Optimization of a Fermentation Process: It’s Just Good Bookkeeping
Professor Sef Heijnen doesn’t like being called “professor,” but when speaking with someone as venerated in the field of fermentation as he is, it’s hard to avoid the formality. Sef is internationally renowned for his expertise in industrial biotechnology, drawing on 15 years of experience working in the fermentation industry and his time as a professor heading up the Cell Systems Engineering group at TU Delft in the Netherlands. He is an award-winning lecturer teaching courses on industrial biotechnology to students around the world, and also advises some of the biggest companies in industrial biotech like DSM, Genomatica, and Amyris.
When asked what he thought was the most important aspect of process development work, Sef replied that it was, simply, “good bookkeeping.” He lamented the fact that most of the data generated during fermentation process development is lost “in the graveyard,” and implored fermentation scientists to do a better job of tracking inputs and outputs from bioreactor runs. “If only we could make conducting mass balance and carbon balance standard in the industry,” he explained, “we’d be helping so much.” Encouragingly, he was quick to add that “none of this is rocket science, it’s just a matter of record keeping and some straightforward calculations.”
Optimizing a production process without understanding mass balance is like trying to improve company profits without an understanding of revenue or costs. The discipline of maintaining and analyzing balance data, Sef noted, is “the bare-minimum” required to truly appreciate what is going on inside of a bioreactor. If a process doesn’t proceed as expected, the first step of diagnosing the problem should be an assessment of all the materials involved in the fermentation and tracking what happened to them.
Worse than not knowing what went wrong with a fermentation is not even knowing that something did go wrong. By not always conducting a mass balance, Sef warned, you might be getting artificially high titers. “Concentration of your product is the wrong quantity to be measuring at the end of a run,” he explained, noting that titer could be high due to evaporation. Instead, he encourages students and fermentation scientists alike to “always look at the total amounts in the vessel.” To make these diagnostic calculations easier, Sef recommends keeping records of substrates, feeds, and gasses in mass rather than just in volume.
From this baseline assessment of grams of feedstock vs. grams of products and wastes, one can dive progressively deeper to identify opportunities for improving a process. The basic principle in these additional analyses, however, is the same: good bookkeeping. How much carbon that went into the fermentation remained in the broth elements you measured and how much left the bioreactor as CO2? Is anything missing? This is why, says Sef, “I always tell people they need to be looking at off-gas, to enable this holistic view.”
Some of this might sound more challenging than it is, Sef acknowledged, due to potential discrepancies between measurements or difficulties weighing certain elements. “But,” Sef was quick to add, “you can have 5-6 linear equations to do data reconciliation, all of which are known and were published a long time ago.”1-3 The issue is just about implementation, but the tools are all readily available: “there is software for this, or you can even do it in Excel.”
For our part, Culture’s cloud-based bioreactor platform has been developed from the outset with the importance of mass-based measurements in mind. Each reactor at Culture is equipped with hardware to accurately measure every input and output for every fermentation process. Custom control software enables all inputs to the reactors to be delivered accurately and all manual additions or removals to be tracked. Together, these features allow mass balances to be calculated across a range of organisms and fermentation processes, giving customers high quality mass-based data measurements. These comprehensive datasets can then be used to calculate metrics that reflect the true performance of a microbe within a fermentation.
To learn how Culture’s system automatically tracks all bioreactor inputs and outputs to ensure high-quality fermentation data with closed mass balances, download our white paper.
1. Van der Heijden, R.T.J.M., Heijnen, J.J., Hellinga, C., Romein, B., Luyben, K.Ch.A.M. (1994a). Linear constraint relations in biochemical reaction systems: I. Classification of the calculability and the balanceability of conversion rates. Biotechnol. Bioeng. 43, 3–10.
2. Van der Heijden, R.T.J.M., Romein, B., Heijnen, J.J., Hellinga, C., Luyben, K.Ch.A.M. (1994b). Linear constraint relations in biochemical reaction systems: II. Diagnosis and estimation of gross errors. Biotechnol. Bioeng. 43, 11–20.
3. Van der Heijden, R.T.J.M., Heijnen, J.J., Hellinga, C., Romein, B., Luyben, K.Ch.A.M. (1994c). Linear constraint relations in biochemical reaction systems: III. Sequential application of data reconciliation for sensitive detection of systematic errors. Biotechnol. Bioeng. 43, 781–791.