Search

Abstract Filamentous fungi are critical in the transition to a more sustainable food system. While genetic modification of these organisms has promise for enhancing the nutritional value, sensory appeal, and scalability of fungal foods, genetic tools and demonstrated use cases for bioengineered food production by edible strains are lacking. Here, we develop a modular synthetic biology toolkit for Aspergillus oryzae, an edible fungus used in fermented foods, protein production, and meat alternatives. Our toolkit includes a CRISPR-Cas9 method for gene integration, neutral loci, and tunable promoters. We use these tools to elevate intracellular levels of the nutraceutical ergothioneine and the flavor-and color molecule heme in the edible biomass. The strain overproducing heme is red in color and is readily formulated into imitation meat patties with minimal processing. These findings highlight the promise of synthetic biology to enhance fungal foods and provide useful genetic tools for applications in food production and beyond.

Abstract Prediction of enzyme kinetic parameters is essential for designing and optimizing enzymes for various biotechnological and industrial applications, but the limited performance of current prediction tools on diverse tasks hinders their practical applications. Here, we introduce UniKP, a unified framework based on pretrained language models for the prediction of enzyme kinetic parameters, including enzyme turnover number (k cat), Michaelis constant (K m), and catalytic efficiency (k cat / K m), from protein sequences and substrate structures. A two-layer framework derived from UniKP (EF-UniKP) has also been proposed to allow robust k cat prediction in considering environmental factors, including pH and temperature. In addition, four representative re-weighting methods are systematically explored to successfully reduce the prediction error in high-value prediction tasks. We have demonstrated the application of UniKP and EF-UniKP in several enzyme discovery and directed evolution tasks, leading to the identification of new enzymes and enzyme mutants with higher activity. UniKP is a valuable tool for deciphering the mechanisms of enzyme kinetics and enables novel insights into enzyme engineering and their industrial applications.

Abstract The evolution of pathway enzymes enhances the biosynthesis of high‐value chemicals, crucial for pharmaceutical, and agrochemical applications. However, unpredictable evolutionary landscapes of pathway genes often hinder successful evolution. Here, the presence of complex epistasis is identifued within the representative naringenin biosynthetic pathway enzymes, hampering straightforward directed evolution. Subsequently, a biofoundry‐assisted strategy is developed for pathway bottlenecking and debottlenecking, enabling the parallel evolution of all pathway enzymes along a predictable evolutionary trajectory in six weeks. This study then utilizes a machine learning model, ProEnsemble, to further balance the pathway by optimizing the transcription of individual genes. The broad applicability of this strategy is demonstrated by constructing an Escherichia coli chassis with evolved and balanced pathway genes, resulting in 3.65 g L−1 naringenin. The optimized naringenin chassis also demonstrates enhanced production of other flavonoids. This approach can be readily adapted for any given number of enzymes in the specific metabolic pathway, paving the way for automated chassis construction in contemporary biofoundries.

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub.

Abstract Methyl jasmonate (MeJA) is a known elicitor of plant specialized metabolism, including triterpenoid saponins. Saponaria vaccaria is an annual herb used in traditional Chinese medicine, containing large quantities of oleanane-type triterpenoid saponins with anticancer properties and structural similarities to the vaccine adjuvant QS-21. Leveraging the MeJA-elicited saponin biosynthesis, we identify multiple enzymes catalyzing the oxidation and glycosylation of triterpenoids in S. vaccaria. This exploration is aided by Pacbio full-length transcriptome sequencing and gene expression analysis. A cellulose synthase-like enzyme can not only glucuronidate triterpenoid aglycones but also alter the product profile of a cytochrome P450 monooxygenase via preference for the aldehyde intermediate. Furthermore, the discovery of a UDP-glucose 4,6-dehydratase and a UDP-4-keto-6-deoxy-glucose reductase reveals the biosynthetic pathway for the rare nucleotide sugar UDP-d-fucose, a likely sugar donor for fucosylation of plant natural products. Our work enables the production and optimization of high-value saponins in microorganisms and plants through synthetic biology approaches.

Abstract Type I modular polyketide synthases (PKSs) are multi-domain enzymes functioning like assembly lines. Many engineering attempts have been made for the last three decades to replace, delete and insert new functional domains into PKSs to produce novel molecules. However, inserting heterologous domains often destabilize PKSs, causing loss of activity and protein misfolding. To address this challenge, here we develop a fluorescence-based solubility biosensor that can quickly identify engineered PKSs variants with minimal structural disruptions. Using this biosensor, we screen a library of acyltransferase (AT)-exchanged PKS hybrids with randomly assigned domain boundaries, and we identify variants that maintain wild type production levels. We then probe each position in the AT linker region to determine how domain boundaries influence structural integrity and identify a set of optimized domain boundaries. Overall, we have successfully developed an experimentally validated, high-throughput method for making hybrid PKSs that produce novel molecules.

Foldy is a cloud-based application that allows non-computational biologists to easily utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. With many deployment options, it can be employed by individuals, labs, universities, and companies in the cloud without requiring hardware resources, but it can also be configured to utilize locally available computers. Foldy enables scientists to predict the structure of proteins and complexes up to 6000 amino acids with AlphaFold, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock. In our manuscript, we detail Foldy's interface design, deployment strategies, and optimization for various user scenarios. We demonstrate its application through case studies including rational enzyme design and analyzing proteins with domains of unknown function. Furthermore, we compare Foldy's interface and management capabilities with other open and closed source tools in the field, illustrating its practicality in managing complex data and computation tasks. Our manuscript underlines the benefits of Foldy as a day-to-day tool for life science researchers, and shows how Foldy can make modern tools more accessible and efficient.

