Real‐time monitoring of high‐gravity corn mash fermentation using in situ raman spectroscopy

In situ Raman spectroscopy was employed for real‐time monitoring of simultaneous saccharification and fermentation (SSF) of corn mash by an industrial strain of Saccharomyces cerevisiae. An accurate univariate calibration model for ethanol was developed based on the very strong 883 cm^?1 C–C stretching band. Multivariate partial least squares (PLS) calibration models for total starch, dextrins, maltotriose, maltose, glucose, and ethanol were developed using data from eight batch fermentations and validated using predictions for a separate batch. The starch, ethanol, and dextrins models showed significant prediction improvement when the calibration data were divided into separate high‐ and low‐concentration sets. Collinearity between the ethanol and starch models was avoided by excluding regions containing strong ethanol peaks from the starch model and, conversely, excluding regions containing strong saccharide peaks from the ethanol model. The two‐set calibration models for starch (R² = 0.998, percent error = 2.5%) and ethanol (R² = 0.999, percent error = 2.1%) provide more accurate predictions than any previously published spectroscopic models. Glucose, maltose, and maltotriose are modeled to accuracy comparable to previous work on less complex fermentation processes. Our results demonstrate that Raman spectroscopy is capable of real time in situ monitoring of a complex industrial biomass fermentation. To our knowledge, this is the first PLS‐based chemometric modeling of corn mash fermentation under typical industrial conditions, and the first Raman‐based monitoring of a fermentation process with glucose, oligosaccharides and polysaccharides present. Biotechnol. Bioeng. 2013; 110: 1654–1662. © 2013 Wiley Periodicals, Inc.     

Real‐time endoscopic Raman spectroscopy for in vivo early lung cancer detection

Currently the most sensitive method for localizing lung cancers in central airways is autofluorescence bronchoscopy (AFB) in combination with white light bronchoscopy (WLB). The diagnostic accuracy of WLB + AFB for high grade dysplasia (HGD) and carcinoma in situ is variable depending on physician's experience. When WLB + AFB are operated at high diagnostic sensitivity, the associated diagnostic specificity is low. Raman spectroscopy probes molecular vibrations and gives highly specific, fingerprint‐like spectral features and has high accuracy for tissue pathology classification. In this study we present the use of a real‐time endoscopy Raman spectroscopy system to improve the specificity. A spectrum is acquired within 1 second and clinical data are obtained from 280 tissue sites (72 HGDs/malignant lesions, 208 benign lesions/normal sites) in 80 patients. Using multivariate analyses and waveband selection methods on the Raman spectra, we have demonstrated that HGD and malignant lung lesions can be detected with high sensitivity (90%) and good specificity (65%).

     

Autofluorescence and white light imaging‐guided endoscopic Raman and diffuse reflectance spectroscopy for in vivo nasopharyngeal cancer detection

Nasopharyngeal cancer (NPC) is an endemic with high incidence in Southern China and Southeast Asia countries. Screening for NPC under conventional white light imaging (WLI) nasopharyngoscope examination remains a great clinical challenge due to its poor sensitivity. Here, we developed an integrated 4‐modality endoscopy system combining WLI, autofluorescence imaging (AFI), diffuse reflectance spectroscopy and Raman spectroscopy technologies for in vivo endoscopic cancer detection for the first time. A pilot clinical test of the system for NPC detection was conducted, in which 283 in vivo Raman and diffuse reflectance spectral data sets from 30 NPC patients and 30 healthy subjects were acquired under the guidance of AFI and WLI. Both high diagnostic sensitivity (98.6%) and high specificity (95.1%) for differentiating cancer from normal tissue sites were achieved using this system combined with principal component analysis‐linear discriminant analysis diagnostic algorithm, demonstrating great potential for improving real‐time, in vivo diagnosis of NPC at endoscopy.      

Rapid characterization and quality control of complex cell culture media solutions using raman spectroscopy and chemometrics

The use of Raman spectroscopy coupled with chemometrics for the rapid identification, characterization, and quality assessment of complex cell culture media components used for industrial mammalian cell culture was investigated. Raman spectroscopy offers significant advantages for the analysis of complex, aqueous‐based materials used in biotechnology because there is no need for sample preparation and water is a weak Raman scatterer. We demonstrate the efficacy of the method for the routine analysis of dilute aqueous solution of five different chemically defined (CD) commercial media components used in a Chinese Hamster Ovary (CHO) cell manufacturing process for recombinant proteins.The chemometric processing of the Raman spectral data is the key factor in developing robust methods. Here, we discuss the optimum methods for eliminating baseline drift, background fluctuations, and other instrumentation artifacts to generate reproducible spectral data. Principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) were then employed in the development of a robust routine for both identification and quality evaluation of the five different media components. These methods have the potential to be extremely useful in an industrial context for “in‐house” sample handling, tracking, and quality control. Biotechnol. Bioeng. 2010;107: 290–301. © 2010 Wiley Periodicals, Inc.     

