Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy

This work was supported by the UK Engineering and Physical Sciences Research Council under grant EP/J01771X/1, A European Union FAMOS project (FP7 ICT, 317744), and the ’BRAINS’ 600th anniversary appeal, and Dr. E. Killick. We would also like to thank The RS Macdonald Charitable Trust for funding support. KD acknowledges support of a Royal Society Leverhulme Trust Senior Fellowship. This work was also supported by the PreDiCT-TB consortium [IMI Joint undertaking grant agreement number 115337, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution (www.imi.europa.eu)]The ability to identify and characterise individual cells of the immune system under label-free conditions would be a significant advantage in biomedical and clinical studies where untouched and unmodified cells are required. We present a multi-modal system capable of simultaneously acquiring both single point Raman spectra and digital holographic images of single cells. We use this combined approach to identify and discriminate between immune cell populations CD4+ T cells, B cells and monocytes. We investigate several approaches to interpret the phase images including signal intensity histograms and texture analysis. Both modalities are independently able to discriminate between cell subsets and dual-modality may therefore be used a means for validation. We demonstrate here sensitivities achieved in the range of 86.8% to 100%, and specificities in the range of 85.4% to 100%. Additionally each modality provides information not available from the other providing both a molecular and a morphological signature of each cell.Publisher PDFPeer reviewe

Vibrational spectroscopy as a powerful tool for follow-up immunoadsorption therapy treatment of dilated cardiomyopathy - a case report

Dilated cardiomyopathy (DCM) is a leading cardiomyopathy condition and is the leading reason for heart transplantation. Due to high etiologic and genetic heterogeneity of the pathologies, different therapeutic treatment strategies are available and have been successful for different treatments. Immunoadsorption (IA) therapy removes the circulating anticardiac antibodies and improves the left ventricular function in substantial proportion of DCM patients. Powerful, non-invasive analytical tools are highly desired to investigate the efficiency and success of IA therapy. In this contribution, we followed the changes of a female DCM patient undergoing IA therapy at different treatment time points in a label-free, non-invasive manner from blood samples (plasma and serum) on the basis of vibrational spectroscopy (Raman scattering and IR absorption). Chemometric methods, including dimension reduction and statistical modeling, were used to interpret spectral data. The impact of different time points of the IA treatment can be identified in both the plasma and serum, using both techniques, with high accuracy. The removal of antibodies of immunoglobulin G (IgG) group during IA therapy and their restoration was reflected in both Raman and FTIR spectra. Relative changes in the spectral bands assigned to IgG agreed well with the immunoturbidimetry measurement of total IgG. Successful clinical treatment was accompanied by spectral differences between vibrational spectra obtained at initial disease state and 11 months after the IA treatment. The long-term follow-up of the patient reveals the stabilization of the health state after therapy. It is noteworthy that the treatment time points were distinguished with a better accuracy using spectra from plasma compared to those from serum samples, which might indicate the involvement of corresponding proteins in the coagulation. Vibrational spectroscopy is a powerful tool for personalized medicine to follow-up the treatment success of IA therapy for the DCM disorder

Biochemical analysis of leukocytes after in vitro and in vivo activation with bacterial and fungal pathogens using raman spectroscopy

Biochemical information from activated leukocytes provide valuable diagnostic infor-mation. In this study, Raman spectroscopy was applied as a label-free analytical technique to characterize the activation pattern of leukocyte subpopulations in an in vitro infection model. Neutro-phils, monocytes, and lymphocytes were isolated from healthy volunteers and stimulated with heat-inactivated clinical isolates of Candida albicans, Staphylococcus aureus, and Klebsiella pneumoniae. Binary classification models could identify the presence of infection for monocytes and lympho-cytes, classify the type of infection as bacterial or fungal for neutrophils, monocytes, and lympho-cytes and distinguish the cause of infection as Gram-negative or Gram-positive bacteria in the mon-ocyte subpopulation. Changes in single-cell Raman spectra, upon leukocyte stimulation, can be ex-plained with biochemical changes due to the leukocyte’s specific reaction to each type of pathogen. Raman spectra of leukocytes from the in vitro infection model were compared with spectra from leukocytes of patients with infection (DRKS-ID: DRKS00006265) with the same pathogen groups, and a good agreement was revealed. Our study elucidates the potential of Raman spectroscopy-based single-cell analysis for the differentiation of circulating leukocyte subtypes and identification of the infection by probing the molecular phenotype of those cells. © 2021 by the authors. Licensee MDPI, Basel, Switzerland