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Multispectral Atomic Force Microscopy-Infrared Nano-Imaging of Malaria Infected Red Blood Cells David Perez-Guaita, Kamila Kochan, Mitchell Batty, Christian Doerig, Jose Garcia-Bustos, Shirley Josefina Espinoza Herrera, Don McNaughton, Philip Heraud, and Bayden R. Wood Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b04318 • Publication Date (Web): 12 Jan 2018 Downloaded from http://pubs.acs.org on February 6, 2018

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Analytical Chemistry

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Hyperspectral Multispectral Atomic Force Microscopy-Infrared Nano-Imaging of Malaria Infected Red Blood Cells

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David Perez-Guaitaa, Kamila Kochana, Mitchell Batty b, Christian Doerigb, Jose Garcia-Bustosb, Shirley Josefina Espinoza Herrera c, Don McNaughtona, Phil Heraud*a,b, Bayden R. Wood*a

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a

Centre for Biospectroscopy, Monash University, Clayton, 3800, Victoria, Australia b Department of Microbiology and Infection & Immunity Program Monash Biomedicine Discovery Institute, Monash University, Clayton, 3800, Victoria, Australia c ELI Beamlines. Institute of Physics. Czech Academy of Science. Na Slovance 2, 18221 Prague, Czech Republic *[email protected], [email protected]

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Abstract

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Atomic Force Microscopy-Infrared (AFM-IR) spectroscopy is a powerful new technique that can be

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applied to study molecular composition of cells and tissues at the nano-scale. One limitation of the

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technology is that the maps generated are univariate in natureAFM-IR maps are generally acquired

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using over one single wavenumber value: they show either the absorbance plotted against a single

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wavenumber value, or a ratio of two absorbance values. Here we implement for the first time

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hyperspectral multivariate image analysis to generate multicomponent multivariate AFM-IR maps,

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and use this approach to resolve subcellular structural information in red blood cells infected with

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Plasmodium falciparum at different stages of development. This was achieved by converting the

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discrete spectral points into a hyperspectral multispectral line spectrum prior to multivariate image

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reconstruction. The approach was used to generate compositional maps of subcellular structures in

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the parasites, including the food vacuole, lipid inclusions and the nucleus, based on the intensity of

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haemozoin, haemoglobin, lipid and DNA IR marker bands, respectively. Confocal Raman

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sSpectroscopy was used to validated the presence of haHemozoin in the regions identified by the

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AFM-IR technique. The high spatial resolution of AFM-IR combined with hyperspectral modelling

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enables the direct detection of subcellular components, without the need for cell sectioning or

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immunological/biochemical staining. HyperspectralMultispectral-AFM-IR thus has the capacity to

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probe the phenotype of the malaria parasite during its intra-erythrocytic development. This enables

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ACS Paragon Plus Environment

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Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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novel approaches to studying the mode of action of antimalarial drugs and the phenotypes of drug-

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resistant parasites, thus contributing to the development of diagnostic and control measures.

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Keywords: AFM-IR, RBC, Plasmodium, nanoimaging, HyperspectralMultispectral analysis.

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INTRODUCTION

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The study of intracellular structures is an important aspect of biology that requires the use of

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techniques with submicron resolution. To date, there are only a fewis not a wide range of available

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techniques that can achieve this level of resolution have been limited tosuch as fluorescence and

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transmission electron microscopy (TEM). The former requires the use of fluorescence stains

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(sometimes coupled to antibodies) and can be used with fixed or more rarely with live cells, while

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the latter can only be applied to cell sections. Other emerging techniques include scanning Near-

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field Optical Microscopy (s-SNOM) (s-SNOM), Atomic Force Microscopy (AFM) or nNanoscale

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Ssecondary Iion Mmass Sspectroscopy (nano-SIMS). Fourier transform Infrared (FTIR)

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hyperspectral imaging has been developed over the recent decades to investigate the composition of

