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Comparative 2D-DIGE proteomic analysis of bovine mammary epithelial cells during lactation reveals protein signatures for lactation persistency and milk yield.

Janjanam J, Singh S, Jena MK, Varshney N, Kola S, Kumar S, Kaushik JK, Grover S, Dang AK, Mukesh M, Prakash BS, Mohanty AK - PLoS ONE (2014)

Bottom Line: Bioinformatics analysis showed that a majority of the differentially expressed proteins are associated in metabolic process, catalytic and binding activity.The differentially expressed proteins were mapped to the available biological pathways and networks involved in lactation.The proteins up-regulated during late stage of lactation are associated with NF-κB stress induced signaling pathways and whereas Akt, PI3K and p38/MAPK signaling pathways are associated with high milk production mediated through insulin hormone signaling.

View Article: PubMed Central - PubMed

Affiliation: Animal Biotechnology Center, National Dairy Research Institute, Karnal, India.

ABSTRACT
Mammary gland is made up of a branching network of ducts that end with alveoli which surrounds the lumen. These alveolar mammary epithelial cells (MEC) reflect the milk producing ability of farm animals. In this study, we have used 2D-DIGE and mass spectrometry to identify the protein changes in MEC during immediate early, peak and late stages of lactation and also compared differentially expressed proteins in MEC isolated from milk of high and low milk producing cows. We have identified 41 differentially expressed proteins during lactation stages and 22 proteins in high and low milk yielding cows. Bioinformatics analysis showed that a majority of the differentially expressed proteins are associated in metabolic process, catalytic and binding activity. The differentially expressed proteins were mapped to the available biological pathways and networks involved in lactation. The proteins up-regulated during late stage of lactation are associated with NF-κB stress induced signaling pathways and whereas Akt, PI3K and p38/MAPK signaling pathways are associated with high milk production mediated through insulin hormone signaling.

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Unsupervised Hierarchical Clustering (HC).The expression maps and spot maps with relative expression values for each are displayed as heat map using a relative scale from −1 (green) to +1 (red). A. HC of total differentially regulated proteins identified at different stages of lactation and B. HC of total differentially regulated proteins identified from high and low milk yielding samples.
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pone-0102515-g006: Unsupervised Hierarchical Clustering (HC).The expression maps and spot maps with relative expression values for each are displayed as heat map using a relative scale from −1 (green) to +1 (red). A. HC of total differentially regulated proteins identified at different stages of lactation and B. HC of total differentially regulated proteins identified from high and low milk yielding samples.

Mentions: Unsupervised PCA and HC were performed to further validate the experimental samples for relevance of differentially expressed genes. These multivariate statistical tests and network mapping of identified proteins establish biological significance of the resulting protein changes. PCA reduces the dimensionality of a multidimensional analysis to display the two principal components that distinguish between the two large sources of variation within the dataset. PCA indicated distinct expression patterns from the three groups of each experiment and demonstrated high reproducibility between the replicate samples (Figure 5). Each data point in the PCA plots describes the collective expression profiles for the subset of proteins identified. The differentially expressed features identified at different stages of lactation, the first principal component distinguished 54.9% of the variance with 40.6% additional variation distinguished by the second principal component. Whereas the differentially expressed proteins of high and low yielding samples represent 68.1% and 16.6% of PC1 and PC2 respectively. In addition, the PCAs demonstrate that the greatest amounts of variation in the experiments are what distinguish the late stage from other two stages and low-yielder samples from both high-yielding and KF samples. These grouping assignments were reiterated in an unsupervised HC analysis of the protein expression patterns within each sample from the experiments (Figure 6). HC performs a similar clustering of the samples based on similarities of expression patterns in the selected proteins, which are visually presented as horizontal lines in an expression matrix “heat map” using a standardized log abundance scale ranging from −1.0 (green) to +1.0 (red). HC expression matrices were calculated using Euclidean correlation and average linkage. Each column in the HC expression matrix is effectively the same as each data point in the PCA plots. The PCA and HC results validate the biological significance of the protein expression changes identified in both the experimental groups. We would not expect these individual samples to cluster in this way if the changes arose stochastically. Some of the differentially expressed spots were graphically represented in supporting figure S1.


