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Chen J, Wang Y, Hong M, Wu J, Zhang Z, Li R, Ding T, Xu H, Zhang X, Chen P. Application of peripheral blood routine parameters in the diagnosis of influenza and Mycoplasma pneumoniae. Virol J 2024; 21:162. [PMID: 39044252 PMCID: PMC11267962 DOI: 10.1186/s12985-024-02429-4] [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: 04/26/2024] [Accepted: 07/05/2024] [Indexed: 07/25/2024] Open
Abstract
OBJECTIVES Influenza and Mycoplasma pneumoniae infections often present concurrent and overlapping symptoms in clinical manifestations, making it crucial to accurately differentiate between the two in clinical practice. Therefore, this study aims to explore the potential of using peripheral blood routine parameters to effectively distinguish between influenza and Mycoplasma pneumoniae infections. METHODS This study selected 209 influenza patients (IV group) and 214 Mycoplasma pneumoniae patients (MP group) from September 2023 to January 2024 at Nansha Division, the First Affiliated Hospital of Sun Yat-sen University. We conducted a routine blood-related index test on all research subjects to develop a diagnostic model. For normally distributed parameters, we used the T-test, and for non-normally distributed parameters, we used the Wilcoxon test. RESULTS Based on an area under the curve (AUC) threshold of ≥ 0.7, we selected indices such as Lym# (lymphocyte count), Eos# (eosinophil percentage), Mon% (monocyte percentage), PLT (platelet count), HFC# (high fluorescent cell count), and PLR (platelet to lymphocyte ratio) to construct the model. Based on these indicators, we constructed a diagnostic algorithm named IV@MP using the random forest method. CONCLUSIONS The diagnostic algorithm demonstrated excellent diagnostic performance and was validated in a new population, with an AUC of 0.845. In addition, we developed a web tool to facilitate the diagnosis of influenza and Mycoplasma pneumoniae infections. The results of this study provide an effective tool for clinical practice, enabling physicians to accurately diagnose and differentiate between influenza and Mycoplasma pneumoniae infection, thereby offering patients more precise treatment plans.
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Affiliation(s)
- Jingrou Chen
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Laboratory Medicine, Nansha Division, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 511466, China
| | - Yang Wang
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Laboratory Medicine, Nansha Division, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 511466, China
| | - Mengzhi Hong
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Laboratory Medicine, Nansha Division, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 511466, China
| | - Jiahao Wu
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Laboratory Medicine, Nansha Division, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 511466, China
| | - Zongjun Zhang
- Department of Laboratory Medicine, Guangdong Province Prevention and Treatment Center for Occupational Diseases, Guangzhou, 510300, China
| | - Runzhao Li
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Laboratory Medicine, Nansha Division, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 511466, China
| | - Tangdan Ding
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Laboratory Medicine, Nansha Division, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 511466, China
| | - Hongxu Xu
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China
- Department of Laboratory Medicine, Nansha Division, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 511466, China
| | - Xiaoli Zhang
- Department of Pediatrics, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Peisong Chen
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China.
- Department of Laboratory Medicine, Nansha Division, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 511466, China.
