Overcoming Protein Orientation Mismatch Enables Efficient Nanoscale Light-Driven ATP Production.

Adenosine triphosphate (ATP)-producing modules energized by light-driven proton pumps are powerful tools for the bottom-up assembly of artificial cell-like systems. However, the maximum efficiency of such modules is prohibited by the random orientation of the proton pumps during the reconstitution process into lipid-surrounded nanocontainers. Here, we overcome this limitation using a versatile approach to uniformly orient the light-driven proton pump proteorhodopsin (pR) in liposomes. pR is post-translationally either covalently or noncovalently coupled to a membrane-impermeable protein domain guiding orientation during insertion into preformed liposomes. In the second scenario, we developed a novel bifunctional linker, trisNTA-SpyTag, that allows for the reversible connection of any SpyCatcher-containing protein and a HisTag-carrying protein. The desired protein orientations are verified by monitoring vectorial proton pumping and membrane potential generation. In conjunction with ATP synthase, highly efficient ATP production is energized by the inwardly pumping population. In comparison to other light-driven ATP-producing modules, the uniform orientation allows for maximal rates at economical protein concentrations. The presented technology is highly customizable and not limited to light-driven proton pumps but applicable to many membrane proteins and offers a general approach to overcome orientation mismatch during membrane reconstitution, requiring little to no genetic modification of the protein of interest.

Current problems and future avenues in proteoliposome research.

Membrane proteins (MPs) are the gatekeepers between different biological compartments separated by lipid bilayers. Being receptors, channels, transporters, or primary pumps, they fulfill a wide variety of cellular functions and their importance is reflected in the increasing number of drugs that target MPs. Functional studies of MPs within a native cellular context, however, is difficult due to the innate complexity of the densely packed membranes. Over the past decades, detergent-based extraction and purification of MPs and their reconstitution into lipid mimetic systems has been a very powerful tool to simplify the experimental system. In this review, we focus on proteoliposomes that have become an indispensable experimental system for enzymes with a vectorial function, including many of the here described energy transducing MPs. We first address long standing questions on the difficulty of successful reconstitution and controlled orientation of MPs into liposomes. A special emphasis is given on coreconstitution of several MPs into the same bilayer. Second, we discuss recent progress in the development of fluorescent dyes that offer sensitive detection with high temporal resolution. Finally, we briefly cover the use of giant unilamellar vesicles for the investigation of complex enzymatic cascades, a very promising experimental tool considering our increasing knowledge of the interplay of different cellular components.

Gene-signature-derived IC50s/EC50s reflect the potency of causative upstream targets and downstream phenotypes.

Multiplexed gene-signature-based phenotypic assays are increasingly used for the identification and profiling of small molecule-tool compounds and drugs. Here we introduce a method (provided as R-package) for the quantification of the dose-response potency of a gene-signature as EC50 and IC50 values. Two signaling pathways were used as models to validate our methods: beta-adrenergic agonistic activity on cAMP generation (dedicated dataset generated for this study) and EGFR inhibitory effect on cancer cell viability. In both cases, potencies derived from multi-gene expression data were highly correlated with orthogonal potencies derived from cAMP and cell growth readouts, and superior to potencies derived from single individual genes. Based on our results we propose gene-signature potencies as a novel valid alternative for the quantitative prioritization, optimization and development of novel drugs.