Measuring similarity and improving stability in biomarker identification methods applied to Fourier-transform infrared (FTIR) spectroscopy

MIR-biospectroscopy coupled with chemometrics in cancer studies

This review focuses on chemometric techniques applied in MIR-biospectroscopy for cancer diagnosis and analysis over the last ten years of research. Experimental applications of chemometrics coupled with biospectroscopy are discussed throughout this work. The advantages and drawbacks of this association are also highlighted. Chemometric algorithms are evidenced as a powerful tool for cancer diagnosis, classification, and in different matrices. In fact, it is shown how chemometrics can be implemented along all different types of cancer analyses.

Differentiation of mixed soil-borne fungi in the genus level using infrared spectroscopy and multivariate analysis

Early detection of soil-borne pathogens, which have a negative effect on almost all agricultural crops, is crucial for effective targeting with the most suitable antifungal agents and thus preventing and/or reducing their severity. They are responsible for severe diseases in various plants, leading in many cases to substantial economic losses. In this study, infrared (IR) spectroscopic method, which is known as sensitive, accurate and rapid, was used to discriminate between different fungi in a mixture was evaluated. Mixed and pure samples of Colletotrichum, Verticillium, Rhizoctonia, and Fusarium genera were measured using IR microscopy. Our spectral results showed that the best differentiation between pure and mixed fungi was obtained in the 675-1800 cm^-1 wavenumber region. Principal components analysis (PCA), followed by linear discriminant analysis (LDA) as a linear classifier, was performed on the spectra of the measured classes. Our results showed that it is possible to differentiate between mixed-calculated categories of phytopathogens with high success rates (~100%) when the mixing percentage range is narrow (40-60) in the genus level; when the mixing percentage range is wide (10-90), the success rate exceeded 85%. Also, in the measured mixed categories of phytopathogens it is possible to differentiate between the different categories with ~100% success rate.

Mid-infrared spectroscopy of serum, a promising non-invasive method to assess prognosis in patients with ascites and cirrhosis

Background & aims

Prognostic tests are critical in the management of patients with cirrhosis and ascites. Biological tests or scores perform poorly in that situation. Mid-infrared fibre evanescent wave spectroscopy (MIR-FEWS) which allows for global serum metabolic profiling may provide more relevant information by measuring a wider range of metabolic parameters in serum. Here we present the accuracy of a MIR-FEWS based predictive model for the prognosis of 6 months survival in patients with ascites and cirrhosis.

Methods

Patients with ascites were prospectively included and followed up for 6 months. MIR-FEWS spectra were measured in serum samples. The most informative spectral variables obtained by MIR-FEWS were selected by FADA algorithm and then used to build the MIR model. Accuracy of this model was assessed by ROC curves and 90%/10% Monte Carlo cross-validation. MIR model accuracy for 6 months survival was compared to that of the Child-Pugh and MELD scores.

Results

119 patients were included. The mean age was 57.36±13.70, the MELD score was 16.32±6.26, and the Child-Pugh score was 9.5±1.83. During follow-up, 23 patients died (20%). The MIR model had an AUROC for 6 months mortality of 0.90 (CI95: 0.88–0.91), the MELD 0.77 (CI95: 0.66–0.89) and Child-Pugh 0.76 (CI95: 0.66–0.88). MELD and Child-Pugh AUROCs were significantly lower than that of the MIR model (p = 0.02 and p = 0.02 respectively). Multivariate logistic regression analysis showed that MELD (p<0.05, OR:0.86;CI95:0.76–0.97), Beta blockers (p = 0.036;OR:0.20;CI95:0.04–0.90), and the MIR model (p<0.001; OR:0.50; CI95:0.37–0.66), were significantly associated with 6 months mortality.

Conclusions

In this pilot study MIR-FEWS more accurately assess the 6-month prognosis of patients with ascites and cirrhosis than the MELD or Child-Pugh scores. These promising results, if confirmed by a larger study, suggest that mid infrared spectroscopy could be helpful in the management of these patients.

Verification of the effectiveness of the Fourier transform infrared spectroscopy computational model for colorectal cancer

Colorectal cancer is one of the most common cancers. Its formation is influenced by genetic and environmental factors. Despite the continuous development of diagnostic tools and cancer therapies, there are no methods that allow a real-time estimation of treatment efficiency. This method can be a vibrational spectroscopy. The resulting infrared spectrum (FTIR) of the tissue gives us information about the chemical composition and the content of the individual components. We have noticed that tumor tissues, healthy and after chemotherapy tissues, have different vibrational spectra. It was also shown that spectra acquired from normal (benign) tissues were similar to those derived from tissues post-chemotherapy. The similarity was greater, when the effectiveness of chemotherapy, confirmed by medical documentation, was better. Therefore, we decided to use the physical model proposed in our earlier paper to verify its correctness and to show whether a particular type of chemotherapy was effective or not. Comparison of the results obtained from the physical model with patients data have been found as close to the physical condition.

