Algae Biofuels: The Process
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Results for “biotechnological methodologies”
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Developing a pipeline to expand the genetic code of diverse bacteria for microbial engineering
Microbial biotechnologies are key to addressing grand challenges to promote human health, reverse carbon emissions, recycle mixed plastic waste, remediate contaminated soils, and achieve sustainable economies. Synthetic biology has enabled design of diverse microbes and their proteins for useful purposes, but the narrowness of the natural genetic code limits functional diversity (e.g., biosynthesis) of engineered microbes. The natural genetic code defines the fundamental rules of translating genetic information into proteins comprised of 22 ‘canonical’ amino acids. However, using a technique called genetic code expansion (GCE), the chemical properties and therefore functions of proteins can be transformed by incorporation of one or more of ~200 chemically diverse ‘non-canonical’ amino acids. The effective application of genetic code expansion in diverse microbes has the potential to revolutionize biotechnology. However, despite over 50 years of research and its transformative potential, the application of genetic code expansion has been limited to a handful of bacterial species. In this project, we will perform three tasks to both overcome the barriers that prevent wide spread adoption of GCE as molecular tool and demonstrate its potential for biotechnological applications. Specifically, we will (1) develop a genetic engineering methodology that will enable use of GCE in a broad range of bacterial hosts, (2) use high-throughput functional genomics methods to identify physiological responses to both genetic code expansion and exposure to non-canonical amino acids in three different bacteria, and (3) demonstrate an application of GCE by selectively incorporate non-canonical amino acids into surface displayed peptides such as those used for biomining.
59 BASIC BIOLOGICAL SCIENCES↗
Aerospace simulation and human performance research.
Human performance relation research relationship with aerospace mission oriented simulation studies, discussing methodological resolution and limitation
HUMAN PERFORMANCE↗
Robust and effective methodologies for cryopreservation and DNA extraction from anaerobic gut fungi
Cell storage and DNA isolation are essential to developing an expanded suite of microorganisms for biotechnology. However, many features of non-model microbes, such as an anaerobic lifestyle and rigid cell wall, present formidable challenges to creating strain repositories and extracting high quality genomic DNA. We establish accessible, high efficiency, and robust techniques to store lignocellulolytic anaerobic gut fungi long term without specialized equipment. Using glycerol as a cryoprotectant, gut fungal isolates were preserved for a minimum of 23 months at -80 °C. Unlike previously reported approaches, this improved protocol is non-toxic and rapid, with samples surviving twice as long with negligible growth impact. Genomic DNA extraction for these isolates was optimized to yield samples compatible with next generation sequencing platforms (e.g. Illumina, PacBio). Popular DNA isolation kits and precipitation protocols yielded preps that were unsuitable for sequencing due to carbohydrate contaminants from the chitin-rich cell wall and extensive energy reserves of gut fungi. To address this, we identified a proprietary method optimized for hardy plant samples that rapidly yielded DNA fragments in excess of 10 kb with minimal RNA, protein or carbohydrate contamination. Collectively, these techniques serve as fundamental tools to manipulate powerful biomass-degrading gut fungi and improve their accessibility among researchers.
59 BASIC BIOLOGICAL SCIENCES↗
Casting Nanoporous Platinum in Metal–Organic Frameworks
Nanocasting based on porous templates is a powerful strategy in accessing materials and structures that are difficult to form by bottom-up syntheses in a controlled fashion. A facile synthetic strategy for casting ordered, nanoporous platinum (NP-Pt) networks with a high degree of control by using metal-organic frameworks (MOFs) as templates is reported here. The Pt precursor is first infiltrated into zirconium-based MOFs and subsequently transformed to 3D metallic networks via a chemical reduction process. It is demonstrated that the dimensions and topologies of the cast NP-Pt networks can be accurately controlled by using different MOFs as templates. The Brunauer-Emmett-Teller surface areas of the NP-Pt networks are estimated to be >100 m 2 g -1 and they exhibit excellent catalytic activities in the methanol electrooxidation reaction (MEOR). Finally, this new methodology presents an attractive route to prepare well-defined nanoporous materials for diverse applications ranging from energy to sensing and biotechnology.
