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Plasmodium falciparum and Plasmodium vivax , the two protozoan parasite species that cause the majority of cases of human malaria, have developed resistance to nearly all known antimalarials. The ability of malaria parasites to develop resistance is primarily due to the high numbers of parasites in the infected person's bloodstream during the asexual blood stage of infection in conjunction with the mutability of their genomes. Identifying the genetic mutations that mediate antimalarial resistance has deepened our understanding of how the parasites evade our treatments and reveals molecular markers that can be used to track the emergence of resistance in clinical samples. In this review, we examine known genetic mutations that lead to resistance to the major classes of antimalarial medications: the 4-aminoquinolines (chloroquine, amodiaquine and piperaquine), antifolate drugs, aryl amino-alcohols (quinine, lumefantrine and mefloquine), artemisinin compounds, antibiotics (clindamycin and doxycycline) and a napthoquinone (atovaquone). We discuss how the evolution of antimalarial resistance informs strategies to design the next generation of antimalarial therapies. [ABSTRACT FROM AUTHOR]

We report a case of Bartonella quintana endocarditis in a homeless man with congenital bicuspid aortic valve and significant cat exposure living in downtown San Diego, California. [ABSTRACT FROM AUTHOR]

A major advance in antimalarial drug discovery has been the shift towards cell-based phenotypic screening, with notable progress in the screening of compounds against the asexual blood stage, liver stage, and gametocytes. A primary method for drug target deconvolution in Plasmodium falciparum is in vitro evolution of compound-resistant parasites followed by whole-genome scans. Several of the most promising antimalarial drug targets, such as translation elongation factor 2 (eEF2) and phenylalanine tRNA synthetase (PheRS), have been identified or confirmed using this method. One drawback of this method is that if a mutated gene is uncharacterized, a substantial effort may be required to determine whether it is a drug target, a drug resistance gene, or if the mutation is merely a background mutation. Thus, the availability of high-throughput, functional genomic datasets can greatly assist with target deconvolution. Studies mapping genome-wide essentiality in P. falciparum or performing transcriptional profiling of the host and parasite during liver-stage infection with P. berghei have identified potentially druggable pathways. Advances in mapping the epigenomic regulation of the malaria parasite genome have also enabled the identification of key processes involved in parasite development. In addition, the examination of the host genome during infection has identified novel gene candidates associated with susceptibility to severe malaria. Here, we review recent studies that have used omics-based methods to identify novel targets for interventions against protozoan parasites, focusing on malaria, and we highlight the advantages and limitations of the approaches used. These approaches have also been extended to other protozoan pathogens, including Toxoplasma, Trypanosoma, and Leishmania spp., and these studies highlight how drug discovery efforts against these pathogens benefit from the utilization of diverse omics-based methods to identify promising drug targets. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. Host-parasite interactions during the exoerythrocytic stage of Plasmodium infection remains poorly understood. Using dual RNA-Seq, the authors show that human mucosal immunity protein mucin-13 is upregulated during Plasmodium hepatic-stage infection and marks infected cells independent of tested Plasmodium species. [ABSTRACT FROM AUTHOR]

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]