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Identification of fur, aconitase, and other proteins expressed by Mycobacterium tuberculosis under conditions of low and high concentrations of iron by combined two-dimensional gel electrophoresis and mass spectrometry.

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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC96314/
No data is associated with this publication.
Creative Commons 'BY' version 4.0 license
Abstract

Iron plays a critical role in the pathophysiology of Mycobacterium tuberculosis. To gain a better understanding of iron regulation by this organism, we have used two-dimensional (2-D) gel electrophoresis, mass spectrometry, and database searching to study protein expression in M. tuberculosis under conditions of high and low iron concentration. Proteins in cellular extracts from M. tuberculosis Erdman strain grown under low-iron (1 microM) and high-iron (70 microM) conditions were separated by 2-D polyacrylamide gel electrophoresis, which allowed high-resolution separation of several hundred proteins, as visualized by Coomassie staining. The expression of at least 15 proteins was induced, and the expression of at least 12 proteins was decreased under low-iron conditions. In-gel trypsin digestion was performed on these differentially expressed proteins, and the digestion mixtures were analyzed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry to determine the molecular masses of the resulting tryptic peptides. Partial sequence data on some of the peptides were obtained by using after source decay and/or collision-induced dissociation. The fragmentation data were used to search computerized peptide mass and protein sequence databases for known proteins. Ten iron-regulated proteins were identified, including Fur and aconitase proteins, both of which are known to be regulated by iron in other bacterial systems. Our study shows that, where large protein sequence databases are available from genomic studies, the combined use of 2-D gel electrophoresis, mass spectrometry, and database searching to analyze proteins expressed under defined environmental conditions is a powerful tool for identifying expressed proteins and their physiologic relevance.

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