1
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Nguyen TL, Kim H. Integrating immunoinformatics and computational epitope prediction for a vaccine candidate against respiratory syncytial virus. Infect Dis Model 2024; 9:763-774. [PMID: 38708060 PMCID: PMC11068479 DOI: 10.1016/j.idm.2024.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/04/2024] [Accepted: 04/10/2024] [Indexed: 05/07/2024] Open
Abstract
Respiratory syncytial virus (RSV) poses a significant global health threat, especially affecting infants and the elderly. Addressing this, the present study proposes an innovative approach to vaccine design, utilizing immunoinformatics and computational strategies. We analyzed RSV's structural proteins across both subtypes A and B, identifying potential helper T lymphocyte, cytotoxic T lymphocyte, and linear B lymphocyte epitopes. Criteria such as antigenicity, allergenicity, toxicity, and cytokine-inducing potential were rigorously examined. Additionally, we evaluated the conservancy of these epitopes and their population coverage across various RSV strains. The comprehensive analysis identified six major histocompatibility complex class I (MHC-I) binding, five MHC-II binding, and three B-cell epitopes. These were integrated with suitable linkers and adjuvants to form the vaccine. Further, molecular docking and molecular dynamics simulations demonstrated stable interactions between the vaccine candidate and human Toll-like receptors (TLR4 and TLR5), with a notable preference for TLR4. Immune simulation analysis underscored the vaccine's potential to elicit a strong immune response. This study presents a promising RSV vaccine candidate and offers theoretical support, marking a significant advancement in vaccine development efforts. However, the promising in silico findings need to be further validated through additional in vivo studies.
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Affiliation(s)
- Truc Ly Nguyen
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Heebal Kim
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Republic of Korea
- eGnome, Inc., Seoul, 05836, Republic of Korea
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2
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Berger S, Seeger F, Yu TY, Aydin M, Yang H, Rosenblum D, Guenin-Macé L, Glassman C, Arguinchona L, Sniezek C, Blackstone A, Carter L, Ravichandran R, Ahlrichs M, Murphy M, Pultz IS, Kang A, Bera AK, Stewart L, Garcia KC, Naik S, Spangler JB, Beigel F, Siebeck M, Gropp R, Baker D. Preclinical proof of principle for orally delivered Th17 antagonist miniproteins. Cell 2024; 187:4305-4317.e18. [PMID: 38936360 PMCID: PMC11316638 DOI: 10.1016/j.cell.2024.05.052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 04/09/2024] [Accepted: 05/29/2024] [Indexed: 06/29/2024]
Abstract
Interleukin (IL)-23 and IL-17 are well-validated therapeutic targets in autoinflammatory diseases. Antibodies targeting IL-23 and IL-17 have shown clinical efficacy but are limited by high costs, safety risks, lack of sustained efficacy, and poor patient convenience as they require parenteral administration. Here, we present designed miniproteins inhibiting IL-23R and IL-17 with antibody-like, low picomolar affinities at a fraction of the molecular size. The minibinders potently block cell signaling in vitro and are extremely stable, enabling oral administration and low-cost manufacturing. The orally administered IL-23R minibinder shows efficacy better than a clinical anti-IL-23 antibody in mouse colitis and has a favorable pharmacokinetics (PK) and biodistribution profile in rats. This work demonstrates that orally administered de novo-designed minibinders can reach a therapeutic target past the gut epithelial barrier. With high potency, gut stability, and straightforward manufacturability, de novo-designed minibinders are a promising modality for oral biologics.
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Affiliation(s)
- Stephanie Berger
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA.
| | - Franziska Seeger
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Ta-Yi Yu
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA; Department of Bioengineering, University of Washington, Seattle, WA 98195, USA
| | - Merve Aydin
- Department of General, Visceral and Transplantation Surgery, LMU University Hospital, LMU Munich, 81377 Munich, Germany
| | - Huilin Yang
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, MD 21231, USA
| | - Daniel Rosenblum
- Department of Pathology, NYU Langone Health, New York, NY 10016, USA
| | - Laure Guenin-Macé
- Department of Pathology, NYU Langone Health, New York, NY 10016, USA; Immunobiology and Therapy Unit, INSERM U1224, Institut Pasteur, Paris 75015, France
| | - Caleb Glassman
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Lauren Arguinchona
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Catherine Sniezek
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Alyssa Blackstone
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Lauren Carter
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Rashmi Ravichandran
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Maggie Ahlrichs
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Michael Murphy
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | | | - Alex Kang
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Asim K Bera
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Lance Stewart
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - K Christopher Garcia
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94304, USA; Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94304, USA; Howard Hughes Medical Institute, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Shruti Naik
- Department of Pathology, NYU Langone Health, New York, NY 10016, USA; Department of Medicine, Ronald O. Perelman Department of Dermatology, Perlmutter Cancer Center, NYU Langone Health, New York, NY 10016, USA
| | - Jamie B Spangler
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, MD 21231, USA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Florian Beigel
- Department of Medicine II, LMU University Hospital, LMU Munich, 80336 Munich, Germany
| | - Matthias Siebeck
- Department of General, Visceral and Transplantation Surgery, LMU University Hospital, LMU Munich, 81377 Munich, Germany
| | - Roswitha Gropp
- Department of General, Visceral and Transplantation Surgery, LMU University Hospital, LMU Munich, 81377 Munich, Germany
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.
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3
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Stejskal L, Thistlethwaite A, Ramirez-Bencomo F, Rashmi S, Harrison O, Feavers IM, Maiden MCJ, Jerse A, Barnes G, Chirro O, Chemweno J, Nduati E, Cehovin A, Tang C, Sanders EJ, Derrick JP. Profiling IgG and IgA antibody responses during vaccination and infection in a high-risk gonorrhoea population. Nat Commun 2024; 15:6712. [PMID: 39112489 PMCID: PMC11306574 DOI: 10.1038/s41467-024-51053-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 07/29/2024] [Indexed: 08/10/2024] Open
Abstract
Development of a vaccine against gonorrhoea is a global priority, driven by the rise in antibiotic resistance. Although Neisseria gonorrhoeae (Ng) infection does not induce substantial protective immunity, highly exposed individuals may develop immunity against re-infection with the same strain. Retrospective epidemiological studies have shown that vaccines containing Neisseria meningitidis (Nm) outer membrane vesicles (OMVs) provide a degree of cross-protection against Ng infection. We conducted a clinical trial (NCT04297436) of 4CMenB (Bexsero, GSK), a licensed Nm vaccine containing OMVs and recombinant antigens, comprising a single arm, open label study of two doses with 50 adults in coastal Kenya who have high exposure to Ng. Data from a Ng antigen microarray established that serum IgG and IgA reactivities against the gonococcal homologs of the recombinant antigens in the vaccine peaked at 10 but had declined by 24 weeks. For most reactive OMV-derived antigens, the reverse was the case. A cohort of similar individuals with laboratory-confirmed gonococcal infection were compared before, during, and after infection: their reactivities were weaker and differed from the vaccinated cohort. We conclude that the cross-protection of the 4CMenB vaccine against gonorrhoea could be explained by cross-reaction against a diverse selection of antigens derived from the OMV component.
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Affiliation(s)
- Lenka Stejskal
- School of Biological Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, M13 9PL, UK
| | - Angela Thistlethwaite
- School of Biological Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, M13 9PL, UK
| | - Fidel Ramirez-Bencomo
- School of Biological Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, M13 9PL, UK
| | - Smruti Rashmi
- School of Biological Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, M13 9PL, UK
| | - Odile Harrison
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Ian M Feavers
- Department of Biology, 11a Mansfield Road, University of Oxford, Oxford, OX1 3SZ, UK
| | - Martin C J Maiden
- Department of Biology, 11a Mansfield Road, University of Oxford, Oxford, OX1 3SZ, UK
| | - Ann Jerse
- Department of Microbiology and Immunology, Uniformed Services University, 4301 Jones Bridge Road, Bethesda, MD, 20814, USA
| | - Grace Barnes
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford, OX1 3RE, UK
| | - Oscar Chirro
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | | | - Eunice Nduati
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Ana Cehovin
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford, OX1 3RE, UK
| | - Christoph Tang
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford, OX1 3RE, UK.
| | | | - Jeremy P Derrick
- School of Biological Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, M13 9PL, UK.
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4
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Tapajóz RCDS, Santos FDS, de Oliveira NR, Maia MAC, Seixas Neto ACP, Maiocchi LDV, Souza PHFC, Oliveira TL, Dellagostin OA. Chimeric lipoproteins for leptospirosis vaccine: immunogenicity and protective potential. Appl Microbiol Biotechnol 2024; 108:424. [PMID: 39037584 PMCID: PMC11263434 DOI: 10.1007/s00253-024-13196-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 05/15/2024] [Accepted: 05/21/2024] [Indexed: 07/23/2024]
Abstract
Leptospirosis, a neglected zoonotic disease, is caused by pathogenic spirochetes belonging to the genus Leptospira and has one of the highest morbidity and mortality rates worldwide. Vaccination stands out as one of the most effective preventive measures for susceptible populations. Within the outer membrane of Leptospira spp., we find the LIC12287, LIC11711, and LIC13259 lipoproteins. These are of interest due to their surface location and potential immunogenicity. Thorough examination revealed the conservation of these proteins among pathogenic Leptospira spp.; we mapped the distribution of T- and B-cell epitopes along their sequences and assessed the 3D structures of each protein. This information aided in selecting immunodominant regions for the development of a chimeric protein. Through gene synthesis, we successfully constructed a chimeric protein, which was subsequently expressed, purified, and characterized. Hamsters were immunized with the chimeric lipoprotein, formulated with adjuvants aluminum hydroxide, EMULSIGEN®-D, Sigma Adjuvant System®, and Montanide™ ISA206VG. Another group was vaccinated with an inactivated Escherichia coli bacterin expressing the chimeric protein. Following vaccination, hamsters were challenged with a virulent L. interrogans strain. Our evaluation of the humoral immune response revealed the production of IgG antibodies, detectable 28 days after the second dose, in contrast to pre-immune samples and control groups. This demonstrates the potential of the chimeric protein to elicit a robust humoral immune response; however, no protection against challenge was achieved. While this study provides valuable insights into the subject, further research is warranted to identify protective antigens that could be utilized in the development of a leptospirosis vaccine. KEY POINTS: • Several T- and B-cell epitopes were identified in all the three proteins. • Four different adjuvants were used in vaccine formulations. • Immunization stimulated significant levels of IgG2/3 in vaccinated animals.
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Affiliation(s)
| | | | | | - Mara Andrade Colares Maia
- Biotechnology Center, Technological Development Center, Federal University of Pelotas, Pelotas, RS, Brazil
| | | | - Laura de Vargas Maiocchi
- Biotechnology Center, Technological Development Center, Federal University of Pelotas, Pelotas, RS, Brazil
| | | | - Thaís Larré Oliveira
- Biotechnology Center, Technological Development Center, Federal University of Pelotas, Pelotas, RS, Brazil
| | - Odir Antônio Dellagostin
- Biotechnology Center, Technological Development Center, Federal University of Pelotas, Pelotas, RS, Brazil.
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5
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Su L, Yan Y, Ma B, Zhao S, Cui Z. GIHP: Graph convolutional neural network based interpretable pan-specific HLA-peptide binding affinity prediction. Front Genet 2024; 15:1405032. [PMID: 39050251 PMCID: PMC11266168 DOI: 10.3389/fgene.2024.1405032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Accepted: 06/20/2024] [Indexed: 07/27/2024] Open
Abstract
Accurately predicting the binding affinities between Human Leukocyte Antigen (HLA) molecules and peptides is a crucial step in understanding the adaptive immune response. This knowledge can have important implications for the development of effective vaccines and the design of targeted immunotherapies. Existing sequence-based methods are insufficient to capture the structure information. Besides, the current methods lack model interpretability, which hinder revealing the key binding amino acids between the two molecules. To address these limitations, we proposed an interpretable graph convolutional neural network (GCNN) based prediction method named GIHP. Considering the size differences between HLA and short peptides, GIHP represent HLA structure as amino acid-level graph while represent peptide SMILE string as atom-level graph. For interpretation, we design a novel visual explanation method, gradient weighted activation mapping (Grad-WAM), for identifying key binding residues. GIHP achieved better prediction accuracy than state-of-the-art methods across various datasets. According to current research findings, key HLA-peptide binding residues mutations directly impact immunotherapy efficacy. Therefore, we verified those highlighted key residues to see whether they can significantly distinguish immunotherapy patient groups. We have verified that the identified functional residues can successfully separate patient survival groups across breast, bladder, and pan-cancer datasets. Results demonstrate that GIHP improves the accuracy and interpretation capabilities of HLA-peptide prediction, and the findings of this study can be used to guide personalized cancer immunotherapy treatment. Codes and datasets are publicly accessible at: https://github.com/sdustSu/GIHP.
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Affiliation(s)
- Lingtao Su
- Shandong University of Science and Technology, Qingdao, China
| | - Yan Yan
- Shandong Guohe Industrial Technology Research Institute Co. Ltd., Jinan, China
| | - Bo Ma
- Qingdao UNIC Information Technology Co. Ltd., Qingdao, China
| | - Shiwei Zhao
- Shandong University of Science and Technology, Qingdao, China
| | - Zhenyu Cui
- Shandong University of Science and Technology, Qingdao, China
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6
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Bhattacharjee A, Hosen MR, Lamisa AB, Ahammad I, Chowdhury ZM, Jamal TB, Sohag MMH, Hossain MU, Das KC, Keya CA, Salimullah M. An integrated comparative genomics, subtractive proteomics and immunoinformatics framework for the rational design of a Pan-Salmonella multi-epitope vaccine. PLoS One 2024; 19:e0292413. [PMID: 38959229 PMCID: PMC11221655 DOI: 10.1371/journal.pone.0292413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 04/23/2024] [Indexed: 07/05/2024] Open
Abstract
Salmonella infections pose a significant global public health concern due to the substantial expenses associated with monitoring, preventing, and treating the infection. In this study, we explored the core proteome of Salmonella to design a multi-epitope vaccine through Subtractive Proteomics and immunoinformatics approaches. A total of 2395 core proteins were curated from 30 different isolates of Salmonella (strain NZ CP014051 was taken as reference). Utilizing the subtractive proteomics approach on the Salmonella core proteome, Curlin major subunit A (CsgA) was selected as the vaccine candidate. csgA is a conserved gene that is related to biofilm formation. Immunodominant B and T cell epitopes from CsgA were predicted using numerous immunoinformatics tools. T lymphocyte epitopes had adequate population coverage and their corresponding MHC alleles showed significant binding scores after peptide-protein based molecular docking. Afterward, a multi-epitope vaccine was constructed with peptide linkers and Human Beta Defensin-2 (as an adjuvant). The vaccine could be highly antigenic, non-toxic, non-allergic, and have suitable physicochemical properties. Additionally, Molecular Dynamics Simulation and Immune Simulation demonstrated that the vaccine can bind with Toll Like Receptor 4 and elicit a robust immune response. Using in vitro, in vivo, and clinical trials, our findings could yield a Pan-Salmonella vaccine that might provide protection against various Salmonella species.
