RNA catalysis in model protocell vesicles.

We are engaged in a long-term effort to synthesize chemical systems capable of Darwinian evolution, based on the encapsulation of self-replicating nucleic acids in self-replicating membrane vesicles. Here, we address the issue of the compatibility of these two replicating systems. Fatty acids form vesicles that are able to grow and divide, but vesicles composed solely of fatty acids are incompatible with the folding and activity of most ribozymes, because low concentrations of divalent cations (e.g., Mg(2+)) cause fatty acids to precipitate. Furthermore, vesicles that grow and divide must be permeable to the cations and substrates required for internal metabolism. We used a mixture of myristoleic acid and its glycerol monoester to construct vesicles that were Mg(2+)-tolerant and found that Mg(2+) cations can permeate the membrane and equilibrate within a few minutes. In vesicles encapsulating a hammerhead ribozyme, the addition of external Mg(2+) led to the activation and self-cleavage of the ribozyme molecules. Vesicles composed of these amphiphiles grew spontaneously through osmotically driven competition between vesicles, and further modification of the membrane composition allowed growth following mixed micelle addition. Our results show that membranes made from simple amphiphiles can form vesicles that are stable enough to retain encapsulated RNAs in the presence of divalent cations, yet dynamic enough to grow spontaneously and allow the passage of Mg(2+) and mononucleotides without specific macromolecular transporters. This combination of stability and dynamics is critical for building model protocells in the laboratory and may have been important for early cellular evolution

Experimental Definition and Validation of Protein Coding Transcripts in Chlamydomonas reinhardtii

Algal fuel sources promise unsurpassed yields in a carbon neutral manner that minimizes resource competition between agriculture and fuel crops. Many challenges must be addressed before algal biofuels can be accepted as a component of the fossil fuel replacement strategy. One significant challenge is that the cost of algal fuel production must become competitive with existing fuel alternatives. Algal biofuel production presents the opportunity to fine-tune microbial metabolic machinery for an optimal blend of biomass constituents and desired fuel molecules. Genome-scale model-driven algal metabolic design promises to facilitate both goals by directing the utilization of metabolites in the complex, interconnected metabolic networks to optimize production of the compounds of interest. Using Chlamydomonas reinhardtii as a model, we developed a systems-level methodology bridging metabolic network reconstruction with annotation and experimental verification of enzyme encoding open reading frames. We reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology. Our approach to generate a predictive metabolic model integrated with cloned open reading frames, provides a cost-effective platform to generate metabolic engineering resources. While the generated resources are specific to algal systems, the approach that we have developed is not specific to algae and can be readily expanded to other microbial systems as well as higher plants and animals

Sugar-stimulated CO2 sequestration by the green microalga Chlorella vulgaris

Post-print (lokagerð höfundar) opið á: https://systemsbiology.hi.is/wp-content/uploads/2018/11/Sugar-stimulated-CO2-sequestration-by-the-green-microalga-Chlorella-vulgaris-draft.pdfTo convert waste CO2 from flue gases of power plants into value-added products, bio-mitigation technologies show promise. In this study, we cultivated a fast-growing species of green microalgae, Chlorella vulgaris, in different sizes of photobioreactors (PBRs) and developed a strategy using small doses of sugars for enhancing CO2 sequestration under light-emitting diode illumination. Glucose supplementation at low levels resulted in an increase of photoautotrophic growth-driven biomass generation as well as CO2 capture by 10% and its enhancement corresponded to an increase of supplied photon flux. The utilization of urea instead of nitrate as the sole nitrogen source increased photoautotrophic growth by 14%, but change of nitrogen source didn't compromise glucose-induced enhancement of photoautotrophic growth. The optimized biomass productivity achieved was 30.4% higher than the initial productivity of purely photoautotrophic culture. The major pigments in the obtained algal biomass were found comparable to its photoautotrophic counterpart and a high neutral lipids productivity of 516.6 mg/(L·day) was achieved after optimization. A techno-economic model was also developed, indicating that LED-based PBRs represent a feasible strategy for converting CO2 into value-added algal biomass.This research was supported by the Icelandic Technology Development Fund, the Geothermal Research Group (GEORG) Fund and NYUAD faculty research funds (AD060).Peer Reviewe

