Awards

Honorine Ward of Tufts Medical Center in the U.S. will develop a three-dimensional model of the human intestine for rapid screening of drugs targeting the parasite Cryptosporidium, which causes potentially lethal diarrhea in young children in developing countries. Developing drugs against Cryptosporidium has been particularly difficult, partly because of the limited understanding of the parasites behavior in the human intestine, and particularly of the effect of malnutrition, which commonly co-occurs with infection and likely contributes to disease severity. They will build a three-dimensional model of the human intestine using a scaffold of silk proteins and a hollow lumen structure lined with cells derived from human intestinal stem cells supported by underlying human myelofibroblasts. They will infect their cell model with fluorescently labelled Cryptosporidium to evaluate how the parasite affects the intestine, and to determine its capacity for high-throughput drug screens.

Nathan McEachen of TerraFrame Inc. in the U.S. will build an extract, transform and load (ETL) plugin so that diverse types of data on disease incidence, spread, and interventions, recorded with different methods can be easily uploaded into the District Health Information Software version 2 (DHIS2) open-source platform, to better inform disease elimination efforts. The DHIS2 is widely used particularly across sub-Saharan Africa to report, analyze and distribute disease-relevant information. However, data collected using different software or in different formats cannot easily be imported despite their potential significance for disease elimination. In cooperation with the Zambia National Malaria Control Centre (NMCC) and their DHIS2-expert in-country partner organization they will identify user requirements for the plugin, such as the systems being used and the nature of the incompatibilities, and test it with NMCCs in other countries.

Howard Ochman of the University of Texas in the U.S. will develop an approach to identify bacteria that can spread antibiotic resistance genes to other bacteria and harm human health. Most methods for monitoring antibiotic resistance are used once resistance has occurred. Here they will measure the capacity for developing resistance, which should help better evaluate how antibiotic resistance persists, spreads and circulates on a global scale. They will develop a simple method based on a single-cell technology to link a marker rRNA gene, for classifying the bacterial species, with a gene known to confer antibiotic resistance. They will use this method to identify antibiotic resistance gene-carrying bacteria within microbial communities comprising trillions of cells, and analyze how it spreads through a mixed bacterial population.

Jane Harries of the University of Cape Town in South Africa will take a multisensory approach to increase the use of contraception, particularly over the long term, across South Africa. By exploring how different contraceptives are perceived via multiple senses, not only visual perceptions but also how they feel, and how their use impacts the daily life of the woman, and her wider network, they hope to identify new barriers that influence uptake. They will present a range of contraceptives to 150 women and 50 men, and encourage them to take photographs and make drawings as a way to explore their different perspectives on the contraceptives and on family planning in general. Group discussions and individual interviews will also be held to further evaluate how people react to the contraceptives, and how they affect their lives.

Yang Cheng of Jiangnan University in China will develop a smartphone application to track Chinese individuals who move to work in other countries with high levels of malaria. When these migrant workers return home, there is a risk that they also import malaria, which can then be locally spread via mosquitoes and cause an outbreak. They will develop the application to measure body temperature and track location, and combine it with an existing malaria response system that is used to identify, track and treat malaria in the Jiangsu province, to improve the accuracy and speed of response.

Martin Matzuk, along with Nicholas Simmons of Baylor College of Medicine in the U.S. and Masahito Ikawa of Osaka University in Japan, will build a male contraceptive drug discovery platform comprising a library of two billion small compounds generated by DNA-Encoded Chemistry Technology (DEC-Tec) at relatively low cost, and a panel of male-specific fertility proteins. Contraception options for men are currently limited to condoms or vasectomy. A safe, low-cost small molecule contraceptive similar to the female "pill", could also help men to better control family planning. They are using the CRISPR/Cas9 mutagenesis strategy to identify new genes essential for male fertility in mice. For ten of these new genes, they will synthesize the corresponding fertility proteins and test them for binding to the compounds in their new, expanded DNA-tagged drug library.

Jianjun Sun of the University of Connecticut in the U.S. is developing non-hormonal contraceptives using a fly-based ovulation assay to identify compounds that specifically block the rupture of follicles, which is required to release eggs for fertilization also in mammals. The popular female contraceptive "pill" alters the hormonal cycle and is widely used throughout the Western world. However, it can have undesirable side effects. In Phase I, they developed a medium-throughput follicle rupture assay using Drosophila follicles and showed that three out of four drugs inhibiting Drosophila follicle rupture had the same effect in mice. They discovered that these drugs also inhibited the production of superoxide, which promotes follicle rupture. Building on this new knowledge, in Phase II, they will develop a high-throughput luminescence-based superoxide-detection assay in Drosophila and screen 13,000 compounds. Top hits will again be validated for activity also in mice, and they will further identify their cellular mechanisms of action using available genetic tools in Drosophila.

Boris Striepen of the University of Georgia in the U.S. will develop a new, more natural mouse model for cryptosporidiosis, which is a leading cause of severe diarrhea in children, to help identify effective treatments. Unlike previous mouse models of this disease, these mice do not need to be immune deficient as they can be infected by a natural strain of the Cryptosporidium parasite, which they previous isolated from house mice. They will genetically modify this strain so it will fluoresce and can thus be easily located in the mice and within individual cells. These mice also experience symptoms more similar to the human disease, and they will use it to assess the effects of malnutrition, which often co-occurs with infection and appears to worsen symptoms. They will also study the effect of different bacterial communities in the gut on disease progression and the effects of existing and emerging treatments.

Arash Shaban-Nejad of the University of Tennessee Health Science Center in the U.S. will develop an analytic framework to help integrate dynamic surveillance data from multiple sources and health systems to support decision making for malaria elimination. Data on malaria is currently scattered in different formats across diverse organizations, making it difficult to access and use. An ontology is a web-based method that explicitly defines specific concepts using logical rules and constraints, and can be used to capture and combine information from numerous sources into a formal framework. They will analyze existing malaria data sources such as Mapping Malaria Risk in Africa (MARA) across selected African countries with different languages including Uganda and Gabon, and use it to generate a service ontology that enables data integration, and implement a semantic web service that can also be used to access the data.

Brian Reich of North Carolina State University in the U.S. will develop a software model to measure the risk of local malaria outbreaks in real-time in the Democratic Republic of Congo and identify treatment strategies for control efforts to more effectively allocate their limited resources. They will build this "recommendation engine" using demographic health survey data from household surveys on disease incidence and types of treatment used, and devise a simple mathematical formula that calculates priority scores, defined by user-specified risk factors, for different regions, which can be easily interpreted by stakeholders.