62 research outputs found

    Sleepy Genes

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    A non-circadian role for clock-genes in sleep homeostasis:a strain comparison

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    BACKGROUND: We have previously reported that the expression of circadian clock-genes increases in the cerebral cortex after sleep deprivation (SD) and that the sleep rebound following SD is attenuated in mice deficient for one or more clock-genes. We hypothesized that besides generating circadian rhythms, clock-genes also play a role in the homeostatic regulation of sleep. Here we follow the time course of the forebrain changes in the expression of the clock-genes period (per)-1, per2, and of the clock-controlled gene albumin D-binding protein (dbp) during a 6 h SD and subsequent recovery sleep in three inbred strains of mice for which the homeostatic sleep rebound following SD differs. We reasoned that if clock genes are functionally implicated in sleep homeostasis then the SD-induced changes in gene expression should vary according to the genotypic differences in the sleep rebound. RESULTS: In all three strains per expression was increased when animals were kept awake but the rate of increase during the SD as well as the relative increase in per after 6 h SD were highest in the strain for which the sleep rebound was smallest; i.e., DBA/2J (D2). Moreover, whereas in the other two strains per1 and per2 reverted to control levels with recovery sleep, per2 expression specifically, remained elevated in D2 mice. dbp expression increased during the light period both during baseline and during SD although levels were reduced during the latter condition compared to baseline. In contrast to per2, dbp expression reverted to control levels with recovery sleep in D2 only, whereas in the two other strains expression remained decreased. CONCLUSION: These findings support and extend our previous findings that clock genes in the forebrain are implicated in the homeostatic regulation of sleep and suggest that sustained, high levels of per2 expression may negatively impact recovery sleep

    Assessment of a non-invasive high-throughput classifier for behaviours associated with sleep and wake in mice

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    This work presents a non-invasive high-throughput system for automatically detecting characteristic behaviours in mice over extended periods of time, useful for phenotyping experiments. The system classifies time intervals on the order of 2 to 4 seconds as corresponding to motions consistent with either active wake or inactivity associated with sleep. A single Polyvinylidine Difluoride (PVDF) sensor on the cage floor generates signals from motion resulting in pressure. This paper develops a linear classifier based on robust features extracted from normalized power spectra and autocorrelation functions, as well as novel features from the collapsed average (autocorrelation of complex spectrum), which characterize transient and periodic properties of the signal envelope. Performance is analyzed through an experiment comparing results from direct human observation and classification of the different behaviours with an automatic classifier used in conjunction with this system. Experimental results from over 28.5 hours of data from 4 mice indicate a 94% classification rate relative to the human observations. Examples of sequential classifications (2 second increments) over transition regions between sleep and wake behaviour are also presented to demonstrate robust performance to signal variation and explain performance limitations

    Oligosaccharide Binding Proteins from Bifidobacterium longum subsp. infantis Reveal a Preference for Host Glycans

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    Bifidobacterium longum subsp. infantis (B. infantis) is a common member of the infant intestinal microbiota, and it has been characterized by its foraging capacity for human milk oligosaccharides (HMO). Its genome sequence revealed an overabundance of the Family 1 of solute binding proteins (F1SBPs), part of ABC transporters and associated with the import of oligosaccharides. In this study we have used the Mammalian Glycan Array to determine the specific affinities of these proteins. This was correlated with binding protein expression induced by different prebiotics including HMO. Half of the F1SBPs in B. infantis were determined to bind mammalian oligosaccharides. Their affinities included different blood group structures and mucin oligosaccharides. Related to HMO, other proteins were specific for oligomers of lacto-N-biose (LNB) and polylactosamines with different degrees of fucosylation. Growth on HMO induced the expression of specific binding proteins that import HMO isomers, but also bind blood group and mucin oligosaccharides, suggesting coregulated transport mechanisms. The prebiotic inulin induced other family 1 binding proteins with affinity for intestinal glycans. Most of the host glycan F1SBPs in B. infantis do not have homologs in other bifidobacteria. Finally, some of these proteins were found to be adherent to intestinal epithelial cells in vitro. In conclusion, this study represents further evidence for the particular adaptations of B. infantis to the infant gut environment, and helps to understand the molecular mechanisms involved in this process

    Pre-Micro RNA Signatures Delineate Stages of Endothelial Cell Transformation in Kaposi Sarcoma

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    MicroRNAs (miRNA) have emerged as key regulators of cell lineage differentiation and cancer. We used precursor miRNA profiling by a novel real-time QPCR method (i) to define progressive stages of endothelial cell transformation cumulating in Kaposi sarcoma (KS) and (ii) to identify specific miRNAs that serve as biomarkers for tumor progression. We were able to compare primary patient biopsies to well-established culture and mouse tumor models. Loss of mir-221 and gain of mir-15 expression demarked the transition from merely immortalized to fully tumorigenic endothelial cells. Mir-140 and Kaposi sarcoma–associated herpesvirus viral miRNAs increased linearly with the degree of transformation. Mir-24 emerged as a biomarker specific for KS

    Whole-genome sequencing reveals host factors underlying critical COVID-19

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease
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