36 MATERIALS SCIENCE↗
Validating genome-wide CRISPR-Cas9 function improves screening in the oleaginous yeast Yarrowia lipolytica
Genome-wide mutational screens are central to understanding the genetic underpinnings of evolved and engineered phenotypes. The widespread adoption of CRISPR-Cas9 genome editing has enabled such screens in many organisms, but identifying functional sgRNAs still remains a challenge. Here, we developed a methodology to quantify the cutting efficiency of each sgRNA in a genome-scale library, and in doing so improve screens in the biotechnologically important yeast Yarrowia lipolytica. Screening in the presence and absence of native DNA repair enabled high-throughput quantification of sgRNA function leading to the identification of high efficiency sgRNAs that cover 94% of genes. Library validation enhanced the classification of essential genes by identifying inactive guides that create false negatives and mask the effects of successful disruptions. Quantification of guide effectiveness also creates a dataset from which determinants of CRISPR-Cas9 can be identified. Finally, application of the library identified novel mutations for metabolic engineering of high lipid accumulation.
59 BASIC BIOLOGICAL SCIENCES↗
Multiplexed Knockouts in the Model Diatom Phaeodactylum by Episomal Delivery of a Selectable Cas9
Marine diatoms are eukaryotic microalgae that play significant ecological and biogeochemical roles in oceans. They also have significant potential as organismal platforms for exploitation to address biotechnological and industrial goals. In order to address both modes of research, sophisticated molecular and genetic tools are required. We presented here new and improved methodologies for introducing CRISPRCas9 to the model diatom Phaeodactylum tricornutum cells and a streamlined protocol for genotyping mutant cell lines with previously unknown phenotypes. First, bacterialconjugation was optimized for the delivery of Cas9 by transcriptionally fusing Cas9 to a selectable marker by the 2A peptide. An episome cloning strategy using both negative and positive selection was developed to streamline CRISPR-episome assembly. Next, cell line picking and genotyping strategies, that utilize manual sequencing curation, TIDE sequencing analysis, and a T7 endonuclease assay, were developed to shorten the time required to generate mutants. Following this new experimental pipeline, both singlegene and two-gene knockout cell lines were generated at mutagenesis efficiencies of 48% and 25%, respectively. Lastly, a protocol for precise gene insertions via CRISPRCas9 targeting was developed using particle-bombardment transformation methods. Overall, the novel Cas9 episome design and improved genotyping methods presented here allow for quick and easy genotyping and isolation of Phaeodactylum mutant cell lines (less than 3 weeks) without relying on a known phenotype to screen for mutants.
59 BASIC BIOLOGICAL SCIENCES↗
A generalized computational framework to streamline thermodynamics and kinetics analysis of metabolic pathways
Metabolic engineering is a critical biotechnological approach in addressing global energy and environment challenges. Most engineering efforts, however, consist of laborious and inefficient trial-and-error of target pathways, due in part to the lack of methodologies that can comprehensively assess pathway properties in thermodynamics and kinetics. Metabolic engineering can benefit from computational tools that evaluate feasibility, expense and stability of non-natural metabolic pathways. Such tools can also help us understand natural pathways and their regulation at systems level. Here we introduce a computational toolbox, PathParser, which, for the first time, integrates multiple important functions for pathway analysis including thermodynamics analysis, kinetics-based protein cost optimization and robustness analysis. Specifically, PathParser enables optimization of the driving force of a pathway by minimizing the Gibbs free energy of least thermodynamically favorable reaction. In addition, based on reaction thermodynamics and enzyme kinetics, it can compute the minimal enzyme protein cost that supports metabolic flux, and evaluate pathway stability and flux in response to enzyme concentration perturbations. In a demo analysis of the Calvin-Benson-Bassham cycle and photorespiration pathway in the model cyanobacterium Synechocystis PCC 6803, the computation results are corroborated by experimental proteomics data as well as metabolic engineering outcomes. This toolbox may have broad application in metabolic engineering and systems biology in other microbial systems.
