Decoding functional glycan biosynthesis
Lead Research Organisation:
University of York
Department Name: Biology
Abstract
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.
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.
Technical Summary
All living cells are covered by glycans, yet these biological polymers are vastly understudied compared to their polymer cousins, DNA, RNA and proteins. A major reason for this is the lack of understanding of glycan biosynthesis. Mammalian glycans are generated through the sequential action of numerous enzymes organised into about half dozen reaction chambers, called cisternae, in the Golgi apparatus. We have engineered cell lines with altered glycan patterns by changing the sorting of enzymes in the Golgi, and also developed methods to determine the glycan profile of the altered cells. Importantly, using a computational model we can establish how enzyme organisation is altered by fitting to the glycan profile data and thereby link enzyme organisation to the ensemble of function-defining glycan-features expressed by each cell.
We propose to generate glycan profile data and model the organisation of the biosynthetic machinery in 12 cell lines with altered glycosylation. This number, while experimentally manageable, will be sufficient to cover a range of glycan-features based on the three cell lines we have investigated thus far. In addition to studying the glycans, we will also investigate phenotypic differences (e.g. adhesion, glycoprotein levels, lectin binding) resulting from altered glycosylation. This is important to link the organisation of glycan biosynthesis to real function-defining glycan-features, akin to function-defining elements in proteins, such as peptide motifs. The data from our study will provide a paradigm shift in understanding and future investigation of glycans, but also deliver a pipeline for generating further cell lines with altered glycosylation characteristics. These cell lines can then be used to study glycan functions, fine-tune the decoding of glycan biosynthesis we establish here, and/or to produce glycoprotein biotherapeutics with improved pharmacokinetic properties.
We propose to generate glycan profile data and model the organisation of the biosynthetic machinery in 12 cell lines with altered glycosylation. This number, while experimentally manageable, will be sufficient to cover a range of glycan-features based on the three cell lines we have investigated thus far. In addition to studying the glycans, we will also investigate phenotypic differences (e.g. adhesion, glycoprotein levels, lectin binding) resulting from altered glycosylation. This is important to link the organisation of glycan biosynthesis to real function-defining glycan-features, akin to function-defining elements in proteins, such as peptide motifs. The data from our study will provide a paradigm shift in understanding and future investigation of glycans, but also deliver a pipeline for generating further cell lines with altered glycosylation characteristics. These cell lines can then be used to study glycan functions, fine-tune the decoding of glycan biosynthesis we establish here, and/or to produce glycoprotein biotherapeutics with improved pharmacokinetic properties.