Heraud 2009 Neuro Image

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First paper published by NeuroImage using any kine of spectroscopic imaging approach.

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Heraud 2009 Neuro Image

  1. 1. ARTICLE IN PRESS YNIMG-06602; No. of pages: 10; 4C: 3, 4, 6, 7, 8 NeuroImage xxx (2009) xxx–xxx Contents lists available at ScienceDirect NeuroImage j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / y n i m g Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging Philip Heraud a,b,1, Sally Caine a,b,1, Naomi Campanale a, Tara Karnezis c, Don McNaughton b, Bayden R. Wood b, Mark J. Tobin d, Claude C.A. Bernard a,⁎ a Multiple Sclerosis Research Group, Monash Immunology and Stem Cell Laboratories, Monash University, Wellington Road, Victoria 3800, Australia b Centre for Biospectroscopy and School of Chemistry, Monash University, Wellington Road, Victoria 3800, Australia c Ludwig Institute for Cancer Research, Post Office Box 2008, Royal Melbourne Hospital, Victoria 3050, Australia d Australian Synchrotron, 800 Blackburn Road, Victoria, 3168, Australia a r t i c l e i n f o a b s t r a c t Article history: Multiple sclerosis (MS) is an inflammatory, demyelinating and neurodegenerative disease of the central Received 7 April 2009 nervous system (CNS). Despite progress in understanding immunogenetic aspects of this disease, the Revised 17 September 2009 mechanisms involved in lesion formation are unknown. To gain new insights into the neuropathology of MS, Accepted 22 September 2009 we used an innovative integration of Fourier transform infrared (FT-IR) microspectroscopy, bioinformatics, Available online xxxx and a synchrotron light source to analyze macromolecular changes in the CNS during the course and prevention of experimental autoimmune encephalomyelitis (EAE), an animal model for MS. We report that subtle chemical and structural changes not observed by conventional histology were detected before the onset of clinical signs of EAE. Moreover, trained artificial neural networks (ANNs) could discriminate, with excellent sensitivity and specificity, pathology from surrounding tissues and the early stage of the disease progression. Notably, we show that this novel measurement platform can detect characteristic differences in biochemical composition of lesion pathology in animals partially protected against EAE by vaccination with Nogo-A, an inhibitor of neural outgrowth, demonstrating the potential for automated screening and evaluation of new therapeutic agents. © 2009 Elsevier Inc. All rights reserved. Introduction from a single data acquisition, without the addition of chemical stains or reagents (McNaughton et al., 2008; Ooi et al., 2008). A key feature Multiple sclerosis (MS), is commonly believed to result from an of the infrared biospectroscopic methodology employed in this study autoimmune response, causing inflammation, demyelination, and is that images of tissue sections can be constructed based on axonal damage of the central nervous system (CNS) (Trapp et al., biochemical changes associated with pathological processes at the 1999; Keegan and Noseworthy, 2002; Lassmann, 2004); however, the single cell level (Kretlow et al., 2006). As biochemical changes are exact etiology of the disease remains uncertain, partly due to a lack of likely to precede, or at the least be concomitant with the morpho- sensitivity in current techniques used to detect the onset and logical changes, the spectroscopic-based approach should logically be progression of the disease at early time points (Barnett et al., 2006). more sensitive in detecting the early stages of a disease, although to While conventional histopathological assessment and magnetic date this has not been proven definitively. Furthermore, the ability to resonance imaging have been useful in providing detailed analysis directly and simultaneously probe multiple macromolecular and of lesional activity, the mechanisms underlying lesion formation are protein conformational changes in situ provides an ideal experimental as yet to be defined (Barnett et al., 2006). platform to elucidate the actions of therapeutics. Moreover, the In contrast to the current histological methods, FT-IR microspec- combination of FT-IR microspectroscopy with bioinformatics enables troscopic imaging and mapping have the ability to detect, simulta- objective pathological detection, which can be potentially automated, neously, discrete changes in molecular structure and composition of providing the means for screening sections from CNS tissues before normal and diseased tissues (Kneipp et al., 2002; Fernandez et al., the onset of clinical signs to detect very early pathological changes. 2005; Diem et al., 2008). Notably, direct biochemical analysis of all Experimental autoimmune encephalomyelitis (EAE) is an animal macromolecular components within tissue samples can be obtained model widely used to investigate the cellular and molecular mechanisms involved in the etiopathology of MS as well as to test ⁎ Corresponding author. Fax: +613 99 05 06 80. novel therapies for MS (Bernard et al., 1997; Liu et al., 1998; Karnezis E-mail address: Claude.Bernard@med.monash.edu.au (C.C.A. Bernard). et al., 2004) and is therefore eminently suited for FT-IR spectroscopic 1 These authors contributed equally to this work. analysis so as to determine the biochemical and protein 1053-8119/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2009.09.053 Please cite this article as: Heraud, P., et al., Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging, NeuroImage (2009), doi:10.1016/j.neuroimage.2009.09.053
