Non-model Microalga Research Articles

Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage

The non-model microalga Messastrum gracile SE-MC4 is a potential species for biodiesel production. However, low biomass productivity hinders it from passing the life cycle assessment for biodiesel production. Therefore, the current study was aimed at uncovering the differences in the transcriptome profiles of the microalgae at early exponential and early stationary growth phases and dissecting the roles of specific differential expressed genes (DEGs) involved in cell division during M. gracile cultivation. The transcriptome analysis revealed that the photosynthetic integral membrane protein genes such as photosynthetic antenna protein were severely down-regulated during the stationary growth phase. In addition, the signaling pathways involving transcription, glyoxylate metabolism and carbon metabolism were also down-regulated during stationary growth phase. Current findings suggested that the coordination between photosynthetic integral membrane protein genes, signaling through transcription and carbon metabolism classified as prominent strategies during exponential growth stage. These findings can be applied in genetic improvement of M. gracile for biodiesel application.

Systematic metabolome profiling and multi-omics analysis of the nitrogen-limited non-model oleaginous algae for biorefining

Oleaginous microalga Chlorella is a promising microbial cell factory for producing lipids, transesterifiable to biodiesel, and phytochemical, high-value molecules (HVMs). To better understand the stress-induced oleaginous mechanism of Chlorella sp. FC2 IITG that closely matches with Chlorella sorokiniana based on 18s rRNA gene sequence, we performed 'Algomics' by systematically integrating metabolomics and proteomics data in response to time-resolved nitrogen-limitation: 40 h (mild), 88 h (moderate), and 120 h (severe). Ten HVMs belonging to four biological classes: triacylglycerol (TAG), polyunsaturated fatty acids (PUFA), phytosterols, and terpenoids were annotated using untargeted metabolomics and MS/MS fragmentation pattern match to the spectral library. In particular, the study evidenced 4× and 6× increased accumulation of two different PUFA: 9(S)HpOTrE and dihomo-gamma-linolenic acid, respectively, in nitrogen-limitation conditions. Co-extraction of TAG and PUFA could lower the biodiesel production cost for feasible commercialization. The investigation found a maximum accumulation of TAG 59:10 at 40 h, while that for TAG 54:4 was recorded at 88 h, which suggests different TAG species could be induced by regulating nitrogen-limitation severity. Elevated ꞵ-oxidation, glycolysis, and tricarboxylic acid (TCA) cycle identified in proteomics analysis could provide the substrates, phosphoenolpyruvate, pyruvate, and acetyl CoA, for different phytochemical accumulation in response to nitrogen limitation. The multiomics data unraveled a metabolic tug-of-war ongoing between biomass and storage lipid (TAG) accumulation during nitrogen-limitation, which involved multiple processes including hindered CO2 fixation, the supply of energy, reductants, and carbon reallocation from proteins and membrane lipids. These findings provide distinct oleaginous mechanisms in non-model microalgae, Chlorella sp. FC2 IITG, and engineerable targets for microalgal trait improvements.

Double-high in palmitic and oleic acids accumulation in a non-model green microalga, Messastrum gracile SE-MC4 under nitrate-repletion and -starvation cultivations

Bioprospecting for biodiesel potential in microalgae primarily involves a few model species of microalgae and rarely on non-model microalgae species. Therefore, the present study determined changes in physiology, oil accumulation, fatty acid composition and biodiesel properties of a non-model microalga Messastrum gracile SE-MC4 in response to 12 continuous days of nitrate-starve (NS) and nitrate-replete (NR) conditions respectively. Under NS, the highest oil content (57.9%) was achieved despite reductions in chlorophyll content, biomass productivity and lipid productivity. However, under both NS and NR, palmitic acid and oleic acid remained as dominant fatty acids thus suggesting high potential of M. gracile for biodiesel feedstock consideration. Biodiesel properties analysis returned high values of cetane number (CN 61.9–64.4) and degree of unsaturation (DU 45.3–57.4) in both treatments. The current findings show the possibility of a non-model microalga to inherit superior ability over model species in oil accumulation for biodiesel development.

