Venn diagram analysis overestimates the extent of circadian rhythm reprogramming

Targeting the intestinal circadian clock by meal timing ameliorates gastrointestinal inflammation

The expression of clock genes has been observed to be impaired in biopsies from patients with inflammatory bowel disease (IBD). Disruption of circadian rhythms, which occurs in shift workers, has been linked to an increased risk of gastrointestinal diseases, including IBD. The peripheral circadian clock in intestinal epithelial cells (IECs) was previously shown to balance gastrointestinal homeostasis by regulating the microbiome. Here, we demonstrated that the intestinal clock is disrupted in an IBD-relevant mouse model (IL-10-/-). A lack of the intestinal clock gene (Bmal1) in intestinal epithelial cells (IECs) in a chemically and a novel genetically induced colitis model (DSS, Bmal1IEC-/-xIL-10-/-) promoted colitis and dramatically reduced survival rates. Germ-free Bmal1IEC-/- mice colonized with disease-associated microbiota from IL-10-/- mice exhibited increased inflammatory responses, highlighting the importance of the local intestinal clock for microbiota-induced IBD development. Targeting the intestinal clock directly by timed restricted feeding (RF) in IL-10-/- mice restored intestinal clock functions, including immune cell recruitment and microbial rhythmicity; improved inflammatory responses; dramatically enhanced survival rates and rescued the histopathological phenotype. In contrast, RF failed to improve IBD symptoms in Bmal1IEC-/-xIL-10-/- mice, demonstrating the significance of the intestinal clock in determining the beneficial effect of RF. Overall, we provide evidence that intestinal clock dysfunction triggers host immune imbalance and promotes the development and progression of IBD-like colitis. Enhancing intestinal clock function by RF modulates the pathogenesis of IBD and thus could become a novel strategy to ameliorate symptoms in IBD patients.

Loss of temporal coherence in the circadian metabolome across multiple tissues during ageing in mice

Circadian clock function declines with ageing, which can aggravate ageing-related diseases such as type 2 diabetes and neurodegenerative disorders. Understanding age-related changes in the circadian system at a systemic level can contribute to the development of strategies to promote healthy ageing. The goal of this study was to investigate the impact of ageing on 24-h rhythms in amine metabolites across four tissues in young (2 months of age) and old (22-25 months of age) mice using a targeted metabolomics approach. Liver, plasma, the suprachiasmatic nucleus (SCN; the location of the central circadian clock in the hypothalamus) and the paraventricular nucleus (PVN; a downstream target of the SCN) were collected from young and old mice every 4 h during a 24-h period (n = 6-7 mice per group). Differential rhythmicity analysis revealed that ageing impacts 24-h rhythms in the amine metabolome in a tissue-specific manner. Most profound changes were observed in the liver, in which rhythmicity was lost in 60% of the metabolites in aged mice. Furthermore, we found strong correlations in metabolite levels between the liver and plasma and between the SCN and the PVN in young mice. These correlations were almost completely abolished in old mice. These results indicate that ageing is accompanied by a severe loss of the circadian coordination between tissues and by disturbed rhythmicity of metabolic processes. The tissue-specific impact of ageing may help to differentiate mechanisms of ageing-related disorders in the brain versus peripheral tissues and thereby contribute to the development of potential therapies for these disorders.

The epidermal circadian clock integrates and subverts brain signals to guarantee skin homeostasis

In mammals, the circadian clock network drives daily rhythms of tissue-specific homeostasis. To dissect daily inter-tissue communication, we constructed a mouse minimal clock network comprising only two nodes: the peripheral epidermal clock and the central brain clock. By transcriptomic and functional characterization of this isolated connection, we identified a gatekeeping function of the peripheral tissue clock with respect to systemic inputs. The epidermal clock concurrently integrates and subverts brain signals to ensure timely execution of epidermal daily physiology. Timely cell-cycle termination in the epidermal stem cell compartment depends upon incorporation of clock-driven signals originating from the brain. In contrast, the epidermal clock corrects or outcompetes potentially disruptive feeding-related signals to ensure the optimal timing of DNA replication. Together, we present an approach for cataloging the systemic dependencies of daily temporal organization in a tissue and identify an essential gate-keeping function of peripheral circadian clocks that guarantees tissue homeostasis.

A glial circadian gene expression atlas reveals cell type and disease-specific reprogramming in response to amyloid pathology or aging

While circadian rhythm disruption may promote neurodegenerative disease, how aging and neurodegenerative pathology impact circadian gene expression patterns in different brain cell types is unknown. Here, we used translating ribosome affinity purification methods to define the circadian translatomes of astrocytes, microglia, and bulk cerebral cortex, in healthy mouse brain and in the settings of amyloid-beta plaque pathology or aging. Our data reveal that glial circadian translatomes are highly cell type-specific and exhibit profound, context-dependent reprogramming of rhythmic transcripts in response to amyloid pathology or aging. Transcripts involved in glial activation, immunometabolism, and proteostasis, as well as nearly half of all Alzheimer Disease (AD)-associated risk genes, displayed circadian oscillations, many of which were altered by pathology. Amyloid-related differential gene expression was also dependent on time of day. Thus, circadian rhythms in gene expression are cell- and context dependent and provide important insights into glial gene regulation in health, AD, and aging.

Icariin ameliorates LPS-induced acute lung injury in mice via complement C5a-C5aR1 and TLR4 signaling pathways

Acute lung injury (ALI) is an acute respiratory-related progressive disorder, which lacks specific pharmacotherapy. Icariin (ICA) has been shown to be effective in treating ALI. However, the targets and pharmacological mechanisms underlying the effects of ICA in the treatment of ALI are relatively lacking. Based on network pharmacology and molecular docking analyses, the gene functions and potential target pathways of ICA in the treatment of ALI were determined. In addition, the underlying mechanisms of ICA were verified by immunohistochemistry, immunofluorescence, quantitative Real-time PCR, and Western blot in LPS-induced ALI mice. The biological processes targeted by ICA in the treatment of ALI included the pathological changes, inflammatory response, and cell signal transduction. Network pharmacology, molecular docking, and in vivo experimental results revealed that ICA inhibited the complement C5a-C5aR1 axis, TLR4 mediated NF-κB, MAPK, and JAK2-STAT3 signaling pathways related gene and protein expressions, and decreased inflammatory cytokine, chemokine, adhesion molecule expressions, and mitochondrial apoptosis in LPS-induced ALI.

Diurnal rhythmicity of infant fecal microbiota and metabolites: A randomized controlled interventional trial with infant formula

Microbiota assembly in the infant gut is influenced by diet. Breastfeeding and human breastmilk oligosaccharides promote the colonization of beneficial bifidobacteria. Infant formulas are supplemented with bifidobacteria or complex oligosaccharides, notably galacto-oligosaccharides (GOS), to mimic breast milk. To compare microbiota development across feeding modes, this randomized controlled intervention study (German Clinical Trial DRKS00012313) longitudinally sampled infant stool during the first year of life, revealing similar fecal bacterial communities between formula- and breast-fed infants (N = 210) but differences across age. Infant formula containing GOS sustained high levels of bifidobacteria compared with formula containing B. longum and B. breve or placebo. Metabolite and bacterial profiling revealed 24-h oscillations and circadian networks. Rhythmicity in bacterial diversity, specific taxa, and functional pathways increased with age and was strongest following breastfeeding and GOS supplementation. Circadian rhythms in dominant taxa were further maintained ex vivo in a chemostat model. Hence, microbiota rhythmicity develops early in life and is impacted by diet.

Tumor circadian clock strength influences metastatic potential and predicts patient prognosis in luminal A breast cancer

Studies in shift workers and model organisms link circadian disruption to breast cancer. However, molecular circadian rhythms in noncancerous and cancerous human breast tissues and their clinical relevance are largely unknown. We reconstructed rhythms informatically, integrating locally collected, time-stamped biopsies with public datasets. For noncancerous breast tissue, inflammatory, epithelial-mesenchymal transition (EMT), and estrogen responsiveness pathways show circadian modulation. Among tumors, clock correlation analysis demonstrates subtype-specific changes in circadian organization. Luminal A organoids and informatic ordering of luminal A samples exhibit continued, albeit dampened and reprogrammed rhythms. However, CYCLOPS magnitude, a measure of global rhythm strength, varied widely among luminal A samples. Cycling of EMT pathway genes was markedly increased in high-magnitude luminal A tumors. Surprisingly, patients with high-magnitude tumors had reduced 5-y survival. Correspondingly, 3D luminal A cultures show reduced invasion following molecular clock disruption. This study links subtype-specific circadian disruption in breast cancer to EMT, metastatic potential, and prognosis.

Coordination of rhythmic RNA synthesis and degradation orchestrates 24- and 12-h RNA expression patterns in mouse fibroblasts

Circadian RNA expression is essential to ultimately regulate a plethora of downstream rhythmic biochemical, physiological, and behavioral processes. Both transcriptional and posttranscriptional mechanisms are considered important to drive rhythmic RNA expression; however, the extent to which each regulatory process contributes to the rhythmic RNA expression remains controversial. To systematically address this, we monitored RNA dynamics using metabolic RNA labeling technology during a circadian cycle in mouse fibroblasts. We find that rhythmic RNA synthesis is the primary contributor of 24-h RNA rhythms, while rhythmic degradation is more important for 12-h RNA rhythms. These rhythms were predominantly regulated by Bmal1 and/or the core clock mechanism, and the interplay between rhythmic synthesis and degradation has a significant impact in shaping rhythmic RNA expression patterns. Interestingly, core clock RNAs are regulated by multiple rhythmic processes and have the highest amplitude of synthesis and degradation, presumably critical to sustain robust rhythmicity of cell-autonomous circadian rhythms. Our study yields invaluable insights into the temporal dynamics of both 24- and 12-h RNA rhythms in mouse fibroblasts.

Circadian protein expression patterns in healthy young adults

OBJECTIVES

To explore how the blood plasma proteome fluctuates across the 24-hour day and identify a subset of proteins that show endogenous circadian rhythmicity.

METHODS

Plasma samples from 17 healthy adults were collected hourly under controlled conditions designed to unmask endogenous circadian rhythmicity; in a subset of 8 participants, we also collected samples across a day on a typical sleep-wake schedule. A total of 6916 proteins were analyzed from each sample using the SomaScan aptamer-based multiplexed platform. We used differential rhythmicity analysis based on a cosinor model with mixed effects to identify a subset of proteins that showed circadian rhythmicity in their abundance.

RESULTS

One thousand and sixty-three (15%) proteins exhibited significant daily rhythmicity. Of those, 431 (6.2%) proteins displayed consistent endogenous circadian rhythms on both a sleep-wake schedule and under controlled conditions: it included both known and novel proteins. When models were fitted with two harmonics, an additional 259 (3.7%) proteins exhibited significant endogenous circadian rhythmicity, indicating that some rhythmic proteins cannot be solely captured by a simple sinusoidal model. Overall, we found that the largest number of proteins had their peak levels in the late afternoon/evening, with another smaller group peaking in the early morning.

CONCLUSIONS

This study reveals that hundreds of plasma proteins exhibit endogenous circadian rhythmicity in humans. Future analyses will likely reveal novel physiological pathways regulated by circadian clocks and pave the way for improved diagnosis and treatment for patients with circadian disorders and other pathologies. It will also advance efforts to include knowledge about time-of-day, thereby incorporating circadian medicine into personalized medicine.

Chronopharmacology of diuresis via metabolic profiling and key biomarker discovery of the traditional Chinese prescription Ji-Ming-San using tandem mass spectrometry in rat models

BACKGROUND

Ji-Ming-Shan (JMS) is a traditional prescription used for patients with rheumatism, tendons swelling, relief of foot pain, athlete's foot, diuresis, gout. Although many studies have investigated the active compounds in each herb, the functional mechanism behind its therapeutic effect remains unclear.

STUDY DESIGN

Metabolic cages for sample collection. The serum components obtained from the experimental animals were analyzed using LC-MS/MS. Furthermore, cross-analysis using the software MetaboAnalyst and Venn diagrams were used to investigate chronopharmacology of JMS in the animal models.

PURPOSE

The aim of this study is to analyze the diuretic effects of JMS and to explore their chronopharmacology involved in organ regulation through four-quarter periods from serum samples of rat models.

METHODS

Metabolic cages were used for collecting the urine samples and PocketChem UA PU-4010, Fuji DRI-CHEM 800 were used to examine the urine biochemical parameters. The serum components were identified through ultra-performance liquid chromatography-quadrupole time-of-flight (UPLC-Q-TOF) with a new developed method. Cross analysis, Venn diagram, MetaboAnalyst were used to investigate the key biomarker and major metabolism route with the oral administration of the drug.

RESULT

JMS significantly changed the 6 h urine volume with no observed kidney toxicity. Urine pH value ranges from 7.0 to 7.5. The chronopharmacology of JMS diuresis activity were 0-6 and 6-12 groups. UPLC-Q-TOF analyses identified 243 metabolites which were determined in positive mode and negative mode respectively. With cross analysis in the Venn diagram, one key biomarker naringenin-7-O-glucoside has been identified. Major metabolic pathways such as 1: Glycerophospholipid metabolism, 2: Primary bile acid biosynthesis, 3: Sphingolipid metabolism, 4: Riboflavin metabolism, 5: Linoleic acid metabolism, 6: Butanoate metabolism.

CONCLUSION

JMS significantly changed the urine output of animals in the 0-6 and 6-12 groups. No change in urine pH was observed and also kidney toxicity. A new UPLC-Q-TOF method was developed for the detection of the metabolites of JMS after oral administration. The cross analysis with Venn diagram and identified the key biomarker of JMS namely naringenin-7-O-glucoside. The results showed that six major pathways are involved in the gastrointestinal system and the liver. This study demonstrated the capability of JMS prescription in the regulation of diuresis and identified a key biomarker that is responsible for its therapeutic effect.

LimoRhyde2: Genomic analysis of biological rhythms based on effect sizes

Genome-scale data have revealed daily rhythms in various species and tissues. However, current methods to assess rhythmicity largely restrict their focus to quantifying statistical significance, which may not reflect biological relevance. To address this limitation, we developed a method called LimoRhyde2 (the successor to our method LimoRhyde), which focuses instead on rhythm-related effect sizes and their uncertainty. For each genomic feature, LimoRhyde2 fits a curve using a series of linear models based on periodic splines, moderates the fits using an Empirical Bayes approach called multivariate adaptive shrinkage (Mash), then uses the moderated fits to calculate rhythm statistics such as peak-to-trough amplitude. The periodic splines capture non-sinusoidal rhythmicity, while Mash uses patterns in the data to account for different fits having different levels of noise. To demonstrate LimoRhyde2's utility, we applied it to multiple circadian transcriptome datasets. Overall, LimoRhyde2 prioritized genes having high-amplitude rhythms in expression, whereas a prior method (BooteJTK) prioritized "statistically significant" genes whose amplitudes could be relatively small. Thus, quantifying effect sizes using approaches such as LimoRhyde2 has the potential to transform interpretation of genomic data related to biological rhythms.

Meta-analysis of Diurnal Transcriptomics in Mouse Liver Reveals Low Repeatability of Rhythm Analyses

To assess the consistency of biological rhythms across studies, 57 public mouse liver tissue timeseries totaling 1096 RNA-seq samples were obtained and analyzed. Only the control groups of each study were included, to create comparable data. Technical factors in RNA-seq library preparation were the largest contributors to transcriptome-level differences, beyond biological or experiment-specific factors such as lighting conditions. Core clock genes were remarkably consistent in phase across all studies. Overlap of genes identified as rhythmic across studies was generally low, with no pair of studies having over 60% overlap. Distributions of phases of significant genes were remarkably inconsistent across studies, but the genes that consistently identified as rhythmic had acrophase clustering near ZT0 and ZT12. Despite the discrepancies between single-study analyses, cross-study analyses found substantial consistency. Running compareRhythms on each pair of studies identified a median of only 11% of the identified rhythmic genes as rhythmic in only 1 of the 2 studies. Data were integrated across studies in a joint and individual variance estimate (JIVE) analysis, which showed that the top 2 components of joint within-study variation are determined by time of day. A shape-invariant model with random effects was fit to the genes to identify the underlying shape of the rhythms, consistent across all studies, including identifying 72 genes with consistently multiple peaks.

A comparative study of algorithms detecting differential rhythmicity in transcriptomic data

Rhythmic transcripts play pivotal roles in driving the daily oscillations of various biological processes. Genetic or environmental disruptions can lead to alterations in the rhythmicity of transcripts, ultimately impacting downstream circadian outputs, including metabolic processes and even behavior. To statistically compare the differences in transcript rhythms between two or more conditions, several algorithms have been developed to analyze circadian transcriptomic data, each with distinct features. In this study, we compared the performance of seven algorithms that were specifically designed to detect differential rhythmicity. We found that even when applying the same statistical threshold, these algorithms yielded varying numbers of differentially rhythmic transcripts. Nevertheless, the set of transcripts commonly identified as differentially rhythmic exhibited substantial overlap among algorithms. Furthermore, the phase and amplitude differences calculated by these algorithms displayed significant correlations. In summary, our study highlights a high degree of similarity in the results produced by these algorithms. Furthermore, when selecting an algorithm for analysis, it is crucial to ensure the compatibility of input data with the specific requirements of the chosen algorithm and to assess whether the algorithm's output fits the needs of the user.

An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent circadian oscillations in stem cells

MOTIVATION

Detecting oscillations in time series remains a challenging problem even after decades of research. In chronobiology, rhythms (for instance in gene expression, eclosion, egg-laying, and feeding) tend to be low amplitude, display large variations amongst replicates, and often exhibit varying peak-to-peak distances (non-stationarity). Most currently available rhythm detection methods are not specifically designed to handle such datasets, and are also limited by their use of P-values in detecting oscillations.

RESULTS

We introduce a new method, ODeGP (Oscillation Detection using Gaussian Processes), which combines Gaussian Process regression and Bayesian inference to incorporate measurement errors, non-uniformly sampled data, and a recently developed non-stationary kernel to improve detection of oscillations. By using Bayes factors, ODeGP models both the null (non-rhythmic) and the alternative (rhythmic) hypotheses, thus providing an advantage over P-values. Using synthetic datasets, we first demonstrate that ODeGP almost always outperforms eight commonly used methods in detecting stationary as well as non-stationary symmetric oscillations. Next, by analyzing existing qPCR datasets, we demonstrate that our method is more sensitive compared to the existing methods at detecting weak and noisy oscillations. Finally, we generate new qPCR data on mouse embryonic stem cells. Surprisingly, we discover using ODeGP that increasing cell-density results in rapid generation of oscillations in the Bmal1 gene, thus highlighting our method's ability to discover unexpected and new patterns. In its current implementation, ODeGP is meant only for analyzing single or a few time-trajectories, not genome-wide datasets.

AVAILABILITY AND IMPLEMENTATION

ODeGP is available at https://github.com/Shaonlab/ODeGP.

Seasonal light hours modulate peripheral clocks and energy metabolism in mice

Except for latitudes close to the equator, seasonal variation in light hours can change dramatically between summer and winter. Yet investigations into the interplay between energy metabolism and circadian rhythms typically use a 12 h light:12 h dark photoperiod corresponding to the light duration at the equator. We hypothesized that altering the seasonal photoperiod affects both the rhythmicity of peripheral tissue clocks and energy homeostasis. Mice were housed at photoperiods representing either light hours in summer, winter, or the equinox. Mice housed at a winter photoperiod exhibited an increase in the amplitude of rhythmic lipid metabolism and a modest reduction in fat mass and liver triglyceride content. Comparing melatonin-proficient and -deficient mice, the effect of seasonal light on energy metabolism was largely driven by differences in the rhythmicity of food intake and not melatonin. Together, these data indicate that seasonal light impacts energy metabolism by modulating the timing of eating.

Bioinformatics approach and experimental validation reveal the hepatoprotective effect of pachyman against acetaminophen-associated liver injury

Pachyman, known as Poria cocos polysaccharides, refers to the bioactive compounds isolated from Poria cocos. Pachyman is thought to exert cytoprotective action. However, the detailed mechanisms of pachyman action for hepatoprotection remain unknown. In this study, we aimed to assess the therapeutic actions, molecular mechanisms, and key target proteins of pachyman in the treatment of liver injury through network pharmacology and molecular docking assays. Furthermore, these bioinformatic findings were validated by an acetaminophen (APAP)-induced liver injury in vivo. Primarily using bioinformatic analysis, we screened and characterized 12 genes that act as potential therapeutic targets of pachyman against APAP-induced liver injury, in which all core targets were obtained. By using enrichment analysis, these core target genes of pachyman were characterized to reveal the pharmacological functions and molecular mechanisms of anti-liver injury induced by APAP. A molecular docking simulation was further performed to certain anti-liver injury target proteins of pachyman, including cytochrome P450 3A4 enzyme (CYP3A4) and inducible nitric oxide synthase (NOS2). In animal experiments, pachyman exerted potent hepatoprotective activities in prenatal APAP-exposed offspring livers, characterized by activated hepatocellular CYP3A4 and NOS2 expressions. These current findings have thus indicated that pachyman exerts hepatoprotective effects and may be the promising nutraceuticals for the treatment of APAP-induced liver injury.

Coordination of rhythmic RNA synthesis and degradation orchestrates 24-hour and 12-hour RNA expression patterns in mouse fibroblasts

Circadian RNA expression is essential to ultimately regulate a plethora of downstream rhythmic biochemical, physiological, and behavioral processes. Both transcriptional and post-transcriptional mechanisms are considered important to drive rhythmic RNA expression, however, the extent to which each regulatory process contributes to the rhythmic RNA expression remains controversial. To systematically address this, we monitored RNA dynamics using metabolic RNA labeling technology during a circadian cycle in mouse fibroblasts. We find that rhythmic RNA synthesis is the primary contributor of 24 hr RNA rhythms, while rhythmic degradation is more important for 12 hr RNA rhythms. These rhythms were predominantly regulated by Bmal1 and/or the core clock mechanism, and interplay between rhythmic synthesis and degradation has a significant impact in shaping rhythmic RNA expression patterns. Interestingly, core clock RNAs are regulated by multiple rhythmic processes and have the highest amplitude of synthesis and degradation, presumably critical to sustain robust rhythmicity of cell-autonomous circadian rhythms. Our study yields invaluable insights into the temporal dynamics of both 24 hr and 12 hr RNA rhythms in mouse fibroblasts.

Circadian transcriptome processing and analysis: a workflow for muscle stem cells

Circadian rhythms coordinate biological processes with Earth's 24-h daily light/dark cycle. In the last years, efforts in the field of chronobiology have sought to understand the ways in which the circadian clock controls transcription across tissues and cells. This has been supported by the development of different bioinformatic approaches that allow the identification of 24-h oscillating transcripts. This workflow aims to describe how to isolate muscle stem cells for RNA sequencing analysis from a typical circadian experiment and introduces bioinformatic tools suitable for the analysis of circadian transcriptomes.

Subtype-specific circadian clock dysregulation modulates breast cancer biology, invasiveness, and prognosis

Studies in shift workers and model organisms link circadian disruption to breast cancer. However, molecular rhythms in non-cancerous and cancerous human breast tissues are largely unknown. We reconstructed rhythms informatically, integrating locally collected, time-stamped biopsies with public datasets. For non-cancerous tissue, the inferred order of core-circadian genes matches established physiology. Inflammatory, epithelial-mesenchymal transition (EMT), and estrogen responsiveness pathways show circadian modulation. Among tumors, clock correlation analysis demonstrates subtype-specific changes in circadian organization. Luminal A organoids and informatic ordering of Luminal A samples exhibit continued, albeit disrupted rhythms. However, CYCLOPS magnitude, a measure of global rhythm strength, varied widely among Luminal A samples. Cycling of EMT pathway genes was markedly increased in high-magnitude Luminal A tumors. Patients with high-magnitude tumors had reduced 5-year survival. Correspondingly, 3D Luminal A cultures show reduced invasion following molecular clock disruption. This study links subtype-specific circadian disruption in breast cancer to EMT, metastatic potential, and prognosis.

Oral supplementation of nicotinamide riboside alters intestinal microbial composition in rats and mice, but not humans

The gut microbiota impacts systemic levels of multiple metabolites including NAD⁺ precursors through diverse pathways. Nicotinamide riboside (NR) is an NAD⁺ precursor capable of regulating mammalian cellular metabolism. Some bacterial families express the NR-specific transporter, PnuC. We hypothesized that dietary NR supplementation would modify the gut microbiota across intestinal sections. We determined the effects of 12 weeks of NR supplementation on the microbiota composition of intestinal segments of high-fat diet-fed (HFD) rats. We also explored the effects of 12 weeks of NR supplementation on the gut microbiota in humans and mice. In rats, NR reduced fat mass and tended to decrease body weight. Interestingly, NR increased fat and energy absorption but only in HFD-fed rats. Moreover, 16S rRNA gene sequencing analysis of intestinal and fecal samples revealed an increased abundance of species within Erysipelotrichaceae and Ruminococcaceae families in response to NR. PnuC-positive bacterial strains within these families showed an increased growth rate when supplemented with NR. The abundance of species within the Lachnospiraceae family decreased in response to HFD irrespective of NR. Alpha and beta diversity and bacterial composition of the human fecal microbiota were unaltered by NR, but in mice, the fecal abundance of species within Lachnospiraceae increased while abundances of Parasutterella and Bacteroides dorei species decreased in response to NR. In conclusion, oral NR altered the gut microbiota in rats and mice, but not in humans. In addition, NR attenuated body fat mass gain in rats, and increased fat and energy absorption in the HFD context.

Data integration and analysis for circadian medicine

Data integration, data sharing, and standardized analyses are important enablers for data-driven medical research. Circadian medicine is an emerging field with a particularly high need for coordinated and systematic collaboration between researchers from different disciplines. Datasets in circadian medicine are multimodal, ranging from molecular circadian profiles and clinical parameters to physiological measurements and data obtained from (wearable) sensors or reported by patients. Uniquely, data spanning both the time dimension and the spatial dimension (across tissues) are needed to obtain a holistic view of the circadian system. The study of human rhythms in the context of circadian medicine has to confront the heterogeneity of clock properties within and across subjects and our inability to repeatedly obtain relevant biosamples from one subject. This requires informatics solutions for integrating and visualizing relevant data types at various temporal resolutions ranging from milliseconds and seconds to minutes and several hours. Associated challenges range from a lack of standards that can be used to represent all required data in a common interoperable form, to challenges related to data storage, to the need to perform transformations for integrated visualizations, and to privacy issues. The downstream analysis of circadian rhythms requires specialized approaches for the identification, characterization, and discrimination of rhythms. We conclude that circadian medicine research provides an ideal environment for developing innovative methods to address challenges related to the collection, integration, visualization, and analysis of multimodal multidimensional biomedical data.

Consumption of a high-fat diet alters transcriptional rhythmicity in liver from pubertal mice

Introduction

Childhood obesity is associated with adult obesity, which is a risk factor for chronic diseases. Obesity, as an environmental cue, alters circadian rhythms. The hypothesis of this study was that consumption of a high-fat diet alters metabolic rhythms in pubertal mice.

Methods

Weanling female C57BL/6NHsd mice were fed a standard AIN93G diet or a high-fat diet (HFD) for 3 weeks. Livers were collected from six-week-old mice every 4 h over a period of 48 h for transcriptome analysis.

Results and discussion

The HFD altered rhythmicity of differentially rhythmic transcripts in liver. Specifically, the HFD elevated expression of circadian genes Clock, Per1, and Cry1 and genes encoding lipid metabolism Fads1 and Fads2, while decreased expression of circadian genes Bmal1 and Per2 and lipid metabolism genes Acaca, Fasn, and Scd1. Hierarchical clustering analysis of differential expression genes showed that the HFD-mediated metabolic disturbance was most active in the dark phase, ranging from Zeitgeber time 16 to 20. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis of differentially expressed genes showed that the HFD up-regulated signaling pathways related to fatty acid and lipid metabolism, steroid and steroid hormone biosynthesis, amino acid metabolism and protein processing in the endoplasmic reticulum, glutathione metabolism, and ascorbate and aldarate metabolism in the dark phase. Down-regulations included MAPK pathway, lipolysis in adipocytes, Ras and Rap1 pathways, and pathways related to focal adhesion, cell adhesion molecules, and extracellular matrix-receptor interaction. In summary, the HFD altered metabolic rhythms in pubertal mice with the greatest alterations in the dark phase. These alterations may disrupt metabolic homeostasis in puberty and lead to metabolic disorders.

Consequences of collagen induced inflammatory arthritis on circadian regulation of the gut microbiome

The gut microbiota is important for host health and immune system function. Moreover autoimmune diseases, such as rheumatoid arthritis, are associated with significant gut microbiota dysbiosis, although the causes and consequences of this are not fully understood. It has become clear that the composition and metabolic outputs of the microbiome exhibit robust 24 h oscillations, a result of daily variation in timing of food intake as well as rhythmic circadian clock function in the gut. Here, we report that experimental inflammatory arthritis leads to a re-organization of circadian rhythmicity in both the gut and associated microbiome. Mice with collagen induced arthritis exhibited extensive changes in rhythmic gene expression in the colon, and reduced barrier integrity. Re-modeling of the host gut circadian transcriptome was accompanied by significant alteration of the microbiota, including widespread loss of rhythmicity in symbiont species of Lactobacillus, and alteration in circulating microbial derived factors, such as tryptophan metabolites, which are associated with maintenance of barrier function and immune cell populations within the gut. These findings highlight that altered circadian rhythmicity during inflammatory disease contributes to dysregulation of gut integrity and microbiome function.

DiffCircaPipeline: a framework for multifaceted characterization of differential rhythmicity

SUMMARY

Circadian oscillations of gene expression regulate daily physiological processes, and their disruption is linked to many diseases. Circadian rhythms can be disrupted in a variety of ways, including differential phase, amplitude and rhythm fitness. Although many differential circadian biomarker detection methods have been proposed, a workflow for systematic detection of multifaceted differential circadian characteristics with accurate false positive control is not currently available. We propose a comprehensive and interactive pipeline to capture the multifaceted characteristics of differentially rhythmic biomarkers. Analysis outputs are accompanied by informative visualization and interactive exploration. The workflow is demonstrated in multiple case studies and is extensible to general omics applications.