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Affiliation(s)
- Arittra Bhattacharjee
- Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
| | - Md. Rakib Hosen
- Department of Genetic Engineering and Biotechnology, Jagannath University, Dhaka, Bangladesh
| | - Anika Bushra Lamisa
- Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
| | - Ishtiaque Ahammad
- Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
| | - Zeshan Mahmud Chowdhury
- Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
| | - Tabassum Binte Jamal
- Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
| | - Md. Mehadi Hasan Sohag
- Department of Genetic Engineering and Biotechnology, Jagannath University, Dhaka, Bangladesh
| | - Mohammad Uzzal Hossain
- Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
| | - Keshob Chandra Das
- Molecular Biotechnology Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
| | - Chaman Ara Keya
- Department of Biochemistry and Microbiology, North South University, Bashundhara, Dhaka, Bangladesh
| | - Md Salimullah
- Molecular Biotechnology Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, Bangladesh
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7
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Seadawy MG, Lotfy MM, Saeed AA, Ageez AM. Novel HER2-based multi-epitope vaccine (HER2-MEV) against HER2-positive breast cancer: In silico design and validation. Hum Immunol 2024; 85:110832. [PMID: 38905717 DOI: 10.1016/j.humimm.2024.110832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 05/10/2024] [Accepted: 06/10/2024] [Indexed: 06/23/2024]
Abstract
Breast cancer (BC) continues to be the malignancy with the highest diagnosis rate worldwide. Between 15 % and 30 % of BC patients show overexpressed human epidermal growth factor receptor 2 (HER2), which is linked to poor clinical results in terms of invasiveness and recurrence risk. Passive immunity-based therapeutic approaches for treating HER2-enriched BC, are not effective and significant problems need to be tackled. Constructing multi-epitope vaccines is favored over single-epitope vaccines due to its ability to induce immunity against a variety of antigenic targets which will improve the efficacy of the vaccine. The current study describes a multi-epitope vaccine from HER2 protein against HER2-positive BC using several immunoinformatic techniques to achieve a potent and durable immune response. Nine Cytotoxic T lymphocytes (CTL) and five Helper T lymphocytes (HTL) epitopes were predicted and validated from HER2 protein using in silico tools. The expressed protein of the designed vaccine is predicted to be highly thermostable with better solubility. The predicted vaccine 3D structure was validated by ProSA servers and by the ERRAT server. Molecular docking analysis revealed a high binding affinity and stability of the designed vaccine with MHCI and TLR-2, 4, 7, and 9 receptors. The analysis of the C-ImmSim server revealed that the novel vaccine construct had the ability to elicit robust anti-cancerous innate, humoral, and cell-mediated immune responses. The vaccine can be a suitable option for HER2-positive BC patients and other patients with HER2-positive cancers to evoke immune responses. However, in vitro and in vivo experiments are needed to assess its effectiveness and safety.
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Affiliation(s)
- Mohamed G Seadawy
- Biodefense Center for Infectious and Emerging Diseases, Ministry of Defense, Cairo, Egypt.
| | - Mai M Lotfy
- Cancer Biology Department, National Cancer Institute, Cairo University, Giza 12613, Egypt.
| | - Aya A Saeed
- Cancer Biology Department, National Cancer Institute, Cairo University, Giza 12613, Egypt.
| | - Amr M Ageez
- Faculty of Biotechnology, October University for Modern Sciences and Arts, MSA University, 6 October City 12451, Giza, Egypt.
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8
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Wang Y, Shen Z, Mo S, Zhang H, Chen J, Zhu C, Lv S, Zhang D, Huang X, Gu Y, Yu X, Ding X, Zhang X. Crosstalk among proximal tubular cells, macrophages, and fibroblasts in acute kidney injury: single-cell profiling from the perspective of ferroptosis. Hum Cell 2024; 37:1039-1055. [PMID: 38753279 PMCID: PMC11194220 DOI: 10.1007/s13577-024-01072-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 04/27/2024] [Indexed: 06/24/2024]
Abstract
The link between ferroptosis, a form of cell death mediated by iron and acute kidney injury (AKI) is recently gaining widespread attention. However, the mechanism of the crosstalk between cells in the pathogenesis and progression of acute kidney injury remains unexplored. In our research, we performed a non-negative matrix decomposition (NMF) algorithm on acute kidney injury single-cell RNA sequencing data based specifically focusing in ferroptosis-associated genes. Through a combination with pseudo-time analysis, cell-cell interaction analysis and SCENIC analysis, we discovered that proximal tubular cells, macrophages, and fibroblasts all showed associations with ferroptosis in different pathways and at various time. This involvement influenced cellular functions, enhancing cellular communication and activating multiple transcription factors. In addition, analyzing bulk expression profiles and marker genes of newly defined ferroptosis subtypes of cells, we have identified crucial cell subtypes, including Egr1 + PTC-C1, Jun + PTC-C3, Cxcl2 + Mac-C1 and Egr1 + Fib-C1. All these subtypes which were found in AKI mice kidneys and played significantly distinct roles from those of normal mice. Moreover, we verified the differential expression of Egr1, Jun, and Cxcl2 in the IRI mouse model and acute kidney injury human samples. Finally, our research presented a novel analysis of the crosstalk of proximal tubular cells, macrophages and fibroblasts in acute kidney injury targeting ferroptosis, therefore, contributing to better understanding the acute kidney injury pathogenesis, self-repairment and acute kidney injury-chronic kidney disease (AKI-CKD) progression.
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Affiliation(s)
- Yulin Wang
- Department of Nephrology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Medical Center of Kidney Disease, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Kidney and Blood Purification, No. 180 Fenglin Road, Shanghai, 200032, China
| | - Ziyan Shen
- Department of Nephrology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Medical Center of Kidney Disease, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Institute of Kidney and Dialysis, No. 180 Fenglin Road, Shanghai, 200032, China
| | - Shaocong Mo
- Department of Digestive Diseases, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Han Zhang
- Department of Nephrology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Medical Center of Kidney Disease, No. 180 Fenglin Road, Shanghai, 200032, China
- Department of Digestive Diseases, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Jing Chen
- Department of Nephrology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Medical Center of Kidney Disease, No. 180 Fenglin Road, Shanghai, 200032, China
- Department of Digestive Diseases, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Cheng Zhu
- Department of Nephrology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Medical Center of Kidney Disease, No. 180 Fenglin Road, Shanghai, 200032, China
- Department of Digestive Diseases, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Shiqi Lv
- Department of Nephrology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Medical Center of Kidney Disease, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Kidney and Blood Purification, No. 180 Fenglin Road, Shanghai, 200032, China
| | - Di Zhang
- Department of Nephrology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Medical Center of Kidney Disease, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Kidney and Blood Purification, No. 180 Fenglin Road, Shanghai, 200032, China
| | - Xinhui Huang
- Department of Nephrology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Medical Center of Kidney Disease, No. 180 Fenglin Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Kidney and Blood Purification, No. 180 Fenglin Road, Shanghai, 200032, China
| | - Yulu Gu
- Division of Nephrology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, 213100, Jiangsu, China
| | - Xixi Yu
- Department of Nephrology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Xiaoqiang Ding
- Department of Nephrology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China.
- Shanghai Medical Center of Kidney Disease, No. 180 Fenglin Road, Shanghai, 200032, China.
- Shanghai Key Laboratory of Kidney and Blood Purification, No. 180 Fenglin Road, Shanghai, 200032, China.
- Shanghai Institute of Kidney and Dialysis, No. 180 Fenglin Road, Shanghai, 200032, China.
| | - Xiaoyan Zhang
- Department of Nephrology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Shanghai, 200032, China.
- Shanghai Medical Center of Kidney Disease, No. 180 Fenglin Road, Shanghai, 200032, China.
- Shanghai Key Laboratory of Kidney and Blood Purification, No. 180 Fenglin Road, Shanghai, 200032, China.
- Shanghai Institute of Kidney and Dialysis, No. 180 Fenglin Road, Shanghai, 200032, China.
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9
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Sehgal A, Sharma D, Kaushal N, Gupta Y, Martynova E, Kabwe E, Chandy S, Rizvanov A, Khaiboullina S, Baranwal M. Designing a Conserved Immunogenic Peptide Construct from the Nucleocapsid Protein of Puumala orthohantavirus. Viruses 2024; 16:1030. [PMID: 39066193 PMCID: PMC11281540 DOI: 10.3390/v16071030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Revised: 06/09/2024] [Accepted: 06/21/2024] [Indexed: 07/28/2024] Open
Abstract
Puumala orthohantavirus (PUUV) is an emerging zoonotic virus endemic to Europe and Russia that causes nephropathia epidemica, a mild form of hemorrhagic fever with renal syndrome (HFRS). There are limited options for treatment and diagnosis of orthohantavirus infection, making the search for potential immunogenic candidates crucial. In the present work, various bioinformatics tools were employed to design conserved immunogenic peptides containing multiple epitopes of PUUV nucleocapsid protein. Eleven conserved peptides (90% conservancy) of the PUUV nucleocapsid protein were identified. Three conserved peptides containing multiple T and B cell epitopes were selected using a consensus epitope prediction algorithm. Molecular docking using the HPEP dock server demonstrated strong binding interactions between the epitopes and HLA molecules (ten alleles for each class I and II HLA). Moreover, an analysis of population coverage using the IEDB database revealed that the identified peptides have over 90% average population coverage across six continents. Molecular docking and simulation analysis reveal a stable interaction with peptide constructs of chosen immunogenic peptides and Toll-like receptor-4. These computational analyses demonstrate selected peptides' immunogenic potential, which needs to be validated in different experimental systems.
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Affiliation(s)
- Ayushi Sehgal
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala 147001, India; (A.S.); (D.S.); (N.K.); (Y.G.)
| | - Diksha Sharma
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala 147001, India; (A.S.); (D.S.); (N.K.); (Y.G.)
| | - Neha Kaushal
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala 147001, India; (A.S.); (D.S.); (N.K.); (Y.G.)
| | - Yogita Gupta
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala 147001, India; (A.S.); (D.S.); (N.K.); (Y.G.)
| | - Ekaterina Martynova
- Institute of Fundamental Medicine and Biology, Kazan (Volga Region) Federal University, Kazan 420008, Russia; (E.M.); (E.K.); (S.K.)
| | - Emmanuel Kabwe
- Institute of Fundamental Medicine and Biology, Kazan (Volga Region) Federal University, Kazan 420008, Russia; (E.M.); (E.K.); (S.K.)
| | - Sara Chandy
- Childs Trust Medical Research Foundation (CTMRF) Kanchi, Chennai 600034, India;
| | - Albert Rizvanov
- Institute of Fundamental Medicine and Biology, Kazan (Volga Region) Federal University, Kazan 420008, Russia; (E.M.); (E.K.); (S.K.)
| | - Svetlana Khaiboullina
- Institute of Fundamental Medicine and Biology, Kazan (Volga Region) Federal University, Kazan 420008, Russia; (E.M.); (E.K.); (S.K.)
| | - Manoj Baranwal
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala 147001, India; (A.S.); (D.S.); (N.K.); (Y.G.)
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10
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Williams RC, Hanson RL, Peters B, Kearns K, Knowler WC, Bogardus C, Baier LJ. Epistasis Between HLA-DRB1*16:02:01 and SLC16A11 T-C-G-T-T Reduces Odds for Type 2 Diabetes in Southwest American Indians. Diabetes 2024; 73:1002-1011. [PMID: 38530923 PMCID: PMC11109785 DOI: 10.2337/db23-0925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 03/18/2024] [Indexed: 03/28/2024]
Abstract
We sought to identify genetic/immunologic contributors of type 2 diabetes (T2D) in an indigenous American community by genotyping all study participants for both high-resolution HLA-DRB1 alleles and SLC16A11 to test their risk and/or protection for T2D. These genes were selected based on independent reports that HLA-DRB1*16:02:01 is protective for T2D and that SLC16A11 associates with T2D in individuals with BMI <35 kg/m2. Here, we test the interaction of the two loci with a more complete data set and perform a BMI sensitivity test. We defined the risk protection haplotype of SLC16A11, T-C-G-T-T, as allele 2 of a diallelic genetic model with three genotypes, SLC16A11*11, *12, and *22, where allele 1 is the wild type. Both earlier findings were confirmed. Together in the same logistic model with BMI ≥35 kg/m2, DRB1*16:02:01 remains protective (odds ratio [OR] 0.73), while SLC16A11 switches from risk to protection (OR 0.57 [*22] and 0.78 [*12]); an added interaction term was statistically significant (OR 0.49 [*12]). Bootstrapped (b = 10,000) statistical power of interaction, 0.4801, yielded a mean OR of 0.43. Sensitivity analysis demonstrated that the interaction is significant in the BMI range of 30-41 kg/m2. To investigate the epistasis, we used the primary function of the HLA-DRB1 molecule, peptide binding and presentation, to search the entire array of 15-mer peptides for both the wild-type and ancient human SLC16A11 molecules for a pattern of strong binding that was associated with risk and protection for T2D. Applying computer binding algorithms suggested that the core peptide at SLC16A11 D127G, FSAFASGLL, might be key for moderating risk for T2D with potential implications for type 1 diabetes. ARTICLE HIGHLIGHTS
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Affiliation(s)
- Robert C. Williams
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Robert L. Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | | | | | - William C. Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Clifton Bogardus
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Leslie J. Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
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11
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Bulashevska A, Nacsa Z, Lang F, Braun M, Machyna M, Diken M, Childs L, König R. Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy. Front Immunol 2024; 15:1394003. [PMID: 38868767 PMCID: PMC11167095 DOI: 10.3389/fimmu.2024.1394003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 05/13/2024] [Indexed: 06/14/2024] Open
Abstract
Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has propelled the development of innovative neoantigen discovery tools and pipelines. These tools have revolutionized our ability to identify tumor-specific antigens, providing the foundation for precision cancer immunotherapy. AI-driven algorithms can process extensive amounts of data, identify patterns, and make predictions that were once challenging to achieve. However, the integration of AI comes with its own set of challenges, leaving space for further research. With particular focus on the computational approaches, in this article we have explored the current landscape of neoantigen prediction, the fundamental concepts behind, the challenges and their potential solutions providing a comprehensive overview of this rapidly evolving field.
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Affiliation(s)
- Alla Bulashevska
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
| | - Zsófia Nacsa
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
| | - Franziska Lang
- TRON - Translational Oncology at the University Medical Center of the Johannes Gutenberg University gGmbH, Mainz, Germany
| | - Markus Braun
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
| | - Martin Machyna
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
| | - Mustafa Diken
- TRON - Translational Oncology at the University Medical Center of the Johannes Gutenberg University gGmbH, Mainz, Germany
| | - Liam Childs
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
| | - Renate König
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
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12
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Sarvmeili J, Baghban Kohnehrouz B, Gholizadeh A, Shanehbandi D, Ofoghi H. Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer. Sci Rep 2024; 14:10297. [PMID: 38704475 PMCID: PMC11069592 DOI: 10.1038/s41598-024-61025-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 04/30/2024] [Indexed: 05/06/2024] Open
Abstract
The ideal vaccines for combating diseases that may emerge in the future require more than simply inactivating a few pathogenic strains. This study aims to provide a peptide-based multi-epitope vaccine effective against various severe acute respiratory syndrome coronavirus 2 strains. To design the vaccine, a library of peptides from the spike, nucleocapsid, membrane, and envelope structural proteins of various strains was prepared. Then, the final vaccine structure was optimized using the fully protected epitopes and the fynomer scaffold. Using bioinformatics tools, the antigenicity, allergenicity, toxicity, physicochemical properties, population coverage, and secondary and three-dimensional structures of the vaccine candidate were evaluated. The bioinformatic analyses confirmed the high quality of the vaccine. According to further investigations, this structure is similar to native protein and there is a stable and strong interaction between vaccine and receptors. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli. In conclusion, the fynomer-based vaccine can be considered as a new style in designing and updating vaccines to protect against coronavirus disease.
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Affiliation(s)
- Javad Sarvmeili
- Department of Plant Breeding and Biotechnology, University of Tabriz, Tabriz, 51666, Iran
| | | | - Ashraf Gholizadeh
- Department of Animal Biology, University of Tabriz, Tabriz, 51666, Iran
| | - Dariush Shanehbandi
- Department of Immunology, Tabriz University of Medical Sciences, Tabriz, 51666, Iran
| | - Hamideh Ofoghi
- Department of Biotechnology, Iranian Research Organization for Science and Technology, Tehran, 33131, Iran
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13
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Yang Y, He X, Li F, He S, Liu M, Li M, Xia F, Su W, Liu G. Animal-derived food allergen: A review on the available crystal structure and new insights into structural epitope. Compr Rev Food Sci Food Saf 2024; 23:e13340. [PMID: 38778570 DOI: 10.1111/1541-4337.13340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 03/19/2024] [Indexed: 05/25/2024]
Abstract
Immunoglobulin E (IgE)-mediated food allergy is a rapidly growing public health problem. The interaction between allergens and IgE is at the core of the allergic response. One of the best ways to understand this interaction is through structural characterization. This review focuses on animal-derived food allergens, overviews allergen structures determined by X-ray crystallography, presents an update on IgE conformational epitopes, and explores the structural features of these epitopes. The structural determinants of allergenicity and cross-reactivity are also discussed. Animal-derived food allergens are classified into limited protein families according to structural features, with the calcium-binding protein and actin-binding protein families dominating. Progress in epitope characterization has provided useful information on the structural properties of the IgE recognition region. The data reveals that epitopes are located in relatively protruding areas with negative surface electrostatic potential. Ligand binding and disulfide bonds are two intrinsic characteristics that influence protein structure and impact allergenicity. Shared structures, local motifs, and shared epitopes are factors that lead to cross-reactivity. The structural properties of epitope regions and structural determinants of allergenicity and cross-reactivity may provide directions for the prevention, diagnosis, and treatment of food allergies. Experimentally determined structure, especially that of antigen-antibody complexes, remains limited, and the identification of epitopes continues to be a bottleneck in the study of animal-derived food allergens. A combination of traditional immunological techniques and emerging bioinformatics technology will revolutionize how protein interactions are characterized.
