Synchrotron-Based Fourier Transform Infrared Microspectroscopy

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Synchrotron-based µFTIR study on the effect of Alzheimer ´s A# amorphous and fibrillar aggregates on PC12 cells Nuria Benseny-Cases, Elena Álvarez-Marimon, Hiram A. CastilloMichel, Marine Cotte, Carlos Falcon, and Josep Cladera Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b04818 • Publication Date (Web): 23 Jan 2018 Downloaded from http://pubs.acs.org on January 25, 2018

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Analytical Chemistry

Synchrotron-based µFTIR study on the effect of Alzheimer’s Aβ amorphous and fibrillar aggregates on PC12 cells Núria Benseny-Cases°*, Elena Álvarez-Marimon∆, Hiram Castillo-Michel□, Marine Cotte□■, Carlos Falcon°, Josep Cladera∆* °ALBA Synchrotron Light Source, Carrer de la Llum 2−26, 08290 Cerdanyola del Vallès, Catalonia, Spain ∆ Unitat de Biofísica, Departament de Bioquímica i de Biologia Molecular, Facultat de Medicina, Universitat Autònoma de Barcelona, 08193 Bellaterra, Catalonia, Spain □ ID21, European Synchrotron Radiation Facility (ESRF), 71 Avenue des Martyrs, 38043 Grenoble, France ■ Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR 8220, Laboratoire d'Archéologie Moléculaire et Structurale (LAMS), 4 place Jussieu, 75005 Paris, France

ABSTRACT: Amyloid plaques made of aggregated Aβ amyloid peptide are a pathological hallmark in brains affected by Alzheimer’s disease. Moreover, the amyloid peptide may play a major role in the onset and development of the disease in association to other factors such as oxidative stress. Although the molecular nature of the amyloid toxic species is still unknown, there is experimental evidence pointing to their non-fibrillar nature. In the present paper we report the use of synchrotron Fourier transform infrared microspectroscopy (µFTIR) for the study of the effect of two different types of Alzheimer’s Aβ(1-40) aggregates (amyloid fibrils and granular non-fibrillar aggregates) on PC12 cultured cells. The Principal Component Analysis (PCA) of the infrared spectra has been complemented with a correlation analysis which permits to study different spectroscopic parameters as a function of peptide aggregation. The results show that the treatment of PC12 cells with amorphous aggregates generates a higher degree of oxidation in the vicinity of the amyloid aggregates than the treatment with pre-formed amyloid fibrils. These results, which permit for the first time the in situ co-localization of amyloid aggregates and oxidized macromolecules in cell culture, are in agreement with previous data from our group showing that oxidation was higher in regions surrounding amyloid plaques in human brain samples affected by Alzheimer’s disease.

Alzheimer disease (AD) is the most prevalent cause of dementia and is described as a multifactorial disease that leads to neuronal cell death. The histological analysis shows deposits of fibrillar proteins: extracellular Aβ amyloid peptide and intracellular tau protein tangles.1-3 Amyloid plaques are made of fibrillar Aβ peptide and are one of the main hallmarks of brains affected by Alzheimer's disease and the amyloid cascade hypothesis is one of the main paradigms in nowadays Alzheimer’s research.4,5 Fibril formation takes place via a nucleation-dependent polymerization process which has been extensively studied in vitro and which implies the formation of different non-fibrillar on-pathway oligomeric intermediates.6-8 Under some physicochemical conditions, such as the presence of metal cations or low pH, off-pathway amorphous aggregates can be formed.9 According to the nowadays prevalent idea, the toxic agents that may be related to the onset and development of the disease must be looked for among these non-fibrillar peptide aggregated species. In this sense, our group has recently described the formation of a type of amorphous aggregates (granular non-fibrillar aggregates, GNAs), which form at pH 5.5 and upon interaction of the peptide with negatively charged (including oxidized) lipid membranes.10 GNAs have been shown to be more toxic than aggregates formed at neutral pH to cultured cell lines.

Similar amorphous aggregates have been reported under different experimental conditions and for different amyloid proteins.11- 14 The mechanism by which amyloid proteins and peptides are toxic is not yet well understood but oxidative stress seems to be closely related to amyloid toxicity. On the one hand, the Aβ peptide has been described as a potential oxidative agent and some of the amino acids have in vitro electrochemical oxidative capacity.15-18 On the other hand, amyloid aggregates have been directly related to oxidative stress in yeast expressing amyloid peptides,19 in APP transgenic mice20 and in in situ infrared imaging studies of human amyloid plaques.21 Moreover, oxidatively modified proteins have been detected in the cerebrospinal fluid in AD patients.22 The elucidation of the molecular mechanisms linking amyloid toxicity and oxidative stress is at present of paramount interest in Alzheimer’s research and in close relation to it, the role that may be played by metal cations such as copper and iron.23 In the present work we aimed to analyze the effect of the Aβ(1-40) amyloid peptide in cell culture depending on the type of amyloid aggregate (fibrillar or amorphous) added to the cell culture, using synchrotron-based µFTIR imaging. For this purpose, we have analyzed PC12 cell cultures when exposed to the amyloid peptide Aβ(1-40) incubated at pH 7.4

