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ImportanceMalaria is a devastating disease caused by Plasmodium parasites. The evolution of parasite drug resistance continues to hamper progress toward malaria elimination, and despite extensive efforts to control malaria, it remains a leading cause of death in Mozambique and other countries in the region. The development of successful vaccines and identification of molecular markers to track drug efficacy are essential for managing the disease burden. We present an analysis of the parasite genome in Mozambique, a country with one of the highest malaria burdens globally and limited available genomic data, revealing current selection pressure. We contribute additional evidence to limited prior studies supporting the effectiveness of SWGA in producing reliable genomic data from complex clinical samples. Our results provide the identity of genomic loci that may be associated with current antimalarial drug use, including artemisinin and lumefantrine, and reveal selection pressure predicted to compromise the efficacy of current vaccine candidates.

Abstract Background Social media platforms enable on-demand, open-access learning which is attractive for busy clinicians and trainees. Additionally, teaching that occurs in a clinically contextualized, case-based setting in real time has the potential to be more effective than traditional didactics. We piloted a teaching tool to enhance learning and engagement with the literature for fellows on the infectious diseases (ID) consult service. Methods During a clinical service rotation, ID faculty posted a brief daily teaching point on Twitter under the hashtag “#IDDailyPearl” with a link to the relevant article. Tweets were required to be related to a patient case, associated with an article, and could not include patient identifiers. Results Over a 3-month period, there were 134 tweets that fit our criteria, with 103 tweets posted by UCSD faculty and 45 by faculty from other institutions. The most common topic was endocarditis and bacteremia (16.4%), followed by fungal infections (11%), tuberculosis (9.4%), and antimicrobials (9.4%) (Figure 1). Article types included review articles (21.6%), retrospective cohort studies (20.2%), case reports (13.5%), randomized controlled trials (12.1%), prospective cohort studies (9.4%), and guidelines (8.8%). Most articles cited were published after 2015 (61.6%), and were from infectious diseases journals (58.2%). The average journal impact factor was 13 (range 0.07–79), with Clinical Infectious Diseases as the most commonly mentioned journal (20.2%). Tweets were “liked” 14.5 times (range 0–80) and re-tweeted 4.6 times (range 0–33). The twitter engagement rate per tweet was 6.3% (range 2.2 to 12%) and article links were clicked 19 times (range 3–164). We are currently identifying Tweet characteristics associated with increased engagement rates. Conclusion Our study provides a snapshot of the literature used to teach while on the ID clinical service and lays the groundwork for identifying teaching points that receive the most engagement. This tool enables teaching points and high-yield articles to be shared within and across institutions. Future studies will examine the impact that this tool has on fellow and faculty learning, and engagement with and knowledge of the current literature. Disclosures All authors: No reported disclosures.

The exoerythrocytic stage of Plasmodium infection is a critical window for prophylactic intervention. Using genome-wide dual RNA sequencing of flow-sorted infected and uninfected hepatoma cells we show that the human mucosal immunity gene, mucin-13 (MUC13), is strongly upregulated during Plasmodium exoerythrocytic hepatic-stage infection. We confirm MUC13 transcript increases in hepatoma cell lines and primary hepatocytes. In immunofluorescence assays, host MUC13 protein expression distinguishes infected cells from adjacent uninfected cells and shows similar colocalization with parasite biomarkers such as UIS4 and HSP70. We further show that localization patterns are species independent, marking both P. berghei and P. vivax infected cells, and that MUC13 can be used to identify compounds that inhibit parasite replication in hepatocytes. This data provides insights into host-parasite interactions in Plasmodium infection, and demonstrates that a component of host mucosal immunity is reprogrammed during the progression of infection.

Chemogenetic characterization through in vitro evolution combined with whole-genome analysis can identify antimalarial drug targets and drug-resistance genes. We performed a genome analysis of 262 Plasmodium falciparum parasites resistant to 37 diverse compounds. We found 159 gene amplifications and 148 nonsynonymous changes in 83 genes associated with drug-resistance acquisition, where gene amplifications contributed to one-third of resistance acquisition events. Beyond confirming previously identified multidrug-resistance mechanisms, we discovered hitherto unrecognized drug target-inhibitor pairs, including thymidylate synthase and a benzoquinazolinone, farnesyltransferase and a pyrimidinedione, and a dipeptidylpeptidase and an arylurea. This exploration of the P. falciparum resistome and druggable genome will likely guide drug discovery and structural biology efforts, while also advancing our understanding of resistance mechanisms available to the malaria parasite.

