HDR: DIRSE-IL: Collaborative Research: Harnessing data advances in systems biology to design a biological 3D printer: the synthetic coral

HDR：DIRSE-IL：协作研究：利用系统生物学的数据进步来设计生物 3D 打印机：合成珊瑚

基本信息

批准号：
1939263
负责人：
Lenore Cowen
金额：
$ 26.01万
依托单位：
Tufts University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-10-01 至 2022-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1939263&HistoricalAwards=false
关键词：
HDR DIRSE IL Collaborative Research

项目摘要

Corals are important natural resources that are key to the ocean's vast biodiversity and provide economic, cultural, and scientific benefits. As a result of human activities, locally and globally, coral reefs are declining rapidly. The complexity of corals makes conserving and restoring reefs very challenging. Corals are made up of thousands of different organisms, including the animal host and the algae, bacteria, viruses, and fungi that coexist as a so-called holobiont. Thus, corals are more like cities than individual animals, as they provide factories, housing, restaurants, nurseries, and more for an entire ecosystem. This project brings together experts in computer science, materials science, and biology to harness the data revolution in biology with machine learning to study how corals grow and function, when viewed as if they were manufacturing sites in the ocean. The study will focus on three key coral capabilities: (1) they create calcium carbonate skeletons that provide 3D structures for diverse sea life to live in, (2) they can heal damage to their tissues, and, (3) they live with the other organisms in a process referred to as symbiosis. Through these remarkable abilities, corals can 'print' resources for themselves and hundreds of thousands of other species, just like a 3D printer. The goal of this project is to understand these processes well enough to control them in the lab. This project may allow finding new ways to help coral survival, by deciphering the reasons why certain conditions damage them and find ways of repairing them. Furthermore, by synthetically growing corals, new types of materials may be identified for manufacturing. This project offers an opportunity to educate a diverse scientific workforce and the public by creating and disseminating the outcomes of a convergent research environment and will train postdoctoral researchers, graduate, and undergraduate students. Results of this research will be made available to the broader scientific community through web interfaces, peer-reviewed publications and workshops/conferences and shared with the public through outreach activities online, at schools, and public aquariums. Through convergence of three disciplines, computer science, material science and biology, this project will provide a data-driven framework and toolset to learn from, control, engineer, and manufacture a combined form of living material, the 'synthetic coral', thereby opening new avenues for material synthesis and manufacturing. The research methodology will offer new analytical approaches to identify and quantify the parameters that govern coral growth and foster innovative new tools for controlling their growth. To understand the key functions of coral biology of biomineralization, wound healing, and symbiosis, this research will : (1) harness and analyze large amounts of coral '-omics' data to decipher critical molecules and their interactions for the aforementioned key functions, (2) experimentally validate the resulting predictions in coral individuals and cell lines, (3) manipulate the material properties of the calcium carbonate structures of the coral individuals and cell lines, and (4) test the biological and physical interactions in a network model of the 'synthetic coral'. This project develops and integrates fundamental building blocks that are essential for an integrated computational and experimental validation system. Specifically, using machine learning, diverse data will be harnessed to identify physical conditions (e.g., surface characteristics), environmental conditions (e.g., temperature, pH), and key biological constituents (e.g., small molecule ligands and proteins encoded in the DNA) that are correlated to key structural and functional properties of the coral holobiont. These predicted conditions and molecules will be verified experimentally by perturbing individual coral nodes in a network of a 3D printed array of intact corals or their constituent cells and measuring their effects on the network of interactions and resulting structures. The results from this prediction-validation cycle will then be transferred back as input to manufacture novel adaptive materials fully embracing the organic/inorganic interface. This project is part of the National Science Foundation's Harnessing the Data Revolution (HDR) Big Idea activity.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

珊瑚是重要的自然资源，是海洋丰富的生物多样性的关键，并提供经济、文化和科学效益。由于人类活动，当地和全球范围内的珊瑚礁正在迅速减少。珊瑚的复杂性使得保护和恢复珊瑚礁非常具有挑战性。珊瑚由数千种不同的生物体组成，包括动物宿主和作为所谓的全生物共存的藻类、细菌、病毒和真菌。因此，珊瑚更像城市而不是个体动物，因为它们为整个生态系统提供工厂、住房、餐馆、托儿所等。该项目汇集了计算机科学、材料科学和生物学领域的专家，利用生物学中的数据革命和机器学习来研究珊瑚的生长和功能，就像它们是海洋中的生产基地一样。该研究将重点关注珊瑚的三个关键能力：(1) 它们创造碳酸钙骨骼，为不同的海洋生物提供 3D 结构，以供其生存；(2) 它们可以治愈组织损伤；(3) 它们与珊瑚一起生活其他生物体参与的过程称为共生。通过这些非凡的能力，珊瑚可以为自己和数十万其他物种“打印”资源，就像 3D 打印机一样。该项目的目标是充分了解这些过程，以便在实验室中控制它们。该项目可能会通过破译某些条件损害珊瑚的原因并找到修复它们的方法，找到帮助珊瑚生存的新方法。此外，通过合成珊瑚，可以确定用于制造的新型材料。该项目通过创建和传播融合研究环境的成果，提供了教育多元化科学工作者和公众的机会，并将培训博士后研究人员、研究生和本科生。这项研究的结果将通过网络界面、同行评审出版物和研讨会/会议向更广泛的科学界提供，并通过在线、学校和公共水族馆的外展活动与公众分享。通过计算机科学、材料科学和生物学这三个学科的融合，该项目将提供一个数据驱动的框架和工具集，用于学习、控制、设计和制造一种组合形式的生物材料，即“合成珊瑚”，从而开启材料合成和制造的新途径。该研究方法将提供新的分析方法来识别和量化控制珊瑚生长的参数，并培育控制珊瑚生长的创新工具。为了了解珊瑚生物学的生物矿化、伤口愈合和共生的关键功能，本研究将：（1）利用和分析大量珊瑚“组学”数据来破译关键分子及其相互作用，以实现上述关键功能，（ 2）通过实验验证珊瑚个体和细胞系的预测结果，（3）操纵珊瑚个体和细胞系的碳酸钙结构的材料特性，以及（4）测试珊瑚个体和细胞系的网络模型中的生物和物理相互作用“合成珊瑚”。该项目开发并集成了对于集成计算和实验验证系统至关重要的基本构建模块。具体来说，使用机器学习，将利用不同的数据来识别物理条件（例如，表面特征）、环境条件（例如，温度、pH）和关键生物成分（例如，小分子配体和 DNA 中编码的蛋白质）。与珊瑚全生物的关键结构和功能特性相关。这些预测的条件和分子将通过扰动完整珊瑚 3D 打印阵列或其组成细胞网络中的单个珊瑚节点并测量它们对相互作用网络和所得结构的影响来进行实验验证。然后，该预测验证周期的结果将作为输入传回，以制造完全包含有机/无机界面的新型自适应材料。该项目是美国国家科学基金会利用数据革命 (HDR) 大创意活动的一部分。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

MEtaData Format for Open Reef Data (MEDFORD)

开放珊瑚礁数据元数据格式 (MEDFORD)

DOI：
发表时间：
2022-04
期刊：
Metadata and Semantic Research. MTSR 2021.
影响因子：
0
作者：
Shpilker, P.;Freeman, J.;McKelvie, H.;Ashey, J.;Fonticella, J.M.;Putnam, H.;Greenberg, J.;Cowen, L.;Couch, A.;Daniels, N.M.
通讯作者：
Daniels, N.M.

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