Protein sensors combining both on-and-off model for antibody homogeneous assay.
Protein sensors combining both on-and-off model for antibody homogeneous assay.
复制标题
结合开关模型的蛋白质传感器用于抗体均质测定
DOI:
10.1016/j.bios.2022.114226
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发表时间:
2022-08-01
影响因子:
12.6
通讯作者:
Hu JL
中科院分区:
文献类型:
--
作者:
Li J;Wang JL;Zhang WL;Tu Z;Cai XF;Wang YW;Gan CY;Deng HJ;Cui J;Shu ZC;Long QX;Chen J;Tang N;Hu X;Huang AL;Hu JL
Protein sensors based on allosteric enzymes responding to target binding with rapid changes in enzymatic activity are potential tools for homogeneous assays. However, a high signal-to-noise ratio (S/N) is difficult to achieve in their construction. A high S/N is critical to discriminate signals from the background, a phenomenon that might largely vary among serum samples from different individuals. Herein, based on the modularized luciferase NanoLuc, we designed a novel biosensor called NanoSwitch. This sensor allows direct detection of antibodies in 1 μl serum in 45 min without washing steps. In the detection of Flag and HA antibodies, NanoSwitches respond to antibodies with S/N ratios of 33-fold and 42-fold, respectively. Further, we constructed a NanoSwitch for detecting SARS-CoV-2-specific antibodies, which showed over 200-fold S/N in serum samples. High S/N was achieved by a new working model, combining the turn-off of the sensor with human serum albumin and turn-on with a specific antibody. Also, we constructed NanoSwitches for detecting antibodies against the core protein of hepatitis C virus (HCV) and gp41 of the human immunodeficiency virus (HIV). Interestingly, these sensors demonstrated a high S/N and good performance in the assays of clinical samples; this was partly attributed to the combination of off-and-on models. In summary, we provide a novel type of protein sensor and a working model that potentially guides new sensor design with better performance.
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DOI:
10.3390/s21030795
发表时间:
2021-01-25
期刊:
Sensors (Basel, Switzerland)
影响因子:
--
作者:
Kim H;Ju J;Lee HN;Chun H;Seong J
通讯作者:
Seong J
影响因子:
3.7
作者:
Engler, Carola;Kandzia, Romy;Marillonnet, Sylvestre
通讯作者:
Marillonnet, Sylvestre
影响因子:
2.9
作者:
Isazadeh, Mohsen;Amandadi, Mojdeh;Hosseinkhani, Saman
通讯作者:
Hosseinkhani, Saman
影响因子:
82.9
作者:
Long, Quan-Xin;Liu, Bai-Zhong;Huang, Ai-Long
通讯作者:
Huang, Ai-Long
影响因子:
8.9
作者:
Arts R;Ludwig SKJ;van Gerven BCB;Estirado EM;Milroy LG;Merkx M
通讯作者:
Merkx M