An overview on biofuel and biochemical production by photosynthetic microorganisms with understanding of the metabolism and by metabolic engineering together with efficient cultivation and downstream processing

Glycosyltransferase Slr1064 regulates carbon metabolism by modulating the levels of UDP-GlcNAc in Synechocystis sp. PCC 6803

Glycosyltransferases (GTs) are enzymes that transfer sugars to various targets. They play important roles in diverse biological processes, including photosynthesis, cell motility, exopolysaccharide biosynthesis, and lipid metabolism; however, their involvement in regulating carbon metabolism in Synechocystis sp. PCC 6803 has not been reported. We identified a novel GT protein, Slr1064, involved in carbon metabolism. The effect of slr1064 deletion on the growth of Synechocystis cells and functional mechanisms of Slr1064 on carbon metabolism were thoroughly investigated through physiological, biochemistry, proteomic, and metabolic analyses. We found that this GT, which is mainly distributed in the membrane compartment, is essential for the growth of Synechocystis under heterotrophic and mixotrophic conditions, but not under autotrophic conditions. The deletion of slr1064 hampers the turnover rate of Gap2 under mixotrophic conditions and disrupts the assembly of the PRK/GAPDH/CP12 complex under dark culture conditions. Additionally, UDP-GlcNAc, the pivotal metabolite responsible for the O-GlcNAc modification of GAPDH, is downregulated in the Δslr1064. Our work provides new insights into the role of GTs in carbon metabolism in Synechocystis and elucidate the mechanism by which carbon metabolism is regulated in this important model organism.

Application of microbial-induced carbonate precipitation (MICP) techniques to remove heavy metal in the natural environment: A critical review

The occurrence of imbalanced heavy metals concentration due to anthropogenic hindrances in the aquatic and terrestrial environment has become a potential risk to life after circulating through different food chains. The microbial-induced carbonate precipitation (MICP) method has gradually received great attention from global researchers but the underlying mechanism of heavy metal mineralization is not well-understood and challenging, limiting the applications in wastewater engineering. This paper reviews the metabolic pathways, mechanisms, operational factors, and mathematical/modeling approaches in the MICP process. Subsequently, the recent advancement in MICP for the remediation of heavy metal pollution is being discussed. In the follow-up, the key challenges and prospective associated with technical bottlenecks of MICP method are elaborated. The prospective study reveals that MICP technology could be efficiently used to remediate heavy metal contaminants from the natural environment in a cost-effective way and has the potential to improve soil properties while remediating heavy metal contaminated soil.

Yeast metabolic engineering for carbon dioxide fixation and its application

As numerous industrial bioprocesses rely on yeast fermentation, developing CO₂-fixing yeast strains can be an attractive option toward sustainable industrial processes and carbon neutrality. Recent studies have shown that the expression of ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO) in yeasts, such as Saccharomyces cerevisiae and Kluyveromyces marxianus, enables mixotrophic CO₂ fixation and production of biofuels. Also, the expression of a synthetic Calvin-Benson-Bassham (CBB) cycle including RuBisCO in Pichia pastoris enables autotrophic growth on CO₂. This review highlights recent advances in metabolic engineering strategies to enable CO₂ fixation in yeasts. Also, we discuss the potentials of other natural and synthetic metabolic pathways independent of RuBisCO for developing CO₂-fixing yeast strains capable of producing value-added biochemicals.

Characterization of isolated UV-C-irradiated mutants of microalga Chlorella vulgaris for future biofuel application

Microalgae-based biofuel is considered as one of the most promising sources of alternative energy because it is sustainable and does not pose threats to the environment and food security. However, attempts in improving microalgal strains to attain the ideal characteristics for biofuel application are yet to unravel. In this study, random UV-C mutagenesis was employed to generate starch-deficient mutants of indigenous Chlorella vulgaris to enhance its productivity. Out of 872 colonies, two isolated mutants (cvm5 and cvm6) were isolated and showed significant increase in cell concentrations by > 1.47-fold and > 1.04-fold, respectively. However, mutant cells exhibited smaller in size which might contributed to the significant decrease in their biomass. Moreover, gathered data revealed that the total lipid content of cvm5 was enhanced significantly (75%, > 1.3-fold increase). Additionally, triacylglycerol (TAG) content of the said mutant constitutes 48% of the dry cell weight (DCW) while cvm6 consist of 41% of the DCW. These promising and novel findings suggest that the two generated and isolated mutants are good candidates for future commercial biofuel production, especially in the Philippines. In addition, these findings may contribute on the prior knowledge of the usage of UV-C for microalgal strain development.

PhotoModPlus: A web server for photosynthetic protein prediction from genome neighborhood features

A new web server called PhotoModPlus is presented as a platform for predicting photosynthetic proteins via genome neighborhood networks (GNN) and genome neighborhood-based machine learning. GNN enables users to visualize the overview of the conserved neighboring genes from multiple photosynthetic prokaryotic genomes and provides functional guidance on the query input. In the platform, we also present a new machine learning model utilizing genome neighborhood features for predicting photosynthesis-specific functions based on 24 prokaryotic photosynthesis-related GO terms, namely PhotoModGO. The new model performed better than the sequence-based approaches with an F1 measure of 0.872, based on nested five-fold cross-validation. Finally, we demonstrated the applications of the webserver and the new model in the identification of novel photosynthetic proteins. The server is user-friendly, compatible with all devices, and available at bicep.kmutt.ac.th/photomod.

