Pathogen receptor discovery with a microfluidic human membrane protein array

Significance

In this work, we report, to our knowledge, the first in vitro tool for host–pathogen screening that encompasses thousands of functional insoluble proteins—primarily transmembrane proteins—immobilized within a microfluidic device. We discovered previously unknown protein–pathogen interactions, and then selected interactions were further validated by conventional methods. Considering the tremendous difficulty in discovering pathogen receptors, this in vitro high-throughput approach is extremely important and efficient for receptor discovery and understanding pathogen tropism, with relevance to emerging human diseases.

Abstract

The discovery of how a pathogen invades a cell requires one to determine which host cell receptors are exploited. This determination is a challenging problem because the receptor is invariably a membrane protein, which represents an Achilles heel in proteomics. We have developed a universal platform for high-throughput expression and interaction studies of membrane proteins by creating a microfluidic-based comprehensive human membrane protein array (MPA). The MPA is, to our knowledge, the first of its kind and offers a powerful alternative to conventional proteomics by enabling the simultaneous study of 2,100 membrane proteins. We characterized direct interactions of a whole nonenveloped virus (simian virus 40), as well as those of the hepatitis delta enveloped virus large form antigen, with candidate host receptors expressed on the MPA. Selected newly discovered membrane protein–pathogen interactions were validated by conventional methods, demonstrating that the MPA is an important tool for cellular receptor discovery and for understanding pathogen tropism.

The human genome contains ∼21,000 distinct protein-coding genes (1), out of which ∼5,360 code for membrane proteins (2). Membrane proteins are critical for many cellular processes, such as signaling, transport, cell–cell communication, and also interaction with pathogens leading to various cellular responses. It is not surprising that 60% of drugs currently in the market target proteins at the cell surface (3). Mapping molecular interactions of membrane proteins is, therefore, of utmost importance. Pathogen–host recognition involves surface interactions regulated by membrane proteins. Many interactions between membrane proteins and pathogens are unknown, partly because of the low sensitivity and limited compatibility of current methodologies with membrane proteins (4). These limitations pose a major obstacle in understanding pathogen tropism, a public health concern in view of emerging diseases, e.g., severe acute respiratory syndrome and Ebola. There is therefore a need for new approaches that would recapitulate the pathogen–host molecular recognition, let alone in the context of intact pathogens.

Mapping protein–protein interaction (PPI) is a major challenge in proteomics. Many molecular interactions are transient and weak, leading to low yield of bound material and thus demanding highly sensitive detection methods. Current methods for characterizing PPI networks suffer from several basic disadvantages: low sensitivity, leading to high false negative rate; low specificity, leading to high false positive rate (5–7); low coverage of known interactions; and high variability, even in screens from the same species (4). Protein arrays could potentially override such limitations (8), but suffer from a purification bottleneck and limited functionality after deposition (9). These difficulties are even more pronounced with membrane proteins. Membrane proteins are usually in low abundance; in addition, they are incompatible with high-throughput methods (e.g., yeast two-hybrid) and are difficult to purify in functional form (e.g., protein arrays). One partial solution to these obstacles was to print DNA and translate into proteins in situ (10, 11). This approach has enabled the study of the Pseudomonas aeruginosa outer membrane protein for immunity (12).

Combining integrated microfluidics with microarrays and in vitro transcription and translation (TNT) systems may overcome all of the above mentioned difficulties (Fig. 1A) (13–16). The integrated microfluidic device allows smart liquid management in very low volumes, partitioning, and process integration (i.e., protein expression, immobilization, and interaction experiments). Microarray technology provides the means for programming thousands of different experiments (17). In vitro TNT expression systems allow protein biosynthesis and are compatible with high throughput (18). Such systems are commercially available and benefit from fast protein expression, low reaction volumes, and short reaction times and enable expression of synthetic proteins with inserted epitope tags. Adding microsomal membranes enable the correct folding of membrane proteins and support posttranslational modifications, such as glycosylation (9). In short, the microfluidic platform facilitates using in vitro TNT systems to produce a reliable membrane protein array (MPA) from DNA with high sensitivity, low material and protein consumption, and compatibility with membrane proteins.

