Engineering a Synthetic Escherichia coli Coculture for Compartmentalized de novo Biosynthesis of Isobutyl Butyrate from Mixed Sugars.

Short-chain esters are versatile chemicals that can be used as flavors, fragrances, solvents, and fuels. The de novo ester biosynthesis consists of diverging and converging pathway submodules, which is challenging to engineer to achieve optimal metabolic fluxes and selective product synthesis. Compartmentalizing the pathway submodules into specialist cells that facilitate pathway modularization and labor division is a promising solution. Here, we engineered a synthetic Escherichia coli coculture with the compartmentalized sugar utilization and ester biosynthesis pathways to produce isobutyl butyrate from a mixture of glucose and xylose. To compartmentalize the sugar-utilizing pathway submodules, we engineered a xylose-utilizing E. coli specialist that selectively consumes xylose over glucose and bypasses carbon catabolite repression (CCR) while leveraging the native CCR machinery to activate a glucose-utilizing E. coli specialist. We found that the compartmentalization of sugar catabolism enabled simultaneous co-utilization of glucose and xylose by a coculture of the two E. coli specialists, improving the stability of the coculture population. Next, we modularized the isobutyl butyrate pathway into the isobutanol, butyl-CoA, and ester condensation submodules, where we distributed the isobutanol submodule to the glucose-utilizing specialist and the other submodules to the xylose-utilizing specialist. Upon compartmentalization of the isobutyl butyrate pathway submodules into these sugar-utilizing specialist cells, a robust synthetic coculture was engineered to selectively produce isobutyl butyrate, reduce the biosynthesis of unwanted ester byproducts, and improve the production titer as compared to the monoculture.

Potency of CRISPR-Cas Antifungals Is Enhanced by Cotargeting DNA Repair and Growth Regulatory Machinery at the Genetic Level.

The emergence of virulent, resistant, and rapidly evolving fungal pathogens poses a significant threat to public health, agriculture, and the environment. Targeting cellular processes with standard small-molecule intervention may be effective but requires long development times and is prone to antibiotic resistance. To overcome the current limitations of antibiotic development and treatment, this study harnesses CRISPR-Cas systems as antifungals by capitalizing on their adaptability, specificity, and efficiency in target design. The conventional design of CRISPR-Cas antimicrobials, based on induction of DNA double-strand breaks (DSBs), is potentially less effective in fungi due to robust eukaryotic DNA repair machinery. Here, we report a novel design principle to formulate more effective CRISPR-Cas antifungals by cotargeting essential genes with DNA repair defensive genes that remove the fungi's ability to repair the DSB sites of essential genes. By evaluating this design on the model fungus Saccharomyces cerevisiae, we demonstrated that essential and defensive gene cotargeting is more effective than either essential or defensive gene targeting alone. The top-performing CRISPR-Cas antifungals performed as effectively as the antibiotic Geneticin. A gene cotargeting interaction analysis revealed that cotargeting essential genes with RAD52 involved in homologous recombination (HR) was the most synergistic combination. Fast growth kinetics of S. cerevisiae induced resistance to CRISPR-Cas antifungals, where genetic mutations mostly occurred in defensive genes and guide RNA sequences.

Proteomes reveal metabolic capabilities of Yarrowia lipolytica for biological upcycling of polyethylene into high-value chemicals.

IMPORTANCE: Sustainable processes for biological upcycling of plastic wastes in a circular bioeconomy are needed to promote decarbonization and reduce environmental pollution due to increased plastic consumption, incineration, and landfill storage. Strain characterization and proteomic analysis revealed the robust metabolic capabilities of Yarrowia lipolytica to upcycle polyethylene into high-value chemicals. Significant proteome reallocation toward energy and lipid metabolisms was required for robust growth on hydrocarbons with n-hexadecane as the preferential substrate. However, an apparent over-investment in these same categories to utilize complex depolymerized plastic (DP) oil came at the expense of protein biosynthesis, limiting cell growth. Taken together, this study elucidates how Y. lipolytica activates its metabolism to utilize DP oil and establishes Y. lipolytica as a promising host for the upcycling of plastic wastes.

Rewiring metabolism of Clostridium thermocellum for consolidated bioprocessing of lignocellulosic biomass poplar to produce short-chain esters.

