Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations.

Across a range of biological processes, cells undergo coordinated changes in gene expression, resulting in transcriptome dynamics that unfold within a low-dimensional manifold. Single-cell RNA-sequencing (scRNA-seq) only measures temporal snapshots of gene expression. However, information on the underlying low-dimensional dynamics can be extracted using RNA velocity, which models unspliced and spliced RNA abundances to estimate the rate of change of gene expression. Available RNA velocity algorithms can be fragile and rely on heuristics that lack statistical control. Moreover, the estimated vector field is not dynamically consistent with the traversed gene expression manifold. Here, we develop a generative model of RNA velocity and a Bayesian inference approach that solves these problems. Our model couples velocity field and manifold estimation in a reformulated, unified framework, so as to coherently identify the parameters of an autonomous dynamical system. Focusing on the cell cycle, we implemented VeloCycle to study gene regulation dynamics on one-dimensional periodic manifolds and validated using live-imaging its ability to infer actual cell cycle periods. We benchmarked RNA velocity inference with sensitivity analyses and demonstrated one- and multiple-sample testing. We also conducted Markov chain Monte Carlo inference on the model, uncovering key relationships between gene-specific kinetics and our gene-independent velocity estimate. Finally, we applied VeloCycle to in vivo samples and in vitro genome-wide Perturb-seq, revealing regionally-defined proliferation modes in neural progenitors and the effect of gene knockdowns on cell cycle speed. Ultimately, VeloCycle expands the scRNA-seq analysis toolkit with a modular and statistically rigorous RNA velocity inference framework.

Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling.

Wearable biosensors and smartphone applications can measure physiological variables over multiple days in free-living conditions. We measure food and drink ingestion, glucose dynamics, physical activity, heart rate (HR), and heart rate variability (HRV) in 25 healthy participants over 14 days. We develop a Bayesian inference framework to learn personal parameters that quantify circadian rhythms and physiological responses to external stressors. Modeling the effects of ingestion events on glucose levels reveals that slower glucose decay kinetics elicit larger postprandial glucose spikes, and we uncover a circadian baseline rhythm for glucose with high amplitudes in some individuals. Physical activity and circadian rhythms explain as much as 40%-65% of the HR variance, whereas the variance explained for HRV is more heterogeneous across individuals. A more complex model incorporating activity, HR, and HRV explains up to 15% of additional glucose variability, highlighting the relevance of integrating multiple biosensors to better predict glucose dynamics.

Sex-dimorphic and age-dependent organization of 24-hour gene expression rhythms in humans.

The circadian clock modulates human physiology. However, the organization of tissue-specific gene expression rhythms and how these depend on age and sex is not defined in humans. We combined data from the Genotype-Tissue Expression (GTEx) project with an algorithm that assigns circadian phases to 914 donors, by integrating temporal information from multiple tissues in each individual, to identify messenger RNA (mRNA) rhythms in 46 tissues. Clock transcripts showed conserved timing relationships and tight synchrony across the body. mRNA rhythms varied in breadth, covering global and tissue-specific functions, including metabolic pathways and systemic responses. The clock structure was conserved across sexes and age groups. However, overall gene expression rhythms were highly sex-dimorphic and more sustained in females. Rhythmic programs generally dampened with age across the body.

Spatiotemporal Metabolic Liver Zonation and Consequences on Pathophysiology.

Hepatocytes are the main workers in the hepatic factory, managing metabolism of nutrients and xenobiotics, production and recycling of proteins, and glucose and lipid homeostasis. Division of labor between hepatocytes is critical to coordinate complex complementary or opposing multistep processes, similar to distributed tasks at an assembly line. This so-called metabolic zonation has both spatial and temporal components. Spatial distribution of metabolic function in hepatocytes of different lobular zones is necessary to perform complex sequential multistep metabolic processes and to assign metabolic tasks to the right environment. Moreover, temporal control of metabolic processes is critical to align required metabolic processes to the feeding and fasting cycles. Disruption of this complex spatiotemporal hepatic organization impairs key metabolic processes with both local and systemic consequences. Many metabolic diseases, such as nonalcoholic steatohepatitis and diabetes, are associated with impaired metabolic liver zonation. Recent technological advances shed new light on the spatiotemporal gene expression networks controlling liver function and how their deregulation may be involved in a large variety of diseases. We summarize the current knowledge about spatiotemporal metabolic liver zonation and consequences on liver pathobiology.

V-ATPase/TORC1-mediated ATFS-1 translation directs mitochondrial UPR activation in C. elegans.

