Applied Microbiology and Biotechnology

, Volume 71, Issue 6, pp 804–811 | Cite as

Effects of pH profiles on nisin production in biofilm reactor

  • Thunyarat Pongtharangkul
  • Ali DemirciEmail author
Biotechnological Products and Process Engineering


Apart from its widely accepted commercial applications as a food preservative, nisin emerges as a promising alternative in medical applications for bacterial infection in both humans and livestock. Improving nisin production through optimization of fermentation parameters would make nisin more cost-effective for various applications. Since nisin production by Lactococcus lactis NIZO 22186 was highly influenced by the pH profile employed during fermentation, three different pH profiles were evaluated in this study: (1) a constant pH profile at 6.8 (profile 1), (2) a constant pH profile with autoacidification at 4 h (profile 2), and (3) a stepwise pH profile with pH adjustment every 2 h (profile 3). The results demonstrated that the low-pH stress exerted during the first 4 h of fermentation in profile 3 detrimentally affected nisin production, resulting in a very low maximum nisin concentration (593 IU ml−1). On the other hand, growth and lactic acid production were only slightly delayed, indicating that the loss in nisin production was not a result of lower growth or shifting of metabolic activity toward lactic acid production. Profile 2, in which pH was allowed to drop freely via autoacidification after 4 h of fermentation, was found to yield almost 1.9 times higher nisin (3,553 IU ml−1) than profile 1 (1,898 IU ml−1), possibly as a result of less adsorption of nisin onto producer cells. Therefore, a combination of constant pH and autoacidification period (profile 2) was recommended as the pH profile during nisin production in a biofilm reactor.


Fermentation Lactic Acid Production Nisin Production Plastic Composite Support Nisin Concentration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors wish to thank Dr. Anthony L. Pometto III from Iowa State University for kindly supplying the PCS tubes used in this research. Funding for this project was provided by the Pennsylvania Agricultural Experiment Station and by a scholarship from the Royal Thai Government.


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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  1. 1.Department of Agricultural and Biological EngineeringThe Pennsylvania State University, University ParkPAUSA
  2. 2.The Huck Institutes for the Life SciencesThe Pennsylvania State University, University ParkPAUSA

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