Enterovirus (EV) 71 infection is known to cause hand-foot-and-mouth disease (HFMD) and in severe cases, induces neurological disorders culminating in fatality. An outbreak of EV71 in South East Asia in 1997 affected over 120,000 people and caused neurological disorders in a few individuals. The control of EV71 infection through public health interventions remains minimal and treatments are only symptomatic. Recently, human scavenger receptor class B, member 2 (SCARB2) has been reported to be a cellular receptor of EV71. We expressed human SCARB2 gene in NIH3T3 cells (3T3-SCARB2) to study the mechanisms of EV71 entry and infection. We demonstrated that human SCARB2 serves as a cellular receptor for EV71 entry. Disruption of expression of SCARB2 using siRNAs can interfere EV71 infection and subsequent inhibit the expression of viral capsid proteins in RD and 3T3-SCARB2 but not Vero cells. SiRNAs specific to clathrin or dynamin or chemical inhibitor of clathrin-mediated endocytosis were all capable of interfering with the entry of EV71 into 3T3-SCARB2 cells. On the other hand, caveolin specific siRNA or inhibitors of caveolae-mediated endocytosis had no effect, confirming that only clathrin-mediated pathway was involved in EV71 infection. Endocytosis of EV71 was also found to be pH-dependent requiring endosomal acidification and also required intact membrane cholesterol. In summary, the mechanism of EV71 entry through SCARB2 as the receptor for attachment, and its cellular entry is through a clathrin-mediated and pH-dependent endocytic pathway. This study on the receptor and endocytic mechanisms of EV71 infection is useful for the development of effective medications and prophylactic treatment against the enterovirus.

Regulated RNA translation is critical to provide proteins needed to maintain persistent modification of synaptic strength, which underlies the molecular basis of long-term memory (LTM). Cytoplasmic polyadenylation element-binding proteins (CPEBs) are sequence-specific RNA-binding proteins and regulate translation in various tissues. All four CPEBs in vertebrates are expressed in the brain, including the hippocampal neurons, suggesting their potential roles in translation-dependent plasticity and memory. Although CPEB1 and CPEB3 have been shown to control specific kinds of hippocampus-related LTM, the role of CPEB2 and CPEB4 in learning and memory remains elusive. Thus, we generated CPEB4 knockout (KO) mice and analyzed them using several behavioral tests. No difference was found in the anxiety level, motor coordination, hippocampus-dependent learning and memory between the KO mice and their wild-type (WT) littermates. Electrophysiological recordings of multiple forms of synaptic plasticity in the Schaffer collateral pathway-CA1 neurons also showed normal responses in the KO hippocampal slices. Morphological analyses revealed that the CPEB4-lacking pyramidal neurons possessed slightly elongated dendritic spines. Unlike its related family members, CPEB1 and CPEB3, CPEB4 seems to be dispensable for hippocampus-dependent plasticity, learning and memory.

Pandemic and epidemic outbreaks of influenza A virus (IAV) infection pose severe challenges to human society. Passive immunotherapy with recombinant neutralizing antibodies can potentially mitigate the threats of IAV infection. With a high throughput neutralizing antibody discovery platform, we produced artificial anti-hemagglutinin (HA) IAV-neutralizing IgGs from phage-displayed synthetic scFv libraries without necessitating prior memory of antibody-antigen interactions or relying on affinity maturation essential for in vivo immune systems to generate highly specific neutralizing antibodies. At least two thirds of the epitope groups of the artificial anti-HA antibodies resemble those of natural protective anti-HA antibodies, providing alternatives to neutralizing antibodies from natural antibody repertoires. With continuing advancement in designing and constructing synthetic scFv libraries, this technological platform is useful in mitigating not only the threats of IAV pandemics but also those from other newly emerging viral infections.

Antibodies provide immune protection by recognizing antigens of diverse chemical properties, but elucidating the amino acid sequence-function relationships underlying the specificity and affinity of antibody-antigen interactions remains challenging. We designed and constructed phage-displayed synthetic antibody libraries with enriched protein antigen-recognition propensities calculated with machine learning predictors, which indicated that the designed single-chain variable fragment variants were encoded with enhanced distributions of complementarity-determining region (CDR) hot spot residues with high protein antigen recognition propensities in comparison with those in the human antibody germline sequences. Antibodies derived directly from the synthetic antibody libraries, without affinity maturation cycles comparable to those in in vivo immune systems, bound to the corresponding protein antigen through diverse conformational or linear epitopes with specificity and affinity comparable to those of the affinity-matured antibodies from in vivo immune systems. The results indicated that more densely populated CDR hot spot residues were sustainable by the antibody structural frameworks and could be accompanied by enhanced functionalities in recognizing protein antigens. Our study results suggest that synthetic antibody libraries, which are not limited by the sequences found in antibodies in nature, could be designed with the guidance of the computational machine learning algorithms that are programmed to predict interaction propensities to molecules of diverse chemical properties, leading to antibodies with optimal characteristics pertinent to their medical applications.

