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Protein profiling of mefloquine resistant Plasmodium falciparum using mass spectrometry-based proteomics.

ABSTRACT: Malaria is a mosquito borne infectious disease caused by protozoa of genus Plasmodium. There are five species of Plasmodium that are found to infect humans. Plasmodium falciparum can cause severe malaria leading to higher morbidity and mortality of malaria than the other four species. Antimalarial resistance is the major obstacle to control malaria. Mefloquine was used in combination with Artesunate for uncomplicated P. falciparum in South East Asia and it has developed and established mefloquine resistance in this region. Here, gel-enhanced liquid chromatography/tandem mass spectrometry (GeLC-MS/MS)-based proteomics and label-free quantification were used to explore the protein profiles of mefloquine-sensitive and -induced resistant P. falciparum. A Thai P. falciparum isolate (S066) was used as a model in this research. Our data revealed for the first time that 69 proteins exhibited at least 2-fold differences in their expression levels between the two parasite lines. Of these, 36 were up-regulated and 33 were down-regulated in the mefloquine-resistant line compared with the mefloquine-sensitive line. These findings are consistent with those of past studies, where the multidrug resistance protein Pgh1 showed an up-regulation pattern consistent with that expected from its average 3-copy pfmdr1 gene number. Pgh1 and eight other up-regulated proteins (i.e., histo-aspartyl protease protein, exportin 1, eukaryotic translation initiation factor 3 subunit 8, peptidyl-prolyl cis-trans isomerase, serine rich protein homologue, exported protein 1, ATP synthase beta chain and phospholipid scramblase 1) were further validated for their expression levels using reverse transcriptase quantitative real-time PCR. The data support the up-regulation status in the mefloquine-resistant parasite line of all the candidate genes referred to above. Therefore, GeLC-MS/MS-based proteomics combined with label-free quantification is a reliable approach for exploring mefloquine resistance biomarkers in P. falciparum. Identification of these proteins leads to better understanding of mefloquine resistant mechanisms in malaria parasites.

SUBMITTER: Reamtong O

PROVIDER: S-EPMC4708064 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Protein profiling of mefloquine resistant Plasmodium falciparum using mass spectrometry-based proteomics.

Reamtong Onrapak O Srimuang Krongkan K Saralamba Naowarat N Sangvanich Polkit P Day Nicholas P J NP White Nicholas J NJ Imwong Mallika M

International journal of mass spectrometry 20151101

Malaria is a mosquito borne infectious disease caused by protozoa of genus Plasmodium. There are five species of Plasmodium that are found to infect humans. Plasmodium falciparum can cause severe malaria leading to higher morbidity and mortality of malaria than the other four species. Antimalarial resistance is the major obstacle to control malaria. Mefloquine was used in combination with Artesunate for uncomplicated P. falciparum in South East Asia and it has develop ...[more]

PMID: 26869851

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Project description:Malaria is a global infectious disease that threatens the lives of millions of people. Transcriptomics, proteomics and functional genomics studies, as well as sequencing of the Plasmodium falciparum and Homo sapiens genomes, have shed new light on this host-parasite relationship. Recent advances in accurate mass measurement mass spectrometry, sophisticated data analysis software, and availability of biological pathway databases, have converged to facilitate our global, untargeted biochemical profiling study of in vitro P. falciparum-infected (IRBC) and uninfected (NRBC) erythrocytes. In order to expand the number of detectable metabolites, several key analytical steps in our workflows were optimized. Untargeted and targeted data mining resulted in detection of over one thousand features or chemical entities. Untargeted features were annotated via matching to the METLIN metabolite database. For targeted data mining, we queried the data using a compound database derived from a metabolic reconstruction of the P. falciparum genome. In total, over one hundred and fifty differential annotated metabolites were observed. To corroborate the representation of known biochemical pathways from our data, an inferential pathway analysis strategy was used to map annotated metabolites onto the BioCyc pathway collection. This hypothesis-generating approach resulted in over-representation of many metabolites onto several IRBC pathways, most prominently glycolysis. In addition, components of the "branched" TCA cycle, partial urea cycle, and nucleotide, amino acid, chorismate, sphingolipid and fatty acid metabolism were found to be altered in IRBCs. Interestingly, we detected and confirmed elevated levels for cyclic ADP ribose and phosphoribosyl AMP in IRBCs, a novel observation. These metabolites may play a role in regulating the release of intracellular Ca(2+) during P. falciparum infection. Our results support a strategy of global metabolite profiling by untargeted data acquisition. Untargeted and targeted data mining workflows, when used together to perform pathway-inferred metabolomics, have the benefit of obviating MS/MS confirmation for every detected compound.

