Whether bacterial drug-resistance is drug-induced or results from rapid propagation of random spontaneous mutations in the flora prior to exposure, remains a long-term key issue concerned and debated in both genetics ...Whether bacterial drug-resistance is drug-induced or results from rapid propagation of random spontaneous mutations in the flora prior to exposure, remains a long-term key issue concerned and debated in both genetics and medicinal fields. In a pio-neering study, Luria and Delbruck exposed E. coli to T1 phage, to investigate whether the number of resistant colonies fol- lowed the Poisson distribution. They deduced that the development of resistant colonies is independent of phage presence. Similar results have since been obtained on solid medium containing antibacterial agents. Luria and Delbruck＇s conclusions were long considered a gold standard for analyzing drug resistance mutations. More recently, the concept of adaptive mutation has triggered controversy over this approach. Microbiological observation shows that, following exposure to drugs of various concentrations, drug-resistant cells emerge and multiply depending on the time course, and show a process function, incon-sistent with the definition of Poisson distribution （which assumes not only that resistance is independent of drug quantity but follows no specific time course）. At the same time, since cells tend to aggregate after division rather than separating, colonies growing on drug plates arise from the multiplication of resistant bacteria cells of various initial population sizes. Thus, statisti-cal analysis based on equivalence of initial populations will yield erroneous results. In this paper, 310 data from the Lu- ria-DelbNck fluctuation experiment were reanalyzed from this perspective. In most cases, a high-end abnormal value, resulting from the non-synchronous variation of the two above-mentioned time variables, was observed. Therefore, the mean value cannot be regarded as an unbiased expectation estimate. The ratio between mean value and variance was similarly incompara-ble, because two different sampling methods were used. In fact, the Luria-Delbrtick data appear to follow an aggregated, rather than Poisson distribution. In stmnnary, the statistical analysis of Luria and Delbruck is insufficient to describe rules of resistant mutant development and multiplication. Correction of this historical misunderstanding will enable new insight into bacterial resistance mechanisms.展开更多
文摘Whether bacterial drug-resistance is drug-induced or results from rapid propagation of random spontaneous mutations in the flora prior to exposure, remains a long-term key issue concerned and debated in both genetics and medicinal fields. In a pio-neering study, Luria and Delbruck exposed E. coli to T1 phage, to investigate whether the number of resistant colonies fol- lowed the Poisson distribution. They deduced that the development of resistant colonies is independent of phage presence. Similar results have since been obtained on solid medium containing antibacterial agents. Luria and Delbruck＇s conclusions were long considered a gold standard for analyzing drug resistance mutations. More recently, the concept of adaptive mutation has triggered controversy over this approach. Microbiological observation shows that, following exposure to drugs of various concentrations, drug-resistant cells emerge and multiply depending on the time course, and show a process function, incon-sistent with the definition of Poisson distribution （which assumes not only that resistance is independent of drug quantity but follows no specific time course）. At the same time, since cells tend to aggregate after division rather than separating, colonies growing on drug plates arise from the multiplication of resistant bacteria cells of various initial population sizes. Thus, statisti-cal analysis based on equivalence of initial populations will yield erroneous results. In this paper, 310 data from the Lu- ria-DelbNck fluctuation experiment were reanalyzed from this perspective. In most cases, a high-end abnormal value, resulting from the non-synchronous variation of the two above-mentioned time variables, was observed. Therefore, the mean value cannot be regarded as an unbiased expectation estimate. The ratio between mean value and variance was similarly incompara-ble, because two different sampling methods were used. In fact, the Luria-Delbrtick data appear to follow an aggregated, rather than Poisson distribution. In stmnnary, the statistical analysis of Luria and Delbruck is insufficient to describe rules of resistant mutant development and multiplication. Correction of this historical misunderstanding will enable new insight into bacterial resistance mechanisms.
