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The PEDtracker: An Automatic Staging Approach for Drosophila melanogaster Larvae

The post-embryonal development of arthropod species, including crustaceans and insects, is characterized by ecdysis or molting. This process defines growth stages and is controlled by a conserved neuroendocrine system. Each molting event is divided in several critical time points, such as pre-molt,...

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Autores principales: Schumann, Isabell, Triphan, Tilman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772430/
https://www.ncbi.nlm.nih.gov/pubmed/33390912
http://dx.doi.org/10.3389/fnbeh.2020.612313
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author Schumann, Isabell
Triphan, Tilman
author_facet Schumann, Isabell
Triphan, Tilman
author_sort Schumann, Isabell
collection PubMed
description The post-embryonal development of arthropod species, including crustaceans and insects, is characterized by ecdysis or molting. This process defines growth stages and is controlled by a conserved neuroendocrine system. Each molting event is divided in several critical time points, such as pre-molt, molt, and post-molt, and leaves the animals in a temporarily highly vulnerable state while their cuticle is re-hardening. The molting events occur in an immediate ecdysis sequence within a specific time window during the development. Each sub-stage takes only a short amount of time, which is generally in the order of minutes. To find these relatively short behavioral events, one needs to follow the entire post-embryonal development over several days. As the manual detection of the ecdysis sequence is time consuming and error prone, we designed a monitoring system to facilitate the continuous observation of the post-embryonal development of the fruit fly Drosophila melanogaster. Under constant environmental conditions we are able to observe the life cycle from the embryonic state to the adult, which takes about 10 days in this species. Specific processing algorithms developed and implemented in Fiji and R allow us to determine unique behavioral events on an individual level—including egg hatching, ecdysis and pupation. In addition, we measured growth rates and activity patterns for individual larvae. Our newly created RPackage PEDtracker can predict critical developmental events and thus offers the possibility to perform automated screens that identify changes in various aspects of larval development. In conclusion, the PEDtracker system presented in this study represents the basis for automated real-time staging and analysis not only for the arthropod development.
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spelling pubmed-77724302020-12-31 The PEDtracker: An Automatic Staging Approach for Drosophila melanogaster Larvae Schumann, Isabell Triphan, Tilman Front Behav Neurosci Behavioral Neuroscience The post-embryonal development of arthropod species, including crustaceans and insects, is characterized by ecdysis or molting. This process defines growth stages and is controlled by a conserved neuroendocrine system. Each molting event is divided in several critical time points, such as pre-molt, molt, and post-molt, and leaves the animals in a temporarily highly vulnerable state while their cuticle is re-hardening. The molting events occur in an immediate ecdysis sequence within a specific time window during the development. Each sub-stage takes only a short amount of time, which is generally in the order of minutes. To find these relatively short behavioral events, one needs to follow the entire post-embryonal development over several days. As the manual detection of the ecdysis sequence is time consuming and error prone, we designed a monitoring system to facilitate the continuous observation of the post-embryonal development of the fruit fly Drosophila melanogaster. Under constant environmental conditions we are able to observe the life cycle from the embryonic state to the adult, which takes about 10 days in this species. Specific processing algorithms developed and implemented in Fiji and R allow us to determine unique behavioral events on an individual level—including egg hatching, ecdysis and pupation. In addition, we measured growth rates and activity patterns for individual larvae. Our newly created RPackage PEDtracker can predict critical developmental events and thus offers the possibility to perform automated screens that identify changes in various aspects of larval development. In conclusion, the PEDtracker system presented in this study represents the basis for automated real-time staging and analysis not only for the arthropod development. Frontiers Media S.A. 2020-12-16 /pmc/articles/PMC7772430/ /pubmed/33390912 http://dx.doi.org/10.3389/fnbeh.2020.612313 Text en Copyright © 2020 Schumann and Triphan. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Behavioral Neuroscience
Schumann, Isabell
Triphan, Tilman
The PEDtracker: An Automatic Staging Approach for Drosophila melanogaster Larvae
title The PEDtracker: An Automatic Staging Approach for Drosophila melanogaster Larvae
title_full The PEDtracker: An Automatic Staging Approach for Drosophila melanogaster Larvae
title_fullStr The PEDtracker: An Automatic Staging Approach for Drosophila melanogaster Larvae
title_full_unstemmed The PEDtracker: An Automatic Staging Approach for Drosophila melanogaster Larvae
title_short The PEDtracker: An Automatic Staging Approach for Drosophila melanogaster Larvae
title_sort pedtracker: an automatic staging approach for drosophila melanogaster larvae
topic Behavioral Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772430/
https://www.ncbi.nlm.nih.gov/pubmed/33390912
http://dx.doi.org/10.3389/fnbeh.2020.612313
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