| 1. |
- Fredriksson, Katarina, et al.
(författare)
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Dysregulation of Mitochondrial Dynamics and the Muscle Transcriptome in ICU Patients Suffering from Sepsis Induced Multiple Organ Failure
- 2008
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 3:11, s. e3686-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Septic patients treated in the intensive care unit (ICU) often develop multiple organ failure including persistent skeletal muscle dysfunction which results in the patient's protracted recovery process. We have demonstrated that muscle mitochondrial enzyme activities are impaired in septic ICU patients impairing cellular energy balance, which will interfere with muscle function and metabolism. Here we use detailed phenotyping and genomics to elucidate mechanisms leading to these impairments and the molecular consequences. Methodology/Principal Findings: Utilising biopsy material from seventeen patients and ten age-matched controls we demonstrate that neither mitochondrial in vivo protein synthesis nor expression of mitochondrial genes are compromised. Indeed, there was partial activation of the mitochondrial biogenesis pathway involving NRF2a/GABP and its target genes TFAM, TFB1M and TFB2M yet clearly this failed to maintain mitochondrial function. We therefore utilised transcript profiling and pathway analysis of ICU patient skeletal muscle to generate insight into the molecular defects driving loss of muscle function and metabolic homeostasis. Gene ontology analysis of Affymetrix analysis demonstrated substantial loss of muscle specific genes, a global oxidative stress response related to most probably cytokine signalling, altered insulin related signalling and a substantial overlap between patients and muscle wasting/inflammatory animal models. MicroRNA 21 processing appeared defective suggesting that post-transcriptional protein synthesis regulation is altered by disruption of tissue microRNA expression. Finally, we were able to demonstrate that the phenotype of skeletal muscle in ICU patients is not merely one of inactivity, it appears to be an actively remodelling tissue, influenced by several mediators, all of which may be open to manipulation with the aim to improve clinical outcome. Conclusions/Significance: This first combined protein and transcriptome based analysis of human skeletal muscle obtained from septic patients demonstrated that losses of mitochondria and muscle mass are accompanied by sustained protein synthesis (anabolic process) while dysregulation of transcription programmes appears to fail to compensate for increased damage and proteolysis. Our analysis identified both validated and novel clinically tractable targets to manipulate these failing processes and pursuit of these could lead to new potential treatments.
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| 2. |
- Scheele, Camilla, et al.
(författare)
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Altered regulation of the PINK1 locus: a link between Type 2 diabetes and neurodegeneration?
- 2007
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Ingår i: The FASEB Journal. - : Wiley. - 0892-6638 .- 1530-6860. ; 21:13, s. 3653-3665
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Tidskriftsartikel (refereegranskat)abstract
- Mutations in PINK1 cause the mitochondrial-related neurodegenerative disease Parkinson’s. Here we investigate whether obesity, type 2 diabetes, or inactivity alters transcription from the PINK1 locus. We utilized a cDNA-array and quantitative real-time PCR for gene expression analysis of muscle from healthy volunteers following physical inactivity, and muscle and adipose tissue from nonobese or obese subjects with normal glucose tolerance or type 2 diabetes. Functional studies of PINK1 were performed utilizing RNA interference in cell culture models. Following inactivity, the PINK1 locus had an opposing regulation pattern (PINK1 was down-regulated while natural antisense PINK1 was up-regulated). In type 2 diabetes skeletal muscle, all transcripts from the PINK1 locus were suppressed and gene expression correlated with diabetes status. RNA interference of PINK1 in human neuronal cell lines impaired basal glucose uptake. In adipose tissue, mitochondrial gene expression correlated with PINK1 expression although remained unaltered following siRNA knockdown of Pink1 in primary cultures of brown preadipocytes. In conclusion, regulation of the PINK1 locus, previously linked to neurodegenerative disease, is altered in obesity, type 2 diabetes and inactivity, while the combination of RNAi experiments and clinical data suggests a role for PINK1 in cell energetics rather than in mitochondrial biogenesis.
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| 3. |
- Scheele, Camilla, et al.
(författare)
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USING FUNCTIONAL GENOMICS TO STUDY PINK1 AND METABOLIC PHYSIOLOGY :
- 2009
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Ingår i: Methods in Enzymology. - 0076-6879 .- 1557-7988. ; 457, s. 211-229
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Forskningsöversikt (refereegranskat)abstract
- Genome sequencing projects have provided the substrate for an unimaginable number of biological experiments. Further, genomic technologies such as microarrays and quantitative and exquisitely sensitive techniques such as real-time quantitative polymerase chain reaction have made it possible to reliably generate millions of data points per experiment. The data can be high quality and yield entirely new insights into how gene expression is coordinated under complex physiological situations. It can also be that the data and interpretation are meaningless because of a lack of physiological context or experimental control. Thus, functional genomics is now being applied to study metabolic physiology with varying degrees of success. From the genome sequencing projects we also have the information needed to design chemical tools that can knock down a gene transcript, even distinguishing between splice variants in mammalian cells. Use of such technologies, inspired by nature's endogenous RNAi mechanism-microRNA targeting, comes with significant caveats. While the discipline of Pharmacology taught us last century that inhibitor action specificity is dependent on the concentration used, these experiences have been ignored by users of siRNA technologies. What we provide in this chapter is some considerations and observations from functional genomic studies. We are largely concerned with the phase that follows a microarray study, where a candidate gene is selected for manipulation in a system that is considered to be simpler than the in vivo mammalian tissue and thus the methods discussed largely apply to this cell biology phase. We apologize for not referring to all relevant publications and for any technical considerations we have also failed to factor into our discussion.
