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Updated: Aug 19, 2025

Microfluidic Picoliter Bioreactor for Microbial Single-cell Analysis: Fabrication, System Setup, and Operation
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Microbial lifelines in bioprocesses: From concept to application.

Luisa Blöbaum1, Cees Haringa2, Alexander Grünberger3

  • 1Multiscale Bioengineering, Technical Faculty, Bielefeld University, Bielefeld, Germany; CeBiTec, Bielefeld University, Bielefeld, Germany.

Biotechnology Advances
|December 4, 2022
PubMed
Summary

Microbial lifeline analysis offers a new way to understand cell behavior in large-scale bioprocesses. This approach helps predict and prevent scale-up failures by tracking individual cell experiences with environmental gradients.

Keywords:
Bioprocess developmentBioprocess modellingBioreactor gradientsComputational fluid dynamicsFlow-following sensorsMicrobial lifelineMicrofluidicsScale-downSingle-cell cultivation

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Area of Science:

  • Biotechnology
  • Bioprocess Engineering
  • Microbial Physiology

Background:

  • Scaling up bioprocesses leads to increased environmental gradients and inefficient mixing.
  • These gradients impact microbial metabolism, hindering performance prediction and causing scale-up failures.
  • Understanding cell-level responses to environmental heterogeneity is crucial for successful bioprocess development.

Purpose of the Study:

  • To review current concepts and challenges in microbial lifeline analysis for bioprocesses.
  • To explore new technical developments enabling interdisciplinary lifeline determination.
  • To outline strategies for integrating lifeline analysis into bioprocess development and scale-up.

Main Methods:

  • Review of existing computational fluid dynamics (CFD) models for lifeline determination.
  • Discussion of emerging technologies like flow-following sensor particles and microfluidic single-cell cultivation.
  • Analysis of the application and integration of lifeline data in bioprocess optimization.

Main Results:

  • Microbial lifelines provide a cell-centric view of environmental gradients, improving understanding of population dynamics.
  • New technologies facilitate more accurate and interdisciplinary determination of microbial lifelines.
  • Lifeline analysis can guide scale-down experiments and identify targets for strain engineering and bioreactor optimization.

Conclusions:

  • Microbial lifeline analysis is a promising approach to overcome scale-up challenges in bioprocessing.
  • Integrating lifeline analysis enhances the prediction of large-scale bioprocess performance.
  • This methodology supports successful scale-up by informing process and strain optimization strategies.