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ISS Microgravity Research Payload Training Methodology
The NASA Microgravity Research Discipline has multiple categories of science payloads that are being planned and currently under development to operate on various ISS on-orbit increments. The current program includes six subdisciplines; Materials Science, Fluids Physics, Combustion Science, Fundamental Physics, Cellular Biology and Macromolecular Biotechnology. All of these experiment payloads will require the astronaut various degrees of crew interaction and science observation. With the current programs planning to build various facility class science racks, the crew will need to be trained on basic core operations as well as science background. In addition, many disciplines will use the Express Rack and the Microgravity Science Glovebox (MSG) to utilize the accommodations provided by these facilities for smaller and less complex type hardware. The Microgravity disciplines will be responsible to have a training program designed to maximize the experiment and hardware throughput as well as being prepared for various contingencies both with anomalies as well as unexpected experiment observations. The crewmembers will need various levels of training from simple tasks as power on and activate to extensive training on hardware mode change out to observing the cell growth of various types of tissue cultures. Sample replacement will be required for furnaces and combustion type modules. The Fundamental Physics program will need crew EVA support to provide module change out of experiment. Training will take place various research centers and hardware development locations. It is expected that onboard training through various methods and video/digital technology as well as limited telecommunication interaction. Since hardware will be designed to operate from a few weeks to multiple research increments, flexibility must be planned in the training approach and procedure skills to optimize the output as well as the equipment maintainability. Early increment lessons learned will be addressed.
Schlagheck, Ronald↗
Contextualizing context for synthetic biology - identifying causes of failure of synthetic biological systems
Despite the efforts that bioengineers have exerted in designing and constructing biological processes that function according to a predetermined set of rules, their operation remains fundamentally circumstantial. The contextual situation in which molecules and single-celled or multicellular organisms find themselves shapes the way they interact, respond to the environment and process external information. Since the birth of the field, synthetic biologists have had to grapple with contextual issues, particularly when the molecular and genetic devices inexplicably fail to function as designed when tested in vivo. In this review, we set out to identify and classify the sources of the unexpected divergences between design and actual function of synthetic systems and analyze possible methodologies aimed at controlling, if not preventing, unwanted contextual issues.
59 BASIC BIOLOGICAL SCIENCES↗
Bacterial communities protect the alga Microchloropsis salina from grazing by the rotifer Brachionus plicatilis
Open algal ponds are likely to succumb to unpredictable, devastating crashes by one or several deleterious species. Developing methodology to mitigate or prevent pond crashes will increase algal biomass production, drive down costs for algae farmers, and reduce the risk involved with algae cultivation, making it more favorable for investment by entrepreneurs and biotechnology companies. In this work, we postulate that specific algal-bacterial co-cultures grown with the green alga Microchloropsis salina prevented grazing by the marine rotifer, Brachionus plicatilis. We obtained seven algal-bacterial co-cultures from crashed rotifer cultures, maintained them in co-culture with Microchloropsis salina , and used a microalgal survival assay to determine that algae present in each co-culture were protected from rotifer grazing and culture crash. After months of routinely diluting and maintaining these seven algal-bacterial co-cultures, we repeated the assay and found the opposite result: none of the seven bacterial communities protected the microalgae from rotifer grazing. We performed 16S rRNA gene amplicon sequencing on the protective and nonprotective co-culture samples and identified substantial differences in the makeup of the bacterial communities. Protective bacterial communities consisted primarily of Alphaproteobacteria (Rhodobacteraceae) and Gammaproteobacteria ( Marinobacter , Pseudomonas, Methylophaga ) while nonprotective bacterial communities were less diverse and missing many putatively crucial members. We compared the seven protective communities with the seven nonprotective communities and we correlated specific bacterial amplicon sequence variants with algal protection. With these data, our future research will aim to define and develop an engineered-microbiome that can stabilize industrial Microchloropsis salina cultures by protecting against grazer-induced pond crashes.
