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A Human Genome-wide Screen for Regulators of Clathrin-coated Vesicle Formation Reveals an Unexpected Role for the V-ATPase

Clathrin-mediated endocytosis is essential for a wide range of cellular functions. We used a multi-step siRNA-based screening strategy to identify regulators of the first step in clathrin-mediated endocytosis, formation of clathrin-coated vesicles (CCVs) at the plasma membrane. A primary genome-wide screen identified 334 hits that caused accumulation of CCV cargo on the cell surface. A secondary screen identified 92 hits that inhibited cargo uptake and/or altered the morphology of clathrin-coated structures. The hits include components of four functional complexes: coat proteins, V-ATPase subunits, spliceosome-associated proteins, and acetyltransferase subunits. Electron microscopy revealed that V-ATPase depletion caused the cell to form aberrant non-constricted clathrin-coated structures at the plasma membrane. The V-ATPase knockdown phenotype was rescued by addition of exogenous cholesterol, indicating that the knockdown blocks clathrin-mediated endocytosis by preventing cholesterol from recycling from endosomes back to the plasma membrane.

phenotype (Figure 2c, Supplementary Figure S4c). An SSMD of greater than 3 was used as the threshold for hit selection. All of the hits for the CD8-YXXΦ cells had at least 2.85-fold more surface CD8 than the negative control, and all of the hits for the CD8-FXNPXY cells had at least 2.39-fold more surface CD8. For both cell lines, CLTC and DNM2 were among the top hits. AP2M1 was a strong hit for the CD8-YXXΦ cells only. DAB2, one of two major FXNPXY adaptors, was a weak hit for the CD8-FXNPXY cells but below the selection threshold, consistent with reports that both DAB2 and ARH have to be knocked down simultaneously to prevent internalization of FXNPXY-containing proteins 8 . As expected, several SMARTpools caused an increase of both CD8-YXXΦ and CD8-FXNPXY (R 2 = 0.47). However, there was no correlation between the CD8 constructs and MHC-I (R 2 = 0.01) (Figure 2d). Table S1 lists the 719 SMARTpools with SSMDs > 3 for either or both of the motifs.

Selection of hits for secondary assays
In order to eliminate some of the potential false positives, we applied three exclusion criteria to the primary hit list (Figure 2e). First, the siRNA targets were re-annotated according to version 25 of the RefSeq database, and where multiple or no target mRNAs were identified, a SMARTpool was excluded from the hit list. Second, we performed microarray analyses and excluded hits for which the target mRNA was represented on the microarray but not detected. Finally, we excluded hits where the increase of CD8 on the cell surface was accompanied by an increase in MHC-I, as these genes are unlikely to control CME. Out of the 334 hits remaining, the 241 top hits (Table S1a) were selected for secondary screens, in which we used a set of different siRNA pools, chemically modified to reduce the off-target activity and designed with improved sequence selection algorithms (ONTARGETplus, OTP) 9,10 .

Efficiency of CME
To confirm that knockdowns causing an increase in surface levels of CD8 specifically affect endocytosis, we determined the internalization efficiency of the CD8 constructs using a previously described antibody uptake assay 5 , adapted here for high-throughput analysis with a plate reader and shown diagrammatically in Figure 1b. Briefly, the siRNA-transfected CD8-YXXΦ and CD8-FXNPXY cells were first allowed to internalize an anti-CD8-Alexa 488 antibody for 40 min at 37°C. The cells were then fixed, surface Alexa 488 fluorescence was quenched with an anti-Alexa 488 antibody, and surface CD8 was relabelled with an Alexa 647 secondary antibody (Figure 3a). The ratio of green to red fluorescence normalised to positive and negative controls in each plate was then used as a measure of internalization efficiency (0 corresponds to inhibition in CLTC knockdown cells, and 1 to uptake efficiency in "no knockdown" controls) (Figure 3b). 28 SMARTpools inhibited internalization of YXXΦ, 38 of FXNPXY, and 20 of these were shared between the two cargo proteins (Figure 3b).

