An ancient Chinese wisdom for metabolic engineering: Yin-Yang

Rapid Biodegradation of the Organophosphorus Insecticide Acephate by a Novel Strain Burkholderia sp. A11 and Its Impact on the Structure of the Indigenous Microbial Community

The acephate-degrading microbes that are currently available are not optimal. In this study, Burkholderia sp. A11, an efficient degrader of acephate, presented an acephate-removal efficiency of 83.36% within 56 h (100 mg·L^-1). The A11 strain has a broad substrate tolerance and presents a good removal effect in the concentration range 10-1600 mg·L^-1. Six metabolites from the degradation of acephate were identified, among which the main products were methamidophos, acetamide, acetic acid, methanethiol, and dimethyl disulfide. The main degradation pathways involved include amide bond breaking and phosphate bond hydrolysis. Moreover, strain A11 successfully colonized and substantially accelerated acephate degradation in different soils, degrading over 90% of acephate (50-200 mg·kg^-1) within 120 h. 16S rDNA sequencing results further confirmed that the strain A11 gradually occupied a dominant position in the soil microbial communities, causing slight changes in the diversity and composition of the indigenous soil microbial community structure.

The pathogenesis and treatment mechanism of Parkinson's disease from the perspective of traditional Chinese medicine

BACKGROUND

Parkinson's disease (PD) is the second most common neurodegenerative disease with no treatment currently available to modify its progression. Traditional Chinese medicine (TCM) has gained attention for its unique theoretical basis and clinical effects. Many studies have reported on the clinical effects and pharmacological mechanisms of Chinese herbs in PD. However, few studies have focused on the treatment mechanisms of anti-PD TCM drugs from the perspective of TCM itself.

PURPOSE

To elaborate the treatment mechanisms of anti-PD TCM drugs in the perspective of TCM.

METHODS

We performed a literature survey using traditional books of Chinese medicine and online scientific databases including PubMed, Web of Science, Google Scholar, China National Knowledge Infrastructure (CNKI), and others up to July 2021.

RESULTS

TCM theory states that PD is caused by a dysfunction of the zang-fu organs (liver, spleen, kidney, and lung) and subsequent pathogenic factors (wind, fire, phlegm, and blood stasis). Based on the pathogenesis, removing pathogenic factors and restoring visceral function are two primary treatment principles for PD in TCM. The former includes dispelling wind, clearing heat, resolving phlegm, and promoting blood circulation, while the latter involves nourishing the liver and kidney and strengthening the spleen. The anti-PD mechanisms of the active ingredients of TCM compounds and herbs at different levels include anti-apoptosis, anti-inflammation, and anti-oxidative stress, as well as the restoration of mitochondrial function and the regulation of autophagy and neurotransmitters.

CONCLUSION

Chinese herbs and prescriptions can be used to treat PD by targeting multiple pharmacological mechanisms.

Novel pathway of acephate degradation by the microbial consortium ZQ01 and its potential for environmental bioremediation

The microbial degradation of acephate in pure cultures has been thoroughly explored, but synergistic metabolism at the community level has rarely been investigated. Here, we report a novel microbial consortium, ZQ01, capable of effectively degrading acephate and its toxic product methamidophos, which can use acephate as a source of carbon, phosphorus and nitrogen. The degradation conditions with consortium ZQ01 were optimized using response surface methodology at a temperature of 34.1 °C, a pH of 8.9, and an inoculum size of 2.4 × 10⁸ CFU·mL^-1, with 89.5% of 200 mg L^-1 acephate degradation observed within 32 h. According to the main products methamidophos, acetamide and acetic acid, a novel degradation pathway for acephate was proposed to include hydrolysis and oxidation as the main pathways of acephate degradation. Moreover, the bioaugmentation of acephate-contaminated soils with consortium ZQ01 significantly enhanced the removal rate of acephate. The results of the present work demonstrate the potential of microbial consortium ZQ01 to degrade acephate in water and soil environments, with a different and complementary acephate degradation pathway.

