Enhancement of Surface-Enhanced Raman Spectroscopy for Bacterial Characterization Using Functionalized Silver Nanoparticles

Surface-enhanced Raman Spectroscopy (SERS) has gained considerable interest as an effective method for bacterial detection owing to its exceptional sensitivity and ability to identify bacterial species at minimal concentrations. Using silver nanoparticles (AgNPs) to improve Raman signals has demonstrated significant potential for advancing bacterial characterization in clinical and environmental contexts. Nonetheless, challenges persist in enhancing SERS for intricate microbial settings such as biofilms and heterogeneous bacterial communities. This study aimed to examine the effect of functionalized AgNPs on augmenting SERS for bacterial detection, emphasizing strengthening the method's sensitivity and selectivity for bacterial identification in intricate microbiological samples. This laboratory experiment used AgNPs functionalized with biomolecular ligands to amplify the Raman signal of several bacterial strains, including Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Streptococcus pneumoniae. The study conducted at University of Agriculture Faisalabad, Punjab, Pakistan. The study also used SERS spectroscopy to quantify the signal enhancement. At the same time, statistical methods, including One-Way ANOVA and Tukey's HSD test, were employed to investigate the differences in SERS intensities between bacterial strains with and without AgNPs. The findings indicated that functionalized AgNPs markedly improved the SERS signal intensity across all tested bacterial strains, yielding a 30% augmentation in Raman signal intensity. The SERS enhancement factor varied among the bacterial strains. S. aureus showed the highest enhancement factor, but the difference across strains is quite small, suggesting similar levels of enhancement. Statistical analysis validated that the augmented SERS signals were substantial (p < 0.05), and the AgNP functionalization facilitated enhanced bacterial detection sensitivity. These data indicate that AgNP-based SERS is an effective strategy for bacterial detection, offering enhanced sensitivity and selectivity for identifying bacterial pathogens in complicated environments. The research emphasizes the potential of employing functionalized silver nanoparticles to enhance fast microbial detection in clinical and environmental contexts.

Authors

Institutions

Publication Details

Journal
Indus journal of bioscience research.
Published
2025-04-15
DOI
https://doi.org/10.70749/ijbr.v3i4.1064
Primary Topic
Spectroscopy Techniques in Biomedical and Chemical Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancement of Surface-Enhanced Raman Spectroscopy for Bacterial Characterization Using Functionalized Silver Nanoparticles

Sadia Saleem, Umair Ahmed, Hasan B. Alam, M. Aslam Siddiqi et al.
Indus journal of bioscience research.
Spectroscopy Techniques in Biomedical and Chemical Research
article

Enhancement of Surface-Enhanced Raman Spectroscopy for Bacterial Characterization Using Functionalized Silver Nanoparticles

Sadia Saleem, Umair Ahmed, Hasan B. Alam, M. Aslam Siddiqi, Farhana Farhana, Rabeea Razaq, Jahangir Khan, A. Rehmat, A Batool, Hafiz Misbah Ud Din
article en

Abstract

Surface-enhanced Raman Spectroscopy (SERS) has gained considerable interest as an effective method for bacterial detection owing to its exceptional sensitivity and ability to identify bacterial species at minimal concentrations. Using silver nanoparticles (AgNPs) to improve Raman signals has demonstrated significant potential for advancing bacterial characterization in clinical and environmental contexts. Nonetheless, challenges persist in enhancing SERS for intricate microbial settings such as biofilms and heterogeneous bacterial communities. This study aimed to examine the effect of functionalized AgNPs on augmenting SERS for bacterial detection, emphasizing strengthening the method's sensitivity and selectivity for bacterial identification in intricate microbiological samples. This laboratory experiment used AgNPs functionalized with biomolecular ligands to amplify the Raman signal of several bacterial strains, including Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Streptococcus pneumoniae. The study conducted at University of Agriculture Faisalabad, Punjab, Pakistan. The study also used SERS spectroscopy to quantify the signal enhancement. At the same time, statistical methods, including One-Way ANOVA and Tukey's HSD test, were employed to investigate the differences in SERS intensities between bacterial strains with and without AgNPs. The findings indicated that functionalized AgNPs markedly improved the SERS signal intensity across all tested bacterial strains, yielding a 30% augmentation in Raman signal intensity. The SERS enhancement factor varied among the bacterial strains. S. aureus showed the highest enhancement factor, but the difference across strains is quite small, suggesting similar levels of enhancement. Statistical analysis validated that the augmented SERS signals were substantial (p < 0.05), and the AgNP functionalization facilitated enhanced bacterial detection sensitivity. These data indicate that AgNP-based SERS is an effective strategy for bacterial detection, offering enhanced sensitivity and selectivity for identifying bacterial pathogens in complicated environments. The research emphasizes the potential of employing functionalized silver nanoparticles to enhance fast microbial detection in clinical and environmental contexts.

Indus journal of bioscience research.Vol. 3(4)
Quaid-i-Azam University (PK), NED University of Engineering and Technology (PK), Islamia University of Bahawalpur (PK), Government College University, Faisalabad (PK), Superior University (PK), University of Agriculture Faisalabad (PK), University of Veterinary and Animal Sciences (PK)
Openalex Percentile: Top 93%
Spectroscopy Techniques in Biomedical and Chemical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.