DELLA proteins recruit the Mediator complex subunit MED15 to coactivate transcription in land plants.

DELLA proteins are negative regulators of the gibberellin response pathway in angiosperms, acting as central hubs that interact with hundreds of transcription factors (TFs) and regulators to modulate their activities. While the mechanism of TF sequestration by DELLAs to prevent DNA binding to downstream targets has been extensively documented, the mechanism that allows them to act as coactivators remains to be understood. Here, we demonstrate that DELLAs directly recruit the Mediator complex to specific loci in Arabidopsis, facilitating transcription. This recruitment involves DELLA amino-terminal domain and the conserved MED15 KIX domain. Accordingly, partial loss of MED15 function mainly disrupted processes known to rely on DELLA coactivation capacity, including cytokinin-dependent regulation of meristem function and skotomorphogenic response, gibberellin metabolism feedback, and flavonol production. We have also found that the single DELLA protein in the liverwort Marchantia polymorpha is capable of recruiting MpMED15 subunits, contributing to transcriptional coactivation. The conservation of Mediator-dependent transcriptional coactivation by DELLA between Arabidopsis and Marchantia implies that this mechanism is intrinsic to the emergence of DELLA in the last common ancestor of land plants.

Multiplexed in-situ mutagenesis driven by a dCas12a-based dual-function base editor.

Mutagenesis driving genetic diversity is vital for understanding and engineering biological systems. However, the lack of effective methods to generate in-situ mutagenesis in multiple genomic loci combinatorially limits the study of complex biological functions. Here, we design and construct MultiduBE, a dCas12a-based multiplexed dual-function base editor, in an all-in-one plasmid for performing combinatorial in-situ mutagenesis. Two synthetic effectors, duBE-1a and duBE-2b, are created by amalgamating the functionalities of cytosine deaminase (from hAPOBEC3A or hAID*Δ ), adenine deaminase (from TadA9), and crRNA array processing (from dCas12a). Furthermore, introducing the synthetic separator Sp4 minimizes interference in the crRNA array, thereby facilitating multiplexed in-situ mutagenesis in both Escherichia coli and Bacillus subtilis. Guided by the corresponding crRNA arrays, MultiduBE is successfully employed for cell physiology reprogramming and metabolic regulation. A novel mutation conferring streptomycin resistance has been identified in B. subtilis and incorporated into the mutant strains with multiple antibiotic resistance. Moreover, surfactin and riboflavin titers of the combinatorially mutant strains improved by 42% and 15-fold, respectively, compared with the control strains with single gene mutation. Overall, MultiduBE provides a convenient and efficient way to perform multiplexed in-situ mutagenesis.

CRISPR-dCas12a-mediated genetic circuit cascades for multiplexed pathway optimization.

The production efficiency of microbial cell factories is sometimes limited by the lack of effective methods to regulate multiple targets in a coordinated manner. Here taking the biosynthesis of glucosamine-6-phosphate (GlcN6P) in Bacillus subtilis as an example, a 'design-build-test-learn' framework was proposed to achieve efficient multiplexed optimization of metabolic pathways. A platform strain was built to carry biosensor signal-amplifying circuits and two genetic regulation circuits. Then, a synthetic CRISPR RNA array blend for boosting and leading (ScrABBLE) device was integrated into the platform strain, which generated 5,184 combinatorial assemblies targeting three genes. The best GlcN6P producer was screened and engineered for the synthesis of valuable pharmaceuticals N-acetylglucosamine and N-acetylmannosamine. The N-acetylglucosamine titer reached 183.9 g liter-1 in a 15-liter bioreactor. In addition, the potential generic application of the ScrABBLE device was also verified using three fluorescent proteins as a case study.

Spontaneously established syntrophic yeast communities improve bioproduction.