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(forming amyloid fibrils) or at pH 5.5 (forming amorphous aggregates, GNAs).10 The technique has largely been shown to be suitable for the detection of amyloid plaques in rodent and human brain samples.24, 25 Moreover, as shown by ourselves and other groups,21, 26, 27 lipid peroxidation can be detected in samples of affected brains and its localization with respect to the amyloid plaques studied. However, in order to properly analyze what frequently is referred to as the lipid region, between 2800 and 3000 cm-1, one has to take into account that peptides and proteins do as well have alkyl and methyl groups that will absorb in the same region. This fact may hamper, especially when addressing the study of amyloid peptide accumulation, the analysis of lipid peroxidation. Principal Component Analysis (PCA) of the data measured in the present study reveals that the treatment of PC12 cells with preformed amorphous aggregates generates a higher degree of oxidation in the vicinity of the amyloid aggregates than the treatment with pre-formed amyloid fibrils. Furthermore, we report a data processing method that permits correctly interpreting the lipid and peptide contributions to the ν(CH2/CH3) region (2800-3000 cm-1), avoiding spurious assignments of the observed intensity changes. EXPERIMENTAL SECTION Preparation of Aβ (1-40) Stock Solutions 500 µM Aβ(1-40) peptide [DAEFRHDSGYEVHHQKLVFFAEDVGSNKGAIIGLMVGGVV] (JPT Germany) with Clas a counter ion was dissolved in 10 mM HEPES buffer with 0.04% NH3 at pH 12 (pH adjusted using NaOH) and sonicated for 30 seconds to ensure that the peptide is in monomeric condition.6,10 Although HEPES has not buffering power at pH 12 it was included in the solution in order to have it there when the pH was later on lowered to 7.4 in order to start the fibril formation process (see next section). The stock solutions were kept at -80°C until used. The infrared spectrum of Aβ(140) showed a maximum centred at 1643 cm-1, typical of unordered structures.6 The spectrum did not show any sign of peptide aggregation around 1620 cm-1. Preparation of the different types of aggregates The pH of the stock solutions was adjusted to pH 7.4 (to trigger amyloid fibril formation) and to pH 5.5 (to trigger amyloid amorphous aggregates formation) using HCl, as described in Benseny-Cases et al. (2012).10 Although HEPES has not buffer capacity at pH 5.5, the buffer was not changed in order to avoid the introduction of a new anion in the solution (they are known to influence the aggregation process). In order to ensure that the incubation was at pH 5.5, the pH was checked throughout the incubation period. Peptide solutions were incubated overnight stirred at 200 rpm and 37°C. After incubation the stock solutions were frozen in N2(l) and stored at -80°C until use. For the analysis of Aβ(1-40) aggregates in vitro in the absence of cells, aliquots of the same stocks and at the same concentration than the one added to cells, were dried directly on CaF2 windows. Cell culture and fixation PC 12 cells were cultured in DMEM media supplemented with 10% fetal bovine serum, 100 units/ml penicillin, 100 µg/ml streptomycin and 2 mM L-glutamine. This cell line’s use in neurobiology is well stablished since the early 1980’s28 and we have previously used it for amyloid cytotoxicity studies.10 Cells were cultured to near confluence on CaF2 windows placed in a 24 wells plate at 2·105 cells/well (seeding

concentration). Duplicates of each condition were prepared. After 24h, Aβ (1-40) pre-incubated at pH 5.5 or pH 7.4 was added to the cells at 25 µM final concentration. The same volume of the corresponding buffer (10 mM HEPES at pH 7.4 or 5.5) was added as a control. After 6h of incubation, cells were fixed as described in Baker et al.29. Briefly cells were washed twice with PBS, fixed with paraformaldehyde 3.7% for 30 min and dipped 3 times in double distilled water. Cells were dried in a desiccator at least 12h before data acquisition. The adequateness of the fixation procedure using PFA and its lack of contribution to the spectra is reported in Mazur et al. 2012.30 Representative optical images of the cell preparations that were measured at the infrared microscope are shown in Fig. S1 (supporting information). It is important to point out that after treatment with the amyloid peptide for six hours the cells retained their original (star-like) shape and no general rounding up due to cell death was observed. Synchrotron-based Fourier Transform Infrared microspectroscopy (µFTIR) and Data Acquisition µFTIR coupled to synchrotron radiation (SR-µFTIR) was carried out at ID21 beamline at ESRF (Grenoble, France). 31 A Thermo Continuum microscope was used equipped with 32× magnification. The microscope was coupled to a Thermo Nicolet Nexus infrared bench equipped with a Michelson interferometer and a KBr beamsplitter (Thermo). SR-µFTIR of the peptides in vitro were performed at the MIRAS beamline at ALBA synchrotron (Catalonia, Spain) using a Hyperion 3000 Microscope equipped with 36x magnification objective coupled to a Vertex 70 spectrometer (Bruker).32 The same measuring conditions were used at both beamlines: the measuring range was 650−4000 cm-1 and the spectra collection was carried out in transmission mode at 4 cm−1 resolution, 10 µm × 10 µm aperture dimensions and coadded from 128−256 scans. Zero filling was performed with the FFT so that in the final spectra there was one point every 2 cm-1. Background spectra were collected from a clean area of the CaF2 window every 15 minutes. In both microscopes an MCT detector was used and the microscope and spectrometer were continuously purged with Nitrogen gas. FTIR Spectra Analysis Spectra were acquired in two different ways: (a) at least 50 spectra on single cells were acquired for each sample in a given sample region; (b) maps with a dimension of minimum 50 µm × 50 µm with an step size of 6 µm × 6 µm. FTIR spectra of single independent cells, the spectra from the different cell maps and the independent spectra of amyloid aggregates without cells were analyzed using Thermo Omnic 7.1 (Thermo Scientific, Inc.) and Opus 7.5 (Bruker) software. The spectra exhibiting a low signal to noise ratio were eliminated. Resonant Mie Scattering correction was carried out using the software freely provided on line by Peter Gardner’s lab (University of Manchester), 33, 34, 35 implemented in Matlab, involving 10 iterations in the range of 3100-1300 cm-1 using a scattering particle diameter from 2 to 8 µm. The effect of the RMieS correction on the whole set of spectra (a total of 1470 spectra) is illustrated in Fig S2. Furthermore, in order to better illustrate the effect of the Mie scattering correction, four representative spectra (with clearly different scattering spectral features in the region 1800-2000 cm-1) are shown in Fig. S3, together with a comparison between the second derivatives of the uncorrected and the corrected spectra in the protein and lipid regions. For data processing, the


