Proteomic analysis reveals perturbed energy metabolism and elevated oxidative stress in hearts of rats with inborn low aerobic capacity

Selection on running capacity has created rat phenotypes of high‐capacity runners (HCRs) that have enhanced cardiac function and low‐capacity runners (LCRs) that exhibit risk factors of metabolic syndrome. We analysed hearts of HCRs and LCRs from generation 22 of selection using DIGE and identified proteins from MS database searches. The running capacity of HCRs was six‐fold greater than LCRs. DIGE resolved 957 spots and proteins were unambiguously identified in 369 spots. Protein expression profiling detected 67 statistically significant ( p <0.05; false discovery rate <10%, calculated using q ‐values) differences between HCRs and LCRs. Hearts of HCR rats exhibited robust increases in the abundance of each enzyme of the β‐oxidation pathway. In contrast, LCR hearts were characterised by the modulation of enzymes associated with ketone body or amino acid metabolism. LCRs also exhibited enhanced expression of antioxidant enzymes such as catalase and greater phosphorylation of α B‐crystallin at serine 59, which is a common point of convergence in cardiac stress signalling. Thus, proteomic analysis revealed selection on low running capacity is associated with perturbations in cardiac energy metabolism and provided the first evidence that the LCR cardiac proteome is exposed to greater oxidative stress.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86916/1/3369_ftp.pd

Intrinsic aerobic capacity sets a divide for aging and longevity

&lt;p&gt;&lt;b&gt;Rationale:&lt;/b&gt; Low aerobic exercise capacity is a powerful predictor of premature morbidity and mortality for healthy adults as well as those with cardiovascular disease. For aged populations, poor performance on treadmill or extended walking tests indicates closer proximity to future health declines. Together, these findings suggest a fundamental connection between aerobic capacity and longevity.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Objectives:&lt;/b&gt; Through artificial selective breeding, we developed an animal model system to prospectively test the association between aerobic exercise capacity and survivability (aerobic hypothesis).&lt;/p&gt; &lt;p&gt;&lt;b&gt;Methods and Results:&lt;/b&gt; Laboratory rats of widely diverse genetic backgrounds (N:NIH stock) were selectively bred for low or high intrinsic (inborn) treadmill running capacity. Cohorts of male and female rats from generations 14, 15, and 17 of selection were followed for survivability and assessed for age-related declines in cardiovascular fitness including maximal oxygen uptake (VO&lt;sub&gt;2max&lt;/sub&gt;), myocardial function, endurance performance, and change in body mass. Median lifespan for low exercise capacity rats was 28% to 45% shorter than high capacity rats (hazard ratio, 0.06; P&#60;0.001). VO&lt;sub&gt;2max&lt;/sub&gt;, measured across adulthood was a reliable predictor of lifespan (P&#60;0.001). During progression from adult to old age, left ventricular myocardial and cardiomyocyte morphology, contractility, and intracellular Ca&lt;sup&gt;2+&lt;/sup&gt; handling in both systole and diastole, as well as mean blood pressure, were more compromised in rats bred for low aerobic capacity. Physical activity levels, energy expenditure (Vo&lt;sub&gt;2&lt;/sub&gt;), and lean body mass were all better sustained with age in rats bred for high aerobic capacity.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; These data obtained from a contrasting heterogeneous model system provide strong evidence that genetic segregation for aerobic exercise capacity can be linked with longevity and are useful for deeper mechanistic exploration of aging.&lt;/p&gt

Maximal Oxidative Capacity during Exercise Is Associated with Skeletal Muscle Fuel Selection and Dynamic Changes in Mitochondrial Protein Acetylation

SummaryMaximal exercise-associated oxidative capacity is strongly correlated with health and longevity in humans. Rats selectively bred for high running capacity (HCR) have improved metabolic health and are longer-lived than their low-capacity counterparts (LCR). Using metabolomic and proteomic profiling, we show that HCR efficiently oxidize fatty acids (FAs) and branched-chain amino acids (BCAAs), sparing glycogen and reducing accumulation of short- and medium-chain acylcarnitines. HCR mitochondria have reduced acetylation of mitochondrial proteins within oxidative pathways at rest, and there is rapid protein deacetylation with exercise, which is greater in HCR than LCR. Fluxomic analysis of valine degradation with exercise demonstrates a functional role of differential protein acetylation in HCR and LCR. Our data suggest that efficient FA and BCAA utilization contribute to high intrinsic exercise capacity and the health and longevity benefits associated with enhanced fitness