Consolidated bioprocessing (CBP) of lignocellulosic biomass uses cellulolytic microorganisms to enable enzyme production, saccharification, and fermentation to produce biofuels, biochemicals, and biomaterials in a single step. However, understanding and redirecting metabolisms of these microorganisms compatible with CBP are limited. Here, a cellulolytic thermophile Clostridium thermocellum was engineered and demonstrated to be compatible with CBP integrated with a Co-solvent Enhanced Lignocellulosic Fractionation (CELF) pretreatment for conversion of hardwood poplar into short-chain esters with industrial use as solvents, flavors, fragrances, and biofuels. The recombinant C. thermocellum engineered with deletion of carbohydrate esterases and stable overexpression of alcohol acetyltransferases improved ester production without compromised deacetylation activities. These esterases were discovered to exhibit promiscuous thioesterase activities and their deletion enhanced ester production by rerouting the electron and carbon metabolism. Ester production was further improved up to 80-fold and ester composition could be modulated by deleting lactate biosynthesis and using poplar with different pretreatment severity.

CASPER: An Integrated Software Platform for Rapid Development of CRISPR Tools.

Both academic and enterprise software solutions exist for designing CRISPR targets. They offer advantages when designing guide RNAs (gRNAs) but often focus on a select number of model organisms. Those that offer a wide variety of organisms can be limited in support of alternative endonucleases and downstream analyses such as multitargeting and population analyses to interrogate a microbiome. To accommodate broad CRISPR utilization, we developed a flexible platform software CRISPR Associated Software for Pathway Engineering and Research (CASPER) for gRNA generation and analysis in any organism and with any CRISPR-Cas system. CASPER combines traditional gRNA design tools with unique functions such as multiple Cas-type gRNA generation and evaluation of spacer redundancy in a single species or microbiome. The analyses have implications for strain-, species-, or genus-specific CRISPR diagnostic probe design and microbiome manipulation. The novel features of CASPER are packaged in a user-friendly interface to create a computational environment for researchers to streamline the utility of CRISPR-Cas systems.

Gene Coexpression Connectivity Predicts Gene Targets Underlying High Ionic-Liquid Tolerance in Yarrowia lipolytica.

Microbial tolerance to organic solvents such as ionic liquids (ILs) is a robust phenotype beneficial for novel biotransformation. While most microbes become inhibited in 1% to 5% (vol/vol) IL (e.g., 1-ethyl-3-methylimidazolium acetate), we engineered a robust Yarrowia lipolytica strain (YlCW001) that tolerates a record high of 18% (vol/vol) IL via adaptive laboratory evolution. Yet, genotypes conferring high IL tolerance in YlCW001 remain to be discovered. In this study, we shed light on the underlying cellular processes that enable robust Y. lipolytica to thrive in inhibitory ILs. By using dynamic transcriptome sequencing (RNA-Seq) data, we introduced Gene Coexpression Connectivity (GeCCo) as a metric to discover genotypes conferring desirable phenotypes that might not be found by the conventional differential expression (DE) approaches. GeCCo selects genes based on their number of coexpressed genes in a subnetwork of upregulated genes by the target phenotype. We experimentally validated GeCCo by reverse engineering a high-IL-tolerance phenotype in wild-type Y. lipolytica. We found that gene targets selected by both DE and GeCCo exhibited the best statistical chance at increasing IL tolerance when individually overexpressed. Remarkably, the best combination of dual-overexpression genes was genes selected by GeCCo alone. This nonintuitive combination of genes, BRN1 and OYE2, is involved in guiding/regulating mitotic cell division, chromatin segregation/condensation, microtubule and cytoskeletal organization, and Golgi vesicle transport. IMPORTANCE Cellular robustness to cope with stressors is an important phenotype. Y. lipolytica is an industrial robust oleaginous yeast that has recently been discovered to tolerate record high concentrations of ILs, beneficial for novel biotransformation in organic solvents. However, genotypes that link to IL tolerance in Y. lipolytica are largely unknown. Due to the complex IL-tolerant phenotype, conventional gene discovery and validation based on differential gene expression approaches are time-consuming due to a large search space and might encounter a high false-discovery rate. Here, using the developed Gene Coexpression Connectivity (GeCCo) method, we identified and validated a subset of most promising gene targets conferring the IL-tolerant phenotypes and shed light on their potential mechanisms. We anticipate GeCCo being a useful method to discover the genotype-to-phenotype link.

Proteome reallocation enables the selective de novo biosynthesis of non-linear, branched-chain acetate esters.

