Biochemical Analysis of Leukocytes after In Vitro and In Vivo Activation with Bacterial and Fungal Pathogens Using Raman Spectroscopy.
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ABSTRACT:
SUBMITTER: Pistiki A
PROVIDER: S-EPMC8508974 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:The cervix must undergo significant biochemical remodeling to allow for successful parturition. This process is not fully understood, especially in instances of spontaneous preterm birth. In vivo Raman spectroscopy is an optical technique that can be used to investigate the biochemical composition of tissue longitudinally and noninvasively in human beings, and has been utilized to measure physiology and disease states in a variety of medical applications. OBJECTIVE:The purpose of this study is to measure in vivo Raman spectra of the cervix throughout pregnancy in women, and to identify biochemical markers that change with the preparation for delivery and postpartum repair. STUDY DESIGN:In all, 68 healthy pregnant women were recruited. Raman spectra were measured from the cervix of each patient monthly in the first and second trimesters, weekly in the third trimester, and at the 6-week postpartum visit. Raman spectra were measured using an in vivo Raman system with an optical fiber probe to excite the tissue with 785 nm light. A spectral model was developed to highlight spectral regions that undergo the most changes throughout pregnancy, which were subsequently used for identifying Raman peaks for further analysis. These peaks were analyzed longitudinally to determine if they underwent significant changes over the course of pregnancy (P < .05). Finally, 6 individual components that comprise key biochemical constituents of the human cervix were measured to extract their contributions in spectral changes throughout pregnancy using a linear combination method. Patient factors including body mass index and parity were included as variables in these analyses. RESULTS:Raman peaks indicative of extracellular matrix proteins (1248 and 1254 cm-1) significantly decreased (P < .05), while peaks corresponding to blood (1233 and 1563 cm-1) significantly increased (P < .0005) in a linear manner throughout pregnancy. In the postpartum cervix, significant increases in peaks corresponding to actin (1003, 1339, and 1657 cm-1) and cholesterol (1447 cm-1) were observed when compared to late gestation, while signatures from blood significantly decreased. Postpartum actin signals were significantly higher than early pregnancy, whereas extracellular matrix proteins and water signals were significantly lower than early weeks of gestation. Parity had a significant effect on blood and extracellular matrix protein signals, with nulliparous patients having significant increases in blood signals throughout pregnancy, and higher extracellular matrix protein signals in early pregnancy compared to patients with prior pregnancies. Body mass index significantly affected actin signal contribution, with low body mass index patients showing decreasing actin contribution throughout pregnancy and high body mass index patients demonstrating increasing actin signals. CONCLUSION:Raman spectroscopy was successfully used to biochemically monitor cervical remodeling in pregnant women during prenatal visits. This foundational study has demonstrated sensitivity to known biochemical dynamics that occur during cervical remodeling, and identified patient variables that have significant effects on Raman spectra throughout pregnancy. Raman spectroscopy has the potential to improve our understanding of cervical maturation, and be used as a noninvasive preterm birth risk assessment tool to reduce the incidence, morbidity, and mortality caused by preterm birth.
| S-EPMC5916496 | biostudies-literature
Project description:Diagnosis of intraocular lymphoma is difficult. Among the hurdles in the diagnosis are the variety of reactive inflammatory and ischemic changes among intraocular lymphoma patients. Thus, a novel diagnostic method is desired such that lymphoma cells can be distinguished by the signals intrinsic to the cells, not by those from the surrounding tissues with reactive changes. Raman spectroscopy is a technique that can detect intrinsic signals from each cell. Therefore, Raman spectroscopy is a good candidate for an intraocular evaluation technology that could contribute to improve the diagnosis of intraocular lymphoma. In this study, we tested whether the intrinsic Raman signals from malignant lymphoma cells, in the absence of surrounding tissue, were sufficient for the discrimination of malignant lymphoma cells from leukocytes. We acquired spectra from dissociated lymphoma cells, along with spectra from normal B cells and other leukocytes involved in intraocular inflammatory diseases. We analysed the spectra using principal component analyses and quadratic discriminant analyses. We found that Raman spectra from dissociated cells without confounding tissues showed high discriminating ability, regardless of the variation due to day-to-day differences and donor differences. The present study demonstrates the possible effectiveness of Raman spectroscopy as a tool for intraocular evaluation.
