کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10903515 1085680 2013 40 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Experimental evolution as an efficient tool to dissect adaptive paths to antibiotic resistance
ترجمه فارسی عنوان
تکامل تجربی به عنوان یک ابزار کارآمد برای تشخیص مسیرهای سازگار برای مقاومت به آنتی بیوتیک
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی تحقیقات سرطان
چکیده انگلیسی
Antibiotic treatments increasingly fail due to rapid dissemination of drug resistance. Comparative genomics of clinical isolates highlights the role of de novo adaptive mutations and horizontal gene transfer (HGT) in the acquisition of resistance. Yet it cannot fully describe the selective pressures and evolutionary trajectories that yielded today's problematic strains. Experimental evolution offers a compelling addition to such studies because the combination of replicated experiments under tightly controlled conditions with genomics of intermediate time points allows real-time reconstruction of evolutionary trajectories. Recent studies thus established causal links between antibiotic deployment therapies and the course and timing of mutations, the cost of resistance and the likelihood of compensating mutations. They particularly underscored the importance of long-term effects. Similar investigations incorporating horizontal gene transfer (HGT) are wanting, likely because of difficulties associated with its integration into experiments. In this review, we describe current advances in experimental evolution of antibiotic resistance and reflect on ways to incorporate horizontal gene transfer into the approach. We contend it provides a powerful tool for systematic and highly controlled dissection of evolutionary paths to antibiotic resistance that needs to be taken into account for the development of sustainable anti-bacterial treatment strategies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Drug Resistance Updates - Volume 16, Issue 6, December 2013, Pages 96-107
نویسندگان
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