A light tunable differentiation system for the creation and control of consortia in yeast

Artificial microbial consortia seek to leverage division-of-labour to optimize function and possess immense potential for bioproduction. Co-culturing approaches, the preferred mode of generating a consortium, remain limited in their ability to give rise to stable consortia having finely tuned compositions. Here, we present an artificial differentiation system in budding yeast capable of generating stable microbial consortia with custom functionalities from a single strain at user-defined composition in space and in time based on optogenetically-driven genetic rewiring. Owing to fast, reproducible, and light-tunable dynamics, our system enables dynamic control of consortia composition in continuous cultures for extended periods. We further demonstrate that our system can be extended in a straightforward manner to give rise to consortia with multiple subpopulations. Our artificial differentiation strategy establishes a novel paradigm for the creation of complex microbial consortia that are simple to implement, precisely controllable, and versatile to use.

Biotechnological basis of microbial consortia for the removal of pesticides from the environment

The application of microbial strains as axenic cultures has frequently been employed in a diverse range of sectors. In the natural environment, microbes exist as multispecies and perform better than monocultures. Cell signaling and communication pathways play a key role in engineering microbial consortia, because in a consortium, the microorganisms communicate via diffusible signal molecules. Mixed microbial cultures have gained little attention due to the lack of proper knowledge about their interactions with each other. Some ideas have been proposed to deal with and study various microbes when they live together as a community, for biotechnological application purposes. In natural environments, microbes can possess unique metabolic features. Therefore, microbial consortia divide the metabolic burden among strains in the group and robustly perform pesticide degradation. Synthetic microbial consortia can perform the desired functions at naturally contaminated sites. Therefore, in this article, special attention is paid to the microbial consortia and their function in the natural environment. This review comprehensively discusses the recent applications of microbial consortia in pesticide degradation and environmental bioremediation. Moreover, the future directions of synthetic consortia have been explored. The review also explores the future perspectives and new platforms for these approaches, besides highlighting the practical understanding of the scientific information behind consortia.

Control strategies to manage trade-offs during microbial production

When engineering microbes to overproduce a target molecule, engineers face multiple layers of trade-offs to allocate limited cellular resources between the target pathway and native cellular systems. These trade-offs arise from limited free ribosomes during translation, competition for metabolic precursors, as well as the negative relationship between production and growth rate. To achieve high production performance, microbes need to spontaneously make decisions in the dynamic and heterogeneous fermentation environment. In this review, we discuss recent advances in microbial control strategies that are used to manage these trade-offs and to improve microbial production. This review focuses on design principles and compares different implementations, with the hope to provide guidelines to future microbial engineering.

Yeast as a promising heterologous host for steroid bioproduction

With the rapid development of synthetic biology and metabolic engineering technologies, yeast has been generally considered as promising hosts for the bioproduction of secondary metabolites. Sterols are essential components of cell membrane, and are the precursors for the biosynthesis of steroid hormones, signaling molecules, and defense molecules in the higher eukaryotes, which are of pharmaceutical and agricultural significance. In this mini-review, we summarize the recent engineering efforts of using yeast to synthesize various steroids, and discuss the structural diversity that the current steroid-producing yeast can achieve, the challenge and the potential of using yeast as the bioproduction platform of various steroids from higher eukaryotes.

Enhancing glutaric acid production in Escherichia coli by uptake of malonic acid

Glutaric acid is an important organic acid applied widely in different fields. Most previous researches have focused on the production of glutaric acid in various strains using the 5-aminovaleric acid (AMV) or pentenoic acid synthesis pathways. We previously utilized a five-step reversed adipic acid degradation pathway (RADP) in Escherichia coli BL21 (DE3) to construct strain Bgl146. Herein, we found that malonyl-CoA was strictly limited in this strain, and increasing its abundance could improve glutaric acid production. We, therefore, constructed a malonic acid uptake pathway in E. coli using matB (malonic acid synthetase) and matC (malonic acid carrier protein) from Clover rhizobia. The titer of glutaric acid was improved by 2.1-fold and 1.45-fold, respectively, reaching 0.56 g/L and 4.35 g/L in shake flask and batch fermentation following addition of malonic acid. Finally, the highest titer of glutaric acid was 6.3 g/L in fed-batch fermentation at optimized fermentation conditions.

