Developing and understanding biofluid vibrational spectroscopy: a critical review.

Vibrational spectroscopy can provide rapid, label-free, and objective analysis for the clinical domain. Spectroscopic analysis of biofluids such as blood components (e.g. serum and plasma) and others in the proximity of the diseased tissue or cell (e.g. bile, urine, and sputum) offers non-invasive diagnostic/monitoring possibilities for future healthcare that are capable of rapid diagnosis of diseases via specific spectral markers or signatures. Biofluids offer an ideal diagnostic medium due to their ease and low cost of collection and daily use in clinical biology. Due to the low risk and invasiveness of their collection they are widely welcomed by patients as a diagnostic medium. This review underscores recent research within the field of biofluid spectroscopy and its use in myriad pathologies such as cancer and infectious diseases. It highlights current progresses, advents, and pitfalls within the field and discusses future spectroscopic clinical potentials for diagnostics. The requirements and issues surrounding clinical translation are also considered.

Glycosaminoglycan profiling in different cell types using infrared spectroscopy and imaging.

We recently identified vibrational spectroscopic markers characteristic of standard glycosaminoglycan (GAG) molecules. The aims of the present work were to further this investigation to more complex biological systems and to characterize, via their spectral profiles, cell types with different capacities for GAG synthesis. After recording spectral information from individual GAG standards (hyaluronic acid, chondroitin sulfate, dermatan sulfate, heparan sulfate) and GAG-GAG mixtures, GAG-defective mutant Chinese hamster ovary (CHO)-745 cells, wild-type CHO cells, and chondrocytes were analyzed as suspensions by high-throughput infrared spectroscopy and as single isolated cells by infrared imaging. Spectral data were processed and interpreted by exploratory unsupervised chemometric methods based on hierarchical cluster analysis and principal component analysis. Our results showed that the spectral information obtained was discriminant enough to clearly delineate between the different cell types both at the cell suspension and single-cell levels. The abilities of the technique are to perform spectral profiling and to identify single cells with different potentials to synthesize GAGs. Infrared microspectroscopy/imaging could therefore be developed for cell screening purposes and further for identifying GAG molecules in normal tissues during physiological conditions (aging, healing process) and numerous pathological states (arthritis, cancer).

An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms.

Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells.

Investigating pre-analytical requirements for serum and plasma based infrared spectro-diagnostic.

Infrared spectroscopy is a rapid, easy-to-operate, label-free and therefore cost-effective technique. Many studies performed on biofluids (eg, serum, plasma, urine, sputum, bile and cerebrospinal fluid) have demonstrated its promising application as a clinical diagnostic tool. Given all these characteristics, infrared spectroscopy appears to be an ideal candidate to be implemented into the clinics. However, before considering its translation, a clear effort is needed to standardise protocols for biofluid spectroscopic analysis. To reach this goal, careful investigations to identify and track errors that can occur during the pre-analytical phase is a crucial step. Here, we report for the first time, results of investigations into pre-analytical factors that can affect the quality of the spectral data acquired on serum and plasma, such as the impact of long-term freezing time storage of samples as well as the month-to-month reproducibility of the spectroscopic analysis. The spectral data discrimination has revealed to be majorly impacted by a residual water content variation in serum and plasma dried samples.