Identification of regulatory network hubs that control lipid metabolism in Chlamydomonas reinhardtii

Advancements of astaxanthin production in Haematococcus pluvialis: Update insight and way forward

The global market demand for natural astaxanthin (AXT) is growing rapidly owing to its potential human health benefits and diverse industry applications, driven by its safety, unique structure, and special function. Currently, the alga Haematococcus pluvialis (alternative name H. lacustris) has been considered as one of the best large-scale producers of natural AXT. However, the industry's further development faces two main challenges: the limited cultivation areas due to light-dependent AXT accumulation and the low AXT yield coupled with high production costs resulting from complex, time-consuming upstream biomass culture and downstream AXT extraction processes. Therefore, it is urgently to develop novel strategies to improve the AXT production in H. pluvialis to meet industrial demands, which makes its commercialization cost-effective. Although several strategies related to screening excellent target strains, optimizing culture condition for high biomass yield, elucidating the AXT biosynthetic pathway, and exploiting effective inducers for high AXT content have been applied to enhance the AXT production in H. pluvialis, there are still some unsolved and easily ignored perspectives. In this review, firstly, we summarize the structure and function of natural AXT focus on those from the algal H. pluvialis. Secondly, the latest findings regarding the AXT biosynthetic pathway including spatiotemporal specificity, transport, esterification, and storage are updated. Thirdly, we systematically assess enhancement strategies on AXT yield. Fourthly, the regulation mechanisms of AXT accumulation under various stresses are discussed. Finally, the integrated and systematic solutions for improving AXT production are proposed. This review not only fills the existing gap about the AXT accumulation, but also points the way forward for AXT production in H. pluvialis.

Ameliorating microalgal OMEGA production using omics platforms

Over the past decade, the focus on omega (ω)-3 fatty acids from microalgae has intensified due to their diverse health benefits. Bioprocess optimization has notably increased ω-3 fatty acid yields, yet understanding of the genetic architecture and metabolic pathways of high-yielding strains remains limited. Leveraging genomics, transcriptomics, proteomics, and metabolomics tools can provide vital system-level insights into native ω-3 fatty acid-producing microalgae, further boosting production. In this review, we explore 'omics' studies uncovering alternative pathways for ω-3 fatty acid synthesis and genome-wide regulation in response to cultivation parameters. We also emphasize potential targets to fine-tune in order to enhance yield. Despite progress, an integrated omics platform is essential to overcome current bottlenecks in optimizing the process for ω-3 fatty acid production from microalgae, advancing this crucial field.

Engineering Fatty Acid Biosynthesis in Microalgae: Recent Progress and Perspectives

Microalgal lipids hold significant potential for the production of biodiesel and dietary supplements. To enhance their cost-effectiveness and commercial competitiveness, it is imperative to improve microalgal lipid productivity. Metabolic engineering that targets the key enzymes of the fatty acid synthesis pathway, along with transcription factor engineering, are effective strategies for improving lipid productivity in microalgae. This review provides a summary of the advancements made in the past 5 years in engineering the fatty acid biosynthetic pathway in eukaryotic microalgae. Furthermore, this review offers insights into transcriptional regulatory mechanisms and transcription factor engineering aimed at enhancing lipid production in eukaryotic microalgae. Finally, the review discusses the challenges and future perspectives associated with utilizing microalgae for the efficient production of lipids.

Deciphering the regulatory networks involved in mild and severe salt stress responses in the roots of wild grapevine Vitis vinifera spp. sylvestris

Transcriptional regulatory networks are pivotal components of plant's response to salt stress. However, plant adaptation strategies varied as a function of stress intensity, which is mainly modulated by climate change. Here, we determined the gene regulatory networks based on transcription factor (TF) TF_gene co-expression, using two transcriptomic data sets generated from the salt-tolerant "Tebaba" roots either treated with 50 mM NaCl (mild stress) or 150 mM NaCl (severe stress). The analysis of these regulatory networks identified specific TFs as key regulatory hubs as evidenced by their multiple interactions with different target genes related to stress response. Indeed, under mild stress, NAC and bHLH TFs were identified as central hubs regulating nitrogen storage process. Moreover, HSF TFs were revealed as a regulatory hub regulating various aspects of cellular metabolism including flavonoid biosynthesis, protein processing, phenylpropanoid metabolism, galactose metabolism, and heat shock proteins. These processes are essentially linked to short-term acclimatization under mild salt stress. This was further consolidated by the protein-protein interaction (PPI) network analysis showing structural and plant growth adjustment. Conversely, under severe salt stress, dramatic metabolic changes were observed leading to novel TF members including MYB family as regulatory hubs controlling isoflavonoid biosynthesis, oxidative stress response, abscisic acid signaling pathway, and proteolysis. The PPI network analysis also revealed deeper stress defense changes aiming to restore plant metabolic homeostasis when facing severe salt stress. Overall, both the gene co-expression and PPI network provided valuable insights on key transcription factor hubs that can be employed as candidates for future genetic crop engineering programs.

Harnessing genetic engineering to drive economic bioproduct production in algae

Our reliance on agriculture for sustenance, healthcare, and resources has been essential since the dawn of civilization. However, traditional agricultural practices are no longer adequate to meet the demands of a burgeoning population amidst climate-driven agricultural challenges. Microalgae emerge as a beacon of hope, offering a sustainable and renewable source of food, animal feed, and energy. Their rapid growth rates, adaptability to non-arable land and non-potable water, and diverse bioproduct range, encompassing biofuels and nutraceuticals, position them as a cornerstone of future resource management. Furthermore, microalgae's ability to capture carbon aligns with environmental conservation goals. While microalgae offers significant benefits, obstacles in cost-effective biomass production persist, which curtails broader application. This review examines microalgae compared to other host platforms, highlighting current innovative approaches aimed at overcoming existing barriers. These approaches include a range of techniques, from gene editing, synthetic promoters, and mutagenesis to selective breeding and metabolic engineering through transcription factors.

Metabolomic response to high light from pgrl1 and pgr5 mutants of Chlamydomonas reinhardtii

Chlamydomonas (C.) reinhardtii metabolomic changes in cyclic electron flow-dependent mutants are still unknown. Here, we used mass spectrometric analysis to monitor the changes in metabolite levels in wild-type, cyclic electron-deficient mutants pgrl1 and pgr5 grown under high-light stress. A total of 55 metabolites were detected using GC-MS analysis. High-light stress-induced selective anaplerotic amino acids in pgr5. In addition, pgr5 showed enhancement in carbohydrate, polyamine, and polyol metabolism by 2.5-fold under high light. In response to high light, pgr5 triggers an increase in several metabolites involved in regulating osmotic pressure. Among these metabolites are glycerol pathway compounds such as glycerol-3-phosphate and glyceryl-glycoside, which increase significantly by 1.55 and 3.07 times, respectively. In addition, pgr5 also enhanced proline and putrescine levels by 2.6- and 1.36-fold under high light. On the other hand, pgrl1-induced metabolites, such as alanine and serine, are crucial for photorespiration when subjected to high-light stress. We also observed a significant increase in levels of polyols and glycerol by 1.37- and 2.97-fold in pgrl1 under high-light stress. Both correlation network studies and KEGG pathway enrichment analysis revealed that metabolites related to several biological pathways, such as amino acid, carbohydrate, TCA cycle, and fatty acid metabolism, were positively correlated in pgrl1 and pgr5 under high-light stress conditions. The relative mRNA expression levels of genes related to the TCA cycle, including PDC3, ACH1, OGD2, OGD3, IDH3, and MDH4, were significantly upregulated in pgrl1 and pgr5 under HL. In pgr5, the MDH1 level was significantly increased, while ACS1, ACS3, IDH2, and IDH3 levels were reduced considerably in pgrl1 under high-light stress. The current study demonstrates both pgr5 and prgl1 showed a differential defense response to high-light stress at the primary metabolites and mRNA expression level, which can be added to the existing knowledge to explore molecular regulatory responses of prg5 and pgrl1 to high-light stress.

