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Kucharski, M.

Publications and source records attributed to Kucharski, M..

7 recordsLinked to original sources

Bacterial-Mimetic Membranes Reveal Hopanoid-Associated Domain-Like Lateral Heterogeneity

Bacterial membranes are increasingly recognized as laterally heterogeneous assemblies whose local organization can regulate transport, stress adaptation, and interactions with membrane-active compounds. However, the physical principles by which bacterial lipid composition generates spatially distinct membrane environments remain poorly understood, partly because experimentally tractable models that reproducibly exhibit lateral segregation and permit quantitative characterization are limited. Here, we show that a multicomponent, hopanoid-containing bacterial-inspired membrane spontaneously self-organizes into laterally distinct physical environments that are consistently resolved in experiments and molecular simulations. Giant unilamellar vesicles prepared from a lipid mixture inspired by lipid classes found in hopanoid-producing bacteria, including Methylorubrum extorquens, exhibit stable micron-scale lateral segregation, which is independently reproduced in compositionally matched coarse-grained molecular dynamics simulations. The resulting membrane environments differ in composition, packing, order, mobility, and mechanical properties. Hopanoid-associated domain-like regions are more condensed, more ordered, and less mobile, whereas PE-rich non-domain regions remain more laterally expanded and exhibit faster lipid diffusion. At the global level, the bacterial-inspired membrane displays greater bending rigidity than a fluid phosphatidylcholine reference, while ATR-FTIR measurements independently support increased lipid-chain ordering and denser membrane packing. Together, these findings establish that hopanoid-containing bacterial-inspired membranes can spontaneously generate coexisting physical environments whose distinct local properties collectively determine global membrane behavior. The resulting experimental-computational framework provides a quantitative basis for investigating bacterial-like membrane heterogeneity and how local composition, dynamics, and mechanics govern responses to membrane-targeting perturbations.

biophysics↗

Multi-omic profiling of Plasmodium knowlesi blood stages identifies host adaptation barriers

The zoonotic parasite Plasmodium knowlesi has emerged as a widespread cause of human malaria in Southeast Asia. We assembled a high-resolution transcriptome of zoonotic P. knowlesi across its intraerythrocytic developmental cycle and combined transcriptomics, quantitative proteomics and thermal stability measurements to compare parasites cultured in macaque and human red blood cells. We found that P. knowlesi accelerates through the ring stage to settle at the same developmental pace as P. falciparum during the trophozoite and schizont stages. Subsequent multi-omic analysis revealed broad transcriptional and proteomic adaptations of P. knowlesi to the human host cell environment. Parasites cultured in human cells expressed glutathione synthetase earlier and displayed changes in upstream processes that include NADPH production by the pentose phosphate pathway and glutamine synthesis. These changes were accompanied by further differences in the expression of ribosomal subunits and mitochondrial respiratory complexes. Together, our findings offer a systems-level view of non-genetic adaptations of P. knowlesi to the human red blood cell environment.

microbiology↗

A Bottom-Up Approach to Fungal Plasma Membrane Model: Lipid Mixture Design and Biophysical-Mechanical Characterization

The rising incidence of invasive fungal diseases emphasizes the need for novel therapeutic strategies, including membrane-targeting antifungal agents, which require representative lipid models for detailed molecular-level studies. In this work, we propose a consensus quinary fungal plasma membrane model based on lipidomic literature data, specifically PC:PE:PI:PA:PS phospholipid model with ratio of 44:29:13:8:6. Using a bottom-up approach, we characterized the biophysical properties of this system - with particular emphasis on mechanical parameters such as bending rigidity and area compressibility - by combining molecular dynamics simulations with experimental flicker-noise and ATR-FTIR spectroscopies. Furthermore, we investigated the effect of two key non-phospholipid components: ergosterol and triacylglycerols. Biophysical analysis revealed that DPPI and its specific interactions with DSPS induced the most substantial deviations in baseline membrane parameters, particularly area per lipid, membrane thickness, and area compressibility, while DSPS influenced bending rigidity change and DLiPA primarily affected lipid packing defects. In addition, ergosterol and TGs were found to influence all of the investigated parameters to different degree. Notably, the overall biophysical profile of the proposed FPMM closely mimicked that of natural vesicles derived from yeast lipid extracts, establishing this model may provide a reliable platform for studying fungal membrane biophysics and lipid-targeting interactions.

biophysics↗

Dihydroartemisinin induces a two-step transcriptional response and stage-specific developmental shifts in malaria parasites, Plasmodium falciparum

