Nitrogen starvation causes lipid remodeling in Rhodotorula toruloides.

BACKGROUND: The oleaginous yeast Rhodotorula toruloides is a promising chassis organism for the biomanufacturing of value-added bioproducts. It can accumulate lipids at a high fraction of biomass. However, metabolic engineering efforts in this organism have progressed at a slower pace than those in more extensively studied yeasts. Few studies have investigated the lipid accumulation phenotype exhibited by R. toruloides under nitrogen limitation conditions. Consequently, there have been only a few studies exploiting the lipid metabolism for higher product titers. RESULTS: We performed a multi-omic investigation of the lipid accumulation phenotype under nitrogen limitation. Specifically, we performed comparative transcriptomic and lipidomic analysis of the oleaginous yeast under nitrogen-sufficient and nitrogen deficient conditions. Clustering analysis of transcriptomic data was used to identify the growth phase where nitrogen-deficient cultures diverged from the baseline conditions. Independently, lipidomic data was used to identify that lipid fractions shifted from mostly phospholipids to mostly storage lipids under the nitrogen-deficient phenotype. Through an integrative lens of transcriptomic and lipidomic analysis, we discovered that R. toruloides undergoes lipid remodeling during nitrogen limitation, wherein the pool of phospholipids gets remodeled to mostly storage lipids. We identify specific mRNAs and pathways that are strongly correlated with an increase in lipid levels, thus identifying putative targets for engineering greater lipid accumulation in R. toruloides. One surprising pathway identified was related to inositol phosphate metabolism, suggesting further inquiry into its role in lipid accumulation. CONCLUSIONS: Integrative analysis identified the specific biosynthetic pathways that are differentially regulated during lipid remodeling. This insight into the mechanisms of lipid accumulation can lead to the success of future metabolic engineering strategies for overproduction of oleochemicals.

Mass Spectrometry-Based High-Throughput Quantification of Bioproducts in Liquid Culture.

To meet the ever-increasing need for high-throughput screening in metabolic engineering, information-rich, fast screening methods are needed. Mass spectrometry (MS) provides an efficient and general approach for metabolite screening and offers the capability of characterizing a broad range of analytes in a label-free manner, but often requires a range of sample clean-up and extraction steps. Liquid extraction surface analysis (LESA) coupled MS is an image-guided MS surface analysis approach that directly samples and introduces metabolites from a surface to MS. Here, we combined the advantages of LESA-MS and an acoustic liquid handler with stable isotope-labeled internal standards. This approach provides absolute quantitation of target chemicals from liquid culture-dried droplets and enables high-throughput quantitative screening for microbial metabolites. In this study, LESA-MS was successfully applied to quantify several different metabolites (itaconic acid, triacetic acid lactone, and palmitic acid) from different yeast strains in different mediums, demonstrating its versatility, accuracy, and efficiency across a range of microbial engineering applications.

Metabolic Engineering: Methodologies and Applications.

Metabolic engineering aims to improve the production of economically valuable molecules through the genetic manipulation of microbial metabolism. While the discipline is a little over 30 years old, advancements in metabolic engineering have given way to industrial-level molecule production benefitting multiple industries such as chemical, agriculture, food, pharmaceutical, and energy industries. This review describes the design, build, test, and learn steps necessary for leading a successful metabolic engineering campaign. Moreover, we highlight major applications of metabolic engineering, including synthesizing chemicals and fuels, broadening substrate utilization, and improving host robustness with a focus on specific case studies. Finally, we conclude with a discussion on perspectives and future challenges related to metabolic engineering.

Design and application of a kinetic model of lipid metabolism in Saccharomyces cerevisiae.

Lipid biosynthesis plays a vital role in living cells and has been increasingly engineered to overproduce various lipid-based chemicals. However, owing to the tightly constrained and interconnected nature of lipid biosynthesis, both understanding and engineering of lipid metabolism remain challenging, even with the help of mathematical models. Here we report the development of a kinetic metabolic model of lipid metabolism in Saccharomyces cerevisiae that integrates fatty acid biosynthesis, glycerophospholipid metabolism, sphingolipid metabolism, storage lipids, lumped sterol synthesis, and the synthesis and transport of relevant target-chemicals, such as fatty acids and fatty alcohols. The model was trained on lipidomic data of a reference S. cerevisiae strain, single knockout mutants, and lipid overproduction strains reported in literature. The model was used to design mutants for fatty alcohol overproduction and the lipidomic analysis of the resultant mutant strains coupled with model-guided hypothesis led to discovery of a futile cycle in the triacylglycerol biosynthesis pathway. In addition, the model was used to explain successful and unsuccessful mutant designs in metabolic engineering literature. Thus, this kinetic model of lipid metabolism can not only enable the discovery of new phenomenon in lipid metabolism but also the engineering of mutant strains for overproduction of lipids.

