Ribotyping Staphylococcus epidermidis Using Probabilistic Sequence Analysis and Levenshtein Distance Algorithm

Area of Science:

• Microbiology
• Genetics
• Bioinformatics

Background:

• Staphylococcus epidermidis (S. epidermidis) is a common bacterium found in diverse environments.
• Accurate sub-typing of S. epidermidis is crucial for epidemiological and ecological studies.
• Existing methods for S. epidermidis sub-typing may require refinement for broader applicability.

Purpose of the Study:

• To identify novel genetic markers for the ribotyping of Staphylococcus epidermidis (S. epidermidis) subspecies.
• To establish reference sequences for S. epidermidis 16S rRNA genes.
• To assess the prevalence and utility of identified motifs in diverse S. epidermidis isolates.

Main Methods:

• Utilized probabilistic sequence analysis of 2507 PCR-amplified 16S rRNA gene reads from a public dataset.
• Constructed a sequence probability logo (sequence pLogo) for S. epidermidis 16S rRNA genes.
• Applied the Levenshtein Distance algorithm to identify conserved 20-base pair (bp) motifs.

Main Results:

• Identified two conserved 20-bp motifs within the S. epidermidis 16S rRNA gene sequences.
• These motifs showed high similarity to sequences from 38 S. epidermidis isolates across human, animal, plant, and environmental samples.
• Verification using 31 additional reads confirmed the feasibility of using these motifs for ribotyping, distinguishing S. epidermidis strains S1 and S3 from S2.

Conclusions:

• Two newly identified 20-bp motifs serve as valuable reference nucleotide residues for S. epidermidis ribotyping.
• These motifs demonstrate broad presence across diverse S. epidermidis isolates and environments.
• The findings provide a refined approach for subspecies identification and phylogenetic analysis of S. epidermidis.