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At least 145 records · Page 8

Data for A Generalized Platform for Artificial Intelligence-powered Autonomous Protein Engineering

Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we report a generally applicable platform for autonomous enzyme engineering that integrates machine learning and large language models with biofoundry automation to eliminate the need for human intervention, judgement, and domain expertise. Requiring only an input protein sequence and a quantifiable way to measure fitness, this automated platform can be applied to engineer a wide array of proteins. As a proof of concept, we engineer Arabidopsis thaliana halide methyltransferase (AtHMT) for a 90-foldimprovement in substrate preference and 16-fold improvement in ethyl-transferase activity, along with developing a Yersinia mollaretii phytase (YmPhytase) variant with 26-fold improvement in activity at neutral pH. This is accomplished in four rounds over 4 weeks, while requiring construction and characterization of fewer than 500 variants for each enzyme. This platform for autonomous experimentation paves the way for rapid advancements across diverse industries, from medicine and biotechnology to renewable energy and sustainable chemistry.

AI/ML↗

Data for "Discovery, Characterization, and Application of Chromosomal Integration Sites in the Hyperthermophilic Archaeon Sulfolobus islandicus"

Sulfolobus islandicus , an emerging archaeal model organism, offers unique advantages for metabolic engineering and synthetic biology applications owing to its ability to thrive in extreme environments. Although several genetic tools have been established for this organism, the lack of well-characterized chromosomal integration sites has limited its potential as a cellular factory. Here, we systematically identified and characterized 13 artificial CRISPR RNAs targeting eight integration sites in S. islandicus using the CRISPR-COPIES pipeline and a multi-omics-informed computational workflow. We leveraged the endogenous CRISPR-Cas system to integrate the reporter gene lacS and validated heterologous expression through a β-galactosidase assay, revealing significant positional effects. As a proof of concept, we utilized these sites to genetically manipulate lipid ether composition by overexpressing glycerol dibiphytanyl glycerol tetraether (GDGT) ring synthase B (GrsB). This study expands the genetic toolbox for S. islandicus and advances its potential as a robust platform for archaeal synthetic biology and industrial biotechnology.

AI/ML↗

Fast growing high-yield wheat and canola for efficient nutrient recycling systems

Wheat and canola are two major rotation crops in the U.S. each offering advantageous traits for the agricultural value chain. Canola, a dicot rotation crop, generally offers high seed oil content. Wheat, a monocot rotation crop, offers more cellulose and other nutritious carbohydrates. As rotation crops, traits such as rapid growth rates, increased harvest yields, and high quality (digestibility, deconstructability) are desirable for food, biorefinery, and also nutrient recycling for crop rotation. Improvement of such traits has been the goal of numerous biotechnology efforts. However, alternative biotechnology techniques are typically constitutive and when applied to commercial crops have resulted in net negative consequences. For example, efforts to improve quality by lowering lignin biosynthesis have resulted in plants with poor structural integrity and diminished mass at maturity. With supports by SBIR programs from DOE and USDA, JBEI/LBNL and AFINGEN previously demonstrated engineered healthy switchgrass and alfalfa which grew with 20-30% more fermentable sugar release, 25% less lignin, faster growth, and more biomass yields than control plants. In this CRADA project supported by NASA STTR program, AFINGEN again collaborated with JBEI/LBNL and transferred the simple tissue-targeting technology from the demonstrated switchgrass and alfalfa to the two major rotation crops wheat and canola for efficient nutrient recycling systems.

09 BIOMASS FUELS↗

Enabling generalized phage therapy to treat secondary infections in COVID-19 (CRADA Final Report)

COVID-19 is a global health threat, with 32 millions infected and more than 500,000 deaths in the U.S. alone. A key aspect of COVID-19 deaths is bacterial secondary infections, with Staphylococcus aureus, Acinetobacter baumannii, and Pseudomonas aeruginosa identified as some of the major causative pathogens. Phage therapy, i.e., the administration of bacteriophages (viruses infecting these bacterial pathogens) to patients offers a complementary solution to antibiotics with multiple key advantages. Felix Biotechnology’s is developing a high-throughput platform to identify phages that not only kill pathogens, but also drive targeted trade-off of pathogenic phenotypes such as reduced virulence and antibiotic resistance, at a fraction of the time and R&D cost of any competitor. In this project, collaboration with scientists from the Lawrence Berkeley National Laboratory enabled Felix Biotechnology to establish robust analysis pipeline to investigate phage-host interactions in complex samples. These should enable a quick and robust identification of promising phages and key genetic determinants for therapy applications, paving the way towards a streamlined and safe use of phages in the clinic.

