Biology subjects

Esser, K. A.

Publications and source records attributed to Esser, K. A..

28 records · Page 2Linked to original sources

bioRxiv2022

An Optimized Approach to Study Sub-Sarcomere Structure Utilizing Super-Resolution Microscopy with Secondary VHH Nanobodies

The sarcomere is the fundamental contractile unit in skeletal muscle, and the maintenance of its structure is critical for its function. While alterations in sarcomere structure are implicated in many clinical conditions of muscle weakness this area has made limited progress due, in part, to limitations in the ability to robustly detect and measure at sub-sarcomere resolution. Classically the field has relied on approaches including confocal and electron microscopy, but there are technique-specific limitations with respect to resolution, tissue morphology, and protein specific labeling. In this study, our goal was to establish a robust and reproducible method to probe sub-sarcomere protein localization in longitudinal muscle sections. We optimized several steps from tissue preparation to antibody selection and imaging to provide the ability to quantitatively assess spatial distribution of proteins within a single sarcomere. This includes 1) in situ fixation for structural integrity, 2) use of multiple same host-species primary antibodies with Fab fragment antibody blocking to maintain specificity, and 3) the use of super-resolution structured illumination microscopy (SIM) to improve from confocal, along with use of emergent VHH secondary nanobodies to double the resolution. The combination of these methods provides a unique approach to improve visualization of sarcomere structure while simultaneously providing the ability to rigorously probe protein localization. While this study focused on assessment of skeletal muscle structure and provides an important set of tools for analysis of skeletal muscle health in disease and aging, we suggest the methods herein may prove advantageous for research outside of skeletal muscle.

physiology↗

bioRxiv2022

Statistical Methods for Detecting Circadian Rhythmicity and Differential Circadian Patterns with Repeated Measurement in Transcriptomic Applications

Circadian analysis via transcriptomic data has been successful in revealing the clock output changes underlying many diseases and physiological processes. Repeated measurement design in a circadian study is prevalent, in which the same subject is repeatedly measured over time. Several methods are currently available to perform circadian analysis, however, none of them take advantage of the repeated measurement design. And ignoring the within-subject correlation from the repeated measurement could result in lower statistical power. To address this issue, we developed linear mixed model based methods to detect (i) circadian rhythmicity (i.e., Rpt_rhythmicity) and (ii) differential circadian patterns comparing two experimental conditions (i.e., Rpt_diff). Our model includes a subject-specific random effect, which will account for the within-subject correlation. Via simulations, we showed our method not only could control the type I error rate around the nominal level, but also achieve higher statistical power compared to other methods that cannot model repeated measurement. The superior performance of Rpt_rhythmicity and Rpt_diff were also demonstrated in two real data applications, including a human restricted feeding data and a human sleep restriction data. An R package for our methods is publicly available on GitHub to promote the application of our methods.

bioinformatics↗

bioRxiv2022

Defining the age-dependent and tissue-specific circadian transcriptome in male mice

Cellular circadian clocks direct a daily transcriptional program that supports homeostasis and resilience. Emerging evidence supports age-associated changes in circadian functions. To define age-dependent changes at the systems level, we profiled the circadian transcriptome in the hypothalamus, lung, heart, kidney, skeletal muscle, and adrenal gland in 3 age groups. We found age-dependent and tissue-specific clock output changes. Aging reduced the number of rhythmically expressed genes (REGs), indicative of weakened circadian control. Many genes gained rhythmicity in old tissues, reflecting an adaptive response. REGs were enriched for the hallmarks of aging, adding a new dimension to our understanding of aging. Differential gene expression analysis found that there were temporally distinct clusters of genes in tissue-specific manner. Increased daily gene expression variability is a common feature of aged tissues. This novel analysis extends the landscape of the understanding of aging and highlights the impact of aging on circadian clock function and temporal changes in gene expression. HIGHLIGHTS- Rhythmically expressed genes (REGs) in Young, but not Old mice, are enriched for the aging hallmarks across all tissues. - The numbers of REGs decline across all tissues with age implicating the circadian clock in altered homeostasis. - Age- and tissue-specific differentially expressed genes (DEGs) cluster at specific times of the day. - Increase in gene expression variability over a day is a common feature of aging tissues.

genomics↗

bioRxiv2022

Experimental Design and Power Calculation in Omics Circadian Rhythmicity Detection

