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Biology subjects

Hirst, W. G.

Publications and source records attributed to Hirst, W. G..

2 recordsLinked to original sources

Purification of functional Plasmodium falciparum tubulin allows for the identification of parasite-specific microtubule inhibitors

Cytoskeletal proteins are essential for parasite proliferation, growth, and transmission, and therefore represent promising drug targets. While {beta}-tubulin, the molecular building block of microtubules, is an established drug target in a variety of cancers, we still lack substantial knowledge of the biochemistry of parasite tubulins, which would allow us to exploit the structural divergence between parasite and human tubulins. Indeed, mechanistic insights have been limited by the lack of purified, functional parasite tubulin. In this study, we isolated Plasmodium falciparum tubulin that is assembly-competent and shows specific microtubule dynamics in vitro. We further present mechanistic evidence that two compounds selectively interact with parasite over host microtubules and inhibit Plasmodium microtubule polymerization at substoichiometric compound concentrations. The ability of compounds to selectively disrupt protozoan microtubule growth without affecting human microtubules provides the exciting possibility for the targeted development of novel antimalarials.

biochemistry↗

MTrack: Automated Detection, Tracking, and Analysis of Dynamic Microtubules

Microtubules are polar, dynamic filaments fundamental to many cellular processes. In vitro reconstitution approaches with purified tubulin are essential to elucidate different aspects of microtubule behavior. To date, deriving data from fluorescence microscopy images by manually creating and analyzing kymographs is still commonplace. Here, we present MTrack, implemented as a plug-in for the open-source platform Fiji, which automatically identifies and tracks dynamic microtubules with sub-pixel resolution using advanced objection recognition. MTrack provides automatic data interpretation yielding relevant parameters of microtubule dynamic instability together with population statistics. The application of our software produces unbiased and comparable quantitative datasets in a fully automated fashion. This helps the experimentalist to achieve higher reproducibility at higher throughput on a user-friendly platform. We use simulated data and real data to benchmark our algorithm and show that it reliably detects, tracks, and analyzes dynamic microtubules and achieves sub-pixel precision even at low signal-to-noise ratios.

biophysics↗