PhD study trip

Physiological state of (model) spoilage organisms during cell damage and repair

Bacteria are present everywhere and are adapted for survival under a wide range of conditions. All bacteria have a range of optimal conditions for their growth and division. If conditions are out of this optimal range, bacterial metabolism gets burdened and the cells go into a so-called stressed state.

The final state of the bacterial population under stress depends on many factors such as availability of nutrients, intensity of stress, adaptation time, and frequency of stress. The balance of the abiotic components of the environment such as temperature, availability of nutrients, osmotic pressure, moisture, pH and availability of oxygen, heavy metals and pressure is essential for optimal microbial growth. However, the presence of these factors in non-optimal range puts the bacterial cells under stress.


The main aim of this project is to provide a better understanding of the mechanisms involved in cell death and recovery.


One of the main objectives of our research is to define a descriptive model system to assess the damage and survival of the cells both at the population level and single-cell level. This model can be easily applied to develop milder methods of processing in food industries. We have established the shock regime to the cells and methods to monitor shock response. Our main research methodology is to expose cells to optimal, non-lethal, sub-lethal and lethal environmental conditions and then study their physiological state through Live/Dead assays and lag in growth period. Techniques such as flow cytometery and real-time fluorescence microscopy would be used. The descriptive model of a population level shock response would then be extended to single-cell level studies. Transcriptomics studies using microarray technology and qPCR would be used to select biomarkers for cell viability.


Using the findings of this research we would be able to identify the reasons underlying cell death in stressed conditions. This information would be used to develop a descriptive model of cell damage and recovery under stressed conditions. We hope to apply this model in development of milder preservations strategies for use in food industries.