Paul Bassan

Using Fourier transform IR spectroscopy to analyze biological materials

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.

Resonant Mie scattering in infrared spectroscopy of biological materials - Understanding the 'dispersion artefact'

Infrared spectroscopic cytology is potentially a powerful clinical tool. However, in order for it to be successful, practitioners must be able to extract reliably a pure absorption spectrum from a measured spectrum that often contains many confounding factors. The most intractable problem to date is the, so called, dispersion artefact which most prominently manifests itself as a sharp decrease in absorbance on the high wavenumber side of the amide I band in the measured spectrum, exhibiting a derivative-like line shape. In this paper we use synchrotron radiation FTIR micro-spectroscopy to record spectra of mono-dispersed poly(methyl methacrylate) (PMMA) spheres of systematically varying size and demonstrate that the spectral distortions in the data can be understood in terms of resonant Mie scattering. A full understanding of this effect will enable us to develop strategies for deconvolving the scattering contribution and recovering the pure absorption spectrum, thus removing one of the last technological barriers to the development of clinical spectroscopic cytology.

Reflection contributions to the dispersion artefact in FTIR spectra of single biological cells

Fourier transform infrared spectra of a single cell in transflection geometry are seen to vary significantly with position on the cell, showing a distorted derivative-like lineshape in the region of the optically dense nucleus. A similar behaviour is observable in a model system of the protein albumin doped in a potassium bromide disk. It is demonstrated that the spectrum at any point is a weighted sum of the sample reflection and transmission and that the dominance of the reflection spectrum in optically dense regions can account for some of the spectral distortions previously attributed to dispersion artefacts. Rather than being an artefact, the reflection contribution is ever present in transflection spectra and it is further demonstrated that the reflection characteristics can be used for cellular mapping.

RMieS-EMSC correction for infrared spectra of biological cells: Extension using full Mie theory and GPU computing

In the field of biomedical infrared spectroscopy it is often desirable to obtain spectra at the cellular level. Samples consisting of isolated single biological cells are particularly unsuited to such analysis since cells are strong scatterers of infrared radiation. Thus measured spectra consist of an absorption component often highly distorted by scattering effects. It is now known that the predominant contribution to the scattering is Resonant Mie Scattering (RMieS) and recently we have shown that this can be corrected for, using an iterative algorithm based on Extended Multiplicative Signal Correction (EMSC) and a Mie approximation formula. Here we present an iterative algorithm that applies full Mie scattering theory. In order to avoid noise accumulation in the iterative algorithm a curve-fitting step is implemented on the new reference spectrum. The new algorithm increases the computational time when run on an equivalent processor. Therefore parallel processing by a Graphics Processing Unit (GPU) was employed to reduce computation time. The optimised RMieS-EMSC algorithm is applied to an IR spectroscopy data set of cultured single isolated prostate cancer (PC-3) cells, where it is shown that spectral distortions from RMieS are removed.

The inherent problem of transflection-mode infrared spectroscopic microscopy and the ramifications for biomedical single point and imaging applications

Transflection-mode FTIR spectroscopy has become a popular method of measuring spectra from biomedical and other samples due to the relative low cost of substrates compared to transmission windows, and a higher absorbance due to a double pass through the same sample approximately doubling the effective path length. In this publication we state an optical description of samples on multilayer low-e reflective substrates. Using this model we are able to explain in detail the so-called electric-field standing wave effect and rationalise the non-linear change in absorbance with sample thickness. The ramifications of this non-linear change, for imaging and classification systems, where a model is built from tissue sectioned at a particular thickness and compared with tissue of a different thickness are discussed. We show that spectra can be distorted such that classification fails leading to inaccurate tissue segmentation which may have subsequent implications for disease diagnostics applications.

FTIR microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm

Transmission and transflection infrared microscopy of biological cells and tissue suffer from significant baseline distortions due to scattering effects, predominantly resonant Mie scattering (RMieS). This scattering can also distort peak shapes and apparent peak positions making interpretation difficult and often unreliable. A correction algorithm, the resonant Mie scattering extended multiplicative signal correction (RMieS-EMSC), has been developed that can be used to remove these distortions. The correction algorithm has two key user defined parameters that influence the accuracy of the correction. The first is the number of iterations used to obtain the best outcome. The second is the choice of the initial reference spectrum required for the fitting procedure. The choice of these parameters influences computational time. This is not a major concern when correcting individual spectra or small data sets of a few hundred spectra but becomes much more significant when correcting spectra from infrared images obtained using large focal plane array detectors which may contain tens of thousands of spectra. In this paper we show that, classification of images from tissue can be achieved easily with a few (<10) iterations but a reliable interpretation of the biochemical differences between classes could require more iterations. Regarding the choice of reference spectrum, it is apparent that the more similar it is to the pure absorption spectrum of the sample, the fewer iterations required to obtain an accurate corrected spectrum. Importantly however, we show that using three different non-ideal reference spectra, the same unique correction solution can be obtained.

