Epitope-Based Immunoinformatic Approach on Heat Shock 70 kDa Protein Complex of Cryptococcus neoformans var. grubii

Design of a cryptococcus neoformans vaccine by subtractive proteomics combined with immunoinformatics

The emergence of Cryptococcus neoformans has posed an undeniable burden to many regions worldwide, with its strains mainly entering the lungs through the respiratory tract and spreading throughout the body. Limitations of drug regimens, such as high costs and limited options, have directed our attention toward the promising field of vaccine development. In this study, the subtractive proteomics approach was employed to select target proteins from databases that can accurately cover serotypes A and D of the Cryptococcus neoformans. Further, two multi-epitope vaccines consisting of T and B cell epitopes were demonstrated that they have good structural stability and could bind with immune receptor to induce desired immune responses in silico. After further evaluation, these vaccines show the potential for large-scale production and applicability to the majority of the population of the world. In summary, these two vaccines have been theoretically proven to combat Cryptococcus neoformans infections, awaiting further experimental validation of their actual protective effects.

A comprehensive immunoinformatic analysis of chitin deacetylase's and MP88 for designing multi-epitope vaccines against Cryptococcus neoformans

Cryptococcus neoformans causes life-threatening pneumonia and meningitis and is regarded as one of the leading killers of immunocompromised individuals. There is currently no vaccine against this pathogen. Recently, WHO placed it at the top among the critical priority groups in the fungal priority pathogens to accelerate the development of effective treatments. Numerous studies suggested the potential of subunit vaccines to overcome the challenges associated with live and inactivated whole-cell vaccines. Therefore, this study exploited integrated reverse vaccinology and immunoinformatic approach to construct and characterize multi-epitope vaccines targeting chitin deacetylases (Cda1, Cda2, Cda3) and MP88 of C. neoformans. 4 CTL, 8 HTL and 6 B cell epitopes were fused with different adjuvants and appropriate linkers to design two multi-epitope vaccines (VC1 and VC2). Both chimeric constructs were predicted to be highly antigenic, non-allergenic, non-toxic, soluble and had satisfactory physicochemical properties. Molecular docking and binding free energy calculation revealed strong binding interactions between vaccine constructs and human TLRs (TLR-2 and TLR-4). Classical MD Simulation and Normal mode analysis verified the stability of the vaccine-TLR complex in the biological environment. Codon adaptation, cloning and in silico expression suggested the efficient expression of recombinant vaccine proteins in E. coli. Both candidates also generated robust immune profiles comprising innate, adaptive and humoral immune responses. Taken together, experimental validations of our findings through extensive in vitro and in vivo testing might provide an effective vaccine for prophylactic control of C. neoformans.Communicated by Ramaswamy H. Sarma.

Fungal Vaccine Development: State of the Art and Perspectives Using Immunoinformatics

Fungal infections represent a serious global health problem, causing damage to health and the economy on the scale of millions. Although vaccines are the most effective therapeutic approach used to combat infectious agents, at the moment, no fungal vaccine has been approved for use in humans. However, the scientific community has been working hard to overcome this challenge. In this sense, we aim to describe here an update on the development of fungal vaccines and the progress of methodological and experimental immunotherapies against fungal infections. In addition, advances in immunoinformatic tools are described as an important aid by which to overcome the difficulty of achieving success in fungal vaccine development. In silico approaches are great options for the most important and difficult questions regarding the attainment of an efficient fungal vaccine. Here, we suggest how bioinformatic tools could contribute, considering the main challenges, to an effective fungal vaccine.

Production of monoclonal antibody of heat-labile toxin A subunit to identify enterotoxigenic Escherichia coli by epitope mapping using synthetic peptides

Background

Enterotoxigenic Escherichia coli (ETEC) is a major cause of diarrhea through two enterotoxins, a heat-labile toxin and a heat-stable toxin. These toxins alter the cellular signaling pathways, ultimately triggering an increase in chloride secretion and watery diarrhea.

