| 11. |
- Scheele, Camilla, et al.
(författare)
-
Altered regulation of the PINK1 locus: a link between Type 2 diabetes and neurodegeneration?
- 2007
-
Ingår i: The FASEB Journal. - : Wiley. - 0892-6638 .- 1530-6860. ; 21:13, s. 3653-3665
-
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.
|
|
| 12. |
- Scheele, Camilla
(författare)
-
Functional genomics studies of PINK1
- 2007
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Functional genomics has become an important and established research discipline during the last 10 years, mainly as a consequence of the completion of large-scale genome sequencing projects. The human genome is now predicted to transcribe 20,000-25,000 protein coding genes, which is only a quarter of the number suggested a few years ago. Instead, a dynamic RNA universe seems to provide diversity to mammalian cells. Around 60-70% of protein coding genes are predicted to generate two or more transcripts by alternative splicing, while non-protein coding RNA are also directly transcribed from the genome. One category of such non-protein coding RNA is cistranscribed natural antisense (NAT). Cis-NATs are transcribed from a gene s antisense DNA strand and are suggested to have regulatory functions through direct interaction. The work described in this thesis includes functional genomics studies of the PINK1 locus. We undertook a study to discover novel candidate genes associated with physical inactivity, a known risk factor for type 2 diabetes. Gene expression profiling of skeletal muscle from subjects before and after 5 weeks of inactivity by quantitative real-time PCR demonstrated a co-ordinated reduction in mitochondrial gene expression. We thus established a human in vivo model for mitochondrial dysfunction. Microarray analyses of the same sample-set suggested that PINK1, a novel mitochondrial kinase, was down regulated during inactivity. PINK1 is transcribed from a complex locus, alternatively spliced and with an annotated cis-NAT. Mutations at this locus had also been linked to Parkinson s disease and we thus selected this locus for subsequent functional genomics studies. We utilized human in vivo models, gene expression and genomic association analysis and RNA interference (RNAi) to study the regulation of PINK1. We demonstrated dynamic expression from the PINK1 locus during modulation of mitochondria in vivo in human skeletal muscle. PINK1 was down regulated in our mitochondrial dysfunction model, while a shorter splice variant of PINK1 (svPINK1) and the NAT (naPINK1) were concordantly up regulated. The opposite expression pattern was obtained in a human in vivo model for increased mitochondrial activity, suggesting a direct association between svPINK1 and naPINK1. Knockdown of naPINK1 utilizing siRNAs targeting two different sites of naPINK1 reduced the level of svPINK1. This directly supports a role for naPINK1 in promoting the abundance of svPINK1, a novel mechanism for regulation by natural antisense. In contrast, all transcripts from the PINK1 locus were less abundant in muscle tissue from diabetics, compared to healthy controls. To investigate whether PINK1 transcript levels could affect metabolic fitness or if the lower expression rather was a secondary effect of diabetes, we measured PINK1 tagging single nucleotide polymorphisms (SNPs). Several SNPs associated with PINK1 transcripts levels. The genotypes associating with higher expression of PINK1 also associated with lower plasma levels of non-esterified fatty acid levels (NEFA) and glucose. Two sets of RNA interference studies provided support for these clinical associations. Firstly, knockdown of PINK1 in human neuroblastoma cells resulted in impaired basal glucose uptake. Secondly, FABP4, a lipid transport protein, was selectively down regulated following PINK1 knockdown in adipocytes. However, mitochondrial genes were not altered when PINK1 expression was ablated, despite the in vivo association between such genes. Taken together, our data suggest a role of PINK1 in lipid and glucose metabolism while PINK1 does not appear to be essential for mitochondrial biogenesis in mammalian cells.
|
|
| 13. |
- Scheele, Camilla, et al.
(författare)
-
USING FUNCTIONAL GENOMICS TO STUDY PINK1 AND METABOLIC PHYSIOLOGY :
- 2009
-
Ingår i: Methods in Enzymology. - 0076-6879 .- 1557-7988. ; 457, s. 211-229
-
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.
|
|
| 14. |
- Timmons, James A, et al.
(författare)
-
Expression profiling following local muscle inactivity in humans provides new perspective on diabetes-related genes
- 2006
-
Ingår i: Genomics. - : Elsevier BV. - 0888-7543 .- 1089-8646. ; 87:1, s. 165-172
-
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.
|
|
| 15. |
- Timmons, James A., et al.
(författare)
-
Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans
- 2010
-
Ingår i: Journal of applied physiology. - : American Physiological Society. - 8750-7587 .- 1522-1601. ; 108:6, s. 1487-1496
-
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.
|
|
| 16. |
- Varemo, Leif, et al.
(författare)
-
Type 2 diabetes and obesity induce similar transcriptional reprogramming in human myocytes
- 2017
-
Ingår i: Genome Medicine. - : BIOMED CENTRAL LTD. - 1756-994X. ; 9
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Skeletal muscle is one of the primary tissues involved in the development of type 2 diabetes (T2D). The close association between obesity and T2D makes it difficult to isolate specific effects attributed to the disease alone. Therefore, here we set out to identify and characterize intrinsic properties of myocytes, associated independently with T2D or obesity. Methods: We generated and analyzed RNA-seq data from primary differentiated myotubes from 24 human subjects, using a factorial design (healthy/T2D and non-obese/obese), to determine the influence of each specific factor on genome-wide transcription. This setup enabled us to identify intrinsic properties, originating from muscle precursor cells and retained in the corresponding myocytes. Bioinformatic and statistical methods, including differential expression analysis, gene-set analysis, and metabolic network analysis, were used to characterize the different myocytes. Results: We found that the transcriptional program associated with obesity alone was strikingly similar to that induced specifically by T2D. We identified a candidate epigenetic mechanism, H3K27me3 histone methylation, mediating these transcriptional signatures. T2D and obesity were independently associated with dysregulated myogenesis, down-regulated muscle function, and up-regulation of inflammation and extracellular matrix components. Metabolic network analysis identified that in T2D but not obesity a specific metabolite subnetwork involved in sphingolipid metabolism was transcriptionally regulated. Conclusions: Our findings identify inherent characteristics in myocytes, as a memory of the in vivo phenotype, without the influence from a diabetic or obese extracellular environment, highlighting their importance in the development of T2D.
|
|
| 17. |
- Väremo, Leif, et al.
(författare)
-
Proteome- and Transcriptome-Driven Reconstruction of the Human Myocyte Metabolic Network and Its Use for Identification of Markers for Diabetes
- 2015
-
Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 11:6, s. 921-933
-
Tidskriftsartikel (refereegranskat)abstract
- Skeletal myocytes are metabolically active and susceptible to insulin resistance and are thus implicated in type 2 diabetes (T2D). This complex disease involves systemic metabolic changes, and their elucidation at the systems level requires genome-wide data and biological networks. Genome-scale metabolic models (GEMs) provide a network context for the integration of high-throughput data. We generated myocyte-specific RNA-sequencing data and investigated their correlation with proteome data. These data were then used to reconstruct a comprehensive myocyte GEM. Next, we performed a meta-analysis of six studies comparing muscle transcription in T2D versus healthy subjects. Transcriptional changes were mapped on the myocyte GEM, revealing extensive transcriptional regulation in T2D, particularly around pyruvate oxidation, branched-chain amino acid catabolism, and tetrahydrofolate metabolism, connected through the downregulated dihydrolipoamide dehydrogenase. Strikingly, the gene signature underlying this metabolic regulation successfully classifies the disease state of individual samples, suggesting that regulation of these pathways is a ubiquitous feature of myocytes in response to T2D.
|
|
| 18. |
- Zenius Jespersen, Naja, et al.
(författare)
-
A classical brown adipose tissue mRNA signature partly overlaps with brite in the supraclavicular region of adult humans
- 2013
-
Ingår i: Cell Metabolism. - : Elsevier BV. - 1550-4131 .- 1932-7420. ; 17:5, s. 798-805
-
Tidskriftsartikel (refereegranskat)abstract
- Human brown adipose tissue (BAT) has been detected in adults but was recently suggested to be of brite/beige origin. We collected BAT from the supraclavicular region in 21 patients undergoing surgery for suspected cancer in the neck area and assessed the gene expression of established murine markers for brown, brite/beige, and white adipocytes. We demonstrate that a classical brown expression signature, including upregulation of miR-206, miR-133b, LHX8, and ZIC1 and downregulation of HOXC8 and HOXC9, coexists with an upregulation of two newly established brite/beige markers, TBX1 and TMEM26. A similar mRNA expression profile was observed when comparing isolated human adipocytes from BAT and white adipose tissue (WAT) depots, differentiated in vitro. In conclusion, our data suggest that human BAT might consist of both classical brown and recruitable brite adipocytes, an observation important for future considerations on how to induce human BAT.
|
|
