Single molecule sequencing of oligosaccharides (SingleCarb)

Oligosaccharide carbohydrate chains decorate most cell surfaces, as membrane bound lipid and proteins are often glycosylated. Alterations in glycosylation structure, or spatial localization, are implicated in a plethora of biological functions ranging from viral recognition and cell entry, to cancer and protein fate. The very diversity however, that underlies oligosacharide (OS) structure and spatial localization, poses a significant impediment for glycobiology. To date, sensitive OS sequencing is a long-standing problem in the field, as current OS sequencing relies on decades old, low sensitivity techniques, averaging the structure and spatial localization of a large number of molecules and missing low-level heterogeneities. The key scope of this project is to establish a direct and ultra-sensitive method for real-time detection and sequencing of oligosaccharides with single-molecule resolution. This completely new methodology will allow the hypersensitive parallelized sequencing of hundreds of OS using subpicogram of material, minimizing time, labor and chemical cost. Combined with advanced machine learning approaches for rapid, agnostic and automated single molecule data treatment, will result in a giant leap in fields of biophysics and glycobiology and offer the potential to analyze glycosylation at the molecular, cellular and organismal level.