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Analytical Chemistry second derivative of the spectra was calculated using a Savitsky−Golay algorithm with a 9-point filter and a polynomial order of 2, to eliminate the baseline contribution. Derivatives using a 5 point smoothing filter were also calculated and no significant differences were appreciated with respect to the results obtained using the 9 points derivatives (data not shown). Unscrambler® X software (CAMO Software, Oslo, NO) was used to perform PCA in the dataset. PCA analysis was applied on the second derivative of the spectra. Unit vector normalization was applied after secondary derivation for PCA analysis.29,36 Principal Components (PCs) were calculated using the Non-linear Iterative Partial Least Squares (NIPALS) algorithm on mean centred data. NIPALS is faster than SVD when both the number of rows and columns in the data set are large,37 which is our case. Nevertheless, since the software package allows the use of both algorithms, we performed the analysis using SVD as well and no significant differences were observed in the calculated score and loadings graphs with respect to the ones resulting from the NIPALS calculation (data not shown). Since the PCA procedure allows weighting the individual variables relative to each other, a constant value (1.00, equal weight) was assigned to all variables (the different wavenumbers in the 650-4000 cm-1 region), as the recommended value. For PCA analysis all RMieS corrected spectra (single point spectra and the spectra from maps) were used. Ratios were calculated over the following peaks of interest: 1627 cm−1 for Amide I β-sheet structures (noted as A1627), 1665 cm−1 as a wavelength at which both the amyloid peptide and the cells have (in the derivative spectrum) a signal clearly distinct from zero (noted as A1665), 1740 cm−1 for ν(C=O) (carbonyl) (noted as A1740), 2925 cm−1 for CH2 asymmetric stretching vibrations (noted as A2925), and 2960 cm−1 for CH3 asymmetric stretching vibrations, (noted as A2960).38,39 It is important to stress out that, since the peptide alone signal at 1657 cm-1 in the derivative spectra is close to zero (see Fig. 2 in the results section), choosing the 1665 cm-1 wavelength permits to estimate peptide aggregation as the ratio A1627/A1665. Origin 9.1 software was used for the ratios calculation, t-test analysis and graphical representation.

experiments with cells) at pH 7.4 (green dots) and at pH 5.5 (grey dots). Fig 1A depicts the score distribution of the two principal components (PC1 and PC2) and the PC1 loadings are shown in Fig 1B. PC1 (accounting for 74% of the total components) is characterized by a maximum in the loadings graph centered at 1627 cm-1 (Fig. 1b), together with a minimum around 1656 cm-1. The maximum at 1627 cm-1 is in a wavenumber region corresponding to radiation absorbed by the amyloid aggregates (intermolecular β-sheet structure) present in the sample, whereas the minimum at 1656 cm-1 is characteristic of the spectra corresponding to the amide I of cells alone.

RESULTS In order to study the effect of pre-formed Aβ(1-40) amyloid aggregates on cultured PC12 cells we have analyzed, using SR-µFTIR, four different types of specimens: (1) PC12 cells treated with Aβ(1-40) pre-aggregated at pH 7.4 (amyloid fibrils); (2) PC12 cells treated with Aβ(1-40) pre-aggregated at pH 5.5 (amorphous aggregates); (3) control cells treated with buffer at pH either 7.4 or 5.5; (4) peptide alone (no cells) preaggregated at pH either 7.4 or 5.5. PCA analysis of the amide I region and spectral changes in the ν(CH2/CH3) and the ν(C=O) regions Figure 1 shows the results of the PCA using the second derivative of the amide I region corresponding to cell cultures treated with Aβ(1-40) pre-incubated at pH 7.4 (fibrillar aggregates, orange dots) and at pH 5.5 (amorphous aggregates, cyan dots) and the corresponding control buffers (pH 7.4 in red and at pH 5.5 in blue). This set of data is presented together with the data from the infrared spectra of aggregated Aβ(1-40) alone (absence of cells, recorded at the same peptide concentration than the one added into the cell culture in the

Fig 1. Principal component analysis (PCA) using the second derivative of the amide I region corresponding to cell cultures treated with Aβ(1-40) pre-incubated at pH 7.4 (fibrillar aggregates, orange dots) and at pH 5.5 (amorphous aggregates, cyan dots), and the corresponding control buffers (red and blue dots at pH 7.4 and 5.5 respectively). Spectra of aggregated Aβ(140) alone (absence of cells, recorded at the same peptide concentration than the one added into the cell culture in the experiments with cells) at pH 7.4 (green dots) and at pH 5.5 (grey dots) were included in the analysis. A) Score graph of the PCA analysis; B) PC1 loadings.