Bioengineering of Microalgae: Recent Advances, Perspectives, and Regulatory Challenges for Industrial Application.

Microalgae, due to their complex metabolic capacity, are being continuously explored for nutraceuticals, pharmaceuticals, and other industrially important bioactives. However, suboptimal yield and productivity of the bioactive of interest in local and robust wild-type strains are of perennial concerns for their industrial applications. To overcome such limitations, strain improvement through genetic engineering could play a decisive role. Though the advanced tools for genetic engineering have emerged at a greater pace, they still remain underused for microalgae as compared to other microorganisms. Pertaining to this, we reviewed the progress made so far in the development of molecular tools and techniques, and their deployment for microalgae strain improvement through genetic engineering. The recent availability of genome sequences and other omics datasets form diverse microalgae species have remarkable potential to guide strategic momentum in microalgae strain improvement program. This review focuses on the recent and significant improvements in the omics resources, mutant libraries, and high throughput screening methodologies helpful to augment research in the model and non-model microalgae. Authors have also summarized the case studies on genetically engineered microalgae and highlight the opportunities and challenges that are emerging from the current progress in the application of genome-editing to facilitate microalgal strain improvement. Toward the end, the regulatory and biosafety issues in the use of genetically engineered microalgae in commercial applications are described.

Evaluation of strategies for improving the transgene expression in an oleaginous microalga Scenedesmus acutus

BackgroundGenetic transformation of microalgae has been hampered by inefficient transgene expression, limiting the progress of microalgal biotechnology. Many vector tools and strategies have been developed in recent years to improve transgene expression in the model microalga Chlamydomonas, but these were hardly applied to other microalgae. In this work, naturally-isolated oleaginous microalgae were accessed for genetic transformation, and various expression systems were evaluated in a selected microalga to circumvent inefficient transgene expression.ResultsInitially, a strain of Scenedesmus acutus was selected from the oleaginous microalgal collection based on its highest transformation rate and transgene stability. This strain, which had very low or no GFP reporter expression, was first tested to improve transgene expression by using intron-containing constructs and the transcript fusion using ble::E2A. The intron-containing constructs yielded 2.5–7.5% of transformants with 2–4-fold fluorescence signals, while the majority of the transformants of the transcript fusion had the fluorescence signals up to 10-fold. Subsequently, three UV-induced S. acutus mutants were isolated with moderate increases in the level and frequency of transgene expression (2–3-fold and 10–12%, respectively). Finally, a transcript fusion system was developed using psy white mutants with an expression vector containing PSY::E2A for complementation and light selection. Transformants with green colonies were selected under light exposure, and the transgene expression was detected at protein levels. Although the improvement using PSY::E2A was only minor (1–2-fold increase and ~ 7% of transformants), this system provides an alternative selectable marker that is compatible with large-scale culture.ConclusionsHere, the overall improvement of transgene expression using the Chlamydomonas tools was moderate. The most effective tool so far is the transcript fusion using ble::E2A system. This work demonstrates that, so far, genetic engineering of non-model microalgae is still a challenging task. Further development of tools and strategies for transgene expression in microalgae are critically needed.

Exploring the transcriptome of non-model oleaginous microalga Dunaliella tertiolecta through high-throughput sequencing and high performance computing

