AlgaePath: comprehensive analysis of metabolic pathways using transcript abundance data from next-generation sequencing in green algae

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.

Microalgae biofuels: illuminating the path to a sustainable future amidst challenges and opportunities

The development of microalgal biofuels is of significant importance in advancing the energy transition, alleviating food pressure, preserving the natural environment, and addressing climate change. Numerous countries and regions across the globe have conducted extensive research and strategic planning on microalgal bioenergy, investing significant funds and manpower into this field. However, the microalgae biofuel industry has faced a downturn due to the constraints of high costs. In the past decade, with the development of new strains, technologies, and equipment, the feasibility of large-scale production of microalgae biofuel should be re-evaluated. Here, we have gathered research results from the past decade regarding microalgae biofuel production, providing insights into the opportunities and challenges faced by this industry from the perspectives of microalgae selection, modification, and cultivation. In this review, we suggest that highly adaptable microalgae are the preferred choice for large-scale biofuel production, especially strains that can utilize high concentrations of inorganic carbon sources and possess stress resistance. The use of omics technologies and genetic editing has greatly enhanced lipid accumulation in microalgae. However, the associated risks have constrained the feasibility of large-scale outdoor cultivation. Therefore, the relatively controllable cultivation method of photobioreactors (PBRs) has made it the mainstream approach for microalgae biofuel production. Moreover, adjusting the performance and parameters of PBRs can also enhance lipid accumulation in microalgae. In the future, given the relentless escalation in demand for sustainable energy sources, microalgae biofuels should be deemed a pivotal constituent of national energy planning, particularly in the case of China. The advancement of synthetic biology helps reduce the risks associated with genetically modified (GM) microalgae and enhances the economic viability of their biofuel production.

Understanding Macroalgae: A Comprehensive Exploration of Nutraceutical, Pharmaceutical, and Omics Dimensions

Driven by a surge in global interest in natural products, macroalgae or seaweed, has emerged as a prime source for nutraceuticals and pharmaceutical applications. Characterized by remarkable genetic diversity and a crucial role in marine ecosystems, these organisms offer not only substantial nutritional value in proteins, fibers, vitamins, and minerals, but also a diverse array of bioactive molecules with promising pharmaceutical properties. Furthermore, macroalgae produce approximately 80% of the oxygen in the atmosphere, highlighting their ecological significance. The unique combination of nutritional and bioactive attributes positions macroalgae as an ideal resource for food and medicine in various regions worldwide. This comprehensive review consolidates the latest advancements in the field, elucidating the potential applications of macroalgae in developing nutraceuticals and therapeutics. The review emphasizes the pivotal role of omics approaches in deepening our understanding of macroalgae's physiological and molecular characteristics. By highlighting the importance of omics, this review also advocates for continued exploration and utilization of these extraordinary marine organisms in diverse domains, including drug discovery, functional foods, and other industrial applications. The multifaceted potential of macroalgae warrants further research and development to unlock their full benefits and contribute to advancing global health and sustainable industries.

A critical review of machine-learning for "multi-omics" marine metabolite datasets

During the last decade, genomic, transcriptomic, proteomic, metabolomic, and other omics datasets have been generated for a wide range of marine organisms, and even more are still on the way. Marine organisms possess unique and diverse biosynthetic pathways contributing to the synthesis of novel secondary metabolites with significant bioactivities. As marine organisms have a greater tendency to adapt to stressed environmental conditions, the chance to identify novel bioactive metabolites with potential biotechnological application is very high. This review presents a comprehensive overview of the available "-omics" and "multi-omics" approaches employed for characterizing marine metabolites along with novel data integration tools. The need for the development of machine-learning algorithms for "multi-omics" approaches is briefly discussed. In addition, the challenges involved in the analysis of "multi-omics" data and recommendations for conducting "multi-omics" study were discussed.

