arising from R. Thomson-Luque et al. Nature Communications https://doi.org/10.1038/s41467-021-25062-z (2021)
We beforehand confirmed in Papua that circulating Plasmodium falciparum inflicting extreme malaria are youthful than these inflicting uncomplicated malaria1. Thomson-Luque et al.2 subsequently claimed that in ours, and different datasets, circulating parasitemia inversely correlated with estimated parasite age and that this was as a result of the P. falciparum that trigger extreme malaria specific PfEMP1s which can be extra cytoadherent, resulting in earlier parasite sequestration within the microvasculature and diminished splenic clearance. Right here, we present that in our dataset circulating parasitemia and the proportion of complete parasites which can be circulating don’t correlate with circulating parasite age, therefore our information don’t assist their speculation.
Thomson-Luque et al. confirmed our discovery that circulating P. falciparum parasites in extreme malaria are youthful than these inflicting uncomplicated malaria1 and so they advised that this distinction confounded comparisons between transcriptomes of parasites inflicting extreme and uncomplicated malaria. That is exactly the explanation why we developed and utilized mathematical approaches to manage for parasite stage variation previous to figuring out genes upregulated in extreme malaria by differential gene expression (DGE) evaluation. It seems that Thomson-Luque et al. missed these particulars which had been outlined in our strategies and outcomes. Thus, they might have misinterpreted our differentially expressed geneset of their reanalysis. Thomson-Luque et al. themselves confirmed that the genes that we recognized as upregulated in extreme malaria weren’t expressed sooner than the genes upregulated in uncomplicated malaria (Thomson-Luque et al. Fig. 3a, b). Thus, our evaluation efficiently managed for parasite stage variation which didn’t confound our differentially expressed geneset.
Thomson-Luque confirmed that the genes upregulated in extreme malaria in our differentially expressed geneset weren’t expressed sooner than the genes upregulated in uncomplicated malaria. They claimed that this similarity in expression timing was as a consequence of a scarcity of distinction in parasitemia between our extreme malaria and uncomplicated malaria sufferers. In our paper we analysed 44 affected person samples for our var gene de novo assemblies and in contrast these parasite densities, however solely 35 of those had been used for DGE as a consequence of drug remedy previous to admission or inadequate sequence protection1. Parasitemias had been considerably larger within the 16 extreme malaria instances used for DGE (median 2.071%, IQR 0.422–12.83) than within the 19 uncomplicated malaria instances used for DGE (median 0.59% IQR 0.092–1.18) p = 0.0136 two-sided Mann–Whitney take a look at U = 78. Thus, as a result of we had not supplied the person parasite densities Thomson-Luque et al. understandably however incorrectly assumed the samples used for DGE additionally didn’t differ in parasitemia.
Thomson-Luque et al. used our combination mannequin to estimate parasite stage in a number of datasets and confirmed inverse correlations between these estimates of parasite age and circulating parasitemias. They inferred that sequestered parasite load correlated with circulating parasitemia and due to this fact correlated inversely with circulating parasite age (Thomson-Luque et al., Fig. 5). Nevertheless, our information don’t assist these correlations. We didn’t present the parasitemias for the person sufferers in our publication however we have now reanalysed our information and in contrast the proportions of parasite levels in our samples to the parasitemias. There is no such thing as a correlation in our dataset between the parasitemia and the proportion of ring stage parasites (Spearman r = 0.2033 95% CI −0.1494 to 0.5101 p = 0.2415) or asexual, non-ring stage parasites estimated by our combination mannequin (Spearman r = −0.2088 95% CI −0.5143 to 0.1438 p = 0.2288) (Fig. 1). Consequently, in our samples parasitemia doesn’t correlate with parasite age.
Of their Fig. 1c, Thomson-Luque et al. ranked 41 of our affected person samples by the RNAseq readcounts of a single glycine tRNA ligase gene PF3D7_1420400 in lieu of the person parasitemias. This gene is described as a housekeeping gene and its stage of expression is inferred to signify parasitemia. Nevertheless, within the 41 samples with sufficient sequence protection for expression evaluation from Tonkin-Hill et al.1 there isn’t a correlation between the degrees of normalised reads of PF3D7_1420400 and parasitemia (Spearman r = −0.1908 95% CI −0.4687 to 0.1213, p = 0.2147). There’s a correlation between ranges of normalised reads of PF3D7_1420400 and proportions of ring levels (Spearman r = 0.4934, 95% CI 0.1432 to 0.6634, p = 0.004) or proportion of asexual non-ring levels (Spearman r = −0.4608 95% CI −0.6782 to −0.1693 p = 0.0024). That the normalised glycine tRNA ligase reads have a constructive correlation with the proportion of ring levels and a detrimental correlation with the proportion of non-ring asexual levels means that the degrees of glycine tRNA ligase transcripts higher displays youth of parasite than parasitemia, according to nearly all of RNAseq datasets ready utilizing the identical method as our personal and obtainable on plasmodb3,4,5,6,7. Thus, the inferred relationship between uncooked reads of glycine tRNA ligase and circulating parasitemia within the samples of Tonkin-Hill et al. was incorrect and the noticed traits in gene expression of the Tonkin-Hill et al. samples in Fig. 1c of Thomson-Luque et al. should not related to rising parasitemia.