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Marques PH, Tiwari S, Felice AG, Jaiswal AK, Aburjaile FF, Azevedo V, Silva-Vergara ML, Ferreira-Paim K, Soares SDC, Fonseca FM. Design of a Multi-Epitope Vaccine against Histoplasma capsulatum through Immunoinformatics Approaches. J Fungi (Basel) 2024; 10:43. [PMID: 38248954 PMCID: PMC10817582 DOI: 10.3390/jof10010043] [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: 10/25/2023] [Revised: 12/20/2023] [Accepted: 12/28/2023] [Indexed: 01/23/2024] Open
Abstract
Histoplasmosis is a widespread systemic disease caused by Histoplasma capsulatum, prevalent in the Americas. Despite its significant morbidity and mortality rates, no vaccines are currently available. Previously, five vaccine targets and specific epitopes for H. capsulatum were identified. Immunoinformatics has emerged as a novel approach for determining the main immunogenic components of antigens through in silico methods. Therefore, we predicted the main helper and cytotoxic T lymphocytes and B-cell epitopes for these targets to create a potential multi-epitope vaccine known as HistoVAC-TSFM. A total of 38 epitopes were found: 23 common to CTL and B-cell responses, 11 linked to HTL and B cells, and 4 previously validated epitopes associated with the B subunit of cholera toxin, a potent adjuvant. In silico evaluations confirmed the stability, non-toxicity, non-allergenicity, and non-homology of these vaccines with the host. Notably, the vaccine exhibited the potential to trigger both innate and adaptive immune responses, likely involving the TLR4 pathway, as supported by 3D modeling and molecular docking. The designed HistoVAC-TSFM appears promising against Histoplasma, with the ability to induce important cytokines, such as IFN-γ, TNF-α, IL17, and IL6. Future studies could be carried out to test the vaccine's efficacy in in vivo models.
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Affiliation(s)
- Pedro Henrique Marques
- Postgraduate Interunits Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil; (P.H.M.); (A.K.J.)
- Department of Preventive Veterinary, Medicine, School of Veterinary Medicine, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil;
| | - Sandeep Tiwari
- Institute of Biology, Federal University of Bahia, Salvador 40170-115, Brazil;
- Institute of Health Sciences, Federal University of Bahia, Salvador 40170-115, Brazil
| | - Andrei Giacchetto Felice
- Department of Microbiology, Immunology and Parasitology, Federal University of Triangulo Mineiro, Uberaba 38015-050, Brazil; (A.G.F.); (S.d.C.S.)
| | - Arun Kumar Jaiswal
- Postgraduate Interunits Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil; (P.H.M.); (A.K.J.)
| | - Flávia Figueira Aburjaile
- Department of Preventive Veterinary, Medicine, School of Veterinary Medicine, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil;
| | - Vasco Azevedo
- Department of Genetics, Ecology and Evolution, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil;
| | - Mario León Silva-Vergara
- Department of Infectious Diseases, Federal University of Triangulo Mineiro, Uberaba 38025-440, Brazil;
| | - Kennio Ferreira-Paim
- Department of Microbiology, Immunology and Parasitology, Federal University of Triangulo Mineiro, Uberaba 38015-050, Brazil; (A.G.F.); (S.d.C.S.)
| | - Siomar de Castro Soares
- Department of Microbiology, Immunology and Parasitology, Federal University of Triangulo Mineiro, Uberaba 38015-050, Brazil; (A.G.F.); (S.d.C.S.)
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Zubair M, Wang J, Yu Y, Rasheed MA, Faisal M, Dawood AS, Ashraf M, Shao G, Feng Z, Xiong Q. Conserved Domains in Variable Surface Lipoproteins A-G of Mycoplasma hyorhinis May Serve as Probable Multi-Epitope Candidate Vaccine: Computational Reverse Vaccinology Approach. Vet Sci 2023; 10:557. [PMID: 37756079 PMCID: PMC10535464 DOI: 10.3390/vetsci10090557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 08/09/2023] [Accepted: 08/30/2023] [Indexed: 09/28/2023] Open
Abstract
Mycoplasma hyorhinis (M. hyorhinis) is responsible for infections in the swine population. Such infections are usually cured by using antimicrobials and lead to develop resistance. Until now, there has been no effective vaccine to eradicate the disease. This study used conserved domains found in seven members of the variable lipoprotein (VlpA-G) family in order to design a multi-epitope candidate vaccine (MEV) against M. hyorhinis. The immunoinformatics approach was followed to predict epitopes, and a vaccine construct consisting of an adjuvant, two B cell epitopes, two HTL epitopes, and one CTL epitope was designed. The suitability of the vaccine construct was identified by its non-allergen, non-toxic, and antigenic nature. A molecular dynamic simulation was executed to assess the stability of the TLR2 docked structure. An immune simulation showed a high immune response toward the antigen. The protein sequence was reverse-translated, and codons were optimized to gain a high expression level in E. coli. The proposed vaccine construct may be a candidate for a multi-epitope vaccine. Experimental validation is required in future to test the safety and efficacy of the hypothetical candidate vaccine.
