Decoding functional glycan biosynthesis

聚糖是覆盖在每个活细胞表面的糖链。这些链由不同类型的糖单体连接在一起组成，因此与DNA（核苷酸单体连接在一起）和蛋白质（氨基酸单体连接在一起）没有什么不同。然而，与使用模板（DNA或RNA）来确定单体顺序的DNA和蛋白质相反，聚糖没有模板。相反，许多不同的酶被组织在一个称为高尔基体的细胞结构中，以产生不同的聚糖。高尔基体的特征形状，看起来很像一套叠在一起的煎饼，反映了它组织产生聚糖的酶的功能。我们知道这些酶是如何将糖添加到不断生长的聚糖链中的，但我们不知道它们在高尔基体煎饼（称为“池”）中的分布如何影响聚糖的产生，更重要的是，聚糖如何影响细胞行为。我们提出的工作将结合联合收割机使用细胞生物学的不同聚糖模式的细胞的生成，使用分析生物化学的这些聚糖模式的测量与使用计算生物学的聚糖生成过程的建模。我们的方法汇集了理解这种复杂的细胞机制所需的不同学科，并解码了高尔基体中的酶组织如何产生不同的聚糖。然而，仅凭这一点还不能完成我们对聚糖生成的理解，因为我们还需要理解高尔基体生成的聚糖链的哪些部分对细胞功能很重要。为了理解这一点，我们将测量各种不同的细胞特性，包括大小，生长速度，细胞移动的情况，使用显微镜中的细胞自动跟踪，以及可以从图像中提取细胞行为的软件。除此之外，我们还将研究聚糖所连接的蛋白质的行为，以及聚糖本身在其自然环境中的行为。通过将这些功能数据与大量具有改变的聚糖的细胞系的聚糖生成解码相结合，我们可以将哪些聚糖特征负责哪些行为，并了解最关键的聚糖特征如何在高尔基体中编码。我们的工作将最终导致细胞中聚糖合成的解码，类似于“DNA到蛋白质”范式的解码。这将开启更系统地研究聚糖功能的可能性;其影响很难估计或夸大。

Glycans are sugar chains that cover the surface of every living cell. These chains are made up of of different types of sugar monomers linked together, and as such not that different from DNA (nucleotide monomers linked together) and proteins (amino acid monomers linked together). However, in contrast to DNA and proteins, which are made using a template (DNA or RNA) to determine the order of the monomers, glycans do not have a template. Instead, many different enzymes are organised in a structure of the cell called the Golgi, to generate different glycans. The characteristic shape of the Golgi, which looks rather like a set of pancakes stacked on top of each other, reflects its function of organising the enzymes that generate glycans. We know how these enzymes work to add sugars to growing glycan chains, but we do not understand how their distribution in the Golgi's pancakes (called "cisternae") influences which glycans are made, and importantly, how glycans influence cell behaviour. The work we are proposing will combine the generation of cells with different glycan patterns using cell biology, the measurement of these glycan patterns using analytical biochemistry with the modelling of the glycan generation process using computational biology. Our approach brings together the different disciplines needed to understand this complex cellular machinery and decode how enzyme organisation in the Golgi generates different glycans. This alone, however, will not complete our understanding of glycan generation, because we also need to comprehend which parts of the glycan chains generated by the Golgi are important for cell functions. To understand this, we will measure a variety of different cellular properties, including size, growth rate, how well cells move around, using automated tracking of cells in a microscope, and a software that can extract the cells' behaviours from the images. Added to this, we will also investigate how the proteins to which glycans are attached behave, and finally how the glycans themselves behave in their natural environment. By combining such functional data with the decoding of glycan generation for a large number of cell lines with altered glycans, we can piece together which glycan features are responsible for which behaviours, and understand how the most critical glycan features are encoded in the Golgi. Our work will ultimately lead to the decoding of glycan synthesis in cells, similar to the decoding of the "DNA to protein" paradigm. This will open up the possibility of investigating glycan functions more systematically; the impact of which is hard to estimate or overstate.