Green genes: bioinformatics and systems-biology innovations drive algal biotechnology

The identification of a correlation between lipid content in the model diatom Phaeodactylum tricornutum and pH treatment strategies

pH treatment promotes single-cell lipid accumulation and significantly affects microalgae growth. This study investigates the correlation between lipid content and environmental pH using the model diatom Phaeodactylum tricornutum (P. tricornutum). We compared three distinct pH treatment strategies-continuous, intermittent, and a two-phase culture-in P. tricornutum. Rigorous analysis of chlorophyll content, cell density, and lipid content indicated that ongoing pH treatment at pH 9.5 (CHES) emerged as the most effective approach for lipid accumulation in P. tricornutum. The CHES buffer treatment significantly boosted total lipid yield and led to a reduction in protein content. Carbohydrate content experienced a slight decline under CHES buffer treatment, but changes were observed in the activities of key enzymes. Specifically, [acyl-carrier-protein] S-malonyltransferase (MAT) activity decreased after 3 days in the control treatment, while no significant change was noted under the CHES buffer treatment. In contrast, diacylglycerol O-acyltransferase (DGAT) activity showed upregulation 2 and 3 days post-CHES buffer treatment. Moreover, the study identified differentially expressed genes enriched in Gene Ontology (GO) terms associated with protein biosynthesis, photosynthesis, nucleoside metabolism, and transferase activity. These outcomes underscore the pivotal role of CHES buffer in orchestrating primary metabolism, potentially steering carbon flux towards lipogenesis. As a result, the potential of microalgae as a sustainable source of biofuels contributes significantly to the transition towards a more environmentally friendly energy landscape.

The Potential of Allelochemicals from Microalgae for Biopesticides

Improvements in agricultural productivity are required to meet the demand of a growing world population. Phytopathogens, weeds, and insects are challenges to agricultural production. The toxicity and widespread application of persistent synthetic pesticides poses a major threat to human and ecosystem health. Therefore, sustainable strategies to control pests are essential for agricultural systems to enhance productivity within a green paradigm. Allelochemicals are a less persistent, safer, and friendly alternative to efficient pest management, as they tend to be less toxic to non-target organisms and more easily degradable. Microalgae produce a great variety of allelopathic substances whose biocontrol potential against weeds, insects, and phytopathogenic fungi and bacteria has received much attention. This review provides up-to-date information and a critical perspective on allelochemicals from microalgae and their potential as biopesticides.

New paradigm in diatom omics and genetic manipulation

Diatoms are one of the most heterogeneous eukaryotic plankton known for regulating earth's biogeochemical cycles and maintaining the marine ecosystems ever since the late Eocene epoch. The advent of multidisciplinary omics approach has both epitomized and revolutionized the nature of their chimeric genetic toolkit, ecophysiology, and metabolic adaptability as well as their interaction with other communities. In addition, advanced functional annotation of transcriptomic and proteomic data using cutting edge bioinformatics tools together with high-resolution genome-scale mathematical modeling has effectively proven as the catapult in solving genetic bottlenecks in microbial as well as diatom exploration. In this review, a corroborative summation of the robust work done in manipulating, engineering, and sequencing of the diatom genomes besides underpinning the holistic application of omics in transcription and translation has been discussed in order to shrewd their multifarious novel potential in the field of biotechnology and provide an insight into their dynamic evolutionary relevance.

Challenging microalgal vitamins for human health

BACKGROUND

Vitamins' deficiency in humans is an important threat worldwide and requires solutions. In the concept of natural biofactory for bioactive compounds production, microalgae represent one of the most promising targets filling many biotechnological applications, and allowing the development of an eco-sustainable production of natural bioactive metabolites. Vitamins are probably one of the cutting edges of microalgal diversity compounds.

