Diet and Feeding Pattern Affect the Diurnal Dynamics of the Gut Microbiome

SummaryThe gut microbiome and daily feeding/fasting cycle influence host metabolism and contribute to obesity and metabolic diseases. However, fundamental characteristics of this relationship between the feeding/fasting cycle and the gut microbiome are unknown. Our studies show that the gut microbiome is highly dynamic, exhibiting daily cyclical fluctuations in composition. Diet-induced obesity dampens the daily feeding/fasting rhythm and diminishes many of these cyclical fluctuations. Time-restricted feeding (TRF), in which feeding is consolidated to the nocturnal phase, partially restores these cyclical fluctuations. Furthermore, TRF, which protects against obesity and metabolic diseases, affects bacteria shown to influence host metabolism. Cyclical changes in the gut microbiome from feeding/fasting rhythms contribute to the diversity of gut microflora and likely represent a mechanism by which the gut microbiome affects host metabolism. Thus, feeding pattern and time of harvest, in addition to diet, are important parameters when assessing the microbiome’s contribution to host metabolism

Circadian Oscillations of Protein-Coding and Regulatory RNAs in a Highly Dynamic Mammalian Liver Epigenome

SummaryIn the mouse liver, circadian transcriptional rhythms are necessary for metabolic homeostasis. Whether dynamic epigenomic modifications are associated with transcript oscillations has not been systematically investigated. We found that several antisense RNA, lincRNA, and microRNA transcripts also showed circadian oscillations in adult mouse livers. Robust transcript oscillations often correlated with rhythmic histone modifications in promoters, gene bodies, or enhancers, although promoter DNA methylation levels were relatively stable. Such integrative analyses identified oscillating expression of an antisense transcript (asPer2) to the gene encoding the circadian oscillator component Per2. Robust transcript oscillations often accompanied rhythms in multiple histone modifications and recruitment of multiple chromatin-associated clock components. Coupling of cycling histone modifications with nearby oscillating transcripts thus established a temporal relationship between enhancers, genes, and transcripts on a genome-wide scale in a mammalian liver. The results offer a framework for understanding the dynamics of metabolism, circadian clock, and chromatin modifications involved in metabolic homeostasis

Genome-Wide Expression Analysis in Drosophila Reveals Genes Controlling Circadian Behavior

In Drosophila, a number of key processes such as emergence from the pupal case, locomotor activity, feeding, olfaction, and aspects of mating behavior are under circadian regulation. Although we have a basic understanding of how the molecular oscillations take place, a clear link between gene regulation and downstream biological processes is still missing. To identify clock-controlled output genes, we have used an oligonucleotide-based high-density array that interrogates gene expression changes on a whole genome level. We found genes regulating various physiological processes to be under circadian transcriptional regulation, ranging from protein stability and degradation, signal transduction, heme metabolism, detoxification, and immunity. By comparing rhythmically expressed genes in the fly head and body, we found that the clock has adapted its output functions to the needs of each particular tissue, implying that tissue-specific regulation is superimposed on clock control of gene expression. Finally, taking full advantage of the fly as a model system, we have identified and characterized a cycling potassium channel protein as a key step in linking the transcriptional feedback loop to rhythmic locomotor behavior.Fil: Ceriani, Maria Fernanda. The Scripps Research Institute; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Hogenesch, John B.. Genomics Institute of the Novartis Research Foundation; Estados UnidosFil: Yanovsky, Marcelo Javier. The Scripps Research Institute; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Panda, Satchidananda. Genomics Institute of the Novartis Research Foundation; Estados Unidos. The Scripps Research Institute; Estados UnidosFil: Straume, Martin. University Of Virginia; Estados UnidosFil: Kay, Steve A.. Genomics Institute of the Novartis Research Foundation; Estados Unidos. The Scripps Research Institute; Estados Unido