Two systems of antibody-drug conjugates (ADCs), noncleavable H32-DM1 and cleavable H32-VCMMAE, were developed by using different linkers and drugs attached to the anti-HER2 antibody H32, which is capable of cell internalization. Activated functional groups, including an N-hydroxysuccinimidyl (NHS) ester and a maleimide, were utilized to make the ADCs. Mass spectrometry, hydrophobic interaction chromatography, polyacrylamide gel electrophoresis, and in vitro cell assays were performed to analyze and optimize the ADCs. Several H32-VCMMAE ADCs were established with higher DARs and greater synthetic yields without compromising potency. The anticancer efficacy of H32-DM1 was 2-to 8-fold greater than that of Kadcyla ®. The efficacy of H32-VCMMAE was in turn better than that of H32-DM1. The anticancer efficacy of these ADCs against N87, SK-BR-3 and BT474 cells was in the following order: H32-VCMMAE series > H32-DM1 series > Kadcyla ®. The optimal DAR for H32-VCMMAE was found to be 6.6, with desirable attributes including good cell penetration, a releasable payload in cancer cells, and high potency. Our results demonstrated the potential of H32-VCMMAE as a good ADC candidate.

Immunoassays based on sandwich immuno-complexes of capture and detection antibodies simultaneously binding to the target analytes have been powerful technologies in molecular analyses. Recent developments in single molecule detection technologies enable the detection limit of the sandwich immunoassays approaching femtomolar (10-15 M), driving the needs of developing sensitive and specific antibodies for ever-increasingly broad applications in detecting and quantifying biomarkers. The key components underlying the sandwich immunoassays are antibody-based affinity reagents, for which the conventional sources are mono-or poly-clonal antibodies from immunized animals. The downsides of the animal-based antibodies as affinity reagents arise from the requirement of months of development timespan and limited choices of antibody candidates due to immunodominance of humoral immune responses in animals. Hence, developing animal antibodies capable of distinguishing highly related antigens could be challenging. To overcome the limitation imposed by the animal immune systems, we developed an in vitro methodology based on phagedisplayed synthetic antibody libraries for diverse antibodies as affinity reagents against closely related influenza virus nucleoprotein (NP) subtypes, aiming to differentiating avian influenza virus (H5N1) from seasonal influenza viruses (H1N1 and H3N2), for which the NPs are closely related by 90-94% in terms of pairwise amino acid sequence identity. We applied the methodology to attain, within four weeks, a panel of IgGs with distinguishable specificities against a group of representative NPs with pairwise amino acid sequence identities up to more than 90%, and the antibodies derived from the antibody libraries without further affinity refinement had comparable affinity of mouse antibodies to the NPs with the detection limit less than 1 nM of viral NP from lysed virus with sandwich ELISA. The panel of IgGs were capable of rapidly distinguishing infections due to virulent avian influenza virus from infections of seasonal flu, in responding to a probable emergency scenario where avian influenza virus would be transmissible among humans overlapping with the seasonal influenza infections. The results indicate that the in vitro antibody development methodology enables developing diagnostic antibodies that would not otherwise be available from animal-based antibody technologies.

Mesothelin (MSLN) is an attractive candidate of targeted therapy for several cancers, and hence there are increasing needs to develop MSLN-targeting strategies for cancer therapeutics. Antibody–drug conjugates (ADCs) targeting MSLN have been demonstrated to be a viable strategy in treating MSLN-positive cancers. However, developing antibodies as targeting modules in ADCs for toxic payload delivery to the tumor site but not to normal tissues is not a straightforward task with many potential hurdles. In this work, we established a high throughput engineering platform to develop and optimize anti-MSLN ADCs by characterizing more than 300 scFv CDR-variants and more than 50 IgG CDR-variants of a parent anti-MSLN antibody as candidates for ADCs. The results indicate that only a small portion of the complementarity determining region (CDR) residues are indispensable in the MSLN-specific targeting. Also, the enhancement of the hydrophilicity of the rest of the CDR residues could drastically increase the overall solubility of the optimized anti-MSLN antibodies, and thus substantially improve the efficacies of the ADCs in treating human gastric and pancreatic tumor xenograft models in mice. We demonstrated that the in vivo treatments with the optimized ADCs resulted in almost complete eradication of the xenograft tumors at the treatment endpoints, without detectable off-target toxicity because of the ADCs’ high specificity targeting the cell surface tumor-associated MSLN. The technological platform can be applied to optimize the antibody sequences for more effective targeting modules of ADCs, even when the candidate antibodies are not necessarily feasible for the ADC development due to the antibodies’ inferior solubility or affinity/specificity to the target antigen.

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