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Molecular Mimicry of Pathogenicity of Neisseria

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Abstract Neisseria, a genus from beta-proteobacteria class, is of potent clinical importance. This genus contains both pathogenic and commensal strains. Gonorrhea and meningitis are two major diseases caused by pathogens belonging to this genus. With increased use of antimicrobial agents against these pathogens they have evolved the antimicrobial resistance (AMR) capacity making these diseases nearly untreatable. The set of anti-bacterial resistance genes (resistome) and genes associated with signal processing (secretomes) are crucial for the host-microbial interaction. With the virtue of whole genome sequences and computational biology it is now possible to study the genomic and proteomic riddles of Neisseria along with their comprehensive evolutionary and metabolic profiling. We have studied relative synonymous codon usage, amino acid usage, reverse ecology, comparative genomics, evolutionary analysis and pathogen-host (Neisseria-human) interaction through bioinformatics analysis. Our analysis revealed the co-evolution of Neisseria genomes with the human host. Moreover, co-occurrence of Neisseria and humans has been supported through reverse ecology analysis. A differential pattern of evolutionary rate of resistomes and secretomes was evident among the pathogenic and commensal strains. Comparative genomics supported the presence of virulent genes in both pathogenic and commensal strains of select genus. Our analysis also indicated a transition from commensal to pathogenic Neisseria strains through the long run of evolution.
Title: Molecular Mimicry of Pathogenicity of Neisseria
Description:
Abstract Neisseria, a genus from beta-proteobacteria class, is of potent clinical importance.
This genus contains both pathogenic and commensal strains.
Gonorrhea and meningitis are two major diseases caused by pathogens belonging to this genus.
With increased use of antimicrobial agents against these pathogens they have evolved the antimicrobial resistance (AMR) capacity making these diseases nearly untreatable.
The set of anti-bacterial resistance genes (resistome) and genes associated with signal processing (secretomes) are crucial for the host-microbial interaction.
With the virtue of whole genome sequences and computational biology it is now possible to study the genomic and proteomic riddles of Neisseria along with their comprehensive evolutionary and metabolic profiling.
We have studied relative synonymous codon usage, amino acid usage, reverse ecology, comparative genomics, evolutionary analysis and pathogen-host (Neisseria-human) interaction through bioinformatics analysis.
Our analysis revealed the co-evolution of Neisseria genomes with the human host.
Moreover, co-occurrence of Neisseria and humans has been supported through reverse ecology analysis.
A differential pattern of evolutionary rate of resistomes and secretomes was evident among the pathogenic and commensal strains.
Comparative genomics supported the presence of virulent genes in both pathogenic and commensal strains of select genus.
Our analysis also indicated a transition from commensal to pathogenic Neisseria strains through the long run of evolution.

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