Fig. 1.

Membrane protein array generated by integrated microfluidic platform. (A) An integrated microfluidics platform (Left) was used for on-chip expression of membrane proteins, to serve as “baits” for protein interactions or modifications (29). The device consists of two polydimethylsiloxane (PDMS) layers, a flow layer with 64 × 64 unit cells array (gray), and a control layer with micromechanical valves (colored) that manipulate the flow of fluids in the experiment (Center). The sandwich valves (pink) separate neighboring unit cells; the neck valves (green) divide each unit cell into a DNA compartment and a reaction compartment. The button valves (blue) enable surface patterning to promote binding of proteins to an antibody surface. The button valves serve as mechanical traps of molecular interactions (MITOMI) and allow measurement at equilibrium concentration. MITOMI increases the sensitivity of the system, facilitating detection of weak and transient interactions (SI Appendix, Fig. S6). Combining the microfluidic platform with microarray technology enables programming of the device with up to several thousand spotted genes (Right). Using assembly PCR (SI Appendix, Fig. S1), we added c-Myc (N-terminal) and His₆ (C-terminal) tags to the ORFs, creating synthetic genes. On-chip in vitro protein expression, following the synthetic gene programming, combined with the corresponding antibody surface patterning, facilitates the self-assembly of a MPA using cell-free TNT (rabbit reticulocyte). The immobilized bait proteins are labeled with fluorescent antibodies and quantified by using a microarray scanner. Expressed proteins form a green circle below the button valve (Right). (B) We expressed 2,686 different human membrane proteins on chip. The z axis represents the average expression level (n = 4); x and y axes represent the position on-chip in the 2D protein array. Membrane proteins were immobilized on the surface by their C terminus (B) or N terminus (C). Unspotted (red) chambers were used as negative controls. Levels of expression that were 2 SDs above the negative controls were considered positive. Color gradients are for easier visualization only. (D) The SE of protein expression was calculated for each protein, and for most proteins it was relatively uniform, with an error of 10% or below. The data represents both intrachip and interchip variability.

In this study, we used a microfluidic platform to combine microarray technology, cell-free protein expression, and integrated microfluidics, allowing high-throughput screening of pathogens with a human membrane proteome library. As a proof-of-concept, we screened two pathogens differing in structure and physiology. The first was simian virus 40 (SV40), a nonenveloped polyomavirus containing circular double-stranded DNA, which can induce membrane invaginations, similarly to other polyomaviruses. It causes infections of the kidney and possibly also other tissues such as the mesothelium, and it has also been associated with cancer (19, 20). The second pathogen was the hepatitis delta virus (HDV). We screened the large-form delta antigen (l-HDAg), a prenylated protein essential for HDV virion assembly by allowing interaction with the envelope proteins of the hepatitis B helper virus (21, 22). Understanding interactions of both these viruses with host membrane proteins may shed light on important pathogenic processes.

We created a library of ∼2,700 synthetic genes, which we arrayed and expressed within the microfluidic platform using a cell-free protein expression system. Then, we screened the assembled MPA for interactions with each pathogen and identified new interactions. A bioinformatics approach was used to identify biological processes associated with the newly found interactions. Specific interactions of interest were chosen for further validation by either coimmunoprecipitation (Co-IP) or protein–fragment complementation assay of luciferase activity (PCA). We successfully demonstrated the effectiveness of using a microfluidic platform for performing a high-throughput screen of pathogen–membrane protein interactions.

Results and Discussion

Protein Expression/MPA Protein.

