Summary

Enhanced Reproducibility and Precision of High-Throughput Quantification of Bacterial Growth Data Using a Microplate Reader

Published: July 27, 2022
doi:

Summary

Here, a high-throughput protocol is presented to measure growth data, including growth curves, growth rate, and maximum growth rate. The protocol was verified and validated using two biofilm-producing bacteria. The results and approach applied in this study can be expanded to other high-throughput protocols using microplate readers.

Abstract

This study aimed to develop a repeatable, reliable, high-throughput protocol to monitor bacterial growth in 96-well plates and analyze the maximum growth rate. The growth curves and maximum growth rates of two bacterial species were determined. Issues including (i) lid condensation, (ii) pathlength correction, (iii) inoculation size, (iv) sampling time interval, and (v) spatial bias were investigated. The repeatability of the protocol was assessed with three independent technical replications, with a standard deviation of 0.03 between the runs. The maximum growth rates of Bacillus mycoides and Paenibacillus tundrae were determined to be (mean ± SD) 0.99 h−1 ±  0.03 h−1 and 0.85 h−1 ± 0.025 h−1, respectively. These bacteria are more challenging to monitor optically due to their affinity to clump together. This study demonstrates the critical importance of inoculation size, path length correction, lid warming, sampling time intervals, and well-plate spatial bias to obtain reliable, accurate, and reproducible data on microplate readers. The developed protocol and its verification steps can be expanded to other methods using microplate readers and high-throughput protocols, reducing the researchers' innate errors and material costs.

Introduction

Developing interest in multi-omics manipulation, including mechanism and metabolic studies of bacteria, emphasizes the importance of high-throughput and automated methods such as recording growth data1,2. Growth data comprising kinetic parameters, such as maximum growth rates, can help characterize bacterial responses to different physical, chemical, and antibacterial conditions. Growth rate data are a standard response variable utilized to uncover potential genotype-phenotypes linkages1 or indicate the microbial safety and shelf life of food produce3,4. Techniques such as adaptive laboratory evolution5,6,7, genome-wide screening, certain chemical assays8, and various forward genetic screens9 rely on growth rates to evaluate the results.

Optical density (OD) measurements of bacterial cultures are a standard microbiological method to monitor bacterial growth. OD measurements are often recorded at a wavelength of 600 nm, relying on light scattering and the cell density10,11. The Beer-Lambert law explains the OD values' dependency on the concentration (i.e., cell density, cell number), path length, and absorptivity coefficient. The geometry and optical system of a spectrophotometer influence the OD readings11. Classical methods of OD measurements can be very time- and labor-intensive, and the data can carry a variety of human errors. In this protocol, a microplate reader is used to decrease the analyst time12,13 and the chance of biological contamination. High-throughput analysis using microplate readers is broadly applied in different microbiology areas, such as screening biofilm-producing bacteria14,15, bacterial growth inhibition16, yeast cell growth17, the determination of antifungal susceptibility18, and toxicity screening of nanomaterials19.

A few researchers have published bacterial growth rate protocols using a microplate reader12,20,21. However, a thorough protocol that examines the reliability of collected data has not been fully established. It is reported that factors such as the type of species22,23,24 and sealing tapes impact the repeatability due to the oxygen transfer inadequacy in a 96-well plate25,26. Delaney et al. reported large clusters of Methylorubrum extorquens (wild-type strain) in the growth medium when using a microplate reader, which caused extremely noisy growth data24. The issue was resolved by removing the genes associated with biofilm production24. Due to the secretion of extracellular polymeric substances, biofilm-producing bacteria have a greater affinity to coalesce together and create cell clusters. Therefore, it is more challenging to monitor their growth using light scattering techniques (e.g., spectrophotometers and microplate readers).

This protocol aims to establish steps to obtain reproducible data in a high-throughput method using a microplate reader. Bacillus mycoides and Paenibacillus tundrae were used due to their fast growth and biofilm-producing ability, which are traditionally challenging in manual and automated approaches. Factors such as (i) pathlength correction, (ii) condensation on the lid, (iii) inoculum size, (iv) sampling time interval, and (v) spatial bias were investigated to assess the reliability and reproducibility of the data. This protocol presents steps for accurately monitoring bacterial growth and measuring specific growth rates using a microplate reader.

