Single-genome sequencing reveals within-host evolution of human malaria parasites

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jMHC: software assistant for multilocus genotyping of gene families using next-generation amplicon sequencing

Genotyping of multilocus gene families, such as the major histocompatibility complex (MHC), may be challenging because of problems with assigning alleles to loci and copy number variation among individuals. Simultaneous amplification and genotyping of multiple loci may be necessary, and in such cases, next-generation deep amplicon sequencing offers a great promise as a genotyping method of choice. Here, we describe jMHC, a computer program developed for analysing and assisting in the visualization of deep amplicon sequencing data. Software operates on FASTA files; therefore, output from any sequencing technology may be used. jMHC was designed specifically for MHC studies but it may be useful for analysing amplicons derived from other multigene families or for genotyping other polymorphic systems. The program is written in Java with user-friendly graphical interface (GUI) and can be run on Microsoft Windows, Linux OS and Mac OS.     

Reemerging vivax malaria: changing patterns of annual incidence and control programs in the Republic of Korea

Changing patterns of the reemerging Plasmodium vivax malaria in the Republic of Korea (South Korea) during the period 1993 to 2005 are briefly analyzed with emphasis on the control measures used and the effects of meteorological and entomological factors. Data were obtained from the Communicable Diseases Monthly Reports published by the Korea Center for Disease Control and Prevention, and webpages of World Health Organization and United Nations. Meteorological data of Kangwon-do (Province) were obtained from local weather stations. After its first reemergence in 1993, the prevalence of malaria increased exponentially, peaking in 2000, and then decreased. In total, 21,419 cases were reported between 1993 and 2005 in South Korea. In North Korea, a total of 916,225 cases were reported between 1999 and 2004. The occurrence of malaria in high risk areas of South Korea was significantly (P > 0.05) correlated with the mosquito population but not with temperature and rainfall. Control programs, including early case detection and treatment, mass chemoprophylaxis of soldiers, and international financial aids to North Korea for malaria control have been instituted. The situation of the reemerging vivax malaria in the Republic of Korea is remarkably improving during the recent years, at least in part, due to the control activities undertaken in South and North Korea.     

The fitness of drug-resistant malaria parasites in a rodent model: multiplicity of infection

Malaria infections normally consist of more than one clonally replicating lineage. Within-host interactions between sensitive and resistant parasites can have profound effects on the evolution of drug resistance. Here, using the Plasmodium chabaudi mouse malaria model, we ask whether the costs and benefits of resistance are affected by the number of co-infecting strains competing with a resistant clone. We found strong competitive suppression of resistant parasites in untreated infections and marked competitive release following treatment. The magnitude of competitive suppression depended on competitor identity. However, there was no overall effect of the diversity of susceptible parasites on the extent of competitive suppression or release. If these findings generalize, then transmission intensity will impact on resistance evolution because of its effect on the frequency of mixed infections, not because of its effect on the distribution of clones per host. This would greatly simplify the computational problems of adequately capturing within-host ecology in models of drug resistance evolution in malaria.     

Efficient and robust approaches for analysis of sequential multiple assignment randomized trials: Illustration using the ADAPT-R trial

Personalized intervention strategies, in particular those that modify treatment based on a participant's own response, are a core component of precision medicine approaches. Sequential multiple assignment randomized trials (SMARTs) are growing in popularity and are specifically designed to facilitate the evaluation of sequential adaptive strategies, in particular those embedded within the SMART. Advances in efficient estimation approaches that are able to incorporate machine learning while retaining valid inference can allow for more precise estimates of the effectiveness of these embedded regimes. However, to the best of our knowledge, such approaches have not yet been applied as the primary analysis in SMART trials. In this paper, we present a robust and efficient approach using targeted maximum likelihood estimation (TMLE) for estimating and contrasting expected outcomes under the dynamic regimes embedded in a SMART, together with generating simultaneous confidence intervals for the resulting estimates. We contrast this method with two alternatives (G-computation and inverse probability weighting estimators). The precision gains and robust inference achievable through the use of TMLE to evaluate the effects of embedded regimes are illustrated using both outcome-blind simulations and a real-data analysis from the Adaptive Strategies for Preventing and Treating Lapses of Retention in Human Immunodeficiency Virus (HIV) Care (ADAPT-R) trial (NCT02338739), a SMART with a primary aim of identifying strategies to improve retention in HIV care among people living with HIV in sub-Saharan Africa.     

Assessment of arbovirus vector infection rates using variable size pooling

Pool testing of vector samples for arboviruses is widely used in surveillance programmes. The proportion of infected mosquitoes (Diptera: Culicidae) is often estimated from the minimum infection rate (MIR), based on the assumption of only one infected mosquito per positive pool. This assumption becomes problematic when pool size is large and/or infection rate is high. By relaxing this constraint, maximum likelihood estimation (MLE) is more useful for a wide range of infection levels that may be encountered in the field. We demonstrate the difference between these two estimation approaches using West Nile virus (WNV) surveillance data from vectors collected by gravid traps in Chicago during 2002. MLE of infection rates of Culex mosquitoes was as high as 60 per 1000 at the peak of transmission in August, whereas MIR was less than 30 per 1000. More importantly, we demonstrate roles of various pooling strategies for better estimation of infection rates based on simulation studies with hypothetical mosquito samples of 18 pools. Variable size pooling (with a serial pool sizes of 5, 10, 20, 30, 40 and 50 individuals) performed consistently better than a constant size pooling of 50 individuals. We conclude that variable pool size coupled with MLE is critical for accurate estimates of mosquito infection rates in WNV epidemic seasons.