Morphology of CCSs at the PM
To identify hits that affect the formation of endocytic CCVs, we designed an automated microscopy-based assay to characterize clathrin-coated structures (CCSs) at the PM. We labelled the CCSs with an antibody against CALM, an accessory protein that colocalizes with clathrin at the PM, but not on intracellular membranes 11,12 (see Figure 1c). The prerequisite for quantitative high throughput microscopy is obtaining good quality images, and in the case of PM CCSs, the optimal focal plane is where cells adhere to the growth surface. Thus, as a reference, we used hydrophilic Cy5-labeled flow cytometry beads, which settle between the cells at the bottom of the dish. Whole cell stain (WCS) was used to demark cell boundaries, and a SpotDetector BioApplication was used to identify CCSs in each cell (Figure 4a).
We screened the 241 selected siRNA pools by reverse transfecting the cells in duplicate as before, then splitting the plates into four different densities after 48 h, and fixing and staining the cells after 72 h. The analysis was performed in two independent experiments with 300-2000 valid cells analyzed for each knockdown (Table S2). Mitotic cells and cells from dense fields were excluded from the analysis (Figure 4b,c). We focused on changes in total fluorescence intensity per spot and spot count per area (Figure 4d,e,f) and selected 67 hits falling into three categories: increase in spot brightness (red), decrease in spot brightness (blue), and decrease in spot count without a change in brightness (yellow).

Ultrastructure of CCSs following depletion or inhibition of V-ATPase
Although V-ATPase plays an important role in endocytic trafficking by controlling the intralumenal pH of endosomes and lysosomes, a role in the formation of CCVs at the PM was unexpected. siRNAs against eight components of V-ATPase were present among the primary hits, and using the OTP pools, we verified that the knockdowns also inhibit internalization of an endogenous ligand, transferrin (Figure 6a). To investigate the ultrastructure of the "brighter" CCSs observed in V-ATPase-depleted cells (Figure 6b), we turned to electron microscopy. Strikingly, knocking down V-ATPase caused the cells to accumulate large and irregular CCPs with average neck diameters of 220 nm (compared to 97 nm in control cells), while constricted pits were notably absent (Figure 6c,d,e).
The inability of pits to constrict and the block in CME upon V-ATPase depletion were surprising, as acute inhibition of the V-ATPase with Bafilomycin A1 (BafA1) does not block transferrin internalization, but instead inhibits its recycling 14 (Figure 6f). However, when we incubated the cells with BafA1 for 24 h, transferrin internalization was completely abolished (Figure 6f). This decrease in the efficiency of internalization occurred progressively over the 24 h period, and resulted in a gradual accumulation of the transferrin receptor at the cell surface (Figure 6g). In a similar time-course experiment, we observed a corresponding increase in the brightness of CALM-labelled CCSs (Figure 6h). EM analysis revealed that at 17 h, BafA1-treated cells also accumulate wide, non-constricted CCSs (Figure 6i,j,k). Together, these data suggest that siRNA-mediated depletion of different V-ATPase subunits, or inhibition of V-ATPase activity with BafA1, block CME by preventing CCPs from forming CCVs.

V-ATPase inhibition and cytosolic acidification
What is the role of V-ATPase in CCP constriction and vesicle budding? Because V-ATPase is a proton pump 15 and clathrin polymerization has been shown to be sensitive to pH 16 , we suspected initially that BafA1 treatment might prevent CCV formation by decreasing the pH of the cytosol. Studies by Heuser on "unroofed" cells have shown that cytosol acidification leads to an accumulation of "arrested" CCSs surrounded by membraneless microcages 16 . Using a similar technique, we generated PM replicas from control and BafA1-treated cells to examine their three-dimensional architecture. The micrographs confirmed the abundance of enlarged CCSs and revealed an astounding variety in their morphologies (Figure 7a,b). However, we did not see any evidence of microcage formation.
Two other treatments that lead to a block in endocytosis coupled with microcage formation, hypertonic sucrose and potassium depletion 17 , simultaneously block clathrin exchange 18 . Therefore, we performed FRAP experiments on cells transfected with GFP-tagged clathrin light chain, cultured in the presence or absence of BafA1 (Figure 7c,d). BafA1 treatment did not significantly affect the recovery kinetics, again arguing that clathrin is unlikely to be "locked" in microcages.
Finally, we measured the cytosolic and submembranous pH using soluble and SuperEcliptic (SE) pHluorin-mCherry proteins 19 (Figure 7e). Since SEpHluorin fluorescence decreases upon protonation, the ratio of green to red signal can be used to estimate pH, as demonstrated by incubating the cells in buffers of different pH in the presence of an ionophore, nigericin (Figure 7f,g). Treatment with BafA1 for 24 h resulted in only a modest pH decrease. Because pH 6.5-6.8 has been consistently reported as the threshold at which CME is inhibited 19,20 , we concluded that changes to cytosolic pH and microcage formation are unlikely to explain CME inhibition in the V-ATPase-depleted cells.

