Thermal Death Kinetics of Agrobacterium tumefaciens in a Complex Substrate

Can Daily Heat Cycles Make Bacteria Stronger?

We use heat to kill microbes all the time. From pasteurizing milk to sterilizing surgical tools, it’s our most reliable method for decontamination. But those processes use constant, high temperatures. What happens in the real world, like in soil during a hot summer, where temperatures rise and fall in a daily cycle? Can soil solarization control a microbial population, or does evolution win out?

This was the central question of my first research project as an undergraduate in the lab of the late Dr. Walt Ream. Working in close collaboration with Dr. Jennifer Parke we aimed to simulate the effects of soil solarization, a process where the sun bakes the ground, with peak temperatures reaching a scorching 49-52°C. The answer we found was far more surprising than I expected.

The Target: Phytopathogenic Agrobacterium tumefaciens

Our “bad actor” for this experiment was Agrobacterium tumefaciens, a bacterium famous in the plant world for causing crown gall disease. The goal was simple: could we determine the temperature profile needed to selectively remove it from a soil environment using a realistic heat cycle?

To do this, we first had to understand its precise weakness to heat. This is where thermal death kinetics comes in.

The How: Building a Predictive Model

Before we could simulate diurnal heat cycles, we had to build a model of the organism’s heat tolerance in ‘simulated soil’ (sterilized sand). This is the same fundamental process used to design commercial pasteurization systems, and it relies on two key parameters: the D-value and the Z-value.

First, we determined the decimal reduction rate (D-value). The D-value is the time (in minutes) required to kill 90% of a microbial population at a constant temperature. To find it, we exposed our bacteria to a specific temperature and pulled samples over time. By plotting the logarithm of surviving cells against time, you get a straight line. The negative reciprocal of that line’s slope is the D-value. It’s a direct measure of an organism’s heat resistance. We meticulously repeated this process at several different temperatures to see how the D-value changed.

Next, we calculated the Z-value. Once you have several D-values at different temperatures, you can plot the logarithm of your D-values against temperature. This also yields a straight line, and its negative reciprocal is the Z-value. The Z-value tells you the temperature change needed to cause a 10-fold change in the D-value. It’s a measure of how much a microbe’s heat resistance changes as things get hotter.

With these two parameters, we had a complete thermal profile. This is the foundation for calculating Thermal Lethality (F-value or PUs) of processes, and building predictive models for systems like tunnel pasteurizers. We could now, in theory, predict the cumulative lethal effect of any temperature-time profile.

It was time to put our model to the test. We added A. tumefaciens to ‘simulated soil’ and placed them in an incubator programmed to mimic the diurnal, high-heat cycle of soil solarization.

The Result: A Surprising Twist

Our initial results were a huge success. We sampled the sand over the first 24-hours and the number of surviving bacteria was almost exactly what our model predicted. We had successfully accounted for the cumulative killing effect of the fluctuating temperatures.

But then, something unexpected happened.

The second cycle killed fewer bacteria than the first. The third cycle had an even smaller effect. After four or five days, despite a daily heat treatment that should have been lethal, the population stabilized. It was as if the survivors had learned to weather the storm.

The Lesson: What Doesn’t Kill You…

This was my first real lesson in the resilience of microbial populations. A simple, static model can make a great prediction for a short time, but it often fails to account for adaptation. The initial heat shock likely acted as a selection event, killing the weakest cells and leaving behind a hardier, more heat-tolerant sub-population. These survivors may have activated heat shock proteins or other defense mechanisms that allowed them to endure subsequent cycles.

It was a classic “what doesn’t kill you makes you stronger” scenario, but for bacteria. That project taught me that microbial systems are dynamic and complex, and it laid the groundwork for my future work in building more sophisticated pasteurization models. It’s a lesson that has stuck with me ever since.