Synthetic and systems biology for microbial production of commodity chemicals

Characterization of cotton stalk as a lignocellulosic feedstock for single-cell protein production

Cotton stalk, an important by-product of cotton farming, is challenging in lignocellulosic feedstock application due to the limited understanding of their compositional and lignin structural characteristics. This study elucidates the composition of lignocellulose components and fundamental lignin structural features of cotton stalk. Lignocellulosic hydrolysates were prepared from various cotton stalk parts and used for single-cell protein production. As a proof of concept, cotton stalk hydrolysates were successfully converted into single-cell protein using the superior microbial host, Candida utilis ACCC20060, owing to its favorable sugar consumption efficiency and high protein quality. The highest SCP concentration of 5.74 g/L was obtained, yielding 0.23 g/g from the lignocellulose-derived sugars released from cotton stalk roots. This study provides valuable references for cotton stalk utilization toward lignocellulosic feedstock application and introduces a promising microbial host for single-cell protein production from such feedstocks.

Enzymatic promiscuity and underground reactions accounted for the capability of Escherichia coli to use the non-natural chemical synthon 2,4-dihydroxybutyric acid as a carbon source for growth

2,4-dihydroxybutyric acid (DHB) and 2-keto-4-hydroxybutyrate (OHB) are non-natural molecules obtained through synthetic pathways from renewable carbon source. As they are structurally similar to lactate and pyruvate respectively, they could possibly interfere with the metabolic network of Escherichia coli. In fact, we showed that DHB can be easily oxidized by the membrane associated L and D-lactate dehydrogenases encoded by lldD, dld and ykgF into OHB, and the latter being cleaved into pyruvate and formaldehyde by several pyruvate-dependent aldolases, with YagE being the most effective. While formaldehyde was readily detoxified into formate, Escherichia coli K12 MG1655 strain failed to grow on DHB despite of the production of pyruvate. To find out the reason for this failure, we constructed a mutant strain whose growth was rendered dependent on DHB and subjected this strain to adaptive evolution. Genome sequencing of the adapted strain revealed an essential role for ygbI encoding a transcriptional repressor of the threonate operon in this DHB-dependent growth. This critical function was attributed to the derepression of ygbN encoding a putative threonate transporter, which was found to exclusively transport the D form of DHB. A subsequent laboratory evolution was carried out with E. coli K12 MG1655 deleted for ΔygbI to adapt for growth on DHB as sole carbon source. Remarkably, only two additional mutations were disclosed in the adapted strain, which were demonstrated by reverse engineering to be necessary and sufficient for robust growth on DHB. One mutation was in nanR encoding the transcription repressor of sialic acid metabolic genes, causing 140-fold increase in expression of nanA encoding N-acetyl neuraminic acid lyase, a pyruvate-dependent aldolase, and the other was in the promoter of dld leading to 14-fold increase in D-lactate dehydrogenase activity on DHB. Taken together, this work illustrates the importance of promiscuous enzymes in underground metabolism and moreover, in the frame of synthetic pathways aiming at producing non-natural products, these underground reactions could potentially penalize yield and title of these bio-based products.

Microbial Squalene: A Sustainable Alternative for the Cosmetics and Pharmaceutical Industry - A Review

Squalene is a natural triterpenoid and a biosynthetic precursor of steroids and hopanoids in microorganisms, plants, humans, and other animals. Squalene has exceptional properties, such as its antioxidant activity, a high penetrability of the skin, and the ability to trigger the immune system, promoting its application in the cosmetic, sustenance, and pharmaceutical industries. Because sharks are the primary source of squalene, there is a need to identify low-cost, environment friendly, and sustainable alternatives for producing squalene commercially. This shift has prompted scientists to apply biotechnological advances to research microorganisms for synthesizing squalene. This review summarizes recent metabolic and bioprocess engineering strategies in various microorganisms for the biotechnological production of this valuable molecule.

Data-driven learning of structure augments quantitative prediction of biological responses

Multi-factor screenings are commonly used in diverse applications in medicine and bioengineering, including optimizing combination drug treatments and microbiome engineering. Despite the advances in high-throughput technologies, large-scale experiments typically remain prohibitively expensive. Here we introduce a machine learning platform, structure-augmented regression (SAR), that exploits the intrinsic structure of each biological system to learn a high-accuracy model with minimal data requirement. Under different environmental perturbations, each biological system exhibits a unique, structured phenotypic response. This structure can be learned based on limited data and once learned, can constrain subsequent quantitative predictions. We demonstrate that SAR requires significantly fewer data comparing to other existing machine-learning methods to achieve a high prediction accuracy, first on simulated data, then on experimental data of various systems and input dimensions. We then show how a learned structure can guide effective design of new experiments. Our approach has implications for predictive control of biological systems and an integration of machine learning prediction and experimental design.

A comprehensive review on methane's dual role: effects in climate change and potential as a carbon-neutral energy source

The unprecedented population and anthropogenic activity rise have challenged the future look up for shifts in global temperature and climate patterns. Anthropogenic activities such as land fillings, building dams, wetlands converting to lands, combustion of biomass, deforestation, mining, and the gas and coal industries have directly or indirectly increased catastrophic methane (CH4) emissions at an alarming rate. Methane is 25 times more potent trapping heat when compared to carbon dioxide (CO2) in the atmosphere. A rise in atmospheric methane, on a 20-year time scale, has an impact of 80 times greater than that of CO2. With increased population growth, waste generation is rising and is predicted to reach 6 Mt by 2025. CH4 emitted from landfills is a significant source that accounts for 40% of overall global methane emissions. Various mitigation and emissions reduction strategies could significantly reduce the global CH4 burden at a cost comparable to the parallel and necessary CO2 reduction measures, reversing the CH4 burden to pathways that achieve the goals of the Paris Agreement. CH4 mitigation directly benefits climate change, has collateral impacts on the economy, human health, and agriculture, and considerably supports CO2 mitigation. Utilizing the CO2 from the environment, methanogens produce methane and lower their carbon footprint. NGOs and the general public should act on time to overcome atmospheric methane emissions by utilizing the raw source for producing carbon-neutral fuel. However, more research potential is required for green energy production and to consider investigating the untapped potential of methanogens for dependable energy generation.

