Use of gene expression studies to investigate the human immunological response to malaria infection

The malarial blood transcriptome: translational applications

The blood transcriptome of malaria patients has been used extensively to elucidate the pathophysiological mechanisms and host immune responses to disease, identify candidate diagnostic and prognostic biomarkers, and reveal new therapeutic targets for drug discovery. This review gives a high-level overview of the three main translational applications of these studies (diagnostics, prognostics, and therapeutics) by summarising recent literature and outlining the main limitations and future directions of each application. It highlights the need for consistent and accurate definitions of disease states and subject groups and discusses how prognostic studies must distinguish clearly between analyses that attempt to predict future disease states and those which attempt to discriminate between current disease states (classification). Lastly it examines how many promising therapeutics fail due to the choice of imperfect animal models for pre-clinical testing and lack of appropriate validation studies in humans, and how future transcriptional studies may be utilised to overcome some of these limitations.

Extracellular Vesicles in Malaria: Shedding Light on Pathogenic Depths

Malaria, a life-threatening infectious disease caused by Plasmodium falciparum, remains a significant global health challenge, particularly in tropical and subtropical regions. The epidemiological data for 2021 revealed a staggering toll, with 247 million reported cases and 619,000 fatalities attributed to the disease. This formidable global health challenge continues to perplex researchers seeking a comprehensive understanding of its pathogenesis. Recent investigations have unveiled the pivotal role of extracellular vesicles (EVs) in this intricate landscape. These tiny, membrane-bound vesicles, secreted by diverse cells, emerge as pivotal communicators in malaria's pathogenic orchestra. This Review delves into the multifaceted roles of EVs in malaria pathogenesis, elucidating their impact on disease progression and immune modulation. Insights into EV involvement offer potential therapeutic and diagnostic strategies. Integrating this information identifies targets to mitigate malaria's global impact. Moreover, this Review explores the potential of EVs as diagnostic biomarkers and therapeutic targets in malaria. By deciphering the intricate dialogue facilitated by these vesicles, new avenues for intervention and novel strategies for disease management may emerge.

Immunogenomic profile at baseline predicts host susceptibility to clinical malaria

Introduction

Host gene and protein expression impact susceptibility to clinical malaria, but the balance of immune cell populations, cytokines and genes that contributes to protection, remains incompletely understood. Little is known about the determinants of host susceptibility to clinical malaria at a time when acquired immunity is developing.

Methods

We analyzed peripheral blood mononuclear cells (PBMCs) collected from children who differed in susceptibility to clinical malaria, all from a small town in Mali. PBMCs were collected from children aged 4-6 years at the start, peak and end of the malaria season. We characterized the immune cell composition and cytokine secretion for a subset of 20 children per timepoint (10 children with no symptomatic malaria age-matched to 10 children with >2 symptomatic malarial illnesses), and gene expression patterns for six children (three per cohort) per timepoint.

Results

We observed differences between the two groups of children in the expression of genes related to cell death and inflammation; in particular, inflammatory genes such as CXCL10 and STAT1 and apoptotic genes such as XAF1 were upregulated in susceptible children before the transmission season began. We also noted higher frequency of HLA-DR+ CD4 T cells in protected children during the peak of the malaria season and comparable levels cytokine secretion after stimulation with malaria schizonts across all three time points.

Conclusion

This study highlights the importance of baseline immune signatures in determining disease outcome. Our data suggests that differences in apoptotic and inflammatory gene expression patterns can serve as predictive markers of susceptibility to clinical malaria.

Impact of high human genetic diversity in Africa on immunogenicity and efficacy of RTS,S/AS01 vaccine

In modern medicine, vaccination is one of the most effective public health strategies to prevent infectious diseases. Indisputably, vaccines have saved millions of lives by reducing the burden of many serious infections such as polio, tuberculosis, measles, pneumonia, and tetanus. Despite the recent recommendation by the World Health Organization (WHO) to roll out RTS,S/AS01, this malaria vaccine still faces major challenges of variability in its efficacy partly due to high genetic variation in humans and malaria parasites. Immune responses to malaria vary between individuals and populations. Human genetic variation in immune system genes is the probable cause for this heterogeneity. In this review, we will focus on human genetic factors that determine variable responses to vaccination and how variation in immune system genes affect the immunogenicity and efficacy of the RTS,S/AS01 vaccine.

A systems biology approach to better understand human tick-borne diseases

Tick-borne diseases (TBDs) are a growing global health concern. Despite extensive studies, ill-defined tick-associated pathologies remain with unknown aetiologies. Human immunological responses after tick bite, and inter-individual variations of immune-response phenotypes, are not well characterised. Current reductive experimental methodologies limit our understanding of more complex tick-associated illness, which results from the interactions between the host, tick, and microbes. An unbiased, systems-level integration of clinical metadata and biological host data - obtained via transcriptomics, proteomics, and metabolomics - offers to drive the data-informed generation of testable hypotheses in TBDs. Advanced computational tools have rendered meaningful analysis of such large data sets feasible. This review highlights the advantages of integrative system biology approaches as essential for understanding the complex pathobiology of TBDs.

GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis

Gene expression profiling techniques, such as DNA microarray and RNA-Sequencing, have provided significant impact on our understanding of biological systems. They contribute to almost all aspects of biomedical research, including studying developmental biology, host-parasite relationships, disease progression and drug effects. However, the high-throughput data generations present challenges for many wet experimentalists to analyze and take full advantage of such rich and complex data. Here we present GeneCloudOmics, an easy-to-use web server for high-throughput gene expression analysis that extends the functionality of our previous ABioTrans with several new tools, including protein datasets analysis, and a web interface. GeneCloudOmics allows both microarray and RNA-Seq data analysis with a comprehensive range of data analytics tools in one package that no other current standalone software or web-based tool can do. In total, GeneCloudOmics provides the user access to 23 different data analytical and bioinformatics tasks including reads normalization, scatter plots, linear/non-linear correlations, PCA, clustering (hierarchical, k-means, t-SNE, SOM), differential expression analyses, pathway enrichments, evolutionary analyses, pathological analyses, and protein-protein interaction (PPI) identifications. Furthermore, GeneCloudOmics allows the direct import of gene expression data from the NCBI Gene Expression Omnibus database. The user can perform all tasks rapidly through an intuitive graphical user interface that overcomes the hassle of coding, installing tools/packages/libraries and dealing with operating systems compatibility and version issues, complications that make data analysis tasks challenging for biologists. Thus, GeneCloudOmics is a one-stop open-source tool for gene expression data analysis and visualization. It is freely available at http://combio-sifbi.org/GeneCloudOmics.

Host Blood Gene Signatures Can Detect the Progression to Severe and Cerebral Malaria

Malaria is a major international public health problem that affects millions of patients worldwide especially in sub-Saharan Africa. Although many tests have been developed to diagnose malaria infections, we still lack reliable diagnostic biomarkers for the identification of disease severity, especially in endemic areas where the diagnosis of cerebral malaria is very difficult and requires the exclusion of all other possible causes. Previous host and pathogen transcriptomic studies have not yielded homogenous results that can be harnessed into a reliable diagnostic tool. Here we utilized a multi-cohort analysis approach using machine-learning algorithms to identify blood gene signatures that can distinguish severe and cerebral malaria from moderate and non-cerebral cases. Using a Regularized Random Forest model, we identified 28-gene and 32-gene signatures that can reliably distinguish severe and cerebral malaria, respectively. We tested the specificity of both signatures against other common infectious diseases to ensure the signatures reliability and suitability as diagnostic markers. The severe and cerebral malaria gene-signatures were further integrated through k-top scoring pairs classifiers into ten and nine gene pairs that could distinguish severe and cerebral malaria, respectively. These signatures have various implications that can be utilized as blood diagnostic tools for malaria severity in endemic countries.

Integrative genomic analysis reveals mechanisms of immune evasion in P. falciparum malaria

The mechanisms behind the ability of Plasmodium falciparum to evade host immune system are poorly understood and are a major roadblock in achieving malaria elimination. Here, we use integrative genomic profiling and a longitudinal pediatric cohort in Burkina Faso to demonstrate the role of post-transcriptional regulation in host immune response in malaria. We report a strong signature of miRNA expression differentiation associated with P. falciparum infection (127 out of 320 miRNAs, B-H FDR 5%) and parasitemia (72 miRNAs, B-H FDR 5%). Integrative miRNA-mRNA analysis implicates several infection-responsive miRNAs (e.g., miR-16-5p, miR-15a-5p and miR-181c-5p) promoting lymphocyte cell death. miRNA cis-eQTL analysis using whole-genome sequencing data identified 1,376 genetic variants associated with the expression of 34 miRNAs (B-H FDR 5%). We report a protective effect of rs114136945 minor allele on parasitemia mediated through miR-598-3p expression. These results highlight the impact of post-transcriptional regulation, immune cell death processes and host genetic regulatory control in malaria.

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

We show that dual RNA-seq from patient blood samples allows characterization of host/parasite interactions during malaria infections and can provide a solid framework to study the acquisition of antimalarial immunity, as well as the adaptations of P. falciparum to malaria-experienced hosts.

Children are highly susceptible to clinical malaria, and in regions where malaria is endemic, their immune systems must face successive encounters with Plasmodium falciparum parasites before they develop immunity, first against severe disease and later against uncomplicated malaria. Understanding cellular and molecular interactions between host and parasites during an infection could provide insights into the processes underlying this gradual acquisition of immunity, as well as to how parasites adapt to infect hosts that are successively more malaria experienced. Here, we describe methods to analyze the host and parasite gene expression profiles generated simultaneously from blood samples collected from five consecutive symptomatic P. falciparum infections in three Malian children. We show that the data generated enable statistical assessment of the proportions of (i) each white blood cell subset and (ii) the parasite developmental stages, as well as investigations of host-parasite gene coexpression. We also use the sequences generated to analyze allelic variations in transcribed regions and determine the complexity of each infection. While limited by the modest sample size, our analyses suggest that host gene expression profiles primarily clustered by individual, while the parasite gene expression profiles seemed to differentiate early from late infections. Overall, this study provides a solid framework to examine the mechanisms underlying acquisition of immunity to malaria infections using whole-blood transcriptome sequencing (RNA-seq).

IMPORTANCE We show that dual RNA-seq from patient blood samples allows characterization of host/parasite interactions during malaria infections and can provide a solid framework to study the acquisition of antimalarial immunity, as well as the adaptations of P. falciparum to malaria-experienced hosts.