A phase-separated CO2-fixing pyrenoid proteome determined by TurboID in Chlamydomonas reinhardtii

Phase separation underpins many biologically important cellular events such as RNA metabolism, signaling, and CO2 fixation. However, determining the composition of a phase-separated organelle is often challenging due to its sensitivity to environmental conditions, which limits the application of traditional proteomic techniques like organellar purification or affinity purification mass spectrometry to understand their composition. In Chlamydomonas reinhardtii, Rubisco is condensed into a crucial phase-separated organelle called the pyrenoid that improves photosynthetic performance by supplying Rubisco with elevated concentrations of CO2. Here, we developed a TurboID-based proximity labeling technique in which proximal proteins in Chlamydomonas chloroplasts are labeled by biotin radicals generated from the TurboID-tagged protein. By fusing 2 core pyrenoid components with the TurboID tag, we generated a high-confidence pyrenoid proxiome that contains most known pyrenoid proteins, in addition to new pyrenoid candidates. Fluorescence protein tagging of 7 previously uncharacterized TurboID-identified proteins showed that 6 localized to a range of subpyrenoid regions. The resulting proxiome also suggests new secondary functions for the pyrenoid in RNA-associated processes and redox-sensitive iron-sulfur cluster metabolism. This developed pipeline can be used to investigate a broad range of biological processes in Chlamydomonas, especially at a temporally resolved suborganellar resolution.

From Feasting to Fasting: The Arginine Pathway as a Metabolic Switch in Nitrogen-Deprived Chlamydomonas reinhardtii

The metabolism of the model microalgae Chlamydomonas reinhardtii under nitrogen deprivation is of special interest due to its resulting increment of triacylglycerols (TAGs), that can be applied in biotechnological applications. However, this same condition impairs cell growth, which may limit the microalgae's large applications. Several studies have identified significant physiological and molecular changes that occur during the transition from an abundant to a low or absent nitrogen supply, explaining in detail the differences in the proteome, metabolome and transcriptome of the cells that may be responsible for and responsive to this condition. However, there are still some intriguing questions that reside in the core of the regulation of these cellular responses that make this process even more interesting and complex. In this scenario, we reviewed the main metabolic pathways that are involved in the response, mining and exploring, through a reanalysis of omics data from previously published datasets, the commonalities among the responses and unraveling unexplained or non-explored mechanisms of the possible regulatory aspects of the response. Proteomics, metabolomics and transcriptomics data were reanalysed using a common strategy, and an in silico gene promoter motif analysis was performed. Together, these results identified and suggested a strong association between the metabolism of amino acids, especially arginine, glutamate and ornithine pathways to the production of TAGs, via the de novo synthesis of lipids. Furthermore, our analysis and data mining indicate that signalling cascades orchestrated with the indirect participation of phosphorylation, nitrosylation and peroxidation events may be essential to the process. The amino acid pathways and the amount of arginine and ornithine available in the cells, at least transiently during nitrogen deprivation, may be in the core of the post-transcriptional, metabolic regulation of this complex phenomenon. Their further exploration is important to the discovery of novel advances in the understanding of microalgae lipids' production.

Widening the landscape of transcriptional regulation of green algal photoprotection

Availability of light and CO₂, substrates of microalgae photosynthesis, is frequently far from optimal. Microalgae activate photoprotection under strong light, to prevent oxidative damage, and the CO₂ Concentrating Mechanism (CCM) under low CO₂, to raise intracellular CO₂ levels. The two processes are interconnected; yet, the underlying transcriptional regulators remain largely unknown. Employing a large transcriptomic data compendium of Chlamydomonas reinhardtii's responses to different light and carbon supply, we reconstruct a consensus genome-scale gene regulatory network from complementary inference approaches and use it to elucidate transcriptional regulators of photoprotection. We show that the CCM regulator LCR1 also controls photoprotection, and that QER7, a Squamosa Binding Protein, suppresses photoprotection- and CCM-gene expression under the control of the blue light photoreceptor Phototropin. By demonstrating the existence of regulatory hubs that channel light- and CO₂-mediated signals into a common response, our study provides an accessible resource to dissect gene expression regulation in this microalga.

A conserved MYB transcription factor is involved in regulating lipid metabolic pathways for oil biosynthesis in green algae

Green algae can accumulate high levels of triacylglycerol (TAG), yet knowledge remains fragmented on the regulation of lipid metabolic pathways by transcription factors (TFs). Here, via bioinformatics and in vitro and in vivo analyses, we revealed the roles of a myeloblastosis (MYB) TF in regulating TAG accumulation in green algae. CzMYB1, an R2R3-MYB from Chromochloris zofingiensis, was transcriptionally upregulated upon TAG-inducing conditions and correlated well with many genes involved in the de novo fatty acid synthesis, fatty acid activation and desaturation, membrane lipid turnover, and TAG assembly. Most promoters of these genes were transactivated by CzMYB1 in the yeast one-hybrid assay and contained the binding elements CNGTTA that were recognized by CzMYB1 through the electrophoretic mobility shift assay. CrMYB1, a close homologue of CzMYB1 from Chlamydomonas reinhardtii that recognized similar elements for binding, also transcriptionally correlated with many lipid metabolic genes. Insertional disruption of CrMYB1 severely suppressed the transcriptional expression of CrMYB1, as well as of key lipogenic genes, and impaired TAG level considerably under stress conditions. Our results reveal that this MYB, conserved in green algae, is involved in regulating global lipid metabolic pathways for TAG biosynthesis and accumulation.

Transcriptional regulation of triacylglycerol accumulation in plants under environmental stress conditions

Triacylglycerol (TAG), a major energy reserve in lipid form, accumulates mainly in seeds. Although TAG concentrations are usually low in vegetative tissues because of the repression of seed maturation programs, these programs are derepressed upon the exposure of vegetative tissues to environmental stresses. Metabolic reprogramming of TAG accumulation is driven primarily by transcriptional regulation. A substantial proportion of transcription factors regulating seed TAG biosynthesis also participates in stress-induced TAG accumulation in vegetative tissues. TAG accumulation leads to the formation of lipid droplets and plastoglobules, which play important roles in plant tolerance to environmental stresses. Toxic lipid intermediates generated from environmental-stress-induced lipid membrane degradation are captured by TAG-containing lipid droplets and plastoglobules. This review summarizes recent advances in the transcriptional control of metabolic reprogramming underlying stress-induced TAG accumulation, and provides biological insight into the plant adaptive strategy, linking TAG biosynthesis with plant survival.

RegEnrich gene regulator enrichment analysis reveals a key role of the ETS transcription factor family in interferon signaling

Changes in a few key transcriptional regulators can lead to different biological states. Extracting the key gene regulators governing a biological state allows us to gain mechanistic insights. Most current tools perform pathway/GO enrichment analysis to identify key genes and regulators but tend to overlook the gene/protein regulatory interactions. Here we present RegEnrich, an open-source Bioconductor R package, which combines differential expression analysis, data-driven gene regulatory network inference, enrichment analysis, and gene regulator ranking to identify key regulators using gene/protein expression profiling data. By benchmarking using multiple gene expression datasets of gene silencing studies, we found that RegEnrich using the GSEA method to rank the regulators performed the best. Further, RegEnrich was applied to 21 publicly available datasets on in vitro interferon-stimulation of different cell types. Collectively, RegEnrich can accurately identify key gene regulators from the cells under different biological states, which can be valuable in mechanistically studying cell differentiation, cell response to drug stimulation, disease development, and ultimately drug development.

