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Abstract Background Larvicides are typically applied to fixed and findable mosquito breeding sites, such as fish farming ponds used in commercial aquaculture, to kill immature forms and thereby reduce the size of adult malaria vector populations. However, there is little evidence suggesting that larviciding may suppress community-wide malaria transmission outside Africa. Here, we tested whether the biological larvicide VectoMax FG applied at monthly intervals to fish farming ponds can reduce malaria incidence in Amazonian Brazil. Methods This study was carried out in Vila Assis Brasil (VAB; population 1700), a peri-urban malaria hotspot in northwestern Brazil with a baseline annual parasite incidence of 553 malaria cases per 1000 inhabitants. The intervention consisted of monthly treatments with 20 kg/ha of VectoMax FG of all water-filled fish ponds in VAB (n ranging between 167 and 170) with a surface area between 20 and 8000 m2, using knapsack power mistblowers. We used single-group interrupted time-series analysis to compare monthly larval density measurements in fish ponds during a 14-month pre-intervention period (September 2017–October 2018), with measurements made during November 2018–October 2019 and shortly after the 12-month intervention (November 2019). We used interrupted time-series analysis with a comparison group to contrast the malaria incidence trends in VAB and nearby nonintervention localities before and during the intervention. Results Average larval densities decreased tenfold in treated fish farming ponds, from 0.467 (95% confidence interval [CI], 0.444–0.490) anopheline larvae per dip pre-intervention (September 2017–October 2018) to 0.046 (95% CI, 0.041–0.051) larvae per dip during (November 2018–October 2019) and shortly after the intervention (November 2019). Average malaria incidence rates decreased by 0.08 (95% CI, 0.04–0.11) cases per 100 person-months (P

Abstract Background A common yet still manual task in basic biology research, high-throughput drug screening and digital pathology is identifying the number, location, and type of individual cells in images. Object detection methods can be useful for identifying individual cells as well as their phenotype in one step. State-of-the-art deep learning for object detection is poised to improve the accuracy and efficiency of biological image analysis. Results We created Keras R-CNN to bring leading computational research to the everyday practice of bioimage analysts. Keras R-CNN implements deep learning object detection techniques using Keras and Tensorflow ( https://github.com/broadinstitute/keras-rcnn ). We demonstrate the command line tool’s simplified Application Programming Interface on two important biological problems, nucleus detection and malaria stage classification, and show its potential for identifying and classifying a large number of cells. For malaria stage classification, we compare results with expert human annotators and find comparable performance. Conclusions Keras R-CNN is a Python package that performs automated cell identification for both brightfield and fluorescence images and can process large image sets. Both the package and image datasets are freely available on GitHub and the Broad Bioimage Benchmark Collection.

Abstract Background Plasmodium falciparum (Pf) whole-organism sporozoite vaccines have been shown to provide significant protection against controlled human malaria infection (CHMI) in clinical trials. Initial CHMI studies showed significantly higher durable protection against homologous than heterologous strains, suggesting the presence of strain-specific vaccine-induced protection. However, interpretation of these results and understanding of their relevance to vaccine efficacy have been hampered by the lack of knowledge on genetic differences between vaccine and CHMI strains, and how these strains are related to parasites in malaria endemic regions. Methods Whole genome sequencing using long-read (Pacific Biosciences) and short-read (Illumina) sequencing platforms was conducted to generate de novo genome assemblies for the vaccine strain, NF54, and for strains used in heterologous CHMI (7G8 from Brazil, NF166.C8 from Guinea, and NF135.C10 from Cambodia). The assemblies were used to characterize sequences in each strain relative to the reference 3D7 (a clone of NF54) genome. Strains were compared to each other and to a collection of clinical isolates (sequenced as part of this study or from public repositories) from South America, sub-Saharan Africa, and Southeast Asia. Results While few variants were detected between 3D7 and NF54, we identified tens of thousands of variants between NF54 and the three heterologous strains. These variants include SNPs, indels, and small structural variants that fall in regulatory and immunologically important regions, including transcription factors (such as PfAP2-L and PfAP2-G) and pre-erythrocytic antigens that may be key for sporozoite vaccine-induced protection. Additionally, these variants directly contributed to diversity in immunologically important regions of the genomes as detected through in silico CD8+ T cell epitope predictions. Of all heterologous strains, NF135.C10 had the highest number of unique predicted epitope sequences when compared to NF54. Comparison to global clinical isolates revealed that these four strains are representative of their geographic origin despite long-term culture adaptation; of note, NF135.C10 is from an admixed population, and not part of recently formed subpopulations resistant to artemisinin-based therapies present in the Greater Mekong Sub-region. Conclusions These results will assist in the interpretation of vaccine efficacy of whole-organism vaccines against homologous and heterologous CHMI.

Abstract Background The genetic diversity of malaria antigens often results in allele variant-specific immunity, imposing a great challenge to vaccine development. Rhoptry Neck Protein 2 (PvRON2) is a blood-stage antigen that plays a key role during the erythrocyte invasion of Plasmodium vivax. This study investigates the genetic diversity of PvRON2 and the naturally acquired immune response to P. vivax isolates. Results Here, the genetic diversity of PvRON21828–2080 and the naturally acquired humoral immune response against PvRON21828–2080 in infected and non-infected individuals from a vivax malaria endemic area in Brazil was reported. The diversity analysis of PvRON21828–2080 revealed that the protein is conserved in isolates in Brazil and worldwide. A total of 18 (19%) patients had IgG antibodies to PvRON21828–2080. Additionally, the analysis of the antibody response in individuals who were not acutely infected with malaria, but had been infected with malaria in the past indicated that 32 patients (33%) exhibited an IgG immune response against PvRON2. Conclusions PvRON2 was conserved among the studied isolates. The presence of naturally acquired antibodies to this protein in the absence of the disease suggests that PvRON2 induces a long-term antibody response. These results indicate that PvRON2 is a potential malaria vaccine candidate.

Abstract Background Technical limitations for culturing the human malaria parasite Plasmodium vivax have impaired the discovery of vaccine candidates, challenging the malaria eradication agenda. The immunogenicity of the M2 domain of the Merozoite Adhesive Erythrocytic Binding Protein (MAEBL) antigen cloned from the Plasmodium yoelii murine parasite, has been previously demonstrated. Results Detailed epitope mapping of MAEBL through immunoinformatics identified several MHCI, MHCII and B cell epitopes throughout the peptide, with several of these lying in the M2 domain and being conserved between P. vivax, P. yoelii and Plasmodium falciparum, hinting that the M2-MAEBL is pan-reactive. This hypothesis was tested through functional assays, showing that P. yoelii M2-MAEBL antisera are able to recognize and inhibit erythrocyte invasion from both P. falciparum and P. vivax parasites isolated from Thai patients, in ex vivo assays. Moreover, the sequence of the M2-MAEBL is shown to be highly conserved between P. vivax isolates from the Amazon and Thailand, indicating that the MAEBL antigen may constitute a vaccine candidate outwitting strain-specific immunity. Conclusions The MAEBL antigen is promising candidate towards the development of a malaria vaccine.