Nutritional codependence (syntrophy) has underexplored potential to improve biotechnological processes by using cooperating cell types. So far, design of yeast syntrophic communities has required extensive genetic manipulation, as the co-inoculation of most eukaryotic microbial auxotrophs does not result in cooperative growth. Here we employ high-throughput phenotypic screening to systematically test pairwise combinations of auxotrophic Saccharomyces cerevisiae deletion mutants. Although most coculture pairs do not enter syntrophic growth, we identify 49 pairs that spontaneously form syntrophic, synergistic communities. We characterized the stability and growth dynamics of nine cocultures and demonstrated that a pair of tryptophan auxotrophs grow by exchanging a pathway intermediate rather than end products. We then introduced a malonic semialdehyde biosynthesis pathway split between different pairs of auxotrophs, which resulted in increased production. Our results report the spontaneous formation of stable syntrophy in S. cerevisiae auxotrophs and illustrate the biotechnological potential of dividing labor in a cooperating intraspecies community.

Vibrio natriegens genome-scale modeling reveals insights into halophilic adaptations and resource allocation.

Vibrio natriegens is a Gram-negative bacterium with an exceptional growth rate that has the potential to become a standard biotechnological host for laboratory and industrial bioproduction. Despite this burgeoning interest, the current lack of organism-specific qualitative and quantitative computational tools has hampered the community's ability to rationally engineer this bacterium. In this study, we present the first genome-scale metabolic model (GSMM) of V. natriegens. The GSMM (iLC858) was developed using an automated draft assembly and extensive manual curation and was validated by comparing predicted yields, central metabolic fluxes, viable carbon substrates, and essential genes with empirical data. Mass spectrometry-based proteomics data confirmed the translation of at least 76% of the enzyme-encoding genes predicted to be expressed by the model during aerobic growth in a minimal medium. iLC858 was subsequently used to carry out a metabolic comparison between the model organism Escherichia coli and V. natriegens, leading to an analysis of the model architecture of V. natriegens' respiratory and ATP-generating system and the discovery of a role for a sodium-dependent oxaloacetate decarboxylase pump. The proteomics data were further used to investigate additional halophilic adaptations of V. natriegens. Finally, iLC858 was utilized to create a Resource Balance Analysis model to study the allocation of carbon resources. Taken together, the models presented provide useful computational tools to guide metabolic engineering efforts in V. natriegens.

A pathway independent multi-modular ordered control system based on thermosensors and CRISPRi improves bioproduction in Bacillus subtilis.

Dynamic regulation is an effective strategy for control of gene expression in microbial cell factories. In some pathway contexts, several metabolic modules must be controlled in a time dependent or ordered manner to maximize production, while the creation of genetic circuits with ordered regulation capacity still remains a great challenge. In this work, we develop a pathway independent and programmable system that enables multi-modular ordered control of metabolism in Bacillus subtilis. First, a series of thermosensors were created and engineered to expand their thresholds. Then we designed single-input-multi-output circuits for ordered control based on the use of thermosensors with different transition points. Meanwhile, a repression circuit was constructed by combining CRISPRi-based NOT gates. As a proof-of-concept, these genetic circuits were applied for multi-modular ordered control of 2'-fucosyllactose (2'-FL) biosynthesis, resulting in a production of 1839.7 mg/l in shake flask, which is 5.16-times that of the parental strain. In a 5-l bioreactor, the 2'-FL titer reached 28.2 g/l with down-regulation of autolysis. Taken together, this work provides programmable and versatile thermosensitive genetic toolkits for dynamic regulation in B. subtilis and a multi-modular ordered control framework that can be used to improve metabolic modules in other chassis cells and for other compounds.

Metabolic engineering strategies to enable microbial utilization of C1 feedstocks.

One-carbon (C1) substrates are preferred feedstocks for the biomanufacturing industry and have recently gained attention owing to their natural abundance, low production cost and availability as industrial by-products. However, native pathways to utilize these substrates are absent in most biotechnologically relevant microorganisms. Recent advances in synthetic biology, genome engineering and laboratory evolution are enabling the first steps towards the creation of synthetic C1-utilizing microorganisms. Here, we briefly review the native metabolism of methane, methanol, CO2, CO and formate, and how these C1-utilizing pathways can be engineered into heterologous hosts. In addition, this review analyses the potential, the challenges and the perspectives of C1-based biomanufacturing.

Combination of microbial and chemical synthesis for the sustainable production of ß-elemene, a promising plant-extracted anticancer compound.

