Sleep is not just for the brain: transcriptional responses to sleep in peripheral tissues

Background: Many have assumed that the primary function of sleep is for the brain. We evaluated the molecular consequences of sleep and sleep deprivation outside the brain, in heart and lung. Using microarrays we compared gene expression in tissue from sleeping and sleep deprived mice euthanized at the same diurnal times.Results: in each tissue, nearly two thousand genes demonstrated statistically significant differential expression as a function of sleep/wake behavioral state. To mitigate the influence of an artificial deprivation protocol, we identified a subset of these transcripts as specifically sleep-enhanced or sleep-repressed by requiring that their expression also change over the course of unperturbed sleep. 3% and 6% of the assayed transcripts showed sleep specific changes in the lung and heart respectively. Sleep specific transcripts in these tissues demonstrated highly significant overlap and shared temporal dynamics. Markers of cellular stress and the unfolded protein response were reduced during sleep in both tissues. These results mirror previous findings in brain. Sleep-enhanced pathways reflected the unique metabolic functions of each tissue. Transcripts related to carbohydrate and sulfur metabolic processes were enhanced by sleep in the lung, and collectively favor buffering from oxidative stress. DNA repair and protein metabolism annotations were significantly enriched among the sleep-enhanced transcripts in the heart. Our results also suggest that sleep may provide a Zeitgeber, or synchronizing cue, in the lung as a large cluster of transcripts demonstrated systematic changes in inter-animal variability as a function of both sleep duration and circadian time.Conclusion: Our data support the notion that the molecular consequences of sleep/wake behavioral state extend beyond the brain to include peripheral tissues. Sleep state induces a highly overlapping response in both heart and lung. We conclude that sleep enhances organ specific molecular functions and that it has a ubiquitous role in reducing cellular metabolic stress in both brain and peripheral tissues. Finally, our data suggest a novel role for sleep in synchronizing transcription in peripheral tissues.Intramural Research Program of the National Institutes of Health, National Institute of Environmental Health SciencesNational Institutes of HealthAmerican Sleep Medicine FoundationNational Heart Lung Blood InstituteUniv Penn, Perelman Sch Med, Div Sleep Med, Philadelphia, PA 19104 USAUniv Penn, Perelman Sch Med, Ctr Sleep & Circadian Neurobiol, Philadelphia, PA 19104 USAChildrens Hosp Philadelphia, Ctr Appl Genom, Philadelphia, PA 19104 USAUniversidade Federal de São Paulo UNIFESP, São Paulo, BrazilNIEHS, US Dept HHS, Biostat Branch, NIH, Res Triangle Pk, NC 27709 USAUniversidade Federal de São Paulo UNIFESP, São Paulo, BrazilNational Institutes of Health: AG-17628National Heart Lung Blood Institute: HL090021: K12Web of Scienc

Balancing Robustness against the Dangers of Multiple Attractors in a Hopfield-Type Model of Biological Attractors

Background: Many chronic human diseases are of unclear origin, and persist long beyond any known insult or instigating factor. These diseases may represent a structurally normal biologic network that has become trapped within the basin of an abnormal attractor. Methodology/Principal Findings: We used the Hopfield net as the archetypical example of a dynamic biological network. By progressively removing the links of fully connected Hopfield nets, we found that a designated attractor of the nets could still be supported until only slightly more than 1 link per node remained. As the number of links approached this minimum value, the rate of convergence to this attractor from an arbitrary starting state increased dramatically. Furthermore, with more than about twice the minimum of links, the net became increasingly able to support a second attractor. Conclusions/Significance: We speculate that homeostatic biological networks may have evolved to assume a degree of connectivity that balances robustness and agility against the dangers of becoming trapped in an abnormal attractor

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding ‘big data’ that is conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Guidelines For Genome-Scale Analysis Of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them