Jingfang Wang

Self-assembling subnanometer pores with unusual mass-transport properties

A long-standing aim in molecular self-assembly is the development of synthetic nanopores capable of mimicking the mass-transport characteristics of biological channels and pores. Here we report a strategy for enforcing the nanotubular assembly of rigid macrocycles in both the solid state and solution based on the interplay of multiple hydrogen-bonding and aromatic π-π stacking interactions. The resultant nanotubes have modifiable surfaces and inner pores of a uniform diameter defined by the constituent macrocycles. The self-assembling hydrophobic nanopores can mediate not only highly selective transmembrane ion transport, unprecedented for a synthetic nanopore, but also highly efficient transmembrane water permeability. These results establish a solid foundation for developing synthetically accessible, robust nanostructured systems with broad applications such as reconstituted mimicry of defined functions solely achieved by biological nanostructures, molecular sensing, and the fabrication of porous materials required for water purification and molecular separations.

Systematic identification of arsenic-binding proteins reveals that hexokinase-2 is inhibited by arsenic

Significance Arsenic holds promise for treating a wide range of tumors. To understand arsenics antitumor mechanism further, we identified 360 arsenic-binding proteins using a human proteome microarray and found proteins of glycolysis to be highly enriched. In-depth in vitro and in vivo analysis revealed that glycolysis in general and the rate-limiting enzyme hexokinase-2 of the glycolytic pathway in particular play a key role in mediating the anticancer activity of arsenic. These findings shed light on the mode of action of arsenic, and the newly identified arsenic-binding proteins may serve as a rich resource for future studies. Arsenic is highly effective for treating acute promyelocytic leukemia (APL) and has shown significant promise against many other tumors. However, although its mechanistic effects in APL are established, its broader anticancer mode of action is not understood. In this study, using a human proteome microarray, we identified 360 proteins that specifically bind arsenic. Among the most highly enriched proteins in this set are those in the glycolysis pathway, including the rate-limiting enzyme in glycolysis, hexokinase-1. Detailed biochemical and metabolomics analyses of the highly homologous hexokinase-2 (HK2), which is overexpressed in many cancers, revealed significant inhibition by arsenic. Furthermore, overexpression of HK2 rescued cells from arsenic-induced apoptosis. Our results thus strongly implicate glycolysis, and HK2 in particular, as a key target of arsenic. Moreover, the arsenic-binding proteins identified in this work are expected to serve as a valuable resource for the development of synergistic antitumor therapeutic strategies.

Identification of serum biomarkers for gastric cancer diagnosis using a human proteome microarray

We aimed to globally discover serum biomarkers for diagnosis of gastric cancer (GC). GC serum autoantibodies were discovered and validated using serum samples from independent patient cohorts encompassing 1,401 participants divided into three groups, i.e. healthy, GC patients, and GC-related disease group. To discover biomarkers for GC, the human proteome microarray was first applied to screen specific autoantibodies in a total of 87 serum samples from GC patients and healthy controls. Potential biomarkers were identified via a statistical analysis protocol. Targeted protein microarrays with only the potential biomarkers were constructed and used to validate the candidate biomarkers using 914 samples. To provide further validation, the abundance of autoantibodies specific to the biomarker candidates was analyzed using enzyme-linked immunosorbent assays. Receiver operating characteristic curves were generated to evaluate the diagnostic accuracy of the serum biomarkers. Finally, the efficacy of prognosis efficacy of the final four biomarkers was evaluated by analyzing the clinical records. The final panel of biomarkers consisting of COPS2, CTSF, NT5E, and TERF1 provides high diagnostic power, with 95% sensitivity and 92% specificity to differentiate GC patients from healthy individuals. Prognosis analysis showed that the panel could also serve as independent predictors of the overall GC patient survival. The panel of four serum biomarkers (COPS2, CTSF, NT5E, and TERF1) could serve as a noninvasive diagnostic index for GC, and the combination of them could potentially be used as a predictor of the overall GC survival rate.

PMD: A Resource for Archiving and Analyzing Protein Microarray data.

Protein microarray is a powerful technology for both basic research and clinical study. However, because there is no database specifically tailored for protein microarray, the majority of the valuable original protein microarray data is still not publically accessible. To address this issue, we constructed Protein Microarray Database (PMD), which is specifically designed for archiving and analyzing protein microarray data. In PMD, users can easily browse and search the entire database by experimental name, protein microarray type, and sample information. Additionally, PMD integrates several data analysis tools and provides an automated data analysis pipeline for users. With just one click, users can obtain a comprehensive analysis report for their protein microarray data. The report includes preliminary data analysis, such as data normalization, candidate identification, and an in-depth bioinformatics analysis of the candidates, which include functional annotation, pathway analysis, and protein-protein interaction network analysis. PMD is now freely available at www.proteinmicroarray.cn.

Rapid production of virus protein microarray using Protein microArray fabrication through GEne Synthesis (PAGES)

The high genetic variability of RNA viruses is a significant factor limiting the discovery of effective biomarkers, the development of vaccines, and characterizations of the immune response during infection. Protein microarrays have been shown to be a powerful method in biomarker discovery and the identification of novel protein–protein interaction networks, suggesting that this technique could also be very useful in studies of infectious RNA viruses. However, to date, the amount of genetic material required to produce protein arrays, as well as the time- and labor-intensive procedures typically needed, have limited their more widespread application. Here, we introduce a method, protein microarray fabrication through gene synthesis (PAGES), for the rapid and efficient construction of protein microarrays particularly for RNA viruses. Using dengue virus as an example, we first identify consensus sequences from 3,604 different strains and then fabricate complete proteomic microarrays that are unique for each consensus sequence. To demonstrate their applicability, we show that these microarrays can differentiate sera from patients infected by dengue virus, related pathogens, or from uninfected patients. We anticipate that the microarray and expression library constructed in this study will find immediate use in further studies of dengue virus and that, more generally, PAGES will become a widely applied method in the clinical characterization of RNA viruses.