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3rd International Conference on Bio-Sensing Technology

Optical forward-scattering for identification
of bacteria within microcolonies.
Antoine CUER
Joe-Loïc KODJA
Arthur LEFEBVRE
Florian LICARI
Robin LOUVET
Anil NARASSIGUIN

Mathieu DUPOY
Pierre MARCOUX

Frédéric MALLARD
Introduction: How a bacterium species can be identified ?
Molecular methods

Microscopy /
staining

Genomic analysis

Morphological
characteristics
ID based upon the
composition of cellular
membrane

Enzymatic activities
[P69] Non-invasive detection of
bacteria via the sensing of volatile
metabolites released by enzymatic
Biochemical
API L.H.
activity test Guillemot, M. Vrignaud, P.R.
tests
Marcoux, T.-H. Tran-Thi.

Antigenic
characteristics
ID based upon the
global cellular
composition
Spectral
fingerprint
|2

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
Introduction: Rapid methods in diagnostic
Reference method

Rapid method under investigation

24h

API tests (bioMérieux):
Pathogen is identified
according to the results (+ or
-) of a series a biochemical
tests

6h

24h

a few
seconds

Raman spectroscopy:
Pathogen is identified
according to its Raman
fingerprint

• identification tests must be performed on a much smaller amount
of cells (1-103 cells), so as to reduce the time dedicated to growth
• identification tests must be faster
|3

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
Introduction: optical methods for identification
1. Raman: inelastic scattering / Forward-scattering: elastic scattering
Elastic scattering yields much more photons:
exposure time in Raman: 30 s (spectrum on a single cell)
exposure time in forward-scattering: ∼1 ms (single-cell; microcolony)
2. Raman: vibrational spectroscopy, a peak is linked with a particular
spectroscopy
vibration mode of a type of covalent bond: e.g. υ(C=O); υ(C−Η)…
Forward-scattering is not a spectroscopy: it does not yield information
about cell composition, but rather about morphological characteristics.

Raman (inelastic
scattering)

Diffraction (elastic
scattering)

|4

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
Introduction: optical methods for identification
3. As for Raman spectroscopy and intrinsic fluorescence, forwardscattering is a label-free method. Non invasive technique, requires
method
little or no consumable, can be automated.
automated
4. In direct space: the packing of bacteria
cells within microcolony induces a
periodic modulation of phase (refraction
index) and absorbance
⇒ in reciprocal space:
it yields diffraction
fringes.

|5

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
Introduction: experimental process and setup
Elastic
diffusion
(laser)
microcolony
(6h of incubation)

(

Forward-scattering
(543 nm)
camera 1
(images in
direct space)

15

5

Multivariate
statistics
strain
EC21
HA4

PCA pl ot f or EC2 1 and HA4 scat t er i ng pat t er ns

classification
(for ex. Principal
Component Analysis)

PC# 2

Microcolony on
agar
camera 2
(acquisition of
scattering
pattern)

)

H. alvei

10

Laser (534nm)

Projection
onto a
basis
α 1 ... α n
functions
descriptor
(n-component vector)

0

E. coli

-5

PC# 1
0

20

40

60

80

|6

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
Introduction
Let’s investigate the possibility of using forward-scattering as an
identification method on microcolonies after 6 hours of incubation
(37°C), directly on agar medium:
1. Scattering patterns: How are they formed ?
patterns
What kind of information do they give ?
2. Image analysis: How can we compare scattering patterns
analysis
quantitatively ?
3. Results: A first database of Gram- species at 6h
on TSA (Tryptic Soy Agar)
4. First results on two CNS (Coagulase-Negative Staphylococci) at 6h
Staphylococci
on ChromID MRSA.

|7

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
1. Scattering patterns : phenotypic information
A scattering pattern contains complex phenotypic information, which is a
sum of various parameters, such as:
1. Refraction index: of nutrient agar medium, of bacteria, of extracellular
matrix.
2. Cellular shape.
shape
3. Geometry of bacteria stacking within microcolony (the scattering of
planktonic cells, i.e. growing in liquid medium, yields a much less complex
pattern).
4. Shape of the whole microcolony: it acts as a micro-lens.
microcolony

|8

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
1. Scattering patterns : two kinds of fringes
 Fringes at low angles: corresponds to low spatial frequencies, the
angles
whole bacterial colony scatters. More light, but less complex shape.
Available from the start. Spatial periods: a few tens of µm.
4h50

 Fringes at high angles: corresponds to high spatial frequencies,
angles
scattering due to the stacking of cells. Much less photons (appears after
several hours of incubation), but more complex shape. Seems to yield
more discrimination.
Spatial periods: ∼ 1 µm and less.