Fourier transform infra-red spectroscopic signatures for lung cells' epithelial mesenchymal transition: A preliminary report

Infra red (IR) spectral characterization can provide label-free cellular metabolic signatures of normal and diseased circumstances in a rapid and non-invasive manner. Present study endeavoured to enlist Fourier transform infra red (FTIR) spectroscopic signatures for lung normal and cancer cells during chemically induced epithelial mesenchymal transition (EMT) for which global metabolic dimension is not well reported yet. Occurrence of EMT was validated with morphological and immunocytochemical confirmation. Pre-processed spectral data was analyzed using ANOVA and principal component analysis-linear discriminant analysis (PCA-LDA). Significant differences observed in peak area corresponding to biochemical fingerprint (900-1800cm^-1) and high wave-number (2800-3800cm^-1) regions contributed to adequate PCA-LDA segregation of cells undergoing EMT. The findings were validated by re-analysis of data using another in-house built binary classifier namely vector valued regularized kernel approximation (VVRKFA), in order to understand EMT progression. To improve the classification accuracy, forward feature selection (FFS) tool was employed in extracting potent spectral signatures by eliminating undesirable noise. Gradual increase in classification accuracy with EMT progression of both cell types indicated prominence of the biochemical alterations. Rapid changes in cellular metabolome noted in cancer cells within first 24h of EMT induction along with higher classification accuracy for cancer cell groups in comparison to normal cells might be attributed to inherent differences between them. Spectral features were suggestive of EMT triggered changes in nucleic acid, protein, lipid and bound water contents which can emerge as the useful markers to capture EMT related cellular characteristics.

Diet-sourced carbon-based nanoparticles induce lipid alterations in tissues of zebrafish (Danio rerio) with genomic hypermethylation changes in brain

With rising environmental levels of carbon-based nanoparticles (CBNs), there is an urgent need to develop an understanding of their biological effects in order to generate appropriate risk assessment strategies. Herein, we exposed zebrafish via their diet to one of four different CBNs: C₆₀ fullerene (C₆₀), single-walled carbon nanotubes (SWCNT), short multi-walled carbon nanotubes (MWCNTs) or long MWCNTs. Lipid alterations in male and female zebrafish were explored post-exposure in three target tissues (brain, gonads and gastrointestinal tract) using ‘omic’ procedures based in liquid chromatography coupled with mass spectrometry (LC-MS) data files. These tissues were chosen as they are often target tissues following environmental exposure. Marked alterations in lipid species are noted in all three tissues. To further explore CBN-induced brain alterations, Raman microspectroscopy analysis of lipid extracts was conducted. Marked lipid alterations are observed with males responding differently to females; in addition, there also appears to be consistent elevations in global genomic methylation. This latter observation is most profound in female zebrafish brain tissues post-exposure to short MWCNTs or SWCNTs (P < 0.05). This study demonstrates that even at low levels, CBNs are capable of inducing significant cellular and genomic modifications in a range of tissues. Such alterations could result in modified susceptibility to other influences such as environmental exposures, pathology and, in the case of brain, developmental alterations.

Infrared spectroscopy detects changes in an amphibian cell line induced by fungicides: Comparison of single and mixture effects

Amphibians are regarded as sensitive sentinels of environmental pollution due to their permeable skin and complex life cycle, which usually involves reproduction and development in the aquatic environment. Fungicides are widely applied agrochemicals and have been associated with developmental defects in amphibians; thus, it is important to determine chronic effects of environmentally-relevant concentrations of such contaminants in target cells. Infrared (IR) spectroscopy has been employed to signature the biological effects of environmental contaminants through extracting key features in IR spectra with chemometric methods. Herein, the Xenopus laevis (A6) cell line was exposed to low concentrations of carbendazim (a benzimidazole fungicide) or flusilazole (a triazole fungicide) either singly or as a binary mixture. Cells were then examined using attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy coupled with multivariate analysis. Results indicate significant changes in the IR spectra of cells induced by both agents at all concentrations following single exposures, primarily in regions associated with protein and phospholipids. Distinct differences were apparent in the IR spectra of cells exposed to carbendazim and those exposed to flusilazole, suggesting different mechanisms of action. Exposure to binary mixtures of carbendazim and flusilazole also induced significant spectral alterations, again in regions associated with phospholipids and proteins, but also in regions associated with DNA and carbohydrates. Overall these findings demonstrate that IR spectroscopy is a sensitive technique for examining the effects of environmentally-relevant levels of fungicides at the cellular level. The combination of IR spectroscopy with the A6 cell line could serve as a useful model to identify agents that might threaten amphibian health in a rapid and high throughput manner.

