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Published on: November 5, 2019
Proteome analysis of Neisseria meningitidis serogroup A
Giulia Bernardini1, Giovanni Renzone, Maurizio Comanducci
1Dipartimento di Biologia Molecolare, Università degli Studi di Siena, Siena, Italy.
Abstract:
Neisseria meningitidis is an encapsulated Gram-negative bacterium responsible for significant morbidity and mortality worldwide. Meningococci are opportunistic pathogens, carried in the nasopharynx of approximately 10% of asymptomatic adults. Occasionally they enter the bloodstream to cause septicaemia and meningitis. Meningococci are classified into serogroups on the basis of polysaccharide capsule diversity, and serogroup A strains have caused major epidemics mainly in the developing world. Here we describe a two-dimensional gel electrophoresis protein map of the serogroup A strain Z4970, a clinical isolate classified as ancestral to several pandemic waves. To our knowledge this is the first systematically annotated proteomic map for N. meningitidis. Total protein samples from bacteria grown on GC-agar were electrophoretically separated and protein species were identified by matrix-assisted laser desorption/ionization time of flight spectrometry. We identified the products of 273 genes, covering several functional classes, including 94 proteins so far considered as hypothetical. We also describe several protein species encoded by genes reported by DNA microarray studies as being regulated in physiological conditions which are relevant to natural meningococcal pathogenicity. Since menA differs from other serogroups by having a fairly stable clonal population structure (i.e. with a low degree of variability), we envisaged comparative mapping as a useful tool for microevolution studies, in conjunction with established genotyping methods. As a proof of principle, we performed a comparative analysis on the B subunit of the meningococcal transferrin receptor, a vaccine candidate encoded by the tbpB gene, and a known marker of population diversity in meningococci. The results show that TbpB spot pattern variation observed in the maps of nine clinical isolates from diverse epidemic spreads, fits previous analyses based on allelic variations of the tbpB gene.
Insights
This study presents the first detailed protein map of the serogroup A Neisseria meningitidis bacterium. Comparative analysis of this map aids in understanding meningococcal microevolution and population diversity.
Area of Science:
- Microbiology
- Proteomics
- Bacteriology
Background:
- Neisseria meningitidis causes significant global morbidity and mortality, particularly serogroup A strains responsible for major epidemics.
- Meningococci are opportunistic pathogens, commonly carried asymptomatically in the nasopharynx.
- Serogroup A strains are linked to major epidemics, necessitating deeper understanding of their biology.
Purpose of the Study:
- To create the first systematically annotated proteomic map of Neisseria meningitidis serogroup A strain Z4970.
- To identify gene products and regulated proteins relevant to meningococcal pathogenicity.
- To demonstrate comparative mapping as a tool for microevolution studies.
Main Methods:
- Two-dimensional gel electrophoresis was used to separate total protein samples from bacteria grown on GC-agar.
- Protein species were identified using matrix-assisted laser desorption/ionization time of flight spectrometry.
- Comparative proteomic mapping was performed on the transferrin receptor B subunit (TbpB).
Main Results:
- A proteomic map of Neisseria meningitidis serogroup A strain Z4970 was generated, identifying 273 gene products, including 94 hypothetical proteins.
- Several proteins encoded by regulated genes relevant to pathogenicity were identified.
- Comparative analysis of TbpB variations across nine clinical isolates validated the proteomic map's utility for microevolution studies.
Conclusions:
- The generated proteomic map provides a valuable resource for Neisseria meningitidis research.
- Comparative proteomic mapping is a viable method for studying meningococcal microevolution and population diversity.
- This approach can complement existing genotyping methods for epidemiological studies.
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