MOSAIC: a joint modeling methodology for combined circadian and non-circadian analysis of multi-omics data

Circadian rhythm, hypoxia, and cellular senescence: From molecular mechanisms to targeted strategies

Cellular senescence precipitates a decline in physiological activities and metabolic functions, often accompanied by heightened inflammatory responses, diminished immune function, and impaired tissue and organ performance. Despite extensive research, the mechanisms underpinning cellular senescence remain incompletely elucidated. Emerging evidence implicates circadian rhythm and hypoxia as pivotal factors in cellular senescence. Circadian proteins are central to the molecular mechanism governing circadian rhythm, which regulates homeostasis throughout the body. These proteins mediate responses to hypoxic stress and influence the progression of cellular senescence, with protein Brain and muscle arnt-like 1 (BMAL1 or Arntl) playing a prominent role. Hypoxia-inducible factor-1α (HIF-1α), a key regulator of oxygen homeostasis within the cellular microenvironment, orchestrates the transcription of genes involved in various physiological processes. HIF-1α not only impacts normal circadian rhythm functions but also can induce or inhibit cellular senescence. Notably, HIF-1α may aberrantly interact with BMAL1, forming the HIF-1α-BMAL1 heterodimer, which can instigate multiple physiological dysfunctions. This heterodimer is hypothesized to modulate cellular senescence by affecting the molecular mechanism of circadian rhythm and hypoxia signaling pathways. In this review, we elucidate the intricate relationships among circadian rhythm, hypoxia, and cellular senescence. We synthesize diverse evidence to discuss their underlying mechanisms and identify novel therapeutic targets to address cellular senescence. Additionally, we discuss current challenges and suggest potential directions for future research. This work aims to deepen our understanding of the interplay between circadian rhythm, hypoxia, and cellular senescence, ultimately facilitating the development of therapeutic strategies for aging and related diseases.

Model integration of circadian- and sleep-wake-driven contributions to rhythmic gene expression reveals distinct regulatory principles

Analyses of gene-expression dynamics in research on circadian rhythms and sleep homeostasis often describe these two processes using separate models. Rhythmically expressed genes are, however, likely to be influenced by both processes. We implemented a driven, damped harmonic oscillator model to estimate the contribution of circadian- and sleep-wake-driven influences on gene expression. The model reliably captured a wide range of dynamics in cortex, liver, and blood transcriptomes taken from mice and humans under various experimental conditions. Sleep-wake-driven factors outweighed circadian factors in driving gene expression in the cortex, whereas the opposite was observed in the liver and blood. Because of tissue- and gene-specific responses, sleep deprivation led to a long-lasting intra- and inter-tissue desynchronization. The model showed that recovery sleep contributed to these long-lasting changes. The results demonstrate that the analyses of the daily rhythms in gene expression must take the complex interactions between circadian and sleep-wake influences into account. A record of this paper's transparent peer review process is included in the supplemental information.

Multi-omics reveals largely distinct transcript- and protein-level responses to the environment in an intertidal mussel

Organismal responses to stressful environments are influenced by numerous transcript- and protein-level mechanisms, and the relationships between expression changes at these levels are not always straightforward. Here, we used paired transcriptomic and proteomic datasets from two previous studies from gill of the California mussel, Mytilus californianus, to explore how simultaneous transcript and protein abundance patterns may diverge under different environmental scenarios. Field-acclimatized mussels were sampled from two disparate intertidal sites; individuals from one site were subjected to three further treatments (common garden, low-intertidal or high-intertidal outplant) that vary in temperature and feeding time. Assessing 1519 genes shared between the two datasets revealed that both transcript and protein expression patterns differentiated the treatments at a global level, despite numerous underlying discrepancies. There were far more instances of differential expression between treatments in transcript only (1451) or protein only (226) than of the two levels shifting expression concordantly (68 instances). Upregulated expression of cilium-associated transcripts (likely related to feeding) was associated with relatively benign field treatments. In the most stressful treatment, transcripts, but not proteins, for several molecular chaperones (including heat shock proteins and endoplasmic reticulum chaperones) were more abundant, consistent with a threshold model for induction of translation of constitutively available mRNAs. Overall, these results suggest that the relative importance of transcript- and protein-level regulation (translation and/or turnover) differs among cellular functions and across specific microhabitats or environmental contexts. Furthermore, the degree of concordance between transcript and protein expression can vary across benign versus acutely stressful environmental conditions.