Since the typical band of intremolecular β-sheet is the dominant band in PC1, PC1 can be used to classify the spectra as a function of amyloid aggregation: points corresponding to spectra from parts of the sample with no peptide aggregates (cells alone) will lie on the positive side of the PC1 axis of the score graph, whereas at the other end, the points with most negative values on the PC1 axis will correspond to the spectra of the aggregates of the peptide alone (absence of cells).



In order to analyze the data according to this strategy, the PC1 axis in Fig. 1A was divided in seven segments with sufficient spectra in each segment for a statistical analysis (C/1, 2, 3, 4, 5, 6 and P).

Fig. 2. Second derivative of the spectra in regions C/1, 2, 3, 4, 5, 6 and P defined in Fig. 1. The red spectrum corresponds to the cells treated with HEPES pH 7.4 (red dots in region C/1 in Fig. 1) and the green spectrum to Aβ(1-40) alone aggregated at pH 7.4 (green dots in region P in Fig. 1). The spectra in between (orange) correspond to the spectra of PC12 cells treated with the amyloid peptides incubated at pH 7.4 (orange dots in regions C/1-6 in Fig. 1). The blue spectrum corresponds to the cells treated with HEPES pH 5.5 (blue dots in region C/1 in Fig. 1) and the grey spectrum to Aβ(1-40) alone aggregated at pH 5.5 (grey dots in region P in Fig. 1). The spectra in between (cyan) correspond to the spectra of PC12 cells treated with the amyloid peptides incubated at pH 5.5 (cyan dots in regions C/1-6 in Fig. 1). Panels A and D correspond to the Amide I region, panels B and E to the CH2-CH3 region and panels C and F to the carbonyl region. The dotted line in 3B corresponds to an expansion (x3) of the gray spectrum (peptide alone) in order to better appreciate the features.

Blue and red dots in Fig 1A corresponding to the control cells treated with buffer at pH 5.5 and buffer at pH 7.4 respectively are all located in segment C/1 (C stands for these control spectra). This is therefore the region containing the spectra with a spectroscopic ‘peptide aggregation degree’ corresponding to cells without any contribution from peptide

aggregates. Region C/1 contains as well some orange and dark cyan points (cells treated with peptide incubated at pH7.4 and 5.5 respectively): these spectra would correspond to regions of the cell cultures treated with the peptide with no (or very small) amounts of the aggregated peptide (number 1 in C/1 stands for these spectra). At the other end, region P contains the spectra with a degree of aggregation corresponding to the aggregated peptide alone (without cells, green and grey dots for pH 7.4 and 5.5 respectively). Between C/1 and P, in regions 2 to 6, there is a spread of points coming from both types of samples treated with the peptide (orange and dark cyan points). With the aim of further analyzing the PCA score distribution of the infrared spectra, the average of the second derivative spectra was calculated for each PC1 segment (C/1 to P). The averages of the non-normalized derivative spectra are shown in Fig. 2 for the experiments with Aβ(1-40) preincubated at pH 7.4 (Fig. 2 A, B, C) and for the experiments with Aβ(1-40) pre-incubated at pH 5.5 (Fig. 2 D, E, F). The corresponding averages of the original spectra are shown in Fig. S4 in the supporting information (SI). It is important to stress out that each derivative average spectra in Fig. 2 has been calculated from the non-normalized version of the spectra in each segment (normalization is only carried out as part of the PCA procedure to get the score distribution and the loadings). Figure 2 clearly shows that there are four spectral parameters that change from segment C/1 to segment 6: (a) a general increase in the intensity of the spectra; (b) a change in the absorbance ratio A1627/A1665 (this peak ratio is a measure of the relative variation in the amount of aggregated peptide; 1665 cm-1 has been chosen as a wavenumber where both the amyloid peptide aggregates and the cells absorb, whereas 1627 cm-1 is characteristic of the peptide aggregates); (c) a change in intensity of the maximum of the band centered at 1740 cm-1 (ν(C=O) carbonyl); (d) a change in the peak ratio A2925/A2960 (a measure of the ν(CH2/CH3) ratio). (a) General increase of the intensity of the spectra The increase in the intensity of the spectra with the PC1 value in the amide I region (1600-1700 cm-1) can be explained by an increasing amount of aggregated peptide for a given number of cells from region C/1 to region 6. In that case, the contribution of the peptide in the ν(CH2/CH3) region should increase mainly at 2960 cm-1, where the peptide absorbs the most in this region (CH3 groups).40 It can be seen in Fig. 2 B and 2E that the y-axis value of the spectrum of the peptide alone at 2925 cm-1 is close to zero. (b) Change in the absorbance ratio A1627/A 1665 For the analysis of the A1627/A1665 (peptide aggregation) ratio change with the PC1 value, we have represented in Fig. 3A,B this ratio as a function of the median PC1 score value of each of the segments defined in Fig. 1A (C/1 to P). The complete set of spectra in each segment was used to calculate each ratio for each spectrum and the corresponding Standard Error of the Mean (SEM) over the set of spectra. According to Fig. 3A,D the higher (that is, the more negative) the PC1 score value, the higher the ratio A1627/A1665 for both the cells treated with peptide incubated at pH 7.4 and the cells treated with peptide at pH 5.5. This, according to what has been said in the previous paragraph can be interpreted as detecting a higher


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amount of aggregated peptide with respect to the amount of cells as we move from region C/1 to 6.

