Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling

Chlamydomonas reinhardtii and Microbacterium forte sp. nov., a mutualistic association that favors sustainable hydrogen production

A naturally occurring multispecies bacterial community composed of Bacillus cereus and two novel bacteria (Microbacterium forte sp. nov. and Stenotrophomonas goyi sp. nov.) has been identified from a contaminated culture of the microalga Chlamydomonas reinhardtii. When incubated in mannitol- and yeast extract-containing medium, this bacterial community can promote and sustain algal hydrogen production up to 313 mL H2·L-1 for 17 days and 163.5 mL H2·L-1 for 25 days in high-cell (76.7 μg·mL-1 of initial chlorophyll) and low-cell density (10 μg·mL-1 of initial chlorophyll) algal cultures, respectively. In low-cell density algal cultures, hydrogen production was compatible with algal growth (reaching up to 60 μg·mL-1 of chlorophyll). Among the bacterial community, M. forte sp. nov. was the sole responsible for the improvement in hydrogen production. However, algal growth was not observed in the Chlamydomonas-M. forte sp. nov. consortium during hydrogen-producing conditions (hypoxia), suggesting that the presence of B. cereus and S. goyi sp. nov. could be crucial to support the algal growth during hypoxia. Still, under non‑hydrogen producing conditions (aerobiosis) the Chlamydomonas-M. forte sp. nov. consortium allowed algal growth (up to 40 μg·mL-1 of chlorophyll) and long-term algal viability (>45 days). The genome sequence and growth tests of M. forte sp. nov. have revealed that this bacterium is auxotroph for biotin and thiamine and unable to use sulfate as sulfur source; it requires S-reduced forms such as cysteine and methionine. Cocultures of Chlamydomonas reinhardtii and M. forte sp. nov. established a mutualistic association: the alga complemented the nutrient deficiencies of the bacterium, while the bacterium released ammonium (0.19 mM·day-1) and acetic acid (0.15 mM·day-1) for the alga. This work offers a promising avenue for photohydrogen production concomitant with algal biomass generation using nutrients not suitable for mixotrophic algal growth.

Genetic evidence for algal auxin production in Chlamydomonas and its role in algal-bacterial mutualism

Interactions between algae and bacteria are ubiquitous and play fundamental roles in nutrient cycling and biomass production. Recent studies have shown that the plant auxin indole acetic acid (IAA) can mediate chemical crosstalk between algae and bacteria, resembling its role in plant-bacterial associations. Here, we report a mechanism for algal extracellular IAA production from L-tryptophan mediated by the enzyme L-amino acid oxidase (LAO1) in the model Chlamydomonas reinhardtii. High levels of IAA inhibit algal cell multiplication and chlorophyll degradation, and these inhibitory effects can be relieved by the presence of the plant-growth-promoting bacterium (PGPB) Methylobacterium aquaticum, whose growth is mutualistically enhanced by the presence of the alga. These findings reveal a complex interplay of microbial auxin production and degradation by algal-bacterial consortia and draws attention to potential ecophysiological roles of terrestrial microalgae and PGPB in association with land plants.

Stenotrophomonas goyi sp. nov., a novel bacterium associated with the alga Chlamydomonas reinhardtii

Background

A culture of the green algae Chlamydomonas reinhardtii was accidentally contaminated with three different bacteria in our laboratory facilities. This contaminated alga culture showed increased algal biohydrogen production. These three bacteria were independently isolated.

Methods

The chromosomic DNA of one of the isolated bacteria was extracted and sequenced using PacBio technology. Tentative genome annotation (RAST server) and phylogenetic trees analysis (TYGS server) were conducted. Diverse growth tests were assayed for the bacterium and for the alga-bacterium consortium.

Results

Phylogenetic analysis indicates that the bacterium is a novel member of the Stenotrophomonas genus that has been termed in this work as S. goyi sp. nov. A fully sequenced genome (4,487,389 base pairs) and its tentative annotation (4,147 genes) are provided. The genome information suggests that S. goyi sp. nov. is unable to use sulfate and nitrate as sulfur and nitrogen sources, respectively. Growth tests have confirmed the dependence on the sulfur-containing amino acids methionine and cysteine. S. goyi sp. nov. and Chlamydomonas reinhardtii can establish a mutualistic relationship when cocultured together.

Conclusions

S. goyi sp. nov. could be of interest for the design of biotechnological approaches based on the use of artificial microalgae-bacteria multispecies consortia that take advantage of the complementary metabolic capacities of their different microorganisms.

