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Advanced Biosensor for Detecting Ampicillin

Given the widespread use of ampicillin (AMP) and the increasing prevalence of ampicillin-resistant bacteria, detecting AMP is vital for managing antibiotic resistance effectively. In a recent article in Scientific Reports, researchers from Vietnam have introduced a proof-of-concept for a sensor that detects AMP with exceptional sensitivity and selectivity. This breakthrough lays the groundwork for a straightforward yet robust biosensing platform.

Advanced Biosensor for Detecting Ampicillin
The schematic to illustrate the working mechanism of PL detection of proposed sensors. Image Credit:


Detecting antibiotics is important across various sectors due to its implications for medical diagnostics, environmental safety, agriculture, and food security. However, detecting low concentrations of ampicillin in complex matrices presents a challenge due to potential interference from other substances and the need for high sensitivity and specificity.

Traditional methods like High-Performance Liquid Chromatography (HPLC), Liquid Chromatography-Mass Spectrometry (LC–MS), Enzyme-Linked Immunosorbent Assay (ELISA), and Microbial Assays have traditionally been used for detecting specific substances but often involve complex equipment and are not always suitable for real-time or on-site analysis.

To overcome these challenges, researchers are now exploring biosensors that utilize nanomaterials and micromaterials. These innovative sensors offer high specificity and sensitivity, along with the potential for rapid detection, making them ideal for immediate and portable use.

The Current Study

In this study, the researchers first synthesized chitosan-coated Mn-doped ZnS nanomaterials using the hydrothermal method. This process began with dissolving chitosan in acetic acid, followed by adding zinc acetate and manganese chloride. The resultant mixture was then precipitated, washed with ethanol, and dried.

For antibiotic treatment, antibiotics were mixed with β-lactamase enzyme and diluted to the required concentration. These mixtures were stored at a constant temperature, and the pH of all samples was measured.

In the fluorescence measurement stage, the sensing materials, at a concentration of 2500 mg L-1, were introduced into cuvettes. Incremental additions of AMP treated by β-lactamase were made to achieve various concentration levels. The fluorescence intensities were recorded using an excitation wavelength of 365 nm and an exposure time of 1 second.

Results and Discussion

The results and discussion of our study are detailed below, highlighting key aspects and findings:

Material Characterization

The material we synthesized was characterized using X-ray diffraction (XRD) and scanning electron microscopy (SEM). XRD analysis showed the cubic sphalerite structure typical of ZnS, confirming the material's successful synthesis. Although small peaks indicating the presence of Mn+2 and chitosan were detected, their influence on the ZnS structure was minimal. SEM images revealed microparticles ranging from 0.2 to 0.5 µm in size. Furthermore, Fourier-transform infrared spectroscopy (FTIR) demonstrated the coating of ZnS with chitosan and the doping with Mn, showing distinct peak alterations that suggest structural modifications due to Mn doping.

Development of Fluorescence Biosensors

The researchers developed fluorescence biosensors using (Mn:ZnS)CH micromaterials to detect ampicillin (AMP). These sensors operate by detecting fluorescent byproducts formed when the β-lactamase enzyme breaks down AMP.

As AMP concentration increased from 13.1 to 72.2 pM, the fluorescence intensity at 510 nm rose significantly, while at 614 nm, it decreased gradually. This dual-channel response facilitated the differentiation and quantification of AMP, displaying a linear relationship between AMP concentration and fluorescence intensity with a detection threshold of 8.24 pM.

Sensor Selectivity and Stability

The selectivity of the sensors was confirmed by testing against various substances, including combinations like AMP-Enzyme and others such as PCN and TET with their respective enzymes. The sensors specifically reacted to AMP-Enzyme under the correct pH conditions, underscoring their specificity. Stability tests conducted over four weeks showed that the sensors consistently responded to AMP-Enzyme, maintaining their performance.

Testing in Various Matrices

The effectiveness of the sensors was also evaluated across different matrices, such as tap water, bottled water, and organic milk. They showed consistent detection capabilities in all tested environments, with particularly high sensitivity in deionized water. The sensors maintained linear detection responses to AMP-Enzyme concentrations across these matrices, with the lowest detection limits observed in tap water.


In conclusion, this study has shown the effectiveness of using chitosan-coated Mn-doped ZnS nanomaterials for detecting AMP. The simple fluorescent sensor accurately detected AMP pretreated by β-lactamase enzymes with high sensitivity and selectivity.

These sensors demonstrated stability and sensitivity across a range of concentrations in different environments, with the highest sensitivity achieved in DI water. By effectively detecting trace amounts of AMP, this technology has the potential to significantly impact healthcare, environmental monitoring, and food safety.

Journal Reference

Nguyen, S.H., Nguyen, VN. & Tran, M.T. (2024). Dual-channel fluorescent sensors based on chitosan-coated Mn-doped ZnS micromaterials to detect ampicillin. Scientific Reports 14, 10066.,

Dr. Noopur Jain

Written by

Dr. Noopur Jain

Dr. Noopur Jain is an accomplished Scientific Writer based in the city of New Delhi, India. With a Ph.D. in Materials Science, she brings a depth of knowledge and experience in electron microscopy, catalysis, and soft materials. Her scientific publishing record is a testament to her dedication and expertise in the field. Additionally, she has hands-on experience in the field of chemical formulations, microscopy technique development and statistical analysis.    


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