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Metamorphosis of the malaria parasite in the liver is associated with organelle clearance.

ABSTRACT: Malaria parasites encounter diverse conditions as they cycle between their vertebrate host and mosquito vector. Within these distinct environments, the parasite undergoes drastic transformations, changing both its morphology and metabolism. Plasmodium species that infect mammals must first take up residence in the liver before initiating red blood cell infection. Following penetration into hepatocytes, the parasite converts from an invasion-competent, motile, elongated sporozoite to a metabolically active, round trophozoite. Relatively little is known about the cellular events involved in sporozoite metamorphosis. Our data uncover the early cellular events associated with these transformations. We illustrate that the beginning of metamorphosis is marked by the disruption of the membrane cytoskeleton beneath the plasma membrane, which results in a protruding area around the nucleus. As this bulbous region expands, the two distal ends of the sporozoite gradually retract and disappear, leading to cell sphericalization. This shape change is associated with major interior renovations and clearance of superfluous organelles, e.g. micronemes involved in invasion. The membrane cytoskeleton is reorganized into dense lamellar arrays within the cytoplasm and is partially expulsed by converting parasites. Simultaneously, micronemes are compartmentalized into large exocytic vesicles and are then discharged into the environment. At the completion of metamorphosis, the parasites only retain organelles necessary for replication. These observations lay the groundwork for further investigations on the developmental pathways implicated in the metamorphosis of the malaria parasite.

SUBMITTER: Jayabalasingham B

PROVIDER: S-EPMC4137911 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature

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Metamorphosis of the malaria parasite in the liver is associated with organelle clearance.

Jayabalasingham Bamini B Bano Nazneen N Coppens Isabelle I

Cell research 20100622 9

Malaria parasites encounter diverse conditions as they cycle between their vertebrate host and mosquito vector. Within these distinct environments, the parasite undergoes drastic transformations, changing both its morphology and metabolism. Plasmodium species that infect mammals must first take up residence in the liver before initiating red blood cell infection. Following penetration into hepatocytes, the parasite converts from an invasion-competent, motile, elongated sporozoite to a metabolica ...[more]

PMID: 20567259

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Project description:BackgroundA significant reduction in parasite clearance rates following artesunate treatment of falciparum malaria, and increased failure rates following artemisinin combination treatments (ACT), signaled emergent artemisinin resistance in Western Cambodia. Accurate measurement of parasite clearance is therefore essential to assess the spread of artemisinin resistance in Plasmodium falciparum. The slope of the log-parasitaemia versus time relationship is considered to be the most robust measure of anti-malarial effect. However, an initial lag phase of numerical instability often precedes a steady exponential decline in the parasite count after the start of anti-malarial treatment. This lag complicates the clearance estimation, introduces observer subjectivity, and may influence the accuracy and consistency of reported results.MethodsTo address this problem, a new approach to modelling clearance of malaria parasites from parasitaemia-time profiles has been explored and validated. The methodology detects when a lag phase is present, selects the most appropriate model (linear, quadratic or cubic) to fit log-transformed parasite data, and calculates estimates of parasite clearance adjusted for this lag phase. Departing from previous approaches, parasite counts below the level of detection are accounted for and not excluded from the calculation.ResultsData from large clinical studies with frequent parasite counts were examined. The effect of a lag phase on parasite clearance rate estimates is discussed, using individual patient data examples. As part of the World Wide Antimalarial Resistance Network's (WWARN) efforts to make innovative approaches available to the malaria community, an automated informatics tool: the parasite clearance estimator has been developed.ConclusionsThe parasite clearance estimator provides a consistent, reliable and accurate method to estimate the lag phase and malaria parasite clearance rate. It could be used to detect early signs of emerging resistance to artemisinin derivatives and other compounds which affect ring-stage clearance.

Project description:BACKGROUND:Emerging resistance to anti-malarial drugs has led malaria researchers to investigate what covariates (parasite and host factors) are associated with resistance. In this regard, investigation of how covariates impact malaria parasites clearance is often performed using a two-stage approach in which the WWARN Parasite Clearance Estimator or PCE is used to estimate parasite clearance rates and then the estimated parasite clearance is regressed on the covariates. However, the recently developed Bayesian Clearance Estimator instead leads to more accurate results for hierarchial regression modelling which motivated the authors to implement the method as an R package, called "bhrcr". METHODS:Given malaria parasite clearance profiles of a set of patients, the "bhrcr" package performs Bayesian hierarchical regression to estimate malaria parasite clearance rates along with the effect of covariates on them in the presence of "lag" and "tail" phases. In particular, the model performs a linear regression of the log clearance rates on covariates to estimate the effects within a Bayesian hierarchical framework. All posterior inferences are obtained by a "Markov Chain Monte Carlo" based sampling scheme which forms the core of the package. RESULTS:The "bhrcr" package can be utilized to study malaria parasite clearance data, and specifically, how covariates affect parasite clearance rates. In addition to estimating the clearance rates and the impact of covariates on them, the "bhrcr" package provides tools to calculate the WWARN PCE estimates of the parasite clearance rates as well. The fitted Bayesian model to the clearance profile of each individual, as well as the WWARN PCE estimates, can also be plotted by this package. CONCLUSIONS:This paper explains the Bayesian Clearance Estimator for malaria researchers including describing the freely available software, thus making these methods accessible and practical for modelling covariates' effects on parasite clearance rates.

Dataset Information

Metamorphosis of the malaria parasite in the liver is associated with organelle clearance.

Publications

Metamorphosis of the malaria parasite in the liver is associated with organelle clearance.

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