Precise, High-throughput Analysis of Bacterial Growth

Abstract

Bacterial growth is a central concept in the development of modern microbial physiology, as well as in the investigation of cellular dynamics at the systems level. Recent studies have reported correlations between bacterial growth and genome-wide events, such as genome reduction and transcriptome reorganization. Correctly analyzing bacterial growth is crucial for understanding the growth-dependent coordination of gene functions and cellular components. Accordingly, the precise quantitative evaluation of bacterial growth in a high-throughput manner is required. Emerging technological developments offer new experimental tools that allow updates of the methods used for studying bacterial growth. The protocol introduced here employs a microplate reader with a highly optimized experimental procedure for the reproducible and precise evaluation of bacterial growth. This protocol was used to evaluate the growth of several previously described Escherichia coli strains. The main steps of the protocol are as follows: the preparation of a large number of cell stocks in small vials for repeated tests with reproducible results, the use of 96-well plates for high-throughput growth evaluation, and the manual calculation of two major parameters (i.e., maximal growth rate and population density) representing the growth dynamics. In comparison to the traditional colony-forming unit (CFU) assay, which counts the cells that are cultured in glass tubes over time on agar plates, the present method is more efficient and provides more detailed temporal records of growth changes, but has a stricter detection limit at low population densities. In summary, the described method is advantageous for the precise and reproducible high-throughput analysis of bacterial growth, which can be used to draw conceptual conclusions or to make theoretical observations.

Correlated chromosomal periodicities according to the growth rate and gene expression

“…The Pearson correlation coefficients between the mean growth rates and the mean numbers of essential genes were -0.03 (p = 0.06) and − 0.15 (p = 3e − 24) in M63 and LB, respectively. www.nature.com/scientificreports/ to locational biases 3,62 . As the replicates were performed in different well locations, the operational bias could be ignored.…”

A decay effect of the bacterial growth rate associated with genome reduction

“…Escherichia coli cells were cultured in minimal medium M63, which contains 62 mM dipotassium hydrogenphosphate, 39 mM potassium dihydrogen phosphate, 15 mM ammonium sulfate, 15 μM thiamine hydrochloride, 1.8 μM Iron (II) sulfate, 0.2 mM magnesium sulfate, and 22 mM glucose. Preparation of the M63 medium was previously described in detail (Kurokawa and Ying, 2017). The colony formation was detected using LB broth agar, Miller (Sigma Aldrich).…”

“…Glycerol stocks of the E. coli cultures collected at the early exponential phase (OD 600 <0.05) were diluted 100- to 1000-fold in M63 medium and well mixed using a vortex. The diluted cell mixture was loaded onto a 96-well microplate (Costar) in multiple wells at varied locations with 200 μL of mixture per well as previously described (Kurokawa and Ying, 2017). The 96-well microplate was incubated in a plate reader (Epoch2, BioTek) with a rotation rate of 600 rpm at 37 °C.…”

“…The raw data sets of these growth curves can be found at Springer Nature Research Data Support and can be accessed online via the following URL: https://doi.org/10.6084/m9.figshare.5918608. The details regarding the determination of the growth data set was previously described (Kurokawa et al, 2016; Kurokawa and Ying, 2017), and the data sets of growth in M63 and LB media were used in the present study. Evaluation of the models (goodness of fit) was assessed based on the sum of squares, which were calculated according to the following equations.…”

“…The most commonly used method is the conventional method to measure the optical turbidity of a bacterial culture at a wavelength of 600 nm (OD 600 ) due to its easy manipulation. To date, this method seems to be the only tool for assessing high-throughput assays of bacterial growth in microplates (Hall et al, 2014; Kurokawa and Ying, 2017), which are commonly used in systematic studies. Several computational techniques have been developed for use in systematic analyses of bacterial growth dynamics (Verissimo et al, 2013; Hall et al, 2014; Sprouffske and Wagner, 2016).…”