Biocomposite thermoplastic polyurethanes containing evolved bacterial spores as living fillers to facilitate polymer disintegration.

The field of hybrid engineered living materials seeks to pair living organisms with synthetic materials to generate biocomposite materials with augmented function since living systems can provide highly-programmable and complex behavior. Engineered living materials have typically been fabricated using techniques in benign aqueous environments, limiting their application. In this work, biocomposite fabrication is demonstrated in which spores from polymer-degrading bacteria are incorporated into a thermoplastic polyurethane using high-temperature melt extrusion. Bacteria are engineered using adaptive laboratory evolution to improve their heat tolerance to ensure nearly complete cell survivability during manufacturing at 135 °C. Furthermore, the overall tensile properties of spore-filled thermoplastic polyurethanes are substantially improved, resulting in a significant improvement in toughness. The biocomposites facilitate disintegration in compost in the absence of a microbe-rich environment. Finally, embedded spores demonstrate a rationally programmed function, expressing green fluorescent protein. This research provides a scalable method to fabricate advanced biocomposite materials in industrially-compatible processes.

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440.

There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules ("functional modules"), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida. Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE: This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

Direct and robust citramalate production from brown macroalgae using fast-growing Vibrio sp. dhg.

Brown macroalgae is a promising feedstock for biorefinery owing to its high biomass productivity and contents of carbohydrates such as alginate and mannitol. However, the limited availability of microbial platforms efficiently catabolizing the brown macroalgae sugars has restricted its utilization. In this study, the direct production of citramalate, an important industrial compound, was demonstrated from brown macroalgae by utilizing Vibrio sp. dhg, which has a remarkably efficient catabolism of alginate and mannitol. Specifically, citramalate synthase from Methanocaldococcus jannaschii was synthetically expressed, and competing pathways were removed to maximally redirect the carbon flux toward citramalate production. Notably, a resulting strain, VXHC, produced citramalate up to 9.8 g/L from a 20 g/L mixture of alginate and mannitol regardless of their ratios. Citramalate was robustly produced even when diverse brown macroalgae were provided directly. Collectively, this study showcased the high potential of brown macroalgae biorefinery using Vibrio sp. dhg.

CyuR is a Dual Regulator for L-Cysteine Dependent Antimicrobial Resistance in Escherichia coli.

Hydrogen sulfide (H 2 S), mainly produced from L-cysteine (Cys), renders bacteria highly resistant to oxidative stress. This mitigation of oxidative stress was suggested to be an important survival mechanism to achieve antimicrobial resistance (AMR) in many pathogenic bacteria. CyuR (known as DecR or YbaO) is a recently characterized Cys-dependent transcription regulator, responsible for the activation of the cyuAP operon and generation of hydrogen sulfide from Cys. Despite its potential importance, the regulatory network of CyuR remains poorly understood. In this study, we investigated the roles of the CyuR regulon in a Cys-dependent AMR mechanism in E. coli strains. We found: 1) Cys metabolism has a significant role in AMR and its effect is conserved in many E. coli strains, including clinical isolates; 2) CyuR negatively controls the expression of mdlAB encoding a transporter that exports antibiotics such as cefazolin and vancomycin; 3) CyuR binds to a DNA sequence motif 'GAAwAAATTGTxGxxATTTsyCC' in the absence of Cys, confirmed by an in vitro binding assay; and 4) CyuR may regulate 25 additional genes as suggested by in silico motif scanning and transcriptome sequencing. Collectively, our findings expanded the understanding of the biological roles of CyuR relevant to antibiotic resistance associated with Cys.

Elucidation of independently modulated genes in Streptococcus pyogenes reveals carbon sources that control its expression of hemolytic toxins.