A timely call to arms: COVID-19, the circadian clock, and critical care

We currently find ourselves in the midst of a global coronavirus disease 2019 (COVID-19) pandemic, caused by the highly infectious novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we discuss aspects of SARS-CoV-2 biology and pathology and how these might interact with the circadian clock of the host. We further focus on the severe manifestation of the illness, leading to hospitalization in an intensive care unit. The most common severe complications of COVID-19 relate to clock-regulated human physiology. We speculate on how the pandemic might be used to gain insights on the circadian clock but, more importantly, on how knowledge of the circadian clock might be used to mitigate the disease expression and the clinical course of COVID-19

Coordinated Transcription of Key Pathways in the Mouse by the Circadian Clock

AbstractIn mammals, circadian control of physiology and behavior is driven by a master pacemaker located in the suprachiasmatic nuclei (SCN) of the hypothalamus. We have used gene expression profiling to identify cycling transcripts in the SCN and in the liver. Our analysis revealed ∼650 cycling transcripts and showed that the majority of these were specific to either the SCN or the liver. Genetic and genomic analysis suggests that a relatively small number of output genes are directly regulated by core oscillator components. Major processes regulated by the SCN and liver were found to be under circadian regulation. Importantly, rate-limiting steps in these various pathways were key sites of circadian control, highlighting the fundamental role that circadian clocks play in cellular and organismal physiology

The effects of time-restricted eating and weight loss on bone metabolism and health: a 6-month randomized controlled trial.

OBJECTIVE This study explored the impact of time-restricted eating (TRE) versus standard dietary advice (SDA) on bone health. METHODS Adults with ≥1 component of metabolic syndrome were randomized to TRE (ad libitum eating within 12 hours) or SDA (food pyramid brochure). Bone turnover markers and bone mineral content/density by dual energy x-ray absorptiometry were assessed at baseline and 6-month follow-up. Statistical analyses were performed in the total population and by weight loss response. RESULTS In the total population (n = 42, 76% women, median age 47 years [IQR: 31-52]), there were no between-group differences (TRE vs. SDA) in any bone parameter. Among weight loss responders (≥0.6 kg weight loss), the bone resorption marker β-carboxyterminal telopeptide of type I collagen tended to decrease after TRE but increase after SDA (between-group differences p = 0.041), whereas changes in the bone formation marker procollagen type I N-propeptide did not differ between groups. Total body bone mineral content decreased after SDA (p = 0.028) but remained unchanged after TRE (p = 0.31) in weight loss responders (between-group differences p = 0.028). Among nonresponders (<0.6 kg weight loss), there were no between-group differences in bone outcomes. CONCLUSIONS TRE had no detrimental impact on bone health, whereas, when weight loss occurred, it was associated with some bone-sparing effects compared with SDA

Inducible Ablation of Melanopsin-Expressing Retinal Ganglion Cells Reveals Their Central Role in Non-Image Forming Visual Responses

Rod/cone photoreceptors of the outer retina and the melanopsin-expressing retinal ganglion cells (mRGCs) of the inner retina mediate non-image forming visual responses including entrainment of the circadian clock to the ambient light, the pupillary light reflex (PLR), and light modulation of activity. Targeted deletion of the melanopsin gene attenuates these adaptive responses with no apparent change in the development and morphology of the mRGCs. Comprehensive identification of mRGCs and knowledge of their specific roles in image-forming and non-image forming photoresponses are currently lacking. We used a Cre-dependent GFP expression strategy in mice to genetically label the mRGCs. This revealed that only a subset of mRGCs express enough immunocytochemically detectable levels of melanopsin. We also used a Cre-inducible diphtheria toxin receptor (iDTR) expression approach to express the DTR in mRGCs. mRGCs develop normally, but can be acutely ablated upon diphtheria toxin administration. The mRGC-ablated mice exhibited normal outer retinal function. However, they completely lacked non-image forming visual responses such as circadian photoentrainment, light modulation of activity, and PLR. These results point to the mRGCs as the site of functional integration of the rod/cone and melanopsin phototransduction pathways and as the primary anatomical site for the divergence of image-forming and non-image forming photoresponses in mammals