To create a human MPA, we constructed ∼2,700 linear synthetic genes encoding for human membrane proteins, using an assembly PCR approach (Materials and Methods; SI Appendix, Fig. S1) (14, 23–25). The transmembrane domain frequency of these synthetic genes matched the predicted frequency in the human membrane proteome (SI Appendix, Fig. S2) (2). A microfluidic device was then programmed with this ORF array (SI Appendix, Fig. S3). The programming (alignment of microarray to the device) was performed manually. On average, 10% of the genes were misaligned and thus could not be expressed. After surface functionalization of the chip, the genes were expressed on-chip by using rabbit reticulocyte TNT and microsomal membranes. We immobilized the expressed membrane proteins to the slide surface via either their N or C terminus, using an antibody. Only full-length proteins were labeled with fluorescent antibodies on their corresponding C (c-Myc tag) or N (6-histidine tag) termini (Fig. 1). Protein expression levels ranged from no expression (0 a.u.) to high expression (>1,000 a.u.). Chambers without spotted DNA were used as negative controls (Materials and Methods). No nonspecific protein labeling was observed by incubating the MPA with a nonspecific fluorescent antibody (SI Appendix, Fig. S4). More than 2,100 proteins (80%) were properly expressed on-chip, regardless of the direction by which they were immobilized to the surface (Fig. 1B, SI Appendix, Table S1, and Dataset S1). Similar results were obtained when we expressed soluble protein arrays on a chip (SI Appendix, Fig. S5). In contrast, the dynamic range of expression was much lower for membrane proteins than for soluble proteins. This finding is consistent with the literature and is most likely due to the addition of microsomal membranes, which become the limiting factor in the reaction (9, 26, 27).

Several possible factors can affect protein expression, including DNA concentration, protein length, and membrane topology. We examined possible bias in protein expression due to spotted DNA concentration (0–0.2 µM) or protein length (60–1,400 aa). We found no correlation between protein expression and DNA concentration or protein length (SI Appendix, Figs. S7 and S8).

We were concerned that transmembrane domain topology may affect the efficiency of protein expression and that bias toward certain topologies may exist. To confirm whether such a bias existed, we divided the proteins according to the number of their transmembrane domain. These ranged from 0 to 14 transmembrane domains. The number of transmembrane domains did not affect average expression levels, which hence were not affected by protein topology (SI Appendix, Fig. S9). We also demonstrated that both sides of the membrane proteins were accessible for interaction (SI Appendix, Fig. S10). We attributed this accessibility to microsomal membrane instability (i.e., vesicle fusion) due to changes in surface tension following protein expression (8, 22, 23).

To demonstrate that the membrane proteins expressed using the cell-free expression procedure were functional, selected membrane proteins with previously established ligand interactions were expressed via the same expression procedure and immobilized onto a chip (SI Appendix, Fig. S11). Interactions of 13 human receptors and their corresponding fluorescently labeled ligand were examined, and 10 pairs (∼75%) demonstrated specific interactions, indicating a likelihood that a significant proportion of the 2,700 membrane proteins were properly folded and functional.

On-Chip Virus Screening.

As proof of concept for host–pathogen recognition, we screened the MPA for potential viral receptors using a fluorescently labeled SV40 as well as l-HDAg (Fig. 2). For SV40 we used a two-step strategy—a wide screen followed by a randomized focused screen. The second screen included the positive hits from the wide screen, a control set of known positives (from the literature) and a set of negative controls for which no interaction was reported or observed in the first screen. A total of 99 interactions were observed (SI Appendix, Table S2 and Dataset S2), including 14 of the 22 positive controls (Fig. 2B). We determined the sensitivity and specificity of this system to SV40-membrane protein interaction to be 64% and 71%, respectively (SI Appendix, Table S3).

Fig. 2.

Pathogen receptor discovery with MPA, an original tool for de novo characterizing viral tropism. (A, Left) Schematic overview of the experimental procedure. Once bait proteins were immobilized on the surface, the virus was introduced into MPA and incubated with the MPA for 30 min. (A, Right) Images of two representative unit cells depicting bait protein (green) and pathogen interaction (red) with positive binding (Upper) and negative control with no binding (Lower). (B and C) Cy5-labeled SV40 virions (B) and l-HDAg (C) were applied to the MPA to test for pathogen–membrane protein interactions. Positives in the large screen were collected and reprinted in a different arrangement to avoid technical biases. Approximately 100 novel SV40–protein interactions and ∼150 l-HDAg–protein interactions were discovered via the MPA screen. Signals below the cutoff (SI Appendix, Fig. S13 and Materials and Methods) and above the background were filtered out. Interactions are presented as the average ratio of pathogen binding to membrane protein expression (n = 4): new interactions are in blue; known SV40 partners detected by MPA are in red.