Debottlenecking mevalonate pathway for antimalarial drug precursor amorphadiene biosynthesis in Yarrowia lipolytica

World Health Organization reports that half of the population in developing countries are at risk of malaria infection. Artemisinin, the most potent anti-malaria drug, is a sesquiterpene endoperoxide extracted from the plant Artemisia annua. Due to scalability and economics issues, plant extraction or chemical synthesis could not provide a sustainable route for large-scale manufacturing of artemisinin. The price of artemisinin has been fluctuating from 200$/Kg to 1100$/Kg, due to geopolitical and climate factors. Microbial fermentation was considered as a promising method to stabilize the artemisinin supply chain. Yarrowia lipolytica, is an oleaginous yeast with proven capacity to produce large quantity of lipids and oleochemicals. In this report, the lipogenic acetyl-CoA pathways and the endogenous mevalonate pathway of Y. lipolytica were harnessed for amorphadiene production. Gene overexpression indicate that HMG-CoA and acetyl-CoA supply are two limiting bottlenecks for amorphadiene production. We have identified the optimal HMG-CoA reductase and determined the optimal gene copy number for the precursor pathways. Amorphadiene production was improved further by either inhibiting fatty acids synthase or activating the fatty acid degradation pathway. With co-expression of mevalonate kinase (encoded by Erg12), a push-and-pull strategy enabled the engineered strain to produce 171.5 ​mg/L of amorphadiene in shake flasks. These results demonstrate that balancing carbon flux and manipulation of precursor competing pathways are key factors to improve amorphadiene biosynthesis in oleaginous yeast; and Y. lipolytica is a promising microbial host to expand nature’s biosynthetic capacity, allowing us to quickly access antimalarial drug precursors.

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Endogenous acetyl-CoA and mevalonate pathway were harnessed for amorphadiene synthesis.

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Expression of native untruncated HMG-CoA reductase (HMG1) removes rate-limiting steps.

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Balancing ADS, HMG1 and MVK activity effectively pull FPP flux toward amorphadiene.

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Activation of fatty acid degradation pushes carbon flux toward HMG-CoA pathways.

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A push-and-pull strategy boosts amorphadiene production to 171.5 ​mg/L in shake flasks.

CF-Targeter: A Rational Biological Cell Factory Targeting Platform for Biosynthetic Target Chemicals

Biosynthesis is a promising method for chemical synthesis. However, due to varieties between different microorganism hosts, yield and heterologous pathways needed for production of target chemical may also vary from different strains. One of the main challenges in metabolic engineering is to select an appropriate chassis host for specified target chemical production. However, with thousands of microorganisms existing in nature and extremely complicated metabolism within them, it is still time-consuming and error-prone work to achieve such a goal only through experimental methods, even with some existing computational methods. Hence, more efficient methods should be proposed to assist in selecting appropriate chassis hosts. In this article, based on symbolic reaction repositories and a pathway search algorithm which performed 1 400 000 searches for per target compound, we established a biological reasoning system for appropriate chassis host selection by coupling with various GEM-models. By using a supercomputer to calculate the biosynthetic pathways for more than 1 month, nearly 50 000 000 biosynthetic pathways are computed for production of 6026 compounds within 70 microorganisms. With retrieved organisms for specified target production, several heterologous biosynthetic pathways can be shown in length order, and then the maximum theoretical yields and thermodynamic feasibility can be calculated in real time under customized growth conditions and physiological states. From the computation results, the system not only identifies experimentally validated pathways but also outputs more efficient solutions with less heterologous steps or higher maximum possible theoretical yield by engineering other organism hosts. CF-targeter is available at http://www.rxnfinder.org/cf_targeter/.

Engineering microbial consortia by division of labor

During microbial applications, metabolic burdens can lead to a significant drop in cell performance. Novel synthetic biology tools or multi-step bioprocessing (e.g., fermentation followed by chemical conversions) are therefore needed to avoid compromised biochemical productivity from over-burdened cells. A possible solution to address metabolic burden is Division of Labor (DoL) via natural and synthetic microbial consortia. In particular, consolidated bioprocesses and metabolic cooperation for detoxification or cross feeding (e.g., vitamin C fermentation) have shown numerous successes in industrial level applications. However, distributing a metabolic pathway among proper hosts remains an engineering conundrum due to several challenges: complex subpopulation dynamics/interactions with a short time-window for stable production, suboptimal cultivation of microbial communities, proliferation of cheaters or low-producers, intermediate metabolite dilution, transport barriers between species, and breaks in metabolite channeling through biosynthesis pathways. To develop stable consortia, optimization of strain inoculations, nutritional divergence and crossing feeding, evolution of mutualistic growth, cell immobilization, and biosensors may potentially be used to control cell populations. Another opportunity is direct integration of non-bioprocesses (e.g., microbial electrosynthesis) to power cell metabolism and improve carbon efficiency. Additionally, metabolic modeling and ¹³C-metabolic flux analysis of mixed culture metabolism and cross-feeding offers a computational approach to complement experimental research for improved consortia performance.