Novel context-specific genome-scale modelling explores the potential of triacylglycerol production by Chlamydomonas reinhardtii

Gene expression data of cell cultures is commonly measured in biological and medical studies to understand cellular decision-making in various conditions. Metabolism, affected but not solely determined by the expression, is much more difficult to measure experimentally. Finding a reliable method to predict cell metabolism for expression data will greatly benefit metabolic engineering. We have developed a novel pipeline, OVERLAY, that can explore cellular fluxomics from expression data using only a high-quality genome-scale metabolic model. This is done through two main steps: first, construct a protein-constrained metabolic model (PC-model) by integrating protein and enzyme information into the metabolic model (M-model). Secondly, overlay the expression data onto the PC-model using a novel two-step nonconvex and convex optimization formulation, resulting in a context-specific PC-model with optionally calibrated rate constants. The resulting model computes proteomes and intracellular flux states that are consistent with the measured transcriptomes. Therefore, it provides detailed cellular insights that are difficult to glean individually from the omic data or M-model alone. We apply the OVERLAY to interpret triacylglycerol (TAG) overproduction by Chlamydomonas reinhardtii, using time-course RNA-Seq data. We show that OVERLAY can compute C. reinhardtii metabolism under nitrogen deprivation and metabolic shifts after an acetate boost. OVERLAY can also suggest possible 'bottleneck' proteins that need to be overexpressed to increase the TAG accumulation rate, as well as discuss other TAG-overproduction strategies.

Biomolecule and Bioentity Interaction Databases in Systems Biology: A Comprehensive Review

Technological advances in high-throughput techniques have resulted in tremendous growth of complex biological datasets providing evidence regarding various biomolecular interactions. To cope with this data flood, computational approaches, web services, and databases have been implemented to deal with issues such as data integration, visualization, exploration, organization, scalability, and complexity. Nevertheless, as the number of such sets increases, it is becoming more and more difficult for an end user to know what the scope and focus of each repository is and how redundant the information between them is. Several repositories have a more general scope, while others focus on specialized aspects, such as specific organisms or biological systems. Unfortunately, many of these databases are self-contained or poorly documented and maintained. For a clearer view, in this article we provide a comprehensive categorization, comparison and evaluation of such repositories for different bioentity interaction types. We discuss most of the publicly available services based on their content, sources of information, data representation methods, user-friendliness, scope and interconnectivity, and we comment on their strengths and weaknesses. We aim for this review to reach a broad readership varying from biomedical beginners to experts and serve as a reference article in the field of Network Biology.

EXPath 2.0: An Updated Database for Integrating High-Throughput Gene Expression Data with Biological Pathways

Co-expressed genes tend to have regulatory relationships and participate in similar biological processes. Construction of gene correlation networks from microarray or RNA-seq expression data has been widely applied to study transcriptional regulatory mechanisms and metabolic pathways under specific conditions. Furthermore, since transcription factors (TFs) are critical regulators of gene expression, it is worth investigating TFs on the promoters of co-expressed genes. Although co-expressed genes and their related metabolic pathways can be easily identified from previous resources, such as EXPath and EXPath Tool, this information is not simultaneously available to identify their regulatory TFs. EXPath 2.0 is an updated database for the investigation of regulatory mechanisms in various plant metabolic pathways with 1,881 microarray and 978 RNA-seq samples. There are six significant improvements in EXPath 2.0: (i) the number of species has been extended from three to six to include Arabidopsis, rice, maize, Medicago, soybean and tomato; (ii) gene expression at various developmental stages have been added; (iii) construction of correlation networks according to a group of genes is available; (iv) hierarchical figures of the enriched Gene Ontology (GO) terms are accessible; (v) promoter analysis of genes in a metabolic pathway or correlation network is provided; and (vi) user's gene expression data can be uploaded and analyzed. Thus, EXPath 2.0 is an updated platform for investigating gene expression profiles and metabolic pathways under specific conditions. It facilitates users to access the regulatory mechanisms of plant biological processes. The new version is available at http://EXPath.itps.ncku.edu.tw.

Identification and Analysis of microRNAs in Chlorella sorokiniana Using High-Throughput Sequencing

Chlorella is a popular microalga with robust physiological and biochemical characteristics, which can be cultured under various conditions. The exploration of the small RNA content of Chlorella could improve strategies for the enhancement of metabolite production from this microalga. In this study, stress was introduced to the Chlorella sorokiniana culture to produce high-value metabolites such as carotenoids and phenolic content. The small RNA transcriptome of C. sorokiniana was sequenced, focusing on microRNA (miRNA) content. From the analysis, 98 miRNAs were identified in cultures subjected to normal and stress conditions. The functional analysis result showed that the miRNA targets found were most often involved in the biosynthesis of secondary metabolites, followed by protein metabolism, cell cycle, and porphyrin and chlorophyll metabolism. Furthermore, the biosynthesis of secondary metabolites such as carotenoids, terpenoids, and lipids was found mostly in stress conditions. These results may help to improve our understanding of regulatory mechanisms of miRNA in the biological and metabolic process of Chlorella species. It is important and timely to determine the true potential of this microalga species and to support the potential for genetic engineering of microalgae as they receive increasing focus for their development as an alternative source of biofuel, food, and health supplements.

