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Ritaparna P, Ray M, Dhal AK, Mahapatra RK. An immunoinformatics approach for design and validation of multi-subunit vaccine against Plasmodium falciparum from essential hypothetical proteins. J Parasit Dis 2024; 48:593-609. [PMID: 39145352 PMCID: PMC11319695 DOI: 10.1007/s12639-024-01696-w] [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: 04/15/2024] [Accepted: 06/11/2024] [Indexed: 08/16/2024] Open
Abstract
Malaria, caused by Plasmodium falciparum, remains a pressing global health concern. Advancements in combating this parasite involve the development of a protein vaccine. This study employs immunoinformatics to identify potential vaccine candidates within the repertoire of 218 P. falciparum exported essential proteins identified through saturaturation mutagenesis study. Our screening approach narrows down to 65 Plasmodium-exported proteins with uncharacterized functions while exhibiting non-mutability in CDS (coding sequences). The transmembrane helix, antigenicity, allergenicity of the shortlisted proteins was assessed through diverse prediction algorithm, culminating in the identification of five promising vaccination contenders, based on probability scores. We discerned B-cell, helper T-lymphocyte, and cytotoxic T-lymphocyte epitopes. Two proteins with the most favorable epitope were harnessed to construct a multi-subunit vaccine, through judicious linker integration. Employing the I-TASSER software, three-dimensional models of the constituent proteins was obtained and was validated using diverse tools like ProSA, VERIFY3D, and ERRAT. The modelled proteins underwent Molecular Dynamics (MD) simulation in a solvent environment to evaluate the stability of the multi-subunit vaccine. Furthermore, we conducted molecular docking through the ClusPro web server to elucidate potential interactions with Toll-like receptors (TLR2 and TLR4). Docking scores revealed a pronounced affinity of the multi-subunit vaccine for TLR2. Significantly, 100 ns MD simulation of the protein-receptor complex unveiled a persistent hydrogen bond linkage between the ARG63 residue of the sub-unit vaccine and the GLU32 residue of the TLR2 receptor. These findings collectively advocate the potential efficacy of the first multi-subunit vaccine from the potential hypothetical proteins of P. falciparum. Supplementary Information The online version contains supplementary material available at 10.1007/s12639-024-01696-w.
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Affiliation(s)
- Prajna Ritaparna
- School of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha 751024 India
- National Innovation Foundation, India, KIIT-TBI, Bhubaneswar, Odisha 751024 India
| | - Muskan Ray
- School of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha 751024 India
| | - Ajit Kumar Dhal
- School of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha 751024 India
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2
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Ahmed MH, Samia NSN, Singh G, Gupta V, Mishal MFM, Hossain A, Suman KH, Raza A, Dutta AK, Labony MA, Sultana J, Faysal EH, Alnasser SM, Alam P, Azam F. An immuno-informatics approach for annotation of hypothetical proteins and multi-epitope vaccine designed against the Mpox virus. J Biomol Struct Dyn 2024; 42:5288-5307. [PMID: 37519185 DOI: 10.1080/07391102.2023.2239921] [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: 04/02/2023] [Accepted: 06/09/2023] [Indexed: 08/01/2023]
Abstract
A worrying new outbreak of Monkeypox (Mpox) in humans is caused by the Mpox virus (MpoxV). The pathogen has roughly 28 hypothetical proteins of unknown structure, function, and pathogenicity. Using reliable bioinformatics tools, we attempted to analyze the MpoxV genome, identify the role of hypothetical proteins (HPs), and design a potential candidate vaccine. Out of 28, we identified seven hypothetical proteins using multi-server validation with high confidence for the occurrence of conserved domains. Their physical, chemical, and functional characterizations, including molecular weight, theoretical isoelectric point, 3D structures, GRAVY value, subcellular localization, functional motifs, antigenicity, and virulence factors, were performed. We predicted possible cytotoxic T cell (CTL), helper T cell (HTL) and linear and conformational B cell epitopes, which were combined in a 219 amino acid multiepitope vaccine with human β defensin as a linker. This multi-epitopic vaccine was structurally modelled and docked with toll-like receptor-3 (TLR-3). The dynamical stability of the vaccine-TLR-3 docked complexes exhibited stable interactions based on RMSD and RMSF tests. Additionally, the modelled vaccine was cloned in-silico in an E. coli host to check the appropriate expression of the final vaccine built. Our results might conform to an immunogenic and safe vaccine, which would require further experimental validation.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Md Hridoy Ahmed
