From systems biology to fuel—Chlamydomonas reinhardtii as a model for a systems biology approach to improve biohydrogen production

Enhancing strategies of photosynthetic hydrogen production from microalgae: Differences in hydrogen production between prokaryotic and eukaryotic algae

Hydrogen production through the metabolic bypass of microalgae photosynthesis is an environmentally friendly method. This review examines the genetic differences in hydrogen production between prokaryotic and eukaryotic microalgae. Additionally, the pathways for enhancing microalgae-based photosynthetic hydrogen generation are summarized. The main strategies for enhancing microalgal hydrogen production involve inhibiting the oxygen-generating process of photosynthesis and promoting the oxygen tolerance of hydrogenase. Future research is needed to explore the regulation of physiological metabolism through quorum sensing in microalgae to enhance photosynthetic hydrogen production. Moreover, effective evaluation of carbon emissions and sequestration across the entire photosynthetic hydrogen production process is crucial for determining the sustainability of microalgae-based production approaches through comprehensive lifecycle assessment. This review elucidates the prospects and challenges associated with photosynthetic hydrogen production by microalgae.

Efficient supply with carbon dioxide from flue gas during large scale production of microalgae: A novel approach for bioenergy facades

The efficiency of using enriched CO2 from flue gas for large scale production of the green microalgae Chlorella sorokiniana in a bioenergy facade was studied. Using a membrane device, the enrichment of CO2 from heating system flue gas in the low pressure product gas was up to 49 vol% and the CO2 recovery was 62 %. With a static mixer the re-compressed product gas was applied to the culture medium with mean losses during cultivation of only 24 %. Thereby the pH could be maintained at a mean of 6.2 and a temperature always below 28 °C, both optimal for growth of Chlorella sorokiniana. Although PAR solar radiation during midday always exceeded 1000 µmol m-2 s-1 mean photosynthetic efficiency was 0.54 g mol-1. Results indicate that the chosen approach for CO2 supply overcomes the problem of CO2 losses and allows for a more economic and sustainable microalgae production in a bioenergy facade.

Natural variation of nutrient homeostasis among laboratory and field strains of Chlamydomonas reinhardtii

Natural variation among individuals and populations exists in all species, playing key roles in response to environmental stress and adaptation. Micro- and macronutrients have a wide range of functions in photosynthetic organisms, and mineral nutrition thus plays a sizable role in biomass production. To maintain nutrient concentrations inside the cell within physiological limits and prevent the detrimental effects of deficiency or excess, complex homeostatic networks have evolved in photosynthetic cells. The microalga Chlamydomonas reinhardtii (Chlamydomonas) is a unicellular eukaryotic model for studying such mechanisms. In this work, 24 Chlamydomonas strains, comprising field isolates and laboratory strains, were examined for intraspecific differences in nutrient homeostasis. Growth and mineral content were quantified in mixotrophy, as full nutrition control, and compared with autotrophy and nine deficiency conditions for macronutrients (-Ca, -Mg, -N, -P, and -S) and micronutrients (-Cu, -Fe, -Mn, and -Zn). Growth differences among strains were relatively limited. However, similar growth was accompanied by highly divergent mineral accumulation among strains. The expression of nutrient status marker genes and photosynthesis were scored in pairs of contrasting field strains, revealing distinct transcriptional regulation and nutrient requirements. Leveraging this natural variation should enable a better understanding of nutrient homeostasis in Chlamydomonas.

Characterization of homogenous acid catalyzed biodiesel production from palm oil: experimental investigation and numerical simulation

Biodiesel is a biological renewable source produced from the conversion of triglycerides to alkyl esters. Palm oil is one of the most used lipid feedstocks for biodiesel production. It becomes necessary to optimize the transesterification reaction parameters to reduce the cost and enhance the quality of biodiesel. This study focuses on the use of homogenous sulfuric acid as a catalyst for the transesterification of palm fatty acids to methyl esters in a batch-scale reactor. A novel examination of transesterification reaction input parameters using the technique for order performance by similarity to ideal solution optimization technique and the effect of these parameters on yield, viscosity, and density of palm biodiesel using 3D surface graphs is investigated in this research. The present optimization approach is implemented to find out the optimum ranking of biodiesel production. From the experimental and numerical simulation, optimum results were observed at the catalyst concentration of 6% (w/w), reaction temperature of 70 °C, the reaction time of 120 min, and alcohol to oil molar ratio of 30:1 at which yield of 95.35%, viscosity of 5.0 cSt, and density of 880 kg/m³ of palm biodiesel were obtained. The different physicochemical properties of produced palm methyl esters are obtained within standards set by international authorities. Selected optimized process parameters can be used for commercial-scale biodiesel production.

Multiomics and optobiotechnological approaches for the development of microalgal strain for production of aviation biofuel and biorefinery

Demand and consumption of fossil fuels is increasing daily, and oil reserves are depleting. Technological developments are required towards developing sustainable renewable energy sources and microalgae are emerging as a potential candidate for various application-driven research. Molecular understanding attained through omics and system biology approach empowering researchers to modify various metabolic pathways of microalgal system for efficient extraction of biofuel and important biomolecules. This review furnish insight into different "advanced approaches" like optogenetics, systems biology and multi-omics for enhanced production of FAS (Fatty Acid Synthesis) and lipids in microalgae and their associated challenges. These new approaches would be helpful in the path of developing microalgae inspired technological platforms for optobiorefinery, which could be explored as source material to produce biofuels and other valuable bio-compounds on a large scale.

