Identification of a Metabolizing Enzyme in Human Kidney by Proteomic Correlation Profiling

• Published in: Molecular & cellular proteomics Vol. 12; no. 8; pp. 2313 - 2323
• Main Authors: Sakurai, Hidetaka, Kubota, Kazuishi, Inaba, Shin-ichi, Takanaka, Kaoru, Shinagawa, Akira
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.08.2013; The American Society for Biochemistry and Molecular Biology
• Subjects: Alkaline Phosphatase - isolation & purification; Alkaline Phosphatase - metabolism; Amino Alcohols - metabolism; Fingolimod Hydrochloride; Humans; Immunosuppressive Agents - metabolism; Isoenzymes - isolation & purification; Isoenzymes - metabolism; Kidney - enzymology; Propylene Glycols - metabolism; Proteomics - methods; Pyrroles - metabolism; Sphingosine - analogs & derivatives; Sphingosine - metabolism
• ISSN: 1535-9476; 1535-9484
• DOI: 10.1074/mcp.M112.023853

Molecular identification of endogenous enzymes and biologically active substances from complex biological sources remains a challenging task, and although traditional biochemical purification is sometimes regarded as outdated, it remains one of the most powerful methodologies for this purpose. While biochemical purification usually requires large amounts of starting material and many separation steps, we developed an advanced method named “proteomic correlation profiling” in our previous study. In proteomic correlation profiling, we first fractionated biological material by column chromatography, and then calculated each protein's correlation coefficient between the enzyme activity profile and protein abundance profile determined by proteomics technology toward fractions. Thereafter, we could choose possible candidates for the enzyme among proteins with a high correlation value by domain predictions using informatics tools. Ultimately, this streamlined procedure requires fewer purification steps and reduces starting materials dramatically due to low required purity compared with conventional approaches. To demonstrate the generality of this approach, we have now applied an improved workflow of proteomic correlation profiling to a drug metabolizing enzyme and successfully identified alkaline phosphatase, tissue-nonspecific isozyme (ALPL) as a phosphatase of CS-0777 phosphate (CS-0777-P), a selective sphingosine 1-phosphate receptor 1 modulator with potential benefits in the treatment of autoimmune diseases including multiple sclerosis, from human kidney extract. We identified ALPL as a candidate protein only by the 200-fold purification and only from 1 g of human kidney. The identification of ALPL as CS-0777-P phosphatase was strongly supported by a recombinant protein, and contribution of the enzyme in human kidney extract was validated by immunodepletion and a specific inhibitor. This approach can be applied to any kind of enzyme class and biologically active substance; therefore, we believe that we have provided a fast and practical option by combination of traditional biochemistry and state-of-the-art proteomic technology.