CCV formation in cells lacking functional V-ATPase can be rescued with soluble cholesterol
If the inhibition of CCV formation upon V-ATPase inhibition cannot be attributed to a decrease in cytosolic pH, could it be related to the alkalization of endosomes? It has been known for over 30 years that if endosomes cannot acidify, trafficking out of them is inhibited 21 , and this is thought to be due to a general block in the formation of carriers 22 . If an essential CCV membrane component were unable to recycle back to the plasma membrane, this would help to explain the BafA1 kinetics, because it would take time for this component to be depleted. A candidate for the "missing component" emerged from the observation that the morphology of the CCSs in V-ATPase-depleted cells is strikingly similar to the enlarged, shallow clathrin-coated invaginations that form upon extraction of cholesterol from the PM with methyl-β-cyclodextrin 23,24 . Like the transferrin receptor, cholesterol recycles from endosomes to the PM 25 , and consequently, in the presence of BafA1 it accumulates in endosomes and is depleted from the cell surface 26,27 . We found that if we either knocked down V-ATPase or treated cells with BafA1 for 24 h, cholesterol (labelled with filipin) was lost from the PM and accumulated in an intracellular compartment, and we were able to quantify this change in three different cell lines using an automated microscopy-based assay ( Fig. 8a,b). Double labelling indicates that the filipinpositive compartment also contains trapped CCV cargo proteins (Supplementary Figure S6). To test whether the loss of PM cholesterol could explain the block in endocytosis, we added exogenous cholesterol to the cells together with BafA1 or siRNAs targeting V-ATPase (Supplementary Figure S7). We found that transferrin internalization was partially rescued (Figure 8c

