AutoCoEv-A High-Throughput In Silico Pipeline for Predicting Inter-Protein Coevolution

Protein-protein interactions govern cellular processes via complex regulatory networks, which are still far from being understood. Thus, identifying and understanding connections between proteins can significantly facilitate our comprehension of the mechanistic principles of protein functions. Coevolution between proteins is a sign of functional communication and, as such, provides a powerful approach to search for novel direct or indirect molecular partners. However, an evolutionary analysis of large arrays of proteins in silico is a highly time-consuming effort that has limited the usage of this method for protein pairs or small protein groups. Here, we developed AutoCoEv, a user-friendly, open source, computational pipeline for the search of coevolution between a large number of proteins. By driving 15 individual programs, culminating in CAPS2 as the software for detecting coevolution, AutoCoEv achieves a seamless automation and parallelization of the workflow. Importantly, we provide a patch to the CAPS2 source code to strengthen its statistical output, allowing for multiple comparison corrections and an enhanced analysis of the results. We apply the pipeline to inspect coevolution among 324 proteins identified to be located at the vicinity of the lipid rafts of B lymphocytes. We successfully detected multiple coevolutionary relations between the proteins, predicting many novel partners and previously unidentified clusters of functionally related molecules. We conclude that AutoCoEv, can be used to predict functional interactions from large datasets in a time- and cost-efficient manner

B cells rapidly target antigen and surface-derived MHCII into peripheral degradative compartments

In order to mount high-affinity antibody responses, B cells internalise specific antigens and process them into peptides loaded onto MHCII for presentation to T helper cells (T H cells). While the biochemical principles of antigen processing and MHCII loading have been well dissected, how the endosomal vesicle system is wired to enable these specific functions remains much less studied. Here, we performed a systematic microscopy-based analysis of antigen trafficking in B cells to reveal its route to the MHCII peptide-loading compartment (MIIC). Surprisingly, we detected fast targeting of internalised antigen into peripheral acidic compartments that possessed the hallmarks of the MIIC and also showed degradative capacity. In these vesicles, intemalised antigen converged rapidly with membrane-derived MHCII and partially overlapped with cathepsin-S and H2-M, both required for peptide loading. These early compartments appeared heterogenous and atypical as they contained a mixture of both early and late endosomal markers, indicating a specialized endosomal route. Together, our data suggest that, in addition to in the previously reported perinuclear late endosomal MIICs, antigen processing and peptide loading could have already started in these specialized early peripheral acidic vesicles (eMlIC) to support fast peptide-MHCII presentation. This article has an associated First Person interview with the first author of the paper.Peer reviewe

B cells rapidly target antigen and surface-derived MHCII into peripheral degradative compartments

In order to mount high-affinity antibody responses, B cells internalise specific antigens and process them into peptides loaded onto MHCII for presentation to T helper cells (TH cells). While the biochemical principles of antigen processing and MHCII loading have been well dissected, how the endosomal vesicle system is wired to enable these specific functions remains much less studied. Here, we performed a systematic microscopy-based analysis of antigen trafficking in B cells to reveal its route to the MHCII peptide-loading compartment (MIIC). Surprisingly, we detected fast targeting of internalised antigen into peripheral acidic compartments that possessed the hallmarks of the MIIC and also showed degradative capacity. In these vesicles, internalised antigen converged rapidly with membrane-derived MHCII and partially overlapped with cathepsin-S and H2-M, both required for peptide loading. These early compartments appeared heterogenous and atypical as they contained a mixture of both early and late endosomal markers, indicating a specialized endosomal route. Together, our data suggest that, in addition to in the previously reported perinuclear late endosomal MIICs, antigen processing and peptide loading could have already started in these specialized early peripheral acidic vesicles (eMIIC) to support fast peptide–MHCII presentation.</p

Humoral immunological kinetics of severe acute respiratory syndrome coronavirus 2 infection and diagnostic performance of serological assays for coronavirus disease 2019: an analysis of global reports