Beta-elemene, a class of sesquiterpene derived from the Chinese medicinal herb Curcuma wenyujin, is widely used in clinical medicine due to its broad-spectrum antitumor activity. However, the unsustainable plant extraction prompted the search for environmentally friendly strategies for ß-elemene production. In this study, we designed a Yarrowia lipolytica cell factory that can continuously produce germacrene A, which is further converted into ß-elemene with 100% yield through a Cope rearrangement reaction by shifting the temperature to 250°C. First, the productivity of four plant-derived germacrene A synthases was evaluated. After that, the metabolic flux of the precursor to germacrene A was maximized by optimizing the endogenous mevalonate pathway, inhibiting the competing squalene pathway, and expressing germacrene A synthase gene in multiple copies. Finally, the most promising strain achieved the highest ß-elemene titer reported to date with 5.08 g/L. This sustainable and green method has the potential for industrial ß-elemene production.

etiBsu1209: A comprehensive multiscale metabolic model for Bacillus subtilis.

Genome-scale metabolic models (GEMs) have been widely used to guide the computational design of microbial cell factories, and to date, seven GEMs have been reported for Bacillus subtilis, a model gram-positive microorganism widely used in bioproduction of functional nutraceuticals and food ingredients. However, none of them are widely used because they often lead to erroneous predictions due to their low predictive power and lack of information on regulatory mechanisms. In this work, we constructed a new version of GEM for B. subtilis (iBsu1209), which contains 1209 genes, 1595 metabolites, and 1948 reactions. We applied machine learning to fill gaps, which formed a relatively complete metabolic network able to predict with high accuracy (89.3%) the growth of 1209 mutants under 12 different culture conditions. In addition, we developed a visualization and code-free software, Model Tool, for multiconstraints model reconstruction and analysis. We used this software to construct etiBsu1209, a multiscale model that integrates enzymatic constraints, thermodynamic constraints, and transcriptional regulatory networks. Furthermore, we used etiBsu1209 to guide a metabolic engineering strategy (knocking out fabI and yfkN genes) for the overproduction of nutraceutical menaquinone-7, and the titer increased to 153.94 mg/L, 2.2-times that of the parental strain. To the best of our knowledge, etiBsu1209 is the first comprehensive multiscale model for B. subtilis and can serve as a solid basis for rational computational design of B. subtilis cell factories for bioproduction.

A robust soft sensor based on artificial neural network for monitoring microbial lipid fermentation processes using Yarrowia lipolytica.

Microbial oils produced by Yarrowia lipolytica offer an environmentally friendly and sustainable alternative to petroleum as well as traditional lipids from animals and plants. The accurate measurement of fermentation parameters, including the substrate concentration, dry cell weight, and lipid accumulation, is the foundation of process control, which is indispensable for industrial lipid production. However, it remains a great challenge to measure the complex parameters online during the lipid fermentation process, which is nonlinear, multivariate, and characterized by strong coupling. As a type of AI technology, the artificial neural network model is a powerful tool for handling extremely complex problems, and it can be employed to develop a soft sensor to monitor the microbial lipid fermentation process of Y. lipolytica. In this study, we first analyzed and emphasized the volume of sodium hydroxide and dissolved oxygen concentration as central parameters of the fermentation process. Then, a soft sensor based on a four-input artificial neural network model was developed, in which the input variables were fermentation time, dissolved oxygen concentration, initial glucose concentration, and additional volume of sodium hydroxide. This provides the possibility of online monitoring of dry cell weight, glucose concentration, and lipid production with high accuracy, which can be extended to similar fermentation processes characterized by the addition of bases or acids, as well as changes of the dissolved oxygen concentration.

High-throughput process development from gene cloning to protein production.

In the post-genomic era, the demand for faster and more efficient protein production has increased, both in public laboratories and industry. In addition, with the expansion of protein sequences in databases, the range of possible enzymes of interest for a given application is also increasing. Faced with peer competition, budgetary, and time constraints, companies and laboratories must find ways to develop a robust manufacturing process for recombinant protein production. In this review, we explore high-throughput technologies for recombinant protein expression and present a holistic high-throughput process development strategy that spans from genes to proteins. We discuss the challenges that come with this task, the limitations of previous studies, and future research directions.