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-PC1 Fig 3. Statistical analysis of the spectral changes corresponding to peptide aggregation, changes in the alkyl/methyl ν(CH2/CH3) ratio and in the lipid carbonyl/CH2 ratio expressed as the ratio of the corresponding absorbance values. The PC1 values represented in the x-axis correspond to the median value of each segment (C/1 to P) defined in Fig. 1 and are represented as positive values (PC1). The ratios were calculated using all spectra in each segment and, for each condition and PC1 range, the average and the Standard Error of the Media (SEM) were calculated. Top panels (A, D): Peptide Aggregation ratio (A1627/1665); middle panels (B, E): Lipid oxidation ratio (carbonyl/CH3+CH2, A1740/2960+2925); bottom panels (C, F): ν(CH2/CH3) ratio (A2925/2960). Left panels (A, B, C) correspond to samples treated with peptide incubated at pH 7.4 and right panels (D, E, F) to samples treated with peptide incubated at pH 5.5. The color code is the same as in Figs. 1 and 2.

(c) Change in intensity of the band centered at 1740 cm-1 (lipid carbonyl) In order to study the change in intensity of the band at 1740 cm-1 as an indicator of lipid oxidation we have referred it to the sum of intensities at 2960 and 2925 cm-1. In the presence of the amyloid peptide the band at 2960 cm-1 will contain a contribution from the peptide itself. How this fact is taken into

account is explained in the ‘correlation analysis’ section below. The representation of A1740/A2925+2960 as a function of the median PC1 score value of each of the segments defined in Fig. 1 (Fig. 3 B, E) shows that the value of this ratio is significantly higher compared to the controls in most of the regions (up to a –PC1 value of 0.4) for the cells treated with peptide incubated at pH 5.5 (Fig. 3E), whereas a decrease of the ratio is observed when the peptide was incubated at pH 7.4 (Fig. 3B). Taken into account that the A1740/A2925+2960 ratio for the peptide alone is low compared to the control (red bar), the observed decrease of this ratio for the cells treated with the peptide incubated at pH 7.4 may reflect just the detection of areas of the sample with an increasing amount of aggregated peptide. The increased A1740/A2925+2960 ratio observed in Fig. 3E, however, can be interpreted as an indication of tissue oxidation due to phospholipid alkyl chain cleavage and subsequent aldehyde group formation. Cell culture oxidation would in this case be due to the treatment of the cells with the pre-formed amorphous aggregates. (d) Change in the ratio A2925/A2960 (a measure of the ν(CH2/CH3) ratio) The contribution of the peptide to the CH2/CH3 infrared region represents a problem to be taken into account when interpreting changes in this region in relation to the lipidic component of the sample. Fig 3 C, F show a clear decrease of the ratio A2925/A2960 assignable to an increase of amount of CH3 with respect to CH2 groups. The decrease in the ratio A2925/A 2960, has been previously described21 as corresponding to a decrease in lipid saturation as a result of C=C formation and can be interpreted as being a consequence of lipid peroxidation. Moreover, Chen et al.41 have shown that protein acetylation implies as well that the ratio A2925/A2960 will decrease. However, in order to interpret the changes observed we must consider the fact that the aggregated peptide absorbs as well in the 2800-3000 cm-1 region, especially at 2960 cm-1. In order to try to distinguish peptide aggregation from the other possible factors, a correlation analysis of the different absorbance ratios is presented in the following section. The same result was achieved for the ratio of the CH2 and CH3 symmetric stretching absorption at 2850 cm-1 and 2870 cm-1 respectively (data not shown). Correlation analysis of the ν(CH ν( ν( 2/CH3) and ν(C=O/ CH2) ratios with the A1627/A1665 ratio As explained above, according to Fig 3 the A1627/A1665 and the A2925/A2960 ratios change (increasing and decreasing respectively) as a function of the PC1 value. This means that a more negative PC1 value corresponds to a higher amount of aggregated amyloid peptide with respect to the cell protein and to a lower number of CH2 groups with respect to the number of CH3 groups. In order to evaluate the contribution of the peptide to the A2925/A2960 ratio both the A1627/A1665 and the A2925/A2960 ratios have been normalized between 0 and 1 and plotted as a correlation graph. The results are shown in Figure 4A,B and it can be appreciated that there is a very good correlation between the change of the two ratios as a function of the aggregation value for the samples treated with peptide incubated at pH 7.4 (Fig. 4A). There is also a quite good correlation for the samples treated with peptide incubated at pH 5.5 (Fig. 4B). This means that the changes observed in the A2925/A2960 ratio for the set of spectra corresponding to cells treated with the peptide (both at pH 7.4 and 5.5) are due to the contribution of the peptide absorption in this infrared region.


