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Liposomal amphotericin B is an important frontline drug for the treatment of visceral leishmaniasis, a neglected disease of poverty. The mechanism of action of amphotericin B (AmB) is thought to involve interaction with ergosterol and other ergostane sterols, resulting in disruption of the integrity and key functions of the plasma membrane. Emergence of clinically refractory isolates of L. donovani and L. infantum is an ongoing issue and knowledge of potential resistance mechanisms can help to alleviate this problem. Here we report the characterisation of four independently selected L. donovani clones that are resistant to AmB. Whole genome sequencing revealed that in three of the moderately resistant clones, resistance was due solely to the deletion of a gene encoding C24-sterol methyltransferase (SMT1). The fourth, hyper-resistant resistant clone (>60-fold) was found to have a 24 bp deletion in both alleles of a gene encoding a putative cytochrome P450 reductase (P450R1). Metabolic profiling indicated these parasites were virtually devoid of ergosterol (0.2% versus 18% of total sterols in wild-type) and had a marked accumulation of 14-methylfecosterol (75% versus 0.1% of total sterols in wild-type) and other 14-alpha methylcholestanes. These are substrates for sterol 14-alpha demethylase (CYP51) suggesting that this enzyme may be a bona fide P450R specifically involved in electron transfer from NADPH to CYP51 during catalysis. Deletion of P450R1 in wild-type cells phenocopied the metabolic changes observed in our AmB hyper-resistant clone as well as in CYP51 nulls. Likewise, addition of a wild type P450R1 gene restored sterol profiles to wild type. Our studies indicate that P450R1 is essential for L. donovani amastigote viability, thus loss of this gene is unlikely to be a driver of clinical resistance. Nevertheless, investigating the mechanisms underpinning AmB resistance in these cells provided insights that refine our understanding of the L. donovani sterol biosynthetic pathway. Author summary: The antifungal drug, amphotericin B, is also used in the treatment of visceral leishmaniasis, a potentially lethal parasitic disease infecting the specialised immune cells (macrophages) in the liver, spleen, and bone marrow. Treatment failures due to emerging drug resistance are a significant concern. Using a combination of genetic and biochemical approaches, we have confirmed the mechanisms by which these parasites become less sensitive to treatment with amphotericin B. In addition, we have identified a novel mechanism involving loss of a key enzyme (cytochrome P450 reductase 1) in the biosynthetic pathway to ergosterol, an important lipid component of the parasite's plasma membrane. These studies increase our fundamental understanding of this important metabolic pathway and provide information that may be exploited to develop novel therapeutic strategies to combat this killer disease. [ABSTRACT FROM AUTHOR]

Abstract Background Protein interactions support cell organization and mediate its response to any specific stimulus. Recent technological advances have produced large data-sets that aim at describing the cell interactome. These data are usually presented as graphs where proteins (nodes) are linked by edges to their experimentally determined partners. This representation reveals that protein-protein interaction (PPI) networks, like other kinds of complex networks, are not randomly organized and display properties that are typical of "hierarchical" networks, combining modularity and local clustering to scale free topology. However informative, this representation is static and provides no clue about the dynamic nature of protein interactions inside the cell. Results To fill this methodological gap, we designed and implemented a computer model that captures the discrete and stochastic nature of protein interactions. In ProtNet, our simplified model, the intracellular space is mapped onto either a two-dimensional or a three-dimensional lattice with each lattice site having a linear size (5 nm) comparable to the diameter of an average globular protein. The protein filled lattice has an occupancy (e.g. 20%) compatible with the estimated crowding of proteins in the cell cytoplasm. Proteins or protein complexes are free to translate and rotate on the lattice that represents a sort of naïve unstructured cell (devoid of compartments). At each time step, molecular entities (proteins or complexes) that happen to be in neighboring cells may interact and form larger complexes or dissociate depending on the interaction rules defined in an experimental protein interaction network. This whole procedure can be seen as a sort of "discrete molecular dynamics" applied to interacting proteins in a cell. We have tested our model by performing different simulations using as interaction rules those derived from an experimental interactome of Saccharomyces cerevisiae (1378 nodes, 2491 edges) and we have compared the dynamics of complex formation in a two and a three dimensional lattice model. Conclusion ProtNet is a cellular automaton model, where each protein molecule or complex is explicitly represented and where simple interaction rules are applied to populations of discrete particles. This tool can be used to simulate the dynamics of protein interactions in the cell.