Probing N-glycoprotein microheterogeneity by lectin affinity purification-mass spectrometry analysis

Abstract

Lectins are carbohydrate binding proteins that recognize specific epitopes present on target glycoproteins. Changes in lectin-reactive carbohydrate repertoires are related to many biological signaling pathways and recognized as hallmarks of several pathological processes. Consequently, lectins are valuable probes, commonly used for examining glycoprotein structural and functional microheterogeneity. However, the molecular interactions between a given lectin and its preferred glycoproteoforms are largely unknown due to the inherent complexity and limitations of methods used to investigate intact glycoproteins. Here, we apply a lectin-affinity purification procedure coupled with native mass spectrometry to characterize lectin-reactive glycoproteoforms at the intact protein level. We investigate the interactions between the highly fucosylated and highly branched glycoproteoforms of haptoglobin and α1-acid glycoprotein using two different lectins Aleuria aurantia lectin (AAL) and Phaseolus vulgaris leucoagglutinin (PHA-L), respectively. Firstly we show a co-occurrence of fucosylation and N-glycan branching on haptoglobin, particularly among highly fucosylated glycoproteoforms. Secondly, we analyze the global heterogeneity of highly branched glycoproteoforms of haptoglobin and α1-acid glycoprotein and reveal that while multi-fucosylation attenuates the lectin PHA-L binding to haptoglobin, it has no impact on AGP. Taken together, our lectin affinity purification native MS approach elucidates lectin specificities between intact glycoproteins, not achievable by other methods. Moreover, since aberrant glycosylation of Hp and AGP are potential markers for many diseases, including pancreatic, hepatic and ovarian cancers, understanding their interactions with lectins will help the development of carbohydrate-centric monitoring methods to understand their pathophysiological implications.

Fig. 1. Native MS analysis of asialo-Hp and asialo-AGP. (A) Native mass spectrum of asialo-Hp. (B) Deconvoluted spectrum of asialo-Hp. The peaks of fully glycosylated Hp are assigned with the corresponding glycan compositions. The peaks with same hexose composition are annotated with same colors. The numbers of fucose residues are labelled on each peak. (C) Heatmap plots of the total number of fucose residues versus the average number of N-glycan antennae of each asialo-Hp glycoproteoform. (D) Native mass spectrum of asialo-AGP. (E) Deconvoluted spectrum of asialo-AGP. The peaks with same hexose composition are annotated with the same colors. The numbers of fucose residues are labelled on each peak. (F) Heatmap plots of the total number of fucose residues versus the average number of N-glycan antennae of each asialo-AGP glycoproteoform.

Fig. 2. MS analysis of AAL fractionated Hp. (A) The deconvoluted spectrum of AAL-bound and unbound asialo-Hp. (B) The relative abundances of fucosylated and branched N-glycans on the three glycosylated tryptic peptides. The N-glycan on Asn203 & 208 are at one tryptic peptide. Error bars represent the standard error of three replicate experiments. (C) The AAL-bound Hp spectrum is divided to two series in which the peaks differ from 146 Da. The two peak envelopes were fitted with multiple Gaussian functions. The peaks under one Gaussian curve are assigned with the same hexose composition. The numbers of fucose residues are labelled on each peak. (D) The N-glycan branching and fucosylation levels of AAL-bound and AAL-unbound Hp are summarized and displayed on heatmaps.

Fig. 3. MS analysis of AAL fractionated AGP. (A) The deconvoluted spectrum of AAL-bound and unbound asialo-AGP. (B) The relative abundances of fucosylated and branched N-glycans on the four glycosylated tryptic peptides. Error bars represent the standard error of three replicate experiments. (C) The AAL-bound AGP spectrum is divided to two series in which the peaks differ from 146 Da. The two peak envelopes were fitted with multiple Gaussian functions. The peaks under one Gaussian curve are assigned with the same hexose composition. The numbers of fucose residues are labelled on each peak. (D) The N-glycan branching and fucosylation levels of AAL-bound and AAL-unbound AGP are summarized and plotted on heatmaps.

Fig. 4. PHA-L and Con-A affinity purification-native MS analysis of Hp and AGP. Native spectra of PHA-L fractionated asialo-Hp and asialo-AGP (Fig. S7†) are deconvoluted to zero-charge spectra as (A) and (B). The N-glycan branching and fucosylation levels are summarized and plotted as heatmaps. The Con A-fractionated asialo-Hp (C) and asialo-AGP (D) are analyzed accordingly (Fig.S8†).

Fig. 5. Lectin specificities to discriminate glycoprotein microheterogeneity. The N-glycan branching and fucosylation levels of PHA-L (A), Con A (B) and AAL (C) fractionated asialo-Hp and asialo-AGP are plotted as heatmaps, respectively. PHA-L and Con A show better separations for less branched Hp and highly branched AGP, respectively. AAL only captures highly fucosylated glycoproteomics.

Fig. 6. Multi-fucosylation enhances the interactions between AAL and glycoproteins, but attenuates PHA-L interactions with less branched glycoprotein. We propose that the PHA-L based lectin detection approach is limited by the attenuation effect of hyper-fucosylation on less branched N-glycoproteins binding to PHA-L.