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Affiliation(s)
- Yang Yang
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, Fujian, China
- College of Environment and Public Health, Xiamen Huaxia University, Xiamen, Fujian, China
| | - Xinrong He
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, Fujian, China
| | - Fajie Li
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, Fujian, China
| | - Shaogui He
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen, Fujian, China
| | - Meng Liu
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, Fujian, China
- College of Marine Biology, Xiamen Ocean Vocational College, Xiamen, Fujian, China
| | - Mengsi Li
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, Fujian, China
- School of Food Engineering, Zhangzhou Institute of Technology, Zhangzhou, Fujian, China
| | - Fei Xia
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, Fujian, China
| | - Wenjin Su
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, Fujian, China
| | - Guangming Liu
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen, Fujian, China
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14
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Wang J, Jiang F, Cheng P, Ye Z, Li L, Yang L, Zhuang L, Gong W. Construction of novel multi-epitope-based diagnostic biomarker HP16118P and its application in the differential diagnosis of Mycobacterium tuberculosis latent infection. MOLECULAR BIOMEDICINE 2024; 5:15. [PMID: 38679629 PMCID: PMC11056354 DOI: 10.1186/s43556-024-00177-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 02/29/2024] [Indexed: 05/01/2024] Open
Abstract
Tuberculosis (TB) is an infectious disease that significantly threatens human health. However, the differential diagnosis of latent tuberculosis infection (LTBI) and active tuberculosis (ATB) remains a challenge for clinicians in early detection and preventive intervention. In this study, we developed a novel biomarker named HP16118P, utilizing 16 helper T lymphocyte (HTL) epitopes, 11 cytotoxic T lymphocyte (CTL) epitopes, and 8 B cell epitopes identified from 15 antigens associated with LTBI-RD using the IEDB database. We analyzed the physicochemical properties, spatial structure, and immunological characteristics of HP16118P using various tools, which indicated that it is a hydrophilic and relatively stable alkaline protein. Furthermore, HP16118P exhibited good antigenicity and immunogenicity, while being non-toxic and non-allergenic, with the potential to induce immune responses. We observed that HP16118P can stimulate the production of high levels of IFN-γ+ T lymphocytes in individuals with ATB, LTBI, and health controls. IL-5 induced by HP16118P demonstrated potential in distinguishing LTBI individuals and ATB patients (p=0.0372, AUC=0.8214, 95% CI [0.5843 to 1.000]) with a sensitivity of 100% and specificity of 71.43%. Furthermore, we incorporated the GM-CSF, IL-23, IL-5, and MCP-3 induced by HP16118P into 15 machine learning algorithms to construct a model. It was found that the Quadratic discriminant analysis model exhibited the best diagnostic performance for discriminating between LTBI and ATB, with a sensitivity of 1.00, specificity of 0.86, and accuracy of 0.93. In summary, HP16118P has demonstrated strong antigenicity and immunogenicity, with the induction of GM-CSF, IL-23, IL-5, and MCP-3, suggesting their potential for the differential diagnosis of LTBI and ATB.
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Affiliation(s)
- Jie Wang
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, The Eighth Medical Center of PLA General Hospital, 17#Heishanhu Road, Haidian District, Beijing, 100091, China
- Department of Clinical Laboratory, The Eighth Medical Center of PLA General Hospital, Beijing, 100091, China
| | - Fan Jiang
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, The Eighth Medical Center of PLA General Hospital, 17#Heishanhu Road, Haidian District, Beijing, 100091, China
- Section of Health, No. 94804 Unit of the Chinese People's Liberation Army, Shanghai, 200434, China
- Resident standardization training cadet corps, Air Force Hospital of Eastern Theater, Nanjing, 210002, China
| | - Peng Cheng
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, The Eighth Medical Center of PLA General Hospital, 17#Heishanhu Road, Haidian District, Beijing, 100091, China
| | - Zhaoyang Ye
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, The Eighth Medical Center of PLA General Hospital, 17#Heishanhu Road, Haidian District, Beijing, 100091, China
- Hebei North University, ZhangjiakouHebei, 075000, China
| | - Linsheng Li
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, The Eighth Medical Center of PLA General Hospital, 17#Heishanhu Road, Haidian District, Beijing, 100091, China
- Hebei North University, ZhangjiakouHebei, 075000, China
| | - Ling Yang
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, The Eighth Medical Center of PLA General Hospital, 17#Heishanhu Road, Haidian District, Beijing, 100091, China
- Hebei North University, ZhangjiakouHebei, 075000, China
| | - Li Zhuang
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, The Eighth Medical Center of PLA General Hospital, 17#Heishanhu Road, Haidian District, Beijing, 100091, China
- Hebei North University, ZhangjiakouHebei, 075000, China
| | - Wenping Gong
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute of Tuberculosis Research, Senior Department of Tuberculosis, The Eighth Medical Center of PLA General Hospital, 17#Heishanhu Road, Haidian District, Beijing, 100091, China.
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15
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Rizarullah, Aditama R, Giri-Rachman EA, Hertadi R. Designing a Novel Multiepitope Vaccine from the Human Papilloma Virus E1 and E2 Proteins for Indonesia with Immunoinformatics and Molecular Dynamics Approaches. ACS OMEGA 2024; 9:16547-16562. [PMID: 38617694 PMCID: PMC11007845 DOI: 10.1021/acsomega.4c00425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 03/04/2024] [Accepted: 03/08/2024] [Indexed: 04/16/2024]
Abstract
One of the deadliest malignant cancer in women globally is cervical cancer. Specifically, cervical cancer is the second most common type of cancer in Indonesia. The main infectious agent of cervical cancer is the human papilloma virus (HPV). Although licensed prophylactic vaccines are available, cervical cancer cases are on the rise. Therapy using multiepitope-based vaccines is a very promising therapy for cervical cancer. This study aimed to develop a multiepitope vaccine based on the E1 and E2 proteins of HPV 16, 18, 45, and 52 using in silico. In this study, we develop a novel multiepitope vaccine candidate using an immunoinformatic approach. We predicted the epitopes of the cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) and evaluated their immunogenic properties. Population coverage analysis of qualified epitopes was conducted to determine the successful use of the vaccine worldwide. The epitopes were constructed into a multiepitope vaccine by using AAY linkers between the CTL epitopes and GPGPG linkers between the HTL epitopes. The tertiary structure of the multiepitope vaccine was modeled with AlphaFold and was evaluated by Prosa-web. The results of vaccine construction were analyzed for B-cell epitope prediction, molecular docking with Toll like receptor-4 (TLR4), and molecular dynamics simulation. The results of epitope prediction obtained 4 CTL epitopes and 7 HTL epitopes that are eligible for construction of multiepitope vaccines. Prediction of the physicochemical properties of multiepitope vaccines obtained good results for recombinant protein production. The interaction showed that the interaction of the multiepitope vaccine-TLR4 complex is stable based on the binding free energy value -106.5 kcal/mol. The results of the immune response simulation show that multiepitope vaccine candidates could activate the adaptive and humoral immune systems and generate long-term B-cell memory. According to these results, the development of a multiepitope vaccine with a reverse vaccinology approach is a breakthrough to develop potential cervical cancer therapeutic vaccines.
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Affiliation(s)
- Rizarullah
- Biochemistry
and Biomolecular Engineering Research Division, Faculty of Mathematics
and Natural Sciences, Bandung Institute
of Technology, Jl. Ganesa No. 10, Bandung 40132, Indonesia
- Department
of Biochemistry, Faculty of Medicine, Abulyatama
University, Jl. Blangbintang Lama, Aceh Besar 23372, Indonesia
| | - Reza Aditama
- Biochemistry
and Biomolecular Engineering Research Division, Faculty of Mathematics
and Natural Sciences, Bandung Institute
of Technology, Jl. Ganesa No. 10, Bandung 40132, Indonesia
| | - Ernawati Arifin Giri-Rachman
- Genetics
and Molecular Biotechnology Research Division, School of Life Sciences
and Technology, Bandung Institute of Technology, Jl. Ganesa No. 10, Bandung 40132, Indonesia
| | - Rukman Hertadi
- Biochemistry
and Biomolecular Engineering Research Division, Faculty of Mathematics
and Natural Sciences, Bandung Institute
of Technology, Jl. Ganesa No. 10, Bandung 40132, Indonesia
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16
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Trabelsi K, Ben Khalaf N, Ramadan AR, Elsharkawy A, Ashoor D, Chlif S, Boussoffara T, Ben-Ahmed M, Kumar M, Fathallah MD. A novel approach to designing viral precision vaccines applied to SARS-CoV-2. Front Cell Infect Microbiol 2024; 14:1346349. [PMID: 38628551 PMCID: PMC11018900 DOI: 10.3389/fcimb.2024.1346349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 03/08/2024] [Indexed: 04/19/2024] Open
Abstract
Efficient precision vaccines against several highly pathogenic zoonotic viruses are currently lacking. Proteolytic activation is instrumental for a number of these viruses to gain host-cell entry and develop infectivity. For SARS-CoV-2, this process is enhanced by the insertion of a furin cleavage site at the junction of the spike protein S1/S2 subunits upstream of the metalloprotease TMPRSS2 common proteolytic site. Here, we describe a new approach based on specific epitopes selection from the region involved in proteolytic activation and infectivity for the engineering of precision candidate vaccinating antigens. This approach was developed through its application to the design of SARS-CoV-2 cross-variant candidates vaccinating antigens. It includes an in silico structural analysis of the viral region involved in infectivity, the identification of conserved immunogenic epitopes and the selection of those eliciting specific immune responses in infected people. The following step consists of engineering vaccinating antigens that carry the selected epitopes and mimic their 3D native structure. Using this approach, we demonstrated through a Covid-19 patient-centered study of a 500 patients' cohort, that the epitopes selected from SARS-CoV-2 protein S1/S2 junction elicited a neutralizing antibody response significantly associated with mild and asymptomatic COVID-19 (p<0.001), which strongly suggests protective immunity. Engineered antigens containing the SARS-CoV-2 selected epitopes and mimicking the native epitopes 3D structure generated neutralizing antibody response in mice. Our data show the potential of this combined computational and experimental approach for designing precision vaccines against viruses whose pathogenicity is contingent upon proteolytic activation.
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Affiliation(s)
- Khaled Trabelsi
- Health Biotechnology Program, King Fahad Chair for Health Biotechnology, Department of Life Sciences College of Graduate Studies, Arabian Gulf University, Manama, Bahrain
| | - Noureddin Ben Khalaf
- Health Biotechnology Program, King Fahad Chair for Health Biotechnology, Department of Life Sciences College of Graduate Studies, Arabian Gulf University, Manama, Bahrain
| | - Ahmed R. Ramadan
- Health Biotechnology Program, King Fahad Chair for Health Biotechnology, Department of Life Sciences College of Graduate Studies, Arabian Gulf University, Manama, Bahrain
| | - Amany Elsharkawy
- Department of Biology, College of Arts and Sciences, Georgia State University, Atlanta, GA, United States
| | - Dana Ashoor
- Health Biotechnology Program, King Fahad Chair for Health Biotechnology, Department of Life Sciences College of Graduate Studies, Arabian Gulf University, Manama, Bahrain
| | - Sadok Chlif
- Department of Family and Community Medicine, College of Medicine and Medical Sciences, Arabian Gulf University, Manama, Bahrain
| | - Thouraya Boussoffara
- Transmission, Control and Immunobiology of Infections Laboratory, Institute Pasteur of Tunis, Tunis, Tunisia
| | - Melika Ben-Ahmed
- Transmission, Control and Immunobiology of Infections Laboratory, Institute Pasteur of Tunis, Tunis, Tunisia
| | - Mukesh Kumar
- Department of Biology, College of Arts and Sciences, Georgia State University, Atlanta, GA, United States
| | - M-Dahmani Fathallah
- Health Biotechnology Program, King Fahad Chair for Health Biotechnology, Department of Life Sciences College of Graduate Studies, Arabian Gulf University, Manama, Bahrain
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17
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Ali Z, Cardoza JV, Basak S, Narsaria U, Bhattacharjee S, G UM, Isaac SP, Franca TCC, LaPlante SR, George SS. A Multi-epitope Vaccine Candidate Against Bolivian Hemorrhagic fever Caused by Machupo Virus. Appl Biochem Biotechnol 2024; 196:2137-2160. [PMID: 37479961 DOI: 10.1007/s12010-023-04604-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/19/2023] [Indexed: 07/23/2023]
Abstract
Bolivian hemorrhagic fever (BHF) caused by Machupo virus (MACV) is a New World arenavirus having a reported mortality rate of 25-35%. The BHF starts with fever, followed by headache, and nausea which rapidly progresses to severe hemorrhagic phase within 7 days of disease onset. One of the key promoters for MACV viral entry into the cell followed by viral propagation is performed by the viral glycoprotein (GPC). GPC is post-transcriptionally cleaved into GP1, GP2 and a signal peptide. These proteins all take part in the viral infection in host body. Therefore, GPC protein is an ideal target for developing therapeutics against MACV infection. In this study, GPC protein was considered to design a multi-epitope, multivalent vaccine containing antigenic and immunogenic CTL and HTL epitopes. Different structural validations and physicochemical properties were analysed to validate the vaccine. Docking and molecular dynamics simulations were conducted to understand the interactions of the vaccine with various immune receptors. Finally, the vaccine was codon optimised in silico and along with which immune simulation studies was performed in order to evaluate the vaccine's effectiveness in triggering an efficacious immune response against MACV.
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Affiliation(s)
- Zeeshan Ali
- Krupanidhi College of Physiotherapy, Bangalore, Karnataka, 560035, India
| | | | | | | | | | | | - Samuel Paul Isaac
- Krupanidhi College of Physiotherapy, Bangalore, Karnataka, 560035, India
| | - Tanos C C Franca
- Military Institute of Engineering, Rio de Janerio, Brazil
- INRS - Centre Armand-Frappier Santé Biotechnologie, Université de Québec, Laval, Québec, H7V 1B7, Canada
- University of Hradec Kralove, Hradec Kralove, Czech Republic
| | - Steven R LaPlante
- INRS - Centre Armand-Frappier Santé Biotechnologie, Université de Québec, Laval, Québec, H7V 1B7, Canada
| | - Sudhan S George
- Krupanidhi College of Physiotherapy, Bangalore, Karnataka, 560035, India.