Streptococcus pyogenes can cause a wide variety of acute infections throughout the body of its human host. An underlying transcriptional regulatory network (TRN) is responsible for altering the physiological state of the bacterium to adapt to each unique host environment. Consequently, an in-depth understanding of the comprehensive dynamics of the S. pyogenes TRN could inform new therapeutic strategies. Here, we compiled 116 existing high-quality RNA sequencing data sets of invasive S. pyogenes serotype M1 and estimated the TRN structure in a top-down fashion by performing independent component analysis (ICA). The algorithm computed 42 independently modulated sets of genes (iModulons). Four iModulons contained the nga-ifs-slo virulence-related operon, which allowed us to identify carbon sources that control its expression. In particular, dextrin utilization upregulated the nga-ifs-slo operon by activation of two-component regulatory system CovRS-related iModulons, altering bacterial hemolytic activity compared to glucose or maltose utilization. Finally, we show that the iModulon-based TRN structure can be used to simplify the interpretation of noisy bacterial transcriptome data at the infection site. IMPORTANCE S. pyogenes is a pre-eminent human bacterial pathogen that causes a wide variety of acute infections throughout the body of its host. Understanding the comprehensive dynamics of its TRN could inform new therapeutic strategies. Since at least 43 S. pyogenes transcriptional regulators are known, it is often difficult to interpret transcriptomic data from regulon annotations. This study shows the novel ICA-based framework to elucidate the underlying regulatory structure of S. pyogenes allows us to interpret the transcriptome profile using data-driven regulons (iModulons). Additionally, the observations of the iModulon architecture lead us to identify the multiple regulatory inputs governing the expression of a virulence-related operon. The iModulons identified in this study serve as a powerful guidepost to further our understanding of S. pyogenes TRN structure and dynamics.

Laboratory evolution reveals general and specific tolerance mechanisms for commodity chemicals.

Although strain tolerance to high product concentrations is a barrier to the economically viable biomanufacturing of industrial chemicals, chemical tolerance mechanisms are often unknown. To reveal tolerance mechanisms, an automated platform was utilized to evolve Escherichia coli to grow optimally in the presence of 11 industrial chemicals (1,2-propanediol, 2,3-butanediol, glutarate, adipate, putrescine, hexamethylenediamine, butanol, isobutyrate, coumarate, octanoate, hexanoate), reaching tolerance at concentrations 60%-400% higher than initial toxic levels. Sequencing genomes of 223 isolates from 89 populations, reverse engineering, and cross-compound tolerance profiling were employed to uncover tolerance mechanisms. We show that: 1) cells are tolerized via frequent mutation of membrane transporters or cell wall-associated proteins (e.g., ProV, KgtP, SapB, NagA, NagC, MreB), transcription and translation machineries (e.g., RpoA, RpoB, RpoC, RpsA, RpsG, NusA, Rho), stress signaling proteins (e.g., RelA, SspA, SpoT, YobF), and for certain chemicals, regulators and enzymes in metabolism (e.g., MetJ, NadR, GudD, PurT); 2) osmotic stress plays a significant role in tolerance when chemical concentrations exceed a general threshold and mutated genes frequently overlap with those enabling chemical tolerance in membrane transporters and cell wall-associated proteins; 3) tolerization to a specific chemical generally improves tolerance to structurally similar compounds whereas a tradeoff can occur on dissimilar chemicals, and 4) using pre-tolerized starting isolates can hugely enhance the subsequent production of chemicals when a production pathway is inserted in many, but not all, evolved tolerized host strains, underpinning the need for evolving multiple parallel populations. Taken as a whole, this study provides a comprehensive genotype-phenotype map based on identified mutations and growth phenotypes for 223 chemical tolerant isolates.

Revealing oxidative pentose metabolism in new Pseudomonas putida isolates.

The Pseudomonas putida group in the Gammaproteobacteria has been intensively studied for bioremediation and plant growth promotion. Members of this group have recently emerged as promising hosts to convert intermediates derived from plant biomass to biofuels and biochemicals. However, most strains of P. putida cannot metabolize pentose sugars derived from hemicellulose. Here, we describe three isolates that provide a broader view of the pentose sugar catabolism in the P. putida group. One of these isolates clusters with the well-characterized P. alloputida KT2440 (Strain BP6); the second isolate clustered with plant growth-promoting strain P. putida W619 (Strain M2), while the third isolate represents a new species in the group (Strain BP8). Each of these isolates possessed homologous genes for oxidative xylose catabolism (xylDXA) and a potential xylonate transporter. Strain M2 grew on arabinose and had genes for oxidative arabinose catabolism (araDXA). A CRISPR interference (CRISPRi) system was developed for strain M2 and identified conditionally essential genes for xylose growth. A glucose dehydrogenase was found to be responsible for initial oxidation of xylose and arabinose in strain M2. These isolates have illuminated inherent diversity in pentose catabolism in the P. putida group and may provide alternative hosts for biomass conversion.

Circuit-guided population acclimation of a synthetic microbial consortium for improved biochemical production.

