BIOBASED CHEMICALS to manipulate the metabolism and the process over and over again at various scales to maximise the production of a single target molecule , DMC started with the end in mind by creating a standard industrial fermentation process , then a standardised and modular metabolic engineering approach and toolkit . The engineering of biology is a difficult challenge . Most approaches to overcoming this challenge today rely on massive experimentation , coupled with machine learning in a high-throughput trial-and-error model . DMC ’ s approach is to simplify the challenge . The first step is to decouple growth from production , creating two optimal states in time ( i . e . growth then production ). The switch to the non-growing and highly active production stage includes the preprogrammed and dynamic reduction of the native metabolism , so that only those network elements required for production remain . As an example of reducing complexity , consider the relatively simple microbe E . coli , which has around 4,000 genes . This results in a potential design space that exceeds 10 25 . In contrast , the DMC approach reduces that design space to around 50 , which can be statistically explored in a matter of weeks . Reducing the potential network in the context of a non-growing system also constrains the ability of the microbe to respond to the process environment , providing robustness . Robustness , in turn , provides predictability when scaling from highthroughput to commercial scale .
Standardised stages
The artisanal nature of historical fermentation approaches has resulted in the creation of an entire discipline of fermentation process engineers whose customary role is to conduct cycles of single- and multi-variable optimisations ( usually employing a Design of Experiments ( DOE ) statistical approach ) for every new strain that is created or scaled up .
The scale-up process of DMC ’ s L-alanine was conducted at EW Biotech ’ s facility in Leuna , Germany
The cost of the equipment , personnel and raw material resources required to routinely conduct these workflows is astronomical - often reaching tens or hundreds of millions of dollars per product to get to full commercial scale . Reducing the metabolic network alone , however , is not sufficient . DMC ’ s approach is to create a standardised , two-stage fermentation process that is independent of the product formed . This requires a single round of process optimisation at lab scale for each product - typically to tailor the feed rate of the fed-batch process to match the production rate for any given product . The primary aim of feed rate optimisation is to ensure that no feedstock remains at the end of the fermentation process that would have to subsequently be removed in the purification process . Eliminating the endless cycles of process optimisation dramatically accelerates development timelines and reduces costs .
Dynamic Metabolic Control
The patented Dynamic Metabolic Control ( DMC ) technology makes it possible to create two sequential optimal states : optimal growth of the biocatalyst followed by using it to produce the desired product at target metrics . An analogy is a network of interconnected pipes with valves that can be shut down dynamically , based on a signal . The open valves allow a high flux of carbon , energy and cofactors needed to grow the microorganism . Then , through an environmental signal , such as the depletion of a nutrient , the valves associated with growth are closed , effectively silencing specific pathways , while other valves associated with production are opened . Importantly , the technology is non-binary , meaning that valves can also be partially open or closed , depending on the specific pathway need . By such directed engineering of the biocatalyst , the desired production path is created to convert feedstock to product at target performance metrics , such as rate , titer and yield . The technology results in robust bioprocesses that are predictable across scale , from 200 microlitre microtiter plates to 85,000 litre fermentation tanks and larger . Standardisation and robustness eliminate endless cycles of process optimisation for every new strain and every new scale . Eliminating those process optimisation cycles dramatically reduces the cost and timeline for development and scale-up . ‣
Photo credit : EW Biotech
61