Download Raman Spectroscopy

Raman Spectroscopy for the analysis of
plant cell wall
Biochemical composition and Si detection on cucumber roots and stem
18.11.2014
Oleksandr Zavoiura, Anna Lopez de Guerenu and Bárbara Gonzalez
Raman Spectroscopy
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Measurement of inelastic scattering
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Requirement for activity:
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Interfering factor: Fluorescence
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Raman Spectroscopy
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Raman Spectroscopy
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Diffraction barrier:
d
x ,y
=
d =
z
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λ
≈ 200nm
2 ⋅ NA
em
2⋅λ
NA
em
2
NA = n ⋅ sin(α )
≈ 500nm
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Plants cell wall
Cucumber Plant Illustration. 4
Cucumber Cell5. ≈100μm
Cucumber Cell Wall6.
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The cell walls is essential for the plant7: Shape – Support – Growth– Signalling – Transport.
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The main components are: Proteins–Polysaccharides– Lipids – Aromatic substances.
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Silicic acid and Silicification
Study of silica deposition in cucumber (cucumis sativus from cucurbitaceae family) plant cell walls
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Which organisms?  Plants, diatoms (algae) and sponges.
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Silica nutrition benefits?  Plant defence, stress resistance and growth factors.
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Mechanisms?  Objective of study in plant physiology.
pKa=9.8
Scheme of the Silica up-taking reactions.8
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Raman Spectroscopy procedure
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Sample preparation: Cutting considerations
Fresh plant sample give the best results
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Planar surface and intact cell walls
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Be aware of stem and fiber orientation in order to cut and
investigate defined planes
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Thickness 8–20 μm
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Bigger than focal depth of laser beam (To avoid
signal from the coverslip)
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High expertise to cut by hand  Rotatory microtome
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Rotatory Microtome semi-automatic
From Mikron Instruments Inc 10
Sample preparation: cryostat vs. embedding
Cryosectioning
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combination of microtome and cryostat
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snapfreezing (liquid N2)
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thickness between 10 and 30 μm
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timing: 1 h to 1 d
Cryostat for cryosectioning
CM1800 from Leica 11
Embedding
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PEG works the best  no matrix effect
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Resin not as good  noise is increased (especially at λ = 532 nm)
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timing: 1 week
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Raman Spectroscopy procedure
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Laser sources
488 nm
Ar+
400 nm
532 nm
Nd:YAG
633 nm
He-Ne
500 nm
600 nm
UV
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785 nm
GaAlAs
700 nm
IR
High
Raman Intensity
Low
Good
Spatial resolution
Poor
High
Fluorescence
Low
Inorganic Samples
Mapping
Resonant Raman Scattering
Preferred for
Highly fluorescent compounds
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Confocal Raman Spectroscopy: setup
Laser
Sources
SALSA’s qualified PhD Student
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Big Raman Lab
(TU Berlin)12
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Output Spectra
Confocal Raman Spectroscopy: setup
Spectrometer
Confocal Microscope
CCD-Detector
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Cucumber: What to expect
Raman spectra of a cell wall membrane of onion (1),
carrot (2), polypogon (3), rice (4) and sweet corn (5) 14
Scale model of a portion of a primary plant cell wall 13
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Cucumber: What to expect
Study of silica deposition on cucumber roots and stem vs non-silica samples
Electron micrographs of silica structures from plants. Stomata of mature E. arvense surrounded by pilulae encrusted with rosettes; the observed specimens
contain 0.1 % w/w C, with the remainder being silica; left, upper surface; right, lower surface. 8
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Cucumber: What to expect
Study of silica deposition on cucumber roots and stem vs non-silica samples
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Cell wall compounds I
Pectic compounds17
Cellulose15
Homogalacturonan
Lignin16
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Rhamnogalacturonan I
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Rhamnogalacturonan II
Cell wall compounds I
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Cell wall compounds II
Chlorophyll
Spectra of chlorophyll water aggregates, suspended in decane. Lower spectrum: chlorophyll a, excitation 457.9 nm. Upper spectrum, chlorophyll b,
excitation 488 nm. 18
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Cell wall compounds III
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Raman
wavenumber
[cm-1]
Assignment
2938
Lignin (20)
1658
Lignin (20)
1650
Protein Amide I (22)
1602
Lignin (20)
1554
Chlorophyll (21)
1533
Chlorophyll(21)
1445
Lipids, Protein ᵟ(CH2, CH3)
1350
Chlorophyll(21)
1333
Lignin (20)
1292
Chlorophyll(21)
1268
Protein Amide III (22)
Polarization dependence
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For crystalline structures the intensity of the
peak depends on the polarization of the light
E.g. cellulose peak at 370 cm-1
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By comparing spectra taken with Raman
light polarized perpendicular or parallel to
the longitudinal axis of the cell, the
orientation of macromolecules in the cell
wall can be investigated
Hypothetical arrangement of organic layers in the algae (diatom) cell wall.