ABSTRACTThis report presents multi-genome evidence that REC protein family expansion occurs when the emergence of new pathways gives rise to functional discordance. Specificity between residues in REC domain containing response regulators with paired histidine kinases is under negative purifying selection, constrained by the presence of other bacterial two-component systems signaling cascades that share sequence and structural identity. Presuming that the two-component systems can evolve by neutral amino acid changes (neutral drift) when purifying evolutionary constraints are relaxed, how might the REC protein family expand by amino acid changes when these constraints remain intact? Using an unsupervised machine learning approach to observe the sequence landscape of REC domains across long phylogenetic distances, we find that within-gene recombination, a subcategory of gene conversion, switched the effector domain and, consequently, the regulatory context of a duplicated response regulator from transcriptional regulation by σ54 to that by σ70. We determined that the recombined response regulator diverged from its parent by episodic diversifying selection and neutral drift. Functional experiments of the parent of recombined response regulators in a model Pseudomonas putida KT2440 model system revealed that the parent and recombined response regulators sense and respond to different carboxylic acids. Finally, a residue-switching experiment using structural predictions and functional characterization suggests that the new residues in the recombined regulator could form a new interaction interface and mediate condition-specific phosphotransfer. Overall, our study finds that genetic perturbations can create conditions of functional discordance, whereby the REC protein family can evolve by episodic diversifying selection.IMPORTANCEWe explore when and why large classes of proteins expand into new sequence space. We used an unsupervised machine learning approach to observe the sequence landscape of REC domains of bacterial response regulator proteins. We find that within-gene recombination can switch effector domains and, consequently, change the regulatory context of the duplicated protein.

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.

Summary: Maximizing the production of heterologous biomolecules is a complex problem that can be addressed with a systems-level understanding of cellular metabolism and regulation. Specifically, growth-coupling approaches can increase product titers and yields and also enhance production rates. However, implementing these methods for non-canonical carbon streams is challenging due to gaps in metabolic models. Over four design-build-test-learn cycles, we rewire Pseudomonas putida KT2440 for growth-coupled production of indigoidine from para-coumarate. We explore 4,114 potential growth-coupling solutions and refine one design through laboratory evolution and ensemble data-driven methods. The final growth-coupled strain produces 7.3 g/L indigoidine at 77% maximum theoretical yield in para-coumarate minimal medium. The iterative use of growth-coupling designs and functional genomics with experimental validation was highly effective and agnostic to specific hosts, carbon streams, and final products and thus generalizable across many systems.

Pseudomonas putida has been engineered to produce medium chain length oleochemicals, including medium chain length free fatty acids and their ester forms, compounds which may be useful as biodiesel blending agents.

Abstract Background Rhodosporidium toruloides is capable of co-utilization of complex carbon sources and robust growth from lignocellulosic hydrolysates. This oleaginous yeast is therefore an attractive host for heterologous production of valuable bioproducts at high titers from low-cost, deconstructed biomass in an economically and environmentally sustainable manner. Here we demonstrate this by engineering R. toruloides to produce the polyketide triacetic acid lactone (TAL) directly from unfiltered hydrolysate deconstructed from biomass with minimal unit process operations. Results Introduction of the 2-pyrone synthase gene into R. toruloides enabled the organism to produce 2.4 g/L TAL from simple media or 2.0 g/L from hydrolysate produced from sorghum biomass. Both of these titers are on par with titers from other better-studied microbial hosts after they had been heavily engineered. We next demonstrate that filtered hydrolysates produced from ensiled sorghum are superior to those derived from dried sorghum for TAL production, likely due to the substantial organic acids produced during ensiling. We also demonstrate that the organic acids found in ensiled biomass can be used for direct synthesis of ionic liquids within the biomass pretreatment process, enabling consolidation of unit operations of in-situ ionic liquid synthesis, pretreatment, saccharification, and fermentation into a one-pot, separations-free process. Finally, we demonstrate this consolidation in a 2 L bioreactor using unfiltered hydrolysate, producing 3.9 g/L TAL. Conclusion Many steps involved in deconstructing biomass into fermentable substrate can be combined into a distinct operation, and directly fed to cultures of engineered R. toruloides cultures for subsequent valorization into gram per liter titers of TAL in a cost-effective manner.

ABSTRACT Agrobacteria are a diverse, polyphyletic group of prokaryotes with multipartite genomes capable of transferring DNA into the genomes of host plants, making them an essential tool in plant biotechnology. Despite their utility in plant transformation, genome-wide transcriptional regulation is not well understood across the three main lineages of agrobacteria. Transcription start sites (TSSs) are a necessary component of gene expression and regulation. In this study, we used differential RNA-seq and a TSS identification algorithm optimized on manually annotated TSS, then validated with existing TSS to identify thousands of TSS with nucleotide resolution for representatives of each lineage. We extend upon the 356 TSSs previously reported in Agrobacterium fabrum C58 by identifying 1,916 TSSs. In addition, we completed genomes and phenotyping of Rhizobium rhizogenes C16/80 and Allorhizobium vitis T60/94, identifying 2,650 and 2,432 TSSs, respectively. Parameter optimization was crucial for an accurate, high-resolution view of genome and transcriptional dynamics, highlighting the importance of algorithm optimization in genome-wide TSS identification and genomics at large. The optimized algorithm reduced the number of TSSs identified internal and antisense to the coding sequence on average by 90.5% and 91.9%, respectively. Comparison of TSS conservation between orthologs of the three lineages revealed differences in cell cycle regulation of ctrA as well as divergence of transcriptional regulation of chemotaxis-related genes when grown in conditions that simulate the plant environment. These results provide a framework to elucidate the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. IMPORTANCE Transcription start sites (TSSs) are fundamental for understanding gene expression and regulation. Agrobacteria, a group of prokaryotes with the ability to transfer DNA into the genomes of host plants, are widely used in plant biotechnology. However, the genome-wide transcriptional regulation of agrobacteria is not well understood, especially in less-studied lineages. Differential RNA-seq and an optimized algorithm enabled identification of thousands of TSSs with nucleotide resolution for representatives of each lineage. The results of this study provide a framework for elucidating the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. The optimized algorithm also highlights the importance of parameter optimization in genome-wide TSS identification and genomics at large.

