Lectin-Based Fluorescent Comparison of Glycan Profile-FDA Validation to Expedite Approval of Biosimilars.

Glycan profile comparisons are one of the most tedious analytical exercises for establishing compliance with recombinant therapeutic protein batches. Based on its intensive research, the FDA has confirmed that lectin array binding with fluorescent monitoring is the fastest and most reliable method for profile comparisons. Using a database of over 150 biological products expressed in nine diverse mammalian cell systems, the FDA immobilized 74 lectins to study their binding using fluorescently labeled glycoproteins. The FDA identified nine distinct lectins from a custom-designed lectin microarray: rPhoSL, rOTH3, RCA120, rMan2, MAL_I, rPSL1a, PHAE, rMOA, and PHALs, which detect core fucose, terminal GlcNAc, terminal ß-galactose, high mannose, α-2,3-linked sialic acids, α-2,6-linked sialic acids, bisecting GlcNAc, terminal α-galactose, and triantennary structures, respectively. This method can be used for screening and routine testing and to monitor batch-to-batch variability of therapeutic proteins, including establishing analytical similarity as a crucial part of biosimilar development.

Employing conductive porous hydrogen-bonded organic framework for ultrasensitive detection of peanut allergen Ara h1.

Peanut allergy has garnered worldwide attention due to its high incidence rate and severe symptoms, stimulating the demand for the ultrasensitive detection method of peanut allergen. Herein, we successfully developed a novel electrochemical aptasensor for ultrasensitive detection Ara h1, a major allergenic protein present in peanuts. A conductive nickel atoms Anchored Hydrogen-Bonded Organic Frameworks (PFC-73-Ni) were utilized as excellent electrocatalysts toward hydroquinone (HQ) oxidation to generate a readable current signal. The developed electrochemical aptasensor offers wide linear range (1-120 nM) and low detection limit (0.26 nM) for Ara h1. This method demonstrated a recovery rate ranging from 95.00% to 107.42% in standard addition detection of non-peanut food samples. Additionally, the developed electrochemical method was validated with actual samples and demonstrated good consistency with the results obtained from a commercial ELISA kit. This indicates that the established Ara h1 detection method is a promising tool for peanut allergy prevention.

[On-line enrichment and separation of glycoprotein by capillary electrophoresis based on pH response coating column].

A capillary column coated with 3-aminophenylboronic acid (APBA)-functionalized gold nanoparticles (AuNPs@APBA) was prepared via electrostatic self-assembly. The coated column exhibited anti-nonspecific adsorption of glycoproteins, enabling selective online enrichment during capillary electrophoresis (CE). First, gold nanoparticles (AuNPs) were synthesized using the sodium citrate reduction method. Then, APBA was self-assembled electrostatically on the surface of the AuNPs to obtain AuNPs@APBA. This nanomaterial was bonded to the inner wall of a capillary through ion adsorption to produce a AuNPs@APBA-coated capillary column. Glycoproteins were adsorbed via bond formation with boric acid groups under alkaline conditions (pH 8) to generate borate esters. Under acidic conditions (pH 3), the borate esters dissociated to release the glycoproteins, thereby achieving the selective online enrichment and separation of glycoproteins. The AuNPs and AuNPs@APBA were characterized using Fourier transform infrared spectroscopy, and their sizes and Zeta potentials were determined. In addition, the electroosmotic flow (EOF) of the AuNPs@APBA-coated capillary column was measured. The results showed that the surface of the AuNPs was successfully modified with APBA and that AuNPs@APBA was adsorbed on the inner wall of the capillary. The peak area of ovalbumin (OVA) on the AuNPs@APBA-coated column was 26.46 times higher than that on a bare column via conventional electrophoresis. In contrast, the peak area of bovine serum albumin (BSA) only increased by 8.47 times, indicating that the AuNPs@APBA coated column selectively enriched glycoproteins. Evaluation of the reproducibility and stability of this method revealed that the AuNPs@APBA coated capillary column could be used continually for 33-67 h. The relative standard deviations (RSDs) of the peak areas for intra-day (n=5) and inter-day (n=6) analyses were 2.2% and 3.0%, respectively. The developed method was successfully applied to enrich glycoproteins in a 1×106-fold diluted egg white sample. Glycoproteins were not detected using conventional electrophoresis on the bare column, whereas the AuNPs@APBA-coated capillary column effectively enriched and separated glycoproteins, resulting in a peak area of 10469 mAU·ms. Furthermore, the entire enrichment and separation process was completed within 3 min. This new online enrichment and separation method for glycoproteins has the advantages of low sample consumption, simple operation, and high separation efficiency.