When a calorie is not just a calorie : Diet quality and timing as mediators of metabolism and healthy aging

Funding Information: We thank Dr. Yih-Woei Fridell of the National Institute on Aging for organizing the meeting, as well as the NIA Division of Aging Biology for their support. We thank Dr. Gino Cortopassi for his edits and suggestions. The figures were created with BioRender.com. The Mihaylova lab is supported in part by the NIA (R00AG054760), Office of the NIH Director (DP2CA271361), the American Federation for Aging Research, the V Foundation, Pew Biomedical Scholar award, and startup funds from the Ohio State University. The Delibegovic lab is funded by the British Heart Foundation, Diabetes UK, BBSRC, NHS Grampian, Tenovus Scotland, and the Development Trust (University of Aberdeen). J.J.R. is supported by NIA PO1AG062817, R21AG064290, and R21AG071156. Research support for J.B. was from NIH National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grants R01DK127800, R01DK113011, R01DK090625, and R01DK050203 and the National Institute on Aging (NIA) grants R01AG065988 and P01AG011412, as well as the University of Chicago Diabetes Research and Training Center grant P30DK020595. This work was supported by NIH grants AG065992 to G.M. and AG068550 to G.M. and S.P. as well as UAB Startup funds 3123226 and 3123227 to G.M. R.S. is supported by NIH grants RF1AG043517, R01AG065985, R01DK123327, R56AG074568, and P01AG031782. Z.C. is primarily funded by The Welch Foundation (AU-1731-20190330) and NIH/NIA (R01AG065984, R56AG063746, RF1AG061901, and R56AG076144). A.C. is supported by NIA grant R01AG065993. W.W.J. is supported by the NIH (R01DC020031). M.S.-H. is supported by NIH R01 R35GM127049, R01 AG045842, and R21 NS122366. The research in the Dixit lab was supported in part by NIH grants AG031797, AG045712, P01AG051459, AR070811, AG076782, AG073969, and AG068863 and Cure Alzheimer's Fund (CAF). A.E.T.-M. is supported by the NIH/NIA (AG075059 and AG058630), NIAMS (AR071133), NHLBI (HL153460), pilot and feasibility funds from the NIDDK-funded UAB Nutrition Obesity Research Center (DK056336) and the NIA-funded UAB Nathan Shock Center (AG050886), and startup funds from UAB. J.A.M. is supported by the Intramural Research Program, NIA, NIH. The Panda lab is supported by the NIH (R01CA236352, R01CA258221, RF1AG068550, and P30CA014195), the Wu Tsai Human Performance Alliance, and the Joe and Clara Tsai Foundation. The Lamming lab is supported in part by the NIA (AG056771, AG062328, AG061635, and AG081482), the NIDDK (DK125859), startup funds from UW-Madison, and the U.S. Department of Veterans Affairs (I01-BX004031), and this work was supported using facilities and resources from the William S. Middleton Memorial Veterans Hospital. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work does not represent the views of the Department of Veterans Affairs or the United States Government. D.W.L. has received funding from, and is a scientific advisory board member of, Aeovian Pharmaceuticals, which seeks to develop novel, selective mTOR inhibitors for the treatment of various diseases. S.P. is the author of the books The Circadian Code and The Circadian Diabetes Code. Funding Information: We thank Dr. Yih-Woei Fridell of the National Institute on Aging for organizing the meeting, as well as the NIA Division of Aging Biology for their support. We thank Dr. Gino Cortopassi for his edits and suggestions. The figures were created with BioRender.com . The Mihaylova lab is supported in part by the NIA ( R00AG054760 ), Office of the NIH Director ( DP2CA271361 ), the American Federation for Aging Research , the V Foundation , Pew Biomedical Scholar award, and startup funds from the Ohio State University . The Delibegovic lab is funded by the British Heart Foundation , Diabetes UK , BBSRC , NHS Grampian , Tenovus Scotland , and the Development Trust ( University of Aberdeen ). J.J.R. is supported by NIA PO1AG062817 , R21AG064290 , and R21AG071156 . Research support for J.B. was from NIH National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grants R01DK127800 , R01DK113011 , R01DK090625 , and R01DK050203 and the National Institute on Aging (NIA) grants R01AG065988 and P01AG011412 , as well as the University of Chicago Diabetes Research and Training Center grant P30DK020595 . This work was supported by NIH grants AG065992 to G.M. and AG068550 to G.M. and S.P., as well as UAB Startup funds 3123226 and 3123227 to G.M. R.S. is supported by NIH grants RF1AG043517 , R01AG065985 , R01DK123327 , R56AG074568 , and P01AG031782 . Z.C. is primarily funded by The Welch Foundation ( AU-1731-20190330 ) and NIH/NIA ( R01AG065984 , R56AG063746 , RF1AG061901 , and R56AG076144 ). A.C. is supported by NIA grant R01AG065993 . W.W.J. is supported by the NIH ( R01DC020031 ). M.S.-H. is supported by NIH R01 R35GM127049 , R01 AG045842 , and R21 NS122366 . The research in the Dixit lab was supported in part by NIH grants AG031797 , AG045712 , P01AG051459 , AR070811 , AG076782 , AG073969 , and AG068863 and Cure Alzheimer's Fund (CAF). A.E.T.-M. is supported by the NIH/NIA ( AG075059 and AG058630 ), NIAMS ( AR071133 ), NHLBI ( HL153460 ), pilot and feasibility funds from the NIDDK -funded UAB Nutrition Obesity Research Center ( DK056336 ) and the NIA -funded UAB Nathan Shock Center ( AG050886 ), and startup funds from UAB . J.A.M. is supported by the Intramural Research Program, NIA, NIH . The Panda lab is supported by the NIH ( R01CA236352 , R01CA258221 , RF1AG068550 , and P30CA014195 ), the Wu Tsai Human Performance Alliance , and the Joe and Clara Tsai Foundation . The Lamming lab is supported in part by the NIA ( AG056771 , AG062328 , AG061635 , and AG081482 ), the NIDDK ( DK125859 ), startup funds from UW-Madison , and the U.S. Department of Veterans Affairs ( I01-BX004031 ), and this work was supported using facilities and resources from the William S. Middleton Memorial Veterans Hospital. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work does not represent the views of the Department of Veterans Affairs or the United States Government.Peer reviewedPostprin

