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Uncovering genes with divergent mRNA-protein dynamics in Streptomyces coelicolor.

Jayapal KP, Philp RJ, Kok YJ, Yap MG, Sherman DH, Griffin TJ, Hu WS - PLoS ONE (2008)

Bottom Line: Many biological processes are intrinsically dynamic, incurring profound changes at both molecular and physiological levels.Despite this overall correlation, by employing a systematic concordance analysis, we estimated that over 30% of the analyzed genes likely exhibited significantly divergent patterns, of which nearly one-third displayed even opposing trends.Our observations suggest that differences between mRNA and protein synthesis/degradation mechanisms are prominent in microbes while reaffirming the plausibility of such mechanisms acting in a concerted fashion at a protein complex or sub-pathway level.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota, United States of America.

ABSTRACT
Many biological processes are intrinsically dynamic, incurring profound changes at both molecular and physiological levels. Systems analyses of such processes incorporating large-scale transcriptome or proteome profiling can be quite revealing. Although consistency between mRNA and proteins is often implicitly assumed in many studies, examples of divergent trends are frequently observed. Here, we present a comparative transcriptome and proteome analysis of growth and stationary phase adaptation in Streptomyces coelicolor, taking the time-dynamics of process into consideration. These processes are of immense interest in microbiology as they pertain to the physiological transformations eliciting biosynthesis of many naturally occurring therapeutic agents. A shotgun proteomics approach based on mass spectrometric analysis of isobaric stable isotope labeled peptides (iTRAQ) enabled identification and rapid quantification of approximately 14% of the theoretical proteome of S. coelicolor. Independent principal component analyses of this and DNA microarray-derived transcriptome data revealed that the prominent patterns in both protein and mRNA domains are surprisingly well correlated. Despite this overall correlation, by employing a systematic concordance analysis, we estimated that over 30% of the analyzed genes likely exhibited significantly divergent patterns, of which nearly one-third displayed even opposing trends. Integrating this data with biological information, we discovered that certain groups of functionally related genes exhibit mRNA-protein discordance in a similar fashion. Our observations suggest that differences between mRNA and protein synthesis/degradation mechanisms are prominent in microbes while reaffirming the plausibility of such mechanisms acting in a concerted fashion at a protein complex or sub-pathway level.

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Relationship between CAI and protein identification or abundance.(A) Percentage of proteins identified in various CAI ranges. Values beside the bars represent the absolute number of proteins identified from each bin (B) Average CAI of identified proteins in different abundance groups; values in horizontal axis correspond to protein abundance, “10” indicating the top 10 percentile (most abundant) to “1” indicating the bottom 10 percentile (least abundant) proteins. Protein abundance was estimated from MS data using emPAI based on number of MS/MS spectral evidences (refer to Materials and Methods)
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pone-0002097-g002: Relationship between CAI and protein identification or abundance.(A) Percentage of proteins identified in various CAI ranges. Values beside the bars represent the absolute number of proteins identified from each bin (B) Average CAI of identified proteins in different abundance groups; values in horizontal axis correspond to protein abundance, “10” indicating the top 10 percentile (most abundant) to “1” indicating the bottom 10 percentile (least abundant) proteins. Protein abundance was estimated from MS data using emPAI based on number of MS/MS spectral evidences (refer to Materials and Methods)

Mentions: Several previous studies including one in S. coelicolor [16] have considered optimal codon usage in genes as a reliable indicator for enhanced protein expression. To examine if this is observed in our dataset, we calculated a Codon Adaptation Index (CAI, [17]) for every gene in S. coelicolor based on ribosomal genes as the reference set. CAI values range from 0 to 1 with higher values indicating optimal codon usage (i.e. codon usage trend similar to ribosomal genes in this case). Figure 2A shows the distribution of proteins identified from different CAI groups. Proteins in high CAI groups were significantly better represented in our identifications. In addition, even amongst those proteins identified, there is a definite positive correlation between CAI and exponentially modified protein abundance index (emPAI), a measure of protein abundance derived from the total number of spectral evidences contributing to a given protein identification [18] (Figure 2B). Also, based on emPAI calculations, some of the most abundant proteins in the cell were found to be the chaperones (GroES/EL1/EL2; SCO4296, 4761–62), elongation factor Tu-1 (SCO4662), a putative tellurium resistance protein (SCO4277) and a type I polyketide cluster reductase (SCO6282).


