the more biologically grounded Monod growth
Why is the Monod model more biologically grounded? It is empiric and NOT based on biological considerations! I only know this equation from enzyme kinetics, not for cell-growth, where the identical Michaelis–Menten equation assumes a random collusion model. So according to this model, your cells would grow more, the more substrate (glucose?) collides against the walls!
It seems quite logical to model enzyme-kinetics or chemical reactions with random collusion models. However, the only relevant biological facts I see are the following:
- Cells divide, which naturally suggest exponential growth.
- Cell-cycles and circadian cycles exist, which naturally suggests a
constant generation time. (within the limits that everyone knows)
So, if everyone learns about growth curves and logistic fits in their wet-lab courses, where logistic fits work perfectly fine to predict growth within the log-phase, then why would there be a need to use other - more complicated - models, while the logistic model is conceptually indicated? (Also note that the Monod model still fails to predict the lag phase and death phase.)
This leads to the final answer to the question:
Is there something holding the synthetic biology community back from
regularly reporting growth characteristics of their cells?
- In daily routine, the typical wet-lab scientist is merely
interested in knowing the expected time until a certain optical
density (OD) of the cell-culture is reached. Practically, this is
done with as few measurements as possible, based on experience and a guess of a generic generation-time.
- Exact predictions are needed in large-scale biotechnological
production. In such a context all parameters must be accurately predicted and validated. Given your exact microorganisms and your production plan, small-batch trails will be performed and up-scaled. Everything must be known and planned in detail and quite often, the whole production facility is designed and built to achieve a single task! Everything, including the generated heat, O2, CO2, Glucose, (end-) concentration of the yield.. is monitored and legally binding deviation-limits must be set before-hand and met at all times. Small deviations can cause losses of millions of dollars and companies don't rely on simple models like "Monod", but stress-test every aspect and monitor and react in automated systems. There is vast knowledge regarding growth-curves and models, just you are not aware of it, as it is kept company-internal, or written in expensive bioprocess-technology books.