Profiling lipid-protein interactions using nonquenched fluorescent liposomal nanovesicles and proteome microarrays

Fluorescent liposomal nanovesicles (liposomes) are commonly used for lipid research and/or signal enhancement. However, the problem of self-quenching with conventional fluorescent liposomes limits their applications because these liposomes must be lysed to detect the fluorescent signals. Here, we developed a nonquenched fluorescent (NQF)1 liposome by optimizing the proportion of sulforhodamine B (SRB) encapsulant and lissamine rhodamine B-dipalmitoyl phosphatidylethanol (LRB-DPPE) on a liposomal surface for signal amplification. Our study showed that 0.3% of LRB-DPPE with 200 μm of SRB provided the maximal fluorescent signal without the need to lyse the liposomes. We also observed that the NQF liposomes largely eliminated self-quenching effects and produced greatly enhanced signals than SRB-only liposomes by 5.3-fold. To show their application in proteomics research, we constructed NQF liposomes that contained phosphatidylinositol 3,5-bisphosphate (PI(3,5)P2) and profiled its protein interactome using a yeast proteome microarray. Our profiling led to the identification of 162 PI(3,5)P2-specific binding proteins (PI(3,5)P2-BPs). We not only recovered many proteins that possessed known PI(3,5)P2-binding domains, but we also found two unknown Pfam domains (Pfam-B_8509 and Pfam-B_10446) that were enriched in our dataset. The validation of many newly discovered PI(3,5)P2-BPs was performed using a bead-based affinity assay. Further bioinformatics analyses revealed that the functional roles of 22 PI(3,5)P2-BPs were similar to those associated with PI(3,5)P2, including vesicle-mediated transport, GTPase, cytoskeleton, and kinase. Among the 162 PI(3,5)P2-BPs, we found a novel motif, HRDIKP[ES]NJLL that showed statistical significance. A docking simulation showed that PI(3,5)P2 interacted primarily with lysine or arginine side chains of the newly identified PI(3,5)P2-binding kinases. Our study showed that this new tool would greatly benefit profiling lipid-protein interactions in high-throughput studies.