| Literature DB >> 31242921 |
Tobias O Apinjoh1, Amed Ouattara2, Vincent P K Titanji3, Abdoulaye Djimde4, Alfred Amambua-Ngwa5.
Abstract
The intensification of malaria control interventions has resulted in its global decline, but it remains a significant public health burden especially in sub-Saharan Africa (sSA). Knowledge on the parasite diversity, its transmission dynamics, mechanisms of adaptation to environmental and interventional pressures could help refine or develop new control and elimination strategies. Critical to this is the accurate assessment of the parasite's genetic diversity and monitoring of genetic markers of anti-malarial resistance across all susceptible populations. Such wide molecular surveillance will require selected tools and approaches from a variety of ever evolving advancements in technology and the changing epidemiology of malaria. The choice of an effective approach for specific endemic settings remains challenging, particularly for countries in sSA with limited access to advanced technologies. This article examines the current strategies and tools for Plasmodium falciparum genetic diversity typing and resistance monitoring and proposes how the different tools could be employed in resource-poor settings. Advanced approaches enabling targeted deep sequencing is valued as a sensitive method for assessing drug resistance and parasite diversity but remains out of the reach of most laboratories in sSA due to the high cost of development and maintenance. It is, however, feasible to equip a limited number of laboratories as Centres of Excellence in Africa (CEA), which will receive and process samples from a network of peripheral laboratories in the continent. Cheaper, sensitive and portable real-time PCR methods can be used in peripheral laboratories to pre-screen and select samples for targeted deep sequence or genome wide analyses at these CEAs.Entities:
Keywords: Drug resistance; Genetic diversity; Monitoring; Plasmodium falciparum
Mesh:
Substances:
Year: 2019 PMID: 31242921 PMCID: PMC6595576 DOI: 10.1186/s12936-019-2844-5
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Tools for drug resistance assessment and parasite diversity monitoring
| Tools | Capacity | Resources required | Advantages | Disadvantages |
|---|---|---|---|---|
| Drug resistance | ||||
| Ex vivo/in vitro tests | Few samples | BSL2 for parasite culture, refrigerator, freezer, microscope, incubator | Several tests possible on same sample, no heavy equipment | Labor-intensive, expensive, generalization difficult due to different tests/methods, requires advance culture infrastructure |
| RSA/PSA | ||||
| TES | Hundreds | Refrigerator, freezer, microscope, incubator, PCR machine, gel electrophoresis, transilluminator | No heavy equipment required | Expensive |
| Molecular markers | Hundreds | PCR machine, Restriction enzymes, refrigerator, freezer, | Ease of sampling, storage and transport | Markers not always linked to clinical outcome, require good infrastructure and trained personnel |
| Parasite diversity monitoring | ||||
| msp/glurp typing | Hundreds | PCR machine, Gel electrophoresis, transilluminator | Simple to implement | Labour-intensive, subjective interpretation |
| DNA barcodes | Thousands | Real time PCR | Sensitive, robust | Requires relatively sophisticated TaqMan or HRM assay |
| Microsatellite typing | Thousands | Real time PCR | Very informative from large range of alleles per locus | Requires relatively sophisticated PCR. Lack of standardization in scoring alleles |
| TDS | Hundreds | Sequencer, Server capacity for data storage | Less subject to inherent bias | High cost, requires large data storage capacity, requires skilled personnel. Target ascertainment bias |
| Genome wide analysis | Hundreds | Sequencers, Server capacity for data storage | Access to whole genome variants including single nucleotide and structural polymorphisms | As for TDS but need for target DNA enrichment against human DNA, difficulty in constructing haplotypes, and low sensitivity to detect minority clones |
BSL2 biosafety level 2, RSA ring stage assay, TES therapeutic efficacy studies, TDS targeted deep sequencing
Mode of action, targets and resistance mechanisms of drugs for P. falciparum malaria treatment and control in sSA
| Drugs | Mode of action | Molecular markers of resistance | Resistance mechanism |
|---|---|---|---|
| Artemether (AM) | Not well understood, oxidative damage to proteins and lipids and/or targeting the phosphatidylinositol-3-kinase (PfPI3K) | Not clearly understood; SNPs, CNVs | |
| Artesunate (AS) | |||
| Dihydroartemisinin (DHA) | |||
| Pyrimethamine | Inhibits folic acid synthesis |
| SNPs |
| Sulphadoxine |
| SNPs | |
| Amodiaquine (AQ), lumefantrine (LM) | Inhibits haem detoxification |
| SNPs |
| SNPs | |||
| Mefloquine (MQ) | CNVs | ||
| SNPs, CNVs | |||
| Quinine (QN) | SNPs | ||
| Piperaquine (PPQ) | Inhibits haem detoxification, inhibits one or more steps in the haemoglobin degradation | ||
| Clindamycin | Inhibits protein synthesis | CNVs | |
| Doxycycline |
Recommended ACTs for treatment of malaria have artemisinin or its derivative combined with one or more drugs and include: AL, AS–AQ, AS–MQ, AS–SP and DHA–PPQ. As of 2016, most African countries use AL and AS–AQ, with some adding DHA–PPQ for uncomplicated malaria, AS, AM and QN for severe malaria and SP for IPTp (1)
CNV copy number variation, Pfmrp-1 P. falciparum multi-resistance protein 1 gene, Pfnhe-1 P. falciparum Na+/H+ exchanger-1, Pfmdt P. falciparum metabolic drug transporter, PftetQ P. falciparum tet Q GTPase