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Observations des données:
recherche des régions spectrales
corrélées
6- Classification de spectres
Etant donné un nombre de spectres, comment
les classer par “ressemblance”
6- Classification de spectreshierarchical clustering
Step 1: the Euclidian distance between each pair of spectra is calculated.
Figure: 5 spectra represented in a 2-D space (say we recorded only the absorbance at two wavenumbers)
6- Classification de spectres
Step 2: grouping starts by linking the closest spectra.
Figure: grouping of spectra (#1 to 5) and clusters (beyond #5)
hierarchical clustering
6- Classification de spectres
Step 3: dendrogram representation.
Statistical significance of the distances
hierarchical clustering
0100200300400500600700
1517136812739111219263114241620274105304422253336341835402123293237414228383947434549504648
Dendrogram, distance: euclidean, linkage: ward, range: 1711-1485
hierarchical clustering
50 protéines
6- Classification de spectres
d1 r2d2 brasiliensis peruviana lainsoni0
1
2
3
4
5
6
7
8
donovani
hierarchical clustering
6- Classification de spectresK-means clustering
kmeans treats each spectrum as an object having a location in space. It finds a partition in which spectra within each cluster are as close to each other as possible, and as far from spectra in other clusters as possible.
kmeans uses an iterative algorithm that minimizes the sum of distances from each object to its cluster centroid, over all clusters. This algorithm moves objects between clusters until the sum cannot be decreased further. The result is a set of clusters that are as compact and well-separated as possible.
Identification de lignées cellulaires
Chemical differencesas(CH3)
10001200140016001800200022002400260028003000
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
cm-1
Absorb
ance
as(CH3) s(CH3)
as(CH2)
(C=O)ester (CH3)
(CH2)
as(PO2-)
(C-O)
s(PO2-)
as(N-(CH3)3+)
Amide I (C=O)amide
Amide II(N-H)amide
(C-OH)
Phospholipid (DMPC)
Glycoprotéine
Mucine
RNA
DNA
Correlated with growth, not with species
INFRARED MEASUREMENTS
X3
1000150020002500300035000
50
100
150
200
250
cm-1
Ab
sorb
anc
e
Infrared spectrum of a cell
• The conformation of the molecules, especially proteins
IR spectrum = fingerprint of:
• The chemical nature of the components (glycosylations, DNA, RNA, proteins, lipids,….)
Fingerprinting and cell classification
Dendrogram of a hierarchical cluster analysis performed on 240 spectra of different strains of Gram-positive andGram-negative bacteria, and of yeasts belonging to the genus Candida (a). Dendrogram obtained when cluster analysis is performed on the yeast spectra only (b).
FTIR of bacteria
FTIR of bacteria
Spectral typing of closely related microorganisms. (a) Clinical isolates of E. coli (numbers in right column) belonging to different serogroups: O 25, O 18, and O 114 according to their O-antigenic structure.