Studies on the Anticancer and Antioxidant Activities of Resveratrol and Long-Chain Fatty Acid Esters.

Resveratrol (RES) is gaining recognition as a natural bioactive compound. To expand the possible applications of RES with its enhanced bioactivity as well as to increase the health benefits of long-chain fatty acids, a lipophilization process of RES was performed using three fatty acids: palmitic acid (PA), oleic acid (OA), and conjugated linoleic acid (CLA). The obtained mono-, di-, and tri-esters of RES were evaluated for their anticancer and antioxidant properties against lung carcinoma (A549), colorectal adenocarcinoma (HT29), and pancreatic ductal adenocarcinoma (BxPC3) cell lines. Human fibroblast (BJ) cells were used as a control. Several parameters were investigated: cell viability and apoptosis, including the expression of major pro- and anti-apoptotic markers, as well as the expression of superoxide dismutase, a key enzyme of the body's antioxidant barrier. Three of the obtained esters: mono-RES-OA, mono-RES-CLA, and tri-RES-PA, which significantly reduced the tumor cell viability up to 23%, at concentrations 25, 10, 50 µg/mL, respectively, turned out to be particularly interesting. The above-mentioned resveratrol derivatives similarly increased the tumor cells' apoptosis by modifying their caspase activity of pro-apoptotic pathways (p21, p53, and Bax). Moreover, among the mentioned esters, mono-RES-OA induced apoptosis of the analyzed cell lines most strongly, reducing the number of viable cells up to 48% for HT29 cells versus 36% for pure RES. Furthermore, the selected esters exhibited antioxidant properties towards the normal BJ cell line by regulating the expression of major pro-antioxidant genes (superoxide dismutases-SOD1 and SOD2) without the effect on their expression in the tumor, and therefore reducing the defense of cancer cells against increased oxidative stress induced by high ROS accumulation. The obtained results indicate that the esters of RES and long-chain fatty acids allow enhancement of their biological activity. The RES derivatives have the potential for being applied in cancer prevention and treatment, as well as for oxidative stress suppression.

Applications of synthetic yeast consortia for the production of native and non-native chemicals.

The application of microbial consortia is a new approach in synthetic biology. Synthetic yeast consortia, simple or complex synthetic mixed cultures, have been used for the production of various metabolites. Cooperation between the members of a consortium and cross-feeding can be applied to create stable microbial communication. These consortia can: consume a variety of substrates, perform more complex functions, produce metabolites in high titer, rate, and yield (TRY), and show higher stability during industrial fermentations. Due to the new research context of synthetic consortia, few yeasts were used to build these consortia, including Saccharomyces cerevisiae, Pichia pastoris, and Yarrowia lipolytica. Here, application of the yeasts for design of synthetic microbial consortia and their advantages and bottlenecks for effective and robust production of valuable metabolites from bioresource, including: cellulose, xylose, glycerol and so on, have been reviewed. Key trends and challenges are also discussed for the future development of synthetic yeast consortia.

Pyruvate-responsive genetic circuits for dynamic control of central metabolism.

Dynamic regulation is a promising strategy for fine-tuning metabolic fluxes in microbial cell factories. However, few of these synthetic regulatory systems have been developed for central carbon metabolites. Here we created a set of programmable and bifunctional pyruvate-responsive genetic circuits for dynamic dual control (activation and inhibition) of central metabolism in Bacillus subtilis. We used these genetic circuits to design a feedback loop control system that relies on the intracellular concentration of pyruvate to fine-tune the target metabolic modules, leading to the glucaric acid titer increasing from 207 to 527 mg l-1. The designed logic gate-based circuits were enabled by the characterization of a new antisense transcription mechanism in B. subtilis. In addition, a further increase to 802 mg l-1 was achieved by blocking the formation of by-products. Here, the constructed pyruvate-responsive genetic circuits are presented as effective tools for the dynamic control of central metabolism of microbial cell factories.

Resource-aware whole-cell model of division of labour in a microbial consortium for complex-substrate degradation.

