| Literature DB >> 30683099 |
Abhinay Ramaprasad1,2, Amit Kumar Subudhi3, Richard Culleton4, Arnab Pain5.
Abstract
BACKGROUND: The transcriptional regulation that occurs in malaria parasites during the erythrocytic stages of infection can be studied in vivo with rodent malaria parasites propagated in mice. Time-series transcriptome profiling commonly involves the euthanasia of groups of mice at specific time points followed by the extraction of parasite RNA from whole blood samples. Current methodologies for parasite RNA extraction involve several steps and when multiple time points are profiled, these protocols are laborious, time-consuming, and require the euthanization of large cohorts of mice.Entities:
Keywords: Malaria; Microsampling; Plasmodium; Rodent malaria parasites; Time-series; Transcriptomics
Mesh:
Substances:
Year: 2019 PMID: 30683099 PMCID: PMC6347755 DOI: 10.1186/s12936-019-2659-4
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Fig. 1Microsampling protocol design and reproducibility. a In terminal blood sampling, at each time point, groups of mice are exsanguinated to obtain 0.5–0.6 mL blood volumes, which are then subject to leukocyte depletion and saponin lysis before TRIzol treatment. Thus, the number of mice increases proportionally with the number of biological replicates and time points in the study design (number of mice per timepoint X number of timepoints; NT). Microsampling involves obtaining sample volumes as low as 20 μL from the same mouse at different time points, thus confining the number of mice to just biological replicates (N) and significantly lowering costs and biological variability. Leukocyte depletion and saponin lysis are also not performed on the low volume samples, thus saving time and manpower. b Heatmap shows pair-wise Pearson correlation coefficients and the inset shows multidimensional scaling to visualize the level of similarity between the P. vinckei microsamples. Microsamples show low degree of variability and are highly reproducible as proved by tight correlations between biological replicates. c High Pearson correlations were observed between normalized gene expression values (shown as logarithm of fragments per kilobase of transcript per million mapped reads) from microsampling (x-axis) and terminal blood sampling (y-axis) methods. d Bioanalyser electrophoregrams of total RNA from Plasmodium vinckei vinckei CY microsamples show that high quality RNA could be extracted consistently from 20 μL microsamples
Microsample characteristics and RNA-seq mapping statistics
| RMP | Microsample | Parasitaemia | RNA yield (μg) | Total reads | Parasite reads | Mapping percentage | Median fragment coverage | Median TIN |
|---|---|---|---|---|---|---|---|---|
|
| Sample I | 7.74 | 0.87 | 26,585,563 | 1,228,998 | 4.62 | 8 | 87.66 |
| Sample II | 6.22 | 0.42 | 19,842,987 | 2,458,755 | 12.39 | 49 | 86.41 | |
| Sample III | 5.75 | 1.71 | 15,332,092 | 676,488 | 4.41 | 10 | 92.2 | |
| Sample IV | 3.64 | 1.03 | 31,385,250 | 1,420,373 | 4.52 | 26 | 91.13 | |
|
| 6h_rep1 | 23.88 | 9.6 | 32,755,140 | 22,915,171 | 69.96 | 499 | 91.27 |
| 6h_rep2 | 22.19 | 9 | 31,427,694 | 21,274,632 | 67.69 | 479 | 91.15 | |
| 6h_rep3 | 23.14 | 9.03 | 31,331,956 | 20,044,950 | 63.98 | 424 | 91.04 | |
| 12h_rep1 | 24.19 | 11.49 | 35,255,928 | 26,290,657 | 74.57 | 710.5 | 91.79 | |
| 12h_rep2 | 24.32 | 11.46 | 28,504,674 | 16,567,841 | 58.12 | 451.5 | 86.61 | |
| 12h_rep3 | 22.75 | 10.14 | 27,368,020 | 17,521,494 | 64.02 | 483.5 | 92 | |
| 18h_rep1 | 24.77 | 6.33 | 27,622,130 | 18,733,720 | 67.82 | 582 | 89.88 | |
| 18h_rep2 | 25.65 | 11.49 | 29,253,240 | 18,590,556 | 63.55 | 552 | 91.11 | |
| 18h_rep3 | 23.11 | 10.23 | 27,377,938 | 15,234,884 | 55.65 | 468 | 90.08 | |
| 24h_rep1 | 27.06 | 5.4 | 33,624,482 | 25,522,094 | 75.90 | 698 | 91.57 | |
| 24h_rep2 | 25.92 | 1.24 | 35,255,928 | 20,282,255 | 57.53 | 501.5 | 87.43 | |
| 24h_rep3 | 26.45 | 1.95 | 35,255,928 | 23,045,897 | 65.37 | 634 | 90.69 |
Microsamples from Plasmodium chabaudi AS had low parasitaemia and therefore, a low percentage of reads mapping to the P. chabaudi genome. In contrast, Plasmodium vinckei vinckei CY microsamples had lesser host contamination resulting in higher median fragment coverage across its transcripts. Transcript integrity number (TIN) was calculated using RSeQC [51] and all samples showed a high TIN value, indicating little to no evidence of RNA degradation
Fig. 2Time-series transcriptome of Plasmodium vinckei vinckei CY. a Heat maps showing gene expression in P. vinckei at 6 h time points during the 24 h asexual cycle, each corresponding to a dominant population of rings (R), early trophozoites (E.T), late trophozoites (L.T) and schizonts (S) respectively. Gene expression values have been centered and normalized as Z-scores with the average level of expression among the genes set as zero (black) and higher and lower levels shown as red and green respectively. On the left panel, all significantly regulated P. vinckei genes (4328 genes) were ordered from top to bottom according to their phase of expression to create a phaseogram. On the right panel, P. vinckei genes with one-to-one orthologs in P. falciparum 3D7 (2480 genes) were ordered based on P. falciparum 3D7 phaseogram shown in [1]. Both kinds of ordering display the transcriptional cascade in P. vinckei, closely reflecting that of P. falciparum. Gene-wise FPKM values are given in Additional files 3 and 4). b Expression profiles of RNA polymerases (known to peak during ring and early trophozoite stages) and invasion-related genes (known to peak during late trophozoite and schizont stages) in P. vinckei vinckei CY. Blue and orange lines represent genes clustered with different expression profiles and the black line represents average trend of expression in a particular gene cluster (fpkm—fragments per kilobase of transcript per million mapped reads). Gene lists are given in Additional file 5