Heraud And Tobin S C R Editorial Paper


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This is an editorial piece for Stem Cell Review, where we try to highlight the emerging importance of biospectroscopy in stem cell research.

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Heraud And Tobin S C R Editorial Paper

  1. 1. This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright
  2. 2. Author's personal copy Stem Cell Research (2009) 3, 12–14 a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m w w w. e l s e v i e r. c o m / l o c a t e / s c r ON THE TOPIC The emergence of biospectroscopy in stem cell research Philip Heraud a,b,⁎, Mark J. Tobin c a Monash Immunology and Stem Cell Laboratories, Monash University, Wellington Road, Victoria 3800, Australia b Centre for Biospectroscopy and School of Chemistry, Monash University, Wellington Road, Victoria 3800, Australia c Australian Synchrotron, 800 Blackburn Road, Victoria 3168, Australia Received 18 April 2009; accepted 25 April 2009 The paper by Walsh et al. (Walsh et al., 2009) appearing in the extant literature resides (see, Two heads are better than this edition of Stem Cell Research demonstrates a new field in one, 2004). It is logical that the crossover that is required for science that can broadly be described as “biospectroscopy” these new methodologies to become more widely known and that has begun to emerge over the last few decades with a used within biomedical research in general depends on the plethora of biomedical studies as diverse as phytoplankton biospectroscopic measurements being closely correlated and productivity (Heraud et al., 2005) and cervical cancer compared with conventional measurements typically (McNaughton and Wood, 2007). The pioneering work by employed in the field of investigation, which is exactly the Walsh et al. joins three recent studies involving human (Krafft approach taken by Walsh et al. (Walsh et al., 2009). et al., 2007; Chan et al., 2009) and mouse (Ami et al., 2008) Specifically, biospectroscopic measurements are used to stem cell differentiation which have demonstrated that probe biochemical changes associated with differentiation biospectroscopic approaches can detect and define biochem- within human intestinal crypts, in situ, hitherto impossible ical changes occurring during the differentiation process in using conventional methods, with the findings compared and cell cultures. The work by Walsh et al. (Walsh et al., 2009), contrasted with conventional approaches. together with other recent FTIR spectroscopic studies (Ger- So what exactly is biospectroscopy, and what new utility or man et al., 2006; Bentley et al., 2007; Walsh et al., 2008), capabilities does it provide to research in biomedicine and demonstrates that these capabilities can be extended from stem cell biology in particular? In most cases the research cell culture to human cell differentiation, in situ. The involves obtaining a measurement by passing light through or research is “biospectroscopic” as it analyzes cells using reflecting it from a biological specimen. This can have spatial infrared microscopes, in this instance coupled to the light resolutions that range from the microscopic to the macro- from a synchrotron, to produce infrared spectral signatures scopic. However, unlike conventional light microscopy, for from single cells. The paper breaks ground because it instance, biospectroscopic approaches seek to obtain more adequately correlates conventional analyses with the bios- than just morphological contrast within the sample, but also pectroscopy and as it is published in a biomedical journal that elemental or molecular information, usually via some kind of is dedicated to the specific questions within its subdiscipline, spectroscopy, hence the name biospectroscopy. Four major in this case stem cell biology, rather than appearing in physical technological approaches have emerged in this field: Raman, chemistry or synchrotron science journals, in which many of infrared, fluorescence, and X-ray microspectroscopy. Fourier- transform infrared (FTIR) microspectroscopy is used by Walsh ⁎ Corresponding author. et al. (Walsh et al., 2009), to obtain information about the E-mail address: phil.heraud@sci.monash.edu.au (P. Heraud). relative concentrations of the macromolecular classes such as 1873-5061/$ – see front matter © 2009 Published by Elsevier B.V. doi:10.1016/j.scr.2009.04.002
  3. 3. Author's personal copy The emergence of biospectroscopy in stem cell research 13 proteins, lipids, carbohydrates, and nucleic acids within (Bhargave and Levin, 2005; Levenson et al., 2006). However individual cells in a single global measurement, achieved the spatial resolution routinely achievable with a synchro- nondestructively in seconds, and requiring minimal prepara- tron is proving critical in examining cellular changes at the tion with no staining. boundaries between tissues, and where the changes in cel- The method relies on knowledge of distinctive spectral lular function are subtle, or confined to small areas. It is bands that relate to vibrational modes of functional groups becoming common for researchers to combine both FPA data within the macromolecules. Naumann and co-workers and synchrotron data to achieve a more complete picture. (Naumann et al., 1991) were the first to identify and start These IR microscope systems are also complemented by to assign the FTIR spectra of biological cells, with over 40 