Monoclonal antibodies to the V2 domain of MN-rgp120: fine mapping of epitopes and inhibition of α4β7 binding

BACKGROUND

Recombinant gp120 (MN-rgp120) was a major component of the AIDSVAX B/E vaccine used in the RV144 trial. This was the first clinical trial to show that vaccination could prevent HIV infection in humans. A recent RV144 correlates of protection study found that protection correlated with the presence of antibodies to the V2 domain. It has been proposed that antibodies to the α4β7 binding site in the V2 domain might prevent HIV-1 infection by blocking the ability of virions to recognize α4β7 on activated T-cells. In this study we investigated the specificity of monoclonal antibodies (MAbs) to the V2 domain of MN-rgp120 and examined the possibility that these antibodies could inhibit the binding of MN-rgp120 to the α4β7 integrin.

METHODOLOGY/PRINCIPAL FINDINGS

Nine MAbs to the V2 domain were isolated from mice immunized with recombinant envelope proteins. The ability of these MAbs to inhibit HIV infection, block the binding of gp120 to CD4, and block the binding of MN-rgp120 to the α4β7 integrin was measured. Mutational analysis showed that eight of the MAbs recognized two immunodominant clusters of amino acids (166-168 and 178-183) located at either end of the C strand within the four-strand anti-parallel sheet structure comprising the V1/V2 domain.

CONCLUSIONS/SIGNIFICANCE

These studies showed that the antigenic structure of the V2 domain is exceedingly complex and that MAbs isolated from mice immunized with MN-rgp120 exhibited a high level of strain specificity compared to MAbs to the V2 domain isolated from HIV-infected humans. We found that immunization with MN-rgp120 readily elicits antibodies to the V2 domain and some of these were able to block the binding of MN-rgp120 to the α4β7 integrin.

EDGE(3): a web-based solution for management and analysis of Agilent two color microarray experiments

Background

The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE³ was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users.

Results

EDGE³ has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE³ has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE³ is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image.

Conclusion

Here, we present EDGE³, an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE³ provides a means for managing RNA samples and arrays during the hybridization process. EDGE³ is freely available for download at .

Hepatic transcriptional networks induced by exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin

The environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) serves as a prototype for a range of environmental toxicants and as a pharmacologic probe to study signal transduction by the aryl hydrocarbon receptor (AHR). Despite a detailed understanding of how TCDD exposure leads to the transcriptional up-regulation of cytochrome P450-dependent monooxygenases, we know little about how compounds like TCDD lead to a variety of AHR-dependent toxic end points such as liver pathology, terata, thymic involution, and cancer. Using an acute exposure protocol and the toxic response of the mouse liver as a model system, we have begun a detailed microarray analysis to describe the transcriptional changes that occur after various TCDD doses and treatment times. Through correlation analysis of time- and dose-dependent toxicological end points, we are able to identify coordinately responsive transcriptional events that can be defined as primary transcriptional events and downstream events that may represent mechanistically linked sequelae or that have potential as biomarkers of toxicity.

EDGE: A Centralized Resource for the Comparison, Analysis, and Distribution of Toxicogenomic Information

Transcriptional profiling via microarrays holds great promise for toxicant classification and hazard prediction. Unfortunately, the use of different microarray platforms, protocols, and informatics often hinders the meaningful comparison of transcriptional profiling data across laboratories. One solution to this problem is to provide a low-cost and centralized resource that enables researchers to share toxicogenomic data that has been generated on a common platform. In an effort to create such a resource, we developed a standardized set of microarray reagents and reproducible protocols to simplify the analysis of liver gene expression in the mouse model. This resource, referred to as EDGE, was then used to generate a training set of 117 publicly accessible transcriptional profiles that can be accessed at http://edge.oncology.wisc.edu/. The Web-accessible database was also linked to an informatics suite that allows on-line clustering and K-means analyses as well as Boolean and sequence-based searches of the data. We propose that EDGE can serve as a prototype resource for the sharing of toxicogenomics information and be used to develop algorithms for efficient chemical classification and hazard prediction.