The growth and the survival of the human malaria parasite Plasmodium falciparum are critically dependent on the functions of the two organelles - the mitochondrion and the apicoplast. However, these two organelles have been known to be difficult to separate from each other when they are released from Plasmodium cell. We have been searching for the conditions with which separation of the mitochondrion and the apicoplast is achieved. In this study, we investigated how the two organelle's separation is affected when the pressure of the nitrogen gas to disrupt the Plasmodium cells by nitrogen cavitation method is lowered from the pressure regularly applied (1200 psi). The parasite cell was sufficiently disrupted even when nitrogen cavitation was carried out at 300 psi. The obtained mitochondrial sample was much less contaminated by DNA compared with the sample prepared using the gas at the regular pressure. After the fractionation by Percoll density gradient, the mitochondrion and the apicoplast from the 300 psi cell lysate exhibited different separation profiles. This is the first experimental evidence that indicates the mitochondrion and the apicoplast of P. falciparum are separable from each other.
We describe here a reverse transcriptase-polymerase chain reaction method for the detection of malaria parasites. Ten in vitro-cultured isolates of Plasmodium falciparum and 16 specimens from patients infected with P. falciparum were used to examine the specificity and sensitivity of the test. The sensitivity of the test was 0.3 parasites per microliter of blood. Specificity was determined by matching the sequences of the specimens' DNA to published sequences of 18S ribosomal RNA genes in the species-specific region. The test proved to be very sensitive and specific for the detection of P. falciparum infection.
The malaria parasite Plasmodium falciparum has a nonphotosynthetic plastid called the apicoplast, which contains its own genome. Regulatory mechanisms for apicoplast gene expression remain poorly understood, despite this organelle being crucial for the parasite life cycle. Here, we identify a nuclear-encoded apicoplast RNA polymerase σ subunit (sigma factor) which, along with the α subunit, appears to mediate apicoplast transcript accumulation. This has a periodicity reminiscent of parasite circadian or developmental control. Expression of the apicoplast subunit gene, apSig, together with apicoplast transcripts, increased in the presence of the blood circadian signaling hormone melatonin. Our data suggest that the host circadian rhythm is integrated with intrinsic parasite cues to coordinate apicoplast genome transcription. This evolutionarily conserved regulatory system might be a future target for malaria treatment.
Plasmodium knowlesi (Pk) is a malaria parasite that naturally infects macaque monkeys in Southeast Asia. Pk malaria, the zoonosis transmitted from the infected monkeys to the humans by Anopheles mosquito vectors, is now a serious health problem in Malaysian Borneo. To create a strategic plan to control Pk malaria, it is important to estimate the occurrence of the disease correctly. The rise of Pk malaria has been explained as being due to ecological changes, especially deforestation. In this research, we analysed the time-series satellite images of MODIS (MODerate-resolution Imaging Spectroradiometer) of the Kudat Peninsula in Sabah and created the "Pk risk map" on which the Land-Use and Land-Cover (LULC) information was visualised. The case number of Pk malaria of a village appeared to have a correlation with the quantity of two specific LULC classes, the mosaic landscape of oil palm groves and the nearby land-use patches of dense forest, surrounding the village. Applying a Poisson multivariate regression with a generalised linear mixture model (GLMM), the occurrence of Pk malaria cases was estimated from the population and the quantified LULC distribution on the map. The obtained estimations explained the real case numbers well, when the contribution of another risk factor, possibly the occupation of the villagers, is considered. This implies that the occurrence of the Pk malaria cases of a village can be predictable from the population of the village and the LULC distribution shown around it on the map. The Pk risk map will help to assess the Pk malaria risk distributions quantitatively and to discover the hidden key factors behind the spread of this zoonosis.