger M (2012) Two steps forward--one step back: advances in affinity purification mass spectrometry of macromolecular complexes. Proteomics 12(10):1591-1608. 5. Fields S & Song O (1989) A novel genetic system to detect protein-protein interactions. Nature 340(6230):245-246. 6. Rual JF, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, Li N, et al. (2005) Towards a proteome- scale map of the human protein-protein interaction network. Nature 437(7062):1173-1178. 7. Eyckerman S, Verhee A, der Heyden JV, Lemmens I, Ostade XV, Vandekerckhove J, et al. (2001) Design and application of a cytokine-receptor-based interaction trap. Nat Cell Biol 3(12):1114-1119. 8. Aaronson DS & Horvath CM (2002) A road map for those who don't know JAK-STAT. Science 296(5573):1653-1655. 9. Shuai K & Liu B (2003) Regulation of JAK-STAT signalling in the immune system. Nat Rev Immunol 3(11):900-911. 10. Lievens S, Vanderroost N, Van der Heyden J, Gesellchen V, Vidal M, & Tavernier J (2009) Array MAPPIT: high-throughput interactome analysis in mammalian cells. J Proteome Res 8(2):877-886. 11. Ren L, Emery D, Kaboord B, Chang E, & Qoronfleh MW (2003) Improved immunomatrix methods to detect protein:protein interactions. J Biochem Biophys Methods 57(2):143-157. 12. Gingras AC, Gstaiger M, Raught B, & Aebersold R (2007) Analysis of protein complexes using mass spectrometry. Nat Rev Mol Cell Biol 8(8):645-654. 13. Rigaut G, Shevchenko A, Rutz B, Wilm M, Mann M, & Seraphin B (1999) A generic protein purification method for protein complex characterization and proteome exploration. Nat Biotechnol 17(10):1030- 1032. 14. Malovannaya A, Lanz RB, Jung SY, Bulynko Y, Le NT, Chan DW, et al. (2011) Analysis of the human endogenous coregulator complexome. Cell 145(5):787-799. 15. Kristensen AR, Gsponer J, & Foster LJ (2012) A high-throughput approach for measuring temporal changes in the interactome. Nat Methods 9(9):907-909. 16. Roux KJ, Kim DI, Raida M, & Burke B (2012) A promiscuous biotin ligase fusion protein identifies proximal and interacting proteins in mammalian cells. J Cell Biol 196(6):801-810. 17. Sinz A (2010) Investigation of protein-protein interactions in living cells by chemical crosslinking and mass spectrometry. Anal Bioanal Chem 397(8):3433-3440. 18. Mellacheruvu D, Wright Z, Couzens AL, Lambert JP, St-Denis NA, Li T, et al. (2013) The CRAPome: a contaminant repository for affinity purification-mass spectrometry data. Nat Methods 10(8):730-736. 19. von Mering C, Krause R, Snel B, Cornell M, Oliver SG, Fields S, et al. (2002) Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417(6887):399-403. 20. Berggard T, Linse S, & James P (2007) Methods for the detection and analysis of protein-protein interactions. Proteomics 7(16):2833-2842. 21. Braun P, Tasan M, Dreze M, Barrios-Rodiles M, Lemmens I, Yu H, et al. (2009) An experimentally derived confidence score for binary protein-protein interactions. Nat Methods 6(1):91-97. 22. Chen YC, Rajagopala SV, Stellberger T, & Uetz P (2010) Exhaustive benchmarking of the yeast two- hybrid system. Nat Methods 7(9):667-668; author reply 668. 23. Venkatesan K, Rual JF, Vazquez A, Stelzl U, Lemmens I, Hirozane-Kishikawa T, et al. (2009) An empirical framework for binary interactome mapping. Nat Methods 6(1):83-90. 24. Royer M, Hong SS, Gay B, Cerutti M, & Boulanger P (1992) Expression and extracellular release of human immunodeficiency virus type 1 Gag precursors by recombinant baculovirus-infected cells. J Virol 66(5):3230-3235. 25. Briggs JA, Simon MN, Gross I, Krausslich HG, Fuller SD, Vogt VM, et al. (2004) The stoichiometry of Gag protein in HIV-1. Nat Struct Mol Biol 11(7):672-675. 26. Latz E, Visintin A, Lien E, Fitzgerald KA, Monks BG, Kurt-Jones EA, et al. (2002) Lipopolysaccharide rapidly traffics to and from the Golgi apparatus with the toll-like receptor 4-MD-2-CD14 complex in a process that is distinct from the initiation of signal transduction. J Biol Chem 277(49):47834-47843. 27. Werts C, Girardin SE, & Philpott DJ (2006) TIR, CARD and PYRIN: three domains for an antimicrobial triad. Cell Death Differ 13(5):798-815. 28. Kawai T & Akira S (2006) TLR signaling. Cell Death Differ 13(5):816-825. 29. O'Neill LA & Bowie AG (2007) The family of five: TIR-domain-containing adaptors in Toll-like receptor 47

