Elucidation of the growth delimitation of Dunaliella tertiolecta under nitrogen stress by integrating transcriptome and peptidome analysis

De novo transcriptome and lipidome analysis of Desmodesmus abundans under model flue gas reveals adaptive changes after ten years of acclimation to high CO2

Microalgae's ability to mitigate flue gas is an attractive technology that can valorize gas components through biomass conversion. However, tolerance and growth must be ideal; therefore, acclimation strategies are suggested. Here, we compared the transcriptome and lipidome of Desmodesmus abundans strains acclimated to high CO2 (HCA) and low CO2 (LCA) under continuous supply of model flue gas (MFG) and incomplete culture medium (BG11-N-S). Initial growth and nitrogen consumption from MFG were superior in strain HCA, reaching maximum productivity a day before strain LCA. However, similar productivities were attained at the end of the run, probably because maximum photobioreactor capacity was reached. RNA-seq analysis during exponential growth resulted in 16,435 up-regulated and 4,219 down-regulated contigs in strain HCA compared to LCA. Most differentially expressed genes (DEGs) were related to nucleotides, amino acids, C fixation, central carbon metabolism, and proton pumps. In all pathways, a higher number of up-regulated contigs with a greater magnitude of change were observed in strain HCA. Also, cellular component GO terms of chloroplast and photosystems, N transporters, and secondary metabolic pathways of interest, such as starch and triacylglycerols (TG), exhibited this pattern. RT-qPCR confirmed N transporters expression. Lipidome analysis showed increased glycerophospholipids in strain HCA, while LCA exhibited glycerolipids. Cell structure and biomass composition also revealed strains differences. HCA possessed a thicker cell wall and presented a higher content of pigments, while LCA accumulated starch and lipids, validating transcriptome and lipidome data. Overall, results showed significant differences between strains, where characteristic features of adaptation and tolerance to high CO2 might be related to the capacity to maintain a higher flux of internal C, regulate intracellular acidification, active N transporters, and synthesis of essential macromolecules for photosynthetic growth.

Meta-analysis of transcriptomic profiles in Dunaliella tertiolecta reveals molecular pathway responses to different abiotic stresses

Microalgae are photosynthetic organisms and a potential source of sustainable metabolite production. However, different stress conditions might affect the production of various metabolites. In this study, a meta-analysis of RNA-seq experiments in Dunaliella tertiolecta was evaluated to compare metabolite biosynthesis pathways in response to abiotic stress conditions such as high light, nitrogen deficiency and high salinity. Results showed downregulation of light reaction, photorespiration, tetrapyrrole and lipid-related pathways occurred under salt stress. Nitrogen deficiency mostly induced the microalgal responses of light reaction and photorespiration metabolism. Phosphoenol pyruvate carboxylase, phosphoglucose isomerase, bisphosphoglycerate mutase and glucose-6-phosphate-1-dehydrogenase (involved in central carbon metabolism) were commonly upregulated under salt, light and nitrogen stresses. Interestingly, the results indicated that the meta-genes (modules of genes strongly correlated) were located in a hub of stress-specific protein-protein interaction (PPI) network. Module enrichment of meta-genes PPI networks highlighted the cross-talk between photosynthesis, fatty acids, starch and sucrose metabolism under multiple stress conditions. Moreover, it was observed that the coordinated expression of the tetrapyrrole intermediated with meta-genes was involved in starch biosynthesis. Our results also showed that the pathways of vitamin B6 metabolism, methane metabolism, ribosome biogenesis and folate biosynthesis responded specifically to different stress factors. Since the results of this study revealed the main pathways underlying the abiotic stress, they might be applied in optimised metabolite production by the microalga Dunaliella in future studies. PRISMA check list was also included in the study.

Optimizing light regimes for neutral lipid accumulation in Dunaliella salina MCC 43: a study on physiological status and carbon allocation

Dunaliella salina is a favourable source of high lipid feedstock for biofuel and medicinal chemicals. Low biomass output from microalgae is a significant barrier to industrial-scale commercialisation. The current study aimed to determine how photosynthetic efficiency, carbon fixation, macromolecular synthesis, accumulation of neutral lipids, and antioxidative defence (ROS scavenging enzyme activities) of D. salina cells were affected by different light intensities (LI) (50, 100, 200, and 400 µmol m-2 s-1). The cells when exposed to strong light (400 µmol m-2 s-1) led to reduction in chlorophyll a but the carotenoid content increased by 19% in comparison to the control (LI 100). The amount of carbohydrate changed significantly under high light and in spite of stress inflicted on the cells by high irradiation, a considerable increase in activity of carbonic anhydrase and fixation rate of CO2 were recorded, thus, preserving the biomass content. The high light exposed biomass when subjected to nitrogen-deficient medium led to increase in lipid content (59.92% of the dry cell weight). However, neutral lipid made up 78.26% of the total lipid while other lipids like phospholipid and glycolipid content decreased, showing that the lipid was redistributed in these cells under nitrogen deprivation, making the organism more appropriate for biodiesel/jet fuel use. Although D. salina cells had a relatively longer generation time (3.5 d) than other microalgal cells, an economic analysis concluded that the amount of carotenoid they produced and the quality of their lipids made them more suited for commercialization.

Realization process of microalgal biorefinery: The optional approach toward carbon net-zero emission

Increasing carbon dioxide (CO2) emission has already become a dire threat to the human race and Earth's ecology. Microalgae are recommended to be engineered as CO2 fixers in biorefinery, which play crucial roles in responding climate change and accelerating the transition to a sustainable future. This review sorted through each segment of microalgal biorefinery to explore the potential for its practical implementation and commercialization, offering valuable insights into research trends and identifies challenges that needed to be addressed in the development process. Firstly, the known mechanisms of microalgal photosynthetic CO2 fixation and the approaches for strain improvement were summarized. The significance of process regulation for strengthening fixation efficiency and augmenting competitiveness was emphasized, with a specific focus on CO2 and light optimization strategies. Thereafter, the massive potential of microalgal refineries for various bioresource production was discussed in detail, and the integration with contaminant reclamation was mentioned for economic and ecological benefits. Subsequently, economic and environmental impacts of microalgal biorefinery were evaluated via life cycle assessment (LCA) and techno-economic analysis (TEA) to lit up commercial feasibility. Finally, the current obstacles and future perspectives were discussed objectively to offer an impartial reference for future researchers and investors.

Different Regulatory Modes of Synechocystis sp. PCC 6803 in Response to Photosynthesis Inhibitory Conditions

Cyanobacteria are promising industrial platforms owing to their ability to produce diverse natural secondary metabolites and nonnative value-added biochemicals from CO₂ and light. To fully utilize their industrial potency, it is critical to understand their photosynthetic efficiency under various environmental conditions. In this study, we elucidated the inhibitory mechanisms of photosynthesis under high-light and low-temperature stress conditions in the model cyanobacterium Synechocystis sp. PCC 6803. Under each stress condition, the transcript abundance and translation efficiency were measured using transcriptome sequencing (RNA-seq) and ribosome profiling, and the genome-wide transcription unit architecture was constructed by data integration of transcription start sites and transcript 3′-end positions obtained from differential RNA-seq and sequencing of 3′-ends (Term-seq), respectively. Our results suggested that the mode of photosynthesis inhibition differed between the two stress conditions; high light stress induced photodamage responses, while low temperature stress impaired the translation efficiency of photosynthesis-associated genes. In particular, poor translation of photosystem I resulted from ribosome stalling at the untranslated regions, affecting the overall photosynthetic yield under low temperature stress. Our comprehensive multiomics analysis with transcription unit architecture provides foundational information on photosynthesis for future industrial strain development.

IMPORTANCE Cyanobacteria are a compelling biochemical production platform for their ability to propagate using light and atmospheric CO₂ via photosynthesis. However, the engineering of strains is hampered by limited understanding of photosynthesis under diverse environmental conditions such as high-light and low-temperature stresses. Herein, we decipher the transcriptomic and translatomic responses of the photosynthetic efficiency to stress conditions using the integrative analysis of multiomic data generated by RNA-seq and ribosome profiling, respectively. Through the generated massive data, along with the guide of the genome-wide transcription unit architecture constructed by transcription start sites and transcript 3′-end positions, we identified the factors affecting photosynthesis at transcription, posttranscription, and translation levels. Importantly, the high-light stress induces photodamage responses, and the low-temperature stress cripples the translation efficiency of photosynthesis-associated genes. The resulting insights provide pivotal information for future cyanobacterial cell factories powered by the engineering toward robust photosynthesis ability.