59 BASIC BIOLOGICAL SCIENCES↗

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗

Produced Water DNA Database (PW-DNA): Utilizing KBase to generate an environmental specific curated molecular database

The deep subsurface is estimated to host the majority of Earth’s microbial biomass yet remains one of the most challenging environments to access and study. One common approach to investigate these microbial communities is through the analysis of produced water from subsurface reservoirs, where researchers can assess water and gas chemistry along with molecular (DNA/RNA) sequence data. Advances in high-throughput sequencing have greatly expanded our understanding of these environments and their biotechnological potential. However, further progress requires large-scale, integrative meta-analyses across diverse datasets. To address this need, we developed the Produced Water-DNA (PW-DNA) Database, a curated, publicly available resource that consolidates microbial DNA/RNA sequences, geochemical data, and relevant metadata from in situ hydrocarbon environments such as coal beds, oil reservoirs, and natural gas systems. The PW-DNA database delivers three core benefits to the research community: (1) it improves data sharing by linking environmental microbial datasets with corresponding geochemical parameters, enabling more robust filtering and analysis; (2) it connects with complementary research databases to promote broader dissemination and interoperability; and (3) it supports technological innovation by serving as a resource for identifying microbial trends and exploring genetic potential. While individual studies have highlighted basin-specific microbial communities and functional redundancy in biogeochemical cycling, a comprehensive, system-wide perspective is needed to better understand connectivity and novelty across subsurface ecosystems. By designing the PW-DNA in the KBase platform, we provide a reproducible, visual framework for integrating large-scale genomic and geochemical data, enabling researchers to perform more informed analyses and experimental design. Ultimately, this resource enhances the ability to identify, characterize, and interpret microbial functions across diverse subsurface environments, thereby accelerating discovery in subsurface microbiology and biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗

A Genomic Catalog of Stress Response Genes in Anaerobic Fungi for Applications in Bioproduction

Anaerobic fungi are a potential biotechnology platform to produce biomass-degrading enzymes. Unlike model fungi such as yeasts, stress responses that are relevant during bioprocessing have not yet been established for anaerobic fungi. In this work, we characterize both the heat shock and unfolded protein responses of four strains of anaerobic fungi ( Anaeromyces robustus, Caecomyces churrovis, Neocallimastix californiae , and Piromyces finnis ). The inositol-requiring 1 (Ire1) stress sensor, which typically initiates the fungal UPR, was conserved in all four genomes. However, these genomes also encode putative transmembrane kinases with catalytic domains that are similar to the metazoan stress-sensing enzyme PKR-like endoplasmic reticulum kinase (PERK), although whether they function in the UPR of anaerobic fungi remains unclear. Furthermore, we characterized the global transcriptional responses of Anaeromyces robustus and Neocallimastix californiae to a transient heat shock. Both fungi exhibited the hallmarks of ER stress, including upregulation of genes with functions in protein folding, ER-associated degradation, and intracellular protein trafficking. Relative to other fungi, the genomes of Neocallimastigomycetes contained the greatest gene percentage of HSP20 and HSP70 chaperones, which may serve to stabilize their asparagine-rich genomes. Taken together, these results delineate the unique stress response of anaerobic fungi, which is an important step toward their development as a biotechnology platform to produce enzymes and valuable biomolecules.

Swift, Candice L.↗

Genomic Analysis of Aspergillus Section Terrei Reveals a High Potential in Secondary Metabolite Production and Plant Biomass Degradation

Aspergillus terreus has attracted interest due to its application in industrial biotechnology, particularly for the production of itaconic acid and bioactive secondary metabolites. As related species also seem to possess a prosperous secondary metabolism, they are of high interest for genome mining and exploitation. Here, we present draft genome sequences for six species from Aspergillus section Terrei and one species from Aspergillus section Nidulantes. Whole-genome phylogeny confirmed that section Terrei is monophyletic. Genome analyses identified between 70 and 108 key secondary metabolism genes in each of the genomes of section Terrei, the highest rate found in the genus Aspergillus so far. The respective enzymes fall into 167 distinct families with most of them corresponding to potentially unique compounds or compound families. Moreover, 53% of the families were only found in a single species, which supports the suitability of species from section Terrei for further genome mining. Intriguingly, this analysis, combined with heterologous gene expression and metabolite identification, suggested that species from section Terrei use a strategy for UV protection different to other species from the genus Aspergillus. Section Terrei contains a complete plant polysaccharide degrading potential and an even higher cellulolytic potential than other Aspergilli, possibly facilitating additional applications for these species in biotechnology.

