Cortical miR-709 links glutamatergic signaling to NREM sleep EEG slow waves in an activity-dependent manner.

MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression that have been implicated in a plethora of neuronal processes. Nevertheless, their role in regulating brain activity in the context of sleep has so far received little attention. To test their involvement, we deleted mature miRNAs in post-mitotic neurons at two developmental ages, i.e., in early adulthood using conditional Dicer knockout (cKO) mice and in adult mice using an inducible conditional Dicer cKO (icKO) line. In both models, electroencephalographic (EEG) activity was affected and the response to sleep deprivation (SD) altered; while the rapid-eye-movement sleep (REMS) rebound was compromised in both, the increase in EEG delta (1 to 4 Hz) power during non-REMS (NREMS) was smaller in cKO mice and larger in icKO mice compared to controls. We subsequently investigated the effects of SD on the forebrain miRNA transcriptome and found that the expression of 48 miRNAs was affected, and in particular that of the activity-dependent miR-709. In vivo inhibition of miR-709 in the brain increased EEG power during NREMS in the slow-delta (0.75 to 1.75 Hz) range, particularly after periods of prolonged wakefulness. Transcriptome analysis of primary cortical neurons in vitro revealed that miR-709 regulates genes involved in glutamatergic neurotransmission. A subset of these genes was also affected in the cortices of sleep-deprived, miR-709-inhibited mice. Our data implicate miRNAs in the regulation of EEG activity and indicate that miR-709 links neuronal activity during wakefulness to brain synchrony during sleep through the regulation of glutamatergic signaling.

Assessment of the Cardiac Noncoding Transcriptome by Single-Cell RNA Sequencing Identifies FIXER, a Conserved Profibrogenic Long Noncoding RNA.

BACKGROUND: Cardiac fibroblasts have crucial roles in the heart. In particular, fibroblasts differentiate into myofibroblasts in the damaged myocardium, contributing to scar formation and interstitial fibrosis. Fibrosis is associated with heart dysfunction and failure. Myofibroblasts therefore represent attractive therapeutic targets. However, the lack of myofibroblast-specific markers has precluded the development of targeted therapies. In this context, most of the noncoding genome is transcribed into long noncoding RNAs (lncRNAs). A number of lncRNAs have pivotal functions in the cardiovascular system. lncRNAs are globally more cell-specific than protein-coding genes, supporting their importance as key determinants of cell identity. METHODS: In this study, we evaluated the value of the lncRNA transcriptome in very deep single-cell RNA sequencing. We profiled the lncRNA transcriptome in cardiac nonmyocyte cells after infarction and probed heterogeneity in the fibroblast and myofibroblast populations. In addition, we searched for subpopulation-specific markers that can constitute novel targets in therapy for heart disease. RESULTS: We demonstrated that cardiac cell identity can be defined by the sole expression of lncRNAs in single-cell experiments. In this analysis, we identified lncRNAs enriched in relevant myofibroblast subpopulations. Selecting 1 candidate we named FIXER (fibrogenic LOX-locus enhancer RNA), we showed that its silencing limits fibrosis and improves heart function after infarction. Mechanitically, FIXER interacts with CBX4, an E3 SUMO protein ligase and transcription factor, guiding CBX4 to the promoter of the transcription factor RUNX1 to control its expression and, consequently, the expression of a fibrogenic gene program.. FIXER is conserved in humans, supporting its translational value. CONCLUSIONS: Our results demonstrated that lncRNA expression is sufficient to identify the various cell types composing the mammalian heart. Focusing on cardiac fibroblasts and their derivatives, we identified lncRNAs uniquely expressed in myofibroblasts. In particular, the lncRNA FIXER represents a novel therapeutic target for cardiac fibrosis.

Multiomics reveals multilevel control of renal and systemic metabolism by the renal tubular circadian clock.

Circadian rhythmicity in renal function suggests rhythmic adaptations in renal metabolism. To decipher the role of the circadian clock in renal metabolism, we studied diurnal changes in renal metabolic pathways using integrated transcriptomic, proteomic, and metabolomic analysis performed on control mice and mice with an inducible deletion of the circadian clock regulator Bmal1 in the renal tubule (cKOt). With this unique resource, we demonstrated that approximately 30% of RNAs, approximately 20% of proteins, and approximately 20% of metabolites are rhythmic in the kidneys of control mice. Several key metabolic pathways, including NAD+ biosynthesis, fatty acid transport, carnitine shuttle, and ß-oxidation, displayed impairments in kidneys of cKOt mice, resulting in perturbed mitochondrial activity. Carnitine reabsorption from primary urine was one of the most affected processes with an approximately 50% reduction in plasma carnitine levels and a parallel systemic decrease in tissue carnitine content. This suggests that the circadian clock in the renal tubule controls both kidney and systemic physiology.

