Transposon Screen of Surface Accessibility in S. aureus

Bacterial cell walls represent one of the most prominent targets of antibacterial agents. These agents include natural products (e.g., vancomycin) and proteins stemming from the innate immune system (e.g., peptidoglycan-recognition proteins and lysostaphin). Among bacterial pathogens that infect humans, Staphylococcus aureus (S. aureus) continues to impose a tremendous healthcare burden across the globe. S. aureus has evolved countermeasures that can directly restrict the accessibility of innate immune proteins, effectively protecting itself from threats that target key cell well components. We recently described a novel assay that directly reports on the accessibility of molecules to the peptidoglycan layer within the bacterial cell wall of S. aureus. The assay relies on site-specific chemical remodeling of the peptidoglycan with a biorthogonal handle. Here, we disclose the application of our assay to a screen of a nonredundant transposon mutant library for susceptibility of the peptidoglycan layer with the goal of identifying genes that contribute to the control of cell surface accessibility. We discovered several genes that resulted in higher accessibility levels to the peptidoglycan layer and showed that these genes modulate sensitivity to lysostaphin. These results indicate that this assay platform can be leveraged to gain further insight into the biology of bacterial cell surfaces.Table of Contents Figure

Bioinformatics analysis of epitope-based vaccine design against the novel SARS-CoV-2

Background An outbreak of infection caused by SARS-CoV-2 recently has brought a great challenge to public health. Rapid identification of immune epitopes would be an efficient way to screen the candidates for vaccine development at the time of pandemic. This study aimed to predict the protective epitopes with bioinformatics methods and resources for vaccine development. Methods The genome sequence and protein sequences of SARS-CoV-2 were retrieved from the National Center for Biotechnology Information (NCBI) database. ABCpred and BepiPred servers were utilized for sequential B-cell epitope analysis. Discontinuous B-cell epitopes were predicted via DiscoTope 2.0 program. IEDB server was utilized for HLA-1 and HLA-2 binding peptides computation. Surface accessibility, antigenicity, and other important features of forecasted epitopes were characterized for immunogen potential evaluation. Results A total of 63 sequential B-cell epitopes on spike protein were predicted and 4 peptides (Spike315–324, Spike333–338, Spike648–663, Spike1064–1079) exhibited high antigenicity score and good surface accessibility. Ten residues within spike protein (Gly496, Glu498, Pro499, Thr500, Leu1141, Gln1142, Pro1143, Glu1144, Leu1145, Asp1146) are forecasted as components of discontinuous B-cell epitopes. The bioinformatics analysis of HLA binding peptides within nucleocapsid protein produced 81 and 64 peptides being able to bind MHC class I and MHC class II molecules respectively. The peptides (Nucleocapsid66–75, Nucleocapsid104–112) were predicted to bind a wide spectrum of both HLA-1 and HLA-2 molecules. Conclusions B-cell epitopes on spike protein and T-cell epitopes within nucleocapsid protein were identified and recommended for developing a protective vaccine against SARS-CoV-2.

Bioinformatics analysis of epitope-based vaccine design against the novel SARS-CoV-2

Background: An outbreak of infection caused by SARS-CoV-2 recently has brought a great challenge to public health. Rapid identification of immune epitopes would be an efficient way to screen the candidates for vaccine development at the time of pandemic. This study aimed to predict the protective epitopes with bioinformatics methods and resources for vaccine development. Methods : The genome sequence and protein sequences of SARS-CoV-2 were retrieved from the National Center for Biotechnology Information (NCBI) database. ABCpred and BepiPred servers were utilized for sequential B-cell epitope analysis. Discontinuous B-cell epitopes were predicted via DiscoTope 2.0 program. IEDB server was utilized for HLA-1 and HLA-2 binding peptides computation. Surface accessibility, antigenicity, and other important features of forecasted epitopes were characterized for immunogen potential evaluation. Results : A total of 63 sequential B-cell epitopes on spike protein were predicted and 4 peptides (Spike 315-324 , Spike 333-338 , Spike 648-663 , Spike 1064-1079 ) exhibited high antigenicity score and good surface accessibility. Ten residues within spike protein (Gly 496 , Glu 498 , Pro 499 , Thr 500 , Leu 1141 , Gln 1142 , Pro 1143 , Glu 1144 , Leu 1145 , Asp 1146 ) are forecasted as components of discontinuous B-cell epitopes. The bioinformatics analysis of HLA binding peptides within nucleocapsid protein produced 81 and 64 peptides being able to bind MHC classⅠand MHC classⅡ molecules respectively. The peptides (Nucleocapsid 66-75 , Nucleocapsid 104-112 ) were predicted to bind a wide spectrum of both HLA-1 and HLA-2 molecules. Conclusions : B-cell epitopes on spike protein and T-cell epitopes within nucleocapsid protein were identified and recommended for developing a protective vaccine against SARS-CoV-2.

