Background: The NCOA7 gene product is an estrogen receptor associated protein that is highly similar to the human OXR1 gene product, which functions in oxidation resistance. OXR genes are conserved among all sequenced eukaryotes from yeast to humans. In this study we examine if NCOA7 has an oxidation resistance function similar to that demonstrated for OXR1. We also examine NCOA7 expression in response to oxidative stress and its subcellular localization in human cells, comparing these properties with those of OXR1.

Background Deep sequencing of targeted genomic regions is becoming a common tool for understanding the dynamics and complexity of Plasmodium infections, but its lower limit of detection is currently unknown. Here, a new amplicon analysis tool, the Parallel Amplicon Sequencing Error Correction (PASEC) pipeline, is used to evaluate the performance of amplicon sequencing on low-density Plasmodium DNA samples. Illumina-based sequencing of two Plasmodium falciparum genomic regions ( CSP and SERA2 ) was performed on two types of samples: in vitro DNA mixtures mimicking low-density infections (1–200 genomes/μl) and extracted blood spots from a combination of symptomatic and asymptomatic individuals (44–653,080 parasites/μl). Three additional analysis tools—DADA2, HaplotypR, and SeekDeep—were applied to both datasets and the precision and sensitivity of each tool were evaluated. Results Amplicon sequencing can contend with low-density samples, showing reasonable detection accuracy down to a concentration of 5 Plasmodium genomes/μl. Due to increased stochasticity and background noise, however, all four tools showed reduced sensitivity and precision on samples with very low parasitaemia (< 5 copies/μl) or low read count (< 100 reads per amplicon). PASEC could distinguish major from minor haplotypes with an accuracy of 90% in samples with at least 30 Plasmodium genomes/μl, but only 61% at low Plasmodium concentrations (< 5 genomes/μl) and 46% at very low read counts (< 25 reads per amplicon). The four tools were additionally used on a panel of extracted parasite-positive blood spots from natural malaria infections. While all four identified concordant patterns of complexity of infection (COI) across four sub-Saharan African countries, COI values obtained for individual samples differed in some cases. Conclusions Amplicon deep sequencing can be used to determine the complexity and diversity of low-density Plasmodium infections. Despite differences in their approach, four state-of-the-art tools resolved known haplotype mixtures with similar sensitivity and precision. Researchers can therefore choose from multiple robust approaches for analysing amplicon data, however, error filtration approaches should not be uniformly applied across samples of varying parasitaemia. Samples with very low parasitaemia and very low read count have higher false positive rates and call for read count thresholds that are higher than current default recommendations. Electronic supplementary material The online version of this article (10.1186/s12936-019-2856-1) contains supplementary material, which is available to authorized users.

Background: In 2006, the Senegalese National Malaria Control Programme recommended artemisinin-based combination therapy (ACT) with artemether-lumefantrine as the first-line treatment for uncomplicated Plasmodium falciparum malaria. To date, multiple mutations associated with artemisinin delayed parasite clearance have been described in Southeast Asia in the Pfk13 gene, such as Y493H, R539T, I543T and C580Y. Even though ACT remains clinically and parasitologically efficacious in Senegal, the spread of resistance is possible as shown by the earlier emergence of resistance to chloroquine in Southeast Asia that subsequently spread to Africa. Therefore, surveillance of artemisinin resistance in malaria endemic regions is crucial and requires the implementation of sensitive tools, such as next-generation sequencing (NGS) which can detect novel mutations at low frequency. Methods: Here, an amplicon sequencing approach was used to identify mutations in the Pfk13 gene in eighty-one P. falciparum isolates collected from three different regions of Senegal. Results: In total, 10 SNPs around the propeller domain were identified; one synonymous SNP and nine non-synonymous SNPs, and two insertions. Three of these SNPs (T478T, A578S and V637I) were located in the propeller domain. A578S, is the most frequent mutation observed in Africa, but has not previously been reported in Senegal. A previous study has suggested that A578S could disrupt the function of the Pfk13 propeller region. Conclusion: As the genetic basis of possible artemisinin resistance may be distinct in Africa and Southeast Asia, further studies are necessary to assess the new SNPs reported in this study.