Synthetic and Systems Biotechnology

Gas-fermenting Clostridium species hold tremendous promise for one-carbon biomanufacturing. To unlock their full potential, it is crucial to unravel and optimize the intricate regulatory networks that govern these organisms; however, this aspect is currently underexplored. In this study, we employed pooled CRISPR interference (CRISPRi) screening to uncover a wide range of functional transcription factors (TFs) in Clostridium ljungdahlii, a representative species of gas-fermenting Clostridium, with a special focus on the TFs associated with the utilization of carbon resources. Among the 425 TF candidates, we identified 75 and 68 TF genes affecting the heterotrophic and autotrophic growth of C. ljungdahlii, respectively. We directed our attention on two of the screened TFs, NrdR and DeoR, and revealed their pivotal roles in the regulation of deoxyribonucleotides (dNTPs) supply, carbon fixation, and product synthesis in C. ljungdahlii, thereby influencing the strain performance in gas fermentation. Based on this, we proceeded to optimize the expression of deoR in C. ljungdahlii by adjusting its promoter strength, leading to improved growth rate and ethanol synthesis of C. ljungdahlii when utilizing syngas. This study highlights the effectiveness of pooled CRISPRi screening in gas-fermenting Clostridium species, expanding the horizons for functional genomic research in these industrially important bacteria.

Promoters are one of the most critical regulatory elements controlling metabolic pathways. However, in recent years, researchers have simply perfected promoter strength, but ignored the relationship between the internal sequences and promoter strength. In this context, we constructed and characterized a mutant promoter library of Ptrc through dozens of mutation-construction-screening-characterization engineering cycles. After excluding invalid mutation sites, we established a synthetic promoter library, which consisted of 3665 different variants, displaying an intensity range of more than two orders of magnitude. The strongest variant was 1.52-fold stronger than a 1 mM isopropyl-{beta}-D-thiogalactoside driven PT7 promoter. Our synthetic promoter library exhibited superior applicability when expressing different reporters, in both plasmids and the genome. Different machine learning models were built and optimized to explore relationships between the promoter sequences and transcriptional strength. Finally, our XgBoost model exhibited optimal performance, and we utilized this approach to precisely predict the strength of artificially designed promoter sequences. Our work provides a powerful platform that enables the predictable tuning of promoters to achieve the optimal transcriptional strength.

Modules, toolboxes, and systems of synthetic biology are being designed to solve environmental problems. However, weak and decentralized functional modules require complicated controls. To address this issue, we investigated an integrated system that can complete detection, degradation, and lethality, in chronological order without exogenous inducers. Biosensors were optimized by regulating expression of receptor and reporter to get higher sensitivity and output signal. Several stationary-phase promoters were selected and compared, while promoter Pfic was chosen to express the degradation enzyme. We created two concepts of lethal circuits by testing various toxic proteins, with a toxin/antitoxin circuit showing a potent lethal effect. Three modules were coupled, step-by-step. Detection, degradation, and lethality were sequentially completed, and the modules had partial attenuation compared to pre-integration, except for degradation. Our study provides a novel concept for integrating and controlling functional modules, which can accelerate the transition of synthetic biology from a concept to practical applications. TeaserWe provide new ideas for integration and chronological control of multiple modules in synthetic biology.

Globally, nearly a million plastic bottles are produced every minute (1). These non-biodegradable plastic products are composed of Polyethylene terephthalate (PET). In 2016, researchers discovered PETase, an enzyme from the bacteria Ideonella sakaiensis which breaks down PET and nonbiodegradable plastic. However, PETase has low efficiency at high temperatures. In this project, we optimized the rate of PET degradation by PETase by designing new mutant enzymes which could break down PET much faster than PETase, which is currently the gold standard. We used machine learning (ML) guided directed evolution to modify the PETase enzyme to have a higher optimal temperature (Topt), which would allow the enzyme to degrade PET more efficiently. First, we trained three machine learning models to predict Topt with high performance, including Logistic Regression, Linear Regression and Random Forest. We then used Random Forest to perform ML-guided directed evolution. Our algorithm generated hundreds of mutants of PETase and screened them using Random Forest to select mutants with the highest Topt, and then used the top mutants as the enzyme being mutated. After 1000 iterations, we produced a new mutant of PETase with Topt of 71.38{degrees}C. We also produced a new mutant enzyme after 29 iterations with Topt of 61.3{degrees}C. To ensure these mutant enzymes would remain stable, we predicted their melting temperatures using an external predictor and found the 29-iteration mutant had improved thermostability over PETase.Our research is significant because using our approach and algorithm, scientists can optimize additional enzymes for improved efficiency.