A review on the progress, challenges and prospects in commercializing microalgal fucoxanthin

Fucoxanthin, the most abundant but nearly untapped carotenoid resource, is in the spotlight in the last decade from various perspectives due to a wide range of bioactivities and healthy benefits. The exploitation of fucoxanthin for nutraceutical and pharmaceutical purposes encompasses enormous scientific and economic potentials. Traditional production of fucoxanthin from brown algae (macroalgae) is constrained by limited yield and prohibitively high cost. Microalgae, as the most diverse photoautotrophs, hold the promises as sustainable sources and ideal cell factories for commercial fucoxanthin production, owing to their rich fucoxanthin content and excellent biomass productivity. In this work, the recent progress in upstream (microalgae selection, optimization of culture conditions, trophic modes, cultivation strategies and biosynthesis pathway) as well as downstream processes (extraction) of fucoxanthin production has been comprehensively and critically reviewed. The major bottlenecks, such as screening of fucoxanthin-producers, conflict between biomass and fucoxanthin accumulation under high light condition, unclear steps in biosynthesis pathway and limited evaluation of outdoor scale-up cultivation and extraction, have been pinpointed. Most importantly, the applications of emerging and conventional techniques facilitating commercialization of microalgal fucoxanthin are highlighted. The reviewed and evaluated include breeding and high-throughput screening methods of elite strains; flashing light effect inducing concurrent biomass and fucoxanthin accumulation; fucoxanthin biosynthesis and the regulatory mechanisms associating with its accumulation elucidated with the development of genetic engineering and omics techniques; and photobioreactors, harvesting and extraction techniques suitable for scaling up fucoxanthin production. In conclusion, the prospects of microalgal fucoxanthin commercialization can be expected with the joint development of fundamental phycology and biotechnology.

Granger-causal testing for irregularly sampled time series with application to nitrogen signalling in Arabidopsis

MOTIVATION

Identification of system-wide causal relationships can contribute to our understanding of long-distance, intercellular signalling in biological organisms. Dynamic transcriptome analysis holds great potential to uncover coordinated biological processes between organs. However, many existing dynamic transcriptome studies are characterized by sparse and often unevenly spaced time points that make the identification of causal relationships across organs analytically challenging. Application of existing statistical models, designed for regular time series with abundant time points, to sparse data may fail to reveal biologically significant, causal relationships. With increasing research interest in biological time series data, there is a need for new statistical methods that are able to determine causality within and between time series data sets. Here, a statistical framework was developed to identify (Granger) causal gene-gene relationships of unevenly spaced, multivariate time series data from two different tissues of Arabidopsis thaliana in response to a nitrogen signal.

RESULTS

This work delivers a statistical approach for modelling irregularly sampled bivariate signals which embeds functions from the domain of engineering that allow to adapt the model's dependence structure to the specific sampling time. Using maximum-likelihood to estimate the parameters of this model for each bivariate time series, it is then possible to use bootstrap procedures for small samples (or asymptotics for large samples) in order to test for Granger-Causality. When applied to the A.thaliana data, the proposed approach produced 3078 significant interactions, in which 2012 interactions have root causal genes and 1066 interactions have shoot causal genes. Many of the predicted causal and target genes are known players in local and long-distance nitrogen signalling, including genes encoding transcription factors, hormones and signalling peptides. Of the 1007 total causal genes (either organ), 384 are either known or predicted mobile transcripts, suggesting that the identified causal genes may be directly involved in long-distance nitrogen signalling through intercellular interactions. The model predictions and subsequent network analysis identified nitrogen-responsive genes that can be further tested for their specific roles in long-distance nitrogen signalling.

AVAILABILITY AND IMPLEMENTATION

The method was developed with the R statistical software and is made available through the R package 'irg' hosted on the GitHub repository https://github.com/SMAC-Group/irg where also a running example vignette can be found (https://smac-group.github.io/irg/articles/vignette.html). A few signals from the original data set are made available in the package as an example to apply the method and the complete A.thaliana data can be found at: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE97500.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Transcription Factor-Based Genetic Engineering in Microalgae

Sequence-specific DNA-binding transcription factors (TFs) are key components of gene regulatory networks. Advances in high-throughput sequencing have facilitated the rapid acquisition of whole genome assembly and TF repertoires in microalgal species. In this review, we summarize recent advances in gene discovery and functional analyses, especially for transcription factors in microalgal species. Specifically, we provide examples of the genome-scale identification of transcription factors in genome-sequenced microalgal species and showcase their application in the discovery of regulators involved in various cellular functions. Herein, we highlight TF-based genetic engineering as a promising framework for designing microalgal strains for microalgal-based bioproduction.

Comprehensive transcriptome analysis of hypothalamus reveals genes associated with disorders of sex development in pigs

XX sex reversal, also called XX disorders of sex development (XX-DSD), is a condition affecting the development of the gonads or genitalia, and is relatively common in pigs. However, its genetic etiology and transcriptional regulation mechanism in the hypothalamic-pituitary-gonadal axis (HPGA) remain mostly unknown. XX-DSD (SRY-negative) pigs and normal sows were selected by external genitalia observation. The hypothalamus, which is the integrated center of the HPGA was sampled for whole-transcriptome RNA-seq. The role of DEmiRNA was validated by its overexpression and knockdown in vitro. A total of 1,258 lncRNAs, 1,086 mRNAs, and 61 microRNAs differentially expressed in XX-DSD pigs compared with normal female pigs. Genes in the hormone biosynthesis and secretion pathway significantly up-regulated, and the up-regulation of GNRH1, KISS1 and AVP may associate with the abnormal secretion of GnRH. We also predicted the lncRNA-miRNA-mRNA co-expression triplets and constructed three competing endogenous RNA (ceRNA) potentially associated with XX-DSD. Functional enrichment studies suggested that TCONS_00340886, TCONS_00000204 and miR-181a related to GnRH secretion. Further, miR-181a inhibitor up-regulated GNRH1, PAK6, and CAMK4 in the GT1-7 cells. Conversely, transfection of miR-181a mimics obtained the opposite trends. The expression levels of FSHR, LHR, ESR1 and ESR2 were significantly higher in XX-DSD gondas than those in normal sows. Taken together, we proposed that the balance of endocrine had broken in XX-DSD pigs. The current study is the first to examine the transcriptomic profile in the hypothalamus of XX-DSD pigs. It provides new insight into coding and non-coding RNAs that may be associated with DSD in pigs.

Large fluxes of fatty acids from membranes to triacylglycerol and back during N-deprivation and recovery in Chlamydomonas

Microalgae accumulate triacylglycerol (TAG) during nutrient deprivation and break it down after nutrient resupply, and these processes involve dramatic shifts in cellular carbon allocation. Due to the importance of algae in the global carbon cycle, and the potential of algal lipids as feedstock for chemical and fuel production, these processes are of both ecophysiological and biotechnological importance. However, the metabolism of TAG is not well understood, particularly the contributions of fatty acids (FAs) from different membrane lipids to TAG accumulation and the fate of TAG FAs during degradation. Here, we used isotopic labeling time course experiments on Chlamydomonas reinhardtii to track FA synthesis and transfer between lipid pools during nitrogen (N)-deprivation and resupply. When cells were labeled before N-deprivation, total levels of label in cellular FAs were unchanged during subsequent N-deprivation and later resupply, despite large fluxes into and out of TAG and membrane lipid pools. Detailed analyses of FA levels and labeling revealed that about one-third of acyl chains accumulating in TAG during N-deprivation derive from preexisting membrane lipids, and in total, at least 45% of TAG FAs passed through membrane lipids at one point. Notably, most acyl chains in membrane lipids during recovery after N-resupply come from TAG. Fluxes of polyunsaturated FAs from plastidic membranes into TAG during N-deprivation were particularly noteworthy. These findings demonstrate a high degree of integration of TAG and membrane lipid metabolism and highlight a role for TAG in storage and supply of membrane lipid components.

HB-PLS: A statistical method for identifying biological process or pathway regulators by integrating Huber loss and Berhu penalty with partial least squares regression

Gene expression data features high dimensionality, multicollinearity, and non-Gaussian distribution noise, posing hurdles for identification of true regulatory genes controlling a biological process or pathway. In this study, we integrated the Huber loss function and the Berhu penalty (HB) into partial least squares (PLS) framework to deal with the high dimension and multicollinearity property of gene expression data, and developed a new method called HB-PLS regression to model the relationships between regulatory genes and pathway genes. To solve the Huber-Berhu optimization problem, an accelerated proximal gradient descent algorithm with at least 10 times faster than the general convex optimization solver (CVX), was developed. Application of HB-PLS to recognize pathway regulators of lignin biosynthesis and photosynthesis in Arabidopsis thaliana led to the identification of many known positive pathway regulators that had previously been experimentally validated. As compared to sparse partial least squares (SPLS) regression, an efficient method for variable selection and dimension reduction in handling multicollinearity, HB-PLS has higher efficacy in identifying more positive known regulators, a much higher but slightly less sensitivity/(1-specificity) in ranking the true positive known regulators to the top of the output regulatory gene lists for the two aforementioned pathways. In addition, each method could identify some unique regulators that cannot be identified by the other methods. Our results showed that the overall performance of HB-PLS slightly exceeds that of SPLS but both methods are instrumental for identifying real pathway regulators from high-throughput gene expression data, suggesting that integration of statistics, machine leaning and convex optimization can result in a method with high efficacy and is worth further exploration.

