Elucidating mechanisms underlying multivalency modulating lectin-glycan binding and assembly properties-implications for lectin function regulation

病原体表面显示高密度碳水化合物，以保护下面的元素不被抗体识别，从而逃避免疫。为了识别异常显示的碳水化合物，在免疫系统中，碳水化合物结合蛋白(称为凝集素)形成多聚体结构，其中每个凝集素包含多个碳水化合物识别结构域(CRD)。这还允许它们之间的多个接触(多价结合)，从而产生类似于尼龙搭扣的强结合。病毒和细菌比凝集素大得多，因此多个凝集素可以与它们结合，使凝集素聚集在一起。由于许多凝集素附着在免疫细胞上，这一簇可以被解释为启动免疫防御的信号。然而，一些病原体已经制定了策略，利用这种强大的结合来促进它们的感染。目前，尚不清楚它们是否改变了碳水化合物的排列以诱导不同的凝集素簇模式，和/或使一些CRD无法结合，从而降低了结合强度和簇稳定性，允许更多的凝集素填充以排除该区域的其他蛋白质。免疫细胞可以不同地解释这些问题。在这里，我们使用树突状细胞(DC)表面凝集素DC-SIGN来解决这些问题。DC-SIGN含有4个CRD，与细菌、病毒(如HIV、SARS-COV-2)和真菌等病原体的甘露糖(一种碳水化合物)结合。结合导致病毒被吞噬，在DC内消化，并导致小片段进一步被用来指示其他免疫细胞产生抗体以消除病原体。作为防御作用的一部分，结合还通过DC-SIGN与TLR4蛋白的交叉对话来刺激DC产生一些蛋白质。然而，沟通是如何实现的尚不清楚，也不清楚它们是否必须密切联系。但像HIV和SARS-COV-2这样的病毒利用结合来增强它们的感染。在HIV的情况下，它以某种方式避免了在DC内被消化，然后逃逸到感染其他细胞。这使得DC-Sign成为本研究的一个很好的凝集素模型。我们还将包括另一种四聚体凝集素DC-SIGNR，它与DC-SIGN几乎相同，唯一的区别是它们的4个CRD具有不同的取向。这使它们成为研究CRD在多价结合强度和簇形成方面的可用性的极佳组合。我们将首先将多个病原体多糖连接到不同密度的荧光量子点(QD)或棒(QR)表面，以模拟病原体表面可能的显示。我们将开发一种新的方法来构建包含4个、3个或2个CRD的DC-SIGN或DC-SIGNR四聚体，以研究CRD结合次数对结合强度的影响。为了研究簇的形成，我们将利用纳米粒子的高密度来使用电子显微镜来查看它们的排列，以获得关于凝集素簇的信息：孤立的粒子意味着凝集素组装在同一粒子上，而聚集的粒子是由蛋白质和粒子交联形成的，这些都产生了不同的簇模式。我们还将用不同形状的纳米颗粒标记TLR4，看看它如何与DC-SIGN簇相关联。蛋白质在电子显微镜下是不可见的，通过跟踪纳米粒子，我们第一次能够在纳米水平上获得蛋白质簇的信息。凝集素结合也可以干扰QD和QR的荧光性质；我们将通过荧光显微镜跟踪光信号来监测信号变化的速度，以获得关于簇稳定性的信息：变化越快，簇越不稳定。然后，我们将使用这些QD/QR-葡聚糖来刺激DC，将观察到的簇信息与DC反应相关联，以解释DC-SIGN如何指导DC反应。这里获得的信息将为设计抗感染治疗和抑制免疫过度反应治疗糖尿病、关节炎和过敏提供指导。

Pathogen surfaces display high density carbohydrates to shield underneath elements from being recognized by antibodies for immune evasion. To recognize the unusually displayed carbohydrate, in immune systems, carbohydrate binding proteins (known as lectins) form multimeric structures where each lectin contains multiple carbohydrate recognition domains (CRDs). This also allows multiple contacts (multivalent binding) between them resulting in strong bindings similar to that observed with Velcro. Viruses and bacteria are much bigger than lectins, hence multiple lectins can bind to them, making the lectins cluster together. As many lectins are attached to immune cells, the cluster can be interpreted as signalling to initiate immune defence. However, some pathogens have developed strategies to exploit such strong binding to facilitate their infection. Currently, it is not clear whether they have changed the arrangement of carbohydrates to induce different lectin cluster patterns, and/or to make some CRDs unavailable for engagement which reduces binding strength and cluster stability, allowing more lectins to pack in to exclude other proteins from the area. These can be interpreted differently by immune cells.Here, we employ a dendritic cell (DC) surface lectin DC-SIGN to address these questions. DC-SIGN contains 4 CRDs and binds to mannose (a type of carbohydrate) on pathogens including bacteria, viruses (such as HIV, SARS-COV-2) and fungi. Binding leads to virus being engulfed, digested inside DC and results in small pieces further being used to instruct other immune cell to produce antibodies for pathogen elimination. Binding also stimulates DC to produce some proteins through DC-SIGN cross-talking to a TLR 4 protein as part of defence actions. However, how communication is achieved is unknown and it is unclear if they have to be closely associated. But viruses such as HIV and SARS-COV-2 exploit binding to enhance their infection. In the case of HIV, it somehow avoids being digested inside DC and escapes later to infect other cells. This makes DC-SIGN an excellent model lectin for this study. We will also include another tetrameric lectin named DC-SIGNR which is almost identical to DC-SIGN with only difference being that their 4 CRDs have different orientations. This makes them an excellent pair to study CRDs availability in multivalent binding strength and cluster formation.We will start with linking multiple pathogen glycans onto fluorescent quantum dot (QD) or rod (QR) surfaces with different densities to mimic possible displays on pathogen surfaces. We will develop a novel method to construct DC-SIGN or DC-SIGNR tetramers containing 4, 3 or 2 CRDs to investigate the effects of CRD engagement numbers on binding strength. To study cluster formation, we will exploit nanoparticles' high density to see their arrangement using electron microscopy to obtain information on lectin clusters: isolated particles mean lectins are assembled on the same particle and clustered particles are formed by proteins and particles cross-linking, these generate distinct cluster patterns. We will also label TLR 4 with a different shaped nanoparticle to see how it associates with DC-SIGN clusters. Proteins are invisible by electron microscope, by following nanoparticles we are able to gain their cluster information at nanometer level for the 1st time. Lectin binding can also be made to interfere with QD and QR's fluorescent property; we will follow the light signal by fluorescence microscopy to monitor the speed of signal change to gain information on cluster stability: the faster the change, the less stable the cluster. We will then use those QD/QR-glycans to stimulate DC to correlate observed cluster information with DC responses to explain how DC-SIGN instructs DC responses.Information obtained here will provide guidance to design treatments against infection and to suppress immune overreaction to treat diabetes, arthritis and allergy.