Amoebiasis is caused by Entamoeba histolytica infection, a protozoan parasite belonging to the phylum Amoebozoa. This parasite undergoes a fundamental cell differentiation process from proliferative trophozoite to dormant cyst, termed “encystation.” The cysts formed by encystation are solely responsible for the transmission of amoebiasis; therefore, Entamoeba encystation is an important subject from both biological and medical perspectives. Here, we have established a flow cytometry strategy for not only determining the percentage of formed cysts but also for monitoring changes in cell populations during encystation. This strategy together with fluorescence microscopy enables visualization of the cell differentiation process of Entamoeba encystation. We also standardized another flow cytometry protocol for counting live trophozoites. These two different flow cytometry techniques could be integrated into 96-well plate-based bioassays for monitoring the processes of cyst formation and trophozoite proliferation, which are crucial to maintain the Entamoeba life cycle. The combined two systems enabled us to screen a chemical library, the Pathogen Box of the Medicine for Malaria Venture, to obtain compounds that inhibit either the formation of cysts or the proliferation of trophozoites, or both. This is a prerequisite for the development of new drugs against amoebiasis, a global public health problem. Collectively, the two different 96-well plate-based Entamoeba bioassay and flow cytometry analysis systems (cyst formation and trophozoite proliferation) provide a methodology that can not only overcome the limitations of standard microscopic counting but also is effective in applied as well as basic Entamoeba biology.

Background Amoebiasis, caused by Entamoeba histolytica infection, is a global public health problem. However, available drugs to treat amoebiasis are currently limited, and no effective vaccine exists. Therefore, development of new preventive measures against amoebiasis is urgently needed. Methodology/Principal findings Here, to develop new drugs against amoebiasis, we focused on E . histolytica adenosine 5′-phosphosulfate kinase (EhAPSK), an essential enzyme in Entamoeba sulfolipid metabolism. Fatty alcohol disulfates and cholesteryl sulfate, sulfolipids synthesized in Entamoeba , play important roles in trophozoite proliferation and cyst formation. These processes are closely associated with clinical manifestation and severe pathogenesis of amoebiasis and with disease transmission, respectively. We validated a combination approach of in silico molecular docking analysis and an in vitro enzyme activity assay for large scale screening. Docking simulation ranked the binding free energy between a homology modeling structure of EhAPSK and 400 compounds. The 400 compounds were also screened by a 96-well plate-based in vitro APSK activity assay. Among fifteen compounds identified as EhAPSK inhibitors by the in vitro system, six were ranked by the in silico analysis as having high affinity toward EhAPSK. Furthermore, 2-(3-fluorophenoxy)-N-[4-(2-pyridyl)thiazol-2-yl]-acetamide, 3-phenyl-N-[4-(2-pyridyl)thiazol-2-yl]-imidazole-4-carboxamide, and auranofin, which were identified as EhAPSK inhibitors by both in silico and in vitro analyses, halted not only Entamoeba trophozoite proliferation but also cyst formation. These three compounds also dose-dependently impaired the synthesis of sulfolipids in E . histolytica . Conclusions/Significance Hence, the combined approach of in silico and in vitro -based EhAPSK analyses identified compounds that can be evaluated for their effects on Entamoeba . This can provide leads for the development of new anti-amoebic and amoebiasis transmission-blocking drugs. This strategy can also be applied to identify specific APSK inhibitors, which will benefit research into sulfur metabolism and the ubiquitous pathway terminally synthesizing essential sulfur-containing biomolecules.

To explore multi-core programming, we re-implement the Lock Free Contention Adapting Search Tree. We follow the structure of the original, using immutable treaps as leaf nodes implemented with an array for better performance with memory caching. Memory leaks are prevented through preallocation of elements. We evaluate the performance of the LFCA tree and compare it to the previous MRLock version. The LFCA tree performs better in all cases with multiple threads.