论文标题

Scan4CFU:低成本的开源细菌菌落跟踪大面积和延长的孵化时间

Scan4CFU: Low-cost, open-source bacterial colony tracking over large areas and extended incubation times

论文作者

Pandey, Santosh, Park, Yunsoo, Ankita, Ankita, Phillips, Gregory J.

论文摘要

在体外培养的细菌种群的标志是它们的生长同质性,其中大多数细胞显示出相同的生长速率,细胞大小和含量。然而,最近的见解表明,对于通常用于测量细胞生长的变量,即使在指数生长阶段生长的细胞也可能是异质的。细菌异质性对细菌如何应对环境应激(例如抗生素)具有重要意义。例如,抗菌持久性的现象与已经进入不再有效的抗生素不再有效的细胞的细胞亚群有关。虽然已经开发出用于鉴定细菌培养物中个体非生长细胞的方法,但对这些细胞如何影响固体表面菌落的生长的关注较少。作为响应,我们开发了一个低成本的开源平台,以同时对多种营养琼脂平板上的细菌菌落生长进行自动图像捕获和图像分析。包括硬件和软件的描述,以及有关温度控制的生长室,高分辨率扫描仪和图形接口的详细信息,以提取和绘制菌落滞后时间和生长动力学。使用大肠杆菌K12的野生型菌株进行实验,以证明我们的设置的可行性和运行。通过自动跟踪菌落中细菌生长动力学的自动跟踪,该系统具有揭示有关了解微生物异质性对抗生素耐药性和持久性的影响的新见解。

A hallmark of bacterial populations cultured in vitro is their homogeneity of growth, where the majority of cells display identical growth rate, cell size and content. Recent insights, however, have revealed that even cells growing in exponential growth phase can be heterogeneous with respect to variables typically used to measure cell growth. Bacterial heterogeneity has important implications for how bacteria respond to environmental stresses, such as antibiotics. The phenomenon of antimicrobial persistence, for example, has been linked to a small subpopulation of cells that have entered into a state of dormancy where antibiotics are no longer effective. While methods have been developed for identifying individual non-growing cells in bacterial cultures, there has been less attention paid to how these cells may influence growth in colonies on a solid surface. In response, we have developed a low-cost, open-source platform to perform automated image capture and image analysis of bacterial colony growth on multiple nutrient agar plates simultaneously. The descriptions of the hardware and software are included, along with details about the temperature-controlled growth chamber, high-resolution scanner, and graphical interface to extract and plot the colony lag time and growth kinetics. Experiments were conducted using a wild type strain of Escherichia coli K12 to demonstrate the feasibility and operation of our setup. By automated tracking of bacterial growth kinetics in colonies, the system holds the potential to reveal new insights into understanding the impact of microbial heterogeneity on antibiotic resistance and persistence.

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