4.6 Article

Effect of the tip length of multi-branched AuNFs on the detection performance of immunochromatographic assays

Journal

ANALYTICAL METHODS
Volume 8, Issue 16, Pages 3316-3324

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/c5ay03274a

Keywords

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Funding

  1. National Basic Research Program of China [2013CB127804]
  2. National Natural Science Foundation of China [31271863]
  3. Training Plan for the Main Subject of Academic Leaders of Jiangxi Province [20142BCB22004]

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The traditional immunochromatographic assay (ICA) using conventional spherical gold nanoparticles (AuNSs, 30-40 nm) as labeled probes usually suffers from low sensitivity because of insufficient probe optical intensity. Previously, we demonstrated that larger gold nanoflowers (AuNFs, 75 nm) possessing higher optical brightness can greatly improve ICA sensitivity over conventional AuNSs. However, the improved mechanism which resulted from either larger diameter or longer tips or both is not clear. To elaborate the influence of the tip length on the sensitivity of ICA, three types of gold nanoparticles (AuNPs) with similar diameters in the range of 30-40 nm, including conventional AuNSs (no tip), shorttip AuNFs (tip length, 7-8 nm), and long-tip AuNFs (tip length, 13-15 nm), were synthesized. Results showed that long-tip AuNFs as labeled probes exhibited the highest signal enhancement in ICA because of the strongest optical absorbance and highest affinity to the sample. The cut-off limit (for visual qualitative detection), half maximum inhibitory concentration, and detection limit (for quantitative analysis) of long-tip AuNF-based strips were 2, 0.61, and 0.07 ng mL(-1) which are 2.5, 2.75, and 4.14 times lower than those of AuNS-based strips, respectively. Additionally, compared with conventional AuNSs, only 20% of long-tip AuNF probes and antibodies were consumed for each strip, which significantly reduce manufacturing costs in the large-scale production. Obviously, long-tip AuNFs show great application potential as an alternative to traditional AuNSs in the ICA platform.

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