scholarly journals N-glycosylation of human interferon-γ: glycans at Asn-25 are critical for protease resistance

1995 ◽  
Vol 308 (1) ◽  
pp. 9-14 ◽  
Author(s):  
T Sareneva ◽  
J Pirhonen ◽  
K Cantell ◽  
I Julkunen
Keyword(s):  
Biological Activities ◽  
Interferon Γ ◽  
Glycosylation Site ◽  
Cathepsin G ◽  
Human Interferon ◽  
Globular Structure ◽  
Ifn Gamma ◽  
Protease Resistance ◽  
Glycosylation Sites ◽  
Defective Mutant

Human interferon-gamma (IFN-gamma) is a secretory, dimeric glycoprotein that forms a compact globular structure with potential N-linked glycosylation sites at Asn-25 and Asn-97 on the surface of the dimer. In natural leucocyte IFN-gamma (nIFN-gamma), 52%, 39% and 9% of the monomers are core-glycosylated in two, one or none of the potential N-glycosylation sites respectively. Chemical cross-linking of nIFN-gamma with glutaraldehyde revealed that 4, 3, 2 or 1 glycosylation sites occupied 28%, 40%, 26% and 6% of the dimers respectively. In baculovirus-produced wild-type (Wt) and N-linked glycosylation site-defective mutant (N25Q or N97Q, Asn-25 or Asn-97 substituted by Gln) IFN-gamma proteins, the extent of core glycosylation of monomers reflected the glycan composition of dimers. This suggests that dimers are formed randomly and independently of glycosylation. The glycan residues of IFN-gamma, especially at Asn-25, play an important role in protease resistance. Unglycosylated recombinant IFN-gamma proteins (from Escherichia coli and baculovirus) and N25Q IFN-gamma were sensitive to crude granulocyte protease, purified elastase, cathepsin G and plasmin degradation. Fully glycosylated nIFN-gamma and baculovirus Wt and N97Q IFN-gamma showed full or partial resistance to these proteases. These results emphasize the importance of glycan residues, especially at Asn-25, in the proteolytic stability of human IFN-gamma. Whether the differential glycosylation of n- and recombinant IFN-gamma (rIFN-gamma) is reflected in their biological activities in tissues or their clinical applicability is not known.

scholarly journals Role of N-glycosylation in the synthesis, dimerization and secretion of human interferon-γ

1994 ◽  
Vol 303 (3) ◽  
pp. 831-840 ◽  
Author(s):  
T Sareneva ◽  
J Pirhonen ◽  
K Cantell ◽  
N Kalkkinen ◽  
I Julkunen
Keyword(s):  
Interferon Γ ◽  
Glycosylation Site ◽  
Biologically Active ◽  
Human Interferon ◽  
Mutant Form ◽  
Ifn Gamma ◽  
Glycosylation Sites ◽  
Mutant Forms ◽  
Kinetics Of

Human interferon-gamma (IFN-gamma) is a secretory glycoprotein, which has two potential N-linked glycosylation sites at positions Asn-25 and Asn-97 of its 143 amino acid long mature polypeptide chain. In order to understand the role of glycan residues in the synthesis and secretion of human IFN-gamma, both or either one of the potential N-linked glycosylation sites were mutated to Gln. The mutant and the wild-type (Wt) polypeptides were expressed in insect cells using a baculovirus vector. Elimination of the N-glycosylation site at position Asn-97 (N97Q) resulted in secreted protein yields of 70-90% as compared with the Wt production, whereas only 10-25% (N25Q) and 1-10% (N25Q,N97Q) levels of protein production was observed when the first or both sites were mutated, respectively. Although there was a difference between extracellular levels of produced protein, the kinetics of secretion was similar for all different IFN-gamma molecules. The Wt and the N-glycosylation site mutants were all secreted as dimers. The formation of biologically active dimers was more efficient for IFN-gamma polypeptides that had the intact glycosylation site at Asn-25 as compared with the other two mutant forms of IFN-gamma. The extent of dimerization correlated well with the observed secretion. The specific antiviral activity was of the same order (1 x 10(7) i.u./mg of protein) for the glycosylated IFN-gamma molecules, whereas it was slightly lower (0.5 x 10(7) i.u./mg of protein) for the unglycosylated mutant form.