Back Cover: Autofluorescence and white light imaging‐guided endoscopic Raman and diffuse reflectance spectroscopy for in vivo nasopharyngeal cancer detection (J. Biophotonics 4/2018)

An integrated 4‐modality endoscopy system combining white light imaging, autofluorescence imaging, diffuse reflectance spectroscopy and Raman spectroscopy technologies was developed for in vivo endoscopic nasopharyngeal cancer detection. Both high diagnostic sensitivity (98.6%) and high specificity (95.1%) for differentiating cancer from normal tissue sites were achieved using this system combined with multivariate diagnostic algorithm, demonstrating great potential for improving real‐time, in vivo diagnosis of cancer at endoscopy. Further details can be found in the article by Duo Lin et al. ( e201700251 )

     

Bladder tissue characterization using probe‐based Raman spectroscopy: Evaluation of tissue heterogeneity and influence on the model prediction

Existing approaches for early‐stage bladder tumor diagnosis largely depend on invasive and time‐consuming procedures, resulting in hospitalization, bleeding, bladder perforation, infection and other health risks for the patient. The reduction of current risk factors, while maintaining or even improving the diagnostic precision, is an underlying factor in clinical instrumentation research. For example, for clinic surveillance of patients with a history of noninvasive bladder tumors real‐time tumor diagnosis can enable immediate laser‐based removal of tumors using flexible cystoscopes in the outpatient clinic. Therefore, novel diagnostic modalities are required that can provide real‐time in vivo tumor diagnosis. Raman spectroscopy provides biochemical information of tissue samples ex vivo and in vivo and without the need for complicated sample preparation and staining procedures. For the past decade there has been a rise in applications to diagnose and characterize early cancer in different organs, such as in head and neck, colon and stomach, but also different pathologies, for example, inflammation and atherosclerotic plaques. Bladder pathology has also been studied but only with little attention to aspects that can influence the diagnosis, such as tissue heterogeneity, data preprocessing and model development. The present study presents a clinical investigative study on bladder biopsies to characterize the tumor grading ex vivo, using a compact fiber probe‐based imaging Raman system, as a crucial step towards in vivo Raman endoscopy. Furthermore, this study presents an evaluation of the tissue heterogeneity of highly fluorescent bladder tissues, and the multivariate statistical analysis for discrimination between nontumor tissue, and low‐ and high‐grade tumor.     

Simultaneous fingerprint and high‐wavenumber fiber‐optic Raman spectroscopy enhances real‐time in vivo diagnosis of adenomatous polyps during colonoscopy

Colorectal cancer can be prevented if detected early (e.g., precancerous polyps‐adenoma). Endoscopic differential diagnosis of hyperplastic polyps (that have little or no risk of malignant transformation) and adenomas (that have prominent malignant latency) remains an unambiguous clinical challenge. Raman spectroscopy is an optical vibrational technique capable of probing biomolecular changes of tissue associated with neoplastic transformation. This work aims to apply a fiber‐optic simultaneous fingerprint (FP) and high wavenumber (HW) Raman spectroscopy technique for real‐time in vivo assessment of adenomatous polyps during clinical colonoscopy. We have developed a fiber‐optic Raman endoscopic technique capable of simultaneously acquiring both the FP (i.e., 800–1800 cm^–1) and HW (i.e., 2800–3600 cm^–1) Raman spectra from colorectal tissue subsurface (<200 µm) for real‐time assessment of colorectal carcinogenesis. In vivo FP/HW Raman spectra were acquired from 50 patients with 17 colorectal polyps during clinical colonoscopy. Prominent Raman spectral differences (p < 0.001) were found between hyperplastic (n = 118 spectra), adenoma (n = 184 spectra) that could be attributed to changes in inter‐ and intra‐cellular proteins, lipids, DNA and water structures and conformations. Simultaneous FP/HW Raman endoscopy provides a diagnostic sensitivity of 90.9% and specificity of 83.3% for differentiating adenoma from hyperplastic polyps, which is superior to either the FP or HW Raman technique alone. This study shows that simultaneous FP/HW Raman spectroscopy technique has the potential to be a clinically powerful tool for improving early diagnosis of adenomatous polyps in vivo during colonoscopic examination.