Identification and classification of proteins by FTIR microspectroscopy. A proof of concept.

FTIR spectroscopy is well known for its molecule fingerprinting capability but is also able to differentiate classes in complex biological systems. This includes strain typing and species level identification of bacterial, yeast or fungal cells, as well as distinguishing between cell layers in eukaryotic tissues. However, its use for the identification of macromolecules such as proteins remains underexplored and rarely used in practice. Here we demonstrate the efficacy of FTIR microspectroscopy coupled with machine learning methods for rapid and accurate identification of proteins in their dry state within minutes, from very small quantities of material, if they are obtained in a pure aqueous solution. FTIR microspectroscopy can provide additional information beside identification: it can detect small differences among different purification batches potentially originating from post-translational modifications or distinct folding states. Moreover, it distinguishes glycoproteins and evaluate glycosylation while detecting contaminants. This methodology presents itself as a valuable quality control tool in protein purification processes or any process requiring the utilization of precisely identified, pure proteins.

Structural and physical-chemical properties of milk fat globules fractionated by a series of silicon carbide membranes.

Driven by the acknowledged health and functional properties of milk fat globules (MFGs), there is a growing interest to develop gentle methodologies for separation of fat from milk. In this study, separation of fat from raw milk and fractionation in streams containing MFGs of different size was achieved using a series of two silicon carbide ceramic membranes. A first step consisting of a 1.4 µm membrane aimed to concentrate the bulk of the fat, i.e. the larger MFGs (D[4,3] âˆ¼ 4 µm) followed by a 0.5 µm fractionation aimed to concentrate the residual milk fat in the permeate, i.e. fraction with the smaller MFGs (D[4,3] âˆ¼ 1.8-2.4 µm. The fat separation performance showed a yield of 92 % for the 1.4 µm membrane and 97 % for the 0.5 µm membrane. Both fat enriched retentates showed, by the confocal laser scanning microscopy, intact MFGs with limited damage in the MFG membrane. The fatty acid profile analysis and SAXS showed minor differences in fat acid composition and the crystallization behavior was related to differences in the fat content. The 0.5 µm permeate containing the smallest MFGs however showed larger aggregates and a trinomial particle size distribution, due to probably pore pressure induced coalescences. The series of silicon carbide membranes showed potential to concentrate some of MFGM proteins such as Periodic Schiff base 3/4 and cluster of differentiation 36 especially in the 0.5 µm retentates. A shift in casein to whey protein ratio from 80:20 (milk) to 50:50 was obtained in the final 0.5 µm permeate, which opens new opportunities for product development.

Clinical glycoprotein mass spectrometry: The future of disease detection and monitoring.

Protein glycosylation is the co- and/or post-translational modification of proteins with oligosaccharides (glycans). This process is not template based and can introduce a heterogeneous set of glycan modifications onto substrate proteins. Glycan structures preserve biomolecular information from the cell, with glycoproteins from different cell types and tissues displaying distinct patterns of glycosylation. Several decades of research have revealed that glycan structures also differ between normal physiology and disease. This suggests that the information stored in glycoproteins and glycans can be utilized for disease diagnosis and monitoring. Methods that enable sensitive and site-specific measurement of protein glycosylation in clinical settings, such as nano-flow liquid chromatography tandem mass spectrometry, are therefore essential. The purpose of this perspective is to discuss recent advances in mass spectrometry and the potential of these advances to facilitate the detection and monitoring of disease-specific glycoprotein glycoforms. Glycoproteomics, the system-wide characterization of glycoprotein identity inclusive of site-specific characterization of carbohydrate modifications on proteins, and glycomics, the characterization of glycan structures, will be discussed in this context. Quantitative measurement of glycopeptide markers via parallel reaction monitoring is highlighted. The development of promising glycopeptide markers for autoimmune disease, liver disease, and liver cancer is discussed. Synthetic glycopeptide standards, ambient ionization mass spectrometry, and consideration of glyco-biomarkers in two- and three-dimensional space within tissue will be critical to the advancement of this field. The authors envision a future in which glycoprotein mass spectrometry workflows will be integrated into clinical settings, to aid in the rapid diagnosis and monitoring of disease.