Granger-Causal Testing for Irregularly Sampled Time Series with Application to Nitrogen Signaling in Arabidopsis

Motivation

Identification of system-wide causal relationships can contribute to our understanding of long-distance, intercellular signalling in biological organisms. Dynamic transcriptome analysis holds great potential to uncover coordinated biological processes between organs. However, many existing dynamic transcriptome studies are characterized by sparse and often unevenly spaced time points that make the identification of causal relationships across organs analytically challenging. Application of existing statistical models, designed for regular time series with abundant time points, to sparse data may fail to reveal biologically significant, causal relationships. With increasing research interest in biological time series data, there is a need for new statistical methods that are able to determine causality within and between time series data sets. Here, a statistical framework was developed to identify (Granger) causal gene-gene relationships of unevenly spaced, multivariate time series data from two different tissues of Arabidopsis thaliana in response to a nitrogen signal.

Results

This work delivers a statistical approach for modelling irregularly sampled bivariate signals which embeds functions from the domain of engineering that allow to adapt the model’s dependence structure to the specific sampling time. Using maximum-likelihood to estimate the parameters of this model for each bivariate time series, it is then possible to use bootstrap procedures for small samples (or asymptotics for large samples) in order to test for Granger-Causality. When applied to the A.thaliana data, the proposed approach produced 3078 significant interactions, in which 2012 interactions have root causal genes and 1066 interactions have shoot causal genes. Many of the predicted causal and target genes are known players in local and long-distance nitrogen signalling, including genes encoding transcription factors, hormones and signalling peptides. Of the 1007 total causal genes (either organ), 384 are either known or predicted mobile transcripts, suggesting that the identified causal genes may be directly involved in long-distance nitrogen signalling through intercellular interactions. The model predictions and subsequent network analysis identified nitrogen-responsive genes that can be further tested for their specific roles in long-distance nitrogen signalling.

Availability and implementation

The method was developed with the R statistical software and is made available through the R package ‘irg’ hosted on the GitHub repository https://github.com/SMAC-Group/irg where also a running example vignette can be found (https://smac-group.github.io/irg/articles/vignette.html). A few signals from the original data set are made available in the package as an example to apply the method and the complete A.thaliana data can be found at: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE97500.

Supplementary information

Supplementary data are available at Bioinformatics online.

AP2/ERF and R2R3-MYB family transcription factors: potential associations between temperature stress and lipid metabolism in Auxenochlorella protothecoides

BACKGROUND

Both APETALA2/Ethylene Responsive Factor (AP2/ERF) superfamily and R2R3-MYB family were from one of the largest diverse families of transcription factors (TFs) in plants, and played important roles in plant development and responses to various stresses. However, no systematic analysis of these TFs had been conducted in the green algae A. protothecoides heretofore. Temperature was a critical factor affecting growth and lipid metabolism of A. protothecoides. It also remained largely unknown whether these TFs would respond to temperature stress and be involved in controlling lipid metabolism process.

RESULTS

Hereby, a total of six AP2 TFs, six ERF TFs and six R2R3-MYB TFs were identified and their expression profiles were also analyzed under low-temperature (LT) and high-temperature (HT) stresses. Meanwhile, differential adjustments of lipid pathways were triggered, with enhanced triacylglycerol accumulation. A co-expression network was built between these 18 TFs and 32 lipid-metabolism-related genes, suggesting intrinsic associations between TFs and the regulatory mechanism of lipid metabolism.

CONCLUSIONS

This study represented an important first step towards identifying functions and roles of AP2 superfamily and R2R3-MYB family in lipid adjustments and response to temperature stress. These findings would facilitate the biotechnological development in microalgae-based biofuel production and the better understanding of photosynthetic organisms' adaptive mechanism to temperature stress.

Transcriptional and Morpho-Physiological Responses of Marchantia polymorpha upon Phosphate Starvation

Phosphate (Pi) is a pivotal nutrient that constraints plant development and productivity in natural ecosystems. Land colonization by plants, more than 470 million years ago, evolved adaptive mechanisms to conquer Pi-scarce environments. However, little is known about the molecular basis underlying such adaptations at early branches of plant phylogeny. To shed light on how early divergent plants respond to Pi limitation, we analyzed the morpho-physiological and transcriptional dynamics of Marchantia polymorpha upon Pi starvation. Our phylogenomic analysis highlights some gene networks present since the Chlorophytes and others established in the Streptophytes (e.g., PHR1–SPX1 and STOP1–ALMT1, respectively). At the morpho-physiological level, the response is characterized by the induction of phosphatase activity, media acidification, accumulation of auronidins, reduction of internal Pi concentration, and developmental modifications of rhizoids. The transcriptional response involves the induction of MpPHR1, Pi transporters, lipid turnover enzymes, and MpMYB14, which is an essential transcription factor for auronidins biosynthesis. MpSTOP2 up-regulation correlates with expression changes in genes related to organic acid biosynthesis and transport, suggesting a preference for citrate exudation. An analysis of MpPHR1 binding sequences (P1BS) shows an enrichment of this cis regulatory element in differentially expressed genes. Our study unravels the strategies, at diverse levels of organization, exerted by M. polymorpha to cope with low Pi availability.

Identification and Biotechnical Potential of a Gcn5-Related N-Acetyltransferase Gene in Enhancing Microalgal Biomass and Starch Production

Microalgae are promising feedstocks for starch production, which are precursors for bioenergy and chemicals manufacturing. Though starch biosynthesis has been intensively studied in the green alga Chlamydomonas reinhardtii, regulatory mechanisms governing starch metabolism in this model species have remained largely unknown to date. We proposed that altering triacylglycerol (TAG) biosynthesis may trigger intrinsic regulatory pathways governing starch metabolism. In accordance with the hypothesis, it was observed in this study that overexpression of the plastidial lysophosphatidic acid acyltransferase gene (i.e. LPAAT1) in C. reinhardtii significantly enhanced TAG biosynthesis under nitrogen (N)-replete conditions, whereas the starch biosynthesis was enhanced in turn under N depletion. By the exploitation of transcriptomics analysis, a putative regulatory gene coding Gcn5-related N-acetyltransferase (GNAT19) was identified, which was up-regulated by 11-12 times in the CrLPAAT1 OE lines. Overexpression of the cloned full-length CrGNAT19 cDNA led to significant increase in the starch content of C. reinhardtii cells grown under both N-replete and N-depleted conditions, which was up to 4 times and 26.7% higher than that of the empty vector control, respectively. Moreover, the biomass yield of the CrGNAT19 OE lines reached 1.5 g L^-1 after 2 days under N-depleted conditions, 72% higher than that of the empty vector control (0.87 g L^-1). Overall, the yield of starch increased by 118.5% in CrGNAT19 OE lines compared to that of the control. This study revealed the great biotechnical potentials of an unprecedented GNAT19 gene in enhancing microalgal starch and biomass production.