- Department of Genetic Engineering and Biotechnology, University of Chittagong, Chittagong, Bangladesh
| | - Nure Sharaf Nower Samia
- Department of Life Sciences (DLS), School of Environment and Life Sciences (SELS), Independent University, Dhaka, Bangladesh
| | - Gagandeep Singh
- Kusuma School of Biological Sciences, Indian Institute of Technology, New Delhi, India
- Section of Microbiology, Central Ayurveda Research Institute, Jhansi CCRAS, Ministry of Ayush, India
| | - Vandana Gupta
- Department of Microbiology, Ram Lal Anand College, University of Delhi, New Delhi, India
| | | | - Alomgir Hossain
- Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, Bangladesh
| | | | - Adnan Raza
- Bioscience department, COMSATS University of Islamabad, Islamabad, Pakistan
| | - Amit Kumar Dutta
- Department of Microbiology, University of Rajshahi, Rajshahi, Bangladesh
| | - Moriom Akhter Labony
- Department of Genetic Engineering and Biotechnology, University of Chittagong, Chittagong, Bangladesh
| | - Jakia Sultana
- Department of Botany, University of Rajshahi, Rajshahi, Bangladesh
| | | | - Sulaiman Mohammed Alnasser
- Department of Pharmacology and Toxicology, Unaizah College of Pharmacy, Qassim University, Buraydah, Saudi Arabia
| | - Prawez Alam
- Department of Pharmacognosy, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al Kharj, Saudi Arabia
| | - Faizul Azam
- Department of Pharmaceutical Chemistry and Pharmacognosy, Unaizah College of Pharmacy, Qassim University, Buraydah, Saudi Arabia
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Khan MF, Ali A, Rehman HM, Noor Khan S, Hammad HM, Waseem M, Wu Y, Clark TG, Jabbar A. Exploring optimal drug targets through subtractive proteomics analysis and pangenomic insights for tailored drug design in tuberculosis. Sci Rep 2024; 14:10904. [PMID: 38740859 DOI: 10.1038/s41598-024-61752-6] [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] [Received: 11/19/2023] [Accepted: 05/09/2024] [Indexed: 05/16/2024] Open
Abstract
Tuberculosis (TB), caused by Mycobacterium tuberculosis, ranks among the top causes of global human mortality, as reported by the World Health Organization's 2022 TB report. The prevalence of M. tuberculosis strains that are multiple and extensive-drug resistant represents a significant barrier to TB eradication. Fortunately, having many completely sequenced M. tuberculosis genomes available has made it possible to investigate the species pangenome, conduct a pan-phylogenetic investigation, and find potential new drug targets. The 442 complete genome dataset was used to estimate the pangenome of M. tuberculosis. This study involved phylogenomic classification and in-depth analyses. Sequential filters were applied to the conserved core genome containing 2754 proteins. These filters assessed non-human homology, virulence, essentiality, physiochemical properties, and pathway analysis. Through these intensive filtering approaches, promising broad-spectrum therapeutic targets were identified. These targets were docked with FDA-approved compounds readily available on the ZINC database. Selected highly ranked ligands with inhibitory potential include dihydroergotamine and abiraterone acetate. The effectiveness of the ligands has been supported by molecular dynamics simulation of the ligand-protein complexes, instilling optimism that the identified lead compounds may serve as a robust basis for the development of safe and efficient drugs for TB treatment, subject to further lead optimization and subsequent experimental validation.
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Affiliation(s)
- Muhammad Fayaz Khan
- Department of Medical Laboratory Technology, The University of Haripur, Haripur, KP, Pakistan
| | - Amjad Ali
- Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan
| | - Hafiz Muzzammel Rehman
- School of Biochemistry and Biotechnology, University of the Punjab, Lahore, Punjab, Pakistan
| | - Sadiq Noor Khan
- Department of Medical Laboratory Technology, The University of Haripur, Haripur, KP, Pakistan
| | - Hafiz Muhammad Hammad
- School of Biochemistry and Biotechnology, University of the Punjab, Lahore, Punjab, Pakistan
| | - Maaz Waseem
- Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan
| | - Yurong Wu
- Department of Chemistry, The Hong Kong University of Science and Technology, Kowloon, Hong Kong, China
| | - Taane G Clark
- London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
| | - Abdul Jabbar
- Department of Medical Laboratory Technology, The University of Haripur, Haripur, KP, Pakistan.