signalling. Nat Rev Immunol 7(5):353-364. 30. Medzhitov R, Preston-Hurlburt P, Kopp E, Stadlen A, Chen C, Ghosh S, et al. (1998) MyD88 is an adaptor protein in the hToll/IL-1 receptor family signaling pathways. Mol Cell 2(2):253-258. 31. Janssens S & Beyaert R (2002) A universal role for MyD88 in TLR/IL-1R-mediated signaling. Trends Biochem Sci 27(9):474-482. 32. Kawai T, Adachi O, Ogawa T, Takeda K, & Akira S (1999) Unresponsiveness of MyD88-deficient mice to endotoxin. Immunity 11(1):115-122. 33. Burns K, Janssens S, Brissoni B, Olivos N, Beyaert R, & Tschopp J (2003) Inhibition of interleukin 1 receptor/Toll-like receptor signaling through the alternatively spliced, short form of MyD88 is due to its failure to recruit IRAK-4. J Exp Med 197(2):263-268. 34. Ulrichts P, Peelman F, Beyaert R, & Tavernier J (2007) MAPPIT analysis of TLR adaptor complexes. FEBS Lett 581(4):629-636. 35. Gray P, Dunne A, Brikos C, Jefferies CA, Doyle SL, & O'Neill LA (2006) MyD88 adapter-like (Mal) is phosphorylated by Bruton's tyrosine kinase during TLR2 and TLR4 signal transduction. J Biol Chem 281(15):10489-10495. 36. Piao W, Song C, Chen H, Wahl LM, Fitzgerald KA, O'Neill LA, et al. (2008) Tyrosine phosphorylation of MyD88 adapter-like (Mal) is critical for signal transduction and blocked in endotoxin tolerance. J Biol Chem 283(6):3109-3119. 37. Yamamoto M, Sato S, Hemmi H, Hoshino K, Kaisho T, Sanjo H, et al. (2003) Role of adaptor TRIF in the MyD88-independent toll-like receptor signaling pathway. Science 301(5633):640-643. 38. Yamamoto M, Sato S, Hemmi H, Uematsu S, Hoshino K, Kaisho T, et al. (2003) TRAM is specifically involved in the Toll-like receptor 4-mediated MyD88-independent signaling pathway. Nat Immunol 4(11):1144-1150. 39. Rowe DC, McGettrick AF, Latz E, Monks BG, Gay NJ, Yamamoto M, et al. (2006) The myristoylation of TRIF-related adaptor molecule is essential for Toll-like receptor 4 signal transduction. Proc Natl Acad Sci U S A 103(16):6299-6304. 40. Akira S & Takeda K (2004) Toll-like receptor signalling. Nat Rev Immunol 4(7):499-511. 41. Janssens S & Beyaert R (2003) Functional diversity and regulation of different interleukin-1 receptor- associated kinase (IRAK) family members. Mol Cell 11(2):293-302. 42. Kawagoe T, Sato S, Matsushita K, Kato H, Matsui K, Kumagai Y, et al. (2008) Sequential control of Toll- like receptor-dependent responses by IRAK1 and IRAK2. Nat Immunol 9(6):684-691. 43. O'Neill LA (2008) The interleukin-1 receptor/Toll-like receptor superfamily: 10 years of progress. Immunol Rev 226:10-18. 44. Kobayashi K, Hernandez LD, Galan JE, Janeway CA, Jr., Medzhitov R, & Flavell RA (2002) IRAK-M is a negative regulator of Toll-like receptor signaling. Cell 110(2):191-202. 45. Zhou H, Yu M, Fukuda K, Im J, Yao P, Cui W, et al. (2013) IRAK-M mediates Toll-like receptor/IL-1R- induced NFkappaB activation and cytokine production. Embo j 32(4):583-596. 46. Boone DL, Turer EE, Lee EG, Ahmad RC, Wheeler MT, Tsui C, et al. (2004) The ubiquitin-modifying enzyme A20 is required for termination of Toll-like receptor responses. Nat Immunol 5(10):1052-1060. 47. O'Neill LA, Golenbock D, & Bowie AG (2013) The history of Toll-like receptors - redefining innate immunity. Nat Rev Immunol 13(6):453-460. 48. Horvath P & Barrangou R (2010) CRISPR/Cas, the immune system of bacteria and archaea. Science 327(5962):167-170. 49. Ran FA, Hsu PD, Wright J, Agarwala V, Scott DA, & Zhang F (2013) Genome engineering using the CRISPR-Cas9 system. Nat Protoc 8(11):2281-2308. 50. Jinek M, Chylinski K, Fonfara I, Hauer M, Doudna JA, & Charpentier E (2012) A programmable dual- RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337(6096):816-821. 51. Ran FA, Hsu PD, Lin CY, Gootenberg JS, Konermann S, Trevino AE, et al. (2013) Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity. Cell 154(6):1380-1389. 52. Homma T, Kato A, Hashimoto N, Batchelor J, Yoshikawa M, Imai S, et al. (2004) Corticosteroid and cytokines synergistically enhance toll-like receptor 2 expression in respiratory epithelial cells. Am J Respir Cell Mol Biol 31(4):463-469. 53. Kurt-Jones EA, Sandor F, Ortiz Y, Bowen GN, Counter SL, Wang TC, et al. (2004) Use of murine embryonic fibroblasts to define Toll-like receptor activation and specificity. J Endotoxin Res 10(6):419- 424. 54. Caron G, Duluc D, Fremaux I, Jeannin P, David C, Gascan H, et al. (2005) Direct stimulation of human T cells via TLR5 and TLR7/8: flagellin and R-848 up-regulate proliferation and IFN-gamma production by memory CD4+ T cells. J Immunol 175(3):1551-1557. 55. Pertel T, Hausmann S, Morger D, Zuger S, Guerra J, Lascano J, et al. (2011) TRIM5 is an innate immune sensor for the retrovirus capsid lattice. Nature 472(7343):361-365.

56. Asaoka K, Ikeda K, Hishinuma T, Horie-Inoue K, Takeda S, & Inoue S (2005) A retrovirus restriction factor TRIM5alpha is transcriptionally regulated by interferons. Biochem Biophys Res Commun 338(4):1950-1956. 57. Helsens K, Colaert N, Barsnes H, Muth T, Flikka K, Staes A, et al. (2010) ms_lims, a simple yet powerful open source laboratory information management system for MS-driven proteomics. Proteomics 10(6):1261-1264. 58. Sarkar A, Duncan M, Hart J, Hertlein E, Guttridge DC, & Wewers MD (2006) ASC directs NF-kappaB activation by regulating receptor interacting protein-2 (RIP2) caspase-1 interactions. J Immunol 176(8):4979-4986. 59. Spankuch-Schmitt B, Bereiter-Hahn J, Kaufmann M, & Strebhardt K (2002) Effect of RNA silencing of polo-like kinase-1 (PLK1) on apoptosis and spindle formation in human cancer cells. J Natl Cancer Inst 94(24):1863-1877. 60. Schulz C, Farkas L, Wolf K, Kratzel K, Eissner G, & Pfeifer M (2002) Differences in LPS-induced activation of bronchial epithelial cells (BEAS-2B) and type II-like pneumocytes (A-549). Scand J Immunol 56(3):294-302. 61. Bacopulos S, Amemiya Y, Yang W, Zubovits J, Burger A, Yaffe M, et al. (2012) Effects of partner proteins on BCA2 RING ligase activity. BMC Cancer 12:63. 62. Guha M & Mackman N (2002) The phosphatidylinositol 3-kinase-Akt pathway limits lipopolysaccharide activation of signaling pathways and expression of inflammatory mediators in human monocytic cells. J Biol Chem 277(35):32124-32132. 63. Schabbauer G, Tencati M, Pedersen B, Pawlinski R, & Mackman N (2004) PI3K-Akt pathway suppresses coagulation and inflammation in endotoxemic mice. Arterioscler Thromb Vasc Biol 24(10):1963-1969. 64. Miyakawa K, Ryo A, Murakami T, Ohba K, Yamaoka S, Fukuda M, et al. (2009) BCA2/Rabring7 promotes tetherin-dependent HIV-1 restriction. PLoS Pathog 5(12):e1000700. 65. Zheng YH, Jeang KT, & Tokunaga K (2012) Host restriction factors in retroviral infection: promises in virus-host interaction. Retrovirology 9:112. 66. Perez-Caballero D, Zang T, Ebrahimi A, McNatt MW, Gregory DA, Johnson MC, et al. (2009) Tetherin inhibits HIV-1 release by directly tethering virions to cells. Cell 139(3):499-511. 67. Neil SJ, Zang T, & Bieniasz PD (2008) Tetherin inhibits retrovirus release and is antagonized by HIV-1 Vpu. Nature 451(7177):425-430. 68. Hsu CY & Uludag H (2012) A simple and rapid nonviral approach to efficiently transfect primary tissue- derived cells using polyethylenimine. Nat Protoc 7(5):935-945.