Systems biology–the transformative approach to integrate sciences across disciplines

Life science is the study of living organisms, including bacteria, plants, and animals. Given the importance of biology, chemistry, and bioinformatics, we anticipate that this chapter may contribute to a better understanding of the interdisciplinary connections in life science. Research in applied biological sciences has changed the paradigm of basic and applied research. Biology is the study of life and living organisms, whereas science is a dynamic subject that as a result of constant research, new fields are constantly emerging. Some fields come and go, whereas others develop into new, well-recognized entities. Chemistry is the study of composition of matter and its properties, how the substances merge or separate and also how substances interact with energy. Advances in biology and chemistry provide another means to understand the biological system using many interdisciplinary approaches. Bioinformatics is a multidisciplinary or rather transdisciplinary field that encourages the use of computer tools and methodologies for qualitative and quantitative analysis. There are many instances where two fields, biology and chemistry have intersection. In this chapter, we explain how current knowledge in biology, chemistry, and bioinformatics, as well as its various interdisciplinary domains are merged into life sciences and its applications in biological research.

Microalgae role in sustainable bioenergy generation as determined by light microscopy

The main aim of this study was to explore the role of light microscopy in the identification of microalgae as a source of study. Three microalgal species (Nostoc, Anabaena, and Volvox) were identified by light. In this study, different parameters of the oil extraction process from algae biomass were studied. The samples of Nostoc, Anabaena, and Volvox were collected from the freshwater bodies in Lahore, and the samples were identified by light microscopy. Pretreatment of algae was done which includes harvesting, drying, and grinding. The sun drying of sample was done. Solvent extraction was done for the extraction of oil from algal cells. Solvent n-hexane and diethyl ether were used alone as well as in combination. Effects of n-hexane to oil ratio, size of algal biomass, and contact time on the percentage yield of extracted oil were studied and analyzed. It was concluded that maximum amount of oil was extracted from algae by using a greater ratio of solvent to algal biomass, maximum contact time, and smaller algal biomass size. The extracted oil yield was satisfactory, demonstrating the potential of microalgae for biodiesel production. It was discovered that if algal oil is subjected to transesterification, it can be turned into biodiesel, and light microscopy can be used to assess anatomical characteristics. However, more research will be required for transesterification.

FPGA-Based Implementation of an Optimization Algorithm to Maximize the Productivity of a Microbial Electrolysis Cell

In this work, the design of the hardware architecture to implement an algorithm for optimizing the Hydrogen Productivity Rate (HPR) in a Microbial Electrolysis Cell (MEC) is presented. The HPR in the MEC is maximized by the golden section search algorithm in conjunction with a super-twisting controller. The development of the digital architecture in the implementation step of the optimization algorithm was developed in the Very High Description Language (VHDL) and synthesized in a Field Programmable Gate Array (FPGA). Numerical simulations demonstrated the feasibility of the proposed optimization strategy embedded in an FPGA Cyclone II. Results showed that only 21% of the total logic elements, 5.19% of dedicated logic registers, and 64% of the total eight-bits multipliers of the FPGA were used. On the other hand, the estimated power consumption required by the FPGA-embedded optimization algorithm was only 146 mW.

Comparative analysis of Chlorosarcinopsis eremi mitochondrial genome with some Chlamydomonadales algae

Chlorosarcinopsis eremi is a member of Chlamydomonadales algae which is isolated from terrestrial environments. In this study, the mitochondrial genome of C. eremi isolated from desert region of Iran, was represented for the first time. Following sequencing, assembly and annotation, comparative analyses of C. eremi and other available Chlamydomonadales algae complete mitochondrial genomes were performed. The mitochondrial genome of C. eremi was circular, had a low number of genes coding in the same strand with a minor amount of repeated sequences; same as other non-Reinhardtinia species of Chlamydomonadales algae. GC content of C. eremi mitochondrial genome was in normal range when compared with non-Chlamydomonadales organisms, but among Chlamydomonadales algae, C. eremi had a low GC content mitochondrial genome. C. eremi had the highest percent of non-coding sequences in comparison with other available Chlamydomonadales mitochondrial genomes which was related to intergenic regions. Identity analysis of protein-coding sequences of Chlamydomonadales mitochondrial genomes showed more divergences and may be related to the high mutation rate of mitochondrial genome reported in microbial eukaryotes.

