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Microalgal biomass production has been proposed for many years for the low-cost production of foods, feeds, fuels and other bio-products, and to treat wastewaters, while reducing greenhouse gas emissions, with raceway ponds the most economical technology for cultivating microalgae.
Microalgal biomass production has been proposed for many years for the low-cost production of foods, feeds, fuels and other bio-products, and to treat wastewaters, while reducing greenhouse gas emissions, with raceway ponds the most economical technology for cultivating microalgae.
Microalgal biomass production has been proposed for many years for the low-cost production of foods, feeds, fuels and other bio-products, and to treat wastewaters, while reducing greenhouse gas emissions, with raceway ponds the most economical technology for cultivating microalgae.
Efficient DNA extraction is essential for accurately monitoring microalgae communities in large-scale cultivation systems such as raceway ponds and wastewater ponds. Traditional phenol chloroform extracts are a staple in microbiology but are obsolete for routine sampling due to its high toxicity reagents and time intensive setups. Commercial DNA extraction kits are more favorable for the microbes found in these ponds, but lack specific kits made for these communities. Little is known about which kits perform the best, leading researchers to use a variety of different kits with inconsistent results. This project compared one precipitation based commercial kit (Lucigen Masterpure) and five wash based kits (Monarch, Zymo Quick-DNA, and three Qiagen DNeasy kits) using four brackish algae strains to determine which methods yield the greatest quantity and quality of genomic DNA. Extractions were evaluated using the manufacturers protocol, and additional pretreatment options were administered before a single kit to compare its potential in being added routinely before extractions. Pretreatment options included both cryogenic freeze-thawing and heat incubation using enzymes. DNA was quantified using Qubit fluorometry and NanoDrop purity ratios. Overall, the Qiagen PowerWater kit provided the highest DNA yield and purity, but at a significantly higher cost then the precipitation-based kit (MasterPure). It was also noted that while the precipitation-based kit was significantly cheaper, provided similar results, it took significantly more time to complete a single run. Cryogenic pretreatment (6x cycles) increased average DNA yields by up to 80%, whereas enzymatic pretreatment most improved purity ratios without substantially improving quantity. The results suggest that it may be more cost and time efficient to use Qiagen kits with the addition of lysis pretreatments to procure better results. Future works includes developing a better system to efficiently collect multi variable data, and to upscale to artificial polycultures using similar methodologies alongside sequencing to confirm kit results.
This Final Technical Report summarizes the goals, approach, and outcomes of the project “Enhanced Production of Algae Lipids and Carbohydrates for Fuel and Polyurethane Precursors”. The project addressed the challenge of improving microalgae biomass productivity and simultaneously producing valuable polyurethane precursors (PUPs), from both lipids and carbohydrates, that can be converted into renewable biofuels and bio-based polyurethane (PU) products. By integrating advanced genetic engineering, traditional breeding, high-throughput screening, pilot cultivation, and chemical conversion technologies, the team achieved significant advancements in algae biotechnology.
This white paper summarizes the historical progress and perspectives on future opportunities for Combined Algae Processing (CAP), a conversion approach centered around fractionating microalgae biomass and producing a slate of fuels and products. We discuss the critical challenges associated with the commercialization of algal biofuels and demonstrate how the CAP approach is uniquely suited to overcome these barriers. The versatility of applying CAP to various sources of algae is highlighted along with conversion to various fuels and product options.
This project developed a process to convert industrial carbon dioxide (CO 2 ) emissions into high-value, sustainable products through genetically engineered algae cultivation. While traditional microalgae cultivation depends on sparging CO 2 gas through water, this method is often inefficient because much of the gas escapes into the atmosphere before the algae can consume it. To overcome this challenge, the project designed an integrated system that first uses a CO 2 to formic acid electrolyzer to convert CO 2 into water-soluble formic acid/formate, then introduces formic acid/formate into the algae pond for cultivation, which allows the algae to access and utilize nearly all of the provided carbon, greatly increasing the efficiency of carbon utilization. The project team has successfully scaled up the CO 2 to formic acid electrolyzer from lab-scale to 1000 cm² and demonstrated industrially relevant current densities with the scaled-up electrolyzers using a CO 2 source that simulates industrial CO 2 waste.
