From the Origins of SARS-CoV-2 to the Correct Application of BLAST. TT -.

Basic local alignment search tool (BLAST) is one of the popular sequence similarity analysis tools. However, some students and researchers just blindly use the default parameters. Moreover, some students are confused about how to choose the right program. In a word, it is prone to be misused and researchers often draw conclusions incorrectly. In view of this, we traced back the internet hot topic in early 2020 - "MORDERATELY STRONG CONFIRMATION OF A LABORATORY ORIGIN OF COVID-19", and took it as teaching materials to guide the student to use BLAST currently through reanalyzing and reproducing the source of errors. Then we arranged an interesting experiment about fabricating dinosaur genes through modifying a chicken gene. In the experimental design to make the students grasp the BLAST tools better, one group fabricated the dinosaur gene and the other group decrypted the added bases. This instructional design could be conducive to cultivate students ' ability about distinguishing different viewpoints correctly, and we hope it can be enlightening and helpful to the teaching of BLAST tools.Copyright © 2022 by the authors.

A joint and simultaneous prediction framework of weekday and weekend daily-activity travel pattern using conditional dependency networks

Daily activity pattern (DAP) prediction models within the Activity-based Modelling paradigm are being currently developed without adequate consideration of the various interdependencies among activities within a multi-day planning horizon. We hereby propose a conditional dependency network structure based interdependent multilabel-multiclass classification framework for joint and simultaneous prediction of weekday and weekend DAP of an individual. The prime advantage of the proposed modelling framework is flexibility of application of any algorithm for parameter estimation. Random Forest Decision Tree (RFDT), eXtreme Gradient Boosting and Light Gradient Boosting Machine (LightGBM) as the base classifier and probabilistic and non-probabilistic inference approaches are explored for measuring their comparative performance to provide insights for future researchers. Several variables representing neighbourhood characteristics are also investigated as DAP de-terminants along with socio-economic characteristics of individuals for the first time.This model is estimated based on two-days (weekday and weekend) activity-travel diary of 1808 households (6521 individuals) in Bidhanangar Municipal Corporation, India. The non-probabilistic approach-based models are found to achieve higher accuracy (0.81-0.92) compared to probabilistic models (0.76 to 0.82). RFDT and LightGBM are found to be the best performers in the probabilistic and non-probabilistic frameworks respectively. External validation results show that all proposed multiday-interdependent models (80%-94%) perform better than independent models (64%-83%).This framework can be applied to other transportations planning problems like household interaction in ac-tivity generation, joint destination and mode choice. This is also one of the first attempts to investigate the determinants of DAPs of urban commuters in an emerging country like India.

WMSA 2: a multiple DNA/RNA sequence alignment tool implemented with accurate progressive mode and a fast win-win mode combining the center star and progressive strategies.

Multiple sequence alignment is widely used for sequence analysis, such as identifying important sites and phylogenetic analysis. Traditional methods, such as progressive alignment, are time-consuming. To address this issue, we introduce StarTree, a novel method to fast construct a guide tree by combining sequence clustering and hierarchical clustering. Furthermore, we develop a new heuristic similar region detection algorithm using the FM-index and apply the k-banded dynamic program to the profile alignment. We also introduce a win-win alignment algorithm that applies the central star strategy within the clusters to fast the alignment process, then uses the progressive strategy to align the central-aligned profiles, guaranteeing the final alignment's accuracy. We present WMSA 2 based on these improvements and compare the speed and accuracy with other popular methods. The results show that the guide tree made by the StarTree clustering method can lead to better accuracy than that of PartTree while consuming less time and memory than that of UPGMA and mBed methods on datasets with thousands of sequences. During the alignment of simulated data sets, WMSA 2 can consume less time and memory while ranking at the top of Q and TC scores. The WMSA 2 is still better at the time, and memory efficiency on the real datasets and ranks at the top on the average sum of pairs score. For the alignment of 1 million SARS-CoV-2 genomes, the win-win mode of WMSA 2 significantly decreased the consumption time than the former version. The source code and data are available at https://github.com/malabz/WMSA2.