Corynebacterium glutamicum is a promising microbial chassis for the industrial production of L-tryptophan, which has exhibited increasing demand due to its diverse applications and high market value. In previous work, we developed an L-tryptophan-overproducing C. glutamicum strain TR26 through multiple rounds of rational metabolic engineering. Here, comparative transcriptome and metabolome analyses were conducted between TR26 and its progenitor strain MB001 to reveal the underlying mechanisms and potential bottlenecks for L-tryptophan production in TR26. Furthermore, by systematically down- and up-regulating differentially expressed genes of interest, two novel genetic targets, glnK and sugR, were identified as being associated with L-tryptophan synthesis. Specifically, the repression of glnK and overexpression of sugR in strain TR26 increased the titer of L-tryptophan by 6.7% and 20.9%, respectively. Gene transcription profiling and intracellular metabolite analysis further suggested that the observed improvements in L-tryptophan synthesis could be attributed to optimized nitrogen transport and metabolism, efficient reallocation of cellular resources and enhanced supply of phosphoenolpyruvate (PEP). This study advances our understanding of the regulation mechanisms governing L-tryptophan synthesis in C. glutamicum and provides valuable insights for further optimization of industrial cell factories.

Foreign proteins are produced by inserting synthetic constructs into host bacteria in biotechnology applications. This process can cause resource competition between synthetic circuits and host cells, placing a metabolic burden on the host cells which may result load stress and detrimental physiological changes. Consequently, the host bacteria can experience slow growth, while the synthetic system may suffer from suboptimal function and reduced productivity. To address this issue, we developed machine learning strategies to select a minimal number of genes that could serve as biomarkers for the design of load stress reporters. We identified pairs of biomarkers that showed discriminative capacity to detect the load stress states induced in 41 engineered E. coli strains. These biomarker genes are mainly involved in Envelope stress response, Ion transport, Energy production and conversion.

Due to their photosynthetic capabilities, cyanobacteria is expected to be an ecologically friendly host for the production of biomaterials. However, compared to other bacteria, there is little information of autonomous replication sequences, and tools for genetic engineering, especially expression vector systems, are limited. In this study, we established an effective screening method, namely AR-seq (Autonomous Replication sequencing), for finding autonomous replication regions in cyanobacteria and utilized the region for constructing expression vector. AR-seq using the genomic library of Synechocystis sp. PCC 6803 revealed that a certain region containing Rep-related protein (here named as Cyanobacterial Rep protein A2: CyRepA2) exhibits high autonomous replication activity in a heterologous host cyanobacterium, Synechococcus elongatus PCC 7942. The reporter assay using GFP showed that the expression vector pYS carrying CyRepA2 can be maintained in a wide range of multiple cyanobacterial species, not only S. 6803 and S. 7942, but also Synechococcus sp. PCC 7002 and Anabaena sp. PCC 7120. In S. 7942, the GFP expression in pYS-based system can be tightly regulated by IPTG, achieving 10-fold higher levels than that of chromosome-based system. Furthermore, pYS can be used together with conventional vector pEX, which was constructed from an endogenous plasmid in 5. 7942. The combination of pYS with other vectors is useful for genetic engineering, such as modifying metabolic pathways, and is expected to improve the performance of cyanobacteria as bioproduction chassis.