As with SV40, the protein array library for screening l-HDAg was expressed on-chip by using cell-free TNT. In parallel, l-HDAg, the prey viral protein, was expressed in-tube by using the same cell-free procedure and microsomal membranes, creating synthetic viroid-like particles. After assembly of the MPA, l-HDAg was loaded onto the device and subsequent incubation period of isolated unit cells allowed possible host-l-HDAg interactions to reach equilibrium. The surface-bound protein array and the trapped l-HDAg were then incubated with fluorescently labeled antibodies for the different tags on the respective proteins. Fluorescent signals were measured by using a microarray laser scanner, and the extracted data was analyzed for specific interactions. A total of 150 interactions were observed and further analyzed (Fig. 2C, SI Appendix, Table S4, and Dataset S3). Indeed, the identified membrane interactome achieved for l-HDAg was distinct from SV40, with only seven interacting proteins common to both pathogens, demonstrating high specificity of the microfluidic platform.

Among our discovered interactions, for example, we detected binding of SV40 to SCRB2, a close homolog of SCRB1, which had been previously reported to bind SV40 (28). Another previously unidentified interaction was with TNR12, a protein that is highly expressed in heart, placenta, and kidney. It is a close homolog of both TNR3 and TNR5, both previously reported to bind SV40 (28). These interactions point to a previously suggested common SV40 binding domain to TNR proteins (28). SV40 traffics via the endosomal pathway into the ER (29) and is known to bind to ganglioside GM1, present in caveolar/lipid raft domains at the plasma membrane (30, 31). Notably, 23% (19 of 85) of our discovered interactions are located in lipid rafts, caveola, and endoplasmic reticulum (ER) membrane (SI Appendix, Table S2 and Dataset S2). This percentage is much higher than their representation in MPA (12%). The mechanism by which SV40 crosses the ER membrane is unknown (32), with possible involvement of these interactions. SV40 interaction with CD20, CD116, CD140b, and BST, an IFN-induced antiviral host restriction factor, may play a role in cell entry of SV40 as well as in its immune evasion.

For interacting proteins of l-HDAg, we used the Database for Annotation, Visualization and Integrated Discovery functional annotation tool (https://david.ncifcrf.gov) to establish the most relevant biological processes [Gene Ontology (GO) terms] associated with the proteins in our interaction list. A total of 63 of the identified interactions are associated with 13 significantly enriched biological processes, including glycoprotein metabolic process, immune response, carbohydrate biosynthetic process, or ER to Golgi vesicle-mediated transport (SI Appendix, Fig. S12).

For both pathogens, their interacting membrane proteins were analyzed by using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING; string-db.org), based on known and predicted PPIs, to examine physical or functional associations among the proteins in the interaction list. STRING provided a graphic representation of a network of interactions between some identified pathogen-interacting proteins (Fig. 3). Interestingly, although the biological function of most of the observed interactions remains to be explored, both SV40 and l-HDAg were shown to interact independently with proteins that are components of the same functional complex. We observed, for example, SV40 binding to TMED1, TMED5, TMED10, and KDELR3 proteins. These have a potential role in vesicular protein trafficking, implying involvement in virion trafficking. l-HDAg interacts with USE1 and syntaxin 18 (STX18), both components of a complex involved in Golgi to ER retrograde transport that directly interact with each other. l-HDAg also interacts with PDGFRA and PDGFRB, which upon ligand binding at the plasma membrane, form a heterodimer and initiate several signaling cascades, depending on the nature of the bound ligand.

Fig. 3.