pH effects on the lipid and fatty acids accumulation in Chlamydomonas reinhardtii

pH variations influence the delivery of essential nutrients and CO₂ solubility, which impact algae metabolism. In this study the microalgal growth and chlorophyll, lipid, and fatty acids content; along with the expression of some genes implicated in the biosynthesis of lipids were examined in Chlamydomonas reinhardtii subjected to pH values of 7.0, 7.8, and 8.5. At pH 7.8 an increase in cell growth was observed with a significant accumulation of chlorophyll (1.75-fold) when compared with growth at pH 7, while at pH 8.5 a sharp decrease in both parameters was observed when compared with the other pH values tested. Lipid content increased 3.0 (14.81% of dry cell weight, dcw) and 2.3 times (11.43% dcw) at pH 7.8 and 8.5, respectively, when compared with the experiment at pH 7 (4.97% dcw). The compositions of major fatty acids in the strains growing at pH 7.0, 7.8, or 8.5 were 25.7, 28.0, and 32.1% for palmitic acid; 17.3, 14.7, and 25.7% for oleic acid; and 9.8, 12.1, and 4.6% for linoleic acid; respectively. qRT-PCR analysis showed that the transcripts of ß-carboxyltransferase, Acyl carrier protein 1, acyl-ACP thiolase 1, acyl-sn-glycerol-3-phosphate acyltransferase, and diacylglycerol acyl transferase isoform 3 were significantly induced at pH 7.8 when compared with the other two pH conditions. These results indicate that the induction of genes implicated in the early and final steps of lipid biosynthesis contributes to their accumulation in the stationary phase. Our research suggests that a pH of 7.8 might be ideal to maximize growth and lipid accumulation.

Development of a Chlamydomonas reinhardtii metabolic network dynamic model to describe distinct phenotypes occurring at different CO2 levels

The increase in atmospheric CO2 due to anthropogenic activities is generating climate change, which has resulted in a subsequent rise in global temperatures with severe environmental impacts. Biological mitigation has been considered as an alternative for environmental remediation and reduction of greenhouse gases in the atmosphere. In fact, the use of easily adapted photosynthetic organisms able to fix CO2 with low-cost operation is revealing its high potential for industry. Among those organism, the algae Chlamydomonas reinhardtii have gain special attention as a model organism for studying CO2 fixation, biomass accumulation and bioenergy production upon exposure to several environmental conditions. In the present study, we studied the Chlamydomonas response to different CO2 levels by comparing metabolomics and transcriptomics data with the predicted results from our new-improved genomic-scale metabolic model. For this, we used in silico methods at steady dynamic state varying the levels of CO2. Our main goal was to improve our capacity for predicting metabolic routes involved in biomass accumulation. The improved genomic-scale metabolic model presented in this study was shown to be phenotypically accurate, predictive, and a significant improvement over previously reported models. Our model consists of 3726 reactions and 2436 metabolites, and lacks any thermodynamically infeasible cycles. It was shown to be highly sensitive to environmental changes under both steady-state and dynamic conditions. As additional constraints, our dynamic model involved kinetic parameters associated with substrate consumption at different growth conditions (i.e., low CO2-heterotrophic and high CO2-mixotrophic). Our results suggest that cells growing at high CO2 (i.e., photoautotrophic and mixotrophic conditions) have an increased capability for biomass production. In addition, we have observed that ATP production also seems to be an important limiting factor for growth under the conditions tested. Our experimental data (metabolomics and transcriptomics) and the results predicted by our model clearly suggest a differential behavior between low CO2-heterotrophic and high CO2-mixotrophic growth conditions. The data presented in the current study contributes to better dissect the biological response of C. reinhardtii, as a dynamic entity, to environmental and genetic changes. These findings are of great interest given the biotechnological potential of this microalga for CO2 fixation, biomass accumulation, and bioenergy production.

Photobiological hydrogen production via immobilization: understanding the nature of the immobilization and investigation on various conventional photobioreactors

Hydrogen photoproduction from microalgae has been an emerging topic for biofuel development. However, low yield for large-scale cultivations seems to be the main challenge. Immobilization seems to be an alternative method for sustainable hydrogen generation. In this study we examined the bead stability, bead diameter and immobilization method in accordance with photobioreactors (PBR). 2.1 mm diameter beads were selected for PBR experiments. CSTR, tubular and panel type PBRs give important results to develop suitable immobilization matrixes and techniques for mass production in scalable PBR systems. In conclusion, we suggest to develop techniques specific for the design and operation characteristic of the PBR for a yield efficient hydrogen generation.

Algal Cell Response to Pulsed Waved Stimulation and Its Application to Increase Algal Lipid Production

Generating renewable energy while sequestering CO₂ using algae has recently attracted significant research attention, mostly directing towards biological methods such as systems biology, genetic engineering and bio-refining for optimizing algae strains. Other approaches focus on chemical screening to adjust culture conditions or culture media. We report for the first time the physiological changes of algal cells in response to a novel form of mechanical stimulation, or a pulsed wave at the frequency of 1.5 MHz and the duty cycle of 20%. We studied how the pulsed wave can further increase algal lipid production on top of existing biological and chemical methods. Two commonly used algal strains, fresh-water Chlorella vulgaris and seawater Tetraselmis chuii, were selected. We have performed the tests in shake flasks and 1 L spinner-flask bioreactors. Conventional Gravimetric measurements show that up to 20% increase for algal lipid could be achieved after 8 days of stimulation. The total electricity cost needed for the stimulations in a one-liter bioreactor is only one-tenth of a US penny. Gas liquid chromatography shows that the fatty acid composition remains unchanged after pulsed-wave stimulation. Scanning electron microscope results also suggest that pulsed wave stimulation induces shear stress and thus increases algal lipid production.