LA

LA

HA

HA

|9

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
2. Image analysis: four strains of the same species at t=6h

E. coli ATCC25922
(EC10)
4h50

E. coli ATCC8739
(EC11)

How can we quantitatively compare
all these scattering patterns ?

E. coli ATCC35421
(EC21)

E. coli ATCC11775
(EC28)

E. coli ATCC8739
| 10

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
2. Image analysis: calculation of descriptor

image
(scatterogram)

vector (descriptor)
V=(V1,V2,…,Vn) made of Anm projections:
4h50

Projection Anm of scattering pattern f(r,θ) onto Zernike polynomial Znm
= similarity coefficient between the image f and the basis function Znm
project
ion

Znm(r,θ )

ction
proje

projection

f(r,θ )
project
ion

The more similar f and Znm look, the
higher is Anm (Zernike moment).
Projections Anm (Zernike
moments) are calculated
for the first 120 Zernike
polynomials Znm
| 11

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
3. Results: a first database on Gram- species (t = 6h)
Classified as
Imaged
scatterogram

EC8

EC8

48,8

7,9

0,0

11,0

EC10

6,4

49,1

14,5

EC11

0,0

7,3

EC21

12,9

EC28

EC10 EC11 EC21 EC28

HA4

CF7

17,3

0,0

15,0

0,0

25,5

2,7

1,8

89,1

0,0

2,7

0,9

0,0

0,0

0,0

81,9

0,0

0,0

5,2

20,5

24,2

1,5

0,8

42,4

0,0

10,6

HA4

0,8

0,0

0,0

0,8

0,0

86,0

12,4

CF7

7,8

0,0

0,0

1,7

0,0

3,5

87,0

sum
100%
(127)
100%
(110)
100%
(110)
100%
(116)
100%
(132)
100%
(121)
100%
(115)

Average classification rate (Naive Bayes) over
the whole database: 69%.

Forward scattering on
microcolonies (6h of
incubation, 37°C) growing on
a thin layer (1mm) of TSA
(Trypcase Soy Agar). Laser
beam: 100µm∅ on bacteria.
bacteria
| 12

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
3. Results: a first database on Gram- species (t = 6h)
Can we discriminate the different
strains of the E. coli species ?

Principal Component Analysis
Supervised learning
(Naive Bayes Continuous)
⇒ Classification rate = 82% on average
| 13

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
4. Results: distinguishing two species of Staphylococci
 Second step: with commercial Petri
dishes (5mm thick), scattering patterns
are acquired without opening lids
 no risk of cross-contamination
between samples
 We chose ChromID MRSA (bioMérieux)
as a nutrient medium: screening of
Gram+ strains resistant to methicillin.
methicillin
 Can we discriminate, after 6h of incubation, two species of
Staphylococci that grow on ChromID MRSA ?
Study on Staphylococcus haemolyticus and Staphylococcus cohnii, two
methicillin-resistant species (Coagulase-Negative Staphylococci).
 As we obtain a significantly slower growth, we reduce the laser beam
on bacteria down to 25µm ∅ .
| 14

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
4. Results: distinguishing two species of Staphylococci
Forward scattering through the whole Petri dish (including lid).
6h of incubation (37°C). 2 species of methicillin-resistant Staphylococci
growing on ChromID MRSA (bioMérieux). Laser beam: 25µm∅ on bacteria.

S. cohnii
S. cohnii
S. haemolyticus

Principal Component Analysis

S. haemolyticus

Supervised learning (Naive Bayes Continuous)
⇒ Classification rates: 92% on average
| 15

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
Conclusion
Identifying pathogenic species is not enough: a complete diagnosis
must include Antibiotic Susceptibility Testing (AST).
→ To guide the selection and modification of antimicrobial therapy
Currently under investigation…

Towards label-free, non invasive (without
opening lids), non destructive, automated
methods.
Less than 6h for identification + AST
| 16

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013
© CEA. All rights reserved
Acknowledgments
Mathieu DUPOY

n
atio
en t
m
stru
in
ical
opt

Antoine CUER, Joe-Loïc KODJA
Arthur LEFEVBRE, Florian LICARI
Robin LOUVET, Anil NARASSIGUIN
Charles-Edmond BICHOT

