Hackathons as a means of accelerating scientific discoveries and knowledge transfer

Scientific research plays a key role in the advancement of human knowledge and pursuit of solutions to important societal challenges. Typically, research occurs within specific institutions where data are generated and subsequently analyzed. Although collaborative science bringing together multiple institutions is now common, in such collaborations the analytical processing of the data is often performed by individual researchers within the team, with only limited internal oversight and critical analysis of the workflow prior to publication. Here, we show how hackathons can be a means of enhancing collaborative science by enabling peer review before results of analyses are published by cross-validating the design of studies or underlying data sets and by driving reproducibility of scientific analyses. Traditionally, in data analysis processes, data generators and bioinformaticians are divided and do not collaborate on analyzing the data. Hackathons are a good strategy to build bridges over the traditional divide and are potentially a great agile extension to the more structured collaborations between multiple investigators and institutions

The extended recovery ring-stage survival assay provides a superior association with patient clearance half-life and increases throughput

Background Tracking and understanding artemisinin resistance is key for preventing global setbacks in malaria eradication efforts. The ring-stage survival assay (RSA) is the current gold standard for in vitro artemisinin resistance phenotyping. However, the RSA has several drawbacks: it is relatively low throughput, has high variance due to microscopy readout, and correlates poorly with the current benchmark for in vivo resistance, patient clearance half-life post-artemisinin treatment. Here a modified RSA is presented, the extended Recovery Ring-stage Survival Assay (eRRSA), using 15 cloned patient isolates from Southeast Asia with a range of patient clearance half-lives, including parasite isolates with and without kelch13 mutations. Methods Plasmodium falciparum cultures were synchronized with single layer Percoll during the schizont stage of the intraerythrocytic development cycle. Cultures were left to reinvade to early ring-stage and parasitaemia was quantified using flow cytometry. Cultures were diluted to 2% haematocrit and 0.5% parasitaemia in a 96-well plate to start the assay, allowing for increased throughput and decreased variability between biological replicates. Parasites were treated with 700 nM of dihydroartemisinin or 0.02% dimethyl sulfoxide (DMSO) for 6 h, washed three times in drug-free media, and incubated for 66 or 114 h, when samples were collected and frozen for PCR amplification. A SYBR Green-based quantitative PCR method was used to quantify the fold-change between treated and untreated samples. Results 15 cloned patient isolates from Southeast Asia with a range of patient clearance half-lives were assayed using the eRRSA. Due to the large number of pyknotic and dying parasites at 66 h post-exposure (72 h sample), parasites were grown for an additional cell cycle (114 h post-exposure, 120 h sample), which drastically improved correlation with patient clearance half-life compared to the 66 h post-exposure sample. A Spearman correlation of − 0.8393 between fold change and patient clearance half-life was identified in these 15 isolates from Southeast Asia, which is the strongest correlation reported to date. Conclusions eRRSA drastically increases the efficiency and accuracy of in vitro artemisinin resistance phenotyping compared to the traditional RSA, which paves the way for extensive in vitro phenotyping of hundreds of artemisinin resistant parasites

Optimizing bulk segregant analysis of drug resistance using Plasmodium falciparum genetic crosses conducted in humanized mice

Classical malaria parasite genetic crosses involve isolation, genotyping, and phenotyping of progeny parasites, which is time consuming and laborious. We tested a rapid alternative approach-bulk segregant analysis (BSA)-that utilizes sequencing of bulk progeny populations with and without drug selection for rapid identification of drug resistance loci. We used dihydroartemisinin (DHA) selection in two genetic crosses and investigated how synchronization, cryopreservation, and the drug selection regimen impacted BSA success. We detected a robust quantitative trait locus (QTL) at kelch13 in both crosses but did not detect QTLs at four other candidate loci. QTLs were detected using synchronized, but not unsynchronized progeny pools, consistent with the stage-specific action of DHA. We also successfully applied BSA to cryopreserved progeny pools, expanding the utility of this approach. We conclude that BSA provides a powerful approach for investigating the genetic architecture of drug resistance in Plasmodium falciparum

Gene-environment interactions in the etiology of human violence

This chapter reviews the current research on gene-environment interactions (G × E) with regard to human violence. Findings are summarized from both behavioral and molecular genetic studies that have investigated the interplay of genetic and environmental factors in terms of influencing violence-related behavior. Together, these studies reveal promising evidence that genetic factors combine with environmental influences to impact on the development of violent behavior and related phenotypes. G × E have been identified for a number of candidate genes implicated in violence. Moreover, the reviewed G × E were found to extend to a broad range of environmental characteristics, including both adverse and favorable conditions. As has been the case with other G × E research, findings have been mixed, with considerable heterogeneity between studies. Lack of replication together with serious methodological limitations remains a major challenge for drawing definitive conclusions about the nature of violence-related G × E. In order to fulfill its potential, it is recommended that future G × E research needs to shift its focus to dissecting the neural mechanisms and the underlying pathophysiological pathways by which genetic variation may influence differential susceptibility to environmental exposures