Lignin peroxidase and protease production by Streptomyces viridosporus T7A in the presence of calcium carbonate

Streptomyces are good producers of enzymes of industrial interest, such as lignin peroxidase (LiP) and proteases. To optimize production of these enzymes by Streptomyces viridosporus T7A, two parameters were evaluated: carbon sources and calcium carbonate. Shake-flask fermentations were performed using culture media, with and without CaCO₃, contained yeast extract, mineral salts and either glucose, lactose, galactose, or corn oil. In the absence of calcium carbonate, the maximum values for LiP and protease activities occurred during the idiophase with LiP activity being favored by glucose, corn oil, and galactose, and protease activity being favored only by corn oil. Calcium carbonate affected the cell morphology by reducing the size of the pellets. Moreover, in the presence of the salt, LiP production was growth-associated in all media but the glucose medium. Higher enzyme levels were observed when galactose and glucose were used as carbon sources. Protease activity was repressed by both glucose and galactose, whereas corn oil was the best carbon source for the enzyme production. Calcium carbonate increased LiP production by up to 2.6-fold. Such improvement was not observed for protease production, suggesting a selective effect of CaCO₃ on LiP activity.     

Fermentation of xylose into acetic acid by Clostridium thermoaceticum

For optimum fermentation, fermenting xylose into acetic acid by Clostridium thermoaceticum (ATCC 49707) requires adaptation of the strain to xylose medium. Exposed to a mixture of glucose and xylose, it preferentially consumesxylose over glucose. The initial concentration of xylose in the medium affects the final concentration and the yield of acetic acid. Batch fermentation of 20 g/L of xylose with 5g/L of yeast extract as the nitrogen source results in a maximum acetate concentration of 15.2 g/L and yield of 0.76 g of acid/g of xylose. Corn steep liquor (CLS) is a good substitute for yeast extract and results in similar fermentation profiles. The organism consumes fructose, xylose, and glucose from a mixture of sugars in batch fermentation. Arabinose, mannose, and galactose are consumed only slightly. This organism loses viability on fed-batch operation, even with supplementation of all the required nutrients. In fed-batch fermentation with CSL supplementation, d-xylulose (an intermediate in the xylose metabolic pathway) accumulates in large quantities.     

Quantitation of plasma 13C-galactose and 13C-glucose during exercise by liquid chromatography/isotope ratio mass spectrometry

The utilisation of carbohydrate sources under exercise conditions is of considerable importance in performance sports. Incorporation of optimal profiles of macronutrients can improve endurance performance in athletes. However, gaining an understanding of the metabolic partitioning under sustained exercise can be problematical and isotope labelling approaches can help quantify substrate utilisation. The utilisation of oral galactose was investigated using ¹³C‐galactose and measurement of plasma galactose and glucose enrichment by liquid chromatography/isotope ratio mass spectrometry (LC/IRMS). As little as 100 μL plasma could readily be analysed with only minimal sample processing. Fucose was used as a chemical and isotopic internal standard for the quantitation of plasma galactose and glucose concentrations, and isotopic enrichment. The close elution of galactose and glucose required a correction routine to be implemented to allow the measurement, and correction, of plasma glucose δ¹³C, even in the presence of very highly enriched galactose. A Bland‐Altman plot of glucose concentration measured by LC/IRMS against glucose measured by an enzymatic method showed good agreement between the methods. Data from seven trained cyclists, undergoing galactose supplementation before exercise, demonstrate that galactose is converted into glucose and is available for subsequent energy metabolism. Copyright © 2011 John Wiley & Sons, Ltd.     

Effect of Fermentation Conditions on the Flocculation of Recombinant Saccharomyces cerevisiae Capable of Co-fermenting Glucose and Xylose

Flocculation is a desirable property in industrial yeasts and is particularly important in the fuel ethanol industry because it provides a simple and cost-free way to separate yeast cells from fermentation products. In the present study, the effect of pH and lignocellulose-derived sugars on yeast flocculation was investigated using a flocculent Saccharomyces cerevisiae, MA-R4, which has been recombinantly engineered to simultaneously co-ferment glucose and xylose to ethanol with high productivity. The flocculation level of MA-R4 dramatically decreased at pH values below 3.0 during co-fermentation of glucose and xylose. Sedimentation and microscopic observation revealed that flocculation was induced in MA-R4 when it fermented glucose, a glucose/xylose mixture, or mannose, whereas attempts to ferment xylose, galactose, and arabinose led to the loss of flocculation. MA-R4 fermented xylose and galactose more slowly than glucose and mannose. Therefore, the various flocculation behaviors shown by MA-R4 should be useful in the control of ethanol fermentation processes.     