Microbial consortia have been considered potential platforms for bioprocessing applications. However, the complexity in process control owing to the use of multiple strains necessitates the use of an efficient population control strategy. Herein, we report circuit-guided synthetic acclimation as a strategy to improve biochemical production by a microbial consortium. We designed a consortium comprising alginate-utilizing Vibrio sp. dhg and 3-hydroxypropionic acid (3-HP)-producing Escherichia coli strains for the direct conversion of alginate to 3-HP. We introduced a genetic circuit, named "Population guider", in the E. coli strain, which degrades ampicillin only when 3-HP is produced. In the presence of ampicillin as a selection pressure, the consortium was successfully acclimated for increased 3-HP production by 4.3-fold compared to that by a simple co-culturing consortium during a 48-h fermentation. We believe this concept is a useful strategy for the development of robust consortium-based bioprocesses.

A Vibrio-based microbial platform for accelerated lignocellulosic sugar conversion.

BACKGROUND: Owing to increasing concerns about climate change and the depletion of fossil fuels, the development of efficient microbial processes for biochemical production from lignocellulosic biomass has been a key issue. Because process efficiency is greatly affected by the inherent metabolic activities of host microorganisms, it is essential to utilize a microorganism that can rapidly convert biomass-derived sugars. Here, we report a novel Vibrio-based microbial platform that can rapidly and simultaneously consume three major lignocellulosic sugars (i.e., glucose, xylose, and arabinose) faster than any previously reported microorganisms. RESULTS: The xylose isomerase pathway was constructed in Vibrio sp. dhg, which naturally displays high metabolic activities on glucose and arabinose but lacks xylose catabolism. Subsequent adaptive laboratory evolution significantly improved xylose catabolism of initial strain and led to unprecedently high growth and sugar uptake rate (0.67 h-1 and 2.15 g gdry cell weight-1 h-1, respectively). Furthermore, we achieved co-consumption of the three sugars by deletion of PtsG and introduction of GalP. We validated its superior performance and applicability by demonstrating efficient lactate production with high productivity (1.15 g/L/h) and titer (83 g/L). CONCLUSIONS: In this study, we developed a Vibrio-based microbial platform with rapid and simultaneous utilization of the three major sugars from lignocellulosic biomass by applying an integrated approach of rational and evolutionary engineering. We believe that the developed strain can be broadly utilized to accelerate the production of diverse biochemicals from lignocellulosic biomass.

A systems approach discovers the role and characteristics of seven LysR type transcription factors in Escherichia coli.

Although Escherichia coli K-12 strains represent perhaps the best known model bacteria, we do not know the identity or functions of all of their transcription factors (TFs). It is now possible to systematically discover the physiological function of TFs in E. coli BW25113 using a set of synergistic methods; including ChIP-exo, growth phenotyping, conserved gene clustering, and transcriptome analysis. Among 47 LysR-type TFs (LTFs) found on the E. coli K-12 genome, many regulate nitrogen source utilization or amino acid metabolism. However, 19 LTFs remain unknown. In this study, we elucidated the regulation of seven of these 19 LTFs: YbdO, YbeF, YcaN, YbhD, YgfI, YiaU, YneJ. We show that: (1) YbdO (tentatively re-named CitR) regulation has an effect on bacterial growth at low pH with citrate supplementation. CitR is a repressor of the ybdNM operon and is implicated in the regulation of citrate lyase genes (citCDEFG); (2) YgfI (tentatively re-named DhfA) activates the dhaKLM operon that encodes the phosphotransferase system, DhfA is involved in formate, glycerol and dihydroxyacetone utilization; (3) YiaU (tentatively re-named LpsR) regulates the yiaT gene encoding an outer membrane protein, and waaPSBOJYZU operon is also important in determining cell density at the stationary phase and resistance to oxacillin microaerobically; (4) YneJ, re-named here as PtrR, directly regulates the expression of the succinate-semialdehyde dehydrogenase, Sad (also known as YneI), and is a predicted regulator of fnrS (a small RNA molecule). PtrR is important for bacterial growth in the presence of L-glutamate and putrescine as nitrogen/energy sources; and (5) YbhD and YcaN regulate adjacent y-genes on the genome. We have thus established the functions for four LTFs and identified the target genes for three LTFs.

Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network.

Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.

Synthetic cellular communication-based screening for strains with improved 3-hydroxypropionic acid secretion.