Implementation of photobiological H2 production: the O 2 sensitivity of hydrogenases

The search for the ultimate carbon-free fuel has intensified in recent years, with a major focus on photoproduction of H2. Biological sources of H2 include oxygenic photosynthetic green algae and cyanobacteria, both of which contain hydrogenase enzymes. Although algal and cyanobacterial hydrogenases perform the same enzymatic reaction through metallo-clusters, their hydrogenases have evolved separately, are expressed differently (transcription of algal hydrogenases is anaerobically induced, while bacterial hydrogenases are constitutively expressed), and display different sensitivity to O2 inactivation. Among various physiological factors, the sensitivity of hydrogenases to O2 has been one of the major factors preventing implementation of biological systems for commercial production of renewable H2. This review addresses recent strategies aimed at engineering increased O2 tolerance into hydrogenases (as of now mainly unsuccessful), as well as towards the development of methods to bypass the O2 sensitivity of hydrogenases (successful but still yielding low solar conversion efficiencies). The author concludes with a description of current approaches from various laboratories to incorporate multiple genetic traits into either algae or cyanobacteria to jointly address limiting factors other than the hydrogenase O2 sensitivity and achieve more sustained H2 photoproduction activity.

Generation of Viable Plant-Vertebrate Chimeras

The extreme dependence on external oxygen supply observed in animals causes major clinical problems and several diseases are related to low oxygen tension in tissues. The vast majority of the animals do not produce oxygen but a few exceptions have shown that photosynthetic capacity is physiologically compatible with animal life. Such symbiotic photosynthetic relationships are restricted to a few aquatic invertebrates. In this work we aimed to explore if we could create a chimerical organism by incorporating photosynthetic eukaryotic cells into a vertebrate animal model. Here, the microalgae Chlamydomonas reinhardtii was injected into zebrafish eggs and the interaction and viability of both organisms were studied. Results show that microalgae were distributed into different tissues, forming a fish-alga chimera organism for a prolonged period of time. In addition, microscopic observation of injected algae, in vivo expression of their mRNA and re-growth of the algae ex vivo suggests that they survived to the developmental process, living for several days after injection. Moreover microalgae did not trigger a significant inflammatory response in the fish. This work provides additional evidence to support the possibility that photosynthetic vertebrates can be engineered.

Algae after dark: mechanisms to cope with anoxic/hypoxic conditions

Chlamydomonas reinhardtii is a unicellular, soil-dwelling (and aquatic) green alga that has significant metabolic flexibility for balancing redox equivalents and generating ATP when it experiences hypoxic/anoxic conditions. The diversity of pathways available to ferment sugars is often revealed in mutants in which the activities of specific branches of fermentative metabolism have been eliminated; compensatory pathways that have little activity in parental strains under standard laboratory fermentative conditions are often activated. The ways in which these pathways are regulated and integrated have not been extensively explored. In this review, we primarily discuss the intricacies of dark anoxic metabolism in Chlamydomonas, but also discuss aspects of dark oxic metabolism, the utilization of acetate, and the relatively uncharacterized but critical interactions that link chloroplastic and mitochondrial metabolic networks.

Characterization of Hydrogen Metabolism in the Multicellular Green Alga Volvox carteri

Hydrogen gas functions as a key component in the metabolism of a wide variety of microorganisms, often acting as either a fermentative end-product or an energy source. The number of organisms reported to utilize hydrogen continues to grow, contributing to and expanding our knowledge of biological hydrogen processes. Here we demonstrate that Volvox carteri f. nagariensis, a multicellular green alga with differentiated cells, evolves H₂ both when supplied with an abiotic electron donor and under physiological conditions. The genome of Volvox carteri contains two genes encoding putative [FeFe]-hydrogenases (HYDA1 and HYDA2), and the transcripts for these genes accumulate under anaerobic conditions. The HYDA1 and HYDA2 gene products were cloned, expressed, and purified, and both are functional [FeFe]-hydrogenases. Additionally, within the genome the HYDA1 and HYDA2 genes cluster with two putative genes which encode hydrogenase maturation proteins. This gene cluster resembles operon-like structures found within bacterial genomes and may provide further insight into evolutionary relationships between bacterial and algal [FeFe]-hydrogenase genes.

Magnetic separation of algae genetically modified for increased intracellular iron uptake

Algae were investigated in the past as a potential source of biofuel and other useful chemical derivatives. Magnetic separation of algae by iron oxide nanoparticle binding to cells has been proposed by others for dewatering of cellular mass prior to lipid extraction. We have investigated feasibility of magnetic separation based on the presence of natural iron stores in the cell, such as the ferritin in Auxenochlorella protothecoides (A. p.) strains. The A. p. cell constructs were tested for inserted genes and for increased intracellular iron concentration by inductively coupled plasma atomic absorption (ICP-AA). They were grown in Sueoka's modified high salt media with added vitamin B1 and increasing concentration of soluble iron compound (FeCl₃ EDTA, from 1× to 8× compared to baseline). The cell magnetic separation conditions were tested using a thin rectangular flow channel pressed against interpolar gaps of a permanent magnet forming a separation system of a well-defined fluid flow and magnetic fringing field geometry (up to 2.2 T and 1,000 T/m) dubbed "magnetic deposition microscopy", or MDM. The presence of magnetic cells in suspension was detected by formation of characteristic deposition bands at the edges of the magnet interpolar gaps, amenable to optical scanning and microscopic examination. The results demonstrated increasing cellular Fe uptake with increasing Fe concentration in the culture media in wild type strain and in selected genetically-modified constructs, leading to magnetic separation without magnetic particle binding. The throughput in this study is not sufficient for an economical scale harvest.