DISCUSSION
To identify regulators of CCV formation, we carried out a multi-step siRNA-based screen. In the primary screen, hits were defined as siRNA pools that caused CCV cargo proteins with YXXΦ or FXNPXY motifs to accumulate on the PM. Using further selection criteria based on gene expression and siRNA pool specificity, we narrowed down the list to 334 hits. Overall, the hit selection criteria applied are highly stringent and therefore may produce false negatives. However, this strategy allowed us to identify a small number of high confidence hits, which we characterized in more detail.
To identify genes that control endocytosis at the step of CCV formation, we performed two secondary screens. First, we carried out an uptake assay, which allowed us to distinguish knockdowns that decrease the efficiency of CME from those than increase surface levels of CD8 for other reasons (e.g., inefficient lysosomal degradation). Second, we carried out a microscopy-based assay, which allowed us to identify knockdowns that alter the morphology of CCSs at the PM. Because the intensity of CALM fluorescence peaks during vesicle scission 28 , an increase in spot brightness could correspond to an accumulation of deeply invaginated pits 29 (e.g., in dynamin-depleted cells 30 ), or to an accumulation of unusually large or clustered pits. A decrease in spot count or brightness suggests inefficient coat nucleation or recruitment 31 .
From the final set of 92 hits, only CLTC, AP2M1, and DNM2 have been detected in CCVs by proteomics 32 . This is, however, not surprising considering that individual knockdowns of accessory CCV components (e.g. CALM 33 or epsins 34 ) rarely lead to endocytic arrest. Thus, the siRNA-based approach appears to be biased towards proteins not physically incorporated into CCVs. Other proteins implicated in CCV formation, such as FCHo1/2 and Rab5A/B/C, were also not picked up as strong hits, possibly because they are encoded by functionally redundant genes (this functional redundancy also helps to explain why only one of the four AP-2 subunits was present in the list).
Although the purpose of this screen was to identify regulators of clathrin-mediated trafficking, the data we have generated can be mined to look for genes involved in other pathways as well. For instance, knockdowns that decrease surface expression of a particular protein may affect its secretion and/or recycling. In addition, for each knockdown, the MHC-I results are also available online and will be an interesting dataset to explore, especially because post-Golgi trafficking pathways of MHC-I are poorly characterized 6 and 30% of MHC-I hits correspond to unknown proteins. All of our data can be accessed at http://www.bioinformatics.cimr.cam.ac.uk/siRNA/Robinson_Screen. Out of our 92 hits, several are uncharacterised proteins, such as HLXB9 and LOC124220, which we have now validated with two or more distinct siRNAs, and which we intend to characterise more fully. Other hits have been at least partially characterised, and this enabled us to group them into three functional networks (plus the network containing coat components). One network consists of several components of the mammalian spliceosome. Interestingly, a number of CCV proteins exist in multiple splice variants, including the α and β subunits of AP-2 35 , clathrin light chains 36 , and dynamin 2 37,38 . The spliceosome is also essential for cell cycle progression 39 , and since endocytosis is arrested in mitotic cells 40 , further experiments will be required to resolve whether the endocytic block in spliceosome-depleted cells is due to incorrect splicing of coat proteins, or is a consequence of the mitotic arrest.
The second unexpected functional cluster contains subunits of the histone acetyltransferase complex. Histone acetylation plays an important role in the regulation of gene expression; however, three lines of evidence suggest that the block in CME may be due to changes in the acetylation of cytoplasmic proteins rather than histones. First, acetylation sites have been identified in three core components of CCVs: clathrin, AP-2, and dynamin 2 41 . Second, both RUVBL2 and KAT5 can translocate to the cytoplasm under certain conditions [42][43][44] . Third, in a hepatic cell line, WIF-B, a 30 min treatment with trichostatin A, a deacetylase inhibitor, was found to arrest deeply invaginated pits prior to fission 45 , and the short time scale argues against this effect being due to transcriptional regulation. Finding the key target(s) of the acetyltransferase complex will be critical for deciphering the role of acetylation in CME.
The third unexpected network, which we analysed in more detail, contains several V-ATPase subunits. We discovered that the block in CCV formation in V-ATPase-depleted cells can be explained by the retention of cholesterol in non-acidified endosomes, and its concomitant loss from the PM. At first glance, this phenotype is reminiscent of Niemann-Pick type C disease, where mutations in pH-sensitive NPC1 or NPC2 lead to accumulation of cholesterol in endosomes and lysosomes 46,47 . However, in NPC cells, cholesterol is still exchanged with the PM 48,49 and endocytosis still occurs 50 . In contrast, when endosomes are unable to acidify, trafficking out of them becomes inhibited. Although this phenomenon was first observed in the 1980s 21 it still awaits a molecular explanation, but endosome acidification is clearly important for the recycling of lipids as well as proteins.
Why is cholesterol needed for CCV formation? Since transbilayer diffusion of cholesterol is fast (< 1 s) 51,52 relative to the half-time of CCV formation (~ 100 s) 28 , it is possible that the spontaneous flip-flop of cholesterol could simply lower the membrane-bending energy. Thus, although the coat is still able to curve the membrane into a CCP in the absence of cholesterol, the energy required for the neck to constrict may be too great 52 (Figure 8h). In yeast, budding of CCVs from intracellular membranes requires a lipid flippase, Drs2p, consistent with the notion that the distribution of lipids between the two leaflets of the bilayer is important for membrane deformation 53 .
The role of V-ATPase in CME is particularly relevant in light of recent therapeutic strategies against cancer that target V-ATPase activity 54 . Interestingly, one such study demonstrated that BafA1-induced inhibition of cell growth can be rescued with cholesterol or iron 55 . The authors assumed that receptor-mediated endocytosis was still occurring normally in the BafA1-treated cells, but that iron and cholesterol were unable to be released in endosomes and lysosomes. However, the present study demonstrates that long-term BafA1 treatment inhibits CME, and this might account, at least in part, for the cytostatic effects of the V-ATPase inhibitors. V-ATPase activity has also been implicated in signalling by both Notch 56,57 and Wnt 58,59 . Although again it was assumed that the molecules were still getting internalised, and that the phenotype was caused by pH-dependent events in the endosome, it is important to note that the Notch and Wnt pathways both require clathrin and dynamin [60][61][62][63] . Thus, the connection we have uncovered between endosome acidification, cholesterol trafficking, and CCV formation may help to explain a number of observations on the role of V-ATPase in growth control and development.