Whole-genome sequencing (WGS) of microbial pathogens from clinical samples is a highly sensitive tool used to gain a deeper understanding of the biology, epidemiology, and drug resistance mechanisms of many infections. However, WGS of organisms which exhibit low densities in their hosts is challenging due to high levels of host genomic DNA (gDNA), which leads to very low coverage of the microbial genome. WGS of Plasmodium vivax, the most widely distributed form of malaria, is especially difficult because of low parasite densities and the lack of an ex vivo culture system. Current techniques used to enrich P. vivax DNA from clinical samples require significant resources or are not consistently effective. Here, we demonstrate that selective whole-genome amplification (SWGA) can enrich P. vivax gDNA from unprocessed human blood samples and dried blood spots for high-quality WGS, allowing genetic characterization of isolates that would otherwise have been prohibitively expensive or impossible to sequence. We achieved an average genome coverage of 24×, with up to 95% of the P. vivax core genome covered by ≥5 reads. The single-nucleotide polymorphism (SNP) characteristics and drug resistance mutations seen were consistent with those of other P. vivax sequences from a similar region in Peru, demonstrating that SWGA produces high-quality sequences for downstream analysis. SWGA is a robust tool that will enable efficient, cost-effective WGS of P. vivax isolates from clinical samples that can be applied to other neglected microbial pathogens.ImportanceMalaria is a disease caused by Plasmodium parasites that caused 214 million symptomatic cases and 438,000 deaths in 2015. Plasmodium vivax is the most widely distributed species, causing the majority of malaria infections outside sub-Saharan Africa. Whole-genome sequencing (WGS) of Plasmodium parasites from clinical samples has revealed important insights into the epidemiology and mechanisms of drug resistance of malaria. However, WGS of P. vivax is challenging due to low parasite levels in humans and the lack of a routine system to culture the parasites. Selective whole-genome amplification (SWGA) preferentially amplifies the genomes of pathogens from mixtures of target and host gDNA. Here, we demonstrate that SWGA is a simple, robust method that can be used to enrich P. vivax genomic DNA (gDNA) from unprocessed human blood samples and dried blood spots for cost-effective, high-quality WGS.

Background: Plasmodium vivax poses a significant challenge to malaria elimination due to its ability to cause relapsed infections from reactivation of dormant liver parasites called hypnozoites. We analyzed 69 P. vivax whole genome sequences obtained from subjects residing in three different villages along the Peruvian Amazon. This included 23 paired P. vivax samples from subjects who experienced recurrent P. vivax parasitemia following observed treatment with chloroquine and primaquine. Methods: Genomic DNA was extracted from whole blood samples collected from subjects. P. vivax DNA was enriched using selective whole genome amplification and whole genome sequencing. We used single nucleotide polymorphisms (SNPs) from the core P. vivax genome to determine characteristics of the parasite population using discriminant analysis of principal components, maximum likelihood estimation of individual ancestries, and phylogenetic analysis. We estimated the relatedness of the paired samples by calculating the number of segregating sites and using a hidden Markov model approach to estimate identity by descent. Results: We present a comprehensive dataset of population genetics of Plasmodium vivax in the Peruvian Amazonian. We define the parasite population structure in this region and demonstrate a novel method for distinguishing homologous relapses from reinfections or heterologous relapses with improved accuracy. The parasite population in this area was quite diverse with an estimated five subpopulations and evidence of a highly heterogeneous ancestry of some of the isolates, similar to previous analyses of P. vivax in this region. Pairwise comparison of recurrent infections determined that there were 12 homologous relapses and 3 likely heterologous relapses with highly related parasites. To the best of our knowledge, this is the first large-scale study to evaluate recurrent P. vivax infections using whole genome sequencing. Conclusions: Whole genome sequencing is a high-resolution tool that can identify P. vivax homologous relapses with increased sensitivity, while also providing data about drug resistance and parasite population genetics. This information is important for evaluating the efficacy of known and novel antirelapse medications in endemic areas and thus advancing the campaign to eliminate malaria. [ABSTRACT FROM AUTHOR]