Conformational changes in the negative arm of the circadian clock correlate with dynamic interactomes involved in post-transcriptional regulation

Biology is tuned to the Earth's diurnal cycle by the circadian clock, a transcriptional/translational negative feedback loop that regulates physiology via transcriptional activation and other post-transcriptional mechanisms. We hypothesize that circadian post-transcriptional regulation might stem from conformational shifts in the intrinsically disordered proteins that comprise the negative arm of the feedback loop to coordinate variation in negative-arm-centered macromolecular complexes. This work demonstrates temporal conformational fluidity in the negative arm that correlates with 24-h variation in physiologically diverse macromolecular complex components in eukaryotic clock proteins. Short linear motifs on the negative-arm proteins that correspond with the interactors localized to disordered regions and known temporal phosphorylation sites suggesting changes in these macromolecular complexes could be due to conformational changes imparted by the temporal phospho-state. Interactors that oscillate in the macromolecular complexes over circadian time correlate with post-transcriptionally regulated proteins, highlighting how time-of-day variation in the negative-arm protein complexes may tune cellular physiology.

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.

The PAICE suite reveals circadian posttranscriptional timing of noncoding RNAs and spliceosome components in Mus musculus macrophages

Circadian rhythms broadly regulate physiological functions by tuning oscillations in the levels of mRNAs and proteins to the 24-h day/night cycle. Globally assessing which mRNAs and proteins are timed by the clock necessitates accurate recognition of oscillations in RNA and protein data, particularly in large omics data sets. Tools that employ fixed-amplitude models have previously been used to positive effect. However, the recognition of amplitude change in circadian oscillations required a new generation of analytical software to enhance the identification of these oscillations. To address this gap, we created the Pipeline for Amplitude Integration of Circadian Exploration suite. Here, we demonstrate the Pipeline for Amplitude Integration of Circadian Exploration suite's increased utility to detect circadian trends through the joint modeling of the Mus musculus macrophage transcriptome and proteome. Our enhanced detection confirmed extensive circadian posttranscriptional regulation in macrophages but highlighted that some of the reported discrepancy between mRNA and protein oscillations was due to noise in data. We further applied the Pipeline for Amplitude Integration of Circadian Exploration suite to investigate the circadian timing of noncoding RNAs, documenting extensive circadian timing of long noncoding RNAs and small nuclear RNAs, which control the recognition of mRNA in the spliceosome complex. By tracking oscillating spliceosome complex proteins using the PAICE suite, we noted that the clock broadly regulates the spliceosome, particularly the major spliceosome complex. As most of the above-noted rhythms had damped amplitude changes in their oscillations, this work highlights the importance of the PAICE suite in the thorough enumeration of oscillations in omics-scale datasets.

Venn diagram analysis overestimates the extent of circadian rhythm reprogramming

The circadian clock modulates key physiological processes in many organisms. This widespread role of circadian rhythms is typically characterized at the molecular level by profiling the transcriptome at multiple time points. Subsequent analysis identifies transcripts with altered rhythms between control and perturbed conditions, that is, are differentially rhythmic (DiffR). Commonly, Venn diagram analysis (VDA) compares lists of rhythmic transcripts to catalog transcripts with rhythms in both conditions, or that have gained or lost rhythms. However, unavoidable errors in rhythmicity detection propagate to the final DiffR classification resulting in overestimated DiffR. We show using artificial experiments on biological data that VDA indeed produces excessive false DiffR hits both in the presence and absence of true DiffR transcripts. We review and benchmark hypothesis testing and model selection approaches that instead compare circadian amplitude and phase of transcripts between the two conditions. These methods identify transcripts that 'gain', 'lose', 'change', or have the 'same' rhythms; the third category is missed by VDA. We reanalyzed three studies on the interplay between metabolism and the clock in the mouse liver that used VDA. We found not only fewer DiffR transcripts than originally reported, but VDA overlooked many relevant DiffR transcripts. Our analyses confirmed some and contradicted other conclusions in the original studies and also generated novel insights. Our conclusions equally apply to circadian studies using other omics technologies. We believe that avoiding Venn diagrams and using our convenient r-package comparerhythms will improve the reliability of analyses in chronobiology.

Tick-Tock Consider the Clock: The Influence of Circadian and External Cycles on Time of Day Variation in the Human Metabolome-A Review

The past decade has seen a large influx of work investigating time of day variation in different human biofluid and tissue metabolomes. The driver of this daily variation can be endogenous circadian rhythms driven by the central and/or peripheral clocks, or exogenous diurnal rhythms driven by behavioural and environmental cycles, which manifest as regular 24 h cycles of metabolite concentrations. This review, of all published studies to date, establishes the extent of daily variation with regard to the number and identity of 'rhythmic' metabolites observed in blood, saliva, urine, breath, and skeletal muscle. The probable sources driving such variation, in addition to what metabolite classes are most susceptible in adhering to or uncoupling from such cycles is described in addition to a compiled list of common rhythmic metabolites. The reviewed studies show that the metabolome undergoes significant time of day variation, primarily observed for amino acids and multiple lipid classes. Such 24 h rhythms, driven by various factors discussed herein, are an additional source of intra/inter-individual variation and are thus highly pertinent to all studies applying untargeted and targeted metabolomics platforms, particularly for the construction of biomarker panels. The potential implications are discussed alongside proposed minimum reporting criteria suggested to acknowledge time of day variation as a potential influence of results and to facilitate improved reproducibility.