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)