MAIN TEXT

Microalgae can usefully provide many of the required vitamins in humans, more than terrestrial plants, for instance. Indeed, vitamins D and K, little present in many plants or fruits, are instead available from microalgae. The same occurs for some vitamins B (B12, B9, B6), while the other vitamins (A, C, D, E) are also provided by microalgae. This large panel of vitamins diversity in microalgal cells represents an exploitable platform in order to use them as natural vitamins' producers for human consumption. This study aims to provide an integrative overview on vitamins content in the microalgal realm, and discuss on the great potential of microalgae as sources of different forms of vitamins to be included as functional ingredients in food or nutraceuticals for the human health. We report on the biological roles of vitamins in microalgae, the current knowledge on their modulation by environmental or biological forcing and on the biological activity of the different vitamins in human metabolism and health protection.

CONCLUSION

Finally, we critically discuss the challenges for promoting microalgae as a relevant source of vitamins, further enhancing the interests of microalgal "biofactory" for biotechnological applications, such as in nutraceuticals or cosmeceuticals.

Microalgae with artificial intelligence: A digitalized perspective on genetics, systems and products

With recent advances in novel gene-editing tools such as RNAi, ZFNs, TALENs, and CRISPR-Cas9, the possibility of altering microalgae toward designed properties for various application is becoming a reality. Alteration of microalgae genomes can modify metabolic pathways to give elevated yields in lipids, biomass, and other components. The potential of such genetically optimized microalgae can give a "domino effect" in further providing optimization leverages down the supply chain, in aspects such as cultivation, processing, system design, process integration, and revolutionary products. However, the current level of understanding the functional information of various microalgae gene sequences is still primitive and insufficient as microalgae genome sequences are long and complex. From this perspective, this work proposes to link up this knowledge gap between microalgae genetic information and optimized bioproducts using Artificial Intelligence (AI). With the recent acceleration of AI research, large and complex data from microalgae research can be properly analyzed by combining the cutting-edge of both fields. In this work, the most suitable class of AI algorithms (such as active learning, semi-supervised learning, and meta-learning) are discussed for different cases of microalgae applications. This work concisely reviews the current state of the research milestones and highlight some of the state-of-art that has been carried out, providing insightful future pathways. The utilization of AI algorithms in microalgae cultivation, system optimization, and other aspects of the supply chain is also discussed. This work opens the pathway to a digitalized future for microalgae research and applications.

Reconstruction and analysis of a carbon-core metabolic network for Dunaliella salina

BACKGROUND

The green microalga Dunaliella salina accumulates a high proportion of β-carotene during abiotic stress conditions. To better understand the intracellular flux distribution leading to carotenoid accumulation, this work aimed at reconstructing a carbon core metabolic network for D. salina CCAP 19/18 based on the recently published nuclear genome and its validation with experimental observations and literature data.

RESULTS

The reconstruction resulted in a network model with 221 reactions and 212 metabolites within three compartments: cytosol, chloroplast and mitochondrion. The network was implemented in the MATLAB toolbox CellNetAnalyzer and checked for feasibility. Furthermore, a flux balance analysis was carried out for different light and nutrient uptake rates. The comparison of the experimental knowledge with the model prediction revealed that the results of the stoichiometric network analysis are plausible and in good agreement with the observed behavior. Accordingly, our model provides an excellent tool for investigating the carbon core metabolism of D. salina.

CONCLUSIONS

The reconstructed metabolic network of D. salina presented in this work is able to predict the biological behavior under light and nutrient stress and will lead to an improved process understanding for the optimized production of high-value products in microalgae.

Biotechnological Advances in the Design of Algae-Based Biosensors

In addition to their use in biomass production and bioremediation, algae have been extensively exploited in biosensing applications. Algae-based biosensors have demonstrated potential for sensitive, sustainable, and multiplexed detection of analytes of agroenvironmental and security interest. Their advantages include the availability of different algal bioreceptors including whole cells and their photosynthetic subcomponents, their potential to be integrated into dual transduction miniaturized devices, and the opportunity for continuous environmental monitoring. Despite obstacles including limited stability and selectivity, algae-based biosensing is a realistic prospect that has some recent effective applications. Strategic exploitation of cutting-edge technologies including materials science, nanotechnology, microfluidics, and genome editing will help to achieve the full potential of algae-based sensors.

