Abstract
Malaria has had a major effect on the human genome, with many protective polymorphisms—such as the sickle-cell trait—having been selected to high frequencies in malaria-endemic regions1,2. The blood group variant Dantu provides 74% protection against all forms of severe malaria in homozygous individuals3,4,5, a similar degree of protection to that afforded by the sickle-cell trait and considerably greater than that offered by the best malaria vaccine. Until now, however, the protective mechanism has been unknown. Here we demonstrate the effect of Dantu on the ability of the merozoite form of the malaria parasite Plasmodium falciparum to invade red blood cells (RBCs). We find that Dantu is associated with extensive changes to the repertoire of proteins found on the RBC surface, but, unexpectedly, inhibition of invasion does not correlate with specific RBC–parasite receptor–ligand interactions. By following invasion using video microscopy, we find a strong link between RBC tension and merozoite invasion, and identify a tension threshold above which invasion rarely occurs, even in non-Dantu RBCs. Dantu RBCs have higher average tension than non-Dantu RBCs, meaning that a greater proportion resist invasion. These findings provide both an explanation for the protective effect of Dantu, and fresh insight into why the efficiency of P. falciparum invasion might vary across the heterogenous populations of RBCs found both within and between individuals.
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Data availability
The authors declare that the data supporting the findings of this study are available within the manuscript and its Supplementary Information files. Source data are provided with this paper.
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Acknowledgements
We thank E. Mabibo, J. Golijo, A. Kazungu, R. Mwarabu, the staff of Kilifi County Hospital and the KEMRI–Wellcome Trust Research Programme, Kilifi, for their help with participant recruitment and data and sample collection; and E. Leffler and G. Band for discussions on the study. We also thank the study participants and their parents for agreeing to participate in this study. J.C.R., A.M. and D.K. were supported by the Wellcome Trust (grant 206194/Z/17/Z). We acknowledge V. Lew and T. Tiffert for the provision of fresh blood and useful discussions. M.P.W. is funded by a Wellcome Senior Fellowship (grant 108070). T.N.W. is funded by fellowships awarded by the Wellcome Trust (grants 091758 and 202800). S.N.K. is supported by a Wellcome Trust funded Initiative to Develop African Research Leaders (IDeAL) early-career postdoctoral fellowship (107769/Z/10/Z), supported through the Developing Excellence in Leadership, Training and Science (DELTAS) Africa Initiative (DEL-15-003). The Wellcome Trust provides core support to the KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya (084535), the Wellcome Sanger Institute, Cambridge, UK (206194/Z/17/Z) and the Wellcome Centre for Human Genetics, Oxford, UK (090532/Z/09/Z and 203141). P.C. is supported by the Engineering and Physical Sciences Research Council (EPSRC); EP/R011443/1), and V.I. is supported by the EPSRC and a Sackler fellowship. This paper is published with permission from the director of KEMRI.
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S.N.K., A.M.-M., V.I., B.J.R., Y.-C.L., M.P.W., P.C., T.N.W. and J.C.R. conceived and planned the experiments. S.N.K. and A.M.-M. carried out genotyping, RBC preference invasion and RBC membrane protein characterization by flow cytometry. V.I. and Y.-C.L. performed live video imaging. V.I. carried out optical-tweezer experiments and RBC membrane contour detection and flickering spectrometry. B.J.R. performed the RBC plasma membrane profiling. Each of the authors analysed the experiments that they had carried out. A.M., J.M., M.T. and W.N. contributed to sample preparation and genotyping. J.K., M.C., J.A.R., K.R. and D.K. contributed to the interpretation of the results. All authors provided essential feedback and helped to shape the research, analysis and manuscript.
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Extended data figures and tables
Extended Data Fig. 1 Erythrocytic cycle of malaria parasites.
