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Kinotypes: stable species- and individual-specific profiles of cellular kinase activity.

Trost B, Kindrachuk J, Scruten E, Griebel P, Kusalik A, Napper S - BMC Genomics (2013)

Bottom Line: Both humans and pigs also exhibited evidence for individual-specific kinome profiles that were independent of natural changes in blood cell populations.Species-specific kinotypes could have applications in disease research by facilitating the selection of appropriate animal models or by revealing a baseline kinomic signature to which treatment-induced profiles could be compared.Similarly, individual-specific kinotypes could have implications in personalized medicine, where the identification of molecular patterns or signatures within the kinome may depend on both the levels of kinome diversity and temporal stability across individuals.

View Article: PubMed Central - HTML - PubMed

Affiliation: Vaccine and Infectious Disease Organization, University of Saskatchewan, Saskatoon, Canada. scott.napper@usask.ca.

ABSTRACT

Background: Recently, questions have been raised regarding the ability of animal models to recapitulate human disease at the molecular level. It has also been demonstrated that cellular kinases, individually or as a collective unit (the kinome), play critical roles in regulating complex biology. Despite the intimate relationship between kinases and health, little is known about the variability, consistency and stability of kinome profiles across species and individuals.

Results: As a preliminary investigation of the existence of species- and individual-specific kinotypes (kinome signatures), peptide arrays were employed for the analysis of peripheral blood mononuclear cells collected weekly from human and porcine subjects (n = 6) over a one month period. The data revealed strong evidence for species-specific signalling profiles. Both humans and pigs also exhibited evidence for individual-specific kinome profiles that were independent of natural changes in blood cell populations.

Conclusions: Species-specific kinotypes could have applications in disease research by facilitating the selection of appropriate animal models or by revealing a baseline kinomic signature to which treatment-induced profiles could be compared. Similarly, individual-specific kinotypes could have implications in personalized medicine, where the identification of molecular patterns or signatures within the kinome may depend on both the levels of kinome diversity and temporal stability across individuals.

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Clustering of human kinome profiles. (a) Hierarchical clustering of human kinome profiles. For details, see the caption for Figure 1a. (b) Distribution of random tree scores. For comparison, the score of the actual tree shown in part A is 62.5. (c) Three dimensional PCA. Individual subjects (H1, H2, H3, H4, H5, and H6) are color-coded. (d) Correlation between PBMC composition and kinome profiles. The Euclidean distance was calculated between each of the C (4,2) = 6 possible pairs of samples from the same individual both for cell counts (as given in Table 1) and for kinome profile (average normalized intensity values for each peptide on the corresponding array). The six Euclidean distances were then averaged for a given individual, giving a single number that represents the level of variation in either cell counts or kinome profile for that individual.
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Figure 2: Clustering of human kinome profiles. (a) Hierarchical clustering of human kinome profiles. For details, see the caption for Figure 1a. (b) Distribution of random tree scores. For comparison, the score of the actual tree shown in part A is 62.5. (c) Three dimensional PCA. Individual subjects (H1, H2, H3, H4, H5, and H6) are color-coded. (d) Correlation between PBMC composition and kinome profiles. The Euclidean distance was calculated between each of the C (4,2) = 6 possible pairs of samples from the same individual both for cell counts (as given in Table 1) and for kinome profile (average normalized intensity values for each peptide on the corresponding array). The six Euclidean distances were then averaged for a given individual, giving a single number that represents the level of variation in either cell counts or kinome profile for that individual.

Mentions: Having demonstrated a species-specific kinotype, we investigated whether individual-specific kinomic patterns exist within members of the same species. The human subjects were investigated first as they were considered to be more likely to display significant individual differences due to variability in age, gender, race and lifestyle. Hierarchical clustering analysis revealed a clear trend for samples from the same individual to cluster together (Figure 2a). The score calculated for the corresponding tree was T = 62.5. This score was not equaled or exceeded by any of the 10,000 random trees, with the highest random tree score being 54.2, and only 0.6% of the random trees having a score >33.3 (Figure 2b). This comparison again gave a P-value <0.0001, supporting the hypothesis that individual-specific patterns of kinome activity exist within human PBMCs. The results of the clustering analysis were further verified using principal component analysis (PCA). The values of the first three principal components were calculated for each human sample and a three-dimensional scatterplot was created (Figure 2c). As with the hierarchical clustering, there was a strong trend for the kinome profiles to segregate on the basis of individual.


