1. By Jay Krishnan

2. Introduction Information gathered from Proteomic techniques + neuroscientific research = Information on protein composition and function of mammalian neurons (neuroproteomic data) Information gathered from Proteomic techniques + neuroscientific research = Information on protein composition and function of mammalian neurons (neuroproteomic data) Mass spectrometric (MS) analyses/identifies proteins associated with various synaptic preparations Mass spectrometric (MS) analyses/identifies proteins associated with various synaptic preparations Synaptosomes Synaptosomes Synaptic Membranes Synaptic Membranes Postsynaptic Density (PSD) Postsynaptic Density (PSD) Synaptic Vesicles Synaptic Vesicles Presynapse (PRE) Presynapse (PRE) AIM: This study has a goal to combine proteomics with graph theory analysis to characterize protein composition of the PRE nerve terminal

3. Proteomics Procedures  Proteomics  In-gel digestion  In-solution digestion  Mass spectrometry  Database search and protein identification

4. Getting the Proteins Background Literature based PPI network of 6,442 proteins were created Background Literature based PPI network of 6,442 proteins were created 17,879 interactions extracted from 12,462 publications 17,879 interactions extracted from 12,462 publications Obtained from BioGrid, HPRD, PPID, and a CA1 neuronal regulatory network Obtained from BioGrid, HPRD, PPID, and a CA1 neuronal regulatory network 306 Proteins were obtained from proteomic studies 306 Proteins were obtained from proteomic studies

5. Database search and protein identification MS data and NCBI (RefSeq) allows same data to be searched that was obtained from the literature using the Sonar program MS data and NCBI (RefSeq) allows same data to be searched that was obtained from the literature using the Sonar program The data was now cross checked to identify the false positive rate or alpha errors The data was now cross checked to identify the false positive rate or alpha errors (False Positive Rate) = RP/ (NP +RP) (False Positive Rate) = RP/ (NP +RP) (RP + NP) = the matches observed between the random and normal databases (RP + NP) = the matches observed between the random and normal databases Protein and peptide scores were changed in order to eliminate the false positives Protein and peptide scores were changed in order to eliminate the false positives

6. Literature-based PRE PPI network Interactions (306) are abstracted into a mixed graph where proteins are nodes and interactions are links Interactions (306) are abstracted into a mixed graph where proteins are nodes and interactions are links UniProt accession numbers; Entrez Gene IDs were used to for standard protein identification so that data from different sources can be effectively combined UniProt accession numbers; Entrez Gene IDs were used to for standard protein identification so that data from different sources can be effectively combined SNAVI was used to analyze and visualize the network SNAVI was used to analyze and visualize the network

7. Interactions between the Merged Data In Silico network PRE interactions created by extracting PPI data from biochemical and physiological literature Calcium plays a central role in neurotransmitter release from the PRE nerve terminal

8. Review of Basoc Statistics Z Score = how many standard deviations are you away from the mean Z Score = how many standard deviations are you away from the mean z = (x – u)/ sigma z = (x – u)/ sigma Within two SD lies 68.2% of the data Within two SD lies 68.2% of the data Within 4 SD lies 95.4% of the data Within 4 SD lies 95.4% of the data Within 6 SD lies 99.7% of the data Within 6 SD lies 99.7% of the data Normal Curve

9. Statistical Analysis N1 = number of proteins in the merged list (306) N2 = number of proteins in background data (6,442) P1 = number of direct interactions in merged list P2 = number of interactions in background list – law of large numbers * This binomial proportion test was used to determine how, “good,” the 306 proteins obtained from studies in proteomics compared to the Backaround genes obtained from BioGrid, HPRD, PPID, and a CA1 neuronal regulatory network *

10. Statistical Analysis  P (difference in proportion) = (p1-p2) / (N1 + N2)  H0 = (p1/N1) – (p2/N2) = 0  Ha = (p1/N1) – (p2/N2) > 0  P value – the probability of obtaining a statistic as extreme as the null hypothesis  If P value is lower that.05 we can reject the null hypothesis and verify that the merged list has a greater percentage of direct interactions

11. Comparison of Proteins based on z-score After statistical analysis proteins with a z-score > 3 were compared to proteins with a z-score < -1 these proteins were than categorized based on Biological Process, Cellular Component and Molecular Function