Applications of stable isotope-based metabolomics and fluxomics toward synthetic biology of cyanobacteria

Unique features of cyanobacteria (e.g., photosynthesis and nitrogen fixation) make them potential candidates for production of biofuels and other value-added biochemicals. As prokaryotes, they can be readily engineered using synthetic and systems biology tools. Metabolic engineering of cyanobacteria for the synthesis of desired compounds requires in-depth knowledge of central carbon and nitrogen metabolism, pathway fluxes, and their regulation. Metabolomics and fluxomics offer the comprehensive analysis of metabolism by directly characterizing the biochemical activities of cells. This information is acquired by measuring the abundance of key metabolites and their rates of interconversion, which can be achieved by labeling cells with stable isotopes, quantifying metabolite pool sizes and isotope incorporation by gas chromatography/liquid chromatography-mass spectrometry GC/LC-MS or nuclear magnetic resonance (NMR), and mathematical modeling to estimate in vivo metabolic fluxes. Herein, we review progress that has been made to adapt metabolomics and fluxomics tools to examine model cyanobacterial species. We summarize the application of metabolic flux analysis (MFA) strategies to identify metabolic bottlenecks that can be targeted to boost cell growth, improve stress tolerance, or enhance biochemical production in cyanobacteria. Despite the advances in metabolomics, fluxomics, and other synthetic and systems biology tools during the past years, further efforts are required to increase our understanding of cyanobacterial metabolism in order to create efficient photosynthetic hosts for the production of value-added compounds. This article is categorized under: Laboratory Methods and Technologies > Metabolomics Biological Mechanisms > Metabolism Analytical and Computational Methods > Analytical Methods.

Engineering xylose metabolism in thraustochytrid T18

BACKGROUND

Thraustochytrids are heterotrophic, oleaginous, marine protists with a significant potential for biofuel production. High-value co-products can off-set production costs; however, the cost of raw materials, and in particular carbon, is a major challenge to developing an economical viable production process. The use of hemicellulosic carbon derived from agricultural waste, which is rich in xylose and glucose, has been proposed as a sustainable and low-cost approach. Thraustochytrid strain T18 is a commercialized environmental isolate that readily consumes glucose, attaining impressive biomass, and oil production levels. However, neither thraustochytrid growth capabilities in the presence of xylose nor a xylose metabolic pathway has been described. The aims of this study were to identify and characterize the xylose metabolism pathway of T18 and, through genetic engineering, develop a strain capable of growth on hemicellulosic sugars.

RESULTS

Characterization of T18 performance in glucose/xylose media revealed diauxic growth and copious extracellular xylitol production. Furthermore, T18 did not grow in media containing xylose as the only carbon source. We identified, cloned, and functionally characterized a xylose isomerase. Transcriptomics indicated that this xylose isomerase gene is upregulated when xylose is consumed by the cells. Over-expression of the native xylose isomerase in T18, creating strain XI 16, increased xylose consumption from 5.2 to 7.6 g/L and reduced extracellular xylitol from almost 100% to 68%. Xylose utilization efficiency of this strain was further enhanced by over-expressing a heterologous xylulose kinase to reduce extracellular xylitol to 20%. Moreover, the ability to grow in media containing xylose as a sole sugar was dependent on the copy number of both xylose isomerase and xylulose kinase present. In fed-batch fermentations, the best xylose metabolizing isolate, XI-XK 7, used 137 g of xylose versus 39 g by wild type and produced more biomass and fatty acid.

CONCLUSIONS

The presence of a typically prokaryotic xylose isomerase and xylitol production through a typically eukaryotic xylose reductase pathway in T18 is the first report of an organism naturally encoding enzymes from two native xylose metabolic pathways. Our newly engineered strains pave the way for the growth of T18 on waste hemicellulosic feedstocks for biofuel production.

Increasing medium chain fatty acids production in Yarrowia lipolytica by metabolic engineering

BACKGROUND

Oleaginous yeast Yarrowia lipolytica is an organism of choice for the development of biofuel and oleochemicals. It has become a chassis for metabolic engineering in order to produce targeted lipids. Understanding the function of key-enzymes involved in lipid metabolism is essential to design better routes for enhanced lipid production and for strains producing lipids of interest. Because medium chain fatty acids (MCFA) are valuable compounds for biokerosene production, we previously generated strains capable of producing MCFA up to 12% of total lipid content (Rigouin et al. in ACS Synth Biol 6:1870-1879, 2017). In order to improve accumulation and content of C14 fatty acid (FA), the elongation, degradation and accumulation of these MCFA in Yarrowia lipolytica were studied.