ANNEXES A. Supplementary methods A.I. Background list for MS

Table AI. Overview of baits used in the background list for Virotrap data analysis Bait protein Number of experiments included in the background list Nck2 SH3 1 EGFP 2 TLR4-IC 2 (not included for the analysis of TLR4 experiments) LCP2 2 Pinch1 L4 1 p53 3 p73 1 EIF2C2 A/B/C 3 S100B 1 GRAP2 1 CKS1B 1 CDK2 1 The experiments included in the background list were selected based on their high number of spectra identified and their high score essential components of a Virotrap VLP (e.g. Gag, VSV-G). Having high scores for these components means particle formation was extremely successful, one can expect a variety of background proteins to have been isolated in a quantity that can be detected by MS.

A.II. Overview of DNA mixes used for the NF-κB reporter assay

Table A.II. Overview of all conditions in the NF-κB reporter assay Positive control 16 ng TLR4-FLAG, 16 ng mMD2, 16 ng mCD14, 4 ng conLuc (+ LPS) Negative control 16 ng TLR4-FLAG, 16 ng mMD2, 16 ng mCD14, 4 ng conLuc Negative control 48 ng mock, 4 ng conLuc MyD88 24 ng MyD88, 24 ng mock, 4 ng conLuc 48 ng MyD88, 4 ng conLuc MyD88-TIR 24 ng MyD88-TIR, 24 ng mock, 4 ng conLuc 48 ng MyD88-TIR, 4 ng conLuc TICAM1 24 ng TICAM1, 24 ng mock, 4 ng conLuc 48 ng TICAM1, 4 ng conLuc TICAM2 24 ng TICAM2, 24 ng mock, 4 ng conLuc 48 ng TICAM2, 4 ng conLuc TIRAP 24 ng TIRAP, 24 ng mock, 4 ng conLuc 48 ng TIRAP, 4 ng conLuc IRAK1 24 ng IRAK1, 24 ng mock, 4 ng conLuc 48 ng IRAK1, 4 ng conLuc IRAK2 24 ng IRAK2, 24 ng mock, 4 ng conLuc 48 ng IRAK2, 4 ng conLuc IRAK3 24 ng IRAK3, 24 ng mock, 4 ng conLuc 48 ng IRAK3, 4 ng conLuc IRAK4 24 ng IRAK4, 24 ng mock, 4 ng conLuc 48 ng IRAK4, 4 ng conLuc TLR4-IC 24 ng TLR4-IC, 24 ng mock, 4 ng conLuc 48 ng TLR4-IC, 4 ng conLuc TLR2-IC 24 ng TLR2-IC, 24 ng mock, 4 ng conLuc 48 ng TLR2-IC, 4 ng conLuc PYCARD 24 ng PYCARD, 24 ng mock, 4 ng conLuc 48 ng PYCARD, 4 ng conLuc As a reporter construct, pNFconluc (‘conLuc’) was used, which contains a luciferase gene under control of an NF-κB promoter sequence. All constructs were assayed in high and low concentrations. For the conditions with low concentrations, the plasmids were complemented with the non-relevant construct pSVsport (‘mock’) to maintain total DNA concentration.

B. Supplementary results B.I. Additional MS results MyD88 Table B.I. All proteins identified as uniquely present in MyD88 samples Gene name Protein description # exp ABCB1 MDR1_HUMAN Multidrug resistance protein 1 1 ABCB11 E1BGI0_BOVIN Uncharacterized protein 1 ADAMTS1 A7MB07_BOVIN ADAMTS1 protein, ATS1_HUMAN A disintegrin and metalloproteinase with thrombospondin motifs2 1 ADAR DSRAD_HUMAN Double-stranded RNA-specific adenosine deaminase 1 ADH4 F1MFZ4_BOVIN Uncharacterized protein 1 AKR7A2 ARK72_HUMAN Aflatoxin B1 aldehyde reductase member 2 2 ANGEL1 ANGE1_HUMAN Protein angel homolog 1, E1B8C9_BOVIN Uncharacterized protein 2 ANTXR1 E1BC74_BOVIN Uncharacterized protein 1 AP3B2 E1BME2_BOVIN Uncharacterized protein 1 ASB6 F1MWW0_BOVIN Uncharacterized protein 1 ASNA1 ASNA_BOVIN ATPase ASNA1 1 ATG7 ATG7_HUMAN Ubiquitin-like modifier-activating enzyme ATG7 1 ATP6V1H F1MZL6_BOVIN V-type proton ATPase subunit H OS=Bos taurus 1 ATXN10 F1MH20_BOVIN Ataxin-10 OS=Bos taurus 1 BAIAP2L1 BI2L1_HUMAN Brain-specific angiogenesis inhibitor 1-associated protein 2-like protein 1 1 BCCIP BCCIP_HUMAN BRCA2 and CDKN1A-interacting protein 1 BTF3 BTF3_HUMAN Transcription factor BTF3 1 BUB1B BUB1B_HUMAN Mitotic checkpoint serine/threonine-protein kinase BUB1 beta 1 Bt.102812 E1BBN7_BOVIN Uncharacterized protein 1 C22orf28 RTCB_HUMAN tRNA-splicing ligase RtcB homolog OS=Homo sapiens 1 C2orf29 CB029_HUMAN UPF0760 protein C2orf29 1 C8orf33 CH033_HUMAN UPF0488 protein C8orf33 2 CACHD1 CAHD1_HUMAN VWFA and cache domain-containing protein 1 1 CAPZA2 CAZA2_HUMAN F-actin-capping protein subunit alpha-2 1 CARM1 CARM1_HUMAN Histone-arginine methyltransferase CARM1, F1MBG0_BOVIN Uncharacterized protein (Fragment) 3 CD44 CD44_HUMAN CD44 antigen 1 CDK4 CDK4_HUMAN Cyclin-dependent kinase 4 3 CHAF1B CAF1B_HUMAN Chromatin assembly factor 1 subunit B 1 CIRBP CIRBP_HUMAN Cold-inducible RNA-binding protein 1 CIRH1A CIR1A_HUMAN Cirhin 1 CKAP5 CKAP5_HUMAN Cytoskeleton-associated protein 5 1 CMAS E1B9W3_BOVIN N-acylneuraminate cytidylyltransferase 1 CMPK1 KCY_HUMAN UMP-CMP kinase 1 CNOT8 E1BJH0_BOVIN Uncharacterized protein 1 COG2 F1MQ89_BOVIN Uncharacterized protein 1 COL4A3BP C43BP_BOVIN Collagen type IV alpha-3-binding protein 1 COLEC10 F1N0Y5_BOVIN Uncharacterized protein (Fragment) 1 CSRP1 CSRP1_BOVIN Cysteine and glycine-rich protein 1 1 CSRP2 CSRP2_HUMAN Cysteine and glycine-rich protein 2 1 CSTF3 E1BGY7_BOVIN Uncharacterized protein 2 CUL2 Q08DE9_BOVIN CUL2 protein 1 CXCR4 CXCR4_BOVIN C-X-C chemokine receptor type 4 1 DAZAP1 E1BAK6_BOVIN Uncharacterized protein (Fragment) 1 DBNL DBNL_BOVIN Drebrin-like protein 1 DCPS A5D7U9_BOVIN DCPS protein 1 DDX18 DDX18_HUMAN ATP-dependent RNA helicase DDX18 1 DDX47 DDX47_HUMAN Probable ATP-dependent RNA helicase DDX47 1 DHFR DYR_HUMAN Dihydrofolate reductase 3 DHRS11 DHR11_BOVIN Dehydrogenase/reductase SDR family member 11 1 DHX36 DHX36_HUMAN Probable ATP-dependent RNA helicase DHX36 2 DHX40 Q08DS9_BOVIN DEAH (Asp-Glu-Ala-His) box polypeptide 40 2 DIMT1 DIM1_HUMAN Probable dimethyladenosine transferase 1 DKC1 A7YWH5_BOVIN DKC1 protein 1 DNAJB4 DNJB4_BOVIN DnaJ homolog subfamily B member 4, DNJB4_HUMAN DnaJ homolog subfamily B member 4 3 DPH5 DPH5_HUMAN Diphthine synthase, DPH5_BOVIN Diphthine synthase OS=Bos taurus 2 DRG2 DRG2_HUMAN Developmentally-regulated GTP-binding protein 2 2

