Quantitative analysis of fucosylated glycoproteins by immobilized lectin-affinity fluorescent labeling

Optimization of glycopeptide enrichment techniques for the identification of clinical biomarkers

INTRODUCTION

The identification and characterization of glycopeptides through LC-MS/MS and advanced enrichment techniques are crucial for advancing clinical glycoproteomics, significantly impacting the discovery of disease biomarkers and therapeutic targets. Despite progress in enrichment methods like Lectin Affinity Chromatography (LAC), Hydrophilic Interaction Liquid Chromatography (HILIC), and Electrostatic Repulsion Hydrophilic Interaction Chromatography (ERLIC), issues with specificity, efficiency, and scalability remain, impeding thorough analysis of complex glycosylation patterns crucial for disease understanding.

AREAS COVERED

This review explores the current challenges and innovative solutions in glycopeptide enrichment and mass spectrometry analysis, highlighting the importance of novel materials and computational advances for improving sensitivity and specificity. It outlines the potential future directions of these technologies in clinical glycoproteomics, emphasizing their transformative impact on medical diagnostics and therapeutic strategies.

EXPERT OPINION

The application of innovative materials such as Metal-Organic Frameworks (MOFs), Covalent Organic Frameworks (COFs), functional nanomaterials, and online enrichment shows promise in addressing challenges associated with glycoproteomics analysis by providing more selective and robust enrichment platforms. Moreover, the integration of artificial intelligence and machine learning is revolutionizing glycoproteomics by enhancing the processing and interpretation of extensive data from LC-MS/MS, boosting biomarker discovery, and improving predictive accuracy, thus supporting personalized medicine.

Profiling of aberrant sialylated N-glycans in hepatocellular carcinoma by liquid chromatography mass spectrometry

BACKGROUND

Aberrant sialylation is closely associated with the tumorigenesis, progression, and metastasis, and may be of importance for disease diagnosis. However, the analysis of altered expression of sialylated glycans (SGs) in blood is particularly challenging due to the low content and poor ionization efficiency of sialylated glycans in mass spectrometry.

METHODS

An analytical strategy based on enrichment of SGs, liquid chromatography-high resolution mass spectrometric detection, and automatic glycan annotation was developed to profile the sialylated N-glycome in serum. The enrichment of sialylated glycans was accomplished using cationic cotton via electrostatic and hydrogen interaction. Using partial least squares-discriminant analysis (PLS-DA), the approach was applied for nontarget screening and profiling of aberrant sialylated N-glycans in hepatocellular carcinoma (HCC).

RESULTS

55 SGs were identified in human serum, and three important SGs (SG35, SG45, and SG46) were screened to have good diagnostic specificity for HCC. Their areas under the receiver operating characteristic (ROC) curve (AUC) were higher than α-fetoprotein (AFP)'s (AUC = 0.85), at 0.88, 0.87, and 0.91, respectively. When three SGs are combined, the diagnostic specificity for HCC may increase to 94 %. The fact that SGs biomarkers are sensitive to AFP-Negative HCC is very noteworthy.

CONCLUSIONS

The method significantly advanced the search for sialylated glycan-based cancer biomarkers. In comparison to traditional indicators like AFP and imaging tools, SGs showed a higher diagnostic sensitivity for HCC.

Diagnostic Potential of Serum Glycome Analysis in Lung Cancer: A Glycopattern Study

Lung cancer is the leading cause of cancer-related death, with high morbidity and mortality rates due to the lack of reliable methods for diagnosing lung cancer at an early stage. Low-dose computed tomography can help detect abnormal areas in the lungs, but only 16% of cases are diagnosed early. Tests for lung cancer markers are often employed to determine genetic expression or mutations in lung carcinogenesis. Serum glycome analysis is a promising new method for early lung cancer diagnosis as glycopatterns exhibit significant differences in lung cancer patients. In this study, we employed a solid-phase chemoenzymatic method to systematically compare glycopatterns in benign cases, adenocarcinoma before and after surgery, and advanced stages of adenocarcinoma. Our findings indicate that serum high-mannose levels are elevated in both benign cases and adenocarcinoma, while complex N-glycans, including fucose and 2,6-linked sialic acid, are downregulated in the serum. Subsequently, we developed an algorithm that utilizes 16 altered N-glycans, 7 upregulated and 9 downregulated, to generate a score based on their intensity. This score can predict the stages of cancer progression in patients through glycan characterization. This methodology offers a potential means of diagnosing lung cancer through serum glycome analysis.

Developing a Fluorescent Inducible System for Free Fucose Quantification in Escherichia coli

L-Fucose is a monosaccharide abundant in mammalian glycoconjugates. In humans, fucose can be found in human milk oligosaccharides (HMOs), mucins, and glycoproteins in the intestinal epithelium. The bacterial consumption of fucose and fucosylated HMOs is critical in the gut microbiome assembly of infants, dominated by Bifidobacterium. Fucose metabolism is important for the production of short-chain fatty acids and is involved in cross-feeding microbial interactions. Methods for assessing fucose concentrations in complex media are lacking. Here we designed and developed a molecular quantification method of free fucose using fluorescent Escherichia coli. For this, low- and high-copy plasmids were evaluated with and without the transcription factor fucR and its respective fucose-inducible promoter controlling the reporter gene sfGFP. E. coli BL21 transformed with a high copy plasmid containing pFuc and fucR displayed a high resolution across increasing fucose concentrations and high fluorescence/OD values after 18 h. The molecular circuit was specific against other monosaccharides and showed a linear response in the 0-45 mM range. Adjusting data to the Hill equation suggested non-cooperative, simple regulation of FucR to its promoter. Finally, the biosensor was tested on different concentrations of free fucose and the supernatant of Bifidobacterium bifidum JCM 1254 supplemented with 2-fucosyl lactose, indicating the applicability of the method in detecting free fucose. In conclusion, a bacterial biosensor of fucose was validated with good sensitivity and precision. A biological method for quantifying fucose could be useful for nutraceutical and microbiological applications, as well as molecular diagnostics.