Analytical Chemistry There is a quite good correlation as well between the peptide aggregation ratio A1625/A1665 and the A1740/A2960+2925 ratio for the data from cell samples treated with the peptide incubated at pH 7.4 (Fig. 4C). The correlation confirms that the decreased A1740/A2960+2925 ratio value observed in Fig. 3B is due to a predominance of aggregated peptide in the area of the sample from which the spectra come from. There is no correlation however between the A1740/A2960+2925 and A1625/A1665 ratios for the data from cells treated with the peptide incubated at pH 5.5, so the increased value of the A1740/A2960+2925 ratio reported in Fig. 3E can be related to an increase in the number of carbonyl groups formed as a consequence of cell oxidation. 1.2

A A1740/A2960+2925

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R=0.990 R2 =0.978 Slope=1.050±0.056

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0.8 0.4 R=0.942 R2 =0.871 Slope=1.198±0.161

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1.2

A1627/A1665

Fig 4. Correlation analysis of the ν(CH2/CH3) and ν(C=O) ratios with the A1627/A1665 ratio. Left panels: correlation graphs of the aggregation ratio (A1627/1665) and the ν(CH2/CH3) ratio (A2925/2960) for cells treated with peptide incubated at pH 7.4 (A) and at pH 5.5 (B). Right panels: correlation of the aggregation ratio (A1627 /1665) and the oxidation bands (A1740/2960+2925) for cells treated with peptide incubated at pH 7.4 (C) and at pH 5.5 (D). The absorbance ratios used to calculate the correlations are those presented in Fig. 3. The values have been normalized between zero and 1. The 0,0 point corresponds to the ratio from the cell samples treated with buffer (no peptide), whereas the 1,1 point corresponds to the ratio from the aggregated peptide alone (no cells). Error bars correspond to the SEM.

Mapping In order to have an ‘in situ’ representation of the peptide aggregates within the cell culture and the oxidation state of the cells with respect to the aggregates, representative maps of the samples treated with the peptides incubated at pH 7.4 and 5.5 are shown in Fig. 5. The region surrounding the amyloid aggregate is clearly more oxidized (red and yellow pixels corresponding to changes in the A1740/A2960+2925) in the sample treated with peptide incubated at pH 5.5 than in the sample treated with peptide at pH 7.4. The map corresponding to the A2925/A2960 ratio shows that this ratio is lower where the peptide aggregate is detected (in blue in the map). As explained above, this is due to the fact that in the peptide the

amount of CH3 groups is higher than the amount of CH2 groups. DISCUSSION Detection of amyloid plaques in human and rodent brain sections by means of SR-µFTIR imaging has been previously reported.24, 25, 42 Recently, we have shown that the technique can be used as well to relate the presence of amyloid plaques in Alzheimer’s brain samples to the oxidation state of the surrounding tissue.21 In the present work we have extended the use of SR-µFTIR imaging to the analysis of cells in cell culture, treated with different types of aggregates (fibrillar and amorphous) made of Aβ(1-40) amyloid peptide. We have used PCA, a method that until now had not been applied to the analysis of amyloid aggregates, to treat the data acquired by SR-µFTIR. The analysis has been carried out after correcting the spectra for resonant Mie scattering taking advantage of the correction method developed by Prof. Gardner’s laboratory.33,34,35 As a result of the PCA analysis a distribution of the infrared spectra based on the relationship between the value of the principal component 1 (PC1) and the amount of aggregated peptide has been established. We have taken this distribution as a function of the PC1 value to carry out a detailed analysis of the different spectroscopic parameters that may yield physicochemical information of the effect of the amyloid peptides on the cultured cells: (a) the A1627/A1665 ratio as a measure of peptide aggregation; (b) the A1740/A 2960+2925 ratio as a potential measure of cell oxidation and (c) the A2925/A 2960 ratio as a measure of the ν(CH2/CH3) chemical groups ratio. The result of this analysis has been then evaluated by means of a correlation analysis which output shows that the variations observed in the A2925/A2960 ratio are due to the accumulation of the aggregated peptides in the sample, whereas the A1740/A2960+2925 ratio can be used as an indicator of changes in the oxidation state of the tissue. In relation to the contribution of the peptide to the CH2-CH3 region we would like to point out that our observation could be tested experimentally using deuterated Aβ(1-40). The lack of spectroscopic overlapping between the CD2 and CD3 groups of the peptide and the CH2 and CH3 groups of the cell molecules would permit an analysis that would contribute to make more robust the conclusion. Altogether we present a method which implies the use of PCA for the analysis of amyloid aggregation and its effects in cell culture, supplemented with a correlation analysis which permits the evaluation of the contribution of the peptide to other regions of the spectra other than the amide I region. This could be especially relevant in systems to which peptides or proteins are added or in which peptides or proteins accumulate in particular regions. It is worth noting that we have tried to be especially careful in trying to assess the possible influence that the different parameters used for derivation and PCA may have on the performance of the analytical method. On one hand, no significant alterations of the results have been found when changing the derivative smoothing filter from 9 to 5 points. On the other hand, using the alternative to the NIPALS algorithm which the unscramble software offers, the SVD algorithm, equivalent PCA results were obtained.


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Analytical Chemistry A1740/A2925+2960 ratio) than the cells treated with fibrillar amyloid. Lipid oxidation and in general oxidative stress is considered to be a potential relevant factor in Alzheimer’s disease, both for its possible influence in the aggregation of the amyloid peptide and for the possible role that the amyloid may play as an oxidative agent. Also for the deleterious effects that tissue oxidation may have on cell viability.43 Although some controversy exists on whether it may really happen in vivo, the amyloid peptide has the potential to generate tissue oxidation via redox reactions which involve Met35 and the participation of metal cations. There is evidence that elevated lipid peroxidation products and protein carbonyl formation in human AD brain and in transgenic AD mice are present in regions with high plaque density.44 Products containing aldehyde groups, such as HNE (9-hydrononenal) have been widely reported to present elevated levels in biochemical studies of affected tissues. We have recently shown using infrared that the tissue surrounding amyloid plaques in human post-mortem samples is oxidized with respect to the controls.21 Besides, it is nowadays widely accepted that the toxic aggregated amyloid species are others than fibrillar amyloid. Although still uncharacterized, they have to be looked among the nonfibrillar intermediaries of the amyloid polymerization process or among off-path aggregation products. The main purpose of the present study was to assess the effect of what we have called Granullar Non-fibrillar Aggregates (GNAs) in cell culture. We have previously described the in vitro formation of GNAs at pH 5.5 and their cytotoxic capacity. We have discussed their possible physiological significance in Benseny Cases et al. (2014), as for example in hypoxia conditions derived from microbleedings in the brain or local acidic pH at membrane surfaces negatively charged (which we have seen may promote the formation of GNAs).10 In the present paper we show that treatment with GNAs generated by incubating the peptide at pH 5.5 cause an increased level of oxidation in PC12 cultured cells. This represents a step forward in the characterization of GNAs and in the consideration of such amorphous aggregated amyloid species of as potential toxic agents in the onset and development of the pathology.