Known and predicted PPI between SV40 (A) and l-HDAg (B) identified pathogen-interacting proteins using STRING. Disconnected proteins (nodes) were excluded.

Validation of Proteomic Results.

SV40 protein interactions were validated by co-IP, and we independently validated 25 interactions including negative controls. These interactions included representative proteins from different biological processes, some of which are observed in the STRING diagram (Fig. 3). Of 20 interactions detected by MPA, 18 were verified by co-IP (Fig. 4A and SI Appendix, Fig. S14), demonstrating very high correlation (90%) between the MPA-detected interactions and co-IP experiments. The failure of two proteins in co-IP with SV40 may be attributed to the higher sensitivity of our MPA. Interactions were measured relative to five negative controls, four of which binding to SV40 was negligible. The cutoff for the positive signal was three SDs above the average of all five negative controls. The bead analysis was performed by fluorescence microscopy because of the limited amount of membrane protein sample available, which further emphasized the advantage of using MPA.

Fig. 4.

Validated pathogen–protein interactions. (A) Co-IP of SV40 and 25 different membrane proteins using magnetic beads. All membrane proteins were tagged similarly to the microfluidics assay and expressed by using cell-free TNT. Proteins were immobilized to T1 magnetic beads coated with α-His antibody and scanned by fluorescent microscopy for either protein expression, following α-c-Myc Cy3 antibody labeling, or for Cy5-labeled SV40, after co-IP. Image analysis revealed that SV40 coimmunoprecipitated with 18 of 20 proteins (blue). These results demonstrate high correlation with the MPA screen (90%). The interactions of 17 proteins were highly significant, and a mild interaction was observed for one protein. *P < 0.01; **P < 0.00001. SV40 failed to co-IP with two proteins (light blue). In addition, four negative control proteins of five showed negligible binding to SV40 virions. The fifth demonstrated some low nonspecific binding. (B) Validation of l-HDAg interactions by PCA. Combinations of plasmids encoding a pair of proteins, a human membrane protein and l-HDAg each fused to a fragment of the G. princeps luciferase protein (Gluc1 and Gluc2, respectively) were cotransfected into 293T cells. Combinations with empty Gluc1 or Gluc2 plasmids were used as negative controls. Results were expressed as a luminescence ratio, representing the average luminescence signal detected in cells transfected with both vectors divided by that measured in control wells.

Validation of the l-HDAg proteomic results was performed for selected proteins by PCA, because very high nonspecific binding was observed with co-IP. Because of the role of l-HDAg in viral assembly and secretion, we selected identified host proteins that are involved in vesicular trafficking for further verification. We also selected several representative proteins from other biological processes, several of which are represented in the STRING analysis (Fig. 3). The luciferase activity of the 21 l-HDAg–protein interactions we found was measured, and results were expressed as normalized luminescence ratios. Seven interactions gained a relative luciferase activity signal that was at least three times greater than their respective negative controls (Fig. 4B). The lower success rate of l-HDAg validation compared with SV40 could be attributed to the differences in validation techniques and/or that its lipid-bilayer envelope reduces the MPA specificity. STX18, PREB, SCAMP4, and CAV-1 are proteins involved in vesicular trafficking. SEC63 is involved in translocation of proteins across the ER membrane, whereas DNAJB11 is involved in the folding of proteins entering the ER. ZDHHC11 is a member of the palmitoyltransferase family.

In conclusion, we have presented the application of our human functional MPA toward discovery of pathogen–host interactions. MPA impact in pathogen tropism research is especially important for investigating emerging diseases. Our results demonstrated that the microfluidic affinity assay is a powerful tool for identifying PPIs in general, and, more specifically, pathogen–transmembrane protein interactions. We estimate the functionality of our MPA to be >65%, based on the number of validated interactions (35 of 54). The proteomics establishment of intertwined relations between many of the identified interacting proteins provide new perspectives on viral behaviors during infection and pave the way for further research in various directions. Furthermore, this platform may also serve for testing for drug design, antibody specificities, or orphan receptors/ligands as well as in a wide spectrum of other research areas that involve membrane proteins.

