Diagnosis of hepatitis C Virus (HCV) infection by antigen-capturing ELISA

Diagnosis and monitoring of hepatocellular carcinoma in Hepatitis C virus patients using attenuated total reflection Fourier transform infrared spectroscopy

BACKGROUND

Current diagnostic methods for assessment of hepatitis C virus related hepatocellular carcinoma and subsequent categorization of hepatocellular carcinoma into non-angio-invasive hepatocellular carcinoma and angio-invasive hepatocellular carcinoma, to establish appropriate treatment strategies, are costly, invasive and requires multiple screening steps. This demands alternative diagnostic approaches that are cost-effective, time-efficient, and minimally invasive, while maintaining their efficacy for screening of hepatitis c virus related hepatocellular carcinoma. In this study, we propose that attenuated total reflection Fourier transform infrared in conjunction with principal component analysis - linear discriminant analysis and support vector machine multivariate algorithms holds a potential as a sensitive tool for the detection of hepatitis C virus-related hepatocellular carcinoma and the subsequent categorization of hepatocellular carcinoma into non-angio-invasive hepatocellular carcinoma and angio-invasive hepatocellular carcinoma.

METHODS

Freeze-dried sera samples collected from 31 hepatitis c virus related hepatocellular carcinoma patients and 30 healthy individuals, were used to acquire mid-infrared absorbance spectra (3500-900 cm-1) using attenuated total reflection Fourier transform infrared. Chemometric machine learning techniques were utilized to build principal component analysis - linear discriminant analysis and support vector machine discriminant models for the spectral data of hepatocellular carcinoma patients and healthy individuals. Sensitivity, specificity, and external validation on blind samples were calculated.

RESULTS

Major variations were observed in the two spectral regions i.e., 3500-2800 and 1800-900 cm-1. IR spectral signatures of hepatocellular carcinoma were reliably different from healthy individuals. Principal component analysis - linear discriminant analysis and support vector machine models computed 100% accuracy for diagnosing hepatocellular carcinoma. To classify the non-angio-invasive hepatocellular carcinoma/ angio-invasive hepatocellular carcinoma status, diagnostic accuracy of 86.21% was achieved for principal component analysis - linear discriminant analysis. While the support vector machine showed a training accuracy of 98.28% and a cross-validation accuracy of 82.75%. External validation for support vector machine based classification observed 100% sensitivity and specificity for accurately classifying the freeze-dried sera samples for all categories.

CONCLUSIONS

We present the specific spectral signatures for non-angio-invasive hepatocellular carcinoma and angio-invasive hepatocellular carcinoma, which were prominently differentiated from healthy individuals. This study provides an initial insight into the potential of attenuated total reflection Fourier transform infrared to diagnose hepatitis C virus related hepatocellular carcinoma but also to further categorize into non-angio-invasive and angio-invasive hepatocellular carcinoma.

Effects of Lower Temperature on Expression and Biochemical Characteristics of HCV NS3 Antigen Recombinant Protein

The nonstructural antigen protein 3 of the hepatitis C virus (HCV NS3), commonly-used for HCV ELISA diagnosis, possesses protease and helicase activities. To prevent auto-degradation, a truncated NS3 protein was designed by removing the protease domain. Firstly, it was overexpressed in E. coli by IPTG induction under two different temperatures (25 and 37 °C), and purified using affinity chromatography to attain homogeneity above 90%. The molecular mass of purified protein was determined to be approx. 55 kDa. While lowering the temperature from 37 to 25 °C, the yield of the soluble fraction of HCV NS3 was increased from 4.15 to 11.1 mgL−1 culture, which also improved the antigenic activity and specificity. The protein stability was investigated after long-term storage (for 6 months at −20 °C) revealed no loss of activity, specificity, or antigenic efficacy. A thermal stability study on both freshly produced and stored HCV NS3 fractions at both temperatures showed that the unfolding curve profile properly obey the three-state unfolding mechanism. In the first transition phase, the midpoints of the thermal denaturation of fresh NS3 produced at 37 °C and 25 °C, and that produced after long-term storage at 37 °C and 25 °C, were 59.7 °C, 59.1 °C, 55.5 °C, and 57.8 °C, respectively. Microplates coated with the fresh NS3 produced at 25 °C or at 37 °C that were used for the HCV ELISA test and the diagnosis outcome were compared with two commercial kits—Abbott HCV EIA 2.0 and Ortho HCV EIA 3.0. Results indicated that the specificity of the HCV NS3 produced fresh at 25 °C was higher than that of the fresh one at 37 °C, hence showing potential for application in HCV ELISA diagnosis.

