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Regulation of oxidative phosphorylation in different muscles and various experimental conditions.

ABSTRACT: It has been shown previously that direct stimulation of oxidative-phosphorylation complexes in parallel with the stimulation of ATP usage is able to explain the stability of intermediate metabolite (ATP/ADP, phosphocreatine/creatine, NADH/NAD+, protonmotive force) concentrations accompanied by a large increase in oxygen consumption and ATP turnover during transition from rest to intensive exercise in skeletal muscle. It has been also postulated that intensification of parallel activation in the ATP supply-demand system is one of the mechanisms of training-induced adaptation of oxidative phosphorylation in skeletal muscle. In the present paper, it is demonstrated, using the computer model of oxidative phosphorylation in intact skeletal muscle developed previously, that the direct activation of oxidative phosphorylation during muscle contraction can account for the following kinetic properties of oxidative phosphorylation in skeletal muscle encountered in different experimental studies: (i) increase in the respiration rate per mg of mitochondrial protein at a given ADP concentration as a result of muscle training and decrease in this parameter in hypothyroidism; (ii) asymmetry (different half-transition time, t(1/2)) in phosphocreatine concentration time course between on-transient (rest-->work transition) and off-transient (recovery after exercise); (iii) overshoot in phosphocreatine concentration during recovery after exercise; (iv) variability in the kinetic properties of oxidative phosphorylation in different kinds of muscle under different experimental conditions. No other postulated mechanism is able to explain all these phenomena at the same time and therefore the present paper strongly supports the idea of the parallel activation of ATP usage and different oxidative-phosphorylation complexes during muscle contraction.

SUBMITTER: Korzeniewski B

PROVIDER: S-EPMC1223721 | biostudies-other | 2003 Nov

REPOSITORIES: biostudies-other

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Project description:BackgroundDifferent human responses to the same vaccine were frequently observed. For example, independent studies identified overlapping but different transcriptomic gene expression profiles in Yellow Fever vaccine 17D (YF-17D) immunized human subjects. Different experimental and analysis conditions were likely contributed to the observed differences. To investigate this issue, we developed a Vaccine Investigation Ontology (VIO), and applied VIO to classify the different variables and relations among these variables systematically. We then evaluated whether the ontological VIO modeling and VIO-based statistical analysis would contribute to the enhanced vaccine investigation studies and a better understanding of vaccine response mechanisms.ResultsOur VIO modeling identified many variables related to data processing and analysis such as normalization method, cut-off criteria, software settings including software version. The datasets from two previous studies on human responses to YF-17D vaccine, reported by Gaucher et al. (2008) and Querec et al. (2009), were re-analyzed. We first applied the same LIMMA statistical method to re-analyze the Gaucher data set and identified a big difference in terms of significantly differentiated gene lists compared to the original study. The different results were likely due to the LIMMA version and software package differences. Our second study re-analyzed both Gaucher and Querec data sets but with the same data processing and analysis pipeline. Significant differences in differential gene lists were also identified. In both studies, we found that Gene Ontology (GO) enrichment results had more overlapping than the gene lists and enriched pathway lists. The visualization of the identified GO hierarchical structures among the enriched GO terms and their associated ancestor terms using GOfox allowed us to find more associations among enriched but often different GO terms, demonstrating the usage of GO hierarchical relations enhance data analysis.ConclusionsThe ontology-based analysis framework supports standardized representation, integration, and analysis of heterogeneous data of host responses to vaccines. Our study also showed that differences in specific variables might explain different results drawn from similar studies.

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Regulation of oxidative phosphorylation in different muscles and various experimental conditions.

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