ABSTRACT The pGinger suite of expression plasmids comprises 43 plasmids that will enable precise constitutive and inducible gene expression in a wide range of Gram-negative bacterial species. Constitutive vectors are composed of 16 synthetic constitutive promoters upstream of red fluorescent protein (RFP), with a broad-host-range BBR1 origin and a kanamycin resistance marker. The family also has seven inducible systems (Jungle Express, Psal/NahR, Pm/XylS, Prha/RhaS, LacO1/LacI, LacUV5/LacI, and Ptet/TetR) controlling RFP expression on BBR1/kanamycin plasmid backbones. For four of these inducible systems (Jungle Express, Psal/NahR, LacO1/LacI, and Ptet/TetR), we created variants that utilize the RK2 origin and spectinomycin or gentamicin selection. Relevant RFP expression and growth data have been collected in the model bacterium Escherichia coli as well as Pseudomonas putida. All pGinger vectors are available via the Joint BioEnergy Institute (JBEI) Public Registry. IMPORTANCE Metabolic engineering and synthetic biology are predicated on the precise control of gene expression. As synthetic biology expands beyond model organisms, more tools will be required that function robustly in a wide range of bacterial hosts. The pGinger family of plasmids constitutes 43 plasmids that will enable both constitutive and inducible gene expression in a wide range of nonmodel Proteobacteria.

Summary: Polycyclopropanated (POP) compounds show promise as fuels as their energy density can be greater than jet and rocket fuels in current use, but realizing their full potential requires significant development. This protocol guides the production of polycyclopropanated fatty acids in Streptomyces; POP production in another host remains to be demonstrated. This method can serve as a baseline for further development of POP as well as other polyketide products.For complete details on the use and execution of this protocol, please refer to Cruz-Morales et al. (2022).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

The synthetic biology toolkit for baker's yeast, Saccharomyces cerevisiae, includes extensive genome engineering toolkits and parts repositories. However, with the increasing complexity of engineering tasks and versatile applications of this model eukaryote, there is a continued interest to expand and diversify the rational engineering capabilities in this chassis by FAIR (findable, accessible, interoperable, and reproducible) compliance. In this study, we designed and characterised 41 synthetic guide RNA sequences to expand the CRISPR-based genome engineering capabilities for easy and efficient replacement of genomically encoded elements. Moreover, we characterize in high temporal resolution 20 native promoters and 18 terminators using fluorescein and LUDOX CL-X as references for GFP expression and OD600 measurements, respectively. Additionally, all data and reported analysis is provided in a publicly accessible jupyter notebook providing a tool for researchers with low-coding skills to further explore the generated data as well as a template for researchers to write their own scripts. We expect the data, parts, and databases associated with this study to support a FAIR-compliant resource for further advancing the engineering of yeasts.

Abstract In nature, biological compartments such as cells rely on dynamically controlled permeability for matter exchange and complex cellular activities. Likewise, the ability to engineer compartment permeability is crucial for in vitro systems to gain sustainability, robustness, and complexity. However, rendering in vitro compartments such a capability is challenging. Here, a facile strategy is presented to build permeability‐configurable compartments, and marked advantages of such compartmentalization are shown in reconstituting sustained synthetic biology systems in vitro. Through microfluidics, the strategy produces micrometer‐sized layered microgels whose shell layer serves as a sieving structure for biomolecules and particles. In this configuration, the transport of DNAs, proteins, and bacteriophages across the compartments can be controlled an guided by a physical model. Through permeability engineering, a compartmentalized cell‐free protein synthesis system sustains multicycle protein production; ≈100 000 compartments are repeatedly used in a five‐cycle synthesis, featuring a yield of 2.2 mg mL−1. Further, the engineered bacteria‐enclosing compartments possess near‐perfect phage resistance and enhanced environmental fitness. In a complex river silt environment, compartmentalized whole‐cell biosensors show maintained activity throughout the 32 h pollutant monitoring. It is anticipated that permeability‐engineered compartmentalization should pave the way for practical synthetic biology applications such as green bioproduction, environmental sensing, and bacteria‐based therapeutics.

Summary Directed evolution is a powerful method to optimize proteins and metabolic reactions towards user‐defined goals. It usually involves subjecting genes or pathways to iterative rounds of mutagenesis, selection and amplification. While powerful, systematic searches through large sequence‐spaces is a labour‐intensive task, and can be further limited by a priori knowledge about the optimal initial search space, and/or limits in terms of screening throughput. Here, we demonstrate an integrated directed evolution workflow for metabolic pathway enzymes that continuously generate enzyme variants using the recently developed orthogonal replication system, OrthoRep and screens for optimal performance in high‐throughput using a transcription factor‐based biosensor. We demonstrate the strengths of this workflow by evolving a rate‐limiting enzymatic reaction of the biosynthetic pathway for cis,cis‐muconic acid (CCM), a precursor used for bioplastic and coatings, in Saccharomyces cerevisiae. After two weeks of simply iterating between passaging of cells to generate variant enzymes via OrthoRep and high‐throughput sorting of best‐performing variants using a transcription factor‐based biosensor for CCM, we ultimately identified variant enzymes improving CCM titers > 13‐fold compared with reference enzymes. Taken together, the combination of synthetic biology tools as adopted in this study is an efficient approach to debottleneck repetitive workflows associated with directed evolution of metabolic enzymes.

