Amino acid transport through the placenta: an experimental and modelling investigation

在子宫里，婴儿从胎盘中获得生长发育所需的所有营养。这个器官将母体血液中的营养物质输送到婴儿的血液中。如果胎盘不能传递足够的营养，胎儿就不能充分生长，可能出生时太小。出生时过小的婴儿更容易出现健康问题，无论是在生命早期还是成年后。为了了解婴儿在子宫内生长的正常过程，以及为什么这个过程有时会受到干扰，我们需要充分了解营养物质是如何通过胎盘运输的。了解正常的胎盘功能将使我们能够确定当婴儿生长受损时可能出现的问题，以及如何在早期阶段预防或治疗这种问题。在这个项目中，我们将开发一个胎盘功能的计算机模型，这可以用来更好地了解胎盘是如何正常工作的，以及它是如何在困难的怀孕中出现问题的。我们对氨基酸的胎盘转移特别感兴趣。这些是构成肌肉和生命所必需的细胞“机器”的蛋白质的基石。因此，氨基酸是一类重要的营养物质，它们的胎盘转移对胎儿在子宫内的最佳生长至关重要。在婴儿出生时体重较轻的孕妇中，胎盘氨基酸运输已被证明低于正常出生体重的婴儿。胎盘氨基酸转移是一个复杂的过程，它依赖于(i)氨基酸转运体（载体），它从母体血液中摄取营养物质并将其释放到胎儿血液中，（ii）依赖于流经胎盘的血液，（iii）依赖于胎盘的内部结构，以及（iv）依赖于母体和胎儿血液以及构成胎盘的细胞内部的氨基酸水平。这些因素影响氨基酸转移的方式不能孤立地理解，因为它们之间存在复杂的相互依存的相互作用。因此，开发这些复杂相互作用的计算机模型将使我们能够研究胎盘如何作为一个综合系统工作。我们已经设计了一个简单的模型，可以模拟人类胎盘中氨基酸转运体的功能，并且可以同时预测多达3个氨基酸的转运。我们对这个模型进行了测试，将其与我们在出生后立即收集的胎盘中观察到的结果进行了比较。这些测试表明，该模型可以令人信服地再现实验数据，但我们现在需要扩展我们的系统，以准确地模拟整套20种氨基酸的同时运输。这样的模型必须考虑其他因素对胎盘运输的影响，如胎盘的内部结构和血流模式。最终，一个经过良好验证的虚拟胎盘氨基酸运输模型将有助于解释正常胎盘的成分如何将氨基酸运输给婴儿并维持最佳生长。它将确定影响胎盘氨基酸运输的最重要因素，并将使未来的研究集中在可能产生最大影响的因素上，从而制定有效的策略，确保婴儿在子宫内最佳生长。这些策略可能包括预测母亲代谢状态如何影响胎盘氨基酸运输的算法（例如，在母亲糖尿病、少女怀孕中），以及开发个性化干预措施或使用该模型确定药物干预的关键目标。最终，我们打算这项工作将有助于开发一个完全成熟的虚拟胎盘，一个不只是模拟氨基酸运输，但所有的胎盘功能。

While in the womb the baby obtains all the nutrients it requires for growth and development from the placenta. This organ transfers nutrients from maternal blood to the baby's blood. If the placenta does not transfer enough nutrients, the fetus will not be able to grow adequately and may be born too small. Babies who are born too small are more likely to develop health problems, both in early life and in adulthood. To understand the normal processes by which babies grow in the womb and to understand why this process is sometimes disturbed, we need to fully appreciate how nutrients are transported across the placenta. Understanding normal placental function will allow us to define what might go wrong when growth of the baby becomes impaired and how this might be prevented or treated at an early stage. In this project we will develop a computer model of how the placenta functions which can be used to better understand how the placenta works normally and also how it can go wrong in a difficult pregnancy. We are particularly interested in the placental transfer of amino acids. These are the building blocks of proteins which form muscles and the cellular 'machinery' essential for life. Thus, amino acids are an important class of nutrients, and their placental transfer is essential for optimal growth of the baby in the womb. In pregnancies where the baby was born small, placental amino acid transport has been shown to be lower than in babies of normal birth weight. Placental amino acid transfer is a complex process which is dependent on (i) amino acid transporters - (carriers) which take nutrients from maternal blood and release them into fetal blood, (ii) on blood flow through the placenta, (iii) on the internal structure of the placenta, and (iv) on the levels of amino acids in maternal and fetal blood as well as inside the cells which make up the placenta. The way these factors affect amino acid transfer cannot be understood in isolation as there are complicated interdependent interactions between them. Therefore, developing a computer model of these complex interactions will allow us to study how the placenta works as an integrated system. We have already designed a simple model that simulates the function of amino acid transporters in the human placenta and which can predict the transport of up to 3 amino acids at any one time. We have tested this model by comparing it to what we observe experimentally in placentas collected immediately after birth. These tests show that the model can convincingly reproduce experimental data, but we now need to expand our system to accurately simulate the simultaneous transport of the entire set of 20 amino acids. Such a model must incorporate other influences on placental transport such as the internal structure and blood flow patterns of the placenta. Ultimately, a well validated virtual placental amino acid transport model will help to explain how the components of the normal placenta function to transport amino acids to the baby and sustain optimal growth. It will identify the most important factors which affect placental amino acid transport and will allow future studies to be focused on such factors that are likely to have the greatest impact, leading to the development of effective strategies to ensure babies grow optimally in the womb. These strategies may include algorithms to predict how mothers metabolic state may affect placental amino acid transport (e.g. in maternal diabetes, teenage pregnancy) and to develop personalised interventions or using the model to identify key targets for pharmacological interventions. Ultimately we intend that this work will contribute to the development of a fully-fledged Virtual Placenta, one that does not just model amino acid transport but all the placental functions.