FoxO3a inhibiting expression of EPS8 to prevent progression of NSCLC: A new negative loop of EGFR signaling

Background

The resistance to EGF receptor (EGFR) tyrosine kinase inhibitors (TKI) is a major challenge in the treatment of non-small cell lung cancer (NSCLC). Understanding the molecular mechanisms behind resistance is therefore an important issue. Here we assessed the role of EGFR pathway substrate 8 (EPS8) and Forkhead box O 3a (FoxO3a) as potentially valuable targets in the resistance of NSCLC .

Methods

The expression levels of EPS8 and FoxO3a in patients with NSCLC (n = 75) were examined by immunohistochemistry staining, while in cells were detected by qPCR and western blot. The effects of EPS8 and FoxO3a on resistance, migration and invasion, cell cycle arrest were detected by MTT, transwell and flow cytometry, respectively. Chromatin immunoprecipitation and luciferase reporter assays were performed to determine the mechanisms of EPS8 expression and FoxO3a regulation.

Findings

We observed that the expression of EPS8 inversely correlated with FoxO3a in NSCLC cell lines and NSCLC patients. FoxO3a levels were significantly decreased in tumor tissues compared with para-carcinoma tissues, while EPS8 is opposite. Besides, they play reverse roles in the resistance to gefitinib, the migration and invasion abilities, the cell cycle arrest in vitro and the tumor growth in vivo. Mechanistically, FoxO3a inhibits EPS8 levels by directly binding its gene promoter and they form a negative loop in EGFR pathway.

Interpretation

Targeting FoxO3a and EPS8 in EGFR signaling pathway prevents the progression of NSCLC, which implied that the negative loop they formed could served as a therapeutic target for overcoming resistance in NSCLC.

Funds

National Natural Science Foundation of China, Science and Technology Project of Henan, Outstanding Young Talent Research Fund of Zhengzhou University and the National Scholarship Fund.

Machine learning framework for assessment of microbial factory performance

Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess conditions. On the other hand, machine learning, complementary to metabolic modeling necessitates large amounts of data. Building such a database for metabolic engineering designs requires significant manpower and is prone to human errors and bias. We propose an approach to integrate data-driven methods with genome scale metabolic model for assessment of microbial bio-production (yield, titer and rate). Using engineered E. coli as an example, we manually extracted and curated a data set comprising about 1200 experimentally realized cell factories from ~100 papers. We furthermore augmented the key design features (e.g., genetic modifications and bioprocess variables) extracted from literature with additional features derived from running the genome-scale metabolic model iML1515 simulations with constraints that match the experimental data. Then, data augmentation and ensemble learning (e.g., support vector machines, gradient boosted trees, and neural networks in a stacked regressor model) are employed to alleviate the challenges of sparse, non-standardized, and incomplete data sets, while multiple correspondence analysis/principal component analysis are used to rank influential factors on bio-production. The hybrid framework demonstrates a reasonably high cross-validation accuracy for prediction of E.coli factory performance metrics under presumed bioprocess and pathway conditions (Pearson correlation coefficients between 0.8 and 0.93 on new data not seen by the model).

Evolutionary engineering of Escherichia coli for improved anaerobic growth in minimal medium accelerated lactate production

Anaerobic fermentation is a favorable process for microbial production of bulk chemicals like ethanol and organic acids. Low productivity is the bottleneck of several anaerobic processes which has significant impact on the technique competitiveness of production strain. Improving growth rate of production strain can speed up the total production cycle and may finally increase productivity of anaerobic processes. In this work, evolutionary engineering of wild-type strain Escherichia coli W3110 was adopted to improve anaerobic growth in mineral medium. Significant increases in exponential growth rate and stationary cell density were achieved in evolved strain WE269, and a 96.5% increase in lactate productivity has also been observed in batch fermentation of this strain with M9 minimal medium. Then, an engineered strain for lactate production (BW100) was constructed by using WE269 as a platform and 98.3 g/L lactate (with an optical purity of D-lactate above 95%) was produced in a 5-L bioreactor after 48 h with a productivity of 2.05 g/(L·h). Finally, preliminary investigation demonstrated that mutation in sucD (sucD M245I) (encoding succinyl-CoA synthetase); ilvG (ilvG Δ1bp) (encoding acetolactate synthase 2 catalytic subunit), and rpoB (rpoB T1037P) (encoding RNA polymerase β subunit) significantly improved anaerobic growth of E. coli. Double-gene mutation in ilvG and sucD resumed most of the growth potential of evolved strain WE269. This work suggested that improving anaerobic growth of production host can increase productivity of organic acids like lactate, and specific mutation-enabled improved growth may also be applied to metabolic engineering for production of other bulk chemicals.