As the coronavirus disease 2019 (COVID-19) pandemic continues to rise and second waves are reported in some countries, serological test kits and strips are being considered to scale up an adequate laboratory response. This study provides an update on the kinetics of humoral immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and performance characteristics of serological protocols (lateral flow assay [LFA], chemiluminescence immunoassay [CLIA] and ELISA) used for evaluations of recent and past SARS-CoV-2 infection. A thorough and comprehensive review of suitable and eligible full-text articles was performed on PubMed, Scopus, Web of Science, Wordometer and medRxiv from 10 January to 16 July 2020. These articles were searched using the Medical Subject Headings terms 'COVID-19', 'Serological assay', 'Laboratory Diagnosis', 'Performance characteristics', 'POCT', 'LFA', 'CLIA', 'ELISA' and 'SARS-CoV-2'. Data from original research articles on SARS-CoV-2 antibody detection >= second day postinfection were included in this study. In total, there were 7938 published articles on humoral immune response and laboratory diagnosis of COVID-19. Of these, 74 were included in this study. The detection, peak and decline period of blood anti-SARS-CoV-2 IgM, IgG and total antibodies for point-of-care testing (POCT), ELISA and CLIA vary widely. The most promising of these assays for POCT detected anti-SARS-CoV-2 at day 3 postinfection and peaked on the 15th day; ELISA products detected anti-SARS-CoV-2 IgM and IgG at days 2 and 6 then peaked on the eighth day; and the most promising CLIA product detected anti-SARS-CoV-2 at day 1 and peaked on the 30th day. The most promising LFA, ELISA and CLIA that had the best performance characteristics were those targeting total SARS-CoV-2 antibodies followed by those targeting anti-SARS-CoV-2 IgG then IgM. Essentially, the CLIA-based SARS-CoV-2 tests had the best performance characteristics, followed by ELISA then POCT. Given the varied performance characteristics of all the serological assays, there is a need to continuously improve their detection thresholds, as well as to monitor and re-evaluate their performances to assure their significance and applicability for COVID-19 clinical and epidemiological purposes

Unemployment, Personality Traits, and the Use of Facebook

Different personality traits respond differently to unfavourable life situations. Unemployment can have several negative social, economic, and domestic consequences. Many people use social media for a variety of reasons. The aim of this study is to examine the way different personality traits respond to Facebook in the period of unemployment. Data was obtained from 3,002 unemployed respondents in Nigeria. The study used regression model to analyse the data. Among the five personality traits, results indicated that the relationship between neuroticism and online social support was negative. However, the relationship between online social support and satisfaction was positive. The study highlights several theoretical and practical implications.peerReviewe

Social Media Usage for Computing Education : The Effect of The Strength and Group Communication on Perceived Learning Outcome

Social media has become an important platform where users share, comment, discuss, communicate, interact, and play games. Aside from using social media for personal, social, and business purposes, the use of social media has gained attention, particularly for collaborative learning in the educational sector. This paper examines the role of social media in computing education based on the use of WhatsApp social media group. Additionally, the study explores how social media usage by students influences their perceived learning outcomes. Given these aims, the study formulated four research hypotheses and tested using Partial Least Square Structural Equation Modelling. With the participants of three hundred and thirteen (n=313) students, the study found a positive relationship between social media usage for computing education and perceived learning outcomes. In addition, the study found a linear relationship between communication in- group and perceived learning outcomes. Finally, the study revealed that social media positively relates to tie strength, and that tie strength influences in-group communication.peerReviewe

Unemployment, personality traits, and the use of Facebook does online social support influence continuous use?

Abstract Different personality traits respond differently to unfavourable life situations. Unemployment can have several negative social, economic, and domestic consequences. Many people use social media for a variety of reasons. The aim of this study is to examine the way different personality traits respond to Facebook in the period of unemployment. Data was obtained from 3,002 unemployed respondents in Nigeria. The study used regression model to analyse the data. Among the five personality traits, results indicated that the relationship between neuroticism and online social support was negative. However, the relationship between online social support and satisfaction was positive. The study highlights several theoretical and practical implications

Social media usage for computing education:the effect of tie strength and group communication on perceived learning outcome

Abstract Social media has become an important platform where users share, comment, discuss, communicate, interact, and play games. Aside from using social media for personal, social, and business purposes, the use of social media has gained attention, particularly for collaborative learning in the educational sector. This paper examines the role of social media in computing education based on the use of WhatsApp social media group. Additionally, the study explores how social media usage by students influences their perceived learning outcomes. Given these aims, the study formulated four research hypotheses and tested using Partial Least Square Structural Equation Modelling. With the participants of three hundred and thirteen (n=313) students, the study found a positive relationship between social media usage for computing education and perceived learning outcomes. In addition, the study found a linear relationship between communication ingroup and perceived learning outcomes. Finally, the study revealed that social media positively relates to tie strength, and that tie strength influences in-group communication