Microalgae as sustainable renewable energy feedstock for biofuel production

The world energy crisis and increased greenhouse gas emissions have driven the search for alternative and environmentally friendly renewable energy sources. According to life cycle analysis, microalgae biofuel is identified as one of the major renewable energy sources for sustainable development, with potential to replace the fossil-based fuels. Microalgae biofuel was devoid of the major drawbacks associated with oil crops and lignocelluloses-based biofuels. Algae-based biofuels are technically and economically viable and cost competitive, require no additional lands, require minimal water use, and mitigate atmospheric CO₂. However, commercial production of microalgae biodiesel is still not feasible due to the low biomass concentration and costly downstream processes. The viability of microalgae biodiesel production can be achieved by designing advanced photobioreactors, developing low cost technologies for biomass harvesting, drying, and oil extraction. Commercial production can also be accomplished by improving the genetic engineering strategies to control environmental stress conditions and by engineering metabolic pathways for high lipid production. In addition, new emerging technologies such as algal-bacterial interactions for enhancement of microalgae growth and lipid production are also explored. This review focuses mainly on the problems encountered in the commercial production of microalgae biofuels and the possible techniques to overcome these difficulties.

A millifluidic study of cell-to-cell heterogeneity in growth-rate and cell-division capability in populations of isogenic cells of Chlamydomonas reinhardtii

To address possible cell-to-cell heterogeneity in growth dynamics of isogenic cell populations of Chlamydomonas reinhardtii, we developed a millifluidic drop-based device that not only allows the analysis of populations grown from single cells over periods of a week, but is also able to sort and collect drops of interest, containing viable and healthy cells, which can be used for further experimentation. In this study, we used isogenic algal cells that were first synchronized in mixotrophic growth conditions. We show that these synchronized cells, when placed in droplets and kept in mixotrophic growth conditions, exhibit mostly homogeneous growth statistics, but with two distinct subpopulations: a major population with a short doubling-time (fast-growers) and a significant subpopulation of slowly dividing cells (slow-growers). These observations suggest that algal cells from an isogenic population may be present in either of two states, a state of restricted division and a state of active division. When isogenic cells were allowed to propagate for about 1000 generations on solid agar plates, they displayed an increased heterogeneity in their growth dynamics. Although we could still identify the original populations of slow- and fast-growers, drops inoculated with a single progenitor cell now displayed a wider diversity of doubling-times. Moreover, populations dividing with the same growth-rate often reached different cell numbers in stationary phase, suggesting that the progenitor cells differed in the number of cell divisions they could undertake. We discuss possible explanations for these cell-to-cell heterogeneities in growth dynamics, such as mutations, differential aging or stochastic variations in metabolites and macromolecules yielding molecular switches, in the light of single-cell heterogeneities that have been reported among isogenic populations of other eu- and prokaryotes.

Flow rate and duty cycle effects in lysis of Chlamydomonas reinhardtii using high-energy pulsed focused ultrasound

To consider microalgae lipid biofuel as a viable energy source, it is a necessity to maximize algal cell lysis, lipid harvest, and thus biofuel production versus the energy used to lyse the cells. Previous techniques have been to use energy consumptive ultrasound waves in the 10-40 kHz range in a stationary exposure environment. This study evaluated the potential of using 1.1 MHz ultrasound pulses in a new flow through type chamber on Chlamydomonas reinhardtii as a model organism for cell breakage. The ultrasound was generated using a spherically focused transducer with a focal length of 6.34 cm and an active diameter of 6.36 cm driven by 20 cycle sine-wave tone bursts at varied pulse repetition frequencies. First, variations in flow rate were examined at a constant duty cycle of 3.6%. After assessing flow rates, the duty cycle was varied to further explore the dependence on the tone burst parameters. Cell lysis was assessed by quantifying protein and chlorophyll release into the supernatant as well as by lipid extractability. Appropriate flow rates with higher duty cycles led to statistically significant increases in cell lysis relative to controls and other exposure conditions.

Over-expression of Dof-type transcription factor increases lipid production in Chlamydomonas reinhardtii

The high demand for less polluting, newer, and cheaper fuel resources has increased the search of the most innovative options for the production of the so-called biofuels. Chlamydomonas reinhardtii is a photosynthetic unicellular algae with multiple biotechnological advantages such as easy handling in the laboratory, a simple scale-up to industrial levels, as well as a feasible genetic modification at nuclear and chloroplast levels. Besides, its fatty acids can be used to produce biofuels. Previous studies in plants have found that the over expression of DOF-type transcription factor genes increases the synthesis and the accumulation of total lipids in seeds. In this context, the over-expression of a DOF-type transcription factor in C. reinhardtii was applied as approach to increase the amount of lipids. The results indicate higher amounts (around 2-fold) of total lipids, which are mainly fatty acids, in the genetically C. reinhardtii modified strains when compared with the non-genetically modified strain. In order to elucidate the possible function of the introduced Dof-type transcription factor, we performed a transcription profile of 8 genes involved in fatty acid biosynthesis and 6 genes involved in glycerolipid biosynthesis, by quantitative real time (qRT-PCR). Differential expression profile was observed, which can explain the increase in lipid accumulation. However, these strains did not show notable changes in the fatty acid profile. This work represents an early effort in generating a strategy to increase fatty acids production in C. reinhardtii and their use in biofuel synthesis.

