An understanding of the immunological footprint of Mycobacterium tuberculosis (MTB) CD4 T cell recognition is still incomplete. Here we report that human Th1 cells specific for MTB are largely contained in a CXCR3+CCR6+ memory subset and highly focused on three broadly immunodominant antigenic islands, all related to bacterial secretion systems. Our results refute the notion that secreted antigens act as a decoy, since both secreted proteins and proteins comprising the secretion system itself are targeted by a fully functional T cell response. In addition, several novel T cell antigens were identified which can be of potential diagnostic use, or as vaccine antigens. These results underline the power of a truly unbiased, genome-wide, analysis of CD4 MTB recognition based on the combined use of epitope predictions, high throughput ELISPOT, and T cell libraries using PBMCs from individuals latently infected with MTB.
In order to identify the most attractive starting points for drugs that can be used to prevent malaria, a diverse chemical space comprising tens of thousands to millions of small molecules may need to be examined. Achieving this throughput necessitates the development of efficient ultra-high-throughput screening methods. Here, we report the development and evaluation of a luciferase-based phenotypic screen of malaria exoerythrocytic-stage parasites optimized for a 1536-well format. This assay uses the exoerythrocytic-stage of the rodent malaria parasite, Plasmodium berghei, and a human hepatoma cell line. We use this assay to evaluate several biased and unbiased compound libraries, including two small sets of molecules (400 and 89 compounds, respectively) with known activity against malaria erythrocytic-stage parasites and a set of 9,886 Diversity-Oriented Synthesis (DOS)-derived compounds. Of the compounds screened we obtain hit rates of 12–13% and 0.6% in preselected and naïve libraries, respectively, and identify 52 compounds with exoerythrocytic-stage activity less than 1 μM, and having minimal host cell toxicity. Our data demonstrate the ability of this method to identify compounds known to have causal prophylactic activity in both human and animal models of malaria, as well as novel compounds, including some exclusively active against parasite exoerythrocytic stages.
The exoerythrocytic stage of Plasmodium infection is a critical window for prophylactic intervention. Using genome-wide dual RNA sequencing of flow-sorted infected and uninfected hepatoma cells we show that the human mucosal immunity gene, mucin-13 (MUC13), is strongly upregulated during Plasmodium exoerythrocytic hepatic-stage infection. We confirm MUC13 transcript increases in hepatoma cell lines and primary hepatocytes. In immunofluorescence assays, host MUC13 protein expression distinguishes infected cells from adjacent uninfected cells and shows similar colocalization with parasite biomarkers such as UIS4 and HSP70. We further show that localization patterns are species independent, marking both P. berghei and P. vivax infected cells, and that MUC13 can be used to identify compounds that inhibit parasite replication in hepatocytes. This data provides insights into host-parasite interactions in Plasmodium infection, and demonstrates that a component of host mucosal immunity is reprogrammed during the progression of infection.
Parasitic diseases caused by protozoan pathogens lead to hundreds of thousands of deaths per year in addition to substantial suffering and socioeconomic decline for millions of people worldwide. The lack of effective vaccines coupled with the widespread emergence of drug-resistant parasites necessitates that the research community take an active role in understanding host-parasite infection biology in order to develop improved therapeutics. Recent advances in next-generation sequencing and the rapid development of publically accessible genomic databases for many human pathogens have facilitated the application of systems biology to the study of host-parasite interactions. Over the past decade, these technologies have led to the discovery of many important biological processes governing parasitic disease. The integration and interpretation of high-throughput –omic data will undoubtedly generate extraordinary insight into host-parasite interaction networks essential to navigate the intricacies of these complex systems. As systems analysis continues to build the foundation for our understanding of host-parasite biology, this will provide the framework necessary to drive drug discovery research forward and accelerate the development of new antiparasitic therapies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.