Kinotypes: stable species- and individual-specific profiles of cellular kinase activity.

Trost B, Kindrachuk J, Scruten E, Griebel P, Kusalik A, Napper S - BMC Genomics (2013)

Clustering of human kinome profiles. (a) Hierarchical clustering of human kinome profiles. For details, see the caption for Figure 1a. (b) Distribution of random tree scores. For comparison, the score of the actual tree shown in part A is 62.5. (c) Three dimensional PCA. Individual subjects (H1, H2, H3, H4, H5, and H6) are color-coded. (d) Correlation between PBMC composition and kinome profiles. The Euclidean distance was calculated between each of the C (4,2) = 6 possible pairs of samples from the same individual both for cell counts (as given in Table 1) and for kinome profile (average normalized intensity values for each peptide on the corresponding array). The six Euclidean distances were then averaged for a given individual, giving a single number that represents the level of variation in either cell counts or kinome profile for that individual.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3924188&req=5

Figure 2: Clustering of human kinome profiles. (a) Hierarchical clustering of human kinome profiles. For details, see the caption for Figure 1a. (b) Distribution of random tree scores. For comparison, the score of the actual tree shown in part A is 62.5. (c) Three dimensional PCA. Individual subjects (H1, H2, H3, H4, H5, and H6) are color-coded. (d) Correlation between PBMC composition and kinome profiles. The Euclidean distance was calculated between each of the C (4,2) = 6 possible pairs of samples from the same individual both for cell counts (as given in Table 1) and for kinome profile (average normalized intensity values for each peptide on the corresponding array). The six Euclidean distances were then averaged for a given individual, giving a single number that represents the level of variation in either cell counts or kinome profile for that individual.
Mentions: Having demonstrated a species-specific kinotype, we investigated whether individual-specific kinomic patterns exist within members of the same species. The human subjects were investigated first as they were considered to be more likely to display significant individual differences due to variability in age, gender, race and lifestyle. Hierarchical clustering analysis revealed a clear trend for samples from the same individual to cluster together (Figure 2a). The score calculated for the corresponding tree was T = 62.5. This score was not equaled or exceeded by any of the 10,000 random trees, with the highest random tree score being 54.2, and only 0.6% of the random trees having a score >33.3 (Figure 2b). This comparison again gave a P-value <0.0001, supporting the hypothesis that individual-specific patterns of kinome activity exist within human PBMCs. The results of the clustering analysis were further verified using principal component analysis (PCA). The values of the first three principal components were calculated for each human sample and a three-dimensional scatterplot was created (Figure 2c). As with the hierarchical clustering, there was a strong trend for the kinome profiles to segregate on the basis of individual.

Bottom Line: Both humans and pigs also exhibited evidence for individual-specific kinome profiles that were independent of natural changes in blood cell populations.Species-specific kinotypes could have applications in disease research by facilitating the selection of appropriate animal models or by revealing a baseline kinomic signature to which treatment-induced profiles could be compared.Similarly, individual-specific kinotypes could have implications in personalized medicine, where the identification of molecular patterns or signatures within the kinome may depend on both the levels of kinome diversity and temporal stability across individuals.

View Article: PubMed Central - HTML - PubMed

Affiliation: Vaccine and Infectious Disease Organization, University of Saskatchewan, Saskatoon, Canada. scott.napper@usask.ca.

ABSTRACT

Background: Recently, questions have been raised regarding the ability of animal models to recapitulate human disease at the molecular level. It has also been demonstrated that cellular kinases, individually or as a collective unit (the kinome), play critical roles in regulating complex biology. Despite the intimate relationship between kinases and health, little is known about the variability, consistency and stability of kinome profiles across species and individuals.

Results: As a preliminary investigation of the existence of species- and individual-specific kinotypes (kinome signatures), peptide arrays were employed for the analysis of peripheral blood mononuclear cells collected weekly from human and porcine subjects (n = 6) over a one month period. The data revealed strong evidence for species-specific signalling profiles. Both humans and pigs also exhibited evidence for individual-specific kinome profiles that were independent of natural changes in blood cell populations.

Conclusions: Species-specific kinotypes could have applications in disease research by facilitating the selection of appropriate animal models or by revealing a baseline kinomic signature to which treatment-induced profiles could be compared. Similarly, individual-specific kinotypes could have implications in personalized medicine, where the identification of molecular patterns or signatures within the kinome may depend on both the levels of kinome diversity and temporal stability across individuals.

Show MeSH