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PEAKS: De Novo Sequencing using Tandem Mass Spectrometry

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Title: PEAKS: De Novo Sequencing using Tandem Mass Spectrometry


1
PEAKS De Novo Sequencing using Tandem Mass
Spectrometry
  • Bin Ma
  • Dept. of Computer Science
  • University of Western Ontario

2
Outline
  • Background
  • Sandwich algorithm for de novo sequencing
  • Software implementation PEAKS

3
Background
  • Diseases are closely related to the abnormal
    proteins.
  • Given a tissue, the identification of the
    proteins (and their posttranslational
    modifications) in it is a fundamental problem in
    proteomics.
  • MS/MS is the most common way for protein
    identification.

4
Sample Preparation
tissue
gel
fraction
GTDIMR
HPLC
PAK
To MS/MS
MPSER


peptides
Add trypsin
5
Tandem Mass Spectrometer
QTOF
detector
parent ions
fragment ions
ions

Quadrupole mass analyzer
P

AK

TOF mass analyzer
MPSER
PAK





collision
AK
P
P
K
PA
AK


PAK
PAK


K

PAK
PA
SG


K
PA
PAK

peptide sequencing
ESI
6
LGSSEVEQVQLVVDGVK
peptide sequence
tandem mass spectrometry
MS/MS spectrum
7
How Does a Peptide Fragment?
m(y1)19m(A4) m(y2)19m(A4)m(A3) m(y3)19m(A4)
m(A3)m(A2)
m(b1)1m(A1) m(b2)1m(A1)m(A2) m(b3)1m(A1)m(
A2)m(A3)
8
Matching Sequence with Spectrum
9
De Novo Sequencing
  • De Novo Sequencing (Dancik et al., JCB
    6327-342.)
  • Given a spectrum, a mass value M, compute a
    sequence P, s.t. m(P)M, and the matching score
    is maximized.
  • We consider the matching score of P is the sum of
    the scores of the matched peaks.
  • We use intensity of a peak as its score to
    illustrate PEAKS algorithm.

10
Spectrum Graph Approach
  • Convert the peak list to a graph. A peptide
    sequence corresponds to a path in the graph.
  • Bartels (1990), Biomed. Environ. Mass Spectrom
    19363-368.
  • Taylor and Johnson (1997). Rapid Comm. Mass Spec.
    111067-1075. (Lutefisk)
  • Dancik et al. (1999), JCB 6327-342.
  • Chen et al. (2001), JCB 8325-337.

11
Warm up Counting Only Y-ions
12
The Score of a Suffix
19
y1
y2
y3
Let Q be a suffix of the peptide. It can
determine some y-ions.
score(Q) are the sum of scores of those y-ions of
Q.
13
Recursive Computation of DP(m)
19
Q
a
Suppose Q is such that DP(m)score(Q).
score(Q)DP(m(Q))
Do not know a?
14
Dynamic Programming
  • for m from 0 to M
  • backtracking

15
Counting Both y and b Ions
16
Good News
y1
y2
y3
bn-1
bn-2
bn-3
17
Bad News
18
Ions Determined By a Pair
PLGEY
QLLVR
score(P,Q) is the sum of matched peak
intensities. A peak can only count once.
19
Chummy Pairs
  • Two strings P and Q are called chummy pairs, iff.
    either of the following two is true
  • (C1)
  • (C2)

20
Recursive Computation of score(P,Q)
PLGEY
QLLVR
um(P), vm(Q)
21
Chummy pairs
  • Lemma 1 Suppose P and Q are a chummy pair.
    um(P), vm(Q). If (C1) is true,
  • If (C2) is true,

22
Chummy Pairs
  • Lemma 2 Let (P,Q) be a chummy pair, a be a
    letter.
  • (C1) ? (P,aQ) is a chummy pair but (Pa,Q) is not.
  • (C2) ? (Pa,Q) is a chummy pair but (P,aQ) is not.
  • Lemma 3 Let S be the optimal solution. Then
    there is a chummy pair (P,Q) and a letter a such
    that SPaQ. Also, there is a chummy pair series
    such that

23
Dynamic Programming
  • Combining Lemma 1, 2, 3, we can compute
  • Suppose (P,Q) is the pair maximizing DP(u,v)
    under the condition m(P)m(Q)m(a)M. Then PaQ
    is the optimal peptide.

24
Algorithm Sandwich
  • DP(0,0) 0 DP(u,v) -infinity for
    (u,v)!(0,0)
  • for u from 1 to M/2 step d do
  • for v from u-m(W) to um(W) step d do
  • for a in S do
  • if ultv then
  • else
  • find u,v,a, s.t. uvm(a)M and DP(u,v)
    maximized
  • backtracking

Time
25
PEAKS The Software
26
Comparison
  • LCQ data (Iontrap instrument)
  • Generously provided by Dr. Richard Johnson. 144
    spectra.
  • Micromass Q-Tof data
  • Measured in UWOs Protein ID lab. 61 spectra
  • Sciex Q-Star data
  • Provided by U. Victorias Genome BC Proteomics
    Centre. 13 good/okay spectra.

27
PEAKS v.s. Lutefisk
  • completely correct sequences
  • 38/144 v.s. 15/144
  • correct amino acids
  • 1067/1702 v.s. 767/1702 v.s.
  • partially correct sequences with 5 or more
    contiguous correct amino acids
  • 94/144 v.s. 64/144

28
PEAKS v.s. Micromass PLGS
  • completely correct sequences
  • 13/61 v.s. 7/61
  • correct amino acids
  • 456/764 v.s. 232/764
  • partially correct sequences with 5 or more
    contiguous correct amino acids
  • 38/61 v.s. 24/61

29
PEAKS v.s. Sciex BioAnalyst
  • completely correct sequences
  • 7/13 v.s. 1/13
  • correct amino acids
  • 115/150 v.s. 86/150
  • partially correct sequences with 5 or more
    contiguous correct amino acids
  • 12/61 v.s. 7/61

30
Users
The company logos have been deleted from the
original presentation. Please visit
http//www.bioinformaticssolutions.com for a list
of users.
31
Other Techniques Used by PEAKS
  • Preprocess the MS/MS spectra
  • Deconvolution, noise reduction, and signal
    enhancement.
  • It does a better job than spectrometer vendors
    software.
  • Recalibration
  • compress/stretch the spectrum for calibration
    error
  • Positional Confidence
  • Estimate the confidence level of individual amino
    acids.

32
Sophisticated Ion Matching Score
  • Score of one peak matching b ion

33
PEAKS 2.xs Additional Feature
  • Identify the proteins by matching the de novo
    (partial) sequences.
  • Then further match the spectra with the peptides
    of the proteins.

34
Collaborators and References
  • Sandwich algorithm
  • B. Ma, K. Zhang, C. Liang, CPM03. (sandwich
    algorithm)
  • PEAKS
  • B. Ma, K. Zhang, C. Hendrie, C. Liang, M. Li, A.
    Doherty-Kirby, G. Lajoie, Rapid Comm. Mass Spec.
    (software feature, score function, experiments)
  • Acknowledgement
  • PEAKS development team. (Bioinformatics Solutions
    Inc.).

35
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