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Conditional independence mapping of DIGE data reveals PDIA3 protein species as key nodes associated with muscle aerobic capacity.

Burniston JG, Kenyani J, Gray D, Guadagnin E, Jarman IH, Cobley JN, Cuthbertson DJ, Chen YW, Wastling JM, Lisboa PJ, Koch LG, Britton SL - J Proteomics (2014)

Bottom Line: Forty protein species were differentially (P<0.05, FDR<10%) expressed between HCR and LCR and conditional independence mapping found distinct networks within these data, which brought insight beyond that achieved by functional annotation.Instead we found that noncanonical STAT3 signalling may be associated with low exercise capacity and skeletal muscle insulin resistance.Moreover, we demonstrate that this novel approach can be applied to 2D gel analysis, which is unsurpassed in its ability to profile protein species but currently has few dedicated bioinformatic tools.

View Article: PubMed Central - PubMed

Affiliation: Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK. Electronic address: j.burniston@ljmu.ac.uk.

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Conditional independence maps of tercile and quintile associations. Conditional independence mapping was used to find multivariate association networks within the protein spots differentially expressed between HCR and LCR muscle (Table 4). Log-transformed continuous data of spot expression were converted to categorical terciles (A) or quintiles (B) to assess course- and fine-grain associations, respectively. To construct the tercile map α was set at 0.05, whereas more stringent (α = 0.01) testing was used in the construction of the quintile map. Post-hoc pair-wise testing was used to approximate the relative strength of associations between vertices in order to dictate edge length (shorter edge = stronger association) during the construction of each map. Spot numbers and protein names correspond with Fig. 1, Table 4 and the World-2DPAGE database (accession #0069).
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Figure 3: Conditional independence maps of tercile and quintile associations. Conditional independence mapping was used to find multivariate association networks within the protein spots differentially expressed between HCR and LCR muscle (Table 4). Log-transformed continuous data of spot expression were converted to categorical terciles (A) or quintiles (B) to assess course- and fine-grain associations, respectively. To construct the tercile map α was set at 0.05, whereas more stringent (α = 0.01) testing was used in the construction of the quintile map. Post-hoc pair-wise testing was used to approximate the relative strength of associations between vertices in order to dictate edge length (shorter edge = stronger association) during the construction of each map. Spot numbers and protein names correspond with Fig. 1, Table 4 and the World-2DPAGE database (accession #0069).

Mentions: Conditional independence maps of course- and fine-grain associations within the DIGE data were complementary with the functional enrichment analysis and also highlighted important additional information. Course-grain mapping (Fig. 3A) based on significant (α = 0.05) associations found using tercile categorisation of the data highlighted 3 clusters focusing on 60 kDa heat shock protein (CH60; spot #328), protein disulphide isomerase A3 (PDIA3; spot #210) and hypoxanthine–guanine phosphoribosyltransferase (HPRT; spot #757). The cluster centred on CH60 primarily consisted of mitochondrial proteins, which is consistent with the functional enrichment analysis and the key role of CH60 in mitochondrial protein import. A second PDIA3 spot (#206) linked the two principal clusters of CH60/spot #238 and PDIA3/spot #210. Thus protein species of PDIA3 were connected with a large number of the differentially regulated proteins and may also provide a link to the different mitochondrial and aerobic capacities of HCR and LCR muscle. PDIA3 (spot #210) became the most prominent feature when more stringent (α = 0.01) conditional independence mapping was performed on quintile categorised data (Fig. 3B) but the link with theCH60was broken. The PDIA3 cluster included, amongst others, PDIA3 spot (#206) and serine protease inhibitor A3K (spot #539), which was the spot exhibiting the greatest difference (3.18-fold) between HCR and LCR muscle. Post-hoc testing revealed that the strongest associations with PDIA3 spot #210 wereNDRG2 (spot #433; K = 1.1761), fumarate hydratase (FUMH, spot #426; K = 1.1761) and very long-chain acetyl CoA dehydrogenase (ACADV, spot #65; K = 1.1573).