Abstract Background Saccharomyces cerevisiae is an important synthetic biology chassis for microbial production of valuable molecules. Promoter engineering has been frequently applied to generate more synthetic promoters with a variety of defined characteristics in order to achieve a well-regulated genetic network for high production efficiency. Galactose-inducible (GAL) expression systems, composed of GAL promoters and multiple GAL regulators, have been widely used for protein overexpression and pathway construction in S. cerevisiae. However, the function of each element in synthetic promoters and how they interact with GAL regulators are not well known. Results Here, a library of synthetic GAL promoters demonstrate that upstream activating sequences (UASs) and core promoters have a synergistic relationship that determines the performance of each promoter under different carbon sources. We found that the strengths of synthetic GAL promoters could be fine-tuned by manipulating the sequence, number, and substitution of UASs. Core promoter replacement generated synthetic promoters with a twofold strength improvement compared with the GAL1 promoter under multiple different carbon sources in a strain with GAL1 and GAL80 engineering. These results represent an expansion of the classic GAL expression system with an increased dynamic range and a good tolerance of different carbon sources. Conclusions In this study, the effect of each element on synthetic GAL promoters has been evaluated and a series of well-controlled synthetic promoters are constructed. By studying the interaction of synthetic promoters and GAL regulators, synthetic promoters with an increased dynamic range under different carbon sources are created.

Abstract Background Cost-effective production of the highly effective anti-cancer drug, paclitaxel (Taxol®), remains limited despite growing global demands. Low yields of the critical taxadiene precursor remains a key bottleneck in microbial production. In this study, the key challenge of poor taxadiene synthase (TASY) solubility in S. cerevisiae was revealed, and the strains were strategically engineered to relieve this bottleneck. Results Multi-copy chromosomal integration of TASY harbouring a selection of fusion solubility tags improved taxadiene titres 22-fold, up to 57 ± 3 mg/L at 30 °C at microscale, compared to expressing a single episomal copy of TASY. The scalability of the process was highlighted through achieving similar titres during scale up to 25 mL and 250 mL in shake flask and bioreactor cultivations, respectively at 20 and 30 °C. Maximum taxadiene titres of 129 ± 15 mg/L and 127 mg/L were achieved through shake flask and bioreactor cultivations, respectively, of the optimal strain at a reduced temperature of 20 °C. Conclusions The results of this study highlight the benefit of employing a combination of molecular biology and bioprocess tools during synthetic pathway development, with which TASY activity was successfully improved by 6.5-fold compared to the highest literature titre in S. cerevisiae cell factories.

The trade-off between growth and production affects the application of engineered microbes. Here, the authors take the minimal cut set approach to predict metabolic reactions for elimination to couple metabolite production strongly with growth and achieve high production of indigoidine in Pseudomonas putida.

In metabolic engineering, mechanistic models require prior metabolism knowledge of the chassis strain, whereas machine learning models need ample training data. Here, the authors combine the mechanistic and machine learning models to improve prediction performance of tryptophan metabolism in baker’s yeast.

Abstract Background Despite the latest advancements in metabolic engineering for genome editing and characterization of host performance, the successful development of robust cell factories used for industrial bioprocesses and accurate prediction of the behavior of microbial systems, especially when shifting from laboratory-scale to industrial conditions, remains challenging. To increase the probability of success of a scale-up process, data obtained from thoroughly performed studies mirroring cellular responses to typical large-scale stimuli may be used to derive crucial information to better understand potential implications of large-scale cultivation on strain performance. This study assesses the feasibility to employ a barcoded yeast deletion library to assess genome-wide strain fitness across a simulated industrial fermentation regime and aims to understand the genetic basis of changes in strain physiology during industrial fermentation, and the corresponding roles these genes play in strain performance. Results We find that mutant population diversity is maintained through multiple seed trains, enabling large scale fermentation selective pressures to act upon the community. We identify specific deletion mutants that were enriched in all processes tested in this study, independent of the cultivation conditions, which include MCK1, RIM11, MRK1, and YGK3 that all encode homologues of mammalian glycogen synthase kinase 3 (GSK-3). Ecological analysis of beta diversity between all samples revealed significant population divergence over time and showed feed specific consequences of population structure. Further, we show that significant changes in the population diversity during fed-batch cultivations reflect the presence of significant stresses. Our observations indicate that, for this yeast deletion collection, the selection of the feeding scheme which affects the accumulation of the fermentative by-product ethanol impacts the diversity of the mutant pool to a higher degree as compared to the pH of the culture broth. The mutants that were lost during the time of most extreme population selection suggest that specific biological processes may be required to cope with these specific stresses. Conclusions Our results demonstrate the feasibility of Bar-seq to assess fermentation associated stresses in yeast populations under industrial conditions and to understand critical stages of a scale-up process where variability emerges, and selection pressure gets imposed. Overall our work highlights a promising avenue to identify genetic loci and biological stress responses required for fitness under industrial conditions.

Hydroxyglutarate synthase (HglS) converts 2-oxoadipate to D-2- hydroxyglutarate during lysine catabolism in bacteria. Here the authors use structural and biochemical approaches to show that HglS acts via successive decarboxylation and intramolecular hydroxylation and that homologous enzymes catalyze the final step of lysine catabolism in plants.