A combination of plasma membrane sterol biosynthesis and autophagy is required for shade-induced hypocotyl elongation.

Plant growth ultimately depends on fixed carbon, thus the available light for photosynthesis. Due to canopy light absorption properties, vegetative shade combines low blue (LB) light and a low red to far-red ratio (LRFR). In shade-avoiding plants, these two conditions independently trigger growth adaptations to enhance light access. However, how these conditions, differing in light quality and quantity, similarly promote hypocotyl growth remains unknown. Using RNA sequencing we show that these two features of shade trigger different transcriptional reprogramming. LB induces starvation responses, suggesting a switch to a catabolic state. Accordingly, LB promotes autophagy. In contrast, LRFR induced anabolism including expression of sterol biosynthesis genes in hypocotyls in a manner dependent on PHYTOCHROME-INTERACTING FACTORs (PIFs). Genetic analyses show that the combination of sterol biosynthesis and autophagy is essential for hypocotyl growth promotion in vegetative shade. We propose that vegetative shade enhances hypocotyl growth by combining autophagy-mediated recycling and promotion of specific lipid biosynthetic processes.

Plasma triacylglycerols are biomarkers of ß-cell function in mice and humans.

OBJECTIVES: To find plasma biomarkers prognostic of type 2 diabetes, which could also inform on pancreatic ß-cell deregulations or defects in the function of insulin target tissues. METHODS: We conducted a systems biology approach to characterize the plasma lipidomes of C57Bl/6J, DBA/2J, and BALB/cJ mice under different nutritional conditions, as well as their pancreatic islet and liver transcriptomes. We searched for correlations between plasma lipids and tissue gene expression modules. RESULTS: We identified strong correlation between plasma triacylglycerols (TAGs) and islet gene modules that comprise key regulators of glucose- and lipid-regulated insulin secretion and of the insulin signaling pathway, the two top hits were Gck and Abhd6 for negative and positive correlations, respectively. Correlations were also found between sphingomyelins and islet gene modules that overlapped in part with the gene modules correlated with TAGs. In the liver, the gene module most strongly correlated with plasma TAGs was enriched in mRNAs encoding fatty acid and carnitine transporters as well as multiple enzymes of the ß-oxidation pathway. In humans, plasma TAGs also correlated with the expression of several of the same key regulators of insulin secretion and the insulin signaling pathway identified in mice. This cross-species comparative analysis further led to the identification of PITPNC1 as a candidate regulator of glucose-stimulated insulin secretion. CONCLUSION: TAGs emerge as biomarkers of a liver-to-ß-cell axis that links hepatic ß-oxidation to ß-cell functional mass and insulin secretion.

Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes.

Most research on human pancreatic islets is conducted on samples obtained from normoglycaemic or diseased brain-dead donors and thus cannot accurately describe the molecular changes of pancreatic islet beta cells as they progress towards a state of deficient insulin secretion in type 2 diabetes (T2D). Here, we conduct a comprehensive multi-omics analysis of pancreatic islets obtained from metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum, from normoglycemia to T2D. We find that islet pools isolated from surgical samples by laser-capture microdissection display remarkably more heterogeneous transcriptomic and proteomic profiles in patients with diabetes than in non-diabetic controls. The differential regulation of islet gene expression is already observed in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive, but disharmonic, remodelling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or transdifferentiation stages in T2D. Furthermore, through integration of islet transcriptomics with preoperative blood plasma lipidomics, we define the relative importance of gene coexpression modules and lipids that are positively or negatively associated with HbA1c levels, pointing to potential prognostic markers.

Contribution of exome sequencing to the identification of genes involved in the response to clopidogrel in cardiovascular patients.

