College of Software, College of Computer Science and Technology, Jilin University, Changchun 130012, China.
Department of Medical and Molecular Genetics and Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Nucleic Acids Res. 2023 Jul 5;51(W1):W180-W190. doi: 10.1093/nar/gkad444.
Quantitative assessment of single cell fluxome is critical for understanding the metabolic heterogeneity in diseases. Unfortunately, laboratory-based single cell fluxomics is currently impractical, and the current computational tools for flux estimation are not designed for single cell-level prediction. Given the well-established link between transcriptomic and metabolomic profiles, leveraging single cell transcriptomics data to predict single cell fluxome is not only feasible but also an urgent task. In this study, we present FLUXestimator, an online platform for predicting metabolic fluxome and variations using single cell or general transcriptomics data of large sample-size. The FLUXestimator webserver implements a recently developed unsupervised approach called single cell flux estimation analysis (scFEA), which uses a new neural network architecture to estimate reaction rates from transcriptomics data. To the best of our knowledge, FLUXestimator is the first web-based tool dedicated to predicting cell-/sample-wise metabolic flux and metabolite variations using transcriptomics data of human, mouse and 15 other common experimental organisms. The FLUXestimator webserver is available at http://scFLUX.org/, and stand-alone tools for local use are available at https://github.com/changwn/scFEA. Our tool provides a new avenue for studying metabolic heterogeneity in diseases and has the potential to facilitate the development of new therapeutic strategies.
单细胞通量组学的定量评估对于理解疾病中的代谢异质性至关重要。不幸的是，基于实验室的单细胞通量组学目前是不切实际的，而当前用于通量估计的计算工具并不是专为单细胞水平预测而设计的。鉴于转录组学和代谢组学图谱之间已经建立了良好的联系，利用单细胞转录组学数据来预测单细胞通量组学不仅是可行的，而且是一项紧迫的任务。在本研究中，我们提出了 FLUXestimator，这是一个在线平台，用于使用单细胞或大样本量的一般转录组学数据来预测代谢通量组学和变化。FLUXestimator 网络服务器实现了一种最近开发的名为单细胞通量估计分析（scFEA）的无监督方法，该方法使用新的神经网络架构从转录组学数据中估计反应速率。据我们所知，FLUXestimator 是第一个专门使用人类、小鼠和 15 种其他常见实验生物的转录组学数据来预测细胞/样本代谢通量和代谢物变化的基于网络的工具。FLUXestimator 网络服务器可在 http://scFLUX.org/ 上访问，本地使用的独立工具可在 https://github.com/changwn/scFEA 上访问。我们的工具为研究疾病中的代谢异质性提供了新的途径，并有可能促进新治疗策略的发展。
