ArticleMicroorganisms2019
Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips.
Article in Microorganisms, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The trial behind it
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Who cites it
10 citing papers in PubMed.
- Scale-down bioreactors-comparative analysis of configurations.Bioprocess and biosystems engineering · 2025Review
- Impact of mixing insufficiencies on L-phenylalanine production with an Escherichia coli reporter strain in a novel two-compartment bioreactor.Microbial cell factories · 2023Article
- Mammalian Cell-Growth Monitoring Based on an Impedimetric Sensor and Image Processing within a Microfluidic Platform.Sensors (Basel, Switzerland) · 2023Article
- 3D Printed Microfluidic Bioreactors Used for the Preferential Growth of Bacterial Biofilms through Dielectrophoresis.Micromachines · 2022Article
- Fibroblast Derived Skin Wound Healing Modeling on Chip under the Influence of Micro-Capillary Shear Stress.Micromachines · 2022Article
- Kinetic Modeling ofMetabolites · 2022Review
- Automated Conditional Screening of MultipleBioengineering (Basel, Switzerland) · 2020Article
- Single-Cell Technologies to Understand the Mechanisms of Cellular Adaptation in Chemostats.Frontiers in bioengineering and biotechnology · 2020Article
- Spiral microfluidic devices for cell separation and sorting in bioprocesses.Biomicrofluidics · 2019Review
- Recent Developments in Bioprocessing of Recombinant Proteins: Expression Hosts and Process Development.Frontiers in bioengineering and biotechnology · 2019Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Microbial cells in industrial large-scale bioreactors are exposed to fluctuating conditions, e.g., nutrient concentration, dissolved oxygen, temperature, and pH. These inhomogeneities can influence the cell physiology and metabolism, e.g., decelerate cell growth and product formation. Microfluidic systems offer new opportunities to study such effects in great detail by examining responses to varying environmental conditions at single-cell level. However, the possibility to reproduce large-scale bioreactor conditions in microscale cultivation systems has not yet been systematically investigated. Hence, we apply computational fluid dynamics (CFD) simulations to analyze and compare three commonly used microfluidic single-cell trapping and cultivation devices that are based on (i) mother machines (MM), (ii) monolayer growth chambers (MGC), and (iii) negative dielectrophoresis (nDEP). Several representative time-variant nutrient concentration profiles are applied at the chip entry. Responses to these input signals within the studied microfluidic devices are comparatively evaluated at the positions of the cultivated cells. The results are comprehensively presented in a Bode diagram that illustrates the degree of signal damping depending on the frequency of change in the inlet concentration. As a key finding, the MM can accurately reproduce signal changes that occur within 1 s or slower, which are typical for the environmental conditions observed by single cells in large-scale bioreactors, while faster changes are levelled out. In contrast, the nDEP and MGC are found to level out signal changes occurring within 10 s or faster, which can be critical for the proposed application.
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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.