BACKGROUND: On-clopidogrel platelet reactivity (PR) is associated with the risk of thrombotic or bleeding event in selected populations of high-risk patients. PR is a highly heritable phenotype and a few variants of cytochrome genes, essentially CYP2C19, are associated with PR but only explain 5% to 12% of the variability. OBJECTIVE: The aim of this study is to delineate genetic determinants of on-clopidogrel PR using high-throughput sequencing. METHODS: We performed a whole exome sequencing of 96 low- and matched high-PR patients in a discovery cohort. Exomes from genes with variants significantly associated with PR were sequenced in 96 low- and matched high-PR patients from an independent replication cohort. RESULTS: We identified 585 variants in 417 genes with an adjusted P value < .05. In the replication cohort, all top variants including CYP2C8, CYP2C18, and CYP2C19 from the discovery population were found again. An original network analysis identified several candidate genes of potential interest such as a regulator of PI3K, a key actor in the downstream signaling pathway of the P2Y12 receptor. CONCLUSION: This study emphasizes the role of CYP-related genes as major regulators of clopidogrel response, including the poorly investigated CYP2C8 and CYP2C18.

Use of preclinical models to identify markers of type 2 diabetes susceptibility and novel regulators of insulin secretion - A step towards precision medicine.

BACKGROUND: Progression from pre-diabetes to type 2 diabetes (T2D) and from T2D to insulin requirement proceeds at very heterogenous rates among patient populations, and the risk of developing different types of secondary complications is also different between patients. The diagnosis of pre-diabetes and T2D solely based on blood glucose measurements cannot capture this heterogeneity, thereby preventing proposition of therapeutic strategies adapted to individual needs and pathogenetic mechanisms. There is, thus, a need to identify novel means to stratify patient populations based on a molecular knowledge of the diverse underlying causes of the disease. Such knowledge would form the basis for a precision medicine approach to preventing and treating T2D according to the need of identified patient subgroups as well as allowing better follow up of pharmacological treatment. SCOPE OF REVIEW: Here, we review a systems biology approach that aims at identifying novel biomarkers for T2D susceptibility and identifying novel beta-cell and insulin target tissue genes that link the selected plasma biomarkers with insulin secretion and insulin action. This work was performed as part of two Innovative Medicine Initiative projects. The focus of the review will be on the use of preclinical models to find biomarker candidates for T2D prediction and novel regulators of beta-cell function. We will demonstrate that the study of mice with different genetic architecture and widely different adaptation to metabolic stress can be a powerful approach to identify biomarkers of T2D susceptibility in humans or for the identification of so far unrecognized genes controlling beta-cell function. MAJOR CONCLUSIONS: The examples developed in this review will highlight the power of the systems biology approach, in particular as it allowed the discovery of dihydroceramide as a T2D biomarker candidate in mice and humans and the identification and characterization of novel regulators of beta-cell function.

System analysis of cross-talk between nuclear receptors reveals an opposite regulation of the cell cycle by LXR and FXR in human HepaRG liver cells.

Transcriptional regulations exert a critical control of metabolic homeostasis. In particular, the nuclear receptors (NRs) are involved in regulating numerous pathways of the intermediate metabolism. The purpose of the present study was to explore in liver cells the interconnectedness between three of them, LXR, FXR, and PPARα, all three known to act on lipid and glucose metabolism, and also on inflammation. The human cell line HepaRG was selected for its best proximity to human primary hepatocytes. Global gene expression of differentiated HepaRG cells was assessed after 4 hours and 24 hours of exposure to GW3965 (LXR agonist), GW7647 (PPARα agonist), and GW4064 and CDCA (FXR synthetic and natural agonist, respectively). Our work revealed that, contrary to our expectations, NR specificity is largely present at the level of target genes, with a smaller than expected overlap of the set of genes targeted by the different NRs. It also highlighted the much broader activity of the synthetic FXR ligand compared to CDCA. More importantly, our results revealed that activation of FXR has a pro-proliferative effect and decreases the number of tetraploid (or binucleated) hepatocytes, while LXR inhibits the cell cycle progression, inducing hepatocyte differentiation and an increase in tetraploidism. Conclusion: these results highlight the importance of analyzing the different NR activities in a context allowing a direct confrontation of each receptor outcome, and reveals the opposite role of FXR and LXR in hepatocyte cells division and maturation.

Sensory neuron lineage mapping and manipulation in the Drosophila olfactory system.

