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Effects of subminimum inhibitory concentrations of antibiotics on the Pasteurella multocida proteome: a systems approach.

Nanduri B, Lawrence ML, Peddinti DS, Burgess SC - Comp. Funct. Genomics (2008)

Bottom Line: We then overlaid the differential protein expression data onto the P. multocida protein interaction network to study the bacterial response.We identified proteins that could enhance antimicrobial activity.Overall compensatory response to antibiotics was characterized by altered expression of proteins involved in purine metabolism, stress response, and cell envelope permeability.

View Article: PubMed Central - PubMed

Affiliation: College of Veterinary Medicine, Mississippi State University, Mississippi State, MS 39762, USA.

ABSTRACT
To identify key regulators of subminimum inhibitory concentration (sub-MIC) antibiotic response in the Pasteurella multocida proteome, we applied systems approaches. Using 2D-LC-ESI-MS(2), we achieved 53% proteome coverage. To study the differential protein expression in response to sub-MIC antibiotics in the context of protein interaction networks, we inferred P. multocida Pm70 protein interaction network from orthologous proteins. We then overlaid the differential protein expression data onto the P. multocida protein interaction network to study the bacterial response. We identified proteins that could enhance antimicrobial activity. Overall compensatory response to antibiotics was characterized by altered expression of proteins involved in purine metabolism, stress response, and cell envelope permeability.

No MeSH data available.


Related in: MedlinePlus

Representation of P. multocida proteins in PSORTb subcellular locations. Percent coverage for each PSORTb predicted subcellularlocalization for P.multocida proteinsidentified in this study is shown. Percent representation was calculated bycomparing the number of proteins identified in each category to the totalnumber of proteins predicted to be in that category from P. multocida genome. PSORTb prediction “unknown*” indicates thatthe proteins may have multiple subcellular localizations while unknown refersto location unknown.
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fig1: Representation of P. multocida proteins in PSORTb subcellular locations. Percent coverage for each PSORTb predicted subcellularlocalization for P.multocida proteinsidentified in this study is shown. Percent representation was calculated bycomparing the number of proteins identified in each category to the totalnumber of proteins predicted to be in that category from P. multocida genome. PSORTb prediction “unknown*” indicates thatthe proteins may have multiple subcellular localizations while unknown refersto location unknown.

Mentions: Furthermore, because protein function depends on cellular location, a systems-wide analysis requiresthat we identify proteins from all cell locations. We used the PSORTb version2.0 bacterial protein subcellular localization prediction tool to classify allproteins in our dataset [28]. PSORTb has an overallprecision of 96% and places all Pm70 proteins into seven categories: extracellular(4), outer membrane (49), periplasmic (61), cytoplasmic membrane (411), cytoplasmic(774), unknown (with multiple localization sites) (37), and unknown (679). To determine the percent coverage in each ofthese categories, the number of proteins identified in each category wascompared to the total number of proteins predicted to be in that category fromthe genome (Figure 1). The average coveragefor each subcellular compartment in our data was 59%, and although proteinsfrom all subcellular compartments were represented, not all subcellularcompartments were equally represented. We identified more outer membrane andperiplasmic proteins (84% and 75%, resp.), than cytoplasmic membrane proteins (36%).


Effects of subminimum inhibitory concentrations of antibiotics on the Pasteurella multocida proteome: a systems approach.

Nanduri B, Lawrence ML, Peddinti DS, Burgess SC - Comp. Funct. Genomics (2008)

Representation of P. multocida proteins in PSORTb subcellular locations. Percent coverage for each PSORTb predicted subcellularlocalization for P.multocida proteinsidentified in this study is shown. Percent representation was calculated bycomparing the number of proteins identified in each category to the totalnumber of proteins predicted to be in that category from P. multocida genome. PSORTb prediction “unknown*” indicates thatthe proteins may have multiple subcellular localizations while unknown refersto location unknown.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2367384&req=5

fig1: Representation of P. multocida proteins in PSORTb subcellular locations. Percent coverage for each PSORTb predicted subcellularlocalization for P.multocida proteinsidentified in this study is shown. Percent representation was calculated bycomparing the number of proteins identified in each category to the totalnumber of proteins predicted to be in that category from P. multocida genome. PSORTb prediction “unknown*” indicates thatthe proteins may have multiple subcellular localizations while unknown refersto location unknown.
Mentions: Furthermore, because protein function depends on cellular location, a systems-wide analysis requiresthat we identify proteins from all cell locations. We used the PSORTb version2.0 bacterial protein subcellular localization prediction tool to classify allproteins in our dataset [28]. PSORTb has an overallprecision of 96% and places all Pm70 proteins into seven categories: extracellular(4), outer membrane (49), periplasmic (61), cytoplasmic membrane (411), cytoplasmic(774), unknown (with multiple localization sites) (37), and unknown (679). To determine the percent coverage in each ofthese categories, the number of proteins identified in each category wascompared to the total number of proteins predicted to be in that category fromthe genome (Figure 1). The average coveragefor each subcellular compartment in our data was 59%, and although proteinsfrom all subcellular compartments were represented, not all subcellularcompartments were equally represented. We identified more outer membrane andperiplasmic proteins (84% and 75%, resp.), than cytoplasmic membrane proteins (36%).

Bottom Line: We then overlaid the differential protein expression data onto the P. multocida protein interaction network to study the bacterial response.We identified proteins that could enhance antimicrobial activity.Overall compensatory response to antibiotics was characterized by altered expression of proteins involved in purine metabolism, stress response, and cell envelope permeability.

View Article: PubMed Central - PubMed

Affiliation: College of Veterinary Medicine, Mississippi State University, Mississippi State, MS 39762, USA.

ABSTRACT
To identify key regulators of subminimum inhibitory concentration (sub-MIC) antibiotic response in the Pasteurella multocida proteome, we applied systems approaches. Using 2D-LC-ESI-MS(2), we achieved 53% proteome coverage. To study the differential protein expression in response to sub-MIC antibiotics in the context of protein interaction networks, we inferred P. multocida Pm70 protein interaction network from orthologous proteins. We then overlaid the differential protein expression data onto the P. multocida protein interaction network to study the bacterial response. We identified proteins that could enhance antimicrobial activity. Overall compensatory response to antibiotics was characterized by altered expression of proteins involved in purine metabolism, stress response, and cell envelope permeability.

No MeSH data available.


Related in: MedlinePlus