scholarly journals Glycan Binding Profiling of Jacalin-Related Lectins from the Pteria Penguin Pearl Shell

2019 ◽  
Vol 20 (18) ◽  
pp. 4629
Author(s):  
Tomohisa Ogawa ◽  
Rie Sato ◽  
Takako Naganuma ◽  
Kayeu Liu ◽  
Agness Ethel Lakudzala ◽  
...  
Keyword(s):  
Matrix Protein ◽  
Binding Specificity ◽  
The Other ◽  
Carbohydrate Binding ◽  
Sequence Variants ◽  
Data Sets ◽  
Binding Properties ◽  
Chromatography Analysis ◽  
Pteria Penguin ◽  
High Mannose

We determined the primary structures of jacalin-related lectins termed PPL3s (PPL3A, 3B, and 3C, which are dimers consisting of sequence variants α + α, α + β, β + β, respectively) and PPL4, which is heterodimer consisting of α + β subunits, isolated from mantle secretory fluid of Pteria penguin (Mabe) pearl shell. Their carbohydrate-binding properties were analyzed, in addition to that of PPL2A, which was previously reported as a matrix protein. PPL3s and PPL4 shared only 35–50% homology to PPL2A, respectively; they exhibited significantly different carbohydrate-binding specificities based on the multiple glycan binding profiling data sets from frontal affinity chromatography analysis. The carbohydrate-binding specificity of PPL3s was similar to that of PPL2A, except only for Man3Fuc1Xyl1GlcNAc2 oligosaccharide, while PPL4 showed different carbohydrate-binding specificity compared with PPL2A and PPL3s. PPL2A and PPL3s mainly recognize agalactosylated- and galactosylated-type glycans. On the other hand, PPL4 binds to high-mannose-and hybrid-type N-linked glycans but not agalactosylated- and galactosylated-type glycans.

scholarly journals Diversified Biomineralization Roles of Pteria penguin Pearl Shell Lectins as Matrix Proteins

2021 ◽  
Vol 22 (3) ◽  
pp. 1081
Author(s):  
Tomohisa Ogawa ◽  
Rie Sato ◽  
Takako Naganuma ◽  
Kayeu Liu ◽  
Saho Sato ◽  
...  
Keyword(s):  
Matrix Proteins ◽  
Carbohydrate Binding ◽  
Data Sets ◽  
Shell Formation ◽  
Binding Properties ◽  
Chromatography Analysis ◽  
Pteria Penguin ◽  
Lectin Family ◽  
Chitin Oligomer ◽  
Mollusk Shell

Previously, we isolated jacalin-related lectins termed PPL2, PPL3 (PPL3A, 3B and 3C) and PPL4 from the mantle secretory fluid of Pteria penguin (Mabe) pearl shell. They showed the sequence homology with the plant lectin family, jacalin-related β-prism fold lectins (JRLs). While PPL3s and PPL4 shared only 35%–50% homology to PPL2A, respectively, they exhibited unique carbohydrate binding properties based on the multiple glycan-binding profiling data sets from frontal affinity chromatography analysis. In this paper, we investigated biomineralization properties of these lectins and compared their biomineral functions. It was found that these lectins showed different effects on CaCO3 crystalization, respectively, although PPL3 and PPL2A showed similar carbohydrate binding specificities. PPL3 suppressed the crystal growth of CaCO3 calcite, while PPL2A increased the number of contact polycrystalline calcite composed of more than one crystal with various orientations. Furthermore, PPL4 alone showed no effect on CaCO3 crystalization; however, PPL4 regulated the size of crystals collaborated with N-acetyl-D-glucosamine and chitin oligomer, which are specific in recognizing carbohydrates for PPL4. These observations highlight the unique functions and molecular evolution of this lectin family involved in the mollusk shell formation.

scholarly journals Overview of the Structure–Function Relationships of Mannose-Specific Lectins from Plants, Algae and Fungi

2019 ◽  
Vol 20 (2) ◽  
pp. 254 ◽  
Author(s):  
Annick Barre ◽  
Yves Bourne ◽  
Els Van Damme ◽  
Pierre Rougé
Keyword(s):  
Structure Function ◽  
Binding Site ◽  
High Specificity ◽  
Binding Specificity ◽  
Binding Pocket ◽  
Carbohydrate Binding ◽  
Specific Recognition ◽  
Mannose Binding ◽  
High Mannose ◽  
Function Relationship