Nervous systems exhibit myriad cell types, but understanding how this diversity arises is hampered by the difficulty to visualize and genetically-probe specific lineages, especially at early developmental stages prior to expression of unique molecular markers. Here, we use a genetic immortalization method to analyze the development of sensory neuron lineages in the Drosophila olfactory system, from their origin to terminal differentiation. We apply this approach to define a fate map of nearly all olfactory lineages and refine the model of temporal patterns of lineage divisions. Taking advantage of a selective marker for the lineage that gives rise to Or67d pheromone-sensing neurons and a genome-wide transcription factor RNAi screen, we identify the spatial and temporal requirements for Pointed, an ETS family member, in this developmental pathway. Transcriptomic analysis of wild-type and Pointed-depleted olfactory tissue reveals a universal requirement for this factor as a switch-like determinant of fates in these sensory lineages.

Systems biology of the IMIDIA biobank from organ donors and pancreatectomised patients defines a novel transcriptomic signature of islets from individuals with type 2 diabetes.

AIMS/HYPOTHESIS: Pancreatic islet beta cell failure causes type 2 diabetes in humans. To identify transcriptomic changes in type 2 diabetic islets, the Innovative Medicines Initiative for Diabetes: Improving beta-cell function and identification of diagnostic biomarkers for treatment monitoring in Diabetes (IMIDIA) consortium ( www.imidia.org ) established a comprehensive, unique multicentre biobank of human islets and pancreas tissues from organ donors and metabolically phenotyped pancreatectomised patients (PPP). METHODS: Affymetrix microarrays were used to assess the islet transcriptome of islets isolated either by enzymatic digestion from 103 organ donors (OD), including 84 non-diabetic and 19 type 2 diabetic individuals, or by laser capture microdissection (LCM) from surgical specimens of 103 PPP, including 32 non-diabetic, 36 with type 2 diabetes, 15 with impaired glucose tolerance (IGT) and 20 with recent-onset diabetes (<1 year), conceivably secondary to the pancreatic disorder leading to surgery (type 3c diabetes). Bioinformatics tools were used to (1) compare the islet transcriptome of type 2 diabetic vs non-diabetic OD and PPP as well as vs IGT and type 3c diabetes within the PPP group; and (2) identify transcription factors driving gene co-expression modules correlated with insulin secretion ex vivo and glucose tolerance in vivo. Selected genes of interest were validated for their expression and function in beta cells. RESULTS: Comparative transcriptomic analysis identified 19 genes differentially expressed (false discovery rate ≤0.05, fold change ≥1.5) in type 2 diabetic vs non-diabetic islets from OD and PPP. Nine out of these 19 dysregulated genes were not previously reported to be dysregulated in type 2 diabetic islets. Signature genes included TMEM37, which inhibited Ca2+-influx and insulin secretion in beta cells, and ARG2 and PPP1R1A, which promoted insulin secretion. Systems biology approaches identified HNF1A, PDX1 and REST as drivers of gene co-expression modules correlated with impaired insulin secretion or glucose tolerance, and 14 out of 19 differentially expressed type 2 diabetic islet signature genes were enriched in these modules. None of these signature genes was significantly dysregulated in islets of PPP with impaired glucose tolerance or type 3c diabetes. CONCLUSIONS/INTERPRETATION: These studies enabled the stringent definition of a novel transcriptomic signature of type 2 diabetic islets, regardless of islet source and isolation procedure. Lack of this signature in islets from PPP with IGT or type 3c diabetes indicates differences possibly due to peculiarities of these hyperglycaemic conditions and/or a role for duration and severity of hyperglycaemia. Alternatively, these transcriptomic changes capture, but may not precede, beta cell failure.

Molecular phenotyping of multiple mouse strains under metabolic challenge uncovers a role for Elovl2 in glucose-induced insulin secretion.

OBJECTIVE: In type 2 diabetes (T2D), pancreatic ß cells become progressively dysfunctional, leading to a decline in insulin secretion over time. In this study, we aimed to identify key genes involved in pancreatic beta cell dysfunction by analyzing multiple mouse strains in parallel under metabolic stress. METHODS: Male mice from six commonly used non-diabetic mouse strains were fed a high fat or regular chow diet for three months. Pancreatic islets were extracted and phenotypic measurements were recorded at 2 days, 10 days, 30 days, and 90 days to assess diabetes progression. RNA-Seq was performed on islet tissue at each time-point and integrated with the phenotypic data in a network-based analysis. RESULTS: A module of co-expressed genes was selected for further investigation as it showed the strongest correlation to insulin secretion and oral glucose tolerance phenotypes. One of the predicted network hub genes was Elovl2, encoding Elongase of very long chain fatty acids 2. Elovl2 silencing decreased glucose-stimulated insulin secretion in mouse and human ß cell lines. CONCLUSION: Our results suggest a role for Elovl2 in ensuring normal insulin secretory responses to glucose. Moreover, the large comprehensive dataset and integrative network-based approach provides a new resource to dissect the molecular etiology of ß cell failure under metabolic stress.