ASSOCIATED CONTENT Supporting Information

Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org. Fig 5. Representative infrared and visible maps of cell samples treated with amyloid peptides incubated at pH 7.4 (left panels) and at pH 5.5 (right panels). (A, B) Visible images of the PC12 cells on the CaF2 windows. (C, D) Lipid area distribution, (E. F) Amide I area distribution. (G, H) Absorbance ratios corresponding to peptide aggregation (A1627/A1665), (I, J) ν(CH2/CH3) ratio (A2925/A2960) and (K, L) oxidation (A1740/A2960+2925). Black lines are drawn in order to mark the position of the peptide aggregates. Color scale (blue is low intensity, red is high intensity). Scale bar is 10 µm.

The main outcome from the application of this analysis to the data from cells treated with fibrillar and amorphous Aβ(140) amyloid peptide aggregates is that cells treated with the amorphous aggregates are found to have a higher level of tissue oxidation (measured as an increased value of the

AUTHOR INFORMATION Corresponding Author * [email protected] & [email protected]

Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

ACKNOWLEDGMENT SR-µFTIR experiments were performed at ID21 at the European Synchrotron Radiation Facility (ESRF), Grenoble, France and at MIRAS beamline at ALBA Synchrotron, Cerdanyola del Vallès, Catalonia, Spain. We are thankful to ESRF and ALBA staff for



their assistance. This work was funded by ALBA and ESRF synchrotrons.

REFERENCES (1) Bachurin, S. O.; Bovina, E. V.; Ustyugov, A. A. Med. Res. Rev. 2017 37(5):1186-1225. (2) Dos Santos Picanço. L. C.; Ozela, P. F.; de Fátima de Brito Brito M.; Pinheiro, A. A.; Padilha, E. C.; Braga, F. S.; da Paula da Silva, C. H.; Dos Santos C. B.; Rosa J. M.; da Silva Hage-Melim L. I. Curr. Med. Chem. 2016, DOI: 10.2174/0929867323666161213101126. (3) Selkoe, D. J. Physiol. Rev. 2001, 81, 741-766. (4) Dobson, C. M. Protein Pept. Lett. 2006, 13, 219-227. (5) Karran, E.; Mercken, M.; De Strooper, B; Nat. Rev. Drug Discov. 2011, 10, 698-712. (6) Benseny-Cases N.; Cócera M.; Cladera J.; Biochem. Biophys. Res. Commun. 2007, 361, 916-921. (7) Salahuddin, P.; Fatima, M. T.; Abdelhameed, A. S.; Nusrat, S.; Khan, R. H., Eur. J. Med. Chem. 2016, 114, 41-58. (8) Radford, S. E.; Dobson C. M. Cell 1999, 97, 291-298. (9) Hane, F.; Leonenko, Z., Biomolecules 2014, 4, 101-116. (10) Benseny-Cases, N.; Klementieva, O.; Maly, J.: Cladera, J. Curr. Alzheimer Rese. 2012, 9, 962-971. (11) Kremer, J. J.; Pallitto, M. M.; Sklansky, D. J.: Murphy, R. M., Biochemistry 2000, 39, 10309-10318. (12) Ha, C.; Ryu, J.; Park, C.B., Biochemistry 2007, 46, 61186125. (13) Mukai, H.; Isagawa, T.; Goyama, E.; Tanaka, S.; Bence, N. F.; Tamura, A.; Ono Y.; Kopito, R. R., Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 10887-10892. (14) Bucciantini, M.; Giannoni, E.; Chiti, F.; Baroni, F.; Formigli, L.; Zurdo, J.; Taddei N.; Ramponi G.; Dobson C. M.; Stefani, M., Nature 2002, 416, 507-511. (15) Bucciantini, M.; Rigacci, S.; Berti, A.; Pieri, L.; Cecchi C.; Nosi, D.; Formigli, L.; Chiti, F.; Stefani M., FASEB J. 2000, 19, 437-439. (16) Butterfield, D. A.; Sultana, R., J. Amino Acids 2011. ID 198430. (17) Butterfield, D. A.; Boyd‐Kimball, D. Brain Pathology 2004, 14, 426-432. (18) Enache, T. A.; Chiorcea-Paquim, A. M.; Oliveira-Brett, A. M., Anal, Chim. Acta 2016, 926, 36-47. (19) França, M. B.; Lima, K. C.; Eleutherio, E. C. J. Cell. Biochem. 2017, 118, 1442-1452. (20) Xie, H.; Hou, S.; Jiang, J.; Sekutowicz, M.; Kelly, J.; Bacskai, B. J. Proc. Natl. Acad. Sci. 2013, 110, 7904-7909. (21) Benseny-Cases, N.; Klementieva, O.; Cotte, M.; Ferrer, I.; Cladera, J., Anal. Chem. 2014, 86, 12047-12054. (22) Di Domenico, F.; Coccia, R.; Butterfield, D. A.; Perluigi, M. Biochim. Biophys. Acta. 2011, 1814, 1785-1795. (23) Eskici, G.; Axelsen, P. H., Biochemistry. 2012, 51, 62896311. (24) Leskovjan, A. C.; Kretlow, A.; Lanzirotti, A.; Barrea, R.; Vogt, S.; Miller, L. M., Neuroimage. 2011, 55, 32-38. (25) Miller, L. M.; Bourassa, M. W.; Smith, R. J. Biochim. Biophys. Acta. 2013, 1828, 2339-2346.