Engineering Microorganisms for Enhanced CO2 Sequestration

Microbial CO₂ sequestration not only provides a green and sustainable approach for ameliorating global warming but also simultaneously produces biofuels and chemicals. However, the efficiency of microbial CO₂ fixation is still very low. In addition, concomitant microbial CO₂ emission decreases the carbon yield of desired chemicals. To address these issues, strategies including engineering CO₂-fixing pathways and energy-harvesting systems have been developed to improve the efficiency of CO₂ fixation in autotrophic and heterotrophic microorganisms. Furthermore, metabolic pathways and energy metabolism can be rewired to reduce microbial CO₂ emissions and increase the carbon yield of value-added products. This review highlights the potential of biotechnology to promote microbial CO₂ sequestration and provides guidance for the broader use of microorganisms as attractive carbon sinks.

Inheritance of Chromosomes, Sex Determination, and the Human Genome

Who is the determining factor for the sex of the offspring—mother, father, or both parents? This fundamental hypothesis proposes a new model of sex determination, challenging the existing dogma that the male Y chromosome of the father is the sole determinant of the sex of the offspring. According to modern science, the 3 X chromosomes (male XY and female XX) are assumed to be similar, and the sex of the offspring is determined after the zygote is formed. In contrast to this, the new hypothesis based on theoretical research proposes that the 3 X chromosomes can be differentiated, based on the presence of Barr bodies. The first X in female XX chromosomes and X in male XY chromosomes are similar as they lack Barr body and are hereby denoted as ‘X’ and referred to as ancestral chromosomes. The second X chromosome in the female cells which is a Barr body, denoted as X, is different. This X chromosome along with the Y chromosome are referred to as parental chromosomes. Sperm with a Y chromosome can only fuse with an ovum containing the ‘X’ chromosome. Similarly, sperm with the ‘X’ chromosome can only fuse with an ovum containing the X chromosome. Cell biology models of gametogenesis and fertilization were simulated with the new hypothesis model and assessed. Only chromosomes that participated in recombination could unite to form the zygote. This resulted in a paradigm shift in our understanding of sex determination, as both parents were found to be equally responsible for determining the sex of the offspring. The gender of the offspring is determined during the prezygotic stage itself and is dependent on natural selection. A new dimension has been given to inheritance of chromosomes. This new model also presents a new nomenclature for pedigree charts. This work of serendipity may contribute to future research in cell biology, gender studies, genome analysis, and genetic disorders including cancer.

Modular Engineering Intracellular NADH Regeneration Boosts Extracellular Electron Transfer of Shewanella oneidensis MR-1

Efficient extracellular electron transfer (EET) of exoelectrogens is essentially for practical applications of versatile bioelectrochemical systems. Intracellular electrons flow from NADH to extracellular electron acceptors via EET pathways. However, it was yet established how the manipulation of intracellular NADH impacted the EET efficiency. Strengthening NADH regeneration from NAD⁺, as a feasible approach for cofactor engineering, has been used in regulating the intracellular NADH pool and the redox state (NADH/NAD⁺ ratio) of cells. Herein, we first adopted a modular metabolic engineering strategy to engineer and drive the metabolic flux toward the enhancement of intracellular NADH regeneration. We systematically studied 16 genes related to the NAD⁺-dependent oxidation reactions for strengthening NADH regeneration in the four metabolic modules of S. oneidensis MR-1, i.e., glycolysis, C1 metabolism, pyruvate fermentation, and tricarboxylic acid cycle. Among them, three endogenous genes mostly responsible for increasing NADH regeneration were identified, namely gapA2 encoding a NAD⁺-dependent glyceraldehyde-3-phosphate dehydrogenase in the glycolysis module, mdh encoding a NAD⁺-dependent malate dehydrogenase in the TCA cycle, and pflB encoding a pyruvate-formate lyase that converted pyruvate to formate in the pyruvate fermentation module. An exogenous gene fdh* from Candida boidinii encoding a NAD⁺-dependent formate dehydrogenase to increase NADH regeneration in the pyruvate fermentation module was further identified. Upon assembling these four genes in S. oneidensis MR-1, ∼4.3-fold increase in NADH/NAD⁺ ratio, and ∼1.2-fold increase in intracellular NADH pool were obtained under anaerobic conditions without discharge, which elicited ∼3.0-fold increase in the maximum power output in microbial fuel cells, from 26.2 ± 2.8 (wild-type) to 105.8 ± 4.1 mW/m² (recombinant S. oneidensis), suggesting a boost in the EET efficiency. This modular engineering method in controlling the intracellular reducing equivalents would be a general approach in tuning the EET efficiency of exoelectrogens.