Multienzymatic Cascades and Nanomaterial Scaffolding-A Potential Way Forward for the Efficient Biosynthesis of Novel Chemical Products

Synthetic biology is touted as the next industrial revolution as it promises access to greener biocatalytic syntheses to replace many industrial organic chemistries. Here, it is shown to what synthetic biology can offer in the form of multienzyme cascades for the synthesis of the most basic of new materials-chemicals, including especially designer chemical products and their analogs. Since achieving this is predicated on dramatically expanding the chemical space that enzymes access, such chemistry will probably be undertaken in cell-free or minimalist formats to overcome the inherent toxicity of non-natural substrates to living cells. Laying out relevant aspects that need to be considered in the design of multi-enzymatic cascades for these purposes is begun. Representative multienzymatic cascades are critically reviewed, which have been specifically developed for the synthesis of compounds that have either been made only by traditional organic synthesis along with those cascades utilized for novel compound syntheses. Lastly, an overview of strategies that look toward exploiting bio/nanomaterials for accessing channeling and other nanoscale materials phenomena in vitro to direct novel enzymatic biosynthesis and improve catalytic efficiency is provided. Finally, a perspective on what is needed for this field to develop in the short and long term is presented.

State-of the-Art Constraint-Based Modeling of Microbial Metabolism: From Basics to Context-Specific Models with a Focus on Methanotrophs

Methanotrophy is the ability of an organism to capture and utilize the greenhouse gas, methane, as a source of energy-rich carbon. Over the years, significant progress has been made in understanding of mechanisms for methane utilization, mostly in bacterial systems, including the key metabolic pathways, regulation and the impact of various factors (iron, copper, calcium, lanthanum, and tungsten) on cell growth and methane bioconversion. The implementation of -omics approaches provided vast amount of heterogeneous data that require the adaptation or development of computational tools for a system-wide interrogative analysis of methanotrophy. The genome-scale mathematical modeling of its metabolism has been envisioned as one of the most productive strategies for the integration of muti-scale data to better understand methane metabolism and enable its biotechnological implementation. Herein, we provide an overview of various computational strategies implemented for methanotrophic systems. We highlight functional capabilities as well as limitations of the most popular web resources for the reconstruction, modification and optimization of the genome-scale metabolic models for methane-utilizing bacteria.

Recent Challenges and Trends of Polyhydroxyalkanoate Production by Extremophilic Bacteria Using Renewable Feedstocks

Polyhydroxyalkanoates (PHAs) are biodegradable polymers with immense potential in addressing the global plastic pollution crisis and advancing sustainable bioplastics production. Among the various microbes known for PHA production, extremophilic bacteria possess unique capabilities to thrive under extreme conditions, making them attractive candidates for PHA synthesis. Furthermore, the utilization of renewable feedstocks for PHA production aligns with the growing demand for sustainable bioplastic alternatives. A diverse range of extremophilic bacteria, especially halophiles and thermophiles, has provided cost-competitive platforms for producing customized PHA polymers. Extremophilic bacteria offer unique advantages over mesophiles due to their contamination resistance, high cell density growth, and unique culture conditions. The current status of Halomonas spp. as a chassis further allows exploration of metabolic engineering approaches to overcome the challenges associated with current industrial biotechnology. This article especially focuses on extremophilic bacteria and explores recent advances in utilizing renewable feedstocks such as lignocellulosic biomass, agro-industrial residues, and waste streams for PHA production. The integration of biorefinery concepts and circular economy principles in PHA manufacturing is also examined. This review is an attempt to provide an understanding of renewable substrates as feedstocks and emerging trends in PHA production by extremophilic bacteria. It underscores the pivotal role of extremophiles and sustainable feedstock sources in advancing the feasibility and eco-friendliness of PHAs as a promising biopolymer alternative.

BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale

Metabolic fluxes, the number of metabolites traversing each biochemical reaction in a cell per unit time, are crucial for assessing and understanding cell function. 13C Metabolic Flux Analysis (13C MFA) is considered to be the gold standard for measuring metabolic fluxes. 13C MFA typically works by leveraging extracellular exchange fluxes as well as data from 13C labeling experiments to calculate the flux profile which best fit the data for a small, central carbon, metabolic model. However, the nonlinear nature of the 13C MFA fitting procedure means that several flux profiles fit the experimental data within the experimental error, and traditional optimization methods offer only a partial or skewed picture, especially in "non-gaussian" situations where multiple very distinct flux regions fit the data equally well. Here, we present a method for flux space sampling through Bayesian inference (BayFlux), that identifies the full distribution of fluxes compatible with experimental data for a comprehensive genome-scale model. This Bayesian approach allows us to accurately quantify uncertainty in calculated fluxes. We also find that, surprisingly, the genome-scale model of metabolism produces narrower flux distributions (reduced uncertainty) than the small core metabolic models traditionally used in 13C MFA. The different results for some reactions when using genome-scale models vs core metabolic models advise caution in assuming strong inferences from 13C MFA since the results may depend significantly on the completeness of the model used. Based on BayFlux, we developed and evaluated novel methods (P-13C MOMA and P-13C ROOM) to predict the biological results of a gene knockout, that improve on the traditional MOMA and ROOM methods by quantifying prediction uncertainty.

A cellular platform for production of C4 monomers

Living organisms carry out a wide range of remarkable functions, including the synthesis of thousands of simple and complex chemical structures for cellular growth and maintenance. The manipulation of this reaction network has allowed for the genetic engineering of cells for targeted chemical synthesis, but it remains challenging to alter the program underlying their fundamental chemical behavior. By taking advantage of the unique ability of living systems to use evolution to find solutions to complex problems, we have achieved yields of up to ∼95% for three C4 commodity chemicals, n-butanol, 1,3-butanediol, and 4-hydroxy-2-butanone. Genomic sequencing of the evolved strains identified pcnB and rpoBC as two gene loci that are able to alter carbon flow by remodeling the transcriptional landscape of the cell, highlighting the potential of synthetic pathways as a tool to identify metabolic control points.

Extreme Sensitivity of Fitness to Environmental Conditions: Lessons from #1BigBatch

The phrase "survival of the fittest" has become an iconic descriptor of how natural selection works. And yet, precisely measuring fitness, even for single-celled microbial populations growing in controlled laboratory conditions, remains a challenge. While numerous methods exist to perform these measurements, including recently developed methods utilizing DNA barcodes, all methods are limited in their precision to differentiate strains with small fitness differences. In this study, we rule out some major sources of imprecision, but still find that fitness measurements vary substantially from replicate to replicate. Our data suggest that very subtle and difficult to avoid environmental differences between replicates create systematic variation across fitness measurements. We conclude by discussing how fitness measurements should be interpreted given their extreme environment dependence. This work was inspired by the scientific community who followed us and gave us tips as we live tweeted a high-replicate fitness measurement experiment at #1BigBatch.