The one-carbon recursive ketoacid elongation pathway is responsible for making various branched-chain amino acids, aldehydes, alcohols, ketoacids, and acetate esters in living cells. Controlling selective microbial biosynthesis of these target molecules at high efficiency is challenging due to enzyme promiscuity, regulation, and metabolic burden. In this study, we present a systematic modular design approach to control proteome reallocation for selective microbial biosynthesis of branched-chain acetate esters. Through pathway modularization, we partitioned the branched-chain ester pathways into four submodules including ketoisovalerate submodule for converting pyruvate to ketoisovalerate, ketoacid elongation submodule for producing longer carbon-chain ketoacids, ketoacid decarboxylase submodule for converting ketoacids to alcohols, and alcohol acyltransferase submodule for producing branched-chain acetate esters by condensing alcohols and acetyl-CoA. By systematic manipulation of pathway gene replication and transcription, enzyme specificity of the first committed steps of these submodules, and downstream competing pathways, we demonstrated selective microbial production of isoamyl acetate over isobutyl acetate. We found that the optimized isoamyl acetate pathway globally redistributed the amino acid fractions in the proteomes and required up to 23-31% proteome reallocation at the expense of other cellular resources, such as those required to generate precursor metabolites and energy for growth and amino acid biosynthesis. From glucose fed-batch fermentation, the engineered strains produced isoamyl acetate up to a titer of 8.8 g/L (>0.25 g/L toxicity limit), a yield of 0.22 g/g (61% of maximal theoretical value), and 86% selectivity, achieving the highest titers, yields and selectivity of isoamyl acetate reported to date.

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.

Probing specificities of alcohol acyltransferases for designer ester biosynthesis with a high-throughput microbial screening platform.

Alcohol acyltransferases (AATs) enables microbial biosynthesis of a large space of esters by condensing an alcohol and an acyl-CoA. However, substrate promiscuity of AATs prevents microbial biosynthesis of designer esters with high selectivity. Here, we developed a high-throughput microbial screening platform that facilitates rapid identification of AATs for designer ester biosynthesis. First, we established a microplate-based culturing technique with in situ fermentation and extraction of esters. We validated its capability in rapid profiling of the alcohol substrate specificity of 20 chloramphenicol acetyltransferase variants derived from Staphylococcus aureus (CATSa ) for microbial biosynthesis of acetate esters with various exogeneous alcohol supply. By coupling the microplate-based culturing technique with a previously established colorimetric assay, we developed a high-throughput microbial screening platform for AATs. We demonstrated that this platform could not only probe the alcohol substrate specificity of both native and engineered AATs but also identify the beneficial mutations in engineered AATs for enhanced ester synthesis. We anticipate the high-throughput microbial screening platform provides a useful tool to identify novel wildtype and engineered AATs that have important roles in nature and industrial biocatalysis for designer bioester production.

Exploring Proteomes of Robust Yarrowia lipolytica Isolates Cultivated in Biomass Hydrolysate Reveals Key Processes Impacting Mixed Sugar Utilization, Lipid Accumulation, and Degradation.

Yarrowia lipolytica is an oleaginous yeast exhibiting robust phenotypes beneficial for industrial biotechnology. The phenotypic diversity found within the undomesticated Y. lipolytica clade from various origins illuminates desirable phenotypic traits not found in the conventional laboratory strain CBS7504 (or W29), which include xylose utilization, lipid accumulation, and growth on undetoxified biomass hydrolysates. Currently, the related phenotypes of lipid accumulation and degradation when metabolizing nonpreferred sugars (e.g., xylose) associated with biomass hydrolysates are poorly understood, making it difficult to control and engineer in Y. lipolytica. To fill this knowledge gap, we analyzed the genetic diversity of five undomesticated Y. lipolytica strains and identified singleton genes and genes exclusively shared by strains exhibiting desirable phenotypes. Strain characterizations from controlled bioreactor cultures revealed that the undomesticated strain YB420 used xylose to support cell growth and maintained high lipid levels, while the conventional strain CBS7504 degraded cell biomass and lipids when xylose was the sole remaining carbon source. From proteomic analysis, we identified carbohydrate transporters, xylose metabolic enzymes, and pentose phosphate pathway proteins stimulated during the xylose uptake stage for both strains. Furthermore, we distinguished proteins involved in lipid metabolism (e.g., lipase, NADPH generation, lipid regulators, and ß-oxidation) activated by YB420 (lipid maintenance phenotype) or CBS7504 (lipid degradation phenotype) when xylose was the sole remaining carbon source. Overall, the results relate genetic diversity of undomesticated Y. lipolytica strains to complex phenotypes of superior growth, sugar utilization, lipid accumulation, and degradation in biomass hydrolysates. IMPORTANCE Yarrowia lipolytica is an important industrial oleaginous yeast due to its robust phenotypes for effective conversion of inhibitory lignocellulosic biomass hydrolysates into neutral lipids. While lipid accumulation has been well characterized in this organism, its interconnected lipid degradation phenotype is poorly understood during fermentation of biomass hydrolysates. Our investigation into the genetic diversity of undomesticated Y. lipolytica strains, coupled with detailed strain characterization and proteomic analysis, revealed metabolic processes and regulatory elements conferring desirable phenotypes for growth, sugar utilization, and lipid accumulation in undetoxified biomass hydrolysates by these natural variants. This study provides a better understanding of the robust metabolism of Y. lipolytica and suggests potential metabolic engineering strategies to enhance its performance.