High-sensitivity detection of glycoproteins by high-density boric acid modified metal-organic framework surface molecularly imprinted polymers resonant light scattering sensor.

Glycoproteins are difficult to be detected by imprinting strategy due to their low natural abundance, high flexible conformation and large size. Herein, a high-density boric acid modified metal-organic framework (MOF) surface molecularly imprinted polymer (SMIP) resonant light scattering sensor was constructed for the high-sensitivity detection of target glycoproteins. A MOF with large specific surface area was selected as the substrate material to support the boric acid group with high loading density (4.66 %). The introduction of the boric acid group in the SMIP provided a high-affinity binding site for the recognition and binding of glycoproteins. Shallow surface cavities with rapid mass transfer (equilibrium time 20 min) were thus formed by surface imprinting. Furthermore, high sensitivity (limit of detection 15 pM) was achieved at physiological pH (7.4), which was conducive to the detection of glycoproteins with low natural abundance in complex biological samples and maintaining physiological activity.

Analysis of Mucin-Domain Glycoproteins Using Mass Spectrometry.

Mucin-domain glycoproteins are characterized by their high density of glycosylated serine and threonine residues, which complicates their analysis by mass spectrometry. The dense glycosylation renders the protein backbone inaccessible to workhorse proteases like trypsin, the vast heterogeneity of glycosylation often results in ion suppression from unmodified peptides, and search algorithms struggle to confidently analyze and site-localize O-glycosites. We have made a number of advances to address these challenges, rendering mucinomics possible for the first time. Here, we summarize these contributions and provide a detailed protocol for mass spectrometric analysis of mucin-domain glycoproteins. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Enrichment of mucin-domain glycoproteins Basic Protocol 2: Enzymatic digestion of mucin-domain glycoprotein(s) Basic Protocol 3: Mass spectrometry data collection for O-glycopeptides Basic Protocol 4: Mass spectrometry data analysis of O-glycopeptides.

Quantum Cascade Laser Infrared Spectroscopy for Glycan Analysis of Glycoprotein Solutions.

Glycans are oligosaccharides attached to proteins or lipids and affect their functions, such as drug efficacy, structural contribution, metabolism, immunogenicity, and molecular recognition. Conventional glycosylation analysis has relied on destructive, slow, system-sensitive methods, including enzymatic reactions, chromatography, fluorescence labeling, and mass spectrometry. Herein, we propose quantum cascade laser (QCL) infrared (IR) spectroscopy as a rapid, nondestructive method to quantify glycans and their monosaccharide composition. Previously, we demonstrated high-sensitivity IR spectroscopy of protein solution using solvent absorption compensation (SAC) and double-beam modulation (DBM) techniques. However, the SAC-DBM approach suffered a limited frequency scanning range (<400 cm-1) due to the light dispersion by acousto-optic modulators (AOMs). Here, we implemented a mirror-based double-pass AOM in the SAC-DBM scheme and successfully extended the frequency range to (970 to 1840 cm-1), which encompasses the vibrational fingerprint of biomolecules. The extended frequency range allowed the simultaneous observation of monosaccharide ring bands (1000 to 1200 cm-1) and protein amide bands (1500 to 1700 cm-1). We compared the IR spectra of six glycoproteins and two nonglycosylated proteins with the results from intact mass spectrometry. The IR absorbance ratios of the ring band to the amide band of glycoproteins in solutions showed a linear correlation with the ratios of glycan to protein backbone masses. Furthermore, a multivariate analysis produced monosaccharide compositions consistent with the reported database for the glycoproteins, and the monosaccharide compositions were used to improve the predictability of the glycan-protein mass ratio from the IR-absorbance ratio. This nondestructive, high-sensitivity QCL-IR spectroscopy could be used as a standard method to monitor batch-to-batch comparability during drug manufacturing and quantify the glycosylation and monosaccharide composition of new glycoproteins and other glycosylated biosystems.

A Glycoprotein-Based Surface-Enhanced Raman Spectroscopy-Lateral Flow Assay Method for Abrin and Ricin Detection.