Johnson Noise Thermometry for Advanced Small Modular Reactors

Temperature is a key process variable at any nuclear power plant (NPP). The harsh reactor environment causes all sensor properties to drift over time. At the higher temperatures of advanced NPPs the drift occurs more rapidly. The allowable reactor operating temperature must be reduced by the amount of the potential measurement error to assure adequate margin to material damage. Johnson noise is a fundamental expression of temperature and as such is immune to drift in a sensor s physical condition. In and near core, only Johnson noise thermometry (JNT) and radiation pyrometry offer the possibility for long-term, high-accuracy temperature measurement due to their fundamental natures. Small, Modular Reactors (SMRs) place a higher value on long-term stability in their temperature measurements in that they produce less power per reactor core and thus cannot afford as much instrument recalibration labor as their larger brethren. The purpose of this project is to develop and demonstrate a drift free Johnson noise-based thermometer suitable for deployment near core in advanced SMR plants

Johnson Noise Thermometry for Advanced Small Modular Reactors

Temperature is a key process variable at any nuclear power plant (NPP). The harsh reactor environment causes all sensor properties to drift over time. At the higher temperatures of advanced NPPs the drift occurs more rapidly. The allowable reactor operating temperature must be reduced by the amount of the potential measurement error to assure adequate margin to material damage. Johnson noise is a fundamental expression of temperature and as such is immune to drift in a sensor s physical condition. In and near core, only Johnson noise thermometry (JNT) and radiation pyrometry offer the possibility for long-term, high-accuracy temperature measurement due to their fundamental natures. Small, Modular Reactors (SMRs) place a higher value on long-term stability in their temperature measurements in that they produce less power per reactor core and thus cannot afford as much instrument recalibration labor as their larger brethren. The purpose of this project is to develop and demonstrate a drift free Johnson noise-based thermometer suitable for deployment near core in advanced SMR plants

Johnson Noise Thermometry for Advanced Small Modular Reactors

Temperature is a key process variable at any nuclear power plant (NPP). The harsh reactor environment causes all sensor properties to drift over time. At the higher temperatures of advanced NPPs the drift occurs more rapidly. The allowable reactor operating temperature must be reduced by the amount of the potential measurement error to assure adequate margin to material damage. Johnson noise is a fundamental expression of temperature and as such is immune to drift in a sensor’s physical condition. In and near the core, only Johnson noise thermometry (JNT) and radiation pyrometry offer the possibility for long-term, high-accuracy temperature measurement due to their fundamental natures. Small Modular Reactors (SMRs) place a higher value on long-term stability in their temperature measurements in that they produce less power per reactor core and thus cannot afford as much instrument recalibration labor as their larger brethren. The purpose of the current ORNL-led project, conducted under the Instrumentation, Controls, and Human-Machine Interface (ICHMI) research pathway of the U.S. Department of Energy (DOE) Advanced SMR Research and Development (R&D) program, is to develop and demonstrate a drift free Johnson noise-based thermometer suitable for deployment near core in advanced SMR plants

YeATS - a tool suite for analyzing RNA-seq derived transcriptome identifies a highly transcribed putative extensin in heartwood/sapwood transition zone in black walnut

The transcriptome provides a functional footprint of the genome by enumerating the molecular components of cells and tissues. The field of transcript discovery has been revolutionized through high-throughput mRNA sequencing (RNA-seq). Here, we present a methodology that replicates and improves existing methodologies, and implements a workflow for error estimation and correction followed by genome annotation and transcript abundance estimation for RNA-seq derived transcriptome sequences (YeATS - Yet Another Tool Suite for analyzing RNA-seq derived transcriptome). A unique feature of YeATS is the upfront determination of the errors in the sequencing or transcript assembly process by analyzing open reading frames of transcripts. YeATS identifies transcripts that have not been merged, result in broken open reading frames or contain long repeats as erroneous transcripts. We present the YeATS workflow using a representative sample of the transcriptome from the tissue at the heartwood/sapwood transition zone in black walnut. A novel feature of the transcriptome that emerged from our analysis was the identification of a highly abundant transcript that had no known homologous genes (GenBank accession: KT023102). The amino acid composition of the longest open reading frame of this gene classifies this as a putative extensin. Also, we corroborated the transcriptional abundance of proline-rich proteins, dehydrins, senescence-associated proteins, and the DNAJ family of chaperone proteins. Thus, YeATS presents a workflow for analyzing RNA-seq data with several innovative features that differentiate it from existing software

