Toward whole-cell models for precision medicine and synthetic biology

项目摘要 我的长期目标是开发全面的基于物理学的人类全细胞计算模型， 从基因型预测表型。这样的模型可以帮助个性化治疗的基础上，每个 病人的组学特征，并帮助可预见地设计细菌来执行有用的任务，如生产药物。 尽管经过了几十年的研究，数据也越来越丰富，但我们仍然不明白基因型是如何影响人类健康的。 在遗传表型上。例如，我们无法定量地了解蛋白质表达是如何控制的， 蛋白质表达如何影响反应速率，进而影响细胞行为，如生长。因此我们 无法准确预测基因如何影响行为、个性化治疗或合理改造细菌。 我们需要新的计算方法来将我们不同的数据联合收割机组合成一个统一的细胞生物学艾德理论。 全细胞建模是一种很有前途的新技术，它能够将数据合并到一个单一的模型中， 发送每个分子种类和基因功能。全细胞模型可以通过组合多个 路径子模型。最近，我和我的同事使用这种方法实现了第一个全细胞模型。 然而，该模型代表了最简单的细菌;该模型没有考虑大量的细胞功能， 该模型不能预测许多表型;我们的模拟算法不能满足我们的核心 子模型时间分离假设。此外，该模型的构建耗时;该模型 难以理解;模型计算成本高;模拟软件不可重复使用。 我们必须开发改进的全细胞建模方法，以促进完整的全细胞模型及其应用。 应用于精准医学，并广泛地使研究人员能够从事全细胞建模。(1)一个 需要改进的多算法仿真元算法来严格地仿真模型。(2)并行化 需要仿真器来快速仿真模型。(3)需要新的数据管理和子模型设计工具 加快模型的建立。(4)需要新的培训材料和讲习班， 全细胞模型 我的长期目标是开发个性化的人类全细胞模型，并利用这些模型来改善 药物治疗为了实现这些目标，我们将（1）开发改进的全细胞建模方法， 更全面的模型，（2）致力于第一个人类全细胞模型，（3）开发使用 个性化模型以优化治疗，以及（4）开发全细胞建模训练材料。这些努力 将解决全细胞建模的方法学挑战，将全细胞建模的前沿扩展到 人类生物学和医学，生产软件工具，广泛地使研究人员能够模拟整个细胞 模型，并推进全细胞建模领域。展望未来，全细胞模型有潜力 通过为科学家提供对细胞生物学的完整理解来彻底改变基础科学， 让医生能够精确地设计治疗方法，并使合成生物学成为可能。

PROJECT SUMMARY My long-term goal is to develop comprehensive physics-based whole-cell computational models of humans and bacteria to predict phenotypes from genotypes. Such models could help personalize therapy based on each patient's 'omics profile and help predictably engineer bacteria to perform useful tasks such as producing drugs. Despite decades of research and the growing wealth of data, we still do not understand how genotypes influence phenotypes. For example, we do not quantitatively understand how protein expression is controlled or how protein expression affects reaction rates, and, in turn, cellular behaviors such as growth. Consequently, we cannot accurately predict how genes influence behavior, personalize therapy, or rationally engineer bacteria. New computational methods are needed to combine our disparate data into a unified theory of cell biology. Whole-cell modeling is a promising new technique that is capable of merging data into a single model that repre- sents every molecular species and gene function. Whole-cell models can be constructed by combining multiple pathway sub-models. Recently, my colleagues and I used this approach to achieve the first whole-cell model. However, the model represents the simplest bacterium; the model does not account for numerous cell func- tions; the model does not predict many phenotypes; and our simulation algorithm does not satisfy our core sub-model time separation assumption. Furthermore, the model was time-consuming to construct; the model is difficult to understand; the model is computationally expensive; and the simulation software is not reusable. We must develop improved whole-cell modeling methods to facilitate complete whole-cell models and their application to precision medicine, and to broadly enable researchers to engage in whole-cell modeling. (1) An improved multi-algorithm simulation meta-algorithm is needed to rigorously simulate models. (2) A parallelized simulator is needed to quickly simulate models. (3) New data curation and sub-model design tools are needed to expedite model building. (4) New training materials and workshops are needed to recruit researchers into whole-cell modeling. My long-term goals are to develop personalized human whole-cell models, and to use these models to improve medical therapy. Toward these goals, we will (1) develop improved whole-cell modeling methods to enable more comprehensive models, (2) work toward the first human whole-cell model, (3) develop methods that use personalized models to optimize therapy, and (4) develop whole-cell modeling training materials. These efforts will address the methodological challenges of whole-modeling, expand the frontier of whole-cell modeling into human biology and medicine, produce software tools which broadly enable researchers to simulate whole-cell models, and advance the whole-cell modeling field. Looking forward, whole-cell models have the potential to revolutionize basic science by providing scientists a complete understanding of cell biology, transform medicine by enabling physicians to precisely design therapy, and enable synthetic biology.