Back

Azithromycin robustly synergizes with tetracyclines to overcome acquired minocycline resistance in Acinetobacter baumannii

Raza, H.; Tiwari, S.; Dillon, N.

2026-01-14 microbiology
10.64898/2026.01.14.699369 bioRxiv
Show abstract

Multidrug-resistant (MDR) Acinetobacter baumannii is a critical nosocomial pathogen with rapidly shrinking treatment options, and although minocycline (MIN) remains useful, resistance is increasingly common, highlighting the need for effective combination therapies. Here, we investigate azithromycin (AZM)-tetracycline synergism as a strategy to overcome acquired MIN resistance and define the antibiotic-specific drivers of this interaction. Using MIC90 and checkerboard fractional inhibitory concentration (FIC) assays, we tested AZM and MIN across multiple A. baumannii strains (AB5075, ATCC19606, BAA1710, BAA1789) in both bacteriological (CA-MHB) and physiologic (RPMI+) media and found AZM-MIN synergy to be robust across strains and media, with enhanced synergy in RPMI+. To determine whether this effect reflects a class-wide phenomenon, we systematically evaluated different macrolide-tetracycline combinations and observed that synergy occurred consistently in AZM containing pairs, identifying AZM (not tetracycline selection) as the dominant driver of synergy. Mechanistically, translation inhibition assays using an AB5075-luxCDABE reporter demonstrated that AZM uniquely sustained strong translational inhibition at multiple sub-inhibitory fractions, supporting a kinetic basis for synergy when combined with tetracyclines. Finally, AZM-MIN synergy was evaluated against 41 MDR isolates from the CDC-FDA Antimicrobial Resistance Isolate Bank, where synergism was detected in 8/41 strains and reduced the inhibitory MIN concentration below the CLSI resistance breakpoint for 4 isolates, indicating that AZM-based combinations can partially restore MIN susceptibility in resistant backgrounds. Together, these findings establish AZM as a potent and distinctive macrolide synergist with tetracyclines against MDR A. baumannii and support further exploration of AZM-tetracycline combination therapy to extend the clinical utility of MIN and mitigate selection for resistance.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.