Hyppää sisältöön
    • Suomeksi
    • In English
  • Suomeksi
  • In English
  • Kirjaudu
Näytä aineisto 
  •   Etusivu
  • 3. UTUCris-artikkelit
  • Rinnakkaistallenteet
  • Näytä aineisto
  •   Etusivu
  • 3. UTUCris-artikkelit
  • Rinnakkaistallenteet
  • Näytä aineisto
JavaScript is disabled for your browser. Some features of this site may not work without it.

Advancing recombinant antibody production in E. coli: Optimization of expression and purification via dual GFP promoter and imaging technology

Korkiakoski, Anttoni; Oksanen, Sami; Huovinen, Tuomas

Advancing recombinant antibody production in E. coli: Optimization of expression and purification via dual GFP promoter and imaging technology

Korkiakoski, Anttoni
Oksanen, Sami
Huovinen, Tuomas
Katso/Avaa
1-s2.0-S1046592825001500-main.pdf (4.462Mb)
Lataukset: 

Academic Press
doi:10.1016/j.pep.2025.106808
URI
https://doi.org/10.1016/j.pep.2025.106808
Näytä kaikki kuvailutiedot
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe202601217026
Tiivistelmä

Fed-batch fermentation results in high recombinant protein titers in limited culture volumes. Therefore, it is the preferred operation mode in the bioprocess industry. Optimizing feeding, induction, and harvest timing is a significant time-consuming challenge in bioprocessing complicated by the fact that expressed target protein is rarely detectable in real-time. In this study, the construction of an online sensor is described integrating a dual GFP promoter construct, a blue LED and a Raspberry Pi camera for real-time monitoring of recombinant antibody expression in Escherichia coli. The dual promoter construct allows simultaneous expression of GFP in the cytoplasm and the recombinant antibody in the periplasm, enabling the use of GFP fluorescence as a proxy for protein yield. GFP fluorescence correlated with Fab and nanobody expression over time and the relative quantity of fluorescence predicted the extent of induction. In nanobody fed-batch fermentations, the decreasing rate of dGFP/dt was a valuable parameter for identifying the optimal harvest point, minimizing excessive incubation time and reducing nanobody leakage into the medium. It was further demonstrated that quantitation of pixel values from RGB images captured with a Raspberry Pi 8 MP camera in the flow cell resulted in equal sensitivity for GFP detection as that achieved with a μPMT and photodiode sensors. The 3D-printable GFP sensor station is a valuable tool for process optimization and for educating bioprocess engineering students through real-time visualization of promoter activation. 

Kokoelmat
  • Rinnakkaistallenteet [29335]

Turun yliopiston kirjasto | Turun yliopisto
julkaisut@utu.fi | Tietosuoja | Saavutettavuusseloste
 

 

Tämä kokoelma

JulkaisuajatTekijätNimekkeetAsiasanatTiedekuntaLaitosOppiaineYhteisöt ja kokoelmat

Omat tiedot

Kirjaudu sisäänRekisteröidy

Turun yliopiston kirjasto | Turun yliopisto
julkaisut@utu.fi | Tietosuoja | Saavutettavuusseloste