Computational design and analysis of modular cells for large libraries of exchangeable product synthesis modules.

Microbial metabolism can be harnessed to produce a large library of useful chemicals from renewable resources such as plant biomass. However, it is laborious and expensive to create microbial biocatalysts to produce each new product. To tackle this challenge, we have recently developed modular cell (ModCell) design principles that enable rapid generation of production strains by assembling a modular (chassis) cell with exchangeable production modules to achieve overproduction of target molecules. Previous computational ModCell design methods are limited to analyze small libraries of around 20 products. In this study, we developed a new computational method, named ModCell-HPC, that can design modular cells for large libraries with hundreds of products with a highly-parallel and multi-objective evolutionary algorithm and enable us to elucidate modular design properties. We demonstrated ModCell-HPC to design Escherichia coli modular cells towards a library of 161 endogenous production modules. From these simulations, we identified E. coli modular cells with few genetic manipulations that can produce dozens of molecules in a growth-coupled manner with different types of fermentable sugars. These designs revealed key genetic manipulations at the chassis and module levels to accomplish versatile modular cells, involving not only in the removal of major by-products but also modification of branch points in the central metabolism. We further found that the effect of various sugar degradation on redox metabolism results in lower compatibility between a modular cell and production modules for growth on pentoses than hexoses. To better characterize the degree of compatibility, we developed a method to calculate the minimal set cover, identifying that only three modular cells are all needed to couple with all compatible production modules. By determining the unknown compatibility contribution metric, we further elucidated the design features that allow an existing modular cell to be re-purposed towards production of new molecules. Overall, ModCell-HPC is a useful tool for understanding modularity of biological systems and guiding more efficient and generalizable design of modular cells that help reduce research and development cost in biocatalysis.

Identification and characterization of proteins of unknown function (PUFs) in Clostridium thermocellum DSM 1313 strains as potential genetic engineering targets.

BACKGROUND: Mass spectrometry-based proteomics can identify and quantify thousands of proteins from individual microbial species, but a significant percentage of these proteins are unannotated and hence classified as proteins of unknown function (PUFs). Due to the difficulty in extracting meaningful metabolic information, PUFs are often overlooked or discarded during data analysis, even though they might be critically important in functional activities, in particular for metabolic engineering research. RESULTS: We optimized and employed a pipeline integrating various "guilt-by-association" (GBA) metrics, including differential expression and co-expression analyses of high-throughput mass spectrometry proteome data and phylogenetic coevolution analysis, and sequence homology-based approaches to determine putative functions for PUFs in Clostridium thermocellum. Our various analyses provided putative functional information for over 95% of the PUFs detected by mass spectrometry in a wild-type and/or an engineered strain of C. thermocellum. In particular, we validated a predicted acyltransferase PUF (WP_003519433.1) with functional activity towards 2-phenylethyl alcohol, consistent with our GBA and sequence homology-based predictions. CONCLUSIONS: This work demonstrates the value of leveraging sequence homology-based annotations with empirical evidence based on the concept of GBA to broadly predict putative functions for PUFs, opening avenues to further interrogation via targeted experiments.

Engineering promiscuity of chloramphenicol acetyltransferase for microbial designer ester biosynthesis.