Materials and Methods

Mold Fabrication.

The microfluidic devices were designed in a similar manner as described (14, 23, 33). Details are described in SI Appendix, SI Materials and Methods).

Device Fabrication.

The microfluidic devices were fabricated on silicone molds casting silicone elastomer polydimethylsiloxane (SYLGARD 184, Dow Corning). Details are described in SI Appendix, SI Materials and Methods.

Production of Human Synthetic Genes Library via Assembly PCR.

Synthetic linear human genes were generated by using two-step assembly PCR (SI Appendix, Fig. S1). As a template for the first PCR, we used a library of the Human ORFome in gateway-donor GW223 plasmids (Open Biosystems). A high-fidelity hot start DNA polymerase (Phusion II; FINNZYMES) was used for all PCR procedures. In the first PCR step, two epitope tags were added to each protein, c-Myc at the N terminus and 6-His at the C terminus. The tags were added by using the primers 5′GW223–c-Myc and 3′-GW223–His. A reaction mix with a total volume of 20 µL was prepared by using 0.8 units of DNA polymerase for each reaction. The PCR assay was performed in a PCR 96-well plate in 25 cycles with annealing temperature of 64 °C. The extension time ranged from 45 to 300 s in 72 °C depending on the ORF length. The first PCR product served as a template for the second PCR. In addition, two different pairs of primers were used for the second PCR step by adding the 5′ UTR (T7 promoter) and 3′ UTR (T7 terminator) for each gene. The reaction mixture with a total volume of 50 µL was prepared containing 1.5 units of DNA polymerase. The first extension primer pair, containing 85 and 95 bp, was added to the mixture in a low concentration (2.5 nM). After 10 cycles, the second primer pair (5′ final and 3′ final) was added to the PCR mixture (0.2 µM) for an additional 25 cycles, completing the PCR process. The PCR products were filtered in multiwell 10k filter plates (AcroPrep; PALL) and eluted with 40 µL of double-distilled water. The yield of gene product was verified twice, at the end of the first PCR step and after 1.5% agarose gel electrophoresis. In addition, PCR products were transferred to 384 UV-readable plates, and concentrations were measured by using a UV plate reader (Synergy 4 Hybrid Microplate Reader; BioTek).

DNA Arraying and Device Alignment.

A series of synthetic genes were spotted onto epoxy-coated glass substrates (CEL Associates) with a MicroGrid 610 (Bio Robotics) microarrayer by using SMT-S75 silicone pins (Parallel Synthesis). Column and row pitch corresponded to the specific device. The device we used contains 65 columns and 64 rows with a pitch of 281.25 by 562.5 µm, respectively. Each sample solution contained 0.125% of polyethylene glycol (PEG; Sigma Aldrich) and d-trehalosedihydrate (Sigma-Aldrich) at a concentration of 12.5 mg/mL in dH₂O to prevent irreversible binding of the DNA to the glass, as well as for visualization during alignment. Finally, the arrays were aligned to the microfluidic device by hand under a stereoscope and bonded for 4 h on a heated plate at 80 °C.

Surface Functionalization.

To prevent nonspecific adsorption and to achieve suitable binding orientation of expressed proteins, all accessible surface area within the microfluidic device was chemically modified. This surface chemical modification also facilitates the self assembly of a protein array on the surface. Biotinylated BSA (1 µg/µL; Thermo) was flowed through the device for 30 min, binding the BSA to the epoxy surface. On top of the biotinylated BSA, 0.5 µg/µL Neutravidin (Pierce) was added for 30 min. The “button” valve was then closed, and biotinylated PEG (1 µg/µL; Nanocs) was flowed through the chip for 30 min, passivating the rest of the device. After passivation, the button valve was released and a flow of 0.2 µg/µL penta-His (Qiagen) or c-Myc (Cell Signaling). Biotinylated antibodies was applied. The antibody bound to the exposed Neutravidin, specifically to the area under the button, creating an anti-His tag or c-Myc tag array. Hepes (50 mM; Biological Industries) was used for washing unreacted substrate between each of the different surface chemistry steps.