60 APPLIED LIFE SCIENCES↗

Engineering Terpene Production Pathways in Methylobacterium extorquens AM1

Terpenes are diverse specialized metabolites naturally found within plants and have important roles in inter-species communication, adaptation and interaction with the environment. Their industrial applications span a broad range, including fragrances, flavors, cosmetics, natural colorants to agrochemicals and therapeutics, yet formal chemical synthesis is economically challenging due to structural complexities. Engineering terpene biosynthesis could represent an alternative in microbial biotechnological workhorses, such as Saccharomyces cerevisiae or Escherichi coli, utilizing sugars or complex media as feedstocks. Host species that metabolize renewable and affordable carbon sources may offer unique sustainable biotechnological alternatives. Methylotrophs are bacteria with the capacity to utilize one-carbon feedstocks, such as methanol or formate. They colonize the phyllosphere (above-ground area) of plants, and many accumulate abundant carotenoid pigments. Methylotrophs have the capacity to take up and use a subset of the rare earth elements known as lanthanides. These metals can enhance one-carbon (methylotrophic) metabolism. Here, we investigated whether manipulating the metabolism enables and enhances terpene production. A carotenoid-deficient mutant potentially liberates carbon, which may contribute to bioproduct accumulation. To test this hypothesis, terpene-producing bacterial strains regulated by two distinct promoters were generated. Wildtype Methylobacterium extorquens, ∆Meta1_3665, a methylotrophic mutant lacking the carotenoid pathway, and an E. coli strain were transformed with an exogenous terpene pathway and grown both in the presence and absence of lanthanides. The extraction, and the comparison of analytical profiles, provided evidence that engineered cultured M. extorquens under control of a native, inducible methylotrophic promoter can yield the sesquiterpene patchoulol when supplemented with lanthanide. In contrast, using a moderate-strength constitutive promoter failed to give production. We demonstrated colonization of the phyllosphere with the engineered strains, supporting the future engineering of selected species of the plant microbiome and with promising implications for the synthetic biology of small molecules.

59 BASIC BIOLOGICAL SCIENCES↗

Agrobacterium tumefaciens : A Bacterium Primed for Synthetic Biology

Agrobacterium tumefaciens is an important tool in plant biotechnology due to its natural ability to transfer DNA into the genomes of host plants. Genetic manipulations of A. tumefaciens have yielded considerable advances in increasing transformational efficiency in a number of plant species and cultivars. Moreover, there is overwhelming evidence that modulating the expression of various mediators of A. tumefaciens virulence can lead to more successful plant transformation; thus, the application of synthetic biology to enable targeted engineering of the bacterium may enable new opportunities for advancing plant biotechnology. In this review, we highlight engineering targets in both A. tumefaciens and plant hosts that could be exploited more effectively through precision genetic control to generate high-quality transformation events in a wider range of host plants. We then further discuss the current state of A. tumefaciens and plant engineering with regard to plant transformation and describe how future work may incorporate a rigorous synthetic biology approach to tailor strains of A. tumefaciens used in plant transformation.

59 BASIC BIOLOGICAL SCIENCES↗

Observing one-divalent-metal-ion-dependent and histidine-promoted His-Me family I-PpoI nuclease catalysis in crystallo

Metal-ion-dependent nucleases play crucial roles in cellular defense and biotechnological applications. Time-resolved crystallography has resolved catalytic details of metal-ion-dependent DNA hydrolysis and synthesis, uncovering the essential roles of multiple metal ions during catalysis. The histidine-metal (His-Me) superfamily nucleases are renowned for binding one divalent metal ion and requiring a conserved histidine to promote catalysis. Many His-Me family nucleases, including homing endonucleases and Cas9 nuclease, have been adapted for biotechnological and biomedical applications. However, it remains unclear how the single metal ion in His-Me nucleases, together with the histidine, promotes water deprotonation, nucleophilic attack, and phosphodiester bond breakage. By observing DNA hydrolysis in crystallo with His-Me I-PpoI nuclease as a model system, we proved that only one divalent metal ion is required during its catalysis. Moreover, we uncovered several possible deprotonation pathways for the nucleophilic water. Interestingly, binding of the single metal ion and water deprotonation are concerted during catalysis. Our results reveal catalytic details of His-Me nucleases, which is distinct from multi-metal-ion-dependent DNA polymerases and nucleases.

