Effects of sialic acid linkage on antibody-fragment crystallizable receptor binding and antibody dependent cytotoxicity depend on levels of fucosylation/bisecting

Bioanalysis ◽  
2019 ◽  
Vol 11 (15) ◽  
pp. 1437-1449 ◽  
Author(s):  
Marco Thomann ◽  
Sebastian Malik ◽  
Felix Kuhne ◽  
Cecile Avenal ◽  
Friederike Plath ◽  
...  
Keyword(s):  
Sialic Acid ◽  
Receptor Binding ◽  
Antibody Fragment ◽  
Quality Attribute ◽  
Fcγ Receptor ◽  
Critical Quality Attribute ◽  
Cytotoxicity Activity ◽  
Terminal Galactose ◽  
The Impact ◽  
Different Levels

Aim: Fragment crystallizable (Fc) glycosylation of immunoglobulin G-type monoclonal antibodies applied to therapeutic applications is regarded a critical quality attribute and can influence bioactivity, pharmacokinetics and/or immunogenicity/safety. Investigating the impact of certain Fc N-glycans is therefore of importance to assess its criticality for a therapeutic product. This has been done for N-glycan types like fucosylation, galactosylation or sialylation. There were contradictory results reported for functionality especially with regard to sialylation. Material & methods: We elucidated the effect of terminal sialic acid residues on Fcγ receptor binding and antibody dependent cytotoxicity activity of two immunoglobulin G1 antibodies with different levels of fucosylation/bi-secting. Conclusion: We found the impact to be specific to the sialylation linkage type, in other words, α2,3- versus α2,6-linked sialic acid attached to the terminal galactose residues

scholarly journals Vaccine-elicited antibody that neutralizes H5N1 influenza and variants binds the receptor site and polymorphic sites

2015 ◽  
Vol 112 (30) ◽  
pp. 9346-9351 ◽  
Author(s):  
Katie L. Winarski ◽  
Natalie J. Thornburg ◽  
Yingchun Yu ◽  
Gopal Sapparapu ◽  
James. E. Crowe ◽  
...  
Keyword(s):  
Sialic Acid ◽  
Binding Site ◽  
Receptor Binding ◽  
Germ Line ◽  
Influenza Viruses ◽  
Antigenic Drift ◽  
Receptor Binding Site ◽  
Critical Feature ◽  
H5n1 Influenza ◽  
The Impact

Antigenic drift of circulating seasonal influenza viruses necessitates an international vaccine effort to reduce the impact on human health. A critical feature of the seasonal vaccine is that it stimulates an already primed immune system to diversify memory B cells to recognize closely related, but antigenically distinct, influenza glycoproteins (hemagglutinins). Influenza pandemics arise when hemagglutinins to which no preexisting adaptive immunity exists acquire the capacity to infect humans. Hemagglutinin 5 is one subtype to which little preexisting immunity exists and is only a few acquired mutations away from the ability to transmit efficiently between ferrets, and possibly humans. Here, we describe the structure and molecular mechanism of neutralization by H5.3, a vaccine-elicited antibody that neutralizes hemagglutinin 5 viruses and variants with expanded host range. H5.3 binds in the receptor-binding site, forming contacts that recapitulate many of the sialic acid interactions, as well as multiple peripheral interactions, yet is not sensitive to mutations that alter sialic acid binding. H5.3 is highly specific for a subset of H5 strains, and this specificity arises from interactions to the periphery of the receptor-binding site. H5.3 is also extremely potent, despite retaining germ line-like conformational flexibility.

scholarly journals Influenza H1N1 A/Solomon Island/3/06 Virus Receptor Binding Specificity Correlates with Virus Pathogenicity, Antigenicity, and Immunogenicity in Ferrets

2010 ◽  
Vol 84 (10) ◽  
pp. 4936-4945 ◽  
Author(s):  
Qi Xu ◽  
Weijia Wang ◽  
Xing Cheng ◽  
James Zengel ◽  
Hong Jin
Keyword(s):  
Sialic Acid ◽  
Respiratory Tract ◽  
Receptor Binding ◽  
Lower Respiratory Tract ◽  
Solomon Island ◽  
Influenza Viruses ◽  
Single Amino Acid ◽  
Wild Type ◽  
Single Amino Acid Change ◽  
The Impact

