GENOMIC CHARACTERIZATION OF ANTIBIOTIC RESISTANT BACTERIA IN CLINICAL AND ENVIRONMENTAL SAMPLES

Abstract

Antibiotic resistance has emerged as a major global health concern affecting clinical treatment, environmental safety, and microbial ecosystem stability. The present study investigated genomic composition patterns associated with antibiotic-resistant bacterial genomes using comparative computational genomics approaches. A publicly available genomic dataset containing 100,000 bacterial genomic sequences with resistant and non resistant classifications was analyzed using bioinformatics and sequence-based comparative analysis methods. The study evaluated genomic sequence length distribution, GC-content variation, nucleotide composition, and dinucleotide frequency patterns associated with antibiotic resistance. The results demonstrated relatively stable genomic sequence lengths across bacterial samples, with balanced resistant and non-resistant genomic categories. GC-content analysis revealed that resistant bacterial genomes exhibited comparatively lower GC content than non-resistant bacterial genomes. Nucleotide composition analysis further demonstrated increased adenine and thymine abundance within resistant bacterial genomes, whereas non-resistant bacterial genomes showed relatively higher guanine and cytosine composition. Dinucleotide frequency analysis identified distinct sequence-level genomic signatures associated with antibiotic resistance, particularly involving AT-, TA-, and TG-associated sequence patterns. Comparative heatmap visualization additionally demonstrated measurable compositional variation between resistant and non-resistant bacterial populations. The findings indicate that computational genomic analysis and comparative bioinformatics approaches can effectively identify resistance associated genomic signatures and sequence-level compositional variation within bacterial genomes. Overall, the study contributes to microbial genomics and antimicrobial resistance research by demonstrating the applicability of sequence-based genomic characterization for comparative analysis of antibiotic-resistant bacterial populations across clinical and environmental contexts.