TY - JOUR
T1 - Quantitative flow cytometry to understand population heterogeneity in response to changes in substrate availability in escherichia coli and saccharomyces cerevisiae chemostats
AU - Heins, Anna Lena
AU - Johanson, Ted
AU - Han, Shanshan
AU - Lundin, Luisa
AU - Carlquist, Magnus
AU - Gernaey, Krist V.
AU - Sørensen, Søren J.
AU - Lantz, Anna Eliasson
PY - 2019
Y1 - 2019
N2 - Microbial cells in bioprocesses are usually described with averaged parameters. But in fact, single cells within populations vary greatly in characteristics such as stress resistance, especially in response to carbon source gradients. Our aim was to introduce tools to quantify population heterogeneity in bioprocesses using a combination of reporter strains, flow cytometry, and easily comprehensible parameters. We calculated mean, mode, peak width, and coefficient of variance to describe distribution characteristics and temporal shifts in fluorescence intensity. The skewness and the slope of cumulative distribution function plots illustrated differences in distribution shape. These parameters are person-independent and precise. We demonstrated this by quantifying growth-related population heterogeneity of Saccharomyces cerevisiae and Escherichia coli reporter strains in steady-state of aerobic glucose-limited chemostat cultures at different dilution rates and in response to glucose pulses. Generally, slow-growing cells showed stronger responses to glucose excess than fast-growing cells. Cell robustness, measured as membrane integrity after exposure to freeze-thaw treatment, of fast-growing cells was strongly affected in subpopulations of low membrane robustness. Glucose pulses protected subpopulations of fast-growing but not slower-growing yeast cells against membrane damage. Our parameters could successfully describe population heterogeneity, thereby revealing physiological characteristics that might have been overlooked during traditional averaged analysis.
AB - Microbial cells in bioprocesses are usually described with averaged parameters. But in fact, single cells within populations vary greatly in characteristics such as stress resistance, especially in response to carbon source gradients. Our aim was to introduce tools to quantify population heterogeneity in bioprocesses using a combination of reporter strains, flow cytometry, and easily comprehensible parameters. We calculated mean, mode, peak width, and coefficient of variance to describe distribution characteristics and temporal shifts in fluorescence intensity. The skewness and the slope of cumulative distribution function plots illustrated differences in distribution shape. These parameters are person-independent and precise. We demonstrated this by quantifying growth-related population heterogeneity of Saccharomyces cerevisiae and Escherichia coli reporter strains in steady-state of aerobic glucose-limited chemostat cultures at different dilution rates and in response to glucose pulses. Generally, slow-growing cells showed stronger responses to glucose excess than fast-growing cells. Cell robustness, measured as membrane integrity after exposure to freeze-thaw treatment, of fast-growing cells was strongly affected in subpopulations of low membrane robustness. Glucose pulses protected subpopulations of fast-growing but not slower-growing yeast cells against membrane damage. Our parameters could successfully describe population heterogeneity, thereby revealing physiological characteristics that might have been overlooked during traditional averaged analysis.
KW - Flow cytometry
KW - Glucose pulse
KW - Membrane robustness
KW - Population heterogeneity
KW - Quantitative flow cytometry
KW - Reporter strain
UR - https://www.scopus.com/pages/publications/85071727214
U2 - 10.3389/fbioe.2019.00187
DO - 10.3389/fbioe.2019.00187
M3 - Article
C2 - 31448270
AN - SCOPUS:85071727214
SN - 2296-4185
VL - 7
JO - Frontiers in Bioengineering and Biotechnology
JF - Frontiers in Bioengineering and Biotechnology
IS - AUG
M1 - 187
ER -