| S-EPMC7519070 | biostudies-literature
Project description:(1) Background: surface-enhanced Raman spectroscopy (SERS) is a novel method for bacteria identification. However, reported applications of SERS in clinical diagnosis are limited. In this study, we used cylindrical SERS chips to detect urine pathogens in urinary tract infection (UTI) patients. (2) Methods: Urine samples were retrieved from 108 UTI patients. A 10 mL urine sample was sent to conventional bacterial culture as a reference. Another 10 mL urine sample was loaded on a SERS chip for bacteria identification and antibiotic susceptibility. We concentrated the urine specimen if the intensity of the Raman spectrum required enhancement. The resulting Raman spectrum was analyzed by a recognition software to compare with spectrum-form reference bacteria and was further confirmed by principal component analysis (PCA). (3) Results: There were 97 samples with single bacteria species identified by conventional urine culture and, among them, 93 can be successfully identified by using SERS without sample concentration. There were four samples that needed concentration for bacteria identification. Antibiotic susceptibility can also be found by SERS. There were seven mixed flora infections found by conventional culture, which can only be identified by the PCA method. (4) Conclusions: SERS can be used in the diagnosis of urinary tract infection with the aid of the recognition software and PCA.
| S-EPMC6321215 | biostudies-literature
Project description:We describe a method for direct, quantitative, in vivo lipid profiling of oil-producing microalgae using single-cell laser-trapping Raman spectroscopy. This approach is demonstrated in the quantitative determination of the degree of unsaturation and transition temperatures of constituent lipids within microalgae. These properties are important markers for determining engine compatibility and performance metrics of algal biodiesel. We show that these factors can be directly measured from a single living microalgal cell held in place with an optical trap while simultaneously collecting Raman data. Cellular response to different growth conditions is monitored in real time. Our approach circumvents the need for lipid extraction and analysis that is both slow and invasive. Furthermore, this technique yields real-time chemical information in a label-free manner, thus eliminating the limitations of impermeability, toxicity, and specificity of the fluorescent probes common in currently used protocols. Although the single-cell Raman spectroscopy demonstrated here is focused on the study of the microalgal lipids with biofuel applications, the analytical capability and quantitation algorithms demonstrated are applicable to many different organisms and should prove useful for a diverse range of applications in lipidomics.
| S-EPMC3048102 | biostudies-literature
Project description:Rice (Oryza sativa) is the primary crop for nearly half of the world's population. Groundwater in many rice-growing parts of the world often has elevated levels of arsenite and arsenate. At the same time, rice can accumulate up to 20 times more arsenic compared to other staple crops. This places an enormous amount of people at risk of chronic arsenic poisoning. In this study, we investigated whether Raman spectroscopy (RS) could be used to diagnose arsenic toxicity in rice based on biochemical changes that were induced by arsenic accumulation. We modeled arsenite and arsenate stresses in four different rice cultivars grown in hydroponics over a nine-day window. Our results demonstrate that Raman spectra acquired from rice leaves, coupled with partial least squares-discriminant analysis, enabled accurate detection and identification of arsenic stress with approximately 89% accuracy. We also performed high-performance liquid chromatography (HPLC)-analysis of rice leaves to identify the key molecular analytes sensed by RS in confirming arsenic poisoning. We found that RS primarily detected a decrease in the concentration of lutein and an increase in the concentration of vanillic and ferulic acids due to the accumulation of arsenite and arsenate in rice. This showed that these molecules are detectable indicators of biochemical response to arsenic accumulation. Finally, a cross-correlation of RS with HPLC and ICP-MS demonstrated RS's potential for a label-free, non-invasive, and non-destructive quantification of arsenic accumulation in rice.