Identification of circRNA-lncRNA-miRNA-mRNA Competitive Endogenous RNA Network as Novel Prognostic Markers for Acute Myeloid Leukemia

Background: Acute myeloid leukemia (AML) is one of the most common malignant and aggressive hematologic tumors, and its pathogenesis is associated with abnormal post-transcriptional regulation. Unbalanced competitive endogenous RNA (ceRNA) promotes tumorigenesis and progression, and greatly contributes to tumor risk classification and prognosis. However, the comprehensive analysis of the circular RNA (circRNA)-long non-coding RNA (lncRNA)-miRNA-mRNA ceRNA network in the prognosis of AML is still rarely reported. Method: We obtained transcriptome data of AML and normal samples from The Cancer Genome Atlas (TCGA), Genotype-tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases, and identified differentially expressed (DE) mRNAs, lncRNAs, and circRNAs. Then, the targeting relationships among lncRNA-miRNA, circRNA-miRNA, and miRNA-mRNA were predicted, and the survival related hub mRNAs were further screened by univariate and multivariate Cox proportional hazard regression. Finally, the AML prognostic circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network was established. Results: We identified prognostic 6 hub mRNAs (TM6SF1, ZMAT1, MANSC1, PYCARD, SLC38A1, and LRRC4) through Cox regression model, and divided the AML samples into high and low risk groups according to the risk score obtained by multivariate Cox regression. Survival analysis verified that the survival rate of the high-risk group was significantly reduced (p < 0.0001). The prognostic ceRNA network of 6 circRNAs, 32 lncRNAs, 8 miRNAs, and 6 mRNAs was established according to the targeting relationship between 6 hub mRNAs and other RNAs. Conclusion: In this study, ceRNA network jointly participated by circRNAs and lncRNAs was established for the first time. It comprehensively elucidated the post-transcriptional regulatory mechanism of AML, and identified novel AML prognostic biomarkers, which has important guiding significance for the clinical diagnosis, treatment, and further scientific research of AML.

Fixing the Broken Phosphorus Cycle: Wastewater Remediation by Microalgal Polyphosphates

Phosphorus (P), in the form of phosphate derived from either inorganic (Pi) or organic (Po) forms is an essential macronutrient for all life. P undergoes a biogeochemical cycle within the environment, but anthropogenic redistribution through inefficient agricultural practice and inadequate nutrient recovery at wastewater treatment works have resulted in a sustained transfer of P from rock deposits to land and aquatic environments. Our present and near future supply of P is primarily mined from rock P reserves in a limited number of geographical regions. To help ensure that this resource is adequate for humanity's food security, an energy-efficient means of recovering P from waste and recycling it for agriculture is required. This will also help to address excess discharge to water bodies and the resulting eutrophication. Microalgae possess the advantage of polymeric inorganic polyphosphate (PolyP) storage which can potentially operate simultaneously with remediation of waste nitrogen and phosphorus streams and flue gases (CO2, SOx, and NOx). Having high productivity in photoautotrophic, mixotrophic or heterotrophic growth modes, they can be harnessed in wastewater remediation strategies for biofuel production either directly (biodiesel) or in conjunction with anaerobic digestion (biogas) or dark fermentation (biohydrogen). Regulation of algal P uptake, storage, and mobilization is intertwined with the cellular status of other macronutrients (e.g., nitrogen and sulphur) in addition to the manufacture of other storage products (e.g., carbohydrate and lipids) or macromolecules (e.g., cell wall). A greater understanding of controlling factors in this complex interaction is required to facilitate and improve P control, recovery, and reuse from waste streams. The best understood algal genetic model is Chlamydomonas reinhardtii in terms of utility and shared resources. It also displays mixotrophic growth and advantageously, species of this genus are often found growing in wastewater treatment plants. In this review, we focus primarily on the molecular and genetic aspects of PolyP production or turnover and place this knowledge in the context of wastewater remediation and highlight developments and challenges in this field.

Photosynthetic Metabolism and Nitrogen Reshuffling Are Regulated by Reversible Cysteine Thiol Oxidation Following Nitrogen Deprivation in Chlamydomonas

As global temperatures climb to historic highs, the far-reaching effects of climate change have impacted agricultural nutrient availability. This has extended to low latitude oceans, where a deficit in both nitrogen and phosphorus stores has led to dramatic decreases in carbon sequestration in oceanic phytoplankton. Although Chlamydomonas reinhardtii, a freshwater model green alga, has shown drastic systems-level alterations following nitrogen deprivation, the mechanisms through which these alterations are triggered and regulated are not fully understood. This study examined the role of reversible oxidative signaling in the nitrogen stress response of C. reinhardtii. Using oxidized cysteine resin-assisted capture enrichment coupled with label-free quantitative proteomics, 7889 unique oxidized cysteine thiol identifiers were quantified, with 231 significantly changing peptides from 184 proteins following 2 h of nitrogen deprivation. These results demonstrate that the cellular response to nitrogen assimilation, photosynthesis, pigment biosynthesis, and lipid metabolism are regulated by reversible oxidation. An enhanced role of non-damaging oxidative pathways is observed throughout the photosynthetic apparatus that provides a framework for further analysis in phototrophs.

Integration of proteome and transcriptome refines key molecular processes underlying oil production in Nannochloropsis oceanica

BACKGROUND

Under nitrogen deficiency situation, Nannochloropsis spp. accumulate large amounts of lipids in the form of triacylglycerides (TAG). Mechanisms of this process from the perspective of transcriptome and metabolome have been obtained previously, yet proteome analysis is still sparse which hinders the analysis of dynamic adaption to nitrogen deficiency. Here, proteomes for 3 h, 6 h, 12 h, 24 h, 48 h and 10th day of nitrogen deplete (N-) and replete (N+) conditions were obtained and integrated with previous transcriptome data for N. oceanica.

RESULTS

Physiological adaptations to N- not apparent from transcriptome data were unveiled: (a) abundance of proteins related to photosynthesis only slightly decreased in the first 48 h, indicating that photosynthesis is still working efficiently, and protein amounts adjust gradually with reduction in chloroplast size. (b) Most proteins related to the TCA cycle were strongly upregulated after 48 h under N-, suggesting that respiration is enhanced after 48 h and that TCA cycle efflux supports the carbon required for lipid synthesis. (c) Proteins related to lipid accumulation via the Kennedy pathway increased their abundance at 48 h, synchronous with the previously reported diversification of fatty acids after 48 h.

CONCLUSIONS

This study adds a proteome perspective on the major pathways for TAG accumulation in Nannochloropsis spp. Temporal changes of proteome exhibited distinct adaptation phases that are usually delayed relative to transcriptomic responses. Notably, proteome data revealed that photosynthesis and carbon fixation are still ongoing even after 48 h of N-. Moreover, sometimes completely opposite trends in proteome and transcriptome demonstrate the relevance of underexplored post-transcriptional regulation for N- adaptation.

Intrinsic limitations in mainstream methods of identifying network motifs in biology

Background

Network motifs are connectivity structures that occur with significantly higher frequency than chance, and are thought to play important roles in complex biological networks, for example in gene regulation, interactomes, and metabolomes. Network motifs may also become pivotal in the rational design and engineering of complex biological systems underpinning the field of synthetic biology. Distinguishing true motifs from arbitrary substructures, however, remains a challenge.

Results

Here we demonstrate both theoretically and empirically that implicit assumptions present in mainstream methods for motif identification do not necessarily hold, with the ramification that motif studies using these mainstream methods are less able to effectively differentiate between spurious results and events of true statistical significance than is often presented. We show that these difficulties cannot be overcome without revising the methods of statistical analysis used to identify motifs.

Conclusions

Present-day methods for the discovery of network motifs, and, indeed, even the methods for defining what they are, are critically reliant on a set of incorrect assumptions, casting a doubt on the scientific validity of motif-driven discoveries. The implications of these findings are therefore far-reaching across diverse areas of biology.

Systems biology approach identifies functional modules and regulatory hubs related to secondary metabolites accumulation after transition from autotrophic to heterotrophic growth condition in microalgae

Heterotrophic growth mode is among the most promising strategies put forth to overcome the low biomass and secondary metabolites productivity challenge. To shedding light on the underlying molecular mechanisms, transcriptome meta-analysis was integrated with weighted gene co-expression network analysis (WGCNA), connectivity analysis, functional enrichment, and hubs identification. Meta-analysis and Functional enrichment analysis demonstrated that most of the biological processes are up-regulated at heterotrophic growth condition, which leads to change of genetic architectures and phenotypic outcomes. WGNCA analysis of meta-genes also resulted four significant functional modules across logarithmic (LG), transition (TR), and production peak (PR) phases. The expression pattern and connectivity characteristics of the brown module as a non-preserved module vary across LG, TR, and PR phases. Functional analysis identified Carotenoid biosynthesis, Fatty acid metabolism and Methane metabolism as enriched pathways in the non-preserved module. Our integrated approach was applied here, identified some hubs, such as a serine hydroxymethyltransferase (SHMT1), which is the best candidate for development of metabolites accumulating strains in microalgae. Current study provided a new insight into underlying metabolite accumulation mechanisms and opens new avenue for the future applied studies in the microalgae field.