Genome-wide functional annotation and structural verification of metabolic ORFeome of Chlamydomonas reinhardtii

<p>Abstract</p> <p>Background</p> <p>Recent advances in the field of metabolic engineering have been expedited by the availability of genome sequences and metabolic modelling approaches. The complete sequencing of the <it>C. reinhardtii</it> genome has made this unicellular alga a good candidate for metabolic engineering studies; however, the annotation of the relevant genes has not been validated and the much-needed metabolic ORFeome is currently unavailable. We describe our efforts on the functional annotation of the ORF models released by the Joint Genome Institute (JGI), prediction of their subcellular localizations, and experimental verification of their structural annotation at the genome scale.</p> <p>Results</p> <p>We assigned enzymatic functions to the translated JGI ORF models of <it>C. reinhardtii</it> by reciprocal BLAST searches of the putative proteome against the UniProt and AraCyc enzyme databases. The best match for each translated ORF was identified and the EC numbers were transferred onto the ORF models. Enzymatic functional assignment was extended to the paralogs of the ORFs by clustering ORFs using BLASTCLUST.</p> <p>In total, we assigned 911 enzymatic functions, including 886 EC numbers, to 1,427 transcripts. We further annotated the enzymatic ORFs by prediction of their subcellular localization. The majority of the ORFs are predicted to be compartmentalized in the cytosol and chloroplast. We verified the structure of the metabolism-related ORF models by reverse transcription-PCR of the functionally annotated ORFs. Following amplification and cloning, we carried out 454FLX and Sanger sequencing of the ORFs. Based on alignment of the 454FLX reads to the ORF predicted sequences, we obtained more than 90% coverage for more than 80% of the ORFs. In total, 1,087 ORF models were verified by 454 and Sanger sequencing methods. We obtained expression evidence for 98% of the metabolic ORFs in the algal cells grown under constant light in the presence of acetate.</p> <p>Conclusions</p> <p>We functionally annotated approximately 1,400 JGI predicted metabolic ORFs that can facilitate the reconstruction and refinement of a genome-scale metabolic network. The unveiling of the metabolic potential of this organism, along with structural verification of the relevant ORFs, facilitates the selection of metabolic engineering targets with applications in bioenergy and biopharmaceuticals. The ORF clones are a resource for downstream studies.</p

Chemical Mutagenesis and Fluorescence-Based High-Throughput Screening for Enhanced Accumulation of Carotenoids in a Model Marine Diatom Phaeodactylum tricornutum

Publisher's version (útgefin grein)Diatoms are a major group of unicellular algae that are rich in lipids and carotenoids. However, sustained research efforts are needed to improve the strain performance for high product yields towards commercialization. In this study, we generated a number of mutants of the model diatom Phaeodactylum tricornutum, a cosmopolitan species that has also been found in Nordic region, using the chemical mutagens ethyl methanesulfonate (EMS) and N-methyl-N′-nitro-N-nitrosoguanidine (NTG). We found that both chlorophyll a and neutral lipids had a significant correlation with carotenoid content and these correlations were better during exponential growth than in the stationary growth phase. Then, we studied P. tricornutum common metabolic pathways and analyzed correlated enzymatic reactions between fucoxanthin synthesis and pigmentation or lipid metabolism through a genome-scale metabolic model. The integration of the computational results with liquid chromatography-mass spectrometry data revealed key compounds underlying the correlative metabolic pathways. Approximately 1000 strains were screened using fluorescence-based high-throughput method and five mutants selected had 33% or higher total carotenoids than the wild type, in which four strains remained stable in the long term and the top mutant exhibited an increase of 69.3% in fucoxanthin content compared to the wild type. The platform described in this study may be applied to the screening of other high performing diatom strains for industrial applications.This research was supported by the Icelandic Technology Development Fund with Grant No. 163922-0611, Landsvirkjun Energy Research Fund and NYUAD faculty research funds (AD060).Peer Reviewe