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biological samples

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each IR spectrum (a set of 15-25 discrete wavenumber valuess in the case of multispectral imaging)

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has a corresponding unique “x, y” coordinate, providing spatial and chemical information

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simultaneously. Sophisticated data treatment procedures have been introduced to generate chemical

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maps based on spectral variance, enabling compositional studies of biological tissues3. The main

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advantages of FTIR hyperspectral imaging is that it provides unbiased chemical information,

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including: i) quantitative distribution of biological molecules such as DNA, carbohydrates, proteins,

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lipids and, in the case of Plasmodium falciparum, haemozoin (Hz)5; ii) higher order data such as

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protein secondary structure 6, nucleic acid conformations

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main drawback is that the long wavelength of the IR photons (3-8 µm) results in diffraction-limited

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images with coarse spatial resolution, unsuitable for the study of features smaller than a few

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microns9.

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utilising a ×25 objective with high Numerical Aperture (NA=0.81) and a focal plane array IR

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imaging microscope, we were previously able to image the food vacuole (FV) in a single malaria

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infected red blood cell (RBC) based on the lower concentration of organic matter in the FV but no

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additional detail within the cell was distinguishable.10

1–4

. In an FTIR hyperspectral image captured using a focal plane array detector,

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or the oxidation state of lipids8. The

This makes resolution of all but the largest sub-cellular structures impossible. By

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More recently, IR has been coupled with atomic force microscopy, leading to AFM-FTIR

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microscopes able to acquire IR spectra with submicron resolution11. Scanning near-field optical

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microscopy (s-SNOM) s-SNOM and photo-thermal induced resonance (PTIR) have also been

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coupled to AFM systems12. The latter uses pulses from a tuneable IR laser, with either an Optical

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Parametric Oscillator (OPO) system or a Quantum Cascade Laser (QCL). Laser energy at

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wavenumber values corresponding to absorbance bands in the sample is absorbed and causes rapid

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thermal expansion, much faster than the AFM feedback, exciting resonant oscillations in the AFM

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cantilever13. A spectrum can thus be obtained by measuring the amplitude cantilever oscillation,

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which is proportional to the absorption coefficient of the sample at different wavenumber values.

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This technique has opened the door to nano-analysis of biological samples using mid-IR

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spectroscopy with resolutions below the diffraction limit 14. The high spatial resolution of AFM-IR

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has allowed the technique to be applied to bacteria15–17, as well as to larger size samples such as

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human hair18 and skin19 . Studies on eukaryotic cells have focused so far on mapping nanoparticles

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within cells. For example, AFM-IR has been applied to map the localization of gold nanoparticles

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within adenocarcinoma cells20 and to study nano-diamond-induced alterations in cellular proteins21.

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To date, no AFM-IR studies have investigated malaria parasites. We have previously applied AFM-

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Raman, known as Tip Enhanced Raman Scattering (TERS), to investigate Hz crystals protruding

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from the surface of sectioned red blood cells infected with Plasmodium falciparum trophozoites22.

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For that application the cell had to be embedded in resin, sectioned, and spectra could only be

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recorded from crystals protruding from the sectioned cell, consequently the approach did not reveal

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any additional structural information besides the haemozoin crystal location.

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Previous AFM-IR studies have mainly focussed on using measuring the absorbance at one

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given wavenumber value, or on obtaining the absorbance ratio from two wavenumber values of

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interesta combination of point spectral measurements with single wavelength imaging. Other s-

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SNOM based studies have used multispectral and hyperspectral imaging in other applications such

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as intramolecular dynamics23 and polymer blends and hair compositional studies24. In this study we 4


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apply IR hyperspectral imagingmultivariate imaging applied to cells, which is normally applied to

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spectra spanning the full mid-IR range (4000-800 cm-1) and mainly used when analysing focal plane

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array data from tissue sections3. Figure 1 shows a schematic diagram of our approach to generate

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the images. First, we use the combination of AFM and IR for measuring the IR signal maps at

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different

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hyperspectralmultispectral images (1b). Finally, the image is analysed using multivariate data

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analysis. The results show that the lateral resolution of the technique along with the multivariate

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analytical approach enable chemical identification of a range of sub-cellular Plasmodium sp.

