| Antibiotic resistance leads to a dramatic increase in the morbidity and mortality caused by infectious diseases. Even though estimates vary widely, the economic cost of antimicrobial-resistant bacteria is on a rise. The current aimed to identify the antimicrobial resistance of Escherichia coli (E. coli). In fact, this study focused on the recent deep-learning methods (sequencing) to investigate E. coli antibiotic resistance and their protein sequences. To evaluate antibiotic resistance, the sequencing method could be considered the method of choice. The E. coli was identified by either specific biochemical tests or polymerase chain reaction (PCR) using the 16S rRNA gene. The results of aadA1 gene sequences demonstrated 10 nucleic acid substitutions throughout, as compared to the reference NCBI database (MG385063). Out of the 10 nucleic acid substitutions, 9 missense effects were observed. While the dfrA1 gene sequences illustrated 20 nucleic acid substitutions throughout, compared to the reference NCBI database (KY706080), out of the 20 nucleic acid substitutions, 8 missense effects were observed. Furthermore, the sul1 gene sequences displayed 20 nucleic acid substitutions throughout, in comparison with the reference NCBI database (CP069561), and out of the 20 nucleic acid substitutions, 12 missense effects were detected. The cat1 gene sequences showed 14 nucleic acid substitutions throughout, compared to the reference NCBI database (NC017660), and out of the 14 nucleic acid substitutions, 8 missense effects were observed. The precise point (Missense) mutation in four genes (aadA1, dfrA1, sul1, and cat1) in the expected sequence is interpreted to be the target site of a site-specific recombination mechanism that led to antibiotics resistance in E. coli isolates. |
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