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Polarization dependence
Degree of polarisation (p):
y2= anisotropy
Symmetry=100%  p=3/4; α=0
α= polarisationtensor
Symmetry<100%  0<p<3/4; α≠0
Fourier transform-Raman spectra of wheat epidermis walls with parallel and perpendicular polarization:
(A) stalk, (B) sheath, and (C) node. Raman Intensity is given on a relative scale. 24
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Raman Spectroscopy procedure
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Data analysis I: Spectra processing
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Cosmic Ray Removal – to get rid of spikes
from the CCD detector in the spectra.
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Smoothing algorithms – to reduce the noise in
the recorded spectra.
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Background–Baseline correction – to eliminate
changes in background (suitable for all spectra
in the data set)
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Additional parameters – depending on the goal
of the data analysis
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Data analysis II: Image generation
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Univariate analysis – Single band imaging:
Each spectrum determines one value of the corresponding pixel in the image.
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Simple filters: a chemical image can be generated by focusing on an area of the map and integrating
over one specific peak of interest. Information about the spatial distribution.
Optical image of the analysis of Tomato cell wall. A) Microscopic image B) polysaccharides at
2940cm-1 C) Pectin at 854cm-1 D) Cellulose at 1090cm-1, γ(COC)glycosidic.19
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Data analysis II: Image generation
Multivariate analysis:
Hyperspectral images generated from matrices containing redundant information
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Principal Component Analysis (PCA): Math–Orthogonal linear transformation. Effective to reduce
the data set to 5–15 principal components, plus the residual error. Contains all the relevant info of
the image.
a) 2D PCA-scores plot of PC1 vs PC2 b) 1D PCA-loadings plot of PC1 vs Raman shift. Raman shift
range 200 – 2000 cm-1.25
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Data analysis II: Image generation
PCA scores images and loading spectra. A) PC2 mainly Pectin B) PC3 mainly Cellulose C) PC2 and PC3 depicted as Pectin and Cellulose distribution D) PC2
loading E) PC3 loading. Analysis of Tomato cell walls.19
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Multivariate curve resolution (MCR):
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recovery of the response profiles of more
than one component in unresolved and
unknown mixtures
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provides information about the nature and
composition of these mixtures.
A) Assigned mainly to Pectin compounds
Characteristic peaks: 2949, 1751, 855 and 816 cm−1
B) Assigned mainly to Cellulose
Characteristic peaks: 2895, 1378, 1122, 1093 and 971 cm−1
C) Assigned mainly to hemicellulose
Characteristic peaks: 2933 and 1257 cm−1
MCR concentration images and the spectra of the sampled purecomponents: A) component 1; B) component 2; C) component 3. 19
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Advantages
Disadvantages
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Can be used with solids and liquids
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No sample preparation needed
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Not interfered by water
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Non-destructive
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Highly specific like a chemical fingerprint of a material
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Can not be used for metals or alloys
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Raman spectra are acquired quickly within seconds
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The Raman effect is very weak. The detection needs a
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Samples can be analyzed through glass or a polymer
packaging
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sensitive and highly optimized instrumentation.
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Laser light and Raman scattered light can be
transmitted by optical fibers over long distances for
hide the Raman spectrum.
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remote analysis
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Raman spectra can be collected from a very small
Inorganic materials are normally easier analyzed by
Raman than by infrared spectroscopy
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Sample heating through the intense laser radiation
destroy the sample or hide the Raman spectrum.
volume (< 1 µm in diameter)
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Fluorescence of impurities or of the sample itself can
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Methods to complement Raman results
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SEM Scanning Electron Microscopy
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Structural differences between the cell wall
regions.
