Do Neuro-Muscular Adaptations Occur in Endurance-Trained Boys and Men?

Most research on the effects of endurance training has focused on endurance training's health-related benefits and metabolic effects in both children and adults. The purpose of this study was to examine the neuromuscular effects of endurance training and to investigate whether they differ in children (9.0-12.9 years) and adults (18.4-35.6 years). Maximal isometric torque, rate of torque development (RTD), rate of muscle activation (Q30), electromechanical delay (EMD), and time to peak torque and peak RTD were determined by isokinetic dynamometry and surface electromyography (EMG) in elbow and knee flexion and extension. The subjects were 12 endurance-trained and 16 untrained boys, and 15 endurance-trained and 20 untrained men. The adults displayed consistently higher peak torque, RTD, and Q30, in both absolute and normalized values, whereas the boys had longer EMD (64.7+/-17.1 vs. 56.6+/-15.4 ms) and time to peak RTD (98.5+/-32.1 vs. 80.4+/-15.0 ms for boys and men, respectively). Q30, normalized for peak EMG amplitude, was the only observed training effect (1.95+/-1.16 vs. 1.10+/-0.67 ms for trained and untrained men, respectively). This effect could not be shown in the boys. The findings show normalized muscle strength and rate of activation to be lower in children compared with adults, regardless of training status. Because the observed higher Q30 values were not matched by corresponding higher performance measures in the trained men, the functional and discriminatory significance of Q30 remains unclear. Endurance training does not appear to affect muscle strength or rate of force development in either men or boys

Development of SYK NanoBRET cellular target engagement assays for gain–of–function variants

Spleen tyrosine kinase (SYK) is a non-receptor tyrosine kinase that is activated by phosphorylation events downstream of FcR, B-cell and T-cell receptors, integrins, and C-type lectin receptors. When the tandem Src homology 2 (SH2) domains of SYK bind to phosphorylated immunoreceptor tyrosine-based activation motifs (pITAMs) contained within these immunoreceptors, or when SYK is phosphorylated in interdomain regions A and B, SYK is activated. SYK gain-of-function (GoF) variants were previously identified in six patients that had higher levels of phosphorylated SYK and phosphorylated downstream proteins JNK and ERK. Furthermore, the increased SYK activation resulted in the clinical manifestation of immune dysregulation, organ inflammation, and a predisposition for lymphoma. The knowledge that the SYK GoF variants have enhanced activity was leveraged to develop a SYK NanoBRET cellular target engagement assay in intact live cells with constructs for the SYK GoF variants. Herein, we developed a potent SYK-targeted NanoBRET tracer using a SYK donated chemical probe, MRL-SYKi, that enabled a NanoBRET cellular target engagement assay for SYK GoF variants, SYK(S550Y), SYK(S550F), and SYK(P342T). We determined that ATP-competitive SYK inhibitors bind potently to these SYK variants in intact live cells. Additionally, we demonstrated that MRL-SYKi can effectively reduce the catalytic activity of SYK variants, and the phosphorylation levels of SYK(S550Y) in an epithelial cell line (SW480) stably expressing SYK(S550Y)

Biological Process Linkage Networks

BACKGROUND. The traditional approach to studying complex biological networks is based on the identification of interactions between internal components of signaling or metabolic pathways. By comparison, little is known about interactions between higher order biological systems, such as biological pathways and processes. We propose a methodology for gleaning patterns of interactions between biological processes by analyzing protein-protein interactions, transcriptional co-expression and genetic interactions. At the heart of the methodology are the concept of Linked Processes and the resultant network of biological processes, the Process Linkage Network (PLN). RESULTS. We construct, catalogue, and analyze different types of PLNs derived from different data sources and different species. When applied to the Gene Ontology, many of the resulting links connect processes that are distant from each other in the hierarchy, even though the connection makes eminent sense biologically. Some others, however, carry an element of surprise and may reflect mechanisms that are unique to the organism under investigation. In this aspect our method complements the link structure between processes inherent in the Gene Ontology, which by its very nature is species-independent. As a practical application of the linkage of processes we demonstrate that it can be effectively used in protein function prediction, having the power to increase both the coverage and the accuracy of predictions, when carefully integrated into prediction methods. CONCLUSIONS. Our approach constitutes a promising new direction towards understanding the higher levels of organization of the cell as a system which should help current efforts to re-engineer ontologies and improve our ability to predict which proteins are involved in specific biological processes.Lynn and William Frankel Center for Computer Science; the Paul Ivanier center for robotics research and production; National Science Foundation (ITR-048715); National Human Genome Research Institute (1R33HG002850-01A1, R01 HG003367-01A1); National Institute of Health (U54 LM008748

Function-Based Discovery of Significant Transcriptional Temporal Patterns in Insulin Stimulated Muscle Cells

Background: Insulin action on protein synthesis (translation of transcripts) and post-translational modifications, especially of those involving the reversible modifications such as phosphorylation of various signaling proteins, are extensively studied but insulin effect on transcription of genes, especially of transcriptional temporal patterns remains to be fully defined. Methodology/Principal Findings: To identify significant transcriptional temporal patterns we utilized primary differentiated rat skeletal muscle myotubes which were treated with insulin and samples were collected every 20 min for 8 hours. Pooled samples at every hour were analyzed by gene array approach to measure transcript levels. The patterns of transcript levels were analyzed based on a novel method that integrates selection, clustering, and functional annotation to find the main temporal patterns associated to functional groups of differentially expressed genes. 326 genes were found to be differentially expressed in response to in vitro insulin administration in skeletal muscle myotubes. Approximately 20 % of the genes that were differentially expressed were identified as belonging to the insulin signaling pathway. Characteristic transcriptional temporal patterns include: (a) a slow and gradual decrease in gene expression, (b) a gradual increase in gene expression reaching a peak at about 5 hours and then reaching a plateau or an initial decrease and other different variable pattern of increase in gene expression over time. Conclusion/Significance: The new method allows identifying characteristic dynamic responses to insulin stimulus, commo

Discovering Networks of Perturbed Biological Processes in Hepatocyte Cultures

The liver plays a vital role in glucose homeostasis, the synthesis of bile acids and the detoxification of foreign substances. Liver culture systems are widely used to test adverse effects of drugs and environmental toxicants. The two most prevalent liver culture systems are hepatocyte monolayers (HMs) and collagen sandwiches (CS). Despite their wide use, comprehensive transcriptional programs and interaction networks in these culture systems have not been systematically investigated. We integrated an existing temporal transcriptional dataset for HM and CS cultures of rat hepatocytes with a functional interaction network of rat genes. We aimed to exploit the functional interactions to identify statistically significant linkages between perturbed biological processes. To this end, we developed a novel approach to compute Contextual Biological Process Linkage Networks (CBPLNs). CBPLNs revealed numerous meaningful connections between different biological processes and gene sets, which we were successful in interpreting within the context of liver metabolism. Multiple phenomena captured by CBPLNs at the process level such as regulation, downstream effects, and feedback loops have well described counterparts at the gene and protein level. CBPLNs reveal high-level linkages between pathways and processes, making the identification of important biological trends more tractable than through interactions between individual genes and molecules alone. Our approach may provide a new route to explore, analyze, and understand cellular responses to internal and external cues within the context of the intricate networks of molecular interactions that control cellular behavior