     

Towards automated cancer screening: Label‐free classification of fixed cell samples using wavelength modulated Raman spectroscopy

The ability to provide quantitative, objective and automated pathological analysis would provide enormous benefits for national cancer screening programmes, in terms of both resource reduction and improved patient wellbeing. The move towards molecular pathology through spectroscopic methods shows great promise, but has been restricted by spectral quality, acquisition times and lack of direct clinical application. In this paper, we present the application of wavelength modulated Raman spectroscopy for the automated label‐ and fluorescence‐free classification of fixed squamous epithelial cells in suspension, such as those produced during a cervical smear test. Direct comparison with standard Raman spectroscopy shows marked improvement of sensitivity and specificity when considering both human papillomavirus (sensitivity +12.0%, specificity +5.3%) and transformation status (sensitivity +10.3%, specificity +11.1%). Studies on the impact of intracellular sampling location and storage effects suggest that wavelength modulated Raman spectroscopy is sufficiently robust to be used in fixed cell classification, but requires further investigations of potential sources of molecular variation in order to improve current clinical tools.      

Raman ChemLighter: Fiber optic Raman probe imaging in combination with augmented chemical reality

Raman spectroscopy using fiber optic probe combines non‐contacted and label‐free molecular fingerprinting with high mechanical flexibility for biomedical, clinical and industrial applications. Inherently, fiber optic Raman probes provide information from a single point only, and the acquisition of images is not straightforward. For many applications, it is highly crucial to determine the molecular distribution and provide imaging information of the sample. Here, we propose an approach for Raman imaging using a handheld fiber optic probe, which is built around computer vision–based assessment of positional information and simultaneous acquisition of spectroscopic information. By combining this implementation with real‐time data processing and analysis, it is possible to create not only fiber‐based Raman imaging but also an augmented chemical reality image of the molecular distribution of the sample surface in real‐time. We experimentally demonstrated that using our approach, it is possible to determine and to distinguish borders of different bimolecular compounds in a short time. Because the method can be transferred to other optical probes and other spectroscopic techniques, it is expected that the implementation will have a large impact for clinical, biomedical and industrial applications.      

In‐line monitoring of amino acids in mammalian cell cultures using raman spectroscopy and multivariate chemometrics models

The application of PAT for in‐line monitoring of biopharmaceutical manufacturing operations has a central role in developing more robust and consistent processes. Various spectroscopic techniques have been applied for collecting real‐time data from cell culture processes. Among these, Raman spectroscopy has been shown to have advantages over other spectroscopic techniques, especially in aqueous culture solutions. Measurements of several process parameters such as glucose, lactate, glutamine, glutamate, ammonium, osmolality and VCD using Raman‐based chemometrics models have been reported in literature. The application of Raman spectroscopy, coupled with calibration models for amino acid measurement in cell cultures, has been assessed. The developed models cover four amino acids important for cell growth and production: tyrosine, tryptophan, phenylalanine and methionine. The chemometrics models based on Raman spectroscopy data demonstrate the significant potential for the quantification of tyrosine, tryptophan and phenylalanine. The model for methionine would have to be further refined to improve quantification.     

Ex vivo detection of cadmium‐induced renal damage by using confocal Raman spectroscopy

Cadmium (Cd) is a toxic heavy metal which is harmful to environment and organisms. The reabsorption of Cd in kidney leads it to be the main damaged organ in animals under the Cd exposure. In this work, we applied confocal Raman spectroscopy to map the pathological changes in situ in normal and Cd‐exposed mice kidney. The renal tissue from Cd‐exposed group displayed a remarkable decreasing in the intensity of typical peaks related to mitochondria, DNA, proteins and lipids. On the contrary, the peaks of collagen in Cd‐exposed group elevated significantly. The components in each tissue were identified and distinguished by principal component analysis. Furthermore, all the biological investigations in this study were consistent with the Raman spectrum detection, which revealed the progression and degree of lesion induced by Cd. The confocal Raman spectroscopy provides a new perspective for in situ monitoring of substances changes in tissues, which exhibits more comprehensive understanding of the pathogenic mechanisms of heavy metals in molecular toxicology.     