Protocol

NOTE: All steps in this protocol must be followed in sterile conditions (i.e., between two flames or a biosafety cabinet). All materials and tools are autoclaved for 20 min. See the Table of Materials for details about all materials, equipment, and software used in this protocol. Gloved hands are disinfected, kept wet with hand disinfectant or 70% alcohol solution for at least 1 min, and not removed from the safety cabinet afterward. Otherwise, the disinfecting procedure must be repeated before introduci…

Representative Results

OD reading validation and pathlength correction factor Split samples of B. mycoides culture were taken at different time points and measured using the microplate reader and the spectrophotometer (Figure 1A). This step was taken to validate the results across different devices. The OD600 data correlated but did not match (Figure 1B). The correlation was linear with a slope of 0.55 (95% confidence interval [CI]: 0.53-0.58…

Discussion

Microplate readers allow for obtaining consistent and repeatable growth rates. This technology minimizes human error and enables high-throughput sampling. The small amount of culture required per sample makes this approach an attractive, low-cost alternative to cell counts using flasks or test tubes. Microplate readers allow a large sample size, increasing the statistical power and subsequently facilitating reliable growth rate calculations while keeping costs and labor low.

This article prese…

Disclosures

The authors have nothing to disclose.

Acknowledgements

This work was funded by the Natural Sciences and Engineering Research Council (NSERC) / Halifax Water Industrial Research Chair in Water Quality and Treatment (Grant No. IRCPJ 349838-16). The team of authors also would like to acknowledge the help of Anita Taylor in reviewing this article.

Materials

Centrifuge  Eppendorf 5810 R
Centrifuge tubes – 15 mL  ThermoFisher- Scientific  339650 Sterile
Centriguge tubes – 50 mL  ThermoFisher- Scientific  339652 Sterile
Disposable inoculating loop , 10 µL Cole-Parmer  UZ-06231-08 Sterile
Erlenmeyer flasks – 250 mL  Cole-Parmer   UZ-34502-59 Glass 
Isopropanol  ThermoFisher- Scientific  396982500 ≥99.0
Phosphate Buffer Saline  Sigma-Aldrich P4417
Pipett tips 1,000 µL ThermoFisher- Scientific   UZ-25001-76
Pipett tips 10 mL  ThermoFisher- Scientific  UZ-25001-83
Pipett tips 200 µL ThermoFisher- Scientific  UZ-25001-85
Pipett tips 5 mL  ThermoFisher- Scientific   UZ-25001-80
Pipettor 1,000 µL Cole-Parmer  UZ-07909-11
Pipettor 10 mL Cole-Parmer  UZ-07909-15
Pipettor 200 µL Cole-Parmer   UZ-07909-09
Pipettor 5 mL  Cole-Parmer  UZ-07859-30
Tryptic Soy Broth  Millipore 22091 Suitable for microbiology