To accelerate the shift to bio-based production and overcome complicated functional implementation of natural and artificial biosynthetic pathways to industry relevant organisms, development of new, versatile, bio-based production platforms is required. Here we present a novel yeast-based platform for biosynthesis of bacterial aromatic polyketides. The platform is based on a synthetic polyketide synthase system enabling a first demonstration of bacterial aromatic polyketide biosynthesis in a eukaryotic host. Keywords: Natural products, Synthetic biology, Aromatic polyketides, CRISPR/Cas9, Polyketide, Production platform in eukaryotes, Metabolic engineering, Biotechnology

Despite tremendous efforts to fight cancer, it remains a major public health problem and a leading cause of death worldwide. With increased knowledge of cancer pathways and improved technological platforms, precision therapeutics that specifically target aberrant cancer pathways have improved patient outcomes. Nevertheless, a primary cause of unsuccessful cancer therapy remains cancer drug resistance. In this review, we summarize the broad classes of resistance to cancer therapy, particularly pharmacokinetics, the tumor microenvironment, and drug resistance mechanisms. Furthermore, we describe how bacterial-mediated cancer therapy, a bygone mode of treatment, has been revitalized by synthetic biology and is uniquely suited to address the primary resistance mechanisms that confound traditional therapies. Through genetic engineering, we discuss how bacteria can be potent anticancer agents given their tumor targeting potential, anti-tumor activity, safety, and coordinated delivery of anti-cancer drugs. Keywords: Cancer therapy, Synthetic biology, Drug resistance, Bacterial-mediated therapy

Following publication of the original article [1], the authors have noted that the standard curve in Additional file 1: Figure S7 is incorrect.

Biofoundries provide an integrated infrastructure to enable the rapid design, construction, and testing of genetically reprogrammed organisms for biotechnology applications and research. Many biofoundries are being built and a Global Biofoundry Alliance has recently been established to coordinate activities worldwide.

Abstract Background The physiological characterization of microorganisms provides valuable information for bioprocess development. Chemostat cultivations are a powerful tool for this purpose, as they allow defined changes to one single parameter at a time, which is most commonly the growth rate. The subsequent establishment of a steady state then permits constant variables enabling the acquisition of reproducible data sets for comparing microbial performance under different conditions. We performed physiological characterizations of a 3-hydroxypropionic acid (3-HP) producing Saccharomyces cerevisiae strain in a miniaturized and parallelized chemostat cultivation system. The physiological conditions under investigation were various growth rates controlled by different nutrient limitations (C, N, P). Based on the cultivation parameters obtained subsequent fed-batch cultivations were designed. Results We report technical advancements of a small-scale chemostat cultivation system and its applicability for reliable strain screening under different physiological conditions, i.e. varying dilution rates and different substrate limitations (C, N, P). Exploring the performance of an engineered 3-HP producing S. cerevisiae strain under carbon-limiting conditions revealed the highest 3-HP yields per substrate and biomass of 16.6 %C-mol and 0.43 g gCDW−1, respectively, at the lowest set dilution rate of 0.04 h−1. 3-HP production was further optimized by applying N- and P-limiting conditions, which resulted in a further increase in 3-HP yields revealing values of 21.1 %C-mol and 0.50 g gCDW−1 under phosphate-limiting conditions. The corresponding parameters favoring an increased 3-HP production, i.e. dilution rate as well as C- and P-limiting conditions, were transferred from the small-scale chemostat cultivation system to 1-L bench-top fermenters operating in fed-batch conditions, revealing 3-HP yields of 15.9 %C-mol and 0.45 g gCDW−1 under C-limiting, as well as 25.6 %C-mol and 0.50 g gCDW−1 under phosphate-limiting conditions. Conclusions Small-scale chemostat cultures are well suited for the physiological characterization of microorganisms, particularly for investigating the effect of changing cultivation parameters on microbial performance. In our study, optimal conditions for 3-HP production comprised (i) a low dilution rate of 0.04 h−1 under carbon-limiting conditions and (ii) the use of phosphate-limiting conditions. Similar 3-HP yields were achieved in chemostat and fed-batch cultures under both C- and P-limiting conditions proving the growth rate as robust parameter for process transfer and thus the small-scale chemostat system as powerful tool for process optimization.

Abstract Background Beyond pathway engineering, the metabolic state of the production host is critical in maintaining the efficiency of cellular production. The biotechnologically important yeast Saccharomyces cerevisiae adjusts its energy metabolism based on the availability of oxygen and carbon sources. This transition between respiratory and non-respiratory metabolic state is accompanied by substantial modifications of central carbon metabolism, which impact the efficiency of metabolic pathways and the corresponding final product titers. Non-ribosomal peptide synthetases (NRPS) are an important class of biocatalysts that provide access to a wide array of secondary metabolites. Indigoidine, a blue pigment, is a representative NRP that is valuable by itself as a renewably produced pigment. Results Saccharomyces cerevisiae was engineered to express a bacterial NRPS that converts glutamine to indigoidine. We characterize carbon source use and production dynamics, and demonstrate that indigoidine is solely produced during respiratory cell growth. Production of indigoidine is abolished during non-respiratory growth even under aerobic conditions. By promoting respiratory conditions via controlled feeding, we scaled the production to a 2 L bioreactor scale, reaching a maximum titer of 980 mg/L. Conclusions This study represents the first use of the Streptomyces lavendulae NRPS (BpsA) in a fungal host and its scale-up. The final product indigoidine is linked to the activity of the TCA cycle and serves as a reporter for the respiratory state of S. cerevisiae. Our approach can be broadly applied to investigate diversion of flux from central carbon metabolism for NRPS and other heterologous pathway engineering, or to follow a population switch between respiratory and non-respiratory modes.