Comparative 2D-DIGE proteomic analysis of bovine mammary epithelial cells during lactation reveals protein signatures for lactation persistency and milk yield.

Janjanam J, Singh S, Jena MK, Varshney N, Kola S, Kumar S, Kaushik JK, Grover S, Dang AK, Mukesh M, Prakash BS, Mohanty AK - PLoS ONE (2014)

Unsupervised Hierarchical Clustering (HC).The expression maps and spot maps with relative expression values for each are displayed as heat map using a relative scale from −1 (green) to +1 (red). A. HC of total differentially regulated proteins identified at different stages of lactation and B. HC of total differentially regulated proteins identified from high and low milk yielding samples.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4128602&req=5

pone-0102515-g006: Unsupervised Hierarchical Clustering (HC).The expression maps and spot maps with relative expression values for each are displayed as heat map using a relative scale from −1 (green) to +1 (red). A. HC of total differentially regulated proteins identified at different stages of lactation and B. HC of total differentially regulated proteins identified from high and low milk yielding samples.
Mentions: Unsupervised PCA and HC were performed to further validate the experimental samples for relevance of differentially expressed genes. These multivariate statistical tests and network mapping of identified proteins establish biological significance of the resulting protein changes. PCA reduces the dimensionality of a multidimensional analysis to display the two principal components that distinguish between the two large sources of variation within the dataset. PCA indicated distinct expression patterns from the three groups of each experiment and demonstrated high reproducibility between the replicate samples (Figure 5). Each data point in the PCA plots describes the collective expression profiles for the subset of proteins identified. The differentially expressed features identified at different stages of lactation, the first principal component distinguished 54.9% of the variance with 40.6% additional variation distinguished by the second principal component. Whereas the differentially expressed proteins of high and low yielding samples represent 68.1% and 16.6% of PC1 and PC2 respectively. In addition, the PCAs demonstrate that the greatest amounts of variation in the experiments are what distinguish the late stage from other two stages and low-yielder samples from both high-yielding and KF samples. These grouping assignments were reiterated in an unsupervised HC analysis of the protein expression patterns within each sample from the experiments (Figure 6). HC performs a similar clustering of the samples based on similarities of expression patterns in the selected proteins, which are visually presented as horizontal lines in an expression matrix “heat map” using a standardized log abundance scale ranging from −1.0 (green) to +1.0 (red). HC expression matrices were calculated using Euclidean correlation and average linkage. Each column in the HC expression matrix is effectively the same as each data point in the PCA plots. The PCA and HC results validate the biological significance of the protein expression changes identified in both the experimental groups. We would not expect these individual samples to cluster in this way if the changes arose stochastically. Some of the differentially expressed spots were graphically represented in supporting figure S1.

Bottom Line: Bioinformatics analysis showed that a majority of the differentially expressed proteins are associated in metabolic process, catalytic and binding activity.The differentially expressed proteins were mapped to the available biological pathways and networks involved in lactation.The proteins up-regulated during late stage of lactation are associated with NF-κB stress induced signaling pathways and whereas Akt, PI3K and p38/MAPK signaling pathways are associated with high milk production mediated through insulin hormone signaling.

View Article: PubMed Central - PubMed

Affiliation: Animal Biotechnology Center, National Dairy Research Institute, Karnal, India.

ABSTRACT
Mammary gland is made up of a branching network of ducts that end with alveoli which surrounds the lumen. These alveolar mammary epithelial cells (MEC) reflect the milk producing ability of farm animals. In this study, we have used 2D-DIGE and mass spectrometry to identify the protein changes in MEC during immediate early, peak and late stages of lactation and also compared differentially expressed proteins in MEC isolated from milk of high and low milk producing cows. We have identified 41 differentially expressed proteins during lactation stages and 22 proteins in high and low milk yielding cows. Bioinformatics analysis showed that a majority of the differentially expressed proteins are associated in metabolic process, catalytic and binding activity. The differentially expressed proteins were mapped to the available biological pathways and networks involved in lactation. The proteins up-regulated during late stage of lactation are associated with NF-κB stress induced signaling pathways and whereas Akt, PI3K and p38/MAPK signaling pathways are associated with high milk production mediated through insulin hormone signaling.

Show MeSH
Related in: MedlinePlus