Using Raman spectroscopy to characterize biological materials

Raman spectroscopy can be used to measure the chemical composition of a sample, which can in turn be used to extract biological information. Many materials have characteristic Raman spectra, which means that Raman spectroscopy has proven to be an effective analytical approach in geology, semiconductor, materials and polymer science fields. The application of Raman spectroscopy and microscopy within biology is rapidly increasing because it can provide chemical and compositional information, but it does not typically suffer from interference from water molecules. Analysis does not conventionally require extensive sample preparation; biochemical and structural information can usually be obtained without labeling. In this protocol, we aim to standardize and bring together multiple experimental approaches from key leaders in the field for obtaining Raman spectra using a microspectrometer. As examples of the range of biological samples that can be analyzed, we provide instructions for acquiring Raman spectra, maps and images for fresh plant tissue, formalin-fixed and fresh frozen mammalian tissue, fixed cells and biofluids. We explore a robust approach for sample preparation, instrumentation, acquisition parameters and data processing. By using this approach, we expect that a typical Raman experiment can be performed by a nonspecialist user to generate high-quality data for biological materials analysis.

Fourier-transform-infrared-spectroscopy based spectral-biomarker selection towards optimum diagnostic differentiation of oral leukoplakia and cancer

In search of specific label-free biomarkers for differentiation of two oral lesions, namely oral leukoplakia (OLK) and oral squamous-cell carcinoma (OSCC), Fourier-transform infrared (FTIR) spectroscopy was performed on paraffin-embedded tissue sections from 47 human subjects (eight normal (NOM), 16 OLK, and 23 OSCC). Difference between mean spectra (DBMS), Mann-Whitney's U test, and forward feature selection (FFS) techniques were used for optimising spectral-marker selection. Classification of diseases was performed with linear and quadratic support vector machine (SVM) at 10-fold cross-validation, using different combinations of spectral features. It was observed that six features obtained through FFS enabled differentiation of NOM and OSCC tissue (1782, 1713, 1665, 1545, 1409, and 1161 cm(-1)) and were most significant, able to classify OLK and OSCC with 81.3 % sensitivity, 95.7 % specificity, and 89.7 % overall accuracy. The 43 spectral markers extracted through Mann-Whitney's U Test were the least significant when quadratic SVM was used. Considering the high sensitivity and specificity of the FFS technique, extracting only six spectral biomarkers was thus most useful for diagnosis of OLK and OSCC, and to overcome inter and intra-observer variability experienced in diagnostic best-practice histopathological procedure. By considering the biochemical assignment of these six spectral signatures, this work also revealed altered glycogen and keratin content in histological sections which could able to discriminate OLK and OSCC. The method was validated through spectral selection by the DBMS technique. Thus this method has potential for diagnostic cost minimisation for oral lesions by label-free biomarker identification.

Multiwavelength Resonance Raman Characterization of the Effect of Growth Phase and Culture Medium on Bacteria

We examine the use of multiwavelength ultraviolet (UV) resonance-Raman signatures to identify the effects of growth phase and growth medium on gram-positive and gram-negative bacteria. Escherichia coli (E. coli), Citrobacter koseri (C. koseri), Citrobacter braakii (C. braakii), and Bacillus cereus (B. cereus) were grown to logarithmic and stationary phases in nutrient broth and brain heart infusion broth. Resonance Raman spectra of bacteria were obtained at multiple wavelengths between 220 and 260 nm; a range that encompasses the resonance frequencies of cellular constituents. We find that spectra of the same bacterial species exhibit differences due to both growth condition and growth phase, but the larger differences reflect changes due to growth phase. The differences in the Raman spectra correlate with genetic differences among the species. Using a Pearson correlation based algorithm, we achieve successful identification of these bacteria in 83% of the cases.

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging of human tissue sections towards improving pathology

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging is an emerging approach to obtain detailed images that have associated biochemical information. FT-IR imaging of tissue is based on the principle that different regions of the mid-infrared are absorbed by different chemical bonds (e.g., C=O, C-H, N-H) within cells or tissue that can then be related to the presence and composition of biomolecules (e.g., lipids, DNA, glycogen, protein, collagen). In an FT-IR image, every pixel within the image comprises an entire Infrared (IR) spectrum that can give information on the biochemical status of the cells that can then be exploited for cell-type or disease-type classification. In this paper, we show: how to obtain IR images from human tissues using an FT-IR system, how to modify existing instrumentation to allow for high-definition imaging capabilities, and how to visualize FT-IR images. We then present some applications of FT-IR for pathology using the liver and kidney as examples. FT-IR imaging holds exciting applications in providing a novel route to obtain biochemical information from cells and tissue in an entirely label-free non-perturbing route towards giving new insight into biomolecular changes as part of disease processes. Additionally, this biochemical information can potentially allow for objective and automated analysis of certain aspects of disease diagnosis.

Analysis of the developing neural system using an in vitro model by Raman spectroscopy

We developed an in vitro model of early neural cell development.

Assignment of Colletotrichum coccodes isolates into vegetative compatibility groups using infrared spectroscopy: a step towards practical application

FTIR spectroscopy may provide a specific, rapid, and inexpensive method for the successful classification of Colletotrichum coccodes isolates into vegetative compatibility groups.

Using Fourier transform IR spectroscopy to analyze biological materials

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.