Applied Microbiology and Biotechnology

, Volume 100, Issue 9, pp 4147–4159 | Cite as

Online analysis of protein inclusion bodies produced in E. coli by monitoring alterations in scattered and reflected light

  • Christian Ude
  • Nadav Ben-Dov
  • André Jochums
  • Zhaopeng Li
  • Ester Segal
  • Thomas Scheper
  • Sascha Beutel
Methods and protocols


The online monitoring of recombinant protein aggregate inclusion bodies during microbial cultivation is an immense challenge. Measurement of scattered and reflected light offers a versatile and non-invasive measurement technique. Therefore, we investigated two methods to detect the formation of inclusion bodies and monitor their production: (1) online 180° scattered light measurement (λ = 625 nm) using a sensor platform during cultivation in shake flask and (2) online measurement of the light reflective interference using a porous Si-based optical biosensor (SiPA). It could be shown that 180° scattered light measurement allows monitoring of alterations in the optical properties of Escherichia coli BL21 cells, associated with the formation of inclusion bodies during cultivation. A reproducible linear correlation between the inclusion body concentration of the non-fluorescent protein human leukemia inhibitory factor (hLIF) carrying a thioredoxin tag and the shift (“Δamp”) in scattered light signal intensity was observed. This was also observed for the glutathione-S-transferase-tagged green fluorescent protein (GFP-GST). Continuous online monitoring of reflective interference spectra reveals a significant increase in the bacterium refractive index during hLIF production in comparison to a non-induced reference that coincide with the formation of inclusion bodies. These online monitoring techniques could be applied for fast and cost-effective screening of different protein expression systems.


Online scattered-light sensor Inclusion bodies Flow cytometry Reflective interference Fourier transform spectra Silicon photonic arrays Optical biosensor 



We would like to thank all members of our research groups for providing feedback and suggestions. This work was partially supported by the Russell Berrie Nanotechnology Institute (RBNI) and the Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering (LS&E). SiPA samples were prepared at the Micro-Nano Fabrication Unit (MNFU), Technion.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights

No research involving human participants and/or animals was carried out.


This study was supported by the Bundesministerium für Wirtschaft und Technologie via Arbeitsgemeinschaft industrieller Forschungsvereinigungen “Otto von Guericke” e. V. within the Zentrale Innovationsoffensive Mittelstand-initiative. Additional funding for this study was provided by the Deutsche Technion-Gesellschaft.

Consent to submit

The authors declare that they agree each with submission of this manuscript. The authors declare that the manuscript has not been submitted to more than one journal for simultaneous consideration.

Supplementary material

253_2016_7403_MOESM1_ESM.pdf (28.4 mb)
ESM 1 (PDF 29087 kb)