RESULTS

We brought evidence of the role of YALI0F0654 (YlELO1) protein in the elongation of exogenous or de novo synthesized C14 FA into C16 FA and C18 FA. YlELO1 deletion into a αFAS_I1220W expressing strain leads to the sole production of C14 FA. However, because this strain does not provide the FA essential for its growth, it requires being cultivated with essential fatty acids and C14 FA yield is limited. To promote MCFA accumulation in Y. lipolytica without compromising the growth, we overexpressed a plant diglyceride acyltransferase specific for MCFA and reached an accumulation of MCFA up to 45% of total lipid content.

CONCLUSION

We characterized the role of YlELO1 in Y. lipolytica by proving its involvement in Medium chain fatty acids elongation. We showed that MCFA content can be increased in Yarrowia lipolytica by promoting their accumulation into a stable storage form (triacylglycerides) to limit their elongation and their degradation.

Enhancement of the lipid productivity and fatty acid methyl ester profile of Chlorella vulgaris by two rounds of mutagenesis

In this study, we applied a second round of random mutagenesis using ethyl methanesulfonate to further increase the lipid productivity of a Chlorella vulgaris mutant strain. We generated a mutant (UV715-EMS25) with a lipid content and biomass that were respectively 67% and 35% higher than those of the wild type (WT). The highest achieved lipid productivity in UV715-EMS25 was 91 mg L^-1 day^-1. Gas chromatography-mass spectrophotometric analysis revealed that the fatty acid methyl ester content of the mutant was 3.9-fold higher compared with that of WT cells. Amounts of saturated and monounsaturated fatty acids were also higher in the mutant, while the total amounts of polyunsaturated fatty acids were lower. Finally, the mutant displayed superior lipid productivity compared with the WT during pilot-scale cultivation in a flat panel photobioreactor. All these results demonstrate that UV715-EMS25 is highly suitable for biodiesel production.

Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data

Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named logical transformation of model (LTM) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.

Lipid Accumulation Mechanisms in Auto- and Heterotrophic Microalgae

Microalgae lipids have attracted great attention in the world as a result of their potential use for biodiesel productions. Microalgae are cultivated in photoautotrophic conditions in most cases, but several species are able to grow under heterotrophic conditions, in which microalgae are cultivated in the dark where the cell growth and reproduction are supported by organic carbons. This perspective is covering the related studies concerning the difference between hetero- and autotrophic cultivation of microalgae. The auto- and heterotrophic central carbon metabolic pathways in microalgae are described, and the catalyzing reactions of several key metabolic enzymes and their corresponding changes in the protein level are summarized. Under adverse environmental conditions, such as nutrient deprivation, microalgae have the ability to highly store energy by forming triacylglycerol (TAG), the reason for which is analyzed. In addition, the biosynthesis of fatty acids and TAGs and their difference between auto- and heterotrophic conditions are compared at the molecular level. The positive regulatory enzymes, such as glucose transporter protein, fructose-1,6-bisphosphate aldolase, and glycerol-3-phosphate dehydrogenase, and the negative regulation enzymes, such as triose phosphate isomerase, played a crucial role in the lipid accumulation auto- and heterotrophic conditions.

Algal Cell Factories: Approaches, Applications, and Potentials

With the advent of modern biotechnology, microorganisms from diverse lineages have been used to produce bio-based feedstocks and bioactive compounds. Many of these compounds are currently commodities of interest, in a variety of markets and their utility warrants investigation into improving their production through strain development. In this review, we address the issue of strain improvement in a group of organisms with strong potential to be productive “cell factories”: the photosynthetic microalgae. Microalgae are a diverse group of phytoplankton, involving polyphyletic lineage such as green algae and diatoms that are commonly used in the industry. The photosynthetic microalgae have been under intense investigation recently for their ability to produce commercial compounds using only light, CO₂, and basic nutrients. However, their strain improvement is still a relatively recent area of work that is under development. Importantly, it is only through appropriate engineering methods that we may see the full biotechnological potential of microalgae come to fruition. Thus, in this review, we address past and present endeavors towards the aim of creating productive algal cell factories and describe possible advantageous future directions for the field.

Growth rate evolution in improved environments under Prodigal Son dynamics

I use an individual-based model to investigate the evolution of cell division rates in asexual populations under chronic environmental enrichment. I show that maintaining increased growth rates over hundreds of generations following environmental improvement can be limited by increases in cellular damage associated with more rapid reproduction. In the absence of further evolution to either increase damage tolerance or decrease the cost of repair or rate of damage, environmental improvement does not reliably lead to long-term increases in reproductive rate in microbes. Here, more rapid cell division rates also increases damage, leading to selection for damage avoidance or repair, and a subsequent decrease in population growth, which I call Prodigal Son dynamics, because the consequences of 'living fast' force a return to ancestral growth rates. Understanding the conditions under which environmental enrichment is expected to sustainably increase cell division rates is important in applications that require rapid cell division (e.g. biofuel reactors) or seek to avoid the emergence of rapid cell division rates (controlling biofouling).