Bioinformatics analysis of epitope-based vaccine design against the novel SARS-CoV-2

Background: An outbreak of infection caused by SARS-CoV-2 recently has brought a great challenge to public health. Rapid identification of immune epitopes would be an efficient way to screen the candidates for vaccine development at the time of pandemic. This study aimed to predict the protective epitopes with bioinformatics methods and resources for vaccine development. Methods : ABCpred and BepiPred servers were utilized for sequential B-cell epitope analysis. Discontinuous B-cell epitopes were predicted via DiscoTope 2.0 program. IEDB server was utilized for HLA-1 and HLA-2 binding peptides computation. Surface accessibility, antigenicity, and other important features of forecasted epitopes were characterized for immunogen potential evaluation. Results : A total of 63 sequential B-cell epitopes on spike protein were predicted and 4 peptides (Spike 315-324 , Spike 333-338 , Spike 648-663 , Spike 1064-1079 ) exhibited high antigenicity score and good surface accessibility. 10 residues within spike protein (Gly 496 , Glu 498 , Pro 499 , Thr 500 , Leu 1141 , Gln 1142 , Pro 1143 , Glu 1144 , Leu 1145 , Asp 1146 ) are forecasted as components of discontinuous B-cell epitopes. The bioinformatics analysis of HLA binding peptides within nucleocapsid protein produced 81 and 64 peptides being able to bind MHC class I and MHC class II molecule respectively. The peptides (Nucleocapsid 66-75 , Nucleocapsid 104-112 ) were predicted to bind a wide spectrum of both HLA-1 and HLA-2 molecules. Conclusions : B-cell epitopes on spike protein and T-cell epitopes within nucleocapsid protein were identified and recommended for developing a protective vaccine against SARS-CoV-2.

Bioinformatics analysis of epitope-based vaccine design against the novel SARS-CoV-2

Background: An outbreak of infection caused by SARS-CoV-2 recently has brought a great challenge to public health. Rapid identification of immune epitopes would be an efficient way to screen the candidates for vaccine development at the time of pandemic. This study aimed to predict the protective epitopes with bioinformatics methods and resources for vaccine development. Methods: ABCpred and BepiPred servers were utilized for sequential B-cell epitope analysis. Discontinuous B-cell epitopes were predicted via DiscoTope 2.0 program. IEDB server was utilized for HLA-1 and HLA-2 binding peptides computation. Surface accessibility, antigenicity, and other important features of forecasted epitopes were characterized for immunogen potential evaluation. Results: A total of 63 sequential B-cell epitopes on spike protein were predicted and 4 peptides (Spike315-324, Spike333-338, Spike648-663, Spike1064-1079) exhibited high antigenicity score and good surface accessibility. 10 residues within spike protein (Gly496, Glu498, Pro499, Thr500, Leu1141, Gln1142, Pro1143, Glu1144, Leu1145, Asp1146) are forecasted as components of discontinuous B-cell epitopes. The bioinformatics analysis of HLA binding peptides within nucleocapsid protein produced 81 and 64 peptides being able to bind class-I and class-II molecule respectively. The peptides (Nucleocapsid66-75, Nucleocapsid104-112) were predicted to bind a wide spectrum of both HLA-1 and HLA-2 molecules. Conclusions: B-cell epitopes on spike protein and T-cell epitopes within nucleocapsid protein were identified and recommended for developing a protective vaccine against SARS-CoV-2.

Synthesis of Hierarchical Hetero-Junction Composite and Gas Detection Performance in Asphalt Road

In this work, we have triumphantly synthesized porous nanosheet-assembled ZnO/NiO hierarchical microflower via a one-step hydrothermal method. On this basis, a corresponding gas sensor was fabricated to detect its sensitivity to H2S gas. The results indicated that porous flower-like hierarchical structures hold favorable superiority in the gas sensing towards H2S as compared to ZnO/NiO nanosheets. The superior sensing behavior may correlate with the special architecture offering abundant reaction sites, rapid channels and surface accessibility for gas transportation. Besides, p–n heterojunction at their interface and strong catalysis of NiO also play an important role in the enhancement of sensing properties.

Computational Prediction of Multi-Epitopes Vaccine from Envelope E Protein against Louping Ill Virus via Reverse Vaccinology

Louping ill disease is a zoonotic viral disease caused by louping ill virus in the genus Flavivirus. It belongs to the tick-borne flavivirus that is a part of the tick-borne encephalitis virus complex.The envelope E protein of louping ill virus is the major structural protein that plays an important role in membrane binding and inducing a protective immune response.The aim of the present study was to design multi epitopes vaccine from the envelope E glycoprotein against louping ill virus using immunoinformatic tools that elicited humoral and cellular immunity. Eighteen envelope E protein sequences were retrieved from NCBI and subjected to various immunoinformatics tools from IEDB to assess their conservancy, surface accessibility and antigenicity as promising epitopes against B cells. The binding affinity of the conserved predicted epitopes was analyzed against MHC-I and MHC-II alleles of the T cells. The predicted epitopes were further assessed for their population coverage. For B-cell 25, 18 and 12 epitopes were predicted as linear conserved epitopes, surface accessibility and antigenic respectively. However, nine epitopes overlapped all the B cell prediction tools. Among them three epitopes (205-TAEHLP-210,336-KPCR-339 and 349-SPDV-352) were proposed as B cell epitopes. For T cell, 75 epitopes were found to interact with MHC-I alleles. The epitopes 130-YVYDANKV-138and356-MLITPNPTI-364 were proposed as a peptide vaccine since they interacted with the highest number of MHC-1 alleles.Moreover a total of 195core epitopes were found to interact with MHC-II alleles. The core epitopes 130-YVYDANKV-138, 219-WFNDLALPW-227, 415-VIGEHAWDF-423 and 462-VALAWLGLN-470 interacted with higher number of MHC-II alleles and proposed as vaccine since they demonstrated high affinity to MHC-II alleles.The population coverage epitopes set for MHC-I and MHC-II alleles was 74.69% and 99.98%, respectively. While the epitopes set for all T cell, proposed epitopes was 100%. Nine epitopes were predicted eliciting B and T cells and proposed as vaccine candidates against louping ill virus. However, these proposed epitopes require clinical trials studies to ensure their efficacy as vaccine candidates.