A Dynamic, Mathematical Model for Quantitative Glycoprofiling Using Label-Free Lectin Microarrays

作者：Salem Daniel P; Nelson Justin T; Kim Sojin; Strano Michael S^*

来源：ACS Sensors, 2016, 1(8): 987-996.

DOI：10.1021/acssensors.6b00121

• lectin
• microarray
• glycan
• glycoprofiling
• kinetic
• model
• label-free

The emergence of label-free lectin microarrays promises rapid and efficient glycoprofiling of complex analyte mixtures. Lectins have limited selectivity for different carbohydrate motifs necessitating relatively large array sizes to discriminate between glycoforms. Microarray technologies able to transduce the dynamics, instead of only the extent of binding, can introduce additional orthogonality in the array and therefore reduce its size. In this work, we develop a mathematical model of glycan binding dynamics to a label-free lectin sensor array, linking the matrix of observed dissociation constants, kinetics of binding, and occupancy to distinct glycoforms for identification. We introduce a matrix algebra approach that formulates the observed array dynamics in terms of a glycosylation matrix containing identifiers for each glycan each protein isoform in the mixture. This formulation allows for straightforward calculation of the minimum array size necessary to distinguish a given set of glycans. As examples, we evaluate the binding of human IgG to two lectins, peanut agglutinin (PNA) and Erythrina cristagalli lectin (ECL), attached to near-infrared fluorescent single-walled carbon nanotube sensor array elements, both of which have affinities for terminal galactose residues. We demonstrate the application of both the steady state and transient model solutions to the glycan-lectin binding data, and we validate that linking microarray dynamics to glycan structure promises to significantly reduce requisite array size and complexity for rapid and efficient glycoprofiling.

• 出版日期2016-8
• 单位MIT