Illustration of the erythrocytic (RBC) stage of the malaria parasite. a, The merozoites undergo repeated rounds of asexual multiplication, progressing through ring, trophozoite and schizont stages. 1, The cycle starts when merozoites contact, attach and successfully invade RBCs in the circulation. The invasion period lasts for less than a minute and we are only able to follow the dynamics of such a fast event with real-time live microscopy11,27. The merozoite has a slightly ovoidal shape of 1 μm in diameter and is adapted for invasion of RBCs. The apical end of the parasite contains secretory organelles called rhoptries and micronemes that release proteins to help the merozoite’s internalization. In the host RBC, the parasite develops and multiplies, digesting haemoglobin, protected from immune attack. In the case of P. falciparum, the erythrocytic cycle lasts about 48 h, and infected cells progress from the ring stage (2; the first 16 h) through the trophozoite stage (3; around 16–36 h) and, finally to the schizont phase (4; a few hours). 5, The infected schizont then ruptures, releasing 15–30 daughter merozoites ready to infect new nearby RBCs. 6, In each cycle, less than 10% of parasites develop into the sexual form of the parasite, called gametocytes. b, Detailed illustration of parasite invasion into the RBC (1; described further in the Methods), involving the pre-invasion phase (contact, merozoite reorientation triggering RBC membrane deformation, and tight attachment of the merozoite to the RBC membrane), the invasion phase (initiation of invasion, penetration, complete internalization of the merozoite, and resealing of the RBC membrane), and the echinocytosis phase (formation of the echinocyte form of the RBC). Icons adapted from ©biorender.com.
Extended Data Fig. 2 Invasion process across Dantu genotype groups studied by time-lapse video microscopy.
a, The force of RBC detachment from a merozoite was measured using optical tweezers across genotype groups. RBCs attached to merozoites were pulled using optical traps, and the adhesive forces at the merozoite–RBC interface were quantified by evaluating the elastic morphological response of the RBCs as they resisted merozoite detachment. Means and standard deviations (s.d.) are shown in Supplementary Table 3. Six biologically independent samples per genotype group were tested, obtaining 21 events for non-Dantu individuals, 19 for Dantu heterozygotes, and 24 for Dantu homozygotes. The experimentalist was blinded to the RBC genotype group. The median is indicated by the middle red line in the boxplots, with the 25th and 75th percentiles indicated by the tops and bottoms of each plot, and the total data range shown by whiskers. If the median is not centred in the box, it shows sample skewness. Pairwise comparisons between genotype groups were performed using the two-sided Mann–Whitney U-test. b, The degree to which merozoites deformed RBCs during invasion is given by a simplified four-point deformation scale (0, 1, 2 and 3), with 3 indicating the most extreme degree of deformation achieved10. The degree of deformation was compared across genotype groups with no significant difference noticed, and between successful and failed invasions. The percentage of RBCs undergoing strong deformations (score 2/3) is substantially higher in the case of successful invasions, while RBCs that were contacted but not invaded experience weak deformations (score 0/1). Data are from 155 cells for non-Dantu individuals, 191 for Dantu heterozygotes, and 233 for Dantu homozygotes. Numbers of successfully invaded cells are 53 for non-Dantu, 43 for Dantu heterozygote, and 41 for Dantu homozygote. The visual assessment was made with blinded data by two different experimentalists. c, Successful invasions are usually followed by a reversible echinocyte phase that lasts between 5 min and 11 min31, until the recovery of newly infected RBC biconcave shape. The duration of echinocytosis here is in agreement with the literature and not significantly different across genotype groups; data from 53 cells non-Dantu, 43 Dantu heterozygotes and 41 Dantu homozygotes.
Extended Data Fig. 3 Distribution of reticulocytes and RNA concentrations across Dantu genotypes.
Reticulocyte counts, and concentrations of RNA extracted from reticulocytes, were compared across Dantu genotypes. Reticulocyte count data were tested for 8 non-Dantu individuals, 7 Dantu heterozygotes and 7 Dantu homozygotes, while RNA concentrations were measured in 9 non-Dantu, 7 Dantu heterozygotes and 7 Dantu homozygotes. Medians are indicated by the middle red lines in the boxplots, with the 25th and 75th percentiles indicated by the tops and bottoms of each plot, and the total data ranges indicated by whiskers. Statistical comparisons across the three genotype groups were performed by a one-way ANOVA; pairwise comparisons between genotype groups were performed using Tukey’s HSD test, correcting for multiple pairwise comparison tests using Benjamini–Hochberg FDR. Significant differences were observed in reticulocyte count (non-Dantu versus Dantu homozygote, P = 0.0023) and RNA concentrations (non-Dantu versus Dantu homozygote, P = 0.0015; non-Dantu versus Dantu heterozygote, P = 0.0088). *P < 0.05; **P < 0.01.