Introduction: Microalgae constitute a prominent feedstock for producing biofuels and biochemicals by virtue of their prolific reproduction, high bioproduct accumulation, and the ability to grow in brackish and saline water. However, naturally occurring wild type algal strains are rarely optimal for industrial use; therefore, bioengineering of algae is necessary to generate superior performing strains that can address production challenges in industrial settings, particularly the bioenergy and bioproduct sectors. One of the crucial steps in this process is deciding on a bioengineering target: namely, which gene/protein to differentially express. These targets are often orthologs which are defined as genes/proteins originating from a common ancestor in divergent species. Although bioinformatics tools for the identification of protein orthologs already exist, processing the output from such tools is nontrivial, especially for a researcher with little or no bioinformatics experience. Methods: The present study introduces AlgaeOrtho, a user-friendly tool that builds upon the SonicParanoid orthology inference tool (based on an algorithm that identifies potential protein orthologs based on amino acid sequences) and the PhycoCosm database from JGI (Joint Genome Institute) to help researchers identify orthologs of their proteins of interest in multiple diverse algal species. Results: The output of this application includes a table of the putative orthologs of their protein of interest, a heatmap showing sequence similarity (%), and an unrooted tree of the putative protein orthologs. Notably, the tool would be instrumental in identifying novel bioengineering targets in different algal strains, including targets in not-fully annotated algal species, since it does not depend on existing protein annotations. We tested AlgaeOrtho using three case studies, for which orthologs of proteins relevant to bioengineering targets, were identified from diverse algal species, demonstrating its ease of use and utility for bioengineering researchers. Discussion: This tool is unique in the protein ortholog identification space as it can visualize putative orthologs, as desired by the user, across several algal species.
“Blue carbon” refers to the carbon sequestered by the world’s oceanic and coastal ecosystems, particularly through coastal vegetation such as mangroves, salt marshes, seagrasses, and marine macroalgae. These ecosystems play a crucial role in the global carbon cycle by serving as significant carbon sinks, absorbing carbon dioxide from the atmosphere and storing it in biomass and sediments over long periods. This study explores the use of environmental DNA (eDNA) to detect marine macrophytes and microalgae assemblages contributing to blue carbon in sediments across various coastal ecosystems. The research addresses the challenges of traditional monitoring methods by utilizing high-throughput sequencing of the 18S-V9 region amplified using eDNA from sediment samples collected at eight locations in the United States and South Korea. The results reveal a diverse array of taxa, underscoring the variability in community composition across different conditions. Notably, sites with seagrass beds and Ulva blooms showed distinct patterns in microalgal community structure. This study underscores the potential of eDNA analysis in providing comprehensive insights into the biodiversity of marine macrophyte ecosystems, thus informing conservation efforts and enhancing the understanding of marine ecological dynamics.
A workshop was conducted to identify the potential problems associated with the use of microalgae in biorregenerative life support systems, and to identify algae rlated research issues that must be addressed through space flight experimentation. Major questions to be resolved relate to the choice of algal species for inclusion in a bioregenerative life support system, their long term behavior in the space environment, and the nature of the techniques required for the continuous growth of algae on the scale required. Consideration was given to the problems associated with the conversion of algal biomass into edible components. Specific concerns were addressed and alternative transformation processes identified and compared. The workshop identified the following major areas to be addressed by space flight experimentation: (1) long term culture stability, (2) optimal design of algal growth reactors, and (3) post growth harvesting and processing in the space environment.
Bioregenerative life support systems for use in space were studied. Concepts of such systems include the use of higher plants and/or microalgae as sources of food, potable water and oxygen, and as sinks for carbon dioxide and metabolic wastes. Recycling of materials within the system will require processing of food organism and crew wastes using microbiological and/or physical chemical techniques. The dynamics of material flow within the system will require monitoring, control, stabilization and maintenance imposed by computers. Studies included higher plant and algal physiology, environmental responses, and control; flight experiments for testing responses of organisms to weightlessness and increased radiation levels; and development of ground based facilities for the study of recycling within a bioregenerative life support system.