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Arega AM, Dhal AK, Pattanaik KP, Nayak S, Mahapatra RK. An Immunoinformatics-Based Study of Mycobacterium tuberculosis Region of Difference-2 Uncharacterized Protein (Rv1987) as a Potential Subunit Vaccine Candidate for Preliminary Ex Vivo Analysis. Appl Biochem Biotechnol 2024; 196:2367-2395. [PMID: 37498378 DOI: 10.1007/s12010-023-04658-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/04/2023] [Indexed: 07/28/2023]
Abstract
Mycobacterium tuberculosis (Mtb) is the pathogen that causes tuberculosis and develops resistance to many of the existing drugs. The sole licensed TB vaccine, BCG, is unable to provide a comprehensive defense. So, it is crucial to maintain the immunological response to eliminate tuberculosis. Our previous in silico study reported five uncharacterized proteins as potential vaccine antigens. In this article, we considered the uncharacterized Mtb H37Rv regions of difference (RD-2) Rv1987 protein as a promising vaccine candidate. The vaccine quality of the protein was analyzed using reverse vaccinology and immunoinformatics-based quality-checking parameters followed by an ex vivo preliminary investigation. In silico analysis of Rv1987 protein predicted it as surface localized, secretory, single helix, antigenic, non-allergenic, and non-homologous to the host protein. Immunoinformatics analysis of Rv1987 by CD4 + and CD8 + T-cells via MHC-I and MHC-II binding affinity and presence of B-cell epitope predicted its immunogenicity. The docked complex analysis of the 3D model structure of the protein with immune cell receptor TLR-4 revealed the protein's capability for potential interaction. Furthermore, the target protein-encoded gene Rv1987 was cloned, over-expressed, purified, and analyzed by mass spectrometry (MS) to report the target peptides. The qRT-PCR gene expression analysis shows that it is capable of activating macrophages and significantly increasing the production of a number of key cytokines (TNF-α, IL-1β, and IL-10). Our in-silico analysis and ex vivo preliminary investigations revealed the immunogenic potential of the target protein. These findings suggest that the Rv1987 be undertaken as a potent subunit vaccine antigen and that further animal model immuno-modulation studies would boost the novel TB vaccine discovery and/or BCG vaccine supplement pipeline.
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Affiliation(s)
- Aregitu Mekuriaw Arega
- School of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha, India
- National Veterinary Institute, Debre Zeit, Ethiopia
| | - Ajit Kumar Dhal
- School of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha, India
| | | | - Sasmita Nayak
- School of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha, India
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19
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Ganji M, Bakhshi S, Ahmadi K, Shoari A, Moeini S, Ghaemi A. Rational design of B-cell and T-cell multi epitope-based vaccine against Zika virus, an in silico study. J Biomol Struct Dyn 2024; 42:3426-3440. [PMID: 37190978 DOI: 10.1080/07391102.2023.2213339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 05/06/2023] [Indexed: 05/17/2023]
Abstract
The Zika virus (ZKV) is a single-stranded positive-sense, enveloped RNA virus. Zika infection during pregnancy can cause congenital microcephaly, Guillain-Barré syndrome, miscarriage, and other CNS abnormalities. The world needs safe and effective vaccinations to fight against ZIKV infection since vaccination is generally regarded as one of the most effective ways to prevent infectious diseases. In the present work, we used immunoinformatics and docking studies to construct a vaccine containing multi-epitopes using the structural and non-structural proteins of ZKV. The structural models of ZKV proteins (PrE, PrM, NS1, and NS2A) were constructed using Pyre2 and RaptorX servers. The epitopes of B-cell, T-cell (HTL and CTL), and IFN-γ were predicted, and each epitope's immunogenic nature and physiochemical properties were confirmed. As an adjuvant, the CPG-Oligodeoxynucleotide, an agonist of Toll-like receptor 9 (TLR9), is associated to cytotoxic T-lymphocytes (CTL) epitopes via PAPAP linker. To assess the binding affinity and the tendency of the designed vaccine to induce an immune response through TLR9, molecular docking was done. In the next step, molecular dynamics (MD) simulation to 100 nanoseconds (ns) was used to evaluate the stability of the interaction of the designed vaccine with TLR9. The designed vaccine is predicted to be highly antigenic, non-toxic, soluble, and stable with low flexibility in MD simulation. MD studies indicated that the finalized vaccine-TLR9 docked complex was stable during simulation time. The vaccine construct is able to stimulate both humoral and cellular immune responses. We suppose that our constructed model of the vaccine may have the ability to induce the host immune response against ZKV. Further studies, including in vitro and in vivo experimental analyses, are needed to prove the constructed vaccine's efficacy with multi-epitopes.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Mahmoud Ganji
- Department of Medical Biotechnology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Shohreh Bakhshi
- Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Khadijeh Ahmadi
- Infectious and Tropical Diseases Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Alireza Shoari
- Department of Cancer Biology, Mayo Clinic, Jacksonville, Florida, USA
| | - Soheila Moeini
- Department of Surgery, Faculty of Medicine, McGill University, Montréal, Québec, Canada
| | - Amir Ghaemi
- Department of Influenza and Other Respiratory Viruses, Pasteur Institute of Iran, Tehran, Iran
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20
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Wang M, Lei C, Wang J, Li Y, Li M. TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning. Brief Bioinform 2024; 25:bbae154. [PMID: 38600667 PMCID: PMC11006794 DOI: 10.1093/bib/bbae154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 02/16/2024] [Accepted: 03/13/2024] [Indexed: 04/12/2024] Open
Abstract
Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding motifs. Based on the discovery, we make the preprocessing and coding closer to the natural biological process. Besides, due to the input being based on multiple types of features and the attention module focused on the BiGRU hidden layer, TripHLApan has learned more sequence level binding information. The application of transfer learning strategies ensures the accuracy of prediction results under special lengths (peptides in length 8) and model scalability with the data explosion. Compared with the current optimal models, TripHLApan exhibits strong predictive performance in various prediction environments with different positive and negative sample ratios. In addition, we validate the superiority and scalability of TripHLApan's predictive performance using additional latest data sets, ablation experiments and binding reconstitution ability in the samples of a melanoma patient. The results show that TripHLApan is a powerful tool for predicting the binding of HLA-I and HLA-II molecular peptides for the synthesis of tumor vaccines. TripHLApan is publicly available at https://github.com/CSUBioGroup/TripHLApan.git.
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Affiliation(s)
- Meng Wang
- School of Computer Science and engineering, Central South University, Changsha 410083, China
| | - Chuqi Lei
- School of Computer Science and engineering, Central South University, Changsha 410083, China
| | - Jianxin Wang
- School of Computer Science and engineering, Central South University, Changsha 410083, China
| | - Yaohang Li
- Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA
| | - Min Li
- School of Computer Science and engineering, Central South University, Changsha 410083, China
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21
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Pastor Y, Reynard O, Iampietro M, Surenaud M, Picard F, El Jahrani N, Lefebvre C, Hammoudi A, Dupaty L, Brisebard É, Reynard S, Moureaux É, Moroso M, Durand S, Gonzalez C, Amurri L, Gallouët AS, Marlin R, Baize S, Chevillard E, Raoul H, Hocini H, Centlivre M, Thiébaut R, Horvat B, Godot V, Lévy Y, Cardinaud S. A vaccine targeting antigen-presenting cells through CD40 induces protective immunity against Nipah disease. Cell Rep Med 2024; 5:101467. [PMID: 38471503 PMCID: PMC10983108 DOI: 10.1016/j.xcrm.2024.101467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 12/23/2023] [Accepted: 02/16/2024] [Indexed: 03/14/2024]
Abstract
Nipah virus (NiV) has been recently ranked by the World Health Organization as being among the top eight emerging pathogens likely to cause major epidemics, whereas no therapeutics or vaccines have yet been approved. We report a method to deliver immunogenic epitopes from NiV through the targeting of the CD40 receptor of antigen-presenting cells by fusing a selected humanized anti-CD40 monoclonal antibody to the Nipah glycoprotein with conserved NiV fusion and nucleocapsid peptides. In the African green monkey model, CD40.NiV induces specific immunoglobulin A (IgA) and IgG as well as cross-neutralizing responses against circulating NiV strains and Hendra virus and T cell responses. Challenge experiments using a NiV-B strain demonstrate the high protective efficacy of the vaccine, with all vaccinated animals surviving and showing no significant clinical signs or virus replication, suggesting that the CD40.NiV vaccine conferred sterilizing immunity. Overall, results obtained with the CD40.NiV vaccine are highly promising in terms of the breadth and efficacy against NiV.
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Affiliation(s)
- Yadira Pastor
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France
| | - Olivier Reynard
- Centre International de Recherche en Infectiologie (CIRI), Université de Lyon, INSERM U1111, Ecole Normale Supérieure de Lyon, Université Lyon 1, CNRS UMR5308, Lyon, France
| | - Mathieu Iampietro
- Centre International de Recherche en Infectiologie (CIRI), Université de Lyon, INSERM U1111, Ecole Normale Supérieure de Lyon, Université Lyon 1, CNRS UMR5308, Lyon, France
| | - Mathieu Surenaud
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France
| | - Florence Picard
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France
| | - Nora El Jahrani
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France
| | - Cécile Lefebvre
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France
| | - Adele Hammoudi
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France
| | - Léa Dupaty
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France
| | | | - Stéphanie Reynard
- Centre International de Recherche en Infectiologie (CIRI), Université de Lyon, INSERM U1111, Ecole Normale Supérieure de Lyon, Université Lyon 1, CNRS UMR5308, Lyon, France; Unité de Biologie des Infections Virales Emergentes, Institut Pasteur, Lyon, Université Paris Cité, Paris, France
| | | | - Marie Moroso
- Laboratoire P4 Inserm Jean Mérieux, Lyon, France
| | - Stéphanie Durand
- Centre International de Recherche en Infectiologie (CIRI), Université de Lyon, INSERM U1111, Ecole Normale Supérieure de Lyon, Université Lyon 1, CNRS UMR5308, Lyon, France
| | - Claudia Gonzalez
- Centre International de Recherche en Infectiologie (CIRI), Université de Lyon, INSERM U1111, Ecole Normale Supérieure de Lyon, Université Lyon 1, CNRS UMR5308, Lyon, France
| | - Lucia Amurri
- Centre International de Recherche en Infectiologie (CIRI), Université de Lyon, INSERM U1111, Ecole Normale Supérieure de Lyon, Université Lyon 1, CNRS UMR5308, Lyon, France
| | - Anne-Sophie Gallouët
- Université Paris-Saclay, Inserm, CEA, Immunologie des maladies virales, autoimmunes, hématologiques et bactériennes (IMVA-HB/IDMIT/UMR1184), Fontenay-aux-Roses, France
| | - Romain Marlin
- Université Paris-Saclay, Inserm, CEA, Immunologie des maladies virales, autoimmunes, hématologiques et bactériennes (IMVA-HB/IDMIT/UMR1184), Fontenay-aux-Roses, France
| | - Sylvain Baize
- Centre International de Recherche en Infectiologie (CIRI), Université de Lyon, INSERM U1111, Ecole Normale Supérieure de Lyon, Université Lyon 1, CNRS UMR5308, Lyon, France; Unité de Biologie des Infections Virales Emergentes, Institut Pasteur, Lyon, Université Paris Cité, Paris, France
| | | | - Hervé Raoul
- Laboratoire P4 Inserm Jean Mérieux, Lyon, France
| | - Hakim Hocini
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France
| | - Mireille Centlivre
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France
| | - Rodolphe Thiébaut
- Vaccine Research Institute (VRI), Créteil, France; University Bordeaux, Department of Public Health, INSERM Bordeaux Population Health Research Centre, Inria SISTM, Bordeaux, France; CHU Bordeaux, Department of Medical Information, Bordeaux, France
| | - Branka Horvat
- Centre International de Recherche en Infectiologie (CIRI), Université de Lyon, INSERM U1111, Ecole Normale Supérieure de Lyon, Université Lyon 1, CNRS UMR5308, Lyon, France
| | - Véronique Godot
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France
| | - Yves Lévy
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France; Assistance Publique-Hôpitaux de Paris, Groupe Henri-Mondor Albert-Chenevier, Service Immunologie Clinique, Créteil, France.
| | - Sylvain Cardinaud
- INSERM U955 - Équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France; Vaccine Research Institute (VRI), Créteil, France.
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22
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Li Y, Wu X, Fang D, Luo Y. Informing immunotherapy with multi-omics driven machine learning. NPJ Digit Med 2024; 7:67. [PMID: 38486092 PMCID: PMC10940614 DOI: 10.1038/s41746-024-01043-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Accepted: 02/14/2024] [Indexed: 03/18/2024] Open
Abstract
Progress in sequencing technologies and clinical experiments has revolutionized immunotherapy on solid and hematologic malignancies. However, the benefits of immunotherapy are limited to specific patient subsets, posing challenges for broader application. To improve its effectiveness, identifying biomarkers that can predict patient response is crucial. Machine learning (ML) play a pivotal role in harnessing multi-omic cancer datasets and unlocking new insights into immunotherapy. This review provides an overview of cutting-edge ML models applied in omics data for immunotherapy analysis, including immunotherapy response prediction and immunotherapy-relevant tumor microenvironment identification. We elucidate how ML leverages diverse data types to identify significant biomarkers, enhance our understanding of immunotherapy mechanisms, and optimize decision-making process. Additionally, we discuss current limitations and challenges of ML in this rapidly evolving field. Finally, we outline future directions aimed at overcoming these barriers and improving the efficiency of ML in immunotherapy research.
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Affiliation(s)
- Yawei Li
- Department of Preventive Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Collaborative AI in Healthcare, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Xin Wu
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, 60612, USA
| | - Deyu Fang
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60611, USA.
- Center for Collaborative AI in Healthcare, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60611, USA.
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23
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Yang Y, Wei Z, Cia G, Song X, Pucci F, Rooman M, Xue F, Hou Q. MHCII-peptide presentation: an assessment of the state-of-the-art prediction methods. Front Immunol 2024; 15:1293706. [PMID: 38646540 PMCID: PMC11027168 DOI: 10.3389/fimmu.2024.1293706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 02/19/2024] [Indexed: 04/23/2024] Open
Abstract
Major histocompatibility complex Class II (MHCII) proteins initiate and regulate immune responses by presentation of antigenic peptides to CD4+ T-cells and self-restriction. The interactions between MHCII and peptides determine the specificity of the immune response and are crucial in immunotherapy and cancer vaccine design. With the ever-increasing amount of MHCII-peptide binding data available, many computational approaches have been developed for MHCII-peptide interaction prediction over the last decade. There is thus an urgent need to provide an up-to-date overview and assessment of these newly developed computational methods. To benchmark the prediction performance of these methods, we constructed an independent dataset containing binding and non-binding peptides to 20 human MHCII protein allotypes from the Immune Epitope Database, covering DP, DR and DQ alleles. After collecting 11 known predictors up to January 2022, we evaluated those available through a webserver or standalone packages on this independent dataset. The benchmarking results show that MixMHC2pred and NetMHCIIpan-4.1 achieve the best performance among all predictors. In general, newly developed methods perform better than older ones due to the rapid expansion of data on which they are trained and the development of deep learning algorithms. Our manuscript not only draws a full picture of the state-of-art of MHCII-peptide binding prediction, but also guides researchers in the choice among the different predictors. More importantly, it will inspire biomedical researchers in both academia and industry for the future developments in this field.
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Affiliation(s)
- Yaqing Yang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Zhonghui Wei
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Gabriel Cia
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Brussels, Belgium
| | - Xixi Song
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Fabrizio Pucci
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Brussels, Belgium
| | - Marianne Rooman
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Brussels, Belgium
| | - Fuzhong Xue
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Qingzhen Hou
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
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24
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Nguyen TL, Kim H. Immunoinformatics and computational approaches driven designing a novel vaccine candidate against Powassan virus. Sci Rep 2024; 14:5999. [PMID: 38472237 PMCID: PMC10933373 DOI: 10.1038/s41598-024-56554-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 03/07/2024] [Indexed: 03/14/2024] Open
Abstract
Powassan virus (POWV) is an arthropod-borne virus (arbovirus) capable of causing severe illness in humans for severe neurological complications, and its incidence has been on the rise in recent years due to climate change, posing a growing public health concern. Currently, no vaccines to prevent or medicines to treat POWV disease, emphasizing the urgent need for effective countermeasures. In this study, we utilize bioinformatics approaches to target proteins of POWV, including the capsid, envelope, and membrane proteins, to predict diverse B-cell and T-cell epitopes. These epitopes underwent screening for critical properties such as antigenicity, allergenicity, toxicity, and cytokine induction potential. Eight selected epitopes were then conjugated with adjuvants using various linkers, resulting in designing of a potentially stable and immunogenic vaccine candidate against POWV. Moreover, molecular docking, molecular dynamics simulations, and immune simulations revealed a stable interaction pattern with the immune receptor, suggesting the vaccine's potential to induce robust immune responses. In conclusion, our study provided a set of derived epitopes from POWV's proteins, demonstrating the potential for a novel vaccine candidate against POWV. Further in vitro and in vivo studies are warranted to advance our efforts and move closer to the goal of combatting POWV and related arbovirus infections.
