Automated growth rate determination in high-throughput microbioreactor systems. (December 2017)

• Record Type: Journal Article
• Authors: Hemmerich, Johannes; Wiechert, Wolfgang; Oldiges, Marco
• Is Part Of: BMC research notes. Volume 10:Number 1(2017)
• Page Start: 1
• Page End: 7
• Publication Date: 2017-12
• Subjects: Microbioreactor -- Online biomass monitoring -- Growth rate -- Exponential growth model -- Quantitative microbial phenotyping; Medicine -- Periodicals; Biology -- Periodicals; 610.5
• DOI: 10.1186/s13104-017-2945-6
• Languages: English
• ISSNs: 1756-0500

Abstract

Abstract Objective The 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. Results A 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 withCorynebacterium glutamicum showing single exponential growth phase andEscherichia 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 reducedC. 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.