Robust and efficient enzymes are essential modules for metabolic engineering and synthetic biology strategies across biological systems to engineer whole-cell biocatalysts. By condensing an acyl-CoA and an alcohol, alcohol acyltransferases (AATs) can serve as interchangeable metabolic modules for microbial biosynthesis of a diverse class of ester molecules with broad applications as flavors, fragrances, solvents, and drop-in biofuels. However, the current lack of robust and efficient AATs significantly limits their compatibility with heterologous precursor pathways and microbial hosts. Through bioprospecting and rational protein engineering, we identified and engineered promiscuity of chloramphenicol acetyltransferases (CATs) from mesophilic prokaryotes to function as robust and efficient AATs compatible with at least 21 alcohol and 8 acyl-CoA substrates for microbial biosynthesis of linear, branched, saturated, unsaturated and/or aromatic esters. By plugging the best engineered CAT (CATec3 Y20F) into the gram-negative mesophilic bacterium Escherichia coli, we demonstrated that the recombinant strain could effectively convert various alcohols into desirable esters, for instance, achieving a titer of 13.9 g/L isoamyl acetate with 95% conversion by fed-batch fermentation. The recombinant E. coli was also capable of simulating the ester profile of roses with high conversion (>97%) and titer (>1 g/L) from fermentable sugars at 37 °C. Likewise, a recombinant gram-positive, cellulolytic, thermophilic bacterium Clostridium thermocellum harboring CATec3 Y20F could produce many of these esters from recalcitrant cellulosic biomass at elevated temperatures (>50 °C) due to the engineered enzyme's remarkable thermostability. Overall, the engineered CATs can serve as a robust and efficient platform for designer ester biosynthesis from renewable and sustainable feedstocks.

Methods to Activate and Elucidate Complex Endogenous Sugar Metabolism in Yarrowia lipolytica.

Yarrowia lipolytica has endogenous metabolism to use complex sugars derived from lignocellulosic biomass. However, many of these pathways are cryptic and hence either inactive or inefficient for xylose, arabinose, and cellobiose assimilation. Here we present collective methods to activate and elucidate these endogenous sugar pathways by performing short-term growth adaptation, determining the pathway efficiency, and conducting transcriptomic, enzymatic, and metabolic analyses to identify rate limiting steps for enhanced sugar consumption.

Development of a Genome-Scale Metabolic Model of Clostridium thermocellum and Its Applications for Integration of Multi-Omics Datasets and Computational Strain Design.

Solving environmental and social challenges such as climate change requires a shift from our current non-renewable manufacturing model to a sustainable bioeconomy. To lower carbon emissions in the production of fuels and chemicals, plant biomass feedstocks can replace petroleum using microorganisms as biocatalysts. The anaerobic thermophile Clostridium thermocellum is a promising bacterium for bioconversion due to its capability to efficiently degrade lignocellulosic biomass. However, the complex metabolism of C. thermocellum is not fully understood, hindering metabolic engineering to achieve high titers, rates, and yields of targeted molecules. In this study, we developed an updated genome-scale metabolic model of C. thermocellum that accounts for recent metabolic findings, has improved prediction accuracy, and is standard-conformant to ensure easy reproducibility. We illustrated two applications of the developed model. We first formulated a multi-omics integration protocol and used it to understand redox metabolism and potential bottlenecks in biofuel (e.g., ethanol) production in C. thermocellum. Second, we used the metabolic model to design modular cells for efficient production of alcohols and esters with broad applications as flavors, fragrances, solvents, and fuels. The proposed designs not only feature intuitive push-and-pull metabolic engineering strategies, but also present novel manipulations around important central metabolic branch-points. We anticipate the developed genome-scale metabolic model will provide a useful tool for system analysis of C. thermocellum metabolism to fundamentally understand its physiology and guide metabolic engineering strategies to rapidly generate modular production strains for effective biosynthesis of biofuels and biochemicals from lignocellulosic biomass.

Harnessing Natural Modularity of Metabolism with Goal Attainment Optimization to Design a Modular Chassis Cell for Production of Diverse Chemicals.

Modular design is key to achieve efficient and robust systems across engineering disciplines. Modular design potentially offers advantages to engineer microbial systems for biocatalysis, bioremediation, and biosensing, overcoming the slow and costly design-build-test-learn cycles in the conventional cell engineering approach. These systems consist of a modular (chassis) cell compatible with exchangeable modules that enable programmed functions such as overproduction of a desirable chemical. We previously proposed a multiobjective optimization framework coupled with metabolic flux models to design modular cells and solved it using multiobjective evolutionary algorithms. However, such approach might not achieve solution optimality and hence limits design options for experimental implementation. In this study, we developed the goal attainment formulation compatible with optimization algorithms that guarantee solution optimality. We applied goal attainment to design an Escherichia coli modular cell capable of synthesizing all molecules in a biochemically diverse library at high yields and rates with only a few genetic manipulations. To elucidate modular organization of the designed cells, we developed a flux variance clustering (FVC) method by identifying reactions with high flux variance and clustering them to identify metabolic modules. Using FVC, we identified reaction usage patterns for different modules in the modular cell, revealing that its broad pathway compatibility is enabled by the natural modularity and flexible flux capacity of endogenous core metabolism. Overall, this study not only sheds light on modularity in metabolic networks from their topology and metabolic functions but also presents a useful synthetic biology toolbox to design modular cells with broad applications.