  2. 2. ARTICLE IN PRESS 2 P. Heraud et al. / NeuroImage xxx (2009) xxx–xxx conformational changes in the CNS during the course and prevention Immunofluorescence of the disease. Accordingly, chemical images based on the absorbance intensity for major macromolecular classes and imaging based on Immunofluorescence was subsequently performed on the same artificial neural network (ANN) models were obtained from unstained tissue sections used for FT-IR spectroscopy. Heat-induced epitope dewaxed paraffin sections of CNS tissue using the FT-IR approach. The retrieval was performed by the standard microwave oven-heated same sections were later stained by immunofluorescence for direct method using 10 mmol/L citrate buffer (pH 6.0) for 10 minutes and comparison. We report that when applied to EAE, this infrared-based allowed to cool to room temperature. Tissue sections were rinsed in biophotonics approach differentiates, in a reproducible and objective Tris-buffered saline (TBS) and subsequent washing steps were fashion, early pathology from normal complex tissue structures, performed using TBS–0.05% Tween-20. Tissue sections were incubat- without the use of stains or immunohistological markers. Further- ed with 10% normal goat serum plus 1% bovine serum albumin in TBS more, subtle changes in the conformation of myelin protein secondary for 30 minutes at room temperature followed by an overnight structure were detected in animals vaccinated against EAE. incubation with a polyclonal anti-myelin basic protein (MBP) antibody (Menon et al., 1997) at 1:200 dilution and rat anti-mouse Materials and methods CD45 (Millipore, Australia) at 4°C. This latter antibody was chosen, as there was a paucity of commercially available CD-4 and CD- Induction and clinical assessment of EAE 8 antibodies for formalin-fixed, paraffin-embedded mouse tissue. These were sought as they could more definitively identify lympho- EAE was induced in C57BL/6 mice by immunization with 200 μg of cytes associated with EAE lesion formation; however, none of these the encephalitogenic myelin oligodendrocyte glycoprotein peptide reagents proved to be functional with our tissue sections. Sections 35–55 (MOG 35–55 , MEVGWYRSPFSRVVHLYRNGK) in complete were subsequently incubated with the appropriate secondary anti- Freund's adjuvant supplemented with 4 mg/mL Mycobacterium bodies, goat anti-rabbit and Alexa Fluor 488 conjugate, and goat anti- tuberculosis H37Ra. Pertussis toxin (350 ng; Sigma) was injected on rat and Alexa Fluor 647 conjugate (1:1000 dilution; Molecular Probes) the day of immunization and again 2 days later (Liu et al., 1998; respectively. 4′,6-Diamidino-2-phenylidole dilactate (DAPI; Molecu- Karnezis et al., 2004). All studies were carried out in accordance with lar Probes) was added to sections to stain nuclei and finally tissue the institutional animal ethics guidelines. Animals were monitored sections were mounted with fluorescence mounting medium (Dako). daily and neurological impairment was scored on an arbitrary clinical Isotype-matched immunoglobulin (rabbit IgG and rat IgG; Zymed) score 0–5 (Bernard et al., 1997; Liu et al., 1998; Karnezis et al., 2004). were used as controls. Vaccination with Nogo-A derived peptide Confocal image acquisition Mice were vaccinated with 200 μg of Nogo623–640 (SYDSIKLE- Sections were analyzed with an Olympus Fluoview 1000 confocal PENPPPYEEA; Auspep, Melbourne, Australia) (Karnezis et al., 2004) microscope (Olympus, GmbH, Germany) and FV10-ASW software emulsified with IFA (Difco laboratories, Michigan, USA) and injected (version 1.7.1.0; Olympus) with images taken using UPLAPO ×10 NA: subcutaneously into the upper flanks (100 μL divided equally) of mice 0.40, UPLAPO ×40 OI NA: 1.00, and PLAPO ×60 O2PH NA: 1.40 4 weeks before the encephalitogenic challenge with MOG35–55 objective lenses. Images were acquired in the XY scan mode between peptide. This was followed by three more injections at weekly 20 and 40 μs/pixel sequentially using Kalman line integration. intervals with 100 μg, 50 μg, and 50 μg of Nogo623–640, respectively. Image processing Cuprizone-induced demyelination Brightness and contrast were adjusted in a linear manner using Chemical demyelination was induced by feeding female C57BL/6 AnalySIS LS professional software (Olympus Soft Imaging Solutions, mice with cuprizone [bis (cyclohexanone)-oxaldihydrazone], mixed GmbH, Germany) as well as to combine single fluorescence to with finely ground food pellets (0.25% wt./wt.). After 6 weeks, normal produce pseudo-colored merged images. Shadow correction was food was restored for an additional 6 weeks (Blakemore, 1972). employed on images taken using the PLAPO ×60 O2PH NA: 1.40 objective lens with the 405 laser. Images were then compiled in Histopathology Adobe Photoshop 9.0 (Adobe Systems Incorporated, USA). Cerebellum and spinal cord were chosen because these CNS Infrared microspectroscopic imaging regions are predilection sites for EAE lesions (Bernard et al., 1997; Liu et al., 1998; Karnezis et al., 2004). CNS samples were analyzed either Spectral data were acquired using an FT-IR spectrometer (Model at day 7 postinjection (dpi) before the onset of any clinical signs of FTS 7000; Varian Inc., Palo Alto, CA, USA) coupled to an infrared EAE (clinical score 0), at the onset (14 dpi: clinical score 1), peak microscope described elsewhere (Heraud et al., 2006a). Spectra were (19 dpi: clinical score 4), and finally at the chronic-progressive phase acquired in reflectance mode, aggregating signals from each set of 4 of the disease (30 dpi: clinical score 3) (Bernard et al., 1997; Liu et al., adjacent pixels on the focal plane array (FPA), and combining 4 1998; Karnezis et al., 2004). Histological evaluation was performed on adjacent FPA image acquisitions covering an area of tissue measuring formalin-fixed, paraffin-embedded sections of brain, cerebellum and 704 μm × 704 μm. Relative concentration images were derived from spinal cord. Sections (4 μm thickness) were placed on MirrIR low-e data from the 4 FPA image acquisitions, which were spatially aligned infrared reflective slides (Tienta Technologies, Ohio, USA) for FT-IR and combined using Resolutions Pro software (Varian). Spectral analysis. Paraffin was removed from the tissue sections prior to FT-IR resolution was 8 cm− 1 