Whole genome sequence analyses of Indonesian isolates SARS-CoV-2 variants and their clinical manifestations

The SARS-CoV-2 virus has been the cause of the global pandemic since the end of 2019. Since then, the virus has mutated to create different types of variants with numerous effects on those infected. This has complicated human intervention for prevention. Indonesia was heavily affected by the pandemic, specifically from May to August 2021, and as a country has recorded many distinct isolates. Thus, characterization of the virus strains from Indonesia is important. GISAID, NCBI BLAST, and MAFFT version 7 were used. There were 9,488 isolates in Indonesia as of November 2021, with the majority including the Delta variant. While most of the isolates have mutations common to those from other countries, there are some atypical ones, such as mutation V1264L in the Delta variant that was suspected to play a role in worsening the pandemic. The Delta variant had the most mutations in the spike protein when compared to the Alpha and Beta variants, giving it important roles in infectivity and vigorous entry into cells, with some general clinical manifestations like fever and sore throat;however, the severity of the Delta variant is attributable to its rapid growth. This is why, from May to November 2021 in Indonesia, cases of the Delta variant rocketed, unlike the other variants. Copyright © 2023 THE AUTHOR(S).

Chemi-Informatic Approach to Investigate Putative Pharmacoactive Agents of Plant Origin to Eradicate COVID-19

Background: The scientific community has supported the medicinal flora of ancient as well as modern times in extracting chemicals, which holds therapeutic potential. In many previous studies, Amentoflavone discovered as an anti-viral agent, and it is present as a bioactive constituent in many plants of different families like Selaginellaceae, Euphorbiaceae, and Calophyllaceae. Withania somnifera (Ashwagandha) is already considered a significant anti-viral agent in traditional medicine, and it is the main source of Somniferine-A and Withanolide-B. Objective(s): In this study, phytochemicals such as withanolide-b, somniferine-a, stigmasterol, amentoflavone, and chavicine were analyzed to screen protein inhibitors, out of them;such proteins are involved in the internalization and interaction of SARS-CoV-2 with human cytological domains. This will help in developing a checkpoint for SARS-CoV-2 internalization. Method(s): Chemi-informatic tools like basic local alignment search tool (BLAST), AutoDock-vina, SwissADME, MDWeb, Molsoft, ProTox-II, and LigPlot were used to examine the action of pharmacoactive agents against SARS-CoV-2. The tools used in the study were based on the finest algorithms like artificial neural networking, machine learning, and artificial intelligence. Result(s): On the basis of binding energies less than equal to-8.5 kcal/mol, amentoflavone, stigmasterol, and somniferine-A were found to be the most effective against COVID-19 disease as these chemical agents exhibit hydrogen bond interactions and competitively inhibit major proteins (SARS-CoV-2 Spike, Human ACE-2 receptor, Human Furin protease, SARS-CoV-2 RNA binding protein) that are involved in its infection and pathogenesis. Simulation analysis provides more validity to the selection of the drug candidate Amentoflavone. ADMET properties were found to be in the feasible range for putative drug candidates. Conclusion(s): Computational analysis was successfully used for searching pharmacoactive phytochemicals like Amentoflavone, Somniferine-A, and Stigmasterol that can bring control over COVID-19 expansion. This new methodology was found to be efficient, as it reduces monetary expenditures and time consumption. Molecular wet-lab validations will provide approval for finalizing our selected drug model for controlling the COVID-19 pandemic.Copyright © 2022 Bentham Science Publishers.

Genetic conservation across SARS-CoV-2 non-structural proteins - Insights into possible targets for treatment of future viral outbreaks.

The majority of SARS-CoV-2 therapeutic development work has focussed on targeting the spike protein, viral polymerase and proteases. As the pandemic progressed, many studies reported that these proteins are prone to high levels of mutation and can become drug resistant. Thus, it is necessary to not only target other viral proteins such as the non-structural proteins (NSPs) but to also target the most conserved residues of these proteins. In order to understand the level of conservation among these viruses, in this review, we have focussed on the conservation across RNA viruses, conservation across the coronaviruses and then narrowed our focus to conservation of NSPs across coronaviruses. We have also discussed the various treatment options for SARS-CoV-2 infection. A synergistic melding of bioinformatics, computer-aided drug-design and in vitro/vivo studies can feed into better understanding of the virus and therefore help in the development of small molecule inhibitors against the viral proteins.

