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Published on: November 12, 2012
In silico Functional Annotation and Characterization of Hypothetical Proteins from Serratia marcescens FGI94
D Prabhu1, S Rajamanikandan2, S Baby Anusha3
1Department of Bioinformatics, Alagappa University, Science Campus, 630004 Karaikudi, Tamil Nadu India.
Abstract:
Serratia marcescens, rod-shaped Gram-negative bacteria is classified as an opportunistic pathogen in the family Enterobacteriaceae. It causes a wide variety of infections in humans, including urinary, respiratory, ocular lens and ear infections, osteomyelitis, endocarditis, meningitis and septicemia. Unfortunately, over the past decade, antibiotic resistance has become a serious health care issue; the effective means to control and dissemination of S. marcescens resistance is the need of hour. The whole genome sequencing of S. marcescens FGI94 strain contains 4434 functional proteins, among which 690 (15.56%) proteins were classified under hypothetical. In the present study, we applied the power of various bioinformatics tools on the basis of protein family comparison, motifs, functional properties of amino acids and genome context to assign the possible functions for the HPs. The pseudo sequences (protein sequence that contain ≤100 amino acid residues) are eliminated from the study. Although we have successfully predicted the function for 483 proteins, we were able to infer the high level of confidence only for 108 proteins. The predicted HPs were classified into various classes such as enzymes, transporters, binding proteins, cell division, cell regulatory and other proteins. The outcome of the study could be helpful to understand the molecular mechanism in bacterial pathogenesis and also provide an insight into the identification of potential targets for drug and vaccine development.
Insights
Bioinformatics tools helped identify functions for hypothetical proteins in the opportunistic pathogen Serratia marcescens. This aids understanding of bacterial pathogenesis and drug development against antibiotic resistance.
Area of Science:
- Microbiology
- Genomics
- Bioinformatics
Background:
- Serratia marcescens is an opportunistic Gram-negative bacterium causing diverse human infections.
- Increasing antibiotic resistance in S. marcescens necessitates novel control strategies.
- The S. marcescens FGI94 genome contains numerous hypothetical proteins of unknown function.
Purpose of the Study:
- To assign putative functions to hypothetical proteins in S. marcescens FGI94 using bioinformatics.
- To identify potential drug and vaccine targets for combating S. marcescens infections.
Main Methods:
- Whole genome sequencing of S. marcescens FGI94.
- Application of bioinformatics tools for protein family comparison, motif analysis, and genome context analysis.
- Exclusion of pseudo sequences (≤100 amino acid residues).
Main Results:
- Functions were predicted for 483 hypothetical proteins, with high confidence for 108.
- Predicted proteins were classified into functional categories including enzymes, transporters, and regulatory proteins.
- The study identified potential targets for antimicrobial drug and vaccine development.
Conclusions:
- Bioinformatics analysis successfully assigned functions to a significant number of hypothetical proteins in S. marcescens.
- Understanding these proteins can elucidate bacterial pathogenesis mechanisms.
- The findings offer valuable insights for developing new therapeutic strategies against S. marcescens.
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