Proteomics Informatics – Analysis of mass spectra: signal processing, peak finding, and isotope clusters (Week 3)

Charge-State Distributions

mass/charge

inte

nsity

MALDI ESI

mass/charge

inte

nsity

1+

1+ 2+

3+

4+

Peptide

Protein

2+

nnHM

zm M - molecular mass

n - number of chargesH – mass of a proton

mass/charge

inte

nsity

mass/charge

inte

nsity 1+ 27+

2+3+

4+

MALDI ESI

5+

31+

Charge-State

Example:

peptide of mass 898 carrying 1 H+ = (898 + 1) / 1 = 899 m/z

carrying 2 H+ = (898 + 2) / 2 = 450

m/z carrying 3 H+ = (898 + 3) / 3 = 300.3

m/z

nnHM

zm M - molecular mass

n - number of chargesH – mass of a proton

m = 1035 Da m = 1878 Da m = 2234 Da

Isotope Distributions

m/z m/z m/z

Inte

nsity

0.015% 2H1.11% 13C 0.366% 15N0.038% 17O, 0.200% 18O, 0.75% 33S, 4.21% 34S, 0.02% 36S

Only 12C and 13C:p=0.0111n is the number of C in the peptidem is the number of 13C in the peptideTm is the relative intensity of the peptide m 13C

𝑇𝑚=( 𝑛𝑚)𝑝𝑚(1−𝑝)𝑛−𝑚

12C14N16O1H32S

+1Da

+2Da+3Da

Isotope distributions

Peptide mass

Inte

nsity

ratio

Peptide massIn

tens

ity ra

tio

m/z

monoisotopicmass

GFP 29kDa

Resolution

Resolution = minimum peak separation, M, which allows to distinguish two ion species

Rela

tive

Inte

nsity

m/z

I II II 501.5 502.0500.5500.0499.5

500

50 %

Resolution = M/M = 500/0.5 = 1000

M = full width at half maximum (FWHM)

R = MM

= resolving power

Resolution

• What resolution do we need to differentiate a 1600 Da peptide that carries either an acetylation (+ 42.0100) or trimethylation (42.0464 )?

• R = 1600/0.0364 = 43,956

R = M

M= resolving power

Resolution

Isotope Clusters and Charge State

m/z

Inte

nsity

1+1

1

1

m/z

Inte

nsity

2+0.5

0.5

0.5

m/z

Inte

nsity

3+0.33

0.33

0.33

Isotope Clusters and Charge State

m/z

Inte

nsity

Possible to Determine Charge?

Yes

Yes

Maybe

No

432.8990

433.2330

433.5671433.9014

713.3225

713.8239

714.3251

714.8263

What is the Charge State?

between the isotopes is 0.5

Da

between the isotopes is 0.33

Da

Noise

Smoothing

Smoothing

Adaptive Background Correction (Unsharp masking)

wlk

wlk

kIwdwdlI )(12

),,('

Unsharp masking

Original

Adaptive Background Correction

Smoothing and Adaptive Background Correction

Peak Finding

m/z

Inte

nsity

wlk

wlk

kIlS )()(Find maxima of

The centroid m/z of a peak

wlk

wlk

wlk

wlk

kI

kzmkI

)(

)()(

Peak Finding

m/z

Inte

nsity

The signal in a peak can beestimated with the RMSD

22

2

//||

))((w

wlkIkI

and the signal-to-noise ratio of a peak can be estimated by dividing the signal with the RMSD of the background

Estimating peptide quantity

Peak heightCurve fittingPeak area

Peak heightCurve fitting

m/z

Inte

nsity

Time dimension

m/z

Inte

nsity

Tim

e

m/z

Tim

e

Sampling

Retention Time

Inte

nsity

0

5

10

15

20

25

30

0.8 0.85 0.9 0.95 1

3 points

0

20

40

60

80

100

120

140

0.8 0.85 0.9 0.95 1

3 points

5%

Acquisition time = 0.05s

5%

Sampling

0.5

0.6

0.7

0.8

0.9

1

1.1

1 2 3 4 5 6 7 8 9 10

Thre

shol

ds (9

0%)

# of points

Sampling

What is the best way to estimate quantity?

Peak height - resistant to interference- poor statistics

Peak area - better statistics - more sensitive to

interference

Curve fitting - better statistics- needs to know the peak

shape- slow

Web Toolhttp://10.193.36.101/plot-filter-cgi/plot_filter.pl or http://10.193.36.219/plot-filter-cgi/plot_filter.pl

Web Toolhttp://10.193.36.101/plot-filter-cgi/plot_filter.pl or http://10.193.36.219/plot-filter-cgi/plot_filter.pl

Proteomics Informatics – Analysis of mass spectra: signal processing, peak finding, and isotope clusters (Week 3)