Agriculture and Agri-Food Canada, London Research and Development Centre, London, Ontario, Canada.
Department of Biology, University of Western Ontario, London, Ontario, Canada.
Appl Environ Microbiol. 2023 Apr 26;89(4):e0026123. doi: 10.1128/aem.00261-23. Epub 2023 Mar 28.
It is generally thought that antibiotics confer upon the producing bacteria the ability to inhibit or kill neighboring microorganisms, thereby providing the producer with a significant competitive advantage. Were this to be the case, the concentrations of emitted antibiotics in the vicinity of producing bacteria might be expected to fall within the ranges of MICs that are documented for a number of bacteria. Furthermore, antibiotic concentrations that bacteria are punctually or chronically exposed to in environments harboring antibiotic-producing bacteria might fall within the range of minimum selective concentrations (MSCs) that confer a fitness advantage to bacteria carrying acquired antibiotic resistance genes. There are, to our knowledge, no available measured antibiotic concentrations in the biofilm environments that bacteria typically live in. The objective of the present study was to use a modeling approach to estimate the antibiotic concentrations that might accumulate in the vicinity of bacteria that are producing an antibiotic. Fick's law was used to model antibiotic diffusion using a series of key assumptions. The concentrations of antibiotics within a few microns of single producing cells could not reach MSC (8 to 16 μg/L) or MIC (500 μg/L) values, whereas the concentrations around aggregates of a thousand cells could reach these concentrations. The model outputs suggest that single cells could not produce an antibiotic at a rate sufficient to achieve a bioactive concentration in the vicinity, whereas a group of cells, each producing the antibiotic, could do so. It is generally assumed that a natural function of antibiotics is to provide their producers with a competitive advantage. If this were the case, sensitive organisms in proximity to producers would be exposed to inhibitory concentrations. The widespread detection of antibiotic resistance genes in pristine environments suggests that bacteria are indeed exposed to inhibitory antibiotic concentrations in the natural world. Here, a model using Fick's law was used to estimate potential antibiotic concentrations in the space surrounding producing cells at the micron scale. Key assumptions were that per-cell production rates drawn from the pharmaceutical manufacturing industry are applicable , that production rates were constant, and that produced antibiotics are stable. The model outputs indicate that antibiotic concentrations in proximity to aggregates of a thousand cells can indeed be in the minimum inhibitory or minimum selective concentration range.
人们普遍认为，抗生素赋予了产生它们的细菌抑制或杀死邻近微生物的能力，从而为生产者提供了显著的竞争优势。如果是这样的话，那么在产生细菌的附近，抗生素的浓度可能会落在已记录的多种细菌的 MIC 范围内。此外，在含有产生抗生素的细菌的环境中，细菌定期或慢性暴露的抗生素浓度可能落在赋予携带获得性抗生素抗性基因的细菌适应性优势的最小选择浓度 (MSC) 范围内。据我们所知，在细菌通常生活的生物膜环境中，没有可测量的抗生素浓度。本研究的目的是使用建模方法来估计产生抗生素的细菌附近可能积累的抗生素浓度。菲克定律被用于使用一系列关键假设来模拟抗生素的扩散。单个产菌细胞附近几微米范围内的抗生素浓度不可能达到 MSC（8-16μg/L）或 MIC（500μg/L）值，而聚集了一千个细胞的周围区域的抗生素浓度可能达到这些值。模型输出表明，单个细胞不可能以足够的速度产生抗生素，从而在附近达到生物活性浓度，而一群细胞，每个细胞都产生抗生素，就可以做到这一点。人们普遍认为，抗生素的自然功能是为其生产者提供竞争优势。如果是这样的话，那么靠近生产者的敏感生物体会暴露在抑制浓度下。在原始环境中广泛检测到抗生素抗性基因表明，在自然界中，细菌确实会暴露在抑制性抗生素浓度下。在这里，使用菲克定律的模型用于估计在微米尺度上产生细胞周围空间中潜在抗生素浓度。关键假设是，从制药行业提取的每个细胞的生产速率是适用的，生产速率是恒定的，并且产生的抗生素是稳定的。模型输出表明，聚集了一千个细胞的抗生素浓度确实可以达到最小抑制或最小选择浓度范围。
