Exploiting CELLULOSE SYNTHASE (CESA) class-specificity to probe cellulose microfibril biosynthesis
Manoj Kumar, Laxmi Mishra, Paul Carr, Michael Pilling, Peter Gardner, Shawn D. Mansfield and Simon R. Turner
Plant Physiology (2018)
Cellulose microfibrils are the basic units of cellulose in plants. The structure of these microfibrils is at least partly determined by the structure of the cellulose synthase complex. In higher plants, this complex is composed of 18 to 24 catalytic subunits known as CELLULOSE SYNTHASE A (CESA) proteins. Three different classes of CESA proteins are required for cellulose synthesis and for secondary cell wall cellulose biosynthesis, which include CESA4, CESA7, and CESA8. To probe the relationship between CESA proteins and microfibril structure, we created mutant cesa proteins that lack catalytic activity but retain sufficient structural integrity to allow assembly of the cellulose synthase complex. Using a series of Arabidopsis mutants and genetic backgrounds, we found consistent differences in the ability of these mutant CESA proteins to complement the cellulose-deficient phenotype of the cesa null mutants. The best complementation was observed with catalytically inactive cesa4 while the equivalent mutation in cesa8 exhibited significantly lower levels of complementation. Using a variety of biophysical techniques, including ssNMR and FTIR, to study these mutant plants we found evidence for changes in cellulose microfibril structure, but these changes largely correlated with cellulose content and reflected differences in the relative proportion of primary and secondary cell walls. Our results suggest that individual CESA classes have similar roles in determining cellulose microfibril structure, and it is likely that the different effects of mutating members of different CESA classes is a consequence of their different catalytic activity and their influence on the overall rate of cellulose synthesis.
Clinical Applications of Infrared and Raman Spectroscopy: State of Play and Future Challenges
Matthew J. Baker, Hugh Byrne, John M. Chalmers, Peter Gardner, Royston Goodacre, Alex Henderson, Sergei Kazarian, Francis L. Martin, Julian Moger, Nick Stone and Josep Sulé-Suso
Vibrational spectroscopies, based on infrared absorption and/or Raman scattering provide a detailed fingerprint of a material, based on the chemical content. Diagnostic and prognostic tools based on these technologies have the potential to revolutionise our clinical systems leading to improved patient outcome, more efficient public services and significant economic savings. However, despite these strong drivers, there are many fundamental scientific and technological challenges which have limited the implementation of this technology in the clinical arena, although recent years have seen significant progress in addressing these challenges. This review examines (i) the state of the art of clinical applications of infrared absorption and Raman spectroscopy, and (ii) the outstanding challenges, and progress towards translation, highlighting specific examples in the areas of in vivo, ex vivo and in vitro applications. In addition, the requirements of instrumentation suitable for use in the clinic, strategies for pre-processing and statistical analysis in clinical spectroscopy and data sharing protocols, will be discussed. Emerging consensus recommendations are presented, and the future perspectives of the field are assessed, particularly in the context of national and international collaborative research initiatives, such as the UK EPSRC Clinical Infrared and Raman Spectroscopy Network, the EU COST Action Raman4Clinics, and the International Society for Clinical Spectroscopy.
An evaluation of the application of the aperture infrared SNOM technique to biomedical imaging
J Ingham, M J Pilling, T Craig, M R F Siggel-King, C I Smith, P Gardner, A Varro, D M Pritchard, S D Barrett, D S Martin, P Harrison, P Unsworth, J D Kumar, A Wolski, A Cricenti, M Luce, M Surman, Y M Saveliev and P Weightman
Biomedical Physics & Engineering Express 4 (2018) 025011
A single human oesophageal adenocarcinoma cell (OE33) has been imaged using aperture infrared scanning near-field optical microscopy (IR-SNOM) in transmission and reflection and also by Fourier-transform infrared (FTIR) microspectroscopy in transmission only. This work presents the first images obtained in both transmission and reflection of the same specimen using the aperture IR-SNOM technique. The results have been used to compare the two SNOM modes and also the two techniques, which have complementary capabilities. The SNOM technique necessitates a very stable source and a careful choice of wavelengths, since it is too slow to yield images at the thousands of wavelengths obtained with FTIR. However the SNOM technique is not diffraction limited and with careful fabrication of tips can yield images with high spatial resolution. There is no significant correlation between the SNOM images obtained in transmission and reflection and the correlations between images obtained at different wavelengths vary with the different imaging modes. These results are attributed to the strong dependence of the evanescent wave on both the wavelength and the distance between the tip and the source of the signal within the sample. While both transmission and reflection SNOM images show some correlation with topography this is not a dominant effect. These results indicate that with suitable calibration a combination of reflection and transmission aperture IR-SNOM measurements has the potential to reveal information on the depth distribution of the chemical structure of a specimen.
FTIR, Raman and SIMS Imaging for Lipidomic Analysis of Cellular Systems
Deadline 17 November 2017
The role of lipid metabolism in a number of cellular processes including (i) stem cell differentiation, (ii) drugcell interactions and (iii) epithelial/adipocyte cell interactions, is generally poorly understood. For example it has been recently shown that PC3 cells when co-cultured with adipocyte cells, sequestrate omega-6 lipids and their metabolites which subsequently stimulate cell migration and whilst promoting proliferation . Similarly lipids have been shown to play a key role in the differentiation of stem-cells, and recent investigations using FTIR have shown that lipid signatures may indicate early signs of differentiation . These fundamental cell processes, mediated by lipids, are currently a major focus of research.