Pseudomonas putida is a saprophytic bacterium with robust metabolisms and strong solvent tolerance making it an attractive host for metabolic engineering and bioremediation. Due to its diverse carbon metabolisms, its genome encodes an array of proteins and enzymes that can be readily applied to produce valuable products. In this work we sought to identify design principles and bottlenecks in the production of type III polyketide synthase (T3PKS)-derived compounds in P. putida. T3PKS products are widely used as nutraceuticals and medicines and often require aromatic starter units, such as coumaroyl-CoA, which is also an intermediate in the native coumarate catabolic pathway of P. putida. Using a randomly barcoded transposon mutant (RB-TnSeq) library, we assayed gene functions for a large portion of aromatic catabolism, confirmed known pathways, and proposed new annotations for two aromatic transporters. The 1,3,6,8-tetrahydroxynapthalene synthase of Streptomyces coelicolor (RppA), a microbial T3PKS, was then used to rapidly assay growth conditions for increased T3PKS product accumulation. The feruloyl/coumaroyl CoA synthetase (Fcs) of P. putida was used to supply coumaroyl-CoA for the curcuminoid synthase (CUS) of Oryza sativa, a plant T3PKS. We identified that accumulation of coumaroyl-CoA in this pathway results in extended growth lag times in P. putida. Deletion of the second step in coumarate catabolism, the enoyl-CoA hydratase-lyase (Ech), resulted in increased production of the type III polyketide bisdemethoxycurcumin.

Mutating natural enzymes is effective in broadening the substrate or product range, but generally leads to reduced titers. Here the authors engineer hybrid polyketide synthases for efficient production of short-chain ketones from plant biomass hydrolysates in Streptomyces, which can increase the octane of gasoline.

Abstract Background Aviation fuels are an important target of biofuels research due to their high market demand and competitive price. Isoprenoids have been demonstrated as good feedstocks for advanced renewable jet fuels with high energy density, high heat of combustion, and excellent cold-weather performance. In particular, sesquiterpene compounds (C15), such as farnesene and bisabolene, have been identified as promising jet fuel candidates. Results In this study, we explored three sesquiterpenes—epi-isozizaene, pentalenene and α-isocomene—as novel jet fuel precursors. We performed a computational analysis to calculate the energy of combustion of these sesquiterpenes and found that their specific energies are comparable to commercial jet fuel A-1. Through heterologous MVA pathway expression and promoter engineering, we produced 727.9 mg/L epi-isozizaene, 780.3 mg/L pentalenene and 77.5 mg/L α-isocomene in Escherichia coli and 344 mg/L pentalenene in Saccharomyces cerevisiae. We also introduced a dynamic autoinduction system using previously identified FPP-responsive promoters for inducer-free production and managed to achieve comparable amounts of each compound. Conclusion We produced tricyclic sesquiterpenes epi-isozizaene, pentalenene and α-isocomene, promising jet fuel feedstocks at high production titers, providing novel, sustainable alternatives to petroleum-based jet fuels.

Abstract Background Switchgrass (Panicum virgatum L.) is a promising bioenergy feedstock because it can be grown on marginal land and produces abundant biomass. Recalcitrance of the lignocellulosic components of the switchgrass cell wall to enzymatic degradation into simple sugars impedes efficient biofuel production. We previously demonstrated that overexpression of OsAT10, a BAHD acyltransferase gene, enhances saccharification efficiency in rice. Results Here we show that overexpression of the rice OsAT10 gene in switchgrass decreased the levels of cell wall-bound ferulic acid (FA) in green leaf tissues and to a lesser extent in senesced tissues, and significantly increased levels of cell wall-bound p-coumaric acid (p-CA) in green leaves but decreased its level in senesced tissues of the T0 plants under greenhouse conditions. The engineered switchgrass lines exhibit an approximate 40% increase in saccharification efficiency in green tissues and a 30% increase in senesced tissues. Conclusion Our study demonstrates that overexpression of OsAT10, a rice BAHD acyltransferase gene, enhances saccharification of lignocellulosic biomass in switchgrass.

Pseudomonas putida is a promising bacterial chassis for metabolic engineering given its ability to metabolize a wide array of carbon sources, especially aromatic compounds derived from lignin. However, this omnivorous metabolism can also be a hindrance when it can naturally metabolize products produced from engineered pathways. Herein we show that P. putida is able to use valerolactam as a sole carbon source, as well as degrade caprolactam. Lactams represent important nylon precursors, and are produced in quantities exceeding one million tons per year (Zhang et al., 2017). To better understand this metabolism we use a combination of Random Barcode Transposon Sequencing (RB-TnSeq) and shotgun proteomics to identify the oplBA locus as the likely responsible amide hydrolase that initiates valerolactam catabolism. Deletion of the oplBA genes prevented P. putida from growing on valerolactam, prevented the degradation of valerolactam in rich media, and dramatically reduced caprolactam degradation under the same conditions. Deletion of oplBA, as well as pathways that compete for precursors L-lysine or 5-aminovalerate, increased the titer of valerolactam from undetectable after 48 h of production to ~90 mg/L. This work may serve as a template to rapidly eliminate undesirable metabolism in non-model hosts in future metabolic engineering efforts.

