Ashdown, G. W. | Search bioRxiv

bioRxiv2021

4D live-cell imaging of microgametogenesis in the human malaria parasite Plasmodium falciparum

Formation of gametes in the malaria parasite occurs in the midgut of the mosquito and is critical to onward parasite transmission. Transformation of the male gametocyte into microgametes, called microgametogenesis, is an explosive cellular event and one of the fastest eukaryotic DNA replication events known. The transformation of one microgametocyte into eight flagellated microgametes requires reorganisation of the parasite cytoskeleton, replication of the 22.9 Mb genome, axoneme formation and host erythrocyte egress, all of which occur simultaneously in <20 minutes. Whilst high-resolution imaging has been a powerful tool for defining stages of microgametogenesis, it has largely been limited to fixed parasite samples, given the speed of the process and parasite photosensitivity. Here, we have developed a live-cell fluorescence imaging workflow that captures the explosive dynamics of microgametogenesis in full. Using the most virulent human malaria parasite, Plasmodium falciparum, our live-cell approach combines three-dimensional imaging through time (4D imaging) and covers early microgametocyte development through to microgamete release. Combining live-cell stains for DNA, tubulin and the host erythrocyte membrane, 4D imaging enables definition of the positioning of newly replicated and segregated DNA. It also shows the microtubular cytoskeleton, location of newly formed basal bodies and elongation of axonemes, as well as behaviour of the erythrocyte membrane, including its specific perforation prior to microgamete egress. 4D imaging was additionally undertaken in the presence of known transmission-blocking inhibitors and the untested proteasomal inhibitor bortezomib. Here, for the first time we find that bortezomib inhibition results in a clear block of DNA replication, full axoneme nucleation and elongation. These data not only define a framework for understanding microgametogenesis in general but also suggest that the process is critically dependent on proteasomal activity, helping to identify potentially novel targets for transmission-blocking antimalarial drug development.

microbiology↗

bioRxiv2019

A machine learning approach to define antimalarial drug action from heterogeneous cell-based screens

Drug resistance threatens the effective prevention and treatment of an ever-increasing range of human infections. This highlights an urgent need for new and improved drugs with novel mechanisms of action to avoid cross-resistance. Current cell-based drug screens are, however, restricted to binary live/dead readouts with no provision for mechanism of action prediction. Machine learning methods are increasingly being used to improve information extraction from imaging data. Such methods, however, work poorly with heterogeneous cellular phenotypes and generally require time-consuming human-led training. We have developed a semi-supervised machine learning approach, combining human- and machine-labelled training data from mixed human malaria parasite cultures. Designed for high-throughput and high-resolution screening, our semi-supervised approach is robust to natural parasite morphological heterogeneity and correctly orders parasite developmental stages. Our approach also reproducibly detects and clusters drug-induced morphological outliers by mechanism of action, demonstrating the potential power of machine learning for accelerating cell-based drug discovery. One Sentence SummaryA machine learning approach to classifying normal and aberrant cell morphology from plate-based imaging of mixed malaria parasite cultures, facilitating clustering of drugs by mechanism of action.

microbiology↗