Conditional independence mapping of DIGE data reveals PDIA3 protein species as key nodes associated with muscle aerobic capacity.

Burniston JG, Kenyani J, Gray D, Guadagnin E, Jarman IH, Cobley JN, Cuthbertson DJ, Chen YW, Wastling JM, Lisboa PJ, Koch LG, Britton SL - J Proteomics (2014)

Conditional independence maps of tercile and quintile associations. Conditional independence mapping was used to find multivariate association networks within the protein spots differentially expressed between HCR and LCR muscle (Table 4). Log-transformed continuous data of spot expression were converted to categorical terciles (A) or quintiles (B) to assess course- and fine-grain associations, respectively. To construct the tercile map α was set at 0.05, whereas more stringent (α = 0.01) testing was used in the construction of the quintile map. Post-hoc pair-wise testing was used to approximate the relative strength of associations between vertices in order to dictate edge length (shorter edge = stronger association) during the construction of each map. Spot numbers and protein names correspond with Fig. 1, Table 4 and the World-2DPAGE database (accession #0069).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4150023&req=5

Figure 3: Conditional independence maps of tercile and quintile associations. Conditional independence mapping was used to find multivariate association networks within the protein spots differentially expressed between HCR and LCR muscle (Table 4). Log-transformed continuous data of spot expression were converted to categorical terciles (A) or quintiles (B) to assess course- and fine-grain associations, respectively. To construct the tercile map α was set at 0.05, whereas more stringent (α = 0.01) testing was used in the construction of the quintile map. Post-hoc pair-wise testing was used to approximate the relative strength of associations between vertices in order to dictate edge length (shorter edge = stronger association) during the construction of each map. Spot numbers and protein names correspond with Fig. 1, Table 4 and the World-2DPAGE database (accession #0069).
Mentions: Conditional independence maps of course- and fine-grain associations within the DIGE data were complementary with the functional enrichment analysis and also highlighted important additional information. Course-grain mapping (Fig. 3A) based on significant (α = 0.05) associations found using tercile categorisation of the data highlighted 3 clusters focusing on 60 kDa heat shock protein (CH60; spot #328), protein disulphide isomerase A3 (PDIA3; spot #210) and hypoxanthine–guanine phosphoribosyltransferase (HPRT; spot #757). The cluster centred on CH60 primarily consisted of mitochondrial proteins, which is consistent with the functional enrichment analysis and the key role of CH60 in mitochondrial protein import. A second PDIA3 spot (#206) linked the two principal clusters of CH60/spot #238 and PDIA3/spot #210. Thus protein species of PDIA3 were connected with a large number of the differentially regulated proteins and may also provide a link to the different mitochondrial and aerobic capacities of HCR and LCR muscle. PDIA3 (spot #210) became the most prominent feature when more stringent (α = 0.01) conditional independence mapping was performed on quintile categorised data (Fig. 3B) but the link with theCH60was broken. The PDIA3 cluster included, amongst others, PDIA3 spot (#206) and serine protease inhibitor A3K (spot #539), which was the spot exhibiting the greatest difference (3.18-fold) between HCR and LCR muscle. Post-hoc testing revealed that the strongest associations with PDIA3 spot #210 wereNDRG2 (spot #433; K = 1.1761), fumarate hydratase (FUMH, spot #426; K = 1.1761) and very long-chain acetyl CoA dehydrogenase (ACADV, spot #65; K = 1.1573).

Bottom Line: Forty protein species were differentially (P<0.05, FDR<10%) expressed between HCR and LCR and conditional independence mapping found distinct networks within these data, which brought insight beyond that achieved by functional annotation.Instead we found that noncanonical STAT3 signalling may be associated with low exercise capacity and skeletal muscle insulin resistance.Moreover, we demonstrate that this novel approach can be applied to 2D gel analysis, which is unsurpassed in its ability to profile protein species but currently has few dedicated bioinformatic tools.

View Article: PubMed Central - PubMed

Affiliation: Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK. Electronic address: j.burniston@ljmu.ac.uk.

Show MeSH
Related in: MedlinePlus