Production of Sugars and Levulinic Acid from Marine Biomass Gelidium amansii

This study focused on optimization of reaction conditions for formation of sugars and levulinic acid from marine algal biomass Gelidium amansii using acid catalyst and by using statistical approach. By this approach, optimal conditions for production of sugars and levulinic acid were found as follows: glucose (reaction temperature of 139.4°C, reaction time of 15.0 min, and catalyst concentration of 3.0%), galactose (108.2°C, 45.0 min, and 3.0%), and levulinic acid (160.0°C, 43.1 min, and 3.0%). While trying to optimize the conditions for the production of glucose and galactose, levulinic acid production was found to be minimum. Similarly, the production of glucose and galactose were found to be minimum while optimizing the conditions for the production of levulinic acid. In addition, optimized production of glucose required a higher reaction temperature and shorter reaction time than that of galactose. Levulinic acid was formed at a high reaction temperature, long reaction time, and high catalyst concentration. The combined results of this study may provide useful information to develop more economical and efficient systems for production of sugars and chemicals from marine biomass.     

α- and β-Glucosidase inhibitors: chemical structure and biological activity

Glycoside trimming enzymes are crucially important in a broad range of metabolic pathways, including glycoprotein and glycolipid processing and carbohydrate digestion in the intestinal tract. Amongst the large array of enzymes, glucosidases are postulated to be a powerful therapeutic target since they catalyze the cleavage of glycosidic bonds releasing glucose from the non-reducing end of an oligo- or polysaccharide chain involved in glycoprotein biosynthesis. Glucosidase inhibitors are currently of interest owing to their promising therapeutic potential in the treatment of disorders such as diabetes, human immunodeficiency virus (HIV) infection, metastatic cancer, and lysosomal storage diseases. Glucosidase inhibitors have also been useful in probing biochemical pathways and understanding structure-activity relationship patterns required for mimicking the enzyme transition state. Amongst the various types of glucosidase inhibitors, disaccharides, iminosugars, carbasugars, thiosugars, and non-sugar derivatives have received great attention. This review is aimed at highlighting the main chemical classes of glucosidase inhibitors, as well as their biological activities toward α- and β-glucosidases, but it is not intended to be an exhaustive review on the subject. Inhibition data on the compounds covered in this review are included in a tabular form as an Appendix, where the type of each glucosidase associated with a specific inhibitor is also given.     

Characterization of heterologous and native enzyme activity profiles in metabolically engineered Zymomonas mobilis strains during batch fermentation of glucose and xylose mixtures

Zymomonas mobilis has been metabolically engineered to broaden its substrate utilization range to include d-xylose and l-arabinose. Both genomically integrated and plasmid-bearing Z. mobilis strains that are capable of fermenting the pentose d-xylose have been created by incorporating four genes: two genes encoding xylose utilization metabolic enzymes (xylA/xylB) and two genes encoding pentose phosphate pathway enzymes (talB/tktA). We have characterized the activities of the four newly introduced enzymes for xylose metabolism, along with those of three native glycolytic enzymes, in two different xylose-fermenting Z. mobilis strains. These strains were grown on glucose-xylose mixtures in computer-controlled fermentors. Samples were collected and analyzed to determine extracellular metabolite concentrations as well as the activities of several intracellular enzymes in the xylose and glucose uptake and catabolism pathways. These measurements provide new insights on the possible bottlenecks in the engineered metabolic pathways and suggest methods for further improving the efficiency of xylose fermentation.     

微藻高油脂化基因工程研究策略

石化能源危机与全球气候变化已成为人类的两大重要难题。生物柴油作为可替代普通柴油的环境友好且可再生的能源受到普遍关注。相比植物油和动物脂肪生产,藻类油脂产率高且容易培养,被认为是未来生物柴油发展的重要原料之一。通过转基因技术强化油脂代谢途径,提高富油微藻含油量,已经成为新的研究热点。已有植物研究表明,增强甘油酯酰基转移酶表达,可以提高Kennedy途径代谢中间体通量,从而增加甘油三酯(TAG)的积累。本文综述了微藻油脂代谢途径的国内外研究现状和提高油脂积累的代谢调控策略;详细阐述了基于植物油脂合成强化的成功经验,通过增强微藻Kennedy途径对提高TAG生物合成的重要作用;讨论了当前转基因微藻的遗传转化方法及其需要解决的关键性科学技术问题;分析了基因工程技术调控微藻脂类代谢途径生产高油脂的可能性,并对该研究的发展进行了展望。     

Programming Super DNA-Enzyme Molecules for On-Demand Enzyme Activity Modulation**