To date, a number of mannose-binding lectins have been isolated and characterized from plants and fungi. These proteins are composed of different structural scaffold structures which harbor a single or multiple carbohydrate-binding sites involved in the specific recognition of mannose-containing glycans. Generally, the mannose-binding site consists of a small, central, carbohydrate-binding pocket responsible for the “broad sugar-binding specificity” toward a single mannose molecule, surrounded by a more extended binding area responsible for the specific recognition of larger mannose-containing N-glycan chains. Accordingly, the mannose-binding specificity of the so-called mannose-binding lectins towards complex mannose-containing N-glycans depends largely on the topography of their mannose-binding site(s). This structure–function relationship introduces a high degree of specificity in the apparently homogeneous group of mannose-binding lectins, with respect to the specific recognition of high-mannose and complex N-glycans. Because of the high specificity towards mannose these lectins are valuable tools for deciphering and characterizing the complex mannose-containing glycans that decorate both normal and transformed cells, e.g., the altered high-mannose N-glycans that often occur at the surface of various cancer cells.

scholarly journals Carbohydrate binding properties of complex-type oligosaccharides on immobilized Datura stramonium lectin.

1987 ◽  
Vol 262 (4) ◽  
pp. 1602-1607 ◽  
Author(s):  
K Yamashita ◽  
K Totani ◽  
T Ohkura ◽  
S Takasaki ◽  
I J Goldstein ◽  
...  
Keyword(s):  
Datura Stramonium ◽  
Carbohydrate Binding ◽  
Complex Type ◽  
Binding Properties

scholarly journals Using historical data to facilitate clinical prevention trials in Alzheimer disease? An analysis of longitudinal MCI (mild cognitive impairment) data sets

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Manfred Berres ◽  
Andreas U. Monsch ◽  
René Spiegel
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Performance ◽  
Placebo Treatment ◽  
Drug Trial ◽  
The Other ◽  
Data Sets ◽  
Control Groups ◽  
Community Needs ◽  
Clinical Prevention

Abstract Background The Placebo Group Simulation Approach (PGSA) aims at partially replacing randomized placebo-controlled trials (RPCTs), making use of data from historical control groups in order to decrease the needed number of study participants exposed to lengthy placebo treatment. PGSA algorithms to create virtual control groups were originally derived from mild cognitive impairment (MCI) data of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. To produce more generalizable algorithms, we aimed to compile five different MCI databases in a heuristic manner to create a “standard control algorithm” for use in future clinical trials. Methods We compared data from two North American cohort studies (n=395 and 4328, respectively), one company-sponsored international clinical drug trial (n=831) and two convenience patient samples, one from Germany (n=726), and one from Switzerland (n=1558). Results Despite differences between the five MCI samples regarding inclusion and exclusion criteria, their baseline demographic and cognitive performance data varied less than expected. However, the five samples differed markedly with regard to their subsequent cognitive performance and clinical development: (1) MCI patients from the drug trial did not deteriorate on verbal fluency over 3 years, whereas patients in the other samples did; (2) relatively few patients from the drug trial progressed from MCI to dementia (about 10% after 4 years), in contrast to the other four samples with progression rates over 30%. Conclusion Conventional MCI criteria were insufficient to allow for the creation of well-defined and internationally comparable samples of MCI patients. More recently published criteria for MCI or “MCI due to AD” are unlikely to remedy this situation. The Alzheimer scientific community needs to agree on a standard set of neuropsychological tests including appropriate selection criteria to make MCI a scientifically more useful concept. Patient data from different sources would then be comparable, and the scientific merits of algorithm-based study designs such as the PGSA could be properly assessed.

scholarly journals DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hossein Ahmadvand ◽  
Fouzhan Foroutan ◽  
Mahmood Fathy
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Processing Time ◽  
Experimental Results ◽  
The Other ◽  
Data Sets ◽  
Multiple Sources ◽  
Evaluation Phase ◽  
Dynamic Voltage ◽  
Processing Resources

