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High-throughput single-molecule analysis of the influenza A genome structure and assembly

High-throughput single-molecule analysis of the influenza A genome structure and assembly
甲型流感基因组结构和组装的高通量单分子分析
批准号:
BB/V001868/1
负责人:
Achillefs Kapanidis
金额:
$56.32万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

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英文摘要
The influenza (flu) virus is the microscopic pathogen that causes flu in humans and animals. We propose to use special microscopy methods to understand the structure of the genetic material of the flu virus, and how interactions between the genetic material can become important in flu pandemics. The genetic material, or genome, of the flu virus is made of RNA (a long chain of molecules that encodes genetic information) and is divided into eight individual segments. The natural host of the flu virus is wild birds; however, in a process called 'reassortment', different strains of the virus can swap RNA segments in a way that allows us to infect other host organisms, including humans. Reassortment events result in the generation of entirely new virus strains, to which humans have never previously been exposed. When there is no existing immunity in the human population to a novel influenza virus, reassortment can cause deadly worldwide pandemics, such as the Spanish flu pandemic in 1918, which was responsible for over 50 million deaths worldwide, and the 'swine flu' pandemic in 2009. Whilst H5N1 'bird flu' strains haven't yet reassorted to the extent that they can reliably infect humans and cause a pandemic, outbreaks in birds have been devastating for the poultry industry since millions of birds have been culled to reduce virus spread, resulting in huge economic losses.Despite flu being one of the best-studied viruses, we are still unsure how exactly the genomic segments contact each other inside virus particles. Much of our knowledge of this process has relied on data obtained using methods that measure the properties of millions of molecules (or particles) in one go, and therefore report on the averaged properties of all of the molecules. We plan to use advanced 'single-molecule techniques', which allow us to study one molecule (or particle) at a time; this allows us to see details unique to each molecule (or particle) that may be impossible to see using traditional analytical or biological methods. We plan to perform our single-molecule analysis by using many small pieces of fluorescent DNA, that will bind all the way along the virus gene segments, to detect the presence and map the structure of the gene segments at very high resolution. Further, the fluorescent DNAs will not be able to bind to sections of the genome that interact with other genomic segments (as these areas will not be accessible due to the close contacts between segments), thereby allowing us to build up a picture of crucial RNA-RNA interactions within virus particles. To image the virus particles as they are being detected by the small DNA pieces, we will use a specialised "single-molecule fluorescence" microscope, which is carefully designed to allow the detection and monitoring of individual fluorescent molecules present in a detection zone (as opposed to conventional microscopes that require thousands or millions of molecules to be present in a detection zone). We anticipate that our research will help the scientific community to better understand how the genome segments of the flu virus interact and cause pandemics, and help in efforts to control and stop its spread. Our discoveries should also help us understand and control other viruses that cause danger to humans and animals, and contribute towards development of new diagnostic tests for rapid and sensitive detection of influenza and other pathogenic viruses.
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会议论文
DOI: 10.1021/acsnano.2c10159
发表时间: 2023-01-10
期刊: ACS NANO
影响因子: 17.1
作者: [Shiaelis, Nicolas, Tometzki, Alexander, Peto, Leon, McMahon, Andrew, Hepp, Christof, Bickerton, Erica, Favard, Cyril, Muriaux, Delphine, Andersson, Monique, Oakley, Sarah, Vaughan, Ali, Matthews, Philippa C., Stoesser, Nicole, Crook, Derrick W., Kapanidis, Achillefs N., Robb, Nicole C.]
通讯作者: Robb, Nicole C.
DOI: 10.1371/journal.ppat.1011484
发表时间: 2023-06
期刊: PLoS pathogens
影响因子: 6.7
作者: []
通讯作者:
Virus detection and identification in minutes using single-particle imaging and deep learning
使用单粒子成像和深度学习在几分钟内检测和识别病毒
DOI: 10.1101/2020.10.13.20212035
发表时间: 2020
期刊:
影响因子: --
作者: [Shiaelis N]
通讯作者: Shiaelis N
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  • 项目类别:
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  • 资助金额:
    $62.66万
  • 财政年份:
    2023
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  • 项目类别:
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  • 资助金额:
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    2016
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