CrABCA2 Facilitates Triacylglycerol Accumulation in Chlamydomonas reinhardtii under Nitrogen Starvation

The microalga Chlamydomonas reinhardtii accumulates triacylglycerols (TAGs) in lipid droplets under stress conditions, such as nitrogen starvation. TAG biosynthesis occurs mainly at the endoplasmic reticulum (ER) and requires fatty acid (FA) substrates supplied from chloroplasts. How FAs are transferred from chloroplast to ER in microalgae was unknown. We previously reported that an Arabidopsis thaliana ATP-binding cassette (ABC) transporter, AtABCA9, facilitates FA transport at the ER during seed development. Here we identified a gene homologous to AtABCA9 in the C. reinhardtii genome, which we named CrABCA2. Under nitrogen deprivation conditions, CrABCA2 expression was upregulated, and the CrABCA2 protein level also increased. CrABCA2 knockdown lines accumulated less TAGs and CrABCA2 overexpression lines accumulated more TAGs than their untransformed parental lines. Transmission electron microscopy showed that CrABCA2 was localized in swollen ER. These results suggest that CrABCA2 transports substrates for TAG biosynthesis to the ER during nitrogen starvation . Our study provides a potential tool for increasing lipid production in microalgae.

Palm seed and fruit lipid composition: phylogenetic and ecological perspectives

BACKGROUND AND AIMS

Palms are vital to worldwide human nutrition, in particular as major sources of vegetable oils. However, our knowledge of seed and fruit lipid diversity in the family Arecaceae is limited. We therefore aimed to explore relationships between seed and fruit lipid content, fatty acid composition in the respective tissues, phylogenetic factors and biogeographical parameters.

METHODS

Oil content and fatty acid composition were characterized in seeds and fruits of 174 and 144 palm species respectively. Distribution, linear regression and multivariate analyses allowed an evaluation of the chemotaxonomic value of these traits and their potential relationship with ecological factors.

KEY RESULTS

A considerable intra-family diversity for lipid traits was revealed. Species with the most lipid-rich seeds belonged to the tribe Cocoseae, while species accumulating oil in the mesocarp occurred in all subfamilies and two-thirds of the tribes studied. Seed and fruit lipid contents were not correlated. Fatty acid composition of mesocarp oil was highly variable within tribes. By contrast, within-tribe diversity for seed lipid traits was low, whereas between-tribe variability was high. Consequently, multivariate analyses of seed lipid traits produced groupings of species belonging to the same tribe. Medium-chain fatty acids predominated in seeds of most palm species, but they were also accumulated in the mesocarp in some cases. Seed unsaturated fatty acid content correlated with temperature at the coldest latitude of natural occurrence.

CONCLUSION

Several previously uncharacterized palms were identified as potential new sources of vegetable oils for comestible or non-food use. Seed lipid traits reflect genetic drift that occurred during the radiation of the family and therefore are highly relevant to palm chemotaxonomy. Our data also suggest that seed unsaturated fatty acids may provide an adaptive advantage in the coldest environments colonized by palms by maintaining storage lipids in liquid form for efficient mobilization during germination.

iTRAQ-Based Proteomic Analysis Reveals Several Strategies to Cope with Drought Stress in Maize Seedlings

Drought stress, especially during the seedling stage, seriously limits the growth of maize and reduces production in the northeast of China. To investigate the molecular mechanisms of drought response in maize seedlings, proteome changes were analyzed. Using an isotopic tagging relative quantitation (iTRAQ) based method, a total of 207 differentially accumulated protein species (DAPS) were identified under drought stress in maize seedlings. The DAPS were classified into ten essential groups and analyzed thoroughly, which involved in signaling, osmotic regulation, protein synthesis and turnover, reactive oxygen species (ROS) scavenging, membrane trafficking, transcription related, cell structure and cell cycle, fatty acid metabolism, carbohydrate and energy metabolism, as well as photosynthesis and photorespiration. The enhancements of ROS scavenging, osmotic regulation, protein turnover, membrane trafficking, and photosynthesis may play important roles in improving drought tolerance of maize seedlings. Besides, the inhibitions of some protein synthesis and slowdown of cell division could reduce the growth rate and avoid excessive water loss, which is possible to be the main reasons for enhancing drought avoidance of maize seedlings. The incongruence between protein and transcript levels was expectedly observed in the process of confirming iTRAQ data by quantitative real-time polymerase chain reaction (qRT-PCR) analysis, which further indicated that the multiplex post-transcriptional regulation and post-translational modification occurred in drought-stressed maize seedlings. Finally, a hypothetical strategy was proposed that maize seedlings coped with drought stress by improving drought tolerance (via. promoting osmotic adjustment and antioxidant capacity) and enhancing drought avoidance (via. reducing water loss). Our study provides valuable insight to mechanisms underlying drought response in maize seedlings.

Identification and characterization of circRNAs as competing endogenous RNAs for miRNA-mRNA in colorectal cancer

Background

Recent studies showed that circRNAs are involved in the biological process of some human cancers. However, little is known about their functions in colorectal cancer (CRC).

Methods

Here we first revealed the expression profiles of circRNAs in the CRC tissues and the adjacent non-tumorous tissues using high-throughput sequencing. The sequence feature, chromosome location, alternative splicing and other characteristics of the circRNAs were also explored. The miRNA and mRNA expression profiles were then obtained by analyzing relevant CRC data retrived from the TCGA database. We obtained and analyzed the competing endogenous RNA (ceRNA) network of the top three pairs of the largest up-regulated and down-regulated circRNAs.

Results

In this study, we obtained 50,410 circRNAs in the CRC tissue and the adjacent non-tumor tissues, of which 33.7% (16,975) were new, and revealed differential changes in circRNA expression during colorectal carcinogenesis. We have identified six potential key circRNAs (circPIEZO1-3, hsa_circ_0067163, hsa_circ_0140188, hsa_circ_0002632, hsa_circ_0001998 and hsa_circ_0023990) associated with CRC, which play important roles in carcinogenesis as ceRNA for regulation of miRNA-mRNA network. In the subsequent KEGG analysis, several CRC-related pathways were found.

Conclusions

Our findings advance the understanding of the pathogenesis of CRC from the perspective of circRNAs and provide some circRNAs as candidate diagnostic biomarkers or potential therapeutic targets.

Plant Networks as Traits and Hypotheses: Moving Beyond Description

Biology relies on the central thesis that the genes in an organism encode molecular mechanisms that combine with stimuli and raw materials from the environment to create a final phenotypic expression representative of the genomic programming. While conceptually simple, the genotype-to-phenotype linkage in a eukaryotic organism relies on the interactions of thousands of genes and an environment with a potentially unknowable level of complexity. Modern biology has moved to the use of networks in systems biology to try to simplify this complexity to decode how an organism's genome works. Previously, biological networks were basic ways to organize, simplify, and analyze data. However, recent advances are allowing networks to move beyond description and become phenotypes or hypotheses in their own right. This review discusses these efforts, like mapping responses across biological scales, including relationships among cellular entities, and the direct use of networks as traits or hypotheses.