Transgenic microalgae as bioreactors

Microalgae are unicellular organisms that act as the crucial primary producers all over the world, typically found in marine and freshwater environments. Most of them can live photo-autotrophically, reproduce rapidly, and accumulate biomass in a short period efficiently. To adapt to the uninterrupted change of the environment, they evolve and differentiate continuously. As a result, some of them evolve special abilities such as toleration of extreme environment, generation of sophisticated structure to adapt to the environment, and avoid predators. Microalgae are believed to be promising bioreactors because of their high lipid and pigment contents. Genetic engineering technologies have given revolutions in the microalgal industry, which decoded the secrets of microalgal genes, express recombinant genes in microalgal genomes, and largely soar the accumulation of interested components in transgenic microalgae. However, owing to several obstructions, the industry of transgenic microalgae is still immature. Here, we provide an overview to emphasize the advantage and imperfection of the existing transgenic microalgal bioreactors.

Identification and characterization of candidates involved in production of OMEGAs in microalgae: a gene mining and phylogenomic approach

Optimizing the production of the high-value renewables such as OMEGAs through pathway engineering requires an in-depth understanding of the structure-function relationship of genes involved in the OMEGA biosynthetic pathways. In this preliminary study, our rationale is to identify and characterize the ∼221 putative genes involved in production of OMEGAs using bioinformatic analysis from the Streptophyte (plants), Chlorophyte (green algae), Rhodophyta (red algae), and Bacillariophyta (diatoms) lineages based on their phylogenomic profiling, conserved motif/domain organization and physico-chemical properties. The MEME suite predicted 12 distinct protein domains, which are conserved among these putative genes. The phylogenomic analysis of the putative candidate genes [such as FAD2 (delta-12 desaturase); ECR (enoyl-CoA reductase); FAD2 (delta-12 desaturase); ACOT (acyl CoA thioesterase); ECH (enoyl-CoA hydratase); and ACAT (acetyl-CoA acyltransferase)] with similar domains and motif patterns were remarkably well conserved. Furthermore, the subcellular network prediction of OMEGA biosynthetic pathway genes revealed a unique interaction between the light-dependent chlorophyll biosynthesis and glycerol-3-phosphate dehydrogenase, which predicts a major cross-talk between the key essential pathways. Such bioinformatic analysis will provide insights in finding the key regulatory genes to optimize the productivity of OMEGAs in microalgal cell factories.

Microalgae, old sustainable food and fashion nutraceuticals

Microalgae have been used for centuries to provide nourishment to humans and animals, only very recently they have become much more widely cultured and harvested at large industrial scale. This paper reviews the potential health benefits and nutrition provided by microalgae whose benefits are contributing to expand their market. We also point out several key challenges that remain to be addressed in this field.

Alga-PrAS (Algal Protein Annotation Suite): A Database of Comprehensive Annotation in Algal Proteomes

Algae are smaller organisms than land plants and offer clear advantages in research over terrestrial species in terms of rapid production, short generation time and varied commercial applications. Thus, studies investigating the practical development of effective algal production are important and will improve our understanding of both aquatic and terrestrial plants. In this study we estimated multiple physicochemical and secondary structural properties of protein sequences, the predicted presence of post-translational modification (PTM) sites, and subcellular localization using a total of 510,123 protein sequences from the proteomes of 31 algal and three plant species. Algal species were broadly selected from green and red algae, glaucophytes, oomycetes, diatoms and other microalgal groups. The results were deposited in the Algal Protein Annotation Suite database (Alga-PrAS; http://alga-pras.riken.jp/), which can be freely accessed online.

Dynamic flux balance modeling to increase the production of high-value compounds in green microalgae

BACKGROUND

Photosynthetic organisms can be used for renewable and sustainable production of fuels and high-value compounds from natural resources. Costs for design and operation of large-scale algae cultivation systems can be reduced if data from laboratory scale cultivations are combined with detailed mathematical models to evaluate and optimize the process.

