Research Suggests New Approach to Combat Antimicrobial Resistant Malaria
The rise of antimicrobial resistant malaria, especially across Asia, has caused great concern and a hunt for new drugs and treatment. A collaborative group across Europe have systematically deleted genes from Plasmodium berghei and uncovered 7 metabolic pathways crucial for the life cycle of the parasite.
Targeting these metabolic pathways can halt the parasite in its tracks, preventing the infected from passing on marlaria or experiencing any of the symptoms.
Malaria is a global health problem, resulting in approximately one million deaths each year, and is caused by the bacterium Plasmodium transferred from mosquitos. Previous anti-malarial drugs have been relatively effective – for instance, the commonly used, dihydroartemisinin and piperaquine – but with the rise of resistant strains, there is a call for new treatments.
When bitten by an infected mosquito, the Plasmodium enters the bloodstream and quickly passes into the liver to multiply. During this liver stage there are no symptoms, until the parasite has multiplied rapidly – at which point the parasites are released and infect the bloodstream. This is when red blood cells are invaded, causing the fever and associated symptoms of malaria.
The group took a systematic approach to finding crucial gene functions in P. berghei by knocking out 1,300 genes individually and following each bacterium through its life cycle to discover any effects. Overall 461 genes were deemed to be essential for the efficient transmission from mosquitos to the liver stage of infected mice. The team identified 7 metabolic pathways that specifically affect the liver stage, including heme and type II fatty acid synthesis and elongation (FAE). These pathways indicate multiple new targets for future drug development that have previously been overlooked.
New drugs are desperately required as despite extensive research into targeting malaria, resistant strains are spreading across the world. The use of whole genome studies and computational models can provide new insights into tackling this deadly disease.