Current perspectives on integrated approaches to enhance lipid accumulation in microalgae

In recent years, research initiatives on renewable bioenergy or biofuels have been gaining momentum, not only due to fast depletion of finite reserves of fossil fuels but also because of the associated concerns for the environment and future energy security. In the last few decades, interest is growing concerning microalgae as the third-generation biofuel feedstock. The CO₂ fixation ability and conversion of it into value-added compounds, devoid of challenging food and feed crops, make these photosynthetic microorganisms an optimistic producer of biofuel from an environmental point of view. Microalgal-derived fuels are currently being considered as clean, renewable, and promising sustainable biofuel. Therefore, most research targets to obtain strains with the highest lipid productivity and a high growth rate at the lowest cultivation costs. Different methods and strategies to attain higher biomass and lipid accumulation in microalgae have been extensively reported in the previous research, but there are fewer inclusive reports that summarize the conventional methods with the modern techniques for lipid enhancement and biodiesel production from microalgae. Therefore, the current review focuses on the latest techniques and advances in different cultivation conditions, the effect of different abiotic and heavy metal stress, and the role of nanoparticles (NPs) in the stimulation of lipid accumulation in microalgae. Techniques such as genetic engineering, where particular genes associated with lipid metabolism, are modified to boost lipid synthesis within the microalgae, the contribution of "Omics" in metabolic pathway studies. Further, the contribution of CRISPR/Cas9 system technique to the production of microalgae biofuel is also briefly described.

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.

Integrated metabonomic-proteomic analysis reveals the effect of glucose stress on metabolic adaptation of Lactococcus lactis ssp. lactis CICC23200

A combined proteomic and metabonomic approach was used to investigate the metabolism of Lactococcus lactis ssp. lactis subjected to glucose stress treatment. A proteomic method was used to determine 1,427 altered proteins, including 278 proteins with increased expression and 255 proteins with decreased expression. A metabonomic approach was adopted to identify 98 altered metabolites, including 62 metabolites with increased expression and 26 metabolites with decreased expression. The integrated analysis indicated that the RNA and DNA mismatch repair process and energy metabolism were enhanced in response to high-glucose stress in L. lactis. Lactococcus lactis responded to glucose stress by up-regulating oxidoreductase activity, which acted on glycosyl bonds, hydrolase activity, and organic acid transmembrane transporter activity. This led to an improvement in the metabolic flux from glucose to pyruvate, lactate, acetate, and maltose. Down-regulation of amino acid transmembrane transporter, aminoacyl-transfer RNA ligase, hydroxymethyl-, formyl-, and related transferase activities resulted in a decrease in the nitrogen metabolism-associated metabolic pathway, which might be related to inhibition of the production of biogenic amines. Overall, we highlight the response of metabolism to glucose stress and provide potential possibilities for the reduced formation of biogenic amines in improved level of sugar in the dairy fermentation industry. Moreover, according to the demand for industrial production, sugar concentration in fermented foods should be higher, or lower, than a set value that is dependent on bacterial strain and biogenic amine yield.

Integration of Cross Species RNA-seq Meta-Analysis and Machine-Learning Models Identifies the Most Important Salt Stress-Responsive Pathways in Microalga Dunaliella

Photosynthetic microalgae are potentially yielding sources of different high-value secondary metabolites. Salinity is a complex stress that influences various metabolite-related pathways in microalgae. To obtain a clear view of the underlying metabolic pathways and resolve contradictory information concerning the transcriptional regulation of Dunaliella species in salt stress conditions, RNA-seq meta-analysis along with systems levels analysis was conducted. A p-value combination technique with Fisher method was used for cross species meta-analysis on the transcriptomes of two Dunaliella salina and Dunaliellatertiolecta species. The potential functional impacts of core meta-genes were surveyed based on gene ontology and network analysis. In the current study, the integration of supervised machine-learning algorithms with RNA-seq meta-analysis was performed. The analysis shows that the lipid and nitrogen metabolism, structural proteins of photosynthesis apparatus, chaperone-mediated autophagy, and ROS-related genes are the keys and core elements of the Dunaliella salt stress response system. Cross-talk between Ca²⁺ signal transduction, lipid accumulation, and ROS signaling network in salt stress conditions are also proposed. Our novel approach opens new avenues for better understanding of microalgae stress response mechanisms and for selection of candidate gene targets for metabolite production in microalgae.

Can Omics Approaches Improve Microalgal Biofuels under Abiotic Stress?

