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Low-temperature carbon utilization is regulated by novel gene activity in the heart of a hibernating mammal.

ABSTRACT: Hibernation is a physiological adaptation characterized by dramatic decreases in heart rate, body temperature, and metabolism, resulting in long-term dormancy. Hibernating mammals survive for periods up to 6 mo in the absence of food by minimizing carbohydrate catabolism and using triglyceride stores as their primary source of fuel. The cellular and molecular mechanisms underlying the changes from a state of activity to the hibernating state are poorly understood; however, the selective expression of genes offers one level of control. To address this problem, we used a differential gene expression screen to identify genes that are responsible for the physiological characteristics of hibernation in the heart of the thirteen-lined ground squirrel (Spermophilus tridecemlineatus). Here, we report that genes for pancreatic lipase and pyruvate dehydrogenase kinase isozyme 4 are up-regulated in the heart during hibernation. Pancreatic lipase is normally expressed exclusively in the pancreas, but when expressed in the hibernating heart it liberates fatty acids from triglycerides at temperatures as low as 0 degreesC. Pyruvate dehydrogenase kinase isozyme 4 inhibits carbohydrate oxidation and depresses metabolism by preventing the conversion of pyruvate to Ac-CoA. The resulting anaerobic glycolysis and low-temperature lipid catabolism provide evidence that adaptive changes in cardiac physiology are controlled by the differential expression of genes during hibernation.

SUBMITTER: Andrews MT

PROVIDER: S-EPMC20986 | biostudies-literature | 1998 Jul

REPOSITORIES: biostudies-literature

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Low-temperature carbon utilization is regulated by novel gene activity in the heart of a hibernating mammal.

Andrews M T MT Squire T L TL Bowen C M CM Rollins M B MB

Proceedings of the National Academy of Sciences of the United States of America 19980701 14

Hibernation is a physiological adaptation characterized by dramatic decreases in heart rate, body temperature, and metabolism, resulting in long-term dormancy. Hibernating mammals survive for periods up to 6 mo in the absence of food by minimizing carbohydrate catabolism and using triglyceride stores as their primary source of fuel. The cellular and molecular mechanisms underlying the changes from a state of activity to the hibernating state are poorly understood; however, the selective expressi ...[more]

PMID: 9653197

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Project description:Hibernation is a physiological and behavioral phenotype that minimizes energy expenditure. Hibernators cycle between profound depression and rapid hyperactivation of multiple physiological processes, challenging our concept of mammalian homeostasis. How the hibernator orchestrates and survives these extremes while maintaining cell to organismal viability is unknown. Here, we enhance the genome integrity and annotation of a model hibernator, the 13-lined ground squirrel. Our new assembly brings this genome to near chromosome-level contiguity and adds thousands of previously unannotated genes. These new genomic resources were used to identify 6,505 hibernation-related, differentially-expressed and processed transcripts using RNA-seq data from three brain regions in animals whose physiological status was precisely defined using body temperature telemetry. A software tool, squirrelBox, was developed to foster further data analyses and visualization. SquirrelBox includes a comprehensive toolset for rapid visualization of gene level and cluster group dynamics, sequence scanning of k-mer and domains, and interactive exploration of gene lists. Using these new tools and data, we deconvolute seasonal from temperature-dependent effects on the brain transcriptome during hibernation for the first time, highlighting the importance of carefully timed samples for studies of differential gene expression in hibernation. The identified genes include a regulatory network of RNA binding proteins that are dynamic in hibernation along with the composition of the RNA pool. In addition to passive effects of temperature, we provide evidence for regulated transcription and RNA turnover during hibernation. Significant alternative splicing, largely temperature dependent, also occurs during hibernation. These findings form a crucial first step and provide a roadmap for future work toward defining novel mechanisms of tissue protection and metabolic depression that may 1 day be applied toward improving human health.

Project description:Mammalian hibernation presents a unique opportunity to study naturally occurring neuroprotection. Hibernating ground squirrels undergo rapid and extreme physiological changes in body temperature, oxygen consumption, and heart rate without suffering neurological damage from ischemia and reperfusion injury. Different brain regions show markedly different activity during the torpor/arousal cycle: the cerebral cortex shows activity only during the periodic returns to normothermia, while the hypothalamus is active over the entire temperature range. Therefore, region-specific neuroprotective strategies must exist to permit this compartmentalized spectrum of activity. In this study, we use the Illumina HiSeq platform to compare the transcriptomes of these two brain regions at four collection points across the hibernation season: April Active, October Active, Torpor, and IBA. In the cerebral cortex, 1,085 genes were found to be differentially expressed across collection points, while 1,063 genes were differentially expressed in the hypothalamus. Comparison of these transcripts indicates that the cerebral cortex and hypothalamus implement very different strategies during hibernation, showing less than 20% of these differentially expressed genes in common. The cerebral cortex transcriptome shows evidence of remodeling and plasticity during hibernation, including transcripts for the presynaptic cytomatrix proteins bassoon and piccolo, and extracellular matrix components, including laminins and collagens. Conversely, the hypothalamic transcriptome displays upregulation of transcripts involved in damage response signaling and protein turnover during hibernation, including the DNA damage repair gene RAD50 and ubiquitin E3 ligases UBR1 and UBR5. Additionally, the hypothalamus transcriptome also provides evidence of potential mechanisms underlying the hibernation phenotype, including feeding and satiety signaling, seasonal timing mechanisms, and fuel utilization. This study provides insight into potential neuroprotective strategies and hibernation control mechanisms, and also specifically shows that the hibernator brain exhibits both seasonal and regional differences in mRNA expression.

Project description:The miniaturization and affordability of new technology is driving a biologging revolution in wildlife ecology with use of animal-borne data logging devices. Among many new biologging technologies, accelerometers are emerging as key tools for continuously recording animal behavior. Yet a critical, but under-acknowledged consideration in biologging is the trade-off between sampling rate and sampling duration, created by battery- (or memory-) related sampling constraints. This is especially acute among small animals, causing most researchers to sample at high rates for very limited durations. Here, we show that high accuracy in behavioral classification is achievable when pairing low-frequency acceleration recordings with temperature. We conducted 84 hr of direct behavioral observations on 67 free-ranging red squirrels (200-300 g) that were fitted with accelerometers (2 g) recording tri-axial acceleration and temperature at 1 Hz. We then used a random forest algorithm and a manually created decision tree, with variable sampling window lengths, to associate observed behavior with logger recorded acceleration and temperature. Finally, we assessed the accuracy of these different classifications using an additional 60 hr of behavioral observations, not used in the initial classification. The accuracy of the manually created decision tree classification using observational data varied from 70.6% to 91.6% depending on the complexity of the tree, with increasing accuracy as complexity decreased. Short duration behavior like running had lower accuracy than long-duration behavior like feeding. The random forest algorithm offered similarly high overall accuracy, but the manual decision tree afforded the flexibility to create a hierarchical tree, and to adjust sampling window length for behavioral states with varying durations. Low frequency biologging of acceleration and temperature allows accurate behavioral classification of small animals over multi-month sampling durations. Nevertheless, low sampling rates impose several important limitations, especially related to assessing the classification accuracy of short duration behavior.

Dataset Information

Low-temperature carbon utilization is regulated by novel gene activity in the heart of a hibernating mammal.

Publications

Low-temperature carbon utilization is regulated by novel gene activity in the heart of a hibernating mammal.

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