Multi-scale modeling for sustainable chemical production

Process modelling and life cycle assessment coupled with experimental work to shape the future sustainable production of chemicals and fuels

Meeting the sustainable development goals and carbon neutrality targets requires transitioning to cleaner products, which poses significant challenges to the future chemical industry. Identifying alternative pathways to cover the growing demand for chemicals and fuels in a more sustainable manner calls for close collaborative programs between experimental and computational groups as well as new tools to support these joint endeavours. In this broad context, we here review the role of process systems engineering tools in assessing and optimising alternative chemical production patterns based on renewable resources, including renewable carbon and energy. The focus is on the use of process modelling and optimisation combined with life cycle assessment methodologies and network analysis to underpin experiments and generate insight into how the chemical industry could optimally deliver chemicals and fuels with a lower environmental footprint. We identify the main gaps in the literature and provide directions for future work, highlighting the role of PSE concepts and tools in guiding the future transition and complementing experimental studies more effectively.

Toward Sustainable Chemical Engineering: The Role of Process Systems Engineering

Products from chemical engineering are essential for human well-being, but they also contribute to the degradation of ecosystem goods and services that are essential for sustaining all human activities. To contribute to sustainability, chemical engineering needs to address this paradox by developing chemical products and processes that meet the needs of present and future generations. Unintended harm of chemical engineering has usually appeared outside the discipline's traditional system boundary due to shifting of impacts across space, time, flows, or disciplines, and exceeding nature's capacity to supply goods and services. Being a subdiscipline of chemical engineering, process systems engineering (PSE) is best suited for ensuring that chemical engineering makes net positive contributions to sustainable development. This article reviews the role of PSE in the quest toward a sustainable chemical engineering. It focuses on advances in metrics, process design, product design, and process dynamics and control toward sustainability. Efforts toward contributing to this quest have already expanded the boundary of PSE to consider economic, environmental, and societal aspects of processes, products, and their life cycles. Future efforts need to account for the role of ecosystems in supporting industrial activities, and the effects of human behavior and markets on the environmental impacts of chemical products. Close interaction is needed between the reductionism of chemical engineering science and the holism of process systems engineering, along with a shift in the engineering paradigm from wanting to dominate nature to learning from it and respecting its limits.

Computational Methods to Assess the Production Potential of Bio-Based Chemicals

Elevated costs and long implementation times of bio-based processes for producing chemicals represent a bottleneck for moving to a bio-based economy. A prospective analysis able to elucidate economically and technically feasible product targets at early research phases is mandatory. Computational tools can be implemented to explore the biological and technical spectrum of feasibility, while constraining the operational space for desired chemicals. In this chapter, two different computational tools for assessing potential for bio-based production of chemicals from different perspectives are described in detail. The first tool is GEM-Path: an algorithm to compute all structurally possible pathways from one target molecule to the host metabolome. The second tool is a framework for Modeling Sustainable Industrial Chemicals production (MuSIC), which integrates modeling approaches for cellular metabolism, bioreactor design, upstream/downstream processes, and economic impact assessment. Integrating GEM-Path and MuSIC will play a vital role in supporting early phases of research efforts and guide the policy makers with decisions, as we progress toward planning a sustainable chemical industry.

A multi-scale, multi-disciplinary approach for assessing the technological, economic and environmental performance of bio-based chemicals

In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry.

Mapping the patent landscape of synthetic biology for fine chemical production pathways

A goal of synthetic biology bio‐foundries is to innovate through an iterative design/build/test/learn pipeline. In assessing the value of new chemical production routes, the intellectual property (IP) novelty of the pathway is important. Exploratory studies can be carried using knowledge of the patent/IP landscape for synthetic biology and metabolic engineering. In this paper, we perform an assessment of pathways as potential targets for chemical production across the full catalogue of reachable chemicals in the extended metabolic space of chassis organisms, as computed by the retrosynthesis‐based algorithm RetroPath. Our database for reactions processed by sequences in heterologous pathways was screened against the PatSeq database, a comprehensive collection of more than 150M sequences present in patent grants and applications. We also examine related patent families using Derwent Innovations. This large‐scale computational study provides useful insights into the IP landscape of synthetic biology for fine and specialty chemicals production.

Multi-scale exploration of the technical, economic, and environmental dimensions of bio-based chemical production

In recent years, bio-based chemicals have gained traction as a sustainable alternative to petrochemicals. However, despite rapid advances in metabolic engineering and synthetic biology, there remain significant economic and environmental challenges. In order to maximize the impact of research investment in a new bio-based chemical industry, there is a need for assessing the technological, economic, and environmental potentials of combinations of biomass feedstocks, biochemical products, bioprocess technologies, and metabolic engineering approaches in the early phase of development of cell factories. To address this issue, we have developed a comprehensive Multi-scale framework for modeling Sustainable Industrial Chemicals production (MuSIC), which integrates modeling approaches for cellular metabolism, bioreactor design, upstream/downstream processes and economic impact assessment. We demonstrate the use of the MuSIC framework in a case study where two major polymer precursors (1,3-propanediol and 3-hydroxypropionic acid) are produced from two biomass feedstocks (corn-based glucose and soy-based glycerol) through 66 proposed biosynthetic pathways in two host organisms (Escherichia coli and Saccharomyces cerevisiae). The MuSIC framework allows exploration of tradeoffs and interactions between economy-scale objectives (e.g. profit maximization, emission minimization), constraints (e.g. land-use constraints) and process- and cell-scale technology choices (e.g. strain design or oxygenation conditions). We demonstrate that economy-scale assessment can be used to guide specific strain design decisions in metabolic engineering, and that these design decisions can be affected by non-intuitive dependencies across multiple scales.

Genome-scale modeling for metabolic engineering

We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

Design of homo-organic acid producing strains using multi-objective optimization

Production of homo-organic acids without byproducts is an important challenge in bioprocess engineering to minimize operation cost for separation processes. In this study, we used multi-objective optimization to design Escherichia coli strains with the goals of maximally producing target organic acids, while maintaining sufficiently high growth rate and minimizing the secretion of undesired byproducts. Homo-productions of acetic, lactic and succinic acids were targeted as examples. Engineered E. coli strains capable of producing homo-acetic and homo-lactic acids could be developed by taking this systems approach for the minimal identification of gene knockout targets. Also, failure to predict effective gene knockout targets for the homo-succinic acid production suggests that the multi-objective optimization is useful in assessing the suitability of a microorganism as a host strain for the production of a homo-organic acid. The systems metabolic engineering-based approach reported here should be applicable to the production of other industrially important organic acids.

Editorial: metabolic modeling in biotechnology and medical research

Metabolic Modeling and Simulation: This special issue of Biotechnology Journal is edited by Diethard Mattanovich and Vassily Hatzimanikatis and covers the state-of-the-art in metabolic modeling, including the major themes of methods in metabolic modeling, modeling of human and microbial metabolism, and modeling of bioprocesses.