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Dynamic characterization of growth and gene expression using high-throughput automated flow cytometry.

Zuleta IA, Aranda-Díaz A, Li H, El-Samad H - Nat. Methods (2014)

Bottom Line: Here we report the development of an automated flow cytometry robotic setup that enables real-time measurement of precise and simultaneous relative growth and protein synthesis rates of multiplexed microbial populations across many conditions.These measurements generate quantitative profiles of dynamically evolving protein synthesis and degradation rates.We demonstrate this setup in the context of gene regulation of the unfolded protein response (UPR) of Saccharomyces cerevisiae and uncover a dynamic and complex landscape of gene expression, growth dynamics and proteolysis following perturbations.

View Article: PubMed Central - PubMed

Affiliation: 1] Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, USA. [2] The California Institute for Quantitative Biosciences, San Francisco, California, USA.

ABSTRACT
Cells adjust to changes in environmental conditions using complex regulatory programs. These cellular programs are the result of an intricate interplay between gene expression, cellular growth and protein degradation. Technologies that enable simultaneous and time-resolved measurements of these variables are necessary to dissect cellular homeostatic strategies. Here we report the development of an automated flow cytometry robotic setup that enables real-time measurement of precise and simultaneous relative growth and protein synthesis rates of multiplexed microbial populations across many conditions. These measurements generate quantitative profiles of dynamically evolving protein synthesis and degradation rates. We demonstrate this setup in the context of gene regulation of the unfolded protein response (UPR) of Saccharomyces cerevisiae and uncover a dynamic and complex landscape of gene expression, growth dynamics and proteolysis following perturbations.

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Automated cell culture incubator with real-time flow cytometry readout(a) Comparison of our HT-FACS robotic setup with other technologies for monitoring cell physiology. (b) Layout showing hardware arrangement for our system. (c) Sequence of main events that occur in a typical experiment. These include liquid transfers and plate transport that take place during the acquisition of one measurement. Steps 1–7 repeat every 20 minutes and involve (1) loading a fresh sample plate into the liquid handler, (2) removal of the culture from the incubator, (3) addition of fresh media and stimulus to the culture, (4) removal of a sample from the culture, (5) returning the culture to the incubator, (6) transport of the sample plate to the high throughput sampler (HTS) and (7) measurement of the sample plate in the flow cytometer. (d) Time and dose-dependent dynamical portraits can be acquired with our system to characterize regulatory networks. (e) Example of one of 96 possible conditions in which the fluorescence of 3 strains is monitored over time after a perturbation.
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Figure 1: Automated cell culture incubator with real-time flow cytometry readout(a) Comparison of our HT-FACS robotic setup with other technologies for monitoring cell physiology. (b) Layout showing hardware arrangement for our system. (c) Sequence of main events that occur in a typical experiment. These include liquid transfers and plate transport that take place during the acquisition of one measurement. Steps 1–7 repeat every 20 minutes and involve (1) loading a fresh sample plate into the liquid handler, (2) removal of the culture from the incubator, (3) addition of fresh media and stimulus to the culture, (4) removal of a sample from the culture, (5) returning the culture to the incubator, (6) transport of the sample plate to the high throughput sampler (HTS) and (7) measurement of the sample plate in the flow cytometer. (d) Time and dose-dependent dynamical portraits can be acquired with our system to characterize regulatory networks. (e) Example of one of 96 possible conditions in which the fluorescence of 3 strains is monitored over time after a perturbation.

Mentions: Simultaneous high-throughput measurement of growth and gene expression is challenging. For example, simple bulk growth and fluorescence measurements using plate readers suffer from poor reproducibility10,11. Although substantial progress has been made in time resolution using microfluidics12 and chemostats13,14, these technologies are limited in their ability to achieve simultaneous growth and gene expression measurements in high throughput at the single-cell level (Fig. 1a). To enable such measurements, we developed a measurement setup that integrates a flow cytometer, a liquid handler and a deep-well plate incubator using a robotic arm and custom control software (Fig. 1b, see Online Methods for implementation details). Briefly, using custom software, robotic and fluidic capabilities, samples of a culture are continuously transferred to a shallow 96-well plate, which is then moved by the robot to the flow cytometer for measurement (Fig. 1c). This capability enables us to repeat the above sequence of events to carry facile and reproducible stimulus-response experiments to explore phenotypes across time and stimulus dose (Fig. 1d). A typical experiment consists of two stages: an outgrowth phase where cells are brought to exponential growth, followed by a stimulus event where a treatment solution is added after the appropriate growth state has been achieved. Following the stimulus, we continuously monitor the culture evolution during the response period (Fig. 1e). Treatment and/or culture conditions are automatically maintained through the experiment (up to 24 hours) by adding the stimulus at its nominal concentration to compensate for dilution (Supplementary Fig. 1a). Different stimuli like pulses, nutrient depletions and ramps can also be easily implemented with a high degree of sample-to-sample and day-to-day reproducibility (Supplementary Fig. 1b–c). Additionally, several strains can be simultaneously cultured (multiplexed) in one well for internally controlled measurements of differential phenotypes under a large number of conditions.


