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Microalgae are unicellular microscopic and photosynthetic organisms. They are found all over the planet and in all sorts of environments. Their role has been and is still very important for the planet, most notably that they are currently accounted for producing half of the atmospheric oxygen. While they used to be studied because of their capabilities to depollute water, the interests have shifted towards oleaginous microalgae and their high level of fatty-acids accumulation. Fatty-acids such as Triacylglycerides (TAG) are of particular interest for their easy chemical treatment to produce clean biodiesel. Even if microalgae have higher energy conversion efficiency than plants, do not need arable lands to grow on, and do not compete with feed production, the optimal conditions of production are still too costly to compete with fossil fuel pricing. To decrease production costs, growth conditions and the physiological efficiency of the microalgae needs to be optimized. This requires a deep understanding of the microalgae phenotype in the relevant growth conditions. A phenotype represents a set of behavioral traits of an organism In this thesis, the internal phenotype, the transcriptional landscape of two oleaginous microalgae species was studied using different growth conditions. The RNA content was chosen because it provides a dynamic system-wide view, can be done in high-throughput and, as proxy, can inform about the cellular and metabolic activities in response to a changing environment.
To analyze the transcriptome, it is necessary to know the functions of the transcripts. In contrast to model organisms like human or Arabidopsis thaliana whose genomes have been deeply annotated and studied, microalgae are far from that state. For both organisms studied in this thesis, Neochloris oleoabundans and Tetradesmus obliquus, it was necessary to annotate the genes and transcripts since it was never done before. To functionally annotate a gene, most methods rely on sequence similarities to identify the closest gene in known organisms. Green algae are a difficult case due to the large genetic distance between them and the greater distance to reference organisms from land plants. Chapter 2 treats about the particular problem of protein annotation in microalgae. I analyzed the general state of data availability in microalgae, and we discussed about several annotation methods that are better suited than sequence similarity and discussed the limitations of using domain-based recognition methods. Besides, we also discussed the identification of the protein localization within the different subcellular compartment in microalgae. Finally, we stressed the importance of a large-scale wet-lab efforts for a few selected microalgae in order to provide a solid foundation for computation based methods.
To obtain more insight into the metabolism of Ettlia oleoabundans in Chapter 3 , a constraint-based metabolic model of Ettlia oleoabundans was built around the central carbon metabolism. This model was built based on the knowledge of central metabolism of algae at that moment and was cross checked with the de novo assembled annotated transcriptome. Experiments in controlled turbidostat were conducted in different combinations of light intensity and nitrogen supply. The measurements from the experimental conditions were used as constraints on the inputs and outputs of the model, effectively allowing us to estimate the metabolic flux distributions. In addition, RNA samples from the different experimental conditions were sequenced and analyzed. These data were used to validate the model structure as stated before, correlate expression levels with flux distributions and get a better understanding of the effect of light and nutrient conditions on algal physiology. The metabolic model calculates a maximum TAG yield of N. oleoabundans on light of 1.06 g (mol photons)-1, more than 3 times the current experimental yield under optimal conditions. The model also shows that TAG yield on light can be more efficiently improved by optimizing photosynthetic conversion than by blocking competing pathways. Geranylgeranyl diphosphate reductase was identified as a potential regulator for photosynthetic capability that complements the fine-tuning of chlorophyll levels from synthesis and degradation. Finally, we identified some key reactions that could be targeted to improve TAG yield, by not only specifically increasing the flux within the lipids and TAG pathways, but also potentially redirect carbons from other pathways.
Water is a precious resource, and using fresh drinkable water to grow plants or microalgae could be considered non sustainable. However, salt-water is abundantly available and would be cheaper to supply. Therefore it is important to understand how algae deal with a salt water environment under growth and production conditions. This allowed us in Chapter 4 to study how algae deal with high salinity conditions under nitrogen replete (growth) and nitrogen deplete (TAG accumulation) conditions using a transcriptomics approach. The oleaginous microalgae, Ettlia oleoabundans (formally known as Neochloris oleoabundans) was chosen as a model algae, since it can accumulate large amounts of TAG and can grow in both fresh and salt-water. For this algae experiments were done in fresh water and salt water in combination with nitrogen replete and nitrogen deplete conditions. In addition to the transcriptome, we analyzed the biomass composition including TAG and starch accumulation and used the data to look into different salt resistance mechanisms. We found that Proline and the ascorbate-glutathione cycle seem to be of importance for successful osmoregulation in N. oleoabundans. Genes involved in Proline biosynthesis were found to be upregulated in salt water, which is supported by Nuclear magnetic resonance (NMR) spectroscopy. Oil accumulation is increased under nitrogen-deplete conditions in a comparable way in both fresh and salt water. The mechanism behind the biosynthesis of compatible osmolytes can be used to improve N. oleoabundans and other industrially relevant microalgal strains to create a more robust and sustainable production platform for microalgae derived products in the future.
