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UWO

Western University
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27 Projects, page 1 of 6
  • Funder: National Science Foundation Project Code: 9530427
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  • Funder: National Science Foundation Project Code: 6113082
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  • Funder: UK Research and Innovation Project Code: NE/T014482/1
    Funder Contribution: 7,609 GBP

    MRC : Heather Grant : MR/N013166/1 HIV is still a huge burden world-wide, with 1.7 million new infections each year (UNAIDS, 2019). The roll out of anti-retroviral therapies (ART) has worked to reduce the numbers of AIDS related deaths and onward transmissions, but to curb further infections still, UNAIDS goals are that 95% of the population should know their status, 95% of those should be on treatment, and 95% of those should be virally supressed. Characterising drivers of new infections will help to identify gaps to be closed. Comparing viral sequences from different patients can be used for epidemiological studies. HIV sequence data for the polymerase gene (pol) is routinely collected for drug-resistance testing, but can then be used secondarily for these purposes, once anonymized, keeping only basic demographic information. Genetic distance (that is, the number of mutational differences between any two viruses) can be used to link closely related viruses together. (A lower genetic distance suggests they shared a common ancestor more recently). HIV mutations are introduced into the genome with each replication cycle. Mutation is said to have its own 'clock' so that changes builds up, on average, in a predictable way over time. Therefore, the genetic distance and time of sampling, can be used to draw linkage, infer networks, patterns of transmission, and other characterisations of the network such as degree distribution. These insights tied with demographic information can inform public health policy. For instance, individuals from groups deemed at high-risk might be advised to take pre-exposure prophylaxis (PrEP). HIV diversity is extremely high, since the virus has been evolving in humans for maybe a hundred years, long before it was first described. It is classified into major lineages (subtypes) that formed early on during its expansion. Where an individual is infected with more than one HIV variant, recombination between the two can occur, creating a hybrid virus, and thus more diversity. This almost certainly happen between two identical viruses from the same infection, but will be undetectable since the new virus is the same as both parents. Where highly divergent viruses recombine, (such as those from different subtypes), this becomes more obvious as there is enough signal to distinguish the two parental viruses. This process of recombination between divergent viruses breaks apart linkages, where one half of the genome might link to the first parental virus, and the other half to the second. Now, if the whole sequence was to be considered in a linkage analysis, no connections would be made as the new sequence is now sufficiently different to both parents. As HIV moves along the transmission network, it will occasionally find itself part of a dual infection, and may take part in a recombination event. This could happen at any time point in time, making it more difficult to spot, as other mutations build up, and the molecular clock moves the virus forward. Dynamic Stochastic Block Modelling is a way of modelling network data, and in our case will be used to find groups or communities of similar viruses over time. This approach will better classify HIV diversity and model networks over time; highly appropriate for a fast-evolving recombinogenic virus. Simulation experiments will be carried out to test the principle and validate the approach. Finally, we will apply this to near-full genome HIV data from Uganda. This research will be undertaken under the supervision of Associate Professor Art Poon in the Department of Pathology and Laboratory Medicine at Western University, Ontario, Canada.

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  • Funder: UK Research and Innovation Project Code: NE/V009982/1
    Funder Contribution: 8,150 GBP

    Throughout Earth's geological history, hydrothermal systems have provided habitats for the most ancient forms of life known on Earth. The warm water in these systems reacts with the local rocks and accelerates chemical reactions. As a result, different chemical compounds are released and can be exploited by microorganisms that utilize chemicals from the bedrock for metabolic energy to form a viable habitat. The geological record of Mars suggests that sulphur-rich hydrothermal systems were widespread during the Hesperian Period, around 3.8 billion years ago and possibly could have supported life as we know it on Earth. This happened shortly after the Late Heavy Bombardment (LHB), when Mars was exposed to extensive impact events. The study of the habitability of these environments is done by researching Mars analogues on Earth. The predominant heat supply of these environments on Earth comes from a magmatic source, either from a volcanic eruption or through a magmatic intrusion into the local rock. On extraterrestrial bodies such as Mars, impacts are the main heat source. The chemical difference between these hydrothermal systems are dependent on the original bedrock and the newly introduced magmatic material. The chemical potential to support microbial life and form a viable habitat between the two different environments will be studied. This will be done by studying relic hydrothermal environments, through analysing rock samples from the sulphur-rich Haughton impact crater in the high Arctic, Canada, and comparing them to magmatic intrusions from the San Raphael Swell, USA. The samples will be collected along a reaction path of unaltered rock to altered rock and analysed for their different mineralogy and chemistry. This will then be used to make a thermodynamic chemical model to understand the reaction path forming the altered rock and the past fluid composition. From the modelled data, the free energy released from the reduction-oxidation reactions will be used to evaluate the different potential of each environment to support microbial life through time and space.

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  • Funder: UK Research and Innovation Project Code: NE/T014326/1
    Funder Contribution: 9,182 GBP

    BBSRC : Laura May Murray : BB/T508330/1 Antibiotics are used to treat infections caused by bacteria. However, bacteria can become resistant to antibiotics, meaning they are still able to grow in the presence of antibiotics. For this reason, infections caused by antibiotic resistant bacteria are becoming more difficult to treat. Infections caused by antibiotic resistant bacteria are also extremely costly, for example, due to increased length of stay in hospital. Overuse and misuse of antibiotics is driving the evolution of antibiotic resistant bacteria, and it has been predicted that by 2050, someone will die every three seconds from an antibiotic resistant infection. However, there is also evidence that other antimicrobial compounds can result in the evolution of antibiotic resistance. Antimicrobials are chemicals or compounds that kill bacteria, but cannot be used for treatment of infections in humans or animals because they are too toxic. Furthermore, there is new research indicating that other chemicals, which are not used as antimicrobials (for example, human medicines) may also lead to the development of antibiotic resistance. How mixtures of antibiotics, antimicrobials and other chemicals may interact and drive the evolution of antibiotic resistance is poorly understood. Antibiotics are not just used to treat and prevent infections in humans and animals; they are also applied to agricultural soils as plant protection products (PPPs). PPPs are used globally to increase crop yields. There are many types of PPPs currently in use, such as herbicides (used to prevent growth of unwanted plants) or insecticides (used to kill pest insects). No research to date has investigated if non-antibiotic PPPs can drive evolution of antibiotic resistance. This research placement will complement work being undertaken in the BBSRC/AstraZeneca iCASE PhD studentship entitled "Investigating selection and co-selection for antimicrobial resistance by non-antibiotic drugs and plant protection products". Laboratory experiments and a variety of culture based and molecular microbiology methods will be used to determine if exposing soil bacterial communities to non-antibiotic PPPs results in increased levels of antibiotic resistance. This placement provides a unique opportunity to study exposure to PPPs in well-established experiment field plots, which are treated with PPPs annually. This will aid interpretation of laboratory experiments and provide an environmentally realistic aspect to the PhD research. The findings from this novel research may be useful for influencing regulation of PPPs, food safety policy and human health risk assessment of exposure to antibiotic resistant bacteria from environmental sources.

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