Probing the secondary effects of Tp53 and BRCA gene mutations upon cellular physiology using advanced analytical techniques.
Prof R Edmondson, Prof P Gardner, Dr N Lockyer, Dr J Denbigh
Deadline: 17 November 2017
Cancer is a disease of DNA in which genomic events allow the cell to develop the autonomy, increased proliferation and other fundamental hallmarks of the disease. This process is often initiated by mutation of one or two key driver genes. Understanding the effects of these driver mutations is crucial in order to not only improve our understanding of the disease process but also to develop new screening and detection methods for cancer. In this exciting PhD the student will develop a novel cell model using primary human tissue to replicate the earliest phases in the development of high grade serous cancer, the commonest and most deadly pelvic cancer. The model will be created using fallopian tube epithelial cells which will be cultured ex vivo. Tp53 and BRCA1 genes will then be silenced using Crispr technology.
Quantum Cascade Laser Spectral Histopathology: Breast Cancer Diagnostics Using High Throughput Chemical Imaging
Michael J. Pilling, Alex Henderson and Peter Gardner
Analytical Chemistry 89(14) (2017) 7348–7355
Fourier transform infrared (FT-IR) microscopy coupled with machine learning approaches has been demonstrated to be a powerful technique for identifying abnormalities in human tissue. The ability to objectively identify the prediseased state and diagnose cancer with high levels of accuracy has the potential to revolutionize current histopathological practice. Despite recent technological advances in FT-IR microscopy, sample throughput and speed of acquisition are key barriers to clinical translation. Wide-field quantum cascade laser (QCL) infrared imaging systems with large focal plane array detectors utilizing discrete frequency imaging have demonstrated that large tissue microarrays (TMA) can be imaged in a matter of minutes. However, this ground breaking technology is still in its infancy, and its applicability for routine disease diagnosis is, as yet, unproven. In light of this, we report on a large study utilizing a breast cancer TMA comprised of 207 different patients. We show that by using QCL imaging with continuous spectra acquired between 912 and 1800 cm–1, we can accurately differentiate between 4 different histological classes. We demonstrate that we can discriminate between malignant and nonmalignant stroma spectra with high sensitivity (93.56%) and specificity (85.64%) for an independent test set. Finally, we classify each core in the TMA and achieve high diagnostic accuracy on a patient basis with 100% sensitivity and 86.67% specificity. The absence of false negatives reported here opens up the possibility of utilizing high throughput chemical imaging for cancer screening, thereby reducing pathologist workload and improving patient care.
Michael J. Pilling, Alex Henderson, Jonathan H. Shanks, Michael D. Brown, Noel W. Clarke and Peter Gardner
Analyst 142 (2017) 1258-1268
Infrared spectral histopathology has shown great promise as an important diagnostic tool, with the potential to complement current pathological methods. While promising, clinical translation has been hindered by the impracticalities of using infrared transmissive substrates which are both fragile and prohibitively very expensive. Recently, glass has been proposed as a potential replacement which, although largely opaque in the infrared, allows unrestricted access to the high wavenumber region (2500–3800 cm−1). Recent studies using unstained tissue on glass have shown that despite utilising only the amide A band, good discrimination between histological classes could be achieved, and suggest the potential of discriminating between normal and malignant tissue. However unstained tissue on glass has the potential to disrupt the pathologist workflow, since it needs to be stained following infrared chemical imaging. In light of this, we report on the very first infrared Spectral Histopathology SHP study utilising coverslipped H&E stained tissue on glass using samples as received from the pathologist. In this paper we present a rigorous study using results obtained from an extended patient sample set consisting of 182 prostate tissue cores obtained from 100 different patients, on 18 separate H&E slides. Utilising a Random Forest classification model we demonstrate that we can rapidly classify four classes of histology of an independent test set with a high degree of accuracy (>90%). We investigate different degrees of staining using nine separate prostate serial sections, and demonstrate that we discriminate on biomarkers rather than the presence of the stain. Finally, using a four-class model we show that we can discriminate normal epithelium, malignant epithelium, normal stroma and cancer associated stroma with classification accuracies over 95%.
Artur Dawid Surowka, Michael Pilling, Alex Henderson, Herve Boutin, Lidan Christie, Magdalena Szczerbowska-Boruchowska and Peter Gardner
Analyst 142 (2017) 156-168
Alzheimer’s disease is one of the major causes of dementia in the elderly. The disease is caused by the misfolding of water soluble alpha-helical proteins, which leads to the accumulation of β-sheets in the form of amyloid plaques, which can subsequently affect surrounding tissue areas by oxidative stress neurotoxicity. The aim of the present study was to design a novel methodology to analyze the extent to the neuronal burden around protein-rich Aβ plaques suspected to affect molecular components by oxidative stress induced by inflammatory states. To do so, sagittal brain tissue sections from triple transgenic APPxPSP1xTAU mice were used to carry high magnification FTIR-FPA bench-top chemical imaging. The study used the combination of chemometric procedures involving spectral curve fitting and image processing to study the molecular changes occurring around the plaques. The study shows the performance of the approach by demonstrating its usefulness to co-localize molecular changes to different areas around the plaques. The results, although very preliminary, point to the strong interplay between the distance from the plaque and co-accumulation of molecular components indicative of inflammatory states.