Metabolic engineering of oleaginous yeast Rhodotorula toruloides for overproduction of triacetic acid lactone.

The plant-sourced polyketide triacetic acid lactone (TAL) has been recognized as a promising platform chemical for the biorefinery industry. However, its practical application was rather limited due to low natural abundance and inefficient cell factories for biosynthesis. Here, we report the metabolic engineering of oleaginous yeast Rhodotorula toruloides for TAL overproduction. We first introduced a 2-pyrone synthase gene from Gerbera hybrida (GhPS) into R. toruloides and investigated the effects of different carbon sources on TAL production. We then systematically employed a variety of metabolic engineering strategies to increase the flux of acetyl-CoA by enhancing its biosynthetic pathways and disrupting its competing pathways. We found that overexpression of ATP-citrate lyase (ACL1) improved TAL production by 45% compared to the GhPS overexpressing strain, and additional overexpression of acetyl-CoA carboxylase (ACC1) further increased TAL production by 29%. Finally, we characterized the resulting strain I12-ACL1-ACC1 using fed-batch bioreactor fermentation in glucose or oilcane juice medium with acetate supplementation and achieved a titer of 28 or 23 g/L TAL, respectively. This study demonstrates that R. toruloides is a promising host for the production of TAL and other acetyl-CoA-derived polyketides from low-cost carbon sources.

Metabolic engineering of Rhodotorula toruloides IFO0880 improves C16 and C18 fatty alcohol production from synthetic media.

BACKGROUND: The oleaginous, carotenogenic yeast Rhodotorula toruloides has been increasingly explored as a platform organism for the production of terpenoids and fatty acid derivatives. Fatty alcohols, a fatty acid derivative widely used in the production of detergents and surfactants, can be produced microbially with the expression of a heterologous fatty acyl-CoA reductase. Due to its high lipid production, R. toruloides has high potential for fatty alcohol production, and in this study several metabolic engineering approaches were investigated to improve the titer of this product. RESULTS: Fatty acyl-CoA reductase from Marinobacter aqueolei was co-expressed with SpCas9 in R. toruloides IFO0880 and a panel of gene overexpressions and Cas9-mediated gene deletions were explored to increase the fatty alcohol production. Two overexpression targets (ACL1 and ACC1, improving cytosolic acetyl-CoA and malonyl-CoA production, respectively) and two deletion targets (the acyltransferases DGA1 and LRO1) resulted in significant (1.8 to 4.4-fold) increases to the fatty alcohol titer in culture tubes. Combinatorial exploration of these modifications in bioreactor fermentation culminated in a 3.7 g/L fatty alcohol titer in the LRO1Δ mutant. As LRO1 deletion was not found to be beneficial for fatty alcohol production in other yeasts, a lipidomic comparison of the DGA1 and LRO1 knockout mutants was performed, finding that DGA1 is the primary acyltransferase responsible for triacylglyceride production in R. toruloides, while LRO1 disruption simultaneously improved fatty alcohol production, increased diacylglyceride and triacylglyceride production, and increased glucose consumption. CONCLUSIONS: The fatty alcohol titer of fatty acyl-CoA reductase-expressing R. toruloides was significantly improved through the deletion of LRO1, or the deletion of DGA1 combined with overexpression of ACC1 and ACL1. Disruption of LRO1 surprisingly increased both lipid and fatty alcohol production, creating a possible avenue for future study of the lipid metabolism of this yeast.

Does green financing help to improve environmental & social responsibility? Designing SDG framework through advanced quantile modelling.

Striving to achieve the Sustainable Development Goals (SDGs), countries are increasingly embracing a sustainable financing mechanism via green bond financing. Green bonds have attracted the attention of the industrial sector and policymakers, however, the impact of green bond financing on environmental and social sustainability has not been confirmed. There is no empirical evidence on how this financial product can contribute to achieving the goals set out in Agenda 2030. In this study, we empirically analyze the impact of green bond financing on environmental and social sustainability by considering the S&P 500 Global Green Bond Index and S&P 500 Environmental and Social Responsibility Index, from October 1, 2010 to 31st July 2020 using a combination of Quantile-on-Quantile Regression and Wavelet Multiscale Decomposition approaches. Our results reveal that green financing mechanisms might have gradual negative transformational impacts on environmental and social responsibility. Furthermore, we attempt to design a policy framework to address the relevant SDG objectives.

