A thermostable recombinant transaldolase with high activity over a broad pH range

Stoichiometric Conversion of Maltose for Biomanufacturing by In Vitro Synthetic Enzymatic Biosystems

Maltose is a natural α-(1,4)-linked disaccharide with wide applications in food industries and microbial fermentation. However, maltose has scarcely been used for in vitro biosynthesis, possibly because its phosphorylation by maltose phosphorylase (MP) yields β-glucose 1-phosphate (β-G1P) that cannot be utilized by α-phosphoglucomutase (α-PGM) commonly found in in vitro synthetic enzymatic biosystems previously constructed by our group. Herein, we designed an in vitro synthetic enzymatic reaction module comprised of MP, β-phosphoglucomutase (β-PGM), and polyphosphate glucokinase (PPGK) for the stoichiometric conversion of each maltose molecule to two glucose 6-phosphate (G6P) molecules. Based on this synthetic module, we further constructed two in vitro synthetic biosystems to produce bioelectricity and fructose 1,6-diphosphate (FDP), respectively. The 14-enzyme biobattery achieved a Faraday efficiency of 96.4% and a maximal power density of 0.6 mW/cm2, whereas the 5-enzyme in vitro FDP-producing biosystem yielded 187.0 mM FDP from 50 g/L (139 mM) maltose by adopting a fed-batch substrate feeding strategy. Our study not only suggests new application scenarios for maltose but also provides novel strategies for the high-efficient production of bioelectricity and value-added biochemicals.

Empirical comparison and analysis of machine learning-based predictors for predicting and analyzing of thermophilic proteins

Thermophilic proteins (TPPs) are critical for basic research and in the food industry due to their ability to maintain a thermodynamically stable fold at extremely high temperatures. Thus, the expeditious identification of novel TPPs through computational models from protein sequences is very desirable. Over the last few decades, a number of computational methods, especially machine learning (ML)-based methods, for in silico prediction of TPPs have been developed. Therefore, it is desirable to revisit these methods and summarize their advantages and disadvantages in order to further develop new computational approaches to achieve more accurate and improved prediction of TPPs. With this goal in mind, we comprehensively investigate a large collection of fourteen state-of-the-art TPP predictors in terms of their dataset size, feature encoding schemes, feature selection strategies, ML algorithms, evaluation strategies and web server/software usability. To the best of our knowledge, this article represents the first comprehensive review on the development of ML-based methods for in silico prediction of TPPs. Among these TPP predictors, they can be classified into two groups according to the interpretability of ML algorithms employed (i.e., computational black-box methods and computational white-box methods). In order to perform the comparative analysis, we conducted a comparative study on several currently available TPP predictors based on two benchmark datasets. Finally, we provide future perspectives for the design and development of new computational models for TPP prediction. We hope that this comprehensive review will facilitate researchers in selecting an appropriate TPP predictor that is the most suitable one to deal with their purposes and provide useful perspectives for the development of more effective and accurate TPP predictors.

Biomass sugar-powered enzymatic fuel cells based on a synthetic enzymatic pathway

Biomass stores a tremendous amount of chemical energy and is considered as an abundant and sustainable alternative to fossil fuels. However, the use of biomass to produce mW-level electricity for portable devices suffers from its structural complexity and therefore low energy conversion efficiency. In this study, we design an enzymatic pathway that could co-utilize and completely oxidize glucose and xylose from biomass hydrolysate to achieve high energy density in EFC. Faraday efficiency of 92% and maximum power density of 0.14 mW cm-2 are achieved in this EFC. After the systematically optimization of enzyme loading and temperature as well as the removal of enzyme inhibitor from biomass hydrolysate by activated charcoal, the biomass sugar-powered EFC could reach a maximum power density of 0.5 mW cm-2 and remain 60% of the initial value after 10 days. These results offer a feasible way to extract the energy stored in biomass as much as possible without the side effects of biomass hydrolysate on EFC.