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Affiliation(s)
- Truc Ly Nguyen
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea
| | - Heebal Kim
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of Korea.
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Republic of Korea.
- eGnome, Inc., Seoul, 05836, Republic of Korea.
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25
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Teixeira DG, Rodrigues-Neto JF, da Cunha DCS, Jeronimo SMB. Understanding SARS-CoV-2 spike glycoprotein clusters and their impact on immunity of the population from Rio Grande do Norte, Brazil. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2024; 118:105556. [PMID: 38242186 DOI: 10.1016/j.meegid.2024.105556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 01/09/2024] [Accepted: 01/15/2024] [Indexed: 01/21/2024]
Abstract
SARS-CoV-2 genome underwent mutations since it started circulating within the human population. The aim of this study was to understand the fluctuation of the spike clusters concomitant to the population immunity either due to natural infection and/or vaccination in a state of Brazil that had both high rate of natural infection and vaccination coverage. A total of 1725 SARS-CoV-2 sequences from the state of Rio Grande do Norte, Brazil, were retrieved from GISAID and subjected to cluster analysis. Immunoinformatics were used to predict T- and B-cell epitopes, followed by simulation to estimate either pro- or anti-inflammatory responses and to correlate with circulating variants. From March 2020 to June 2022, the state of Rio Grande do Norte reported 579,931 COVID-19 cases with a 1.4% fatality rate across the three major waves: May-Sept 2020, Feb-Aug 2021, and Jan-Mar 2022. Cluster 0 variants (wild type strain, Zeta) were prevalent in the first wave and Delta (AY.*), which circulated in Brazil in the latter half of 2021, featuring fewer unique epitopes. Cluster 1 (Gamma (P.1 + P.1.*)) dominated the first half of 2021. Late 2021 had two new clusters, Cluster 2 (Omicron, (B.1.1.529 + BA.*)), and Cluster 3 (BA.*) with the most unique epitopes, in addition to Cluster 4 (Delta sub lineages) which emerged in the second half of 2021 with fewer unique epitopes. Cluster 1 epitopes showed a high pro-inflammatory propensity, while others exhibited a balanced cytokine induction. The clustering method effectively identified Spike groups that may contribute to immune evasion and clinical presentation, and explain in part the clinical outcome.
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Affiliation(s)
- Diego Gomes Teixeira
- Instituto de Medicina Tropical do Rio Grande do Norte, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - João Firmino Rodrigues-Neto
- Instituto de Medicina Tropical do Rio Grande do Norte, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil; Escola Multicampi de Ciências Médicas do Rio Grande do Norte, Universidade Federal do Rio Grande do Norte, Caicó, Rio Grande do Norte, Brazil
| | - Dayse Caroline Severiano da Cunha
- Instituto de Medicina Tropical do Rio Grande do Norte, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Selma Maria Bezerra Jeronimo
- Instituto de Medicina Tropical do Rio Grande do Norte, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil; Departmento de Bioquímica, Centro de Biociências, Universidade Federal do Rio Grande Norte, Natal, Rio Grande do Norte, Brazil; Instituto Nacional de Ciência e Tecnologia de Doenças Tropicais, Natal, Rio Grande do Norte, Brazil.
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26
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Long Q, Wei M, Wang Y, Pang F. Design of a multi-epitope vaccine against goatpox virus using an immunoinformatics approach. Front Cell Infect Microbiol 2024; 13:1309096. [PMID: 38487680 PMCID: PMC10937444 DOI: 10.3389/fcimb.2023.1309096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 12/22/2023] [Indexed: 03/17/2024] Open
Abstract
Introduction Goatpox, a severe infectious disease caused by goatpox virus (GTPV), leads to enormous economic losses in the livestock industry. Traditional live attenuated vaccines cause serious side effects and exist a risk of dispersal. Therefore, it is urgent to develop efficient and safer vaccines to prevent and control of GTPV. Methods In the present study, we are aimed to design a multi-epitope subunit vaccine against GTPV using an immunoinformatics approach. Various immunodominant cytotoxic T lymphocytes (CTL) epitopes, helper T lymphocytes (HTL) epitopes, and B-cell epitopes from P32, L1R, and 095 proteins of GTPV were screened and liked by the AAY, GPGPG, and KK connectors, respectively. Furthermore, an adjuvant β-defensin was attached to the vaccine's N-terminal using the EAAAK linker to enhance immunogenicity. Results The constructed vaccine was soluble, non-allergenic and non-toxic and exhibited high levels of antigenicity and immunogenicity. The vaccine's 3D structure was subsequently predicted, refined and validated, resulting in an optimized model with a Z-value of -3.4. Molecular docking results demonstrated that the vaccine had strong binding affinity with TLR2(-27.25 kcal/mol), TLR3(-39.84 kcal/mol), and TLR4(-59.42 kcal/mol). Molecular dynamics simulation results indicated that docked vaccine-TLR complexes were stable. Immune simulation analysis suggested that the vaccine can induce remarkable increase in antibody titers of IgG and IgM, higher levels of IFN-γ and IL-2. Conclusion The designed GTPV multi-epitope vaccine is structurally stable and can induce robust humoral and cellular immune responses, which may be a promising vaccine candidate against GTPV.
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Affiliation(s)
| | | | | | - Feng Pang
- Department of Veterinary Medicine, College of Animal Science, Guizhou University, Guiyang, China
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Lahimchi MR, Madanchi H, Ahmadi K, Shahbazi B, Yousefi B. In silico designing a novel TLR4-mediating multiepitope vaccine against monkeypox via advanced immunoinformatics and bioinformatics approaches. J Biomol Struct Dyn 2024; 42:2094-2110. [PMID: 37129119 DOI: 10.1080/07391102.2023.2203253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 04/10/2023] [Indexed: 05/03/2023]
Abstract
Monkeypox virus is a member of the Poxviridae family, which causes monkeypox zoonotic disease. Since July 2022, the prevention of monkeypox have become more considerable due to the new outbreak, making it a global concern. Therefore, we used an in silico-based method, including immunoinformatics, bioinformatics, molecular docking, and gene cloning approaches to design a novel multiepitope vaccine against monkeypox. Three immunogenic envelope proteins of monkeypox virus, including G10R, E8L, and A30L, were selected to predict appropriate immune system stimulator epitopes. The A30L is common between smallpox and monkeypox virus, so the proposed vaccine may be effective against smallpox too. There is no evidence of allergenicity and toxicity of the vaccine epitopes. To boost the immunogenicity of the designed vaccine, we used the helper epitope of PADRE and RS01as adjuvants. Furthermore, some linkers are used to link epitopes and adjuvants together. The physicochemical futures of the designed vaccine were assessed. The tertiary structure of the vaccine was modeled and then refined to improve its structure and physicochemical properties. To analyze the vaccine construct and TLR4 complex affinity, they were docked to gather. Besides, the vaccine was cloned into E.coli. pET-21b(+) plasmid to reveal that it can be expressed and stimulate the immune system. Immune stimulation evaluation showed that the candidate vaccine could induce the production of IgM, IgG1, and IgG2 antibodies. Overall, we suggested an effective vaccine candidate against monkeypox. However, Future studies and clinical trials should be done to ensure the efficacy and safety of this vaccine.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Mohammad Reza Lahimchi
- Department of Medical Immunology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran
| | - Hamid Madanchi
- Department of Medical Biotechnology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran
- Drug Design and Bioinformatics Unit, Department of Medical Biotechnology, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Khadijeh Ahmadi
- Infectious and Tropical Diseases Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Behzad Shahbazi
- Department of Molecular Medicine, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Bahman Yousefi
- Department of Medical Immunology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran
- Cancer Research Center, Semnan University of Medical Sciences, Semnan, Iran
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28
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Bahadori Z, Shafaghi M, Sabzevari J, Madanchi H, Ranjbar MM, Mousavi SF, Shabani AA. Design, development, and assessment of a novel multi-peptide vaccine targeting PspC, PsaA, and PhtD proteins of Streptococcus pneumoniae. Int J Biol Macromol 2024; 258:128924. [PMID: 38143051 DOI: 10.1016/j.ijbiomac.2023.128924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/15/2023] [Accepted: 12/18/2023] [Indexed: 12/26/2023]
Abstract
Pneumococcus is the top cause of diseases such as pneumonia/meningitis, and of secondary infections after viral respiratory diseases like COVID-19/flu. Pneumococcal protein-based vaccines consisting of proteins with various functions in virulence might provide a qualified alternative for present vaccines. In this project, PspC, PsaA, and PhtD proteins were considered to anticipate B/T-cell epitopes using immunoinformatics to develop 4 multi-peptide constructs (C, A, and D individual constructs, and a fusion construct CAD). We tested whether vaccination with CAD is able to elicit more efficient protective responses against infection than vaccination with the individual constructs or combination of C + A + D. Based on the in silico results, the constructs were predicted to be antigenic, soluble, non-toxic, and stable, and also be able to provoke humoral/cellular immune reactions. When mice were immunized with the fusion protein, significantly higher levels of IgG and cytokines were induced in serum. The IgG in the fusion group had an effective bioactivity for pneumococcus clearance utilizing the complement pathway. The mice immunized with fusion protein were the most protected from challenge. This report for the first time presents a novel multi-peptide vaccine composed of immunodominant peptides of PspC, PsaA, and PhtD. In general, the experimental results supported the immunoinformatics predictions.
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Affiliation(s)
- Zohreh Bahadori
- Department of Medical Biotechnology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran; Department of Bacteriology, Pasteur Institute of Iran, Tehran, Iran.
| | - Mona Shafaghi
- Department of Medical Biotechnology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran; Department of Bacteriology, Pasteur Institute of Iran, Tehran, Iran.
| | - Jahangir Sabzevari
- Department of Microbiology and Microbial Biotechnology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran
| | - Hamid Madanchi
- Department of Medical Biotechnology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran; Drug Design and Bioinformatics Unit, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran; Nervous System Stem Cells Research Center, Semnan University of Medical Sciences, Semnan, Iran
| | - Mohammad Mehdi Ranjbar
- Razi Vaccine and Serum Research Institute, Agricultural Research, Education, and Extension Organization (AREEO), Karaj, Iran
| | | | - Ali Akbar Shabani
- Department of Medical Biotechnology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran.
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29
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Mikhaylov V, Brambley CA, Keller GLJ, Arbuiso AG, Weiss LI, Baker BM, Levine AJ. Accurate modeling of peptide-MHC structures with AlphaFold. Structure 2024; 32:228-241.e4. [PMID: 38113889 PMCID: PMC10872456 DOI: 10.1016/j.str.2023.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 08/17/2023] [Accepted: 11/22/2023] [Indexed: 12/21/2023]
Abstract
Major histocompatibility complex (MHC) proteins present peptides on the cell surface for T cell surveillance. Reliable in silico prediction of which peptides would be presented and which T cell receptors would recognize them is an important problem in structural immunology. Here, we introduce an AlphaFold-based pipeline for predicting the three-dimensional structures of peptide-MHC complexes for class I and class II MHC molecules. Our method demonstrates high accuracy, outperforming existing tools in class I modeling accuracy and class II peptide register prediction. We validate its performance and utility with new experimental data on a recently described cancer neoantigen/wild-type peptide pair and explore applications toward improving peptide-MHC binding prediction.
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Affiliation(s)
- Victor Mikhaylov
- The Simons Center for Systems Biology, Institute for Advanced Study, 1 Einstein Drive, Princeton, NJ 08540, USA.
| | - Chad A Brambley
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Grant L J Keller
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Alyssa G Arbuiso
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Laura I Weiss
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Brian M Baker
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Arnold J Levine
- The Simons Center for Systems Biology, Institute for Advanced Study, 1 Einstein Drive, Princeton, NJ 08540, USA
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30
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Yu Y, Zu L, Jiang J, Wu Y, Wang Y, Xu M, Liu Q. Structure-aware deep model for MHC-II peptide binding affinity prediction. BMC Genomics 2024; 25:127. [PMID: 38291350 PMCID: PMC10826266 DOI: 10.1186/s12864-023-09900-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 12/12/2023] [Indexed: 02/01/2024] Open
Abstract
The prediction of major histocompatibility complex (MHC)-peptide binding affinity is an important branch in immune bioinformatics, especially helpful in accelerating the design of disease vaccines and immunity therapy. Although deep learning-based solutions have yielded promising results on MHC-II molecules in recent years, these methods ignored structure knowledge from each peptide when employing the deep neural network models. Each peptide sequence has its specific combination order, so it is worth considering adding the structural information of the peptide sequence to the deep model training. In this work, we use positional encoding to represent the structural information of peptide sequences and validly combine the positional encoding with existing models by different strategies. Experiments on three datasets show that the introduction of position-coding information can further improve the performance built upon the existing model. The idea of introducing positional encoding to this field can provide important reference significance for the optimization of the deep network structure in the future.
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Affiliation(s)
- Ying Yu
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Lipeng Zu
- Department of Computer Science, Florida State University, Tallahassee, 32306, USA
| | - Jiaye Jiang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Yafang Wu
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Yinglin Wang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Midie Xu
- Department of Pathology, Fudan University, Shanghai Cancer Center, Shanghai, 200032, China.
- Department of Medical Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
- Institute of Pathology, Fudan University, Shanghai, 200032, China.
| | - Qing Liu
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
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31
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Du H, Liu J, Jude KM, Yang X, Li Y, Bell B, Yang H, Kassardjian A, Mobedi A, Parekh U, Sperberg RAP, Julien JP, Mellins ED, Garcia KC, Huang PS. A general platform for targeting MHC-II antigens via a single loop. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.26.577489. [PMID: 38352315 PMCID: PMC10862749 DOI: 10.1101/2024.01.26.577489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Class-II major histocompatibility complexes (MHC-IIs) are central to the communications between CD4+ T cells and antigen presenting cells (APCs), but intrinsic structural features associated with MHC-II make it difficult to develop a general targeting system with high affinity and antigen specificity. Here, we introduce a protein platform, Targeted Recognition of Antigen-MHC Complex Reporter for MHC-II (TRACeR-II), to enable the rapid development of peptide-specific MHC-II binders. TRACeR-II has a small helical bundle scaffold and uses an unconventional mechanism to recognize antigens via a single loop. This unique antigen-recognition mechanism renders this platform highly versatile and amenable to direct structural modeling of the interactions with the antigen. We demonstrate that TRACeR-II binders can be rapidly evolved across multiple alleles, while computational protein design can produce specific binding sequences for a SARS-CoV-2 peptide of unknown complex structure. TRACeR-II sheds light on a simple and straightforward approach to address the MHC peptide targeting challenge, without relying on combinatorial selection on complementarity determining region (CDR) loops. It presents a promising basis for further exploration in immune response modulation as well as a broad range of theragnostic applications.