12. Confirming Genuity of Data (Western Blot) PRE fractions were separated by SDSPAGE and probed with selected antibodies to confirm the presence of the predicted proteins Validation of the predicted presynaptic protein complex by co-immunoprecipitation For further confirmation immunofluorescence studies were performed using cultured primary cortical neurons

13. Predict a PRE complex Proteins from merged list were analyzed for the presence of overlapping interactions Proteins from merged list were analyzed for the presence of overlapping interactions 21 pairs were observed 21 pairs were observed Percent SN = SN / (SN + ON1 + ON2) Percent SN = SN / (SN + ON1 + ON2) SN = shared neighbors SN = shared neighbors ON1: other neighbors of a chosen protein ON1: other neighbors of a chosen protein ON2: other neighbors of another chosen protein ON2: other neighbors of another chosen protein

14. Interactions between Background proteins and Proteins from Merged List Protein interactions (17 proteins) between background proteins and merged proteins when combined

15. Identification of Proteins using LC-MS/MS followed by In-Gel and In-Solution Digestion Sonar helps identifies the proteins based on based on statistical analysis and stored algorithms Output that helped identify what are the proteins and what they interacted with

16. Core List – Confirmed Interactions; Contains101 proteins Core PRE list is a compiled lists of proteins gathered from… 1)proteomic studies of PRE fractions 2)Literature based PRE network (converted to list of components), and 3) Two published proteomic studies of PRE fractions

17. Generating the final core presynaptic list With Proteomics and literature-based networks lists of proteins were created. With Proteomics and literature-based networks lists of proteins were created. Core list = PRE Proteins identified twice in independent experiments Core list = PRE Proteins identified twice in independent experiments Schematic illustrating the data compilation process creates a core presynaptic list of 117 PRE proteins. Schematic illustrating the data compilation process creates a core presynaptic list of 117 PRE proteins. Protein lists from proteomic studies, two other published studies, and a literature-based presynaptic network were combined to form a merged list containing 306 proteins. Protein lists from proteomic studies, two other published studies, and a literature-based presynaptic network were combined to form a merged list containing 306 proteins. 16 intermediates identified from the merged list that interact directly with proteins from the core list. 16 intermediates identified from the merged list that interact directly with proteins from the core list. These proteins were added to the core list These proteins were added to the core list

18. Conclusion Biological Relevant predictions deduced from the literature can be tested experimentally Biological Relevant predictions deduced from the literature can be tested experimentally A complex of PPI has been created successfully and proper constraints have been made to reduce the FPR A complex of PPI has been created successfully and proper constraints have been made to reduce the FPR

19. Conclusion A described approach to characterize the composition of the PRE nerve terminal was found A described approach to characterize the composition of the PRE nerve terminal was found Testing (as indicated from p value and z score) proved that the merged list was a good list of proteins with interactions Testing (as indicated from p value and z score) proved that the merged list was a good list of proteins with interactions

20. Future Research Scientists can use the knowledge of PPI present in this paper in order to expand their knowledge over a designed/chosen protein Scientists can use the knowledge of PPI present in this paper in order to expand their knowledge over a designed/chosen protein The network created can be always expanded and added to in the future as long as the same experimental procedures are used The network created can be always expanded and added to in the future as long as the same experimental procedures are used

21. References 1) Ma’ayan, A., Jenkins, S. L., Neves, S., Hasseldine, A. et al., Formation of regulatory patterns during signal propagation in a Mammalian cellular network. Science 2005, 309, 1078–1083. 1) Ma’ayan, A., Jenkins, S. L., Neves, S., Hasseldine, A. et al., Formation of regulatory patterns during signal propagation in a Mammalian cellular network. Science 2005, 309, 1078–1083. 2) Krycer, James R., Chi NI Pang, and Mark R. Wilkins. "High throughput protein-protein interaction data: clues for the architecture of protein complexes." Proteome Science (2008). Print. 2) Krycer, James R., Chi NI Pang, and Mark R. Wilkins. "High throughput protein-protein interaction data: clues for the architecture of protein complexes." Proteome Science (2008). Print. 3) Ling, Lee. Normal Curve. Digital image. Web. 3) Ling, Lee. Normal Curve. Digital image. Web.