Abstract
Rapidly changing concentrations of substrates frequently occur during large-scale microbial cultivations. These changing conditions, caused by large mixing times, result in a heterogeneous population distribution. Here, we present a powerful and efficient modeling approach to predict the influence of varying substrate levels on the transcriptional and translational response of the cell. This approach consists of two parts, a single-cell model to describe transcription and translation for an exemplary operon (trp operon) and a second part to characterize cell distribution during the experimental setup. Combination of both models enables prediction of transcriptional patterns for the whole population. In summary, the resulting model is not only able to anticipate the experimentally observed short-term and long-term transcriptional response, it further allows envision of altered protein levels. Our model shows that locally induced stress responses propagate throughout the bioreactor, resulting in temporal, and spatial population heterogeneity. Stress induced transcriptional response leads to a new population steady-state shortly after imposing fluctuating substrate conditions. In contrast, the protein levels take more than 10 h to achieve steady-state conditions.
Highlights
Large-scale industrial bioprocesses make use of reactors ranging from 100 to 800 m3 reaction volume
The following key assumptions were made: (i) Once transcription of mRNA has started, it continued until the stop signal was achieved at the end of the operon, namely on the relative position 6726 nt after trpEDCBA (Stoltzfus et al, 1988), (ii) mRNA was assumed to be immediately translated into proteins
We used the trp operon as an example because its polycistronic mRNA consisting of five structural genes and a leader peptide was repeatedly transcribed envisaging ammonia limitation (Simen et al, 2017) and, most importantly, its induction was followed by attenuation which directly linked transcription and translation of the gene products
Summary
Large-scale industrial bioprocesses make use of reactors ranging from 100 to 800 m3 reaction volume. For aerobic processes, stirred tank reactors are still preferred, albeit alternative setups such as airlift reactors may be attractive if reactor sizes exceed the volume of about 500 m3. All reactors have in common that gradients of substrates, dissolved gases and pH occur, which are the consequence of poor mixing conditions (Nienow et al, 1997). Cells are circulating in these reactors, thereby frequently passing through zones of different substrate availability. Cellular interactions are repeatedly triggered (Oldiges and Takors, 2005; Lara et al, 2006; Neubauer and Junne, 2010; Takors, 2012). Related regulatory responses are not limited to changes of metabolism and comprise transcriptional and translational programs (Löffler et al, 2016, 2017; Simen et al, 2017)
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