1. Mass Spectrometry I Basic Data Processing

2. Mass spectrometry A mass spectrometer measures molecular masses. The mass unit is called dalton, which is 1/12 of the mass of a carbon atom, and is about the mass of one hydrogen atom. If there is a mixture of different molecules in a sample, all the masses are measured simultaneously. So you get a spectrum.

3. Some Pictures MALDI-RQ-Tof Micro FT-ICR LTQ-Orbitrap

4. Each peak corresponds to a different type of molecule in your sample... … 2789.22 3597.0 2790.22 5018.0 2791.23 4406.0 2792.23 2868.0 2793.23 1234.0 … peak list

5. Three Components of an MS A typical mass spectrometer contains – Ionizer – Mass analyzer – Detector Ion source charges the to-be-measured molecules. – Charge can be negative but often positive. – Two common types: MALDI and ESI. – John B. Fenn & Koichi Tanaka 2002 Nobel Prize in Chemistry for Electrospray and MALDI Mass analyzer separates ions according to the mass to charge ratio (m/z) of the ions. – Iontrap, TOF, Quadrupole, FTICR. Detector detects the ions.

6. Matrix Assisted Laser Desorption/Ionization Formation of singly charged ions Sample is co-crystallized with matrix (solid) Koichi Tanaka, Nobel Prize 2002 Ionization (1): MALDI Other ionization method exists.

7. Mass Analyzer (1) – TOF Time of Flight. +- + Detector Time of flight is proportional to sqrt(m/z) Other mass analyzer exists.

8. Drift region (D) MALDI Time-of-flight Putting Them Together MALDI TOF Average time in TOF: 10 -7 sec : average speed 1-2 x 10 5 km/h

11. MALDI-TOF Linear Mass range = 800-200,000 Sensitivity and accuracy decrease rapidly with size !

12. MALDI-TOF Linear vs Reflectron Mode Reflectron gives much better resolution for mass < 6,000 Linear = poor resolution due to velocity variation of ions with the same m/z Reflectron = Contact lens for a near sighted machine!

13. Protein “identification” with intact mass We measure the intact mass of the protein. Then search in the protein database to find a protein with the same mass. Good idea but there are too many proteins with the same mass. In the rest of the lecture we study more sophisticated methods and why protein ID is important.

14. Complications isotopes widened peaks profile

15. Centroiding

16. Another example with lower resolution

17. Isotopes

18. Chemical Composition of Living Matter 27 of 92 natural elements are essential. Elements in biomolecules (organic matter): H, C, N, O, P, S These elements represent approximately 92% of dry weight. Organic Matter Organized in "building blocks" amino acids polypeptides ( proteins) monosaccharidesstarch, glycogen nucleic acidsDNA, RNA Back to Basics…

19. element nominal exact Percent average mass mass abundance mass C 1212.00000 98.9% 1313.003351.1% 12.00115 H 11.0078399.98% 22.0140 0.02% 1.008665 O 1615.9949199.8% 1817.9992 0.02% 15.994 N 1414.0030799.63% 1515.000110.37% 14.0067 S 32 31.97207 94.93% 33 32.97146 0.76% 34 33.96787 4.29% excercise Mass (Weights) of Atoms and Molecules

20. Ethyl acetate C 4 H 8 O 2 4 C 12 4 x 12.000048.0000 8 H 1 8 x 1.0078 8.064 2 O 16 2 x 15.9994931.9898 Nominal Mass: 48 + 8 + 32 = 88 Monoisotopic Mass: 88.0555 Average Mass: 48.04446 + 8.06932 + 31.988 = 88.10178 Mass or Molecular Weight of molecules

21. Amino Acids There are 20 amino acids. All have the same basic structure but with different side chains: Examples: side chain group H Glycine, or Gly, or G Arginine, or Arg, or R

22. All the 20 Structures * Picture copied from Dr. R.J. Huskey’s website: http://www.people.virginia.ed u/~rjh9u/aminacid.html

23. Peptides and Proteins H Glycine, or Gly, or G Arginine, or Arg, or R GR peptide bonds N-terminal C-terminal

24. Exact Mass of Amino Acid Residues in Proteins Note: Leu (L) = Ile (I) = 113.08410 Mass of Amino Acids Residues

25. Amino Acid Table AA CodesMono. IONSOURCE.COMIONSOURCE.COM AA Codes Mono. GlyG57.021464AspD115.02694 AlaA71.037114GlnQ128.05858 SerS87.032029LysK128.09496 ProP97.052764GluE129.04259 ValV99.068414MetM131.04048 ThrT101.04768HisH137.05891 CysC103.00919PheF147.06841 LeuL113.08406ArgR156.10111 IleI113.08406CMC161.01467 AsnN114.04293TyrY163.06333 --- TrpW186.07931

26. Cysteine Proteins are often treated so that cysteine becomes carboxyamidomethyl cysteine (CamC) or Carboxymethyl (CmC) in order to break the disulphide bonds. CamC = 160.03

27. tripeptide (MW 71.04+87.03+147.07+18.01)=323.15 More precisely: monoisotopic mass 323.1481 average mass 323.3490 Ala-Ser-Phe (ASF) Mass of Peptides and Proteins

28. In a mass spectrum 323.15324.15325.15 Deconvolution adds all the isotopic peaks to the monoisotopic peak. So, the later process does not need to worry about the isotopes. Monoisotope peak isotope peaks

29. Check the difference

30. ESI and Multiply Charged Ions

31. Electrospray

32. Electrospray Ionization: Formation of Charged Droplets Formation of multiply charged ions Ionization (2) – ESI

33. Multiply Charged Ions The same molecules may be charged differently, and therefore form a few peaks in the spectrum. 323.15 324.15 325.15 162.08 162.58 163.08 m/z(M+2)/2(M+3)/3 For protein/peptide with positive charges, the charge is obtained from adding protons (which has mass approx. 1 dalton. As a result, a molecule with mass M will have peaks at (M+Z)/Z (M+1)/1

34. How to determine charge states? Isotope ions when resolution is enough. Check different charge states when resolution is not enough.

35. Exercise 395.73 396.22 397.24

36. Exercise

37. (A) “Multi-charge envelope” ( B) After “Charge-deconvolution algorithm” 1541.9 1413.2 1304.7 1211.9

38. Baseline

39. Baseline correction

40. Convex Hull Method convex not convex

41. Convex Hull A convex hull is such that all the data points are above the lines and their extensions.

42. How to calculate convex hull? Stack S contains all the data points that form the convex hull so far. Data point D[i] = (D[i].x, D[i].y). Algorithm: 1. S.push( D[0] ); s.push(D[1]) 2. for i from 2 to n 2.1 while D[i], S.top(), S.secondtop() are concave 2.1.1 S.pop(); 2.2 S.push(D[i]); 3. return S S.top() S.secondtop() D[i]

43. Analyze the convex hull algorithm Correctness – The algorithm finishes. – The output is a convex hull. – The proof will be included in an assignment. Time complexity – O(n) time. – Proof: each point is checked only once, and added to (and therefore removed from) the stack at most once.

44. Summarize of spectrum preprocessing Baseline correction Centroiding Charge recognition and deconvolution Noise removal