Expression of dehydroshikimate dehydratase in poplar induces transcriptional and metabolic changes in the phenylpropanoid pathway.

Modification of lignin in feedstocks via genetic engineering aims to reduce biomass recalcitrance to facilitate efficient conversion processes. These improvements can be achieved by expressing exogenous enzymes that interfere with native biosynthetic pathways responsible for the production of the lignin precursors. In planta expression of a bacterial 3-dehydroshikimate dehydratase in poplar trees reduced lignin content and altered the monomer composition, which enabled higher yields of sugars after cell wall polysaccharide hydrolysis.

Ectopic Production of 3,4-Dihydroxybenzoate Affects Cellulose Structure and Organization.

Lignocellulosic biomass is a highly sustainable and largely carbon dioxide neutral feedstock for the production of biofuels and advanced biomaterials. Although thermochemical pretreatment is typically used to increase the efficiency of cell wall deconstruction, genetic engineering of the major plant cell wall polymers, especially lignin, has shown promise as an alternative approach to reduce biomass recalcitrance. Poplar trees with reduced lignin content and altered composition were previously developed by overexpressing bacterial 3-dehydroshikimate dehydratase (QsuB) enzyme to divert carbon flux from the shikimate pathway.

Putative rhamnogalacturonan-II glycosyltransferase identified through callus gene editing which bypasses embryo lethality.

Rhamnogalacturonan II (RG-II) is a structurally complex and conserved domain of the pectin present in the primary cell walls of vascular plants. Borate cross-linking of RG-II is required for plants to grow and develop normally. Mutations that alter RG-II structure also affect cross-linking and are lethal or severely impair growth.

Convergence in simulating global soil organic carbon by structurally different models after data assimilation.

Current biogeochemical models produce carbon-climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage.

Physics-Based Machine Learning Models Predict Carbon Dioxide Solubility in Chemically Reactive Deep Eutectic Solvents.

Carbon dioxide (CO) is a detrimental greenhouse gas and is the main contributor to global warming. In addressing this environmental challenge, a promising approach emerges through the utilization of deep eutectic solvents (DESs) as an ecofriendly and sustainable medium for effective CO capture. Chemically reactive DESs, which form chemical bonds with the CO, are superior to nonreactive, physically based DESs for CO absorption.

Agricultural Waste Management by Production of Second-Generation Bioethanol from Sugarcane Bagasse Using Indigenous Yeast Strain.

In the wake of rapid industrialization and burgeoning transportation networks, the escalating demand for fossil fuels has accelerated the depletion of finite energy reservoirs, necessitating urgent exploration of sustainable alternatives. To address this, current research is focusing on renewable fuels like second-generation bioethanol from agricultural waste such as sugarcane bagasse. This approach not only circumvents the contentious issue of food-fuel conflicts associated with biofuels but also tackles agricultural waste management.

Discovery of Borosin Catalytic Strategies and Function through Bioinformatic Profiling.

Borosins are ribosomally synthesized and post-translationally modified peptides (RiPPs) containing backbone α--methylations. These modifications confer favorable pharmacokinetic properties including increased membrane permeability and resistance to proteolytic degradation. Previous studies have biochemically and bioinformatically explored several borosins, revealing (1) numerous domain architectures and (2) diverse core regions lacking conserved sequence elements.

Perspective on Lignin Conversion Strategies That Enable Next Generation Biorefineries.

The valorization of lignin, a currently underutilized component of lignocellulosic biomass, has attracted attention to promote a stable and circular bioeconomy. Successful approaches including thermochemical, biological, and catalytic lignin depolymerization have been demonstrated, enabling opportunities for lignino-refineries and lignocellulosic biorefineries. Although significant progress in lignin valorization has been made, this review describes unexplored opportunities in chemical and biological routes for lignin depolymerization and thereby contributes to economically and environmentally sustainable lignin-utilizing biorefineries.

Utilization of microalgae for agricultural runoff remediation and sustainable biofuel production through an integrated biorefinery approach.

Generally wastewater such agricultural runoff is considered a nuisance; however, it could be harnessed as a potential source of nutrients like nitrates and phosphates in integrated biorefinery context. In the current study, microalgae Chlorella sp. S5 was used for bioremediation of agricultural runoff and the leftover algal biomass was used as a potential source for production of biofuels in an integrated biorefinery context.

A map of the rubisco biochemical landscape.

Rubisco is the primary CO fixing enzyme of the biosphere yet has slow kinetics. The roles of evolution and chemical mechanism in constraining the sequence landscape of rubisco remain debated. In order to map sequence to function, we developed a massively parallel assay for rubisco using an engineered where enzyme function is coupled to growth.

Triumphs and Challenges of Natural Product Discovery in the Postgenomic Era.

Natural products have played significant roles as medicine and food throughout human history. Here, we first provide a brief historical overview of natural products, their classification and biosynthetic origins, and the microbiological and genetic methods used for their discovery. We also describe and discuss the technologies that revolutionized the field, which transitioned from classic genetics to genome-centric discovery approximately two decades ago.

Genome-scale model development and genomic sequencing of the oleaginous clade .

