RON4L1 is a new member of the moving junction complex in Toxoplasma gondii

Abstract Apicomplexa parasites, including Toxoplasma and Plasmodium species, possess a unique invasion mechanism that involves a tight apposition between the parasite and the host plasma membranes, called “moving junction” (MJ). The MJ is formed by the assembly of the microneme protein AMA1, exposed at the surface of the parasite, and the parasite rhoptry neck (RON) protein RON2, exposed at the surface of the host cell. In the host cell, RON2 is associated with three additional parasite RON proteins, RON4, RON5 and RON8. Here we describe RON4L1, an additional member of the MJ complex in Toxoplasma. RON4L1 displays some sequence similarity with RON4 and is cleaved at the C-terminal end before reaching the rhoptry neck. Upon secretion during invasion, RON4L1 is associated with MJ and targeted to the cytosolic face of the host membrane. We generated a RON4 L1 knock-out cell line and showed that it is not essential for the lytic cycle in vitro, although mutant parasites kill mice less efficiently. Similarly to RON8, RON4L1 is a coccidian-specific protein and its traffic to the MJ is not affected in absence of RON2, RON4 and RON5, suggesting the co-existence of independent MJ complexes in tachyzoite of Toxoplasma

Improving Prognostic Modeling in Myelodysplastic Syndromes

Myelodysplastic syndromes (MDSs) are a heterogeneous group of disorders characterized by the accumulation of complex genetic alterations that drive disease pathogenesis and outcome. Several prognostic models have been developed over the last two decades to risk stratify patients with MDS. These models mainly used clinical variables including blast percentage, cytopenias, cytogenetics, transfusion dependency, and age. Recently, somatic mutations in specific genes have been shown to impact overall survival in MDS and can be incorporated into established prognostic models to improve their predictive abilities. Here, we review the advantages and disadvantages of established prognostic models in MDS and the impact of emerging data regarding the incorporation of somatic mutations in risk stratification