Endogenous carbohydrate esterases of Clostridium thermocellum are identified and disrupted for enhanced isobutyl acetate production from cellulose.

Medium-chain esters are versatile chemicals with broad applications as flavors, fragrances, solvents, and potential drop-in biofuels. Currently, these esters are largely produced by the conventional chemical process that uses harsh operating conditions and requires high energy input. Alternatively, the microbial conversion route has recently emerged as a promising platform for sustainable and renewable ester production. The ester biosynthesis pathways can utilize either lipases or alcohol acyltransferase (AAT), but the AAT-dependent pathway is more thermodynamically favorable in an aqueous fermentation environment. Even though a cellulolytic thermophile Clostridium thermocellum harboring an AAT-dependent pathway has recently been engineered for direct conversion of lignocellulosic biomass into esters, the production is not efficient. One potential bottleneck is the ester degradation caused by the endogenous carbohydrate esterases (CEs) whose functional roles are poorly understood. The challenge is to identify and disrupt CEs that can alleviate ester degradation while not negatively affecting the efficient and robust capability of C. thermocellum for lignocellulosic biomass deconstruction. In this study, by using bioinformatics, comparative genomics, and enzymatic analysis to screen a library of CEs, we identified and disrupted the two most critical CEs, Clo1313_0613 and Clo1313_0693, that significantly contribute to isobutyl acetate degradation in C. thermocellum. We demonstrated that an engineered esterase-deficient C. thermocellum strain not only reduced ester hydrolysis but also improved isobutyl acetate production while maintaining effective cellulose assimilation.

Draft Genome Assemblies of Ionic Liquid-Resistant Yarrowia lipolytica PO1f and Its Superior Evolved Strain, YlCW001.

Adaptive laboratory evolution of Yarrowia lipolytica PO1f in the benchmark ionic liquid (IL; 1-ethyl-3-methylimidazolium acetate) produced a superior IL-tolerant microorganism, strain YlCW001. Here, we report the genome sequences of PO1f and YlCW001 to study the robustness of Y. lipolytica and its potential use as a microbial platform for producing fuels and chemicals.

Towards renewable flavors, fragrances, and beyond.

Esters constitute a large space of unique molecules with broad range of applications as flavors, fragrances, pharmaceuticals, cosmetics, green solvents, and advanced biofuels. Global demand of natural esters in food, household cleaner, personal care, and perfume industries is increasing while the ester supply from natural sources has been limited. Development of novel microbial cell factories for ester production from renewable feedstocks can potentially provide an alternative and sustainable source of natural esters and hence help fulfill growing demand. Here, we highlight recent advances in microbial production of esters and provide perspectives for improving its economic feasibility. As the field matures, microbial ester production platforms will enable renewable and sustainable production of flavors and fragrances, and open new market opportunities beyond what nature can offer.

Plant Biosystems Design Research Roadmap 1.0.

Human life intimately depends on plants for food, biomaterials, health, energy, and a sustainable environment. Various plants have been genetically improved mostly through breeding, along with limited modification via genetic engineering, yet they are still not able to meet the ever-increasing needs, in terms of both quantity and quality, resulting from the rapid increase in world population and expected standards of living. A step change that may address these challenges would be to expand the potential of plants using biosystems design approaches. This represents a shift in plant science research from relatively simple trial-and-error approaches to innovative strategies based on predictive models of biological systems. Plant biosystems design seeks to accelerate plant genetic improvement using genome editing and genetic circuit engineering or create novel plant systems through de novo synthesis of plant genomes. From this perspective, we present a comprehensive roadmap of plant biosystems design covering theories, principles, and technical methods, along with potential applications in basic and applied plant biology research. We highlight current challenges, future opportunities, and research priorities, along with a framework for international collaboration, towards rapid advancement of this emerging interdisciplinary area of research. Finally, we discuss the importance of social responsibility in utilizing plant biosystems design and suggest strategies for improving public perception, trust, and acceptance.