Harnessing the Periplasm of Bacterial Cells To Develop Biocatalysts for the Biosynthesis of Highly Pure Chemicals

Although biocatalytic transformation has shown great promise in chemical synthesis, there remain significant challenges in controlling high selectivity without the formation of undesirable by-products. For instance, few attempts to construct biocatalysts for de novo synthesis of pure flavin mononucleotide (FMN) have been successful, due to riboflavin (RF) accumulating in the cytoplasm and being secreted with FMN. To address this problem, we show here a novel biosynthesis strategy, compartmentalizing the final FMN biosynthesis step in the periplasm of an engineered Escherichia coli strain. This construct is able to overproduce FMN with high specificity (92.4% of total excreted flavins). Such a biosynthesis approach allows isolation of the final biosynthesis step from the cytoplasm to eliminate undesirable by-products, providing a new route to develop biocatalysts for the synthesis of high-purity chemicals.IMPORTANCE The periplasm of Gram-negative bacterial hosts is engineered to compartmentalize the final biosynthesis step from the cytoplasm. This strategy is promising for the overproduction of high-value products with high specificity. We demonstrate the successful implementation of this strategy in microbial production of highly pure FMN.

Individualized prevention against hypertension based on Traditional Chinese Medicine Constitution Theory: A large community-based retrospective, STROBE-compliant study among Chinese population

Traditional Chinese Medicine Constitution (TCMC) theory states that individuals with a biased TCMC are more likely to suffer from specific diseases. However, little is known regarding the influence of TCMC on susceptibility to hypertension. The aim of this study is to examine the possible relationship between TCMC and hypertension. Retrospective evaluation and observation were performed using the STROBE guidelines checklist. A large community-based cross-sectional study was conducted between 2009 and 2013 in Changsha, China. TCMC was assessed using a questionnaire that included 68 items. TCMC distributions and the associations of different TCMCs with hypertension risk were analyzed. In total, 144,439 subjects underwent evaluations of TCMC and blood pressure (BP). There were significant differences in the hypertension prevalence among the various TCMC groups (P < .01). An adjusted logistic regression model indicated that those with phlegm wetness, yin deficiency, blood stasis, or qi deficiency were more likely to have hypertension. Analysis of the clinical characteristics related to TCMC indicated that different TCMCs corresponded to different hypertension classifications using Western medicine criteria; for example, phlegm wetness with hypertension was similar to obesity-related hypertension. Our results suggest that phlegm wetness, yin deficiency, blood stasis, and qi deficiency have different effects on the prevalence of hypertension. More attention should be paid to TCMCs associated with susceptibility to hypertension, and corresponding preventive and therapeutic treatments should be developed according to different TCMCs.

Synthetic biology for manufacturing chemicals: constraints drive the use of non-conventional microbial platforms