  1. Ami D, Natalello A, Taylor G, Tonon G, Maria Doglia S (2006) Structural analysis of protein inclusion bodies by Fourier transform infrared microspectroscopy. Biochim Biophys Acta BBA—Proteins Proteomics 1764:793–799. doi: 10.1016/j.bbapap.2005.12.005 CrossRefPubMedGoogle Scholar
  2. Bleasdale JKA, Nelder JA (1960) Plant population and crop yield. Nature 188:342–342. doi: 10.1038/188342a0 CrossRefGoogle Scholar
  3. Castellanos-Mendoza A, Castro-Acosta RM, Olvera A, Zavala G, Mendoza-Vera M, García-Hernández E, Alagón A, Trujillo-Roldán MA, Valdez-Cruz NA (2014) Influence of pH control in the formation of inclusion bodies during production of recombinant sphingomyelinase-D in Escherichia coli. Microb Cell Factories 13:137. doi: 10.1186/s12934-014-0137-9 CrossRefGoogle Scholar
  4. Crisman RL, Randolph TW (2009) Refolding of proteins from inclusion bodies is favored by a diminished hydrophobic effect at elevated pressures. Biotechnol Bioeng 102:483–492. doi: 10.1002/bit.22082 CrossRefPubMedGoogle Scholar
  5. Drezek R, Dunn A, Richards-Kortum R (1999) Light scattering from cells: finite-difference time-domain simulations and goniometric measurements. Appl Opt 38:3651. doi: 10.1364/AO.38.003651 CrossRefPubMedGoogle Scholar
  6. Espargaró A, Sabate R, Ventura S (2012) Thioflavin-S staining coupled to flow cytometry. A screening tool to detect in vivo protein aggregation. Mol Biosyst 8:2839. doi: 10.1039/c2mb25214g CrossRefPubMedGoogle Scholar
  7. Fioroni M, Dworeck T, Rodriguez-Ropero F (2014) ß-barrel channel proteins as tools in nanotechnology. Springer Netherlands, DordrechtCrossRefGoogle Scholar
  8. Gálvez A, Iglesias A (2011) Efficient particle swarm optimization approach for data fitting with free knot-splines. Comput Aided Des 43:1683–1692. doi: 10.1016/j.cad.2011.07.010 CrossRefGoogle Scholar
  9. Gubellini F, Verdon G, Karpowich NK, Luff JD, Boel G, Gauthier N, Handelman SK, Ades SE, Hunt JF (2011) Physiological response to membrane protein overexpression in E. coli. Mol Cell Proteomics 10:M111.007930–M111.007930. doi: 10.1074/mcp.M111.007930 CrossRefPubMedPubMedCentralGoogle Scholar
  10. Hedhammar M, Stenvall M, Lönneborg R, Nord O, Sjölin O, Brismar H, Uhlén M, Ottosson J, Hober S (2005) A novel flow cytometry-based method for analysis of expression levels in Escherichia coli, giving information about precipitated and soluble protein. J Biotechnol 119:133–146. doi: 10.1016/j.jbiotec.2005.03.024 CrossRefPubMedGoogle Scholar
  11. Hewitt CJ, Nebe-Von-Caron G (2004) The application of multi-parameter flow cytometry to monitor individual microbial cell physiological state. In: Physiological stress responses in bioprocesses. Springer, Berlin Heidelberg, Berlin, Heidelberg, pp. 197–223CrossRefGoogle Scholar
  12. Hoffmann F, Rinas U (2004) Stress induced by recombinant protein production in Escherichia coli. In: Physiological stress responses in bioprocesses. Springer Berlin Heidelberg, Berlin, Heidelberg, 73–92Google Scholar
  13. Ignatova Z, Gierasch LM (2004) Monitoring protein stability and aggregation in vivo by real-time fluorescent labeling. Proc Natl Acad Sci 101:523–528. doi: 10.1073/pnas.0304533101 CrossRefPubMedPubMedCentralGoogle Scholar
  14. Jones JJ, Bridges AM, Fosberry AP, Gardner S, Lowers RR, Newby RR, James PJ, Hall RM, Jenkins O (2004) Potential of real-time measurement of GFP-fusion proteins. J Biotechnol 109:201–211. doi: 10.1016/j.jbiotec.2003.10.039 CrossRefPubMedGoogle Scholar
  15. Kensy F, Zang E, Faulhammer C, Tan R-K, Büchs J (2009) Validation of a high-throughput fermentation system based on online monitoring of biomass and fluorescence in continuously shaken microtiter plates. Microb Cell Factories 8:31. doi: 10.1186/1475-2859-8-31 CrossRefGoogle Scholar