AVAILABILITY AND IMPLEMENTATION

R package, Shiny app and source code are available in GitHub (https://github.com/DiffCircaPipeline) and Zenodo (https://doi.org/10.5281/zenodo.7507989).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Inter-layer and inter-subject variability of diurnal gene expression in human skin

The skin is the largest human organ with a circadian clock that regulates its function. Although circadian rhythms in specific functions are known, rhythms in the proximal clock output, gene expression, in human skin have not been thoroughly explored. This work reports 24 h gene expression rhythms in two skin layers, epidermis and dermis, in a cohort of young, healthy adults, who maintained natural, regular sleep-wake schedules. 10% of the expressed genes showed such diurnal rhythms at the population level, of which only a third differed between the two layers. Amplitude and phases of diurnal gene expression varied more across subjects than layers, with amplitude being more variable than phases. Expression amplitudes in the epidermis were larger and more subject-variable, while they were smaller and more consistent in the dermis. Core clock gene expression was similar across layers at the population-level, but were heterogeneous in their variability across subjects. We also identified small sets of biomarkers for internal clock phase in each layer, which consisted of layer-specific non-core clock genes. This work provides a valuable resource to advance our understanding of human skin and presents a novel methodology to quantify sources of variability in human circadian rhythms.

Integrative Analysis of Rhythmicity: From Biology to Urban Environments and Sustainability

From biological to socio-technical systems, rhythmic processes are pervasive in our environment. However, methods for their comprehensive analysis are prevalent only in specific fields that limit the transfer of knowledge across scientific disciplines. This hinders interdisciplinary research and integrative analyses of rhythms across different domains and datasets. In this paper, we review recent developments in cross-disciplinary rhythmicity research, with a focus on the importance of rhythmic analyses in urban planning and biomedical research. Furthermore, we describe the current state of the art of (integrative) computational methods for the investigation of rhythmic data. Finally, we discuss the further potential and propose necessary future developments for cross-disciplinary rhythmicity analysis to foster integration of heterogeneous datasets across different domains, as well as guide data-driven decision making beyond the boundaries of traditional intradisciplinary research, especially in the context of sustainable and healthy cities.

Chronic inflammatory arthritis drives systemic changes in circadian energy metabolism

Chronic inflammation underpins many human diseases. Morbidity and mortality associated with chronic inflammation are often mediated through metabolic dysfunction. Inflammatory and metabolic processes vary through circadian time, suggesting an important temporal crosstalk between these systems. Using an established mouse model of rheumatoid arthritis, we show that chronic inflammatory arthritis results in rhythmic joint inflammation and drives major changes in muscle and liver energy metabolism and rhythmic gene expression. Transcriptional and phosphoproteomic analyses revealed alterations in lipid metabolism and mitochondrial function associated with increased EGFR-JAK-STAT3 signaling. Metabolomic analyses confirmed rhythmic metabolic rewiring with impaired β-oxidation and lipid handling and revealed a pronounced shunt toward sphingolipid and ceramide accumulation. The arthritis-related production of ceramides was most pronounced during the day, which is the time of peak inflammation and increased reliance on fatty acid oxidation. Thus, our data demonstrate that localized joint inflammation drives a time-of-day–dependent build-up of bioactive lipid species driven by rhythmic inflammation and altered EGFR-STAT signaling.

Nitecap: An Exploratory Circadian Analysis Web Application

Circadian omics analyses present investigators with large amounts of data to consider and many choices for methods of analysis. Visualization is crucial as rhythmicity can take many forms and p-values offer an incomplete picture. Yet statically viewing the entirety of high-throughput datasets is impractical, and there is often limited ability to assess the impact of choices, such as significance threshold cutoffs. Nitecap provides an intuitive and unified web-based solution to these problems. Through highly responsive visualizations, Nitecap enables investigators to see dataset-wide behavior. It supports deep analyses, including comparisons of two conditions. Moreover, it focuses upon ease-of-use and enables collaboration through dataset sharing. As an application, we investigated cross talk between peripheral clocks in adipose and liver tissues and determined that adipocyte clock disruption does not substantially modulate the transcriptional rhythmicity of liver but does advance the phase of core clock gene Bmal1 (Arntl) expression in the liver. Nitecap is available at nitecap.org and is free-to-use.