59 BASIC BIOLOGICAL SCIENCES↗

Coupled Microbial-Conversion and Computational-Fluid-Dynamics (CFD) Models for Butanediol Production in Micro-Aerated Reactors

Microbial conversion of substrates to macromolecules has been widely used in the synthesis of value-added products in pharmaceutical and biotechnology industries. These bioreactions are also being investigated in the production of low-value commodities such as biofuels [1]. Gas-liquid mass-transfer and transport-reaction coupling are important challenges when designing and scaling up these reactor systems. Experiments in wellmixed small-scale reactors have enabled characterization of microbial reactivity, while their coupling with macroscale transport remains relatively unexplored. In this work, we use a coupled metabolic-CFD model to study the action of a genetically engineered microbe Zymomonas mobilis [2] on sugars to produce 2,3-Butanediol (BDO). BDO is an important hydrocarbon intermediate that can be catalytically upgraded to several fuels and chemicals [3]. An important aspect to this particular microbial conversion is the need for micro-aerated environments as opposed to traditional aerobic fermentation. Slight variations in oxygen concentration can result in competing reaction pathways that disable BDO production. Hence, gas-liquid mass transfer and transport need to be optimized in large-scale reactors to maximize BDO production, for which CFD is a valuable tool. The aerobic-fermentation CFD model previously developed by the authors [5] for simulating bubble-column and airlift reactors at scale was used in this study. The Reynolds-averaged mass, momentum and energy transport equations for interpenetrating gas and liquid phase are solved in this model along with the transport and interphase mass transfer of oxygen. Our previous work used a phenomenological model for microbial oxygen uptake that neglected microbial growth and other reaction pathways. In this work, a detailed metabolic model enabled prediction of product formation and inhibition pathways. In order to manage computational cost, we used a subcycling technique [6] that takes advantage of the clear separation in transport (~ 200 sec) and reaction (~ 2-3 hours) timescales. The CFD model is first solved to steady state, after which the metabolic model is advanced at every cell in the computational domain using the local oxygen concentration. The CFD model is then run to achieve a new steady state that provides a new oxygen distribution for the metabolic model. This process, where reaction and fluid updates are interleaved together, is iterated until reactants are completely exhausted. This work will examine the performance of different reactor designs such as bubble column and airlift reactors at scale (250-500 m3). Oxygen mass-transfer coefficient and distribution are critically analyzed among reactors, and optimization studies pertaining to aeration is presented. Furthermore, it has been observed in experiments that high BDO production may be achieved by manipulating the aerobic environment over the course of reaction, such that oxygen concentration is high during the growth phase, and very low as sugar is depleted. This characteristic will be addressed by our simulations for which a timedependent scheduling strategy for aeration is presented that maximizes BDO production. [1] Humbird, D., Davis, R., and McMillan, J., Aeration costs in stirred-tank and bubble column bioreactors, Biochemical Engineering Journal, 127, 161—166, 2017 [2] Yang, S., Mohagheghi, A., Franden, M. A., Chou, Y.-C., Chen, X., Dowe, N., Himmel, M. E., and Zhang, M., Metabolic engineering of zymomonas mobilis for 2, 3-butanediol production from lignocellulosic biomass sugars. Biotechnology for biofuels, 9(1):189, 2016 [3] Kim, S. J., Sim, H. J., Kim, J. W., Lee, Y. G., Park, Y. C., and Seo, J. H., Enhanced production of 2,3-butanediol from xylose by combinatorial engineering of xylose metabolic pathway and cofactor regeneration in pyruvate decarboxylase-deficient Saccharomyces cerevisiae. Bioresource Technology, 245:1551–1557, 2017 [4] Weller, H., Tabor, G., Jasak, H. and Fureby, C., A tensorial approach to computational continuum mechanics using object-oriented techniques, Computers in physics, 12, 6, 620--631, 1998

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Molecular and biochemical characterization of rice developed through conventional integration of nDart1-0 transposon gene

