Three components of sustainability (environmental, economic and societal) of various bioprocesses become increasingly important. Neglecting the sustainability issues may cause adverse environmental and societal problems proportional to the production volumes. Governmental bodies are expected to pay more attention to environmental and societal parameters of industry in near future.
Sustainable metabolic engineering (SME) is defined by Stalidzans and Dace (2021) as optimization of metabolism where economic, environmental and societal sustainability parameters of all incoming and outgoing fluxes and produced biomass of the applied organisms are considered.
Constraint-based stoichiometric modelling framework can be adapted for the calculation of the integrated sustainability score (ISS) that consists of weighed economic (Econ), environmental (Env) and social (Soc) components. ISS= WeconEcon + WenvEnv + Wsoc*Soc.
The calculations are carried out introducing economic and environmental sustainability indicator vectors for all exchange metabolites that have to be multiplied by the metabolic flux vector of all exchange fluxes accounting for the contribution of each exchange metabolite. The economic indicator vector (Econ) contains prices of substrates, products and by-products. The environmental vector (Env) contains characteristics of environmental impact parameters of substrates, products, by-products and biomass. The value of the social component (Soc) is calculated for the whole design of the organism (does not depend directly on the values of exchange fluxes). Social component takes into account characteristics like health and safety risks, newly created working places (depend on the estimated financial turnover), social acceptance of genetic engineering methods and others.
Growth-coupled production approach where the production of the target metabolite is coupled with the production of biomass has been selected as an option to implement SME. In case of SME the biomass production is coupled with the ISS that can be introduced as an objective function. An important side-effect of growth-coupling is the reduction of exchange flux variability that reduces also the variability of ISS.
OptGene tool is adapted for the implementation of ISS and applied for deletion-based design development. Sustainable designs of E.coli and some other organisms are proposed and compared indicating advantages and disadvantages of designs for production of particular metabolites pointing at some patterns in sustainability analysis. We have observed that the environmental and societal sustainability components can be improved without harming the economic parameters of target metabolite production.
Currently SME can be used as a tool for preliminary selection of appropriate organisms and designs to study them in more detail. Further development of SME approach depends on the availability of suitable data for environmental assessment of metabolite production and consumption impact on the environment.