Lysis of Chlamydomonas reinhardtii by high-intensity focused ultrasound as a function of exposure time

Efficient lysis of microalgae for lipid extraction is an important concern when processing biofuels. Historically, ultrasound frequencies in the range of 10-40 kHz have been utilized for this task. However, greater efficiencies might be achievable if higher frequencies could be used. In our study, we evaluated the potential of using 1.1 MHz ultrasound to lyse microalgae for biofuel production while using Chlamydomonas reinhardtii as a model organism. The ultrasound was generated using a spherically focused transducer with a focal length of 6.34 cm and an active diameter of 6.36 cm driven by 20 cycle sine-wave tone bursts at a pulse repetition frequency of 2 kHz (3.6% duty cycle). The time-average acoustic power output was 26.2 W while the spatial-peak-pulse-average intensity (ISPPA) for each tone burst was 41 kW/cm(2). The peak compressional and rarefactional pressures at the focus were 102 and 17 MPa, respectively. The exposure time was varied for the different cases in the experiments from 5s to 9 min and cell lysis was assessed by quantifying the percentage of protein and chlorophyll release into the supernate as well as the lipid extractability. Free radical generation and lipid oxidation for the different ultrasound exposures were also determined. We found that there was a statistically significant increase in lipid extractability for all of the exposures compared to the control. The longer exposures also completely fragmented the cells releasing almost all of the protein and chlorophyll into the supernate. The cavitation activity did not significantly increase lipid oxidation while there was a minor trend of increased free radical production with increased ultrasound exposure.

Induction of triacylglycerol production in Chlamydomonas reinhardtii: comparative analysis of different element regimes

In this study, impacts of different element absence (nitrogen, sulfur, phosphorus and magnesium) and supplementation (nitrogen and zinc) on element uptake and triacylglycerol production was followed in wild type Chlamydomonas reinhardtii CC-124 strain. Macro- and microelement composition of C. reinhardtii greatly differed under element regimes studied. In particular, heavy metal quotas of the microalgae increased strikingly under zinc supplementation. Growth was suppressed, cell biovolume, carbohydrate, total neutral lipid and triacylglycerol levels increased when microalgae were incubated under these element regimes. Most of the intracellular space was occupied by lipid bodies under all nutrient starvations, as observed by confocal microscopy and transmission electron micrographs. Results suggest that sulfur, magnesium and phosphorus deprivations are superior to nitrogen deprivation for the induction triacylglycerol production in C. reinhardtii. On the other hand, FAME profiles of the nitrogen, sulfur and phosphorus deprived cells were found to meet the requirements of international standards for biodiesel.

Carbon dioxide bio-fixation and wastewater treatment via algae photochemical synthesis for biofuels production

Utilizing the energy, nutrients and CO₂held within residual waste materials to provide all necessary inputs except for sunlight, the cultivation of algae becomes a closed-loop engineered ecosystem. Developing this green biotechnology is a tangible step towards a waste-free sustainable society.

Molecular mechanisms of system responses to novel stimuli are predictable from public data

Systems scale models provide the foundation for an effective iterative cycle between hypothesis generation, experiment and model refinement. Such models also enable predictions facilitating the understanding of biological complexity and the control of biological systems. Here, we demonstrate the reconstruction of a globally predictive gene regulatory model from public data: a model that can drive rational experiment design and reveal new regulatory mechanisms underlying responses to novel environments. Specifically, using ∼ 1500 publically available genome-wide transcriptome data sets from Saccharomyces cerevisiae, we have reconstructed an environment and gene regulatory influence network that accurately predicts regulatory mechanisms and gene expression changes on exposure of cells to completely novel environments. Focusing on transcriptional networks that induce peroxisomes biogenesis, the model-guided experiments allow us to expand a core regulatory network to include novel transcriptional influences and linkage across signaling and transcription. Thus, the approach and model provides a multi-scalar picture of gene dynamics and are powerful resources for exploiting extant data to rationally guide experimentation. The techniques outlined here are generally applicable to any biological system, which is especially important when experimental systems are challenging and samples are difficult and expensive to obtain-a common problem in laboratory animal and human studies.

Modelling Farm Animal Welfare

The use of models in the life sciences has greatly expanded in scope and advanced in technique in recent decades. However, the range, type and complexity of models used in farm animal welfare is comparatively poor, despite the great scope for use of modeling in this field of research. In this paper, we review the different modeling approaches used in farm animal welfare science to date, discussing the types of questions they have been used to answer, the merits and problems associated with the method, and possible future applications of each technique. We find that the most frequently published types of model used in farm animal welfare are conceptual and assessment models; two types of model that are frequently (though not exclusively) based on expert opinion. Simulation, optimization, scenario, and systems modeling approaches are rarer in animal welfare, despite being commonly used in other related fields. Finally, common issues such as a lack of quantitative data to parameterize models, and model selection and validation are discussed throughout the review, with possible solutions and alternative approaches suggested.