Quantitative analysis of human blood serum using vibrational spectroscopy

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State of the art of quantitative Vibrational Spectroscopic analysis of human blood serum is reviewed.

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Technical considerations for infrared absorption and Raman analysis are discussed.

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Quantitative analyses of Endogenous and Exogenous constituents are presented.

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The potential for clinical translation of spectroscopic serology is argued.

Analysis of bodily fluids using vibrational spectroscopy has attracted increasing attention in recent years. In particular, infrared spectroscopic screening of blood products, particularly blood serum, for disease diagnostics has been advanced considerably, attracting commercial interests. However, analyses requiring quantification of endogenous constituents or exogenous agents in blood are less well advanced. Recent advances towards this end are reviewed, focussing on infrared and Raman spectroscopic analyses of human blood serum. The importance of spectroscopic analysis in the native aqueous environment is highlighted, and the relative merits of infrared absorption versus Raman spectroscopy are considered, in this context. It is argued that Raman spectroscopic analysis is more suitable to quantitative analysis in liquid samples, and superior performance for quantification of high and low molecular weight components, is demonstrated. Applications for quantitation of viral loads, and therapeutic drug monitoring are also discussed.

Identification of new spectral signatures from hepatitis C virus infected human sera

Hepatitis C virus (HCV) infection is one of the leading causes of morbidity and mortality worldwide. Mortality linked with HCV infection can be lowered with effective and prompt diagnosis in early stages of infection. In this study potential of Raman spectroscopy to differentiate between healthy and HCV infected serum samples was investigated. Clear differences were observed in the Raman spectra of HCV infected and healthy sera samples. Using the analysis of variance (ANOVA) and t-test (p < 0.001) on Raman spectra of diseased and healthy samples, we observed eleven unique Raman bands at 676, 825, 853, 936, 1029, 1105, 1155, 1305, 1620, 1654 and 1757 cm^-1 associated with only HCV infected sera and have not been reported in earlier studies. In addition, six Raman bands at 556, 585, 716, 815, 1273 and 1142 cm^-1were observed in healthy sera only. Three Raman bands at 1330, 1526 and 1572 cm^-1 were observed in both type of samples but their intensity was drastically reduced in diseased samples. Various multivariate analysis techniques were employed to demonstrate the robustness of the results. We employed multivariate and unsupervised principal component analysis (PCA) in conjunction with supervised classification linear discriminant analysis (LDA), using ten-fold jackknife cross-validation, in order to develop effective diagnostic algorithm technique (PCA-LDA). Our PCA-LDA model yielded sufficient sensitivity and specificity i.e. correctly identified all infected samples included in this study. Ours results indicate that these unique Raman bands have the potential to be used as biomarkers for optical diagnosis of HCV infection.

High Sensitivity Bacillus thuringiensis Cry1Ac Protein Detections Using Fluorescein Diacetate Nanoparticles

A highly sensitive transgenic protein analysis method was proposed here based on fluorescein diacetate (FDA). First, FDA was prepared by the ball mill to harvest the nano-sized organic particles. Further examines showed that the FDA size can be controlled by the speed of centrifugation which can obtain FDA in well-distributed size. Cy3 antibody immobilization tests showed that the proteins can attach onto the FDA particles while keep bioactivities. FDA and Cry1Ac antibody immunoassay tests showed that when the FDA particle was in 150 nm, the linear range was 0.01 ng/L-30 μg/mL. And it has the lower detection limitation of 0.01 ng/L, which is 100 times more sensitive than the ELISA methods. These results indicate that the FDA related immunoassays are the promising approach in the transgenic analysis.