To adapt mitochondrial function to the ever-changing intra- and extracellular environment, multiple mitochondrial stress response (MSR) pathways, including the mitochondrial unfolded protein response (UPRmt), have evolved. However, how the mitochondrial stress signal is sensed and relayed to UPRmt transcription factors, such as ATFS-1 in Caenorhabditis elegans, remains largely unknown. Here, we show that a panel of vacuolar H+-ATPase (v-ATPase) subunits and the target of rapamycin complex 1 (TORC1) activity are essential for the cytosolic relay of mitochondrial stress to ATFS-1 and for the induction of the UPRmt. Mechanistically, mitochondrial stress stimulates v-ATPase/Rheb-dependent TORC1 activation, subsequently promoting ATFS-1 translation. Increased translation of ATFS-1 upon mitochondrial stress furthermore relies on a set of ribosomal components but is independent of GCN-2/PEK-1 signaling. Finally, the v-ATPase and ribosomal subunits are required for mitochondrial surveillance and mitochondrial stress-induced longevity. These results reveal a v-ATPase-TORC1-ATFS-1 signaling pathway that links mitochondrial stress to the UPRmt through intimate crosstalks between multiple organelles.

Comprehensive analysis of the circadian nuclear and cytoplasmic transcriptome in mouse liver.

In eukaryotes, RNA is synthesised in the nucleus, spliced, and exported to the cytoplasm where it is translated and finally degraded. Any of these steps could be subject to temporal regulation during the circadian cycle, resulting in daily fluctuations of RNA accumulation and affecting the distribution of transcripts in different subcellular compartments. Our study analysed the nuclear and cytoplasmic, poly(A) and total transcriptomes of mouse livers collected over the course of a day. These data provide a genome-wide temporal inventory of enrichment in subcellular RNA, and revealed specific signatures of splicing, nuclear export and cytoplasmic mRNA stability related to transcript and gene lengths. Combined with a mathematical model describing rhythmic RNA profiles, we could test the rhythmicity of export rates and cytoplasmic degradation rates of approximately 1400 genes. With nuclear export times usually much shorter than cytoplasmic half-lives, we found that nuclear export contributes to the modulation and generation of rhythmic profiles of 10% of the cycling nuclear mRNAs. This study contributes to a better understanding of the dynamic regulation of the transcriptome during the day-night cycle.

Ribo-DT: An automated pipeline for inferring codon dwell times from ribosome profiling data.

Protein synthesis is an energy consuming process characterised as a pivotal and highly regulated step in gene expression. The net protein output is dictated by a combination of translation initiation, elongation and termination rates that have remained difficult to measure. Recently, the development of ribosome profiling has enabled the inference of translation parameters through modelling, as this method informs on the ribosome position along the mRNA. Here, we present an automated, reproducible and portable computational pipeline to infer relative single-codon and codon-pair dwell times as well as gene flux from raw ribosome profiling sequencing data. As a case study, we applied our workflow to a publicly available yeast ribosome profiling dataset consisting of 57 independent gene knockouts related to RNA and tRNA modifications. We uncovered the effects of those modifications on translation elongation and codon selection during decoding. In particular, knocking out mod5 and trm7 increases codon-specific dwell times which indicates their potential tRNA targets, and highlights effects of nucleotide modifications on ribosome decoding rate.

Comment on "Circadian rhythms in the absence of the clock gene Bmal1".

Ray et al (Reports, 14 February 2020, p. 800) recently claimed temperature-compensated, free-running mRNA oscillations in Bmal1 -/- liver slices and skin fibroblasts. We reanalyzed these data and found far fewer reproducible mRNA oscillations in this genotype. We also note errors and potentially inappropriate analyses.

The Effects of Time-Restricted Eating versus Standard Dietary Advice on Weight, Metabolic Health and the Consumption of Processed Food: A Pragmatic Randomised Controlled Trial in Community-Based Adults.

