Mapping the Acetylamino and Carboxyl Groups on Glycans by Engineered α-Hemolysin Nanopores

Abstract

Glycan is a crucial class of biological macromolecules with important biological functions. Functional groups determine the chemical properties of glycans, which further affect their biological activities. However, the structural complexity of glycans has set a technical hurdle for their direct identification. Nanopores have emerged as highly sensitive biosensors that are capable of detecting and characterizing various analytes. Here, we identified the functional groups on glycans with a designed αhemolysin nanopore containing arginine mutations (M113R), which is specifically sensitive to glycans with acetamido and carboxyl groups. Molecular dynamics simulations indicated that the acetamido and carboxyl groups of the glycans produce unique electrical signatures by forming polar and electrostatic interactions with the M113R nanopores. Using these electrical features as the fingerprints, we mapped the length of the glycans containing acetamido and carboxyl groups at the monosaccharide, disaccharide, and trisaccharide levels. This proof-of-concept study provides a promising foundation for developing single-molecule glycan fingerprinting libraries and demonstrates the capability of biological nanopores in glycan sequencing.

Direct Identification of Complex Glycans via a Highly Sensitive Engineered Nanopore

“…The basic properties of M113R/T115A were further characterized. It could keep open continuously and stably for hours on the lipid bilayer under −40 mV with 27.17 ± 1.28 pA, and the conductance was 679.2 ± 31.9 pS (Figure S3g) ( n ≥ 10), which was comparable to that of wild-type (WT) pores . Considering the nanopore stability, discrimination ability, and sensitivity, M113R/T115A was chosen for identifying glycans with subtle structural differences.…”

“…When the disaccharide molecules approached the vicinity of M113R/T115A from the trans side, five residues (R113, A115, T117, S114, and T145) on the pore wall may interact with glycan molecules during simulations (Figure S9a,b). It was noticed that, compared with the movement of the GlcNAc molecule through α-HL(M113R) described in our previous work, Galβ1,3-GlcNAc and Galβ1,4-GlcNAc are more likely to bind to the A115 site rather than to the R113 site (Figure S9a,b). These differences might account for the different Level 2 event occurrence probabilities between M113R/T115A and M113R.…”

“…Both compositional heterogeneity and structural isomerism caused the complexity of glycan, posing great challenges to glycan analysis . In recent years, researchers have made significant efforts to develop nanopore-based glycan identification methods, promoting the development of the nanopore technique for glycan structure analysis. − These reported works provided precious insights for the realization of nanopore-based glycan sequencing. To date, this field is still in the initial stage, with many issues remaining to be addressed, such as achieving single building block resolution, reading the glycan chain length, and sensing multiple glycan structures with a single nanopore.…”

“…The development of nanopore-based DNA sequencing suggests that biological nanopores not only responds to building blocks but also shows their potential for the detection of biopolymers. ,− Accordingly, we proposed the hypothesis that biological nanopores could also be developed as the sensor for large-sized complex glycan, which is the main form of saccharide performing biological functions in life. , This hypothesis was partly supported by the size discrimination of glycosaminoglycan polysaccharides up to 20-mer via wild-type AeL nanopore, although the resolution offered by wild-type AeL needs further improvement. In our previous study, the acetylamino ( N -acetyl) and carboxyl groups on glycans were mapped at monosaccharide, disaccharide, and trisaccharide levels with an engineered α-HL, which implies that multiple structure differences between complex glycans could be identified by the biological nanopore. A satisfactory nanopore sensor for complex glycans needs to recognize multiple kinds of structural differences.…”

Recent advances in nanopore-based analysis for carbohydrates and glycoconjugates

“…Bingqing Xia et al 104 designed the α-hemolysin nanopore with an arginine mutation (M113R), which detected glycans with acetamido and carboxyl groups. Furthermore, this strategy not only identifies the two groups of modified glycans in complex solutions but also identifies the size of oligosaccharides through the fingerprint pattern of functional groups.…”