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Affiliation(s)
- Muhammad Zubair
- Key Laboratory of Veterinary Biological Engineering and Technology, Ministry of Agriculture, Institute of Veterinary Medicine, Jiangsu Academy of Agricultural Sciences, Nanjing 210000, China; (M.Z.); (J.W.); (Y.Y.); (G.S.); (Z.F.)
- GuoTai (Taizhou) Center of Technology Innovation for Veterinary Biologicals, Taizhou 225300, China
| | - Jia Wang
- Key Laboratory of Veterinary Biological Engineering and Technology, Ministry of Agriculture, Institute of Veterinary Medicine, Jiangsu Academy of Agricultural Sciences, Nanjing 210000, China; (M.Z.); (J.W.); (Y.Y.); (G.S.); (Z.F.)
- GuoTai (Taizhou) Center of Technology Innovation for Veterinary Biologicals, Taizhou 225300, China
| | - Yanfei Yu
- Key Laboratory of Veterinary Biological Engineering and Technology, Ministry of Agriculture, Institute of Veterinary Medicine, Jiangsu Academy of Agricultural Sciences, Nanjing 210000, China; (M.Z.); (J.W.); (Y.Y.); (G.S.); (Z.F.)
- GuoTai (Taizhou) Center of Technology Innovation for Veterinary Biologicals, Taizhou 225300, China
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
| | - Muhammad Asif Rasheed
- Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus, Islamabad 45550, Pakistan;
| | - Muhammad Faisal
- Division of Hematology, Department of Medicine, The Ohio State University College of Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH 43210, USA;
| | - Ali Sobhy Dawood
- The State Key Laboratory of Agricultural Microbiology, Department of Preventive Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China;
- Faculty of Veterinary Medicine, University of Sadat City, Sadat City 32897, Egypt
| | - Muhammad Ashraf
- Institute of Microbiology, University of Agriculture Faisalabad, Faisalabad 37000, Pakistan;
| | - Guoqing Shao
- Key Laboratory of Veterinary Biological Engineering and Technology, Ministry of Agriculture, Institute of Veterinary Medicine, Jiangsu Academy of Agricultural Sciences, Nanjing 210000, China; (M.Z.); (J.W.); (Y.Y.); (G.S.); (Z.F.)
- GuoTai (Taizhou) Center of Technology Innovation for Veterinary Biologicals, Taizhou 225300, China
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Zhixin Feng
- Key Laboratory of Veterinary Biological Engineering and Technology, Ministry of Agriculture, Institute of Veterinary Medicine, Jiangsu Academy of Agricultural Sciences, Nanjing 210000, China; (M.Z.); (J.W.); (Y.Y.); (G.S.); (Z.F.)
- GuoTai (Taizhou) Center of Technology Innovation for Veterinary Biologicals, Taizhou 225300, China
| | - Qiyan Xiong
- Key Laboratory of Veterinary Biological Engineering and Technology, Ministry of Agriculture, Institute of Veterinary Medicine, Jiangsu Academy of Agricultural Sciences, Nanjing 210000, China; (M.Z.); (J.W.); (Y.Y.); (G.S.); (Z.F.)