The parasite Plasmodium falciparum causes malaria, the deadliest human parasitic disease, which remains fatal when not promptly treated. Evolving parasite resistance to frontline artemisinin-based therapies threatens vulnerable populations and decades of progress toward malaria elimination. Yet the mode of action of dihydroartemisinin (DHA), the active metabolite of these treatments, remains incompletely understood. Here we applied dose-response transcriptomics across the three intraerythrocytic stages - rings, trophozoites, and schizonts, revealing a two-tier transcriptional response to DHA, with low- and high-dose programs consistent with specific drug action and cytotoxic damage. The trophozoite stage mounts the strongest and most coordinated response, including a striking reversal of the developmental cascade in which protein synthesis machinery is broadly downregulated and a ring-like transcriptional profile is reactivated - reminiscent of drug-induced quiescence. Coordinated regulation of multiple protein complexes, most notably Kelch13 and its interacting partners (KIC), points to organized transcriptional control of the parasites drug response. This work provides a stage- and dose-resolved view of DHA action in P. falciparum and a template for future antimalarial mechanism-of-action studies.

Systems Biology↗

Integrative genomics of Plasmodium knowlesi reveals parasite-intrinsic regulators of severe human malaria

To dissect parasite determinants of clinical disease severity in Plasmodium knowlesi, we performed the first integrative genome-wide association (GWAS), transcriptomic, and expression quantitative trait locus (eQTL) analysis from clinical malaria isolates. We identify distinct parasite programs associated with WHO-defined severe disease, characterized by transcriptional activation of stress-response and host-interaction pathways. In contrast, invasion-linked programs were more strongly associated with parasite burden, while immune-evasion pathways showed overlapping but distinct associations with both burden and severity. GWAS and eQTL analyses revealed genetic regulation of transcriptional states, including immune-evasion variant antigen families (SICAvar and kir) and chromatin-associated regulators. Mature gametocyte transcripts were detectable across infections, including those with low parasitaemia, indicating that transmission-stage expression occurs independently of both clinical severity and parasite density. Together, these findings show that severe P. knowlesi malaria is associated with genetically regulated parasite transcriptional programs that are not fully explained by parasite burden.

genomics↗

Genomic epidemiology of Plasmodium knowlesi reveals putative genetic drivers of adaptation in Malaysia.

Sabah, Malaysia, has amongst the highest burden of human Plasmodium knowlesi infection in the country, associated with increasing encroachment on the parasites macaque host habitat. However, the genomic make-up of P. knowlesi in Sabah was previously poorly understood. To inform on local patterns of transmission and putative adaptive drivers, we conduct population-level genetic analyses of P. knowlesi human infections using 52 new whole genomes from Sabah, Malaysia, in combination with publicly available data. We identify the emergence of distinct geographical subpopulations within the macaque-associated clusters using IBD-based connectivity analysis. Secondly, we report on introgression events between the clusters, which may be linked to differentiation of the subpopulations, and that overlap genes critical for survival in human and mosquito hosts. Using village-level locations from P. knowlesi infections, we also identify associations between several introgressed regions and both intact forest perimeter-area ratio and mosquito vector habitat suitability. Our findings provide further evidence of the complex role of changing ecosystems and sympatric macaque hosts in Malaysia driving distinct genetic changes seen in P. knowlesi populations. Future expanded analyses of evolving P. knowlesi genetics and environmental drivers of transmission will be important to guide public health surveillance and control strategies. Author SummaryThe zoonotic P. knowlesi parasite is an emerging, yet understudied, cause of malaria in Southeast Asia. Sabah, Malaysia, has amongst the highest burden of human P. knowlesi infection in the country, however, the region is currently understudied. Thus, we produced a collection of high-quality P. knowlesi genomes from Sabah, and in combination with publicly available data, performed an extensive population genetics analysis. Our work contributes novel insights for Plasmodium knowlesi population genetics and genetic epidemiology.

genomics↗

The mechanism of artemisinin resistance of Plasmodium falciparum malaria parasites originates in their initial transcriptional response.

The emergence and spread of artemisinin resistant Plasmodium falciparum, first in the Greater Mekong Subregion (GMS), and now in East Africa, is a major threat to global malaria eliminations ambitions. To investigate the artemisinin resistance mechanism, transcriptome analysis was conducted of 577 P. falciparum isolates collected in the GMS between 2016-2018. A specific artemisinin resistance-associated transcriptional profile was identified that involves a broad but discrete set of biological functions related to proteotoxic stress, host cytoplasm remodeling and REDOX metabolism. The artemisinin resistance-associated transcriptional profile evolved from initial transcriptional responses of susceptible parasites to artemisinin. The genetic basis for this adapted response is likely to be complex. One sentence summaryThe transcriptional profile that characterize artemisinin resistant infections with malaria parasites Plasmodium falciparum originates in the initial transcriptional response to the drug.

systems biology↗