Add reference Rhodococcus jostii RHA1 is a catabolically versatile soil actinomycete that can utilize a wide range of organic compounds as growth substrates including steroids. To globally assess the adaptation of the protein composition in the membrane fraction to steroids, the membrane proteomes of RHA1 grown on each of cholesterol and cholate were compared to pyruvate-grown cells using gel-free SIMPLE-MudPIT technology. Label-free quantification by spectral counting revealed 59 significantly regulated proteins, many of them present only during growth on steroids. Cholesterol and cholate induced distinct sets of steroid-degrading enzymes encoded by paralogous gene clusters, consistent with transcriptomic studies. CamM and CamABCD, two systems that take up cholate metabolites, were found exclusively in cholate-grown cells. Similarly, 9 of the 10 Mce4 proteins of the cholesterol uptake system were found uniquely in cholesterol-grown cells. Bioinformatic tools were used to construct a model of Mce4 transporter within the RHA1 cell envelope. Finally, comparison of the membrane and cytoplasm proteomes indicated that several steroid-degrading enzymes are membrane-associated. The implications for the degradation of steroids by actinomycetes, including cholesterol by the pathogen Mycobacterium tuberculosis , are discussed. Bioinformatics and data processing: All database searches were performed using SEQUEST algorithm, embedded in BioworksTM (Rev. 3.3.1, Thermo Fisher Scientific Inc., Waltham, MA), with a RHA1 database containing 9145 sequences. Only tryptic peptides with up to two missed cleavages were accepted. No fixed modifications were considered. Oxidation of methionine was permitted as variable modification. The mass tolerance for precursor ions was set to 10 ppm; the mass tolerance for fragment ions was set to 1 amu. For protein identification a threshold for deltaCn (0.08) and for XCorr values was defined, depending on the peptide charge (>2.5 (+2); > 3.5 (+3)). A protein was considered identified if at least two different peptides met these criteria. To assess the false discovery rate (FDR) of protein identification, a database with reversed protein sequences was searched retaining the search parameters and filter criteria. The FDR was calculated by dividing the absolute number of hits from the reversed database through the sum of hits from both database searches (reversed database and original database). Using the stringent criteria described above, no reversed database hit was found; therefore, the FDR was 0% in all measurements. This low error rate can be attributed to the additional demand for two different peptide matches per protein, which eliminated all otherwise observed protein hits against the decoy database.