Microalgae hold the promise of an inexpensive and sustainable source of biofuels. The existing microalgal cultivation technologies need significant improvement to outcompete other biofuel sources such as terrestrial plants. Application of 'algomics' approaches under different abiotic stress conditions could be an effective strategy for optimization of microalgal growth and production of high-quality biofuels. In this review, we discuss the roles of omics in understanding genome structure and biocomponents metabolism in various microalgal species to optimize sustainable biofuel production. Application of individual and integrated omics revealed that genes and metabolic pathways of microalgae have been altered under multiple stress conditions, resulting in an increase in biocomponents, providing a research platform for expansion of genetic engineering studies in microalgal strains.

Evaluation of changes in Microcystis aeruginosa growth and microcystin production by urea via transcriptomic surveys

The freshwater cyanobacteria, Microcystis aeruginosa (M. aeruginosa), is well known to produce microcystins (MCs) and induce the formation of harmful algal blooms (HABs) in aquatic environments, but the effects that urea fertilizer has on cyanobacterial growth and toxin production from a molecular biology perspective remain poorly understood. We evaluated changes in the growth and toxicity of M. aeruginosa cultured under different conditions of nitrogen (N) starvation (NN), low nitrogen (LN), and high nitrogen (HN). Cell density and chlorophyll-a concentrations decreased in cyanobacteria exposed to N starvation and increased following the addition of urea, whereas MCs content increased to a peak and then decreased after urea addition. Transcriptomic analysis confirmed that most genes encoding MCs and genes involved in N metabolic pathways were upregulated under N starvation and LN conditions, whereas these genes were downregulated under HN conditions. Our results offer important insights into the exploring N in controlling the formation of HABs and toxin production based on both physiological and molecular response.

Sequestration of carbon dioxide and production of biomolecules using cyanobacteria

A cyanobacterial strain, Synechococcus sp. NIT18, has been applied to sequester CO₂ using sodium carbonate as inorganic carbon source due to its efficiency of CO₂ bioconversion and high biomass production. The biomass obtained is used for the extraction of biomolecules - protein, carbohydrate and lipid. The main objective of the study is to maximize the biomass and biomolecules production with CO₂ sequestration using cyanobacterial strain cultivated under different concentrations of CO₂ (5-20%), pH (7-11) and inoculum size (5-12.5%) within a statistical framework. Maximum sequestration of CO₂ and maximum productivities of protein, carbohydrate and lipid are 71.02%, 4.9 mg/L/day, 6.7 mg/L/day and 1.6 mg/L/day respectively, at initial CO₂ concentration: 10%, pH: 9 and inoculum size: 12.5%. Since flue gas contains 10-15% CO₂ and the present strain is able to sequester CO₂ in this range, the strain could be considered as a useful tool for CO₂ mitigation for greener world.

Label-free non-invasive quantitative measurement of lipid contents in individual microalgal cells using refractive index tomography

Microalgae are promising candidates for biofuel production due to their high lipid content. To facilitate utilization of the microalgae for biofuel, rapid quantification of the lipid contents in microalgae is necessary. However, conventional methods based on the chemical extraction of lipids require a time-consuming destructive extraction process. Here, we demonstrate label-free, non-invasive, rapid quantification of the lipid contents in individual micro-algal cells measuring the three-dimensional refractive index tomograms. We measure three-dimensional refractive index distributions within Nannochloropsis oculata cells and find that lipid droplets are identifiable in tomograms by their high refractive index. In addition, we alter N. oculata under nitrogen deficiency by measuring the volume, lipid weight, and dry cell weight of individual cells. Characterization of individual cells allows correlative analysis between the lipid content and size of individual cells.

Leveraging algal omics to reveal potential targets for augmenting TAG accumulation

Ongoing global efforts to commercialize microalgal biofuels have expedited the use of multi-omics techniques to gain insights into lipid biosynthetic pathways. Functional genomics analyses have recently been employed to complement existing sequence-level omics studies, shedding light on the dynamics of lipid synthesis and its interplay with other cellular metabolic pathways, thus revealing possible targets for metabolic engineering. Here, we review the current status of algal omics studies to reveal potential targets to augment TAG accumulation in various microalgae. This review specifically aims to examine and catalog systems level data related to stress-induced TAG accumulation in oleaginous microalgae and inform future metabolic engineering strategies to develop strains with enhanced bioproductivity, which could pave a path for sustainable green energy.