Although cellular secretion is important in industrial biotechnology, its assessment is difficult due to the lack of efficient analytical methods. This study describes a synthetic cellular communication-based microfluidic platform for screening strains with the improved secretion of 3-hydroxypropionic acid (3-HP), an industry-relevant platform chemical. 3-HP-secreting cells were compartmentalized in droplets, with receiving cells equipped with a genetic circuit that converts the 3-HP secretion level into an easily detectable signal. This platform was applied to identify Escherichia coli genes that enhance the secretion of 3-HP. As a result, two genes (setA, encoding a sugar exporter, and yjcO, encoding a Sel1 repeat-containing protein) found by this platform enhance the secretion of 3-HP and its production. Given the increasing design capability for chemical-detecting cells, this platform has considerable potential in identifying efflux pumps for not only 3-HP but also many important chemicals.

Unraveling the functions of uncharacterized transcription factors in Escherichia coli using ChIP-exo.

Bacteria regulate gene expression to adapt to changing environments through transcriptional regulatory networks (TRNs). Although extensively studied, no TRN is fully characterized since the identity and activity of all the transcriptional regulators comprising a TRN are not known. Here, we experimentally evaluate 40 uncharacterized proteins in Escherichia coli K-12 MG1655, which were computationally predicted to be transcription factors (TFs). First, we used a multiplexed chromatin immunoprecipitation method combined with lambda exonuclease digestion (multiplexed ChIP-exo) assay to characterize binding sites for these candidate TFs; 34 of them were found to be DNA-binding proteins. We then compared the relative location between binding sites and RNA polymerase (RNAP). We found 48% (283/588) overlap between the TFs and RNAP. Finally, we used these data to infer potential functions for 10 of the 34 TFs with validated DNA binding sites and consensus binding motifs. Taken together, this study: (i) significantly expands the number of confirmed TFs to 276, close to the estimated total of about 280 TFs; (ii) provides putative functions for the newly discovered TFs and (iii) confirms the functions of four representative TFs through mutant phenotypes.

Plug-in repressor library for precise regulation of metabolic flux in Escherichia coli.

In metabolic engineering, enhanced production of value-added chemicals requires precise flux control between growth-essential competing and production pathways. Although advances in synthetic biology have facilitated the exploitation of a number of genetic elements for precise flux control, their use requires expensive inducers, or more importantly, needs complex and time-consuming processes to design and optimize appropriate regulator components, case-by-case. To overcome this issue, we devised the plug-in repressor libraries for target-specific flux control, in which expression levels of the repressors were diversified using degenerate 5' untranslated region (5' UTR) sequences employing the UTR Library Designer. After we validated a wide expression range of the repressor libraries, they were applied to improve the production of lycopene from glucose and 3-hydroxypropionic acid (3-HP) from acetate in Escherichia coli via precise flux rebalancing to enlarge precursor pools. Consequently, we successfully achieved optimal carbon fluxes around the precursor nodes for efficient production. The most optimized strains were observed to produce 2.59 g/L of 3-HP and 11.66 mg/L of lycopene, which were improved 16.5-fold and 2.82-fold, respectively, compared to those produced by the parental strains. These results indicate that carbon flux rebalancing using the plug-in library is a powerful strategy for efficient production of value-added chemicals in E. coli.

Identification of a transcription factor, PunR, that regulates the purine and purine nucleoside transporter punC in E. coli.

Many genes in bacterial genomes are of unknown function, often referred to as y-genes. Recently, the analytic methods have divided bacterial transcriptomes into independently modulated sets of genes (iModulons). Functionally annotated iModulons that contain y-genes lead to testable hypotheses to elucidate y-gene function. The inversely correlated expression of a putative transporter gene, ydhC, relative to purine biosynthetic genes, has led to the hypothesis that it encodes a purine-related transporter and revealed a LysR-family regulator, YdhB, with a predicted 23-bp palindromic binding motif. RNA-Seq analysis of a ydhB knockout mutant confirmed the YdhB-dependent activation of ydhC in the presence of adenosine. The deletion of either the ydhC or the ydhB gene led to a substantially decreased growth rate for E. coli in minimal medium with adenosine, inosine, or guanosine as the nitrogen source. Taken together, we provide clear evidence that YdhB activates the expression of the ydhC gene that encodes a purine transporter in E. coli. We propose that the genes ydhB and ydhC be re-named as punR and punC, respectively.

Synthetic biosensor accelerates evolution by rewiring carbon metabolism toward a specific metabolite.