Weight loss is key to controlling the increasing prevalence of metabolic syndrome (MS) and its components, i.e., central obesity, hypertension, prediabetes and dyslipidaemia. The goals of our study were two-fold. First, we characterised the relationships between eating duration, unprocessed and processed food consumption and metabolic health. During 4 weeks of observation, 213 adults used a smartphone application to record food and drink consumption, which was annotated for food processing levels following the NOVA classification. Low consumption of unprocessed food and low physical activity showed significant associations with multiple MS components. Second, in a pragmatic randomised controlled trial, we compared the metabolic benefits of 12 h time-restricted eating (TRE) to standard dietary advice (SDA) in 54 adults with an eating duration > 14 h and at least one MS component. After 6 months, those randomised to TRE lost 1.6% of initial body weight (SD 2.9, p = 0.01), compared to the absence of weight loss with SDA (-1.1%, SD 3.5, p = 0.19). There was no significant difference in weight loss between TRE and SDA (between-group difference -0.88%, 95% confidence interval -3.1 to 1.3, p = 0.43). Our results show the potential of smartphone records to predict metabolic health and highlight that further research is needed to improve individual responses to TRE such as a shorter eating window or its actual clock time.

The circadian oscillator analysed at the single-transcript level.

The circadian clock is an endogenous and self-sustained oscillator that anticipates daily environmental cycles. While rhythmic gene expression of circadian genes is well-described in populations of cells, the single-cell mRNA dynamics of multiple core clock genes remain largely unknown. Here we use single-molecule fluorescence in situ hybridisation (smFISH) at multiple time points to measure pairs of core clock transcripts, Rev-erbα (Nr1d1), Cry1 and Bmal1, in mouse fibroblasts. The mean mRNA level oscillates over 24 h for all three genes, but mRNA numbers show considerable spread between cells. We develop a probabilistic model for multivariate mRNA counts using mixtures of negative binomials, which accounts for transcriptional bursting, circadian time and cell-to-cell heterogeneity, notably in cell size. Decomposing the mRNA variability into distinct noise sources shows that clock time contributes a small fraction of the total variability in mRNA number between cells. Thus, our results highlight the intrinsic biological challenges in estimating circadian phase from single-cell mRNA counts and suggest that circadian phase in single cells is encoded post-transcriptionally.

Oscillating and stable genome topologies underlie hepatic physiological rhythms during the circadian cycle.

The circadian clock drives extensive temporal gene expression programs controlling daily changes in behavior and physiology. In mouse liver, transcription factors dynamics, chromatin modifications, and RNA Polymerase II (PolII) activity oscillate throughout the 24-hour (24h) day, regulating the rhythmic synthesis of thousands of transcripts. Also, 24h rhythms in gene promoter-enhancer chromatin looping accompany rhythmic mRNA synthesis. However, how chromatin organization impinges on temporal transcription and liver physiology remains unclear. Here, we applied time-resolved chromosome conformation capture (4C-seq) in livers of WT and arrhythmic Bmal1 knockout mice. In WT, we observed 24h oscillations in promoter-enhancer loops at multiple loci including the core-clock genes Period1, Period2 and Bmal1. In addition, we detected rhythmic PolII activity, chromatin modifications and transcription involving stable chromatin loops at clock-output gene promoters representing key liver function such as glucose metabolism and detoxification. Intriguingly, these contacts persisted in clock-impaired mice in which both PolII activity and chromatin marks no longer oscillated. Finally, we observed chromatin interaction hubs connecting neighbouring genes showing coherent transcription regulation across genotypes. Thus, both clock-controlled and clock-independent chromatin topology underlie rhythmic regulation of liver physiology.

Systematic analysis of differential rhythmic liver gene expression mediated by the circadian clock and feeding rhythms.

The circadian clock and feeding rhythms are both important regulators of rhythmic gene expression in the liver. To further dissect the respective contributions of feeding and the clock, we analyzed differential rhythmicity of liver tissue samples across several conditions. We developed a statistical method tailored to compare rhythmic liver messenger RNA (mRNA) expression in mouse knockout models of multiple clock genes, as well as PARbZip output transcription factors (Hlf/Dbp/Tef). Mice were exposed to ad libitum or night-restricted feeding under regular light-dark cycles. During ad libitum feeding, genetic ablation of the core clock attenuated rhythmic-feeding patterns, which could be restored by the night-restricted feeding regimen. High-amplitude mRNA expression rhythms in wild-type livers were driven by the circadian clock, but rhythmic feeding also contributed to rhythmic gene expression, albeit with significantly lower amplitudes. We observed that Bmal1 and Cry1/2 knockouts differed in their residual rhythmic gene expression. Differences in mean expression levels between wild types and knockouts correlated with rhythmic gene expression in wild type. Surprisingly, in PARbZip knockout mice, the mean expression levels of PARbZip targets were more strongly impacted than their rhythms, potentially due to the rhythmic activity of the D-box-repressor NFIL3. Genes that lost rhythmicity in PARbZip knockouts were identified to be indirect targets. Our findings provide insights into the diurnal transcriptome in mouse liver as we identified the differential contributions of several core clock regulators. In addition, we gained more insights on the specific effects of the feeding-fasting cycle.

