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Needles in the migraine haystack, cerebrospinal fluid biomarkers

Needles in the migraine haystack, cerebrospinal fluid biomarkers. Company: Huntington Medical Research Institutes Mentors: Alfred Fonteh Ph.D., Mike Harrington M.B. Ch.B., F.R.C.P. Intern: Samuel Wein Earlham College, IN. USA. Uncovering the protein changes brought about by migraine.

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Needles in the migraine haystack, cerebrospinal fluid biomarkers

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  1. Needles in the migraine haystack, cerebrospinal fluid biomarkers Company: Huntington Medical Research Institutes Mentors: Alfred Fonteh Ph.D., Mike Harrington M.B. Ch.B., F.R.C.P. Intern: Samuel Wein Earlham College, IN. USA

  2. Uncovering the protein changes brought about by migraine Goal: To process MS/MS data to graph the levels of proteins from cerebrospinal fluid (CSF) during migraine and then combine these graphs with protein protein interaction data to create a map of expressions.

  3. Why do we care? • Chronic Migraine is a debilitating disorder affecting as many as 10% of people • Migraine has a direct medical cost of over $1 billion dollars • By understanding how the brain changes during migraine we come closer to finding better treatments • CSF is a likely pool for biomarkers as it is within the blood brain barrier

  4. What is migraine? • A neurological disorder which manifests in severe headaches, photophobia, phonophobia, and nausea • Caused by over-excitation of various nerves

  5. What is CSF? • Produced in the brain • Pushed down spinal column where it is absorbed • Physically protects the brain • Acts as a conduit for signals

  6. What I am doing Taking protein sequence data from CSF samples taken over a four day period Using existing databases to find how the proteins interact Mapping expression levels of each protein every day onto their interactions Grouping proteins by expression profile over time Grouping proteins by presence in specific pathways

  7. Protein sequence data • Data was collected from a stent inserted into the spinal column • CSF was harvested every four hours • Protein sequence was obtained using liquid chromatography and mass spectrometry

  8. Input:

  9. MS/MS data • Proteins were digested with trypsin • MS/MS data was interpreted using BioWorks • SEQUEST algorithm was used to determine protein composition as well as frequency of protein appearance • Protein abundance was measured by height of peaks

  10. CSV file with Protein namenumber of expressions Protein similarities Raw Ms/MsData Parser Interactionsbetweenproteins VANTED Return SeparatedList of Protein names APID2Net& Cytoscape Final Graph PICR List ofsynonyms

  11. Python & Shell Scripts • Used to convert between different formats • Populate VANTED templates • Creates a list of proteins

  12. CSV file with Protein namenumber of expressions Protein similarities Raw Ms/MsData Parser Interactionsbetweenproteins VANTED Return SeparatedList of Protein names APID2Net& Cytoscape Final Graph PICR List ofsynonyms

  13. Cytoscape

  14. CSV file with Protein namenumber of expressions Protein similarities Raw Ms/MsData Parser Interactionsbetweenproteins VANTED Return SeparatedList of Protein names APID2Net& Cytoscape Final Graph PICR List ofsynonyms

  15. Apid2NET • Proteins are tagged based upon what known pathways they participate in • Can also be tagged by structural homology

  16. Apid2NET

  17. CSV file with Protein namenumber of expressions Protein similarities Raw Ms/MsData Parser Interactionsbetweenproteins VANTED Return SeparatedList of Protein names APID2Net & Cytoscape Final Graph PICR List ofsynonyms

  18. PICR • Protein identifier cross-reference service • Finds synonyms of protein names and uniprot numbers

  19. CSV file with Protein namenumber of expressions Protein similarities Raw Ms/MsData Parser Interactionsbetweenproteins VANTED Return SeparatedList of Protein names APID2Net& Cytoscape Final Graph PICR List ofsynonyms

  20. VANTED • Links represent known protein interactions • Colors represent similar expression profiles • Line graphs show the expression levels

  21. VANTED

  22. A schematic procedure CSV file with Protein namenumber of expressions Protein similarities Raw Ms/MsData Parser Interactionsbetweenproteins VANTED Return SeparatedList of Protein names APID2Net & Cytoscape Final Graph PICR List ofsynonyms

  23. Conclusion Automated generation of protein expression graphs Automated ability to search protein functions These tools will be invaluable in searching the migraine haystack

  24. Thanks and acknowledgements Drs Fonteh and Harrington HMRI All of the SocalBSI staff All of my fellow students NSF and NIH

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