Genetically modified microbes have had much industrial success producing protein-based products (such as antibodies and enzymes). However, engineering microbial workhorses for biomanufacturing of commodity compounds remains challenging. First, microbes cannot afford burdens with both overexpression of multiple enzymes and metabolite drainage for product synthesis. Second, synthetic circuits and introduced heterologous pathways are not yet as "robust and reliable" as native pathways due to hosts' innate regulations, especially under suboptimal fermentation conditions. Third, engineered enzymes may lack channeling capabilities for cascade-like transport of metabolites to overcome diffusion barriers or to avoid intermediate toxicity in the cytoplasmic environment. Fourth, moving engineered hosts from laboratory to industry is unreliable because genetic mutations and non-genetic cell-to-cell variations impair the large-scale fermentation outcomes. Therefore, synthetic biology strains often have unsatisfactory industrial performance (titer/yield/productivity). To overcome these problems, many different species are being explored for their metabolic strengths that can be leveraged to synthesize specific compounds. Here, we provide examples of non-conventional and genetically amenable species for industrial manufacturing, including the following: Corynebacterium glutamicum for its TCA cycle-derived biosynthesis, Yarrowia lipolytica for its biosynthesis of fatty acids and carotenoids, cyanobacteria for photosynthetic production from its sugar phosphate pathways, and Rhodococcus for its ability to biotransform recalcitrant feedstock. Finally, we discuss emerging technologies (e.g., genome-to-phenome mapping, single cell methods, and knowledge engineering) that may facilitate the development of novel cell factories.

The Analysis of Constitutions of Traditional Chinese Medicine in Relation to Cerebral Infarction in a Chinese Sample

OBJECTIVE

To investigate the relationships between the constitutions of Traditional Chinese Medicine (TCM) and patients with cerebral infarction (CI) in a Chinese sample.

METHODS

A total of 3748 participants with complete data were available for data analysis. All study subjects underwent complete clinical baseline characteristics' evaluation, including a physical examination and response to a structured, nurse-assisted, self-administrated questionnaire. A population of 2010 neutral participants were used as the control group. Multiple variable regression (MLR) were employed to estimate the relationship between constitutions of TCM and the outcome.

DESIGN

A cross-sectional study was conducted to evaluate the association of body constitution of TCM and CI.

SETTINGS/LOCATION

Communications and healthcare centers in Shanghai.

SUBJECTS

A total of 3748 participants with complete data were available for data analysis.

OUTCOME MEASURES

All study subjects underwent complete clinical baseline characteristics' evaluation, including a physical examination and response to a structured, nurse-assisted, self-administrated questionnaire. A population of 2010 neutral participants were used as the control group. MLR were employed to estimate the relationship between constitutions of TCM and the outcome.

RESULT

The prevalence of CI was 2.84% and 4.66% in neutral participants and yang-deficient participants (p = 0.012), respectively. Univariate analysis demonstrated a positive correlation between yang deficiency and CI. After adjustment for relevant potential confounding factors, the MLR detected significant associations between yang deficiency and CI (odds ratio = 1.44, p = 0.093).

CONCLUSION

A yang-deficient constitution was significantly and independently associated with CI. A higher prevalence of CI was found in yang-deficient participants as compared with neutral participants.

Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming

13C metabolic flux analysis (13C-MFA) has been widely used to measure in vivo enzyme reaction rates (i.e., metabolic flux) in microorganisms. Mining the relationship between environmental and genetic factors and metabolic fluxes hidden in existing fluxomic data will lead to predictive models that can significantly accelerate flux quantification. In this paper, we present a web-based platform MFlux (http://mflux.org) that predicts the bacterial central metabolism via machine learning, leveraging data from approximately 100 13C-MFA papers on heterotrophic bacterial metabolisms. Three machine learning methods, namely Support Vector Machine (SVM), k-Nearest Neighbors (k-NN), and Decision Tree, were employed to study the sophisticated relationship between influential factors and metabolic fluxes. We performed a grid search of the best parameter set for each algorithm and verified their performance through 10-fold cross validations. SVM yields the highest accuracy among all three algorithms. Further, we employed quadratic programming to adjust flux profiles to satisfy stoichiometric constraints. Multiple case studies have shown that MFlux can reasonably predict fluxomes as a function of bacterial species, substrate types, growth rate, oxygen conditions, and cultivation methods. Due to the interest of studying model organism under particular carbon sources, bias of fluxome in the dataset may limit the applicability of machine learning models. This problem can be resolved after more papers on 13C-MFA are published for non-model species.