ABSTRACT Influenza viruses attach to cells via a sialic acid moiety (sialic acid receptor) that is α2-3 linked or α2-6 linked to galactose (α2-3SAL or α2-6SAL); sialic acid acts as a receptor for the virus. Using lectin staining, we demonstrated that the α2-6SAL configuration is predominant in the respiratory tract of ferrets, including trachea, bronchus, and lung alveolus tissues. Recombinant wild-type (rWT) influenza A/Solomon Island/3/06 (SI06) (H1N1) viruses were constructed to assess the impact of the hemagglutinin (HA) variations (amino acids 190 or 226) identified in natural variants on virus replication in the upper and lower respiratory tract of ferrets, as well as virus antigenicity and immunogenicity. A single amino acid change at residue 226 (from Gln to Arg) in the HA of SI06 resulted in the complete loss of binding to α2-6SAL and a concomitant loss of the virus's ability to replicate in the lower respiratory tract of ferrets. In contrast, the virus with Gln226 in the HA protein has a receptor binding preference for α2-6SAL and replicates efficiently in the lungs. There was a good correlation between viral replication in the lungs of ferrets and disease symptoms. In addition, we also showed that the 190 and 226 residues affected viral antigenicity and immunogenicity. Our data emphasize the necessity of thoroughly assessing wild-type influenza viruses for their suitability as reference strains and for carefully selecting the HA antigen for vaccine production during annual influenza vaccine evaluation processes.

TEACH-POT: Provide Opportunities in Teaching

2020 ◽  
pp. 79-91 ◽  
Author(s):  
Maria Giulia Ballatore ◽  
Ettore Felisatti ◽  
Laura Montanaro ◽  
Anita Tabacco
Keyword(s):  
Academic Community ◽  
Real Effect ◽  
The Real ◽  
Main Components ◽  
The Impact ◽  
Training Opportunities ◽  
Different Levels

This paper is aimed to describe and critically analyze the so-called "TEACHPOT" experience (POT: Provide Opportunities in Teaching) performed during the last few years at Politecnico di Torino. Due to career criteria, the effort and the time lecturers spend in teaching have currently undergone a significant reduction in quantity. In order to support and meet each lecturers' expectations towards an improvement in their ability to teach, a mix of training opportunities has been provided. This consists of an extremely wide variety of experiences, tools, relationships, from which everyone can feel inspired to increase the effectiveness of their teaching and the participation of their students. The provided activities are designed around three main components: methodological training, teaching technologies, methodological experiences. A discussion on the findings is included and presented basing on the data collected through a survey. The impact of the overall experience can be evaluated on two different levels: the real effect on redesigning lessons, and the discussion on the matter within the entire academic community.

scholarly journals The impact of IFRS-based accounting standards on earnings management: evidence from Malaysia

2016 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Yosra Makni Fourati ◽  
Rania Chakroun Ghorbel
Keyword(s):  
Earnings Management ◽  
Financial Reporting ◽  
Emerging Market ◽  
Accounting Standards ◽  
Absolute Value ◽  
Financial Reporting Standards ◽  
Ifrs Adoption ◽  
Earning Quality ◽  
The Impact ◽  
Different Levels

This study aims to examine the consequences of International Financial Reporting Standards (IFRS) convergence in an emerging market. More specifically, we investigate whether the adoption of the new set of accounting standards in Malaysia is associated with lower earnings management. Using a sample of 3,340 firm-year observations across three reporting periods with different levels of IFRS adoption, we provide evidence that IFRS convergence improves earning quality. In particular, we find a significant decrease in the absolute value of discretionary acccruals in the partial IFRS-convergence period (2007-2011), whereas this effect is restrictive after the complete IFRS- implementation.

scholarly journals Gamification and Hazard Communication in Virtual Reality: A Qualitative Study

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4663
Author(s):  
Janaina Cavalcanti ◽  
Victor Valls ◽  
Manuel Contero ◽  
David Fonseca
Keyword(s):  
Virtual Reality ◽  
New Technologies ◽  
Training Environment ◽  
Hazard Communication ◽  
Head Mounted Display ◽  
Compliance Behavior ◽  
Before And After ◽  
Recorded Data ◽  
The Impact ◽  
Different Levels

