Data processing After filtering the results from SEQUEST using DTASelect2, ion chromatograms were generated using an updated version of a program previously written in our laboratory [29]. This software, called Census [30], is available from the authors for individual use (for details, see http://fields.scripps.edu/Census). Census calculates peptide ion intensity ratios for each pair of extracted ion chromatograms. The basis of the program is a linear least-squares correlation that is used to calculate the ratio (i.e., slope of the line) and closeness of fit (i.e., correlation coefficient [r]) between the data points of the unlabeled and labeled ion chromatograms. In this study, only peptide ratios with determi- nant scores (r2.0.5) were used for further analysis [31]. Peptides were evaluated after first taking the union of search results (DTASelect2.0 output files) so that a peptide needs only be identified in one of the replicates to be quantified. Quantification data of proteins were acquired by calculating a weighted average of the identified and quantified peptides of the protein from all fractions. The output from Census is a ratio 1 of the unlabeled and labeled sample for the drug treated sample (unlabeled drug treated1/labeled control1) as well as a ratio 2 for the control sample (unlabeled control2/labeled control2) of a different MudPIT run (normalization run). Through calculation of References 1. Greenwood BM, Fidock DA, Kyle DE, Kappe SHI, Alonso PL, et al. (2008) Malaria: progress, perils, and prospects for eradication. J Clin Invest 118: 1266–1276. 2. List EO, Berryman DE, Bower B, Sackmann-Sala L, Gosney E, et al. (2008) The use of proteomics to study infectious diseases. Infect Disord Drug Targets 8: 31–45. 3. Florens L, Washburn MP, Raine JD, Anthony RM, Grainger M, et al. (2002) A proteomic view of the Plasmodium falciparum life cycle. Nature 419: 520–526. 4. Lasonder E, Ishihama Y, Andersen JS, Vermunt AM, Pain A, et al. (2002) Analysis of the Plasmodium falciparum proteome by high-accuracy mass spectrometry. Nature 419: 537–542. 5. Dong MQ, Venable JD, Au N, Xu T, Park SK, et al. (2007) Quantitative mass spectrometry identifies insulin signaling targets in C. elegans. Science 317: 660–663. 6. Fournier ML, et al. (2007) Multidimensional separations-based shotgun proteomics. Chem Rev 107: 3654–3686. 7. Nirmalan N, Sims PF, Hyde JE (2004) Quantitative proteomics of the human malaria parasite Plasmodium falciparum and its application to studies of development and inhibition. Mol Microbiol 52: 1187–1199. 8. Park SK, Venable JD, Xu T, Yates III JR (2008) A quantitative analysis software tool for mass spectrometry-based proteomics. Nat Methods 5: 319–322. 9. ter Kuile F, White NJ, Holloway P, Pasvol G, Krishna S (1993) Plasmodium falciparum: in vitro studies of the pharmacodynamic properties of drugs used for the treatment of severe malaria. Exp Parasitol 76: 85–95. 10. Maerki S, Brun R, Charman SA, Dorn A, Matile H, Wittlin S (2006) In vitro assessment of the pharmacodynamic properties and the partitioning of OZ277/ RBx-11160 in cultures of Plasmodium falciparum. J Antimicrob Chemother 58: 52–58. 11. Olliaro P (2001) Mode of action and mechanism of resistance for antimalarial drugs. Pharmacol Ther 89: 207–219. 12. Hyde JE (2007) Drug-resistant malaria–an insight. FEBS J 274: 4688–4698. 13. Lelie`vre J, Berry A, Benoit-Vical F (2007) Artemisinin and chloroquine: do mode of action and mechanism of resistance involve the same protagonists? Curr Opin Investig Drugs 8: 117–124. 14. Roberts L, Egan TJ, Joiner KA, Hoppe HC (2008) Differential effects of quinoline antimalarials on endocytosis in Plasmodium falciparum. Antimicrob Agents Chemother 52: 1840–1842. 