Project description:BackgroundDeclining in susceptibility of Plasmodium falciparum to mefloquine is reported in South-East Asia. A revisiting on mefloquine pharmacokinetics-pharmacodynamics (PK/PD) could assist in finding new appropriate dosage regimens in combination with artesunate as a three-day course treatment.ObjectiveThis study aimed to investigate promising alternative artesunate-mefloquine combination regimens that are effective for the treatment of patients with mefloquine-sensitive and resistant P. falciparum malaria.MethodsData collected during 2008-2009 from 124 patients with uncomplicated P. falciparum malaria were included in the analysis, 90 and 34 patients with sensitive and recrudescence response, respectively. All patients were treated with a three-day combination of artesunate-mefloquine. Population PK-PD models were developed. The developed models were validated with clinically observed data. Simulations of clinical efficacy of alternative mefloquine regimens were performed based on mefloquine sensitivity, patients' adherence and parasite biomass.ResultsThe developed PK/PD models well described with clinically observed data. For mefloquine-resistant P. falciparum, a three-day standard regimen of artesunate-mefloquine is suitable (>50% efficacy) only when the level of parasite sensitivity was < 1.5-fold of the cut-off level (IC50 < 36 nM). For mefloquine-sensitive parasite with IC50 < 23.19 nM (0.96-fold), all regimens provided satisfactory efficacy. In the isolates with IC50 of 24 nM, regimen-I is recommended. Curative treatment criteria for mefloquine and artesunate were C336h (>408 ng.mL-1) or Cmax/IC50 (>130.1 g.m/M), and Cmax/IC50 (>381.2 g.m/M), respectively.ConclusionsClinical use of a three-day standard artesunate-mefloquine is suitable only when the IC50 of P. falciparum isolates is lower than 36 nM. Otherwise, other ACT regimens should be replaced. For mefloquine-sensitive parasite, a dose reduction is recommended with the IC50 is lower than 23.19 nM.

Project description:BackgroundArtemisinin-based combination therapy (ACT) is recommended as a means of prolonging the effectiveness of first-line malaria treatment regimens. Different brands of mefloquine (MQ) have been reported to be non-bioequivalent; this could result in sub-therapeutic levels of mefloquine with decreased efficacy. In 2002, mefloquine-artesunate (MQ-AS) combination therapy was adopted as the first-line treatment for uncomplicated Plasmodium falciparum malaria in the Amazon region of Peru. Although MQ resistance has yet to be reported from the Peruvian Amazon, it has been reported from other countries in the Amazon Region. Therefore, continuous monitoring is warranted to ensure that the first-line therapy remains efficacious. This study examines the in vivo efficacy and pharmacokinetic parameters through Day 56 of three commercial formulations of MQ (Lariam, Mephaquin, and Mefloquina-AC Farma) given in combination with artesunate.MethodsThirty-nine non-pregnant adults with P. falciparum mono-infection were randomly assigned to receive artesunate in combination with either (1) Lariam, (2) Mephaquin, or (3) Mefloquina AC. Patients were assessed on Day 0 (with blood samples for pharmacokinetics at 0, 2, 4, and 8 hours), 1, 2, 3, 7, and then weekly until day 56. Clinical and parasitological outcomes were based on the standardized WHO protocol.Whole blood mefloquine concentrations were determined by high-performance liquid chromatography and pharmacokinetic parameters were determined using non-compartmental analysis of concentration versus time data.ResultsBy day 3, all patients had cleared parasitaemia except for one patient in the AC Farma arm; this patient cleared by day 4. No recurrences of parasitaemia were seen in any of the 34 patients. All three MQ formulations had a terminal half-life of 14-15 days and time to maximum plasma concentration of 45-52 hours. The maximal concentration (Cmax) and interquartile range was 2,820 ng/ml (2,614-3,108) for Lariam, 2,500 ng/ml (2,363-2,713) for Mephaquin, and 2,750 ng/ml (2,550-3,000) for Mefloquina AC Farma. The pharmacokinetics of the three formulations were generally similar, with the exception of the Cmax of Mephaquin which was significantly different to that of Lariam (p = 0.04).ConclusionAll three formulations had similar pharmacokinetics; in addition, the pharmacokinetics seen in this Peruvian population were similar to reports from other ethnic groups. All patients rapidly cleared their parasitaemia with no evidence of recrudescence by Day 56. Continued surveillance is needed to ensure that patients continue to receive optimal therapy.

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Protein profiling of mefloquine resistant Plasmodium falciparum using mass spectrometry-based proteomics.

Publications

Protein profiling of mefloquine resistant <i>Plasmodium falciparum</i> using mass spectrometry-based proteomics.

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