III

DUS3L DUS3L_HUMAN tRNA-dihydrouridine(47) synthase [NAD(P)(+)]-like 1 DYNLT1 DYLT1_BOVIN Dynein light chain Tctex-type 1 2 ECM29 ECM29_HUMAN Proteasome-associated protein ECM29 homolog 1 EDC3 E1BEA2_BOVIN Uncharacterized protein 1 EIF1AY IF1AY_HUMAN Eukaryotic translation initiation factor 1A, Y-chromosomal 1 EIF2B2 EI2BB_HUMAN Translation initiation factor eIF-2B subunit beta 2 EIF2B3 EI2BG_HUMAN Translation initiation factor eIF-2B subunit gamma 1 EIF2B4 EI2BD_HUMAN Translation initiation factor eIF-2B subunit delta 2 EIF2D EIF2D_HUMAN Eukaryotic translation initiation factor 2D 1 EIF2S3 IF2G_HUMAN Eukaryotic translation initiation factor 2 subunit 3 1 EIF3K EIF3K_BOVIN Eukaryotic translation initiation factor 3 subunit K 1 EIF4G2 F2Z4C6_BOVIN Eukaryotic translation initiation factor 4 gamma 2 (Fragment) 1 ELAVL1 ELAV1_HUMAN ELAV-like protein 1 3 EPB41L4B E41LB_HUMAN Band 4.1-like protein 4B 1 EPHB4 E1BIE4_BOVIN Uncharacterized protein 1 EXOSC4 EXOS4_BOVIN Exosome complex component RRP41 1 EXOSC6 EXOS6_HUMAN Exosome complex component MTR3 1 F2RL1 PAR2_HUMAN Proteinase-activated receptor 2 1 FAM115A F115A_HUMAN Protein FAM115A 3 FAM188A F188A_BOVIN Protein FAM188A, F188A_HUMAN Protein FAM188A 3 FAM203B F203B_HUMAN Protein FAM203B 1 FAM63A FA63A_HUMAN Protein FAM63A 1 FAM83D FA83D_HUMAN Protein FAM83D 1 FANCD2 FACD2_HUMAN Fanconi anemia group D2 protein 1 FAT1 FAT1_HUMAN Protocadherin Fat 1 1 FEN1 FEN1_HUMAN Flap endonuclease 1 1 FHL1 FHL1_HUMAN Four and a half LIM domains protein 1 2 FHOD1 FHOD1_HUMAN FH1/FH2 domain-containing protein 1 1 FKBP3 FKBP3_BOVIN Peptidyl-prolyl cis-trans isomerase FKBP3 1 FKBP5 FKBP5_HUMAN Peptidyl-prolyl cis-trans isomerase FKBP5 1 FLII FLII_HUMAN Protein flightless-1 homolog 1 FNBP1 F1MQ90_BOVIN Uncharacterized protein (Fragment) 1 G3BP1 G3BP1_HUMAN Ras GTPase-activating protein-binding protein 1 3 G3BP2 G3BP2_HUMAN Ras GTPase-activating protein-binding protein 2 1 GAK GAK_HUMAN Cyclin-G-associated kinase 1 GALNT1 GALT1_HUMAN Polypeptide N-acetylgalactosaminyltransferase 1 1 GAN GAN_HUMAN Gigaxonin 1 GAPVD1 GAPD1_HUMAN GTPase-activating protein and VPS9 domain-containing protein 1 1 GATAD2A P66A_HUMAN Transcriptional repressor p66-alpha 1 GCLM GSH0_HUMAN Glutamate--cysteine ligase regulatory subunit 1 GET4 GET4_HUMAN Golgi to ER traffic protein 4 homolog 1 GIGYF2 A7MB14_BOVIN GIGYF2 protein 1 GINS1 PSF1_BOVIN DNA replication complex GINS protein PSF1 1 GLE1 GLE1_BOVIN Nucleoporin GLE1 1 GLUL GLNA_HUMAN Glutamine synthetase 1 GOLGA7B Q0IID5_BOVIN Golgi autoantigen, golgin subfamily a, 7B 1 GOLPH3 GOLP3_HUMAN Golgi phosphoprotein 3 1 GPN1 GPN1_HUMAN GPN-loop GTPase 1 1 GSK3A A6QLB8_BOVIN GSK3A protein 1 GSK3B GSK3B_HUMAN Glycogen synthase kinase-3 beta 1 GTPBP1 G3MX26_BOVIN GTP-binding protein 1 1 HDLBP VIGLN_HUMAN Vigilin 3 HEATR1 HEAT1_HUMAN HEAT repeat-containing protein 1 2 HECTD1 E1BLD1_BOVIN Uncharacterized protein 1 HERC4 E1BAV2_BOVIN Uncharacterized protein 2 HK2 HXK2_HUMAN Hexokinase-2 1 HSPA2 HSP72_BOVIN Heat shock-related 70 kDa protein 2 2 ILF2 F2Z4E7_BOVIN Uncharacterized protein 1 IMP3 F1MZR5_BOVIN U3 small nucleolar ribonucleoprotein protein IMP3 2 IPO8 E1B8Q9_BOVIN Uncharacterized protein, IPO8_HUMAN Importin-8 2 IRAK1 IRAK1_HUMAN Interleukin-1 receptor-associated kinase 1, F1N593_BOVIN Interleukin-1 receptor-associated kinase 1 3(Fragment) IRAK4 IRAK4_BOVIN Interleukin-1 receptor-associated kinase 4, IRAK4_HUMAN Interleukin-1 receptor-associated kinase 4 2 IV

