MEMO: A Method for Computing Metabolic Modules for Cell-Free Production Systems

Cell-free bioproduction
systems represent a promising alternative
to classical microbial fermentation processes to synthesize value-added
products from biological feedstocks. An essential step for establishing
cell-free production systems is the identification of suitable metabolic
modules with defined properties. Here we present MEMO, a novel computational
approach to find smallest metabolic modules with specified stoichiometric
and thermodynamic constraints supporting the design of cell-free systems
in various regards. In particular, one key challenge for a sustained
operation of cell-free systems is the regeneration of utilized cofactors
(such as ATP and NAD­(P)­H). Given a production pathway with certain
cofactor requirements, MEMO can be used to compute smallest regeneration
modules that recover these cofactors with required stoichiometries.
MEMO incorporates the stoichiometric and thermodynamic constraints
in a single mixed-integer linear program, which can then be solved
to find smallest suitable modules from a given reaction database.
We illustrate the applicability of MEMO by calculating regeneration
modules for the recently published synthetic CETCH cycle for in vitro
carbon dioxide fixation. We demonstrate that MEMO is very flexible
in taking into account the diverse constraints of the CETCH cycle
(e.g., regeneration of 1 ATP, 4 NADPH and of 1 acetyl-group
without net production of CO2 and with permitted side production
of malate) and is able to determine multiple solutions in reasonable
time in two large reaction databases (MetaCyc and BiGG). The most
promising regeneration modules found utilize glycerol as substrate
and require only 8 enzymatic steps. It is also shown that some of
these modules are robust against spontaneous loss of cofactors (e.g., oxidation of NAD­(P)H or hydrolysis of ATP). Furthermore,
we demonstrate that MEMO can also find cell-free production systems
with integrated product synthesis and cofactor regeneration. Overall,
MEMO provides a powerful method for finding metabolic modules and
for designing cell-free production systems as one particular application.