Antibodies, plasmids and other reagents
The following antibodies were used in the primary screen: The pHluorin-mCherry plasmids (cytosolic and PM-targeted) were a kind gift from Sergio Grinstein 19 . The CD63-pEGFP C2 plasmid was a kind gift from Paul Luzio. The GFPclathrin light chain A plasmid was a kind gift from Steve Royle (University of Liverpool). The pHluorin-transferrin receptor plasmid was a kind gift from Christien Merrifield (LEBS, Gif-sur-Yvette, France).
For DNA transfections, cells were grown to 50% confluency and transfected for 24 h using a TransIT-HeLaMONSTER Transfection Kit (Mirus) with 2 μg plasmid DNA per 6-well.

mRNA analysis
RNA was isolated from 10 6 CD8-YXXΦ or CD8-FXNPXY cells (harvested by trypsinization) using the Purescript® RNA Purification Kit (Life Sciences Germany). Samples were processed and analyzed at the Centre for Microarray Resources (Department of Pathology, University of Cambridge). The analysis was performed using Illumina HumanRef-8.v2 BeadChip array scanned on Illumina BeadStation 500 platform. The list of expressed genes was generated using low stringency criteria to minimize the number of false negatives. Variance Stabilizing Transform and Robust Spline Normalization algorithms 65 from the lumi R package 66 were used to process the signal intensity data. 12,269 probes with signal intensity above the background in at least one of the technical replicates of either of the cell line were selected using a p-value threshold of < 0.01 (listed in Supplementary  Table S3). MIAME-compatible data was submitted to GEO (accession: GSE39954).

siRNA reverse transfection protocol
A 96-well plate with 10 μl of 1 μM pre-aliquoted siRNAs was used to generate 4 assay plates (Viewplates, Cat. No. 6005182, PerkinElmer) (see Supplementary Figure S1). First, 72 μl of Optimem I (Invitrogen) was added into each well of the transfection plate. Oligofectamine (Invitrogen) was pre-incubated with Optimem in a 1:8 ratio for 8 min, and 18 μl of the mix was added to each well. The transfection mix was incubated for 20 min at RT, and aliquoted into assay plates (20 μl per well). Next, 4500 cells in 100 μl of DMEM (with P/S and L-glutamine) were added to each well, and the plates were gently vortexed, then incubated at 37°C in 5% CO 2 for 72 h. For knockdowns in 6-well plates, the volumes per well were scaled up 20x.

Genome-wide and secondary screens
Detailed protocols, methods for data analysis, and hit selection strategy are provided in the Supplementary Note.

Cholesterol redistribution assay
The cells were seeded in the 96-well plates 24 h before the analysis and fixed in 3.3% formaldehyde in PBS for 30 min at room temperature. The cells were then washed in PBS and stained with filipin (1:1000 in PBS) and WCS Green for 2 h. Cy5 beads (see CCS assay) in PBS were added before imaging. The images were acquired on the Arrayscan platform using beads as the focusing reference. Filipin was imaged at two focal plates: offset: -4 μm and -1 μm, and the WCS was imaged without an offset. The images were then analyzed using a SpotDetector Bioapplication. PM cholesterol was quantified using the image with -4 μm offset where fluorescence was quantified within the "ring" region, and intracellular cholesterol was quantified using the image with -1 μm offset where fluorescence was quantified within the perinuclear "circular" region. Total fluorescence of the "spots" per object within the "ring" region was used to estimate cholesterol loss from the PM. On the scatter plot in Figure 8b, the amount of the intracellular cholesterol was estimated using average intensity of the spots identified within the circular region. For each condition 1400-9000 cells were imaged in total in at least three independent experiments.