ISY1 ISY1_HUMAN Pre-mRNA-splicing factor ISY1 homolog 1 ITGA4 ITA4_HUMAN Integrin alpha-4 2 ITPA ITPA_HUMAN Inosine triphosphate pyrophosphatase 1 KHDRBS3 A4FV24_BOVIN KHDRBS3 protein 1 KIAA1279 KBP_HUMAN KIF1-binding protein 2 KIAA1609 K1609_HUMAN TLD domain-containing protein KIAA1609 2 KIAA1967 K1967_HUMAN DBIRD complex subunit KIAA1967, E1B9H3_BOVIN Uncharacterized protein 3 KIF3A E1B999_BOVIN Uncharacterized protein 1 KPNA6 IMA7_HUMAN Importin subunit alpha-7 2 KTI12 KTI12_HUMAN Protein KTI12 homolog 1 LARP4B LAR4B_HUMAN La-related protein 4B 2 LOC100297522 G3MY09_BOVIN Uncharacterized protein (Fragment) 1 LOC100335559 F1MIE2_BOVIN Uncharacterized protein 1 LOC100849054 F1N7F4_BOVIN Uncharacterized protein 1 LOC100849658 F1MEF6_BOVIN Uncharacterized protein 1 LOC100850639 E1BNY9_BOVIN Uncharacterized protein 2 LOC505465 E1BBQ3_BOVIN Uncharacterized protein 1 LOC512271 F1N1D4_BOVIN Uncharacterized protein 1 LRRC47 LRC47_HUMAN Leucine-rich repeat-containing protein 47 2 MAGOH MGN_HUMAN Protein mago nashi homolog 2 MAP2K4 A5PJP8_BOVIN MAP2K4 protein 1 MAP2K6 MP2K6_HUMAN Dual specificity mitogen-activated protein kinase kinase 6 1 MAPRE1 MARE1_HUMAN Microtubule-associated protein RP/EB family member 1 1 MCMBP MCMBP_HUMAN Mini-chromosome maintenance complex-binding protein 1 METAP1 AMPM1_BOVIN Methionine aminopeptidase 1 1 MGC3248 Q58D67_BOVIN Dynactin 4 1 MID1 TRI18_HUMAN Midline-1 1 MORC3 MORC3_HUMAN MORC family CW-type zinc finger protein 3 1 MOXD1 MOXD1_HUMAN DBH-like monooxygenase protein 1 1 MPP6 F1MU05_BOVIN Uncharacterized protein (Fragment) 1 MRE11A E1BIN9_BOVIN Uncharacterized protein 2 MTA1 MTA1_HUMAN Metastasis-associated protein MTA1 2 MYD88 MYD88_HUMAN Myeloid differentiation primary response protein MyD88 3 MYO6 E1BPK6_BOVIN Uncharacterized protein, MYO6_HUMAN Unconventional myosin-VI 2 NAA11 E1BIH2_BOVIN Uncharacterized protein 1 NAA50 NAA50_BOVIN N-alpha-acetyltransferase 50 2 NABP2 SOSB1_HUMAN SOSS complex subunit B1 1 NAE1 E1B8X4_BOVIN Uncharacterized protein 1 NCBP1 NCBP1_HUMAN Nuclear cap-binding protein subunit 1 1 NCBP2 NCBP2_HUMAN Nuclear cap-binding protein subunit 2 1 NCBP2L NCB2L_HUMAN Nuclear cap-binding protein subunit 2-like 1 NCS1 F1MZQ0_BOVIN Neuronal calcium sensor 1 (Fragment) 1 NDRG1 NDRG1_HUMAN Protein NDRG1, F1MS38_BOVIN Protein NDRG1 2 NFKB2 NFKB2_HUMAN Nuclear factor NF-kappa-B p100 subunit 1 NGLY1 NGLY1_HUMAN Peptide-N(4)-(N-acetyl-beta-glucosaminyl)asparagine amidase 1 NHLRC2 NHLC2_BOVIN NHL repeat-containing protein 2 1 NHP2L1 NH2L1_HUMAN NHP2-like protein 1 1 NKRF NKRF_HUMAN NF-kappa-B-repressing factor, G3MYW2_BOVIN Uncharacterized protein 2 NMD3 NMD3_HUMAN 60S ribosomal export protein NMD3 2 NOB1 F1MDA9_BOVIN RNA-binding protein NOB1 1 NOC4L NOC4L_HUMAN Nucleolar complex protein 4 homolog 1 NOL6 NOL6_HUMAN Nucleolar protein 6 2 NT5C G3X6X2_BOVIN Uncharacterized protein 1 NTPCR NTPCR_HUMAN Cancer-related nucleoside-triphosphatase 2 NUP214 NU214_HUMAN Nuclear pore complex protein Nup214 1 NUP43 NUP43_HUMAN Nucleoporin Nup43 2 NUP85 NUP85_HUMAN Nuclear pore complex protein Nup85 1 OGT OGT1_HUMAN UDP-N-acetylglucosamine--peptide N-acetylglucosaminyltransferase 110 kDa subunit, A5D7G1_BOVIN2 OGT protein, OIT3 G3MXH8_BOVIN Oncoprotein-induced transcript 3 protein (Fragment) 1 ORAI1 A5PKA7_BOVIN ORAI1 protein 2 OSBPL3 OSBL3_HUMAN Oxysterol-binding protein-related protein 3 1 OXSR1 F1MYV9_BOVIN Uncharacterized protein, OXSR1_HUMAN Serine/threonine-protein kinase OSR1 2 V