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| 4. |
- Timmons, James A, et al.
(författare)
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Expression profiling following local muscle inactivity in humans provides new perspective on diabetes-related genes
- 2006
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Ingår i: Genomics. - : Elsevier BV. - 0888-7543 .- 1089-8646. ; 87:1, s. 165-172
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Tidskriftsartikel (refereegranskat)abstract
- Physical activity enhances muscle mitochondrial gene expression, while inactivity and mitochondrial dysfunction are both risk factors for developing diabetes. Defective activation of the transcriptional coactivator PGC-1 may contribute to the gene expression pattern observed in diabetic and insulin-resistant skeletal muscle. We proposed that greater insight into the mitochondrial component of skeletal muscle “diabetes” would be possible if the clinical transcriptome data were contrasted with local muscle inactivity-induced modulation of mitochondrial genes in otherwise healthy subjects. We studied PPARGC1A (PGC-1), PPARGC1B (PGC-1β), NRF1, and a variety of mitochondrial DNA (mtDNA) and nuclear-encoded mitochondrial genes critical for oxidative phosphorylation in soleus muscle biopsies obtained from six healthy men and women before and after 5 weeks of local muscle inactivity. Muscle inactivity resulted in a coordinated down-regulation of PGC-1 and genes involved with mitochondrial metabolism, including muscle substrate delivery genes. Decreased expression of the mtDNA helicase Twinkle was related to the decline in mitochondrial RNA polymerase (r = 0.83, p < 0.04), suggesting that mtDNA transcription and replication are coregulated in human muscle tissue. In contrast to the situation in diabetes, PGC-1β expression was not significantly altered, while NRF1 expression was actually up-regulated following muscle inactivity. We can conclude that reduced PGC-1 expression described in Type 2 diabetes may be partly explained by muscle inactivity. Further, although diabetes patients are typically inactive, our analysis indicates that local muscle inactivity may not be expected to contribute to the decreased NRF1 and PGC-1β expression noted in insulin-resistant and Type 2 diabetes patients, suggesting these changes may be more disease specific.
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| 5. |
- Timmons, James A., et al.
(författare)
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Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans
- 2010
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Ingår i: Journal of applied physiology. - : American Physiological Society. - 8750-7587 .- 1522-1601. ; 108:6, s. 1487-1496
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Tidskriftsartikel (refereegranskat)abstract
- Timmons JA, Knudsen S, Rankinen T, Koch LG, Sarzynski M, Jensen T, Keller P, Scheele C, Vollaard NB, Nielsen S, Akerstrom T, MacDougald OA, Jansson E, Greenhaff PL, Tarnopolsky MA, van Loon LJ, Pedersen BK, Sundberg CJ, Wahlestedt C, Britton SL, Bouchard C. Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans. J Appl Physiol 108: 1487-1496, 2010. First published February 4, 2010; doi:10.1152/japplphysiol.01295.2009.-A low maximal oxygen consumption ((V) over dotO(2max)) is a strong risk factor for premature mortality. Supervised endurance exercise training increases (V) over dotO(2max) with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial sample sizes. In the present study, we first use RNA expression profiling to produce a molecular classifier that predicts (V) over dotO(2max) training response. We then hypothesized that the classifier genes would harbor DNA variants that contributed to the heterogeneous (V) over dotO(2max) response. Two independent preintervention RNA expression data sets were generated (n = 41 gene chips) from subjects that underwent supervised endurance training: one identified and the second blindly validated an RNA expression signature that predicted change in (V) over dotO(2max) (""predictor"" genes). The HERITAGE Family Study (n = 473) was used for genotyping. We discovered a 29-RNA signature that predicted (V) over dotO(2max) training response on a continuous scale; these genes contained similar to 6 new single-nucleotide polymorphisms associated with gains in (V) over dotO(2max) in the HERITAGE Family Study. Three of four novel candidate genes from the HERITAGE Family Study were confirmed as RNA predictor genes (i.e., ""reciprocal"" RNA validation of a quantitative trait locus genotype), enhancing the performance of the 29-RNA-based predictor. Notably, RNA abundance for the predictor genes was unchanged by exercise training, supporting the idea that expression was preset by genetic variation. Regression analysis yielded a model where 11 single-nucleotide polymorphisms explained 23% of the variance in gains in (V) over dotO(2max), corresponding to similar to 50% of the estimated genetic variance for (V) over dotO(2max). In conclusion, combining RNA profiling with single-gene DNA marker association analysis yields a strongly validated molecular predictor with meaningful explanatory power. (V) over dotO(2max) responses to endurance training can be predicted by measuring a similar to 30-gene RNA expression signature in muscle prior to training. The general approach taken could accelerate the discovery of genetic biomarkers, sufficiently discrete for diagnostic purposes, for a range of physiological and pharmacological phenotypes in humans.
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