| S-EPMC10999542 | biostudies-literature
Project description:We use a 785 nm shifted excitation Raman difference (SERDS) technique to measure the Raman spectra of the conidia of 10 mold species of especial toxicological, medical, and industrial importance, including Stachybotrys chartarum, Penicillium chrysogenum, Aspergillus fumigatus, Aspergillus flavus, Aspergillus oryzae, Aspergillus niger, and others. We find that both the pure Raman and fluorescence signals support the hypothesis that for an excitation wavelength of 785 nm the Raman signal originates from the melanin pigments bound within the cell wall of the conidium. In addition, the major features of the pure Raman spectra group into profiles that we hypothesize may be due to differences in the complex melanin biosynthesis pathways. We then combine the Raman spectral data with neural network models to predict species classification with an accuracy above 99%. Finally, the Raman spectral data of all species investigated is made freely available for download and use.
| S-EPMC7682877 | biostudies-literature
Project description:BackgroundBiochemical cervical change during labor is not well understood, in part, because of a dearth of technologies capable of safely probing the pregnant cervix in vivo. The need for such a technology is 2-fold: (1) to gain a mechanistic understanding of the cervical ripening and dilation process and (2) to provide an objective method for evaluating the cervical state to guide clinical decision-making. Raman spectroscopy demonstrates the potential to meet this need, as it is a noninvasive optical technique that can sensitively detect alterations in tissue components, such as extracellular matrix proteins, lipids, nucleic acids, and blood, which have been previously established to change during the cervical remodeling process.ObjectiveWe sought to demonstrate that Raman spectroscopy can longitudinally monitor biochemical changes in the laboring cervix to identify spectral markers of impending parturition.Study designOverall, 30 pregnant participants undergoing either spontaneous or induced labor were recruited. The Raman spectra were acquired in vivo at 4-hour intervals throughout labor until rupture of membranes using a Raman system with a fiber-optic probe. Linear mixed-effects models were used to determine significant (P<.05) changes in peak intensities or peak ratios as a function of time to delivery in the study population. A nonnegative least-squares biochemical model was used to extract the changing contributions of specific molecule classes over time.ResultsWe detected multiple biochemical changes during labor, including (1) significant decreases in Raman spectral features associated with collagen and other extracellular matrix proteins (P=.0054) attributed to collagen dispersion, (2) an increase in spectral features associated with blood (P=.0372), and (3) an increase in features indicative of lipid-based molecules (P=.0273). The nonnegative least-squares model revealed a decrease in collagen contribution with time to delivery, an increase in blood contribution, and a change in lipid contribution.ConclusionOur findings have demonstrated that in vivo Raman spectroscopy is sensitive to multiple biochemical remodeling changes in the cervix during labor. Furthermore, in vivo Raman spectroscopy may be a valuable noninvasive tool for objectively evaluating the cervix to potentially guide clinical management of labor.
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Project description:Osteoarthritis (OA) is the most common rheumatic disease, characterized by progressive articular cartilage degradation. Raman spectroscopy (RS) has been recently proposed as a label-free tool to detect molecular changes in musculoskeletal tissues. We used cartilage samples derived from human femoral heads to perform an ex vivo study of different Raman signals and ratios, related to major and minor molecular components of articular cartilage, hereby proposed as candidate optical biomarkers for OA. Validation was performed against the radiological Kellgren-Lawrence (K-L) grading system, as a gold standard, and cross-validated against sulfated glycosaminoglycans (sGAGs) and total collagens (Hyp) biochemical contents. Our results showed a significant decrease in sGAGs (SGAGs, A1063 cm-1/A1004 cm-1) and proteoglycans (PGs, A1375 cm-1/A1004 cm-1) and a significant increase in collagen disorganization (ColD/F, A1245 cm-1/A1270 cm-1), with OA severity. These were correlated with sGAGs or Hyp contents, respectively. Moreover, the SGAGs/HA ratio (A1063 cm-1/A960 cm-1), representing a functional matrix, rich in proteoglycans, to a mineralized matrix-hydroxyapatite (HA), was significantly lower in OA cartilage (K-L I vs. III-IV, p < 0.05), whilst the mineralized to collagenous matrix ratio (HA/Col, A960 cm-1/A920 cm-1) increased, being correlated with K-L. OA samples showed signs of tissue mineralization, supported by the presence of calcium crystals-related signals, such as phosphate, carbonate, and calcium pyrophosphate dihydrate (MGP, A960 cm-1/A1004 cm-1, MGC, A1070 cm-1/A1004 cm-1 and A1050 cm-1/A1004 cm-1). Finally, we observed an increase in lipids ratio (IL, A1450 cm-1/A1670 cm-1) with OA severity. As a conclusion, we have described the molecular fingerprint of hip cartilage, validating a panel of optical biomarkers and the potential of RS as a complementary diagnostic tool for OA.