AbstractData variety is one of the most important features of Big Data. Data variety is the result of aggregating data from multiple sources and uneven distribution of data. This feature of Big Data causes high variation in the consumption of processing resources such as CPU consumption. This issue has been overlooked in previous works. To overcome the mentioned problem, in the present work, we used Dynamic Voltage and Frequency Scaling (DVFS) to reduce the energy consumption of computation. To this goal, we consider two types of deadlines as our constraint. Before applying the DVFS technique to computer nodes, we estimate the processing time and the frequency needed to meet the deadline. In the evaluation phase, we have used a set of data sets and applications. The experimental results show that our proposed approach surpasses the other scenarios in processing real datasets. Based on the experimental results in this paper, DV-DVFS can achieve up to 15% improvement in energy consumption.

scholarly journals Theory and Applications of the Unit Gamma/Gompertz Distribution

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1850
Author(s):  
Rashad A. R. Bantan ◽  
Farrukh Jamal ◽  
Christophe Chesneau ◽  
Mohammed Elgarhy
Keyword(s):  
Stochastic Ordering ◽  
Real Data ◽  
Rate Function ◽  
The Other ◽  
Likelihood Method ◽  
Model Parameters ◽  
Data Sets ◽  
Gompertz Distribution ◽  
Probability And Statistics ◽  
Analytical Behavior

Unit distributions are commonly used in probability and statistics to describe useful quantities with values between 0 and 1, such as proportions, probabilities, and percentages. Some unit distributions are defined in a natural analytical manner, and the others are derived through the transformation of an existing distribution defined in a greater domain. In this article, we introduce the unit gamma/Gompertz distribution, founded on the inverse-exponential scheme and the gamma/Gompertz distribution. The gamma/Gompertz distribution is known to be a very flexible three-parameter lifetime distribution, and we aim to transpose this flexibility to the unit interval. First, we check this aspect with the analytical behavior of the primary functions. It is shown that the probability density function can be increasing, decreasing, “increasing-decreasing” and “decreasing-increasing”, with pliant asymmetric properties. On the other hand, the hazard rate function has monotonically increasing, decreasing, or constant shapes. We complete the theoretical part with some propositions on stochastic ordering, moments, quantiles, and the reliability coefficient. Practically, to estimate the model parameters from unit data, the maximum likelihood method is used. We present some simulation results to evaluate this method. Two applications using real data sets, one on trade shares and the other on flood levels, demonstrate the importance of the new model when compared to other unit models.

scholarly journals Integrated Counts of Carbohydrate-Active Protein Domains as Metabolic Readouts to Distinguish Probiotic Biology and Human Fecal Metagenomes

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hong-Hsing Liu ◽  
Yu-Chen Lin ◽  
Chen-Shuan Chung ◽  
Kevin Liu ◽  
Ya-Hui Chang ◽  
...  
Keyword(s):  
Markov Models ◽  
Protein Domains ◽  
Degradation Pathway ◽  
The Other ◽  
Carbohydrate Binding ◽  
Gram Stain ◽  
Active Protein ◽  
Metabolic Potential ◽  
Independent Validation ◽  
Carbohydrate Binding Modules

AbstractBowel microbiota is a “metaorgan” of metabolisms on which quantitative readouts must be performed before interventions can be introduced and evaluated. The study of the effects of probiotic Clostridium butyricum MIYAIRI 588 (CBM588) on intestine transplantees indicated an increased percentage of the “other glycan degradation” pathway in 16S-rRNA-inferred metagenomes. To verify the prediction, a scoring system of carbohydrate metabolisms derived from shotgun metagenomes was developed using hidden Markov models. A significant correlation (R = 0.9, p < 0.015) between both modalities was demonstrated. An independent validation revealed a strong complementarity (R = −0.97, p < 0.002) between the scores and the abundance of “glycogen degradation” in bacteria communities. On applying the system to bacteria genomes, CBM588 had only 1 match and ranked higher than the other 8 bacteria evaluated. The gram-stain properties were significantly correlated to the scores (p < 5 × 10−4). The distributions of the scored protein domains indicated that CBM588 had a considerably higher (p < 10−5) proportion of carbohydrate-binding modules than other bacteria, which suggested the superior ability of CBM588 to access carbohydrates as a metabolic driver to the bowel microbiome. These results demonstrated the use of integrated counts of protein domains as a feasible readout for metabolic potential within bacteria genomes and human metagenomes.

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