The current limitations of antiretroviral therapy is driving interest in alternative therapeutics which fully resolve inflammation and achieve complete eradication of HIV latently-infected cells. Exosomes are nano-sized membrane vesicles and key players of intercellular signaling. Interestingly, exosomes have shown promise as engineerable therapeutic agents for a broad range of diseases. The objective of this grant is to surface engineer exosomes ex vivo using surface display technology and pack the decorated exosomes with cytotoxic cargo. The engineered exosomes will be utilized as specific delivery nanoshuttles to bind and mediate clearance of specific cells of interest. In our preliminary results, we show that exosomes can be surface decorated with anti-HIV envelope fusion proteins and can significantly suppress HIV infection in Jurkat and primary human CD4+ T cells in a dose dependent manner (p<0.05, paired t-test). In addition, the designer exosomes show potent binding to HIV particles in nanoimaging analyses, while control exosomes do not bind to virions. Engineered exosomes are preferentially internalized by cells expressing specific surface markers of interest (p<0.0001, Chi square test), demonstrating that decoration with functional fusion proteins enables targeted cell delivery. Hence, in this RAP proposal, we will assess the binding efficiency of anti-HIV envelope surface decorated exosomes to target cells in a mixed population of envelope-positive and envelope-negative cells (Aim 1). Also, we will measure the efficiency of engineered exosomes to bind, deliver cytotoxic cargo, and mediate selective killing of targeted HIV-infected envelope expressing cells in mixed populations (Aim 2). Aim 1 will be completed in 4 months and aim 2 will be concluded in 6 months. For statistical analysis, we will use Chi square tests for individual experiments to measure associations between exosome uptake, HIV infection, and cell surface HIV envelope expression, and perform paired non-parametric tests (paired Wilcoxon) to analyze these associations across independent experiments.