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.

We present an approach for estimating and correcting Mie scattering occurring in infrared spectra of single cells, at diffraction limited probe size, as in synchrotron based microscopy. The Mie scattering is modeled by extended multiplicative signal correction (EMSC) and subtracted from the vibrational absorption. Because the Mie scattering depends non-linearly on alpha, the product of the radius and the refractive index of the medium/sphere causing it, a new method was developed for estimating the Mie scattering by EMSC for unknown radius and refractive index of the Mie scatterer. The theoretically expected Mie contributions for a range of different alpha values were computed according to the formulae developed by Van de Hulst (1957). The many simulated spectra were then summarized by a six-dimensional subspace model by principal component analysis (PCA). This subspace model was used in EMSC to estimate and correct for Mie scattering, as well as other additive and multiplicative interference effects. The approach was applied to a set of Fourier transform infrared (FT-IR) absorbance spectra measured for individual lung cancer cells in order to remove unwanted interferences and to estimate ranges of important alpha values for each spectrum. The results indicate that several cell components may contribute to the Mie scattering.

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.

Raman microspectroscopy allows probing subcellular compartments and provides a unique spectral fingerprint indicative of endogenous molecular composition. Although several spectroscopic cell studies have been reported on fixed samples, only few attempts concern single growing cells. Here, we have tested different optical substrates that would best preserve cell integrity and allow direct measurement of Raman spectra at the single living cell level. Calu-1 lung cancer cells were used as a model and their morphology and growth were assessed on Raman substrates like quartz, calcium fluoride, and zinc selenide. Data show that quartz was the most appropriate taking into consideration both cell morphology and proliferation rate (47% on quartz vs. 55% of BrdU-positive cells on conventional plastic). Using quartz, 40 cells were analysed and Raman spectra were collected from nuclei and cytoplasms using a 785 nm laser excitation of 30 mW at the sample, in the spectral range of 580-1750 cm(-1), and an acquisition time of 2 x 10 sec/spectrum. Discriminant spectral information related to nucleus and cytoplasm were extracted by multivariate statistical methods and attributed to nucleic acids, lipids, and proteins. Finally, Raman spectral imaging was performed to show the distribution of these components within the cell.

No abstract

Although the potential of vibrational spectroscopy for biomedical applications has been well demonstrated, translation into clinical practice has been relatively slow. This Editorial assesses the challenges facing the field and the potential way forward. While many technological challenges have been addressed to date, considerable effort is still required to gain acceptance of the techniques among the medical community, standardise protocols, extend to a clinically relevant scale, and ultimately assess the health economics underlying clinical deployment. National and international research networks can contribute much to technology development and standardisation. Ultimately, large-scale funding is required to engage in clinical trials and instrument development.

Raman spectroscopy has proven its potential for the analysis of cell constituents and processes. However, sample preparation methods compatible with clinical practice must be implemented for collection of accurate spectral information. This study aims at assessing, using micro-Raman imaging, the effects of some routinely used fixation methods such as formalin-fixation, formalin-fixation/air drying, cytocentrifugation, and air drying on intracellular spectral information. Data were compared with those acquired from single living cells. In parallel to these spectral information, cell morphological modifications that accompany sample preparation were compared. Spectral images of isolated cells were first analyzed in an unsupervised way using hierarchical cluster analysis (HCA), which allowed delimitation of the cellular compartments. The resulting nuclei cluster centers were compared and revealed at the molecular level that fixation induced changes in spectral information assigned to nucleic acids and proteins. In a second approach, a supervised fitting procedure using model spectra of DNA, RNA, and proteins, chemically extracted from living cells, revealed very small modifications at the level of the localization and quantification of these macromolecules. Finally, HCA and principal components analysis (PCA) performed on individual spectra randomly selected from the nuclear regions showed that formalin-fixation and cytocentrifugation are sample preparation methods that have little impact on the biochemical information as compared to living conditions. Any step involving cell air drying seems to accentuate the spectral deviations from the other preparation methods. It is therefore important in a future context of spectral cytology to take into account these variations.

Analytical technologies that can improve disease diagnosis are highly sought after. Current screening/diagnostic tests for several diseases are limited by their moderate diagnostic performance, invasiveness, costly and laborious methodologies or the need for multiple tests before a definitive diagnosis. Spectroscopic techniques, including infrared (IR) and Raman, have attracted great interest in the medical field, with applications expanding from early disease detection to monitoring and real-time diagnosis. This review highlights applications of IR and Raman spectroscopy, with a focus on cancer and infectious diseases since 2015, and underscores the diverse sample types that can be analyzed, such as biofluids, cells and tissues. Studies involving more than 25 participants per group (disease and control group; if no control group >25 in disease group) were considered eligible, to retain the clinical focus of the paper. Following literature searches, we identified 94 spectroscopic studies on different cancers and 30 studies on infectious diseases. The review KEYWORDS