Back scattering electrons
EDX + WDX
WAXS / SAXS
Microfibrils orientation / Microfibrils Angle (MFA)
Wide/Small Angle X-Rays Scattering
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Polarized light
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Acoustic scanning microscopy
Study of MFA
Stiffness and density of the sample
• ICP-MS
Induced-Coupled Plasma MS
Elemental composition of the sample.
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References
1- Raman Spectroscopy. Wikipedia. Online (http://en.wikipedia.org/wiki/Raman_spectroscopy), visited 12.11.2014.
2- Raman.de Dr. Bernd Dippel. Online (www.raman.de), visited 16.11.2014.
3- Fenn M. B. et al. Raman Spectroscopy for Clinical Oncology. Advance in Optical Technology, Hindawi Publishing Corporation, 2011.
4- East-west seed Plant Doctor. Online (http://plantdoctor.eastwestseed.com/plant-parts/Cucumber), visited 11.11.2014.
5- Gottalovebio, Cells. Online (http://gottalovebio.wikispaces.com/Team+5), visited 11.11.2014.
6- Yellow tang, Cell wall in plants. Online (http://www.yellowtang.org/images/cell_walls_in_plant_c_ph_784.jpg), visited 11.11.2014.
7- College of St. Benedict/St. John's University, Biology Department, Plant Physiology. Online
(http://employees.csbsju.edu/ssaupe/biol327/Lecture/cell-wall.htm), visited 11.11.2014.
8- Heater A. C. and Carole C. P. Silica in Plants: Biological, Biochemical and Chemical Studies. Annals of Botany 100; 1383-1389, 2007.
9- Gierlinger N. et. al. Imaging of plant cell wall by confocal Raman microscopy. Nature Protocol, 7 no.9; 1694-1708, 2012.
10- Mikron Instruments Inc. Online (www.mikronet.com), visited 11.11.2014.
11- Leica BIOSYSTEMS. Online (www.leicabiosystems.com), visited 11.11.2014.
12- Pictures acquired from Raman Laboratory from Prof. Peter Hildebrandt research group, TU Berlin. Taken 13.11.2014.
13- Cosgrove D., Nature Reviews Molecular Cell Biology 6, 850-861, 2005.
14- Sene et al. Plant Physiology. vol. 106 no. 4, 1623-1631, 1994.
15- Sarkar P et al., J. of Exp. Botany, Vol. 60, No 13, 3615-3635, 2009.
16- Wikipedia, Lignin. Online (http://en.wikipedia.org/wiki/Lignin), visited 13.11.2014.
17- Ochoa-Villarreal M et al. Plant Cell Wall Polymers: Function, Structure and Biological Activity of Their Derivatives. Polymerization 4, 63-86, 2012.
18- M. lutz, Resonant Raman spectral of chlorophyll in solution. Journal of Raman Spectroscopy, Vol 2; 497-516, 1974.
19- Chylinska M, et. al. Imaging of polysaccharides in the tomato cell wall with Raman microspectroscopy. Plant Methods 10:14, 2014.
20- Rowel M.R. Handbook of Wood Chemistry and Wood Composites, Second Edition 2013, p. 233.
21- Z.Cai, et al. Biochimica et Biophysica Acta (BBA) – Bioenergetics, Vol.1556,(2–3), 2002, 89-91.
22- Schulte F. et al. , Anal. Chem., 2008, 80, 9551-9556.
24- Cao et al, Ann Bot. Jun 2006; 97(6): 1091–1094.
25- Mobili P. et. al. Multivariate analysis of Raman spectra applied to microbiology: Discrimination of microorganisms at the species level.
Revista mexicana de fisica 56 (5) 378–385, 2010.
26- Sielbold M, et. al. Application of elemental bioimaging using laser ablation ICP-MS in forest pathology: distribution of elements in the bark
of Picea sitchensis following wounding. Anal Bioanal Chem 402:3323– 3331, 2012.
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Iona Sighiartau
Robert Harmel
Virginia Merk
Sven Schulz
&
Konrad Löhr
Prof. Janina Kneipp
José Villatoro
Thi Hoa Hoang
Felix Rösicke
Thank you …!
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