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4
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Chou RT, Ouattara A, Adams M, Berry AA, Takala-Harrison S, Cummings MP. Positive-unlabeled learning identifies vaccine candidate antigens in the malaria parasite Plasmodium falciparum. NPJ Syst Biol Appl 2024; 10:44. [PMID: 38678051 PMCID: PMC11055854 DOI: 10.1038/s41540-024-00365-1] [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: 06/14/2023] [Accepted: 03/29/2024] [Indexed: 04/29/2024] Open
Abstract
Malaria vaccine development is hampered by extensive antigenic variation and complex life stages of Plasmodium species. Vaccine development has focused on a small number of antigens, many of which were identified without utilizing systematic genome-level approaches. In this study, we implement a machine learning-based reverse vaccinology approach to predict potential new malaria vaccine candidate antigens. We assemble and analyze P. falciparum proteomic, structural, functional, immunological, genomic, and transcriptomic data, and use positive-unlabeled learning to predict potential antigens based on the properties of known antigens and remaining proteins. We prioritize candidate antigens based on model performance on reference antigens with different genetic diversity and quantify the protein properties that contribute most to identifying top candidates. Candidate antigens are characterized by gene essentiality, gene ontology, and gene expression in different life stages to inform future vaccine development. This approach provides a framework for identifying and prioritizing candidate vaccine antigens for a broad range of pathogens.
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Affiliation(s)
- Renee Ti Chou
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Amed Ouattara
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Matthew Adams
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Andrea A Berry
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Shannon Takala-Harrison
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Michael P Cummings
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA.
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5
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Musundi SD, Gitaka J, Kanoi BN. Identification of conserved cross-species B-cell linear epitopes in human malaria: a subtractive proteomics and immuno-informatics approach targeting merozoite stage proteins. Front Immunol 2024; 15:1352618. [PMID: 38404581 PMCID: PMC10884153 DOI: 10.3389/fimmu.2024.1352618] [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: 12/08/2023] [Accepted: 01/25/2024] [Indexed: 02/27/2024] Open
Abstract
Human malaria, caused by five Plasmodium species (P. falciparum, P. vivax, P. malariae, P. ovale, and P. knowlesi), remains a significant global health burden. While most interventions target P. falciparum, the species associated with high mortality rates and severe clinical symptoms, non-falciparum species exhibit different transmission dynamics, remain hugely neglected, and pose a significant challenge to malaria elimination efforts. Recent studies have reported the presence of antigens associated with cross-protective immunity, which can potentially disrupt the transmission of various Plasmodium species. With the sequencing of the Plasmodium genome and the development of immunoinformatic tools, in this study, we sought to exploit the evolutionary history of Plasmodium species to identify conserved cross-species B-cell linear epitopes in merozoite proteins. We retrieved Plasmodium proteomes associated with human malaria and applied a subtractive proteomics approach focusing on merozoite stage proteins. Bepipred 2.0 and Epidope were used to predict B-cell linear epitopes using P. falciparum as the reference species. The predictions were further compared against human and non-falciparum databases and their antigenicity, toxicity, and allergenicity assessed. Subsequently, epitope conservation was carried out using locally sequenced P. falciparum isolates from a malaria-endemic region in western Kenya (n=27) and Kenyan isolates from MalariaGEN version 6 (n=131). Finally, physiochemical characteristics and tertiary structure of the B-cell linear epitopes were determined. The analysis revealed eight epitopes that showed high similarity (70-100%) between falciparum and non-falciparum species. These epitopes were highly conserved when assessed across local isolates and those from the MalariaGEN database and showed desirable physiochemical properties. Our results show the presence of conserved cross-species B-cell linear epitopes that could aid in targeting multiple Plasmodium species. Nevertheless, validating their efficacy in-vitro and in-vivo experimentally is essential.