Cellulose degradation and assimilation by the unicellular phototrophic eukaryote Chlamydomonas reinhardtii

Plants convert sunlight to biomass, which is primarily composed of lignocellulose, the most abundant natural biopolymer and a potential feedstock for fuel and chemical production. Cellulose assimilation has so far only been described for heterotrophic organisms that rely on photosynthetically active primary producers of organic compounds. Among phototrophs, the unicellular green microalga Chlamydomonas reinhardtii is widely known as one of the best established model organisms. It occupies many habitats, including aquatic and soil ecosystems. This ubiquity underscores the versatile metabolic properties of this microorganism. Here we present yet another paradigm of adaptation for C. reinhardtii, highlighting its photoheterotrophic ability to utilize cellulose for growth in the absence of other carbon sources. When grown under CO(2)-limiting conditions in the light, secretion of endo-β-1,4-glucanases by the cell causes digestion of exogenous cellulose, followed by cellobiose uptake and assimilation. Phototrophic microbes like C. reinhardtii may thus serve as biocatalysts for cellulosic biofuel production.

Application of Top-Down and Bottom-up Systems Approaches in Ruminant Physiology and Metabolism

Systems biology is a computational field that has been used for several years across different scientific areas of biological research to uncover the complex interactions occurring in living organisms. Applications of systems concepts at the mammalian genome level are quite challenging, and new complimentary computational/experimental techniques are being introduced. Most recent work applying modern systems biology techniques has been conducted on bacteria, yeast, mouse, and human genomes. However, these concepts and tools are equally applicable to other species including ruminants (e.g., livestock). In systems biology, both bottom-up and top-down approaches are central to assemble information from all levels of biological pathways that must coordinate physiological processes. A bottom-up approach encompasses draft reconstruction, manual curation, network reconstruction through mathematical methods, and validation of these models through literature analysis (i.e., bibliomics). Whereas top-down approach encompasses metabolic network reconstructions using ‘omics’ data (e.g., transcriptomics, proteomics) generated through DNA microarrays, RNA-Seq or other modern high-throughput genomic techniques using appropriate statistical and bioinformatics methodologies. In this review we focus on top-down approach as a means to improve our knowledge of underlying metabolic processes in ruminants in the context of nutrition. We also explore the usefulness of tissue specific reconstructions (e.g., liver and adipose tissue) in cattle as a means to enhance productive efficiency.

Bioprospecting the thermal waters of the Roman baths: isolation of oleaginous species and analysis of the FAME profile for biodiesel production

The extensive diversity of microalgae provides an opportunity to undertake bioprospecting for species possessing features suited to commercial scale cultivation. The outdoor cultivation of microalgae is subject to extreme temperature fluctuations; temperature tolerant microalgae would help mitigate this problem. The waters of the Roman Baths, which have a temperature range between 39°C and 46°C, were sampled for microalgae. A total of 3 green algae, 1 diatom and 4 cyanobacterial species were successfully isolated into ‘unialgal’ culture. Four isolates were filamentous, which could prove advantageous for low energy dewatering of cultures using filtration.

Lipid content, profiles and growth rates of the isolates were examined at temperatures of 20, 30, 40°C, with and without nitrogen starvation and compared against the oil producing green algal species, Chlorella emersonii. Some isolates synthesized high levels of lipids, however, all were most productive at temperatures lower than those of the Roman Baths. The eukaryotic algae accumulated a range of saturated and polyunsaturated FAMEs and all isolates generally showed higher lipid accumulation under nitrogen deficient conditions (Klebsormidium sp. increasing from 1.9% to 16.0% and Hantzschia sp. from 31.9 to 40.5%). The cyanobacteria typically accumulated a narrower range of FAMEs that were mostly saturated, but were capable of accumulating a larger quantity of lipid as a proportion of dry weight (M. laminosus, 37.8% fully saturated FAMEs). The maximum productivity of all the isolates was not determined in the current work and will require further effort to optimise key variables such as light intensity and media composition.

In silico prediction of mRNA poly(A) sites in Chlamydomonas reinhardtii

Accurately predicting polyadenylation [poly(A)] sites is important for defining the end of genes and understanding gene regulation mechanisms. Alternative polyadenylation (APA) has been demonstrated to play an important role in transcriptome diversity and regulating gene expression. To accurately predict poly(A) and APA sites in Chlamydomonas reinhardtii, a green alga that can be used to produce renewable energy, we proposed a novel model that integrated five methods for representing the features of these sites with a combined classifier. We presented a new grouping method based on pattern assembly to classify the poly(A) sites into four groups. We used five methods, involving the predicted RNA secondary structure, the term frequency-inverse document frequency weight, first-order Markov chain, pentamer ratio and a position weight matrix, to generate the feature space. We then developed a heuristic method to form the combined classifier by weighting multiple classifiers to predict poly(A) sites in each group. The high specificity and sensitivity of this model were demonstrated by testing the four groups of poly(A) sites and the intronic APA sites. The average prediction performance was approximately 8 % higher than the performance of a previous prediction model. For the group without any conserved patterns, the prediction accuracy was 9 % higher than for the accuracy with the previous technique. However, the prediction efficiency of this group was still significantly lower than that of the other groups, indicating the importance of identifying additional signal patterns for poly(A) site prediction. We also predicted the alternative poly(A) sites in introns with good accuracy. This prediction model was designed to be easily expanded with new classifiers or new features. Therefore, this model is applicable to new data or other species. Our model will be useful both in genome annotation because it predicts the end of a mature transcript and in genetic engineering because it enables researchers to eliminate undesirable poly(A) sites.