Detection of human adenovirus F41 in wastewater and its relationship to clinical cases of acute hepatitis of unknown aetiology

As of 8 July 2022, the World Health Organization (WHO) have reported 1010 probable cases of acute hepatitis of unknown aetiology in children worldwide, including approximately 250 cases in the United Kingdom (UK). Clinical presentations have often been severe, with liver transplantation a frequent clinical outcome. Human adenovirus F41 (HAdV-F41) has been detected in most children with acute hepatitis, but its role in the pathogenesis of this infection has yet to be established. Wastewater-based epidemiology (WBE) has become a well-established tool for monitoring the community spread of SARS-CoV-2, as well as other pathogens and chemicals. In this study, we adopted a WBE approach to monitoring levels of HAdV-F40/41 in wastewater before and during an acute hepatitis outbreak in Northern Ireland. We report increasing detection of HAdV-F40/41 in wastewater, concomitant with increasing numbers of clinical cases. Amplicon whole genome sequencing further classified the wastewater-derived HAdV as belonging to the F41 genotype which in turn was homologous to clinically derived sequences. We propose that WBE has the potential to inform community surveillance of HAdV-F41 and can further contribute to the ongoing global discussion supporting HAdV-F41 involvement in acute hepatitis cases. © 2022 The Authors

AFMC: An alignment framework for multiple computing services and providers

The Hirschberg algorithm is commonly used for protein sequence alignment, which is a very important task in bioinformatics. This article presents the AFMC framework for using the Hirschberg method to perform sequence alignment in multiple cloud computing services of different models, such as Infrastructure-as-a-Service and Function-as-a-Service (FaaS). Experiments were carried out in which several instances of AWS EC2, Azure VMs and Google Compute Engine as well as varied configurations of AWS Lambda, Azure Function, and Google Cloud Function were used to pairwise align COVID-19 spike proteins. The services were submitted to different levels of simultaneity to align the genetic sequences. The findings reveal that there is a tradeoff between predicted execution time and cost for this application, for example, FaaS-oriented cloud service models generally took less time to process the workloads. On the other hand, it was observed that, as the level of concurrence increased, there was a marked augmentation in cost. In this context, a framework that provides multi cloud solutions for bioinformatics such as AFMC is essential. © 2023 John Wiley & Sons, Ltd.

Computational tools for aptamer identification and optimization

Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the procedure is challenging and time-consuming. Moreover, the identified aptamers tend to be insufficient in stability, specificity, and affinity. Thus, only a handful of aptamers have entered the practical use stage. Recently, computational approaches have demonstrated a significant capacity to assist in the discovery of high-performance aptamers. This review discusses the advances achieved in several aspects of computational tools in this field, as well as the new progress in machine learning and deep learning, which are used in aptamer identification and optimization. To illustrate these computationally aided processes, aptamer selections against SARS-CoV-2 are discussed in detail as a case study. We hope that this review will aid and motivate researchers to develop and utilize more computational techniques to discover ideal aptamers effectively. Copyright © 2022 Elsevier B.V.

Analyzing Kinship in Severe Acute Respiratory Syndrome Coronavirus 2 DNA Sequences Based on Hierarchical and K-Means Clustering Methods Using Multiple Encoding Vector

Based on the World Health Organization data obtained in mid-April 2021, Coronavirus or Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has already infected more than 134.9 million people worldwide. The virus attacks human breathing, which can cause lung infections and even death. More than 2.9 million people worldwide have died due to coronavirus infection. Meanwhile, more than 1.5 million people in Indonesia have been infected, and 42.5 thousand died because of this coronavirus. Based on this data, carrying out a kinship analysis of the coronavirus is important to reduce its spread. Identifying the kinship of the COVID-19 virus and its spread can be done by forming a phylogenetic tree and clustering. This study uses the Multiple Encoding Vector method in analyzing the sequences and Euclidean distance to determine the distance matrix. This research will then use the Hierarchical clustering method to determine the number of initial centroids, which will be used later by the K-Means clustering method kinship in the SARS-CoV-2 DNA sequence. This study took samples of DNA sequences of SARS-CoV-2 from several infected countries. From the simulation results, the ancestors of SARS-CoV-2 came from China. The analysis results also show that the closest ancestors of COVID-19 to Indonesia came from India. The SARS-CoV-2 DNA sequence also consisted of nine clusters, and the sixth cluster has the greatest number of members. © IJASEIT is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.

Propagation research of SARS-CoV-2 based on evolutionary tree and spectral clustering

RNA viruses have the characteristics of a high mutation rate. New Coronavirus (SARS-CoV-2), as a RNA virus, has been mutated to some extent since the outbreak of New Coronavirus pneumonia (COVID-19). It is of great significance to study the evolution and variation of novel coronavirus genes to analyze the source of virus infection and understand the evolution of viruses. This research is based on the Novel Coronavirus 2019 database at the National Genomics Data Center. We combined macro and micro. We used the phylogenetic tree to analyze the gene fragments of the virus, constructed an evolutionary tree with a depth of 301, searched the root node of the tree to find the source of the virus in the data set and used spectral clustering to analyze the degree of novel Coronavirus variation in each country and the clustering results were visualized to make them easier to observe. The experimental results show that the strain sample at the top of the evolutionary tree originated in New Zealand based on the existing data. In the evolutionary tree, the evolutionary process of the virus can be divided into three branches. After clustering the virus source data and constructing the visual map of the variation degree of SARS-COV-2, we found that the viruses in South Africa, New Zealand and other countries had a higher degree of variation, and the viruses in Australia, the United States and other countries have a relatively lower degree of virus variation. © 2022 IEEE.