Extended Data Fig. 4 Plasma membrane profiling by tandem mass tag (TMT)-based MS3 mass spectrometry.
The impact of the Dantu polymorphism on the levels of proteins expressed on RBC membranes was quantified using mass spectrometry. a, Hierarchical cluster analysis of all membrane proteins, quantified and annotated as described in the Methods. Fold change was calculated for each donor by: (signal-to-noise (donor)/average signal-to-noise (non-Dantu)). b, Proteomic quantification of the markers shown in Fig. 2a (three biologically independent samples per genotype group). All markers except for GYPB were quantified by proteomics. Statistical comparisons of quantitative protein expression across Dantu genotype groups were performed using a two-tailed t-test with Benjamini–Hochberg multiple hypothesis correction: *P < 0.05, **P < 0.01. All P values are listed in Supplementary Table 4.
Extended Data Fig. 5 Representative membrane fluctuation spectra for non-Dantu, Dantu-heterozygous and Dantu-homozygous RBCs.
Example of contour detection and flickering spectra across genotype groups. a, Contour of an RBC (dashed blue line), showing the inner and outer bounds used in image analysis (green lines). b, Final contour of an RBC following image analysis of the frame in a. c, Mean square fluctuation amplitudes, <|h(qx)|2>, as function of modes qx for non-Dantu (green line), Dantu-heterozygote (orange line), and Dantu-homozygote (purple line) RBCs. Fitted modes 8–20. Dashed lines qx−1 and qx−3, respectively, indicate the two possible limiting behaviours when tension or bending modulus dominates. The error bars (not shown for clarity) were calculated as \(\mathrm{s.d.}/\sqrt{(n\times {\rm{d}}t)\,}\), where s.d. is the standard deviation, n the total number of frames, and dt the time gap between frames.
Extended Data Fig. 6 Relationship between biophysical properties in non-Dantu and Dantu-homozygote RBCs.
a, Scatter plot showing the correlation between tension and radius in non-Dantu and Dantu-homozygote RBCs. The coloured points in the background are all the data considered for non-Dantu (249) and Dantu (247) RBCs from six different biological replicates. The big marks in the foreground represent the mean and standard deviation in tension and radius of the six samples for non-Dantu and Dantu RBCs. There is a linear inverse relation between radius and tension: RBCs with higher tension have lower radii. The radius change between Dantu and non-Dantu RBCs is very small (0.3 μm); we believe that the decrease in equatorial radius is due to a shape change caused by increased tension, and that the two biophysical parameters have no different fluctuation modes. b, The impact of tension on RBC deformation during pre-invasion, induced by merozoites contacting RBCs, was compared across Dantu genotype groups. RBCs having tension above the tension threshold tended to be weakly deformed (scores 0 and 1), whereas RBCs with tensions below the threshold were more strongly deformed (scores 2 and 3). Deformation scores are as defined in ref. 10.
Extended Data Fig. 7 Reduction of membrane tension in non-Dantu and Dantu-homozygous RBCs on treatment with phloretin.
a–d, Biophysical properties in non-Dantu (a, b) and Dantu-homozygous (c, d) RBCs after treatment with phloretin. **P < 0.01. Phloretin treatment causes a decrease in tension without affecting the bending modulus at 150 μM (P = 0.0015) and 200 μM (P = 1.72 × 10−4) μM for both non-Dantu and Dantu samples. Above 200 μM phloretin, most RBCs become crenated and cannot be used for flickering spectroscopy. Phloretin has an effect on RBC tension only when it is present in the medium; that is, RBCs recover their normal tension when washed. a, b, Data from about 30 cells from 3 biologically independent non-Dantu samples. c, d, Data from 60 cells from 4 biologically independent Dantu samples. Statistical comparisons between untreated RBCs and those treated with 150 μM phloretin (P = 0.01) or with 200 μM phloretin (P = 0.0022) were carried out using a two-sided Mann–Whitney U-test.