| S-EPMC8003208 | biostudies-literature
Project description:Coffee endophytes have been studied for almost 74 years, and several studies have demonstrated coffee-endophytic fungi with antibacterial and antifungal potential for human and plant pathogens. In this study, we isolated and identified a total of 235 strains of endophytic fungi from coffee leaf tissues collected in four coffee plantations in Pu'er city, Yunnan province, China. Molecular identification was carried out using maximum likelihood phylogenetic analysis of nuclear ribosomal internal transcribed spacer (ITS1-5.8S rDNA-ITS2) sequences, while the colonization rate and the isolation frequency were also calculated. Two pathogenic fungi (Alternaria alternata and Penicillium digitatum) and two pathogenic bacteria (Pseudomonas syringae and Salmonella enterica subsp. enterica) were used for screening the antagonistic activities of 61 strains of coffee-endophytic fungi by a dual-culture test assay while maximum likelihood phylogenetic analysis confirmed their natural classification. This is the first study of coffee-leaf-endophytic fungal diversity in China, and the results revealed that coffee-endophytic fungi from this study belong to the Ascomycota, distributed among two classes, 10 orders, and 17 families. Concurrently, endophytic fungi isolates distributed in Arthrinium, Biscogniauxia, Daldinia, Diaporthe, and Nigrospora showed strong antagonistic activities against the pathogens. For the pathogens Alternaria alternata and Pseudomonas syringae, Nigrospora XCE-7 showed the best inhibitory effects with inhibition rates of 71.76% and 61.11%, respectively. For the pathogen Penicillium digitatum, Daldinia ME-9 showed the best inhibitory effect with a 74.67% inhibition rate, while Biscogniauxia PTE-7 and Daldinia T5E-1-3 showed the best inhibitory effect with a rate of 60.42% against the pathogen Salmonella enterica subsp. enterica. Overall, our study shows the diversity of coffee endophytes in four coffee-growing areas in Pu'er city, Yunnan province, China, and their potential use as biological control agents against two fungal and two bacterial pathogens.
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Project description:Oleaginous filamentous fungi can accumulate large amount of cellular lipids and biopolymers and pigments and potentially serve as a major source of biochemicals for food, feed, chemical, pharmaceutical, and transport industries. We assessed suitability of Fourier transform (FT) Raman spectroscopy for screening and process monitoring of filamentous fungi in biotechnology. Six Mucoromycota strains were cultivated in microbioreactors under six growth conditions (three phosphate concentrations in the presence and absence of calcium). FT-Raman and FT-infrared (FTIR) spectroscopic data was assessed in respect to reference analyses of lipids, phosphorus, and carotenoids by using principal component analysis (PCA), multiblock or consensus PCA, partial least square regression (PLSR), and analysis of spectral variation due to different design factors by an ANOVA model. All main chemical biomass constituents were detected by FT-Raman spectroscopy, including lipids, proteins, cell wall carbohydrates, and polyphosphates, and carotenoids. FT-Raman spectra clearly show the effect of growth conditions on fungal biomass. PLSR models with high coefficients of determination (0.83-0.94) and low error (approximately 8%) for quantitative determination of total lipids, phosphates, and carotenoids were established. FT-Raman spectroscopy showed great potential for chemical analysis of biomass of oleaginous filamentous fungi. The study demonstrates that FT-Raman and FTIR spectroscopies provide complementary information on main fungal biomass constituents.
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