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Correlation of imaging and impedimetric data to predict cell state and changes in bioreactors

Correlation of imaging and impedimetric data to predict cell state and changes in bioreactors
成像和阻抗测量数据的相关性以预测细胞状态和生物反应器的变化
批准号:
2439724
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --

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英文摘要
The ability to monitor and influence the physiological state of a cell (population) is of critical importance not just for reproducible results in academia but especially in the pharmaceutical industry. Here, the cell physiological state is directly correlated with the production of biologicals and consequently profitability and quality.There are multiple ways to measure the cell state but most look at a single parameter. It is much more informative to integrate and correlate different types of data. Correlative Light Electron Microscopy (CLEM) is one of the most powerful imaging technologies combining the advantages of (live) light microscopy (LM) with the nanometer spatial resolution of electron microscopy (EM) into one experiment. Using this technology, key biological questions have been answered [1].Cell structures and metabolic activity affect the electrical properties of the cell and by employing a broadband approach to impedance spectroscopy multiple cell properties can be investigated. In general terms, high-frequencies are associated with changes in the cell cytoplasm/internal structures (10-60Mz), middle-frequencies with the cell membrane (2-10MHz) and lower-frequencies with cell size (0.1-2 MHz). We have shown that dose-dependent characteristics of the impedance spectra of cell culture when exposed to a toxic challenge are related to the toxin's mode of action [2].There is a need and drive to extract more than just LM and EM data from a single experiment and to include other types of information, expanding the CLEM field to an approach called Correlative Multimodal Imaging (CMI). In principle the CMI approach would extract any type of information from a single event and correlate and integrate the data.This project enables, for the first time, to understand and correlate morphological and anatomical changes in the cell structure, detected microscopically, to changes in characteristics of an impedance spectrum. Impedance spectroscopy can be employed to monitor cells growing in a bioreactor and by understanding the changes in the impedance spectra related to cell stress will enable the early detection and mitigation of cell stress.We propose to develop a CMI approach that combines live imaging with impedance measurements in control and stressed (e.g. toxins) conditions in order to better understand the different responses to stressors. We will use live calcium and / or ATP imaging in combination with impedance measurements. Subsequently we will also aim to introduce stress receptor-GFP imaging and EM morphology into this correlative approach to increase the power of the technology.
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