Extended Data Fig. 8 Comparing parasite invasion and biomechanical properties of frozen and fresh RBCs.
a, The invasion efficiency of P. falciparum laboratory strain 3D7 was compared across frozen and fresh RBCs (n = 6 frozen and n = 14 non-Dantu, 12 Dantu-heterozygote and 12 Dantu-homozygote fresh biologically independent RBC samples per genotype group). The percentage of parasitized RBCs that successfully invaded each genotype group was measured using a flow-cytometry-based invasion assay. Boxplots indicate the median (middle line) and interquartile ranges (top and bottom of boxes) of the data; whiskers denote the total data range. Statistical comparison across the three genotype groups was performed using one-way ANOVA; pairwise comparisons between genotype groups were performed using Tukey’s HSD test, with significant differences in 3D7 invasion observed in frozen RBCs (non-Dantu versus Dantu homozygote, P = 0.001) and in fresh RBCs (non-Dantu versus Dantu homozygote, P = 0.001). *P < 0.05; **P < 0.01. b, Membrane flickering spectrometry enabled measurement of RBC biomechanical properties (bending modulus, tension, radius and viscosity) of fresh (n = 53) and frozen (n = 51) RBCs from the same donor. No statistically significant differences were detected between the two conditions for all of the measured biophysical properties. Pairwise comparisons were performed using a two-sided Mann–Whitney U-test; bending modulus, P = 0.1; tension, P = 0.6; radius, P = 0.7; viscosity, P = 0.6.
Extended Data Fig. 9 Decoupling tension and bending modulus with flickering analysis.
To test our ability to decouple tension and bending modulus from our data during the flickering analysis, we took the 20 highest-tension and the 20 lowest-tension cells from our database and analysed their fluctuation power spectra, covering a wide enough range of q-values that both tension and bending moduli can be robustly extracted. a, b, Boxplots for the tensions and bending moduli of the 20 cells with extreme high and 20 with extreme low tensions. Although there is an obvious significant difference in tension (P = 4.0302 × 10−13; two-sided Mann–Whitney U-test), the bending moduli are similar. c, This is also evident from the overlapping of the two spectra for the high modes, where a bending-dominated regime prevails, although the divergence of the fluctuation amplitudes between the two spectra becomes noticeable when tension predominates. Each mean square fluctuation spectrum is obtained by averaging all 20 fluctuation spectra for both low-tension (blue) and high-tension (yellow) cells. As tension dominates low modes (q−1 behaviour) and bending modulus dominates high modes of the spectra (q−3 trend), the decoupling between tension and bending modulus becomes evident from these two spectra (Supplementary Information Section S2).
Extended Data Fig. 10 Membrane flickering spectroscopy amplitude analysis.
a, To justify our choice of modes for fitting Supplementary equation (S4) (see Supplementary Information), we calculated the residuals of mean square fluctuation amplitudes at different ranges of modes for the same RBC. The figure shows that the residues derived from fitting modes above 20 increase steadily, suggesting a systematic error in fitting modes above 20. Our chosen range of modes (8–20) seems the most convincing range, as does range 5–20, with no systematic deviations. By studying the dynamics of modes it is possible to extract the viscosity of the RBC interior, and this analysis can be used as further proof of the method. From the time scale of decorrelation of mode amplitudes, it is also possible to obtain the viscosity of the RBC interior, using the values of tension and bending modulus obtained from the static spectrum of the same cell. This is achieved by fitting the relaxation time with Equation S7. The viscosity is statistically the same across the non-Dantu and Dantu groups, which have statistically different tension values. This is thus a further independent check confirming that the static study is measuring tension values reliably. b, The viscosities of RBCs with extreme low and high tension are not significantly different (P = 0.14, two-sided Mann–Whitney U-test). The fit in the inset shows data from one of the RBCs in the sample. c, The relaxation times, plotted against qx for modes 5–11, are represented for both low- and high-tension RBCs; the trend is 1/q, consistent with the limiting behaviour of Supplementary equation (S7) (see Supplementary Information) for \((\sigma \gg \kappa {q}_{x}^{2})\). The range of modes that can be studied dynamically is limited by the camera acquisition rate, as well as by other factors that also limit the static analysis.
Supplementary information
Supplementary Information
This file contains Supplementary Methods, Supplementary Tables 1-7, Supplementary Figure 1 and additional references.
