Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite

Enhancing Gene Co-Expression Network Inference for the Malaria Parasite Plasmodium falciparum

BACKGROUND

Malaria results in more than 550,000 deaths each year due to drug resistance in the most lethal Plasmodium (P.) species P. falciparum. A full P. falciparum genome was published in 2002, yet 44.6% of its genes have unknown functions. Improving the functional annotation of genes is important for identifying drug targets and understanding the evolution of drug resistance.

RESULTS

Genes function by interacting with one another. So, analyzing gene co-expression networks can enhance functional annotations and prioritize genes for wet lab validation. Earlier efforts to build gene co-expression networks in P. falciparum have been limited to a single network inference method or gaining biological understanding for only a single gene and its interacting partners. Here, we explore multiple inference methods and aim to systematically predict functional annotations for all P. falciparum genes. We evaluate each inferred network based on how well it predicts existing gene-Gene Ontology (GO) term annotations using network clustering and leave-one-out crossvalidation. We assess overlaps of the different networks' edges (gene co-expression relationships), as well as predicted functional knowledge. The networks' edges are overall complementary: 47-85% of all edges are unique to each network. In terms of the accuracy of predicting gene functional annotations, all networks yielded relatively high precision (as high as 87% for the network inferred using mutual information), but the highest recall reached was below 15%. All networks having low recall means that none of them capture a large amount of all existing gene-GO term annotations. In fact, their annotation predictions are highly complementary, with the largest pairwise overlap of only 27%. We provide ranked lists of inferred gene-gene interactions and predicted gene-GO term annotations for future use and wet lab validation by the malaria community.

CONCLUSIONS

The different networks seem to capture different aspects of the P. falciparum biology in terms of both inferred interactions and predicted gene functional annotations. Thus, relying on a single network inference method should be avoided when possible.

SUPPLEMENTARY DATA

Attached.

Sources of transcription variation in Plasmodium falciparum

Variation in transcript abundance can contribute to both short-term environmental response and long-term evolutionary adaptation. Most studies are designed to assess differences in mean transcription levels and do not consider other potentially important and confounding sources of transcriptional variation. Detailed quantification of variation sources will improve our ability to detect and identify the mechanisms that contribute to genome-wide transcription changes that underpin adaptive responses. To quantify innate levels of expression variation, we measured mRNA levels for more than 5000 genes in the malaria parasite, Plasmodium falciparum, among clones derived from two parasite strains across biologically and experimentally replicated batches. Using a mixed effects model, we partitioned the total variation among four sources - between strain, within strain, environmental batch effects, and stochastic noise. We found 646 genes with significant variation attributable to at least one of these sources. These genes were categorized by their predominant variation source and further examined using gene ontology enrichment analysis to associate function with each source of variation. Genes with environmental batch effect and within strain transcript variation may contribute to phenotypic plasticity, while genes with between strain variation may contribute to adaptive responses and processes that lead to parasite strain-specific survival under varied conditions.

Cyclical regression covariates remove the major confounding effect of cyclical developmental gene expression with strain-specific drug response in the malaria parasite Plasmodium falciparum

Background

The cyclical nature of gene expression in the intraerythrocytic development cycle (IDC) of the malaria parasite, Plasmodium falciparum, confounds the accurate detection of specific transcriptional differences, e.g. as provoked by the development of drug resistance. In lab-based studies, P. falciparum cultures are synchronized to remove this confounding factor, but the rapid detection of emerging resistance to artemisinin therapies requires rapid analysis of transcriptomes extracted directly from clinical samples. Here we propose the use of cyclical regression covariates (CRC) to eliminate the major confounding effect of developmentally driven transcriptional changes in clinical samples. We show that elimination of this confounding factor reduces both Type I and Type II errors and demonstrate the effectiveness of this approach using a published dataset of 1043 transcriptomes extracted directly from patient blood samples with different patient clearance times after treatment with artemisinin.