Dynamic interactions of enzymes, including programmable configuration and cycling of enzymes, play important roles in the regulation of cellular metabolism. Here, we constructed a super DNA-enzymes molecule (SDEM) that comprises at least two cascade enzymes and multiple linked DNA strands to control and detect metabolism. We found that the programmable SDEM, which comprises glucose oxidase (GOx) and horseradish peroxidase (HRP), has a 20-fold lower detection limit and a 1.6-fold higher reaction rate than free enzymes. An SDEM can be assembled and disassembled using a hairpin structure and a displacement DNA strand to complete multiple cycles. An entropically driven catalytic assembly (catassembly) enables different SDEMs to switch from an SDEM with GOx and HRP cascades to an SDEM with sarcosine oxidase (SOX) and HRP cascades in over six orders of magnitude less time than without the catassembly to detect different metabolisms (GO and sarcosine) on demand.     

In-line determination of metabolites and milk components with electrochemical biosensors

Electrochemical biosensors for lactate, pyruvate and β-hydroxybutyrate based on oxygen, hydrogen peroxide, and NADH sensors coupled with oxidase and dehydrogenase enzymes were developed and used in conjunction with an artificial pancreas in experiments with extracorporeal circulation. Such procedures allow the fate of these species involved in glucose metabolism to be clarified during insulin treatment of diabetic patients. Studies with a glucose oxidase electrode for in-line determination of glucose produced by hydrolysis of cellobiose in a bioreactor are reported; for the determination of glucose in the presence of high concentrations of cellobiose, the purity of glucose oxidase is important in obtaining linear calibration plots. Impurities like amylase, maltase, invertase, and galactose oxidase, which are usually present in commercial preparations of glucose oxidase, must be absent. Another application is the amperometric determination of lactose, lactate and glucose in milk samples by using a hydrogen peroxide sensor coupled with β-galactosidase, lactate oxidase and glucose oxidase. The procedures outlined are simple and the short response times enable milk to be monitored during processing.     

Theoretical aspects of C metabolic flux analysis with sole quantification of carbon dioxide labeling

The potential of using sole respirometric CO2 labeling measurement for 13C metabolic flux analysis was investigated by metabolic simulations. For this purpose a model was created, considering all CO2 forming and consuming reactions in the central catabolic and anabolic pathways. To facilitate the interpretation of the simulation results, the underlying metabolic network was parameterized by physiologically meaningful flux parameters such as flux partitioning ratios at metabolic branch points and reaction reversibilities. For real case flux scenarios of the industrial amino acid producer Corynebacterium glutamicum and different commercially available (13)C-labeled tracer substrates, observability and output sensitivity towards key flux parameters was investigated. Metabolic net fluxes in the central metabolism, involving, e.g. glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, anaplerotic carboxylation, and glyoxylate pathway were found to be determinable by the respirometric approach using a combination of [1-13C] and [6-13C] glucose in two parallel studies. The reversibilities of bidirectional reactions influence the isotopic labeling of CO2 only to a negligible degree. On one hand, they therefore cannot be determined. On the other hand, their precise values are not required for the quantification of net fluxes. Computer-aided optimal experimental design was carried out to predict the quality of the information from the respirometric tracer experiments and identify suitable tracer substrates. A combination of [1-13C] and [6-13C] glucose in two parallel studies was found to yield a similar quality of information as compared to an approach with mass spectrometric labeling analysis of secreted products. The quality of information can be further increased by additional studies with [1,2-13C2] or [1,6-13C2] glucose. Respirometric tracer studies with sole labeling analysis of CO2 are therefore promising for 13C metabolic flux analysis.     

Engineering of Therapeutic and Detoxifying Enzymes

Therapeutic enzymes present excellent opportunities for the treatment of human disease, modulation of metabolic pathways and system detoxification. However, current use of enzyme therapy in the clinic is limited as naturally occurring enzymes are seldom optimal for such applications and require substantial improvement by protein engineering. Engineering strategies such as design and directed evolution that have been successfully implemented for industrial biocatalysis can significantly advance the field of therapeutic enzymes, leading to biocatalysts with new-to-nature therapeutic activities, high selectivity, and suitability for medical applications. This minireview highlights case studies of how state-of-the-art and emerging methods in protein engineering are explored for the generation of therapeutic enzymes and discusses gaps and future opportunities in the field of enzyme therapy.     