RESULTS

In this work we present a flexible modeling formulation for accumulation of high-value storage molecules in microalgae that provides quantitative predictions under various light and nutrient conditions. The modeling approach is based on dynamic flux balance analysis (DFBA) and includes regulatory models to predict the accumulation of pigment molecules. The accuracy of the model predictions is validated through independent experimental data followed by a subsequent model-based fed-batch optimization. In our experimentally validated fed-batch optimization study we increase biomass and [Formula: see text]-carotene density by factors of about 2.5 and 2.1, respectively.

CONCLUSIONS

The analysis shows that a model-based approach can be used to develop and significantly improve biotechnological processes for biofuels and pigments.

Metabolic regulation of triacylglycerol accumulation in the green algae: identification of potential targets for engineering to improve oil yield

The great need for more sustainable alternatives to fossil fuels has increased our research interests in algal biofuels. Microalgal cells, characterized by high photosynthetic efficiency and rapid cell division, are an excellent source of neutral lipids as potential fuel stocks. Various stress factors, especially nutrient-starvation conditions, induce an increased formation of lipid bodies filled with triacylglycerol in these cells. Here we review our knowledge base on glycerolipid synthesis in the green algae with an emphasis on recent studies on carbon flux, redistribution of lipids under nutrient-limiting conditions and its regulation. We discuss the contributions and limitations of classical and novel approaches used to elucidate the algal triacylglycerol biosynthetic pathway and its regulatory network in green algae. Also discussed are gaps in knowledge and suggestions for much needed research both on the biology of triacylglycerol accumulation and possible avenues to engineer improved algal strains.

Role of riboswitches in gene regulation and their potential for algal biotechnology

Riboswitches are regulatory elements in messenger RNA to which specific ligands can bind directly in the absence of proteins. Ligand binding alters the mRNA secondary structure, thereby affecting expression of the encoded protein. Riboswitches are widespread in prokaryotes, with over 20 different effector ligands known, including amino acids, cofactors, and Mg(2+) ions, and gene expression is generally regulated by affecting translation or termination of transcription. In plants, fungi, and microalgae, riboswitches have been found, but only those that bind thiamine pyrophosphate. These eukaryotic riboswitches operate by causing alternative splicing of the transcript. Here, we review the current status of riboswitch research with specific emphasis on microalgae. We discuss new riboswitch discoveries and insights into the underlying mechanism of action, and how next generation sequencing technology provides the motivation and opportunity to improve our understanding of these rare but important regulatory elements. We also highlight the potential of microalgal riboswitches as a tool for synthetic biology and industrial biotechnology.

dEMBF: A Comprehensive Database of Enzymes of Microalgal Biofuel Feedstock

Microalgae have attracted wide attention as one of the most versatile renewable feedstocks for production of biofuel. To develop genetically engineered high lipid yielding algal strains, a thorough understanding of the lipid biosynthetic pathway and the underpinning enzymes is essential. In this work, we have systematically mined the genomes of fifteen diverse algal species belonging to Chlorophyta, Heterokontophyta, Rhodophyta, and Haptophyta, to identify and annotate the putative enzymes of lipid metabolic pathway. Consequently, we have also developed a database, dEMBF (Database of Enzymes of Microalgal Biofuel Feedstock), which catalogues the complete list of identified enzymes along with their computed annotation details including length, hydrophobicity, amino acid composition, subcellular location, gene ontology, KEGG pathway, orthologous group, Pfam domain, intron-exon organization, transmembrane topology, and secondary/tertiary structural data. Furthermore, to facilitate functional and evolutionary study of these enzymes, a collection of built-in applications for BLAST search, motif identification, sequence and phylogenetic analysis have been seamlessly integrated into the database. dEMBF is the first database that brings together all enzymes responsible for lipid synthesis from available algal genomes, and provides an integrative platform for enzyme inquiry and analysis. This database will be extremely useful for algal biofuel research. It can be accessed at http://bbprof.immt.res.in/embf.