with 128 interferograms co-added and using analysis with three washes in clean xylene for five minutes. The next Happ–Genzel apodization. three adjacent sections were stained with haematoxylin and eosin (H&E), luxol fast blue (LFB), and Bielshowsky silver impregnation to Infrared synchrotron mapping assess inflammation, demyelination, and axonal pathology, respec- tively, and to guide the spatial location FT-IR microspectroscopic High spatial resolution infrared spectral maps were collected using examinations (Bernard et al., 1997; Liu et al., 1998). About 20–30 beamline 2BM1 at the Australian Synchrotron with a Bruker Vertex sections per mouse were examined for each stain. V80 vacuum FT-IR spectrometer and Hyperion 2000 IR microscope Please cite this article as: Heraud, P., et al., Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging, NeuroImage (2009), doi:10.1016/j.neuroimage.2009.09.053
  3. 3. ARTICLE IN PRESS P. Heraud et al. / NeuroImage xxx (2009) xxx–xxx 3 (Bruker Optik GmbH, Ettlingen, Germany), using IR radiation emitted (integrated area of the P–O–C stretching band from the sugar from a bending magnet of the synchrotron storage ring (Creagh et al., backbone of nucleic acids from 950 to 980 cm− 1) relative concentra- 2005). The sample was mapped through the focused beam using a X– tion. Images and maps were contrasted using the “Jet” color scheme Y step size of 5 μm with a 5 μm aperture in the microscope focal plane available in CytoSpec, with red indicating the highest relative with a spectral resolution of 8 cm− 1 with 128 interferograms co- concentration, and blue, the lowest. added. All acquisition and control functions of the microscope were performed though Bruker Opus version 6.5. Principal component analysis Spectral preprocessing and imaging analysis Principal component analysis (PCA) was performed using Un- scrambler 9.5 software (Camo Inc., Oslo, Norway). Spectra were first FPA data were processed and images were constructed using preprocessed as described above. PCA was employed as described CytoSpec 1.3 (CytoSpec Inc., New York, USA) software. A quality test previously (Heraud et al., 2006b). rejecting spectra with too low or high absorbance (maximum abs b0.1 or abs N1.0) was first applied to the data, then second derivative Artificial neural network (ANN) spectra were obtained using a Savitzky–Golay smoothing function (9 points) to minimize baseline differences and vector normalized FPA spectra were trained using Synthon NeuroDeveloper 2.3 (Heraud et al., 2006b) to account for differences in sample thickness. (Synthon Analytics GmbH, Heidelberg, Germany) software. A total of FPA images were constructed showing either lipid (integrated area of 4576 spectra were extracted from 6 control and 6 EAE mice, 944 the ester carbonyl region, from 1750 to 1725 cm− 1) or nucleic acid molecular spectra from 6 control and 6 EAE mice, 821 white matter Fig. 1. Histopathology and infrared spectroscopic imaging of the cerebellum during the development of EAE. Representative assessment of the normal and diseased architecture of the cerebellum. W, white matter; G, granular layer; M, molecular layer. Arrows indicate areas containing inflammatory lesions. (A) Immunofluorescence staining performed on the same tissue section as the infrared analysis showing myelin organization and cellular infiltrate following staining with an anti-MBP antibody (green) and DAPI (blue). (B and C) Infrared chemical imaging was performed on the unstained tissue section before immunofluorescence staining to determine the relative concentration of (B) lipid and (C) nucleic acids. Concentrations were determined by the area under the curve for the lipid ester carbonyl band centered at 1735 cm− 1 and nucleic acid absorbance band centered at 965 cm− 1 in normalized second derivative infrared spectra. (D) Lipid (1735 cm− 1) region of the infrared spectrum showing concentration differences between normal cerebellum tissue structure and EAE lesions. (E) as for (D) but for bands associated with nucleic acid (1235 cm− 1 asymmetric PO− stretch, 1080 cm− 1 symmetric PO− stretch, and 965 cm− 1 P–O–C 2 2 stretch). Scale bar = 100 μm. Please cite this article as: Heraud, P., et al., Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging, NeuroImage (2009), doi:10.1016/j.neuroimage.2009.09.053
  4. 4. ARTICLE IN PRESS 4 P. Heraud et al. / NeuroImage xxx (2009) xxx–xxx spectra from 6 control and 6 EAE mice, 1951 granular layer spectra regions classified by the ANN were compared using Metamorph from 6 control and 8 EAE mice, and 860 lesion spectra from 5 EAE mice 7.1.3 (Molecular Devices, CA, USA) allowing sensitivity and specificity were used in the ANN modelling. FPA cerebellum images were to be calculated. acquired throughout the progression of the disease. Spectra were Some regions of the tissue map, such as the boundaries between preprocessed as described above, with 30% of the spectra for each different tissues or where tissue density was low such as the centre of class of tissue or pathology randomly selected for internal validation blood vessels, corresponded to spectra that showed aberrant spectral of the ANN. Three binary ANNs were trained using the Resilient back profiles consistent with the “dispersion artefact,” supporting the view propagation (Rprog) learning algorithm in NeuroDeveloper and later that this effect is most prevalent on reflective substrates where the joined to produce a modular ANN (Udelhoven et al., 2003; Lasch et al., sample density is lower (Romeo and Diem, 2005). Accordingly, we 2006). The optimal ANN architecture was achieved by minimization avoided these regions when selecting spectra for the ANN training of training and validation set errors. The ability of the modular ANN to sets. Spectra were selected in a random fashion from central areas of classify different tissue types or pathology using FPA spectral data was tissue avoiding tissue boundaries or areas where tissue density was tested against