Development of functional anti-Gn nanobodies specific for SFTSV based on next-generation sequencing and proteomics.

Severe fever with thrombocytopenia syndrome (SFTS) is an acute infectious disease caused by novel bunyavirus (SFTSV), with a mortality rate of 6.3% ~ 30%. To date, there is no specific treatment for SFTS. Previously, we demonstrated that SFTSV surface glycoprotein (Glycoprotein N, Gn) was a potential target for the development of SFTS vaccine or therapeutic antibodies, and anti-Gn neutralizing antibodies played a protective role in SFTS infection. Compared with traditional antibodies, nanobodies from camelids have various advantages, including small molecular weight, high affinity, low immunogenicity, convenient production by gene engineering, etc. In this study, we combined next-generation sequencing (NGS) with proteomics technology based on affinity purification-mass spectrometry (AP-MS) and bioinformatics analysis to high-throughput screen monoclonal anti-Gn nanobodies from camel immunized with Gn protein. We identified 19 anti-Gn monoclonal nanobody sequences, of which six sequences were selected for recombinant protein expression and purification. Among these six anti-Gn nanobodies, nanobody 57,493 was validated to be highly specific for Gn. The innovative high-throughput technical route developed in this study could also be expanded to the production of nanobodies specific for other viruses like SARS-CoV-2.

Mutation Pattern in the Receptor Binding Motif of SARS-Cov-2 Variants and the Effect on Molecular Interactions in Docked Ligand Complexes

The spike glycoprotein of SARS-Cov-2 is a therapeutic target for Covid-19 and mutations in the Receptor Binding Motif (RBM) may alter the binding properties of ligands proposed to inhibit viral entry. This study aimed to identify the existence of a mutation pattern in the RBMs of SARS-Cov-2 variants and study the effect on ligand binding interactions. RBM sequences were obtained using NCBI BLASTP and subjected to multiple and pairwise sequence alignment analysis. Hypothetical generations were drawn from the phylogenetic tree. The effect of mutation on ligand binding was studied by docking zafirlukast on selected RBMs. Molecular dynamics simulations were conducted to explain molecular interactions. The sequences at the same phylogenetic level showed higher similarity with the observed differences defined by the crystallized chain length. 6XDG_E, a leaf node sequence was 76% similar to 7NXA_E, a branch from the root, and had the highest mutation. Differences in sequence similarity across successive generations were based on mutations and crystallized chain length and the amino acid substitution is not predictable. Different bond types and binding affinities were observed as well as varying Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and Region of Gyration (RoG) values for the RBMs in different variants. The RMSD, RMSF, and RoG did not differ significantly in the bound and free states of RBM from specific variants suggesting that the observed differences are attributable to amino acid substitutions. This information is crucial for drug development intended to block SARS-Cov-2 entry.

SARS-Arena: Sequence and Structure-Guided Selection of Conserved Peptides from SARS-related Coronaviruses for Novel Vaccine Development.

The pandemic caused by the SARS-CoV-2 virus, the agent responsible for the COVID-19 disease, has affected millions of people worldwide. There is constant search for new therapies to either prevent or mitigate the disease. Fortunately, we have observed the successful development of multiple vaccines. Most of them are focused on one viral envelope protein, the spike protein. However, such focused approaches may contribute for the rise of new variants, fueled by the constant selection pressure on envelope proteins, and the widespread dispersion of coronaviruses in nature. Therefore, it is important to examine other proteins, preferentially those that are less susceptible to selection pressure, such as the nucleocapsid (N) protein. Even though the N protein is less accessible to humoral response, peptides from its conserved regions can be presented by class I Human Leukocyte Antigen (HLA) molecules, eliciting an immune response mediated by T-cells. Given the increased number of protein sequences deposited in biological databases daily and the N protein conservation among viral strains, computational methods can be leveraged to discover potential new targets for SARS-CoV-2 and SARS-CoV-related viruses. Here we developed SARS-Arena, a user-friendly computational pipeline that can be used by practitioners of different levels of expertise for novel vaccine development. SARS-Arena combines sequence-based methods and structure-based analyses to (i) perform multiple sequence alignment (MSA) of SARS-CoV-related N protein sequences, (ii) recover candidate peptides of different lengths from conserved protein regions, and (iii) model the 3D structure of the conserved peptides in the context of different HLAs. We present two main Jupyter Notebook workflows that can help in the identification of new T-cell targets against SARS-CoV viruses. In fact, in a cross-reactive case study, our workflows identified a conserved N protein peptide (SPRWYFYYL) recognized by CD8+ T-cells in the context of HLA-B7+. SARS-Arena is available at https://github.com/KavrakiLab/SARS-Arena.