YeATS - a tool suite for analyzing RNA-seq derived transcriptome identifies a highly transcribed putative extensin in heartwood/sapwood transition zone in black walnut [version 2; referees: 3 approved]

The transcriptome provides a functional footprint of the genome by enumerating the molecular components of cells and tissues. The field of transcript discovery has been revolutionized through high-throughput mRNA sequencing (RNA-seq). Here, we present a methodology that replicates and improves existing methodologies, and implements a workflow for error estimation and correction followed by genome annotation and transcript abundance estimation for RNA-seq derived transcriptome sequences (YeATS - Yet Another Tool Suite for analyzing RNA-seq derived transcriptome). A unique feature of YeATS is the upfront determination of the errors in the sequencing or transcript assembly process by analyzing open reading frames of transcripts. YeATS identifies transcripts that have not been merged, result in broken open reading frames or contain long repeats as erroneous transcripts. We present the YeATS workflow using a representative sample of the transcriptome from the tissue at the heartwood/sapwood transition zone in black walnut. A novel feature of the transcriptome that emerged from our analysis was the identification of a highly abundant transcript that had no known homologous genes (GenBank accession: KT023102). The amino acid composition of the longest open reading frame of this gene classifies this as a putative extensin. Also, we corroborated the transcriptional abundance of proline-rich proteins, dehydrins, senescence-associated proteins, and the DNAJ family of chaperone proteins. Thus, YeATS presents a workflow for analyzing RNA-seq data with several innovative features that differentiate it from existing software

Evaluation of the current knowledge limitations in breast cancer research: a gap analysis

BACKGROUND A gap analysis was conducted to determine which areas of breast cancer research, if targeted by researchers and funding bodies, could produce the greatest impact on patients. METHODS Fifty-six Breast Cancer Campaign grant holders and prominent UK breast cancer researchers participated in a gap analysis of current breast cancer research. Before, during and following the meeting, groups in seven key research areas participated in cycles of presentation, literature review and discussion. Summary papers were prepared by each group and collated into this position paper highlighting the research gaps, with recommendations for action. RESULTS Gaps were identified in all seven themes. General barriers to progress were lack of financial and practical resources, and poor collaboration between disciplines. Critical gaps in each theme included: (1) genetics (knowledge of genetic changes, their effects and interactions); (2) initiation of breast cancer (how developmental signalling pathways cause ductal elongation and branching at the cellular level and influence stem cell dynamics, and how their disruption initiates tumour formation); (3) progression of breast cancer (deciphering the intracellular and extracellular regulators of early progression, tumour growth, angiogenesis and metastasis); (4) therapies and targets (understanding who develops advanced disease); (5) disease markers (incorporating intelligent trial design into all studies to ensure new treatments are tested in patient groups stratified using biomarkers); (6) prevention (strategies to prevent oestrogen-receptor negative tumours and the long-term effects of chemoprevention for oestrogen-receptor positive tumours); (7) psychosocial aspects of cancer (the use of appropriate psychosocial interventions, and the personal impact of all stages of the disease among patients from a range of ethnic and demographic backgrounds). CONCLUSION Through recommendations to address these gaps with future research, the long-term benefits to patients will include: better estimation of risk in families with breast cancer and strategies to reduce risk; better prediction of drug response and patient prognosis; improved tailoring of treatments to patient subgroups and development of new therapeutic approaches; earlier initiation of treatment; more effective use of resources for screening populations; and an enhanced experience for people with or at risk of breast cancer and their families. The challenge to funding bodies and researchers in all disciplines is to focus on these gaps and to drive advances in knowledge into improvements in patient care