Identification of functional clusters
The STRING database was used to identify known and predicted protein-protein interactions between the hits (v8.3) 13 . Only interactions with scores above 0.7 are reported here.

Alexa 488 -labelled transferrin uptake assay
siRNA-transfected or BafA1-treated cells were incubated in serum-free DMEM for 45 min prior to a 7 min pulse with Alexa 488 -labelled transferrin at 37°C. The cells were then washed and fixed (3.3% formaldehyde, 15 min) at 4°C, surface transferrin receptor was labelled using an Alexa 647 secondary antibody, and the DNA was stained with Hoechst. Fluorescence data were collected using the plate reader as described above. The Alexa 488 / Alexa 647 and Alexa 647 /Hoechst ratios were used as a measure of endocytosis efficiency and transferrin receptor accumulation at the cell surface respectively. For the knockdown experiments, the ratios were normalised per experimental repeat by dividing by the mean value of the RISC-free control wells. For time course experiments, triplicates within an experiment were averaged (Alexa 488 /Hoechst and Alexa 647 /Hoechst ratios calculated for each well) and for each time point, the values from the BafA1-treated wells were normalised to the mean of the wells treated with DMSO for the same length of time. The Alexa 488 / Alexa 647 ratios were then calculated by dividing the normalised values.

I-labeled transferrin uptake assay
The 125 I-transferrin uptake assay has been previously described 31 . Briefly, control and treated cells were pre-incubated on ice with 125 I-labeled transferrin in serum-free medium for 30 min at 4°C, followed by incubations at 37°C for various times. The medium was collected, surface-bound transferrin was stripped with a low pH wash, and the cells were extracted with 1 M NaOH. Counts were quantified with a gamma counter. The graphs represent counts associated with intracellular transferrin as a fraction of total.

Fluorescence microscopy
For FRAP experiments, the cells were transfected with clathrin light chain A-GFP, BafA1treated 2 h post transfection, and imaged 24 h later in CO 2 -independent medium (Invitrogen) with a Zeiss LSM710 microscope equipped with a temperature controlled incubator (37°C). Fluorescence intensity data were collected in the bleach region (ROI1), a reference region within the same cell (ROI2), and a background region (ROI3). The measurements were performed at 2 s intervals for 180 s, with the beach following the 5 th readout. Bleaching resulted in average loss of 73% and 83% of fluorescence for control and BafA1-treated samples respectively. The data for ROI1 was corrected for the background and photobleaching (F ROI1 -F ROI3 )/(F ROI2 -F ROI3 ), the fluorescence of the first post-bleach readout was subtracted from the measurements, and the results were divided by the average fluorescence of the first five time points. Three independent experiments were performed; in each from 9 to 18 cells per condition were analyzed.
For filipin staining, the cells were fixed for 30 min in 3.3% formaldehyde/PBS and incubated with filipin for 2 h. Alexa 488 transferrin uptake for microscopy was performed for 7 min at 37°C and the cells were fixed in 3.3% formaldehyde for 15 min. Images were acquired using a Zeiss Axiovert 200M widefield fluorescence microscope equipped with a Roper Scientific CoolSNAP cf camera and a Plan-Apo 63x/1.4 oil-immersion lens using OpenLab software. The panels were assembled using Adobe Photoshop CS4.

Resin embedding of whole cells
For thin section electron microscopy, control, V-ATPase depleted cells (using ATP6V0C and ATP6V1B2 SMARTpools) and BafA1-treated (16 hr) cells were fixed in tissue culture dishes and prepared for EM as previously described 30 . Ultrathin sections were cut, collected onto formvar/carbon-coated EM grids, and stained with uranyl acetate and lead citrate. The sections were observed in a Philips CM 100 transmission electron microscope (Philips Electron Optics) at 80 kV.
For quantitative analysis of the size of CCSs, micrographs were taken of cells sectioned perpendicular to the PM at a magnification of ×34,000 using a digital camera (Megaview III TEM; Soft Imaging System). For CCSs that were in continuity with the PM, the depth of the pit and the width of the neck were measured, whereas for cross-sectioned CCSs (within 250 nm of the PM), two axes were measured using iTEM software. For each condition, at least 93 CCSs were scored.