a pathologist who drew boundaries between different low. Approximately 300 spectra, acquired from the synchrotron tissues and regions of pathology using Adobe Photoshop 9.0 (Adobe mapping were extracted for each tissue structure and pathology in the Systems Incorporated, USA) on images taken from immunofluores- cerebellum, from 2 EAE mice sacrificed at the peak stage (19 dpi) of cence-stained sections of cerebellum and spinal cord. The total areas the disease. No manual removal of spectra via visual examination was and the overlapping areas for each tissue type and pathology region performed. Spectra were preprocessed using second derivative with 5 identified by pathologist in comparison with the corresponding points smoothing, vector normalized from 900 to 1800 cm− 1, and the Fig. 2. Histopathology and infrared spectroscopic imaging of the spinal cord during the development of EAE. Representative assessment of the normal and diseased architecture of the spinal cord. W, white matter; G, gray matter; arrows indicate areas containing inflammatory lesions. (A) Immunofluorescence staining performed on the same tissue section as the infrared analysis showing myelin organization and cellular infiltrate following staining with an anti-MBP antibody (green) and DAPI (blue). (B and C) Infrared chemical imaging was performed on the unstained tissue section before immunofluorescence staining, to determine the relative concentration of (B) lipid and (C) nucleic acids. Concentrations were determined by the area under the curve for the lipid ester carbonyl band centered at 1735 cm− 1 and nucleic acid absorbance band centered at 965 cm− 1 in normalized second derivative infrared spectra. (D) Lipid (1735 cm− 1) region of the infrared spectrum showing concentration differences between normal spinal cord tissue structure and EAE lesions. (E) Same as for (D) but showing bands associated with nucleic acids (1235 cm− 1 asymmetric PO− stretch, 1080 cm− 1 symmetric PO− stretch, and 965 cm− 1 P–O–C stretch). Scale 2 2 bar = 100 μm. Please cite this article as: Heraud, P., et al., Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging, NeuroImage (2009), doi:10.1016/j.neuroimage.2009.09.053
  5. 5. ARTICLE IN PRESS P. Heraud et al. / NeuroImage xxx (2009) xxx–xxx 5 best 20 points were selected using COVAR. Training of ANNs was with the fact that the white matter contains predominantly performed as above. myelinated axons, with myelin composed of 70% lipid by weight (Figs. 1B and 2B) (Norton and Poduslo, 1973). These regions showed Statistical analysis low nucleic acid concentration, corresponding to a paucity of cell bodies (Figs. 1C and 2C). Conversely, the surrounding granular layers Nonparametric Kolmogorov–Smirnov was used (Elandt-Johnson in the cerebellum had low lipid and high nucleic acid concentration, and Johnson, 1999) to assess significant differences in concentration because of the presence of cell bodies, containing high amounts of of lipid and nucleic acid in the different structures of the cerebellum. protein and nucleic acids. In agreement with its mixed composition of ANOVA was used to assess the significant differences in the axons, dendrites, and cell bodies, the molecular layer of the cerebellum proportion of α-helix to β-pleated sheet structure, where a P value had intermediate characteristics in terms of lipid and nucleic acid b0.05 was considered to be significant. concentration. The differences in both lipid and nucleic acid concen- tration observed in the normal-appearing white matter and EAE Results lesions were statistically significant ( P b 0.01; 50 lesion spectra from 3 mice; 50 white matter spectra from 10 mice; Supplementary Fig. S6). FT-IR imaging delineates inflammatory lesions from normal surrounding The presence of the ester carbonyl band in dewaxed paraffin tissue sections differed to previous studies with other tissue types (Faoláin et al., 2005). The persistence of endogenous lipids in the white matter Cerebellum and spinal cords of mice immunized with MOG35–55 layer, following paraffin-embedding histological tissue-processing peptide (Bernard et al., 1997; Liu et al., 1998; Karnezis et al., 2004) methods, was observed in all tissue sections from the mouse were analyzed either at day 7 postinjection (dpi) before the onset of cerebellum we analyzed. It is likely that the endogenous lipid detected any clinical signs of EAE (clinical score 0), at the onset (14 dpi: clinical is attributable to the covalently bound lipid in proteolipid protein score 1), peak (19 dpi: clinical score 4) and finally at the chronic- (PLP) major myelin protein found in the CNS (Greer and Lees, 2002), progressive phase of the disease (30 dpi: clinical score 3). Normal which is evidently conserved in the tissue after cross-linking of PLP by mice or mice injected with adjuvants alone were used as controls. formalin fixation. Indeed, this information further corroborates the Inflammatory and demyelinating EAE lesions, visualized at each stage view that loss of ester carbonyl absorbance observed in IR spectra EAE of the disease by immunofluorescence microscopy using an anti-MBP lesions represents the results of autoimmune destruction of myelin. antibody (Figs. 1A and 2A, also see Supplementary Figs. S1–S5), correlated with regions where the FT-IR images revealed high nucleic Unique spectral phenotypes allow unbiased automated tissue and acid and low lipid concentration (attributed to all proliferating pathology classification nucleated cells such as T cells, astrocytes, macrophages, microglia, combined with a loss of lipid-rich myelin, respectively), as compared Using the entire IR spectrum, “spectral phenotypes” of a particular to surrounding areas of normal-appearing white matter (Figs. 1B and tissue structure or of pathology were generated enabling us to C and 2B and C). FT-IR imaging of the cerebellum was capable of develop an automated and unbiased method to specifically detect contrasting the molecular and