Using phage and yeast display to select hundreds of monoclonal antibodies: application to antigen 85, a tuberculosis biomarker.
Using phage and yeast display to select hundreds of monoclonal antibodies: application to antigen 85, a tuberculosis biomarker.
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使用噬菌体和酵母展示来选择数百种单克隆抗体:抗原85(结核病生物标志物)的应用。
DOI:
10.1371/journal.pone.0049535
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发表时间:
2012
期刊:
影响因子:
3.7
通讯作者:
Bradbury AR
中科院分区:
文献类型:
--
作者:
Ferrara F;Naranjo LA;Kumar S;Gaiotto T;Mukundan H;Swanson B;Bradbury AR
Current diagnostic methods for tuberculosis (TB), a major global health challenge that kills nearly two million people annually, are time-consuming and inadequate. During infection a number of bacterial molecules that play a role in the infective process are released and have been proposed as biomarkers for early TB diagnosis. Antigen 85 (Ag85) is the most abundant secreted TB protein, and a potential target for this diagnostic approach. One of the bottlenecks in the direct detection of such bacterial targets is the availability of robust, sensitive, specific antibodies. Using Ag85 as a model, we describe a method to select antibodies against any potential target using a novel combination of phage and yeast display that exploits the advantage of each approach. The efficiency of this approach was attested to by the 111 specific antibodies identified in initial screens. These were assessed for binding to the different Ag85 subunits, affinity, and activity in sandwich assays. The novelty of this approach lies in the possibility of screening the entire output of a phage antibody selection in a single experiment by yeast display. This can be considered analogous to carrying out a million ELISAs. The monoclonal antibodies (mAbs) identified in this way show high binding affinity and selectivity for the antigens and offer an advantage over traditional mAbs produced by relatively expensive and time consuming techniques. This approach has wide applicability, and the affinity of selected antibodies can be significantly improved, if required.
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影响因子:
3.7
作者:
Kashyap, Rajpal S.;Rajan, Anju N.;Ramteke, Sonali S.;Agrawal, Vijay S.;Kelkar, Sanjivani S.;Purohit, Hemant J.;Taori, Girdhar M.;Daginawala, Hatim F.
通讯作者:
Daginawala, Hatim F.
影响因子:
46.9
作者:
通讯作者:
--
影响因子:
6.8
作者:
Gai, S. Annie;Wittrup, K. Dane
通讯作者:
Wittrup, K. Dane
影响因子:
56.9
作者:
Bostrom, Jenny;Yu, Shang-Fan;Fuh, Germaine
通讯作者:
Fuh, Germaine
影响因子:
3.1
作者:
Bentley-Hibbert, SI;Quan, X;Godfrey, HP
通讯作者:
Godfrey, HP