168 Chapter 9 dissemination of certain ESBL genes or the occurrence of fewer nosocomial outbreaks associated with AmpC-mediated resistance (David M. Livermore et al. 2007; Bevan, Jones, and Hawkey 2017). Potential factors, such as the association of certain ESBL genes, like blaCTX-M types, with clonal strains that exhibit enhanced human-to-human transmission, as observed in ST131 E. coli, might be one of the causes of this difference (David M. Livermore et al. 2007; Bevan, Jones, and Hawkey 2017). Alternatively, the acquisition of plasmid-encoded ampC genes may exert a greater fitness cost on bacteria, compared to ESBL genes on mobile elements (San Millan and MacLean 2017). The cooccurrence of plasmid-encoded ampC genes and ESBL genes within the same isolate is seem to be quite uncommon in most prevalence studies(Alvarez et al. 2004), as is the presence of plasmid-encoded ampC genes in isolates harbouring mutations in the ampC promoter/attenuator region associated with AmpC hyperproduction. While it seems plausible that possessing multiple resistance mechanisms could be impractical for microorganisms, comprehensive studies exploring this phenomenon are limited. Another crucial consideration is the difficulty in detecting plasmid-encoded AmpC (pAmpC) genes, particularly in low-resource settings or low- and middle-income countries where access to molecular confirmation tests may be limited. Developing effective surveillance strategies for pAmpC detection in these settings is essential for understanding the true burden of antibiotic resistance. Furthermore, multiple surveillance strategies should be explored to optimize the detection of AmpC-mediated resistance. This includes evaluating the use of nonspecific agars versus specific agars in different settings. For instance, in an intensive care unit (ICU) with selective digestive tract decontamination (SDD) practices, the screening approach may differ from that used in the general population or community settings. Understanding the context-specific strategies for AmpC detection is crucial for implementing appropriate control measures and treatment strategies. Looking ahead, further investigations are necessary to address these knowledge gaps and unravel the complexities underlying AmpC-mediated resistance. By delving deeper into these areas of inquiry, we can enhance our understanding of the interplay between different resistance mechanisms and their implications for treatment strategies and control measures. In the near future, advancements in our knowledge, such as the ability to predict phenotypical traits based on sequence data in combination with machine learning, may pave the way for more precise and effective treatment strategies.
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