Poly {gamma}-glutamic acid ({gamma}-PGA) is a widely used biopolymer whose synthesis relies on external nitrogen sources. PhoP is a global transcription factor that has been reported to be involved in regulation of phosphorus and nitrogen metabolisms, whether PhoP regulates {gamma}-PGA synthesis is worthy of further study. In this study, {gamma}-PGA yield was decreased by 19.4% in phoP deletion strain, while PhoP overexpression benefited {gamma}-PGA synthesis in Bacillus licheniformis, and the results of transcriptional level, electrophoretic mobility shift (EMSA) and GFP expression assays confirmed the direct positive regulation on {gamma}-PGA synthetase gene pgsB by PhoP. Furthermore, based on metabolomic and physiological analysis, we dissected three aspects that {gamma}-PGA synthesis indirectly regulated by PhoP. (i) PhoP influences glutamate transport through positively regulating glutamate transporter GltT. (ii) PhoP influences nitrogen source utilization through negatively regulating nitrogen metabolic repressor TnrA and positively regulating GlnR. (iii) PhoP influences ammonia assimilation through GlnR and TnrA. Together, our study improved metabolic regulatory network of {gamma}-PGA synthesis, and laid a foundation for PhoP regulation nitrogen metabolic network in Bacillus.

DNA nucleases TnpB and IscB were regarded as new antibacterial strategy to combat the drug-resistant bacteria represented by Escherichia coli due to its specificity in targeting DNA and smallest size, but the genome-editing of TnpB/IscB in E. coli remains unclear. This study characterized the genome-editing of TnpB/IscB in E. coli strains. First, the toxicity and cleavage results showed TnpB only worked in E. coli MG1655, while IscB and enIscB could perform in ATCC9637 and BL21(DE3). Next, TnpB-based genome-editing tool was established in MG1655, while IscB/enIscB achieved in ATCC9637/BL21(DE3). The copy number of TnpB/IscB/enIscB were changed to explore the impact of editing efficiency. Moreover, the editing plasmids were successfully cured. Finally, the escaping mechanism of E. coli under editing of TnpB/IscB was revealed. Overall, this study successfully applied TnpB/IscB/enIscB to genome-editing in E. coli, which will broaden genetic manipulation toolbox in E. coli and facilitate the development of new antimicrobial drugs.

Medium optimization and development for selective bacterial culture are essential for isolating and functionalizing individual bacteria in microbial communities; nevertheless, it remains challenging due to the unknown mechanisms between bacterial growth and medium components. The present study first tried combining machine learning (ML) with active learning to finetune the medium components for the selective culture of two divergent bacteria, i.e., Lactobacillus plantarum and Escherichia coli. ML models considering multiple growth parameters of the two bacterial strains were constructed to predict the finetuned medium combinations for higher specificity of bacterial growth. The growth parameters were designed as the exponential growth rate (r) and maximal growth yield (K), which were calculated according to the growth curves. The eleven chemical components in the commercially available medium MRS were subjected to medium optimization and specialization. High-throughput growth assays of both strains grown separately were performed to obtain thousands of growth curves in more than one hundred medium combinations, and the resultant datasets linking the growth parameters to the medium combinations were used for the ML training. Repeated rounds of active learning (i.e., ML model construction, medium prediction, and experimental verification) successfully improved the specific growth of a single strain out of the two. Both r and K showed maximized differentiation between the two strains. Further analysis of all data accumulated in active learning identified the decision-making medium components for growth specificity and the differentiated determinative manner of growth decision of the two strains. In summary, this study demonstrated the efficiency and practicality of active learning in medium optimization for selective culture and offered novel insights into the contribution of the chemical components to specific bacterial growth.

Gene therapy studies have been of great importance in the elimination of genetic diseases, and the capability of the CRISPR/Cas9 genome editing technique to correct genetic defects has shown great promise. As DNA-based Cas9 nuclease delivery is preferable because of its low cost and higher stability, effective vector-based CRISPR/Cas9 administration is urgently needed. Here, we used the multicellular organism Caenorhabditis elegans to optimize the polymer-mediated DNA delivery system to generate mutants with CRISPR/Cas9. Toward this end, the cationically quaternized polymer of POEGMA-b-P4VP (POEGMA-b-QP4VP) as a carrier of CRISPR/Cas9 components was first synthesized, followed by the formation of plasmid DNA-polymer complex called polyplexes. 1H NMR, Zeta-Sizer, Scanning Electron Microscopy (SEM) analysis, and gel retardation experiments confirmed the polyplexes formation, including pRF4 (Roller) and sgRNA dpy-10, which were then incubated with C. elegans. The polymer-mediated delivery system facilitated the generation of transgenic Roller animals and heritable Dumpy mutants with CRISPR/Cas9. Our study for the first time demonstrated optimized administration of CRISPR/Cas 9 components to C. elegans.

