Prospects for the application of aptamer based assay platforms in pathogen detection

Banu, Kauser; Mondal, Bhairab; Rai, Bhawana; Monica, N.; Raju, H.

doi:10.1016/j.bbe.2022.07.005

Cited by 5 publications

(1 citation statement)

References 107 publications

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“…Using aptamers to decorate Au NPs for bacterial targeting assays is a common strategy at present ( Chen et al, 2020 , Chen et al, 2021 , Qi et al, 2023 ). Unfortunately, the technology depends on specialized expertise for aptamer generation, and the success rate for producing targeted aptamers is comparatively low ( Banu et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Colorimetric sensor array for the rapid distinction and detection of various antibiotic-resistant psychrophilic bacteria in raw milk based-on machine learning

Qin,

Sun,

Huang

et al. 2024

Food Chemistry: X

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Section: Introductionmentioning

confidence: 99%

Colorimetric sensor array for the rapid distinction and detection of various antibiotic-resistant psychrophilic bacteria in raw milk based-on machine learning

Qin,

Sun,

Huang

et al. 2024

Food Chemistry: X

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Surface plasmon resonance aptasensing and computational analysis of Staphylococcus aureusIsdA surface protein

Bruce‐Tagoe,

Harnish,

Soleimani

et al. 2024

Biotechnology Progress

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Staphylococcus aureus (S. aureus), a common foodborne pathogen, poses significant public health challenges due to its association with various infectious diseases. A key player in its pathogenicity, which is the IsdA protein, is an essential virulence factor in S. aureus infections. In this work, we present an integrated in‐silico and experimental approach using MD simulations and surface plasmon resonance (SPR)‐based aptasensing measurements to investigate S. aureus biorecognition via IsdA surface protein binding. SPR, a powerful real‐time and label‐free technique, was utilized to characterize interaction dynamics between the aptamer and IsdA protein, and MD simulations was used to characterize the stable and dynamic binding regions. By characterizing and optimizing pivotal parameters such as aptamer concentration and buffer conditions, we determined the aptamer's binding performance. Under optimal conditions of pH 7.4 and 150 mM NaCl concentration, the kinetic parameters were determined; ka = 3.789 × 104/Ms, kd = 1.798 × 103/s, and KD = 4.745 × 10−8 M. The simulations revealed regions of interest in the IsdA‐aptamer complex. Region I, which includes interactions between amino acid residues H106 and R107 and nucleotide residues 9G, 10U, 11G and 12U of the aptamer, had the strongest interaction, based on ΔG and B‐factor values, and hence contributed the most to the stability of the interaction. Region II, which covers residue 37A reflects the dynamic nature of the interaction due to frequent contacts. The approach presents a rigorous characterization of aptamer‐IsdA binding behavior, supporting the potential application of the IsdA‐binding aptamer system for S. aureus biosensing.

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Key steps for improving bacterial SERS signals in complex samples: Separation, recognition, detection, and analysis

Xie,

Zhu,

et al. 2024

Talanta

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Prospects for the application of aptamer based assay platforms in pathogen detection

Cited by 5 publications

References 107 publications

Colorimetric sensor array for the rapid distinction and detection of various antibiotic-resistant psychrophilic bacteria in raw milk based-on machine learning

Colorimetric sensor array for the rapid distinction and detection of various antibiotic-resistant psychrophilic bacteria in raw milk based-on machine learning

Surface plasmon resonance aptasensing and computational analysis of Staphylococcus aureusIsdA surface protein

Key steps for improving bacterial SERS signals in complex samples: Separation, recognition, detection, and analysis

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