Stenotrophomonas goyi sp. nov., a novel bacterium associated with the alga Chlamydomonas reinhardtii

BACKGROUND

A culture of the green algae Chlamydomonas reinhardtii was accidentally contaminated with three different bacteria in our laboratory facilities. This contaminated alga culture showed increased algal biohydrogen production. These three bacteria were independently isolated.

METHODS

The chromosomic DNA of one of the isolated bacteria was extracted and sequenced using PacBio technology. Tentative genome annotation (RAST server) and phylogenetic trees analysis (TYGS server) were conducted. Diverse growth tests were assayed for the bacterium and for the alga-bacterium consortium.

RESULTS

Phylogenetic analysis indicates that the bacterium is a novel member of the Stenotrophomonas genus that has been termed in this work as S. goyi sp. nov. A fully sequenced genome (4,487,389 base pairs) and its tentative annotation (4,147 genes) are provided. The genome information suggests that S. goyi sp. nov. is unable to use sulfate and nitrate as sulfur and nitrogen sources, respectively. Growth tests have confirmed the dependence on the sulfur-containing amino acids methionine and cysteine. S. goyi sp. nov. and Chlamydomonas reinhardtii can establish a mutualistic relationship when cocultured together.

CONCLUSIONS

S. goyi sp. nov. could be of interest for the design of biotechnological approaches based on the use of artificial microalgae-bacteria multispecies consortia that take advantage of the complementary metabolic capacities of their different microorganisms.

Chlamydomonas reinhardtii, a Reference Organism to Study Algal-Microbial Interactions: Why Can't They Be Friends?

The stability and harmony of ecological niches rely on intricate interactions between their members. During evolution, organisms have developed the ability to thrive in different environments, taking advantage of each other. Among these organisms, microalgae are a highly diverse and widely distributed group of major primary producers whose interactions with other organisms play essential roles in their habitats. Understanding the basis of these interactions is crucial to control and exploit these communities for ecological and biotechnological applications. The green microalga Chlamydomonas reinhardtii, a well-established model, is emerging as a model organism for studying a wide variety of microbial interactions with ecological and economic significance. In this review, we unite and discuss current knowledge that points to C. reinhardtii as a model organism for studying microbial interactions.

Chlamydomonas-Methylobacterium oryzae cooperation leads to increased biomass, nitrogen removal and hydrogen production

In the context of algal wastewater bioremediation, this study has identified a novel consortium formed by the bacterium Methylobacterium oryzae and the microalga Chlamydomonas reinhardtii that greatly increase biomass generation (1.22 g L^-1·d^-1), inorganic nitrogen removal (>99%), and hydrogen production (33 mL·L^-1) when incubated in media containing ethanol and methanol. The key metabolic aspect of this relationship relied on the bacterial oxidation of ethanol to acetate, which supported heterotrophic algal growth. However, in the bacterial monocultures the acetate accumulation inhibited bacterial growth. Moreover, in the absence of methanol, ethanol was an unsuitable carbon source and its incomplete oxidation to acetaldehyde had a toxic effect on both the alga and the bacterium. In cocultures, both alcohols were used as carbon sources by the bacteria, the inhibitory effects were overcome and both microorganisms mutually benefited. Potential biotechnological applications in wastewater treatment, biomass generation and hydrogen production are discussed.

Unraveling the Antimicrobial Effectiveness of Coridothymus capitatus Hydrolate against Listeria monocytogenes in Environmental Conditions Encountered in Foods: An In Vitro Study

The increased resistance of bacteria to antimicrobials, as well as the growing interest in innovative and sustainable alternatives to traditional food additives, are driving research towards the use of natural food preservatives. Among these, hydrolates (HYs) have gained attention as “mild” alternatives to conventional antimicrobial compounds. In this study, the response of L. monocytogenes ATCC 7644 exposed to increasing concentrations of Coridothymus capitatus HY (CHY) for 1 h at 37 °C was evaluated by means of Phenotype Microarray, modelling the kinetic data obtained by inoculating control and treated cells into GEN III microplates, after CHY removal. The results revealed differences concerning the growth dynamics in environmental conditions commonly encountered in food processing environments (different carbon sources, pH 6.0, pH 5.0, 1–8% NaCl). More specifically, for treated cells, the lag phase was extended, the growth rate was slowed down and, in most cases, the maximum concentration was diminished, suggesting the persistence of stress even after CHY removal. Confocal Laser Scanner Microscopy evidenced a diffuse aggregation and suffering of the treated cells, as a response to the stress encountered. In conclusion, the treatment with HY caused a stressing effect that persisted after its removal. The results suggest the potential of CHY application to control L. monocytogenes in food environments.