PABPN1 F1MTN4_BOVIN Polyadenylate-binding protein 2 1 PAFAH1B1 A5D7P3_BOVIN PAFAH1B1 protein 1 PCOLCE2 F1MKP1_BOVIN Uncharacterized protein 1 PCYT2 PCY2_HUMAN Ethanolamine-phosphate cytidylyltransferase 2 PDLIM5 G3MY19_BOVIN Uncharacterized protein 1 PDPK1 PDPK1_HUMAN 3-phosphoinositide-dependent protein kinase 1 1 PELO PELO_BOVIN Protein pelota homolog 1 PHB2 PHB2_BOVIN Prohibitin-2, PHB2_HUMAN Prohibitin-2 2 PIK3R4 PI3R4_HUMAN Phosphoinositide 3-kinase regulatory subunit 4 1 PIP4K2C G3X6D7_BOVIN Phosphatidylinositol 5-phosphate 4-kinase type-2 gamma, PI42C_HUMAN Phosphatidyl… 3 PITPNB PIPNB_HUMAN Phosphatidylinositol transfer protein beta isoform 1 PKN2 F1MFK1_BOVIN Uncharacterized protein2, PKN2_HUMAN Serine/threonine-protein kinase N2 3 PKP2 PKP2_HUMAN Plakophilin-2 3 PLEKHA1 PKHA1_HUMAN Pleckstrin homology domain-containing family A member 1 1 PLEKHB2 A4FV32_BOVIN PLEKHB2 protein 1 PMM2 PMM2_HUMAN Phosphomannomutase 2 1 PNO1 PNO1_HUMAN RNA-binding protein PNO1 1 POLD1 DPOD1_HUMAN DNA polymerase delta catalytic subunit 2 POLD2 DPOD2_HUMAN DNA polymerase delta subunit 2 1 POLD3 DPOD3_HUMAN DNA polymerase delta subunit 3 1 POLR2E F2Z4J4_BOVIN DNA-directed RNA polymerases I, II, and III subunit RPABC1 1 POP7 POP7_HUMAN Ribonuclease P protein subunit p20 1 PPP6R1 PP6R1_HUMAN Serine/threonine-protein phosphatase 6 regulatory subunit 1 1 PRIM1 PRI1_HUMAN DNA primase small subunit, G8JKZ3_BOVIN DNA primase 2 PRKAR2B F6Q9S4_BOVIN cAMP-dependent protein kinase type II-beta regulatory subunit 1 PRPF4 PRP4_HUMAN U4/U6 small nuclear ribonucleoprotein Prp4 1 PRPF4B PRP4B_BOVIN Serine/threonine-protein kinase PRP4 homolog 1 PSEN1 A7MBA9_BOVIN PSEN1 protein, PSN1_HUMAN Presenilin-1 2 PTGR2 PTGR2_BOVIN Prostaglandin reductase 2 1 PTPRA E1BPA0_BOVIN Uncharacterized protein (Fragment) 1 PUM1 E1BE82_BOVIN Uncharacterized protein 1 PVRL3 PVRL3_HUMAN Poliovirus receptor-related protein 3 1 PWP2 PWP2_HUMAN Periodic tryptophan protein 2 homolog 1 RAB9A RAB9A_HUMAN Ras-related protein Rab-9A 2 RAD50 RAD50_HUMAN DNA repair protein RAD50, G3X6W2_BOVIN Uncharacterized protein 3 RANBP2 RBP2_HUMAN E3 SUMO-protein ligase RanBP2 1 RAVER1 RAVR1_HUMAN Ribonucleoprotein PTB-binding 1 1 RBM15 RBM15_HUMAN Putative RNA-binding protein 15 1 RBM4 RBM4_HUMAN RNA-binding protein 4 2 RBM4B Q2KIV3_BOVIN RNA binding motif protein 4B 1 RCC2 RCC2_HUMAN Protein RCC2, A6QL85_BOVIN RCC2 protein 2 RCL1 RCL1_BOVIN RNA 3'-terminal phosphate cyclase-like protein 1 RFC3 RFC3_HUMAN Replication factor C subunit 3 2 RNF115 RN115_HUMAN E3 ubiquitin-protein ligase RNF115 2 RNF126 RN126_HUMAN RING finger protein 126 1 RNF20 BRE1A_HUMAN E3 ubiquitin-protein ligase BRE1A 1 RNF213 RN213_HUMAN E3 ubiquitin-protein ligase RNF213 1 RNGTT MCE1_HUMAN mRNA-capping enzyme 1 ROR2 A5PKA4_BOVIN ROR2 protein 1 RPA1 RFA1_HUMAN Replication protein A 70 kDa DNA-binding subunit 3 RPA3 RFA3_HUMAN Replication protein A 14 kDa subunit 2 RPL32 RL32_HUMAN 60S ribosomal protein L32 1 RPL37A RL37A_HUMAN 60S ribosomal protein L37a 1 RPS19 RS19_HUMAN 40S ribosomal protein S19 1 RPS27 RS27_HUMAN 40S ribosomal protein S27 1 RQCD1 RCD1_BOVIN Cell differentiation protein RCD1 homolog 1 RRP9 U3IP2_HUMAN U3 small nucleolar RNA-interacting protein 2 2 S1PR2 S1PR2_HUMAN Sphingosine 1-phosphate receptor 2 2 SAE1 SAE1_BOVIN SUMO-activating enzyme subunit 1 2 SAR1B SAR1B_BOVIN GTP-binding protein SAR1b 1 SCML2 SCML2_HUMAN Sex comb on midleg-like protein 2 1 SCPEP1 RISC_HUMAN Retinoid-inducible serine carboxypeptidase 2 VI

SEC23IP E1BKW5_BOVIN Uncharacterized protein 1 SEPSECS E1BPY3_BOVIN Uncharacterized protein 3 SEPT6 SEPT6_HUMAN Septin-6 1 SERPINA11 A5PK77_BOVIN SERPINA11 protein 1 SETD3 SETD3_HUMAN Histone-lysine N-methyltransferase setd3 2 SHBG A5PKC2_BOVIN SHBG protein 1 SIRPA SHPS1_HUMAN Tyrosine-protein phosphatase non-receptor type substrate 1 1 SKIV2L2 F1MJX4_BOVIN Uncharacterized protein 1 SLAIN1 F1MVT5_BOVIN Uncharacterized protein (Fragment) 1 SLC47A1 S47A1_HUMAN Multidrug and toxin extrusion protein 1 1 SLC5A6 SC5A6_HUMAN Sodium-dependent multivitamin transporter 3 SLC6A6 F1N460_BOVIN Transporter 1 SMARCAD1 SMRCD_HUMAN SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily A containing DEAD/H1 box 1 SMARCB1 SNF5_HUMAN SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily B member 1 1 SMARCD2 SMRD2_HUMAN SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily D member 2 2 SMG9 F1MBJ5_BOVIN Protein SMG9 1 SMS SPSY_HUMAN Spermine synthase 1 SRP19 SRP19_HUMAN Signal recognition particle 19 kDa protein 2 SRPK1 E1BNV4_BOVIN Uncharacterized protein, SRPK1_HUMAN SRSF protein kinase 1 3 STAT1 B0JYL6_BOVIN STAT1 protein 1 TARS SYTC_HUMAN Threonine--tRNA ligase, cytoplasmic 3 TBCD TBCD_HUMAN Tubulin-specific chaperone D 1 TENM3 TEN3_HUMAN Teneurin-3 1 THOC6 F1MPQ0_BOVIN Uncharacterized protein 1 TIA1 TIA1_HUMAN Nucleolysin TIA-1 isoform p40 1 TIMP3 A5PKB4_BOVIN Metalloproteinase inhibitor 3 1 TLE3 F1ML22_BOVIN Uncharacterized protein 2 TMEM178B T178B_HUMAN Transmembrane protein 178B 1 TMEM30A CC50A_HUMAN Cell cycle control protein 50A 1 TMEM51 TMM51_HUMAN Transmembrane protein 51 1 TOE1 TOE1_HUMAN Target of EGR1 protein 1 1 TOMM34 TOM34_HUMAN Mitochondrial import receptor subunit TOM34 1 TOP2A F1MDU7_BOVIN DNA topoisomerase 2 1 TRAPPC5 F1MSD6_BOVIN Trafficking protein particle complex subunit 5 1 TRIP12 TRIPC_HUMAN E3 ubiquitin-protein ligase TRIP12 1 TRMT1 TRM1_HUMAN tRNA (guanine(26)-N(2))-dimethyltransferase 1 TRMT1L TRM1L_HUMAN TRMT1-like protein 2 TRMT5 TRM5_HUMAN tRNA (guanine(37)-N1)-methyltransferase OS=Homo sapiens 1 TRMT6 TRM6_BOVIN tRNA (adenine(58)-N(1))-methyltransferase non-catalytic subunit TRM6, TRM6_HUMAN … 3 TRMT61A TRM61_BOVIN tRNA (adenine(58)-N(1))-methyltransferase catalytic subunit TRMT61 1 TSEN34 Q3MHE1_BOVIN Uncharacterized protein 1 TTC4 TTC4_HUMAN Tetratricopeptide repeat protein 4 1 TYMS F1MY63_BOVIN Thymidylate synthase, TYSY_HUMAN Thymidylate synthase 2 UBA5 UBA5_BOVIN Ubiquitin-like modifier-activating enzyme 5 1 UBE2V2 UB2V2_HUMAN Ubiquitin-conjugating enzyme E2 variant 2 1 UBE2Z F1N1X8_BOVIN Uncharacterized protein 1 UBE3C F1N703_BOVIN Uncharacterized protein 1 UBQLN2 UBQL2_HUMAN Ubiquilin-2 2 UBXN6 UBXN6_HUMAN UBX domain-containing protein 6 1 UCK2 E1BMA5_BOVIN Uridine kinase 1 UEVLD UEVLD_HUMAN Ubiquitin-conjugating enzyme E2 variant 3 1 UFL1 UFL1_HUMAN E3 UFM1-protein ligase 1 1 ULK3 F1N332_BOVIN Uncharacterized protein 2 UPB1 A7MBE8_BOVIN UPB1 protein 1 USP19 F1MUD4_BOVIN Ubiquitin carboxyl-terminal hydrolase (Fragment) 1 USP24 E1BND0_BOVIN Ubiquitin carboxyl-terminal hydrolase 1 USP7 F1N556_BOVIN Ubiquitin carboxyl-terminal hydrolase (Fragment) 1 UTP15 UTP15_BOVIN U3 small nucleolar RNA-associated protein 15 homolog 1 VCPIP1 VCIP1_HUMAN Deubiquitinating protein VCIP135 1 VPS18 VPS18_HUMAN Vacuolar protein sorting-associated protein 18 homolog 1 VRK1 VRK1_HUMAN Serine/threonine-protein kinase VRK1 1 WDR3 E1BM03_BOVIN Uncharacterized protein 2 VII