PhytoNet: comparative co-expression network analyses across phytoplankton and land plants

Phytoplankton consists of autotrophic, photosynthesizing microorganisms that are a crucial component of freshwater and ocean ecosystems. However, despite being the major primary producers of organic compounds, accounting for half of the photosynthetic activity worldwide and serving as the entry point to the food chain, functions of most of the genes of the model phytoplankton organisms remain unknown. To remedy this, we have gathered publicly available expression data for one chlorophyte, one rhodophyte, one haptophyte, two heterokonts and four cyanobacteria and integrated it into our PlaNet (Plant Networks) database, which now allows mining gene expression profiles and identification of co-expressed genes of 19 species. We exemplify how the co-expressed gene networks can be used to reveal functionally related genes and how the comparative features of PhytoNet allow detection of conserved transcriptional programs between cyanobacteria, green algae, and land plants. Additionally, we illustrate how the database allows detection of duplicated transcriptional programs within an organism, as exemplified by two putative DNA repair programs within Chlamydomonas reinhardtii. PhytoNet is available from www.gene2function.de.

Applications of metabolomics in assessing ecological effects of emerging contaminants and pollutants on plants

Metabolomics, the global profiling of metabolite composition, is a powerful technique that can be applied to answer a diverse set of research questions concerning effects of toxicants on organisms. It has recently emerged as a tool to understand complex environmental perturbations in biological systems, especially at sub-lethal concentrations. Organisms can be affected by different stressors such as xenobiotics or increase in concentration of natural compounds such as nitrogen, phosphorous, and sulfur. Metabolomics has facilitated a better understanding of the effects of these perturbations on organisms such as plants, animals, and humans providing phenotypic and biological information in a high throughput manner. In this review, we will discuss recent applications of metabolomics to study the ecological effects of different environmental perturbations, including nanoparticles, pharmaceuticals and personal care products, pesticides, as well as the changes in natural compounds found in the environment with a focus on plant systems.

Multiomics analysis reveals a distinct mechanism of oleaginousness in the emerging model alga Chromochloris zofingiensis

Chromochloris zofingiensis, featured due to its capability to simultaneously synthesize triacylglycerol (TAG) and astaxanthin, is emerging as a leading candidate alga for production uses. To better understand the oleaginous mechanism of this alga, we conducted a multiomics analysis by systematically integrating time-resolved transcriptomes, lipidomes and metabolomes in response to nitrogen deprivation. The data analysis unraveled the distinct mechanism of TAG accumulation, which involved coordinated stimulation of multiple biological processes including supply of energy and reductants, carbon reallocation from protein and starch, and 'pushing' and 'pulling' carbon to TAG synthesis. Unlike the model alga Chlamydomonas, de novo fatty acid synthesis in C. zofingiensis was promoted, together with enhanced turnover of both glycolipids and phospholipids, supporting the drastic need of acyls for TAG assembly. Moreover, genomewide analysis identified many key functional enzymes and transcription factors that had engineering potential for TAG modulation. Two genes encoding glycerol-3-phosphate acyltransferase (GPAT), the first committed enzyme for TAG assembly, were found in the C. zofingiensis genome; in vivo functional characterization revealed that extrachloroplastic GPAT instead of chloroplastic GPAT played a central role in TAG synthesis. These findings illuminate distinct oleaginousness mechanisms in C. zofingiensis and pave the way towards rational manipulation of this alga to becone an emerging model for trait improvements.

Caracterización <i>in silico</i> y análisis de la expresión de la subunidad alfa de la acetil-coenzima a carboxilasa heteromérica de dos microalgas

Las microalgas son microorganismos fotosintéticos con gran potencial para abastecer las demandas energéticas mundiales. Sin embargo, los limitados conocimientos que se tienen de estos organismos, en particular a nivel molecular de los procesos metabólicos, han limitado su uso con estos propósitos. En esta investigación se ha realizado el análisis in silico de la subunidad alfa de la acetil-Coenzima A carboxilasa heteromérica (αACCasa), una enzima clave en la biosíntesis de lípidos de las microalgas Chlorella sp. y Scenedesmus sp. Asimismo, se ha medido la expresión de este gen en ambas especies cultivadas en medios deficientes de nitrógeno. Los resultados indican que la αACCasa muestra conservación estructural y funcional en ambas especies de microalgas y su mayor similitud genética con otras especies de microalgas. Asimismo, se ha mostrado que el nivel de expresión del gen se incrementa significativamente cuando las microalgas son cultivadas en ausencia de nitrógeno, lo cual se relaciona a su vez con una mayor acumulación de lípidos microalgales. En conclusión, el análisis in silico de la αACCasa de Chlorella sp. y Scenedesmus sp. presentan características estructurales, funcionales y evolutivas muy similares con otras especies de microalgas y plantas. Asimismo, el estudio revela que en ambas especies el gen se sobreexpresa cuando las microalgas son sometidas a estrés por deficiencia de nitrógeno, el cual se relaciona significativamente con la acumulación de lípidos totales en estas células.

Transcriptomic and lipidomic analysis of an EPA-containing Nannochloropsis sp. PJ12 in response to nitrogen deprivation

To understand genes involved in neutral lipid accumulation upon nitrogen deprivation (ND) in a novel isolate of Nannochloropsis sp. PJ12, we performed comparative transcriptomic and lipidomic analyses of cells under ND and NR (nitrogen replete) conditions. Transcriptomic profiling indicated that, while enzymes involved in TCA cycle in PJ12 under ND condition were upregulated compared to that under NR condition, those involved in Calvin cycle and glycolysis under ND condition were downregulated. Furthermore, we showed that enzymes involved in fatty acid synthesis and glycerolipid synthesis were downregulated but not β-oxidation. Lipidomic profiling indicated that, while the level of neutral lipids in ND cells was increased compared to that of NR cells, level of photosynthetic membrane-lipids DGDG and PG was decreased. Taken together, our analysis indicated that TAG accumulation is attributed to the modification of membrane lipids derived primarily from “prokaryotic” pathway and secondarily from “eukaryotic” pathway based on the 16:X or 18:X fatty acid at the sn2 position of the glycerol backbone. We propose that two-phase (NR-ND) growth is ideal for biomass and biofuel production because ND reduces cell growth rate due to the loss of photosynthetic membrane and decreased quantum yield.

The lipid biochemistry of eukaryotic algae

Algal lipid metabolism fascinates both scientists and entrepreneurs due to the large diversity of fatty acyl structures that algae produce. Algae have therefore long been studied as sources of genes for novel fatty acids; and, due to their superior biomass productivity, algae are also considered a potential feedstock for biofuels. However, a major issue in a commercially viable "algal oil-to-biofuel" industry is the high production cost, because most algal species only produce large amounts of oils after being exposed to stress conditions. Recent studies have therefore focused on the identification of factors involved in TAG metabolism, on the subcellular organization of lipid pathways, and on interactions between organelles. This has been accompanied by the development of genetic/genomic and synthetic biological tools not only for the reference green alga Chlamydomonas reinhardtii but also for Nannochloropsis spp. and Phaeodactylum tricornutum. Advances in our understanding of enzymes and regulatory proteins of acyl lipid biosynthesis and turnover are described herein with a focus on carbon and energetic aspects. We also summarize how changes in environmental factors can impact lipid metabolism and describe present and potential industrial uses of algal lipids.

Comprehensive analysis of the lncRNA-associated ceRNA network identifies neuroinflammation biomarkers for Alzheimer's disease

Accumulating evidence has highlighted the important roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in Alzheimer's disease (AD).

Characterization of type I and type II diacylglycerol acyltransferases from the emerging model alga Chlorella zofingiensis reveals their functional complementarity and engineering potential

BACKGROUND

The green alga Chlorella zofingiensis has been recognized as an industrially relevant strain because of its robust growth under multiple trophic conditions and the potential for simultaneous production of triacylglycerol (TAG) and the high-value keto-carotenoid astaxanthin. Nevertheless, the mechanism of TAG synthesis remains poorly understood in C. zofingiensis. Diacylglycerol acyltransferase (DGAT) is thought to catalyze the committed step of TAG assembly in the Kennedy pathway. C. zofingiensis genome is predicted to possess eleven putative DGAT-encoding genes, the greatest number ever found in green algae, pointing to the complexity of TAG assembly in the alga.