Predictable expression of heterologous genes in a production host is a fundamental challenge in biotechnology. While traditional methods focus on manipulating expression and the property of the heterologous gene, a systems biology approach can complement with designs to improve the host itself. Previously, Independent Component Analysis (ICA) of the RNAseq data helped reveal independently modulated gene sets (iModulons) in bacteria. This was later applied to identify common stress responses related to heterologous gene expression for Escherichia coli. In this study, we expand this analysis with additional non-enzymatic proteins and apply our findings to design novel protein production optimization. By leveraging the Precise-1K transcriptomics knowledge base, we identify three iModulons as novel transcriptional responses to protein production stress; Cold Shock, gcvB sRNA, and the uncharacterized UC-9 iModulons. By studying the gene membership in the UC-9 iModulon, we discover effective novel design targets for improving protein production. This study demonstrates the value of big data analytics and systems understanding of host responses for designing novel strategies to optimize protein production.

Pectin deconstruction is the initial step in breaking the recalcitrance of plant biomass by using selected microorganisms that carry pectinolytic enzymes. Pectate lyases that cleave -1,4-galacturonosidic linkage of pectin are widely used in industries, such as paper making and fruit softening. However, reports on pectate lyases with high thermostability are few. Two pectate lyases (CbPL3 and CbPL9) from a thermophilic bacterium Caldicellulosiruptor bescii were investigated. Although these two enzymes belonged to different families of polysaccharide lyase, both were Ca2+-dependent. Similar biochemical properties were shown under optimized conditions 80 {degrees}C-85 {degrees}C and pH 8-9. However, the degradation products on pectin and polygalacturonic acids (pGA) were different, revealing the distinct mode of action. A concanavalin A-like lectin/glucanase (CALG) domain, located in the N-terminus of two CbPLs, shares 100% amino acid identity. CALG-truncated mutant of CbPL9 showed lower activities than the wild-type, whereas the CbPL3 with CALG knock-out portion was reported with enhanced activities, thereby revealing the different roles of CALG in two CbPLs. I-TASSER predicted that the CALG in two CbPLs is structurally close to the family 66 carbohydrate binding module (CBM66). Furthermore, substrate-binding assay indicated that the catalytic domains in two CbPLs had strong affinities on pectate-related substrates, but CALG showed weak interaction with a number of lignocellulosic carbohydrates, except sodium carboxymethyl cellulose and sodium alginate. Finally, scanning electron microscope analysis and total reducing sugar assay showed that the two enzymes could improve the saccharification of switchgrass. The two CbPLs are impressive sources for degradation of plant biomass. ImportanceThermophilic proteins could be implemented in diverse industrial applications. We sought to characterize two pectate lyases, CbPL3 and CbPL9, from a thermophilic bacterium Caldicellulosiruptor bescii. The two enzymes had high optimum temperature, low optimum pH, and good thermostability at evaluated temperature. A family-66 carbohydrate binding module (CBM66) was identified in two CbPLs with sharing 100% amino acid identity. Deletion of CBM66 obviously decreased the activity of CbPL9, but increase the activity and thermostability of CbPL3, suggesting the different roles of CBM66 in two enzymes. Moreover, the degradation products by two CbPLs were different. These results revealed these enzymes could represent a potential pectate lyase for applications in paper and textile industries.

The soil dwelling bacteria Streptomyces is an abundant producer of numerous anticancer, antifungal, and antibiotic compounds (i.e. Natural Products, NPs). The sophisticated cellular machinery required to produce NPs is frequently regulated by quorum-sensing systems, consisting of cluster situated regulators (CSRs), such as TetR-like repressors, and small-molecule autoregulator (AR) ligands. Only a small fraction of bioinformatically predicted quorum-sensing AR circuits have been experimentally determined, and fewer still have been engineered as inducible expression systems for synthetic biology. This research details the development of eight CSR-based AR biosensors and the synthetic routes to their AR ligands. Overall, the AR biosensors exhibit a range of maximum activation, AR affinity, and AR selectivity. We examined crosstalk between noncognate CSRs and ARs, as well as the ability of CSRs to regulate alternative operators. Additionally, we establish these biosensors can be cocultured with Streptomyces for rapid analysis of AR production. Finally, we demonstrate the CSR-based biosensor vectors can be combined to create orthogonal signaling systems in bacterial coculturing or multi-input genetic circuits. Longterm, these Streptomyces AR biosensors will contribute to the elucidation of small molecule quorum sensing circuits employed by Streptomyces as well as increasing the complexity of genetic circuits used in industrial or agricultural settings.