the granular layers, the white matter, pathology in independent samples. Using principal component as well as perivascular infiltration of inflammatory cells (Figs. 1B and analysis (PCA) (Heraud et al., 2006b), which allows spectral C, black arrows). Similarly, white matter, gray matter, and EAE lesions similarities and differences to be more readily identified and were clearly imaged in the spinal cord (Fig. 2). The contrast in the explained, we demonstrate that infrared spectra extracted from the images (Figs. 1B and C and 2B and C) is provided by the relative different structures of the cerebellum are distinct from each other and absorbance of the lipid ester carbonyl band (νC = O at 1735 cm− 1; can also be differentiated from lesion spectra. Distinct clustering of Figs. 1D and 2D) and the nucleic acid ribose sugar backbone vibration spectra from different structures is observed in the PCA scores plot (νP–O–C at 965 cm− 1; Figs. 1E and 2E), which relates directly to the along principal component 1 (PC1; x-axis; explaining 82% total relative concentration of the respective analytes (Fernandez et al., variance), except for white matter (Fig. 3A, red circle), which was 2005; see Table 1 for band assignments). White matter regions in both separated along principal component 2 (PC2; y-axis; explaining 9% the cerebellum and the spinal cord showed high lipid concentration total variance). Spectra were extracted from a number of animals compared with the surrounding tissue layers, a finding consistent throughout the progression of the disease; white matter n = 5 for Table 1 Infrared absorbance bands and assigned functional groups in the IR spectra of CNS tissue. Wave number Assignment Comments values (cm− 1) ∼ 1735 v(C = O) of ester functional groups primarily from lipids and fatty acids (Amharref et al., 2006; Krafft et al., 2007; Diem et al., 2008). ∼ 1700–1600 Mainly v(C = O) associated with proteins (Diem et al., 2008). Referred to as the Amide I band, also contributed by N–H bending. Specifically sensitive to protein secondary structure ∼ 1690 Amide I—anti-parallel β-sheet secondary structure (Surewicz et al., 1987; Stuart, 1996). ∼ 1650 Amide I—α-helix protein secondary structure (Surewicz et al., 1987; Ruiz-Sanz et al., 1992; Stuart, 1996). ∼ 1635 Amide I—β-sheet protein secondary structure (Surewicz et al., 1987; Ruiz-Sanz et al., 1992; Stuart, 1996). ∼ 1560 Mainly v(C–N) associated with proteins (Diem et al., 2008). Referred to as the Amide II band, also contributed by in-plane N–H bending. ∼ 1235 vasPO−, associated with the phosphodiester backbone of nucleic acids (DNA and RNA) 2 As well as bands associated with the collagen triple helix (Zhizhina and Oleinik, 1972; Boydston-White et al., 1999; Diem et al., 2008). occur in this region − ∼ 1080 vsPO2 , associated with the backbone of nucleic acids (DNA and RNA) (Zhizhina and Oleinik, 1972; Boydston-White et al., 1999; Diem et al., 2008). ∼ 965 v(P–O–C) associated with the backbone of nucleic acids (DNA and RNA) (Zhizhina and Oleinik, 1972; Boydston-White et al., 1999). v, stretching vibration; vas, asymmetric stretch; vs, symmetric stretch. Please cite this article as: Heraud, P., et al., Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging, NeuroImage (2009), doi:10.1016/j.neuroimage.2009.09.053
  6. 6. ARTICLE IN PRESS 6 P. Heraud et al. / NeuroImage xxx (2009) xxx–xxx Fig. 3. The unique chemical composition of the cerebellum allows an unbiased and automated pathology classification. (A) Principal component analysis (PCA) scores plot showing the unique chemical composition of the different tissue structures of the cerebellum of EAE mice visualized as distinct clusters along PC1 versus PC2 (white matter n = 5 for both control and EAE mice; molecular layer n = 6 for both control and EAE mice; granular layer n = 6 controls and n = 5 for EAE mice; lesion n = 3 for EAE mice; PC1 and PC2 explain 82% and 9% of the total variance, respectively). (B) Loadings plot showing spectral regions associated with chemical functional groups responsible for the clustering seen in the scores plot. (C) Immunofluorescence stained section from an independent mouse at peak of disease showing myelin organization and cellular infiltrate following staining with an anti-MBP antibody (green) and DAPI (blue). (D) Immunofluorescence with white lines defining the tissue boundaries determined by a pathologist. (E) ANN map assigning each spectrum composing the image to one of the four tissue structures (positions of unclassified spectra are in black). Scale bar = 100 μm. (F) The table shows the sensitivity and specificity achieved with tissue classification from an independent mouse at the peak of disease. Sensitivity and specificity were determined using pathological diagnosis as the “gold standard.” both control and EAE mice; molecular layer n = 6 for both control and (Figs. 3C and D). Using the pathologist tissue identification (Fig. 3D, EAE mice; granular layer n = 6 controls and n = 5 for EAE mice; lesion white lines) as the “gold standard,” the ANN classification was found n = 3 for EAE mice. The PC1 loadings plot (Fig. 3B) shows that lipid to be highly specific with above 95% of all spectra specific to the tissue and nucleic acid bands, employed to differentiate the different tissue types identified by the neuropathologist in independent mice (Fig. structures in the chemical imaging shown in Fig. 1, are important 3F). The sensitivity of the ANN was also high for molecular and discriminators in this clustering, as well as other bands associated granular layers (88% and 80%; blue circle and green triangle, with proteins (PC1 loadings at 1658 and 1546 cm− 1; Fig. 3B). respectively), but slightly less for the lesion and white matter tissues Importantly, differences in α-helix and β-pleated sheet protein (72% and 77%; gray triangle and red circle, respectively; Fig. 3F). It secondary structure (loadings at 1646 and 1623 cm− 1, respectively), must be emphasized that sensitivity and specificity are used here not as revealed by the PC2 loadings plots, explain the spectroscopic in terms of the identification of the microlesions, per se, but are used differences observed between white matter and the other tissue to evaluate the accuracy of whether individual pixel elements are structures and are attributed to myelin proteins (Polverini et al., 1999 correctly assigned to a particular tissue structures or pathology. The Greer and Lees, 2002) as shown by comparison with FT-IR spectra accuracy of the ANN is also dependent on where the tissue boundaries from isolated myelin proteins (Surewicz et al., 1987; Ruiz-Sanz et al., are drawn which is likely to vary between observers. 