PRIB2012

1. Principal com ponent analysis for bacterial
proteom ic analysis
Y-h. Taguchi
Chuo University
Akira Okam oto*,
Nagoya University
* present: Aichi University of Education

2. 1. Introduction
2. Incubation condition of Streptococcus
pyogenes & retrieval for proteom ics data
3. Proposed m ethod：Feature Extraction (FE)
4. Biological m eanings of obtained proteins
5. S m ary & Conclusion
um

3. 1. Introduction
Streptococcus pyogenes (化膿レンサ球菌) is ...
norm al bacteria flora,
but also can cause
life-threatening diseases.
Thus, it is im portant to know what the
triggers for S. pyogenes to cause such
dangerous diseases are.
→In this study, we em ploy proteom ic
analysis of S. pyogenes during growing
phase under two distinct conditions.

4. 2. Incubation condition of Streptococcus
pyogenes & retrieval for proteom ics data
37 ℃, until 4(5), 6(7), 14 and 20 hours
(OD660 = 0.40, 0.83, 0.92, and 0.90)
Under two distinct conditions
1) shaking (sha): m ore oxidize stress
2) static (sta): ordinary condition
Fraction
Cell (wc) and Supernatant (snt) [using centrifuge]

5. Retrieval of proteom ic data
m ass spectrom etry detection of fragm ented proteins
[by LTQ-Orbitrap XL + LC]
Protein identification by MASCOT Software
%em PAI (norm alized am ount of proteins) are used for
further analysis.

6. 3. Proposed m ethod：Feature Extraction (FE)
S ples
am
Em bedding Proteins
Proteins
Matrix × ×
× × ×
×
PCA Outliner Selected
Original After FE
〜
Em bedding S ples
am

7. We would like to list “any” significant features (proteins)
in this experim ent, e.g.,
T poral significance
em
protein expression
sta:wc sta:snt sha:wc sha:snt
tim e
Incubation condition significance
protein expression
sta:wc sta:snt sha:wc sha:snt
tim e

8. Fraction significance
sta:wc sta:snt sha:wc sha:snt
tim e
Or their com binations.....
sta:wc sta:snt sha:wc sha:snt
tim e
Unsupervised m ethods like PCA is useful.
(Clustering m ay be OK, too. but it forces
hierarchical or prejudged num ber of clusters.)

9. Results
PCA em beddings of sam ples sha05_wc
⇒ three clear clusters sha05_snt
⇒ What are representative proteins? sha07_wc
sha07_snt
sha14_wc
sha14_snt
sha20_wc
sha20_snt
sta04_wc
sta04_snt
sta06_wc
sta06_snt
sta14_wc
sta14_snt
sta20_wc

10. PCA em beddings of proteins
23 proteins selcted
(underlined are ribosom al ptoteins) SPy1489:hlpA
SPy2039:speB
Spy1073:rplL
SPy2005
SPy2018:em m 1
Spy0059:rpm C
Spy0611:tufA
Spy0274:plr
Spy0062:rplX
SPy2043:m f
Spy0613:tpi
Spy2079:AhpC
SPy1831:rpsF}
Spy2160:rpm G
SPy1373:ptsH
SPy0731:eno
Spy1371:gapN
Spy1881:pgk
SPy0711:speC
Spy0071:rpm D
SPy2070:groEL
Spy0019

11. PCA em beddings of sam ples with only selected 23 proteins
⇒ Configuration is conserved
⇒ These 23 proteins are critical for this configuration
We have repeated
sam e procedure again
after rem oving 23
proteins, and
additional 30 proteins

13. 4. Biological m eanings of obtained proteins
Peroxiredoxin reductase (S Py2079:AhpC), which is
estim ated to be involved in oxygen m etabolism and
hydrogen peroxide decom position, is found in shaking
culture condition rather than static condition. It seem s
reasonable that the increasing am ount of AhpC in
shaking condition because the shaking condition induces
the higher oxygen stress.
T is just an exam ple.
his
Alm ost all selected proteins
are biologically reasonable.
shaking condition

14. 5. S m ary & Conclusion
um
・Proteom ics analysis is applied to growth
phases of S. pyogenes
・ PCA based, unsupervised feature extraction m ethod
is applied to proteom ics data.
・Feature (protein) extraction based upon PCA
extracted biologically im portant proteins.
・At the m om ent, we have not yet figure out the
trigger of disease but m ore extensive researches
will enable us to understand it.

15. Collaborator
wanted!