- GuoTai (Taizhou) Center of Technology Innovation for Veterinary Biologicals, Taizhou 225300, China
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
- School of Life Sciences, Jiangsu University, Zhenjiang 212013, China
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Inácio MM, Moreira ALE, Cruz-Leite VRM, Mattos K, Silva LOS, Venturini J, Ruiz OH, Ribeiro-Dias F, Weber SS, Soares CMDA, Borges CL. Fungal Vaccine Development: State of the Art and Perspectives Using Immunoinformatics. J Fungi (Basel) 2023; 9:633. [PMID: 37367569 DOI: 10.3390/jof9060633] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 05/12/2023] [Accepted: 05/19/2023] [Indexed: 06/28/2023] Open
Abstract
Fungal infections represent a serious global health problem, causing damage to health and the economy on the scale of millions. Although vaccines are the most effective therapeutic approach used to combat infectious agents, at the moment, no fungal vaccine has been approved for use in humans. However, the scientific community has been working hard to overcome this challenge. In this sense, we aim to describe here an update on the development of fungal vaccines and the progress of methodological and experimental immunotherapies against fungal infections. In addition, advances in immunoinformatic tools are described as an important aid by which to overcome the difficulty of achieving success in fungal vaccine development. In silico approaches are great options for the most important and difficult questions regarding the attainment of an efficient fungal vaccine. Here, we suggest how bioinformatic tools could contribute, considering the main challenges, to an effective fungal vaccine.
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Affiliation(s)
- Moisés Morais Inácio
- Laboratory of Molecular Biology, Institute of Biological Sciences, Federal University of Goiás, Goiânia 74605-170, Brazil
- Estácio de Goiás University Center, Goiânia 74063-010, Brazil
| | - André Luís Elias Moreira
- Laboratory of Molecular Biology, Institute of Biological Sciences, Federal University of Goiás, Goiânia 74605-170, Brazil
| | | | - Karine Mattos
- Faculty of Medicine, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Brazil
| | - Lana O'Hara Souza Silva
- Laboratory of Molecular Biology, Institute of Biological Sciences, Federal University of Goiás, Goiânia 74605-170, Brazil
| | - James Venturini
- Faculty of Medicine, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Brazil
| | - Orville Hernandez Ruiz
- MICROBA Research Group-Cellular and Molecular Biology Unit-CIB, School of Microbiology, University of Antioquia, Medellín 050010, Colombia
| | - Fátima Ribeiro-Dias
- Laboratório de Imunidade Natural (LIN), Instituto de Patologia Tropical e Saúde Pública, Federal University of Goiás, Goiânia 74001-970, Brazil
| | - Simone Schneider Weber
- Bioscience Laboratory, Faculty of Pharmaceutical Sciences, Food and Nutrition, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Brazil
| | - Célia Maria de Almeida Soares
- Laboratory of Molecular Biology, Institute of Biological Sciences, Federal University of Goiás, Goiânia 74605-170, Brazil
| | - Clayton Luiz Borges
- Laboratory of Molecular Biology, Institute of Biological Sciences, Federal University of Goiás, Goiânia 74605-170, Brazil
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Comparative Genomics of Histoplasma capsulatum and Prediction of New Vaccines and Drug Targets. J Fungi (Basel) 2023; 9:jof9020193. [PMID: 36836308 PMCID: PMC9963733 DOI: 10.3390/jof9020193] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 01/18/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023] Open
Abstract
Histoplasma capsulatum is a thermodymorphic fungus that causes histoplasmosis, a systemic mycosis that presents different clinical manifestations, ranging from self-limiting to acute lung infection, chronic lung infection and disseminated infection. Usually, it affects severely immunocompromised patients although immunocompetent patients can also be infected. Currently, there are no vaccines to prevent histoplasmosis and the available antifungal treatment presents moderate to high toxicity. Additionally, there are few options of antifungal drugs. Thus, the aim of this study was to predict possible protein targets for the construction of potential vaccine candidates and predict potential drug targets against H. capsulatum. Whole genome sequences from four previously published H. capsulatum strains were analyzed and submitted to different bioinformatic approaches such as reverse vaccinology and subtractive genomics. A total of four proteins were characterized as good protein candidates (vaccine antigens) for vaccine development, three of which are membrane-bound and one is secreted. In addition, it was possible to predict four cytoplasmic proteins which were classified as good protein candidates and, through molecular docking performed for each identified target, we found four natural compounds that showed favorable interactions with our target proteins. Our study can help in the development of potential vaccines and new drugs that can change the current scenario of the treatment and prevention of histoplasmosis.
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