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Affiliation(s)
- Haotian Du
- Department of Chemistry, Stanford University, Stanford, CA, USA
| | - Jingjia Liu
- Department of Bioengineering, Stanford University, CA, USA
| | - Kevin M. Jude
- Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Xinbo Yang
- Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Ying Li
- Department of Pediatrics, Divisions of Human Gene Therapy and Allergy, Immunology & Rheumatology, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Program in Immunology, Stanford University School of Medicine, Stanford, CA, USA
| | - Braxton Bell
- Department of Chemistry, Stanford University, Stanford, CA, USA
| | - Hongli Yang
- Department of Bioengineering, Stanford University, CA, USA
| | - Audrey Kassardjian
- Program in Molecular Medicine, The Hospital for Sick Children Research Institute, Toronto, ON M5G 0A4, Canada
- Department of Immunology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Ali Mobedi
- Department of Bioengineering, Stanford University, CA, USA
| | - Udit Parekh
- Department of Bioengineering, Stanford University, CA, USA
| | | | - Jean-Philippe Julien
- Program in Molecular Medicine, The Hospital for Sick Children Research Institute, Toronto, ON M5G 0A4, Canada
- Department of Immunology, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Biochemistry, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Elizabeth D. Mellins
- Department of Pediatrics, Divisions of Human Gene Therapy and Allergy, Immunology & Rheumatology, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Program in Immunology, Stanford University School of Medicine, Stanford, CA, USA
| | - K. Christopher Garcia
- Departments of Molecular and Cellular Physiology and Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Po-Ssu Huang
- Department of Bioengineering, Stanford University, CA, USA
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32
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Wang Y, Wu A, Xu Z, Zhang H, Li H, Fu S, Liu Y, Cui L, Miao Y, Wang Y, Zhumanov K, Xu Y, Sheng J, Yi J, Chen C. A multi-epitope subunit vaccine based on CU/ZN-SOD, OMP31 and BP26 against Brucella melitensis infection in BALB/C mice. Int Immunopharmacol 2024; 127:111351. [PMID: 38113688 DOI: 10.1016/j.intimp.2023.111351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 12/02/2023] [Accepted: 12/05/2023] [Indexed: 12/21/2023]
Abstract
Brucellosis, a zoonosis caused by Brucella, is highly detrimental to both humans and animals. Most existing vaccines are live attenuated vaccines with safety flaws for people and animals. Therefore, it is advantageous to design a multi-epitope subunit vaccine (MEV) to prevent Brucella infection. To this end, we applied a reverse vaccinology approach. Six cytotoxic T cell (CTL) epitopes, seven T helper cell (HTL) epitopes, and four linear B cell epitopes from CU/ZN-SOD, Omp31, and BP26 were obtained. We linked the CTL, HTL, B-cell epitopes, the appropriate CTB molecular adjuvant, and the universal T helper lymphocyte epitope, PADRE, with linkers AAY, GPPGG, and KK, respectively. This yielded a 412-amino acid MEV construct, which we named MEVcob. The immunogenicity, stability, safety, and feasibility of the construct were evaluated by bioinformatics tools (including the AlphaFold2 prediction tool, the AlphaFold2 tool, NetMHC-I pan 4.0 server, IEDB MHC-I server, ABCpred service, and C-ImmSim server); the physicochemical properties, secondary and tertiary structures, and binding ability of MEVocb to toll-like receptor 4 (TLR4) was analyzed. Then, codon adaptation and computer cloning studies were performed. MEVocb is highly immunogenic in immunostimulation experiments, The proteins translated by these sequences were relatively stable, exhibiting a high antigenic index. Furthermore, mouse experiments confirmed that the MEVocb construct could raise IFN-γ, IgG, IgG2a, IgG1, IL-2, TNF-α levels in mice, indicating that induced a specific humoral and cellular immune response in BALB/c mice. This vaccine induced a statistically significant level of protection in BALB/c mice when challenged with Brucella melitensis 043 in Xinjiang. Briefly, we utilized immunoinformatic tools to design a novel multi-epitope subunit candidate vaccine against Brucella. This vaccine aims to induce host immune responses and confer specific protective effects. The study results offer a theoretical foundation for the development of a novel Brucella subunit vaccine.
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Affiliation(s)
- Yueli Wang
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China
| | - Aodi Wu
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China
| | - Zhenyu Xu
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China
| | - Huan Zhang
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China
| | - Honghuan Li
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China
| | - Shuangshuang Fu
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China
| | - Yajing Liu
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China
| | - Lijin Cui
- Fujian Biotechnology Co., LTD., 353000 Nanping, Fujian, China
| | - Yuhe Miao
- Fujian Biotechnology Co., LTD., 353000 Nanping, Fujian, China
| | - Yong Wang
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China
| | - Kaiat Zhumanov
- Kazakh National Agrarian University, The Republic of Kazakhstan
| | - Yimei Xu
- Xinjiang Center for Disease Control and Prevention, 830000 Urumqi, Xinjiang, China
| | - Jinliang Sheng
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China.
| | - Jihai Yi
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China.
| | - Chuangfu Chen
- School of Animal Science and Technology, Shihezi University, 832000 Shihezi City, Xinjiang, China.
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33
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Roja B, Chellapandi P. Design and characterization of a multi-epitope vaccine against Clostridium botulinum A3 Loch Maree intoxication in humans. Gene 2024; 892:147865. [PMID: 37783297 DOI: 10.1016/j.gene.2023.147865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 09/03/2023] [Accepted: 09/29/2023] [Indexed: 10/04/2023]
Abstract
Clostridium botulinum Loch Maree expresses an extremely potent botulinum neurotoxin subtype, A3 causing botulism and several gastrointestinal disorders in mammals. Several recombinant vaccines have been developed for human botulism and no vaccine is currently available for the treatment of diseases caused by other virulence factors. Hence, we designed, constructed, and characterized a multi-epitope vaccine from new virulence proteins identified from this organism using an immunoinformatics approach. The vaccine construct used in this study was designed from 6B cell linear epitopes, 12 cytotoxic T cell lymphocyte epitopes, and 15 helper T cell lymphocyte epitopes, with a defensin adjuvant and adjusting linker sequences. A molecular modeling approach was used to model, refine, and validate the 3D structure of the vaccine construct. Molecular docking studies were performed to determine the stability of the molecular interactions between the vaccine construct and human toll-like receptor 7. The in silico molecular cloning was used to clone a codon-optimized synthetic vaccine gene in pCYB1 vector and expressed in Escherichia coli. The results of this study identified six new virulence proteins: peptidoglycan hydrolase, SCP-like extracellular protein, N-acetylmuramoyl-l-alanine amidase, putative membrane protein, drug/metabolite exporter, and bacillolysin. The top B-cell, cytotoxic T-cell lymphocyte, and helper T-lymphocyte epitopes were predicted from these virulence proteins with greater accuracy and reliability. HLA-A*02:01 and HLA-A*03:01 were identified as HLA-A-binding alleles for cytotoxic T-cell lymphocyte epitopes. DRB1*0110 and DRB1*0115 are the dominant alleles that bind to helper T-cell lymphocyte epitopes. The synthetic gene construct was highly expressed in a heterologous host and produced considerable amounts of antigenic protein. The multi-epitope vaccine is more conservative in the sequence-structure-function link, immunogenic with less allergenicity, and possibly provokes cellular and humoral immunity. The present study suggests that the designed multi-epitope vaccine is a promising prophylactic candidate for the virulence and intoxication caused by subtype A3 strains.
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Affiliation(s)
- B Roja
- Industrial Systems Biology Lab, Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu, India
| | - P Chellapandi
- Industrial Systems Biology Lab, Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu, India.
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Atkins TK, Solanki A, Vasmatzis G, Cornette J, Riedel M. Evaluating NetMHCpan performance on non-European HLA alleles not present in training data. Front Immunol 2024; 14:1288105. [PMID: 38292493 PMCID: PMC10825027 DOI: 10.3389/fimmu.2023.1288105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Accepted: 12/21/2023] [Indexed: 02/01/2024] Open
Abstract
Bias in neural network model training datasets has been observed to decrease prediction accuracy for groups underrepresented in training data. Thus, investigating the composition of training datasets used in machine learning models with healthcare applications is vital to ensure equity. Two such machine learning models are NetMHCpan-4.1 and NetMHCIIpan-4.0, used to predict antigen binding scores to major histocompatibility complex class I and II molecules, respectively. As antigen presentation is a critical step in mounting the adaptive immune response, previous work has used these or similar predictions models in a broad array of applications, from explaining asymptomatic viral infection to cancer neoantigen prediction. However, these models have also been shown to be biased toward hydrophobic peptides, suggesting the network could also contain other sources of bias. Here, we report the composition of the networks' training datasets are heavily biased toward European Caucasian individuals and against Asian and Pacific Islander individuals. We test the ability of NetMHCpan-4.1 and NetMHCpan-4.0 to distinguish true binders from randomly generated peptides on alleles not included in the training datasets. Unexpectedly, we fail to find evidence that the disparities in training data lead to a meaningful difference in prediction quality for alleles not present in the training data. We attempt to explain this result by mapping the HLA sequence space to determine the sequence diversity of the training dataset. Furthermore, we link the residues which have the greatest impact on NetMHCpan predictions to structural features for three alleles (HLA-A*34:01, HLA-C*04:03, HLA-DRB1*12:02).
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Affiliation(s)
- Thomas Karl Atkins
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Arnav Solanki
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States
| | - George Vasmatzis
- Biomarker Discovery Group, Mayo Clinic, Center for Individualized Medicine, Rochester, MN, United States
| | - James Cornette
- Department of Mathematics, Iowa State University, Ames, IA, United States
| | - Marc Riedel
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States
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Nguyen TL, Kim H. Designing a Multiepitope Vaccine against Eastern Equine Encephalitis Virus: Immunoinformatics and Computational Approaches. ACS OMEGA 2024; 9:1092-1105. [PMID: 38222668 PMCID: PMC10785064 DOI: 10.1021/acsomega.3c07322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/21/2023] [Accepted: 11/27/2023] [Indexed: 01/16/2024]
Abstract
Eastern equine encephalitis virus (EEEV) is a significant threat to human and animal populations, causing severe encephalitis, often leading to long-term neurological complications and even mortality. Despite this, no approved antiviral treatments or EEEV human vaccines currently exist. In response, we utilized immunoinformatics and computational approaches to design a multiepitope vaccine candidate for EEEV. By screening the structural polyprotein of EEEV, we predicted both T-cell and linear B-cell epitopes. These epitopes underwent comprehensive evaluations for their antigenicity, toxicity, and allergenicity. From these evaluations, we selected ten epitopes highly suitable for vaccine design, which were connected with adjuvants using a stable linker. The resulting vaccine construct demonstrated exceptional antigenic, nontoxic, nonallergenic, and physicochemical properties. Subsequently, we employed molecular docking and molecular dynamics simulations to reveal a stable interaction pattern between the vaccine candidate and Toll-like receptor 5. Besides, computational immune simulations predicted the vaccine's capability to induce robust immune responses. Our study addresses the urgent need for effective EEEV preventive strategies and offers valuable insights for EEEV vaccine development. As EEEV poses a severe threat with potential spread due to climate change, our research provides a crucial step in enhancing public health defenses against this menacing zoonotic disease.
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Affiliation(s)
- Truc Ly Nguyen
- Department
of Agricultural Biotechnology and Research Institute of Agriculture
and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Heebal Kim
- Department
of Agricultural Biotechnology and Research Institute of Agriculture
and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
- Interdisciplinary
Program in Bioinformatics, Seoul National
University, Seoul 08826, Republic
of Korea
- eGnome,
Inc., Seoul 05836, Republic of Korea
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Ricker CA, Meli K, Van Allen EM. Historical perspective and future directions: computational science in immuno-oncology. J Immunother Cancer 2024; 12:e008306. [PMID: 38191244 PMCID: PMC10826578 DOI: 10.1136/jitc-2023-008306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/07/2023] [Indexed: 01/10/2024] Open
Abstract
Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastatic cancers. Despite these achievements, only a minority of patients respond to immunotherapy, underscoring the importance of elucidating molecular mechanisms responsible for response and resistance to inform the development and selection of treatments. Breakthroughs in molecular sequencing technologies have led to the generation of an immense amount of genomic and transcriptomic sequencing data that can be mined to uncover complex tumor-immune interactions using computational tools. In this review, we discuss existing and emerging computational methods that contextualize the composition and functional state of the tumor microenvironment, infer the reactivity and clonal dynamics from reconstructed immune cell receptor repertoires, and predict the antigenic landscape for immune cell recognition. We further describe the advantage of multi-omics analyses for capturing multidimensional relationships and artificial intelligence techniques for integrating omics data with histopathological and radiological images to encapsulate patterns of treatment response and tumor-immune biology. Finally, we discuss key challenges impeding their widespread use and clinical application and conclude with future perspectives. We are hopeful that this review will both serve as a guide for prospective researchers seeking to use existing tools for scientific discoveries and inspire the optimization or development of novel tools to enhance precision, ultimately expediting advancements in immunotherapy that improve patient survival and quality of life.
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Affiliation(s)
- Cora A Ricker
- Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Kevin Meli
- Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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Wang X, Wu T, Jiang Y, Chen T, Pan D, Jin Z, Xie J, Quan L, Lyu Q. RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding. Bioinformatics 2024; 40:btad785. [PMID: 38175759 PMCID: PMC10796178 DOI: 10.1093/bioinformatics/btad785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 12/20/2023] [Accepted: 12/28/2023] [Indexed: 01/06/2024] Open
Abstract
MOTIVATION Binding of peptides to major histocompatibility complex (MHC) molecules plays a crucial role in triggering T cell recognition mechanisms essential for immune response. Accurate prediction of MHC-peptide binding is vital for the development of cancer therapeutic vaccines. While recent deep learning-based methods have achieved significant performance in predicting MHC-peptide binding affinity, most of them separately encode MHC molecules and peptides as inputs, potentially overlooking critical interaction information between the two. RESULTS In this work, we propose RPEMHC, a new deep learning approach based on residue-residue pair encoding to predict the binding affinity between peptides and MHC, which encode an MHC molecule and a peptide as a residue-residue pair map. We evaluate the performance of RPEMHC on various MHC-II-related datasets for MHC-peptide binding prediction, demonstrating that RPEMHC achieves better or comparable performance against other state-of-the-art baselines. Moreover, we further construct experiments on MHC-I-related datasets, and experimental results demonstrate that our method can work on both two MHC classes. These extensive validations have manifested that RPEMHC is an effective tool for studying MHC-peptide interactions and can potentially facilitate the vaccine development. AVAILABILITY The source code of the method along with trained models is freely available at https://github.com/lennylv/RPEMHC.
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Affiliation(s)
- Xuejiao Wang
- School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China
| | - Tingfang Wu
- School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China
- Province Key Lab for Information Processing Technologies, Soochow University, Suzhou, Jiangsu 215006, China
- Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing, Jiangsu 210000, China
| | - Yelu Jiang
- School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China
| | - Taoning Chen
- School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China
| | - Deng Pan
- School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China
| | - Zhi Jin
- School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China
| | - Jingxin Xie
- School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China
| | - Lijun Quan
- School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China
- Province Key Lab for Information Processing Technologies, Soochow University, Suzhou, Jiangsu 215006, China
- Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing, Jiangsu 210000, China
| | - Qiang Lyu
- School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China
- Province Key Lab for Information Processing Technologies, Soochow University, Suzhou, Jiangsu 215006, China
- Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing, Jiangsu 210000, China
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Nyesiga B, Levin M, Säll A, Rosén A, Jansson K, Fritzell S, Hägerbrand K, Weilguny D, von Schantz L. RUBY® - a tetravalent (2+2) bispecific antibody format with excellent functionality and IgG-like stability, pharmacology and developability properties. MAbs 2024; 16:2330113. [PMID: 38527972 DOI: 10.1080/19420862.2024.2330113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 03/08/2024] [Indexed: 03/27/2024] Open
Abstract
Despite the large number of existing bispecific antibody (bsAb) formats, the generation of novel bsAbs is still associated with development and bioprocessing challenges. Here, we present RUBY, a novel bispecific antibody format that allows rapid generation of bsAbs that fulfill key development criteria. The RUBYTM format has a 2 + 2 geometry, where two Fab fragments are linked via their light chains to the C-termini of an IgG, and carries mutations for optimal chain pairing. The unique design enables generation of bsAbs with mAb-like attributes. Our data demonstrate that RUBY bsAbs are compatible with small-scale production systems for screening purposes and can be produced at high yields (>3 g/L) from stable cell lines. The bsAbs produced are shown to, in general, contain low amounts of aggregates and display favorable solubility and stress endurance profiles. Further, compatibility with various IgG isotypes is shown and tailored Fc gamma receptor binding confirmed. Also, retained interaction with FcRn is demonstrated to translate into a pharmacokinetic profile in mice and non-human primates that is comparable to mAb controls. Functionality of conditional active RUBY bsAbs is confirmed in vitro. Anti-tumor effects in vivo have previously been demonstrated, and shown to be superior to a comparable mAb, and here it is further shown that RUBY bsAbs penetrate and localize to tumor tissue in vivo. In all, the RUBY format has attractive mAb-like attributes and offers the possibility to mitigate many of the development challenges linked to other bsAb formats, facilitating both high functionality and developability.