The unicellular heterotrophic thraustochytrids are attractive candidates for commercial polyunsaturated fatty acids (PUFA) production. However, the reactive oxygen species (ROS) generated in their aerobic fermentation process often limits their PUFA titer. Yet, the specific mechanisms of ROS involvement in the crosstalk between oxidative stress and intracellular lipid synthesis remain poorly described. Metabolic engineering to improve the PUFA yield in thraustochytrids without compromising growth is an important aspect of economic feasibility. To fill this gap, we overexpressed the antioxidative gene superoxide dismutase (SOD1) by integrating it into the genome of thraustochytrid Schizochytrium sp. PKU#Mn4 using a novel genetic transformation system. This study reports the ROS alleviation, enhanced PUFA production and transcriptome changes resulting from the SOD1 overexpression. SOD1 activity in the recombinant improved by 5.2–71.6% along with 7.8–38.5% decline in ROS during the fermentation process. Interestingly, the total antioxidant capacity in the recombinant remained higher than wild-type and above zero in the entire process. Although lipid profile was similar to that of wild-type, the concentrations of major fatty acids in the recombinant were significantly (p ≤ 0.05) higher. The PUFA titer increased up to 1232 ± 41 mg/L, which was 32.9% higher (p ≤ 0.001) than the wild type. Transcriptome analysis revealed strong downregulation of genes potentially involved in β-oxidation of fatty acids in peroxisome and upregulation of genes catalyzing lipid biosynthesis. Our results enrich the knowledge on stress-induced PUFA biosynthesis and the putative role of ROS in the regulation of lipid metabolism in oleaginous thraustochytrids. This study provides a new and alternate strategy for cost-effective industrial fermentation of PUFA. Keywords: Polyunsaturated fatty acids, Schizochytrium sp., Superoxide dismutase, Transgene, Transcriptomic analysis

Production of aromatic monoterpene molecules in hop flowers is affected by genetic, environmental, and processing factors. Here, the authors engineer brewer’s yeast for the production of linalool and geraniol, and show pilot-scale beer produced by engineered strains reconstitutes some qualities of hop flavor.

Abstract Background Economical conversion of lignocellulosic biomass into biofuels and bioproducts is central to the establishment of a robust bioeconomy. This requires a conversion host that is able to both efficiently assimilate the major lignocellulose-derived carbon sources and divert their metabolites toward specific bioproducts. Results In this study, the carotenogenic yeast Rhodosporidium toruloides was examined for its ability to convert lignocellulose into two non-native sesquiterpenes with biofuel (bisabolene) and pharmaceutical (amorphadiene) applications. We found that R. toruloides can efficiently convert a mixture of glucose and xylose from hydrolyzed lignocellulose into these bioproducts, and unlike many conventional production hosts, its growth and productivity were enhanced in lignocellulosic hydrolysates relative to purified substrates. This organism was demonstrated to have superior growth in corn stover hydrolysates prepared by two different pretreatment methods, one using a novel biocompatible ionic liquid (IL) choline α-ketoglutarate, which produced 261 mg/L of bisabolene at bench scale, and the other using an alkaline pretreatment, which produced 680 mg/L of bisabolene in a high-gravity fed-batch bioreactor. Interestingly, R. toruloides was also observed to assimilate p-coumaric acid liberated from acylated grass lignin in the IL hydrolysate, a finding we verified with purified substrates. R. toruloides was also able to consume several additional compounds with aromatic motifs similar to lignin monomers, suggesting that this organism may have the metabolic potential to convert depolymerized lignin streams alongside lignocellulosic sugars. Conclusions This study highlights the natural compatibility of R. toruloides with bioprocess conditions relevant to lignocellulosic biorefineries and demonstrates its ability to produce non-native terpenes.

Metabolic engineering efforts toward rewiring metabolism of cells to produce new compounds often require the utilization of non-native enzymatic machinery that is capable of producing a broad range of chemical functionalities. Polyketides encompass one of the largest classes of chemically diverse natural products. With thousands of known polyketides, modular polyketide synthases (PKSs) share a particularly attractive biosynthetic logic for generating chemical diversity. The engineering of modular PKSs could open access to the deliberate production of both existing and novel compounds. In this review, we discuss PKS engineering efforts applied at both the protein and cellular level for the generation of a diverse range of chemical structures, and we examine future applications of PKSs in the production of medicines, fuels and other industrially relevant chemicals.

Abstract Background Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics, proteomics and metabolomics) are urgently needed. Results The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and 13C Metabolic Flux Analysis. Moreover, it introduces the capability to use 13C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13C Metabolic Flux Analysis (2S-13C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user’s specific needs. Conclusions jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it will attract additions from the community and grow with the rapidly changing field of metabolic engineering.

Chemolithoautotrophic bacteria that oxidize reduced sulfur compounds, such as H2S, while fixing CO2 are an untapped source of renewable bioproducts from sulfide-laden waste, such as municipal wastewater. In this study, we report engineering of the chemolithoautotrophic bacterium Thiobacillus denitrificans to produce up to 52-fold more fatty acids than the wild-type strain when grown with thiosulfate and CO2. A modified thioesterase gene from E. coli (‘tesA) was integrated into the T. denitrificans chromosome under the control of Pkan or one of two native T. denitrificans promoters. The relative strength of the two native promoters as assessed by fatty acid production in engineered strains was very similar to that assessed by expression of the cognate genes in the wild-type strain. This proof-of-principle study suggests that engineering sulfide-oxidizing chemolithoautotrophic bacteria to overproduce fatty acid-derived products merits consideration as a technology that could simultaneously produce renewable fuels/chemicals as well as cost-effectively remediate sulfide-contaminated wastewater. Keywords: Chemolithoautotrophic, Sulfide, Fatty acids, tesA, Thiobacillus denitrificans

2-Pyrrolidone is a valuable bulk chemical with myriad applications as a solvent, polymer precursor and active pharmaceutical intermediate. A novel 2-pyrrolidone synthase, ORF27, from Streptomyces aizunensis was identified to catalyze the ring closing dehydration of γ-aminobutyrate. ORF27's tendency to aggregate was resolved by expression at low temperature and fusion to the maltose binding protein (MBP). Recombinant Escherichia coli was metabolically engineered for the production of 2-pyrrolidone from glutamate by expressing both the genes encoding GadB, a glutamate decarboxylase, and ORF27. Incorporation of a GadB mutant lacking H465 and T466, GadB_ΔHT, improved the efficiency of one-pot 2-pyrrolidone biosynthesis in vivo. When the recombinant E. coli strain expressing the E. coli GadB_ΔHT mutant and the ORF27-MBP fusion was cultured in ZYM-5052 medium containing 9 g/L of l-glutamate, 7.7 g/L of l-glutamate was converted to 1.1 g/L of 2-pyrrolidone within 31 h, achieving 25% molar yield from the consumed substrate. Keywords: 2-Pyrrolidone, E. coli, Glutamate, Metabolic engineering, Biosynthesis