Thomson-Luque et al. used staging of transcriptomes of circulating parasites to deduce relationships between parasite stage and circulating parasite density and proposed that earlier sequestration happens in excessive parasitemia/extreme malaria. Nevertheless, we current information suggesting that in our samples this was not the case utilizing estimated complete parasite biomass (Ptot) calculated from HRP2 ranges. Ptot estimates each sequestered and circulating parasites8 and thus extra instantly measures the elimination of parasites from circulation by cytoadhesion than inferring cytoadhesion from variations in circulating parasitemia. Ptot can be affected by variation within the parasite multiplication price, period of an infection, quantity of distribution, and inter-individual variation in PfHRP2 half-life however is nonetheless a greater univariate correlate with medical end result and prognostic indicators of severity than is peripheral blood parasitemia8. Ptot may very well be calculated for 21 uncomplicated and 16 extreme malaria samples1. √Ptot was larger in extreme malaria (imply ± SEM 2,132,578 ± 399,093) than in uncomplicated malaria (imply ± SEM 1,090,126 ± 133,654) in these samples (two-sided unpaired t-test p = 0.0094, t = 2.749, df = 35, uncooked Ptot had been right-skewed so information had been sq. root reworked after which normality was confirmed by D’Agostino & Pearson normality take a look at). Nevertheless, the ratio of circulating parasitemia/Ptot, i.e., a relative measure of the proportion that circulating parasites represent of the physique’s complete parasite load, didn’t correlate with the proportion of circulating parasites that had been rings (Spearman r = −0.0767 95% CI −0.3994 to 0.2629, p = 0.6520) or asexual non-ring levels (Spearman r = 0.0923 95% CI −0.2483 to 0.4125, p = 0.5871) (Fig. 2). This highlights that in our dataset the proportion of complete parasites that had been sequestered had no affiliation with the stage of the circulating parasites. These outcomes don’t assist the mannequin proposed by Thomson-Luque of excessive parasitemia resulting in extreme illness as a consequence of earlier sequestration and thus youthful circulating parasites, which we’d anticipate to manifest as a decrease proportion of complete parasites circulating in sufferers with youthful circulating parasites.
Our information do assist a part of the speculation of Thomson-Luque et al., notably the established position of PfEMP1-mediated sequestration in extreme illness. Whereas that was a principal focus of our examine, Thomson-Luque et al. interpreted our manuscript as reporting var gene expression was diminished in extreme instances when in reality we reported that “There was no distinction between extreme malaria and uncomplicated malaria in complete var gene expression”1. Thomson-Luque et al. seem to have misinterpreted our assertion that “var gene expression was modulated”, which referred to a histone methyl transferase concerned in var gene silencing and switching that was downregulated in extreme malaria. Thus, we had been referring to doubtlessly altered var gene switching or silencing, which might have an effect on which var genes had been expressed not the overall stage of var gene expression.
In abstract, we beforehand reported that parasites circulating in extreme malaria had been youthful than these in uncomplicated malaria1. Our interpretation of those information differs considerably from that of Thomson-Luque et al. as a result of in our information neither parasitemia (Fig. 1) nor direct proof of the proportion of complete parasites that had been circulating (Fig. 2) correlated with circulating parasite age. Whereas the information of Thomson-Luque et al. are of potential significance in understanding pathogenesis in malaria, our information don’t assist the speculation of Thomson-Luque et al., which was based mostly on not directly inferring sequestered parasite load from circulating parasitemia. Each our examine and that of Thomson-Luque et al. used bulk RNAseq information to estimate circulating parasite lifecycle stage distributions. This permits broad conclusions that parasite ages differ however full decision of life-cycle stage distribution would require single-cell RNAseq analyses, which may additionally enhance expressed var gene assemblies. The identification of floor expressed PfEMP1s would require improvement of PfEMP1 variant-specific detection reagents.
Additional info on analysis design is obtainable within the Nature Analysis Reporting Abstract linked to this text.