Identification of carbapenem‐resistant Acinetobacter baumannii clones using infrared spectroscopy

In this work we assessed the discriminatory ability of Fourier‐transform Infrared Spectroscopy (FTIR) in 22 representative isolates from a collection of 318 carbapenem‐hydrolyzing class D β ‐lactamases (CHDL)‐producing Acinetobacter spp. (5 hospitals; 2001–2008) previously characterized by DNA‐based typing methods. FTIR spectra were acquired with a Bruker spectrometer and analyzed with support of several chemometric tools. The results showed that FTIR spectroscopy was able to distinguish the main CHDL‐producing Acinetobacter baumannii lineages causing infection in Portugal, the ST103 carrying bla_OXA‐58, ST98 carrying bla_OXA‐24/40and ST92 carrying bla_OXA‐23. Moreover, this study revealed distinctive phenotypic features of A. baumannii lineages causing infections that might justify different epidemic potential. Spectroscopy may arise as a low cost and easily to perform alternative for typing A. baumannii isolates. (© 2014 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Real‐time monitoring of antibody glycosylation site occupancy by in situ Raman spectroscopy during bioreactor CHO cell cultures

The glycosylation of therapeutic monoclonal antibodies (mAbs), a known critical quality attribute, is often greatly modified during the production process by animal cells. It is essential for biopharmaceutical industries to monitor and control this glycosylation. However, current glycosylation characterization techniques involve time‐ and labor‐intensive analyses, often carried out at the end of the culture when the product is already synthesized. This study proposes a novel methodology for real‐time monitoring of antibody glycosylation site occupancy using Raman spectroscopy. It was first observed in CHO cell batch culture that when low nutrient concentrations were reached, a decrease in mAb glycosylation was induced, which made it essential to rapidly detect this loss of product quality. By combining in situ Raman spectroscopy with chemometric tools, efficient prediction models were then developed for both glycosylated and nonglycosylated mAbs. By comparing variable importance in projection profiles of the prediction models, it was confirmed that Raman spectroscopy is a powerful method to distinguish extremely similar molecules, despite the high complexity of the culture medium. Finally, the Raman prediction models were used to monitor batch and feed‐harvest cultures in situ. For the first time, it was demonstrated that the concentrations of glycosylated and nonglycosylated mAbs could be successfully and simultaneously estimated in real time with high accuracy, including their sudden variations due to medium exchanges. Raman spectroscopy can thus be considered as a promising PAT tool for feedback process control dedicated to on‐line optimization of mAb quality. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:486–493, 2018     

Identification and characterization of bladder cancer by low‐resolution fiber‐optic Raman spectroscopy

Raman spectroscopy has been proved to be a promising diagnostic technique for various cancers detection. A major drawback for its clinical translation is the intrinsic weakness of Raman effects. Highly sensitive equipment and optimal measurement conditions are generally applied to overcome this drawback. However, these equipment are usually bulky, expensive and may also be easily influenced by surrounding environment. In this preliminary work, a low‐resolution fiber‐optic Raman sensing system is applied to evaluate the diagnostic potential of Raman spectroscopy to identify different bladder pathologies ex vivo. A total number of 262 spectra taken from 32 bladder specimens are included in this study. These spectra are categorized into 3 groups by histopathological analysis, namely normal bladder tissues, low‐grade bladder tumors and high‐grade bladder tumors. Principal component analysis fed artificial neural network are used to train a classification model for the spectral data with 10‐fold cross‐validation and an overall prediction accuracy of 93.1% is obtained. The sensitivities and specificities for normal bladder tissues, low‐grade bladder tumors and high‐grade bladder tumors are 88.5% and 95.1%, 90.3% and 98%, and 97.5% and 96.4%, respectively. These results demonstrate the potential of using a low‐resolution fiber‐optic Raman system for in vivo bladder cancer diagnosis.      

Chiroptical spectroscopy and metabolomics for blood‐based sensing of pancreatic cancer

To enable the early diagnosis of pancreatic cancer, the search for and definition of reliable biomarkers remain a subject of great interest, with the specificity and sensitivity of the currently used biomarkers being below the required values. We tested a novel diagnostic approach for pancreatic cancer based on the specific molecular signature of blood plasma components. To acquire more detailed structural information, structure‐sensitive chiroptical methods (electronic circular dichroism and Raman optical activity) were supplemented by conventional Raman and infrared spectroscopies. The obtained spectra were subsequently processed by linear discriminant analysis yielding high values of specificity and sensitivity. In addition, to monitor not only large biomolecules as potential biomarkers but also those of low molecular weight, we conducted an analysis of blood plasma samples by using metabolomics. The achieved results suggest a panel of promising biomarkers for a reliable detection of pancreatic cancer.     