ABSTRACT Despite intensive study for 50 years, the biochemical and genetic links between lysine metabolism and central metabolism in Pseudomonas putida remain unresolved. To establish these biochemical links, we leveraged random barcode transposon sequencing (RB-TnSeq), a genome-wide assay measuring the fitness of thousands of genes in parallel, to identify multiple novel enzymes in both l- and d-lysine metabolism. We first describe three pathway enzymes that catabolize l-2-aminoadipate (l-2AA) to 2-ketoglutarate (2KG), connecting d-lysine to the TCA cycle. One of these enzymes, P. putida 5260 (PP_5260), contains a DUF1338 domain, representing a family with no previously described biological function. Our work also identified the recently described coenzyme A (CoA)-independent route of l-lysine degradation that results in metabolization to succinate. We expanded on previous findings by demonstrating that glutarate hydroxylase CsiD is promiscuous in its 2-oxoacid selectivity. Proteomics of selected pathway enzymes revealed that expression of catabolic genes is highly sensitive to the presence of particular pathway metabolites, implying intensive local and global regulation. This work demonstrated the utility of RB-TnSeq for discovering novel metabolic pathways in even well-studied bacteria, as well as its utility a powerful tool for validating previous research. IMPORTANCE P. putida lysine metabolism can produce multiple commodity chemicals, conferring great biotechnological value. Despite much research, the connection of lysine catabolism to central metabolism in P. putida remained undefined. Here, we used random barcode transposon sequencing to fill the gaps of lysine metabolism in P. putida. We describe a route of 2-oxoadipate (2OA) catabolism, which utilizes DUF1338-containing protein P. putida 5260 (PP_5260) in bacteria. Despite its prevalence in many domains of life, DUF1338-containing proteins have had no known biochemical function. We demonstrate that PP_5260 is a metalloenzyme which catalyzes an unusual route of decarboxylation of 2OA to d-2-hydroxyglutarate (d-2HG). Our screen also identified a recently described novel glutarate metabolic pathway. We validate previous results and expand the understanding of glutarate hydroxylase CsiD by showing that can it use either 2OA or 2KG as a cosubstrate. Our work demonstrated that biological novelty can be rapidly identified using unbiased experimental genetics and that RB-TnSeq can be used to rapidly validate previous results.

We present a selection design that couples S-adenosylmethionine-dependent methylation to growth. We demonstrate its use in improving the enzyme activities of not only N-type and O-type methyltransferases by 2-fold but also an acetyltransferase of another enzyme category when linked to a methylation pathway in Escherichia coli using adaptive laboratory evolution. We also demonstrate its application for drug discovery using a catechol O-methyltransferase and its inhibitors entacapone and tolcapone. Implementation of this design in Saccharomyces cerevisiae is also demonstrated.

Recent improvements in the speed and sensitivity of liquid chromatography-mass spectrometry systems have driven significant progress toward system-wide characterization of the proteome of many species. These efforts create large proteomic datasets that provide insight into biological processes and identify diagnostic proteins whose abundance changes significantly under different experimental conditions. Yet, these system-wide experiments are typically the starting point for hypothesis-driven, follow-up experiments to elucidate the extent of the phenomenon or the utility of the diagnostic marker, wherein many samples must be analyzed. Transitioning from a few discovery experiments to quantitative analyses on hundreds of samples requires significant resources both to develop sensitive and specific methods as well as analyze them in a high-throughput manner. To aid these efforts, we developed a workflow using data acquired from discovery proteomic experiments, retention time prediction, and standard-flow chromatography to rapidly develop targeted proteomic assays. We demonstrated this workflow by developing MRM assays to quantify proteins of multiple metabolic pathways from multiple microbes under different experimental conditions. With this workflow, one can also target peptides in scheduled/dynamic acquisition methods from a shotgun proteomic dataset downloaded from online repositories, validate with appropriate control samples or standard peptides, and begin analyzing hundreds of samples in only a few minutes.

The conversion of biomass to biofuels presents a solution to one of the largest global challenges of our era, climate change. A critical part of this pipeline is the process of breaking down cellulosic sugars from plant matter to be used by microbes containing biosynthetic pathways that produce biofuels or bioproducts. In this inquiry-based course, students complete a research project that isolates cellulase-producing bacteria from samples collected from the environment. After obtaining isolates, the students characterize the production of cellulases. Students then amplify and sequence the 16S rRNA genes of confirmed cellulase producers and use bioinformatic methods to identify the bacterial isolates. Throughout the course, students learn about the process of generating biofuels and bioproducts through the deconstruction of cellulosic biomass to form monosaccharides from the biopolymers in plant matter. The program relies heavily on active learning and enables students to connect microbiology with issues of sustainability. In addition, it provides exposure to basic microbiology, molecular biology, and biotechnology laboratory techniques and concepts. The described activity was initially developed for the Introductory College Level Experience in Microbiology (iCLEM) program, a research-based immersive laboratory course at the US Department of Energy Joint BioEnergy Institute. Originally designed as an accelerated program for high-potential, low-income, high school students (11th–12th grade), this curriculum could also be implemented for undergraduate coursework in a research-intensive laboratory course at a two- or four-year college or university.