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structures, such as the FV, lipid inclusions and the nucleus, providing information about the

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chemical composition of the parasite at submicron resolution without staining or modification of

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cellular chemistry beyond the initial fixation.

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METHODS

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P. falciparum culturing and staining

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P. falciparum 3D7 parasites were cultured in O+ erythrocytes at 4% haematocrit in RPMI 1640 - HEPES

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medium (Thermo Fisher), supplemented with 0.5% Albumax II (Thermo Fisher), 50mg/L hypoxanthine

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(Sigma), 10mg/L gentamycin (Pfizer) and 25mM sodium bicarbonate (Sigma) as previously described23.

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Cultures were gassed with 1% O2, 5% CO2 and 94% N2. Ring stage parasites were synchronised by

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incubating with 10ml of 5% D-sorbitol (Sigma) for 10 minutes at 37°C and lifecycle stage determined for

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each experiment using Giemsa staining. After AFM-IR and Raman analysis, parasites were stained for

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observation by light microscopy by fixing thin blood smears in 100% methanol for 10 seconds, followed by

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staining with 10% (v/v) Giemsa solution for 5 minutes and imaged using an Olympus BX51 microscope

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coupled with an Olympus DP70 digital camera.P. falciparum 3D7 parasites were cultured in O+ erythrocytes

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at 4% haematocrit in RPMI 1640 - HEPES medium (Thermo Fisher), supplemented with 0.5% Albumax II

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(Thermo Fisher), 50mg/L hypoxanthine (Sigma), 10mg/L gentamycin (Pfizer) and 25mM sodium

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bicarbonate (Sigma) as previously described23. Cultures were gassed with 1% O2, 4% CO2 and 95% N2. After

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AFM-IR and Raman analysis, parasites were stained for observation by light microscopy by fixing thin

wavenumber

values

(1a).

Then

the

maps

are

registered

to

5


generate

the


1

blood smears in 100% methanol for 10 seconds, followed by staining with 10% (v/v) Giemsa solution for 5

2

minutes and imaged using an Olympus BX51 microscope coupled with an Olympus DP70 digital camera.

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Sample Preparation

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1 microliter of packed RBC, which contained 5% parasitemia was deposited in a 10x2 mm2 window

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purchased from Crystan Limted (Dorset, UK). Because we needed to examine the samples using Raman

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spectroscopy after the AFM-IR analysis, only windows with Raman grade purity were used. The blood

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sample was smeared using a standard glass coverslip and the resulting monolayer of RBCs was dried and

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fixed using 100% methanol for 10 seconds. The CaF2 window was then mounted to a steel holder.

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Calibration and optimization of the AFM-IR signal

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In order to daily calibrate the IR signal and compensate the contribution of atmospheric gases, a background

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was acquired averaging 3 spectra obtained in the spectral ranges 3050-2750 and 1800-800 cm-1, using a

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spectral resolution of 4 cm-1 and co-averaging 2048 values per point. Prior to each measurement, the second

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cantilever oscillation mode was used for the optimization of the cantilever frequency, which was normally

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located at 17000 Hz ± 60. Then, for maximizing the IR signal, the tip was placed in contact with an

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uninfected RBC and the IR laser position on the sample was optimised. The signal was monitored as a

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function of the laser position, establishing the optimum position for a representative set of wavenumber

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values across the spectra (e.g. 2914, 1640 and 1208 cm-1). A function that relates the position of the laser to

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the wavenumber value was computed using the measured optimum position of the representative

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wavenumber values. The function was used for interpolating the optimal position of the other wavenumbers.