Although the TAG content that can be reached in Ettlia oleoabundans is high, the volumetric TAG productivity in Tetradesmus obliquus was evaluated to be clearly higher, while reaching the same TAG content. This was mainly due to the ability of T. obliquus to maintain photosynthetic efficiency for a longer time longer during the nitrogen depletion phase. Therefore, it was decided to switch to T. obliquus as a model organism. To obtain an idea of the capabilities of T. obliquus and to make transcriptome experiments easier to analyze, the genome of T. obliquus was sequenced. In Chapter 5 , the sequencing of the genome of T. obliquus is presented. The assembly approach was unconventional by combining two different methods and was able to combine the higher coverage from one method with the precision of the other method. In this way, the coverage and the accuracy of the assembly was maximized.
Production using microalgae will in many cases occur outdoors using sunlight. Consequently the algae will be exposed to the naturally occurring day night cycle. To better understand the effect of these day night cycles, in Chapters 6 and 7, the transcriptional response of algae to diurnal cycles was studied under nitrogen replete conditions and nitrogen limiting conditions for the wild type and a mutant that can not synthesize starch. In Chapter 6 , hourly samples of RNA of Tetradesmus obliquus UTEX 393 were taken from a turbidostat culture operated under nitrogen replete conditions over a diurnal cycle of 16 hour light and 8 hours dark, to obtain more insight in in the transcriptional response towards diurnal cycles. In addition, to understand the effects of a lack of starch, the major transient energy storage, we sequenced samples of the starchless mutant slm1 that were collected every three hours under the same conditions. At the same time, samples were collected and measurements of the biochemical composition of biomass and the specific light absorption rate were performed. These data are presented in a previously published article . The genome features were annotated using more than 38 RNA-seq samples from this study, using a specially developed extension of the FAIR principle based framework called SAPP. The work done to extend this framework for transcriptome analysis is described in the discussion Chapter 8 . We described the succession of metabolic events that occurred during the diurnal cycle, which are in agreement with the biochemical measurements. Comparing the wild-type with the starchless mutant slm1, we found a few temporal shifts in expression that reflect transcriptional adaptation to the lack of a transient energy storage compound during the dark period. Our study provides new perspectives on the role of starch and the adaptation to LD cycles of oleaginous microalgae.
In Chapter 7 a similar experimental approach was taken, where samples were taken for biochemical and transcriptome analysis every 3 hours from a turbidostat culture operated at the same diurnal cycle of 16 hours light and 8 hours dark, but this time in nitrogen limiting conditions, resulting in TAG accumulation. Again this was done for the wild type and the starchless mutant. The transcriptional landscape and biochemical data are compared to the nitrogen replete condition in Chapter 6 , to evaluate the effect of nitrogen limitation in general and study how the lack of starch is affecting TAG accumulation under nitrogen limiting conditions. We observed that the cycling diurnal effect is greatly reduced in comparison to nitrogen replete condition. The wild-type accumulated more starch than in nitrogen replete condition (Chapter 6 ), and small oscillation was observed, indicating that it is being used as transient energy storage during the dark period. While the biochemical analysis did not reveal any oscillation in total lipids content in either strain, slm1 over-expresses transcripts associated to TAG and lipid degradation during the dark period. Besides, while slm1 accumulated more TAG than the wild-type, its conversion efficiency was only half of the wild-type. It appears also that the organism recycles more proteins during the dark period to supply nitrogen for the strong increase in amino acid synthesis right after light is turned on.
In Chapter 8 , the results of this thesis are discussed. The interest in analyzing the transcriptome of microalgae is explained. Then, the annotation methods are explained to show the large improvements between them, and could it still be improved. Basic numbers of the later annotation results are compared to the current status in UniProtKB. Particular points from the transcriptomics data are discussed, notably the expression of the mutant gene responsible for slm1 phenotype, and the interests from using single-cell technologies. Suggestions are then made to improve the experimental conditions and the photobioreactors setups. The efforts made in the thesis to generate and store the data according to the FAIR principles are explained. Finally, using the knowledge acquired during this thesis, suggestions are made to improve the growth conditions and to improve TAG production with divers metabolic engineering strategies. The work of this thesis contributes for the future of sustainable production of biofuels, which ultimately will help alleviating human society’s dependence on fossil fuels.
|Qualification||Doctor of Philosophy|
|Award date||20 Nov 2019|
|Place of Publication||Wageningen|
|Publication status||Published - 2019|
- biobased economy
- diurnal activity