An effective warning attracts attention, elicits knowledge, and enables compliance behavior. Game mechanics, which are directly linked to human desires, stand out as training, evaluation, and improvement tools. Immersive virtual reality (VR) facilitates training without risk to participants, evaluates the impact of an incorrect action/decision, and creates a smart training environment. The present study analyzes the user experience in a gamified virtual environment of risks using the HTC Vive head-mounted display. The game was developed in the Unreal game engine and consisted of a walk-through maze composed of evident dangers and different signaling variables while user action data were recorded. To demonstrate which aspects provide better interaction, experience, perception and memory, three different warning configurations (dynamic, static and smart) and two different levels of danger (low and high) were presented. To properly assess the impact of the experience, we conducted a survey about personality and knowledge before and after using the game. We proceeded with the qualitative approach by using questions in a bipolar laddering assessment that was compared with the recorded data during the game. The findings indicate that when users are engaged in VR, they tend to test the consequences of their actions rather than maintaining safety. The results also reveal that textual signal variables are not accessed when users are faced with the stress factor of time. Progress is needed in implementing new technologies for warnings and advance notifications to improve the evaluation of human behavior in virtual environments of high-risk surroundings.

scholarly journals Design of a companion bioinformatic tool to detect the emergence and geographical distribution of SARS-CoV-2 Spike protein genetic variants

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Alice Massacci ◽  
Eleonora Sperandio ◽  
Lorenzo D’Ambrosio ◽  
Mariano Maffei ◽  
Fabio Palombo ◽  
...  
Keyword(s):  
Receptor Binding ◽  
Consensus Sequence ◽  
Cell Epitope ◽  
Vaccine Design ◽  
Binding Domain ◽  
Spike Protein ◽  
Antibody Activity ◽  
Binding Motif ◽  
Receptor Binding Domain ◽  
The Impact

Abstract Background Tracking the genetic variability of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) is a crucial challenge. Mainly to identify target sequences in order to generate robust vaccines and neutralizing monoclonal antibodies, but also to track viral genetic temporal and geographic evolution and to mine for variants associated with reduced or increased disease severity. Several online tools and bioinformatic phylogenetic analyses have been released, but the main interest lies in the Spike protein, which is the pivotal element of current vaccine design, and in the Receptor Binding Domain, that accounts for most of the neutralizing the antibody activity. Methods Here, we present an open-source bioinformatic protocol, and a web portal focused on SARS-CoV-2 single mutations and minimal consensus sequence building as a companion vaccine design tool. Furthermore, we provide immunogenomic analyses to understand the impact of the most frequent RBD variations. Results Results on the whole GISAID sequence dataset at the time of the writing (October 2020) reveals an emerging mutation, S477N, located on the central part of the Spike protein Receptor Binding Domain, the Receptor Binding Motif. Immunogenomic analyses revealed some variation in mutated epitope MHC compatibility, T-cell recognition, and B-cell epitope probability for most frequent human HLAs. Conclusions This work provides a framework able to track down SARS-CoV-2 genomic variability.

scholarly journals Predicting bacteriophage hosts based on sequences of annotated receptor-binding proteins

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dimitri Boeckaerts ◽  
Michiel Stock ◽  
Bjorn Criel ◽  
Hans Gerstmans ◽  
Bernard De Baets ◽  
...  
Keyword(s):  
Machine Learning ◽  
Predictive Model ◽  
Receptor Binding ◽  
Bacterial Infections ◽  
Sequence Data ◽  
Sequence Similarity ◽  
Area Under The Curve ◽  
Local Alignment ◽  
Search Tool ◽  
Different Levels

AbstractNowadays, bacteriophages are increasingly considered as an alternative treatment for a variety of bacterial infections in cases where classical antibiotics have become ineffective. However, characterizing the host specificity of phages remains a labor- and time-intensive process. In order to alleviate this burden, we have developed a new machine-learning-based pipeline to predict bacteriophage hosts based on annotated receptor-binding protein (RBP) sequence data. We focus on predicting bacterial hosts from the ESKAPE group, Escherichia coli, Salmonella enterica and Clostridium difficile. We compare the performance of our predictive model with that of the widely used Basic Local Alignment Search Tool (BLAST). Our best-performing predictive model reaches Precision-Recall Area Under the Curve (PR-AUC) scores between 73.6 and 93.8% for different levels of sequence similarity in the collected data. Our model reaches a performance comparable to that of BLASTp when sequence similarity in the data is high and starts outperforming BLASTp when sequence similarity drops below 75%. Therefore, our machine learning methods can be especially useful in settings in which sequence similarity to other known sequences is low. Predicting the hosts of novel metagenomic RBP sequences could extend our toolbox to tune the host spectrum of phages or phage tail-like bacteriocins by swapping RBPs.

scholarly journals Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jonatan Almagor ◽  
Stefano Picascia
Keyword(s):  
High Rate ◽  
Contact Tracing ◽  
Agent Based Model ◽  
Agent Based ◽  
The Social ◽  
Behavioural Factors ◽  
The Impact ◽  
Different Levels ◽  
User Rate

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.

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