Frédéric MALLARD
Frédéric PINSTON

y
o lo g
bi
icro
m

g
inin
m
ata
d
and
is
alys
n
ge a
i ma

http://eric.univ-lyon2.fr/~ricco/tanagra/fr/tanagra.html
| 17
http://www.cs.waikato.ac.nz/ml/weka/

P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013

© CEA. All rights reserved

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Optical forward-scattering for identification of bacteria within microcolonies

  • 1. 3rd International Conference on Bio-Sensing Technology Optical forward-scattering for identification of bacteria within microcolonies. Antoine CUER Joe-Loïc KODJA Arthur LEFEBVRE Florian LICARI Robin LOUVET Anil NARASSIGUIN Mathieu DUPOY Pierre MARCOUX Frédéric MALLARD
  • 2. Introduction: How a bacterium species can be identified ? Molecular methods Microscopy / staining Genomic analysis Morphological characteristics ID based upon the composition of cellular membrane Enzymatic activities [P69] Non-invasive detection of bacteria via the sensing of volatile metabolites released by enzymatic Biochemical API L.H. activity test Guillemot, M. Vrignaud, P.R. tests Marcoux, T.-H. Tran-Thi. Antigenic characteristics ID based upon the global cellular composition Spectral fingerprint |2 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 3. Introduction: Rapid methods in diagnostic Reference method Rapid method under investigation 24h API tests (bioMérieux): Pathogen is identified according to the results (+ or -) of a series a biochemical tests 6h 24h a few seconds Raman spectroscopy: Pathogen is identified according to its Raman fingerprint • identification tests must be performed on a much smaller amount of cells (1-103 cells), so as to reduce the time dedicated to growth • identification tests must be faster |3 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 4. Introduction: optical methods for identification 1. Raman: inelastic scattering / Forward-scattering: elastic scattering Elastic scattering yields much more photons: exposure time in Raman: 30 s (spectrum on a single cell) exposure time in forward-scattering: ∼1 ms (single-cell; microcolony) 2. Raman: vibrational spectroscopy, a peak is linked with a particular spectroscopy vibration mode of a type of covalent bond: e.g. υ(C=O); υ(C−Η)… Forward-scattering is not a spectroscopy: it does not yield information about cell composition, but rather about morphological characteristics. Raman (inelastic scattering) Diffraction (elastic scattering) |4 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 5. Introduction: optical methods for identification 3. As for Raman spectroscopy and intrinsic fluorescence, forwardscattering is a label-free method. Non invasive technique, requires method little or no consumable, can be automated. automated 4. In direct space: the packing of bacteria cells within microcolony induces a periodic modulation of phase (refraction index) and absorbance ⇒ in reciprocal space: it yields diffraction fringes. |5 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 6. Introduction: experimental process and setup Elastic diffusion (laser) microcolony (6h of incubation) ( Forward-scattering (543 nm) camera 1 (images in direct space) 15 5 Multivariate statistics strain EC21 HA4 PCA pl ot f or EC2 1 and HA4 scat t er i ng pat t er ns classification (for ex. Principal Component Analysis) PC# 2 Microcolony on agar camera 2 (acquisition of scattering pattern) ) H. alvei 10 Laser (534nm) Projection onto a basis α 1 ... α n functions descriptor (n-component vector) 0 E. coli -5 PC# 1 0 20 40 60 80 |6 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 7. Introduction Let’s investigate the possibility of using forward-scattering as an identification method on microcolonies after 6 hours of incubation (37°C), directly on agar medium: 1. Scattering patterns: How are they formed ? patterns What kind of information do they give ? 2. Image analysis: How can we compare scattering patterns analysis quantitatively ? 3. Results: A first database of Gram- species at 6h on TSA (Tryptic Soy Agar) 4. First results on two CNS (Coagulase-Negative Staphylococci) at 6h Staphylococci on ChromID MRSA. |7 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 8. 1. Scattering patterns : phenotypic information A scattering pattern contains complex phenotypic information, which is a sum of various parameters, such as: 1. Refraction index: of nutrient agar medium, of bacteria, of extracellular matrix. 2. Cellular shape. shape 3. Geometry of bacteria stacking within microcolony (the scattering of planktonic cells, i.e. growing in liquid medium, yields a much less complex pattern). 4. Shape of the whole microcolony: it acts as a micro-lens. microcolony |8 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 9. 