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Affiliation(s)
- Barnabas Nyesiga
- Alligator Bioscience AB, Medicon Village, Lund, Sweden
- Faculty of Health and Society, Malmö University, Malmö, Sweden
| | - Mattias Levin
- Alligator Bioscience AB, Medicon Village, Lund, Sweden
| | - Anna Säll
- Alligator Bioscience AB, Medicon Village, Lund, Sweden
| | - Anna Rosén
- Alligator Bioscience AB, Medicon Village, Lund, Sweden
| | - Kim Jansson
- Alligator Bioscience AB, Medicon Village, Lund, Sweden
| | - Sara Fritzell
- Alligator Bioscience AB, Medicon Village, Lund, Sweden
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Addala V, Newell F, Pearson JV, Redwood A, Robinson BW, Creaney J, Waddell N. Computational immunogenomic approaches to predict response to cancer immunotherapies. Nat Rev Clin Oncol 2024; 21:28-46. [PMID: 37907723 DOI: 10.1038/s41571-023-00830-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/03/2023] [Indexed: 11/02/2023]
Abstract
Cancer immunogenomics is an emerging field that bridges genomics and immunology. The establishment of large-scale genomic collaborative efforts along with the development of new single-cell transcriptomic techniques and multi-omics approaches have enabled characterization of the mutational and transcriptional profiles of many cancer types and helped to identify clinically actionable alterations as well as predictive and prognostic biomarkers. Researchers have developed computational approaches and machine learning algorithms to accurately obtain clinically useful information from genomic and transcriptomic sequencing data from bulk tissue or single cells and explore tumours and their microenvironment. The rapid growth in sequencing and computational approaches has resulted in the unmet need to understand their true potential and limitations in enabling improvements in the management of patients with cancer who are receiving immunotherapies. In this Review, we describe the computational approaches currently available to analyse bulk tissue and single-cell sequencing data from cancer, stromal and immune cells, as well as how best to select the most appropriate tool to address various clinical questions and, ultimately, improve patient outcomes.
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Affiliation(s)
- Venkateswar Addala
- Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
- Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia.
| | - Felicity Newell
- Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - John V Pearson
- Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Alec Redwood
- National Centre for Asbestos Related Diseases, University of Western Australia, Perth, Western Australia, Australia
- Institute of Respiratory Health, Perth, Western Australia, Australia
- School of Biomedical Science, University of Western Australia, Perth, Western Australia, Australia
| | - Bruce W Robinson
- National Centre for Asbestos Related Diseases, University of Western Australia, Perth, Western Australia, Australia
- Institute of Respiratory Health, Perth, Western Australia, Australia
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
- Medical School, University of Western Australia, Perth, Western Australia, Australia
| | - Jenette Creaney
- National Centre for Asbestos Related Diseases, University of Western Australia, Perth, Western Australia, Australia
- Institute of Respiratory Health, Perth, Western Australia, Australia
- School of Biomedical Science, University of Western Australia, Perth, Western Australia, Australia
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - Nicola Waddell
- Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
- Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia.
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40
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He S, Zhou F. Characterization of T-Cell Epitopes in Food Allergens by Bioinformatic Tools. Methods Mol Biol 2024; 2717:77-99. [PMID: 37737979 DOI: 10.1007/978-1-0716-3453-0_6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/23/2023]
Abstract
The identification of T-cell epitopes is a critical step in the understanding of the immunologic mechanisms such as food allergy. Epitope screening in silico by bioinformatic tools can be used to identify T-cell epitopes, which can save time and resources. In this chapter, a multiparametric approach to predict and assess major histocompatibility complex (MHC) class II binding T-cell epitopes using bioinformatics was introduced for food allergens. Furthermore, the ability of predicted T-cell epitopes to induce interleukin (IL)-4, as well as the allergenicity potential based on the sequence analysis and population coverage of epitopes were also determined. The molecular docking approach was further used to explore the binding ability between epitopes and human leukocyte antigen (HLA) class II molecules. The amino acids that might be responsible for binding to HLA class II molecules and their binding interactions were analyzed.
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Affiliation(s)
- Shudong He
- School of Food and Biological Engineering, Engineering Research Center of Bio-process of Ministry of Education, Hefei University of Technology, Hefei, China.
| | - Fanlin Zhou
- School of Food and Biological Engineering, Engineering Research Center of Bio-process of Ministry of Education, Hefei University of Technology, Hefei, China
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41
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Kumar P, Kumar P, Shrivastava A, Dar MA, Lokhande KB, Singh N, Singh A, Velayutham R, Mandal D. Immunoinformatics-based multi-epitope containing fused polypeptide vaccine design against visceral leishmaniasis with high immunogenicity and TLR binding. Int J Biol Macromol 2023; 253:127567. [PMID: 37866569 DOI: 10.1016/j.ijbiomac.2023.127567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/16/2023] [Accepted: 10/18/2023] [Indexed: 10/24/2023]
Abstract
Visceral leishmaniasis (VL) is the most lethal among all leishmaniasis diseases and remains categorized as a neglected tropical disease (NTD). This study aimed to develop a peptide-based multi-epitope vaccine construct against VL using immunoinformatics methodologies. To achieve this, four distinct proteins were screened to identify peptides consisting of 9-15 amino acids with high binding affinity to toll-like receptors (TLRs), strong antigenicity, low allergenicity, and minimal toxicity. The resulting multi-epitope vaccine construct was fused in a tandem arrangement with appropriate linker peptides and exhibited superior properties related to cytotoxic T lymphocytes (CTLs), helper T lymphocytes (HTLs), and B-cell epitopes. Subsequently, a three-dimensional (3D) model of the vaccine construct was generated, refined, and validated for structural stability and immune response capabilities. Molecular docking and simulations confirmed the vaccine construct's stability and binding affinities with TLRs, with TLR4 displaying the highest binding affinity, followed by TLR2 and TLR3. Additionally, simulations predicted robust cellular and humoral antibody-mediated immune responses elicited by the designed vaccine construct. Notably, this vaccine construct includes proteins from various pathways of Leishmania donovani (LD), which have not been previously utilized in VL vaccine design. Thus, this study opens new avenues for the development of vaccines against diverse protozoan diseases.
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Affiliation(s)
- Pawan Kumar
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER) Hajipur-Vaishali, Bihar 844102, India
| | - Prakash Kumar
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER) Hajipur-Vaishali, Bihar 844102, India
| | - Ashish Shrivastava
- Translational Bioinformatics and Computational Genomics Research Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
| | - Mukhtar Ahmad Dar
- Department of Pharmacy Practice, National Institute of Pharmaceutical Education and Research (NIPER) Hajipur-Vaishali, Bihar 844102, India
| | - Kiran Bharat Lokhande
- Translational Bioinformatics and Computational Genomics Research Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
| | - Nidhi Singh
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER) Ahmedabad, India
| | - Ashutosh Singh
- Translational Bioinformatics and Computational Genomics Research Lab, Department of Life Sciences, Shiv Nadar Institution of Eminence, Gautam Buddha Nagar, UP, India
| | - Ravichandiran Velayutham
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER) Hajipur-Vaishali, Bihar 844102, India; National Institute of Pharmaceutical Education and Research (NIPER) Kolkata, India
| | - Debabrata Mandal
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER) Hajipur-Vaishali, Bihar 844102, India.
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42
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Liu S, Wei S, Sun Y, Xu G, Zhang S, Li J. Molecular Characteristics, Functional Definitions, and Regulatory Mechanisms for Cross-Presentation Mediated by the Major Histocompatibility Complex: A Comprehensive Review. Int J Mol Sci 2023; 25:196. [PMID: 38203367 PMCID: PMC10778590 DOI: 10.3390/ijms25010196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 01/12/2024] Open
Abstract
The major histocompatibility complexes of vertebrates play a key role in the immune response. Antigen-presenting cells are loaded on MHC I molecules, which mainly present endogenous antigens; when MHC I presents exogenous antigens, this is called cross-presentation. The discovery of cross-presentation provides an important theoretical basis for the study of exogenous antigens. Cross-presentation is a complex process in which MHC I molecules present antigens to the cell surface to activate CD8+ T lymphocytes. The process of cross-representation includes many components, and this article briefly outlines the origins and development of MHC molecules, gene structures, functions, and their classical presentation pathways. The cross-presentation pathways of MHC I molecules, the cell lines that support cross-presentation, and the mechanisms of MHC I molecular transporting are all reviewed. After more than 40 years of research, the specific mechanism of cross-presentation is still unclear. In this paper, we summarize cross-presentation and anticipate the research and development prospects for cross-presentation.
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Affiliation(s)
| | | | | | | | - Shidong Zhang
- Engineering Technology Research Center of Traditional Chinese Veterinary Medicine of Gansu Province, Lanzhou Institute of Animal Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (S.L.); (S.W.); (Y.S.); (G.X.)
| | - Jianxi Li
- Engineering Technology Research Center of Traditional Chinese Veterinary Medicine of Gansu Province, Lanzhou Institute of Animal Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (S.L.); (S.W.); (Y.S.); (G.X.)
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43
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La Paglia L, Vazzana M, Mauro M, Urso A, Arizza V, Vizzini A. Bioactive Molecules from the Innate Immunity of Ascidians and Innovative Methods of Drug Discovery: A Computational Approach Based on Artificial Intelligence. Mar Drugs 2023; 22:6. [PMID: 38276644 PMCID: PMC10817596 DOI: 10.3390/md22010006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 12/12/2023] [Accepted: 12/17/2023] [Indexed: 01/27/2024] Open
Abstract
The study of bioactive molecules of marine origin has created an important bridge between biological knowledge and its applications in biotechnology and biomedicine. Current studies in different research fields, such as biomedicine, aim to discover marine molecules characterized by biological activities that can be used to produce potential drugs for human use. In recent decades, increasing attention has been paid to a particular group of marine invertebrates, the Ascidians, as they are a source of bioactive products. We describe omics data and computational methods relevant to identifying the mechanisms and processes of innate immunity underlying the biosynthesis of bioactive molecules, focusing on innovative computational approaches based on Artificial Intelligence. Since there is increasing attention on finding new solutions for a sustainable supply of bioactive compounds, we propose that a possible improvement in the biodiscovery pipeline might also come from the study and utilization of marine invertebrates' innate immunity.
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Affiliation(s)
- Laura La Paglia
- Istituto di Calcolo e Reti ad Alte Prestazioni–Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy; (L.L.P.); (A.U.)
| | - Mirella Vazzana
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche–Università di Palermo, Via Archirafi 18, 90100 Palermo, Italy; (M.V.); (M.M.); (V.A.)
| | - Manuela Mauro
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche–Università di Palermo, Via Archirafi 18, 90100 Palermo, Italy; (M.V.); (M.M.); (V.A.)
| | - Alfonso Urso
- Istituto di Calcolo e Reti ad Alte Prestazioni–Consiglio Nazionale delle Ricerche, Via Ugo La Malfa 153, 90146 Palermo, Italy; (L.L.P.); (A.U.)
| | - Vincenzo Arizza
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche–Università di Palermo, Via Archirafi 18, 90100 Palermo, Italy; (M.V.); (M.M.); (V.A.)
| | - Aiti Vizzini
- Dipartimento di Scienze e Tecnologie Biologiche, Chimiche e Farmaceutiche–Università di Palermo, Via Archirafi 18, 90100 Palermo, Italy; (M.V.); (M.M.); (V.A.)
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44
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Toribio L, Guzman C, Noazin S, Zimic-Sheen A, Zimic M, Gonzales I, Saavedra H, Pretell EJ, Bustos JA, Handali S, García HH. Multiantigen print immunoassay (MAPIA) for the diagnosis of neurocysticercosis: a single-center diagnostic optimization and accuracy study in Lima, Peru. J Clin Microbiol 2023; 61:e0076023. [PMID: 37966225 PMCID: PMC10729656 DOI: 10.1128/jcm.00760-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 09/21/2023] [Indexed: 11/16/2023] Open
Abstract
Neurocysticercosis (NCC) is the most common helminthic infection of the human central nervous system. The antibody detection assay of choice is the enzyme-linked immunoelectrotransfer blot assay using lentil-lectin purified parasite antigens (LLGP-EITB, Western blot), an immunoassay with exceptional performance in clinical samples. However, its use is mainly restricted to a few research laboratories because the assay is labor-intensive and requires sophisticated equipment, expertise, and large amounts of parasite material for preparation of reagents. We report a new immunoprint assay (MAPIA) that overcomes most of these barriers. We initially compared the performance of five different antigen combinations in a subset of defined samples in the MAPIA format. After selecting the best-performing assay format (a combination of rGP50 + rT24H + sTs14 antigens), 148 archived serum samples were tested, including 40 from individuals with parenchymal NCC, 40 with subarachnoid NCC, and 68 healthy controls with no evidence of neurologic disease. MAPIA using three antigens (rGP50 + rT24H + sTs14) was highly sensitive and specific for detecting antibodies in NCC. It detected 39 out of 40 (97.5%) parenchymal NCC cases and 40/40 (100%) subarachnoid cases and was negative in 67 out of 68 (98.53%) negative samples. MAPIA using three recombinant and synthetic antigens is a simple and economical tool with a performance equivalent to the LLGP-EITB assay for the detection of specific antibodies to NCC. The MAPIA overcomes existing barriers to adoption of the EITG LLGP and is a candidate for worldwide use.