59 BASIC BIOLOGICAL SCIENCES↗
Computational Modeling of Fluctuations in Energy and Metabolic Pathways of Methanogenic Archaea
The methanogenic archaea, anaerobic microbes that convert CO2 and H2 and/or other small organic fermentation products into methane, play an unusually large role in the global carbon cycle. As they perform the final step in the anaerobic breakdown of biomass, methanogens are a biogenic source of an estimated one billion tons methane each year. Depending on the location, produced methane can be considered as either a greenhouse gas (agricultural byproduct), sequestered carbon storage (methane hydrate deposits), or a potential energy source (organic wastewater treatment). These microbes therefore represent an important target for biotechnology applications. Computational models of methanogens with predictive power are useful aids in the adaptation of methanogenic systems, but need to connect processes of wide-ranging time and length scales. In this project, we developed several computational methodologies for modeling the dynamic behavior of entire cells that connects stochastic reaction-diffusion dynamics of individual biochemical pathways with genome-scale modeling of metabolic networks. While each of these techniques were in the realm of well-defined computational methods, here we integrated them to develop several entirely new approaches to systems biology. The first scientific aim of the project was to model how noise in a biochemical pathway propagates into cellular phenotypes. Genetic circuits have been optimized by evolution to regulate molecular processes despite stochastic noise, but the effect of such noise on a cellular biochemical networks is currently unknown. An integrated stochastic/systems model of Escherichia coli species was created to analyze how noise in protein expression gives—and therefore noise in metabolic fluxes—gives rise to multiple cellular phenotype in isogenic population. After the initial work developing and validating methods that allow characterization of the heterogeneity in the model organism E. coli, the project shifted toward investigations of the methanogen Methanosarcina acetivorans. By integrating an unprecedented transcriptomics dataset for growth of the methanogen on many substrates with an in silico model, heterogeneity in metabolic pathway usage and methane production were examined. This lent insight into the physiological requirements of the organism under different environmental conditions and uncovered the unique regulatory role that mRNA half-life has in shaping metabolic flux distributions in this organism.
59 BASIC BIOLOGICAL SCIENCES↗
Measurements of soil protist richness and community composition are influenced by primer pair, annealing temperature, and bioinformatics choices
ABSTRACT Protists are a diverse and understudied group of microbial eukaryotic organisms especially in terrestrial environments. Advances in molecular methods are increasing our understanding of the distribution and functions of these creatures; however, there is a vast array of choices researchers make including barcoding genes, primer pairs, PCR settings, and bioinformatic options that can impact the outcome of protist community surveys. Here, we tested four commonly used primer pairs targeting the V4 and V9 regions of the 18S rRNA gene using different PCR annealing temperatures and processed the sequences with different bioinformatic parameters in 10 diverse soils to evaluate how primer pair, amplification parameters, and bioinformatic choices influence the composition and richness of protist and non-protist taxa using Illumina sequencing. Our results showed that annealing temperature influenced sequencing depth and protist taxon richness for most primer pairs, and that merging forward and reverse sequencing reads for the V4 primer pairs dramatically reduced the number of sequences and taxon richness of protists. The data sets of primers that targeted the same 18S rRNA gene region (e.g., V4 or V9) had similar protist community compositions; however, data sets from primers targeting the V4 18S rRNA gene region detected a greater number of protist taxa compared to those prepared with primers targeting the V9 18S rRNA region. There was limited overlap of protist taxa between data sets targeting the two different gene regions (80/549 taxa). Together, we show that laboratory and bioinformatic choices can substantially affect the results and conclusions about protist diversity and community composition using metabarcoding. IMPORTANCE Ecosystem functioning is driven by the activity and interactions of the microbial community, in both aquatic and terrestrial environments. Protists are a group of highly diverse, mostly unicellular microbes whose identity and roles in terrestrial ecosystem ecology have been largely ignored until recently. This study highlights the importance of choices researchers make, such as primer pair, on the results and conclusions about protist diversity and community composition in soils. In order to better understand the roles protist taxa play in terrestrial ecosystems, biases in methodological and analytical choices should be understood and acknowledged.