scholarly journals Recombinant human interferon-γ. Differences in glycosylation and proteolytic processing lead to heterogeneity in batch culture

1990 ◽  
Vol 272 (2) ◽  
pp. 333-337 ◽  
Author(s):  
E M Curling ◽  
P M Hayter ◽  
A J Baines ◽  
A T Bull ◽  
K Gull ◽  
...  
Keyword(s):  
Batch Culture ◽  
Cho Cells ◽  
Chinese Hamster ◽  
Interferon Γ ◽  
Proteolytic Processing ◽  
Human Interferon ◽  
Oxygen Control ◽  
Ifn Gamma ◽  
Sds Page ◽  
Dissolved Oxygen Control

Recombinant human interferon-gamma (Hu-IFN-gamma) produced by Chinese-hamster ovary (CHO) cells was analysed by immunoprecipitation and SDS/PAGE. Up to twelve molecular-mass variants were secreted by this cell line. Three variants were recovered after enzymic removal of all N-linked oligosaccharides or when glycosylation was inhibited by tunicamycin. The presence of three polypeptide forms rather than a single form suggested that proteolytic cleavage had occurred at two sites in both the glycosylated and non-glycosylated forms. Proteolytically cleaved IFN-gamma was more prevalent in cell lysates than in the secreted glycoprotein. In common with naturally produced IFN-gamma, both fully glycosylated IFN-gamma (asparagine residues 28 and 100 occupied) and partially glycosylated product (thought to be substituted at position Asn28) were secreted. This was deduced from the Mr of the glycosylated products and the relative amounts of sialic acid expressed by each variant. In contrast with naturally produced IFN-gamma, non-glycosylated IFN-gamma was also secreted by the transfected CHO cells. When the cells were grown in batch culture in serum-free medium under pH and dissolved-oxygen control, the proportion of non-glycosylated IFN-gamma increased from 3 to 5% after 3 h, to 30% of the total IFN-gamma present after 195 h. This change in the proportion of glycosylated protein produced was not seen when metabolically labelled IFN-gamma was incubated for 96 h with cell-free supernatant from actively growing CHO cells. This implied that an alteration in intracellular glycosylation was occurring rather than a degradation of oligosaccharide side chains after secretion. The decrease in IFN-gamma glycosylation was independent of the glucose concentration in the culture medium, but could be related to specific growth and IFN-gamma production rates, as these declined steadily after 50 h of culture, in line with the increased production of non-glycosylated IFN-gamma.

Nglyc: A Random Forest Method for Prediction of N-Glycosylation Sites in Eukaryotic Protein Sequence

2020 ◽  
Vol 27 (3) ◽  
pp. 178-186 ◽  
Author(s):  
Ganesan Pugalenthi ◽  
Varadharaju Nithya ◽  
Kuo-Chen Chou ◽  
Govindaraju Archunan
Keyword(s):  
Random Forest ◽  
Protein Sequence ◽  
Glycosylation Site ◽  
Computational Method ◽  
The Other ◽  
Eukaryotic Protein ◽  
Random Forest Method ◽  
Glycosylation Sites ◽  
Human And Mouse ◽  
Better Than

Background: N-Glycosylation is one of the most important post-translational mechanisms in eukaryotes. N-glycosylation predominantly occurs in N-X-[S/T] sequon where X is any amino acid other than proline. However, not all N-X-[S/T] sequons in proteins are glycosylated. Therefore, accurate prediction of N-glycosylation sites is essential to understand Nglycosylation mechanism. Objective: In this article, our motivation is to develop a computational method to predict Nglycosylation sites in eukaryotic protein sequences. Methods: In this article, we report a random forest method, Nglyc, to predict N-glycosylation site from protein sequence, using 315 sequence features. The method was trained using a dataset of 600 N-glycosylation sites and 600 non-glycosylation sites and tested on the dataset containing 295 Nglycosylation sites and 253 non-glycosylation sites. Nglyc prediction was compared with NetNGlyc, EnsembleGly and GPP methods. Further, the performance of Nglyc was evaluated using human and mouse N-glycosylation sites. Results: Nglyc method achieved an overall training accuracy of 0.8033 with all 315 features. Performance comparison with NetNGlyc, EnsembleGly and GPP methods shows that Nglyc performs better than the other methods with high sensitivity and specificity rate. Conclusion: Our method achieved an overall accuracy of 0.8248 with 0.8305 sensitivity and 0.8182 specificity. Comparison study shows that our method performs better than the other methods. Applicability and success of our method was further evaluated using human and mouse N-glycosylation sites. Nglyc method is freely available at https://github.com/bioinformaticsML/ Ngly.