Proper carbon flux distribution between cell growth and production of a target compound is important for biochemical production because improper flux reallocation inhibits cell growth, thus adversely affecting production yield. Here, using a synthetic biosensor to couple production of a specific metabolite with cell growth, we spontaneously evolve cells under the selective condition toward the acquisition of genotypes that optimally reallocate cellular resources. Using 3-hydroxypropionic acid (3-HP) production from glycerol in Escherichia coli as a model system, we determine that mutations in the conserved regions of proteins involved in global transcriptional regulation alter the expression of several genes associated with central carbon metabolism. These changes rewire central carbon flux toward the 3-HP production pathway, increasing 3-HP yield and reducing acetate accumulation by alleviating overflow metabolism. Our study provides a perspective on adaptive laboratory evolution (ALE) using synthetic biosensors, thereby supporting future efforts in metabolic pathway optimization.

Design of mutualistic microbial consortia for stable conversion of carbon monoxide to value-added chemicals.

Carbon monoxide (CO) is a promising carbon source for producing value-added biochemicals via microbial fermentation. However, its microbial conversion has been challenging because of difficulties in genetic engineering of CO-utilizing microorganisms and, more importantly, maintaining CO consumption which is negatively affected by the toxicity of CO and accumulated byproducts. To overcome these issues, we devised mutualistic microbial consortia, co-culturing Eubacterium limosum and genetically engineered Escherichia coli for the production of 3-hydroxypropionic acid (3-HP) and itaconic acid (ITA). During the co-culture, E. limosum assimilated CO and produced acetate, a toxic by-product, while E. coli utilized acetate as a sole carbon source. We found that this mutualistic interaction dramatically stabilized and improved CO consumption of E. limosum compared to monoculture. Consequently, the improved CO consumption allowed successful production of 3-HP and ITA from CO. This study is the first demonstration of value-added biochemical production from CO using a microbial consortium. Moreover, it suggests that synthetic mutualistic microbial consortium can serve as a powerful platform for the valorization of CO.

Auxotrophic Selection Strategy for Improved Production of Coenzyme B12 in Escherichia coli.

The production of coenzyme B12 using well-characterized microorganisms, such as Escherichia coli, has recently attracted considerable attention to meet growing demands of coenzyme B12 in various applications. In the present study, we designed an auxotrophic selection strategy and demonstrated the enhanced production of coenzyme B12 using a previously engineered coenzyme B12-producing E. coli strain. To select a high producer, the coenzyme B12-independent methionine synthase (metE) gene was deleted in E. coli, thus limiting its methionine synthesis to only that via coenzyme B12-dependent synthase (encoded by metH). Following the deletion of metE, significantly enhanced production of the specific coenzyme B12 validated the coenzyme B12-dependent auxotrophic growth. Further precise tuning of the auxotrophic system by varying the expression of metH substantially increased the cell biomass and coenzyme B12 production, suggesting that our strategy could be effectively applied to E. coli and other coenzyme B12-producing strains.

Vibrio sp. dhg as a platform for the biorefinery of brown macroalgae.

Although brown macroalgae holds potential as an alternative feedstock, its utilization by conventional microbial platforms has been limited due to the inability to metabolize one of the principal sugars, alginate. Here, we isolate Vibrio sp. dhg, a fast-growing bacterium that can efficiently assimilate alginate. Based on systematic characterization of the genomic information of Vibrio sp. dhg, we establish a genetic toolbox for its engineering. We also demonstrate its ability to rapidly produce ethanol, 2,3-butanediol, and lycopene from brown macroalgae sugar mixture with high productivities and yields. Collectively, Vibrio sp. dhg can be used as a platform for the efficient conversion of brown macroalgae sugars into diverse value-added biochemicals.

Bicontinuous Interfacially Jammed Emulsion Gels (bijels) as Media for Enabling Enzymatic Reactive Separation of a Highly Water Insoluble Substrate.

Although enzymes are efficient catalysts capable of converting various substrates into desired products with high specificity under mild conditions, their effectiveness as catalysts is substantially reduced when substrates are poorly water-soluble. In this study, to expedite the enzymatic conversion of a hydrophobic substrate, we use a bicontinuous interfacially jammed emulsion gel (bijel) which provides large interfacial area between two immiscible liquids: oil and water. Using lipase-catalyzed hydrolysis of tributyrin as a model reaction in a batch mode, we show that bijels can be used as media to enable enzymatic reaction. The bijel system gives a four-fold increase in the initial reaction rate in comparison to a stirred biphasic medium. Our results demonstrate that bijels are powerful biphasic reaction media to accelerate enzymatic reactions with various hydrophobic reagents. This work also demonstrates that bijels can potentially be used as reaction media to enable continuous reactive separations.