FTIR of bacteria
Application à des cellules eucaryotes
1. Identification de Leismania sp.
2. Cellules leucémiques K562 wt ou résistantes
3. Classification de cellules gliales
4. Mode d’action de molécules anticancéreuses
5. Etudes microscopiques de tissus
L. lainsoni versus L. brasiliensis
(87 spectra)
1000150020002500300035004000
0
100
200
300
400
500
600
700
800
cm-1
Abs
orba
nce
• recording: 2 cm-1, 256 scans
• noise evaluation
• Water vapor subtraction (when necessary), apodization at 4 cm-1 final resolution
• Baseline subtraction (typically 3620 3010 2700 2395 2247 1775 1718
1483 1434 1353 1196 948 845)
• Scaling for a same area under 1718-1483 cm-1
Spectra recording and processing
140014501500155016001650170017501800
0
200
400
600
800
1000
1200
1400
1600
cm-1
Abs
orb
anc
e
0 20 40 60 80 100 120 1400
0.05
0.1
0.15
0.2
0.25
150015201540156015801600162016401660168017000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
cm-1
Ab
sorb
an
ce
1000150020002500300035004000
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
cm-1
Ab
sorb
an
ce
100015002000250030000
0.02
0.04
0.06
0.08
0.1
0.12
cm-1
Abs
orba
nce
Identification de cellules eucaryotes
10001200140016001800200022002400260028003000
0
100
200
300
400
500
cm-1
Abs
orb
anc
e
Leishmania lainsoni
Leishmania
brasiliensis
Différences significatives (Student test)
100012001400160018002000220024002600280030000
50
100
150
200
250
300
cm-1
Abs
orb
anc
e
Différence des moyennes
Moyenne pour L. lainsoni
Moyenne pour L. brasiliensis
* Student positive, alpha=0.01
Classification supervisée / non supervisée
0 100 200 300-50
-45
-40
-35
-30
-25
-20
-15
1
2
3
4
5
67
8
9
10
11
12
13
14
15
16
17
18
19
20 21
22
23
24
25
26
2728
2930
31
32
3334
3536
37
38
39
40
41
42
43
44
45
CP 1
CP
2
Score plot, selected wavenumbers: 3025 2996; 2945 2835; 1760 1725; , unknown in magenta
-20 0 20 40-28
-26
-24
-22
-20
-18
-16
-14
-12
-10
12
34 5
6
7
8
9
10
11
12
13
1415
16
17
18
19
2021
22
23
24
25
26
27
28
2930
31
32
33
3435
36
37
3839
40
41
42
43
44
45
CP 3
CP
4
-5 0 5-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
1
2
3
4
5
67
8
9
10
11
12 13
1415
16
17
1819
20
21
22
23
24
25 26 2728
29
30
31
32
3334
3536
37
38
39
40
41
42
43
44
45
CP 5
CP
6
0 10 20 30 40 500.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
1
2
3
4
5
6
7
8
9
10
1112131415
16
17
181920
2122
23
24
25
26
2728
29
30
31
3233
34
35
36
3738
39
40
41
4243
4445
Spectrum number
Gro
up
Lin reg of scores on groups, selected wavnb: 3025 2996; 2945 2835; 1760 1725;
Analyse non supervisée: decomposition en composants principaux
(cross validation)
Analyse supervisée: régression linéaire
(cross validation)
Distance between spectraModel built after variable selection and principal component analysis
10 14 23 15 29 39 1 9 5 3 2 22 25 28 35 32 34 44 4 8 38 6 13 19 45 46 7 49 16 55 50 31 18 36 26 20 48 27 11 30 37 47 24 40 56 12 42 41 17 59 60 43 21 33 84 79 85 51 53 71 77 57 67 58 83 69 75 65 72 86 54 64 66 80 81 82 63 74 70 68 78 87 52 61 62 73 760
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Leishmania lainsoniLeishmani
a brasiliensis
gr1 gr3 gr2 gr4 gr5 gr6 gr9 gr7 gr8
0.5
1
1.5
2
2.5
3
3.5
4
L. lainsoni versus L. brasiliensis
MANOVA using 1753, 1724, 3008 and 1430 cm-1
L. brasiliensis
L. lainsoni
Classification de quatre espèces
Leishmania peruviana
Leishmania lainsoni
Leishmania donovani
Leishmania brasiliensis
1400145015001550160016501700175018000
100
200
300
400
500
cm-1
Abs
orba
nce
Distance analysis between species
d1 r2d2 brasiliensis peruviana lainsoni0
1
2
3
4
5
6
7
8
donovani
Chemical differences
10001200140016001800200022002400260028003000
-4
-3
-2
-1
0
1
2
3
cm-1
Abs
orba
nce
* Student positive, alpha=0.01
Mean L. brasiliensis – Mean L. lainsoni
as(CH3)
10001200140016001800200022002400260028003000
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
cm-1
Absorb
ance
as(CH3) s(CH3)
as(CH2)
(C=O)ester (CH3)
(CH2)
as(PO2-)
(C-O)
s(PO2-)
as(N-(CH3)3+)
Amide I (C=O)amide
Amide II(N-H)amide
(C-OH)
Phospholipid (DMPC)
Glycoprotéine
Mucine
RNA
DNA
Correlated with growth, not with species
100012001400160018002000220024002600280030000
50
100
150
200
250
300
cm-1
Absorb
ance
Difference of the means
Strain 1, mean
Strain 2, mean
Effect of culture growth. Comparing two strains.