Supplementary Data
This zipped folder contains Supplementary Codes 1 and 2. Supplementary Code 1: Flickering Analysis Script. A Matlab algorithm for RBC contour detection and analysis to obtain cell amplitudes of fluctuations. The contour of the RBC membrane is detected in brightfield for all the frames of the video. The static spectrum of fluctuations is then obtained using the Fourier transform, and fitted with the flickering formula S.4 to obtain membrane tension and bending modulus of cells. From the autocorrelation of the temporal evolution of the static spectrum’s modes we calculate the relaxation time of the modes, and the viscosity by using Eq. S7. Supplementary Code 2: Example Run file for Flickering Analysis Script. An example run file for the flickering analysis script for the video recordings of RBC membrane fluctuations. Parameters for temperature, camera can be specified here and the initial manual tracking of red blood cell centre and surface.
Supplementary Video 1
Merozoite invasion studied by time-lapse video recordings in non-Dantu RBCs Merozoite invasion into non-Dantu RBCs was studied using time-lapse live video microscopy (4 frames/s), enabling the evaluation of the merozoite invasion efficiency as well as the kinetics of the entire invasion process. The invading parasites are highlighted in the video, where we point out the beginning of merozoite penetration (starting at 15.5 ±1.0 s). Invasion was followed by a reversible morphological change called echinocytosis and finally a ring was formed. The duration and dynamics of each step of the invasion process was established by studying multiple real-time videos by eye, following the strategy described in previous reports (Gilson and Crabb, Int J Parasitol, 2009 and Weiss et al. PLOS, 2015). We discarded all measurements for which the view of the parasite was unclear, and to avoid human biases videos were analyzed by two researchers within our group. The penetration instant can be identified within <1s by following the process frame-by-frame, backwards and forwards. This is further helped by processing each frame to enhance the parasite-cell contrast and facilitate parasite tracking during data analysis. Moreover, depending on the parasite point of contact, either on the top or on the side of the RBC, the size of the parasite can be an additional feature. Since the parasite is on the top of the RBC in Video 1, its circumference/diameter reduces during the penetration. This type of experiment was repeated 144 times of which 53 ending with a successful invasion.
Supplementary Video 2
Merozoite invasion studied by time-lapse video recordings in Dantu homozygote RBCs Merozoite invasion into Dantu variant RBCs was studied using time-lapse live video microscopy (4 frames/s). Merozoites contacted and deformed Dantu RBC membranes many times in different points of the RBC surface without proceeding to invasion. This type of experiment was repeated 233 times of which 41 ending with a successful invasion.
Supplementary Video 3
Merozoite-erythrocyte adhesion force measured by optical tweezers An erythrocyte-merozoite-erythrocyte system was formed by trapping and moving an erythrocyte onto a nearby erythrocyte undergoing invasion. One optical trap was used to keep one erythrocyte fixed, while another trap pulled the second erythrocyte in a normal direction away from the point of merozoite attachment, until detachment. Adhesive forces at the merozoite-erythrocyte contact were quantified by measuring the maximum elongation of erythrocyte before detachment, as described in Materials and Methods. This experiment was repeated 21 times for non-Dantu RBCs, 19 for Dantu heterozygotes, and 24 for Dantu homozygotes with similar results.
Supplementary Video 4
Video recording of all RBC membrane fluctuations around a schizont before egress used to determine their membrane tension Videos of uninfected RBCs around a schizont were recorded at 514 frames/s a few minutes before its egress. At this high frame rate, it is possible to analyse RBC membrane fluctuations to obtain biophysical parameters such as tension, bending modulus, radius, and viscosity without altering or interfering with the sample. This experiment was performed 163 times in total (details in Supplementary Table 6).
Supplementary Video 5
Egress-invasion process following Supplementary Video 4 After measuring the biophysical properties for all RBCs near a schizont that is prompt to egress, we recorded merozoite release and the successive invasion process. We then correlated the RBC biomechanical characteristics with their aptitude to be successfully invaded or not. This experiment was performed 163 times in total (details in Supplementary Table 6).
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Kariuki, S.N., Marin-Menendez, A., Introini, V. et al. Red blood cell tension protects against severe malaria in the Dantu blood group. Nature 585, 579–583 (2020). https://doi.org/10.1038/s41586-020-2726-6
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DOI: https://doi.org/10.1038/s41586-020-2726-6
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