(26) Vileno, B.; Jeney, S.; Sienkiewicz, A.; Marcoux, P. R.; Miller, L. M.; Forró, L. Biophys. Chem. 2010, 152, 164-169. (27) Petibois, C.; Déléris, G., Analyst. 2004, 129, 912-916. (28) Greene, L. A.; Tischler, A. S.; Celt. Neurobiol. Adv., 1982, 3, 373-414. (29) Baker, M. J.; Trevisan, J.; Bassan, P.; Bhargava, R.; Butler, H. J.; Dorling, K. M.; Fielden, P. R.; Fogarty, S. W.; Fullwood N. J.; Heys, K. A.; Hughes, C.; Lasch, P.; MartinHirsch, P. L.; Obinaju, B.; Sockalingum, G. D.; Sulé-Suso, J.; Strong, R. J.; Walsh, M.J.; Wood, B. R.; Gardner, P.; Martin, F. L.; Nat. Protoc. 2014, 9, 1771-1791. (30) Mazur A.; Marcsisin E. J.; Bird B.; Miljković M.; Diem M.; Anal Chem. 2012, 84, 1259-1266. (31) Cotte, M.; Pouyet, E.; Salome, M.; Rivard, C.; De Nolf, W.; Castillo-Michel, H; Fabris, T; Monico, L.; Janssens, K.; Wang, T.; Sciau, P.; Verger, L.; Cormier, L.; Dargaud, O.; Brun, E.;, Bugnazet, D.; Fayard, B.;. Hesse, B.; Pradas del Real A. E.; Veronesi, G.; Langlois, J.; Balcar, N.; Vandenberghe, Y.; Solé, V. A.; Kieffer, J.; Barrett, R.; Cohen, C.; Cornu, C.; Baker, R.; Gagliardini, E.; Papillon E.; Susini, J. Anal. At. Spectrom. 2017, 32, 477-493. (32) Yousef I.; Ribó L.; Crisol A.; Šics I.; Ellis E.; Ducic T.; Kreuzer M.; Benseny-Cases N.; Quispe M.; Dumas P.; Lefrançois S.; Moreno T.; García G.; Ferrer S.; Nicolas J.; Aranda MAG. Synchrotron Radiat. News. 2017, 30, 4-6. (33) Bassan P.; Kohler A.; Martens H.; Lee J.; Byrne H. J.; Dumas P.; Gazi E.; Brown M.; Clarke N.; Gardner P.; Analyst. 2010, 135, 268-677. (34) Bassan P.; A.; Sachdeva A.; Kohler A.; Hughes C.; Henderson A.; Boyle J.; Shanks J. H.; Brown M.; Clarke N. W.; Gardner P.; Analyst. 2012; 137, 13701377. (35) Bassan P.; Kohler A.; Martens H.; Lee J.; Jackson E.; Lockyer N.; Dumas P.; Brown M.; Clarke N.; Gardner P. J Biophotonics, 2010, 3, 609-620. (36) Sandt C.; Nadaradjane C.; Richards R.; Dumas P.; Sée V.; Analyst. 2016, 141, 870-883. (37) Dayal S.; MacGregor J. F.; J. Chemom., 1997, 11, 73-85. (38) Petibois, C.; Drogat, B.; Bikfalvi, A.; Déléris, G.; Moenner, M. FEBS Lett. 2007, 581, 5469−5474. (39) Chwiej, J.; Dulinska, J.; Janeczko, K.; Dumas, P.; Eichert, D.; Dudala, J.; Setkowicz, Z. J. Chem. Neuroanat. 2010, 40, 140−147. (40) Chen, L.; Holman, H. N.; Hao, Z.; Bechtel, H. A.; Martin M. C.; Wu C.; Chu, S. Anal. Chem. 2012, 84, 4118−4125. (41) Chen, T.; Lee, M. J.; Kim Y. S.; Lee, S.; Kummar, S.; Gutierrez, M.; Hewitt, S. M.; Trepel, J. B.,; Levin, I. W., Anal. Chem. 2008, 80, 6390–6396. (42) Klementieva, O.; Willén, K.; Martinsson, I.; Israelsson, B.; Engdahl, A.; Cladera, J.; Uvdal, P.; Gouras, G. K. Nat Commun. 2017, 8, 14726.-14735. (43) Gaschler, M. M.; Stockwell, B. R., Biochem. Biophys. Res. Commun. 2017, 482, 419-425. (44) Leskovjan, A. C.; Lanzirotti, A.; Miller, L. M., Neuroimage. 2009, 7, 1215-1220.


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