Optical Detection of Foodborne Bacterial Pathogens using Nanosensors

"This programme of research involves the development of a new tool based on the use of innovative bionanosensors with superior performance for the detection of bacterial pathogens in a sensitive, quantitative and multiplexed manner. This will involve developing nanoparticle based analytical technology for the simultaneous detection of multiple bacterial pathogens associated with food poisoning. Current methods for detecting bacteria are time consuming (1-2 days in the case of bacteria culturing on selective media), expensive and require specialised personnel and equipment. Therefore, there is a strong need for faster, simpler and more reliable isolation and detection of bacterial pathogens that can be carried out in the field and can simultaneously detect multiple bacteria within a single test. Therefore, development of a simple, portable detection platform is proposed which can carry out multiplexed point of care (POC) detection.

Successful pathogen detection is crucial for the health of the general public as the threat of infectious disease is dramatically increasing as a result of bacteria developing resistance to antimicrobial drugs. Major threats to human health from bacterial infections such as E. coli have led to urgent demands to develop highly efficient strategies for isolating and detecting microorganisms in connection with food safety, medical diagnostics, water quality, and counter terrorism. Virulent strains of E. coli can cause gastroenteritis, urinary tract infections, and neonatal meningitis and Salmonella attacks the stomach lining and intestines and in severe cases can result in blood poisoning.

The research involves the use of an optical detection technique called Raman scattering which will be developed for the POC detection of bacterial pathogens. If light of a particular wavelength is directed onto a molecule then some of the scattered light will change wavelength. This change in wavelength is related to the structure of the molecules and provides a molecular fingerprint that can be used for definitive identification. However Raman scattering is an intrinsically weak process and the signal can be greatly enhanced if the molecule is coloured and is adsorbed onto a roughened metal surface (surface enhanced resonance Raman). The metal can be thought of as essentially amplifying the Raman scattering from a molecule on the surface and in this case the metal will take the form of metal nanoparticles. Since a fingerprint unique to the molecule is produced, the composition of mixtures can easily be identified without separation.

A novel diagnostic tool will be developed for the detection of multiple bacterial pathogens, namely Escherichia coli, Salmonella typhimurium and Campylobacter jejunii in a single assay combined with enhanced Raman detection. However, this technology will not be limited to these organisms and can readily be applied to other pathogens. This will involve using magnetic nanoparticles which have a biomolecule on the surface known as a lectin which will bind to the surface of bacterial cells. This will allow isolation and separation of bacteria from the surrounding medium upon application of a magnetic. Additionally, silver nanoparticles which are functionalised with a coloured molecule or label, resulting in intense surface enhanced Raman signals, and a biomolecule which will bind specifically to a particular strain of bacteria (antibody or aptamer) will be added. When the correct bacteria are present binding will occur resulting in magnetic isolation of the bacteria from the matrix as well as it now having a SERS response. By using a different label for each biomarker, a unique spectrum will be achieved for each biomarker allowing multiple biomarkers to be detected simultaneously. A portable Raman spectrometer will then be used to detect the bacteria present."

Optical Detection of Foodborne Bacterial Pathogens using Nanosensors

The summary of the key outcomes of this research and it has been spilt into three distinct sections for clarity:
1. Functionalisation of nanoparticles with biomarker recognition molecules
i. Lectin functionalised magnetic nanoparticle for bacteria capture and isolation
A lectin is carbohydrate binding protein. Concanvalin A (Con A) is a lectin binds specifically to terminal α-D-mannosyl and α-D-glucosyl groups present on the surface of all bacteria and as such was chosen as the biomolecule to capture and isolate the 3 bacterial pathogens from the sample mixture. Silver coated magnetic nanoparticles (Ag@MNP) were successfully conjugated to Con A using a large PEGylated linker via carbodiimide cross-linking chemistry to yield Ag@MNP conjugates.
Magnetic separation can be achieved by applying a magnet and thus isolating the sample from the sample matrix, allowing for concentration of the sample and wash steps.
ii. Biorecognition nanoparticles for bacteria identification
Antibodies (Ab) bind specifically to a particular strain of bacteria and as such allow strain specific identification. 3 types of antibodies were purchased; E. Coli, S. Typh and S. Aureus. The antibody-nanoparticle (Ab-NP) conjugates contained the following: silver nanoparticles (AgNP) plus Raman reporter conjugated to Ab using a PEGylated linker. Each of the conjugates had a different Raman reporter so that a unique Raman fingerprint of that conjugate would be provided. The 3 sets of Ab-NP conjugates were successfully synthesised and characterised using the same techniques described above for the Ag@MNP conjugates.
This work showed that nanoparticles with the necessary biorecognition molecules were successfully functionalised and optimised for the three bacteria targets.
2. Fixed Bacterial Imaging
To ensure the conjugates were successfully binding to the bacteria surface, mapping and imaging experiments were conducted. From the dark field images and 2D Raman maps it was evident that the nanoparticle conjugates bound to single bacteria cell. This was confirmed when the single bacteria cells were mapped, because intense SERS signals were obtained from the same locations and where there was no nanoparticles bound there was no Raman signal.
This showed that it was possible to image single bacteria cells with the nanoparticle conjugates bound to the bacteria surface.
3. Solution Assay
Single-plex tests were developed for each of the targets and the sensitivity was established. It was found that for the 3 bacterial strains, the optimum concentration to be used in the assay was 1000 CFU/mL. In terms of the assay’s sensitivity we can confidently detect 100 CFU/mL but the lowest discrimination between the sample and control was found to be 10 CFU/mL for all three bacterial strains. We then extended this to multiplex detection. We have successfully developed SERS biosensors for the isolation and detection of duplex and triplex samples where we are able to discriminate between each of the bacterial strains. In the triplex sample we can successfully identify 3 distinct peaks to identify E. Coli, S. Typh and S. Aureus simultaneously in the one sample.
This work showed that SERS biosensors for the isolation and detection of each of the 3 bacterial strains have been developed.