Intelligent Techniques Analysis for Glycosylation Site Prediction

2021 ◽  
Vol 15 ◽  
Author(s):  
Alhassan Alkuhlani ◽  
Walaa Gad ◽  
Mohamed Roushdy ◽  
Abdel-Badeeh M. Salem
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Cell Interaction ◽  
Glycosylation Site ◽  
Machine Learning Classification ◽  
Site Prediction ◽  
Glycosylation Sites ◽  
Wide Range ◽  
Feature Extraction And Selection ◽  
Computational Intelligent

Background: Glycosylation is one of the most common post-translation modifications (PTMs) in organism cells. It plays important roles in several biological processes including cell-cell interaction, protein folding, antigen’s recognition, and immune response. In addition, glycosylation is associated with many human diseases such as cancer, diabetes and coronaviruses. The experimental techniques for identifying glycosylation sites are time-consuming, extensive laboratory work, and expensive. Therefore, computational intelligence techniques are becoming very important for glycosylation site prediction. Objective: This paper is a theoretical discussion of the technical aspects of the biotechnological (e.g., using artificial intelligence and machine learning) to digital bioinformatics research and intelligent biocomputing. The computational intelligent techniques have shown efficient results for predicting N-linked, O-linked and C-linked glycosylation sites. In the last two decades, many studies have been conducted for glycosylation site prediction using these techniques. In this paper, we analyze and compare a wide range of intelligent techniques of these studies from multiple aspects. The current challenges and difficulties facing the software developers and knowledge engineers for predicting glycosylation sites are also included. Method: The comparison between these different studies is introduced including many criteria such as databases, feature extraction and selection, machine learning classification methods, evaluation measures and the performance results. Results and conclusions: Many challenges and problems are presented. Consequently, more efforts are needed to get more accurate prediction models for the three basic types of glycosylation sites.

scholarly journals Engineered disulfide bonds in recombinant human interferon-γ: the impact of the N-terminal helix A and the AB-loop on protein stability

1996 ◽  
Vol 9 (10) ◽  
pp. 905-912 ◽  
Author(s):  
Gero Waschütza ◽  
Volkhart Li ◽  
Thomas Schäfer ◽  
Dietmar Schomburg ◽  
Carmen Villmann ◽  
...  
Keyword(s):  
Protein Stability ◽  
Disulfide Bonds ◽  
Interferon Γ ◽  
Human Interferon ◽  
The Impact

A point mutation that decreases the thermal stability of human interferon γ

1992 ◽  
Vol 5 (3) ◽  
pp. 249-252 ◽  
Author(s):  
C.A. Lunn ◽  
J. Fossetta ◽  
N. Murgolo ◽  
P. J. Zavodny ◽  
D. Lundell ◽  
...  
Keyword(s):  
Thermal Stability ◽  
Point Mutation ◽  
Interferon Γ ◽  
Human Interferon ◽  
Thermal Stability Of

scholarly journals Mouse Macrophages Carrying Both Subunits of the Human Interferon-γ (IFN-γ) Receptor Respond to Human IFN-γ but Do Not Acquire Full Protection against Viral Cytopathic Effect

1996 ◽  
Vol 271 (51) ◽  
pp. 32659-32666 ◽  
Author(s):  
David Lembo ◽  
Paola Ricciardi-Castagnoli ◽  
Gottfried Alber ◽  
Laurence Ozmen ◽  
Santo Landolfo ◽  
...  
Keyword(s):  
Cytopathic Effect ◽  
Interferon Γ ◽  
Human Interferon ◽  
Mouse Macrophages ◽  
Ifn Γ ◽  
Full Protection ◽  
Viral Cytopathic Effect

scholarly journals Biosynthetic analysis of the human interferon-γ receptor

1989 ◽  
Vol 264 (20) ◽  
pp. 11981-11988
Author(s):  
G K K Hershey ◽  
R D Schreiber
Keyword(s):  
Interferon Γ ◽  
Human Interferon
Sign in / Sign up

Export Citation Format

Share Document