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Analysis of RBCs infected with P. Falciparum with AFM-IR

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AFM-IR analysis was carried out using a nanoIR2 instrument from Anasys (Santa Barbara, USA) controlled

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by the Analysis Studio software also from Anasys. An OPO laser was used as the IR emission source and

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standard contact mode NIR2 probes provided by Anasys. First, topography images were recorded at 1Hz rate 6


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revealing spatcial features corresponding to the presence of the parasite. Then, the tip was placed in the

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regions of interest and spectra were recorded within the regions 3050-2750 and 1800-800 cm-1 by co-

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averaging 2048 scans at a spectral resolution of 4 cm-1. The laser power was selected by considering a trade-

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off value between a reasonable signal-to-noise ratio and a safe power for not burning the sample. Because

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each spectral region absorbed a variable amount of light, the laser power was tuned to the different spectral

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regions always ranging between 5% and 45%. Wavenumber values with a large variance were selected and a

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sequence of maps using the chosen wavenumber values was recorded. IR maps were created measuring 200

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horizontal lines of 200 points each giving simultaneously 4 × 200 pixel by 200 pixel maps containing the IR

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peak, IR amplitude, deflection and height values at each pixel. Considering the 1000 Hz frequency of the

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OPO laser, the scanning rate was adjusted to 0.07 Hz, which allowed the accumulation of 64 scans for each

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point. The measurement time for each map was approximatelyround 47 minutes. Further information about

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calibration and optimization of the signal is available in the Section B of Supporting Material.

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Analysis of standards with AFM-IR

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Haemozoin was obtained from Invivogen (San Diego, USA). Human haemoglobin (98%) and DNA from

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Calf thymus was obtained from Sigma Aldrich (St Louis, USA). 5 microliters of a suspension of each

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standard in MiliQ water was spread onto a CaF2 window and allowed to dry. Spectra were acquired in the

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same conditions as the RBCs.

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Data Analysis

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Data analysis was performed using Matlab from Mathworks (Natick, USA), using in-house written scripts

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based on functions available in the Imaging processing toolbox from Matlab and in PLS-toolbox from

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eigenvector Eigenvector Researchresearch (Manson, USA). The set of maps were registered to one of the

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maps obtained in the middle of the sequence in order to minimize the effect of the drift. This map was

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considered as the reference map. In short, the drift was calculated comparing the deflection maps

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corresponding to the IR map to register to the deflection map of the reference IR map and then this drift was

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used to co-register the IR map. The Matlab function imregtform, available in at the image processing

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toolbox was employed for the registering the maps. All the registered images were integrated in a 3D matrix. 7


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The hierarchical cluster analysis was performed using a Standard Normal Variate (by dividing each sample

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vector by the standard deviation of the sample) and autoscaling. For figures 3e, 4eh and 5f, the average

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variables of each class where computed after normalizing the signal of each pixel (Sum=1). For each variable,

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the average value of each class was divided by the average value of all the intensity values.

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Raman Spectroscopy

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Raman maps were acquired with the use of Confocal Raman Microscope (WITec alpha300 R, Melbourne,

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Australia). The system is equipped with a dry Olympus MPLAN (10×/0.90NA) objective, an air–cooled

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solid–state laser, 600 grooves/mm grating (BLZ = 500 nm) and a back – illuminated CCD camera, cooled to

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–60°C. The laser was operating at 532 nm and was coupled to the spectrometer by an optical fibre with a

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diameter of 50 µ m. The laser power was adjusted individually to each sample and did not exceed 6 mW. A

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standard single point calibration procedure based on Raman scattering line of silica plate (520.5 cm-1) was

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performed before data collection. Spectra were collected with spectral resolution of from 3 cm-1 to 5 cm-1, in -1

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the range of 0 – 3705 cm . The integration time of single spectrum was 0.05 – 0.1 s and the size of imaged

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areas was 10 × 10 µm (30 × 30 points, sampling density: 0.33 µm). All measurements were controlled by

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Witec Control Software.