Abrin and ricin, both type II ribosome-inactivating proteins, are toxins of significant concern and are under international restriction by the Chemical Weapons Convention and the Biological and Toxin Weapons Convention. The development of a rapid and sensitive detection method for these toxins is of the utmost importance for the first emergency response. Emerging rapid detection techniques, such as surface-enhanced Raman spectroscopy (SERS) and lateral flow assay (LFA), have garnered attention due to their high sensitivity, good selectivity, ease of operation, low cost, and disposability. In this work, we generated stable and high-affinity nanotags, via an efficient freezing method, to serve as the capture module for SERS-LFA. We then constructed a sandwich-style lateral flow test strip using a pair of glycoproteins, asialofetuin and concanavalin A, as the core affinity recognition molecules, capable of trace measurement for both abrin and ricin. The limit of detection for abrin and ricin was 0.1 and 0.3 ng/mL, respectively. This method was applied to analyze eight spiked white powder samples, one juice sample, and three actual botanic samples, aligning well with cytotoxicity assay outcomes. It demonstrated good inter-batch and intra-batch reproducibility among the test strips, and the detection could be completed within 15 min, indicating the suitability of this SERS-LFA method for the on-site rapid detection of abrin and ricin toxins.

Experimentally Determined Diagnostic Ions for Identification of Peptide Glycotopes.

The analysis of the structures of glycans present on glycoproteins is an essential component for determining glycoprotein function; however, detailed glycan structural assignment on glycopeptides from proteomics mass spectrometric data remains challenging. Glycoproteomic analysis by mass spectrometry currently can provide significant, yet incomplete, information about the glycans present, including the glycan monosaccharide composition and in some circumstances the site(s) of glycosylation. Advancements in mass spectrometric resolution, using high-mass accuracy instrumentation and tailored MS/MS fragmentation parameters, coupled with a dedicated definition of diagnostic fragmentation ions have enabled the determination of some glycan structural features, or glycotopes, expressed on glycopeptides. Here we present a collation of diagnostic glycan fragments produced by traditional positive-ion-mode reversed-phase LC-ESI MS/MS proteomic workflows and describe the specific fragmentation energy settings required to identify specific glycotopes presented on N- or O-linked glycopeptides in a typical proteomics MS/MS experiment.

MS-PyCloud: A Cloud Computing-Based Pipeline for Proteomic and Glycoproteomic Data Analyses.

Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.

Analysis of mutation-originated gain-of-glycosylation using mass spectrometry-based N-glycoproteomics.

RATIONALE: A general N-glycoproteomics analysis pipeline has been established for characterization of mutation-related gain-of-glycosylation (GoG) at intact N-glycopeptide molecular level, generating comprehensive site and structure information of N-glycosylation. METHODS: This study focused on mutation-originated GoG using a mass spectrometry-based N-glycoproteomics analysis workflow. In brief, GoG intact N-glycopeptide databases were built, consisting of 2701 proteins (potential GoG N-glycosites and amino acids derived from MUTAGEN, VARIANT and VAR_SEQ in UniProt) and 6709 human N-glycans (≤50 sequence isomers per monosaccharide composition). We employed the site- and structure-specific N-glycoproteomics workflow utilizing intact N-glycopeptides search engine GPSeeker to identify GoG intact N-glycopeptides from parental breast cancer stem cells (MCF-7 CSCs) and adriamycin-resistant breast cancer stem cells (MCF-7/ADR CSCs). RESULTS: With the criteria of spectrum-level false discovery rate control of ≤1%, we identified 87 and 94 GoG intact N-glycopeptides corresponding to 37 and 35 intact N-glycoproteins from MCF-7 CSCs and MCF-7/ADR CSCs, respectively. Micro-heterogeneity and macro-heterogeneity of N-glycosylation from GoG intact N-glycoproteins with VAR_SEQ and VARIANT were found in both MCF-7 CSCs and MCF-7/ADR CSCs systems. CONCLUSIONS: The integration of site- and structure-specific N-glycoproteomics approach, conjugating with GoG characterization, provides a universal workflow for revealing comprehensive N-glycosite and N-glycan structure information of GoG. The analysis of mutation-originated GoG can be extended to GoG characterization of other N-glycoproteome systems including complex clinical tissues and body fluids.

Maximizing Glycoproteomics Results through an Integrated Parallel Accumulation Serial Fragmentation Workflow.