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

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

dEMBF v2.0: An Updated Database of Enzymes for Microalgal Biofuel Feedstock

In light of increasing algal genomics data and knowledge of biosynthetic pathways responsible for biofuel production, an integrated resource for easy access to all information is essential to improve our understanding of algal lipid metabolism. Against this backdrop, dEMBF v2.0, a significantly updated and improved version of our database of microalgae lipid biosynthetic enzymes for biofuel production, has been developed. dEMBF v2.0 now contains a comprehensive annotation of 2018 sequences encoding 35 enzymes, an increase of over 7-fold as compared with the first version. Other improved features include an increase in species coverage to 32 algal genomes, analysis of additional metabolic pathways, expanded annotation thoroughly detailing sequence and structural features, including enzyme-ligand interactions, and integration of supporting experimental evidence to demonstrate the role of enzymes in increasing lipid content. Along with a complete redesign of the interface, the updated database provides several inbuilt tools and user-friendly functionalities for more interactive and dynamic visualization of data.

Marine Natural Products from Microalgae: An -Omics Overview

Over the last decade, genome sequences and other -omics datasets have been produced for a wide range of microalgae, and several others are on the way. Marine microalgae possess distinct and unique metabolic pathways, and can potentially produce specific secondary metabolites with biological activity (e.g., antipredator, allelopathic, antiproliferative, cytotoxic, anticancer, photoprotective, as well as anti-infective and antifouling activities). Because microalgae are very diverse, and adapted to a broad variety of environmental conditions, the chances to find novel and unexplored bioactive metabolites with properties of interest for biotechnological and biomedical applications are high. This review presents a comprehensive overview of the current efforts and of the available solutions to produce, explore and exploit -omics datasets, with the aim of identifying species and strains with the highest potential for the identification of novel marine natural products. In addition, funding efforts for the implementation of marine microalgal -omics resources and future perspectives are presented as well.

Genome-wide identification and characterization of CKIN/SnRK gene family in Chlamydomonas reinhardtii

The SnRK (Snf1-Related protein Kinase) gene family plays an important role in energy sensing and stress-adaptive responses in plant systems. In this study, Chlamydomonas CKIN family (SnRK in Arabidopsis) was defined after a genome-wide analysis of all sequenced Chlorophytes. Twenty-two sequences were defined as plant SnRK orthologs in Chlamydomonas and classified into two subfamilies: CKIN1 and CKIN2. While CKIN1 subfamily is reduced to one conserved member and a close protein (CKIN1L), a large CKIN2 subfamily clusters both plant-like and algae specific CKIN2s. The responsiveness of these genes to abiotic stress situations was tested by RT-qPCR. Results showed that almost all elements were sensitive to osmotic stress while showing different degrees of sensibility to other abiotic stresses, as occurs in land plants, revealing their specialization and the family pleiotropy for some elements. The regulatory pathway of this family may differ from land plants since these sequences shows unique regulatory features and some of them are sensitive to ABA, despite conserved ABA receptors (PYR/PYL/RCAR) and regulatory domains are not present in this species. Core Chlorophytes and land plant showed divergent stress signalling, but SnRKs/CKINs share the same role in cell survival and stress response and adaption including the accumulation of specific biomolecules. This fact places the CKIN family as well-suited target for bioengineering-based studies in microalgae (accumulation of sugars, lipids, secondary metabolites), while promising new findings in stress biology and specially in the evolution of ABA-signalling mechanisms.

