Identification of Promoter Region Markers Associated With Altered Expression of Resistance-Nodulation-Division Antibiotic Efflux Pumps in .

Genetic alterations leading to the constitutive upregulation of specific efflux pumps contribute to antibacterial resistance in multidrug resistant bacteria. The identification of such resistance markers remains one of the most challenging tasks of genome-level resistance predictors. In this study, 487 non-redundant genetic events were identified in upstream zones of three operons coding for resistance-nodulation-division (RND) efflux pumps of 4,130 isolates. These events included insertion sequences, small indels, and single nucleotide polymorphisms. In some cases, alterations explicitly modified the expression motifs described for these operons, such as the promoter boxes, operators, and Shine-Dalgarno sequences. In addition, changes in DNA curvature and mRNA secondary structures, which are structural elements that regulate expression, were also calculated. According to their influence on RND upregulation, the catalog of upstream modifications were associated with "experimentally verified," "presumed," and "probably irrelevant" degrees of certainty. For experimental verification, DNA of upstream sequences independently carrying selected markers, three for each RND operon, were fused to a luciferase reporter plasmid system. Five out of the nine selected markers tested showed significant increases in expression with respect to the wild-type sequence control. In particular, a 25-fold expression increase was observed with the IS1 insertion sequence upstream the pump. Next, overexpression of each of the three multi-specific RND pumps was linked to their respective antibacterial substrates by a deep literature screen. Consequently, a data flow framework was then developed to link genomic upregulatory RND determinants to potential antibiotic resistance. Assignment of potential increases in minimal inhibitory concentrations at the "experimentally verified" level was permitted for 42 isolates to 7-8 unrelated antibacterial agents including tigecycline, which is overlooked by conventional resistome predictors. Thus, our protocol may represent a time-saving filter step prior to laborious confirmation experiments for efflux-driven resistance. Altogether, a computational-experimental pipeline containing all components required for identifying the upstream regulatory resistome is proposed. This schema may provide the foundational stone for the elaboration of tools approaching antibiotic efflux that complement routine resistome predictors for preventing antimicrobial therapy failure against difficult-to-threat bacteria.