Circadian clocks are 24-hour endogenous oscillators in physiological and behavioral processes. Though recent transcriptomic studies have been successful in revealing the circadian rhythmicity in gene expression, the power calculation for omics circadian analysis have not been fully explored. In this paper, we develop a statistical method, namely CircaPower, to perform power calculation for circadian pattern detection. Our theoretical framework is determined by three key factors in circadian gene detection: sample size, intrinsic effect size and sampling design. Via simulations, we systematically investigate the impact of these key factors on circadian power calculation. We not only demonstrate that CircaPower is fast and accurate, but also show its underlying cosinor model is robust against variety of violations of model assumptions. In real applications, we demonstrate the performance of CircaPower using mouse pan-tissue data and human post-mortem brain data, and illustrate how to perform circadian power calculation using mouse skeleton muscle RNA-Seq pilot as case study. Our method CircaPower has been implemented in an R package, which is made publicly available on GitHub (https://github.com/circaPower/circaPower).

genomics↗

bioRxiv2021

The skeletal muscle circadian clock regulates sarcomere length homeostasis through titin splicing

Circadian rhythms are maintained by a cell autonomous, transcriptional-translational feedback loop known as the molecular clock. While previous research suggests a role of the molecular clock in regulating skeletal muscle structure and function, no mechanisms have connected the molecular clock to sarcomere filaments. Utilizing inducible, skeletal muscle specific, Bmal1 knockout (iMSBmal1-/-) mice, we showed that knocking out skeletal muscle clock function alters titin isoform expression using RNAseq, LC-MS, and SDS-VAGE. This alteration in titins spring length resulted in sarcomere length heterogeneity. We demonstrate the direct link between altered titin splicing and sarcomere length in vitro using U7 snRNPs that truncate the region of titin altered in iMSBmal1-/- muscle. We identified a mechanism whereby the skeletal muscle clock regulates titin isoform expression through transcriptional regulation of Rbm20, a potent splicing regulator of titin. Lastly, we used an environmental model of circadian rhythm disruption and identified significant down-regulation of Rbm20 expression. Our findings demonstrate the importance of the skeletal muscle circadian clock in maintaining titin isoform through regulation of RBM20 expression. Because circadian rhythm disruption is a feature of many chronic diseases, our results highlight a novel pathway that could be targeted to maintain skeletal muscle structure and function in a range of pathologies.

physiology↗

bioRxiv2021

Disrupted circadian core-clock oscillations in Type 2 Diabetes are linked to altered rhythmic mitochondrial metabolism

Circadian rhythms are generated by an auto-regulatory feedback loop composed of transcriptional activators and repressors. Disruption of circadian rhythms contributes to Type 2 diabetes (T2D) pathogenesis. We elucidated whether altered circadian rhythmicity of clock genes is associated with metabolic dysfunction in T2D. Transcriptional cycling of core clock genes ARNTL, CLOCK, CRY1 and NR1D1 was altered in skeletal muscle from individuals with T2D and this was coupled with reduced number and amplitude of cycling genes and disturbed circadian oxygen consumption. Mitochondrial associated genes were enriched for differential circadian amplitudes in T2D, and positively correlated with insulin sensitivity. ChIP- sequencing identified CLOCK and BMAL1 binding to circadian mitochondrial genes associated with insulin sensitivity, implicating regulation by the core clock. Mitochondria disruption altered core-clock gene expression and free-radical production, phenomena that were restored by resveratrol treatment. We identify bi-directional communication between mitochondrial function and rhythmic gene expression, processes which are disturbed in diabetes.

physiology↗

bioRxiv2021

Likelihood-based Tests for Detecting CircadianRhythmicity and Differential Circadian Patterns in Transcriptomic Applications

Circadian rhythmicity in transcriptomic profiles has been shown in many physiological processes, and the disruption of circadian patterns has been founded to associate with several diseases. In this paper, we developed a series of likelihood-based methods to detect (i) circadian rhythmicity (denoted as LR rhythmicity) and (ii) differential circadian patterns comparing two experimental conditions (denoted as LR diff). In terms of circadian rhythmicity detection, we demonstrated that our proposed LR rhythmicity could better control the type I error rate compared to existing methods under a wide variety of simulation settings. In terms of differential circadian patterns, we developed methods in detecting differential amplitude, differential phase, differential basal level, and differential fit, which also successfully controlled the type I error rate. In addition, we demonstrated that the proposed LR diff could achieve higher statistical power in detecting differential fit, compared to existing methods. The superior performance of LR rhythmicity and LR diff was demonstrated in two real data applications, including a brain aging data (gene expression microarray data of human postmortem brain) and a time-restricted feeding data (RNA sequencing data of human skeletal muscles). An R package for our methods is publicly available on GitHub https://github.com/diffCircadian/diffCircadian.

bioinformatics↗

bioRxiv2020

Exercise mitigates sleep-loss-induced changes in glucose tolerance, mitochondrial function, sarcoplasmic protein synthesis, and circadian rhythms.

