1. Discrimination of symbiotic/parasitic bacterial type III secretion system effector protein using principal component analysis Yuuichi Nakano1 Mitsuo Iwadate2 Hideaki Umeyama2 Y-h. Taguchi1 1 Dept. Phys., Chuo Uinv., 2 Dept. Bio. Sci., Chuo Univ.

2. 1. Introduction 2. Previous Researches 3. Reanalysis of Yahara's data set 4. Discrimination between plant pathogenic, plant symbiotic, and animal pathogenic T3SS effector proteins 5. Yahara's feature vector vs protein folds 6. Conclusion 3. 1. Introduction http://mol-biol4masters.masters.grkraj.org/html/Co_and_Post_Translational_Events2- Bacterial_Systems_files/image060.jpg Type III secretion system (T3SS) is the system by which bacteria injects various proteins to host cells Effector proteins 4. Wide range of bacteria has T3SS http://ja.wikipedia.org/wiki/ %E3%83%95%E3%82%A1%E3%82%A4%E3%83%AB:TEM_of_isolated_T3SS_needle_compl exes.jpg Wide range includes animal/plant pathogenic, plant symbiotic Why symbiotic, too? New drug target 5. 2. Previous Researches Koji Yahara, Ying Jiang, Takashi Yanagawa Computational Identification of Discriminating Features of Pathogenic and Symbiotic Type III Secreted Effector Proteins Information and Media Technologies Vol. 6 (2011) No. 1 pp. 39-51 2010 SIGBIO Best Student Presentation Award 2011 Generationby EMBOSS of 44 protein features from only sequence Successful discrimination between symbiotic and pathogenit T3SS effector proteins with kernel (non-linear) methods 6. Y. Nakano, Y-h. Taguchi, Feature extraction for discriminance of symbiotic/parasitic bacterial type III effector protein using principal component analysis, Bioinformatics and Biomedicine Workshops (BIBMW), 2011 IEEE International Conference pp.964-965, 12-15 Nov. 2011 Following Yahara et al's research, successful discrimination with PCA+LDA (linear) using independent data set of pathogenic/symbiotic T3SS effector Proteins Essential points are not methods but features 7. 3. Reanalysis of Yahara's data set PCA+LDA competitive performance However....., More than half of Yahara's symbiotic T3SS effector proteins turn out to be pathogenic.. Why was discrimination between symbiotic and pathogenic T3SS effector proteins successful, in spite of the erroneous dataset? 8. 4. Discrimination between plant pathogenic, plant symbiotic, and animal pathogenic T3SS effector proteins Yahara et al (2011) This study Pathogenic Animal Pathogenic Symbiotic Plant Pathogenic Plant Symbiotic (new) Discrimination : PCA+LDA Feature : 43 (sequence through EMBOSS) most of them : Amino Acid Ratio (N=20) small, tiny, etc protein ratio (N=9) 9. PS: Plant Symbiotic PP: Plant Pathogenic AP: Animal Pathogenic PS PP AP PS 46 6 0 PP 11 28 10 AP 2 3 36 Predict True Accuracy: 77% Symbiotic 46 6 Pathogenic 13 77 Pathogenic Symbiotic Accuracy 93% Plant 81 10 Animal 5 36 Animal Plant Accuracy 88% 10. +PS PP AP Animal Plant Yahara et al (2011) Pathogenic Symbiotic 11. Yahara et al wrongly discriminated between animal and plant T3SS effector protein and misrecognized successful discrimination between symbiotic and pathogenic T3SS effector protein. However, this may suggest that Yahara et al's feature vector is universal.... 12. 5. Yahara's feature vector vs protein folds No matter what to be discriminated, Yahara's vector works well. Yahara's vector should reflect something critical about Protein Conjecture: Yahara's vector discriminates protein folds Cf. Taguchi & Gromiha, 2007, BMC Bioinformatics Amino Acid Composition Protein folds discrimination 13. Amino Acid Sequence Prediction Server (FAMS,phyre2) 3D Structure 3Dblast folds in SCOP replace with randomly picked protein that belong to the same fold feature extraction + PCA + LDA 14. Creator:GPL Ghostscript 905 (ps2write) CreationDate:D:20130519140222+09'00' LanguageLevel:2 +PS PP AP 15. Accuracy : 0.45 (3 class) average over 100 replacements PS PP AP class a 4% 21% 52% (all ) class b 18% 5% 7% (all ) class c 37% 32% 22% (/) class d 37% 37% 11% (+) class e 0% 5% 7% (multi domain) class f 4% 0% 7% (membrane protein) Even in class level, significant difference 16. Conjecture, not Confirmed yet, because..... Low success rate for protein structure prediction (~ 50% cf. 90% for human protein) Low coverage (structure prediction for only a part of sequence) SCOP is old (last updated June 2009) These problem will be solved in the future 17. Towards Drug Discovery..... Aim: drug effective only for pathogen 18. 6. Conclusion Excellent performance of discrimination between symbiotic and pathogenic T3SS effector protein can be achieved by simpler linear method. This means, what cause this performance is not a method but a selection of feature vector. Analysis of updated data set shows that discrimination between plant symbiotic, plant pathogenic, and animal pathogenic T3SS effector proteins can be discriminaed. 19. Conjecture: Yahara's feature vector possibly discriminate between protein folds. Drugs specific to animal pathogenic T3SS effector proteins may be possible Yahara's vector may discriminate something other. Nogami et al, Talk (28), Today 16:15 !