Plasma Dihydroceramides Are Diabetes Susceptibility Biomarker Candidates in Mice and Humans.

Plasma metabolite concentrations reflect the activity of tissue metabolic pathways and their quantitative determination may be informative about pathogenic conditions. We searched for plasma lipid species whose concentrations correlate with various parameters of glucose homeostasis and susceptibility to type 2 diabetes (T2D). Shotgun lipidomic analysis of the plasma of mice from different genetic backgrounds, which develop a pre-diabetic state at different rates when metabolically stressed, led to the identification of a group of sphingolipids correlated with glucose tolerance and insulin secretion. Quantitative analysis of these and closely related lipids in the plasma of individuals from two population-based prospective cohorts revealed that specific long-chain fatty-acid-containing dihydroceramides were significantly elevated in the plasma of individuals who will progress to diabetes up to 9 years before disease onset. These lipids may serve as early biomarkers of, and help identify, metabolic deregulation in the pathogenesis of T2D.

A neuron-specific deletion of the microRNA-processing enzyme DICER induces severe but transient obesity in mice.

MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression post-transcriptionally. MiRNAs are implicated in various biological processes associated with obesity, including adipocyte differentiation and lipid metabolism. We used a neuronal-specific inhibition of miRNA maturation in adult mice to study the consequences of miRNA loss on obesity development. Camk2a-CreERT2 (Cre+) and floxed Dicer (Dicerlox/lox) mice were crossed to generate tamoxifen-inducible conditional Dicer knockouts (cKO). Vehicle- and/or tamoxifen-injected Cre+;Dicerlox/lox and Cre+;Dicer+/+ served as controls. Four cohorts were used to a) measure body composition, b) follow food intake and body weight dynamics, c) evaluate basal metabolism and effects of food deprivation, and d) assess the brain transcriptome consequences of miRNA loss. cKO mice developed severe obesity and gained 18 g extra weight over the 5 weeks following tamoxifen injection, mainly due to increased fat mass. This phenotype was highly reproducible and observed in all 38 cKO mice recorded and in none of the controls, excluding possible effects of tamoxifen or the non-induced transgene. Development of obesity was concomitant with hyperphagia, increased food efficiency, and decreased activity. Surprisingly, after reaching maximum body weight, obese cKO mice spontaneously started losing weight as rapidly as it was gained. Weight loss was accompanied by lowered O2-consumption and respiratory-exchange ratio. Brain transcriptome analyses in obese mice identified several obesity-related pathways (e.g. leptin, somatostatin, and nemo-like kinase signaling), as well as genes involved in feeding and appetite (e.g. Pmch, Neurotensin) and in metabolism (e.g. Bmp4, Bmp7, Ptger1, Cox7a1). A gene cluster with anti-correlated expression in the cerebral cortex of post-obese compared to obese mice was enriched for synaptic plasticity pathways. While other studies have identified a role for miRNAs in obesity, we here present a unique model that allows for the study of processes involved in reversing obesity. Moreover, our study identified the cortex as a brain area important for body weight homeostasis.

Malaria haplotype frequency estimation.

We present a Bayesian approach for estimating the relative frequencies of multi-single nucleotide polymorphism (SNP) haplotypes in populations of the malaria parasite Plasmodium falciparum by using microarray SNP data from human blood samples. Each sample comes from a malaria patient and contains one or several parasite clones that may genetically differ. Samples containing multiple parasite clones with different genetic markers pose a special challenge. The situation is comparable with a polyploid organism. The data from each blood sample indicates whether the parasites in the blood carry a mutant or a wildtype allele at various selected genomic positions. If both mutant and wildtype alleles are detected at a given position in a multiply infected sample, the data indicates the presence of both alleles, but the ratio is unknown. Thus, the data only partially reveals which specific combinations of genetic markers (i.e. haplotypes across the examined SNPs) occur in distinct parasite clones. In addition, SNP data may contain errors at non-negligible rates. We use a multinomial mixture model with partially missing observations to represent this data and a Markov chain Monte Carlo method to estimate the haplotype frequencies in a population. Our approach addresses both challenges, multiple infections and data errors.