Multi-omics approaches and genetic engineering of metabolism for improved biorefinery and wastewater treatment in microalgae

Microalgae, a group of photosynthetic microorganisms rich in diverse and novel bioactive metabolites, have been explored for the production of biofuels, high value-added compounds as food and feeds, and pharmaceutical chemicals as agents with therapeutic benefits. This article reviews the development of omics resources and genetic engineering techniques including gene transformation methodologies, mutagenesis, and genome-editing tools in microalgae biorefinery and wastewater treatment. The introduction of these enlisted techniques has simplified the understanding of complex metabolic pathways undergoing microalgal cells. The multiomics approach of the integrated omics datasets, big data analysis, and machine learning for the discovery of objective traits and genes responsible for metabolic pathways was reviewed. Recent advances and limitations of multiomics analysis and genetic bioengineering technology to facilitate the improvement of microalgae as the dual role of wastewater treatment and biorefinery feedstock production are discussed. This article is protected by copyright. All rights reserved.

Data Management and Modeling in Plant Biology

The study of plant-environment interactions is a multidisciplinary research field. With the emergence of quantitative large-scale and high-throughput techniques, amount and dimensionality of experimental data have strongly increased. Appropriate strategies for data storage, management, and evaluation are needed to make efficient use of experimental findings. Computational approaches of data mining are essential for deriving statistical trends and signatures contained in data matrices. Although, current biology is challenged by high data dimensionality in general, this is particularly true for plant biology. Plants as sessile organisms have to cope with environmental fluctuations. This typically results in strong dynamics of metabolite and protein concentrations which are often challenging to quantify. Summarizing experimental output results in complex data arrays, which need computational statistics and numerical methods for building quantitative models. Experimental findings need to be combined by computational models to gain a mechanistic understanding of plant metabolism. For this, bioinformatics and mathematics need to be combined with experimental setups in physiology, biochemistry, and molecular biology. This review presents and discusses concepts at the interface of experiment and computation, which are likely to shape current and future plant biology. Finally, this interface is discussed with regard to its capabilities and limitations to develop a quantitative model of plant-environment interactions.

Large-scale genome sequencing reveals the driving forces of viruses in microalgal evolution

Being integral primary producers in diverse ecosystems, microalgal genomes could be mined for ecological insights, but representative genome sequences are lacking for many phyla. We cultured and sequenced 107 microalgae species from 11 different phyla indigenous to varied geographies and climates. This collection was used to resolve genomic differences between saltwater and freshwater microalgae. Freshwater species showed domain-centric ontology enrichment for nuclear and nuclear membrane functions, while saltwater species were enriched in organellar and cellular membrane functions. Further, marine species contained significantly more viral families in their genomes (p = 8e-4). Sequences from Chlorovirus, Coccolithovirus, Pandoravirus, Marseillevirus, Tupanvirus, and other viruses were found integrated into the genomes of algal from marine environments. These viral-origin sequences were found to be expressed and code for a wide variety of functions. Together, this study comprehensively defines the expanse of protein-coding and viral elements in microalgal genomes and posits a unified adaptive strategy for algal halotolerance.

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.

Towards model-driven characterization and manipulation of plant lipid metabolism

Plant lipids have versatile applications and provide essential fatty acids in human diet. Therefore, there has been a growing interest to better characterize the genetic basis, regulatory networks, and metabolic pathways that shape lipid quantity and composition. Addressing these issues is challenging due to context-specificity of lipid metabolism integrating environmental, developmental, and tissue-specific cues. Here we systematically review the known metabolic pathways and regulatory interactions that modulate the levels of storage lipids in oilseeds. We argue that the current understanding of lipid metabolism provides the basis for its study in the context of genome-wide plant metabolic networks with the help of approaches from constraint-based modeling and metabolic flux analysis. The focus is on providing a comprehensive summary of the state-of-the-art of modeling plant lipid metabolic pathways, which we then contrast with the existing modeling efforts in yeast and microalgae. We then point out the gaps in knowledge of lipid metabolism, and enumerate the recent advances of using genome-wide association and quantitative trait loci mapping studies to unravel the genetic regulations of lipid metabolism. Finally, we offer a perspective on how advances in the constraint-based modeling framework can propel further characterization of plant lipid metabolism and its rational manipulation.