References

  1. Reuß, D. R., et al. Large-scale reduction of the Bacillus subtilis genome: Consequences for the transcriptional network, resource allocation, and metabolism. Genome Research. 27 (2), 289-299 (2017).
  2. Sparkes, A., et al. Towards Robot Scientists for autonomous scientific discovery. Automated Experimentation. 2 (1), (2010).
  3. Zwietering, M. H., Jongenburger, I., Rombouts, F. M., van t Riet, K. Modeling of the bacterial growth curve. Applied and Environmental Microbiology. 56 (6), 1875-1881 (1990).
  4. Pla, M., Oltra, S., Esteban, M., Andreu, S., Palop, A. Comparison of primary models to predict microbial growth by the plate count and absorbance methods. BioMed Research International. 2015 (6), 1-14 (2015).
  5. Choe, D., et al. Adaptive laboratory evolution of a genome-reduced Escherichia coli. Nature Communications. 10 (1), 935 (2019).
  6. Dykhuizen, D. E., Dean, A. M. Enzyme activity and fitness: Evolution in solution. Trends in Ecology and Evolution. 5 (8), 257-262 (1990).
  7. McDonald, M. J. Microbial experimental evolution – A proving ground for evolutionary theory and a tool for discovery. EMBO Reports. 20 (8), 1-14 (2019).
  8. Lum, P. Y., et al. Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes. Cell. 116 (1), 121-137 (2004).
  9. Cagnon, C., et al. Development of a forward genetic screen to isolate oil mutants in the green microalga Chlamydomonas reinhardtii. Biotechnology for Biofuels. 6 (1), 178 (2013).
  10. Stevenson, K., McVey, A. F., Clark, I. B. N., Swain, P. S., Pilizota, T. General calibration of microbial growth in microplate readers. Scientific Reports. 6 (1), 38828 (2016).
  11. Matlock, B. C., Beringer, R. W., Ash, D. L., Page, A. F., Allen, M. W. Differences in Bacterial Optical Density Measurements between Spectrophotometers. Technical Note. ThermoScientific. , (2011).
  12. Hall, B. G., Acar, H., Nandipati, A., Barlow, M. Growth rates made easy. Molecular Biology and Evolution. 31 (1), 232-238 (2014).
  13. Rolfe, M. D., et al. Lag phase is a distinct growth phase that prepares bacteria for exponential growth and involves transient metal accumulation. Journal of Bacteriology. 194 (3), 686-701 (2012).
  14. Djordjevic, D., Wiedmann, M., Mclandsborough, L. A. Microtiter plate assay for assessment of Listeria monocytogenes biofilm formation. Applied and Environmental Microbiology. 68 (6), 2950-2958 (2002).
  15. O’Toole, G. A. Microtiter dish biofilm formation assay. Journal of Visualized Experiments. (47), e2437 (2011).
  16. Campbell, J. High-throughput assessment of bacterial growth inhibition by optical density measurements. Current Protocols in Chemical Biology. 3 (3), 1-20 (2012).
  17. Toussaint, M., Conconi, A. High-throughput and sensitive assay to measure yeast cell growth: A bench protocol for testing genotoxic agents. Nature Protocols. 1 (4), 1922-1928 (2006).
  18. Goughenour, K. D., Balada-Llasat, J. -. M., Rappleye, C. A. Quantitative microplate-based growth assay for determination of antifungal susceptibility of Histoplasma capsulatum yeasts. Journal of Clinical Microbiology. 53 (10), 3286-3295 (2015).
  19. Qiu, T. A., et al. Growth-based bacterial viability assay for interference-free and high-throughput toxicity screening of nanomaterials. Analytical Chemistry. 89 (3), 2057-2064 (2017).
  20. Kurokawa, M., Precise Ying, B. -. W. Precise, high-throughput analysis of bacterial growth. Journal of Visualized Experiments. (127), e56197 (2017).
  21. Bredit, F., Romick, T. L., Fleming, H. P. A rapid method for determination of bacterial growth kinetics. Journal of Rapid Methods and Automation in Microbiology. 3, 59-68 (1994).
  22. Delaney, N. F., et al. Development of an optimized medium, strain and high-throughput culturing methods for Methylobacterium extorquens. PLOS ONE. 8 (4), 62957 (2013).
  23. Haire, T. C., et al. Robust microplate-based methods for culturing and in vivo phenotypic screening of Chlamydomonas reinhardtii. Frontiers in Plant Science. 9, 235 (2018).
  24. McBirney, S. E., Trinh, K., Wong-Beringer, A., Armani, A. M. Wavelength-normalized spectroscopic analysis of Staphylococcus aureus and Pseudomonas aeruginosa growth rates. Biomedical Optics Express. 7 (10), 4034 (2016).
  25. Sieben, M., Giese, H., Grosch, J. H., Kauffmann, K., Büchs, J. Permeability of currently available microtiter plate sealing tapes fail to fulfil the requirements for aerobic microbial cultivation. Biotechnology Journal. 11 (12), 1525-1538 (2016).
  26. Zimmermann, H. F., John, G. T., Trauthwein, H., Dingerdissen, U., Huthmacher, K. Rapid evaluation of oxygen and water permeation through microplate sealing tapes. Biotechnology Progress. 19 (3), 1061-1063 (2003).
  27. Abkar, L., Gagnon, G. A. Biological responses to P-limitation in indigenous bacteria isolated from drinking water. AWWA Water Science. 3 (5), 1248 (2021).
  28. Sanders, E. R. Aseptic laboratory techniques: Plating methods. Journal of Visualized Experiments. (63), e3064 (2012).
  29. Hart, S. F. M., Skelding, D., Waite, A. J., Burton, J. C., Shou, W. High-throughput quantification of microbial birth and death dynamics using fluorescence microscopy. Quantitative Biology. 7 (1), 69-81 (2019).
  30. Periago, P. M., Abee, T., Wouters, J. A. Analysis of the heat-adaptive response of psychrotrophic Bacillus weihenstephanensis. International Journal of Food Microbiology. 79 (1-2), 17-26 (2002).
  31. Mira, P., Barlow, M., Meza, J. C., Hall, B. G. Statistical package for growth rates made easy. Molecular Biology and Evolution. 34 (12), 3303-3309 (2017).
This article has been published
Video Coming Soon
Keep me updated:

.

Cite This Article
Abkar, L., Wilfart, F. M., Piercey, M., Gagnon, G. A. Enhanced Reproducibility and Precision of High-Throughput Quantification of Bacterial Growth Data Using a Microplate Reader. J. Vis. Exp. (185), e63849, doi:10.3791/63849 (2022).

View Video