1. Scattering patterns : two kinds of fringes  Fringes at low angles: corresponds to low spatial frequencies, the angles whole bacterial colony scatters. More light, but less complex shape. Available from the start. Spatial periods: a few tens of µm. 4h50  Fringes at high angles: corresponds to high spatial frequencies, angles scattering due to the stacking of cells. Much less photons (appears after several hours of incubation), but more complex shape. Seems to yield more discrimination. Spatial periods: ∼ 1 µm and less. LA LA HA HA |9 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 10. 2. Image analysis: four strains of the same species at t=6h E. coli ATCC25922 (EC10) 4h50 E. coli ATCC8739 (EC11) How can we quantitatively compare all these scattering patterns ? E. coli ATCC35421 (EC21) E. coli ATCC11775 (EC28) E. coli ATCC8739 | 10 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 11. 2. Image analysis: calculation of descriptor image (scatterogram) vector (descriptor) V=(V1,V2,…,Vn) made of Anm projections: 4h50 Projection Anm of scattering pattern f(r,θ) onto Zernike polynomial Znm = similarity coefficient between the image f and the basis function Znm project ion Znm(r,θ ) ction proje projection f(r,θ ) project ion The more similar f and Znm look, the higher is Anm (Zernike moment). Projections Anm (Zernike moments) are calculated for the first 120 Zernike polynomials Znm | 11 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 12. 3. Results: a first database on Gram- species (t = 6h) Classified as Imaged scatterogram EC8 EC8 48,8 7,9 0,0 11,0 EC10 6,4 49,1 14,5 EC11 0,0 7,3 EC21 12,9 EC28 EC10 EC11 EC21 EC28 HA4 CF7 17,3 0,0 15,0 0,0 25,5 2,7 1,8 89,1 0,0 2,7 0,9 0,0 0,0 0,0 81,9 0,0 0,0 5,2 20,5 24,2 1,5 0,8 42,4 0,0 10,6 HA4 0,8 0,0 0,0 0,8 0,0 86,0 12,4 CF7 7,8 0,0 0,0 1,7 0,0 3,5 87,0 sum 100% (127) 100% (110) 100% (110) 100% (116) 100% (132) 100% (121) 100% (115) Average classification rate (Naive Bayes) over the whole database: 69%. Forward scattering on microcolonies (6h of incubation, 37°C) growing on a thin layer (1mm) of TSA (Trypcase Soy Agar). Laser beam: 100µm∅ on bacteria. bacteria | 12 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 13. 3. Results: a first database on Gram- species (t = 6h) Can we discriminate the different strains of the E. coli species ? Principal Component Analysis Supervised learning (Naive Bayes Continuous) ⇒ Classification rate = 82% on average | 13 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 14. 4. Results: distinguishing two species of Staphylococci  Second step: with commercial Petri dishes (5mm thick), scattering patterns are acquired without opening lids  no risk of cross-contamination between samples  We chose ChromID MRSA (bioMérieux) as a nutrient medium: screening of Gram+ strains resistant to methicillin. methicillin  Can we discriminate, after 6h of incubation, two species of Staphylococci that grow on ChromID MRSA ? Study on Staphylococcus haemolyticus and Staphylococcus cohnii, two methicillin-resistant species (Coagulase-Negative Staphylococci).  As we obtain a significantly slower growth, we reduce the laser beam on bacteria down to 25µm ∅ . | 14 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 15. 4. Results: distinguishing two species of Staphylococci Forward scattering through the whole Petri dish (including lid). 6h of incubation (37°C). 2 species of methicillin-resistant Staphylococci growing on ChromID MRSA (bioMérieux). Laser beam: 25µm∅ on bacteria. S. cohnii S. cohnii S. haemolyticus Principal Component Analysis S. haemolyticus Supervised learning (Naive Bayes Continuous) ⇒ Classification rates: 92% on average | 15 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 16. Conclusion Identifying pathogenic species is not enough: a complete diagnosis must include Antibiotic Susceptibility Testing (AST). → To guide the selection and modification of antimicrobial therapy Currently under investigation… Towards label-free, non invasive (without opening lids), non destructive, automated methods. Less than 6h for identification + AST | 16 P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved
  • 17. Acknowledgments Mathieu DUPOY n atio en t m stru in ical opt Antoine CUER, Joe-Loïc KODJA Arthur LEFEVBRE, Florian LICARI Robin LOUVET, Anil NARASSIGUIN Charles-Edmond BICHOT Frédéric MALLARD Frédéric PINSTON y o lo g bi icro m g inin m ata d and is alys n ge a i ma http://eric.univ-lyon2.fr/~ricco/tanagra/fr/tanagra.html | 17 http://www.cs.waikato.ac.nz/ml/weka/ P.R. Marcoux | Forward-scattering for bacterial identification | 13 May 2013 © CEA. All rights reserved