Comparative 3D ultrastructure of Plasmodium falciparum gametocytes

April 07, 2023

Felix Evers (1), Rona Roverts (2) (3), Cas Boshoven (1), Mariska Kea-te Lindert (2) (3), Julie M.J. Verhoef (1), Robert E. Sinden (4), Anat Akiva (2) (3), Taco W.A. Kooij (1)
bioXriv. (7 April 2023). DOI: https://doi.org/10.1101/2023.03.10.531920


Abstract

Despite the enormous significance of malaria parasites for global health, some basic features of their ultrastructure remain obscure. In this study, we apply high-resolution volumetric electron microscopy to examine and compare the ultrastructure of Plasmodium falciparumgametocytes of both genders and in different stages of development as well as the more intensively studied asexual blood stages revisiting previously described phenomena in 3D. In doing so, we challenge the widely accepted notion of a single mitochondrion by demonstrating the presence of multiple mitochondria in gametocytes. We also provide evidence for a gametocyte-specific cytostome variant. Furthermore, we generate, among other organelles, the first 3D reconstructions of endoplasmic reticulum (ER), Golgi apparatus, and extraparasitic structures in gametocytes. Assessing interconnectivity between organelles, we find frequent structural appositions between the nucleus, mitochondria, and apicoplast. We provide evidence that the ER is a promiscuous interactor with numerous organelles and the trilaminar membrane of the gametocyte. Public availability of these volumetric electron microscopy resources of wild-type asexual and sexual blood-stage malaria parasites will facilitate reinterrogation of this global dataset with different research questions and expertise. Taken together, we reconstruct the 3D ultrastructure of P. falciparumgametocytes in high detail and shed light on the unique organellar biology of these deadly parasites.


How Our Software Was Used

All processing, visualization and analysis were performed in Dragonfly. Whenever necessary image stacks were aligned using the mutual information and sum of squared differences registration methods available in Dragonfly’s Slice Registration module. Contrast was enhanced through application of contrast limited adaptive histogram equalization (CLAHE). 3D segmentation was performed using either manual segmentation or deep learning based segmentation, based on which cellular feature was segmented. For 3D rendering the segmented regions of interest were converted to triangle meshes.


Author Affiliation

(1) Department of Medical Microbiology, Radboudumc Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
(2) Electron Microscopy Center, RTC Microscopy, Radboud University Medical Center, Nijmegen, the Netherlands
(3) Department of Medical Biosciences, Radboud University Medical Center, Nijmegen, the Netherlands
(4) Department of Life Sciences, Imperial College London, London, UK