Imaging Voltage with Microbial Rhodopsins

Computational drug development for membrane protein targets

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learning structure-based design and the evaluation of big data. Recent protein structure predictions based on machine learning tools have delivered surprisingly reliable results for water-soluble and membrane proteins but have limitations for development of drugs that target membrane proteins. Structural transitions of membrane proteins have a central role during transmembrane signaling and are often influenced by therapeutic compounds. Resolving the structural and functional basis of dynamic transmembrane signaling networks, especially within the native membrane or cellular environment, remains a central challenge for drug development. Tackling this challenge will require an interplay between experimental and computational tools, such as super-resolution optical microscopy for quantification of the molecular interactions of cellular signaling networks and their modulation by potential drugs, cryo-electron microscopy for determination of the structural transitions of proteins in native cell membranes and entire cells, and computational tools for data analysis and prediction of the structure and function of cellular signaling networks, as well as generation of promising drug candidates.

Nanotechnology and Cancer Bioelectricity: Bridging the Gap Between Biology and Translational Medicine

Bioelectricity is the electrical activity that occurs within living cells and tissues. This activity is critical for regulating homeostatic cellular function and communication, and disruptions of the same can lead to a variety of conditions, including cancer. Cancer cells are known to exhibit abnormal electrical properties compared to their healthy counterparts, and this has driven researchers to investigate the potential of harnessing bioelectricity as a tool in cancer diagnosis, prognosis, and treatment. In parallel, bioelectricity represents one of the means to gain fundamental insights on how electrical signals and charges play a role in cancer insurgence, growth, and progression. This review provides a comprehensive analysis of the literature in this field, addressing the fundamentals of bioelectricity in single cancer cells, cancer cell cohorts, and cancerous tissues. The emerging role of bioelectricity in cancer proliferation and metastasis is introduced. Based on the acknowledgement that this biological information is still hard to access due to the existing gap between biological findings and translational medicine, the latest advancements in the field of nanotechnologies for cellular electrophysiology are examined, as well as the most recent developments in micro- and nano-devices for cancer diagnostics and therapy targeting bioelectricity.

Fluorescence of the Retinal Chromophore in Microbial and Animal Rhodopsins

Fluorescence of the vast majority of natural opsin-based photoactive proteins is extremely low, in accordance with their functions that depend on efficient transduction of absorbed light energy. However, several recently proposed classes of engineered rhodopsins with enhanced fluorescence, along with the discovery of a new natural highly fluorescent rhodopsin, NeoR, opened a way to exploit these transmembrane proteins as fluorescent sensors and draw more attention to studies on this untypical rhodopsin property. Here, we review the available data on the fluorescence of the retinal chromophore in microbial and animal rhodopsins and their photocycle intermediates, as well as different isomers of the protonated retinal Schiff base in various solvents and the gas phase.

Voltage Imaging with Engineered Proton-Pumping Rhodopsins: Insights from the Proton Transfer Pathway

Voltage imaging using genetically encoded voltage indicators (GEVIs) has taken the field of neuroscience by storm in the past decade. Its ability to create subcellular and network level readouts of electrical dynamics depends critically on the kinetics of the response to voltage of the indicator used. Engineered microbial rhodopsins form a GEVI subclass known for their high voltage sensitivity and fast response kinetics. Here we review the essential aspects of microbial rhodopsin photocycles that are critical to understanding the mechanisms of voltage sensitivity in these proteins and link them to insights from efforts to create faster, brighter and more sensitive microbial rhodopsin-based GEVIs.