Molecular characterization of CO2 sequestration and assimilation in microalgae and its biotechnological applications

Microalgae are renewable feedstock for sustainable biofuel production, cell factory for valuable chemicals and promising in alleviation of greenhouse gas CO₂. However, the carbon assimilation capacity is still the bottleneck for higher productivity. Molecular characterization of CO₂ sequestration and assimilation in microalgae has advanced in the past few years and are reviewed here. In some cyanobacteria, genes for 2-oxoglytarate dehydrogenase was replaced by four alternative mechanisms to fulfill TCA cycle. In green algae Coccomyxa subellipsoidea C-169, alternative carbon assimilation pathway was upregulated under high CO₂ conditions. These advances thus provide new insights and new targets for accelerating CO₂ sequestration rate and enhancing bioproduct synthesis in microalgae. When integrated with conventional parameter optimization, molecular approach for microalgae modification targeting at different levels is promising in generating value-added chemicals from green algae and cyanobacteria efficiently in the near future.

Triacylglycerol is produced from starch and polar lipids in the green alga Dunaliella tertiolecta

The halotolerant green alga Dunaliella tertiolecta accumulates starch and triacylglycerol (TAG) amounting to 70% and 10-15% of total cellular carbon, respectively, when exposed to nitrogen (N) deprivation. The purpose of this study was to clarify the inter-relationships between the biosynthesis of TAG, starch, and polar lipids (PLs) in this alga. Pulse labeling with [14C]bicarbonate was utilized to label starch and [14C]palmitic acid (PlA) to label lipids. Transfer of 14C into TAG was measured and used to calculate rates of synthesis. About two-thirds of the carbon in TAG originates from starch, and one-third is made de novo by direct CO2 assimilation. The level made from degradation of pre-formed PLs is estimated to be very small. Most of the de novo synthesis involves fatty acid transfer through PLs made during the first day of N deprivation. The results suggest that starch made by photosynthetic carbon assimilation at the early stages of N deprivation is utilized for synthesis of TAG. Trans-acylation from PLs is the second major contributor to TAG biosynthesis. The utilization of starch for TAG biosynthesis may have biotechnological applications to optimize TAG biosynthesis in algae.

Elevated acetyl-CoA by amino acid recycling fuels microalgal neutral lipid accumulation in exponential growth phase for biofuel production

Microalgal neutral lipids [mainly in the form of triacylglycerols (TAGs)], feasible substrates for biofuel, are typically accumulated during the stationary growth phase. To make microalgal biofuels economically competitive with fossil fuels, generating strains that trigger TAG accumulation from the exponential growth phase is a promising biological approach. The regulatory mechanisms to trigger TAG accumulation from the exponential growth phase (TAEP) are important to be uncovered for advancing economic feasibility. Through the inhibition of pyruvate dehydrogenase kinase by sodium dichloroacetate, acetyl-CoA level increased, resulting in TAEP in microalga Dunaliella tertiolecta. We further reported refilling of acetyl-CoA pool through branched-chain amino acid catabolism contributed to an overall sixfold TAEP with marginal compromise (4%) on growth in a TAG-rich D. tertiolecta mutant from targeted screening. Herein, a three-step α loop-integrated metabolic model is introduced to shed lights on the neutral lipid regulatory mechanism. This article provides novel approaches to compress lipid production phase and heightens lipid productivity and photosynthetic carbon capture via enhancing acetyl-CoA level, which would optimize renewable microalgal biofuel to fulfil the demanding fuel market.

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

Background

RNA-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.

Results

Dunaliella 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.

Conclusions

The 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.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1551-x) contains supplementary material, which is available to authorized users.

Genome-wide transcriptome analysis revealed organelle specific responses to temperature variations in algae

Temperature is a critical environmental factor that affects microalgal growth. However, microalgal coping mechanisms for temperature variations are unclear. Here, we determined changes in transcriptome, total carbohydrate, total fatty acid methyl ester, and fatty acid composition of Tetraselmis sp. KCTC12432BP, a strain with a broad temperature tolerance range, to elucidate the tolerance mechanisms in response to large temperature variations. Owing to unavailability of genome sequence information, de novo transcriptome assembly coupled with BLAST analysis was performed using strand specific RNA-seq data. This resulted in 26,245 protein-coding transcripts, of which 83.7% could be annotated to putative functions. We identified more than 681 genes differentially expressed, suggesting an organelle-specific response to temperature variation. Among these, the genes related to the photosynthetic electron transfer chain, which are localized in the plastid thylakoid membrane, were upregulated at low temperature. However, the transcripts related to the electron transport chain and biosynthesis of phosphatidylethanolamine localized in mitochondria were upregulated at high temperature. These results show that the low energy uptake by repressed photosynthesis under low and high temperature conditions is compensated by different mechanisms, including photosystem I and mitochondrial oxidative phosphorylation, respectively. This study illustrates that microalgae tolerate different temperature conditions through organelle specific mechanisms.