Whole organ cross-section chemical imaging using label-free mega-mosaic FTIR microscopy

FTIR chemical imaging has been demonstrated as a promising technique to construct automated systems to complement histopathological evaluation of biomedical tissue samples. The rapid chemical imaging of large areas of tissue has previously been a limiting factor in this application. Consequently, smaller areas of tissue have previously had to be sampled, possibly introducing sampling bias and potentially missing diagnostically important areas. In this report a high spatial resolution chemical image of a whole prostate cross section is shown comprising 66 million pixels. Each pixel represents an area 5.5 × 5.5 μm(2) of tissue and contains a full infrared spectrum providing a chemical fingerprint. The data acquisition time was 14 hours, thus showing that a clinical time frame of hours rather than days has been achieved.

The action of all-trans-retinoic acid (ATRA) and synthetic retinoid analogues (EC19 and EC23) on human pluripotent stem cells differentiation investigated using single cell infrared microspectroscopy

All trans-retinoic acid (ATRA) is widely used to direct the differentiation of cultured stem cells. When exposed to the pluripotent human embryonal carcinoma (EC) stem cell line, TERA2.cl.SP12, ATRA induces ectoderm differentiation and the formation of neuronal cell types. We have previously generated synthetic analogues of retinoic acid (EC23 and EC19) which also induce the differentiation of EC cells. Even though EC23 and EC19 have similar chemical structures, they have differing biochemical effects in terms of EC cell differentiation. EC23 induces neuronal differentiation in a manner similar to ATRA, whereas EC19 directs the cells to form epithelial-like derivatives. Previous MALDI-TOF MS analysis examined the response of TERA2.cl.SP12 cells after exposure to ATRA, EC23 and EC19 and further demonstrated the similarly in the effect of ATRA and EC23 activity whilst responses to EC19 were very different. In this study, we show that Fourier Transform Infrared Micro-Spectroscopy (FT-IRMS) coupled with appropriate scatter correction and multivariate analysis can be used as an effective tool to further investigate the differentiation of human pluripotent stem cells and monitor the alternative affects different retinoid compounds have on the induction of differentiation. FT-IRMS detected differences between cell populations as early as 3 days of compound treatment. Populations of cells treated with different retinoid compounds could easily be distinguished from one another during the early stages of cell differentiation. These data demonstrate that FT-IRMS technology can be used as a sensitive screening technique to monitor the status of the stem cell phenotype and progression of differentiation along alternative pathways in response to different compounds.

Substrate contributions in micro-ATR of thin samples: implications for analysis of cells, tissue and biological fluids

Low-e microscope slides are a common substrate for biological samples. Typically they are used for transflection infrared microspectroscopy but increasingly they are also being used for micro-ATR experiments since it is assumed that the FTIR-ATR absorbance spectra of cells and tissue on low-e substrates will not contain any spectral contributions from the substrate materials. This, in part, is due to the expectation that all the infrared light will be reflected at the highly reflective surface. At low sample thicknesses, however (e.g. less than 2 μm) the electric field does indeed penetrate through the substrate layers and undergoes absorption, from the glass supporting layer making up the majority of the slide. In this paper we show experimental evidence of the substrate contributions in ATR spectra and also a theoretical model giving insight into the spectral contributions of the substrate as a function of sample thickness.

Comparison of transmission and transflectance mode FTIR imaging of biological tissue

FTIR microscopy is a powerful technique which has become popular due to its ability to provide complementary information during histopathological assessment of biomedical tissue samples. Recently however, questions have been raised on the suitability of the transflection mode of operation for clinical diagnosis due to the so called Electric Field Standing Wave (EFSW) effect. In this paper we compare chemical images measured in transmission and transflection from prostate tissue obtained from five different patients, and discuss the variability of the spectra acquired with each sampling modality. We find that spectra obtained in transflection undergo a non-linear distortion, i.e. non-linear variations in absorption band strength across the spectra, and that there are significant differences in spectra measured from the same area of tissue depending on the mode of operation. Principal Component Analysis (PCA) is used to highlight that poorer discrimination between benign and cancerous tissue is obtained in transflection mode. In addition we show that use of second derivatives, while qualitatively improves spectral discrimination, does not completely alleviate the underlying problem.