Theoretical aspects of 13C metabolic flux analysis with sole quantification of carbon dioxide labeling

The potential of using sole respirometric CO2 labeling measurement for 13C metabolic flux analysis was investigated by metabolic simulations. For this purpose a model was created, considering all CO2 forming and consuming reactions in the central catabolic and anabolic pathways. To facilitate the interpretation of the simulation results, the underlying metabolic network was parameterized by physiologically meaningful flux parameters such as flux partitioning ratios at metabolic branch points and reaction reversibilities. For real case flux scenarios of the industrial amino acid producer Corynebacterium glutamicum and different commercially available (13)C-labeled tracer substrates, observability and output sensitivity towards key flux parameters was investigated. Metabolic net fluxes in the central metabolism, involving, e.g. glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, anaplerotic carboxylation, and glyoxylate pathway were found to be determinable by the respirometric approach using a combination of [1-13C] and [6-13C] glucose in two parallel studies. The reversibilities of bidirectional reactions influence the isotopic labeling of CO2 only to a negligible degree. On one hand, they therefore cannot be determined. On the other hand, their precise values are not required for the quantification of net fluxes. Computer-aided optimal experimental design was carried out to predict the quality of the information from the respirometric tracer experiments and identify suitable tracer substrates. A combination of [1-13C] and [6-13C] glucose in two parallel studies was found to yield a similar quality of information as compared to an approach with mass spectrometric labeling analysis of secreted products. The quality of information can be further increased by additional studies with [1,2-13C2] or [1,6-13C2] glucose. Respirometric tracer studies with sole labeling analysis of CO2 are therefore promising for 13C metabolic flux analysis.     

Genetic control by a metabolite binding mRNA

Messenger RNAs are typically thought of as passive carriers of genetic information that are acted upon by protein- or small RNA-regulatory factors and by ribosomes during the process of translation. We report that the 5'-untranslated sequence of the Escherichia coli btuB mRNA assumes a more proactive role in metabolic monitoring and genetic control. The mRNA serves as a metabolite-sensing genetic switch by selectively binding coenzyme B(12) without the need for proteins. This binding event establishes a distinct RNA structure that is likely to be responsible for inhibition of ribosome binding and consequent reduction in synthesis of the cobalamin transport protein BtuB. This finding, along with related observations, supports the hypothesis that metabolic monitoring through RNA-metabolite interactions is a widespread mechanism of genetic control.     

Perspectives in Metabolic Engineering: Understanding Cellular Regulation Towards the Control of Metabolic Routes

Metabolic engineering seeks to redirect metabolic pathways through the modification of specific biochemical reactions or the introduction of new ones with the use of recombinant technology. Many of the chemicals synthesized via introduction of product-specific enzymes or the reconstruction of entire metabolic pathways into engineered hosts that can sustain production and can synthesize high yields of the desired product as yields of natural product-derived compounds are frequently low, and chemical processes can be both energy and material expensive; current endeavors have focused on using biologically derived processes as alternatives to chemical synthesis. Such economically favorable manufacturing processes pursue goals related to sustainable development and “green chemistry”. Metabolic engineering is a multidisciplinary approach, involving chemical engineering, molecular biology, biochemistry, and analytical chemistry. Recent advances in molecular biology, genome-scale models, theoretical understanding, and kinetic modeling has increased interest in using metabolic engineering to redirect metabolic fluxes for industrial and therapeutic purposes. The use of metabolic engineering has increased the productivity of industrially pertinent small molecules, alcohol-based biofuels, and biodiesel. Here, we highlight developments in the practical and theoretical strategies and technologies available for the metabolic engineering of simple systems and address current limitations.     

Modeling Structure–Activity Relationship of AMPK Activation

The adenosine monophosphate activated protein kinase (AMPK) is critical in the regulation of important cellular functions such as lipid, glucose, and protein metabolism; mitochondrial biogenesis and autophagy; and cellular growth. In many diseases—such as metabolic syndrome, obesity, diabetes, and also cancer—activation of AMPK is beneficial. Therefore, there is growing interest in AMPK activators that act either by direct action on the enzyme itself or by indirect activation of upstream regulators. Many natural compounds have been described that activate AMPK indirectly. These compounds are usually contained in mixtures with a variety of structurally different other compounds, which in turn can also alter the activity of AMPK via one or more pathways. For these compounds, experiments are complicated, since the required pure substances are often not yet isolated and/or therefore not sufficiently available. Therefore, our goal was to develop a screening tool that could handle the profound heterogeneity in activation pathways of the AMPK. Since machine learning algorithms can model complex (unknown) relationships and patterns, some of these methods (random forest, support vector machines, stochastic gradient boosting, logistic regression, and deep neural network) were applied and validated using a database, comprising of 904 activating and 799 neutral or inhibiting compounds identified by extensive PubMed literature search and PubChem Bioassay database. All models showed unexpectedly high classification accuracy in training, but more importantly in predicting the unseen test data. These models are therefore suitable tools for rapid in silico screening of established substances or multicomponent mixtures and can be used to identify compounds of interest for further testing.