近日，来自Wageningen大学的研究者揭示了细菌对抗生素头孢噻肟的耐药性是可以提前进行预测的。很多研究表明细菌中由于许多基因的突变因此产生了对抗生素的耐药性，因此众多抗生素的治疗效果并不明显。和德国的研究者共同合作，Wageningen大学的研究者开发出了一种新的方法，这种新型方法可以帮助我们预测耐药菌株是否会对其它抗生素产生抗性，以及如何产生抗性。相关研究成果刊登在了近日的国际杂志PLoS Genetics上。
文章中，研究者研究了细菌对抗生素头孢噻肟产生抗性的主要酶类，β-内酰胺酶类的主要功能就是破坏β-内酰胺类抗生素，研究者在对抗生素头孢噻肟产生耐药的菌株中发现了众多突变，β-内酰胺酶类的突变提高了细菌对β-内酰胺类抗生素耐药性达3倍以上。基于此前的研究，研究者可以轻松地估计细菌的耐药性效应。
细菌中突变的存在使得科学家可以更容易预测抗生素耐药菌株的产生以及发展。研究者在数量上进行了遗传发现的研究，运用数学模型可以帮助研究者继续深入研究，这样一来研究者就能够解释细菌变得对抗生素产生耐药。通过研究者De Visser的方法，科学家们可以预测细菌对于其它抗生素的“可维持性”（即什么时候产生耐药）。（生物谷Bioon.com）
编译自：Development of Antibiotic Resistance More Predictable Than Expected
doi:10.1371/journal.pgen.1002783
PMC:
PMID:
Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme
Martijn F. Schenk1,2, Ivan G. Szendro3, Joachim Krug3,4, J. Arjan G. M. de Visser2*
For a quantitative understanding of the process of adaptation, we need to understand its “raw material,” that is, the frequency and fitness effects of beneficial mutations. At present, most empirical evidence suggests an exponential distribution of fitness effects of beneficial mutations, as predicted for Gumbel-domain distributions by extreme value theory. Here, we study the distribution of mutation effects on cefotaxime (Ctx) resistance and fitness of 48 unique beneficial mutations in the bacterial enzyme TEM-1 β-lactamase, which were obtained by screening the products of random mutagenesis for increased Ctx resistance. Our contributions are threefold. First, based on the frequency of unique mutations among more than 300 sequenced isolates and correcting for mutation bias, we conservatively estimate that the total number of first-step mutations that increase Ctx resistance in this enzyme is 87 [95% CI 75–189], or 3.4% of all 2,583 possible base-pair substitutions. Of the 48 mutations, 10 are synonymous and the majority of the 38 non-synonymous mutations occur in the pocket surrounding the catalytic site. Second, we estimate the effects of the mutations on Ctx resistance by determining survival at various Ctx concentrations, and we derive their fitness effects by modeling reproduction and survival as a branching process. Third, we find that the distribution of both measures follows a Fréchet-type distribution characterized by a broad tail of a few exceptionally fit mutants. Such distributions have fundamental evolutionary implications, including an increased predictability of evolution, and may provide a partial explanation for recent observations of striking parallel evolution of antibiotic resistance.