Two-Color Imaging of Nonrepetitive Endogenous Loci in Human Cells.

Tools for live cell imaging of multiple nonrepetitive genomic loci in mammalian cells are necessary to study chromatin dynamics. Here, we report a new system based on two chromosomally integrated orthogonal irregular repeat arrays and particularly a new general strategy to construct irregular repeat arrays. Briefly, we utilized a "bridge oligonucleotide-mediated ligation" protocol to assemble 8-mer repeats de novo which were then combined into a final 96-mer repeat array using Golden Gate cloning. This strategy was used for assembling a new mutant TetO irregular repeat array, which worked orthogonally to the wild type TetO repeat. Single copy integration of the new repeat array did not cause replication deficiencies at the tagged locus. Moreover, the mutant TetO irregular repeat could also be visualized by CRISPR imaging. Our new irregular repeat assembly method demonstrates a generally applicable strategy that can be used for assembling additional orthogonal repeat arrays for imaging genomic loci and irregular repeats to visualize RNA or proteins via signal amplification.

Biosystems Design by Machine Learning.

Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. However, the intricate connectivity and resulting complexity of biosystems poses a major hurdle in designing biosystems with desirable features. As -omics and other high throughput technologies have been rapidly developed, the promise of applying machine learning (ML) techniques in biosystems design has started to become a reality. ML models enable the identification of patterns within complicated biological data across multiple scales of analysis and can augment biosystems design applications by predicting new candidates for optimized performance. ML is being used at every stage of biosystems design to help find nonobvious engineering solutions with fewer design iterations. In this review, we first describe commonly used models and modeling paradigms within ML. We then discuss some applications of these models that have already shown success in biotechnological applications. Moreover, we discuss successful applications at all scales of biosystems design, including nucleic acids, genetic circuits, proteins, pathways, genomes, and bioprocesses. Finally, we discuss some limitations of these methods and potential solutions as well as prospects of the combination of ML and biosystems design.

A mass spectrometry-based high-throughput screening method for engineering fatty acid synthases with improved production of medium-chain fatty acids.

Microbial cell factories have been extensively engineered to produce free fatty acids (FFAs) as key components of crucial nutrients, soaps, industrial chemicals, and fuels. However, our ability to control the composition of microbially synthesized FFAs is still limited, particularly, for producing medium-chain fatty acids (MCFAs). This is mainly due to the lack of high-throughput approaches for FFA analysis to engineer enzymes with desirable product specificity. Here we report a mass spectrometry (MS)-based method for rapid profiling of MCFAs in Saccharomyces cerevisiae by using membrane lipids as a proxy. In particular, matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) MS was used to detect shorter acyl chain phosphatidylcholines from membrane lipids and a higher m/z peak ratio at 730 and 758 was used as an indication for improved MCFA production. This colony-based method can be performed at a rate of ~2 s per sample, representing a substantial improvement over gas chromatography-MS (typically >30 min per sample) as the gold standard method for FFA detection. To demonstrate the power of this method, we performed site-saturation mutagenesis of the yeast fatty acid synthase and identified nine missense mutations that resulted in improved MCFA production relative to the wild-type strain. Colony-based MALDI-ToF MS screening provides an effective approach for engineering microbial fatty acid compositions in a high-throughput manner.

Recent advances in metabolic engineering of Saccharomyces cerevisiae: New tools and their applications.

Metabolic engineering aims to develop efficient cell factories by rewiring cellular metabolism. As one of the most commonly used cell factories, Saccharomyces cerevisiae has been extensively engineered to produce a wide variety of products at high levels from various feedstocks. In this review, we summarize the recent development of metabolic engineering approaches to modulate yeast metabolism with representative examples. Particularly, we highlight new tools for biosynthetic pathway optimization (i.e. combinatorial transcriptional engineering and dynamic metabolic flux control) and genome engineering (i.e. clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated (Cas) system based genome engineering and RNA interference assisted genome evolution) to advance metabolic engineering in yeast. We also discuss the challenges and perspectives for high throughput metabolic engineering.

Engineering biological systems using automated biofoundries.

Engineered biological systems such as genetic circuits and microbial cell factories have promised to solve many challenges in the modern society. However, the artisanal processes of research and development are slow, expensive, and inconsistent, representing a major obstacle in biotechnology and bioengineering. In recent years, biological foundries or biofoundries have been developed to automate design-build-test engineering cycles in an effort to accelerate these processes. This review summarizes the enabling technologies for such biofoundries as well as their early successes and remaining challenges.