This article is devoted to applying bioinformatics and immunoinformatics approaches for the development of a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. The study’s relevance is dictated by the fact that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began its global threat at the end of 2019 and since then has had a devastating impact on the whole world. Measures to reduce threats from the pandemic include social restrictions, restrictions on international travel, and vaccine development. In most cases, vaccine development depends on the spike glycoprotein, which serves as a medium for its entry into host cells. Although several variants of SARS-CoV-2 have emerged from mutations crossing continental boundaries, about 6000 delta variants have been reported along the coast of more than 20 countries in Africa, with South Africa accounting for the highest percentage. This also applies to the omicron variant of the SARS-CoV-2 virus in South Africa. The authors suggest that bioinformatics and immunoinformatics approaches be used to develop a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. Various immunoinformatics tools have been used to predict T- and B-lymphocyte epitopes. The epitopes were further subjected to multiple evaluations to select epitopes that could elicit a sustained immunological response. The candidate vaccine consisted of seven epitopes, a highly immunogenic adjuvant, an MHC I-targeting domain (MITD), a signal peptide, and linkers. The molecular weight (MW) was predicted to be 223.1 kDa, well above the acceptable threshold of 110 kDa on an excellent vaccine candidate. In addition, the results showed that the candidate vaccine was antigenic, non-allergenic, non-toxic, thermostable, and hydrophilic. The vaccine candidate has good population coverage, with the highest range in East Africa (80.44%) followed by South Africa (77.23%). West Africa and North Africa have 76.65% and 76.13%, respectively, while Central Africa (75.64%) has minimal coverage. Among seven epitopes, no mutations were observed in 100 randomly selected SARS-CoV-2 spike glycoproteins in the study area. Evaluation of the secondary structure of the vaccine constructs revealed a stabilized structure showing 36.44% alpha-helices, 20.45% drawn filaments, and 33.38% random helices. Molecular docking of the TLR4 vaccine showed that the simulated vaccine has a high binding affinity for TLR-4, reflecting its ability to stimulate the innate and adaptive immune response.

Food and water‐borne enterohemorrhagic Escherichia coli (EHEC) serotype O157:H7 is a zoonotic bacterium that causes gastroenteritis and other human diseases. It has also been linked to chronic foodborne diseases with high mortality rates worldwide, particularly in children. Hence, this study was carried out to designed a peptide base kit for quick detection of E. coli in food. A peptide‐based rapid detection kit was designed using an immunoinformatic technique and some antigenic target genes (stx1A, stx2B, escC, fliC, and eae). The antigenic gene sequences retrieved were screened for antigenicity, transmembrane topology, B‐cells and helper T‐cells. Selected epitopes were joined with appropriate linkers to form a chimeric protein which consists of five B‐cell epitopes, five interleukin‐4 (IL‐4) inducer epitopes and five interleukin‐10 (IL‐10) inducer epitopes. The improved and optimized chimeric protein sequence was cloned in‐silico in a suitable expression host, E. coli‐strain K12. The designed peptide refined and validated tertiary structure was molecularly docked with the tertiary structures of each antigenic target gene. The physicochemical properties of the chimeric protein showed that the construct has an amino acid length of 295 amino acids, a molecular weight of 29.876 kiloDalton (kDa), an aliphatic index of 75.05 and an instability index of 14.82 which confers stability. The construct was hydrophilic with a GRAVY value of −0.261 and had a considerable half‐life of 4.4 h (mammalian reticulocytes, in vitro), >20 h (yeast, in vivo) and >10 h (E. coli, in vivo). Conclusively, the final construct has successfully met the design requirements for the development of a lateral flow kit, which has the potential to provide fast and efficient detection of E. coli O157:H7. However, it is the additional validation through the vitro and in vivo techniques needed to confirm that this designed peptide based test kit.

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Chlamydia trachomatis, a major cause of sexually transmitted infection, poses a range of symptoms including genital discharge, pain during urination, and abdominal pains in women, and can lead to serious health complications such as pelvic inflammatory diseases, infertility, and ectopic pregnancy if left untreated. The need for rapid and accurate detection is imperative so prompt treatment and control of the disease can be achieved. This study conducted an immunoinformatic analysis of proteins of Chlamydia trachomatis (incA, hctA, ompA, omcB, rpoB, and HSP60) for the development of a lateral flow assay-based diagnostic test. Detailed in silico evaluation of selected proteins from publicly available genomic databases was conducted to evaluate their suitability as targets for lateral flow assay-based detection. The series of tests included antigenicity, toxicity, solubility, physicochemical characteristics and molecular docking of the derived constructs, and protein sequence. Chimeric construct was derived from the prediction of linear B cell epitopes, helper T cell major histocompatibility complex II binding epitopes, and IL4 and IL10 inducers using bioinformatic tools at standard thresholds. With a Ramachandra’s score of 95.4% and Z-score of -5.1, results indicate that the construct efficacy is high in potential to provide extreme specificity and sensitivity for the detection of Chlamydia trachomatis in clinical samples as compared to traditional culture-based methods using nucleic acid amplification, hereby providing a quicker and more accurate diagnostic tool for Chlamydia trachomatis infection. Findings offer valuable data for the development of a rapid and reliable diagnostic point-of-care test kit for Chlamydia trachomatis that allows for drastic reduction in clinical wait time and treatment.

Chlamydia trachomatis, a major cause of sexually transmitted infection, poses a range of symptoms including genital discharge, pain during urination, and abdominal pains in women, and can lead to serious health complications such as pelvic inflammatory diseases, infertility, and ectopic pregnancy if left untreated. The need for rapid and accurate detection is imperative so prompt treatment and control of the disease can be achieved. This study conducted an immunoinformatic analysis of proteins of Chlamydia trachomatis (incA, hctA, ompA, omcB, rpoB, and HSP60) for the development of a lateral flow assay-based diagnostic test. Detailed in silico evaluation of selected proteins from publicly available genomic databases was conducted to evaluate their suitability as targets for lateral flow assay-based detection. The series of tests included antigenicity, toxicity, solubility, physicochemical characteristics and molecular docking of the derived constructs, and protein sequence. Chimeric construct was derived from the prediction of linear B cell epitopes, helper T cell major histocompatibility complex II binding epitopes, and IL4 and IL10 inducers using bioinformatic tools at standard thresholds. With a Ramachandra’s score of 95.4% and Z-score of -5.1, results indicate that the construct efficacy is high in potential to provide extreme specificity and sensitivity for the detection of Chlamydia trachomatis in clinical samples as compared to traditional culture-based methods using nucleic acid amplification, hereby providing a quicker and more accurate diagnostic tool for Chlamydia trachomatis infection. Findings offer valuable data for the development of a rapid and reliable diagnostic point-of-care test kit for Chlamydia trachomatis that allows for drastic reduction in clinical wait time and treatment.