1992) (Fig. 3B). Our ability to discriminate different structures of the cerebellum Synchrotron FT-IR imaging detects macromolecular changes before onset by PCA prompted us to train ANNs (Udelhoven et al., 2003; Lasch et of EAE al., 2006) to recognize EAE pathology in independent samples. A total of 4576 spectra obtained from 6 control and 8 EAE mice (944 Given the ability to identify cerebellum tissues and pathology molecular layer spectra from 6 control and 6 EAE mice; 821 white based on macromolecular changes with high sensitivity and specific- matter spectra from 6 control and 6 EAE mice; 1951 granular layer ity, the biophotonic approach was used to identify putative changes spectra from 6 control and 8 EAE mice and 860 lesion spectra from 5 that may occur during the early stages in the disease process. EAE mice) were used in the ANN modelling. These were acquired Accordingly, we examined the cerebellum of mice taken 7 days after throughout the progression of the disease (7, 14, 19, and 30 dpi, induction of EAE, before the appearance of clinical signs. Using an FPA respectively), with the aim that a model representative of all stages of microspectrometer, we imaged an area of the white matter, where EAE pathology, could be generated. The final ANN design incorporated some clustering of nucleated cells were visualized following H&E a series of linked ANNs aimed at facilitating tissue classification. As staining of the adjacent section, but where ambiguity existed as to illustrated in Fig. 3E, spectral structures classified by the ANN whether the presence of nucleated cells indeed indicated lesional colocalized with the different tissue structures identified in the activity or was simply part of the structure of underlying granular immunofluorescence-stained section from an independent animal layer (Figs. 4B and E). As shown in Figs. 4A and C, some loss of lipid Please cite this article as: Heraud, P., et al., Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging, NeuroImage (2009), doi:10.1016/j.neuroimage.2009.09.053
  7. 7. ARTICLE IN PRESS P. Heraud et al. / NeuroImage xxx (2009) xxx–xxx 7 Fig. 4. Synchrotron-based chemical mapping detects early EAE pathology. (A) Cerebellum images showing the relative concentration of lipid and (C) nucleic acid derived from FPA spectral data. (B) Contiguous section stained with H&E; red square indicates the area interrogated by infrared FPA imaging; blue square indicates area interrogated using the higher spatial resolution mapping using the synchrotron source. Scale bar = 100 μm. (E) Increased magnification of the areas interrogated with the synchrotron light source with immunofluorescence performed on the same tissue section as the infrared analysis showing myelin organization and cellular infiltrate following staining with an anti-MBP antibody (green) and DAPI (blue). (D) Lipid ester carbonyl concentration map and (F) nucleic acid concentration derived from synchrotron mapping data overlaid onto the immunofluorescence stained section. (G to I) Immunofluorescence stained areas identified in (E) compared with the lipid and nucleic acid concentration maps (D and F) at 50% optical opacity. Corroboration of the pathologically nature of the microlesion provided by ANN classification (G–I). These areas are classified in a similar manner to that seen in the advance stages of EAE; red classifies the cerebellum white matter, green classifies the granular layer, gray classifies the lesion spectra, and black pixels are unclassified spectra. Scale bar = 50 μm. colocalizing with increased nucleic acid concentration were observed correspond with the position of the nucleated cells identified by DAPI in this region. However, due to the limited spatial resolution of the staining using confocal immunofluorescence microscopy on the same FPA technique, no fine-scale information could be obtained. Accord- section used for the synchrotron IR imaging (Figs. 4G–I). Although ingly, synchrotron IR microspectroscopic mapping, which affords staining for myelin basic protein (MBP) did not reveal any qualitative superior spatial resolution (wavelength dependent, diffraction limit- myelin loss in these microlesion areas, the lower lipid concentration ed spacial resolution between 2 and 5 μm as compared to ∼20 μm for in the IR images together with the presence of some perivascular FPA imaging; Heraud et al., 2006a), was used to interrogate these leukocyte infiltrations supported the view that the areas studied regions (Figs. 4D and F). A detailed examination of the selected region contain very early small EAE lesions. Further corroboration for the showed distinctly lower lipid concentration equivalent to advanced pathological nature of the microlesions came from the classification of lesions (cf., Fig. 4D and Fig. 1) in areas approximately 20–30 μm in spectra within these regions as lesion spectra based on an ANN diameter, which colocalized with an increased nucleic acid concen- trained with spectra taken from the advanced stages of EAE (Figs. 4G– tration (Fig. 4F). Notably, the regions with high nucleic acid contents I, ANN). The power of the ANN to discriminate unambiguously were smaller than the region of decreased lipid (Figs. 4D and F) and pathology on a fine spatial scale is shown in Fig. 4H (bottom right Please cite this article as: Heraud, P., et al., Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging, NeuroImage (2009), doi:10.1016/j.neuroimage.2009.09.053