BackgroundRNA-Seq technology has received a lot of attention in recent years for microalgal global transcriptomic profiling. It is widely used in transcriptome-wide analysis of gene expression., particularly for microalgal strains with potential as biofuel sources. However, insufficient genomic or transcriptomic information of non-model microalgae has limited the understanding of their regulatory mechanisms and hampered genetic manipulation to enhance biofuel production. As such, an optimal microalgal transcriptomic database construction is a subject of urgent investigation.ResultsDunaliella tertiolecta, a non-model oleaginous microalgal species, was sequenced via Illumina MISEQ and HISEQ 4000 in RNA-Seq studies. The high quality high-throughout sequencing data were explored using high performance computing (HPC) in a petascale data center and subjected to de novo assembly and parallelized mpiBLASTX search with multiple species. As a result, a transcriptome database of 17,845 was constructed (~95% completeness). This enlarged database constructed fueled the RNA-Seq data analysis, which was validated by a nitrogen deprivation (ND) study that induces triacylglycerol (TAG) production.ConclusionsThe new paralleled assembly and annotation method under HPC presented here allows the solution of large-scale data processing problems in acceptable computation time. There is significant increase in the number of transcriptomic data achieved and observable heterogeneity in the performance to identify differentially expressed genes in the ND treatment paradigm. The results provide new insights as to how response to ND treatment in microalgae is regulated. ND analyses highlight the advantages of this database generated in this study that could also serve as a useful resource for future gene manipulation and transcriptome-wide analysis. We thus demonstrate the usefulness of exploring the transcriptome as an informative platform for functional studies and genetic manipulations in similar species.

Mass spectrometry-based metabolomics of value-added biochemicals from Ettlia oleoabundans

Microalgae are promising feedstocks for biofuels and other value-added biochemicals. Ettlia oleoabundans, a non-model green microalga, produces increased levels of key precursors for lipid-based biofuels under nutrient stress conditions. Here, we introduce a method for analysis of hydrophobic metabolites in E. oleoabundans and apply this method to microalgae grown under different nutrient conditions. We combined targeted analysis using gas chromatography/tandem mass spectrometry (GC–MS/MS) with targeted and untargeted metabolomics using liquid chromatography-quadrupole-time-of-flight mass spectrometry (LC-Q-ToF MS). Our method allows simultaneous detection of compounds from major lipid families, and other value-added biochemicals using less biomass, hence allowing analysis of larger number of samples to be processed simultaneously. In this study, we showed that 202 metabolites were enhanced or depleted under nutrient stress and annotated 163 of these species. A complex regulation of different classes of metabolites under nutrient stress was observed. Overall, triacylglycerols and sulfoquinovosyldiacylglycerols were accumulated, chlorophylls were depleted, and diacylglycerols were differentially regulated at the molecular level when grown under limited nutrient conditions. The method that we developed will serve as a template for targeted and untargeted metabolomics in E. oleoabundans and other non-model microalgae to understand biochemical regulations under different experimental conditions.

Discovery of genes for production of biofuels through transcriptome sequencing of Dunaliella parva

Compared with first generation plant-based biofuels, microalgae have potential advantages as feedstock for biofuel production. However, the genome sequences were insufficient in non-model microalgae with potential for biofuel production, which limited the development of genetic engineering of these microalgae. Here we described the de novo transcriptome sequencing and assembly for the halophilic green alga Dunaliella parva and identified important pathways, genes and transcription factor gene wri1 involved in biofuel production. The Illumina Hiseq 2000 platform was applied to D. parva transcriptome sequencing, which produced 26,304,060 (assembled into 60,883 contigs) and 26,797,446 (assembled into 55,236 contigs) high quality reads in samples SCH-5.0mMA (control sample) and SCH-0.5mMA (nitrogen limitation sample) respectively. Assembled contigs were subjected to Blastx search and annotated with NCBI non-redundant protein database, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes orthology identifiers. These analyses obtained the majority of genes involved in the biosynthesis and degradation of lipid and starch in D. parva. In addition, we have identified numerous differentially expressed genes, especially important transcription factor gene wri1 (GenBank KR185335) and studied differential expression of wri1 between control and nitrogen limitation sample, which provided foundation for illuminating the regulation mechanism of lipid biosynthesis induced by nitrogen limitation.

Transcriptome analysis reveals unique C4-like photosynthesis and oil body formation in an arachidonic acid-rich microalga Myrmecia incisa Reisigl H4301.

