Development of anti-aflatoxin B1 nanobodies from a novel mutagenesis-derived synthetic library for traditional Chinese medicine and foods safety testing.

BACKGROUND: The main commercially available methods for detecting small molecules of mycotoxins in traditional Chinese medicine (TCM) and functional foods are enzyme-linked immunosorbent assay and mass spectrometry. Regarding the development of diagnostic antibody reagents, effective methods for the rapid preparation of specific monoclonal antibodies are inadequate. METHODS: In this study, a novel synthetic phage-displayed nanobody Golden Glove (SynaGG) library with a glove-like cavity configuration was established using phage display technology in synthetic biology. We applied this unique SynaGG library on the small molecule aflatoxin B1 (AFB1), which has strong hepatotoxicity, to isolate specific nanobodies with high affinity for AFB1. RESULT: These nanobodies exhibit no cross-reactivity with the hapten methotrexate, which is recognized by the original antibody template. By binding to AFB1, two nanobodies can neutralize AFB1-induced hepatocyte growth inhibition. Using molecular docking, we found that the unique non-hypervariable complementarity-determining region 4 (CDR4) loop region of the nanobody was involved in the interaction with AFB1. Specifically, the CDR4's positively charged amino acid arginine directed the binding interaction between the nanobody and AFB1. We then rationally optimized the interaction between AFB1 and the nanobody by mutating serine at position 2 into valine. The binding affinity of the nanobody to AFB1 was effectively improved, and this result supported the use of molecular structure simulation for antibody optimization. CONCLUSION: In summary, this study revealed that the novel SynaGG library, which was constructed through computer-aided design, can be used to isolate nanobodies that specifically bind to small molecules. The results of this study could facilitate the development of nanobody materials to detect small molecules for the rapid screening of TCM materials and foods in the future.

Astragalus membranaceus-Derived Anti-Programmed Death-1 Monoclonal Antibodies with Immunomodulatory Therapeutic Effects against Tumors.

Astragalus membranaceus polysaccharide (APS) components are main ingredients of TCM and have proven efficacy to activate T cells and B cells, enhancing immunity in humans. In this study, elevated cytokine and anti-PD-1 antibody titers were found in mice after immunization with APS. Therefore, phage-display technology was utilized to isolate specific anti-programmed death-1 (PD-1) antibodies from mice stimulated by APS and to confirm whether the isolated anti-PD-1 antibody could inhibit the interaction of PD-1 with the programmed death-ligand 1 (PD-L1), resulting in tumor growth inhibition. The isolated single-chain fragment variable (scFv) S12 exhibited the highest binding affinity of 20 nM to PD-1, completed the interaction between PD-1 and PD-L1, and blocked the effect of PD-L1-induced T cell exhaustion in peripheral blood mononuclear cells in vitro. In the animal model, the tumor growth inhibition effect after scFv S12 treatment was approximately 48%. However, meaningful synergistic effects were not observed when scFv S12 was used as a cotreatment with ixabepilone. Moreover, this treatment caused a reduction in the number of tumor-associated macrophages in the tumor tissue. These experimental results indirectly indicate the ability of APS to induce specific antibodies associated with the immune checkpoint system and the potential benefits for improving immunity in humans.

Comparison of two treatments on a covariate variable.

In clinical trials, the efficacy of treatment might be dependent on the value of a covariate variable. Therefore, it might be possible to detect the region over the covariate variable where the two treatments under investigation do not have significantly different efficacy or the region of superiority of one treatment. The non-significant region can be verified to be a confidence interval for the abscissa of the intersection point of two regression lines, and each of the complementary regions of the confidence interval corresponds to a region of superiority. In this study, we develop a method of constructing the confidence interval based on the concept of a generalized pivotal quantity, so as to perform the task of detecting the possible three regions for a clinical trial. Two real-world examples are given to illustrate the application of our proposed method, and a simulation study is conducted to evaluate its performance.