high-throughput FTIR systems capable of examining large distinctive bands in mid-infrared frequencies from 4000 to populations of cells grown in a multiwell format on infrared- 600 cm−1 that can be uniquely identified to macromolecular compatible substrates (Benezzeddine-Boussaidi et al., components in the FTIR spectrum of biological cells. Many of 2009). Combining such systems with automated sample these bands overlap in the raw, unprocessed spectrum and handling allows the screening of many cell populations for are only revealed as distinct and individual bands when the changes in cellular chemistry as revealed by their IR spectra. data are preprocessed by taking a first or second derivative Bioinformatic approaches to data reduction and analysis of the original data. The need to apply appropriate mathe- are a cornerstone of this research area. This arises because matical processing and analysis is the final unifying aspect FTIR spectroscopic data are multivariate in nature containing that defines biospectroscopy, i.e., the use of sophisticated many bands, with important biological differences often bioinformatic approaches to objectively define the changes registered as subtle changes in band intensities, band maxima in biochemistry measured, as well as being used in the position, and broadening, often with a combination of factors construction of images based on this information. The paper that change in synchrony in response to a biological change or by Walsh et al. illustrates all these aspects of biospectro- phenomenon. This is illustrated well in the study by Walsh et scopy and is an instructive starting point for further reading al. (Walsh et al., 2009), where the discrimination of different for the uninitiated (Diem et al., 2008). cell types is based on clustering in scores plots generated by The overarching and powerful principal of Naumann's Principal Component Analysis (PCA) (Wold, 1976), the most early work was that not only is detailed investigation of parts commonly employed multivariate approach used in biospec- of the FTIR spectra useful for determining the nature of troscopic research. In the study the PCA approach is extended biochemical changes in cells via the FTIR spectrum, but more to allow objective classification of independent validation sets importantly that the complete spectral data derived from using Linear Discriminant Analysis (LDA) (McLachlan, 2004). the cell constituted what Naumann described as a “spectral The multivariate analysis provides the ability to use loadings fingerprint,” which uniquely defined the type of cell under plots that show the spectral bands that are changing and investigation. This principle was powerfully demonstrated by explain the clustering observed in the PCA scores plots, which Naumann and co-workers being able to reproducibly and shows the types of biochemical changes occurring and whether accurately discriminate different strains within individual the components are increasing or decreasing relative to one pathogenic bacteria species (Kirschner et al., 2001). Other another. Another classification approach coming into vogue in studies have shown that human cell types also can be biospectroscopy is Artificial Neural Network (ANN) (Hornik discriminated in a similar way (Wood et al., 1998) and from et al., 1989; Lasch et al., 2006) classification, which provides a these studies a variety of cancers and many other human useful comparison to PCA-based analyses, in that it is not disease states have been discriminated and pathology reliant on linear relationships between the data, but succeed imaged using FTIR spectroscopy (McNaughton et al., 2008). by the ability to train ANNs to recognize distinctive patterns. It is this notion of the existence of spectral phenotypes for ANN analysis is also attractive as it is computationally much different cell types that Walsh et al. use to demonstrate less intensive compared to the linear-based approaches such longitudinal changes in differentiation states along small and as LDA (Lasch et al., 2006). large intestinal crypts and also demonstrate relatedness Biospectroscopy can still be considered in its infancy, between particular cell types. Furthermore, the nature and despite enormous breakthroughs and advances in instrumen- direction of biochemical changes broadly associated with the tation over the previous few decades, and this is evidenced differentiation process are identified, underscoring the by most published work still being found within journals difference between spectroscopic approaches and histologi- strongly associated with physical chemistry. The break- cal approaches. through for these extremely powerful new techniques into The work by Walsh et al. employs mapping of areas of mainstream biomedical research areas depends on careful tissue sections at the single cell level necessitating emplo- integration of the new approaches with the established ying light from a synchrotron source. This type of approach is measurements, with the aim to correlate and corroborate usually taken when the highest spatial resolution and signal the new approaches. Walsh et al. (Walsh et al., 2009) rely on to noise measurements are required. The nature of the position coordinates within equally spaced grids as an synchrotron source allows an infrared beam to be focused to innovative first approach to establishing the relationship a spot size that is equivalent to or smaller than the size of a between the cell type and the spectra obtained to achieve a single mammalian cell, allowing chemical information to be correlation between the FTIR mapping data and histology. gained, with high sensitivity, at subcellular spatial resolu- Their paper demonstrates the enormous potential for tion. The trade-off for this gain in sensitivity and spatial biospectroscopic approaches to add new information to the resolution is that the area of sample that can be studied in an field of stem cell biology by providing biochemical data of a acceptable time is much smaller than is possible with a state- global nature that can either fingerprint cell types or provide of-the art Focal Plane Array (FPA) infrared imaging system an indication of overall changes in macromolecular