BackgroundArachidonic acid (ArA) is important for human health because it is one of the major components of mammalian brain membrane phospholipids. The interest in ArA inspired the search for a new sustainable source, and the green microalga Myrmecia incisa Reisigl H4301 has been found a potential ArA-producer due to a high content of intracellular ArA. To gain more molecular information about metabolism pathways, including the biosynthesis of ArA in the non-model microalga, a transcriptomic analysis was performed.ResultsThe 454 pyrosequencing generated 371,740 high-quality reads, which were assembled into 51,908 unique sequences consisting of 22,749 contigs and 29,159 singletons. A total of 11,873 unique sequences were annotated through BLAST analysis, and 3,733 were assigned to Gene Ontology (GO) categories. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis uncovered a C4-like photosynthesis pathway in M. incisa. The biosynthesis pathways of lipid particularly those of ArA and triacylglycerol (TAG) were analyzed in detail, and TAG was proposed to be accumulated in oil bodies in the cytosol with the help of caleosin or oil globule-associated proteins. In addition, the carotenoid biosynthesis pathways are discussed.ConclusionThis transcriptomic analysis of M. incisa enabled a global understanding of mechanisms involved in photosynthesis, de novo biosynthesis of ArA, metabolism of carotenoids, and accumulation of TAG in M. incisa. These findings provided a molecular basis for the research and possibly economic exploitation of this ArA-rich microalga.

De Novo Transcriptomic Analysis of an Oleaginous Microalga: Pathway Description and Gene Discovery for Production of Next-Generation Biofuels

Background Eustigmatos cf. polyphem is a yellow-green unicellular soil microalga belonging to the eustimatophyte with high biomass and considerable production of triacylglycerols (TAGs) for biofuels, which is thus referred to as an oleaginous microalga. The paucity of microalgae genome sequences, however, limits development of gene-based biofuel feedstock optimization studies. Here we describe the sequencing and de novo transcriptome assembly for a non-model microalgae species, E. cf. polyphem, and identify pathways and genes of importance related to biofuel production.ResultsWe performed the de novo assembly of E. cf. polyphem transcriptome using Illumina paired-end sequencing technology. In a single run, we produced 29,199,432 sequencing reads corresponding to 2.33 Gb total nucleotides. These reads were assembled into 75,632 unigenes with a mean size of 503 bp and an N50 of 663 bp, ranging from 100 bp to >3,000 bp. Assembled unigenes were subjected to BLAST similarity searches and annotated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology identifiers. These analyses identified the majority of carbohydrate, fatty acids, TAG and carotenoids biosynthesis and catabolism pathways in E. cf. polyphem.ConclusionsOur data provides the construction of metabolic pathways involved in the biosynthesis and catabolism of carbohydrate, fatty acids, TAG and carotenoids in E. cf. polyphem and provides a foundation for the molecular genetics and functional genomics required to direct metabolic engineering efforts that seek to enhance the quantity and character of microalgae-based biofuel feedstock.

Transcriptome sequencing and annotation of the microalgae Dunaliella tertiolecta: Pathway description and gene discovery for production of next-generation biofuels

BackgroundBiodiesel or ethanol derived from lipids or starch produced by microalgae may overcome many of the sustainability challenges previously ascribed to petroleum-based fuels and first generation plant-based biofuels. The paucity of microalgae genome sequences, however, limits gene-based biofuel feedstock optimization studies. Here we describe the sequencing and de novo transcriptome assembly for the non-model microalgae species, Dunaliella tertiolecta, and identify pathways and genes of importance related to biofuel production.ResultsNext generation DNA pyrosequencing technology applied to D. tertiolecta transcripts produced 1,363,336 high quality reads with an average length of 400 bases. Following quality and size trimming, ~ 45% of the high quality reads were assembled into 33,307 isotigs with a 31-fold coverage and 376,482 singletons. Assembled sequences and singletons were subjected to BLAST similarity searches and annotated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology (KO) identifiers. These analyses identified the majority of lipid and starch biosynthesis and catabolism pathways in D. tertiolecta.ConclusionsThe construction of metabolic pathways involved in the biosynthesis and catabolism of fatty acids, triacylglycrols, and starch in D. tertiolecta as well as the assembled transcriptome provide a foundation for the molecular genetics and functional genomics required to direct metabolic engineering efforts that seek to enhance the quantity and character of microalgae-based biofuel feedstock.