WDR36 WDR36_HUMAN WD repeat-containing protein 36 2 WDR43 WDR43_HUMAN WD repeat-containing protein 43 1 WDR46 WDR46_HUMAN WD repeat-containing protein 46 1 WRAP53 WAP53_HUMAN Telomerase Cajal body protein 1 1 YRDC YRDC_HUMAN YrdC domain-containing protein, mitochondrial 1 YTHDF3 E1BH80_BOVIN Uncharacterized protein 1 ZC3HAV1L ZCCHL_HUMAN Zinc finger CCCH-type antiviral protein 1-like 1 ZNF598 ZN598_HUMAN Zinc finger protein 598 1 ZNHIT2 ZNHI2_HUMAN Zinc finger HIT domain-containing protein 2 1 ZW10 ZW10_HUMAN Centromere/kinetochore protein zw10 homolog 1

This table contains all proteins that were found in the MyD88 samples, but not in any of the 19 background experiments. Note that IRAK-4 is present in this table, even though it was not retained in the analysis, as analysis is based only on those proteins that were identified by at least two different peptides in the sample.

B.II. Additional MS results MyD88-TIR Table B.II. All proteins identified as uniquely present in MyD88-TIR samples Gene name Protein description # exp ACIN1 ACINU_HUMAN Apoptotic chromatin condensation inducer in the nucleus 1 AKR7A2 ARK72_HUMAN Aflatoxin B1 aldehyde reductase member 2 1 ANGEL1 ANGE1_HUMAN Protein angel homolog 1 1 ANKRD13A AN13A_HUMAN Ankyrin repeat domain-containing protein 13A 1 ARL6IP1 F1MBM4_BOVIN Uncharacterized protein 1 B3GNT1 B3GN1_HUMAN N-acetyllactosaminide beta-1,3-N-acetylglucosaminyltransferase 1 Bt.26229 E1BNF9_BOVIN Uncharacterized protein 2 C7 F1N045_BOVIN Complement component C7 1 CARM1 CARM1_HUMAN Histone-arginine methyltransferase CARM1 1 CGI-301 CG301_HUMAN Putative protein CGI-301 1 CNTFR CNTFR_HUMAN Ciliary neurotrophic factor receptor subunit alpha 1 DHFR DYR_HUMAN Dihydrofolate reductase 2 DKC1 DKC1_HUMAN H/ACA ribonucleoprotein complex subunit 4 1 DNAJB4 DNJB4_BOVIN DnaJ homolog subfamily B member 4, DNJB4_HUMAN DnaJ homolog subfamily B member 4 3 DRG1 DRG1_BOVIN Developmentally-regulated GTP-binding protein 1 1 EFNA5 F6QDM0_BOVIN Uncharacterized protein (Fragment) 2 EIF3G F2Z4J5_BOVIN Eukaryotic translation initiation factor 3 subunit G 1 EIF3K EIF3K_BOVIN Eukaryotic translation initiation factor 3 subunit K 1 ELAVL1 ELAV1_HUMAN ELAV-like protein 1 1 EPHB4 E1BIE4_BOVIN Uncharacterized protein 1 EPS15L1 A7MB30_BOVIN EPS15L1 protein 2 FAM115A F115A_HUMAN Protein FAM115A 1 FAM188A F188A_BOVIN Protein FAM188A, F188A_HUMAN Protein FAM188A 3 FAM63A FA63A_HUMAN Protein FAM63A 1 FAT1 FAT1_HUMAN Protocadherin Fat 1 1 FKBP3 FKBP3_BOVIN Peptidyl-prolyl cis-trans isomerase FKBP3 2 FREM2 F1MFH3_BOVIN Uncharacterized protein 1 GALNT1 GALT1_HUMAN Polypeptide N-acetylgalactosaminyltransferase 1 1 GEMIN5 GEMI5_HUMAN Gem-associated protein 5 1 GINS1 PSF1_BOVIN DNA replication complex GINS protein PSF1 1 GOLGA7B Q0IID5_BOVIN Golgi autoantigen, golgin subfamily a, 7B 1 GOLT1B GOT1B_BOVIN Vesicle transport protein GOT1B 1 GPS2 F1MPA7_BOVIN Uncharacterized protein 1 GUCY1A1 GCYA1_BOVIN Guanylate cyclase soluble subunit alpha-1 1 HCK F1MWN2_BOVIN Uncharacterized protein (Fragment) 1 HGFAC E1BCW0_BOVIN Uncharacterized protein (Fragment) 1 HPRT1 HPRT_HUMAN Hypoxanthine-guanine phosphoribosyltransferase 1 HS3ST2 E1BKQ1_BOVIN Uncharacterized protein 1 HSPA2 HSP72_BOVIN Heat shock-related 70 kDa protein 2 1 ITGA4 ITA4_HUMAN Integrin alpha-4 2 KHDRBS3 A4FV24_BOVIN KHDRBS3 protein 1 KIAA1609 K1609_HUMAN TLD domain-containing protein KIAA1609 1 LNPEP F1N1Q8_BOVIN Uncharacterized protein (Fragment) 1