Cyanophages are considered a promising biological management option for treating cyanobacterial blooms. Broadening the host range of cyanophages and/or shortening the lysis cycle by designing and synthesizing artificial cyanophages are potential strategies to enhance their effectiveness and efficiency. However, the rescue of artificial cyanophage genomes remains unexplored. In this study, we achieved the integration of a full-length cyanophage genome, PP, which originally infects Plectonema boryanum FACHB-240, into the model cyanobacterium Synechococcus elongatus PCC 7942. Since the integration of these large fragments ([~]42 kb) into cyanobacteria depended on conjugation via Escherichia coli, the toxic open reading frames (ORFs) of PP to E. coli were first identified, leading to the identification of toxic ORF6, ORF11, and ORF22. The original PP genome was then rearranged, and the three toxic ORFs were controlled using a tandem induction switch. The full length of the PP genome was integrated into the genome of S. elongatus PCC 7942 via two rounds of homologous recombination. Interestingly, compared to the control strain, the integration of the PP genome decreased photosynthesis and carbon fixation in S. elongatus PCC 7942, exhibiting cyanophage-like behavior. Transcriptomic analysis revealed that 32 of the 41 ORFs of the PP genome were transcribed in S. elongatus PCC 7942, significantly altering the energy metabolism and carbon fixation pathways. These influences were further demonstrated using metabolomics. This study provides a comprehensive approach for the artificial design and integration of cyanophage genomes in cyanobacteria, laying the foundation for their real rescue in the future.

The Gram-positive model bacterium Bacillus subtilis is used for many biotechnological applications, including the large-scale production of vitamins. For vitamin B5, a precursor for coenzyme A synthesis, there is so far no established fermentation process available, partly due to the incomplete knowledge on the metabolic pathways that involve this vitamin. In this study, we have elucidated the complete pathways for the biosynthesis pantothenate and coenzyme A in B. subtilis. We have identified the enzymes involved in the pathway and have identified a salvage pathway for coenzyme A acquisition that acts on complex medium even in the absence of pantothenate synthesis. This pathway requires rewiring of sulfur metabolism resulting in the expression of a cysteine transporter. In the salvage pathway, the bacteria import cysteinopantetheine, a novel naturally occurring metabolite, using the cystine transport system TcyJKLMN. This work lays the foundation for the development of effective processes for vitamin B5 production.

Functional microbial agents play a crucial role in various fields such as agriculture, feed fermentation, aquaculture, and environmental protection. However, traditional microbial agents were confronted with critical challenges such as limited shelf-life, reduced activity, and inconsistent efficacy. In this case, we innovatively proposed the concept of Directed Micro-Ecology (DME) and developed its application system, including a core module named DME intelligent fermentor (DME25). Over 40 functional strains, including bacterial strains and fungus strains, were successfully cultured to 10[~]50 x108 CFU/mL within 20[~]48 h and maintained a relatively low contamination rate (<2.5%). Finally, the stability and effectiveness of these DME-fermented strains were validated in different application areas, all of which exhibited perfect functional characteristics. Firstly, the bacillus strains inhibited the progression of wilt disease and significantly improved the growth of tomatoes. Secondly, all tested lactobacillus strains improved the nutrition and quality of fermented feed, complying with feed industry standards. Lastly, the ammonia nitrogen concentration, nitrite concentration of aquaculture water and phosphate concentration, COD of aquaculture tail water were significantly reduced within 1[~]4 d. The successful application of the DME intelligent fermentor in different fields marks a pivotal breakthrough in technological innovation of microbial agents on-site one-step fermentation. This technological advancement opens new avenues for enhancing the stability and effectiveness of microbial agents, infusing powerful impetus to the development of microbial application.