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Affiliation(s)
| | | | - Bernard N. Kanoi
- Centre for Malaria Elimination, Institute of Tropical Medicine, Mount Kenya University, Thika, Kenya
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Devarakonda Y, Reddy MVNJ, Neethu RS, Chandran A, Syal K. Multi epitope vaccine candidate design against Streptococcus pneumonia. J Biomol Struct Dyn 2023; 41:12654-12667. [PMID: 36636838 DOI: 10.1080/07391102.2023.2167123] [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: 06/29/2022] [Accepted: 01/05/2023] [Indexed: 01/14/2023]
Abstract
Streptococcus pneumonia, the causative agent of sepsis, meningitis and pneumonia, is held responsible for causing invasive diseases predominantly in children along with adults from both developing and developed countries. The available vaccines coverage in the context of different serotypes is limited and emergence of non-vaccine serotypes could further emerge as a threat in future. Advanced immunoinformatics tools have been used for developing a multi epitope subunit vaccine. In the current study we have subjected these four surface antigenic proteins Ply, PsaA, PspA and PspK to construct vaccine designs. We have predicted different B-cell and T-cell epitopes by using NetCTL 1.2, IEDB (Immune Epitope Databases) and ABCpred. An adjuvant (griselimycin) has been added to the vaccine construct sequence in order to improve its immunogenicity. The vaccine construct has been evaluated for its antigenicity, allergenicity, toxicity and different physio-chemical properties. The bioinformatic tools have been used for prediction, refinement and validation of the 3 D structure. Further, the vaccine structure has been docked with a toll-like receptor (TLR-4) by ClusPro 2.0. In conclusion, the proposed multi-epitope vaccine designs could potentially activate both humoral and cellular immune responses and has a potential to be a vaccine candidate against S.pneumoniae, and requires experimental validation for ensuring immunogenicity and safety profile.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Yogeshwar Devarakonda
- Department of Biological Sciences, Center for Genetics and Molecular Microbiology, Institute of Eminence, Birla Institute of Technology and Sciences-Pilani, Hyderabad, India
| | - M V N Janaradhan Reddy
- Department of Biological Sciences, Center for Genetics and Molecular Microbiology, Institute of Eminence, Birla Institute of Technology and Sciences-Pilani, Hyderabad, India
| | - R S Neethu
- Department of Biological Sciences, Center for Genetics and Molecular Microbiology, Institute of Eminence, Birla Institute of Technology and Sciences-Pilani, Hyderabad, India
| | - Aneesh Chandran
- Department of Biotechnology and Microbiology, Kannur University, Kannur, India
| | - Kirtimaan Syal
- Department of Biological Sciences, Center for Genetics and Molecular Microbiology, Institute of Eminence, Birla Institute of Technology and Sciences-Pilani, Hyderabad, India
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7
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Engineering Modified mRNA-Based Vaccine against Dengue Virus Using Computational and Reverse Vaccinology Approaches. Int J Mol Sci 2022; 23:ijms232213911. [PMID: 36430387 PMCID: PMC9698390 DOI: 10.3390/ijms232213911] [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: 10/10/2022] [Revised: 11/07/2022] [Accepted: 11/07/2022] [Indexed: 11/16/2022] Open
Abstract
Dengue virus belonging to the family Flaviviridae and its four serotypes are responsible for dengue infections, which extend over 60 countries in tropical and subtropical areas of the world including Pakistan. During the ongoing dengue outbreak in Pakistan (2022), over 30,000 cases have been reported, and over 70 lives have been lost. The only commercialized vaccine against DENV, Dengvaxia, cannot be administered as a prophylactic measure to cure this infection due to various complications. Using machine learning and reverse vaccinology approaches, this study was designed to develop a tetravalent modified nucleotide mRNA vaccine using NS1, prM, and EIII sequences of dengue virus from Pakistani isolates. Based on high antigenicity, non-allergenicity, and toxicity profiling, B-cell epitope, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) putative vaccine targets were predicted. Molecular docking confirmed favorable interactions between T-cell epitopes and their respective HLA alleles, while normal mode analysis validated high-affinity interactions of vaccine proteins with immune receptors. In silico immune simulations confirmed adequate immune responses to eliminate the antigen and generate memory. Codon optimization, physicochemical features, nucleotide modifications, and suitable vector availability further ensured better antigen expression and adaptive immune responses. We predict that this vaccine construct may prove to be a good vaccinal candidate against dengue virus in vitro as well.