  8. 8. ARTICLE IN PRESS 8 P. Heraud et al. / NeuroImage xxx (2009) xxx–xxx corner). Indeed, the adjacent granular layer (green area) is clearly integrity of the CNS after an autoimmune insult (Karnezis et al., 2004), differentiated from microlesion (gray area) by ANN classification. we next assessed by PCA whether the macromolecular chemistry of the CNS pathology of EAE–Nogo-A mice was different to that of EAE FT-IR imaging reveals protein secondary structure changes in mice. The PCA scores plot shows that the spectra extracted from lesion EAE-protected mice areas from EAE–Nogo-A and EAE mice or unaffected perivascular white matter from controls (adjuvants only) in multiple animals, The ability of the biophotonic FT-IR imaging method to detect early clustered separately along PC1 and PC2 (Fig. 5C; PC1 explained 73% EAE pathology prompted us to use this approach to ascertain the variance and PC2 explained 13%) indicating that each group has a biochemical and structural changes occurring in the CNS of mice in distinctly different biochemical composition. The white matter which EAE was prevented by vaccination with Nogo-A, a major spectra of mice receiving adjuvants only, contain higher concentra- neurite outgrowth inhibitor (Karnezis et al., 2004). Ten out of the 14 tions of lipid (1740 cm− 1, negative loading), lower amounts of Nogo-A vaccinated mice in this study were completely protected from nucleic acids concentration (965 cm− 1, positive loading), and the clinical manifestation of EAE and no obvious lesions could be display differences in their protein secondary structure (1660 and detected in the CNS of these animals (Fig. 5A). The four mice that 1640 cm− 1; Table 1) as compared to EAE and EAE–Nogo-A vaccinated developed EAE (EAE-Nogo-A) had clinical scores ranging from 1 of 3 animals, respectively (Fig. 5D). These findings indicate that the lesions (mean score = 2.25 ± 0.32) and all had inflammatory and demyelin- of both the EAE and EAE–Nogo-A groups are very similar with respect ation lesions (Fig. 5B and Supplementary Fig. S7), as compared to to their nucleic acid and lipid content. those observed in untreated EAE control mice (mean score = 4.0, cf., However, differences between the EAE and EAE–Nogo-A groups in Fig. 5B and Fig. 1). The FT-IR images obtained from these mice terms of protein secondary structure were revealed in the PC2 revealed a similar pattern of loss of lipid and increase in nucleic acid loadings plot (Fig. 5D). Lesion spectra from EAE–Nogo-A mice contain (Fig. 5B) as observed in the lesion areas in cerebellums of untreated higher proportion of α-helix protein secondary structure (1654 cm− 1, EAE mice (Fig. 1). The cerebellums of fully protected mice were PC2 negative loading) while lesion spectra from EAE mice are indistinguishable from noninjected mice or mice receiving adjuvants dominated by anti-parallel β-pleated and β-pleated sheet compo- only (data not shown). Given our previous report that Nogo-A is an nents (1690 cm− 1 and 1635 cm− 1, PC2 positive loading). These important modulator of autoimmune-mediated demyelination and findings are supported by the relative proportions of α-helix and β- that its blockade may help to maintain and/or restore the neural pleated sheet calculated from the band intensities (1654 cm− 1 and Fig. 5. The protein secondary structure in the CNS of EAE–Nogo-A vaccinated mice is different from that of control EAE animals. (A) H&E stained cerebellum with corresponding lipid and nucleic acid relative concentration images from a fully protected Nogo-A vaccinated mouse (clinical score 0). (B) chemical maps constructed as in (A) but for an EAE-Nogo-A vaccinated mouse (clinical score 3). Scale bar = 100 μm. (C) PCA shows that the chemical composition of the 3 groups of animals is different with PC1 versus PC2 scores plot showing distinct clustering of spectra from control white matter (red, representing 137 spectra from 5 mice), normal EAE lesions (blue, representing 72 spectra from 2 mice), and lesions from EAE–Nogo-A vaccinated mice (yellow, representing 132 spectra from 4 mice; PC1 and PC2 explain 73% and 13% of the total variation, respectively). (D) Loadings plot showing spectral regions indicating chemical functional groups responsible for the clustering in scores plot. Loadings show that lesion spectra from both EAE–Nogo-A vaccinated and EAE controls are similar with respect to lipid and nucleic acids but they differ in protein secondary structure, α-helix (1654 cm− 1) and β-pleated sheet (1690 and 1635 cm− 1). Please cite this article as: Heraud, P., et al., Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging, NeuroImage (2009), doi:10.1016/j.neuroimage.2009.09.053
  9. 9. ARTICLE IN PRESS P. Heraud et al. / NeuroImage xxx (2009) xxx–xxx 9 1635 cm− 1, respectively) in EAE–Nogo-A mice compared to EAE respect to their protein secondary structures. Based on the FT-IR untreated mice (Supplementary Fig. S8). The proportion of α-helix spectra of isolated myelin proteins (Surewicz et al., 1987; Ruiz-Sanz et structure is significantly higher in lesion spectra from EAE–Nogo-A al., 1992), we postulate that the lesions present in EAE–Nogo-A mice compared to spectra from untreated EAE mice (n = 3; P b 0.01 by vaccinated mice contain myelin proteins with different protein ANOVA), which appear to contain predominately β-pleated sheet secondary structure conformation. This view is further supported by motifs. The assignment of these bands corresponds to those observed the observation that, in a cuprizone-demyelinating model in mice in the FT-IR spectra of isolated myelin proteins (Surewicz et al., 1987; (Blakemore, 1972), similar spectral changes involving protein Ruiz-Sanz et al., 1992; see Table 1 for band assignments). secondary structure were found to be