Surface-enhanced Raman spectroscopy of polymerase chain reaction (PCR) products of Rifampin resistant and susceptible tuberculosis patients

Dastgir, Ghulam; Majeed, Muhammad Irfan; Nawaz, Haq; Rashid, Nosheen; Raza, Ali; Ali, Muhammad; Shakeel, Muhammad; Javed, Mahrosh; Ehsan, Usama; Ishtiaq, Shazra; Fatima, Rida; Abdulraheem, Aliza

doi:10.1016/j.pdpdt.2022.102758

Cited by 19 publications

(16 citation statements)

References 45 publications

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“…The 3060–3090 cm –1 peaks assigned to the stretch vibrations of heteroaromatic groups (Figure S10), the 2882, 2933, and 3060 cm –1 peaks assigned to the C–H stretch vibrations and the 1450 cm –1 peak assigned to CH 2 bending vibration associated with proteins and fats ,− and are strongly included in the spectra of all bacterial species. Ring breathing and ring stretching vibration modes associated with the five main nucleobases (adenine, guanine, thymine, uracil, and cytosine) in the nucleic acids are observed at 673, 785, and 1580 cm –1 . ,− Amino acids such as tryptophan (C–H bending peak at 1339 cm –1 ) and phenylalanine (the C–C aromatic ring breathing mode at 1004 cm –1 ) and typical amide I and amide III bands of proteins are also observed at 1230–1247 and 1660 cm –1 . ,− Each bacteria species showed multiple complex peaks some of which seem to be unique (Figure and Table S6). It should be noted here that the differences in all these spectra are due to the Ag–Cu x O nanostructures because the spectra of bacteria collected on a glass slide look similar (Figure S11).…”

Section: Resultsmentioning

confidence: 99%

Disintegration and Machine-Learning-Assisted Identification of Bacteria on Antimicrobial and Plasmonic Ag–Cu_xO Nanostructures

Şahin

Çamdal

Sahin

et al. 2023

ACS Appl. Mater. Interfaces

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Bacteria cause many common infections and are the culprit of many outbreaks throughout history that have led to the loss of millions of lives. Contamination of inanimate surfaces in clinics, the food chain, and the environment poses a significant threat to humanity, with the increase in antimicrobial resistance exacerbating the issue. Two key strategies to address this issue are antibacterial coatings and effective detection of bacterial contamination. In this study, we present the formation of antimicrobial and plasmonic surfaces based on Ag–Cu x O nanostructures using green synthesis methods and low-cost paper substrates. The fabricated nanostructured surfaces exhibit excellent bactericidal efficiency and high surface-enhanced Raman scattering (SERS) activity. The Cu x O ensures outstanding and rapid antibacterial activity within 30 min, with a rate of >99.99% against typical Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus bacteria. The plasmonic Ag nanoparticles facilitate the electromagnetic enhancement of Raman scattering and enables rapid, label-free, and sensitive identification of bacteria at a concentration as low as 103 cfu/mL. The detection of different strains at this low concentration is attributed to the leaching of the intracellular components of the bacteria caused by the nanostructures. Additionally, SERS is coupled with machine learning algorithms for the automated identification of bacteria with an accuracy that exceeds 96%. The proposed strategy achieves effective prevention of bacterial contamination and accurate identification of the bacteria on the same material platform by using sustainable and low-cost materials.

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Section: Resultsmentioning

confidence: 99%

Disintegration and Machine-Learning-Assisted Identification of Bacteria on Antimicrobial and Plasmonic Ag–Cu_xO Nanostructures

Şahin

Çamdal

Sahin

et al. 2023

ACS Appl. Mater. Interfaces

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“…[16][17][18][19] SERS coupled with PCR (polymerase chain reaction) utilizes amplication of the analyte to detect single base changes in DNA. 20 Magnetic lateral ow immunoassays utilize magnetic nanoparticles (MNPs) as the detection label instead of the traditional gold or latex beads to facilitate the enrichment of the analytes. These MNPs can be detected and measured using external devices, enabling the creation of immunochromatographic tests that can produce quantitative results (Table 1).…”