RESULTS

The transcription start site of C. zofingiensis DGATs was determined by 5'-rapid amplification of cDNA ends (RACE), and their coding sequences were cloned and verified by sequencing, which identified ten DGAT genes (two type I DGATs designated as CzDGAT1A and CzDGAT1B, and eight type II DGATs designated as CzDGTT1 through CzDGTT8) and revealed that the previous gene models of seven DGATs were incorrect. Function complementation in the TAG-deficient yeast strain confirmed the functionality of most DGATs, with CzDGAT1A and CzDGTT5 having the highest activity. In vitro DGAT assay revealed that CzDGAT1A and CzDGTT5 preferred eukaryotic and prokaryotic diacylglycerols (DAGs), respectively, and had overlapping yet distinctive substrate specificity for acyl-CoAs. Subcellular co-localization experiment in tobacco leaves indicated that both CzDGAT1A and CzDGTT5 were localized at endoplasmic reticulum (ER). Upon nitrogen deprivation, TAG was drastically induced in C. zofingiensis, accompanied by a considerable up-regulation of CzDGAT1A and CzDGTT5. These two genes were probably regulated by the transcription factors (TFs) bZIP3 and MYB1, as suggested by the yeast one-hybrid assay and expression correlation. Moreover, heterologous expression of CzDGAT1A and CzDGTT5 promoted TAG accumulation and TAG yield in different hosts including yeast and oleaginous alga.

CONCLUSIONS

Our study represents a pioneering work on the characterization of both type I and type II C. zofingiensis DGATs by systematically integrating functional complementation, in vitro enzymatic assay, subcellular localization, yeast one-hybrid assay and overexpression in yeast and oleaginous alga. These results (1) update the gene models of C. zofingiensis DGATs, (2) shed light on the mechanism of oleaginousness in which CzDGAT1A and CzDGTT5, have functional complementarity and probably work in collaboration at ER contributing to the abundance and complexity of TAG, and (3) provide engineering targets for future trait improvement via rational manipulation of this alga as well as other industrially relevant ones.

Nitrogen-dependent coordination of cell cycle, quiescence and TAG accumulation in Chlamydomonas

Microalgae hold great promises as sustainable cellular factories for the production of alternative fuels, feeds, and biopharmaceuticals for human health. While the biorefinery approach for fuels along with the coproduction of high-value compounds with industrial, therapeutic, or nutraceutical applications have the potential to make algal biofuels more economically viable, a number of challenges continue to hamper algal production systems at all levels. One such hurdle includes the metabolic trade-off often observed between the increased yields of desired products, such as triacylglycerols (TAG), and the growth of an organism. Initial genetic engineering strategies to improve lipid productivity in microalgae, which focused on overproducing the enzymes involved in fatty acid and TAG biosynthesis or inactivating competing carbon (C) metabolism, have seen some successes albeit at the cost of often greatly reduced biomass. Emergent approaches that aim at modifying the dynamics of entire metabolic pathways by engineering of pertinent transcription factors or signaling networks appear to have successfully achieved a balance between growth and neutral lipid accumulation. However, the biological knowledge of key signaling networks and molecular components linking these two processes is still incomplete in photosynthetic eukaryotes, making it difficult to optimize metabolic engineering strategies for microalgae. Here, we focus on nitrogen (N) starvation of the model green microalga, Chlamydomonas reinhardtii, to present the current understanding of the nutrient-dependent switch between proliferation and quiescence, and the drastic reprogramming of metabolism that results in the storage of C compounds following N starvation. We discuss the potential components mediating the transcriptional repression of cell cycle genes and the establishment of quiescence in Chlamydomonas, and highlight the importance of signaling pathways such as those governed by the target of rapamycin (TOR) and sucrose nonfermenting-related (SnRK) kinases in the coordination of metabolic status with cellular growth. A better understanding of how the cell division cycle is regulated in response to nutrient scarcity and of the signaling pathways linking cellular growth to energy and lipid homeostasis, is essential to improve the prospects of biofuels and biomass production in microalgae.

An integrated omics analysis reveals molecular mechanisms that are associated with differences in seed oil content between Glycine max and Brassica napus

BACKGROUND

Rapeseed (Brassica napus L.) and soybean (Glycine max L.) seeds are rich in both protein and oil, which are major sources of biofuels and nutrition. Although the difference in seed oil content between soybean (~ 20%) and rapeseed (~ 40%) exists, little is known about its underlying molecular mechanism.

RESULTS

An integrated omics analysis was performed in soybean, rapeseed, Arabidopsis (Arabidopsis thaliana L. Heynh), and sesame (Sesamum indicum L.), based on Arabidopsis acyl-lipid metabolism- and carbon metabolism-related genes. As a result, candidate genes and their transcription factors and microRNAs, along with phylogenetic analysis and co-expression network analysis of the PEPC gene family, were found to be largely associated with the difference between the two species. First, three soybean genes (Glyma.13G148600, Glyma.13G207900 and Glyma.12G122900) co-expressed with GmPEPC1 are specifically enriched during seed storage protein accumulation stages, while the expression of BnPEPC1 is putatively inhibited by bna-miR169, and two genes BnSTKA and BnCKII are co-expressed with BnPEPC1 and are specifically associated with plant circadian rhythm, which are related to seed oil biosynthesis. Then, in de novo fatty acid synthesis there are rapeseed-specific genes encoding subunits β-CT (BnaC05g37990D) and BCCP1 (BnaA03g06000D) of heterogeneous ACCase, which could interfere with synthesis rate, and β-CT is positively regulated by four transcription factors (BnaA01g37250D, BnaA02g26190D, BnaC01g01040D and BnaC07g21470D). In triglyceride synthesis, GmLPAAT2 is putatively inhibited by three miRNAs (gma-miR171, gma-miR1516 and gma-miR5775). Finally, in rapeseed there was evidence for the expansion of gene families, CALO, OBO and STERO, related to lipid storage, and the contraction of gene families, LOX, LAH and HSI2, related to oil degradation.

CONCLUSIONS

The molecular mechanisms associated with differences in seed oil content provide the basis for future breeding efforts to improve seed oil content.

High-value bioproducts from microalgae: Strategies and progress

Microalgae have been considered as alternative sustainable resources for high-value bioproducts such as lipids (especially triacylglycerides [TAGs]), polyunsaturated fatty acids (PUFAs), and carotenoids, due to their relatively high photosynthetic efficiency, no arable land requirement, and ease of scale-up. It is of great significance to exploit microalgae for the production of high-value bioproducts. How to improve the content or productivity of specific bioproducts has become one of the most urgent challenges. In this review, we will describe high-value bioproducts from microalgae and their biosynthetic pathways (mainly for lipids, PUFAs, and carotenoids). Recent progress and strategies for the enhanced production of bioproducts from microalgae are also described in detail, and these strategies take advantages of optimized cultivation conditions with abiotic stress, chemical stress (addition of metabolic precursors, phytohormones, chemical inhibitors, and chemicals inducing oxidative stress response), and molecular approaches such as metabolic engineering, transcriptional engineering, and gene disruption strategies (mainly RNAi, antisense RNA, miRNA-based knockdown, and CRISPR/Cas9).

Microalgae for the production of lipid and carotenoids: a review with focus on stress regulation and adaptation

Microalgae have drawn great attention as promising sustainable source of lipids and carotenoids. Their lipid and carotenoids accumulation machinery can be trigged by the stress conditions such as nutrient limitation or exposure to the damaging physical factors. However, stressful conditions often adversely affect microalgal growth and cause oxidative damage to the cells, which can eventually reduce the yield of the desired products. To overcome these limitations, two-stage cultivation strategies and supplementation of growth-promoting agents have traditionally been utilized, but developing new highly adapted strains is theoretically the simplest strategy. In addition to genetic engineering, adaptive laboratory evolution (ALE) is frequently used to develop beneficial phenotypes in industrial microorganisms during long-term selection under specific stress conditions. In recent years, many studies have gradually introduced ALE as a powerful tool to improve the biological properties of microalgae, especially for improving the production of lipid and carotenoids. In this review, strategies for the manipulation of stress in microalgal lipids and carotenoids production are summarized and discussed. Furthermore, this review summarizes the overall state of ALE technology, including available selection pressures, methods, and their applications in microalgae for the improved production of lipids and carotenoids.