Host and Parasite Transcriptomic Changes upon Successive Plasmodium falciparum Infections in Early Childhood

Gene expression analyses reveal differences in children's response to malaria according to their age

In Bandiagara, Mali, children experience on average two clinical malaria episodes per year. However, even in the same transmission area, the number of uncomplicated symptomatic infections, and their parasitemia, can vary dramatically among children. We simultaneously characterize host and parasite gene expression profiles from 136 Malian children with symptomatic falciparum malaria and examine differences in the relative proportion of immune cells and parasite stages, as well as in gene expression, associated with infection and or patient characteristics. Parasitemia explains much of the variation in host and parasite gene expression, and infections with higher parasitemia display proportionally more neutrophils and fewer T cells, suggesting parasitemia-dependent neutrophil recruitment and/or T cell extravasation to secondary lymphoid organs. The child's age also strongly correlates with variations in gene expression: Plasmodium falciparum genes associated with age suggest that older children carry more male gametocytes, while variations in host gene expression indicate a stronger innate response in younger children and stronger adaptive response in older children. These analyses highlight the variability in host responses and parasite regulation during P. falciparum symptomatic infections and emphasize the importance of considering the children's age when studying and treating malaria infections.

Gene expression analyses reveal differences in children's response to malaria according to their age

In Bandiagara, Mali, children experience on average two clinical malaria episodes per season. However, even in the same transmission area, the number of uncomplicated symptomatic infections, and their parasitemia, vary dramatically among children. To examine the factors contributing to these variations, we simultaneously characterized the host and parasite gene expression profiles from 136 children with symptomatic falciparum malaria and analyzed the expression of 9,205 human and 2,484 Plasmodium genes. We used gene expression deconvolution to estimate the relative proportion of immune cells and parasite stages in each sample and to adjust the differential gene expression analyses. Parasitemia explained much of the variation in both host and parasite gene expression and revealed that infections with higher parasitemia had more neutrophils and fewer T cells, suggesting parasitemia-dependent neutrophil recruitment and/or T cell extravasation to secondary lymphoid organs. The child's age was also strongly correlated with gene expression variations. Plasmodium falciparum genes associated with age suggested that older children carried more male gametocytes, while host genes associated with age indicated a stronger innate response (through TLR and NLR signaling) in younger children and stronger adaptive immunity (through TCR and BCR signaling) in older children. These analyses highlight the variability in host responses and parasite regulation during P. falciparum symptomatic infections and emphasize the importance of considering the children's age when studying and treating malaria infections.

Malian children infected with Plasmodium ovale and Plasmodium falciparum display very similar gene expression profiles

Plasmodium parasites caused 241 million cases of malaria and over 600,000 deaths in 2020. Both P. falciparum and P. ovale are endemic to Mali and cause clinical malaria, with P. falciparum infections typically being more severe. Here, we sequenced RNA from nine pediatric blood samples collected during infections with either P. falciparum or P. ovale, and characterized the host and parasite gene expression profiles. We found that human gene expression varies more between individuals than according to the parasite species causing the infection, while parasite gene expression profiles cluster by species. Additionally, we characterized DNA polymorphisms of the parasites directly from the RNA-seq reads and found comparable levels of genetic diversity in both species, despite dramatic differences in prevalence. Our results provide unique insights into host-pathogen interactions during malaria infections and their variations according to the infecting Plasmodium species, which will be critical to develop better elimination strategies against all human Plasmodium parasites.