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RESULTS AND DISCUSSION

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AFM-IR location of Hz inside RBCs infected with P. falciparum.

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We imaged human RBCs infected with P. falciparum parasites at different stages (rings,

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trophozoites and schizonts) fixed in methanol. These are the blood stages relevant for malaria

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pathology, named for their morphology and listed in the temporal order of development inside red

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blood cells. Immediately after cell invasion the parasite adopts a characteristic ring morphology.

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This is followed hours later by the irregularly shaped trophozoite stage, responsible for

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haemoglobin (Hb) degradation and the deposition of liberated haem groups as crystalline

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haemozoin (Hz). Trophozoites are the most biochemically active stage and they completely remodel

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the red blood cell architecture. Finally, the single-celled parasite undergoes multiple rounds of 8


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nuclear divisions transforming itself into a schizont, which precedes an atypical form of cell

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division yielding 8 to 32 daughter parasites that rupture the cell to reinitiate the cycle. Figure 2a

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shows the topography of a fixed RBC infected with a trophozoite on a CaF2 window, obtained using

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AFM. The centre of the infected RBC presents an irregular topography compared with the

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homogenous cell membrane observed in uninfected RBCs. These irregularities have already been

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characterised by AFM in a previous study2624. A semi-spherical protrusion in the centre of the

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infected red blood cell is shown in Figure 1a and is marked with an arrow. The protrusion measured

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300 nm in height and 650 nm in radius. In order to study the chemical composition of this

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protrusion, 15 spectra in the 1800-800 cm-1 and 3050-2750 cm-1 regions were obtained from inside

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the protrusion and compared with 15 spectra obtained in parts of the cell not showing evidence of

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the parasite along with spectra of uninfected RBCs adjacent to the infected cell (see points marked

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blue and red in the deflection AFM image shown in Figure 2b). Figures 2c and 2d show AFM-IR

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spectra acquired at different cellular locations along with AFM-IR spectra obtained from crystals of

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Haemoglobin (Hb), Hz and DNA standards. The different band assignments used in this study are

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summarized in Table 1. Clear spectral differences are apparent, with bands at 1708 cm-1 and 1207

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cm-1 present in the protrusion (blue class) but not in the non-infected cellular locations (red class).

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These bands are prominent also in the Hz reference spectrum and have been assigned as IR markers

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of Hz, a by-product of Hb digestion by the parasite27–2925–27. The 1207 cm-1 band is assigned to the

19

C-O stretching mode of the propionate side chain of Hz, whilst the 1708 cm-1 band is assigned to a

20

carbonyl group2826. Hence the protrusion appears to be mainly Hz deposited inside the FV of the

Field Code Changed

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parasite3028. The band at 1540 cm-1 has higher absorbance in the uninfected cell spectra and is also

Field Code Changed

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prominent in the Hb standard. It is assigned to the amide II mode, indicating a higher concentration

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of Hb outside the protrusion. An image of the absorbance in the 1207 cm-1 band (See Figure 2e)

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indicates that Hz is present only in the protrusion. This is in contrast to the absorbance intensity

25

map at 1660 cm-1 (Figure 2f), which has contributions from both the carboxylate stretch of Hz and

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the Amide I mode of the protein peptide group of Hb. The image in Figure 2f shows that uninfected 9


Field Code Changed

Field Code Changed


1

cells have a homogenous distribution of protein based on the absorbance of the amide II mode. It

2

has to be noted that the intensity of the Amide II band is abnormally low compared with the

3

intensity of the Amide I band

4

observation was consistent in all the spectra acquired during the study and may be caused by

5

changes in the focus of the laser during the optimization process.