A novel sequence-based predictor for identifying and characterizing thermophilic proteins using estimated propensity scores of dipeptides

Owing to their ability to maintain a thermodynamically stable fold at extremely high temperatures, thermophilic proteins (TTPs) play a critical role in basic research and a variety of applications in the food industry. As a result, the development of computation models for rapidly and accurately identifying novel TTPs from a large number of uncharacterized protein sequences is desirable. In spite of existing computational models that have already been developed for characterizing thermophilic proteins, their performance and interpretability remain unsatisfactory. We present a novel sequence-based thermophilic protein predictor, termed SCMTPP, for improving model predictability and interpretability. First, an up-to-date and high-quality dataset consisting of 1853 TPPs and 3233 non-TPPs was compiled from published literature. Second, the SCMTPP predictor was created by combining the scoring card method (SCM) with estimated propensity scores of g-gap dipeptides. Benchmarking experiments revealed that SCMTPP had a cross-validation accuracy of 0.883, which was comparable to that of a support vector machine-based predictor (0.906-0.910) and 2-17% higher than that of commonly used machine learning models. Furthermore, SCMTPP outperformed the state-of-the-art approach (ThermoPred) on the independent test dataset, with accuracy and MCC of 0.865 and 0.731, respectively. Finally, the SCMTPP-derived propensity scores were used to elucidate the critical physicochemical properties for protein thermostability enhancement. In terms of interpretability and generalizability, comparative results showed that SCMTPP was effective for identifying and characterizing TPPs. We had implemented the proposed predictor as a user-friendly online web server at http://pmlabstack.pythonanywhere.com/SCMTPP in order to allow easy access to the model. SCMTPP is expected to be a powerful tool for facilitating community-wide efforts to identify TPPs on a large scale and guiding experimental characterization of TPPs.

A transaldolase-dependent sulfoglycolysis pathway in Bacillus megaterium DSM 1804

Sulfoquinovose (6-deoxy-6-sulfoglucose, SQ) is a component of sulfolipids found in the photosynthetic membranes of plants and other photosynthetic organisms, and is one of the most abundant organosulfur compounds in nature. Microbial degradation of SQ, termed sulfoglycolysis, constitutes an important component of the biogeochemical sulfur cycle. Two sulfoglycolysis pathways have been reported, with one resembling the Embden-Meyerhof-Parnas (sulfo-EMP) pathway, and the other resembling the Entner-Doudoroff (sulfo-ED) pathway. Here we report a third sulfoglycolysis pathway in the bacterium Bacillus megaterium DSM 1804, in which sulfosugar cleavage is catalyzed by the transaldolase SqvA, which converts 6-deoxy-6-sulfofructose and glyceraldehyde 3-phosphate into fructose -6-phosphate and (S)-sulfolactaldehyde. Variations of this transaldolase-dependent sulfoglycolysis (sulfo-TAL) pathway are present in diverse bacteria, and add to the diversity of mechanisms for the degradation of this abundant organosulfur compound.

The Pentose Phosphate Pathway Dynamics in Cancer and Its Dependency on Intracellular pH

The Pentose Phosphate Pathway (PPP) is one of the key metabolic pathways occurring in living cells to produce energy and maintain cellular homeostasis. Cancer cells have higher cytoplasmic utilization of glucose (glycolysis), even in the presence of oxygen; this is known as the "Warburg Effect". However, cytoplasmic glucose utilization can also occur in cancer through the PPP. This pathway contributes to cancer cells by operating in many different ways: (i) as a defense mechanism via the reduced form of nicotinamide adenine dinucleotide phosphate (NADPH) to prevent apoptosis, (ii) as a provision for the maintenance of energy by intermediate glycolysis, (iii) by increasing genomic material to the cellular pool of nucleic acid bases, (iv) by promoting survival through increasing glycolysis, and so increasing acid production, and (v) by inducing cellular proliferation by the synthesis of nucleic acid, fatty acid, and amino acid. Each step of the PPP can be upregulated in some types of cancer but not in others. An interesting aspect of this metabolic pathway is the shared regulation of the glycolytic and PPP pathways by intracellular pH (pHi). Indeed, as with glycolysis, the optimum activity of the enzymes driving the PPP occurs at an alkaline pHi, which is compatible with the cytoplasmic pH of cancer cells. Here, we outline each step of the PPP and discuss its possible correlation with cancer.

Applications of Marine-Derived Microorganisms and Their Enzymes in Biocatalysis and Biotransformation, the Underexplored Potentials

Biodiversity has been explored in the search for novel enzymes, including forests, savannas, tundras, deserts, and finally the sea. Marine microorganisms and their enzymes are capable of being active in high-salt concentration, large range of temperature, and high incidence of light and pressure, constituting an important source of unique biocatalysts. This review presents studies employing whole-cell processes of marine bacteria and fungi, aiming for new catalysts for different reactions in organic synthesis, such as reduction, oxidation, hydroxylation, hydrolysis, elimination, and conjugation. Genomics and protein engineering studies were also approached, and reactions employing isolated enzymes from different classes (oxidoreductases, hydrolases, lyases, and ligases) were described and summarized. Future biotechnological studies and process development should focus on molecular biology for the obtention of enzymes with interesting, fascinating and enhanced properties, starting from the exploration of microorganisms from the marine environment. This review approaches the literature about the use of marine-derived bacteria, fungi, and their enzymes for biocatalytic reactions of organic compounds, promoting a discussion about the possibilities of these microorganisms in the synthesis of different substances.