BACKGROUND: Low-cost sustainable feedstocks are essential for commercially viable biotechnologies. These feedstocks, often derived from plant or food waste, contain a multitude of different complex biomolecules which require multiple enzymes to hydrolyse and metabolise. Current standard biotechnology uses monocultures in which a single host expresses all the proteins required for the consolidated bioprocess. However, these hosts have limited capacity for expressing proteins before growth is impacted. This limitation may be overcome by utilising division of labour (DOL) in a consortium, where each member expresses a single protein of a longer degradation pathway. RESULTS: Here, we model a two-strain consortium, with one strain expressing an endohydrolase and a second strain expressing an exohydrolase, for cooperative degradation of a complex substrate. Our results suggest that there is a balance between increasing expression to enhance degradation versus the burden that higher expression causes. Once a threshold of burden is reached, the consortium will consistently perform better than an equivalent single-cell monoculture. CONCLUSIONS: We demonstrate that resource-aware whole-cell models can be used to predict the benefits and limitations of using consortia systems to overcome burden. Our model predicts the region of expression where DOL would be beneficial for growth on starch, which will assist in making informed design choices for this, and other, complex-substrate degradation pathways.

Hypersecretion of OmlA antigen in Corynebacterium glutamicum through high-throughput based development process.

Outer membrane lipoprotein A (OmlA) is a vaccine antigen against porcine contagious pleuropneumonia (PCP), a disease severely affecting the swine industry. Here, we aimed to systematically potentiate the secretory production of OmlA in Corynebacterium glutamicum (C. glutamicum), a widely used microorganism in the food industry, by establishing a holistic development process based on our high-throughput culture platform. The expression patterns, expression element combinations, medium composition, and induction conditions were comprehensively screened or optimized in microwell plates (MWPs), followed by fermentation parameter optimization in a 4 × 1 L parallel fermentation system (CUBER4). An unprecedented yield of 1.01 g/L OmlA was ultimately achieved in a 5-L bioreactor following the scaling-up strategy of fixed oxygen mass transfer coefficient (kLa), and the produced OmlA antigen showed well-protective immunity against Actinobacillus pleuropneumoniae challenge. This result provides a rapid and reliable pipeline to achieve the hyper-production of OmlA, and possibly other recombinant vaccines, in C. glutamicum. KEY POINTS: • Established a holistic development process and applied it to potentiate the secretion of OmlA. • The secretion of OmlA reached an unprecedented yield of 1.01 g/L. • The recombinant OmlA antigen induced efficient protective immunity.

CRISPR-Cas13a cascade-based viral RNA assay for detecting SARS-CoV-2 and its mutations in clinical samples.

SARS-CoV-2 is one of the greatest threats to global human health. Point-of-care diagnostic tools for SARS-CoV-2 could facilitate rapid therapeutic intervention and mitigate transmission. In this work, we report CRISPR-Cas13a cascade-based viral RNA (Cas13C) assay for label-free and isothermal determination of SARS-CoV-2 and its mutations in clinical samples. Cas13a/crRNA was utilized to directly recognize the target of SARS-CoV-2 RNA, and the recognition events sequentially initiate the transcription amplification to produce light-up RNA aptamers for output fluorescence signal. The recognition of viral RNA via Cas13a-guide RNA ensures a high specificity to distinguish SARS-CoV-2 from MERS-CoV and SARS-CoV, as well as viral mutations. A post transcription amplification strategy was triggered after CRISPR-Cas13a recognition contributes to an amplification cascade that achieves high sensitivity for detecting SARS-CoV-2 RNA, with a limit of detection of 0.216 fM. In addition, the Cas13C assay could be able to discriminate single-nucleotide mutation, which was proven with N501Y in SARS-Cov-2 variant. This method was validated by a 100% agreement with RT-qPCR results from 12 clinical throat swab specimens. The Cas13C assay has the potential to be used as a routine nucleic acid test of SARS-CoV-2 virus in resource-limited regions.

Design of a programmable biosensor-CRISPRi genetic circuits for dynamic and autonomous dual-control of metabolic flux in Bacillus subtilis.

