Preparation and application of a Brucella multiepitope fusion protein based on bioinformatics and Tandem Mass Tag-based proteomics technology Article Swipe
Qi Wu
,
Yuan Yuan
,
Liping Guo
,
Yujia Xie
,
Meixue Yao
,
Dehui Yin
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3389/fimmu.2024.1509534
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3389/fimmu.2024.1509534
Introduction Brucellosis is a widespread zoonotic disease that poses a considerable challenge to global public health. Existing diagnostic methods for this condition, such as serological assays and bacterial culture, encounter difficulties due to their limited specificity and high operational complexity. Therefore, there is an urgent need for the development of enhanced diagnostic approaches for brucellosis. Methods Tandem mass tag (TMT) proteomic analysis was conducted on the wild-type strain Brucella abortus ( B. abortus ) DT21 and the vaccine strain B. abortus A19 to identify proteins with high expression levels. The proteins that exhibited high expression in the wild-type strain were selected based on the proteomic results. Subsequently, B-cell linear epitopes were predicted using multiple computational tools, including ABCpred, SVMTriP, BCPred, and Bepipred Linear Epitope Prediction 2.0. These epitopes were concatenated to construct a multiepitope fusion protein. Following prokaryotic expression and purification, an indirect enzyme-linked immunosorbent assay (iELISA) was developed. A total of 100 positive serum samples, 96 negative serum samples, and 40 serum samples from patients infected with other pathogens were collected and analyzed using the established iELISA. Furthermore, the protein was assessed for its capability to differentiate human brucellosis from lipopolysaccharide (LPS). Results Proteomic analysis revealed the presence of 152 proteins with high expression levels in the wild-type strains. A multiepitope fusion protein, comprising a total of 32 predicted B-cell linear epitopes, was successfully prepared. The results from the iELISA indicated that the multiepitope fusion protein exhibited exceptional diagnostic performance, evidenced by an area under the receiver operating characteristic curve (AUC) of 0.9576, a sensitivity of 0.9300, and a specificity of 0.8542. In comparison to the commonly utilized LPS antigen, the fusion protein demonstrated a reduced level of cross-reactivity. Conclusions A novel multiepitope fusion protein has been successfully developed utilizing bioinformatics and TMT proteomics technology. This fusion protein demonstrates significant potential as a diagnostic antigen for brucellosis, exhibiting high sensitivity and specificity.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fimmu.2024.1509534
- https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1509534/pdf
- OA Status
- gold
- Cited By
- 4
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4406254005
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4406254005Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fimmu.2024.1509534Digital Object Identifier
- Title
-
Preparation and application of a Brucella multiepitope fusion protein based on bioinformatics and Tandem Mass Tag-based proteomics technologyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-01-10Full publication date if available
- Authors
-
Qi Wu, Yuan Yuan, Liping Guo, Yujia Xie, Meixue Yao, Dehui YinList of authors in order
- Landing page
-
https://doi.org/10.3389/fimmu.2024.1509534Publisher landing page
- PDF URL
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https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1509534/pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1509534/pdfDirect OA link when available
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Proteomics, Brucella, Computational biology, Bioinformatics, Biology, Virology, Computer science, Genetics, Brucellosis, GeneTop concepts (fields/topics) attached by OpenAlex
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4Total citation count in OpenAlex
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2025: 4Per-year citation counts (last 5 years)
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35Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.prepared. | 225 |
| abstract_inverted_index.proteomic | 60, 104 |
| abstract_inverted_index.utilizing | 290 |
| abstract_inverted_index.wild-type | 66, 97, 208 |
| abstract_inverted_index.Prediction | 124 |
| abstract_inverted_index.Therefore, | 40 |
| abstract_inverted_index.approaches | 52 |
| abstract_inverted_index.capability | 185 |
| abstract_inverted_index.comparison | 264 |
| abstract_inverted_index.comprising | 214 |
| abstract_inverted_index.condition, | 21 |
| abstract_inverted_index.developed. | 148 |
| abstract_inverted_index.diagnostic | 17, 51, 239, 304 |
| abstract_inverted_index.exhibiting | 308 |
| abstract_inverted_index.expression | 87, 94, 138, 204 |
| abstract_inverted_index.proteomics | 294 |
| abstract_inverted_index.widespread | 4 |
| abstract_inverted_index.Brucellosis | 1 |
| abstract_inverted_index.Conclusions | 280 |
| abstract_inverted_index.brucellosis | 189 |
| abstract_inverted_index.complexity. | 39 |
| abstract_inverted_index.development | 48 |
| abstract_inverted_index.established | 176 |
| abstract_inverted_index.exceptional | 238 |
| abstract_inverted_index.operational | 38 |
| abstract_inverted_index.prokaryotic | 137 |
| abstract_inverted_index.sensitivity | 255, 310 |
| abstract_inverted_index.serological | 24 |
| abstract_inverted_index.significant | 300 |
| abstract_inverted_index.specificity | 35, 260 |
| abstract_inverted_index.technology. | 295 |
| abstract_inverted_index.Furthermore, | 178 |
| abstract_inverted_index.Introduction | 0 |
| abstract_inverted_index.brucellosis, | 307 |
| abstract_inverted_index.brucellosis. | 54 |
| abstract_inverted_index.concatenated | 129 |
| abstract_inverted_index.considerable | 10 |
| abstract_inverted_index.demonstrated | 274 |
| abstract_inverted_index.demonstrates | 299 |
| abstract_inverted_index.difficulties | 30 |
| abstract_inverted_index.multiepitope | 133, 211, 234, 283 |
| abstract_inverted_index.performance, | 240 |
| abstract_inverted_index.specificity. | 312 |
| abstract_inverted_index.successfully | 224, 288 |
| abstract_inverted_index.Subsequently, | 106 |
| abstract_inverted_index.computational | 114 |
| abstract_inverted_index.differentiate | 187 |
| abstract_inverted_index.enzyme-linked | 143 |
| abstract_inverted_index.immunosorbent | 144 |
| abstract_inverted_index.purification, | 140 |
| abstract_inverted_index.bioinformatics | 291 |
| abstract_inverted_index.characteristic | 249 |
| abstract_inverted_index.cross-reactivity. | 279 |
| abstract_inverted_index.lipopolysaccharide | 191 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 97 |
| corresponding_author_ids | https://openalex.org/A5061193945, https://openalex.org/A5100758013 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I177388780 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.550000011920929 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.9853383 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |