Your browser doesn't support javascript.
loading
Evaluating microarrays using a semiparametric approach: application to the central carbon metabolism of Escherichia coli BL21 and JM109.
Phue, Je-Nie; Kedem, Benjamin; Jaluria, Pratik; Shiloach, Joseph.
Affiliation
  • Phue JN; Biotechnology Unit, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Building 14A, Room 170, 9000 Rockville Pike, Bethesda, MD 20892, USA.
Genomics ; 89(2): 300-5, 2007 Feb.
Article in En | MEDLINE | ID: mdl-17125967
ABSTRACT
Escherichia coli K (JM109) and E. coli B (BL21) are strains used routinely for recombinant protein production. These two strains grow and respond differently to environmental factors such as glucose and oxygen concentration. The differences have been attributed to differential expression of individual genes that constitute certain metabolic pathways that are part of the central carbon metabolism. By implementing a semiparametric algorithm, which is based on a density ratio model, it was possible to compare and quantify the expression patterns of groups of genes involved in several central carbon metabolic pathways. The groups comprising the glyoxylate shunt, TCA cycle, fatty acid, and gluconeogenesis and anaplerotic pathways were expressed differently between the two strains, whereas no differences were apparent for the groups comprising either glycolysis or the pentose phosphate pathway. These results further characterized differences between the two E. coli strains and illustrated the potency of the semiparametric algorithm.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Carbon / Oligonucleotide Array Sequence Analysis / Escherichia coli Type of study: Evaluation_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Genomics Journal subject: GENETICA Year: 2007 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Carbon / Oligonucleotide Array Sequence Analysis / Escherichia coli Type of study: Evaluation_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Genomics Journal subject: GENETICA Year: 2007 Type: Article Affiliation country: United States