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New ways from photon to behaviour: Finding new phototransduction cascades in fan worms

Periodic Reporting for period 1 - PhoToBe (New ways from photon to behaviour: Finding new phototransduction cascades in fan worms)

Reporting period: 2020-01-01 to 2021-12-31

Seeing is essential for us, and so we wonder how easily it evolves? Its fundamental unit is the photoreceptor cell. Such a cell uses a molecular transduction system that detects photons and translates them into a cellular signal, which then the animal uses for behavior. Even though all animals share the molecular and cellular origin, they evolved a diversity of eyes independently. However, comparative vision research has only focused on a few taxa such as vertebrates, arthropods, and cephalopods. Therefore, our knowledge of eye evolution is limited. Fanworms evolved relatively recently eyes on their radioles, which are tentacles that form their fans. These radioles are used for respiration and collecting food particles. Fanforms are sessile and live in tubes. When their eyes see a predator, the worm quickly retreats into its tube to protect the fan. The eyes in different fanworm species evolved independently and thus probably also their phototransduction cascades. Therefore, fanworms are an ideal new model system to study eye evolution and the possible phototransduction cascades.

The overall objectives of the project were to determine all the phototransduction components in the eyes of two fan worm species: Spirobranchus corniculatus and Acromegalomma vesiculosum. The first step was to find putative opsin and G-alpha protein sequences in existing transcriptomes and identify those by phylogenetic reconstruction. The second step was to check whether mRNA of those sequences were expressed in the eyes of the focal species by in situ hybridization, and more importantly to check whether the opsin and the G-alpha protein mRNA were expressed in the same cell as this is required for the encoded proteins to interact with each other so that they can be part of the phototransduction cascade. The third step was to establish the interaction via electrophysiology with knock-down and pharmacology. Knowing the identity of the opsin and the G-protein narrows down significantly the possibilities of molecules that could be further downstream in the phototransduction cascade. These potential downstream molecules would be checked with the same methods whether they are indeed in the phototransduction cascade.
When the Covid-19 pandemic came and the lockdown closed the lab, I was ready to start the lab work. I had all the worms I needed, however because of the lockdown the worms died, and I could not get new ones because of broken delivery chains. Therefore, I refocused and expanded on the Bioinformatics parts of the project to complete these parts and publish the results. I am very pleased that I could achieve this, despite the difficulties the pandemic posed.

I improved a previously existing method called phylogenetically informed annotation (PIA). This version of PIA is already publicly available ( and will be mentioned in an upcoming and already submitted paper. I used PIA to extract from the existing fanworm transcriptomes putative phototransduction components.

To identify these putative phototransduction components, I built an automatic pipeline for reconstructing phylogenies. This pipeline reconstructs large scale phylogenies de novo for any protein. With it, I reconstructed phylogenies for opsins and G-alpha-proteins. I found opsins that lost the lysine in the seventh transmembrane domain that is used to covalently bind retinal. This bound retinal is required to make opsins light sensitive and thus turn them into photoreceptors. This result further supports the existence of non-photoreceptive functions for some opsins.

I have already submitted a paper about the opsins that lost the chromophore-binding lysine. Additionally, I will publish a paper about the full opsin phylogeny and another paper about the G-alpha-protein phylogeny.
The automatic pipeline allows me and other researchers to reconstruct large scale phylogenies de novo with ease. Since it collects the sequences needed automatically, biases by manual sequence collection are minimized and since most steps are automatic, it accelerates phylogenetic reconstruction. This is important for large scale phylogenies. I can easily use it not only for an opsin phylogeny but also for a G-alpha protein phylogeny, and more phylogenies will follow.

With the pipeline, I did not only reconstruct the largest opsin phylogeny up to date, but I also found opsins that lost the lysine for binding retinal. Something that would have been difficult with a limited set of opsin sequences.

This result changes our traditional view of opsins, which requires opsins to have such a lysine. According to this view, if this lysine is lost, the opsin would become functionless and thus would be eliminated by evolution. However, since clades of opsins exist that have lost that lysine, our definition of opsins must be updated and should only be based on phylogeny. This puts the spotlight on opsin functions beyond light reception and will spark interest in research focusing on those non-light-related functions.