Results

We apply this method to two publicly available datasets and demonstrate its ability to reduce the confounding of differences in transcript levels due to misaligned intraerythrocytic development time. Adjusting the clinical 1043 transcriptomes dataset with CRC results in detection of fewer functional categories than previously reported from the same data set adjusted using other methods. We also detect mostly the same functional categories, but observe fewer genes within these categories. Finally, the CRC method identifies genes in a functional category that was absent from the results when the dataset was adjusted using other methods. Analysis of differential gene expression in the clinical data samples that vary broadly for developmental stage resulted in the detection of far fewer transcripts in fewer functional categories while, at the same time, identifying genes in two functional categories not present in the unadjusted data analysis. These differences are consistent with the expectation that CRC reduces both false positives and false negatives with the largest effect on datasets from samples with greater variance in developmental stage.

Conclusions

Cyclical regression covariates have immediate application to parasite transcriptome sequencing directly from clinical blood samples and to cost-constrained in vitro experiments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08281-y.

The RNA structurome in the asexual blood stages of malaria pathogen plasmodium falciparum

Plasmodium falciparum is a deadly human pathogen responsible for the devastating disease called malaria. In this study, we measured the differential accumulation of RNA secondary structures in coding and non-coding transcripts from the asexual developmental cycle in P. falciparum in human red blood cells. Our comprehensive analysis that combined high-throughput nuclease mapping of RNA structures by duplex RNA-seq, SHAPE-directed RNA structure validation, immunoaffinity purification and characterization of antisense RNAs collectively measured differentially base-paired RNA regions throughout the parasite's asexual RBC cycle. Our mapping data not only aligned to a diverse pool of RNAs with known structures but also enabled us to identify new structural RNA regions in the malaria genome. On average, approximately 71% of the genes with secondary structures are found to be protein coding mRNAs. The mapping pattern of these base-paired RNAs corresponded to all regions of mRNAs, including the 5' UTR, CDS and 3' UTR as well as the start and stop codons. Histone family genes which are known to form secondary structures in their mRNAs and transcripts from genes which are important for transcriptional and post-transcriptional control, such as the unique plant-like transcription factor family, ApiAP2, DNA-/RNA-binding protein, Alba3 and proteins important for RBC invasion and malaria cytoadherence also showed strong accumulation of duplex RNA reads in various asexual stages in P. falciparum. Intriguingly, our study determined stage-specific, dynamic relationships between mRNA structural contents and translation efficiency in P. falciparum asexual blood stages, suggesting an essential role of RNA structural changes in malaria gene expression programs.

Discerning novel drug targets for treating Mycobacterium avium ss. paratuberculosis-associated autoimmune disorders: an in silico approach

Mycobacterium avium subspecies paratuberculosis (MAP) exhibits 'molecular mimicry' with the human host resulting in several autoimmune diseases such as multiple sclerosis, type 1 diabetes mellitus (T1DM), Hashimoto's thyroiditis, Crohn's disease (CD), etc. The conventional therapy for autoimmune diseases includes immunosuppressants or immunomodulators that treat the symptoms rather than the etiology and/or causative mechanism(s). Eliminating MAP-the etiopathological agent might be a better strategy to treat MAP-associated autoimmune diseases. In this case study, we conducted a systematic in silico analysis to identify the metabolic chokepoints of MAP's mimicry proteins and their interacting partners. The probable inhibitors of chokepoint proteins were identified using DrugBank. DrugBank molecules were stringently screened and molecular interactions were analyzed by molecular docking and 'off-target' binding. Thus, we identified 18 metabolic chokepoints of MAP mimicry proteins and 13 DrugBank molecules that could inhibit three chokepoint proteins viz. katG, rpoB and narH. On the basis of molecular interaction between drug and target proteins finally eight DrugBank molecules, viz. DB00609, DB00951, DB00615, DB01220, DB08638, DB08226, DB08266 and DB07349 were selected and are proposed for treatment of three MAP-associated autoimmune diseases namely, T1DM, CD and multiple sclerosis. Because these molecules are either approved by the Food and Drug Administration or these are experimental drugs that can be easily incorporated in clinical studies or tested in vitro. The proposed strategy may be used to repurpose drugs to treat autoimmune diseases induced by other pathogens.