Biotechnology & Applied Microbiology↗
Thermophilic Chassis-Enabled High-Throughput Selection of a Thermostable Fluorogenic Reporter
Thermostable proteins show increased shelf life and performance at elevated temperatures and under harsh conditions, resulting in lower costs for various industrial and biotechnological applications. However, due to a limited understanding of the relationship between stability and function, protein stabilization remains primarily a trial-and-error approach. Therefore, building a combinatorial library of mutations predicted to improve stability, followed by experimental testing, represents a markedly improved methodology. However, the lack of high-throughput approaches to screen even a moderately sized library presents a major bottleneck in the field. Here, in this study, we use a thermophile, Parageobacillus thermoglucosidasius (Ptherm) to rapidly screen combinatorial libraries consisting of rationally designed thermostabilizing mutations (∼10 3 –10 4 ) of a mesophilic fluorescent reporter, Y-FAST. On a Petri dish, microbial growth at an elevated temperature and exposure to fluorogen yielded several colonies of Ptherm that showed distinct fluorescence at 55 and 68 °C in our two sequentially generated libraries using Rosetta and ProteinMPNN, respectively. The Y-FAST variants isolated from fluorescent colonies were brighter than Y-FAST and showed higher resistance to thermal and chemical denaturation. AlphaFold-predicted structures and MD simulations revealed stability-enhancing salt bridges and hydrogen bond networks in the isolated FAST variants. The moderately thermostable FAST (tsFAST) and hyperstable FAST (hsFAST) were then demonstrated as translation reporters for protein expression and folding at elevated temperatures, such as 55 and 68 °C. Our approach of combinatorial library generation and high-throughput screening in a thermophilic chassis could, in principle, be extended to other proteins fused to these translation reporters. Furthermore, the hsFAST protein is small─half the size of the green fluorescent protein─and does not require oxygen for maturation, making it ideal for engineering extremophilic anaerobes for biosensing and bioconversion.
59 BASIC BIOLOGICAL SCIENCES↗
Kinetic modeling of microbial growth, enzyme activity, and gene deletions: An integrated model of β-glucosidase function in Cellvibrio japonicus
Understanding the complex growth and metabolic dynamics in microorganisms requires advanced kinetic models containing both metabolic reactions and enzymatic regulation to predict phenotypic behaviors under different conditions and perturbations. Most current kinetic models lack gene expression dynamics and are separately calibrated to distinct media, which consequently makes them unable to account for genetic perturbations or multiple substrates. This challenge limits our ability to gain a comprehensive understanding of microbial processes towards advanced metabolic optimizations that are desired for many biotechnology applications. Here, we present an integrated computational and experimental approach for the development and optimization of mechanistic kinetic models for microbial growth and metabolic and enzymatic dynamics. Our approach integrates growth dynamics, gene expression, protein secretion, and gene-deletion phenotypes. We applied this methodology to build a dynamic model of the growth kinetics in batch culture of the bacterium Cellvibrio japonicus grown using either cellobiose or glucose media. The model parameters were inferred from an experimental data set using an evolutionary computation method. The resulting model was able to explain the growth dynamics of C. japonicus using either cellobiose or glucose media and was also able to accurately predict the metabolite concentrations in the wild-type strain as well as in β-glucosidase gene deletion mutant strains. We validated the model by correctly predicting the non-diauxic growth and metabolite consumptions of the wild-type strain in a mixed medium containing both cellobiose and glucose, made further predictions of mutant strains growth phenotypes when using cellobiose and glucose media, and demonstrated the utility of the model for designing industrially-useful strains. Importantly, the model is able to explain the role of the different β-glucosidases and their behavior under genetic perturbations. Here, this integrated approach can be extended to other metabolic pathways to produce mechanistic models for the comprehensive understanding of enzymatic functions in multiple substrates.