Nitrogen-induced metabolic changes and molecular determinants of carbon allocation in Dunaliella tertiolecta

Certain species of microalgae are natural accumulators of lipids, while others are more inclined to store starch. However, what governs the preference to store lipids or starch is not well understood. In this study, the microalga Dunaliella tertiolecta was used as a model to study the global gene expression profile regulating starch accumulation in microalgae. D. tertiolecta, when depleted of nitrogen, produced only 1% of dry cell weight (DCW) in neutral lipids, while starch was rapidly accumulated up to 46% DCW. The increased in starch content was accompanied by a coordinated overexpression of genes shunting carbon towards starch synthesis, a response not seen in the oleaginous microalgae Nannochloropsis oceanica, Chlamydomonas reinhardtii or Chlorella vulgaris. Genes in the central carbon metabolism pathways, particularly those of the tricarboxylic acid cycle, were also simultaneously upregulated, indicating a robust interchange of carbon skeletons for anabolic and catabolic processes. In contrast, fatty acid and triacylglycerol synthesis genes were downregulated or unchanged, suggesting that lipids are not a preferred form of storage in these cells. This study reveals the transcriptomic influence behind storage reserve allocation in D. tertiolecta and provides valuable insights into the possible manipulation of genes for engineering microorganisms to synthesize products of interest.

Transcriptome Analysis and Ultrastructure Observation Reveal that Hawthorn Fruit Softening Is due to Cellulose/Hemicellulose Degradation

Softening, a common phenomenon in many fruits, is a well coordinated and genetically determined process. However, the process of flesh softening during ripening has rarely been described in hawthorn. In this study, we found that 'Ruanrou Shanlihong 3 Hao' fruits became softer during ripening, whereas 'Qiu JinXing' fruits remained hard. At late developmental stages, the firmness of 'Ruanrou Shanlihong 3 Hao' fruits rapidly declined, and that of 'Qiu JinXing' fruits remained essentially unchanged. According to transmission electron microscopy, the middle lamella of 'Qiu JinXing' and 'Ruanrou Shanlihong 3 Hao' fruit flesh was largely degraded as the fruits matured. Microfilaments in 'Qiu JinXing' flesh were arranged close together and were deep in color, whereas those in 'Ruanrou Shanlihong 3 Hao' fruit flesh were arranged loosely, partially degraded and light in color. RNA-Seq analysis yielded approximately 46.72 Gb of clean data and 72,837 unigenes. Galactose metabolism and pentose and glucuronate interconversions are involved in cell wall metabolism, play an important role in hawthorn texture. We identified 85 unigenes related to the cell wall between hard- and soft-fleshed hawthorn fruits. Based on data analysis and real-time PCR, we suggest that β-GAL and PE4 have important functions in early fruit softening. The genes Ffase, Gns,α-GAL, PE63, XTH, and CWP, which are involved in cell wall degradation, are responsible for the different textures of hawthorn fruits. Thus, we hypothesize that the different textures of 'Qiu JinXing' and 'Ruanrou Shanlihong 3 Hao' fruits at maturity mainly result from cellulose/hemicelluloses degradation rather than from lamella degradation. Overall, we propose that different types of hydrolytic enzymes in cells interact to degrade the cell wall, resulting in ultramicroscopic Structure changes in the cell wall and, consequently, fruit softening. These results provide fundamental insight regarding the mechanisms by which hawthorn fruits acquire different textures and also lay a solid foundation for further research.

Rational Protein Engineering Guided by Deep Mutational Scanning

Sequence-function relationship in a protein is commonly determined by the three-dimensional protein structure followed by various biochemical experiments. However, with the explosive increase in the number of genome sequences, facilitated by recent advances in sequencing technology, the gap between protein sequences available and three-dimensional structures is rapidly widening. A recently developed method termed deep mutational scanning explores the functional phenotype of thousands of mutants via massive sequencing. Coupled with a highly efficient screening system, this approach assesses the phenotypic changes made by the substitution of each amino acid sequence that constitutes a protein. Such an informational resource provides the functional role of each amino acid sequence, thereby providing sufficient rationale for selecting target residues for protein engineering. Here, we discuss the current applications of deep mutational scanning and consider experimental design.