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.

A Plasmodium falciparum genetic cross reveals the contributions of pfcrt and plasmepsin II/III to piperaquine drug resistance.

Piperaquine (PPQ) is widely used in combination with dihydroartemisinin as a first-line treatment against malaria. Multiple genetic drivers of PPQ resistance have been reported, including mutations in the Plasmodium falciparum chloroquine resistance transporter (pfcrt) and increased copies of plasmepsin II/III (pm2/3). We generated a cross between a Cambodia-derived multidrug-resistant KEL1/PLA1 lineage isolate (KH004) and a drug-susceptible Malawian parasite (Mal31). Mal31 harbors a wild-type (3D7-like) pfcrt allele and a single copy of pm2/3, while KH004 has a chloroquine-resistant (Dd2-like) pfcrt allele with an additional G367C substitution and multiple copies of pm2/3. We recovered 104 unique recombinant parasites and examined a targeted set of progeny representing all possible combinations of variants at pfcrt and pm2/3. We performed a detailed analysis of competitive fitness and a range of PPQ susceptibility phenotypes with these progenies, including PPQ survival assay, area under the dose response curve, and a limited point IC50. We find that inheritance of the KH004 pfcrt allele is required for reduced PPQ sensitivity, whereas copy number variation in pm2/3 further decreases susceptibility but does not confer resistance in the absence of additional mutations in pfcrt. A deep investigation of genotype-phenotype relationships demonstrates that progeny clones from experimental crosses can be used to understand the relative contributions of pfcrt, pm2/3, and parasite genetic background to a range of PPQ-related traits. Additionally, we find that the resistance phenotype associated with parasites inheriting the G367C substitution in pfcrt is consistent with previously validated PPQ resistance mutations in this transporter.IMPORTANCEResistance to piperaquine, used in combination with dihydroartemisinin, has emerged in Cambodia and threatens to spread to other malaria-endemic regions. Understanding the causal mutations of drug resistance and their impact on parasite fitness is critical for surveillance and intervention and can also reveal new avenues to limiting the evolution and spread of drug resistance. An experimental genetic cross is a powerful tool for pinpointing the genetic determinants of key drug resistance and fitness phenotypes and has the distinct advantage of quantifying the effects of naturally evolved genetic variation. Our study was strengthened since the full range of copies of KH004 pm2/3 was inherited among the progeny clones, allowing us to directly test the role of the pm2/3 copy number on resistance-related phenotypes in the context of a unique pfcrt allele. Our multigene model suggests an important role for both loci in the evolution of this multidrug-resistant parasite lineage.

A Plasmodium falciparum genetic cross reveals the contributions of pfcrt and plasmepsin II/III to piperaquine drug resistance.

Piperaquine (PPQ) is widely used in combination with dihydroartemisinin (DHA) as a first-line treatment against malaria parasites. Multiple genetic drivers of PPQ resistance have been reported, including mutations in the Plasmodium falciparum chloroquine resistance transporter (pfcrt) and increased copies of plasmepsin II/III (pm2/3). We generated a cross between a Cambodia-derived multi-drug resistant KEL1/PLA1 lineage isolate (KH004) and a drug susceptible parasite isolated in Malawi (Mal31). Mal31 harbors a wild-type (3D7-like) pfcrt allele and a single copy of pm2/3, while KH004 has a chloroquine-resistant (Dd2-like) pfcrt allele with an additional G367C substitution and four copies of pm2/3. We recovered 104 unique recombinant progeny and examined a targeted set of progeny representing all possible combinations of variants at pfcrt and pm2/3 for detailed analysis of competitive fitness and a range of PPQ susceptibility phenotypes, including PPQ survival assay (PSA), area under the dose-response curve (AUC), and a limited point IC50 (LP-IC50). We find that inheritance of the KH004 pfcrt allele is required for PPQ resistance, whereas copy number variation in pm2/3 further enhances resistance but does not confer resistance in the absence of PPQ-R-associated mutations in pfcrt. Deeper investigation of genotype-phenotype relationships demonstrates that progeny clones from experimental crosses can be used to understand the relative contributions of pfcrt, pm2/3, and parasite genetic background, to a range of PPQ-related traits and confirm the critical role of the PfCRT G367C substitution in PPQ resistance.

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.

The extended recovery ring-stage survival assay provides a superior association with patient clearance half-life and increases throughput.

BACKGROUND: Tracking and understanding artemisinin resistance is key for preventing global setbacks in malaria eradication efforts. The ring-stage survival assay (RSA) is the current gold standard for in vitro artemisinin resistance phenotyping. However, the RSA has several drawbacks: it is relatively low throughput, has high variance due to microscopy readout, and correlates poorly with the current benchmark for in vivo resistance, patient clearance half-life post-artemisinin treatment. Here a modified RSA is presented, the extended Recovery Ring-stage Survival Assay (eRRSA), using 15 cloned patient isolates from Southeast Asia with a range of patient clearance half-lives, including parasite isolates with and without kelch13 mutations. METHODS: Plasmodium falciparum cultures were synchronized with single layer Percoll during the schizont stage of the intraerythrocytic development cycle. Cultures were left to reinvade to early ring-stage and parasitaemia was quantified using flow cytometry. Cultures were diluted to 2% haematocrit and 0.5% parasitaemia in a 96-well plate to start the assay, allowing for increased throughput and decreased variability between biological replicates. Parasites were treated with 700 nM of dihydroartemisinin or 0.02% dimethyl sulfoxide (DMSO) for 6 h, washed three times in drug-free media, and incubated for 66 or 114 h, when samples were collected and frozen for PCR amplification. A SYBR Green-based quantitative PCR method was used to quantify the fold-change between treated and untreated samples. RESULTS: 15 cloned patient isolates from Southeast Asia with a range of patient clearance half-lives were assayed using the eRRSA. Due to the large number of pyknotic and dying parasites at 66 h post-exposure (72 h sample), parasites were grown for an additional cell cycle (114 h post-exposure, 120 h sample), which drastically improved correlation with patient clearance half-life compared to the 66 h post-exposure sample. A Spearman correlation of - 0.8393 between fold change and patient clearance half-life was identified in these 15 isolates from Southeast Asia, which is the strongest correlation reported to date. CONCLUSIONS: eRRSA drastically increases the efficiency and accuracy of in vitro artemisinin resistance phenotyping compared to the traditional RSA, which paves the way for extensive in vitro phenotyping of hundreds of artemisinin resistant parasites.