The Ancient Phosphatidylinositol 3-Kinase Signaling System Is a Master Regulator of Energy and Carbon Metabolism in Algae

Algae undergo a complete metabolic transformation under stress by arresting cell growth, inducing autophagy and hyper-accumulating biofuel precursors such as triacylglycerols and starch. However, the regulatory mechanisms behind this stress-induced transformation are still unclear. Here, we use biochemical, mutational, and "omics" approaches to demonstrate that PI3K signaling mediates the homeostasis of energy molecules and influences carbon metabolism in algae. In Chlamydomonas reinhardtii, the inhibition and knockdown (KD) of algal class III PI3K led to significantly decreased cell growth, altered cell morphology, and higher lipid and starch contents. Lipid profiling of wild-type and PI3K KD lines showed significantly reduced membrane lipid breakdown under nitrogen starvation (-N) in the KD. RNA-seq and network analyses showed that under -N conditions, the KD line carried out lipogenesis rather than lipid hydrolysis by initiating de novo fatty acid biosynthesis, which was supported by tricarboxylic acid cycle down-regulation and via acetyl-CoA synthesis from glycolysis. Remarkably, autophagic responses did not have primacy over inositide signaling in algae, unlike in mammals and vascular plants. The mutant displayed a fundamental shift in intracellular energy flux, analogous to that in tumor cells. The high free fatty acid levels and reduced mitochondrial ATP generation led to decreased cell viability. These results indicate that the PI3K signal transduction pathway is the metabolic gatekeeper restraining biofuel yields, thus maintaining fitness and viability under stress in algae. This study demonstrates the existence of homeostasis between starch and lipid synthesis controlled by lipid signaling in algae and expands our understanding of such processes, with biotechnological and evolutionary implications.

Cellular toxicity pathways of inorganic and methyl mercury in the green microalga Chlamydomonas reinhardtii

Contamination by mercury (Hg) is a worldwide concern because of Hg toxicity and biomagnification in aquatic food webs. Nevertheless, bioavailability and cellular toxicity pathways of inorganic (IHg) and methyl-Hg (MeHg) remain poorly understood. We analyzed the uptake, transcriptomic, and physiological responses in the microalga Chlamydomonas reinhardtii exposed to IHg or MeHg. Bioavailability of MeHg was up to 27× higher than for IHg. Genes involved in cell processes, energy metabolism and transport were dysregulated by both Hg species. Physiological analysis revealed an impact on photosynthesis and reduction–oxidation reaction metabolism. Nevertheless, MeHg dysregulated a larger number of genes and with a stronger fold-change than IHg at equivalent intracellular concentration. Analysis of the perturbations of the cell’s functions helped to derive a detailed mechanistic understanding of differences in cellular handling of IHg and MeHg resulting in MeHg having a stronger impact. This knowledge is central for the prediction of impact of toxicants on organisms.

Knock-Down of the IFR1 Protein Perturbs the Homeostasis of Reactive Electrophile Species and Boosts Photosynthetic Hydrogen Production in Chlamydomonas reinhardtii

The protein superfamily of short-chain dehydrogenases/reductases (SDR), including members of the atypical type (aSDR), covers a huge range of catalyzed reactions and in vivo substrates. This superfamily also comprises isoflavone reductase-like (IRL) proteins, which are aSDRs highly homologous to isoflavone reductases from leguminous plants. The molecular function of IRLs in non-leguminous plants and green microalgae has not been identified as yet, but several lines of evidence point at their implication in reactive oxygen species homeostasis. The Chlamydomonas reinhardtii IRL protein IFR1 was identified in a previous study, analyzing the transcriptomic changes occurring during the acclimation to sulfur deprivation and anaerobiosis, a condition that triggers photobiological hydrogen production in this microalgae. Accumulation of the cytosolic IFR1 protein is induced by sulfur limitation as well as by the exposure of C. reinhardtii cells to reactive electrophile species (RES) such as reactive carbonyls. The latter has not been described for IRL proteins before. Over-accumulation of IFR1 in the singlet oxygen response 1 (sor1) mutant together with the presence of an electrophile response element, known to be required for SOR1-dependent gene activation as a response to RES, in the promoter of IFR1, indicate that IFR1 expression is controlled by the SOR1-dependent pathway. An implication of IFR1 into RES homeostasis, is further implied by a knock-down of IFR1, which results in a diminished tolerance toward RES. Intriguingly, IFR1 knock-down has a positive effect on photosystem II (PSII) stability under sulfur-deprived conditions used to trigger photobiological hydrogen production, by reducing PSII-dependent oxygen evolution, in C. reinhardtii. Reduced PSII photoinhibition in IFR1 knock-down strains prolongs the hydrogen production phase resulting in an almost doubled final hydrogen yield compared to the parental strain. Finally, IFR1 knock-down could be successfully used to further increase hydrogen yields of the high hydrogen-producing mutant stm6, demonstrating that IFR1 is a promising target for genetic engineering approaches aiming at an increased hydrogen production capacity of C. reinhardtii cells.