  16. Kraft M, Knüpfer U, Wenderoth R, Pietschmann P, Hock B, Horn U (2007) An online monitoring system based on a synthetic sigma32-dependent tandem promoter for visualization of insoluble proteins in the cytoplasm of Escherichia coli. Appl Microbiol Biotechnol 75:397–406. doi: 10.1007/s00253-006-0815-6 CrossRefPubMedGoogle Scholar
  17. Kubitschek HE, Friske JA (1986) Determination of bacterial cell volume with the Coulter Counter. J Bacteriol 168:1466–1467PubMedPubMedCentralGoogle Scholar
  18. Kyle S, James KAR, McPherson MJ (2012) Recombinant production of the therapeutic peptide lunasin. Microb Cell Factories 11:28. doi: 10.1186/1475-2859-11-28 CrossRefGoogle Scholar
  19. Laubacher ME, Melquist AL, Chandramohan L, Young KD (2013) Cell sorting enriches Escherichia coli mutants that rely on peptidoglycan endopeptidases to suppress highly aberrant morphologies. J Bacteriol 195:855–866. doi: 10.1128/JB.01450-12 CrossRefPubMedPubMedCentralGoogle Scholar
  20. Lewis G, Taylor IW, Nienow AW, Hewitt CJ (2004) The application of multi-parameter flow cytometry to the study of recombinant Escherichia coli batch fermentation processes. J Ind Microbiol Biotechnol 31:311–322. doi: 10.1007/s10295-004-0151-8 CrossRefPubMedGoogle Scholar
  21. Li Z, Kessler W, van den Heuvel J, Rinas U (2011) Simple defined autoinduction medium for high-level recombinant protein production using T7-based Escherichia coli expression systems. Appl Microbiol Biotechnol 91:1203–1213. doi: 10.1007/s00253-011-3407-z CrossRefPubMedGoogle Scholar
  22. Margreiter G, Messner P, Caldwell KD, Bayer K (2008) Size characterization of inclusion bodies by sedimentation field-flow fractionation. J Biotechnol 138:67–73. doi: 10.1016/j.jbiotec.2008.07.1995 CrossRefPubMedPubMedCentralGoogle Scholar
  23. Massad-Ivanir N, Mirsky Y, Nahor A, Edrei E, Bonanno-Young LM, Ben Dov N, Sa’ar A, Segal E (2014) Trap and track: designing self-reporting porous Si photonic crystals for rapid bacteria detection. Analyst 139:3885. doi: 10.1039/C4AN00364K CrossRefPubMedGoogle Scholar
  24. Medwid R, Krebs L, Welch S (2007) Evaluation of Escherichia coli cell disruption and inclusion body release using nucleic acid binding fluorochromes and flow cytometry. Biotechniques 43:777–782. doi: 10.2144/000112621 CrossRefPubMedGoogle Scholar
  25. Mirsky Y, Nahor A, Edrei E, Massad-Ivanir N, Bonanno LM, Segal E, Sa’ar A (2013) Optical biosensing of bacteria and cells using porous silicon based, photonic lamellar gratings. Appl Phys Lett 103:033702. doi: 10.1063/1.4813740 CrossRefGoogle Scholar
  26. Nadungodage CH, Xia Y, Li F, Lee JJ, Ge J (2011) StreamFitter: a real time linear regression analysis system for continuous data streams. In: Yu JX, Kim MH, Unland R (eds) Database Systems for advanced applications. Springer, Berlin Heidelberg, Berlin, Heidelberg, pp. 458–461CrossRefGoogle Scholar
  27. Nelson DE, Young KD (2000) Penicillin binding protein 5 affects cell diameter, contour, and morphology of Escherichia coli. J Bacteriol 182:1714–1721. doi: 10.1128/JB.182.6.1714-1721.2000 CrossRefPubMedPubMedCentralGoogle Scholar
  28. Nemecek S, Marisch K, Juric R, Bayer K (2008) Design of transcriptional fusions of stress sensitive promoters and GFP to monitor the overburden of Escherichia coli hosts during recombinant protein production. Bioprocess Biosyst Eng 31:47–53. doi: 10.1007/s00449-007-0143-y CrossRefPubMedGoogle Scholar