VIII

LOC100850639 E1BNY9_BOVIN Uncharacterized protein 1 LOC512271 F1N1D4_BOVIN Uncharacterized protein 1 LOC534200 F1MHR3_BOVIN Uncharacterized protein (Fragment) 1 LOC538060 E1BG58_BOVIN Uncharacterized protein (Fragment) 1 LUC7L F1MMH3_BOVIN Uncharacterized protein 1 MAGOH MGN_HUMAN Protein mago nashi homolog 1 MGC148692 F1MJF9_BOVIN Uncharacterized protein (Fragment) 1 MKRN4P MKRN4_HUMAN Putative E3 ubiquitin-protein ligase makorin-4 1 MOXD1 MOXD1_HUMAN DBH-like monooxygenase protein 1 1 MYD88 MYD88_HUMAN Myeloid differentiation primary response protein MyD88 3 NAA50 NAA50_BOVIN N-alpha-acetyltransferase 50 1 NCS1 F1MZQ0_BOVIN Neuronal calcium sensor 1 (Fragment) 1 PDPN PDPN_HUMAN Podoplanin 2 PKP2 PKP2_HUMAN Plakophilin-2 1 PLEKHB2 PKHB2_HUMAN Pleckstrin homology domain-containing family B member 2 1 PRRC2A PRC2A_HUMAN Protein PRRC2A 1 PVRL3 PVRL3_HUMAN Poliovirus receptor-related protein 3 1 PYCARD ASC_HUMAN Apoptosis-associated speck-like protein containing a CARD 1 RAB9A RAB9A_HUMAN Ras-related protein Rab-9A 1 RBM25 E1BHM5_BOVIN Uncharacterized protein 1 REEP5 REEP5_HUMAN Receptor expression-enhancing protein 5 1 RNF115 RN115_HUMAN E3 ubiquitin-protein ligase RNF115 3 RPL37A RL37A_HUMAN 60S ribosomal protein L37a 1 S1PR2 S1PR2_HUMAN Sphingosine 1-phosphate receptor 2 1 SEPSECS E1BPY3_BOVIN Uncharacterized protein, SPCS_HUMAN O-phosphoseryl-tRNA(Sec) selenium transferase 3 SLC5A6 SC5A6_HUMAN Sodium-dependent multivitamin transporter 1 SLTM SLTM_HUMAN SAFB-like transcription modulator 1 SMOC1 SMOC1_HUMAN SPARC-related modular calcium-binding protein 1 1 SNX9 F1N6W6_BOVIN Uncharacterized protein (Fragment) 1 SRP19 SRP19_HUMAN Signal recognition particle 19 kDa protein 1 TARS SYTC_BOVIN Threonine--tRNA ligase, cytoplasmic 1 TENM3 TEN3_HUMAN Teneurin-3 1 TIRAP TIRAP_HUMAN Toll/interleukin-1 receptor domain-containing adapter protein 1 TMED5 TMED5_BOVIN Transmembrane emp24 domain-containing protein 5 1 TMEM178B T178B_HUMAN Transmembrane protein 178B 2 TNIP2 TNIP2_HUMAN TNFAIP3-interacting protein 2 2 UBE2V2 UB2V2_HUMAN Ubiquitin-conjugating enzyme E2 variant 2 1 UBQLN2 UBQL2_HUMAN Ubiquilin-2 2 UBXN6 UBXN6_HUMAN UBX domain-containing protein 6 1 ULK3 F1N332_BOVIN Uncharacterized protein 1 VPS37D VP37D_HUMAN Vacuolar protein sorting-associated protein 37D 1 YIPF5 YIPF5_HUMAN Protein YIPF5 1 gypb D5MTL9_BOVIN Glycophorin B variant 1 1

This table contains all proteins that were found in the MyD88-TIR samples, but not in any of the 19 background experiments. Note that Mal (TIRAP) was identified here in one experiment, even tough it was not retained in the analysis.

B.III. Additional co-IP results

Figure B.III.I. Results for initial co-IP using mild buffer

Figure B.III.II.. Insoluble fractions of samples RNF115, WDR36, PKP2 and ULK3

Figure B.III.III. Results for co-IP using RIPA buffer

C. List of abbreviations AD Activating domain, also see Y2H AP1 Activating protein 1 AP-MS Affinity purification-mass spectrometry BTK Bruton's tyrosine kinase CaP Calcium phosphate Cas CRISPR-associated CNRQ Calibrated normalized relative quantity Co-IP Co-immunoprecipitation CRISPR Clustered regularly interspaced short palindromic repeats crRNA CRISPR-RNA DB DNA binding domain, also see Y2H DD Death domain DMEM Dulbecco's modified Eagle medium FBS Fetal bovine serum FDR False discovery rate HeBS HEPES buffered saline HEK293T Human embryonic kidney 293 T HIV Human immunodeficiency virus HTS High-throughput screen ID Intermediate domain IFN Interferon IL Interleukin IP-MS Immunoprecipitation-mass spectrometry IRAK IL-1 receptor-associated kinase IRF IFN responsive factor JAK Janus kinase KD Kinase domain LLR Leucine rich repeat LPS Lipopolysaccharide Mal MyD88 adaptor-like MAPK Mitogen activated protein kinase MAPPIT Mammalian protein-protein interaction trap MEF Mouse embryonic fibroblast MS Mass spectrometry MyD88 Myeloid Differentiation Primary Response 88 NAP1 NAK-associated protein 1 NF-kB Nuclear factor-kappaB NHS Normal human serum ORF Open reading frame PAM Protoscaper adjacent motif PAMP Pathogen associated molecular pattern PEI Polyethyleneimine PIP2 Phosphatidylinositol-4,5-bisphosphate-binding PKCε Protein kinase Cε PLK1 Polo-like kinase 1 PPI Protein-protein interaction PRR Pattern recognition receptor PRS Positive reference set, also see RRS PTM Post-translational modification XII

RA Reducing agent Rabring7 Rab7-interacting RING finger protein RHIM RIP homotypic interaction motif RIP Receptor interacting protein RNF115 Ring finger protein 115, also see Rabring7 RPMI 1640 Roswell Park Memorial Institute 1640 RRS Random reference set SDS Sodium dodecyl sulfate SDS-PAGE SDS-polyacrylamide gel elctrophoresis SEC-SILAC Size exclusion chromatography-stable isotope labeling of amino acids in cell culture sgRNA Single guide RNA SH2 Src homology domain siRNA Short interfering RNA STAT Signal transducer and activator of transcription T6BM TRAF6-binding motif TAB TAK1-binding protein tacrRNA Transacticating crRNA TAK1 TGF-β-activated protein kinase 1 TANK TRAF family member-associated NF-κB activator TAP Tandem affinity purification TBK1 TANK-binding kinase TEV Tobacco etch virus TF Transcription factor TGF Transforming growth factor TIR Toll/IL-1 receptor domain TIRAP TIR domain containing adaptor protein TLR Toll-like receptor TNF Tumor necrosis factor TNFAIP3 TNF-α induced protein 3 TRAF6 TNF receptor associated factor 6 TRAM TRIF-related adaptor molecule TRIF TIR-domain-containing adaptor protein inducing IFN-β TRIM5 Tripartite motif containing 5 UBC13 Ubiquitin-conjugating enzyme 13 UEV1A Ubiquitin-conjugating enzyme E2 variant 1 VLP Virus-like particle VSV-G Vesicular stomatitis virus glycoprotein Y2H Yeast two hybrid

XIII