  4. 4. Author's personal copy 14 P. Heraud, M.J. Tobin composition that is associated with stem differentiation. fication and identification of enterococci: A comparative pheno- There can be little doubt that these studies demonstrate the typic, genotypic, and vibrational spectroscopic study. J. Clin. application of new and powerful complimentary biospectro- Microbiol. 39, 1763–1770. Krafft, C., Salzer, R., Seitz, S., Ern, C., Schieker, M., 2007. Diffe- scopic approaches for shedding new light on stem cell biology rentiation of individual human mesenchymal stem cells probed and hopefully herald a burgeoning of the new methodologies by FTIR microscopic imaging. Analyst 132, 647–653. into stem cell research. Lasch, P., Diem, M., Hänsch, W., Naumann, D., 2006. Artificial neural networks as supervised techniques for FT-IR microspectroscopic imaging. J. Chemometr. 20, 209–220. References Levenson, E., Lerch, P., Martin, M.C., 2006. Infrared imaging: Syn- chrotrons vs. arrays, resolution vs. speed. Infrared Phys. Technol. Ami, T., Neri, A., Natalello, P., Mereghetti, S.M., Doglia, M., Zanoni, 49, 45–48. M., Zuccotti, S., Garagna, C.A., 2008. Redi, Embryonic stem cell McLachlan, G.J., 2004. Discriminant Analysis and Statistical Pattern differentiation studied by FT-IR spectroscopy. BBA – Mol. Cell Recognition. Wiley-Interscience, USA. Res. 1783, 98–106. McNaughton, D., Wood, B.R., 2007. Applications of FTIR imaging in Benezzeddine-Boussaidi, L., Cazorla, G., Melin, A.M., 2009. Valida- cancer research. In: Kneipp, K., Aroca, R., Kneipp, H., Wentrup- tion for quantification of immunoglobulins by Fourier transform Byrne, E. (Eds.), New Approaches in Biomedical Spectroscopy, infrared spectrometry. Clin. Chem. Lab. Med. 47, 83–90. ACS Symposium Book Series, 963, pp. 14–29. Washington DC. Bentley, A.J., Nakamura, T., Hammiche, A., Pollock, H.M., Martin, F.L., McNaughton, D., Bambery, K., Wood, B.R., 2008. Spectral Histo- Kinoshita, S., Fullwood, N.J., 2007. Characterization of human pathology of the human cervix. In: Diem, M., Chalmers, J.M., corneal stem cells by synchrotron infrared micro-spectroscopy. Griffiths, P.R. (Eds.), Vibrational Spectroscopy for Medical Mol. Vis. 13, 237–242. Diagnosis. Wiley, UK. Bhargave, R., Levin, I., 2005. Spectrochemical Analyses Using Naumann, D., Helman, D., Labischinski, H., 1991. Microbiological Multichannel Infrared Detectors. Blackwell, UK. characterizations by FT-IR spectroscopy. Nature 351, 81–82. Chan, J.W., Lieu, D.K., Huser, T., Li, R.A., 2009. Label-free separation Two heads are better than one. Nat. Methods 1, 183, doi:10.1038/ of human embryonic stem cells and their cardiac derivatives using nmeth1204–183. Raman spectroscopy. Anal. Chem. 81, 1324–1331. Walsh, M.J., Fellous, T.G., Hammiche, A., Lin, W.R., Fullwood, N.J., Diem, M., Chalmers, J.M., Griffiths, P.R., 2008. Vibrational Spectro- Grude, O., Bahrami, F., Nicholson, J.M., Cotte, M., Susini, J., scopy for Medical Diagnosis. Wiley, UK. Pollock, H.M., Brittan, M., Martin-Hirsch, P.L., Alison, M.R., German, M.J., Pollock, H.M., Zhao, B., Tobin, M.J., Hammiche, A., Martin, F.L., 2008. Fourier transform infrared microspectroscopy Bentley, A., Cooper, L.J., Martin, F.L., Fullwood, N.J., 2006. Cha- identifies symmetric PO-2 modifications as a marker of the racterization of putative stem cell populations in the cornea using putative stem cell region of human intestinal crypts. Stem Cells synchrotron infrared microspectroscopy. Investig. Ophthalmol. Vis. 26, 108–118. Sci. 47, 2417–2421. Walsh, M.J., Hammiche, A., Fellous, T.G., Nicholson, J.M., Cotte, M., Heraud, P., Wood, B.R., Tobin, M., Beardall, J., McNaughton, D., Susini, J., Fullwood, N.J., Martin-Hirsch, P.L., Alison, M.R., Martin, 2005. Mapping of nutrient-induced biochemical changes in living F.L., 2009. Tracking the cell hierarchy in the human intestine using algal cells using synchrotron infrared microspectroscopy. FEMS biochemical signatures derived by mid-infrared microspectro- Microbiol. Lett. 249, 219–225. scopy. Stem Cell Res 3, 15–27. Hornik, K., Stinchcombe, M., White, H., 1989. Multilayer feed- Wold, S., 1976. Pattern recognition by means of disjoint principal forward networks are universal approximators. Neural Netw. 2, component models. Pattern Recogn. 8, 127–139. 359–366. Wood, B.R., Quinn, M., Tait, B., Ashdown, M., Hislop, T., Romeo, M., Kirschner, C., Maquelin, K., Pina, P., Thi, N., Choo-Smith, L.P ., McNaughton, D., 1998. FTIR microspectroscopic study of cell Sockalingum, G.D., Sandt, C., Ami, D., Orsini, F., Doglia, S.M., types and potential confounding variables in screening for Allouch, P., Mainfait, M., Puppels, G.J., Naumann, D., 2001. Classi- cervical malignancies. Biospectroscopy 4, 75–91.