Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels

Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to...

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Main Author: Nicolas Lessios
Format: Article
Language:English
Published: PeerJ Inc. 2017-07-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/3595.pdf
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spelling doaj-755d06eeca8b4066985583eb75726e9f2020-11-24T21:04:40ZengPeerJ Inc.PeerJ2167-83592017-07-015e359510.7717/peerj.3595Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levelsNicolas Lessios0School of Life Sciences, Arizona State University, Tempe, AZ, USAUnderstanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike’s information criterion (AICc) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis, the branchiopod water flea, Daphnia magna, normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus, which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei. The modeling approach presented here will be useful in selecting the most likely alternative hypotheses of opsin-based spectral photoreceptor classes, using relative opsin expression and extracellular electroretinography.https://peerj.com/articles/3595.pdfColor visionElectrophysiologyVisual systemSpectral sensitivityPhotoreceptorOpsin expression
collection DOAJ
language English
format Article
sources DOAJ
author Nicolas Lessios
spellingShingle Nicolas Lessios
Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
PeerJ
Color vision
Electrophysiology
Visual system
Spectral sensitivity
Photoreceptor
Opsin expression
author_facet Nicolas Lessios
author_sort Nicolas Lessios
title Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title_short Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title_full Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title_fullStr Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title_full_unstemmed Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title_sort using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
publisher PeerJ Inc.
series PeerJ
issn 2167-8359
publishDate 2017-07-01
description Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike’s information criterion (AICc) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis, the branchiopod water flea, Daphnia magna, normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus, which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei. The modeling approach presented here will be useful in selecting the most likely alternative hypotheses of opsin-based spectral photoreceptor classes, using relative opsin expression and extracellular electroretinography.
topic Color vision
Electrophysiology
Visual system
Spectral sensitivity
Photoreceptor
Opsin expression
url https://peerj.com/articles/3595.pdf
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