Burkholderia cepacia is an opportunistic pathogen for cystic fibrosis patients but is very beneficial to plants and the environment. Very few proteomic studies have been carried out with this bacterium because of the lack of a sequenced genome. In this research the bacterial proteome was divided into three fractions: extracellular, intra-cellular and cell surface. The fractions were analyzed separately using several different mass spectrometric methods such as LC-MS/MS and LC/LC-MS/MS (MudPIT). SEQUEST and XTANDEM database search algorithms were used to interpret the mass spectra obtained and data were searched against a database consisting of all sequenced Burkholderia species. Each sample of extracted proteins was divided into two parts and one part was separated by 1D-SDSPAGE and digested with trypsin using a liquid handling robot prior to LC-MS/MS analysis. The other part was manually digested with Lys C and then trypsin and loaded into a cation exchange column. Peptides were separated using an ammonium acetate buffer gradient followed by a C18 reverse phase separation, and then nano-electrosprayed into a mass spectrometer (MudPIT). Data obtained from both methods were compared and combined to get an extensive coverage of the proteome of the bacteria. Based on the preliminary results, a MudPIT analysis provides more protein IDs than a gel separated LC/MSMS experiment. Among the proteins identified there were several low abundance virulence factors including phasing, flagellin and porin, indicating that mass spectrometry can be used to identify low abundance proteins as an alternative to expressing the proteins in other organisms.