Determination of the Stage Composition of Plasmodium Infections from Bulk Gene Expression Data

Malaria symptoms are caused by the development of the parasites within the blood of an infected host. Bulk RNA sequencing (RNA-seq) of infected blood can reveal interactions between parasites and the host immune system during an infection, but because multiple developmental stages with distinct transcriptional profiles are concurrently present in infected blood, it is necessary to correct such analyses for differences in cell composition among samples. Gene expression deconvolution is a statistical approach that has been developed for inferring the cell composition of complex tissues characterized by bulk RNA-seq using gene expression profiles from reference cell types. Here, we describe the evaluation of a species-agnostic reference data set that can be used for efficient and accurate gene expression deconvolution of bulk RNA-seq data generated from any Plasmodium species and for correct gene expression analyses for biases caused by differences in stage composition among samples. IMPORTANCE Differences in cell type proportions among samples can introduce artifacts in gene expression analyses and mask genuine differences in gene regulation. Gene expression deconvolution allows estimation of the proportion of each cell type present in one sample directly from bulk RNA sequencing data, but this approach requires a reference data set with the signature profile of each cell type. Here, we evaluate the suitability of a rodent malaria parasite gene expression data set for estimating the proportions of each parasite developmental stage present in bulk RNA sequencing data generated from blood-stage infections with the human parasites Plasmodium falciparum and Plasmodium vivax. These analyses provide a species-agnostic approach for reliably estimating stage proportions in infected human blood and correcting subsequent gene expression analyses for these variations.

RNAseq of Infected Erythrocyte Surface Antigen-Encoding Genes

Massive parallel sequencing technology has greatly increased the breadth and depth of transcriptomic data that can be captured from P. falciparum samples. This has revolutionized in vitro studies but uptake has been slower in the analysis of clinical samples. The principal barriers are the removal of contaminating white blood cells in a malaria endemic setting and preservation of the RNA. We provide here detailed methods for the collection of purified infected erythrocytes and the preservation and extraction of RNA. We also provide methods for assessing and addressing contaminating RNA from erythroid cells, and a protocol for RNAseq library preparation optimized to maximize yield from low amounts of parasite mRNA. Finally, we provide some examples of RNAseq library characteristics that may fail quality control for other species but are in fact satisfactory for P. falciparum RNAseq.

Dual RNA Sequencing Meta-analysis in Plasmodium Infection Identifies Host-Parasite Interactions

Dual RNA sequencing (RNA-Seq) is the simultaneous transcriptomic analysis of interacting symbionts, for example, in malaria. Potential cross-species interactions identified by correlated gene expression might highlight interlinked signaling, metabolic, or gene regulatory pathways in addition to physically interacting proteins. Often, malaria studies address one of the interacting organisms-host or parasite-rendering the other "contamination." Here we perform a meta-analysis using such studies for cross-species expression analysis. We screened experiments for gene expression from host and Plasmodium. Out of 171 studies in Homo sapiens, Macaca mulatta, and Mus musculus, we identified 63 potential studies containing host and parasite data. While 16 studies (1,950 samples) explicitly performed dual RNA-Seq, 47 (1,398 samples) originally focused on one organism. We found 915 experimental replicates from 20 blood studies to be suitable for coexpression analysis and used orthologs for meta-analysis across different host-parasite systems. Centrality metrics from the derived gene expression networks correlated with gene essentiality in the parasites. We found indications of host immune response to elements of the Plasmodium protein degradation system, an antimalarial drug target. We identified well-studied immune responses in the host with our coexpression networks, as our approach recovers known broad processes interlinked between hosts and parasites in addition to individual host and parasite protein associations. The set of core interactions represents commonalities between human malaria and its model systems for prioritization in laboratory experiments. Our approach might also allow insights into the transferability of model systems for different pathways in malaria studies.IMPORTANCE Malaria still causes about 400,000 deaths a year and is one of the most studied infectious diseases. The disease is studied in mice and monkeys as lab models to derive potential therapeutic intervention in human malaria. Interactions between Plasmodium spp. and its hosts are either conserved across different host-parasite systems or idiosyncratic to those systems. Here we use correlation of gene expression from different RNA-Seq studies to infer common host-parasite interactions across human, mouse, and monkey studies. First, we find a set of very conserved interactors, worth further scrutiny in focused laboratory experiments. Second, this work might help assess to which extent experiments and knowledge on different pathways can be transferred from models to humans for potential therapy.