PM replicas
Control and BafA1-treated cells (24 h), with or without 12.5 μg/ml cholesterol in the media, were grown on glass coverslips, washed in warm PBS, incubated for several seconds with polylysine in PBS and 'unroofed' using sonication as described 67 , except that sonication was performed in warm Hank's solution (HBSS). The exposed PMs were immediately fixed in 2% gluteraldehyde in 25 mM HEPES, 125 mM K-acetate, 50 mM-Mg-acetate, pH 7.3 and further processed by critical point drying and rotary shadowing, as described 33 and viewed in a Tecnai Spirit Biotwin 120 keV TEM (FEI Company). The images were acquired with a Gatan Orius CCD camera.

pH measurements
For pH measurements, cells were transfected with pH constructs 24 h prior to being assayed. The cells were harvested in either 10% FCS/PBS or pH buffers (15 mM NaOH, 10 mM PIPES, 10 mM HEPES, 5 mM Glucose, 1 mM NaH 2 PO 4 , 0.5 mM MgSO 4 , 1 mM CaCl 2 , 50 mM KCl and 90 mM potassium L-glutamate brought to required pH using KCl or NaOH) and analysed on the BD LSRFortessa (BD Biosciences) Flow Cytometer using a 488 nm laser with 430/30 filters to excite SEpHluorin and a 561 nm laser with 610/20 filters to excite mCherry.
Moderate expressors gated in the mCherry channel were selected for analysis. For quantification, mCherry and pHluorin were background-corrected, and the SEpHluorin/ mCherry ratio was calculated (using the 'derived parameter' function in FlowJo Version 7.6). Then the median values of the ratio from BafA1, DMSO or pH buffer-treated cells were normalised to untreated cells. Two-tailed, unpaired t-test was used to estimate statistical significance.

Statistical methods
Details of statistical analyses are provided in subsections referring to the individual assays.

Figure 1. Summary of the multi-step screening strategy
In the primary genome-wide screen (a), 21,121 siGENOME SMARTpools (four siRNAs per gene) were screened using a plate reader-based assay for hits that lead to accumulation of clathrin-dependent cargo proteins on the cell surface, without increasing the levels of surface MHC class I (see also Figure 2). CD8 chimeras with YXXΦ or FXNPXY motifs inserted into their cytoplasmic tails were used as model CCV cargo. 241 primary screen positives were selected for the secondary screens (b, c). The efficiency of endocytosis was measured using the CD8 chimera-expressing cells (b, see also Figure 3) and the morphology of CCSs at the plasma membrane was assessed using a CALM immunolabelling and automated microscopy-based assay (c, see also Figure 4). For selected genes, knockdown cells were tested for the ability to internalize transferrin (d), and CCSs at the PM were characterized using electron microscopy (e).  Table S3), and phenotype specificity (increase on the cell surface specific for CCV-cargo only, not accompanied by an increase of MHC-I).  (c) CALM labelling in fields with low and high cell density. Scatter plot represents average intensity per pixel of CCSs from fields (within a single well) with lowest and highest density (one dot per cell). Bar chart shows average intensity per pixel and total intensity per spot from RISC-free wells, data from 45 wells, 15 plates over two independent Hits with a phenotype in either the endocytosis or the CCS morphology assay were pooled and analyzed using STRING. Four functional clusters were identified. Within each network, the colour of the symbol indicates the phenotype in the CCS morphology screen, and the shape of the symbol indicates the phenotype in the endocytosis efficiency screen. KAT5 is the official gene symbol for the gene annotated in the library as HTATIP. Although theoretically one would expect all of the genes encoding subunits of the same complex to have the same knockdown phenotype, in practice there are differences due to factors such as knockdown efficiency and threshold for hit selection. In addition, genes from the same functional cluster might have different regulatory effects on CCVs components, and therefore different effects on CCS intensity.  reference, untreated cells were harvested in K + /nigericin buffers of predetermined pH. The histograms represent the pHluorin/mCherry fluorescence ratios. (g) Medians of SEpHluorin/ mCherry ratios normalised to the median of untreated cells in each experiment. *** p ≤ 0.001, * p ≤ 0.05.