1. Much like a single organism, colonies of social insects regulate their collective nutrition towards a specific intake of nutrients. Yet, the mechanisms behind this colony-level regulation are not fully understood. Although foraging behaviour in social insects has been studied extensively, not much is known on its relation with feeding processes that occur within the nest. In the nest, food is commonly transferred between individuals in numerous oral feeding interactions (trophallaxis). Studies on the properties of these trophallactic networks have so far been limited by: (a) the difficulty to non-intrusively measure food inside individual ants, let alone its nutritional composition, and (b) the meticulous manual labour involved in detecting trophallactic events.
2. Our dual-fluorescence imaging set-up is designed to track two food sources, each labelled with a different fluorophore, as they are disseminated throughout a freely behaving colony of individually tagged ants. Additionally, our image-based deep learning algorithm for automatic detection of ant trophallaxis events efficiently yields a detailed record of all food-transfer interactions.
3. Using a series of calibration experiments, we demonstrate the reliability of our measurements. We then exemplify the capabilities of our new method by tracking food dissemination in a colony of Camponotus sanctus ants supplied with two nutritionally distinct food sources. We follow the amount of each food type in the crop of each ant in the colony. Our data reveal the path in nutrient space that the colony took to reach its final nutrient intake, the contributions of the different forager ants to this path and the dynamic nutritional states of all ants in the colony. We further demonstrate the potential applicability of dual-fluorescence food imaging to other insect species.
4. Our system provides access to data that were previously unavailable and is crucial for a complete description of nutrient regulation by social insects. More broadly, the ability to simultaneously and efficiently track two material flows in a behaving colony provides new opportunities for tackling many open and emerging questions on topics other than nutrition, such as disease spread and social regulation of colony development.

中文翻译：

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双荧光成像和自动滋养液检测用于研究超有机体中的多营养调节

1. 就像一个单一的有机体一样，群居昆虫群落调节它们的集体营养，以达到特定的营养摄入量。然而，这种菌落水平调控背后的机制尚不完全清楚。尽管已经对群居昆虫的觅食行为进行了广泛的研究，但对其与巢内摄食过程的关系知之甚少。在巢中，食物通常在个体之间通过许多口服喂养相互作用（trophallaxis）转移。迄今为止，对这些滋养层网络特性的研究受到以下因素的限制：(a) 难以非侵入性地测量单个蚂蚁体内的食物，更不用说其营养成分了，以及 (b) 检测滋养层事件所涉及的细致体力劳动。
2. 我们的双荧光成像装置旨在追踪两个食物来源，每个食物来源都标有不同的荧光团，因为它们散布在自由行为的单独标记蚂蚁群体中。此外，我们基于图像的深度学习算法用于自动检测蚂蚁吞食事件，可以有效地生成所有食物转移相互作用的详细记录。
3. 使用一系列校准实验，我们证明了我们测量的可靠性。然后，我们通过跟踪提供两种营养不同食物来源的Camponotus sanctus蚂蚁群体中的食物传播来举例说明我们的新方法的能力。我们跟踪群体中每只蚂蚁的作物中每种食物类型的数量。我们的数据揭示了蚁群达到其最终营养摄入所采取的营养空间路径、不同觅食蚂蚁对这条路径的贡献以及蚁群中所有蚂蚁的动态营养状态。我们进一步证明了双荧光食物成像对其他昆虫物种的潜在适用性。
4. 我们的系统提供了对以前无法获得的数据的访问，这对于完整描述社会昆虫的营养调节至关重要。更广泛地说，同时有效地跟踪行为群体中两种物质流的能力为解决营养以外的许多开放和新兴问题提供了新的机会，例如疾病传播和群体发展的社会调节。