Dynamic metabolic profiling together with transcription analysis reveals salinity-induced starch-to-lipid biosynthesis in alga Chlamydomonas sp. JSC4

Biodiesel production using microalgae would play a pivotal role in satisfying future global energy demands. Understanding of lipid metabolism in microalgae is important to isolate oleaginous strain capable of overproducing lipids. It has been reported that reducing starch biosynthesis can enhance lipid accumulation. However, the metabolic mechanism controlling carbon partitioning from starch to lipids in microalgae remains unclear, thus complicating the genetic engineering of algal strains. We here used “dynamic” metabolic profiling and essential transcription analysis of the oleaginous green alga Chlamydomonas sp. JSC4 for the first time to demonstrate the switching mechanisms from starch to lipid synthesis using salinity as a regulator, and identified the metabolic rate-limiting step for enhancing lipid accumulation (e.g., pyruvate-to-acetyl-CoA). These results, showing salinity-induced starch-to-lipid biosynthesis, will help increase our understanding of dynamic carbon partitioning in oleaginous microalgae. Moreover, we successfully determined the changes of several key lipid-synthesis-related genes (e.g., acetyl-CoA carboxylase, pyruvate decarboxylase, acetaldehyde dehydrogenase, acetyl-CoA synthetase and pyruvate ferredoxin oxidoreductase) and starch-degradation related genes (e.g., starch phosphorylases), which could provide a breakthrough in the marine microalgal production of biodiesel.

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

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

ChlamyNET: a Chlamydomonas gene co-expression network reveals global properties of the transcriptome and the early setup of key co-expression patterns in the green lineage

BACKGROUND

Chlamydomonas reinhardtii is the model organism that serves as a reference for studies in algal genomics and physiology. It is of special interest in the study of the evolution of regulatory pathways from algae to higher plants. Additionally, it has recently gained attention as a potential source for bio-fuel and bio-hydrogen production. The genome of Chlamydomonas is available, facilitating the analysis of its transcriptome by RNA-seq data. This has produced a massive amount of data that remains fragmented making necessary the application of integrative approaches based on molecular systems biology.

RESULTS

We constructed a gene co-expression network based on RNA-seq data and developed a web-based tool, ChlamyNET, for the exploration of the Chlamydomonas transcriptome. ChlamyNET exhibits a scale-free and small world topology. Applying clustering techniques, we identified nine gene clusters that capture the structure of the transcriptome under the analyzed conditions. One of the most central clusters was shown to be involved in carbon/nitrogen metabolism and signalling, whereas one of the most peripheral clusters was involved in DNA replication and cell cycle regulation. The transcription factors and regulators in the Chlamydomonas genome have been identified in ChlamyNET. The biological processes potentially regulated by them as well as their putative transcription factor binding sites were determined. The putative light regulated transcription factors and regulators in the Chlamydomonas genome were analyzed in order to provide a case study on the use of ChlamyNET. Finally, we used an independent data set to cross-validate the predictive power of ChlamyNET.

CONCLUSIONS

The topological properties of ChlamyNET suggest that the Chlamydomonas transcriptome posseses important characteristics related to error tolerance, vulnerability and information propagation. The central part of ChlamyNET constitutes the core of the transcriptome where most authoritative hub genes are located interconnecting key biological processes such as light response with carbon and nitrogen metabolism. Our study reveals that key elements in the regulation of carbon and nitrogen metabolism, light response and cell cycle identified in higher plants were already established in Chlamydomonas. These conserved elements are not only limited to transcription factors, regulators and their targets, but also include the cis-regulatory elements recognized by them.