Assessment of horizontal gene transfer-mediated destabilization of Synechococcus elongatus PCC 7942 biocontainment system

Biological containment is a biosafety strategy that prevents the dispersal of genetically modified organisms in natural ecosystems. We previously established a biocontainment system that makes bacterial growth dependent on the availability of phosphite (Pt), an ecologically rare form of phosphorus (P), by introducing Pt metabolic pathway genes and disrupting endogenous phosphate and organic phosphate transporter genes. Although this system proved highly effective, horizontal gene transfer (HGT) mediated recovery of a P transporter gene is considered as a potential pathway to abolish the Pt-dependent growth, resulting in escape from the containment. Here, we assessed the risk of HGT driven escape using the Pt-dependent cyanobacterium Synechococcus elongatus PCC 7942. Transformation experiments revealed that the Pt-dependent strain could regain phosphate transporter genes from the S. elongatus PCC 7942 wild-type genome and from the genome of the closely related strain, S. elongatus UTEX 2973. Transformed S. elongatus PCC 7942 became viable in a phosphate-containing medium. Meanwhile, transformation of the Synechocystis sp. PCC 6803 genome or environmental DNA did not yield escape strains, suggesting that only genetic material derived from phylogenetically-close species confer high risk to generate escape. Eliminating a single gene necessary for natural competence from the Pt-dependent strain reduced the escape occurrence rate. These results demonstrate that natural competence could be a potential risk to destabilize Pt-dependence, and therefore inhibiting exogenous DNA uptake would be effective for enhancing the robustness of the gene disruption-dependent biocontainment.

Microbial Production of Human Milk Oligosaccharides

Human milk oligosaccharides (HMOs) are complex nonnutritive sugars present in human milk. These sugars possess prebiotic, immunomodulatory, and antagonistic properties towards pathogens and therefore are important for the health and well-being of newborn babies. Lower prevalence of breastfeeding around the globe, rising popularity of nutraceuticals, and low availability of HMOs have inspired efforts to develop economically feasible and efficient industrial-scale production platforms for HMOs. Recent progress in synthetic biology and metabolic engineering tools has enabled microbial systems to be a production system of HMOs. In this regard, the model organism Escherichia coli has emerged as the preferred production platform. Herein, we summarize the remarkable progress in the microbial production of HMOs and discuss the challenges and future opportunities in unraveling the scope of production of complex HMOs. We focus on the microbial production of five HMOs that have been approved for their commercialization.

High-throughput genetic engineering tools for regulating gene expression in a microbial cell factory

With the rapid advances in biotechnological tools and strategies, microbial cell factory-constructing strategies have been established for the production of value-added compounds. However, optimizing the tradeoff between the biomass, yield, and titer remains a challenge in microbial production. Gene regulation is necessary to optimize and control metabolic fluxes in microorganisms for high-production performance. Various high-throughput genetic engineering tools have been developed for achieving rational gene regulation and genetic perturbation, diversifying the cellular phenotype and enhancing bioproduction performance. In this paper, we review the current high-throughput genetic engineering tools for gene regulation. In particular, technological approaches used in a diverse range of genetic tools for constructing microbial cell factories are introduced, and representative applications of these tools are presented. Finally, the prospects for high-throughput genetic engineering tools for gene regulation are discussed.

Dynamic feedback regulation for efficient membrane protein production using a small RNA-based genetic circuit in Escherichia coli

BACKGROUND

Membrane proteins (MPs) are an important class of molecules with a wide array of cellular functions and are part of many metabolic pathways. Despite their great potential-as therapeutic drug targets or in microbial cell factory optimization-many challenges remain for efficient and functional expression in a host such as Escherichia coli.

RESULTS

A dynamically regulated small RNA-based circuit was developed to counter membrane stress caused by overexpression of different MPs. The best performing small RNAs were able to enhance the maximum specific growth rate with 123%. On culture level, the total MP production was increased two-to three-fold compared to a system without dynamic control. This strategy not only improved cell growth and production of the studied MPs, it also suggested the potential use for countering metabolic burden in general.

CONCLUSIONS

A dynamically regulated feedback circuit was developed that can sense metabolic stress caused by, in casu, the overexpression of an MP and responds to it by balancing the metabolic state of the cell and more specifically by downregulating the expression of the MP of interest. This negative feedback mechanism was established by implementing and optimizing simple-to-use genetic control elements based on post-transcriptional regulation: small non-coding RNAs. In addition to membrane-related stress when the MP accumulated in the cytoplasm as aggregates, the sRNA-based feedback control system was still effective for improving cell growth but resulted in a decreased total protein production. This result suggests promiscuity of the MP sensor for more than solely membrane stress.

Fate of carotenoids in yeasts: synthesis and cleavage

Carotenoids and their cleavage products (norisoprenoids) have excellent functional properties with diverse applications in foods, medicaments, cosmetics, etc. Carotenoids can be oxidatively cleaved through nonspecific reactions or by carotenoid cleavage oxygenases (CCOs), the product of which could further modify food flavor. This review provides comprehensive information on both carotenoid synthesis and cleavage processes with emphasis on enzyme characterization and biosynthetic pathway optimization. The use of interdisciplinary approaches of bioengineering and computer-aided experimental technology for key enzyme modification and systematic pathway design is beneficial to monitor metabolic pathways and assess pathway bottlenecks, which could efficiently lead to accumulation of carotenoids in microorganisms. The identification of CCOs spatial structures isolated from different species has made a significant contribution to the current state of knowledge. Current trends in carotenoid-related flavor modification are also discussed. In particular, we propose the carotenoid-synthesizing yeast Rhodotorula spp. for the production of food bioactive compounds. Understanding the behavior underlying the formation of norisoprenoids from carotenoids using interdisciplinary approaches may point toward other areas of investigation that could lead to better exploiting the potential use of autochthonous yeast in flavor enhancement.

Multiscale engineering of microbial cell factories: A step forward towards sustainable natural products industry

Microbial cell factories (bacteria and fungi) are the leading producers of beneficial natural products such as lycopene, carotene, herbal medicine, and biodiesel etc. These microorganisms are considered efficient due to their effective bioprocessing strategy (monoculture- and consortial-based approach) under distinct processing conditions. Meanwhile, the advancement in genetic and process optimization techniques leads to enhanced biosynthesis of natural products that are known functional ingredients with numerous applications in the food, cosmetic and medical industries. Natural consortia and monoculture thrive in nature in a small proportion, such as wastewater, food products, and soils. In similitude to natural consortia, it is possible to engineer artificial microbial consortia and program their behaviours via synthetic biology tools. Therefore, this review summarizes the optimization of genetic and physicochemical parameters of the microbial system for improved production of natural products. Also, this review presents a brief history of natural consortium and describes the functional properties of monocultures. This review focuses on synthetic biology tools that enable new approaches to design synthetic consortia; and highlights the syntropic interactions that determine the performance and stability of synthetic consortia. In particular, the effect of processing conditions and advanced genetic techniques to improve the productibility of both monoculture and consortial based systems have been greatly emphasized. In this context, possible strategies are also discussed to give an insight into microbial engineering for improved production of natural products in the future. In summary, it is concluded that the coupling of genomic modifications with optimum physicochemical factors would be promising for producing a robust microbial cell factory that shall contribute to the increased production of natural products.

Stabilization of antithetic control via molecular buffering

A key goal in synthetic biology is the construction of molecular circuits that robustly adapt to perturbations. Although many natural systems display perfect adaptation, whereby stationary molecular concentrations are insensitive to perturbations, its de novo engineering has proven elusive. The discovery of the antithetic control motif was a significant step towards a universal mechanism for engineering perfect adaptation. Antithetic control provides perfect adaptation in a wide range of systems, but it can lead to oscillatory dynamics due to loss of stability; moreover, it can lose perfect adaptation in fast growing cultures. Here, we introduce an extended antithetic control motif that resolves these limitations. We show that molecular buffering, a widely conserved mechanism for homeostatic control in Nature, stabilizes oscillations and allows for near-perfect adaptation during rapid growth. We study multiple buffering topologies and compare their performance in terms of their stability and adaptation properties. We illustrate the benefits of our proposed strategy in exemplar models for biofuel production and growth rate control in bacterial cultures. Our results provide an improved circuit for robust control of biomolecular systems.

Modular, synthetic chromosomes as new tools for large scale engineering of metabolism

The construction of powerful cell factories requires intensive genetic engineering for the addition of new functionalities and the remodeling of native pathways and processes. The present study demonstrates the feasibility of extensive genome reprogramming using modular, specialized de novo-assembled neochromosomes in yeast. The in vivo assembly of linear and circular neochromosomes, carrying 20 native and 21 heterologous genes, enabled the first de novo production in a microbial cell factory of anthocyanins, plant compounds with a broad range pharmacological properties. Turned into exclusive expression platforms for heterologous and essential metabolic routes, the neochromosomes mimic native chromosomes regarding mitotic and genetic stability, copy number, harmlessness for the host and editability by CRISPR/Cas9. This study paves the way for future microbial cell factories with modular genomes in which core metabolic networks, localized on satellite, specialized neochromosomes can be swapped for alternative configurations and serve as landing pads for the addition of functionalities.

Molecular Tools for Leveraging the Potential of the Acid-Tolerant Yeast Zygosaccharomyces bailii as Cell Factory

Microorganisms offer a tremendous potential as cell factories, and they are indeed been used by humans since the previous centuries for biotransformations. Among them, yeasts combine the advantage of a unicellular state with a eukaryotic organization. Moreover, in the era of biorefineries, their biodiversity can offer solutions to specific process constraints. Zygosaccharomyces bailii, an ascomycete budding yeast, is widely known for its peculiar tolerance to different stresses, among which are organic acids. Moreover, the recent reclassification of the species, including diverse hybrids, is further expanding both fundamental and applied interests. It is therefore reasonable that despite the possibility to apply with this yeast some of the molecular tools and protocols routinely used to manipulate Saccharomyces cerevisiae, adjustments and optimizations are necessary. Here we describe in detail the methods for determining chromosome number, size, and aneuploidy, transformation, classical target gene disruption or gene integration, and designing of episomal expression plasmids helpful for engineering the yeast Z. bailii .

Lysinibacillus Isolate MK212927: A Natural Producer of Allylamine Antifungal ‘Terbinafine’

Resistance to antifungal agents represents a major clinical challenge, leading to high morbidity and mortality rates, especially in immunocompromised patients. In this study, we screened soil bacterial isolates for the capability of producing metabolites with antifungal activities via the cross-streak and agar cup-plate methods. One isolate, coded S6, showed observable antifungal activity against Candida (C.) albicans ATCC 10231 and Aspergillus (A.) niger clinical isolate. This strain was identified using a combined approach of phenotypic and molecular techniques as Lysinibacillus sp. MK212927. The purified metabolite displayed fungicidal activity, reserved its activity in a relatively wide range of temperatures (up to 60 °C) and pH values (6–7.8) and was stable in the presence of various enzymes and detergents. As compared to fluconazole, miconazole and Lamisil, the minimum inhibitory concentration of the metabolite that showed 90% inhibition of the growth (MIC₉₀) was equivalent to that of Lamisil, half of miconazole and one fourth of fluconazole. Using different spectroscopic techniques such as FTIR, UV spectroscopy, 1D NMR and 2D NMR techniques, the purified metabolite was identified as terbinafine, an allylamine antifungal agent. It is deemed necessary to note that this is the first report of terbinafine production by Lysinibacillus sp. MK212927, a fast-growing microbial source, with relatively high yield and that is subject to potential optimization for industrial production capabilities.

Controlling selectivity of modular microbial biosynthesis of butyryl-CoA-derived designer esters

Short-chain esters have broad utility as flavors, fragrances, solvents, and biofuels. Controlling selectivity of ester microbial biosynthesis has been an outstanding metabolic engineering problem. In this study, we enabled the de novo fermentative microbial biosynthesis of butyryl-CoA-derived designer esters (e.g., butyl acetate, ethyl butyrate, butyl butyrate) in Escherichia coli with controllable selectivity. Using the modular design principles, we generated the butyryl-CoA-derived ester pathways as exchangeable production modules compatible with an engineered chassis cell for anaerobic production of designer esters. We designed these modules derived from an acyl-CoA submodule (e.g., acetyl-CoA, butyryl-CoA), an alcohol submodule (e.g., ethanol, butanol), a cofactor regeneration submodule (e.g., NADH), and an alcohol acetyltransferase (AAT) submodule (e.g., ATF1, SAAT) for rapid module construction and optimization by manipulating replication (e.g., plasmid copy number), transcription (e.g., promoters), translation (e.g., codon optimization), pathway enzymes, and pathway induction conditions. To further enhance production of designer esters with high selectivity, we systematically screened various strategies of protein solubilization using protein fusion tags and chaperones to improve the soluble expression of multiple pathway enzymes. Finally, our engineered ester-producing strains could achieve 19-fold increase in butyl acetate production (0.64 g/L, 96% selectivity), 6-fold increase in ethyl butyrate production (0.41 g/L, 86% selectivity), and 13-fold increase in butyl butyrate production (0.45 g/L, 54% selectivity) as compared to the initial strains. Overall, this study presented a generalizable framework to engineer modular microbial platforms for anaerobic production of butyryl-CoA-derived designer esters from renewable feedstocks.

Microbial production of advanced biofuels

Concerns over climate change have necessitated a rethinking of our transportation infrastructure. One possible alternative to carbon-polluting fossil fuels is biofuels produced by engineered microorganisms that use a renewable carbon source. Two biofuels, ethanol and biodiesel, have made inroads in displacing petroleum-based fuels, but their uptake has been limited by the amounts that can be used in conventional engines and by their cost. Advanced biofuels that mimic petroleum-based fuels are not limited by the amounts that can be used in existing transportation infrastructure but have had limited uptake due to costs. In this Review, we discuss engineering metabolic pathways to produce advanced biofuels, challenges with substrate and product toxicity with regard to host microorganisms and methods to engineer tolerance, and the use of functional genomics and machine learning approaches to produce advanced biofuels and prospects for reducing their costs.

Definitive screening accelerates Taxol biosynthetic pathway optimization and scale up in Saccharomyces cerevisiae cell factories

BACKGROUND

Recent technological advancements in synthetic and systems biology have enabled the construction of microbial cell factories expressing diverse heterologous pathways in unprecedentedly short time scales. However, the translation of such laboratory scale breakthroughs to industrial bioprocesses remains a major bottleneck.

METHODS AND MAJOR RESULTS

In this study, an accelerated bioprocess development approach was employed to optimize the biosynthetic pathway of the blockbuster chemotherapy drug, Taxol. Statistical design of experiments approaches were coupled with an industrially relevant high-throughput microbioreactor system to optimize production of key Taxol intermediates, Taxadien-5α-ol and Taxadien-5α-yl-acetate, in engineered yeast cell factories. The optimal factor combination was determined via data driven statistical modelling and validated in 1 L bioreactors leading to a 2.1-fold improvement in taxane production compared to a typical defined media. Elucidation and mitigation of nutrient limitation enhanced product titers a further two-fold and titers of the critical Taxol precursors, Taxadien-5α-ol and Taxadien-5α-yl-acetate were improved to 34 and 11 mg L^-1 , representing a three-fold improvement compared to the highest literature titers in S. cerevisiae. Comparable titers were obtained when the process was scaled up a further five-fold using 5 L bioreactors.

CONCLUSIONS

The results of this study highlight the benefits of a holistic design of experiments guided approach to expedite early stage bioprocess development.

High-throughput optofluidic screening for improved microbial cell factories via real-time micron-scale productivity monitoring

The industrial synthetic biology sector has made huge investments to achieve relevant miniaturized screening systems for scalable fermentation. Here we present the first example of a high-throughput (>10³ genotypes per week) perfusion-based screening system to improve small-molecule secretion from microbial strains. Using the Berkeley Lights Beacon® system, the productivity of each strain could be directly monitored in real time during continuous culture, yielding phenotypes that correlated strongly (r² > 0.8, p < 0.0005) with behavior in industrially relevant bioreactor processes. This method allows a much closer approximation of a typical fed-batch fermentation than conventional batch-like droplet or microplate culture models, in addition to rich time-dependent data on growth and productivity. We demonstrate these advantages by application to the improvement of high-productivity strains using whole-genome random mutagenesis, yielding mutants with substantially improved (by up to 85%) peak specific productivities in bioreactors. Each screen of ∼5 × 10³ mutants could be completed in under 8 days (including 5 days involving user intervention), saving ∼50-75% of the time required for conventional microplate-based screening methods.

A Brief Journey into the History of and Future Sources and Uses of Fatty Acids

Fats and lipids have always had a primary role in the history of humankind, from ancient civilisations to the modern and contemporary time, going from domestic and cosmetic uses, to the first medical applications and later to the large-scale industrial uses for food, pharmaceutical, cosmetics, and biofuel production. Sources and uses of those have changed during time following the development of chemical sciences and industrial technological advances. Plants, fish, and animal fats have represented the primary source of lipids and fats for century. Nowadays, the use of fatty acid sources has taken a turn: industries are mainly interested in polyunsaturated fatty acids (PUFAs), which have beneficial properties in human health; and also, for high-value fatty acids product for innovative and green production of biofuel and feedstocks. Thus, the constant increase in demand of fatty acids, the fact that marine and vegetable sources are not adequate to meet the high level of fatty acids required worldwide and climate change, have determined the necessity of the search for renewable and sustainable sources for fatty acids. Biotechnological advances and bioengineering have started looking at the genetic modification of algae, bacteria, yeasts, seeds, and plants to develop cell factory able to produce high value fatty acid products in a renewable and sustainable manner. This innovative approach applied to FA industry is a peculiar example of how biotechnology can serve as a powerful mean to drive the production of high value fatty acid derivatives on the concept of circular bioeconomy, based on the reutilisation of organic resources for alternative and sustainable productive patterns that are environmentally friendly.

Engineering Microbes to Bio-Upcycle Polyethylene Terephthalate

Polyethylene terephthalate (PET) is globally the largest produced aromatic polyester with an annual production exceeding 50 million metric tons. PET can be mechanically and chemically recycled; however, the extra costs in chemical recycling are not justified when converting PET back to the original polymer, which leads to less than 30% of PET produced annually to be recycled. Hence, waste PET massively contributes to plastic pollution and damaging the terrestrial and aquatic ecosystems. The global energy and environmental concerns with PET highlight a clear need for technologies in PET "upcycling," the creation of higher-value products from reclaimed PET. Several microbes that degrade PET and corresponding PET hydrolase enzymes have been successfully identified. The characterization and engineering of these enzymes to selectively depolymerize PET into original monomers such as terephthalic acid and ethylene glycol have been successful. Synthetic microbiology and metabolic engineering approaches enable the development of efficient microbial cell factories to convert PET-derived monomers into value-added products. In this mini-review, we present the recent progress of engineering microbes to produce higher-value chemical building blocks from waste PET using a wholly biological and a hybrid chemocatalytic-biological strategy. We also highlight the potent metabolic pathways to bio-upcycle PET into high-value biotransformed molecules. The new synthetic microbes will help establish the circular materials economy, alleviate the adverse energy and environmental impacts of PET, and provide market incentives for PET reclamation.

Biotransformation of Benzoate to 2,4,6-Trihydroxybenzophenone by Engineered Escherichia coli

The synthesis of natural products by E. coli is a challenging alternative method of environmentally friendly minimization of hazardous waste. Here, we establish a recombinant E. coli capable of transforming sodium benzoate into 2,4,6-trihydroxybenzophenone (2,4,6-TriHB), the intermediate of benzophenones and xanthones derivatives, based on the coexpression of benzoate-CoA ligase from Rhodopseudomonas palustris (BadA) and benzophenone synthase from Garcinia mangostana (GmBPS). It was found that the engineered E. coli accepted benzoate as the leading substrate for the formation of benzoyl CoA by the function of BadA and subsequently condensed, with the endogenous malonyl CoA by the catalytic function of BPS, into 2,4,6-TriHB. This metabolite was excreted into the culture medium and was detected by the high-resolution LC-ESI-QTOF-MS/MS. The structure was elucidated by in silico tools: Sirius 4.5 combined with CSI FingerID web service. The results suggested the potential of the new artificial pathway in E. coli to successfully catalyze the transformation of sodium benzoate into 2,4,6-TriHB. This system will lead to further syntheses of other benzophenone derivatives via the addition of various genes to catalyze for functional groups.

Cell-free synthetic biochemistry upgrading of ethanol to 1,3 butanediol

It is now possible to efficiently fix flue gas CO/CO₂ into ethanol using acetogens, thereby making carbon negative ethanol. While the ethanol could be burned as a fuel, returning the CO₂ to the atmosphere, it might also be possible to use the fixed carbon in more diverse chemicals, thereby keeping it fixed. Here we describe a simple synthetic biochemistry approach for converting carbon negative ethanol into the synthetic building block chemical 1,3 butanediol (1,3-BDO). The pathway completely conserves carbon from ethanol and can ultimately be powered electrochemically via formate oxidation. Our proof-of-principle system reached a maximum productivity of 0.16 g/L/h and, with replenishment of feedstock and enzymes, achieved a titer of 7.7 g/L. We identify a number of elements that can be addressed in future work to improve both cell-free and cell-based production of 1,3-BDO.

Engineering and optimization of the 2-phenylethylglucosinolate production in Nicotiana benthamiana by combining biosynthetic genes from Barbarea vulgaris and Arabidopsis thaliana

2-Phenylethylglucosinolate (2PE) derived from homophenylalanine is present in plants of the Brassicales order as a defense compound. It is associated with multiple biological properties, including deterrent effects on pests and antimicrobial and health-promoting functions, due to its hydrolysis product 2-phenylethyl isothiocyanate, which confers 2PE as a potential application in agriculture and industry. In this study, we characterized the putative key genes for 2PE biosynthesis from Barbarea vulgaris W.T. Aiton and demonstrated the feasibility of engineering 2PE production in Nicotiana benthamiana Domin. We used different combinations of genes from B. vulgaris and Arabidopsis thaliana (L.) Heynh. to demonstrate that: (i) BvBCAT4 performed more efficiently than AtBCAT4 in biosynthesis of both homophenylalanine and dihomomethionine; (ii) MAM1 enzymes were critical for the chain-elongated profile, while CYP79F enzymes accepted both chain-elongated methionine and homophenylalanine; (iii) aliphatic but not aromatic core structure pathway catalyzed the 2PE biosynthesis; (iv) a chimeric pathway containing BvBCAT4, BvMAM1, AtIPMI and AtIPMDH1 resulted in a two-fold increase in 2PE production compared with the B. vulgaris-specific chain elongation pathway; and (v) profiles of chain-elongated products and glucosinolates partially mirrored the profiles in the gene donor plant, but were wider in N. benthamiana than in the native plants. Our study provides a strategy to produce the important homophenylalanine and 2PE in a heterologous host. Furthermore, chimeric engineering of the complex 2PE biosynthetic pathway enabled detailed understanding of catalytic properties of individual enzymes - a prerequisite for understanding biochemical evolution. The new-to-nature gene combinations have the potential for application in biotechnological and plant breeding.

Application of CRISPR/Cas System in the Metabolic Engineering of Small Molecules

Clustered regularly interspaced short palindromic repeats (CRISPR) and their associated Cas protein technology area is rapidly growing technique for genome editing and modulation of transcription of several microbes. Successful engineering in microbes requires an emphasis on the aspect of efficiency and targeted aiming, which can be employed using CRISPR/Cas system. Hence, this type of system is used to modify the genome of several microbes such as yeast and bacteria. In recent years, CRISPR/Cas systems have been chosen for metabolic engineering in microbes due to their specificity, orthogonality, and efficacy. Therefore, we need to review the scheme which was acquired for the execution of the CRISPR/Cas system for the modification and metabolic engineering in yeast and bacteria. In this review, we highlighted the application of the CRISPR/Cas system which has been used for the production of small molecules in the microbial system that is chemically and biologically important.

Future trends in synthetic biology in Asia

Synthetic biology research and technology translation has garnered increasing interest from the governments and private investors in Asia, where the technology has great potential in driving a sustainable bio-based economy. This Perspective reviews the latest developments in the key enabling technologies of synthetic biology and its application in bio-manufacturing, medicine, food and agriculture in Asia. Asia-centric strengths in synthetic biology to grow the bio-based economy, such as advances in genome editing and the presence of biofoundries combined with the availability of natural resources and vast markets, are also highlighted. The potential barriers to the sustainable development of the field, including inadequate infrastructure and policies, with suggestions to overcome these by building public-private partnerships, more effective multi-lateral collaborations and well-developed governance framework, are presented. Finally, the roles of technology, education and regulation in mitigating potential biosecurity risks are examined. Through these discussions, stakeholders from different groups, including academia, industry and government, are expectantly better positioned to contribute towards the establishment of innovation and bio-economy hubs in Asia.

A supernumerary designer chromosome for modular in vivo pathway assembly in Saccharomyces cerevisiae

The construction of microbial cell factories for sustainable production of chemicals and pharmaceuticals requires extensive genome engineering. Using Saccharomyces cerevisiae, this study proposes synthetic neochromosomes as orthogonal expression platforms for rewiring native cellular processes and implementing new functionalities. Capitalizing the powerful homologous recombination capability of S. cerevisiae, modular neochromosomes of 50 and 100 kb were fully assembled de novo from up to 44 transcriptional-unit-sized fragments in a single transformation. These assemblies were remarkably efficient and faithful to their in silico design. Neochromosomes made of non-coding DNA were stably replicated and segregated irrespective of their size without affecting the physiology of their host. These non-coding neochromosomes were successfully used as landing pad and as exclusive expression platform for the essential glycolytic pathway. This work pushes the limit of DNA assembly in S. cerevisiae and paves the way for de novo designer chromosomes as modular genome engineering platforms in S. cerevisiae.

A Biological Route to Conjugated Alkenes: Microbial Production of Hepta-1,3,5-triene

Conjugated alkenes such as dienes and polyenes have a range of applications as pharmaceutical agents and valuable building blocks in the polymer industry. Development of a renewable route to these compounds provides an alternative to fossil fuel derived production. The enzyme family of the UbiD decarboxylases offers substantial scope for alkene production, readily converting poly unsaturated acids. However, biochemical pathways producing the required substrates are poorly characterized, and UbiD-application has hitherto been limited to biological styrene production. Herein, we present a proof-of-principle study for microbial production of polyenes using a bioinspired strategy employing a polyketide synthase (PKS) in combination with a UbiD-enzyme. Deconstructing a bacterial iterative type II PKS enabled repurposing the broad-spectrum antibiotic andrimid biosynthesis pathway to access the metabolic intermediate 2,4,6-octatrienoic acid, a valuable chemical for material and pharmaceutical industry. Combination with the fungal ferulic acid decarboxylase (Fdc1) led to a biocatalytic cascade-type reaction for the production of hepta-1,3,5-triene in vivo. Our approach provides a novel route to generate unsaturated hydrocarbons and related chemicals and provides a blue-print for future development and application.