Novel Hydrogen Bioreactor and Detection Apparatus

In vitro hydrogen generation represents a clear opportunity for novel bioreactor and system design. Hydrogen, already a globally important commodity chemical, has the potential to become the dominant transportation fuel of the future. Technologies such as in vitro synthetic pathway biotransformation (SyPaB)-the use of more than 10 purified enzymes to catalyze unnatural catabolic pathways-enable the storage of hydrogen in the form of carbohydrates. Biohydrogen production from local carbohydrate resources offers a solution to the most pressing challenges to vehicular and bioenergy uses: small-size distributed production, minimization of CO2 emissions, and potential low cost, driven by high yield and volumetric productivity. In this study, we introduce a novel bioreactor that provides the oxygen-free gas phase necessary for enzymatic hydrogen generation while regulating temperature and reactor volume. A variety of techniques are currently used for laboratory detection of biohydrogen, but the most information is provided by a continuous low-cost hydrogen sensor. Most such systems currently use electrolysis for calibration; here an alternative method, flow calibration, is introduced. This system is further demonstrated here with the conversion of glucose to hydrogen at a high rate, and the production of hydrogen from glucose 6-phosphate at a greatly increased reaction rate, 157 mmol/L/h at 60 °C.

Non-complexed four cascade enzyme mixture: simple purification and synergetic co-stabilization

Cell-free biosystems comprised of synthetic enzymatic pathways would be a promising biomanufacturing platform due to several advantages, such as high product yield, fast reaction rate, easy control and access, and so on. However, it was essential to produce (purified) enzymes at low costs and stabilize them for a long time so to decrease biocatalyst costs. We studied the stability of the four recombinant enzyme mixtures, all of which originated from thermophilic microorganisms: triosephosphate isomerase (TIM) from Thermus thermophiles, fructose bisphosphate aldolase (ALD) from Thermotoga maritima, fructose bisphosphatase (FBP) from T. maritima, and phosphoglucose isomerase (PGI) from Clostridium thermocellum. It was found that TIM and ALD were very stable at evaluated temperature so that they were purified by heat precipitation followed by gradient ammonia sulfate precipitation. In contrast, PGI was not stable enough for heat treatment. In addition, the stability of a low concentration PGI was enhanced by more than 25 times in the presence of 20 mg/L bovine serum albumin or the other three enzymes. At a practical enzyme loading of 1000 U/L for each enzyme, the half-life time of free PGI was prolong to 433 h in the presence of the other three enzymes, resulting in a great increase in the total turn-over number of PGI to 6.2×10⁹ mole of product per mole of enzyme. This study clearly suggested that the presence of other proteins had a strong synergetic effect on the stabilization of the thermolabile enzyme PGI due to in vitro macromolecular crowding effect. Also, this result could be used to explain why not all enzymes isolated from thermophilic microorganisms are stable in vitro because of a lack of the macromolecular crowding environment.

Cell-free biosystems for biomanufacturing

Although cell-free biosystems have been used as a tool for investigating fundamental aspects of biological systems for more than 100 years, they are becoming an emerging biomanufacturing platform in the production of low-value biocommodities (e.g., H(2), ethanol, and isobutanol), fine chemicals, and high-value protein and carbohydrate drugs and their precursors. Here we would like to define the cell-free biosystems containing more than three catalytic components in a single reaction vessel, which although different from one-, two-, or three-enzyme biocatalysis can be regarded as a straightforward extension of multienzymatic biocatalysis. In this chapter, we compare the advantages and disadvantages of cell-free biosystems versus living organisms, briefly review the history of cell-free biosystems, highlight a few examples, analyze any remaining obstacles to the scale-up of cell-free biosystems, and suggest potential solutions. Cell-free biosystems could become a disruptive technology to microbial fermentation, especially in the production of high-impact low-value biocommodities mainly due to the very high product yields and potentially low production costs.