Surface-enhanced Raman spectral analysis for comparison of PCR products of hepatitis B and hepatitis C

Fatima Batool; Haq Nawaz; Muhammad Irfan Majeed; Nosheen Rashid; Saba Bashir; Saira Bano; Fatima Tahir; Anwar Ul Haq; Mudassar Saleem; Muhammad Zaman Nawaz; Farakh Almas; Imran Amin

doi:10.1016/j.pdpdt.2021.102440

Surface-enhanced Raman spectral analysis for comparison of PCR products of hepatitis B and hepatitis C

Photodiagnosis Photodyn Ther. 2021 Sep:35:102440. doi: 10.1016/j.pdpdt.2021.102440. Epub 2021 Jul 16.

Authors

Affiliations

¹ Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan.
² Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan. Electronic address: irfan.majeed@uaf.edu.pk.
³ Institute of Microbiology, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan.
⁴ Department of Chemistry, University of Central Punjab, Faisalabad Campus, Faisalabad, Pakistan.

PMID: 34280557
DOI: 10.1016/j.pdpdt.2021.102440

Abstract

Background: Surface-enhanced Raman spectroscopy is a reliable tool for identification and differentiation of two diseases showing similar symptoms, hepatitis B (HBV) and hepatitis C (HCV).

Objectives: To develop a polymerase chain reaction technique (PCR) based SERS technique for differentiation of two human pathological conditions sharing the same symptoms using multivariate data analysis techniques e.g. principle component analysis (PCA) and partial least square discriminate analysis (PLS-DA).

Methods: PCR products of HBV and HCV were differentiated by SERS using silver nanoparticles (AgNPs) as a SERS substrate. For this analysis, PCR products of both the diseases with predetermined viral loads were collected and analyzed under SERS instrument and unique SERS spectra of HBV and HCV was compared showing many differences at various points. Diseased classes of HBV and HCV and their negative control classes (viral load less than 1) were compared. PCR products of true healthy DNA and RNA were also compared, which were significantly separated. Moreover, SERS data was analyzed using multivariate data analysis techniques including principle component analysis (PCA) and partial least square discriminate analysis (PLS-DA) and differences were so prominent to observe.

Results: SERS spectral data of HBV and HCV showed clear differences and were significantly separated using PCA. Negative control samples of both disorders and their true healthy samples of DNA and RNA were separated according to 1^st principle component. By analyzing data using partial least square discriminate analysis, differentiation of two disease classes was considered more valid with sensitivity, specificity and accuracy value of 96%, 94% and 98% respectively. Value of area under curve (AUROC) was 0.7527.

Conclusion: SERS can be employed for identification and comparison of two human pathological conditions sharing the same symptomology.

Keywords: Disease diagnosis; Hepatitis B; Hepatitis C; Multivariate data analysis; Surface enhanced Raman Spectroscopy.

MeSH terms

Hepatitis B* / diagnosis
Hepatitis C* / diagnosis
Humans
Metal Nanoparticles*
Photochemotherapy* / methods
Photosensitizing Agents
Polymerase Chain Reaction
Silver
Spectrum Analysis, Raman

Substances

Photosensitizing Agents
Silver