Experimentally Validated Reconstruction and Analysis of a Genome-Scale Metabolic Model of an Anaerobic Neocallimastigomycota Fungus

Anaerobic gut fungi in the phylum Neocallimastigomycota typically inhabit the digestive tracts of large mammalian herbivores, where they play an integral role in the decomposition of raw lignocellulose into its constitutive sugar monomers. However, quantitative tools to study their physiology are lacking, partially due to their complex and unresolved metabolism that includes the largely uncharacterized fungal hydrogenosome. Modern omics approaches combined with metabolic modeling can be used to establish an understanding of gut fungal metabolism and develop targeted engineering strategies to harness their degradation capabilities for lignocellulosic bioprocessing. Here, we introduce a high-quality genome of the anaerobic fungus Neocallimastix lanati from which we constructed the first genome-scale metabolic model of an anaerobic fungus. Relative to its size (200 Mbp, sequenced at 62× depth), it is the least fragmented publicly available gut fungal genome to date. Of the 1,788 lignocellulolytic enzymes annotated in the genome, 585 are associated with the fungal cellulosome, underscoring the powerful lignocellulolytic potential of N. lanati. The genome-scale metabolic model captures the primary metabolism of N. lanati and accurately predicts experimentally validated substrate utilization requirements. Additionally, metabolic flux predictions are verified by ¹³C metabolic flux analysis, demonstrating that the model faithfully describes the underlying fungal metabolism. Furthermore, the model clarifies key aspects of the hydrogenosomal metabolism and can be used as a platform to quantitatively study these biotechnologically important yet poorly understood early-branching fungi.

IMPORTANCE Recent genomic analyses have revealed that anaerobic gut fungi possess both the largest number and highest diversity of lignocellulolytic enzymes of all sequenced fungi, explaining their ability to decompose lignocellulosic substrates, e.g., agricultural waste, into fermentable sugars. Despite their potential, the development of engineering methods for these organisms has been slow due to their complex life cycle, understudied metabolism, and challenging anaerobic culture requirements. Currently, there is no framework that can be used to combine multi-omic data sets to understand their physiology. Here, we introduce a high-quality PacBio-sequenced genome of the anaerobic gut fungus Neocallimastix lanati. Beyond identifying a trove of lignocellulolytic enzymes, we use this genome to construct the first genome-scale metabolic model of an anaerobic gut fungus. The model is experimentally validated and sheds light on unresolved metabolic features common to gut fungi. Model-guided analysis will pave the way for deepening our understanding of anaerobic gut fungi and provides a systematic framework to guide strain engineering efforts of these organisms for biotechnological use.

Multiomics Data Collection, Visualization, and Utilization for Guiding Metabolic Engineering

Biology has changed radically in the past two decades, growing from a purely descriptive science into also a design science. The availability of tools that enable the precise modification of cells, as well as the ability to collect large amounts of multimodal data, open the possibility of sophisticated bioengineering to produce fuels, specialty and commodity chemicals, materials, and other renewable bioproducts. However, despite new tools and exponentially increasing data volumes, synthetic biology cannot yet fulfill its true potential due to our inability to predict the behavior of biological systems. Here, we showcase a set of computational tools that, combined, provide the ability to store, visualize, and leverage multiomics data to predict the outcome of bioengineering efforts. We show how to upload, visualize, and output multiomics data, as well as strain information, into online repositories for several isoprenol-producing strain designs. We then use these data to train machine learning algorithms that recommend new strain designs that are correctly predicted to improve isoprenol production by 23%. This demonstration is done by using synthetic data, as provided by a novel library, that can produce credible multiomics data for testing algorithms and computational tools. In short, this paper provides a step-by-step tutorial to leverage these computational tools to improve production in bioengineered strains.

The sum is greater than the parts: exploiting microbial communities to achieve complex functions

Multi-species microbial communities are ubiquitous in nature. The widespread prevalence of these communities is due to highly elaborated interactions among their members thereby accomplishing metabolic functions that are unattainable by individual members alone. Harnessing these communal capabilities is an emerging field in biotechnology. The rational intervention of microbial communities for the purpose of improved function has been facilitated in part by developments in multi-omics approaches, synthetic biology, and computational methods. Recent studies have demonstrated the benefits of rational interventions to human and animal health as well as agricultural productivity. Emergent technologies, such as in situ modification of complex microbial community and community metabolic modeling, represent an avenue to engineer sustainable microbial communities. In this opinion, we review relevant computational and experimental approaches to study and engineer microbial communities and discuss their potential for biotechnological applications.

Recent advances in systems and synthetic biology approaches for developing novel cell-factories in non-conventional yeasts

Microbial bioproduction of chemicals, proteins, and primary metabolites from cheap carbon sources is currently an advancing area in industrial research. The model yeast, Saccharomyces cerevisiae, is a well-established biorefinery host that has been used extensively for commercial manufacturing of bioethanol from myriad carbon sources. However, its Crabtree-positive nature often limits the use of this organism for the biosynthesis of commercial molecules that do not belong in the fermentative pathway. To avoid extensive strain engineering of S. cerevisiae for the production of metabolites other than ethanol, non-conventional yeasts can be selected as hosts based on their natural capacity to produce desired commodity chemicals. Non-conventional yeasts like Kluyveromyces marxianus, K. lactis, Yarrowia lipolytica, Pichia pastoris, Scheffersomyces stipitis, Hansenula polymorpha, and Rhodotorula toruloides have been considered as potential industrial eukaryotic hosts owing to their desirable phenotypes such as thermotolerance, assimilation of a wide range of carbon sources, as well as ability to secrete high titers of protein and lipid. However, the advanced metabolic engineering efforts in these organisms are still lacking due to the limited availability of systems and synthetic biology methods like in silico models, well-characterised genetic parts, and optimized genome engineering tools. This review provides an insight into the recent advances and challenges of systems and synthetic biology as well as metabolic engineering endeavours towards the commercial usage of non-conventional yeasts. Particularly, the approaches in emerging non-conventional yeasts for the production of enzymes, therapeutic proteins, lipids, and metabolites for commercial applications are extensively discussed here. Various attempts to address current limitations in designing novel cell factories have been highlighted that include the advances in the fields of genome-scale metabolic model reconstruction, flux balance analysis, 'omics'-data integration into models, genome-editing toolkit development, and rewiring of cellular metabolisms for desired chemical production. Additionally, the understanding of metabolic networks using ¹³C-labelling experiments as well as the utilization of metabolomics in deciphering intracellular fluxes and reactions have also been discussed here. Application of cutting-edge nuclease-based genome editing platforms like CRISPR/Cas9, and its optimization towards efficient strain engineering in non-conventional yeasts have also been described. Additionally, the impact of the advances in promising non-conventional yeasts for efficient commercial molecule synthesis has been meticulously reviewed. In the future, a cohesive approach involving systems and synthetic biology will help in widening the horizon of the use of unexplored non-conventional yeast species towards industrial biotechnology.

