1. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt1 Analysis of mitochondrial transit peptides of Plasmodium falciparum Andreas Bender Diplomarbeit Research Group Gisbert Schneider April 2002 - September 2002 Goethe-University, Frankfurt

2. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt2 Contents Why … ? Our results – in short Biological background Data coding and analysis Detailed results P. falciparum and other organisms Summary and outlook

3. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt3 Why … ? Why P. falciparum ? –It causes malaria –Genome sequencing recently completed –„Apicoplastic pressure“ –Closely related to Toxoplasma gondii etc.

4. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt4 Why … ? Why mitochondrial transit peptides? –Recent related work for apicoplast exists –Major compartment –Failure of established tools

5. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt5 Our results – in short Artificial neural networks results: –Mathews coefficient cc = 0.74 (test set), corresponding to ~90% correct predictions –381 to 1177 mTPs found in 5334 annotated genes (7% to 22%) of Plasmodium falciparum

6. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt6 Biological background Female Anopheles

7. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt7 Biological background Courtesy of Mark F. Wiser, Tulane University

8. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt8 Biological background - Targeting Courtesy of the Division of Biological Sciences, University of Montana

9. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt9 Biological background Mitochondrial targeting signals – Characteristics –N-terminal, internal, C-terminal –Matrix-targeting or IMS-targeting (bipartite) –No sequence conservation –On average 20-30 amino acids –Net positive charge, forms α-Helix –Distinct cleavage site (Arg at -2 or -3,…)

10. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt10 Data coding and analysis 3 Lengths: N-terminal 24, 31, 42 residues Redundance reduction Two representations: –Relative amino acid frequencies (20-dim.) –Physikochemical properties (19-dim.) SOM ANN Variable selection

11. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt11 Data coding and analysis

12. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt12 Data coding and analysis Three-layer feed-forward perceptrons Input data –N-terminal 24, 31 and 42 amino acids –Coded in relative amino acid frequency and in physikochemical space All parameters varied one-at-a-time 10-fold cross-validation, 40 positive examples, 135 negative

13. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt13 Data coding and analysis

14. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt14 Data coding and analysis Two ANNs –Best cc: 1177 of 5334 annotated genes have mTPs (~22%) –High penalty for overpredictions: 381 of 5334 annotated genes have mTPs (~7%) –Arabidopsis thaliana: 8% mTPs –Saccharomyces cerevisiae: 11% mTPs

15. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt15 Data coding and analysis Matthews cc SensitivitySelectivity MitoProtII0.490.800.47 TargetP0.600.550.81 PlasMit0.740.940.68

16. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt16 P. falciparum and other organisms

17. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt17 P. falciparum and other organisms 25% G+C-Content in coding regions (sample of chromsome 2 and 3) In good agreement with work of Lobry for 50 bacterial genomes

18. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt18 Summary Failure of established tools for mTP pred. There are general differences in AA usage between P. falciparum and other eukaryotes Low G+C-Content of coding regions New tool PlasMit outperforms existing algorithms

19. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt19 Outlook Question: Why are there so many positive predictions in P. falciparum ? Using PlasMit for assembling putative metabolic pathways in the mitochondria will now be possible Final goal: Full map of P. falciparum´s metabolism

20. Andreas Bender - Research Group Gisbert Schneider - Goethe-University Frankfurt20 Thank you!