eGUT: a Tool for Predictive Computer Simulation of the Gut Microbiota and Host Interactions

我们希望建立、应用和推广eGUT，一个新的动物和人类肠道计算机模拟平台，以减少和取代动物实验。肠道，特别是大肠，充满了微生物，统称为微生物群：50%的粪便是微生物。总的来说，被称为细菌的本土微生物对宿主是有益的，无菌动物发育相当差的事实说明了这一点。这是微生物群的行为及其对宿主的代谢和其他影响，我们希望在eGUT中模拟。宿主可以用肠壁来代表由于所有的相互作用都是通过肠道壁来介导的，因此随着人们对肠道菌群重要性的认识不断提高，使用动物实验的研究数量急剧增加，因此开发动物实验替代品的需求变得越来越迫切。很难估计eGUT将避免的动物实验数量，所以应该谨慎对待这些数字。我们估计，eGUT一旦完全开发和接受，每年可以在全球范围内拯救多达15万只动物。然而，在eGUT的使用被广泛接受之前，还需要一些彻底的案例研究来改进和验证eGUT，并证明eGUT可以根据体外实验室数据对动物实验进行可靠的预测。因此，我们将专注于这些案例研究，为eGUT的使用提供令人信服的案例。在此之后，越来越多的科学家将采用它，主要是为了减少使用的动物数量，但最终将完全取代一系列动物实验，例如在营养领域。目标：1.构建eGUTeGUT将基于JK和合作者开发基于个体的微生物相互作用模型的长期经验。它将建立在我们最先进的基于个体的微生物群落动力学模拟器iDynoMiCS的基础上，iDynoMiCS于2011年出版并公开使用虽然iDynoMiCS是eGUT的一个很好的基础，但有必要增加一些模拟肠道的内容（添加肠壁的描述，添加超级个体和相关程序以允许模拟大系统，将单个肠隔室的几个模拟耦合到多隔室模拟中）。此外，我们希望eGUT通过添加图形用户界面和提供更详细的文档和实践教程来更加用户友好。这很耗时，但对于没有数学或计算机科学背景的科学家使用eGUT非常重要，并且该功能将使更多的用户能够使用，因此对3R产生更大的影响。应用eGUT因为我们需要eGUT的测试用例来验证它，并说服其他人它可以做出可靠的预测，所以我们将eGUT应用于三个测试用例。不止一个是必要的，以表明它不仅仅适用于一个特定的问题，但重要的是不要尝试太多，因为如果要做得好，每个案例都需要时间。建议的测试用例为：一个来自我们自己的实验室一个来自荷兰瓦赫宁根大学的Hauke Saughter教授，另一个来自丹麦技术大学国家食品研究所的Tine Licht教授。传播eGUT传播对于建立eGUT的用户群非常重要，因此我们将举办两个为期一周的研讨会，向eGUT的潜在用户传授如何将其应用于自己的研究，以减少或取代动物实验。此外，我们将建立一个专门的网站，并利用媒体渠道推广eGUT（博客，YouTube，科普杂志），以及其他传播计划。

We want to build, apply, and disseminate eGUT, a new computer simulation platform for the animal and human gut, to reduce and replace animal experiments.The gut, in particular the large intestine, is teeming with microorganisms, collectively called the microbiota: 50% of faeces are microorganisms. Overall the indigenous microorganisms called commensals are beneficial for the host, illustrated by the fact that germ-free animals develop rather poorly. It is the behaviour of the microbiota and their metabolic and other effects on the host which we want to simulate in eGUT. The host can be represented by the gut wall (the mucosa), as all interactions are mediated through the gut wall.Due to an increasing awareness of the importance of the gut microbiota, the number of studies using animal experiments has risen sharply, so that the need to develop alternatives to animal experiments is becoming increasingly urgent.It is very difficult to estimate the number of animal experiments that eGUT will avoid, so the numbers should be treated with caution. We estimate that eGUT, once fully developed and accepted, could save up to 150,000 animals globally per year. However, it will take some thorough case studies to improve and validate eGUT and to demonstrate that eGUT can make reliable predictions of animal experiments based on in vitro laboratory data, before the use of eGUT will become widely accepted. We will therefore focus on these case studies to make a convincing case for the use of eGUT. After this, more and more scientists will adopt it, mainly to reduce the numbers of animals used, but eventually to fully replace a range of animal experiments, for example in the area of nutrition.Objectives:1. Build eGUTeGUT will be based on the long experience of JK and collaborators with developing individual-based models of the interactions of microorganisms. It will build on our state of the art individual-based Dynamics of Microbial Communities Simulator iDynoMiCS, which was published in 2011 and released for public use (open source) on www.idynomics.org. While iDynoMiCS is an excellent basis for eGUT, a number of additions to simulate the gut will be necessary (add a description of the gut wall, add superindividuals and related procedures to allow simulation of a large system, couple several simulations of individual gut compartments into a multi-compartment simulation). Moreover, we want eGUT to be more user-friendly by adding a graphical user interface and by providing more detailed documentation and hands-on tutorials. This is time consuming but very important to allow scientists without mathematical or computer science backgrounds to use eGUT, and this functionality will enable a far wider number or users and therefore far more impact on the 3Rs.2. Apply eGUTBecause we need test cases for eGUT to validate it and to convince others that it makes reliable predictions, we will apply eGUT to three test cases. More than one is necessary to show that it does not just work for one specific problem, but it is important to not attempt too many as each case will require time if it is to be done well. The test cases proposed are: one from our own laboratory; one from Prof Hauke Smidt at Wageningen University in The Netherlands; and one from Prof Tine Licht from the National Food Institute at the Technical University of Denmark.3. Disseminate eGUTDissemination is very important to build up a user base for eGUT, so we will run two one-week workshops where we will teach potential users of eGUT how they can apply it to their own research in order to reduce or replace animal experiments. Further, we will build a dedicated web site and use media channels to promote eGUT (blogs, YouTube, popular science magazines), amongst other plans for dissemination.