Impact of Sleep and Circadian Disruption on Energy Balance and Diabetes: A Summary of Workshop Discussions

A workshop was held at the National Institute for Diabetes and Digestive and Kidney Diseases with a focus on the impact of sleep and circadian disruption on energy balance and diabetes. The workshop identified a number of key principles for research in this area and a number of specific opportunities. Studies in this area would be facilitated by active collaboration between investigators in sleep/circadian research and investigators in metabolism/diabetes. There is a need to translate the elegant findings from basic research into improving the metabolic health of the American public. There is also a need for investigators studying the impact of sleep/circadian disruption in humans to move beyond measurements of insulin and glucose and conduct more in-depth phenotyping. There is also a need for the assessments of sleep and circadian rhythms as well as assessments for sleep-disordered breathing to be incorporated into all ongoing cohort studies related to diabetes risk. Studies in humans need to complement the elegant short-term laboratory-based human studies of simulated short sleep and shift work etc. with studies in subjects in the general population with these disorders. It is conceivable that chronic adaptations occur, and if so, the mechanisms by which they occur needs to be identified and understood. Particular areas of opportunity that are ready for translation are studies to address whether CPAP treatment of patients with pre-diabetes and obstructive sleep apnea (OSA) prevents or delays the onset of diabetes and whether temporal restricted feeding has the same impact on obesity rates in humans as it does in mice