The clade contains oleaginous yeast species with advantageous metabolic features for biochemical and biofuel production. Limited knowledge about the metabolic networks of the species and limited tools for genetic engineering have led to a relatively small amount of research on the microbes. Here, a genome-scale metabolic model (GSM) of NRRL Y-11557 was built using orthologous protein mappings to model yeast species.

Yeast Platforms for Production and Screening of Bioactive Derivatives of Rauwolscine.

Monoterpene indole alkaloids (MIAs) make up a highly bioactive class of metabolites produced by a range of tropical and subtropical plants. The corynanthe-type MIAs are a stereochemically complex subclass with therapeutic potential against a large number of indications including cancer, psychotic disorders, and erectile dysfunction. Here, we report yeast-based cell factories capable of de novo production of corynanthe-type MIAs rauwolscine, yohimbine, tetrahydroalstonine, and corynanthine.

Elucidation of genes enhancing natural product biosynthesis through co-evolution analysis.

Streptomyces has the largest repertoire of natural product biosynthetic gene clusters (BGCs), yet developing a universal engineering strategy for each Streptomyces species is challenging. Given that some Streptomyces species have larger BGC repertoires than others, we proposed that a set of genes co-evolved with BGCs to support biosynthetic proficiency must exist in those strains, and that their identification may provide universal strategies to improve the productivity of other strains. We show here that genes co-evolved with natural product BGCs in Streptomyces can be identified by phylogenomics analysis.

Spatial co-transcriptomics reveals discrete stages of the arbuscular mycorrhizal symbiosis.

The symbiotic interaction of plants with arbuscular mycorrhizal (AM) fungi is ancient and widespread. Plants provide AM fungi with carbon in exchange for nutrients and water, making this interaction a prime target for crop improvement. However, plant-fungal interactions are restricted to a small subset of root cells, precluding the application of most conventional functional genomic techniques to study the molecular bases of these interactions.

An Engineered Laccase from Accelerates Lignocellulose Degradation.

Laccases from white-rot fungi catalyze lignin depolymerization, a critical first step to upgrading lignin to valuable biodiesel fuels and chemicals. In this study, a wildtype laccase from the basidiomycete (Fom_lac) and a variant engineered to have a carbohydrate-binding module (Fom_CBM) were studied for their ability to catalyze cleavage of β-O-4' ether and C-C bonds in phenolic and non-phenolic lignin dimers using a nanostructure-initiator mass spectrometry-based assay. Fom_lac and Fom_CBM catalyze β-O-4' ether and C-C bond breaking, with higher activity under acidic conditions (pH < 6).

The complex polyploid genome architecture of sugarcane.

Sugarcane, the world's most harvested crop by tonnage, has shaped global history, trade and geopolitics, and is currently responsible for 80% of sugar production worldwide. While traditional sugarcane breeding methods have effectively generated cultivars adapted to new environments and pathogens, sugar yield improvements have recently plateaued. The cessation of yield gains may be due to limited genetic diversity within breeding populations, long breeding cycles and the complexity of its genome, the latter preventing breeders from taking advantage of the recent explosion of whole-genome sequencing that has benefited many other crops.

Biosynthesis of Strained Amino Acids by a PLP-Dependent Enzyme through Cryptic Halogenation.

Amino acids (AAs) are modular building blocks which nature uses to synthesize both macromolecules, such as proteins, and small molecule natural products, such as alkaloids and non-ribosomal peptides. While the 20 main proteinogenic AAs display relatively limited side chain diversity, a wide range of non-canonical amino acids (ncAAs) exist that are not used by the ribosome for protein synthesis, but contain a broad array of structural features and functional groups. In this communication, we report the discovery of the biosynthetic pathway for a new ncAA, pazamine, which contains a cyclopropane ring formed in two steps.

Edible mycelium bioengineered for enhanced nutritional value and sensory appeal using a modular synthetic biology toolkit.

Filamentous fungi are critical in the transition to a more sustainable food system. While genetic modification of these organisms has promise for enhancing the nutritional value, sensory appeal, and scalability of fungal foods, genetic tools and demonstrated use cases for bioengineered food production by edible strains are lacking. Here, we develop a modular synthetic biology toolkit for Aspergillus oryzae, an edible fungus used in fermented foods, protein production, and meat alternatives.

Engineered as a Biosynthetic Platform of Nucleotide Sugars.

Glycosylation of biomolecules can greatly alter their physicochemical properties, cellular recognition, subcellular localization, and immunogenicity. Glycosylation reactions rely on the stepwise addition of sugars using nucleotide diphosphate (NDP)-sugars. Making these substrates readily available will greatly accelerate the characterization of new glycosylation reactions, elucidation of their underlying regulation mechanisms, and production of glycosylated molecules.

Land Resources for Wind Energy Development Requires Regionalized Characterizations.

Estimates of the land area occupied by wind energy differ by orders of magnitude due to data scarcity and inconsistent methodology. We developed a method that combines machine learning-based imagery analysis and geographic information systems and examined the land area of 318 wind farms (15,871 turbines) in the U.S.