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    Distinguishing Turkish pine honey from multi-floral honey through MALDI-MS-based N-glycomics and machine learning
    (Springer, 2024) Masri, Saad; Aksoy, Sena; Duman, Hatice; Karav, Sercan; Kayili, Haci Mehmet; Salih, Bekir
    Honey, a multifaceted blend of sugars, amino acids, vitamins, proteins, and minerals, exhibits compositional variability dependent upon the floral source. While previous studies have attempted to categorize honey, the use of glycomic profiles for honey classification remains an unexplored avenue. This investigation seeks to establish a methodology for distinguishing honey types, specifically multi-floral and pine honey, employing mass spectrometry-based glycomic analysis in tandem with machine learning. In this search, seven samples of pine honey and eight samples of multi-floral honey were obtained from diverse regions of Turkey. Subsequently, the proteins within these honey samples were extracted, and glycans were enzymatically released. The released glycans were labeled with 2-aminobenzoic acid (2-AA) and subjected to analysis via matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The glycan profiles of pine and multi-floral honey were determined through these analytical procedures, revealing a total of 76 distinct N-glycan structures. Among these, 13 N-glycan profiles consistently established at high levels across experimental replicates and were incorporated in subsequent analyses. Following the quantification of individual glycan abundances, statistically significant differences in glycan profiles were determined. Notably, N-glycans Hex5HexNAc2, Hex4HexNAc3, and Hex5HexNAc3 displayed considerable differences. Using the 13 N-glycan profiles, an accuracy rate of 93.5% was obtained from machine learning analysis, which increased to 100% when incorporating the identified significantly changed glycans. The most productive models were identified as subspace and fine k-nearest neighbors (KNN). The findings underscore the potential of mass spectrometry-based glycomics in conjunction with machine learning as a robust tool for precise honey type classification and its prospective utility in quality control and honey product authentication.
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    Distinguishing Turkish pine honey from multi-foral honey through MALDI-MS-based N-glycomics and machine learning (vol 18, pg 5673, 2024)
    (Springer, 2024) Masri, Saad; Aksoy, Sena; Duman, Hatice; Karav, Sercan; Kayili, Haci Mehmet; Salih, Bekir
    [No abstract available]
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    Immobilization of a Bifidobacterial Endo-ss-N-Acetylglucosaminidase to Generate Bioactive Compounds for Food Industry
    (Frontiers Media Sa, 2022) Pekdemir, Burcu; Duman, Hatice; Arslan, Aysenur; Kaplan, Merve; Karyelioglu, Melda; ozer, Tolgahan; Kayili, Haci Mehmet
    Conjugated N-glycans are considered next-generation bioactive prebiotic compounds due to their selective stimulation of beneficial microbes. These compounds are glycosidically attached to proteins through N-acetylglucosamines via specific asparagine residue (AsN-X-Ser/Thr). Certain bacteria such as Bifidobacterium longum subspecies infantis (B. infantis) have been shown to be capable of utilizing conjugated N-glycans, owing to their specialized genomic abilities. B. infantis possess a unique enzyme, Endo-ss-N-acetylglucosaminidase (EndoBI-1), which cleaves all types of conjugated N-glycans from glycoproteins. In this study, recombinantly cloned EndoBI-1 enzyme activity was investigated using various immobilization methods: 1) adsorption, 2) entrapment-based alginate immobilization, 3) SulfoLink-, and 4) AminoLink-based covalent bonding immobilization techniques were compared to develop the optimum application of EndoBI-1 to food processes. The yield of enzyme immobilization and the activity of each immobilized enzyme by different approaches were investigated. The N-glycans released from lactoperoxidase (LPO) using different immobilized enzyme forms were characterized using MALDI-TOF mass spectrometry (MS). As expected, regardless of the techniques, the enzyme activity decreased after the immobilization methods. The enzyme activity of adsorption and entrapment-based alginate immobilization was found to be 71.55% +/- 0.6 and 20.32% +/- 3.18, respectively, whereas the activity of AminoLink- and SulfoLink-based covalent bonding immobilization was found to be 58.05 +/- 1.98 and 47.49% +/- 0.30 compared to the free form of the enzyme, respectively. However, extended incubation time recovery achieved activity similar to that of the free form. More importantly, each immobilization method resulted in the same glycan profile containing 11 different N-glycan structures from a model glycoprotein LPO based on MALDI-TOF MS analysis. The glycan data analysis suggests that immobilization of EndoBI-1 is not affecting the enzyme specificity, which enables full glycan release without a limitation. Hence, different immobilization methods investigated in this study can be chosen for effective enzyme immobilization to obtain bioactive glycans. These findings highlight that further optimization of these methods can be a promising approach for future processing scale-up and commercialization of EndoBI-1 and similar enzymes.
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    Potential Applications of Endo-?-N-Acetylglucosaminidases From Bifidobacterium longum Subspecies infantis in Designing Value-Added, Next-Generation Infant Formulas
    (Frontiers Media Sa, 2021) Duman, Hatice; Kaplan, Merve; Arslan, Aysenur; Sahutoglu, Arif Sercan; Kayili, Haci Mehmet; Frese, Steven A.; Karav, Sercan
    Human milk is the optimal source of infant nutrition. Among many other health benefits, human milk can stimulate the development of a Bifidobacterium-rich microbiome through human milk oligosaccharides (HMOs). In recent years, the development of novel formulas has placed particular focus on incorporating some of the beneficial functional properties of human milk. These include adding specific glycans aimed to selectively stimulate the growth of Bifidobacterium. However, the bifidogenicity of human milk remains unparalleled. Dietary N-glycans are carbohydrate structures conjugated to a wide variety of glycoproteins. These glycans have a remarkable structural similarity to HMOs and, when released, show a strong bifidogenic effect. This review discusses the biocatalytic potential of the endo-beta-N-acetylglucosaminidase enzyme (EndoBI-1) from Bifidobacterium longum subspecies infantis (B. infantis), in releasing N-glycans inherently present in infant formula as means to increase the bifidogenicity of infant formula. Finally, the potential implications for protein deglycosylation with EndoBI-1 in the development of value added, next-generation formulas are discussed from a technical perspective.
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    Recombinant Production of Bifidobacterial Endoglycosidases for N-glycan Release
    (Journal Of Visualized Experiments, 2021) Sucu, Berfin; Bayraktar, Ayse; Duman, Hatice; Arslan, Aysenur; Kaplan, Merve; Karyelioglu, Melda; Ntelitze, Eda
    Protein glycosylation is a diverse and common post-translational modification that has been associated with many important roles such as protein function, including protein folding, stability, enzymatic protection, and biological recognition. N-glycans attached to glycoproteins (such as lactoferrin, lactadherin, and immunoglobulins) cannot be digested by the host and reach the large intestine, where they are consumed by certain beneficial microbes. Therefore, they are considered nextgeneration prebiotic compounds that can selectively stimulate the gut microbiome's beneficial microorganisms. However, the isolation of these new classes of prebiotics requires novel enzymes. Here, we describe the recombinant production of novel glycosidases from different Bifidobacteria strains (isolated from infants, rabbits, chicken, and bumblebee) for improved N-glycan isolation from glycoproteins. The method presented in this study includes the following steps: molecular cloning of Bifidobacterial genes by an in vivo recombinational cloning strategy, control of transformation success, protein induction, and protein purification.