Towards a Dynamic Interaction Network of Life to unify and expand the evolutionary theory

The classic Darwinian theory and the Synthetic evolutionary theory and their linear models, while invaluable to study the origins and evolution of species, are not primarily designed to model the evolution of organisations, typically that of ecosystems, nor that of processes. How could evolutionary theory better explain the evolution of biological complexity and diversity? Inclusive network-based analyses of dynamic systems could retrace interactions between (related or unrelated) components. This theoretical shift from a Tree of Life to a Dynamic Interaction Network of Life, which is supported by diverse molecular, cellular, microbiological, organismal, ecological and evolutionary studies, would further unify evolutionary biology.

Simultaneous genome-wide gene expression and transcript isoform profiling in the human malaria parasite

Gene expression DNA microarrays have been vital for characterizing whole-genome transcriptional profiles. Nevertheless, their effectiveness relies heavily on the accuracy of genome sequences, the annotation of gene structures, and the sequence-dependent performance of individual probes. Currently available gene expression arrays for the malaria parasite Plasmodium falciparum rely on an average of 2 probes per gene, usually positioned near the 3′ end of genes; consequently, existing designs are prone to measurement bias and cannot capture complexities such as the occurrence of transcript isoforms arising from alternative splicing or alternative start/ stop sites. Here, we describe two novel gene expression arrays with exon-focused probes designed with an average of 12 and 20 probes spanning each gene. This high probe density minimizes signal noise inherent in probe-to-probe sequence-dependent hybridization intensity. We demonstrate that these exon arrays accurately profile genome-wide expression, comparing favorably to currently available arrays and RNA-seq profiling, and can detect alternatively spliced transcript isoforms as well as non-coding RNAs (ncRNAs). Of the 964 candidate alternate splicing events from published RNA-seq studies, 162 are confirmed using the exon array. Furthermore, the exon array predicted 330 previously unidentified alternate splicing events. Gene expression microarrays continue to offer a cost-effective alternative to RNA-seq for the simultaneous monitoring of gene expression and alternative splicing events. Microarrays may even be preferred in some cases due to their affordability and the rapid turn-around of results when hundreds of samples are required for fine-scale systems biology investigations, including the monitoring of the networks of gene co-expression in the emergence of drug resistance.

Molecular Mechanisms for Drug Hypersensitivity Induced by the Malaria Parasite's Chloroquine Resistance Transporter

Mutations in the Plasmodium falciparum ‘chloroquine resistance transporter’ (PfCRT) confer resistance to chloroquine (CQ) and related antimalarials by enabling the protein to transport these drugs away from their targets within the parasite’s digestive vacuole (DV). However, CQ resistance-conferring isoforms of PfCRT (PfCRT^CQR) also render the parasite hypersensitive to a subset of structurally-diverse pharmacons. Moreover, mutations in PfCRT^CQR that suppress the parasite’s hypersensitivity to these molecules simultaneously reinstate its sensitivity to CQ and related drugs. We sought to understand these phenomena by characterizing the functions of PfCRT^CQR isoforms that cause the parasite to become hypersensitive to the antimalarial quinine or the antiviral amantadine. We achieved this by measuring the abilities of these proteins to transport CQ, quinine, and amantadine when expressed in Xenopus oocytes and complemented this work with assays that detect the drug transport activity of PfCRT in its native environment within the parasite. Here we describe two mechanistic explanations for PfCRT-induced drug hypersensitivity. First, we show that quinine, which normally accumulates inside the DV and therewithin exerts its antimalarial effect, binds extremely tightly to the substrate-binding site of certain isoforms of PfCRT^CQR. By doing so it likely blocks the normal physiological function of the protein, which is essential for the parasite’s survival, and the drug thereby gains an additional killing effect. In the second scenario, we show that although amantadine also sequesters within the DV, the parasite’s hypersensitivity to this drug arises from the PfCRT^CQR-mediated transport of amantadine from the DV into the cytosol, where it can better access its antimalarial target. In both cases, the mutations that suppress hypersensitivity also abrogate the ability of PfCRT^CQR to transport CQ, thus explaining why rescue from hypersensitivity restores the parasite’s sensitivity to this antimalarial. These insights provide a foundation for understanding clinically-relevant observations of inverse drug susceptibilities in the malaria parasite.