02
46
810
12
9001000
11001200
13001400
1500
-50
0
50
100
150
200
Culture day
0 2 4 6 8 10-150
-100
-50
0
50
1240
1085
CONCLUSIONS
1. Certaines régions spectrales décrivent la croissance de la culture indépendamment de l’espèce
2. D’autres régions décrivent l’espèce indépendamment de l’état de la culture
3. La spectroscopie FTIR peut devenir un outil rapide et économique pour la détermination de Leishmania sp.
90011001300150017001900210023002500270029003100-1
1
3
5
7
9
frequency, cm-1
inte
nsity
A.B.C.D.
trace A: Representative infrared spectrum of resistant K562 cells. trace B: Representative infrared spectrum of sensitive K562 cells. trace C: Difference infrared spectrum between resistant and sensitive K562 cells, this spectrum is magnified 4 times.trace D: Result of the Student test performed at alpha level = 5% , the wavelengths in blue are significantly different between the two cell lines.
Example of information retrieved from the data: the intensity ratio between 2958cm -1 (CH3 stretching) and 2923cm-1 (CH2 stretching) is increased by 20% in resistant cells, suggesting a qualitative modification of the lipids in the cell membranes.
2) Resistant / sensitive K562
-2 -1.5 -1 -0.5 0 0.5 1 1.5 2
x 10-3
-10
-8
-6
-4
-2
0
2
4
6
8x 10
PC3 = 0.041%
PC
6 =
0.0
103
%
2D plot of K562 sensitive (22 spectra, blue points) and resistant (26 spectra, red stars) cells spectra reduced by PCA.
Unsupervised classification
Belot et al., Glia 2001, 36, 375-390
3) Identification de phénotypes: le cas des gliomes
In vitro parameters :
Motility : Maximum Relative Distance from the Origin
Motility : Average Speed
Growth : Anchorage-dependent growth
Growth : Anchorage-independent growth (in semi-solid agar)
Invasion : percentage of cells invading a collagen matrix
In vivo parameter :
Aggressiveness : Median Survival Time
2852 cm-1
2983 cm-1
2945 cm-1
Identification de phénotypes: le cas des gliomes
Sample preparation
FTIR de cellulesIdentification de phénotypes: le cas des gliomes
FREQUENCY (CM-1)
100011501300145016001750285029253000
INF
RA
RE
D A
BS
OR
BA
NC
E (
A.U
.) 16 cell lines used
Identification de phénotypes: le cas des gliomes
Calculated values
Actu
al v
alue
s
A172
H4
HS683
SW1088
SW1783
T98U118
U87
U373
5
6
7
8
9
10
11
12
5 6 7 8 9 10 11 12
Calculated values
Actu
al v
alue
sA172
H4
HS683
SW1088
T98U118
U87
U373
-2
2
6
10
14
18
22
-2 2 6 10 14 18 22 26
Multiple regression explaining the average speed
R = 0.96 (P = 0.003).
Multiple regression explaining the median survival periods of the nude mice grafted with glioma cells.
R = 0.97 (P = 5 10-3).
Average speed Median survival time
Identification de phénotypes: le cas des gliomes
Mode d’action de molécules
anticancéreuses
Studies on cells
- PC-3 prostate cancer cells in culture
- Washed in 0.9% NaCl
- Deposited on a BaF2 window
Daunorubicine
Doxorubicine
Irinotecan
Mercaptopurine
Méthotrexate
Paclitaxel
Vinblastine
Vincristine
Non traitées100011001200130014001500160017001800
0
200
400
600
800
1000
1200
cm-1
Abs
orba
nce
406080100120140160180
taxol.ir
vcri.ir
vbla.ir
dauno.ir
doxo.ir
merco.ir
metox.ir
Dendrogram, distance: euclidean, linkage: ward, range: 1724-1300
Daunorubicin
Doxorubicin
Mercaptopurine
Methotrexate
Paclitaxel
Vinblastine
Vincristine
Distance
Hierarchichal classification of “ difference spectra”
FTIR of drug signature on cancer cells
FTIR of drug signature on cancer cells