Objective

For the development of an ETEC vaccine, we attempted to construct a peptide-specific monoclonal antibody library against heat-labile enterotoxin A subunit (LT-A) by epitope mapping using synthetic peptides.

Methods

Sera produced by five mice immunized with recombinant LT-A protein were examined for specific recognition with synthetic 15-mer and 34-mer peptides of LT-A proteins using enzyme-linked immunosorbent assay. The analysis revealed that the synthetic peptides number 8, 16, 24, 33, 36, 38, and 39 reacted with an anti-LT-A polyclonal antibody. For the possible prediction of LT-A epitopes, each full-length protein sequence was subjected to BCPreds analysis and three-dimensional protein structure analysis. The data showed that three peptides (synthetic peptide numbers: 33, 36, and 38-39) have identical antigenic specificities with LT-A protein, suggesting the usefulness of these linear peptide epitopes.

Results

Based on these peptides, we produced monoclonal antibodies to improve the specificity of LT-A detection. Monoclonal antibodies produced from two peptides (numbers 33 and 36) showed affinity for an LT-A recombinant antigen. Moreover, peptide epitope prediction analysis showed that the sites of the three peptides were identical to those exhibiting actual antigenicity. Also, it was confirmed that the amino acid sequence that actually showed antigenicity was included in the peptide predicted only by ETEC-LT-A-33. Also, the specificity of the antibody for ETEC-LT-A-33 was validated using bacterial cells, and the neutralizing effect of the antibody was determined by assessing cytokine release in infected HCT-8 cells.

Conclusion

The monoclonal antibodies produced in this study are useful toolsfor vaccine production against ETEC and can be used to identify peptide antigencandidates.

Adaptive immunology of Cryptococcus neoformans infections-an update

The fungal genus Cryptococcus comprises a group of pathogens with considerable phenotypic and genotypic diversity that can lead to cryptococcosis in both healthy and immunocompromised individuals. With the emergence of the HIV pandemic, cryptococcosis, mainly meningoencephalitis, afflicts HIV-infected patients with severe dysfunction of T cells. It has also been reported in recipients of solid organ transplantation and in patients with autoimmune diseases who take immunosuppressive agents long-term, as well as in those with unidentified immunodeficiency. The clinical outcome of the disease is primarily determined by the immune response resulting from the interplay between the host immune system and the pathogen. Most human infections are caused by Cryptococcus neoformans, and nearly all immunological studies have focused on C. neoformans. This review provides an updated understanding of the role of adaptive immunity during infection with C. neoformans in human and animal models over the past half-decade.

Utilizing Immunoinformatics to Target Brain Tumors; An Aid to Current Neurosurgical Practice

Context: Despite major advancements in the field, the current neurosurgical practice requires an interdisciplinary approach. It is known that surgical practice and other cancer-eliminating treatments can be combined for optimal results. However, recent attempts have failed to address many debilitating conditions, indicating an emergent need for novel interdisciplinary therapeutic approaches. Evidence Acquisition: We searched PubMed and Google Scholar for the keywords “immunoinformatics,” “in silico,” “neurology,” and “neurosurgery.” Without time restriction. Results: The immune system is versatile because it is involved in physiological brain function and affects the course of central nervous system (CNS) disease and infection. A novel approach combines neurosurgery and immunoinformatics for optimal results. For instance, brain tumors, such as glioblastoma multiforme (GBM), are still associated with a severely reduced survival of patients, and resection of tumors may provide little help. In silico approaches could help to identify molecular pathways and design immunotherapies for such conditions at a significantly increased speed compared to traditional vaccinology approaches. Conclusions: The neurosurgical practice could be affected by different infectious organisms. These organisms can be targeted by in silico vaccinology techniques. Here, we provide a brief overview of bioinformatics/immunoinformatics and discuss the possible role of immunoinformatics in neurosurgery. In light of the current Coronavirus disease-2019 (COVID-19) epidemic, projections for future studies are also included.