Glycoproteins play important roles in numerous physiological processes and are often implicated in disease. Analysis of site-specific protein glycobiology through glycoproteomics has evolved rapidly in recent years thanks to hardware and software innovations. Particularly, the introduction of parallel accumulation serial fragmentation (PASEF) on hybrid trapped ion mobility time-of-flight mass spectrometry instruments combined deep proteome sequencing with separation of (near-)isobaric precursor ions or converging isotope envelopes through ion mobility separation. However, the reported use of PASEF in integrated glycoproteomics workflows to comprehensively capture the glycoproteome is still limited. To this end, we developed an integrated methodology using timsTOF Pro 2 to enhance N-glycopeptide identifications in complex mixtures. We systematically optimized the ion optics tuning, collision energies, mobility isolation width, and the use of dopant-enriched nitrogen gas (DEN). Thus, we obtained a marked increase in unique glycopeptide identification rates compared to standard proteomics settings, showcasing our results on a large set of glycopeptides. With short liquid chromatography gradients of 30 min, we increased the number of unique N-glycopeptide identifications in human plasma samples from around 100 identifications under standard proteomics conditions to up to 1500 with our optimized glycoproteomics approach, highlighting the need for tailored optimizations to obtain comprehensive data.

Textural Precursor Compositions Harvested for Independent Signal Generators: Scaling Micron-Sized Flower-Like Metal-Organic Frameworks as Amplifying Units for Dual-Mode Glycoprotein Assay.

In this work, a micron-sized flower-like metal-organic frameworks (MOFs)-based boronate-affinity sandwich-type immunoassay was fabricated for the dual-mode glycoprotein assay. For proof of concept, the flower-like MOFs were synthesized from transition Cu nodes and tetrakis (4-carboxyphenyl) porphyrin (TCPP) ligands by spontaneous standing assembly. In addition, the specificity toward glycoprotein involved the antigen recognition as well as covalent bonding via the boronate-glycan affinity, and the immediate signal responses were initiated by textural decomposition of the flower-like MOFs. Intriguingly, Cu nodes, of which the valence state is dominant by CuI species, can endow the Fenton-like catalytic reaction of the fluorogenic substrate for generating fluorescence signals. For benefits, TCPP ligands, in which each TCPP molecule has four guest donors, can provide multiple valences for the assembly of cyclodextrin-capped gold nanoparticles via host-guest interaction for colorimetry output. Albeit important, the scaling micrometer patterns for the flower-like MOFs carrying numerous Cu nodes and TCPP ligands can also function as amplifying units, signifying the output signal. The detection limit of the dual-mode glycoprotein assay can reach 10.5 nM for the fluorescence mode and 18.7 nM for the colorimetry mode, respectively. Furthermore, the merits of harvesting different signal generators toward the multimodal readout patterns can allow the mutual verification and make the analytical results more reliable. Collectively, our proposed assay may offer a new idea in combining the inherent textural merits from MOFs for dual signal generators, which can also emphasize accurate detection capability for glycoprotein assay.

Lectin-Based SP3 Technology Enables N-Glycoproteomic Analysis of Mouse Oocytes.

N-glycosylation is one of the most universal and complex protein post-translational modifications (PTMs), and it is involved in many physiological and pathological activities. Owing to the low abundance of N-glycoproteins, enrichment of N-glycopeptides for mass spectrometry analysis usually requires a large amount of peptides. Additionally, oocyte protein N-glycosylation has not been systemically characterized due to the limited sample amount. Here, we developed a glycosylation enrichment method based on lectin and a single-pot, solid-phase-enhanced sample preparation (SP3) technology, termed lectin-based SP3 technology (LectinSP3). LectinSP3 immobilized lectin on the SP3 beads for N-glycopeptide enrichment. It could identify over 1100 N-glycosylation sites and 600 N-glycoproteins from 10 µg of mouse testis peptides. Furthermore, using the LectinSP3 method, we characterized the N-glycoproteome of 1000 mouse oocytes in three replicates and identified a total of 363 N-glycosylation sites from 215 N-glycoproteins. Bioinformatics analysis revealed that these oocyte N-glycoproteins were mainly enriched in cell adhesion, fertilization, and sperm-egg recognition. Overall, the LectinSP3 method has all procedures performed in one tube, using magnetic beads. It is suitable for analysis of a low amount of samples and is expected to be easily adaptable for automation. In addition, our mouse oocyte protein N-glycosylation profiling could help further characterize the regulation of oocyte functions.

