Biomimetic magnetic nanoparticles for bacterial magnetic concentration in liquids and qPCR-detection

Food Control(2023)

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Abstract
The development of improved systems for the fast detection of trace amounts of infectious agents is of vital importance. Magnetic nanoparticles (MNPs) are an interesting alternative in this context due to (1) their large surface area, that maximizes the potential interaction between the target microorganism and the nanoparticle, and (2) their magnetic susceptibility, that allows the concentration of the nanoparticles (and thus, the attached microorganisms) by means of an external magnetic field. In the present study, biomimetic magnetic nanoparticles (BMNPs) were synthesized with the mediation of MamC, a magnetosome protein from Magnetococcus marinus MC-1, and used to concentrate and detect bacteria. As a novelty compared to the existing biosensors based on MNPs, the surface characteristics of BMNPs allow a direct and efficient electrostatic interaction between microorganisms and nanoparticles without the need of post-production coating of BMNPs. Our results show that BMNPs, without any post-production functionalization, are very efficient binding both Gram positive and Gram negative bacteria and concentrating these microorganisms following upon the application of an external magnetic field. Once concentrated, the target microorganisms (Staphylococcus aureus used here as a model bacterium) can be specifically detected up to bacterial loads as low as 10 CFU/mL by using qPCR. Although the binding is unspecific, the specificity for detection is given by qPCR testing of the attached microorganisms. The system described here, without the need of functionalization, maintains (or improves) the detection limit for S. aureus compared to that obtained by using the Protocol ISO 6888-1:2022 and to that obtained by using antibodyfunctionalized MNPs, thus becoming a suitable, cost- and time-effective alternative for bacteria detection in fluid samples.
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Key words
Magnetic nanoparticles,MamC,Biosensor
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