Dynamic characterization of growth and gene expression using high-throughput automated flow cytometry.

Zuleta IA, Aranda-Díaz A, Li H, El-Samad H - Nat. Methods (2014)

Automated cell culture incubator with real-time flow cytometry readout(a) Comparison of our HT-FACS robotic setup with other technologies for monitoring cell physiology. (b) Layout showing hardware arrangement for our system. (c) Sequence of main events that occur in a typical experiment. These include liquid transfers and plate transport that take place during the acquisition of one measurement. Steps 1–7 repeat every 20 minutes and involve (1) loading a fresh sample plate into the liquid handler, (2) removal of the culture from the incubator, (3) addition of fresh media and stimulus to the culture, (4) removal of a sample from the culture, (5) returning the culture to the incubator, (6) transport of the sample plate to the high throughput sampler (HTS) and (7) measurement of the sample plate in the flow cytometer. (d) Time and dose-dependent dynamical portraits can be acquired with our system to characterize regulatory networks. (e) Example of one of 96 possible conditions in which the fluorescence of 3 strains is monitored over time after a perturbation.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4016179&req=5

Figure 1: Automated cell culture incubator with real-time flow cytometry readout(a) Comparison of our HT-FACS robotic setup with other technologies for monitoring cell physiology. (b) Layout showing hardware arrangement for our system. (c) Sequence of main events that occur in a typical experiment. These include liquid transfers and plate transport that take place during the acquisition of one measurement. Steps 1–7 repeat every 20 minutes and involve (1) loading a fresh sample plate into the liquid handler, (2) removal of the culture from the incubator, (3) addition of fresh media and stimulus to the culture, (4) removal of a sample from the culture, (5) returning the culture to the incubator, (6) transport of the sample plate to the high throughput sampler (HTS) and (7) measurement of the sample plate in the flow cytometer. (d) Time and dose-dependent dynamical portraits can be acquired with our system to characterize regulatory networks. (e) Example of one of 96 possible conditions in which the fluorescence of 3 strains is monitored over time after a perturbation.
Mentions: Simultaneous high-throughput measurement of growth and gene expression is challenging. For example, simple bulk growth and fluorescence measurements using plate readers suffer from poor reproducibility10,11. Although substantial progress has been made in time resolution using microfluidics12 and chemostats13,14, these technologies are limited in their ability to achieve simultaneous growth and gene expression measurements in high throughput at the single-cell level (Fig. 1a). To enable such measurements, we developed a measurement setup that integrates a flow cytometer, a liquid handler and a deep-well plate incubator using a robotic arm and custom control software (Fig. 1b, see Online Methods for implementation details). Briefly, using custom software, robotic and fluidic capabilities, samples of a culture are continuously transferred to a shallow 96-well plate, which is then moved by the robot to the flow cytometer for measurement (Fig. 1c). This capability enables us to repeat the above sequence of events to carry facile and reproducible stimulus-response experiments to explore phenotypes across time and stimulus dose (Fig. 1d). A typical experiment consists of two stages: an outgrowth phase where cells are brought to exponential growth, followed by a stimulus event where a treatment solution is added after the appropriate growth state has been achieved. Following the stimulus, we continuously monitor the culture evolution during the response period (Fig. 1e). Treatment and/or culture conditions are automatically maintained through the experiment (up to 24 hours) by adding the stimulus at its nominal concentration to compensate for dilution (Supplementary Fig. 1a). Different stimuli like pulses, nutrient depletions and ramps can also be easily implemented with a high degree of sample-to-sample and day-to-day reproducibility (Supplementary Fig. 1b–c). Additionally, several strains can be simultaneously cultured (multiplexed) in one well for internally controlled measurements of differential phenotypes under a large number of conditions.

Bottom Line: Here we report the development of an automated flow cytometry robotic setup that enables real-time measurement of precise and simultaneous relative growth and protein synthesis rates of multiplexed microbial populations across many conditions.These measurements generate quantitative profiles of dynamically evolving protein synthesis and degradation rates.We demonstrate this setup in the context of gene regulation of the unfolded protein response (UPR) of Saccharomyces cerevisiae and uncover a dynamic and complex landscape of gene expression, growth dynamics and proteolysis following perturbations.

View Article: PubMed Central - PubMed

Affiliation: 1] Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, USA. [2] The California Institute for Quantitative Biosciences, San Francisco, California, USA.

ABSTRACT
Cells adjust to changes in environmental conditions using complex regulatory programs. These cellular programs are the result of an intricate interplay between gene expression, cellular growth and protein degradation. Technologies that enable simultaneous and time-resolved measurements of these variables are necessary to dissect cellular homeostatic strategies. Here we report the development of an automated flow cytometry robotic setup that enables real-time measurement of precise and simultaneous relative growth and protein synthesis rates of multiplexed microbial populations across many conditions. These measurements generate quantitative profiles of dynamically evolving protein synthesis and degradation rates. We demonstrate this setup in the context of gene regulation of the unfolded protein response (UPR) of Saccharomyces cerevisiae and uncover a dynamic and complex landscape of gene expression, growth dynamics and proteolysis following perturbations.

Show MeSH
Related in: MedlinePlus