Mutations, the genetic variations in genomic sequences, play an important role in molecular biology and biotechnology. During DNA replication or meiosis, one of the mutations is transposons or jumping genes. An indigenous transposon nDart1-0 was successfully introduced into local indica cultivar Basmati-370 from transposon-tagged line viz., GR-7895 (japonica genotype) through conventional breeding technique, successive backcrossing. Plants from segregating populationsshowed variegated phenotypes were tagged as BM-37 mutants. Blast analysis of the sequence data revealed that the GTP-binding protein, located on the BAC clone OJ1781_H11 of chromosome 5, contained an insertion of DNA transposon nDart1-0. The nDart1-0 has “A” at position 254 bp, whereas nDart1 homologs have “G”, which efficiently distinguishes nDart1-0 from its homologs. The histological analysis revealed that the chloroplast of mesophyll cells in BM-37 was disrupted with reduction in size of starch granules and higher number of osmophillic plastoglobuli, which resulted in decreased chlorophyll contents and carotenoids, gas exchange parameters (Pn, g, E, Ci), and reduced expression level of genes associated with chlorophyll biosynthesis, photosynthesis and chloroplast development. Along with the rise of GTP protein, the salicylic acid (SA) and gibberellic acid (GA) and antioxidant contents(SOD) and MDA levels significantly enhanced, while, the cytokinins (CK), ascorbate peroxidase (APX), catalase (CAT), total flavanoid contents (TFC) and total phenolic contents (TPC) significantly reduced in BM-37 mutant plants as compared with WT plants. These results support the notion that GTP-binding proteins influence the process underlying chloroplast formation. Therefore, it is anticipated that to combat biotic or abiotic stress conditions, the nDart1-0 tagged mutant (BM-37) of Basmati-370 would be beneficial.

60 APPLIED LIFE SCIENCES↗

Electric Vehicles, Biofuels, and Transitions in Transportation Energy

The decarbonization of power sources for light duty transportation is moving towards the use of renewable energies, biofuels, and electric vehicles. Currently there are three major light transportation fuels: gasoline (US gasoline is 98% E10), biofuels (E85), and electricity. Currently fuel ethanol in biofuels is obtained principally from corn in the US and sugarcane in Brazil with a small amount from cellulose. The transition to alternative fuels has been occurring since 1980, although light transportation still relies on gasoline. The rise of battery electric vehicles (BEV) is now beginning to offset internal combustion engines (ICE), while recent advances in biotechnology and integrated plant design have enhanced the economic feasibility of cellulosic biofuels. This paper explores the potential role of these fuels in reducing the carbon footprint associated with light transportation. We compare three different cases: Gasoline, E85 and full electric based on the Argonne AFLEET tool to calculate generation of greenhouse gases due to manufacturing and operation of BEV and ICE cars, respectively, in the US assuming an average useful automobile life of 200,000 miles or 12 years. We concluded that significant liquid fuel use (both renewable and non-renewable) will continue for the next 50 years. Here, renewable liquid fuels have an important role to play as the transportation sector transitions from petroleum to other energy sources.

09 BIOMASS FUELS↗

Assembly and comparative genome analysis of a Patagonian Aureobasidium pullulans isolate reveals unexpected intraspecific variation

Aureobasidium pullulans is a yeast-like fungus with remarkable phenotypic plasticity widely studied for its importance for the pharmaceutical and food industries. So far, genomic studies with strains from all over the world suggest they constitute a genetically unstructured population, with no association by habitat. However, the mechanisms by which this genome supports so many phenotypic permutations are still poorly understood. Recent works have shown the importance of sequencing yeast genomes from extreme environments to increase the repertoire of phenotypic diversity of unconventional yeasts. In this study, we present the genomic draft of A. pullulans strain from a Patagonian yeast diversity hotspot, re-evaluate its taxonomic classification based on taxogenomic approaches, and annotate its genome with high-depth transcriptomic data. Here, our analysis suggests this isolate could be considered a novel variant at an early stage of the speciation process. The discovery of divergent strains in a genomically homogeneous group, such as A. pullulans, can be valuable in understanding the evolution of the species. The identification and characterization of new variants will not only allow finding unique traits of biotechnological importance, but also optimize the choice of strains whose phenotypes will be characterized, providing new elements to explore questions about plasticity and adaptation.

59 BASIC BIOLOGICAL SCIENCES↗

Adaptive Laboratory Evolution for algal strain improvement: methodologies and applications

Originally developed in bacterial and fungal models, Adaptive Laboratory Evolution (ALE) experimentally selects for targeted phenotypes by allowing cells containing beneficial random genetic mutations to replicate more quickly in the presence of environmental stress. When applied to microalgae, this technique has been used to increase growth rate, stress tolerance, substrate utilization, and product yield. This review discusses ALE experimental design parameters, and summarizes key results and lessons learned from recent microalgal ALE studies. By documenting the current state of the field, we provide insight on the ways microalgal ALE might be used to develop commercially viable biotechnology strains.

09 BIOMASS FUELS↗