(see Figure 2d) in both, the spectra of RBCs and Hb. This

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Principal Component Analysis (PCA) was performed on the CH stretching (3050-2800 cm-1)

7

region to investigate lipid contributions, which have been previously shown to be associated with

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Hz formation3129. Scores and loadings of the first PC explaining 47.34% of the variance are

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depicted in Figure 2g and 2h, respectively. The box plot (Figure 2g) indicates that the score values

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from spectra obtained inside the FV were significantly higher than the ones obtained from regions

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in the uninfected RBCs. Loading values describe the relationship between the PC and the IR

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wavenumber variables (Figure 2h). Loading values show positive bands at 2854 cm-1 and 2914 cm-1,

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which are assigned to νsCH2 and νasCH2 stretching vibrational modes. The negative bands at 2870

14

cm-1 and 2958 cm-1 are assigned to νsCH3 and νasCH3 stretching vibrational modes. This indicates

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that the ratio CH2 to CH3 is higher inside the FV, which can be interpreted as a higher concentration

16

of aliphatic chains around Hz, presumably reflecting a lipid-rich FV environment when compared to

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the uninfected RBCs and the cytoplasm surrounding the parasite in infected cells.

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The spatial resolution of the measurement was carefully determined by acquiring spectra over

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a line across the Hz deposit (Figure 3a). The line comprises of 10 spectra spanning a 2.2 µ m

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distance, resulting in a separation of 220 nm between points. Progressive changes are observed in

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the spectra along the line across the FV. Bands at 1207 cm-1 and 1300 cm-1 increased as the AFM

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tip approached the FV and decreased as spectra were recorded further away. This demonstrates

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submicron resolution of subcellular structures, because spectral differences could be clearly

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observed between points located only 220 nm apart.

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HyperspectralMultispectral AFM-IR imaging of P. falciparum infected RBC. 10


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The chemical characterization of the FV using AFM-IR shows that more information can be

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obtained compared to topographical AFM images of infected RBCs. Figure 4 shows AFM-IR

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images of a trophozoite-infected RBC using 23 wavenumber absorbance variables. Absorption

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maps at different wavenumber values were sequentially collected during several hours18 hours of

5

measurement. During this time a 2 µm drift was observed, precluding direct co-registration of the

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IR maps. AFM topographic images collected simultaneously with the IR intensity images were used

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to calculate the drift for each IR image, and subsequently used for co-registration. In this image,

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each pixel contained a “spectrum” with 23 intensity values from non-continuously spaced

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wavenumber values (See Supplementary Information SI-1). The wavenumber values of the

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absorbances to be measured were selected according to two criteria: either they showed large

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changes in preliminary spectra obtained across the cell; and/or they were well described markers of

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specific biological constituents.

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The AFM topographical map showed that the RBC (see Figure 4b and the superposition

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image in 4d) was thicker along its perimeter (a well-known property of erythrocytes), at 400 nm in

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height. The rest of the cell was only 200 nm in height except for the centre of cell, which contained

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a mass of Hz with a height of 400 nm and two circular holes approximately 600 nm in diameter. In

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order to study the relationship between the spectral variables and the pixels in the image, k-means

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cluster analysis (KMCA) was employed. This is a standard procedure in the analysis of

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hyperspectralmultispectral images that groups pixels according to their distance apart in the spectral

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space32. The KMCA identified 5 classes related to the topographical features (see cluster image in

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Figure 4c and the superposition image in Figure 4d). Classes coded orange and green are located at

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the edge of the cell, a class coded violet is associated with the Hz crystal mass, a blue-coded class

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appears in the centre of the cell, and pixels coded yellow are mainly found in or scattered around

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the cavities.

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The average class intensities of selected wavenumber values shown in figure 4e provides

26

information on the chemical composition of each cluster. Boxplots of the distribution of the 23 11



1

variables measured for each class are available in the SI-2. Green and orange coded classes show

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significant high intensity bands (p

Multispectral Atomic Force Microscopy-Infrared Nano-Imaging of

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