Synthetic and systems biology for microbial production of commodity chemicals

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

Engineering Promoter Architecture in Oleaginous Yeast Yarrowia lipolytica

Eukaryotic promoters have a complex architecture to control both the strength and timing of gene transcription spanning up to thousands of bases from the initiation site. This complexity makes rational fine-tuning of promoters in fungi difficult to predict; however, this very same complexity enables multiple possible strategies for engineering promoter strength. Here, we studied promoter architecture in the oleaginous yeast, Yarrowia lipolytica. While recent studies have focused on upstream activating sequences, we systematically examined various components common in fungal promoters. Here, we examine several promoter components including upstream activating sequences, proximal promoter sequences, core promoters, and the TATA box in autonomously replicating expression plasmids and integrated into the genome. Our findings show that promoter strength can be fine-tuned through the engineering of the TATA box sequence, core promoter, and upstream activating sequences. Additionally, we identified a previously unreported oleic acid responsive transcription enhancement in the XPR2 upstream activating sequences, which illustrates the complexity of fungal promoters. The promoters engineered here provide new genetic tools for metabolic engineering in Y. lipolytica and provide promoter engineering strategies that may be useful in engineering other non-model fungal systems.

Elucidation of the co-metabolism of glycerol and glucose in Escherichia coli by genetic engineering, transcription profiling, and (13)C metabolic flux analysis

BACKGROUND

Glycerol, a byproduct of biodiesel, has become a readily available and inexpensive carbon source for the production of high-value products. However, the main drawback of glycerol utilization is the low consumption rate and shortage of NADPH formation, which may limit the production of NADPH-requiring products. To overcome these problems, we constructed a carbon catabolite repression-negative ΔptsGglpK* mutant by both blocking a key glucose PTS transporter and enhancing the glycerol conversion. The mutant can recover normal growth by co-utilization of glycerol and glucose after loss of glucose PTS transporter. To reveal the metabolic potential of the ΔptsGglpK* mutant, this study examined the flux distributions and regulation of the co-metabolism of glycerol and glucose in the mutant.

RESULTS

By labeling experiments using [1,3-(13)C]glycerol and [1-(13)C]glucose, (13)C metabolic flux analysis was employed to decipher the metabolisms of both the wild-type strain and the ΔptsGglpK* mutant in chemostat cultures. When cells were maintained at a low dilution rate (0.1 h(-1)), the two strains showed similar fluxome profiles. When the dilution rate was increased, both strains upgraded their pentose phosphate pathway, glycolysis and anaplerotic reactions, while the ΔptsGglpK* mutant was able to catabolize much more glycerol than glucose (more than tenfold higher). Compared with the wild-type strain, the mutant repressed its flux through the TCA cycle, resulting in higher acetate overflow. The regulation of fluxomes was consistent with transcriptional profiling of several key genes relevant to the TCA cycle and transhydrogenase, namely gltA, icdA, sdhA and pntA. In addition, cofactor fluxes and their pool sizes were determined. The ΔptsGglpK* mutant affected the redox NADPH/NADH state and reduced the ATP level. Redox signaling activated the ArcA regulatory system, which was responsible for TCA cycle repression.

CONCLUSIONS

This work employs both (13)C-MFA and transcription/metabolite analysis for quantitative investigation of the co-metabolism of glycerol and glucose in the ΔptsGglpK* mutant. The ArcA regulatory system dominates the control of flux redistribution. The ΔptsGglpK* mutant can be used as a platform for microbial cell factories for the production of biofuels and biochemicals, since most of fuel molecule (e.g., alcohols) synthesis requires excess reducing equivalents.

Targeted cofactor quantification in metabolically engineered E. coli using solid phase extraction and hydrophilic interaction liquid chromatography-mass spectrometry

Quantification of energy and redox cofactors is of great value to synthetic biologists to infer the balance of energy metabolism in engineered microbial strains and assess each strain's potential for further improvement. Most currently used methods for intracellular cofactor measurement suffer from incomplete coverage, low reproducibility, suboptimal sensitivity or specificity. In this study, we described an SPE-HILIC/MS approach for simultaneous determination of six cofactor targets (ATP, ADP, NAD, NADH, NADP, NADPH) in Escherichia coli cells. Sufficient linearity, precision and metabolite recoveries of this new approach justified its reliability in targeted cofactor quantification. Our approach was then compared with conventional enzymatic assays to demonstrate its superior performance. We applied the SPE-HILIC/MS approach to profile shift of cofactor balances in several engineered E. coli strains with varying isobutanol production. Our cofactor analysis clearly revealed that optimal energy fitness was achieved in the highest-yield strain through combined modulation of a transhydrogenase and a NAD(+) kinase. Apart from the targeted cofactors, the SPE enrichment procedure also allowed for confident identification of 39 groups of polar metabolites mainly involved in central carbon metabolism in E. coli cells.