Functional network inference of the suprachiasmatic nucleus

Abel, John H.; Meeker, Kirsten; Granados-Fuentes, Daniel; St. John, Peter C.; Wang, Thomas J.; Bales, Benjamin B.; Doyle, III, Francis J.; Herzog, Erik D.; Petzold, Linda R.

doi:10.1073/pnas.1521178113

Title: Functional network inference of the suprachiasmatic nucleus

Journal Article · Mon Apr 04 00:00:00 EDT 2016 · Proceedings of the National Academy of Sciences of the United States of America

DOI:https://doi.org/10.1073/pnas.1521178113· OSTI ID:1249409

Abel, John H. ^[1]; Meeker, Kirsten ^[2]; Granados-Fuentes, Daniel ^[3]; St. John, Peter C. ^[4]; Wang, Thomas J. ^[3]; Bales, Benjamin B. ^[2]; Doyle, III, Francis J. ^[1]; Herzog, Erik D. ^[3]; Petzold, Linda R. ^[2]

Univ. of California, Santa Barbara, CA (United States); Harvard Univ., Cambridge, MA (United States)
Univ. of California, Santa Barbara, CA (United States)
Washington Univ., St. Louis, MO (United States)
Univ. of California, Santa Barbara, CA (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)

In the mammalian suprachiasmatic nucleus (SCN), noisy cellular oscillators communicate within a neuronal network to generate precise system-wide circadian rhythms. Although the intracellular genetic oscillator and intercellular biochemical coupling mechanisms have been examined previously, the network topology driving synchronization of the SCN has not been elucidated. This network has been particularly challenging to probe, due to its oscillatory components and slow coupling timescale. In this work, we investigated the SCN network at a single-cell resolution through a chemically induced desynchronization. We then inferred functional connections in the SCN by applying the maximal information coefficient statistic to bioluminescence reporter data from individual neurons while they resynchronized their circadian cycling. Our results demonstrate that the functional network of circadian cells associated with resynchronization has small-world characteristics, with a node degree distribution that is exponential. We show that hubs of this small-world network are preferentially located in the central SCN, with sparsely connected shells surrounding these cores. Lastly, we used two computational models of circadian neurons to validate our predictions of network structure.

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Research Organization:: National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Organization:: National Institutes of Health (NIH); US Army Research Office (ARO)

Grant/Contract Number:: AC36-08GO28308; 1R01GM096873-01; W911NF-09-0001

OSTI ID:: 1249409

Report Number(s):: NREL/JA-2700-66276

Journal Information:: Proceedings of the National Academy of Sciences of the United States of America, Vol. 113, Issue 16; Related Information: Proceedings of the National Academy of Sciences of the United States of America; ISSN 0027-8424

Publisher:: National Academy of SciencesCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 40 works

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