One design goal of Closed Ecological Life Support Systems (CELSS) for long duration space missions is to maintain an atmosphere which is healthy for all the desirable biological species and not deleterious to any of the mechanical components in that atmosphere. CELESS design must take into account the interactions of at least six major components; (1) humans and animals, (2) higher plants, (3) microalgae, (4) bacteria and fungi, (5) the waste processing system, and (6) other mechanical systems. Each of these major components can be both a source and a target of airborne trace contaminants in a CELSS. A range of possible airborne trace contaminants is discussed within a chemical classification scheme. These contaminants are analyzed with respect to their probable sources among the six major components and their potential effects on those components. Data on airborne chemical contaminants detected in shuttle missions is presented along with this analysis. The observed concentrations of several classes of compounds, including hydrocarbons, halocarbons, halosilanes, amines and nitrogen oxides, are considered with respect to the problems which they present to CELSS.
Microalgae are well-suited as a component of a Closed Environmental Life Support System (CELSS), since they can couple the closely related functions of food production and atmospheric regeneration. The objective was to provide a basis for predicting the response of CELSS algal cultures, and thus the food supply and air regeneration system, to changes in the culture parameters. Scenedesmus growth was measured as a function of light intensity, and the spectral dependence of light absorption by the algae as well as algal respiration in the light were determined as a function of cell concentration. These results were used to test and confirm a mathematical model that describes the productivity of an algal culture in terms of the competing processes of photosynthesis and respiration. The relationship of algal productivity to cell concentration was determined at different carbon dioxide concentrations, temperatures, and light intensities. The maximum productivity achieved by an air-grown culture was found to be within 10% of the computed maximum productivity, indicating that CO2 was very efficiently removed from the gas stream by the algal culture. Measurements of biomass productivity as a function of cell concentration at different light intensities indicated that both the productivity and efficiency of light utilization were greater at higher light intensities.
The feasibility of using photosynthetic microalgae (cyanobacteria) as a subsystem component for the closed ecological life support system program, with particular emphasis on the manipulation of the biomass (protein/carbohydrate) was addressed. Using factors which retard growth rates, but not photosynthetic electron flux, the partitioning of photosynthetically derived reductant may be dictated towards CO2 fixation (carbohydrate formation) and away from N2 fixation (protein formation). Cold shock treatment of fairly dense cultures markedly increases the glycogen content from 1 to 35 percent (dry weight), and presents a useful technique to change the protein/carbohydrate ratio of these organisms to a more nutritionally acceptable form.
Report describes investigation of chemical composition of blue-green algae Synechococcus 6311, as well as preparation of protein isolate from green alga Scenedesmus obliquus and incorporation into variety of food products evaluated for taste. Part of program to investigate growth of microalgae aboard spacecraft for use as food.
A 2D numerical ecosystem model of Antarctic land fast ice is developed to elucidate the primary production with the Antarctic sea ice zone. The physical component employs atmospheric data to simulate congelation ice growth, initial brine entrapment, desalination, and nutrient flux. The biological component is based on the concept of a maximum temperature-dependent algal growth rate which is reduced by limitations imposed from insufficient light or nutrients, as well as suboptimal salinity. Preliminary simulations indicate that, during a bloom, microalgae are able to maintain their vertical position relative to the lower congelation ice margin and are not incorporated into the crystal matrix as the ice sheet thickens. It is inferred that land fast sea ice contains numerous microhabitats that are functionally distinct based upon the unique set of processes that control microalgal growth and accumulation within each.
Ice microalgae, collected from the underside of annual sea ice in McMurdo Sound, Antarctica, were found to contain and release to seawater a number of brominated hydrocarbons. These included bromoform, dibromomethane, mixed bromochloromethanes, and methyl bromide. Atmospheric measurements in the McMurdo Sound vicinity revealed the presence of bromoform and methyl bromide in the lower atmosphere, with lowest concentrations inland, further indicating that biogenic activity in the Sound is a source of organic bromine gases to the Antarctic atmosphere. This may have important implications for boundary layer chemistry in Antarctica. In the Arctic, the presence of bromoform has been linked to loss of surface ozone in the spring. We report here preliminary evidence for similar surface ozone loss at McMurdo Station.
Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum, in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.