Zymomonas mobilis metabolizes sugar through the Entner-Doudoroff pathway with less ATP generated for lower biomass accumulation and more substrate to product formation with improved yield, since ATP is dissipated predominately through growth for intracellular energy homeostasis, making it a platform to be engineered as microbial cell factories, particularly for producing bulk commodities with major cost from feedstock consumption. ZM401, a self-flocculating mutant, presents advantages for production including cost-effective biomass recovery through gravity sedimentation, self-immobilization within bioreactors for high cell density to improve productivity and enhanced tolerance to environmental stresses for high product titers, but molecular mechanism underlying this phenotype is largely unknown. In this work, we sequenced and assembled the genome of ZM401 to explore genetic basis for the self-flocculation of the bacterial cells through comparative genomic and transcriptomic analyses, molecular docking simulations for enzymes encoded by functional genes and their substrates/activators, and experimental validations. Our results demonstrated that the single nucleotide deletion in ZMO1082 disrupted its stop codon for the putative gene being fused with ZMO1083, which created an exciting gene encoding the subunit A of the bacterial cellulose synthase with unique function for synthesizing cellulose microfibrils to flocculate the bacterial cells, and the single nucleotide mutation in ZMO1055 compromised the function of bifunctional diguanylate cyclase/phosphodiesterase encoded by the gene on the degradation of c-di-GMP for its intracellular accumulation to activate the cellulose biosynthesis. These discoveries are significant not only for optimizing the self-flocculation of Z. mobilis, but also engineering other bacteria with the self-flocculating phenotype for robust production.

Improving catalytic ability of protein biocatalysts leads to reduction in the production cost of biocatalytic manufacturing process, but the search space of possible proteins/mutants is too large to explore exhaustively through experiments. To some extent, highly soluble recombinant proteins tend to exhibit high activity. Here, we demonstrate that an optimization methodology based on machine learning prediction model can effectively predict which peptide tags can improve protein solubility quantitatively. Based on the protein sequence information, a support vector machine model we recently developed was used to evaluate protein solubility after randomly mutated tags were added to a target protein. The optimization algorithm guided the tags to evolve towards variants that can result in higher solubility. Moreover, the optimization results were validated successfully by adding the tags designed by our optimization algorithm to a model protein, expressing it in vivo and experimentally quantifying its solubility and activity. For example, solubility of a tyrosine ammonium lyase was more than doubled by adding two tags to its N- and C-terminus. Its protein activity was also increased nearly 3.5 fold by adding the tags. Additional experiments also supported that the designed tags were effective for improving activity of multiple proteins and are better than previously reported tags. The presented optimization methodology thus provides a valuable tool for understanding the correlation between amino acid sequence and protein solubility and for engineering protein biocatalysts.\n\nContactkang.zhou@nus.edu.sg, chewxia@nus.edu.sg

Purple non-sulfur photosynthetic bacteria (PNSB) such as R. capsulatus serve as a versatile platform for fundamental studies and various biotechnological applications. In this study, we sought to develop the class II RNA-guided CRISPR/Cas12a system from Francisella novicida for both genome editing and gene down-regulation in R. capsulatus. About 90% editing efficiency was achieved by using CRISPR/Cas12a driven by a strong promoter Ppuc when targeting ccoO or nifH gene. When both genes were simultaneously targeted, the multiplex gene editing efficiency reached >63%. In addition, CRISPR interference using deactivated Cas12a was also evaluated using reporter genes gfp and lacZ, and the repression efficiency reached >80%. In summary, our work represents the first report to develop CRISPR/Cas12a mediated genome editing/transcriptional repression in R. capsulatus, which would greatly accelerate PNSB-related researches. IMPORTANCEPurple non-sulfur photosynthetic bacteria (PNSB) such as R. capsulatus serve as a versatile platform for fundamental studies and various biotechnological applications. However, lack of efficient gene editing tools remains a main obstacle for progressing in PNSB-related researches. Here, we developed CRISPR/Cas12a for genome editing via the non-homologous end joining (NHEJ) repair machinery in R. capsulatus. In addition, DNase-deactivated Cas12a was found to simultaneously suppress multiple targeted genes. Taken together, our work offers a new set of tools for efficient genome engineering in PNSB such as R. capsulatus.