Comparison of automated system D2-MINI with conventional method and VITEK-2 for identification and antibiotic susceptibility pattern of gram-negative non-fermentative bacteria

Abstract

This study evaluates and compares the performance of the automated D2-MINI system with conventional microbiological methods and the VITEK-2 system for the identification and antibiotic susceptibility testing (AST) of gram-negative non-fermentative bacteria (NFGNB). A total of 30 clinical isolates were analyzed, including Burkholderia cepacia (n=6), Burkholderia pseudomallei (n=6), Pseudomonas aeruginosa (n=6), Acinetobacter baumannii complex (n=4), Stenotrophomonas maltophilia (n=4), Pseudomonas fluorescens (n=1), Pseudomonas stutzeri (n=1), Achromobacter xylosoxidans (n=1), and Rhizobium radiobacter (n=1). The isolates were recovered from blood (43.3%), pus (23.3%), wound swabs (20.0%), catheter tips (10.0%), and urine (3.3%). Identification was performed using conventional methods (Gram staining, biochemical tests, and AST by disk diffusion) and compared with automated systems (VITEK-2 and D2-MINI). The results showed that both the VITEK-2 and conventional methods achieved 100% concordance for genus and species identification. However, the D2-MINI system demonstrated high genus-level concordance (100%) for common pathogens like Burkholderia spp., Pseudomonas aeruginosa, and Stenotrophomonas maltophilia but failed to identify Rhizobium radiobacter at both genus and species levels. Additionally, it misidentified Pseudomonas fluorescens as Pseudomonas putida and Achromobacter xylosoxidans as Brucella maltose and showed 83.3% species-level accuracy for Acinetobacter baumannii complex. Antibiotic susceptibility testing revealed that VITEK-2 exhibited 100% concordance with the disk diffusion method for key antibiotics like ceftazidime, meropenem, and piperacillin-tazobactam (TZP). However, it failed to generate susceptibility profiles for Burkholderia pseudomallei and had limited data for Stenotrophomonas maltophilia. The D2-MINI system showed 100% concordance for ceftazidime and trimethoprim-sulfamethoxazole but performed poorly for meropenem and TZP. Both systems had database limitations, with D2-MINI unable to test amoxicillin-clavulanate, doxycycline, and ciprofloxacin for Burkholderia spp., while VITEK-2 lacked results for ceftazidime and doxycycline in Pseudomonas spp. This study highlights the strengths and limitations of automated systems in diagnosing NFGNB. While VITEK-2 offers higher accuracy and broader antibiotic panels, the D2-MINI provides a cost-effective alternative for common pathogens but struggles with rare species and certain antibiotics. The findings underscore the need for database improvements in automated systems, particularly for non-fermentative bacteria and last-resort antibiotics, to enhance clinical utility in resource-limited settings.