In acquiring resistance to one drug, many pathogens and cancer cells become hypersensitive to other drugs. This phenomenon could be exploited to combat existing drug resistance and to delay the emergence of resistance to new drugs. However, much remains to be understood about the mechanisms that underlie drug hypersensitivity in otherwise drug-resistant microbes. Here, we describe two mechanisms by which the Plasmodium falciparum ‘chloroquine resistance transporter’ (PfCRT) causes the malaria parasite to become hypersensitive to structurally-diverse drugs. First, we show that an antimalarial drug that normally exerts its killing effect within the parasite’s digestive vacuole is also able to bind extremely tightly to certain forms of PfCRT. This activity will block the natural, essential function of the protein and thereby provide the drug with an additional killing effect. The second mechanism arises when a cytosolic-acting drug that normally sequesters within the digestive vacuole is leaked back into the cytosol via PfCRT. In both cases, mutations that suppress hypersensitivity also abrogate the ability of PfCRT to transport chloroquine, thus explaining why rescue from hypersensitivity restores the parasite’s sensitivity to this antimalarial. These insights provide a foundation for understanding and exploiting the hypersensitivity of chloroquine-resistant parasites to several of the current antimalarials.

PfCRT and PfMDR1 modulate interactions of artemisinin derivatives and ion channel blockers

Treatment of the symptomatic asexual stage of Plasmodium falciparum relies almost exclusively on artemisinin (ART) combination therapies (ACTs) in endemic regions. ACTs combine ART or its derivative with a long-acting partner drug to maximize efficacy during the typical three-day regimen. Both laboratory and clinical studies have previously demonstrated that the common drug resistance determinants P. falciparum chloroquine resistance transporter (PfCRT) and multidrug resistance transporter (PfMDR1) can modulate the susceptibility to many current antimalarial drugs and chemical compounds. Here we investigated the parasite responses to dihydroartemisinin (DHA) and various Ca²⁺ and Na⁺ channel blockers and showed positively correlated responses between DHA and several channel blockers, suggesting potential shared transport pathways or mode of action. Additionally, we demonstrated that PfCRT and PfMDR1 could also significantly modulate the pharmacodynamic interactions of the compounds and that the interactions were influenced by the parasite genetic backgrounds. These results provide important information for better understanding of drug resistance and for assessing the overall impact of drug resistance markers on parasite response to ACTs.

Genome-wide transcriptome profiling reveals functional networks involving the Plasmodium falciparum drug resistance transporters PfCRT and PfMDR1

BACKGROUND

The acquisition of multidrug resistance by Plasmodium falciparum underscores the need to understand the underlying molecular mechanisms so as to counter their impact on malaria control. For the many antimalarials whose mode of action relates to inhibition of heme detoxification inside infected erythrocytes, the digestive vacuole transporters PfCRT and PfMDR1 constitute primary resistance determinants.

RESULTS

Using gene expression microarrays over the course of the parasite intra-erythrocytic developmental cycle, we compared the transcriptomic profiles between P. falciparum strains displaying mutant or wild-type pfcrt or varying in pfcrt or pfmdr1 expression levels. To account for differences in the time of sampling, we developed a computational method termed Hypergeometric Analysis of Time Series, which combines Fast Fourier Transform with a modified Gene Set Enrichment Analysis. Our analysis revealed coordinated changes in genes involved in protein catabolism, translation initiation and DNA/RNA metabolism. We also observed differential expression of genes with a role in transport or coding for components of the digestive vacuole. Interestingly, a global comparison of all profiled transcriptomes uncovered a tight correlation between the transcript levels of pfcrt and pfmdr1, extending to dozens of other genes, suggesting an intricate regulatory balance in order to maintain optimal physiological processes.

CONCLUSIONS

This study provides insight into the mechanisms by which P. falciparum adjusts to the acquisition of mutations or gene amplification in key transporter loci that mediate drug resistance. Our results implicate several biological pathways that may be differentially regulated to compensate for impaired transporter function and alterations in parasite vacuole physiology.