Alireza Ebrahiminezhad, Abdolreza Karami, Zeinab Karimi, Mohammad Kargar, Ahmad Vaez, Aydin Berenjian
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In fact, after an incubation time, the number of viable bacteria can be determined with a single OD measurement and through an equation. In this regard, four standard bacterial strains, including Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922), Pseudomonas aeruginosa (ATCC 27853), and Bacillus subtilis (ATCC 23857), were cultured with descending inoculum densities (1.5 × 10<sup>7</sup> to 15 CFU/mL) and growth curves were drawn. As expected, growth in the samples with lower inoculum densities recorded with longer lag phase. Also, a direct relation was observed between the recorded turbidities and initial cell counts. A logarithmic curve (lag plot) was obtained by plotting the OD, after 12-18 h incubation, against initial cell counts. In all examined strains, R<sup>2</sup> was calculated in the range of 0.96-0.99 which is acceptable value for coefficient of determination. Equation corresponding to the lag plot was obtained and called lag equation. 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引用次数: 0
摘要
杀菌活性是衡量抗菌化合物的一个重要参数。评估杀菌活性的现有标准方案是基于直接菌落计数。菌落计数需要连续稀释、平板、过夜培养和直接计数,耗时耗力。为了消除直接平板计数,人们开发了基于实时生长监测的新技术,但这种技术也有一些局限性和缺点。这些缺点促使我们开发出一种程序简单的新技术来测定存活细菌细胞数。在这种方法中,不需要进行实时生长监测。事实上,经过一段时间的培养后,只需测量一次 OD 值并通过一个等式就能确定存活细菌的数量。为此,我们培养了四种标准细菌菌株,包括金黄色葡萄球菌(ATCC 25923)、大肠杆菌(ATCC 25922)、铜绿假单胞菌(ATCC 27853)和枯草芽孢杆菌(ATCC 23857),接种密度依次降低(1.5 × 107 至 15 CFU/mL),并绘制了生长曲线。不出所料,接种密度较低的样品生长滞后期较长。此外,还观察到所记录的浊度与初始细胞数之间存在直接关系。通过绘制培养 12-18 小时后的 OD 值与初始细胞数的对数曲线(滞后图),可以得出结论。在所有检测菌株中,计算出的 R2 在 0.96-0.99 之间,这是可以接受的判定系数值。与滞后图相对应的方程式被称为滞后方程式。该方程适用于计算未知样品中的存活细胞数,只需接种、培养和单次 OD 测量即可。所开发的技术可简单替代费时费力的直接菌落计数法。
Lag Plot: A Novel Method to Determine Viable Bacterial Cell Number via a Single OD Measurement.
Bactericidal activity is a valuable parameter which is considered and measured for antimicrobial compounds. The available standard protocol to evaluate bactericidal activity is based on the direct colony count. Colony counting requires serial dilution, plating, overnight incubation, and direct counting, which is time-and labor-intensive. In regard to eliminate direct plate count, novel techniques were developed based on the real-time growth monitoring which can come with some limitations and drawbacks. These drawbacks encourage us to develop a novel technique with simple procedure to determine viable bacterial cell count. In this procedure, real-time growth monitoring is not required. In fact, after an incubation time, the number of viable bacteria can be determined with a single OD measurement and through an equation. In this regard, four standard bacterial strains, including Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922), Pseudomonas aeruginosa (ATCC 27853), and Bacillus subtilis (ATCC 23857), were cultured with descending inoculum densities (1.5 × 107 to 15 CFU/mL) and growth curves were drawn. As expected, growth in the samples with lower inoculum densities recorded with longer lag phase. Also, a direct relation was observed between the recorded turbidities and initial cell counts. A logarithmic curve (lag plot) was obtained by plotting the OD, after 12-18 h incubation, against initial cell counts. In all examined strains, R2 was calculated in the range of 0.96-0.99 which is acceptable value for coefficient of determination. Equation corresponding to the lag plot was obtained and called lag equation. This equation is applicable to calculate the number of viable cells in unknown samples simply by inoculation, incubation, and single OD measurement. Developed technique can be introduced as a simple substitution for labor- and time-intensive direct colony counting.
期刊介绍:
Molecular Biotechnology publishes original research papers on the application of molecular biology to both basic and applied research in the field of biotechnology. Particular areas of interest include the following: stability and expression of cloned gene products, cell transformation, gene cloning systems and the production of recombinant proteins, protein purification and analysis, transgenic species, developmental biology, mutation analysis, the applications of DNA fingerprinting, RNA interference, and PCR technology, microarray technology, proteomics, mass spectrometry, bioinformatics, plant molecular biology, microbial genetics, gene probes and the diagnosis of disease, pharmaceutical and health care products, therapeutic agents, vaccines, gene targeting, gene therapy, stem cell technology and tissue engineering, antisense technology, protein engineering and enzyme technology, monoclonal antibodies, glycobiology and glycomics, and agricultural biotechnology.