Drosophila PSI controls circadian period and the phase of circadian behavior under temperature cycle via tim splicing

  1. Lauren Foley
  2. Jinli Ling
  3. Radhika Joshi
  4. Naveh Evantal
  5. Sebastian Kadener
  6. Patrick Emery  Is a corresponding author
  1. University of Massachusetts Medical School, United States
  2. The Hebrew University of Jerusalem, Israel
  3. Brandeis University, United States

Abstract

The Drosophila circadian pacemaker consists of transcriptional feedback loops subjected to post-transcriptional and post-translational regulation. While post-translational regulatory mechanisms have been studied in detail, much less is known about circadian post-transcriptional control. Thus, we targeted 364 RNA binding and RNA associated proteins with RNA interference. Among the 43 hits we identified was the alternative splicing regulator P-element somatic inhibitor (PSI). PSI regulates the thermosensitive alternative splicing of timeless (tim), promoting splicing events favored at warm temperature over those increased at cold temperature. Psi downregulation shortens the period of circadian rhythms and advances the phase of circadian behavior under temperature cycle. Interestingly, both phenotypes were suppressed in flies that could produce TIM proteins only from a transgene that cannot form the thermosensitive splicing isoforms. Therefore, we conclude that PSI regulates the period of Drosophila circadian rhythms and circadian behavior phase during temperature cycling through its modulation of the tim splicing pattern.

Data availability

All source data are included in this submission

The following previously published data sets were used

Article and author information

Author details

  1. Lauren Foley

    Department of Neurobiology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jinli Ling

    Department of Neurobiology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Radhika Joshi

    Department of Neurobiology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Naveh Evantal

    Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
    Competing interests
    The authors declare that no competing interests exist.
  5. Sebastian Kadener

    Biology Department, Brandeis University, Waltham, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0080-5987
  6. Patrick Emery

    Department of Neurobiology, University of Massachusetts Medical School, Worcester, United States
    For correspondence
    Patrick.Emery@umassmed.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5176-6565

Funding

National Institute of General Medical Sciences (1R35GM118087)

  • Patrick Emery

National Institute of General Medical Sciences (1R01GM125859)

  • Sebastian Kadener

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2019, Foley et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,614
    views
  • 253
    downloads
  • 25
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Lauren Foley
  2. Jinli Ling
  3. Radhika Joshi
  4. Naveh Evantal
  5. Sebastian Kadener
  6. Patrick Emery
(2019)
Drosophila PSI controls circadian period and the phase of circadian behavior under temperature cycle via tim splicing
eLife 8:e50063.
https://doi.org/10.7554/eLife.50063

Share this article

https://doi.org/10.7554/eLife.50063

Further reading

    1. Medicine
    2. Neuroscience
    Sophie Leclercq, Hany Ahmed ... Nathalie Delzenne
    Research Article

    Background:

    Alcohol use disorder (AUD) is a global health problem with limited therapeutic options. The biochemical mechanisms that lead to this disorder are not yet fully understood, and in this respect, metabolomics represents a promising approach to decipher metabolic events related to AUD. The plasma metabolome contains a plethora of bioactive molecules that reflects the functional changes in host metabolism but also the impact of the gut microbiome and nutritional habits.

    Methods:

    In this study, we investigated the impact of severe AUD (sAUD), and of a 3-week period of alcohol abstinence, on the blood metabolome (non-targeted LC-MS metabolomics analysis) in 96 sAUD patients hospitalized for alcohol withdrawal.

    Results:

    We found that the plasma levels of different lipids ((lyso)phosphatidylcholines, long-chain fatty acids), short-chain fatty acids (i.e. 3-hydroxyvaleric acid) and bile acids were altered in sAUD patients. In addition, several microbial metabolites, including indole-3-propionic acid, p-cresol sulfate, hippuric acid, pyrocatechol sulfate, and metabolites belonging to xanthine class (paraxanthine, theobromine and theophylline) were sensitive to alcohol exposure and alcohol withdrawal. 3-Hydroxyvaleric acid, caffeine metabolites (theobromine, paraxanthine, and theophylline) and microbial metabolites (hippuric acid and pyrocatechol sulfate) were correlated with anxiety, depression and alcohol craving. Metabolomics analysis in postmortem samples of frontal cortex and cerebrospinal fluid of those consuming a high level of alcohol revealed that those metabolites can be found also in brain tissue.

    Conclusions:

    Our data allow the identification of neuroactive metabolites, from interactions between food components and microbiota, which may represent new targets arising in the management of neuropsychiatric diseases such as sAUD.

    Funding:

    Gut2Behave project was initiated from ERA-NET NEURON network (Joint Transnational Call 2019) and was financed by Academy of Finland, French National Research Agency (ANR-19-NEUR-0003-03) and the Fonds de la Recherche Scientifique (FRS-FNRS; PINT-MULTI R.8013.19, Belgium). Metabolomics analysis of the TSDS samples was supported by grant from the Finnish Foundation for Alcohol Studies.

    1. Neuroscience
    Masahiro Takigawa, Marta Huelin Gorriz ... Daniel Bendor
    Research Article

    During rest and sleep, memory traces replay in the brain. The dialogue between brain regions during replay is thought to stabilize labile memory traces for long-term storage. However, because replay is an internally-driven, spontaneous phenomenon, it does not have a ground truth - an external reference that can validate whether a memory has truly been replayed. Instead, replay detection is based on the similarity between the sequential neural activity comprising the replay event and the corresponding template of neural activity generated during active locomotion. If the statistical likelihood of observing such a match by chance is sufficiently low, the candidate replay event is inferred to be replaying that specific memory. However, without the ability to evaluate whether replay detection methods are successfully detecting true events and correctly rejecting non-events, the evaluation and comparison of different replay methods is challenging. To circumvent this problem, we present a new framework for evaluating replay, tested using hippocampal neural recordings from rats exploring two novel linear tracks. Using this two-track paradigm, our framework selects replay events based on their temporal fidelity (sequence-based detection), and evaluates the detection performance using each event's track discriminability, where sequenceless decoding across both tracks is used to quantify whether the track replaying is also the most likely track being reactivated.