concomitant with the remyelination process following retrieval of cuprizone (Supplemen- Discussion tary Fig. S9). Moreover, it is unlikely that the differences observed were due to the presence of anti-Nogo-A antibodies at the site of The marked heterogeneity in clinical course and response to lesions in view of the fact that the effect of intravenously injected therapy in MS patients suggest that diverse pathogenic mechanisms antibodies in mice is short-lived (McQualter et al., 2001; Karnezis et are operating (Trapp et al., 1999; Matute and Pérez-Cerdá, 2005; al., 2004) and since no immunoglobulin deposition was found in the Barnett et al., 2006). Detection and elucidation of the early CNS of EAE–Nogo-A treated animals (data not shown). Thus, it would pathological events that precede the development of overt MS appear that the observed differences in protein chemistry within the symptoms are therefore urgently needed as these may have lesion sites of Nogo-A vaccinated mice relate to the differences in fundamental implications for the diagnosis and therapy of this clinical outcomes. Given that the mechanism of suppression observed disease. Two preliminary infrared nonimaging studies performed in here may be mediated by an enhancement of axonal regeneration at the 1990s on dissected chronic MS plaques reported loss of lipid, the site of damage (Karnezis et al., 2004), further investigations are oxidation products, and water depletion when compared to similar currently underway to determine the exact cause of these differences human white matter regions of control brains (Choo et al., 1993; and how they may relate to the pathology of myelin loss and or repair LeVine and Wetzel, 1998). Unfortunately, these early studies provided in this experimental model of MS. limited information due to crude spatial resolution provided by macroscopic measurement (Choo et al., 1993), simple line mapping Conclusions (LeVine and Wetzel, 1998), and absence of nucleic acid measurement or usage of bioinformatic approaches to characterize pathological The biophotonic approach reported here for studying autoim- lesions. Moreover, these studies only provided limited chemical mune-mediated demyelination, illustrates the potential of this changes at an advanced stage of the disease, underscoring the experimental platform to investigate early pathologies occurring in a necessity of full spectral characterization of tissues and pathology in variety of experimentally induced and naturally occurring CNS models of human diseases before application to clinical specimens. By diseases, such as MS. Our ability to differentiate changes in contrast, this study uses well-correlated comparisons between the biochemistry particularly in relation to protein secondary structure infrared mapping and imaging, conventional histology via H&E and demonstrates how the spectroscopic platform described here provides LFB staining, and confocal fluorescence microscopy, with highly additional, complementary tools that can be directly correlated with replicated longitudinal measurements in a well-known and widely existing methods such as immunochemistry in the analysis of MS-like studied animal model of MS. This establishes, we believe, a reliable pathology. The direct probing of biochemical changes in tissues basis whereby an informed study of human MS tissues can proceed without the addition of contrast agents provides a complementary using new infrared laboratory-based techniques and synchrotron approach to existing histological methodologies that is particularly mapping. sensitive to detecting early stages of the disease process. In this study, we show that the integration of FT-IR microspectro- scopic imaging and synchrotron mapping together with bioinfor- Acknowledgments matics is a powerful approach to directly probe the early biochemical changes observed in the CNS following an autoimmune insult. This We thank Professor A. Trounson for his continued support and approach not only was able to identify and characterize the distinct interest in this study and V. Juan, Drs. S. Petratos, and S. Wang for their and heterogeneous cell layer structures of the cerebellum and spinal help with the cuprizone-induced demyelination model. We also thank cord but also was capable of detecting significant chemical differences Drs. C. Siatskas, D. Elliott, and S. Petratos for kindly reviewing the between normal healthy tissue and areas of inflammation and manuscript. This work is supported by grants from the Baker demyelination. The potential of this approach, as an unbiased and Foundation, the National Health and Medical Research Council of automated system for the detection of normal and pathological tissue Australia, the National Multiple Sclerosis Society of New York, and the structures in the EAE model, was demonstrated by the ability of Australian Research Council. Synchrotron beam time was awarded by trained ANNs to detect EAE lesions in the cerebellum with high the Australian Synchrotron under the merit-based proposal scheme. sensitivity and specificity. Moreover, the use of ANNs was crucial for Sally Caine is the recipient of an Australian Postgraduate Award. the detection of the microlesions formed before onset of clinical signs. The ANN approach combined with laboratory-based focal plane array Appendix A. Supplementary data multidetector systems allows the potential for automated detection of the very early pathological changes in tissue sections providing scope Supplementary data associated with this article can be found, in for studies focused on characterization of the early stages in the the online version, at doi:10.1016/j.neuroimage.2009.09.053. development of pathology of disease processes at the biochemical References level. Finally, we ascertain whether the macromolecular chemistry of the Amharref, N., Beljebbar, A., Dukic, S., Venteo, L., Schneider, L., Pluot, M., Vistelle, R., Manfait, M., 2006. 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