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Automated growth rate determination in high-throughput microbioreactor systems

机译:高通量生物反应器系统中的自动化生长速率测定

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摘要

ObjectiveThe calculation of growth rates provides basic metric for biological fitness and is standard task when using microbioreactors (MBRs) in microbial phenotyping. MBRs easily produce huge data at high frequency from parallelized high-throughput cultivations with online monitoring of biomass formation at high temporal resolution. Resulting high-density data need to be processed efficiently to accelerate experimental throughput.ResultsA MATLAB code is presented that detects the exponential growth phase from multiple microbial cultivations in an iterative procedure based on several criteria, according to the model of exponential growth. These were obtained with Corynebacterium glutamicum showing single exponential growth phase and Escherichia coli exhibiting diauxic growth with exponential phase followed by retarded growth. The procedure reproducibly detects the correct biomass data subset for growth rate calculation. The procedure was applied on data set detached from growth phenotyping of library of genome reduced C. glutamicum strains and results agree with previously reported results where manual effort was needed to pre-process the data. Thus, the automated and standardized method enables a fair comparison of strain mutants for biological fitness evaluation. The code is easily parallelized and greatly facilitates experimental throughout in biological fitness testing from strain screenings conducted with MBR systems.
机译:目的增长率的计算提供了生物适应性的基本指标,并且是在微生物表型分析中使用微生物反应器(MBR)时的标准任务。 MBR可以轻松地从并行化的高通量栽培中以高频率产生大量数据,并以高时间分辨率在线监测生物质形成。需要高效处理得到的高密度数据,以提高实验通量。结果根据指数增长模型,提出了一个MATLAB代码,该代码基于多个准则,通过迭代程序,从多个微生物培养中检测指数增长阶段。这些是用显示单个指数生长期的谷氨酸棒杆菌和显示指数生长期的双生大肠埃希氏菌,然后是延迟生长的大肠杆菌获得的。该过程可重复地检测正确的生物量数据子集以进行增长率计算。该程序应用于从基因组还原的谷氨酸棒杆菌菌株的文库的生长表型分离的数据集,并且该结果与先前报道的结果一致,其中需要人工来预处理数据。因此,自动化和标准化的方法能够对菌株突变体进行公平的比较,以进行生物学适应性评估。该代码易于并行化,并极大地促进了通过MBR系统进行的菌株筛选在整个生物学适应性测试中进行的实验。

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