Genomic and phylogenetic analysis of the ORF7b gene from a Chinese feline infectious peritonitis virus isolate

FCoV viruses exhibit great genetic diversity, leading to the presence of FIPV-causing variants. Current molecular evolution analysis and genetic variation studies of FCoV in China are predominately focused on gene encoding the spike protein or other structural proteins, while few studies have evaluated genetic variations in nonstructural FCoV genes, which can play an important role in disease pathogenesis. In this study, the gene encoding the open reading frame (ORF) 7b nonstructural FCoV protein of the Chinese Fujian strain FJLY20201 was amplified from the ascitic fluid of a Chinese domestic cat infected with FIPV and compared with ORF 7b from previously published FCoV strains. Multiple sequence alignment revealed that FJLY20201 exhibited high identity with other Chinese FCoV strains. Phylogenetic analyses indicated that the Chinese strains did not differentiate between type I and type II serotypes of FCoV based on S proteins. In addition, they formed clades and differed genetically from strains originating outside China. This study provides the molecular epidemiology data about the ORF 7b genes of FCoV strains in China. Our results show that the identity of ORF 7b genes was closer between the Chinese isolates, and suggest that variation in ORF 7b is more dependent on geographical origin.

Highly Conserve Sequences in Envelope, Nucleoprotein and RNA-Dependent RNA Polymerase of SARS-CoV-2 in Nasopharyngeal Samples of the COVID-19 Patients;a Diagnostic Target for Further Studies

Background: The etiological agent of coronavirus diseases 2019 (COVID-19) is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Conventional molecular methods are used to detect viruses in COVID-19 infected patients. This study aimed to investigate escape mutations from molecular detection on SARS-CoV-2 targeted genes, which indicates the importance of mutations in false-negative PCR test results in the detection of virus in clinical specimens of patients with COVID-19. Materials and Methods: The 20 nasopharyngeal swabs samples collected from COVID-19 confirmed patients. The SARS-CoV-2 E, nsp12, and N genetic regions are amplified by RT-PCR assay. PCR products were sequenced using the Sanger sequencing method and Multiple sequence alignment (MSA) to assess the polymorphism and mutations performed using MEGA X software and the Maximum likelihood method for the phylogenetic evaluation. Results: Among all COVID-19 cases, 60% and 40% were male and female, respectively. The MSA showed high conservation between all evaluated samples and VOCs in all N, E, and nsp12 genes. Also, the phylogenetic evaluation by the Maximum likelihood method reported high similarity between all SARS-CoV-2 sequenced samples, VOCs, and Wuhan reference sequences in the evaluated region. Conclusion: Our study results approved the relatively conserved suitability of the E, N, and RdRp-gene regions with no diversity, therefore, making them perfect candidates for first-line screening.

Structure-function relationships among selected human coronaviruses

Identifying the key proteins among different types of human disease-causing coronaviruses is essential for the molecular mechanism and thereby designing potential drug molecules. Eight selected proteins of seven types of disease-causing coronaviruses, viz.SARS-CoV-2 (severe acute respiratory syndrome coronavirus2), SARS-CoV (severe acute respiratory syndrome coronavirus), MERS-CoV (middle east respiratory syndrome coronavirus), Human coronavirus OC43, Human coronavirus HKU1, Human coronavirus 229E and Human coronavirus NL63, were chosen for the comparison. Further, an attempt has been made to explore the most important host-pathogen interactions with a special focus on spike (RBD) protein region as this region deemed to be functionally most important. Epitope region was also identified which helps in the design of epitope-based vaccines. The structural comparison carried out among the seven types of human coronaviruses has revealed the molecular level details on the similarity among this series. This study has facilitated the identification of the important residues in the studied proteins which control the key functions such as viral replication and transmission. Thus, exploring the protein space in the family of coronaviruses, provide valuable insights into the molecular basis associated with the role of proteins and viral infections, which is expected to trigger the identification of the drug targets for coronaviruses infections, in a rational way.