  29. Neumeyer A, Hübschmann T, Müller S, Frunzke J (2013) Monitoring of population dynamics of Corynebacterium glutamicum by multiparameter flow cytometry: population dynamics of Corynebacterium glutamicum. Microb Biotechnol 6:157–167. doi: 10.1111/1751-7915.12018 CrossRefPubMedPubMedCentralGoogle Scholar
  30. Patkar A, Vijayasankaran N, Urry DW, Srienc F (2002) Flow cytometry as a useful tool for process development: rapid evaluation of expression systems. J Biotechnol 93:217–229CrossRefPubMedGoogle Scholar
  31. Rolinson GN (1980) Effect of beta-lactam antibiotics on bacterial cell growth rate. J Gen Microbiol 120:317–323PubMedGoogle Scholar
  32. Schmidt-Hager J, Ude C, Findeis M, John GT, Scheper T, Beutel S (2014) Non-invasive online biomass detector system for cultivation in shake flasks. Eng Life Sci. doi: 10.1002/elsc.201400026 Google Scholar
  33. Sun S, Liu M, Dong F, Fan S, Yao Y (2013) A histone-like protein induces plasmid DNA to form liquid crystals in vitro and gene compaction in vivo. Int J Mol Sci 14:23842–23857. doi: 10.3390/ijms141223842 CrossRefPubMedPubMedCentralGoogle Scholar
  34. Tomala M, Lavrentieva A, Moretti P, Rinas U, Kasper C, Stahl F, Schambach A, Warlich E, Martin U, Cantz T, Scheper T (2010) Preparation of bioactive soluble human leukemia inhibitory factor from recombinant Escherichia coli using thioredoxin as fusion partner. Protein Expr Purif 73:51–57. doi: 10.1016/j.pep.2010.04.002 CrossRefPubMedGoogle Scholar
  35. Ude C, Schmidt-Hager J, Findeis M, John GT, Scheper T, Beutel S (2014) Application of an online-biomass sensor in an optical multisensory platform prototype for growth monitoring of biotechnical relevant microorganism and cell lines in single-use shake flasks. Sensors 14:17390–17405. doi: 10.3390/s140917390 CrossRefPubMedPubMedCentralGoogle Scholar
  36. Upadhyay P, Patra A, Mukhopadhyay R, Panda A (2001) Real time detection and quantification of inclusion bodies expressed in Escherichia coli by impedance measurements. Biotechnol Lett 23:839–843. doi: 10.1023/A:1010550015147 CrossRefGoogle Scholar
  37. Wållberg F, Sundström H, Ledung E, Hewitt CJ, Enfors S-O (2005) Monitoring and quantification of inclusion body formation in Escherichia coli by multi-parameter flow cytometry. Biotechnol Lett 27:919–926. doi: 10.1007/s10529-005-7184-6 CrossRefPubMedGoogle Scholar
  38. Wittrup KD, Mann MB, Fenton DM, Tsai LB, Bailey JE (1988) Single-cell light scatter as a probe of refractile body formation in recombinant Escherichia coli. Nat Biotechnol 6:423–426. doi: 10.1038/nbt0488-423 CrossRefGoogle Scholar
  39. Wu Y, Benson JD, Almasri M (2012) Micromachined Coulter counter for dynamic impedance study of time sensitive cells. Biomed Microdevices 14:739–750. doi: 10.1007/s10544-012-9655-6 CrossRefPubMedGoogle Scholar
  40. Yablonovitch E (1987) Inhibited spontaneous emission in solid-state physics and electronics. Phys Rev Lett 58:2059–2062. doi: 10.1103/PhysRevLett.58.2059 CrossRefPubMedGoogle Scholar
  41. Zengin H, Baysal A (2014) Antibacterial and antioxidant activity of essential oil terpenes against pathogenic and spoilage-forming bacteria and cell structure-activity relationships evaluated by SEM microscopy. Molecules 19:17773–17798. doi: 10.3390/molecules191117773 CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Christian Ude
    • 1
  • Nadav Ben-Dov
    • 2
  • André Jochums
    • 1
  • Zhaopeng Li
    • 1
  • Ester Segal
    • 2
  • Thomas Scheper
    • 1
  • Sascha Beutel
    • 1
  1. 1.Institut für Technische ChemieGottfried Wilhelm Leibniz Universität HannoverHannoverGermany
  2. 2.Department of Biotechnology and Food EngineeringTechnion—Israel Institute of TechnologyHaifaIsrael

Personalised recommendations