Literature DB >> 29155709

A Computational Method to Quantify Fly Circadian Activity.

Andrey Lazopulo1, Sheyum Syed2.   

Abstract

In most animals and plants, circadian clocks orchestrate behavioral and molecular processes and synchronize them to the daily light-dark cycle. Fundamental mechanisms that underlie this temporal control are widely studied using the fruit fly Drosophila melanogaster as a model organism. In flies, the clock is typically studied by analyzing multiday locomotor recording. Such a recording shows a complex bimodal pattern with two peaks of activity: a morning peak that happens around dawn, and an evening peak that happens around dusk. These two peaks together form a waveform that is very different from sinusoidal oscillations observed in clock genes, suggesting that mechanisms in addition to the clock have profound effects in producing the observed patterns in behavioral data. Here we provide instructions on using a recently developed computational method that mathematically describes temporal patterns in fly activity. The method fits activity data with a model waveform that consists of four exponential terms and nine independent parameters that fully describe the shape and size of the morning and evening peaks of activity. The extracted parameters can help elucidate the kinetic mechanisms of substrates that underlie the commonly observed bimodal activity patterns in fly locomotor rhythms.

Entities:  

Mesh:

Year:  2017        PMID: 29155709      PMCID: PMC5755250          DOI: 10.3791/55977

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  10 in total

Review 1.  Clocks not winding down: unravelling circadian networks.

Authors:  Eric E Zhang; Steve A Kay
Journal:  Nat Rev Mol Cell Biol       Date:  2010-11       Impact factor: 94.444

2.  Quantitative analysis of Drosophila period gene transcription in living animals.

Authors:  J D Plautz; M Straume; R Stanewsky; C F Jamison; C Brandes; H B Dowse; J C Hall; S A Kay
Journal:  J Biol Rhythms       Date:  1997-06       Impact factor: 3.182

3.  A Neural Network Underlying Circadian Entrainment and Photoperiodic Adjustment of Sleep and Activity in Drosophila.

Authors:  Matthias Schlichting; Pamela Menegazzi; Katharine R Lelito; Zepeng Yao; Edgar Buhl; Elena Dalla Benetta; Andrew Bahle; Jennifer Denike; James John Hodge; Charlotte Helfrich-Förster; Orie Thomas Shafer
Journal:  J Neurosci       Date:  2016-08-31       Impact factor: 6.167

4.  Irreversible binding kinetics of neuropeptide Y ligands to Y2 but not to Y1 and Y5 receptors.

Authors:  Frank M Dautzenberg; Shiva Neysari
Journal:  Pharmacology       Date:  2005-05-20       Impact factor: 2.547

5.  The molecular ticks of the Drosophila circadian clock.

Authors:  Ozgur Tataroglu; Patrick Emery
Journal:  Curr Opin Insect Sci       Date:  2015-02-01       Impact factor: 5.186

6.  Differential control of morning and evening components in the activity rhythm of Drosophila melanogaster--sex-specific differences suggest a different quality of activity.

Authors:  C Helfrich-Förster
Journal:  J Biol Rhythms       Date:  2000-04       Impact factor: 3.182

7.  Assaying locomotor activity to study circadian rhythms and sleep parameters in Drosophila.

Authors:  Joanna C Chiu; Kwang Huei Low; Douglas H Pike; Evrim Yildirim; Isaac Edery
Journal:  J Vis Exp       Date:  2010-09-28       Impact factor: 1.355

8.  High-resolution positional tracking for long-term analysis of Drosophila sleep and locomotion using the "tracker" program.

Authors:  Nathan C Donelson; Nathan Donelson; Eugene Z Kim; Justin B Slawson; Christopher G Vecsey; Robert Huber; Leslie C Griffith
Journal:  PLoS One       Date:  2012-05-15       Impact factor: 3.240

9.  Circadian neuron feedback controls the Drosophila sleep--activity profile.

Authors:  Fang Guo; Junwei Yu; Hyung Jae Jung; Katharine C Abruzzi; Weifei Luo; Leslie C Griffith; Michael Rosbash
Journal:  Nature       Date:  2016-08-01       Impact factor: 49.962

10.  A mathematical model provides mechanistic links to temporal patterns in Drosophila daily activity.

Authors:  Andrey Lazopulo; Sheyum Syed
Journal:  BMC Neurosci       Date:  2016-04-18       Impact factor: 3.288

  10 in total
  1 in total

1.  Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier.

Authors:  Bing Qiao; Chiyuan Li; Victoria W Allen; Mimi Shirasu-Hiza; Sheyum Syed
Journal:  Elife       Date:  2018-02-27       Impact factor: 8.140

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.