In Metabolic Engineering of Eukaryotic Microalgae: Potential and Challenges Come with Great Diversity

The great phylogenetic diversity of microalgae is corresponded by a wide arrange of interesting and useful metabolites. Nonetheless metabolic engineering in microalgae has been limited, since specific transformation tools must be developed for each species for either the nuclear or chloroplast genomes. Microalgae as production platforms for metabolites offer several advantages over plants and other microorganisms, like the ability of GMO containment and reduced costs in culture media, respectively. Currently, microalgae have proved particularly well suited for the commercial production of omega-3 fatty acids and carotenoids. Therefore most metabolic engineering strategies have been developed for these metabolites. Microalgal biofuels have also drawn great attention recently, resulting in efforts for improving the production of hydrogen and photosynthates, particularly triacylglycerides. Metabolic pathways of microalgae have also been manipulated in order to improve photosynthetic growth under specific conditions and for achieving trophic conversion. Although these pathways are not strictly related to secondary metabolites, the synthetic biology approaches could potentially be translated to this field and will also be discussed.

A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses

Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii. The model, iCre1355, represents a major advance over previous models, both in content and predictive power. iCre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting for 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using iCre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae.

Trade-Off between Growth and Carbohydrate Accumulation in Nutrient-Limited Arthrospira sp. PCC 8005 Studied by Integrating Transcriptomic and Proteomic Approaches

Cyanobacteria have a strong potential for biofuel production due to their ability to accumulate large amounts of carbohydrates. Nitrogen (N) stress can be used to increase the content of carbohydrates in the biomass, but it is expected to reduce biomass productivity. To study this trade-off between carbohydrate accumulation and biomass productivity, we characterized the biomass productivity, biomass composition as well as the transcriptome and proteome of the cyanobacterium Arthrospira sp. PCC 8005 cultured under N-limiting and N-replete conditions. N limitation resulted in a large increase in the carbohydrate content of the biomass (from 14 to 74%) and a decrease in the protein content (from 37 to 10%). Analyses of fatty acids indicated that no lipids were accumulated under N-limited conditions. Nevertheless, it did not affect the biomass productivity of the culture up to five days after N was depleted from the culture medium. Transcriptomic and proteomic analysis indicated that de novo protein synthesis was down-regulated in the N-limited culture. Proteins were degraded and partly converted into carbohydrates through gluconeogenesis. Cellular N derived from protein degradation was recycled through the TCA and GS-GOGAT cycles. In addition, photosynthetic energy production and carbon fixation were both down-regulated, while glycogen synthesis was up-regulated. Our results suggested that N limitation resulted in a redirection of photosynthetic energy from protein synthesis to glycogen synthesis. The fact that glycogen synthesis has a lower energy demand than protein synthesis might explain why Arthrospira is able to achieve a similar biomass productivity under N-limited as under N-replete conditions despite the fact that photosynthetic energy production was impaired by N limitation.

Establishing Chlamydomonas reinhardtii as an industrial biotechnology host

Microalgae constitute a diverse group of eukaryotic unicellular organisms that are of interest for pure and applied research. Owing to their natural synthesis of value-added natural products microalgae are emerging as a source of sustainable chemical compounds, proteins and metabolites, including but not limited to those that could replace compounds currently made from fossil fuels. For the model microalga, Chlamydomonas reinhardtii, this has prompted a period of rapid development so that this organism is poised for exploitation as an industrial biotechnology platform. The question now is how best to achieve this? Highly advanced industrial biotechnology systems using bacteria and yeasts were established in a classical metabolic engineering manner over several decades. However, the advent of advanced molecular tools and the rise of synthetic biology provide an opportunity to expedite the development of C. reinhardtii as an industrial biotechnology platform, avoiding the process of incremental improvement. In this review we describe the current status of genetic manipulation of C. reinhardtii for metabolic engineering. We then introduce several concepts that underpin synthetic biology, and show how generic parts are identified and used in a standard manner to achieve predictable outputs. Based on this we suggest that the development of C. reinhardtii as an industrial biotechnology platform can be achieved more efficiently through adoption of a synthetic biology approach.