Sleep loss has emerged as a risk factor for the development of impaired glucose tolerance. The mechanisms underpinning this observation are unknown; however, both mitochondrial dysfunction and circadian misalignment have been proposed. Given that exercise improves glucose tolerance, mitochondrial function, and alters circadian rhythms, we investigated whether exercise may counteract the effects induced by inadequate sleep. We report that sleeping 4 hours per night, for five nights, reduced glucose tolerance, with novel observations of associated reductions in mitochondrial function, sarcoplasmic protein synthesis, and measures of circadian rhythmicity; however, incorporating three sessions of high-intensity interval exercise (HIIE) during this period mitigates these effects. These data demonstrate, for the first time, a sleep loss-induced concomitant reduction in a range of physiological processes linked to metabolic function. These same effects are not observed when exercise is performed during a period of inadequate sleep, supporting the use of HIIE as an intervention to mitigate the detrimental physiological effects of sleep loss.Competing Interest StatementThe authors have declared no competing interest.View Full Text

physiology↗

bioRxiv2020

Time of Day Dependent Effects of Contractile Activity on the Phase of the Skeletal Muscle Clock

Exercise has been proposed to be a zeitgeber for the muscle circadian clock mechanism. However, this is not well defined and it is unknown if exercise timing induces directional shifts of the muscle clock. Our purpose herein was to assess the effect of one bout of treadmill exercise on skeletal muscle clock phase changes. We subjected PERIOD2::LUCIFERASE mice (n=30F) to one 60-minute treadmill exercise bout at three times of day. Exercise at ZT5, 5h after lights on, induced a phase advance (1.4{+/-}0.53h; p=0.038), whereas exercise at ZT11, 1h before lights off, induced a phase delay (-0.95{+/-}0.43h; p=0.0315). Exercise at ZT17, middle of the dark phase, did not alter muscle clock phase. Exercise induces diverse systemic changes so we developed an in-vitro model system to examine effects of contractile activity on muscle clock phase. Contractions applied at peak or trough Bmal1 expression induced significant phase delays (applied at peak: 1.3{+/-}0.02h; p=0.0425; applied at trough: 1.8{+/-}0.02h, p=0.0074). Contractions applied during the transition from peak to trough Bmal1 expression induced a phase advance (1.8{+/-}0.03h; p=0.0265). Lastly, contractions at different times of day resulted in differential changes of core-clock gene expression demonstrating an exercise and clock interaction, providing insight into potential mechanisms exercise-induced phase shifts. These data demonstrate that muscle contractions, as part of exercise, are sufficient to shift muscle circadian clock phase, likely through changes in core-clock gene expression. Additionally, our findings that exercise induces directional muscle clock phase changes confirms exercise is a bone fide environmental time cue for skeletal muscle.

physiology↗

bioRxiv2017

Transcriptional profiling reveals extraordinary diversity among skeletal muscle tissues

Skeletal muscle comprises a family of diverse tissues with highly specialized morphology, function, and metabolism. Many acquired diseases - including HIV, COPD, cancer cachexia, critical illness myopathy, and sepsis - affect specific muscles while sparing others. Even monogenic muscular dystrophies tend to selectively affect certain muscle groups, despite their causative genetic mutations being present in all tissues. These observations suggest that factors intrinsic to muscle tissues influence their susceptibility to various disease mechanisms. Nevertheless, most studies have not addressed transcriptional diversity among skeletal muscles. Here we use RNA sequencing (RNA-seq) to profile global mRNA expression in a wide array of skeletal, smooth, and cardiac muscle tissues from mice and rats. Our data set, MuscleDB, reveals extensive transcriptional diversity, with greater than 50% of transcripts differentially expressed among skeletal muscle tissues. This diversity is only partly explained by fiber type composition and developmental history, suggesting that specialized transcriptional profiles establish the functional identity of muscle tissues. We find conservation in the transcriptional profiles across species as well as between males and females, indicating that these data may be useful in predicting gene expression in related species. Notably, thousands of differentially expressed genes in skeletal muscle are associated with human disease, and hundreds of these genes encode targets of drugs on the market today. We detect mRNA expression of hundreds of putative myokines that may underlie the endocrine functions of skeletal muscle. In addition to demonstrating the intrinsic diversity of skeletal muscles, these data provide a resource for generating testable hypotheses regarding the mechanisms that establish differential disease susceptibility in muscle.\n\nSignificance StatementSkeletal muscles are a diverse family of tissues with a common contractile function but divergent morphology, development, and metabolism. One need only reflect on the different functions of limb muscles and the diaphragm to realize the highly specialized nature of these tissues. Nevertheless, every study of global gene expression has analyzed at most one representative skeletal muscle. Here we measure gene expression from 11 different skeletal muscles in mice and rats. We show that there is no such thing as a representative skeletal muscle, as gene expression profiles vary widely among the tissues analyzed. These data are an important resource for pharmacologists, tissue engineers, and investigators studying the mechanisms of cellular specialization.

systems biology↗