Functional Interface for Glycoprotein Sensing: Focusing on Biosensors.

Glycosylated proteins or glycoproteins make up a large family of glycoconjugates, and they participate in a variety of fundamental biological events. Glycoproteins have become important biomarkers in the diagnosis and treatment of a number of tumors. Biosensors are quite suitable for glycoprotein detection. The design and fabrication of a functional sensing interface play a crucial role in the biosensor construction to target glycoproteins. The functional interface, particularly receptors, typically determines the key characteristics of a biosensor, such as selectivity and sensitivity. Antibody, peptide, aptamer, boronic acid derivative, lectin, and molecularly imprinted polymer are all capable receptors for glycoprotein recognition, and each of these will be discussed. Most glycoproteins exist in low abundance, thus rendering signal amplification techniques indispensable. Nucleic acid-mediated and nanomaterial-mediated signal amplification for the detection of glycoproteins will be focused on herein. This review aims to highlight these different functional interfaces for glycoprotein sensing.

Glycoproteomics: Charting new territory in mass spectrometry and glycobiology.

Glycosylation is an incredibly common and diverse post-translational modification that contributes widely to cellular health and disease. Mass spectrometry is the premier technique to study glycoproteins; however, glycoproteomics has lagged behind traditional proteomics due to the challenges associated with studying glycosylation. For instance, glycans dissociate by collision-based fragmentation, thus necessitating electron-based fragmentation for site-localization. The vast glycan heterogeneity leads to lower overall abundance of each glycopeptide, and often, ion suppression is observed. One of the biggest issues facing glycoproteomics is the lack of reliable software for analysis, which necessitates manual validation and serves as a massive bottleneck in data processing. Here, I will discuss each of these challenges and some ways in which the field is attempting to address them, along with perspectives on how I believe we should move forward.

Lipidomic Comparisons of Whole Cream Buttermilk Whey and Cheese Whey Cream Buttermilk of Caprine Milk.

Buttermilk is a potential material for the production of a milk fat globule membrane (MFGM) and can be mainly classified into two types: whole cream buttermilk and cheese whey cream buttermilk (WCB). Due to the high casein micelle content of whole cream buttermilk, the removal of casein micelles to improve the purity of MFGM materials is always required. This study investigated the effects of rennet and acid coagulation on the lipid profile of buttermilk rennet-coagulated whey (BRW) and buttermilk acid-coagulated whey (BAW) and compared them with WCB. BRW has significantly higher phospholipids (PLs) and ganglioside contents than BAW and WCB. The abundance of arachidonic acid (ARA)- and eicosapentaenoic acid (EPA)-structured PLs was higher in WCB, while docosahexaenoic acid (DHA)-structured PLs were higher in BRW, indicating that BRW and WCB intake might have a greater effect on improving cardiovascular conditions and neurodevelopment. WCB and BRW had a higher abundance of plasmanyl PL and plasmalogen PL, respectively. Phosphatidylcholine (PC) (28:1), LPE (20:5), and PC (26:0) are characteristic lipids among BRW, BAW, and WCB, and they can be used to distinguish MFGM-enriched whey from different sources.

Droplet Microfluidics with Capillary Electrophoresis for Glycan Biomarker Analysis.

Several glycoproteins are validated biomarkers of various diseases such as cancer, cardiovascular diseases, chronic alcohol abuse, or congenital disorders of glycosylation (CDG). In particular, CDG represent a group of more than 150 inherited diseases with varied symptoms affecting multiple organs. The distribution of glycans from target glycoprotein(s) can be used to extract information to help the diagnosis and possibly differentiate subtypes of CDG. Indeed, depending on the glycans and the proteins to which they are attached, glycans can play a very broad range of roles in both physical and biological properties of glycoproteins. For glycans in general, capillary electrophoresis with laser-induced fluorescence detection (CE-LIF) has become a staple. Analysis of glycans with CE-LIF requires several sample preparation steps, including release of glycans from the target glycoprotein, fluorescent labeling of glycans, and purification of labeled glycans. Here, we describe the protocol for glycan sample treatment in a microfluidic droplet system prior to CE-LIF of labeled glycans. The microfluidic droplet approach offers full automation, sample, and reagent volume reduction and elimination of contamination from external environment.