Uncovering genes with divergent mRNA-protein dynamics in Streptomyces coelicolor.

Jayapal KP, Philp RJ, Kok YJ, Yap MG, Sherman DH, Griffin TJ, Hu WS - PLoS ONE (2008)

Relationship between CAI and protein identification or abundance.(A) Percentage of proteins identified in various CAI ranges. Values beside the bars represent the absolute number of proteins identified from each bin (B) Average CAI of identified proteins in different abundance groups; values in horizontal axis correspond to protein abundance, “10” indicating the top 10 percentile (most abundant) to “1” indicating the bottom 10 percentile (least abundant) proteins. Protein abundance was estimated from MS data using emPAI based on number of MS/MS spectral evidences (refer to Materials and Methods)
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2367054&req=5

pone-0002097-g002: Relationship between CAI and protein identification or abundance.(A) Percentage of proteins identified in various CAI ranges. Values beside the bars represent the absolute number of proteins identified from each bin (B) Average CAI of identified proteins in different abundance groups; values in horizontal axis correspond to protein abundance, “10” indicating the top 10 percentile (most abundant) to “1” indicating the bottom 10 percentile (least abundant) proteins. Protein abundance was estimated from MS data using emPAI based on number of MS/MS spectral evidences (refer to Materials and Methods)
Mentions: Several previous studies including one in S. coelicolor [16] have considered optimal codon usage in genes as a reliable indicator for enhanced protein expression. To examine if this is observed in our dataset, we calculated a Codon Adaptation Index (CAI, [17]) for every gene in S. coelicolor based on ribosomal genes as the reference set. CAI values range from 0 to 1 with higher values indicating optimal codon usage (i.e. codon usage trend similar to ribosomal genes in this case). Figure 2A shows the distribution of proteins identified from different CAI groups. Proteins in high CAI groups were significantly better represented in our identifications. In addition, even amongst those proteins identified, there is a definite positive correlation between CAI and exponentially modified protein abundance index (emPAI), a measure of protein abundance derived from the total number of spectral evidences contributing to a given protein identification [18] (Figure 2B). Also, based on emPAI calculations, some of the most abundant proteins in the cell were found to be the chaperones (GroES/EL1/EL2; SCO4296, 4761–62), elongation factor Tu-1 (SCO4662), a putative tellurium resistance protein (SCO4277) and a type I polyketide cluster reductase (SCO6282).

Bottom Line: Many biological processes are intrinsically dynamic, incurring profound changes at both molecular and physiological levels.Despite this overall correlation, by employing a systematic concordance analysis, we estimated that over 30% of the analyzed genes likely exhibited significantly divergent patterns, of which nearly one-third displayed even opposing trends.Our observations suggest that differences between mRNA and protein synthesis/degradation mechanisms are prominent in microbes while reaffirming the plausibility of such mechanisms acting in a concerted fashion at a protein complex or sub-pathway level.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota, United States of America.

ABSTRACT
Many biological processes are intrinsically dynamic, incurring profound changes at both molecular and physiological levels. Systems analyses of such processes incorporating large-scale transcriptome or proteome profiling can be quite revealing. Although consistency between mRNA and proteins is often implicitly assumed in many studies, examples of divergent trends are frequently observed. Here, we present a comparative transcriptome and proteome analysis of growth and stationary phase adaptation in Streptomyces coelicolor, taking the time-dynamics of process into consideration. These processes are of immense interest in microbiology as they pertain to the physiological transformations eliciting biosynthesis of many naturally occurring therapeutic agents. A shotgun proteomics approach based on mass spectrometric analysis of isobaric stable isotope labeled peptides (iTRAQ) enabled identification and rapid quantification of approximately 14% of the theoretical proteome of S. coelicolor. Independent principal component analyses of this and DNA microarray-derived transcriptome data revealed that the prominent patterns in both protein and mRNA domains are surprisingly well correlated. Despite this overall correlation, by employing a systematic concordance analysis, we estimated that over 30% of the analyzed genes likely exhibited significantly divergent patterns, of which nearly one-third displayed even opposing trends. Integrating this data with biological information, we discovered that certain groups of functionally related genes exhibit mRNA-protein discordance in a similar fashion. Our observations suggest that differences between mRNA and protein synthesis/degradation mechanisms are prominent in microbes while reaffirming the plausibility of such mechanisms acting in a concerted fashion at a protein complex or sub-pathway level.

Show MeSH
Related in: MedlinePlus