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Genome-Based Multi-Antigenic Epitopes Vaccine Construct Designing against Staphylococcus hominis Using Reverse Vaccinology and Biophysical Approaches. Vaccines (Basel) 2022; 10:vaccines10101729. [PMID: 36298594 PMCID: PMC9611379 DOI: 10.3390/vaccines10101729] [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: 09/01/2022] [Revised: 10/11/2022] [Accepted: 10/14/2022] [Indexed: 11/07/2022] Open
Abstract
Staphylococcus hominis is a Gram-positive bacterium from the staphylococcus genus; it is also a member of coagulase-negative staphylococci because of its opportunistic nature and ability to cause life-threatening bloodstream infections in immunocompromised patients. Gram-positive and opportunistic bacteria have become a major concern for the medical community. It has also drawn the attention of scientists due to the evaluation of immune evasion tactics and the development of multidrug-resistant strains. This prompted the need to explore novel therapeutic approaches as an alternative to antibiotics. The current study aimed to develop a broad-spectrum, multi-epitope vaccine to control bacterial infections and reduce the burden on healthcare systems. A computational framework was designed to filter the immunogenic potent vaccine candidate. This framework consists of pan-genomics, subtractive proteomics, and immunoinformatics approaches to prioritize vaccine candidates. A total of 12,285 core proteins were obtained using a pan-genome analysis of all strains. The screening of the core proteins resulted in the selection of only two proteins for the next epitope prediction phase. Eleven B-cell derived T-cell epitopes were selected that met the criteria of different immunoinformatics approaches such as allergenicity, antigenicity, immunogenicity, and toxicity. A vaccine construct was formulated using EAAAK and GPGPG linkers and a cholera toxin B subunit. This formulated vaccine construct was further used for downward analysis. The vaccine was loop refined and improved for structure stability through disulfide engineering. For an efficient expression, the codons were optimized as per the usage pattern of the E coli (K12) expression system. The top three refined docked complexes of the vaccine that docked with the MHC-I, MHC-II, and TLR-4 receptors were selected, which proved the best binding potential of the vaccine with immune receptors; this was followed by molecular dynamic simulations. The results indicate the best intermolecular bonding between immune receptors and vaccine epitopes and that they are exposed to the host’s immune system. Finally, the binding energies were calculated to confirm the binding stability of the docked complexes. This work aimed to provide a manageable list of immunogenic and antigenic epitopes that could be used as potent vaccine candidates for experimental in vivo and in vitro studies.
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Dhanda SK, Malviya J, Gupta S. Not all T cell epitopes are equally desired: a review of in silico tools for the prediction of cytokine-inducing potential of T-cell epitopes. Brief Bioinform 2022; 23:6692551. [PMID: 36070623 DOI: 10.1093/bib/bbac382] [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: 06/07/2022] [Revised: 08/01/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
Assessment of protective or harmful T cell response induced by any antigenic epitope is important in designing any immunotherapeutic molecule. The understanding of cytokine induction potential also helps us to monitor antigen-specific cellular immune responses and rational vaccine design. The classical immunoinformatics tools served well for prediction of B cell and T cell epitopes. However, in the last decade, the prediction algorithms for T cell epitope inducing specific cytokines have also been developed and appreciated in the scientific community. This review summarizes the current status of such tools, their applications, background algorithms, their use in experimental setup and functionalities available in the tools/web servers.
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Affiliation(s)
- Sandeep Kumar Dhanda
- Department of Oncology, St Jude Children's Research Hospital, Memphis, Tennessee, USA-38015.,Center for Transdisciplinary Research, Department of Pharmacology, Saveetha Dental College, Saveetha Institute of Medical and Technical Science, Chennai, India
| | - Jitendra Malviya
- Department of Life Sciences and Biological Science, IES University Bhopal, India
| | - Sudheer Gupta
- NGS & Bioinformatics Division, 3B BlackBio Biotech India Ltd., 7-C, Industrial Area, Govindpura, Bhopal, India
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Deciphering the Potential Coding of Human Cytomegalovirus: New Predicted Transmembrane Proteome. Int J Mol Sci 2022; 23:ijms23052768. [PMID: 35269907 PMCID: PMC8911422 DOI: 10.3390/ijms23052768] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 02/18/2022] [Accepted: 02/26/2022] [Indexed: 02/06/2023] Open
Abstract
CMV is a major cause of morbidity and mortality in immunocompromised individuals that will benefit from the availability of a vaccine. Despite the efforts made during the last decade, no CMV vaccine is available. An ideal CMV vaccine should elicit a broad immune response against multiple viral antigens including proteins involved in virus-cell interaction and entry. However, the therapeutic use of neutralizing antibodies targeting glycoproteins involved in viral entry achieved only partial protection against infection. In this scenario, a better understanding of the CMV proteome potentially involved in viral entry may provide novel candidates to include in new potential vaccine design. In this study, we aimed to explore the CMV genome to identify proteins with putative transmembrane domains to identify new potential viral envelope proteins. We have performed in silico analysis using the genome sequences of nine different CMV strains to predict the transmembrane domains of the encoded proteins. We have identified 77 proteins with transmembrane domains, 39 of which were present in all the strains and were highly conserved. Among the core proteins, 17 of them such as UL10, UL139 or US33A have no ascribed function and may be good candidates for further mechanistic studies.
