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Related Concept Videos

Microbial Growth Measurement: Indirect Methods01:27

Microbial Growth Measurement: Indirect Methods

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Estimating microbial growth is essential for understanding population dynamics and environmental adaptations. Indirect methods provide valuable insights by measuring parameters such as turbidity, metabolic activity, and biomass, enabling efficient and reproducible assessments.During exponential growth, microbial cells scatter light proportionally to their biomass, a principle used in turbidity measurements. About one million cells per milliliter produce detectable scattering, which a...
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Microbial Growth Measurement: Direct Methods01:23

Microbial Growth Measurement: Direct Methods

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Direct methods for measuring microbial populations in a culture are essential tools in microbiology, providing quantitative data for various applications. Among these, microscopic counts, plate counts, and serial dilution are widely used techniques, each with unique principles and applications.Microscopic CountsMicroscopic counting involves the use of a Petroff-Hausser chamber, a specialized microscope slide with a grid and defined depth. By observing a liquid culture under a microscope,...
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ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth
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Quantification of Microbial Robustness in Yeast.

Cecilia Trivellin1, Lisbeth Olsson1, Peter Rugbjerg1,2

  • 1Department of Biology and Biological Engineering, Division of Industrial Biotechnology, Chalmers University of Technology, Gothenburg 412 96, Sweden.

ACS Synthetic Biology
|March 11, 2022
PubMed
Summary

We developed a new method to quantify microbial robustness in changing environments. This approach reveals that while one industrial yeast strain shows better growth, its product yield is less consistent, highlighting function-specific trade-offs.

Keywords:
Fano factorbioprocesshigh-throughputphenomicsrobustness quantificationyeast

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Area of Science:

  • Microbial biotechnology
  • Synthetic biology
  • Bioprocess engineering

Background:

  • Sustainable bioproduction and synthetic cell functions rely on stable microbial performance in fluctuating environments.
  • Quantifying microbial robustness, a key factor for stability, remains a challenge.
  • Existing methods lack standardization for comparing robustness across different cellular functions and strains.

Purpose of the Study:

  • To develop and validate a high-throughput strategy for quantifying microbial robustness across multiple cellular functions and strains.
  • To establish a standardized metric for accurate and reliable robustness quantification.
  • To investigate robustness and its trade-offs in the context of lignocellulosic bioethanol production.

Main Methods:

  • Developed a high-throughput strategy to assess cellular robustness under various perturbations.
  • Applied quantification theory to experimental data to identify the most reliable metric.
  • Utilized the mean-normalized Fano factor for standardized robustness measurement.
  • Evaluated the methodology on industrial and laboratory strains of *Saccharomyces cerevisiae* for bioethanol production.

Main Results:

  • The mean-normalized Fano factor provides accurate, reliable, and standardized quantification of microbial robustness.
  • The industrial *Saccharomyces cerevisiae* strain Ethanol Red demonstrated superior and more robust growth rates compared to laboratory (CEN.PK) and other industrial (PE-2) strains.
  • A trade-off was observed where increased robustness in product yield was associated with lower mean product yield levels.
  • Robustness was confirmed to be function-specific, involving both positive and negative trade-offs.

Conclusions:

  • Systematic quantification of microbial robustness is crucial for strain development and bioproduction.
  • The developed methodology enables standardized assessment of robustness to specific end-use perturbations.
  • Understanding function-specific trade-offs is essential for engineering robust microbial strains with predictable functionalities.
  • This approach facilitates the analysis and construction of more resilient microbial cell factories.