Reviewing findings on the polypeptide sequence of the SARS-CoV-2 S-protein to discuss the origins of the virus.

Several investigations suggested origins of SARS-CoV-2 from the recombination of coronaviruses of various animals, including the bat Rhinolophus affinis and the pangolin Manis javanica, despite the processes describing the adaptation from a reservoir of animals to human are still debated. In this perspective, I will remark two main inconsistencies on the origins of SARS-CoV-2: polypeptide sequence alignment of the S-proteins does not return the expected identity of the receptor-binding motif among most of pangolin-CoVs and SARS-CoV-2; accurate referencing for samplings and sequencing deposition of the ancestral bat coronavirus named RaTG13 was missing since the first reports on the SARS-CoV-2 coronavirus. This contribution aims to stimulate discussion about the origins of SARS-CoV-2 and considers other intermediate hosts as a reservoir for coronavirus.

SPIKE MUTATION T403R ALLOWS BAT CORONAVIRUS RaTG13 to USE HUMAN ACE2

Background: The bat coronavirus RaTG13 shares 96% sequence identity to SARS-CoV-2, the causative agent of the COVID-19 pandemic. However, the RaTG13 Spike (S) protein interacts only weakly with the human SCoV-2 receptor Angiotensin-converting Enzyme 2 (ACE2) and does not mediate efficient infection of human cells. Here, we examined which alterations are required to allow the RaTG13 S protein to use human ACE2 for efficient entry into human cells. Methods: Sequence alignments showed that SARS-CoV-2 almost invariantly encodes a positively charged amino acid at position 403 of its S protein, while RaTG13 has a neutral Threonine (T). REAX based computational modeling suggested that S R403 contributes to binding of human ACE2. Wild-type and T403R mutant RaTG13 S proteins were investigated for their ability to bind ACE2 and to mediate infection of pseudotyped VSV particles in human lung-and intestine-derived cell lines as well as hPSC-derived gut organoids. Replication-competent recombinant SCoV2 S R403T was produced and replication monitored. In addition, we mutated human ACE2 to map the interacting residue of S R403. Finally, sera of vaccinated individuals were analyzed for their neutralizing potential against various WT CoV and RaTG13 S as well as mutant S containing pseudoparticles. Results: Our results show that a single amino acid change of T403R allows the RaTG13 S to utilize human ACE2 for viral entry. Spike T403R enhanced infection of VSV-based RatG13 S pseudotypes in human lung and colon cells as well as gut-derived organoids. Vice versa R403T mutation reduced infectivity of SCoV2 S pseudotypes and recombinant SCoV2 replication. The enhancing effect of T403R in RaTG13 S depends on E37 in ACE2. RaTG13 T403R S-mediated infection was blocked by the fusion inhibitor EK-1 but not by the SCoV-2 antibody Casirivimab. SARS-CoV-2 and the T403R RaTG13 S were equally susceptible to neutralization by sera from individuals vaccinated against COVID-19. Conclusion: A positively charged amino acid at position 403 in the S protein of bat coronaviruses is critical for efficient utilization of human ACE2. Our results help to better assess the zoonotic potential of bat sarbecoviruses and suggest that COVID-19 vaccination will also protect against closely bat relatives of SARS-CoV-2 that may emerge in the future.

From the Origins of SARS-CoV-2 to the Correct Application of BLAST

Basic local alignment search tool (BLAST) is one of the popular sequence similarity analysis tools. However, some students and researchers just blindly use the default parameters. Moreover, some students are confused about how to choose the right program. In a word, it is prone to be misused and researchers often draw conclusions incorrectly. In view of this, we traced back the internet hot topic in early 2020 - "MORDERATELY STRONG CONFIRMATION OF A LABORATORY ORIGIN OF COVID-19", and took it as teaching materials to guide the student to use BLAST currently through reanalyzing and reproducing the source of errors. Then we arranged an interesting experiment about fabricating dinosaur genes through modifying a chicken gene. In the experimental design to make the students grasp the BLAST tools better, one group fabricated the dinosaur gene and the other group decrypted the added bases. This instructional design could be conducive to cultivate students ' ability about distinguishing different viewpoints correctly, and we hope it can be enlightening and helpful to the teaching of BLAST tools. © 2022 by the authors.