An integrative Raman microscopy-based workflow for rapid in situ analysis of microalgal lipid bodies

Additional file 1. Schematic diagram of Raman imaging technique

A systematic approach to identify host targets and rapidly deliver broad-spectrum antivirals.

peer reviewe

Combined artificial high-silicate medium and LED illumination promote carotenoid accumulation in the marine diatom Phaeodactylum tricornutum

Publisher's version (útgefin grein).Background: Diatoms, which can accumulate large amounts of carotenoids, are a major group of microalgae and the dominant primary producer in marine environments. Phaeodactylum tricornutum, a model diatom species, acquires little silicon for its growth although silicon is known to contribute to gene regulation and play an important role in diatom intracellular metabolism. In this study, we explored the effects of artificial high-silicate medium (i.e. 3.0 mM sodium metasilicate) and LED illumination conditions on the growth rate and pigment accumulation in P.Tricornutum, which is the only known species so far that can grow without silicate. It's well known that light-emitting diodes (LEDs) as novel illuminants are emerging to be superior monochromatic light sources for algal cultivation with defined and efficient red and blue lights. Results: Firstly, we cultivated P.Tricornutum in a synthetic medium supplemented with either 0.3 mM or 3.0 mM silicate. The morphology and size of diatom cells were examined: The proportion of the oval and triradiate cells decreased while the fusiform cells increased with more silicate addition in high-silicate medium; the average length of fusiform cells also slightly changed from 14.33 μm in 0.3 mM silicate medium to 12.20 μm in 3.0 mM silicate medium. Then we cultivated P.Tricornutum under various intensities of red light in combination with the two different levels of silicate in the medium. Higher biomass productivity also achieved in 3.0 mM silicate medium than in 0.3 mM silicate medium under red LED light irradiation at 128 μmol/m2/s or higher light intensity. Increasing silicate reversed the down-regulation of fucoxanthin and chlorophyll a under high red-light illumination (i.e. 255 μmol/m2/s). When doubling the light intensity, fucoxanthin content decreased under red light but increased under combined red and blue (50:50) lights while chlorophyll a content reduced under both conditions. Fucoxanthin accumulation and biomass productivity increased with enhanced red and blue (50:50) lights. Conclusion: High-silicate medium and blue light increased biomass and fucoxanthin production in P.Tricornutum under high light conditions and this strategy may be beneficial for large-scale production of fucoxanthin in diatoms.This research was supported by the Icelandic Technology Development Fund (163922-0611), Landsvirkjun Energy Research Fund and NYU Abu Dhabi faculty research funds (AD060).Peer Reviewe

Enhancing algal production strategies: strain selection, AI-informed cultivation, and mutagenesis

Microalgae are emerging as a sustainable source of bioproducts, including food, animal feed, nutraceuticals, and biofuels. This review emphasizes the need to carefully select suitable species and highlights the importance of strain optimization to enhance the feasibility of developing algae as a sustainable resource for food and biomaterial production. It discusses microalgal bioprospecting methods, different types of cultivation systems, microalgal biomass yields, and cultivation using wastewater. The paper highlights advances in artificial intelligence that can optimize algal productivity and overcome the limitations faced in current microalgal industries. Additionally, the potential of UV mutagenesis combined with high-throughput screening is examined as a strategy for generating improved strains without introducing foreign genetic material. The necessity of a multifaceted optimization approach for enhanced productivity is acknowledged. This review provides an overview of recent developments crucial for the commercial success of microalgal production