Detection of Membrane Potential-Dependent Rhodopsin Fluorescence Using Low-Intensity Light Emitting Diode for Long-Term Imaging

Microbial rhodopsin is a family of photoreceptive membrane proteins that commonly consist of a seven-transmembrane domain and a derivative of vitamin-A, retinal, as a chromophore. In 2011, archaeorhodopsin-3 (AR3) was shown to exhibit voltage-dependent fluorescence changes in mammalian cells. Since then, AR3 and its variants have been used as genetically encoded voltage indicators, in which mostly intense laser stimulation (1-1000 W/cm²) is used for the detection of dim fluorescence of rhodopsin, leading to high spatiotemporal resolution. However, intense laser stimulation potentially causes serious cell damage, particularly during long-term imaging over minutes. In this study, we present the successful detection of voltage-sensitive fluorescence of AR3 and its high fluorescence mutant Archon1 in a variety of mammalian cell lines using low-intensity light emitting diode stimulation (0.15 W/cm²) with long exposure time (500 ms). The detection system enables real-time imaging of drug-induced slow changes in voltage within the cells for minutes harmlessly and without fluorescence bleaching. Therefore, we demonstrate a method to quantitatively understand the dynamics of slow changes in membrane voltage on long time scales.

Automated QM/MM Screening of Rhodopsin Variants with Enhanced Fluorescence

We present a computational protocol for the fast and automated screening of excited-state hybrid quantum mechanics/molecular mechanics (QM/MM) models of rhodopsins to be used as fluorescent probes based on the automatic rhodopsin modeling protocol (a-ARM). Such "a-ARM fluorescence screening protocol" is implemented through a general Python-based driver, PyARM, that is also proposed here. The implementation and performance of the protocol are benchmarked using different sets of rhodopsin variants whose absorption and, more relevantly, emission spectra have been experimentally measured. We show that, despite important limitations that make unsafe to use it as a black-box tool, the protocol reproduces the observed trends in fluorescence and it is capable of selecting novel potentially fluorescent rhodopsins. We also show that the protocol can be used in mechanistic investigations to discern fluorescence enhancement effects associated with a near degeneracy of the S₁/S₂ states or, alternatively, with a barrier generated via coupling of the S₀/S₁ wave functions.

Rhodopsins: An Excitingly Versatile Protein Species for Research, Development and Creative Engineering

The first member and eponym of the rhodopsin family was identified in the 1930s as the visual pigment of the rod photoreceptor cell in the animal retina. It was found to be a membrane protein, owing its photosensitivity to the presence of a covalently bound chromophoric group. This group, derived from vitamin A, was appropriately dubbed retinal. In the 1970s a microbial counterpart of this species was discovered in an archaeon, being a membrane protein also harbouring retinal as a chromophore, and named bacteriorhodopsin. Since their discovery a photogenic panorama unfolded, where up to date new members and subspecies with a variety of light-driven functionality have been added to this family. The animal branch, meanwhile categorized as type-2 rhodopsins, turned out to form a large subclass in the superfamily of G protein-coupled receptors and are essential to multiple elements of light-dependent animal sensory physiology. The microbial branch, the type-1 rhodopsins, largely function as light-driven ion pumps or channels, but also contain sensory-active and enzyme-sustaining subspecies. In this review we will follow the development of this exciting membrane protein panorama in a representative number of highlights and will present a prospect of their extraordinary future potential.

Far-Red Absorbing Rhodopsins, Insights From Heterodimeric Rhodopsin-Cyclases

The recently discovered Rhodopsin-cyclases from Chytridiomycota fungi show completely unexpected properties for microbial rhodopsins. These photoreceptors function exclusively as heterodimers, with the two subunits that have very different retinal chromophores. Among them is the bimodal photoswitchable Neorhodopsin (NeoR), which exhibits a near-infrared absorbing, highly fluorescent state. These are features that have never been described for any retinal photoreceptor. Here these properties are discussed in the context of color-tuning approaches of retinal chromophores, which have been extensively studied since the discovery of the first microbial rhodopsin, bacteriorhodopsin, in 1971 (Oesterhelt et al., Nature New Biology, 1971, 233 (39), 149–152). Further a brief review about the concept of heterodimerization is given, which is widely present in class III cyclases but is unknown for rhodopsins. NIR-sensitive retinal chromophores have greatly expanded our understanding of the spectral range of natural retinal photoreceptors and provide a novel perspective for the development of optogenetic tools.