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@ARTICLE{Ho:907221,
      author       = {Ho, Phuong and Täuber, Sarah and Stute, Birgit and
                      Grünberger, Alexander and von Lieres, Eric},
      title        = {{M}icrofluidic {R}eproduction of {D}ynamic {B}ioreactor
                      {E}nvironment {B}ased on {C}omputational {L}ifelines},
      journal      = {Frontiers in chemical engineering},
      volume       = {4},
      issn         = {2673-2718},
      address      = {Lausanne},
      publisher    = {Frontiers Media},
      reportid     = {FZJ-2022-01902},
      pages        = {826485},
      year         = {2022},
      abstract     = {The biotechnological production of fine chemicals, proteins
                      and pharmaceuticals is usually hampered by loss of microbial
                      performance during scale-up. This challenge is mainly caused
                      by discrepancies between homogeneous environmental
                      conditions at laboratory scale, where bioprocesses are
                      optimized, and inhomogeneous conditions in large-scale
                      bioreactors, where production takes place. Therefore, to
                      improve strain selection and process development, it is of
                      great interest to characterize these fluctuating conditions
                      at large-scale and to study their effects on microbial
                      cells. In this paper, we demonstrate the potential of
                      computational fluid dynamics (CFD) simulation of large-scale
                      bioreactors combined with dynamic microfluidic single-cell
                      cultivation (dMSCC). Environmental conditions in a 200 L
                      bioreactor were characterized with CFD simulations.
                      Computational lifelines were determined by combining
                      simulated turbulent multiphase flow, mass transport and
                      particle tracing. Glucose availability for Corynebacterium
                      glutamicum cells was determined. The reactor was simulated
                      with average glucose concentrations of 6 g m−3, 10 g m−3
                      and 16 g m−3. The resulting computational lifelines,
                      discretized into starvation and abundance regimes, were used
                      as feed profiles for the dMSCC to investigate how varying
                      glucose concentration affects cell physiology and growth
                      rate. In this study, each colony in the dMSCC device
                      represents a single cell as it travels through the reactor.
                      Under oscillating conditions reproduced in the dMSCC device,
                      a decrease in growth rate of about $40\%$ was observed
                      compared to continuous supply with the same average glucose
                      availability. The presented approach provides insights into
                      environmental conditions observed by microorganisms in
                      large-scale bioreactors. It also paves the way for an
                      improved understanding of how inhomogeneous environmental
                      conditions influence cellular physiology, growth and
                      production.},
      cin          = {IBG-1},
      ddc          = {540},
      cid          = {I:(DE-Juel1)IBG-1-20101118},
      pnm          = {2171 - Biological and environmental resources for
                      sustainable use (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2171},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000994427700001},
      doi          = {10.3389/fceng.2022.826485},
      url          = {https://juser.fz-juelich.de/record/907221},
}