Surface-enhanced Raman spectroscopy for characterization of filtrates of blood serum samples from patients with tuberculosis obtained by 50 kDa filtration devices.
Ali Kamran, Abdul Naman, Muhammad Irfan Majeed, Haq Nawaz, Najah Alwadie, Noor Ul Huda, Umm-E- Habiba, Tania Tabussam, Aqsa Bano, Hawa Hajab, Rabeea Razaq, Ayesha Ashraf, Saima Aziz, Maria Asghar, Muhammad Imran
Author Information
Ali Kamran: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com. ORCID
Abdul Naman: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com.
Muhammad Irfan Majeed: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com. ORCID
Haq Nawaz: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com. ORCID
Najah Alwadie: Department of Physics, College of Science, Princess Nourah bint Abdulrahman University P. O. Box 84428 Riyadh 11671 Saudi Arabia nhalwadie@pnu.edu.sa.
Noor Ul Huda: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com.
Umm-E- Habiba: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com.
Tania Tabussam: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com. ORCID
Aqsa Bano: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com.
Hawa Hajab: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com.
Rabeea Razaq: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com.
Ayesha Ashraf: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com.
Saima Aziz: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com.
Maria Asghar: Department of Chemistry, University of Agriculture Faisalabad Faisalabad 38000 Pakistan irfan.majeed@uaf.edu.pk haqchemist@yahoo.com.
Muhammad Imran: Department of Chemistry, Faculty of Science, King Khalid University P. O. Box 9004 Abha 61413 Saudi Arabia. ORCID
The ability of surface-enhanced Raman spectroscopy (SERS) to generate spectroscopic fingerprints has made it an emerging tool for biomedical applications. The objective of this study is to confirm the potential use of Raman spectroscopy for early disease diagnosis based on blood serum. In this study, a total of sixty blood serum samples, consisting of forty from diseased patients and twenty (controls) from healthy individuals, was used. Because disease biomarkers, found in the lower molecular weight fraction, are suppressed by higher molecular weight proteins, 50 kDa Amicon ultrafiltration centrifugation devices were used to produce two fractions from whole blood serum consisting of a filtrate, which is a low molecular weight fraction, and a residue, which is a high molecular weight fraction. These fractions were then analyzed, and their SERS spectral data were compared with those of healthy fractions. The SERS technique was utilized on blood serum, filtrate and residue of patients with tuberculosis to identify characteristic SERS spectral features associated with the development of disease, which can be used to differentiate them from healthy samples using silver nanoparticles as a SERS substrate. For further analysis, the effective chemometric technique of principal component analysis (PCA) was used to qualitatively differentiate all the analyzed samples based on their SERS spectral features. Partial least squares discriminant analysis (PLS-DA) accurately classified the filtrate portions of healthy and tuberculosis samples with 97% accuracy, 97% specificity, 98% sensitivity, and an area under the receiver operating characteristic (AUROC) curve of 0.74.