15. Radfar A, Diez A, Bautista JM (2008) Chloroquine mediates specific proteome oxidative damage across the erythrocytic cycle of resistant Plasmodium falciparum. Free Radic Biol Med 44: 2034–2042. 16. Gunasekera AM, Patankar S, Schug J, Eisen G, Wirth DF (2003) Drug-induced alterations in gene expression of the asexual blood forms of Plasmodium falciparum. Mol Microbiol 50: 1229–1239. Drug Induced Proteome Changes a ratio of ratios (1/2) for each quantified peptide we filtered out eventual labeling deficiencies and received a ratio that corresponds to (unlabeled drug treated/unlabeled control). The changes observed by Census identify proteins with differential expression status upon drug treatment. Supporting Information Table S1 Found at: doi:10.1371/journal.pone.0004098.s001 (1.69 DOC) MB Acknowledgments The authors wish to thank Stefan Rahlfs for helpful discussions and Elisabeth Fischer for her excellent technical assistance. Author Contributions Conceived and designed the experiments: JHP SK JY KB. Performed the experiments: JHP SK. Analyzed the data: JHP SK SKP KB. Contributed reagents/materials/analysis tools: JY KB. Wrote the paper: JHP SK SKP JY KB. 17. Gunasekera AM, Myrick A, Le Roch K, Winzeler E, Wirth DF (2007) Plasmodium falciparum: Genome wide perturbations in transcript profiles among mixed stage cultures after chloroquine treatment. Exp Parasitol 117: 87–92. 18. Kuhn T, Wang Y (2008) Artemisinin–an innovative cornerstone for anti-malaria therapy. Prog Drug Res 66: 383385–422. 19. Meshnick SR (2002) Artemisinin: mechanisms of action, resistance and toxicity. Int J Parasitol 32: 1655–1660. 20. Duraisingh MT, Cowman AF (2005) Contribution of the pfmdr1 gene to antimalarial drug-resistance. Acta Trop 94: 181–190. 21. Koncarevic S, Bogumil R, Becker K (2007) SELDI-TOF-MS analysis of chloroquine resistant and sensitive Plasmodium falciparum strains. Proteomics 7: 711–721. 22. Washburn MP, Wolters D, Yates III JR (2001) Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat Biotechnol 19: 242–247. 23. McClatchy DB, Liao L, Park SK, Venable JD, Yates III JR (2007) Quantification of the synaptosomal proteome of the rat cerebellum during post-natal development. Genome Res 17: 1378–1388. 24. Eng JK, McCormack AL, Yates III JR (1994) An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J Am Soc Mass Spectrom 5: 976–989. 25. Cociorva DTD, Tabb DL, Yates III JR (2006) Validation of Tandem Mass Spectrometry Database Search Results using DTASelect. In Current Protocols in Bioinformatics. New York: John Wiley & Sons, Chapter 13: Unit 13.4. 26. Bahl A, Brunk B, Crabtree J, Fraunholz MJ, Gajira B, et al. (2003) PlasmoDB: the Plasmodium genome resource. A database integrating experimental and computational data. Nucleic Acids Res 31: 212–215. 27. Tabb DL, McDonald WH, Yates III JR (2002) DTASelect and Contrast: tools for assembling and comparing protein identifications from shotgun proteomics. J Proteome Res 1: 21–26. 28. Elias JE, Gygi SP (2007) Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat Methods 4: 207–214. 29. MacCoss MJ, Wu CC, Liu H, Sadygov R, Yates III JR (2003) A correlation algorithm for the automated quantitative analysis of shotgun proteomics data. Anal Chem 75: 6912–6921. 30. Park SK, Venable JD, Xu T, Liao L, Yates III JR (2006) A tool for quantitative analysis of high-throughput mass spectrometry data. Long Beach, CA: Human Proteome Organisation Fifth Annual World Congress. 31. Venable JD, Wohlschlegel J, McClatchy DB, Park SK, Yates III JR (2007) Relative quantification of stable isotope labeled peptides using a linear ion trap- Orbitrap hybrid mass spectrometer. Anal Chem 79: 3056–3064. PLoS ONE | www.plosone.org 9 December 2008 | Volume 3 | Issue 12 | e4098