2020BBSRC-NSF/BIO: Linking Mass Spectrometry Computational Ecosystems to Enhance Biological Insights of Publicly-Available Data

所有的生物系统都是由重要的化学物质组成的，这些化学物质有助于系统的生长、对环境的反应和交流。基因组由携带生殖、生长和发育所需遗传信息的DNA组成，其组成在一生中保持相对稳定。代谢组由来自食物（如糖）和环境（如处方药）的代谢物组成，其组成是动态的，与存在的代谢物和浓度有关。科学研究界研究代谢物是为了了解我们如何代谢食物和药物，我们如何对环境做出动态反应，以及识别对生物系统功能至关重要的代谢物。这些研究中的许多都是发现性研究，应用一种叫做代谢组学的科学技术，可以在生物样本中检测到数百或数千种不同的代谢物。这些研究发现了新的代谢物，然后必须对其进行分析，以了解其化学结构，这对生物学解释至关重要。世界各地进行的许多代谢组学研究正在向科学界发布，以便这些数据可以重复使用和重新分析，以获得新的生物信息。这些研究的数据存储在数据库中，其中两个例子是英国的代谢产物和美国的GNPS。然而，在这些数据库中检测和报告的许多代谢物没有分配给它们的化学特性。因此，有必要为尽可能多的代谢物分配化学结构，以便数据可以重复使用，并从数据中获得生物信息。计划中的项目将进一步开发和应用计算方法来处理储存在代谢物和GNPS中的所有数据。这将允许更多的代谢物被分配一个化学特性，并增加正确结构的信心。完成后，储存的数据集中可获得的生物信息的数量和质量将大大提高，并将允许提出和回答新的研究问题，而无需收集新的数据。

All biological systems are composed of important chemicals which help the systems grow, respond to the environment and communicate. The genome is composed of DNA which carries genetic information required for reproduction, growth and development and whose composition remains relatively static throughout a lifetime. The metabolome is composed of metabolites derived from food (e.g. sugars) and the environment (e.g. prescribed drugs) and whose composition is dynamic in relation to which metabolites are present and at what concentration. The scientific research community studies metabolites to understand how we metabolise food and drugs, how we respond dynamically to the environment and also to identify metabolites which are important for a biological system to function. Many of these investigations are discovery studies which apply a scientific technique called metabolomics that can detect hundreds or low thousands of different metabolites in a biological sample. These studies discover new metabolites which then have to be analysed to understand their chemical structure which is essential for biological interpretation. Many metabolomic studies performed across the world are being released to the scientific community so that these data can be re-used and re-analysed to derive new biological information. The data from these studies are stored in data repositories and two examples of these are MetaboLights in the UK and GNPS in the USA. However, many of the metabolites detected and reported in these data repositories do not have a chemical identity assigned to them. Therefore there is an essential requirement to assign chemical structures to as many metabolites as is possible so that the data can be reused and biological information derived from the data. The planned project will further develop and apply computational approaches to all data deposited in MetaboLights and GNPS. This will allow more metabolites to be assigned a chemical identity and for the confidence that the correct structure has been assigned to be increased. When completed, the volume and quality of biological information available in the deposited datasets will be much greater and will allow new research questions to be asked and answered without the need to collect new data.