Section: Comparison Of Different Lfa Designsmentioning

confidence: 99%

New technologies and reagents in lateral flow assay (LFA) designs for enhancing accuracy and sensitivity

Dey¹,

Iftesum²,

Devireddy³

et al. 2023

Anal. Methods

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“…In addition, integration of machine learning can make SR a more effective TB screening method [71]. A recent study on developing PCR-based SERS has reported it can rapidly distinguish TB positive rifampicin-resistant and TB positive rifampicin-susceptible patients [72].…”

Section: Raman Spectroscopymentioning

confidence: 99%

Tuberculosis Diagnosis: Updates and Challenges

Shivakumar¹,

Shettigar²

2023

Bacterial Infectious Diseases Annual Volume 2023

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Tuberculosis (TB) is caused by a single infectious agent, Mycobacterium tuberculosis, and a public health concern due to increased cases of drug-resistance and high mortality rates. Rapid identification of tuberculosis is necessary for its early treatment and to prevent the emergence of drug-resistant strains. For effective management of patients, rapid, cost-effective, and point-of-care (POC) diagnostic methods are required. The commonly used screening and identification methods are clinical examination, radiography, sputum smear microscopy, culture method, serological method, and tuberculin skin test. In addition, several molecular methods such as NAAT based GeneXpert, loop-mediated isothermal amplification (LAMP), line probe assay (LPA), whole genome sequencing (WGS) and other non-invasive methods of lateral flow urine lipoarabinomannan assay (LF-LAM) and eNose assays are developed. Sputum smear microscopy, Xpert MTB/RIF, and LED-Fluorescence microscopy (LED-FM) are the preferred methods to use in peripheral laboratories. The non-invasive methods of tuberculosis diagnosis are more beneficial in patients from whom collecting sputum sample is difficult particularly in children and HIV co-infected patients. Molecular methods can simultaneously identify the pathogen, M. tuberculosis, and mutations in drug-resistance genes. Even though, many advanced methods are currently available, accurate and affordable diagnostic method for tuberculosis is still challenging. Here, we review and highlight the uses and challenges of currently available conventional and advanced diagnostic methods of tuberculosis screening and diagnosis.

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Surface-enhanced Raman spectroscopy of polymerase chain reaction (PCR) products of Rifampin resistant and susceptible tuberculosis patients

Cited by 19 publications

References 45 publications

Disintegration and Machine-Learning-Assisted Identification of Bacteria on Antimicrobial and Plasmonic Ag–Cu_xO Nanostructures

Disintegration and Machine-Learning-Assisted Identification of Bacteria on Antimicrobial and Plasmonic Ag–Cu_xO Nanostructures

New technologies and reagents in lateral flow assay (LFA) designs for enhancing accuracy and sensitivity

Tuberculosis Diagnosis: Updates and Challenges

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Surface-enhanced Raman spectroscopy of polymerase chain reaction (PCR) products of Rifampin resistant and susceptible tuberculosis patients

Cited by 19 publications

References 45 publications

Disintegration and Machine-Learning-Assisted Identification of Bacteria on Antimicrobial and Plasmonic Ag–CuxO Nanostructures

Disintegration and Machine-Learning-Assisted Identification of Bacteria on Antimicrobial and Plasmonic Ag–CuxO Nanostructures

New technologies and reagents in lateral flow assay (LFA) designs for enhancing accuracy and sensitivity

Tuberculosis Diagnosis: Updates and Challenges

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Product

Resources

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Disintegration and Machine-Learning-Assisted Identification of Bacteria on Antimicrobial and Plasmonic Ag–Cu_xO Nanostructures

Disintegration and Machine-Learning-Assisted Identification of Bacteria on Antimicrobial and Plasmonic Ag–Cu_xO Nanostructures