59 BASIC BIOLOGICAL SCIENCES↗
Cloning, expression, and characterization of a peptidoglycan hydrolase from the Burkholderia pseudomallei phage ST79
The lytic phage ST79 of Burkholderia pseudomallei can lyse a broad range of its host including antibiotic resistant isolates from within using a set of proteins, holin, lysB, lysC and endolysin, a peptidoglycan (PG) hydrolase enzyme. The phage ST79 endolysin gene identified as peptidase M15A was cloned, expressed and purified to evaluate its potential to lyse pathogenic bacteria. The molecular size of the purified enzyme is approximately 18 kDa and the in silico study cited here indicated the presence of a zinc-binding domain predicted to be a member of the subfamily A of a metallopeptidase. Its activity, however, was reduced by the presence of Zn2+. When Escherichia coli PG was used as a substrate and subjected to digestion for 5 min with 3 μg/ml of enzyme, the peptidase M15A showed 2 times higher in lysis efficiency when compared to the commercial lysozyme. The enzyme works in a broad alkaligenic pH range of 7.5–9.0 and temperatures from 25 to 42 °C. The enzyme was able to lyse 18 Gram-negative bacteria in which the outer membrane was permeabilized by chloroform treatment. Interestingly, it also lysed Enterococcus sp., but not other Gram-positive bacteria. In general, endolysin cannot lyse Gram-negative bacteria from outside, however, the cationic amphipathic C-terminal in some endolysins showed permeability to Gram-negative outer membranes. Genetically engineered ST79 peptidase M15A that showed a broad spectrum against Gram-negative bacterial PG or, in combination with an antibiotic the same way as combined drug methodology, could facilitate an effective treatment of severe or antibiotic resistant cases.
59 BASIC BIOLOGICAL SCIENCES↗
Low-Cost Screening of Algae for Extreme Tolerance to pH, Temperature, Salinity, and Light
AbstractBioprospecting algae strains with tolerance to extreme conditions such as pH, temperature, salinity, and light is crucial for advancing biotechnology and environmental applications. However, traditional screening methods often involve significant costs and labor, restricting their accessibility and practical use. In this study, we developed and validated low-cost, high-throughput screening techniques, predominantly employing agar plates and liquid culture assays, to effectively differentiate tolerance levels among various algae strains. The methodologies were optimized using the model microalgaChlamydomonas reinhardtiiand its closely related speciesChlamydomonas incertaand the recently discovered extremophilicChlamydomonas pacifica. We systematically evaluated the algae for tolerance to extremes by establishing precise gradients of pH (acidic to alkaline conditions), salinity (0 to 5 M NaCl), temperature (34–42°C), and light intensity (40 to 2977 μE·m⁻²·s⁻¹). Our results demonstrated that these cost-effective, agar plate-based methods effectively distinguished algae strains exhibiting superior tolerance to extreme environmental conditions. These screening techniques not only provided clear differentiation among the closely related strains but also delivered reproducible outcomes suitable for scaling up to larger bioprospecting efforts. Furthermore, the affordability and simplicity of these methods facilitate their implementation in resource-limited laboratories, thereby broadening participation in algae bioprospecting endeavors. This study highlights the potential of low-cost, accessible screening techniques to significantly enhance the discovery and characterization of algal strains with extreme traits. Ultimately, these methods support the development of robust algae-based resources, driving innovation in diverse industrial processes and environmental solutions.Graphical Abstract
Saucedo, Barbara (ORCID:0009000008860839)↗
Systems Level Engineering of Plant Cell Wall Biosynthesis to Improve Biofuel Feedstock Quality
Our new regulatory model of cell wall biosynthesis proposes original network architecture with several newly incorporated components. The mapped set of protein-DNA interactions will serve as a foundation for 1) understanding the regulation of a complex and integral plant component and 2) the manipulation of crop species for biofuel and biotechnology purposes. This study revealed interesting and novel aspects of grass growth and development and further enforce the importance of a grass model system. By functionally characterizing a suite of genes, we have begun to improve the sparse model for transcription regulation of biomass accumulation in grasses. In the process, we have advanced methodology and brachy molecular genetic tools that will serve as valuable community resource.
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