Detection of distinct glycosylation patterns on XXXX   -glutamyl transpeptidase 1 using antibody-lectin sandwich array (ALSA) technology.

@entity1 @entity15533 @entity5 @entity10056 @entity16589 @entity375
Background  -Glutamyl transpeptidase 1 ( @entity15533 ) is an N-glycosylated membrane protein that catabolizes extracellular glutathione and other   -glutamyl-containing substrates. In a variety of disease states, including @entity5 formation, the enzyme is shed from the surface of the cell and can be detected in serum. The structures of the N-glycans on @entity1 @entity15533 ( @entity15533 ) have been shown to be tissue-specific. Tumor-specific changes in the glycans have also been observed, suggesting that the N-glycans on @entity15533 would be an important biomarker for detecting @entity5 and monitoring their progression during treatment. However, the large quantities of purified protein required to fully characterize the carbohydrate content poses a significant challenge for biomarker development. Herein, we investigated a new antibody-lectin sandwich array (ALSA) platform to determine whether this microanalytical technique could be applied to the characterization of N-glycan content of @entity15533 in complex biological samples.ResultsOur data show that @entity15533 can be isolated from detergent extracted membrane proteins by binding to the ALSA platform. Probing @entity15533 with lectins enables characterization of the N-glycans. We probed @entity15533 from normal @entity1 liver tissue, normal @entity1 kidney tissue, and @entity15533 expressed in the @entity375 @entity10056 . The lectin binding patterns obtained with the ALSA platform are consistent with the @entity15533 N-glycan composition obtained from previous large-scale @entity15533 N-glycan characterizations from these sources. We also validate the implementation of the @entity16589 lectin, microvirin, in this platform and provide refined evidence for its efficacy in specifically recognizing high-mannose-type N-glycans, a class of carbohydrate modification that is distinctive of @entity15533 expressed by many @entity5 .ConclusionUsing this microanalytical approach, we provide proof-of-concept for the implementation of ALSA in conducting high-throughput studies aimed at investigating disease-related changes in the glycosylation patterns on @entity15533 with the goal of enhancing clinical diagnoses and targeted treatment regimens.
