Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics
IntroductionThis study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosisMethodsProteomic analysis was conducted on serum samples from patients with acute and chronic brucellosis, a...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Cellular and Infection Microbiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcimb.2024.1446339/full |
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| author | Xiao Li Bo Wang Xiaocong Li Juan He Yue Shi Rui Wang Dongwei Li Ding Haitao Ding Haitao |
| author_facet | Xiao Li Bo Wang Xiaocong Li Juan He Yue Shi Rui Wang Dongwei Li Ding Haitao Ding Haitao |
| author_sort | Xiao Li |
| collection | DOAJ |
| description | IntroductionThis study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosisMethodsProteomic analysis was conducted on serum samples from patients with acute and chronic brucellosis, as well as from healthy controls. Differential expression analysis was performed to identify proteins with altered expression, while Weighted Gene Co-expression Network Analysis (WGCNA) was applied to detect co-expression modules associated with clinical features of brucellosis. Machine learning algorithms were subsequently used to identify the optimal combination of diagnostic biomarkers. Finally, ELISA was employed to validate the identified proteins.ResultsA total of 1,494 differentially expressed proteins were identified, revealing two co-expression modules significantly associated with the clinical characteristics of brucellosis. The Gaussian Mixture Model (GMM) algorithm identified six proteins that were concurrently present in both the differentially expressed and co-expression modules, demonstrating promising diagnostic potential. After ELISA validation, five proteins were ultimately selected.DiscussionThese five proteins are implicated in the innate immune processes of brucellosis, potentially associated with its pathogenic mechanisms and chronicity. Furthermore, we highlighted their potential as diagnostic biomarkers for brucellosis. This study further enhances our understanding of brucellosis at the protein level, paving the way for future research endeavors. |
| format | Article |
| id | doaj-art-5e825c62914d49f3a111bb6a59f580f9 |
| institution | Kabale University |
| issn | 2235-2988 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cellular and Infection Microbiology |
| spelling | doaj-art-5e825c62914d49f3a111bb6a59f580f92025-01-13T06:11:06ZengFrontiers Media S.A.Frontiers in Cellular and Infection Microbiology2235-29882025-01-011410.3389/fcimb.2024.14463391446339Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformaticsXiao Li0Bo Wang1Xiaocong Li2Juan He3Yue Shi4Rui Wang5Dongwei Li6Ding Haitao7Ding Haitao8Department of Inner Mongolia Clinical Medicine College, Inner Mongolia Medical University, Hohhot, Inner Mongolia, ChinaDepartment of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People’s Hospital, Hohhot, Inner Mongolia, ChinaDepartment of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People’s Hospital, Hohhot, Inner Mongolia, ChinaDepartment of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People’s Hospital, Hohhot, Inner Mongolia, ChinaDepartment of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People’s Hospital, Hohhot, Inner Mongolia, ChinaDepartment of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People’s Hospital, Hohhot, Inner Mongolia, ChinaDepartment of Inner Mongolia Clinical Medicine College, Inner Mongolia Medical University, Hohhot, Inner Mongolia, ChinaDepartment of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People’s Hospital, Hohhot, Inner Mongolia, ChinaInner Mongolia Academy of Medical Sciences, Hohhot, Inner Mongolia, ChinaIntroductionThis study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosisMethodsProteomic analysis was conducted on serum samples from patients with acute and chronic brucellosis, as well as from healthy controls. Differential expression analysis was performed to identify proteins with altered expression, while Weighted Gene Co-expression Network Analysis (WGCNA) was applied to detect co-expression modules associated with clinical features of brucellosis. Machine learning algorithms were subsequently used to identify the optimal combination of diagnostic biomarkers. Finally, ELISA was employed to validate the identified proteins.ResultsA total of 1,494 differentially expressed proteins were identified, revealing two co-expression modules significantly associated with the clinical characteristics of brucellosis. The Gaussian Mixture Model (GMM) algorithm identified six proteins that were concurrently present in both the differentially expressed and co-expression modules, demonstrating promising diagnostic potential. After ELISA validation, five proteins were ultimately selected.DiscussionThese five proteins are implicated in the innate immune processes of brucellosis, potentially associated with its pathogenic mechanisms and chronicity. Furthermore, we highlighted their potential as diagnostic biomarkers for brucellosis. This study further enhances our understanding of brucellosis at the protein level, paving the way for future research endeavors.https://www.frontiersin.org/articles/10.3389/fcimb.2024.1446339/fullbrucellosisbiomarkersproteomicsbioinformaticsdifferential expression analysisweighted gene co-expression network analysis (WGCNA) |
| spellingShingle | Xiao Li Bo Wang Xiaocong Li Juan He Yue Shi Rui Wang Dongwei Li Ding Haitao Ding Haitao Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics Frontiers in Cellular and Infection Microbiology brucellosis biomarkers proteomics bioinformatics differential expression analysis weighted gene co-expression network analysis (WGCNA) |
| title | Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics |
| title_full | Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics |
| title_fullStr | Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics |
| title_full_unstemmed | Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics |
| title_short | Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics |
| title_sort | analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics |
| topic | brucellosis biomarkers proteomics bioinformatics differential expression analysis weighted gene co-expression network analysis (WGCNA) |
| url | https://www.frontiersin.org/articles/10.3389/fcimb.2024.1446339/full |
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