Space-time logic of liver gene expression at sub-lobular scale.

The mammalian liver is a central hub for systemic metabolic homeostasis. Liver tissue is spatially structured, with hepatocytes operating in repeating lobules, and sub-lobule zones performing distinct functions. The liver is also subject to extensive temporal regulation, orchestrated by the interplay of the circadian clock, systemic signals and feeding rhythms. However, liver zonation has previously been analysed as a static phenomenon, and liver chronobiology has been analysed at tissue-level resolution. Here, we use single-cell RNA-seq to investigate the interplay between gene regulation in space and time. Using mixed-effect models of messenger RNA expression and smFISH validations, we find that many genes in the liver are both zonated and rhythmic, and most of them show multiplicative space-time effects. Such dually regulated genes cover not only key hepatic functions such as lipid, carbohydrate and amino acid metabolism, but also previously unassociated processes involving protein chaperones. Our data also suggest that rhythmic and localized expression of Wnt targets could be explained by rhythmically expressed Wnt ligands from non-parenchymal cells near the central vein. Core circadian clock genes are expressed in a non-zonated manner, indicating that the liver clock is robust to zonation. Together, our scRNA-seq analysis reveals how liver function is compartmentalized spatio-temporally at the sub-lobular scale.

What determines eukaryotic translation elongation: recent molecular and quantitative analyses of protein synthesis.

Protein synthesis from mRNA is an energy-intensive and tightly controlled cellular process. Translation elongation is a well-coordinated, multifactorial step in translation that undergoes dynamic regulation owing to cellular state and environmental determinants. Recent studies involving genome-wide approaches have uncovered some crucial aspects of translation elongation including the mRNA itself and the nascent polypeptide chain. Additionally, these studies have fuelled quantitative and mathematical modelling of translation elongation. In this review, we provide a comprehensive overview of the key determinants of translation elongation. We discuss consequences of ribosome stalling or collision, and how the cells regulate translation in case of such events. Next, we review theoretical approaches and widely used mathematical models that have become an essential ingredient to interpret complex molecular datasets and study translation dynamics quantitatively. Finally, we review recent advances in live-cell reporter and related analysis techniques, to monitor the translation dynamics of single cells and single-mRNA molecules in real time.

How to tell time: advances in decoding circadian phase from omics snapshots.

The ability of organisms to keep track of external time, by means of the circadian clock interacting with the environment, is essential for health. The focus of this review is recent methods to detect the internal circadian time of an omics sample. Before reaching our main topic, we introduce the circadian clock, its hierarchical structure, and its main functions; we will also explain the notion of internal time, or circadian phase, and how it differs from the geophysical time. We then focus on the role played by the clock in the maintenance of human heath, in particular in the context of cancer. Thereafter, we analyze an important methodological question: how to infer the circadian phase of unlabeled omics snapshot measurements. Answering this question could both significantly increase our understanding of the circadian clock and allow the use of this knowledge in biomedical applications. We review existing methods, focusing on the more recent ones, following a historical trajectory. We explain the basic concepts underlying the methods, as well as some crucial technical aspects of each. We conclude by reporting how some of these methods have, more or less effectively, enabled furthering our understanding of the clock and given insights regarding potential biomedical applications.

Robust landscapes of ribosome dwell times and aminoacyl-tRNAs in response to nutrient stress in liver.

Translation depends on messenger RNA (mRNA)-specific initiation, elongation, and termination rates. While translation elongation is well studied in bacteria and yeast, less is known in higher eukaryotes. Here we combined ribosome and transfer RNA (tRNA) profiling to investigate the relations between translation elongation rates, (aminoacyl-) tRNA levels, and codon usage in mammals. We modeled codon-specific ribosome dwell times from ribosome profiling, considering codon pair interactions between ribosome sites. In mouse liver, the model revealed site- and codon-specific dwell times that differed from those in yeast, as well as pairs of adjacent codons in the P and A site that markedly slow down or speed up elongation. While translation efficiencies vary across diurnal time and feeding regimen, codon dwell times were highly stable and conserved in human. Measured tRNA levels correlated with codon usage and several tRNAs showed reduced aminoacylation, which was conserved in fasted mice. Finally, we uncovered that the longest codon dwell times could be explained by aminoacylation levels or high codon usage relative to tRNA abundance.