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Kleinwort KJH, Hobmaier BF, Mayer R, Hölzel C, Degroote RL, Märtlbauer E, Hauck SM, Deeg CA. Mycobacterium avium subsp. paratuberculosis Proteome Changes Profoundly in Milk. Metabolites 2021; 11:metabo11080549. [PMID: 34436489 PMCID: PMC8399727 DOI: 10.3390/metabo11080549] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 08/10/2021] [Accepted: 08/18/2021] [Indexed: 11/16/2022] Open
Abstract
Mycobacterium avium subspecies paratuberculosis (MAP) are detectable viable in milk and other dairy products. The molecular mechanisms allowing the adaptation of MAP in these products are still poorly understood. To obtain information about respective adaptation of MAP in milk, we differentially analyzed the proteomes of MAP cultivated for 48 h in either milk at 37 °C or 4 °C or Middlebrook 7H9 broth as a control. From a total of 2197 MAP proteins identified, 242 proteins were at least fivefold higher in abundance in milk. MAP responded to the nutritional shortage in milk with upregulation of 32% of proteins with function in metabolism and 17% in fatty acid metabolism/synthesis. Additionally, MAP upregulated clusters of 19% proteins with roles in stress responses and immune evasion, 19% in transcription/translation, and 13% in bacterial cell wall synthesis. Dut, MmpL4_1, and RecA were only detected in MAP incubated in milk, pointing to very important roles of these proteins for MAP coping with a stressful environment. Dut is essential and plays an exclusive role for growth, MmpL4_1 for virulence through secretion of specific lipids, and RecA for SOS response of mycobacteria. Further, 35 candidates with stable expression in all conditions were detected, which could serve as targets for detection. Data are available via ProteomeXchange with identifier PXD027444.
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Affiliation(s)
- Kristina J. H. Kleinwort
- Chair of Physiology, Department of Veterinary Sciences, LMU Munich, D-82152 Martinsried, Germany; (K.J.H.K.); (B.F.H.); (R.L.D.)
| | - Bernhard F. Hobmaier
- Chair of Physiology, Department of Veterinary Sciences, LMU Munich, D-82152 Martinsried, Germany; (K.J.H.K.); (B.F.H.); (R.L.D.)
| | - Ricarda Mayer
- Chair of Hygiene and Technology of Milk, Department of Veterinary Sciences, LMU Munich, D-85764 Oberschleißheim, Germany; (R.M.); (C.H.); (E.M.)
| | - Christina Hölzel
- Chair of Hygiene and Technology of Milk, Department of Veterinary Sciences, LMU Munich, D-85764 Oberschleißheim, Germany; (R.M.); (C.H.); (E.M.)
- Institute of Animal Breeding and Husbandry, Faculty of Agricultural and Nutritional Sciences, CAU Kiel, D-24098 Kiel, Germany
| | - Roxane L. Degroote
- Chair of Physiology, Department of Veterinary Sciences, LMU Munich, D-82152 Martinsried, Germany; (K.J.H.K.); (B.F.H.); (R.L.D.)
| | - Erwin Märtlbauer
- Chair of Hygiene and Technology of Milk, Department of Veterinary Sciences, LMU Munich, D-85764 Oberschleißheim, Germany; (R.M.); (C.H.); (E.M.)
| | - Stefanie M. Hauck
- Research Unit Protein Science, Helmholtz Center Munich, German Research Center for Environmental Health, D-80939 Munich, Germany;
| | - Cornelia A. Deeg
- Chair of Physiology, Department of Veterinary Sciences, LMU Munich, D-82152 Martinsried, Germany; (K.J.H.K.); (B.F.H.); (R.L.D.)
- Correspondence:
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