OK, thanks! A new mutualism between Chlamydomonas and methylobacteria facilitates growth on amino acids and peptides

Nitrogen is a key nutrient for land plants and phytoplankton in terrestrial and aquatic ecosystems. The model alga Chlamydomonas reinhardtii can grow efficiently on several inorganic nitrogen sources (e.g. ammonium, nitrate, nitrite) as well as many amino acids. In this study, we show that Chlamydomonas is unable to use proline, hydroxyproline and peptides that contain these amino acids. However, we discovered that algal growth on these substrates is supported in association with Methylobacterium spp., and that a mutualistic carbon-nitrogen metabolic exchange between Chlamydomonas and Methylobacterium spp. is established. Specifically, the mineralization of these amino acids and peptides by Methylobacterium spp. produces ammonium that can be assimilated by Chlamydomonas, and CO2 photosynthetically fixed by Chlamydomonas yields glycerol that can be assimilated by Methylobacterium. As Chlamydomonas is an algal ancestor to land plants and Methylobacterium is a plant growth-promoting bacterium, this new model of mutualism may facilitate insights into the ecology and evolution of plant-bacterial interactions and design principles of synthetic ecology.

Metabolic modelling and simulation of the light and dark metabolism of Chlamydomonas reinhardtii

A metabolic network model of the green microalga Chlamydomonas reinhardtii was used to characterize photoautotrophic and heterotrophic (i.e. growth on stored compounds) growth under light and dark, respectively. The metabolic network comprised 2514 reactions distributed among nine intracellular compartments and the extracellular space. The metabolic network included all the key biochemical pathways for synthesis and metabolism of starch and triacylglycerols (TAGs). Under light and nitrogen limitation, the model simulated the accumulation of the energy-rich compounds (TAGs and starch) in the cell. In the dark, the model could simulate cell growth and maintenance on stored compounds. The model-predicted consumption rates of storage compounds (starch or TAGs) to enable growth in the dark, were found to be greater than the rates of synthesis under light. This implied utilization of the storage compounds for cell maintenance in the dark. Under constant illumination, the simulations of cell growth and intracellular starch content agreed closely with independent experimental data. In other simulations, compared with the case without photorespiration, light uptake rate increased 1.04-fold when the ratio of the rates of oxygenation and carboxylation (Rubisco) was 0.1. Although extensive experimental work exists on culture and physiology of microalgae, it does not allow quantitative predictions of the influence of dark metabolism on the productivity of metabolites to be made. This limitation is overcome using the present model. A metabolic network model of Chlamydomonas reinhardtii is shown to simulate growth and synthesis of energy-rich compounds (triacylglycerols and starch) under light. The same model also simulates dark growth and maintenance through consumption of the stored energy-rich compounds.

Advances in metabolic modeling of oleaginous microalgae

Production of biofuels and bioenergy precursors by phototrophic microorganisms, such as microalgae and cyanobacteria, is a promising alternative to conventional fuels obtained from non-renewable resources. Several species of microalgae have been investigated as potential candidates for the production of biofuels, for the most part due to their exceptional metabolic capability to accumulate large quantities of lipids. Constraint-based modeling, a systems biology approach that accurately predicts the metabolic phenotype of phototrophs, has been deployed to identify suitable culture conditions as well as to explore genetic enhancement strategies for bioproduction. Core metabolic models were employed to gain insight into the central carbon metabolism in photosynthetic microorganisms. More recently, comprehensive genome-scale models, including organelle-specific information at high resolution, have been developed to gain new insight into the metabolism of phototrophic cell factories. Here, we review the current state of the art of constraint-based modeling and computational method development and discuss how advanced models led to increased prediction accuracy and thus improved lipid production in microalgae.

Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation

Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii, a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolic network that we have reconstructed for C. reinhardtii, we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii's network in dealing with varied environmental challenges that the species may face. The defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites.

Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production

Background

Nannochloropsis salina (= Eustigmatophyceae) is a marine microalga which has become a biotechnological target because of its high capacity to produce polyunsaturated fatty acids and triacylglycerols. It has been used as a source of biofuel, pigments and food supplements, like Omega 3. Only some Nannochloropsis species have been sequenced, but none of them benefit from a genome-scale metabolic model (GSMM), able to predict its metabolic capabilities.

Results

We present iNS934, the first GSMM for N. salina, including 2345 reactions, 934 genes and an exhaustive description of lipid and nitrogen metabolism. iNS934 has a 90% of accuracy when making simple growth/no-growth predictions and has a 15% error rate in predicting growth rates in different experimental conditions. Moreover, iNS934 allowed us to propose 82 different knockout strategies for strain optimization of triacylglycerols.

Conclusions

iNS934 provides a powerful tool for metabolic improvement, allowing predictions and simulations of N. salina metabolism under different media and genetic conditions. It also provides a systemic view of N. salina metabolism, potentially guiding research and providing context to -omics data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0441-1) contains supplementary material, which is available to authorized users.

