Experimental data from our group suggested that adaptation to iron-deficiency is a sequential process dependant on the severity of the deficiency and that the adaptive process requires the remodeling of the photosynthetic apparatus (1, 2). To identify proteins that respond to various degrees of iron-deprivation we enriched mitochondria and chloroplasts from C. reinhardtii cells at different stages of iron-deficiency (from mild to severe) and isolated chloroplast and mitochondrial membranes. Membranes were separated by one and two-dimensional gel electrophoresis, protein bands and spots were excised out of the gel, digested in-gel with trypsin and analyzed by tandem mass spectrometry (MS/MS). The MS/MS data were further evaluated using Sequest (3) and de novo amino acid sequencing in conjunction with a new algorithm we devised, the GenomicPeptideFinder (GPF), which enables detection of intron-split and/or alternatively spliced peptides when deduced from genomic DNA (4). We generated a platform where high throughput de novo sequencing of MS/MS spectra is combined with GPF performance operating on a 128 node computer cluster. The concerted action of Sequest and GPF allowed identification of about 12000 unique peptides, including about 960 intron-spit peptides, resulting in the identification of novel proteins and improved annotation of proteins. Using this list of identified protein we are currently performing comparative quantitative proteomics. For comparative quantitative peptide analysis we are taking advantage of stable isotope labeling by amino acids in Chlamydomonas (2). The protein samples are analyzed by the application of high resolution protein separation techniques in combination with liquid chromatography-MS/MS. We have at present quantified more than 60 distinct thylakoid or inner-membrane proteins, allowing thorough insights into adaptation of the bioenergetic machinery to iron-deprivation. Interestingly among the proteins, two newly identified hypothetical proteins were largely induced by iron-deficiency and may represent key players in the regulatory circuits operating in cellular iron-homeostasis.
We propose that our data-mining strategy will be very useful to explore nuclear gene structures and identify alternative splicing in eukaryotic organism with complex genomes, in general. We further propose that complex protein networks, like in iron-homeostasis, could be dissected in respect to identity and dynamics of the players by combing in genomic data mining with quantitative proteomics.
1. Moseley, J. L., Allinger, T., Herzog, S., Hoerth, P., Wehinger, E., Merchant, S. & Hippler, M. (2002) EMBO J 21, 6709-20.
2. Naumann, B., Stauber, E. J., Busch, A., Sommer, F. & Hippler, M. (2005) J Biol Chem 280, 20431-41.
3. Eng, J., McCormack, A. L. & Yates, J. R. (1994) J Am Soc Mass Spectrom 5, 976-989.
4. Allmer, J., Markert, C., Stauber, E. J. & Hippler, M. (2004) FEBS Lett 562, 202-6.
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