Analysis of autophagy genes in microalgae: Chlorella as a potential model to study mechanism of autophagy

BACKGROUND

Microalgae, with the ability to mitigate CO(2) emission and produce carbohydrates and lipids, are considered one of the most promising resources for producing bioenergy. Recently, we discovered that autophagy plays a critical role in the metabolism of photosynthetic system and lipids production. So far, more than 30-autophagy related (ATG) genes in all subtypes of autophagy have been identified. However, compared with yeast and mammals, in silico and experimental research of autophagy pathways in microalgae remained limited and fragmentary.

PRINCIPAL FINDINGS

In this article, we performed a genome-wide analysis of ATG genes in 7 microalgae species and explored their distributions, domain structures and evolution. Eighteen "core autophagy machinery" proteins, four mammalian-specific ATG proteins and more than 30 additional proteins (including "receptor-adaptor" complexes) in all subtypes of autophagy were analyzed. Data revealed that receptor proteins in cytoplasm-to-vacuole targeting and mitophagy seem to be absent in microalgae. However, most of the "core autophagy machinery" and mammalian-specific proteins are conserved among microalgae, except for the ATG9-cycling system in Chlamydomonas reinhardtii and the second ubiquitin-like protein conjugation complex in several algal species. The catalytic and binding residues in ATG3, ATG5, ATG7, ATG8, ATG10 and ATG12 are also conserved and the phylogenetic tree of ATG8 coincides well with the phylogenies. Chlorella contains the entire set of the core autophagy machinery. In addition, RT-PCR analysis verified that all crucial ATG genes tested are expressed during autophagy in both Chlorella and Chlamydomonas reinhardtii. Finally, we discovered that addition of 3-Methyladenine (a PI3K specific inhibitor) could suppress the formation of autophagic vacuoles in Chlorella.

CONCLUSIONS

Taken together, Chlorella may represent a potential model organism to investigate autophagy pathways in photosynthetic eukaryotes. The study will not only promote understanding of the general features of autophagic pathways, but also benefit the production of Chlorella-derived biofuel with future commercial applications.

Characterization of photochemical processes for H2 production by CdS nanorod-[FeFe] hydrogenase complexes

We have developed complexes of CdS nanorods capped with 3-mercaptopropionic acid (MPA) and Clostridium acetobutylicum [FeFe]-hydrogenase I (CaI) that photocatalyze reduction of H(+) to H(2) at a CaI turnover frequency of 380-900 s(-1) and photon conversion efficiencies of up to 20% under illumination at 405 nm. In this paper, we focus on the compositional and mechanistic aspects of CdS:CaI complexes that control the photochemical conversion of solar energy into H(2). Self-assembly of CdS with CaI was driven by electrostatics, demonstrated as the inhibition of ferredoxin-mediated H(2) evolution by CaI. Production of H(2) by CdS:CaI was observed only under illumination and only in the presence of a sacrificial donor. We explored the effects of the CdS:CaI molar ratio, sacrificial donor concentration, and light intensity on photocatalytic H(2) production, which were interpreted on the basis of contributions to electron transfer, hole transfer, or rate of photon absorption, respectively. Each parameter was found to have pronounced effects on the CdS:CaI photocatalytic activity. Specifically, we found that under 405 nm light at an intensity equivalent to total AM 1.5 solar flux, H(2) production was limited by the rate of photon absorption (~1 ms(-1)) and not by the turnover of CaI. Complexes were capable of H(2) production for up to 4 h with a total turnover number of 10(6) before photocatalytic activity was lost. This loss correlated with inactivation of CaI, resulting from the photo-oxidation of the CdS capping ligand MPA.

Genomics of Volvocine Algae

Volvocine algae are a group of chlorophytes that together comprise a unique model for evolutionary and developmental biology. The species Chlamydomonas reinhardtii and Volvox carteri represent extremes in morphological diversity within the Volvocine clade. Chlamydomonas is unicellular and reflects the ancestral state of the group, while Volvox is multicellular and has evolved numerous innovations including germ-soma differentiation, sexual dimorphism, and complex morphogenetic patterning. The Chlamydomonas genome sequence has shed light on several areas of eukaryotic cell biology, metabolism and evolution, while the Volvox genome sequence has enabled a comparison with Chlamydomonas that reveals some of the underlying changes that enabled its transition to multicellularity, but also underscores the subtlety of this transition. Many of the tools and resources are in place to further develop Volvocine algae as a model for evolutionary genomics.

Modeling and optimization of fermentative hydrogen production

Biohydrogen is a sustainable energy resource due to its potentially higher efficiency of conversion to usable power, non-polluting nature and high energy density. The purpose of modeling and optimization is to improve, analyze and predict biohydrogen production. Biohydrogen production depends on a number of variables, including pH, temperature, substrate concentration and nutrient availability, among others. Mathematical modeling of several distinct processes such as kinetics of microbial growth and products formation, steady state behavior of organic substrate along with its utilization and inhibition have been presented. Present paper summarizes the experimental design methods used to investigate effects of various factors on fermentative hydrogen production, including one-factor-at-a-time design, full factorial and fractional factorial designs. Each design method is briefly outlined, followed by the introduction of its analysis. In addition, the applications of artificial neural network, genetic algorithm, principal component analysis and optimization process using desirability function have also been highlighted.