Dynamic regulation is an effective strategy for fine-tuning metabolic pathways in order to maximize target product synthesis. However, achieving dynamic and autonomous up- and down-regulation of the metabolic modules of interest simultaneously, still remains a great challenge. In this work, we created an autonomous dual-control (ADC) system, by combining CRISPRi-based NOT gates with novel biosensors of a key metabolite in the pathway of interest. By sensing the levels of the intermediate glucosamine-6-phosphate (GlcN6P) and self-adjusting the expression levels of the target genes accordingly with the GlcN6P biosensor and ADC system enabled feedback circuits, the metabolic flux towards the production of the high value nutraceutical N-acetylglucosamine (GlcNAc) could be balanced and optimized in Bacillus subtilis. As a result, the GlcNAc titer in a 15-l fed-batch bioreactor increased from 59.9 g/l to 97.1 g/l with acetoin production and 81.7 g/l to 131.6 g/l without acetoin production, indicating the robustness and stability of the synthetic circuits in a large bioreactor system. Remarkably, this self-regulatory methodology does not require any external level of control such as the use of inducer molecules or switching fermentation/environmental conditions. Moreover, the proposed programmable genetic circuits may be expanded to engineer other microbial cells and metabolic pathways.

The elucidation of phosphosugar stress response in Bacillus subtilis guides strain engineering for high N-acetylglucosamine production.

Bacillus subtilis is a preferred microbial host for the industrial production of nutraceuticals and a promising candidate for the synthesis of functional sugars, such as N-acetylglucosamine (GlcNAc). Previously, a GlcNAc-overproducer B. subtilis SFMI was constructed using glmS ribozyme dual-regulatory tool. Herein, we further engineered to enhance carbon flux from glucose towards GlcNAc synthesis. As a result, the increased flux towards GlcNAc synthesis triggered phosphosugar stress response, which caused abnormal cell growth. Unfortunately, the mechanism of phosphosugar stress response had not been elucidated in B. subtilis. To reveal the stress mechanism and overcome its negative effect in bioproduction, we performed comparative transcriptome analysis. The results indicate that cells slow glucose utilization by repression of glucose import and accelerate catabolic reactions of phosphosugar. To verify these results, we overexpressed the phosphatase YwpJ, which relieved phosphosugar stress and allowed us to identify the enzyme responsible for GlcNAc synthesis from GlcNAc 6-phosphate. In addition, the deletion of nagBB and murQ, responsible for GlcNAc precursor degradation, further improved GlcNAc synthesis. The best engineered strain, B. subtilis FMIP34, increased GlcNAc titer from 11.5 to 26.1 g/L in shake flasks and produced 87.5 g/L GlcNAc in 30-L fed-batch bioreactor. Our results not only elucidate, for the first time, the phosphosugar stress response mechanism in B. subtilis, but also demonstrate how the combination of rational metabolic engineering with novel insights into physiology and metabolism allows the construction of highly efficient microbial cell factories for the production of high-value chemicals.

Assembly of pathway enzymes by engineering functional membrane microdomain components for improved N-acetylglucosamine synthesis in Bacillus subtilis.

Enzyme clustering can improve catalytic efficiency by facilitating the processing of intermediates. Functional membrane microdomains (FMMs) in bacteria can provide a platform for enzyme clustering. However, the amount of FMMs at the cell basal level is still facing great challenges in multi-enzyme immobilization. Here, using the nutraceutical N-acetylglucosamine (GlcNAc) synthesis in Bacillus subtilis as a model, we engineered FMM components to improve the enzyme assembly in FMMs. First, by overexpression of the SPFH (stomatin-prohibitin-flotillin-HflC/K) domain and YisP protein, an enzyme involved in the synthesis of squalene-derived polyisoprenoid, the membrane order of cells was increased, as verified using di-4-ANEPPDHQ staining. Then, two heterologous enzymes, GlcNAc-6-phosphate N-acetyltransferase (GNA1) and haloacid dehalogenase-like phosphatases (YqaB), required for GlcNAc synthesis were assembled into FMMs, and the GlcNAc titer in flask was increased to 8.30 ± 0.57 g/L, which was almost three times that of the control strains. Notably, FMM component modification can maintain the OD600 in stationary phase and reduce cell lysis in the later stage of fermentation. These results reveal that the improved plasma membrane ordering achieved by the engineering FMM components could not only promote the enzyme assembly into FMMs, but also improve the cell fitness.