Protein Expression.

Proteins were expressed on the device by using rabbit reticulocyte quick-coupled TNT reaction (Promega). Microsomal membranes (Promega) were added to the extract to express membrane proteins (including l-HDAg). The expression of the proteins from the spotted synthetic genes on the device created an array of proteins ready for use in a binding screen. By opening the “neck” valves, 12.5 µL of the expression mix was flowed through the device into the gene chamber. Next, the “sandwich” valves were closed, leaving each unit cell separated from its environment, and the device was incubated on a hot plate for 2.5 h at 32 °C. Expressed proteins were then diffused through the gene chamber to the reaction chamber, binding their C terminus His tag to the anti-His antibody or their N terminus c-Myc tag to the c-Myc antibody under the button valve, immobilizing the protein. Proteins were labeled with a c-Myc (Sigma-Aldrich) or penta-His (Qiagen) Cy3 antibody, which bound to its corresponding epitope and labeled it. Unspotted chambers were used as negative controls. Because no DNA was spotted in these chambers, we expect that no proteins can be expressed. Thus, any signal from these chambers is nonspecific background. Nonspecific labeling of the fluorescent antibody was determined by using an anti–V5-FITC antibody (Cell Signaling). Protein expression levels were determined with a microarray scanner (LS Reloaded; Tecan) using a 532-nm laser and 575-nm filter.

Receptor–Ligand Interactions.

Human receptors with N terminus c-Myc and C terminus T7 tag were expressed by using rabbit reticulocyte quick-coupled TNT reaction in the presence of microsomal membrane (Promega). The expression was performed in a final volume of 12.5 µL, including 1 µg of DNA. The tube was incubated at 32 °C for 2.5 h with agitation (600 rpm). In parallel, we prepared the surface chemistry and α-T7 biotinylated antibodies (Qiagen) bound under the button. Next, each expressed receptor was attached to a specific part of the device and bound to its corresponding antibody, creating a receptors array. Finally, His-tagged recombinant ligands (CXCL10, CTLA4, ZP3, EGF, CD40L, TNF-α, TNF-β, and CD48; purchased from Prospec) and FASL (Peprotech) were applied to the device. By closing the sandwich valves, each unit cell separated from its environment. Next, the button valves opened, exposing the receptor array. Ligands were allowed to incubate with the receptor array for 30 min at 32 °C. Proteins were then labeled with α-c-Myc Cy3 (Sigma) and α-HIS Alexa Fluor 647 (Qiagen) antibodies. Protein interactions were determined with a microarray scanner (LS Reloaded; Tecan) using a 633-nm laser and 695-nm filter for Cy5 and a 535-nm laser and 595-nm filter for Cy3.

Production, Purification, and Labeling of SV40 Virions.

SV40 virions were produced and purified as described (25). Next, SV40 virions were labeled by using commercial kits, according to the manufacturer’s instructions (Molecular Probes). All experiments were performed in accordance with regulations approved by the Bar Ilan University Pathogen Oversight Committee.

MPA Pathogen–Host Large Screen.

For MPA screening, 2,686 membrane proteins expressed on-chip as above. Cy5-labeled SV40 virions (15 nM) were applied to the device and incubated with the protein array for 30 min at 32 °C. After incubation, buttons were closed and unbound viruses were washed out. Interaction levels were determined with a microarray scanner (LS Reloaded; Tecan) using a 633-nm laser and 695-nm filter for Cy5 and normalized to protein expression level.

MPA Pathogen–Host Second Screen.