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Affiliation(s)
- L. Toribio
- Cysticercosis Unit, Instituto Nacional de Ciencias Neurológicas, Lima, Peru
- Center for Global Health, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - C. Guzman
- Cysticercosis Unit, Instituto Nacional de Ciencias Neurológicas, Lima, Peru
- Center for Global Health, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - S. Noazin
- Department of International Health, Bloomberg School of Public Health. Johns Hopkins University, Baltimore, Maryland, USA
| | - A. Zimic-Sheen
- Bioinformatics Laboratory, Molecular Biology and Technological Developments, Faculty of Sciences and Philosophy, Universidad Peruana Cayetano Heredia, San Martín de Porres, Peru
| | - M. Zimic
- Bioinformatics Laboratory, Molecular Biology and Technological Developments, Faculty of Sciences and Philosophy, Universidad Peruana Cayetano Heredia, San Martín de Porres, Peru
| | - I. Gonzales
- Cysticercosis Unit, Instituto Nacional de Ciencias Neurológicas, Lima, Peru
| | - H. Saavedra
- Cysticercosis Unit, Instituto Nacional de Ciencias Neurológicas, Lima, Peru
| | - E. J. Pretell
- Hospital Nacional Alberto Sabogal Sologuren, ESSALUD, Callao, Peru
| | - J. A. Bustos
- Cysticercosis Unit, Instituto Nacional de Ciencias Neurológicas, Lima, Peru
- Center for Global Health, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - S. Handali
- Parasitic Diseases Branch, Division of Parasitic Diseases & Malaria, Center for Global Health, Centers for Disease Control & Prevention, Atlanta, Georgia, USA
| | - H. H. García
- Cysticercosis Unit, Instituto Nacional de Ciencias Neurológicas, Lima, Peru
- Center for Global Health, Universidad Peruana Cayetano Heredia, Lima, Peru
- Department of International Health, Bloomberg School of Public Health. Johns Hopkins University, Baltimore, Maryland, USA
| | - on behalf of The Cysticercosis Working Group in Peru
- Cysticercosis Unit, Instituto Nacional de Ciencias Neurológicas, Lima, Peru
- Center for Global Health, Universidad Peruana Cayetano Heredia, Lima, Peru
- Department of International Health, Bloomberg School of Public Health. Johns Hopkins University, Baltimore, Maryland, USA
- Bioinformatics Laboratory, Molecular Biology and Technological Developments, Faculty of Sciences and Philosophy, Universidad Peruana Cayetano Heredia, San Martín de Porres, Peru
- Hospital Nacional Alberto Sabogal Sologuren, ESSALUD, Callao, Peru
- Parasitic Diseases Branch, Division of Parasitic Diseases & Malaria, Center for Global Health, Centers for Disease Control & Prevention, Atlanta, Georgia, USA
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Marques PH, Rodrigues TCV, Santos EH, Bleicher L, Aburjaile FF, Martins FS, Oliveira CJF, Azevedo V, Tiwari S, Soares S. Design of a multi-epitope vaccine (vme-VAC/MST-1) against cholera and vibriosis based on reverse vaccinology and immunoinformatics approaches. J Biomol Struct Dyn 2023:1-16. [PMID: 38112302 DOI: 10.1080/07391102.2023.2293256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 11/25/2023] [Indexed: 12/21/2023]
Abstract
Vibriosis and cholera are serious diseases distributed worldwide and caused by six marine bacteria of the Vibrio genus. Thousands of deaths occur each year due to these illnesses, necessitating the development of new preventive measures. Presently, the existing cholera vaccine demonstrates an effectiveness of approximately 60%. Here we describe a new multi-epitope vaccine, 'vme-VAC/MST-1' based on vaccine targets identified by reverse vaccinology and epitopes predicted by immunoinformatics, two currently effective tools for predicting new vaccines for bacterial pathogens. The vaccine was designed to combat vibriosis and cholera by incorporating epitopes predicted for CTL, HTL, and B cells. These epitopes were identified from six vaccine targets revealed through subtractive genomics, combined with reverse vaccinology, and were further filtered using immunoinformatics approaches based on their predicted immunogenicity. To construct the vaccine, 28 epitopes (24 CTL/B and 4 HTL/B) were linked to the sequence of the cholera toxin B subunit adjuvant. In silico analyses indicate that the resulting immunogen is stable, soluble, non-toxic, and non-allergenic. Furthermore, it exhibits no homology to the host and demonstrates a strong capacity to elicit innate, B-cell, and T-cell immune responses. Our analysis suggests that it is likely to elicit immune reactions mediated through the TLR5 pathway, as evidenced by the molecular docking of the vaccine with the receptor, which revealed high affinity and a favorable reaction. Thus, vme-VAC/MST-1 is predicted to be a safe and effective solution against pathogenic Vibrio spp. However, further experimental analyses are required to measure the vaccine's effects In vivo.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Pedro Henrique Marques
- Institute of Biological Sciences, Post-graduate Interunits Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
- Department of Preventive Veterinary Medicine, School of Veterinary Medicine, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Thais Cristina Vilela Rodrigues
- Department of Genetics, Ecology and Evolution, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Eduardo Horta Santos
- Institute of Biological Sciences, Post-graduate Interunits Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
- Department of Biochemistry and Immunology, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Lucas Bleicher
- Department of Biochemistry and Immunology, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Flavia Figueira Aburjaile
- Department of Preventive Veterinary Medicine, School of Veterinary Medicine, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Flaviano S Martins
- Department of Microbiology, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Carlo Jose Freire Oliveira
- Department of Microbiology, Immunology and Parasitology, Institute of Biological Sciences, Federal University of Triângulo Mineiro, Uberaba, MG, Brazil
| | - Vasco Azevedo
- Department of Genetics, Ecology and Evolution, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Sandeep Tiwari
- Institute of Biology, Federal University of Bahia, Salvador, BA, Brazil
- Institute of Health Sciences, Federal University of Bahia, Salvador, BA, Brazil
| | - Siomar Soares
- Department of Microbiology, Immunology and Parasitology, Institute of Biological Sciences, Federal University of Triângulo Mineiro, Uberaba, MG, Brazil
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46
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Sulfianti A, Karimah N, Nurhasanah A. In silico analysis of HLA-1 and HLA-2 recognition of a designed recombinant human papillomavirus vaccine based on L1 protein HPV subtype 45. J Genet Eng Biotechnol 2023; 21:167. [PMID: 38091180 PMCID: PMC10719189 DOI: 10.1186/s43141-023-00593-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 11/06/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND Human leukocyte antigen (HLA) can bind and present the processed antigenic peptide derived from the vaccine to the T cell receptor, and this capability is crucial in determining the effectivity of the vaccine to terminate virus-infected cells, activate macrophages, and induce B cells to produce antibodies. A recombinant vaccine candidate based on protein L1 HPV45 was designed and analysed whether it is recognisable by T cells through the binding of their epitopes to HLAs. METHODS The study consisted of two parts: part one was the analysis of the L1 recombinant protein binding to HLA-1 and 2 epitopes, whereas part two was the distribution analysis of HPV-linked HLA allele. HLA allele sets found at high frequency in the general population and in specific Indonesian population were listed for the binding analysis of the recombinant L1 HPV45 protein. In part one, immunoepitope servers from IEDB were used to predict the binding of the designed proteins to HLA alleles. The prediction method for MHC-I binding prediction was the NetMHCpan EL 4.1 whilst for MHC-II binding prediction was the Consensus approach. Antigenicity analysis for each peptide was conducted using VaxiJen 2.0 with the threshold 1.0 to select the highly antigenic peptides, and positions of these epitopes in the secondary and tertiary structure of the recombinant protein were also predicted. The percent population coverage of the alleles capable of binding to these epitopes worldwide was also estimated. In part two, the worldwide distribution and frequency of HPV-related HLA-1 and 2 were studied. RESULT Two highly antigenic peptides (EEYDLQFIF and KLKFWTVDLK) were recognised by high-frequency HLA-1 alleles in both, the general and Western Javanese. In addition to these two epitopes, a few more peptides are also recognised by the high-frequency Western Javanese HLA-1 alleles, which are not in Weiskopf's list of high-frequency HLA-1 alleles in the general population. Analysis of the highly antigenic epitopes binding to HLA-DRB1 alleles in general (YIKGTSANM) and Western Javanese (LRRRPTIGP) populations showed that these peptide cores associate to HLA-DRB1*04, albeit the different sub-types, due to the presence of different allele in each population group. Analysis of the epitopes and the positive binding alleles showed on average 25.65% population coverage. CONCLUSION The recombinant vaccine candidate based on protein L1 HPV45 is presumed to contain highly antigenic peptides that can bind to high-frequency HLA-1 and 2 alleles present in general and Western Javanese populations. It was expected that the protein is capable of eliciting T cell-mediated responses in both populations; however, in vitro study is needed to prove the protectiveness of the designed recombinant protein.
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Affiliation(s)
- Asri Sulfianti
- Centre for Vaccine and Drug Research, National Research and Innovation Agency Republic of Indonesia, LAPTIAB 1, Gedung 611, Kawasan Puspiptek Serpong, Tangerang Selatan, Banten, 15314, Indonesia
| | - Nihayatul Karimah
- Centre for Vaccine and Drug Research, National Research and Innovation Agency Republic of Indonesia, LAPTIAB 1, Gedung 611, Kawasan Puspiptek Serpong, Tangerang Selatan, Banten, 15314, Indonesia
| | - Astutiati Nurhasanah
- Centre for Vaccine and Drug Research, National Research and Innovation Agency Republic of Indonesia, LAPTIAB 1, Gedung 611, Kawasan Puspiptek Serpong, Tangerang Selatan, Banten, 15314, Indonesia.
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Razali SA, Shamsir MS, Ishak NF, Low CF, Azemin WA. Riding the wave of innovation: immunoinformatics in fish disease control. PeerJ 2023; 11:e16419. [PMID: 38089909 PMCID: PMC10712311 DOI: 10.7717/peerj.16419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 10/17/2023] [Indexed: 12/18/2023] Open
Abstract
The spread of infectious illnesses has been a significant factor restricting aquaculture production. To maximise aquatic animal health, vaccination tactics are very successful and cost-efficient for protecting fish and aquaculture animals against many disease pathogens. However, due to the increasing number of immunological cases and their complexity, it is impossible to manage, analyse, visualise, and interpret such data without the assistance of advanced computational techniques. Hence, the use of immunoinformatics tools is crucial, as they not only facilitate the management of massive amounts of data but also greatly contribute to the creation of fresh hypotheses regarding immune responses. In recent years, advances in biotechnology and immunoinformatics have opened up new research avenues for generating novel vaccines and enhancing existing vaccinations against outbreaks of infectious illnesses, thereby reducing aquaculture losses. This review focuses on understanding in silico epitope-based vaccine design, the creation of multi-epitope vaccines, the molecular interaction of immunogenic vaccines, and the application of immunoinformatics in fish disease based on the frequency of their application and reliable results. It is believed that it can bridge the gap between experimental and computational approaches and reduce the need for experimental research, so that only wet laboratory testing integrated with in silico techniques may yield highly promising results and be useful for the development of vaccines for fish.
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Affiliation(s)
- Siti Aisyah Razali
- Faculty of Science and Marine Environment, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia
- Biological Security and Sustainability Research Interest Group (BIOSES), Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia
| | - Mohd Shahir Shamsir
- Department of Biosciences, Faculty of Science, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia
| | - Nur Farahin Ishak
- Faculty of Science and Marine Environment, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia
| | - Chen-Fei Low
- Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Wan-Atirah Azemin
- School of Biological Sciences, Universiti Sains Malaysia, Minden, Pulau Pinang, Malaysia
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Mao Y, Xiao X, Zhang J, Mou X, Zhao W. Designing a multi-epitope vaccine against Peptostreptococcus anaerobius based on an immunoinformatics approach. Synth Syst Biotechnol 2023; 8:757-770. [PMID: 38099061 PMCID: PMC10720267 DOI: 10.1016/j.synbio.2023.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/15/2023] [Accepted: 11/15/2023] [Indexed: 12/17/2023] Open
Abstract
Peptostreptococcus anaerobius is an anaerobic bacterium, which has been found selectively en-riched in the fecal and mucosal microbiota of colorectal cancer (CRC) patients. Emerging evidence suggest P. anaerobius may contribute to the development of CRC in human. In this study, we designed a multi-epitope chimeric vaccine against P. anaerobius PCWBR2, a recently identified adhesin that interacts directly with colon cell lines by binding α2/β1 integrin frequently overexpressed in human CRC tumors and cell lines. Immunoinformatics tools predicted six cytotoxic T lymphocyte epitopes, five helper T lymphocyte epitopes, and six linear B lymphocyte epitopes. The predicted epitopes were joined with AAY or GPGPG linkers and a previously reported TLR4 agonist was added to the vaccine construct's N terminal as an adjuvant using EAAAK linkers and the order of epitopes was optimized. Further in silico analysis revealed that the vaccine construct possesses satisfactory antigenicity, allergenicity, solubility, physicochemical properties, adjuvant-TLR4 molecular docking, and immune profile characteristics. Our study provided a promising design for vaccines against P. anaerobius.
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Affiliation(s)
- Yudan Mao
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
| | - Xianzun Xiao
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
| | - Jie Zhang
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
| | - Xiangyu Mou
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
| | - Wenjing Zhao
- Shenzhen Key Laboratory of Systems Medicine for Inflammatory Diseases, School of Medicine, Shenzhen Campus of Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
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Kumari S, Kessel A, Singhal D, Kaur G, Bern D, Lemay-St-Denis C, Singh J, Jain S. Computational identification of a multi-peptide vaccine candidate in E2 glycoprotein against diverse Hepatitis C virus genotypes. J Biomol Struct Dyn 2023; 41:11044-11061. [PMID: 37194293 DOI: 10.1080/07391102.2023.2212777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 12/11/2022] [Indexed: 05/18/2023]
Abstract
Hepatitis C Virus (HCV) is estimated to affect nearly 180 million people worldwide, culminating in ∼0.7 million yearly casualties. However, a safe vaccine against HCV is not yet available. This study endeavored to identify a multi-genotypic, multi-epitopic, safe, and globally competent HCV vaccine candidate. We employed a consensus epitope prediction strategy to identify multi-epitopic peptides in all known envelope glycoprotein (E2) sequences, belonging to diverse HCV genotypes. The obtained peptides were screened for toxicity, allergenicity, autoimmunity and antigenicity, resulting in two favorable peptides viz., P2 (VYCFTPSPVVVG) and P3 (YRLWHYPCTV). Evolutionary conservation analysis indicated that P2 and P3 are highly conserved, supporting their use as part of a designed multi-genotypic vaccine. Population coverage analysis revealed that P2 and P3 are likely to be presented by >89% Human Leukocyte Antigen (HLA) molecules from six geographical regions. Indeed, molecular docking predicted the physical binding of P2 and P3 to various representative HLAs. We designed a vaccine construct using these peptides and assessed its binding to toll-like receptor 4 (TLR-4) by molecular docking and simulation. Subsequent analysis by energy-based and machine learning tools predicted high binding affinity and pinpointed the key binding residues (i.e. hotspots) in P2 and P3. Also, a favorable immunogenic profile of the construct was predicted by immune simulations. We encourage the scientific community to validate our vaccine construct in vitro and in vivo.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Shweta Kumari
- University Institute of Biotechnology, Chandigarh University, Mohali, Punjab, India
| | - Amit Kessel
- Department of Biochemistry and Molecular Biology, Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv, Israel
| | - Divya Singhal
- University Institute of Biotechnology, Chandigarh University, Mohali, Punjab, India
| | - Gurpreet Kaur
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala, Punjab, India
| | - David Bern
- Department of Biochemistry and Molecular Biology, Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv, Israel
| | - Claudèle Lemay-St-Denis
- Department of Biochemistry and Molecular Medicine, Université de Montréal, Montréal, QC, Canada
- PROTEO, The Québec Network for Research on Protein, Function, Engineering and Applications, Québec, QC, Canada
- CGCC, Center in Green Chemistry and Catalysis, Montréal, QC, Canada
| | - Jasdeep Singh
- University Institute of Biotechnology, Chandigarh University, Mohali, Punjab, India
| | - Sahil Jain
- University Institute of Biotechnology, Chandigarh University, Mohali, Punjab, India
- Department of Biochemistry and Molecular Biology, Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv, Israel
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Mohapatra S, Kumar S, Kumar S, Singh AK, Nayak B. Immunodominant conserved moieties on spike protein of SARS-CoV-2 renders virulence factor for the design of epitope-based peptide vaccines. Virusdisease 2023; 34:456-482. [PMID: 38046066 PMCID: PMC10686954 DOI: 10.1007/s13337-023-00852-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 11/03/2023] [Indexed: 12/05/2023] Open
Abstract
The outbreak of novel SARS-CoV-2 virion has wreaked havoc with a high prevalence of respiratory illness and high transmission due to a vague understanding of the viral antigenicity, augmenting the dire challenge to public health globally. This viral member necessitates the expansion of diagnostic and therapeutic tools to track its transmission and confront it through vaccine development. Therefore, prophylactic strategies are mandatory. Virulent spike proteins can be the most desirable candidate for the computational design of vaccines targeting SARS-CoV-2, followed by the meteoric development of immune epitopes. Spike protein was characterized using existing bioinformatics tools with a unique roadmap related to the immunological profile of SARS-CoV-2 to predict immunogenic virulence epitopes based on antigenicity, allergenicity, toxicity, immunogenicity, and population coverage. Applying in silico approaches, a set of twenty-four B lymphocyte-based epitopes and forty-six T lymphocyte-based epitopes were selected. The predicted epitopes were evaluated for their intrinsic properties. The physico-chemical characterization of epitopes qualifies them for further in vitro and in vivo analysis and pre-requisite vaccine development. This study presents a set of screened epitopes that bind to HLA-specific allelic proteins and can be employed for designing a peptide vaccine construct against SARS-CoV-2 that will confer vaccine-induced protective immunity due to its structural stability. Supplementary Information The online version contains supplementary material available at 10.1007/s13337-023-00852-9.
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Affiliation(s)
- Subhashree Mohapatra
- Immunology and Molecular Medicine Laboratory, Department of Life Science, National Institute of Technology Rourkela, Rourkela, Odisha 769008 India
| | - Santosh Kumar
- RNA Biology Laboratory, Department of Life Science, National Institute of Technology Rourkela, Rourkela, Odisha 769008 India
| | - Shashank Kumar
- Molecular Signalling and Drug Discovery Laboratory, Department of Biochemistry, Central University of Punjab, Bathinda, Punjab 151401 India
| | - Atul Kumar Singh
- Molecular Signalling and Drug Discovery Laboratory, Department of Biochemistry, Central University of Punjab, Bathinda, Punjab 151401 India
| | - Bismita Nayak
- Immunology and Molecular Medicine Laboratory, Department of Life Science, National Institute of Technology Rourkela, Rourkela, Odisha 769008 India
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