| Literature DB >> 25881267 |
Casper Hempel1, Ida M Boisen2,3, Akinwale Efunshile4,5, Jørgen A L Kurtzhals6,7, Trine Staalsø8.
Abstract
BACKGROUND: Plasmodium falciparum exports antigens to the surface of infected erythrocytes causing cytoadhesion to the host vasculature. This is central in malaria pathogenesis but in vitro studies of cytoadhesion rely mainly on manual counting methods. The current study aimed at developing an automated high-throughput method for this purpose utilizing the pseudoperoxidase activity of intra-erythrocytic haemoglobin.Entities:
Mesh:
Year: 2015 PMID: 25881267 PMCID: PMC4391601 DOI: 10.1186/s12936-015-0632-4
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Figure 1Intraerythrocytic haem acts as a pseudoperoxidase and can be quantified with a chromogenic substrate. A) Lysed P. falciparum-infected erythrocytes oxidize the chromogenic substrate TMB. There is a strong correlation between the OD-value and number of lysed iRBC (r2 = 0.98, p <0.001). B) The chromogenic signals generated from lysates of known numbers of erythrocytes and infected erythrocytes from different conditions were compared 1 min after addition of TMB. No statistical difference was observed between erythrocyte populations (p >0.7). See text for details. C) When the haem-driven reaction was continued 11 min the signal decreased in wells with the highest numbers of erythrocytes and increased in wells with low number of erythrocytes. On all graphs, symbols represent mean values and error bars show standard deviation.
Figure 2Automated counting can detect binding comparable to manual microscopic examination. A) Increasing densities of parasites were added to wells and the numbers of adherent cells were quantified using both microscopic examination and automated detection. B) The mean value for each tested density for both methods was plotted against each other. The quantifications were highly correlated (r = 0.98, p <0.001). For the regression line, erythrocyte counts were calculated from OD-values in the automated method using a standard curve. C) Bland-Altman plot from a single experiment. Each circle represents the difference in mean quantity of adherent cells when counts from manual, microscopic counting are subtracted from automated reading at different seeding densities. 0 on the y-axis denotes identical result using both methods.
Figure 3Inhibition of binding can be assayed with high precision. A) Dose-dependent inhibition of binding to CHO-D677 (only expressing CS) after addition of increasing concentrations of soluble CS-A. CHO-A745 was included as non-CS-A control. B) Dose-dependent inhibition of binding to CHO-CD36 (transfected with human CD36) after addition of increasing concentrations of anti-CD36 is added. CHO-K1 (wild type) was included as CD36-negative control. Error bars show standard deviation.
Figure 4Binding of field isolates to human endothelial cells as well as parasites pre-selected for endothelial cytoadhesion can be quantified. Seven different parasite lines were tested for binding to hBMEC and hAEC. A) Bar graph showing binding to hBMEC. Binding to hBMEC is normalised to the binding of 3D7 SM [18] parasites not pre-selected to endothelial binding. B) Bar graph showing binding to hAEC. Binding to hAEC is normalised to the binding of 3D7 SM [18] parasites not pre-selected to endothelial binding. Bar show the mean fold change and error bars show standard deviation.