Sleep-wake-driven and circadian contributions to daily rhythms in gene expression and chromatin accessibility in the murine cortex.

The timing and duration of sleep results from the interaction between a homeostatic sleep-wake-driven process and a periodic circadian process, and involves changes in gene regulation and expression. Unraveling the contributions of both processes and their interaction to transcriptional and epigenomic regulatory dynamics requires sampling over time under conditions of unperturbed and perturbed sleep. We profiled mRNA expression and chromatin accessibility in the cerebral cortex of mice over a 3-d period, including a 6-h sleep deprivation (SD) on day 2. We used mathematical modeling to integrate time series of mRNA expression data with sleep-wake history, which established that a large proportion of rhythmic genes are governed by the homeostatic process with varying degrees of interaction with the circadian process, sometimes working in opposition. Remarkably, SD caused long-term effects on gene-expression dynamics, outlasting phenotypic recovery, most strikingly illustrated by a damped oscillation of most core clock genes, including Arntl/Bmal1, suggesting that enforced wakefulness directly impacts the molecular clock machinery. Chromatin accessibility proved highly plastic and dynamically affected by SD. Dynamics in distal regions, rather than promoters, correlated with mRNA expression, implying that changes in expression result from constitutively accessible promoters under the influence of enhancers or repressors. Serum response factor (SRF) was predicted as a transcriptional regulator driving immediate response, suggesting that SRF activity mirrors the build-up and release of sleep pressure. Our results demonstrate that a single, short SD has long-term aftereffects at the genomic regulatory level and highlights the importance of the sleep-wake distribution to diurnal rhythmicity and circadian processes.

Engineered signaling centers for the spatially controlled patterning of human pluripotent stem cells.

Signaling centers, localized groups of cells that secrete morphogens, play a key role in early development and organogenesis by orchestrating spatial cell fate patterning. Here we present a microfluidic approach that exposes human pluripotent stem cell (hPSC) colonies to spatiotemporally controlled morphogen gradients generated from artificial signaling centers. In response to a localized source of bone morphogenetic protein 4 (BMP4), hPSC colonies reproducibly break their intrinsic radial symmetry to produce distinct, axially arranged differentiation domains. Counteracting sources of the BMP antagonist NOGGIN enhance this spatial control of cell fate patterning. We also show how morphogen concentration and cell density affect the BMP response and germ layer patterning. These results demonstrate that the intrinsic capacity of stem cells for self-organization can be extrinsically controlled through the use of engineered signaling centers.

Memory and relatedness of transcriptional activity in mammalian cell lineages.

Phenotypically identical mammalian cells often display considerable variability in transcript levels of individual genes. How transcriptional activity propagates in cell lineages, and how this varies across genes is poorly understood. Here we combine live-cell imaging of short-lived transcriptional reporters in mouse embryonic stem cells with mathematical modelling to quantify the propagation of transcriptional activity over time and across cell generations in phenotypically homogenous cells. In sister cells we find mean transcriptional activity to be strongly correlated and transcriptional dynamics tend to be synchronous; both features control how quickly transcriptional levels in sister cells diverge in a gene-specific manner. Moreover, mean transcriptional activity is transmitted from mother to daughter cells, leading to multi-generational transcriptional memory and causing inter-family heterogeneity in gene expression.

Quantitative relationships between SMAD dynamics and target gene activation kinetics in single live cells.

The transduction of extracellular signals through signaling pathways that culminate in a transcriptional response is central to many biological processes. However, quantitative relationships between activities of signaling pathway components and transcriptional output of target genes remain poorly explored. Here we developed a dual bioluminescence imaging strategy allowing simultaneous monitoring of nuclear translocation of the SMAD4 and SMAD2 transcriptional activators upon TGF-ß stimulation, and the transcriptional response of the endogenous connective tissue growth factor (ctgf) gene. Using cell lines allowing to vary exogenous SMAD4/2 expression levels, we performed quantitative measurements of the temporal profiles of SMAD4/2 translocation and ctgf transcription kinetics in hundreds of individual cells at high temporal resolution. We found that while nuclear translocation efficiency had little impact on initial ctgf transcriptional activation, high total cellular SMAD4 but not SMAD2 levels increased the probability of cells to exhibit a sustained ctgf transcriptional response. The approach we present here allows time-resolved single cell quantification of transcription factor dynamics and transcriptional responses and thereby sheds light on the quantitative relationship between SMADs and target gene responses.