Statistical Design of Experiments for Synthetic Biology

The design and optimization of biological systems is an inherently complex undertaking that requires careful balancing of myriad synergistic and antagonistic variables. However, despite this complexity, much synthetic biology research is predicated on One Factor at A Time (OFAT) experimentation; the genetic and environmental variables affecting the activity of a system of interest are sequentially altered while all other variables are held constant. Beyond being time and resource intensive, OFAT experimentation crucially ignores the effect of interactions between factors. Given the ubiquity of interacting genetic and environmental factors in biology this failure to account for interaction effects in OFAT experimentation can result in the development of suboptimal systems. To address these limitations, an increasing number of studies have turned to Design of Experiments (DoE), a suite of methods that enable efficient, systematic exploration and exploitation of complex design spaces. This review provides an overview of DoE for synthetic biologists. Key concepts and commonly used experimental designs are introduced, and we discuss the advantages of DoE as compared to OFAT experimentation. We dissect the applicability of DoE in the context of synthetic biology and review studies which have successfully employed these methods, illustrating the potential of statistical experimental design to guide the design, characterization, and optimization of biological protocols, pathways, and processes.

Bioprospecting of microbial strains for biofuel production: metabolic engineering, applications, and challenges

The issues of global warming, coupled with fossil fuel depletion, have undoubtedly led to renewed interest in other sources of commercial fuels. The search for renewable fuels has motivated research into the biological degradation of lignocellulosic biomass feedstock to produce biofuels such as bioethanol, biodiesel, and biohydrogen. The model strain for biofuel production needs the capability to utilize a high amount of substrate, transportation of sugar through fast and deregulated pathways, ability to tolerate inhibitory compounds and end products, and increased metabolic fluxes to produce an improved fermentation product. Engineering microbes might be a great approach to produce biofuel from lignocellulosic biomass by exploiting metabolic pathways economically. Metabolic engineering is an advanced technology for the construction of highly effective microbial cell factories and a key component for the next-generation bioeconomy. It has been extensively used to redirect the biosynthetic pathway to produce desired products in several native or engineered hosts. A wide range of novel compounds has been manufactured through engineering metabolic pathways or endogenous metabolism optimizations by metabolic engineers. This review is focused on the potential utilization of engineered strains to produce biofuel and gives prospects for improvement in metabolic engineering for new strain development using advanced technologies.

Improved production of 2,3-butanediol and isobutanol by engineering electron transport chain in Escherichia coli

The electron transport chain (ETC) is one of the major energy generation pathways in microorganisms under aerobic condition. Higher yield of ATP can be achieved through oxidative phosphorylation with consumption of NADH than with substrate level phosphorylation. However, most value-added metabolites are in an electrochemically reduced state, which requires reducing equivalent NADH as a cofactor. Therefore, optimal production of value-added metabolites should be balanced with ETC in terms of energy production. In this study, we attempted to reduce the activity of ETC to secure availability of NADH. The ETC mutants exhibited poor growth rate and production of fermentative metabolites compared to parental strain. Introduction of heterologous pathways for synthesis of 2,3-butanediol and isobutanol to ETC mutants resulted in increased titres and yields of the metabolites. ETC mutants yielded higher NADH/NAD+ ratio but similar ATP content than that by the parental strain. Furthermore, ETC mutants operated fermentative metabolism pathways independent of oxygen supply in large-scale fermenter, resulting in increased yield and titre of 2,3-butanediol. Thus, engineering of ETC is a useful metabolic engineering approach for production of reduced metabolites.

An insight to flux-balance analysis for biochemical networks

Systems biology is one of the integrated ways to study biological systems and is more favourable than the earlier used approaches. It includes metabolic pathway analysis, modelling, and regulatory as well as signal transduction for getting insights into cellular behaviour. Among the various techniques of modelling, simulation, analysis of networks and pathways, flux-based analysis (FBA) has been recognised because of its extensibility as well as simplicity. It is widely accepted because it is not like a mechanistic simulation which depends on accurate kinetic data. The study of fluxes through the network is informative and can give insights even in the absence of kinetic data. FBA is one of the widely used tools to study biochemical networks and needs information of reaction stoichiometry, growth requirements, specific measurement parameters of the biological system, in particular the reconstruction of the metabolic network for the genome-scale, many of which have already been built previously. It defines the boundaries of flux distributions which are possible and achievable with a defined set of genes. This review article gives an insight into FBA, from the extension of flux balancing to mathematical representation followed by a discussion about the formulation of flux-balance analysis problems, defining constraints for the stoichiometry of the pathways and the tools that can be used in FBA such as FASIMA, COBRA toolbox, and OptFlux. It also includes broader areas in terms of applications which can be covered by FBA as well as the queries which can be addressed through FBA.

Biotransformation of Oleanane and Ursane Triterpenic Acids

Oleanane and ursane pentacyclic triterpenoids are secondary metabolites of plants found in various climatic zones and regions. This group of compounds is highly attractive due to their diverse biological properties and possible use as intermediates in the synthesis of new pharmacologically promising substances. By now, their antiviral, anti-inflammatory, antimicrobial, antitumor, and other activities have been confirmed. In the last decade, methods of microbial synthesis of these compounds and their further biotransformation using microorganisms are gaining much popularity. The present review provides clear evidence that industrial microbiology can be a promising way to obtain valuable pharmacologically active compounds in environmentally friendly conditions without processing huge amounts of plant biomass and using hazardous and expensive chemicals. This review summarizes data on distribution, microbial synthesis, and biological activities of native oleanane and ursane triterpenoids. Much emphasis is put on the processes of microbial transformation of selected oleanane and ursane pentacyclic triterpenoids and on the bioactivity assessment of the obtained derivatives.

Machine learning for metabolic engineering: A review

Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing in-depth illustrative examples leveraging omics data and improving production. We also include practical advice for the practitioner in terms of data management, algorithm libraries, computational resources, and important non-technical issues. A variety of applications ranging from pathway construction and optimization, to genetic editing optimization, cell factory testing, and production scale-up are discussed. Moreover, the promising relationship between machine learning and mechanistic models is thoroughly reviewed. Finally, the future perspectives and most promising directions for this combination of disciplines are examined.