The genome and phenome of the green alga Chloroidium sp. UTEX 3007 reveal adaptive traits for desert acclimatization

To investigate the phenomic and genomic traits that allow green algae to survive in deserts, we characterized a ubiquitous species, Chloroidium sp. UTEX 3007, which we isolated from multiple locations in the United Arab Emirates (UAE). Metabolomic analyses of Chloroidium sp. UTEX 3007 indicated that the alga accumulates a broad range of carbon sources, including several desiccation tolerance-promoting sugars and unusually large stores of palmitate. Growth assays revealed capacities to grow in salinities from zero to 60 g/L and to grow heterotrophically on >40 distinct carbon sources. Assembly and annotation of genomic reads yielded a 52.5 Mbp genome with 8153 functionally annotated genes. Comparison with other sequenced green algae revealed unique protein families involved in osmotic stress tolerance and saccharide metabolism that support phenomic studies. Our results reveal the robust and flexible biology utilized by a green alga to successfully inhabit a desert coastline.

DOI:http://dx.doi.org/10.7554/eLife.25783.001

Single-celled green algae, also known as green microalgae, play an important role for the world’s ecosystems, in part, because they can harness energy from sunlight to produce carbon-rich compounds. Microalgae are also important for biotechnology and people have harnessed them to make food, fuel and medicines. Green microalgae live in many types of habitats from streams to oceans, and they can also be found on the land, including in deserts. Like plants that live in the desert, these microalgae have likely evolved specific traits that allow them to live in these hot and dry regions. Yet, fewer scientists have studied microalgae compared to land plants, and until now it was not well understood how microalgae could survive in the desert.

Nelson et al. analyzed green microalgae from different locations around the United Arab Emirates and found that one microalga, known as Chloroidium, is one of the most dominant algae in this area. This included samples from beaches, mangroves, desert oases, buildings and public fresh water sources. Chloroidium has a unique set of genes and proteins and grew particularly well in freshwater and saltwater. Rather than just harnessing sunlight, the microalgae were able to consume over 40 different varieties of carbon sources to produce energy. The microalgae also accumulated oily molecules with a similar composition to palm oil, which may help this species to survive in desert regions.

A next step will be to develop biotechnological assets based on the information obtained. In the future, microalgae could be used to make an oil that represents an alternative to palm oil; this would reduce the demand for palm tree plantations, which pose a major threat to the natural environment. Moreover, understanding how microalgae can colonize a desert region will help us to understand the effects of climate change in the region.

DOI:http://dx.doi.org/10.7554/eLife.25783.002

Algal Cell Factories: Approaches, Applications, and Potentials

With the advent of modern biotechnology, microorganisms from diverse lineages have been used to produce bio-based feedstocks and bioactive compounds. Many of these compounds are currently commodities of interest, in a variety of markets and their utility warrants investigation into improving their production through strain development. In this review, we address the issue of strain improvement in a group of organisms with strong potential to be productive “cell factories”: the photosynthetic microalgae. Microalgae are a diverse group of phytoplankton, involving polyphyletic lineage such as green algae and diatoms that are commonly used in the industry. The photosynthetic microalgae have been under intense investigation recently for their ability to produce commercial compounds using only light, CO₂, and basic nutrients. However, their strain improvement is still a relatively recent area of work that is under development. Importantly, it is only through appropriate engineering methods that we may see the full biotechnological potential of microalgae come to fruition. Thus, in this review, we address past and present endeavors towards the aim of creating productive algal cell factories and describe possible advantageous future directions for the field.

Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine.

Whole-Genome Resequencing Reveals Extensive Natural Variation in the Model Green Alga Chlamydomonas reinhardtii

We performed whole-genome resequencing of 12 field isolates and eight commonly studied laboratory strains of the model organism Chlamydomonas reinhardtii to characterize genomic diversity and provide a resource for studies of natural variation. Our data support previous observations that Chlamydomonas is among the most diverse eukaryotic species. Nucleotide diversity is ∼3% and is geographically structured in North America with some evidence of admixture among sampling locales. Examination of predicted loss-of-function mutations in field isolates indicates conservation of genes associated with core cellular functions, while genes in large gene families and poorly characterized genes show a greater incidence of major effect mutations. De novo assembly of unmapped reads recovered genes in the field isolates that are absent from the CC-503 assembly. The laboratory reference strains show a genomic pattern of polymorphism consistent with their origin as the recombinant progeny of a diploid zygospore. Large duplications or amplifications are a prominent feature of laboratory strains and appear to have originated under laboratory culture. Extensive natural variation offers a new source of genetic diversity for studies of Chlamydomonas, including naturally occurring alleles that may prove useful in studies of gene function and the dissection of quantitative genetic traits.