The recently discovered rhodopsin family of heliorhodopsins (HeRs) is abundant in diverse microbial environments. So far, the functional and biological roles of HeRs remain unknown. To tackle this issue, we combined experimental and computational screens to gain some novel insights. Here, 10 readily expressed HeR genes were found using functional metagenomics on samples from two freshwater environments. These HeRs originated from diverse prokaryotic groups: Actinobacteria, Chloroflexi and Archaea. Heterologously expressed HeRs absorbed light in the green and yellow wavelengths (543-562 nm) and their photocycles exhibited diverse kinetic characteristics. To approach the physiological function of the HeRs, we used our environmental clones along with thousands of microbial genomes to analyze genes neighbouring HeRs. The strongest association was found with the DegV family involved in activation of fatty acids, which allowed us to hypothesize that HeRs might be involved in light-induced membrane lipid modifications.

Microbial rhodopsins are photoreceptive membrane proteins, which are used as molecular tools in optogenetics. Here, a machine learning (ML)-based experimental design method is introduced for screening rhodopsins that are likely to be red-shifted from representative rhodopsins in the same subfamily. Among 3,022 ion-pumping rhodopsins that were suggested by a protein BLAST search in several protein databases, the ML-based method selected 65 candidate rhodopsins. The wavelengths of 39 of them were able to be experimentally determined by expressing proteins with the Escherichia coli system, and 32 (82%, p = 7.025 × 10−5) actually showed red-shift gains. In addition, four showed red-shift gains >20 nm, and two were found to have desirable ion-transporting properties, indicating that they would be potentially useful in optogenetics. These findings suggest that data-driven ML-based approaches play effective roles in the experimental design of rhodopsin and other photobiological studies. (141/150 words).

Rhodopsins are widespread in microbes residing in diverse aquatic environments across the globe. Recently, a new unusual rhodopsin family, the heliorhodopsins (HeRs), was discovered, distributed among diverse bacteria, archaea, eukarya and even viruses. Here, using functional metagenomics on samples from Lake Ha'Hula and Ein Afek reserve, we found and characterized ten HeRs representing divergent members of the family. The expressed HeRs absorb light in the green and yellow wavelengths and originate from Actinobacteria, Chloroflexi and Archaea. The photocycle of the HeR from Chloroflexi revealed a low accumulation of the M-intermediate that we connect to the lack of two conserved histidine residues in transmembrane helices 1 and 2 in this protein. Another of HeR, from Actinobacteria, exhibited an unusually fast photocycle (166 ms, 5 times faster than HeR-48C12). To further explore the still unresolved question of the HeR function, we performed an analysis of protein families among genes neighboring HeRs, in our clones and thousands of other microbes. This analysis revealed a putative connection between HeRs and genes involved in oxidative stress. At the same time, very few protein families were found to distinguish genes surrounding prokaryotic HeRs from those surrounding rhodopsin pumps. The strongest association was found with the DegV family involved in activation of fatty acids and uncharacterized family DUF2177, which allowed us to hypothesize that HeRs are involved in membrane lipid remodeling. This work further establishes functional metagenomics as a simple and fruitful method of screening for new rhodopsins.

31Microbial rhodopsins are photoreceptive membrane proteins utilized as molecular tools in 32 optogenetics. In this paper, a machine learning (ML)-based model was constructed to 33 approximate the relationship between amino acid sequences and absorption wavelengths using 34 ∼800 rhodopsins with known absorption wavelengths. This ML-based model was specifically 35 designed for screening rhodopsins that are red-shifted from representative rhodopsins in the 36 same subfamily. Among 5,558 candidate rhodopsins suggested by a protein BLAST search of 37 several protein databases, 40 were selected by the ML-based model. The wavelengths of these 38 40 selected candidates were experimentally investigated, and 32 (80%) showed red-shift gains. 39 In addition, four showed red-shift gains > 20 nm, and two were found to have desirable ion-40 transporting properties, indicating that they were potentially useful in optogenetics. These 41 findings suggest that an ML-based model can reduce the cost for exploring new functional 42 proteins. 43 44 48 (Fig. 1a). The first microbial rhodopsin, bacteriorhodopsin (BR), was discovered in the plasma 49 membrane of the halophilic archaea Halobacterium salinarum (formerly called H. halobium) 2 . 50 BR forms a purple-coloured patch in the plasma membrane called purple membrane, which 51 outwardly transports H + using sunlight energy 3 . After the discovery of BR, various types of 52 microbial rhodopsins were reported from diverse microorganisms, and recent progress in 53 genome sequencing techniques has uncovered several thousand microbial rhodopsin genes 1,4-54 6 . These microbial rhodopsins show various types of biological functions upon light absorption, 55 leading to all-trans-to-13-cis retinal isomerization. Among these, ion transporters, including 56 light-driven ion pumps and light-gated ion channels, are the most ubiquitous (Fig. 1b). Ion-57 transporting rhodopsins can transport several types of cations and anions, including H + , Na + , 58 K + , halides (Cl -, Br -, I -), NO -, and SO4 2-1,7-9 . The molecular mechanisms of ion-transporting 59 rhodopsins have been detailed in numerous biophysical, structural, and theoretical studies 1 . 60 In recent years, many ion-transporting rhodopsins have been used as molecular tools in 61 optogenetics to control the activity of animal neurons optically in vivo by heterologous 62 expression 10 , and optogenetics has revealed various new insights regarding the neural network 63 relevant to memory, movement, and emotional behaviour 11-14 . However, strong light scattering 64 by biological tissues and the cellular toxicity of shorter wavelength light make precise optical 65 control difficult. To circumvent this difficulty, new molecular optogenetics tools based on red-66shifted rhodopsins that can be controlled by weak scattering and low toxicity longer-67 wavelength light are urgently needed. Therefore, many approaches to obtain red-shifted 68 rhodopsins, including gene screening, amino acid mutation based on biophysical and structural 69 ...