ALCOdb: Gene Coexpression Database for Microalgae

In the era of energy and food shortage, microalgae have gained much attention as promising sources of biofuels and food ingredients. However, only a small fraction of microalgal genes have been functionally characterized. Here, we have developed the Algae Gene Coexpression database (ALCOdb; http://alcodb.jp), which provides gene coexpression information to survey gene modules for a function of interest. ALCOdb currently supports two model algae: the green alga Chlamydomonas reinhardtii and the red alga Cyanidioschyzon merolae. Users can retrieve coexpression information for genes of interest through three unique data pages: (i) Coexpressed Gene List; (ii) Gene Information; and (iii) Coexpressed Gene Network. In addition to the basal coexpression information, ALCOdb also provides several advanced functionalities such as an expression profile viewer and a differentially expressed gene search tool. Using these user interfaces, we demonstrated that our gene coexpression data have the potential to detect functionally related genes and are useful in extrapolating the biological roles of uncharacterized genes. ALCOdb will facilitate molecular and biochemical studies of microalgal biological phenomena, such as lipid metabolism and organelle development, and promote the evolutionary understanding of plant cellular systems.

EXPath: a database of comparative expression analysis inferring metabolic pathways for plants

BACKGROUND

In general, the expression of gene alters conditionally to catalyze a specific metabolic pathway. Microarray-based datasets have been massively produced to monitor gene expression levels in parallel with numerous experimental treatments. Although several studies facilitated the linkage of gene expression data and metabolic pathways, none of them are amassed for plants. Moreover, advanced analysis such as pathways enrichment or how genes express under different conditions is not rendered.

DESCRIPTION

Therefore, EXPath was developed to not only comprehensively congregate the public microarray expression data from over 1000 samples in biotic stress, abiotic stress, and hormone secretion but also allow the usage of this abundant resource for coexpression analysis and differentially expression genes (DEGs) identification, finally inferring the enriched KEGG pathways and gene ontology (GO) terms of three model plants: Arabidopsis thaliana, Oryza sativa, and Zea mays. Users can access the gene expression patterns of interest under various conditions via five main functions (Gene Search, Pathway Search, DEGs Search, Pathways/GO Enrichment, and Coexpression analysis) in EXPath, which are presented by a user-friendly interface and valuable for further research.

CONCLUSIONS

In conclusion, EXPath, freely available at http://expath.itps.ncku.edu.tw, is a database resource that collects and utilizes gene expression profiles derived from microarray platforms under various conditions to infer metabolic pathways for plants.

System-level network analysis of nitrogen starvation and recovery in Chlamydomonas reinhardtii reveals potential new targets for increased lipid accumulation

BACKGROUND

Nitrogen starvation is known to cause drastic alterations in physiology and metabolism leading to the accumulation of lipid bodies in many microalgae, and it thus presents an important alternative for biofuel production. However, despite the importance of this process, the molecular mechanisms that mediate the metabolic remodeling induced by N starvation and especially by stress recovery are still poorly understood, and new candidates for bioengineering are needed to make this process useful for biofuel production.

RESULTS

We have studied the molecular changes involved in the adaptive mechanisms to N starvation and full recovery of the vegetative cells in the microalga Chlamydomonas reinhardtii during a four-day time course. High throughput mass spectrometry was employed to integrate the proteome and the metabolome with physiological changes. N starvation led to an accumulation of oil bodies and reduced Fv/Fm.. Distinct enzymes potentially participating in the carbon-concentrating mechanism (CAH7, CAH8, PEPC1) are strongly accumulated. The membrane composition is changed, as indicated by quantitative lipid profiles. A reprogramming of protein biosynthesis was observed by increased levels of cytosolic ribosomes, while chloroplastidic were dramatically reduced. Readdition of N led to, the identification of early responsive proteins mediating stress recovery, indicating their key role in regaining and sustaining normal vegetative growth. Analysis of the data with multivariate correlation analysis, Granger causality, and sparse partial least square (sPLS) provided a functional network perspective of the molecular processes. Cell growth and N metabolism were clearly linked by the branched chain amino acids, suggesting an important role in this stress. Lipid accumulation was also tightly correlated to the COP II protein, involved in vesicle and lysosome coating, and a major lipid droplet protein. This protein, together with other key proteins mediating signal transduction and adaption (BRI1, snRKs), constitute a series of new metabolic and regulatory targets.

CONCLUSIONS

This work not only provides new insights and corrects previous models by analyzing a complex dataset, but also increases our biochemical understanding of the adaptive mechanisms to N starvation in Chlamydomonas, pointing to new bioengineering targets for increased lipid accumulation, a key step for a sustainable and profitable microalgae-based biofuel production.