ArticleFrontiers in bioengineering and biotechnology2019
Quantitative Flow Cytometry to Understand Population Heterogeneity in Response to Changes in Substrate Availability in
Article in Frontiers in bioengineering and biotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 29 citations in OpenAlex.
- Influence of Varying Pre-Culture Conditions on the Level of Population Heterogeneity in Batch Cultures with anMicroorganisms · 2023Article
- Expression of the Bacterial Enzyme IdeS Using a GFP Fusion in the Yeast Saccharomyces cerevisiae.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Identifying cell-to-cell variability in internalization using flow cytometry.Journal of the Royal Society, Interface · 2022Article
- Advances in automated real-time flow cytometry for monitoring of bioreactor processes.Engineering in life sciences · 2022Review
- Article
- Cascaded processing enables continuous upstream processing with E. coli BL21(DE3).Scientific reports · 2021Article
- Single Cell Analysis of Drug Susceptibility ofAntibiotics (Basel, Switzerland) · 2020Article
- A robust flow cytometry-based biomass monitoring tool enables rapid at-line characterization of S. cerevisiae physiology during continuous bioprocessing of spent sulfite liquor.Analytical and bioanalytical chemistry · 2020Article
- Development and characterization of Escherichia coli triple reporter strains for investigation of population heterogeneity in bioprocesses.Microbial cell factories · 2020Article
- Single-Cell Technologies to Understand the Mechanisms of Cellular Adaptation in Chemostats.Frontiers in bioengineering and biotechnology · 2020Article
- Development of Novel Bioreactor Control Systems Based on Smart Sensors and Actuators.Frontiers in bioengineering and biotechnology · 2020Review
- The LazarusFrontiers in bioengineering and biotechnology · 2020Article
- The Rocky Road From Fed-Batch to Continuous Processing WithFrontiers in bioengineering and biotechnology · 2019Review
- Quantitation and Comparison of Phenotypic Heterogeneity Among Single Cells of Monoclonal Microbial Populations.Frontiers in microbiology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.