Real‐time detection of single‐living pancreatic β‐cell by laser tweezers Raman spectroscopy: High glucose stimulation

Glucose acts as a β‐cell stimulus factor and leads to cellular responses that involve a large amount of biomolecule formation, relocation, and transformation. We hypothesize that information about these changes can be obtained in real‐time by laser tweezers Raman spectroscopy. To test this hypothesis, repeated measurements designs in accordance with the application of Raman spectroscopy detection were used in the current experiment. Single rat β‐cells were measured by Raman spectroscopy in 2.8 mmol/l glucose culture medium as a basal condition. After stimulation with high glucose (20 mmol/l), the same cells were measured continuously. Each cell was monitored over a total time span of 25 min, in 5 min intervals. During this period of time, cells were maintained at an appropriate temperature controlled by an automatic heater, to provide near‐physiological conditions. It was found that some significant spectral changes induced by glucose were taking place during the stimulation time course. The most noticeable changes were the increase of spectral intensity at the 1002, 1085, 1445, and 1655 cm^?1 peaks, mainly corresponding to protein and lipid. We speculate that these changes might have to do with β‐cell protein and lipid synthesis. Using laser tweezers Raman spectroscopy in combination with glucose stimulation, optical spectral information from rat β‐cells was received and analyzed. © 2010 Wiley Periodicals, Inc. Biopolymers 93: 587–594, 2010. This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com     

Determination of inclusion depth in ex vivo animal tissues using surface enhanced deep Raman spectroscopy

This work presents recent developments in spatially offset and transmission Raman spectroscopy for noninvasive detection and depth prediction of a single SERS inclusion located deep inside ex vivo biological tissues. The concept exploits the differential attenuation of Raman bands brought about by their different absorption due to tissue constituents enabling to predict the inclusion depth. Four different calibration models are tested and evaluated to predict the depth of surface enhanced Raman scattering labelled nanoparticles, within an up to 40 mm slab of porcine tissue. An external measurement carried out in transmission mode, with a noninvasively built model on the analysed sample, is shown to be insensitive to variations of the overall thickness of the tissue yielding an average root‐mean‐square error of prediction of 6.7%. The results pave the way for future noninvasive deep Raman spectroscopy in vivo enabling to localise cancer biomarkers for an early diagnosis of multiple diseases.      

Development of a visually guided Raman spectroscopy probe for cervical assessment during pregnancy

Preterm birth (PTB) is the leading cause of neonatal death, however, accurate prediction methods do not exist. Detection of early changes in the cervix, an organ that biochemically remodels to deliver the fetus, has potential to predict PTB risk. Researchers have employed light‐based methods to monitor biochemical changes in the cervix during pregnancy, however, these approaches required patients to undergo a speculum examination which many patients find uncomfortable and is not standard practice during prenatal care. Herein, a visually guided optical probe is presented that measures the cervix via introduction by bimanual examination, a procedure that is commonly performed during prenatal visits and labor for tactile monitoring of the cervix. The device incorporates a Raman spectroscopy probe for biochemical monitoring and a camera for visualizing measurement location to ensure it is void of cervical mucus and blood. This probe was tested in 15 patients receiving obstetric and gynecological care, and results acquired with and without a speculum revealed similar spectra, demonstrating that the visually guided probe conserved data quality. Additionally, the majority of patients reported reduced discomfort from the device. In summary, the visual guidance probe successfully measured the cervix while integrating with standard prenatal care, reducing a barrier in clinical translation.      

Raman spectroscopy for accurately characterizing biomolecular changes in androgen‐independent prostate cancer cells

Metastatic prostate cancer resistant to hormonal manipulation is considered the advanced stage of the disease and leads to most cancer‐related mortality. With new research focusing on modulating cancer growth, it is essential to understand the biochemical changes in cells that can then be exploited for drug discovery and for improving responsiveness to treatment. Raman spectroscopy has a high chemical specificity and can be used to detect and quantify molecular changes at the cellular level. Collection of large data sets generated from biological samples can be employed to form discriminatory algorithms for detection of subtle and early changes in cancer cells. The present study describes Raman finger printing of normal and metastatic hormone‐resistant prostate cancer cells including analyses with principal component analysis and linear discrimination. Amino acid‐specific signals were identified, especially loss of arginine band. Androgen‐resistant prostate cancer cells presented a higher content of phenylalanine, tyrosine, DNA and Amide III in comparison to PNT2 cells, which possessed greater amounts of L‐arginine and had a B conformation of DNA. The analysis utilized in this study could reliably differentiate the 2 cell lines (sensitivity 95%; specificity 88%).