After the MPA large screen, a second microfluidic device programmed with membrane proteins binders from the first screen, including 22 positive controls and 50 negative controls. Proteins expressed on-chip as described. Cy5-labeled SV40 virions (15 nM) were applied to the device and incubated with the protein array for 30 min at 32 °C. After incubation, buttons were closed and unbound viruses were washed out. Interaction levels were determined with a microarray scanner (LS Reloaded; Tecan) using a 633-nm laser and 695-nm filter for Cy5 and normalized to protein expression level. A cutoff of 2 and 4 SDs were used for the SV40 (SI Appendix, Fig. S13) and the l-HDAg screens, respectively.

Human “synthetic genes” were created with c-Myc (N-terminal) and six histidine (C-terminal) tags and expressed in vitro as described above. The expression was performed in a final volume of 12.5 µL, including 1 µg of DNA and incubated at 32 °C for 2.5 h with agitation (600 rpm). Expressed proteins were then incubated either with anti–c-Myc-Cy3 antibody (Sigma-Aldrich) or with Cy5-labeled SV40 virions (15 nM). Next, the proteins were immobilized to T1 magnetic beads (Invitrogen) coated by α-His–biotinylated antibody (Qiagen). The beads were washed with PBS and scanned by Nikon Eclipse fluorescent microscope for either protein expression or for SV40 co-IP. Images were analyzed by Nikon’s NIS elements software. Single beads’ median intensities were measured for either protein expression or SV40 co-IP. Statistical significance was determined by calculating P values for bead intensities of each protein compared with bead intensities of all negative controls.

l-HDAg Interaction Validation by PCA.

Two engineered Gateway vectors, pGluc1-Nter-Gateway and pGluc2-Nter-Gateway, encode for two fragments of the Gaussia princeps luciferase protein. A total of 21 ORFs encoding the human proteins were picked from the Human ORFeome library (34) (Open Biosystems) and inserted as described (35, 36) into the pGluc1-Nter-Gateway plasmid, and l-HDAg was inserted into pGluc2-Nter-Gateway (22, 37). A human membrane protein and l-HDAg fused to each plasmid, respectively, or control empty vectors were cotransfected into 293T or Huh-7.5 cells plated in 96-well plates in triplicates. At 24 h after transfection, cells were lysed and subjected to standard luciferase reporter gene assays by using the Renilla luciferase assays system (Promega). Results were expressed as luminescence ratio, which represents the average luminescence signal detected in cells transfected with both Gluc1 and Gluc2, divided by the average of luminescence measured in negative control wells transfected with Gluc1 and an empty Gluc2 vector and those transfected with Gluc2 and an empty Gluc1 vector. A combination with TSG101, which has been identified as a l-HDAg partner in a small-scale microfluidic screen (33), was used as a positive control for the assay.

Image and Data Analysis.

For MPA expression experiment, images were analyzed with GenePix7.0 (Molecular Devices). The image (cy3 channel) was used to determine bait (on ChIP-expressed protein) expression level. Rows and columns without DNA array were used to assess nonspecific binding of labeled antibodies to the surface. Each row and column was then normalized by subtracting the nonspecific baseline signal. A signal that was 2 SD above the average noise was considered successful protein expression.

For interaction two images (Cy3 and Cy5/GFP channels) were analyzed with GenePix (Molecular Devices). Rows without DNA array were used to assess nonspecific binding to the surface. Columns with no prey were used to assess nonspecific binding of labeled antibodies to the surface proteins. Each row and column was then normalized by subtracting the nonspecific baseline signal. The “interaction ratio” (Cy5/Cy3 or GFP/Cy3) was calculated, and the highest ratio was normalized to 1.

For each MPA-expressed protein, the l-HDAg interaction signal was calculated as the average of median signals obtained from the respective quadruplet. The average of median signals obtained from unit cells in the array with no spotted DNA was used to calculate a control background signal. A histogram of the l-HDAg interaction signal was plotted and allowed determination of a cutoff at 4 SD above the array control background signal as the threshold above which the interactions were considered positive (SI Appendix, Fig. S2). Each quadruplet above that threshold was examined, and interactions with false signal that resulted from visible aggregates on the glass slide or inside the microfluidic device or high SD within the quadruplet-resulting inconsistent l-HDAg interaction signal were discarded.