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Drosophila melanogaster--the model organism of choice for the complex biology of multi-cellular organisms
Drosophila melanogaster has been intensely studied for almost 100 years. The sophisticated array of genetic and molecular tools that have evolved for analysis of gene function in this organism are unique. Further, Drosophila is a complex multi-cellular organism in which many aspects of development and behavior parallel those in human beings. These combined advantages have permitted research in Drosophila to make seminal contributions to the understanding of fundamental biological processes and ensure that Drosophila will continue to provide unique insights in the genomic era. An overview of the genetic methodologies available in Drosophila is given here, together with examples of outstanding recent contributions of Drosophila to our understanding of cell and organismal biology. The growing contribution of Drosophila to our knowledge of gravity-related responses is addressed.
Purinyl-cobamide is a native prosthetic group of reductive dehalogenases
Here, cobamides such as vitamin B 12 are structurally conserved, cobalt-containing tetrapyrrole biomolecules that have essential biochemical functions in all domains of life. In organohalide respiration, a vital biological process for the global cycling of natural and anthropogenic organohalogens, cobamides are the requisite prosthetic groups for carbon–halogen bond-cleaving reductive dehalogenases. This study reports the biosynthesis of a new cobamide with unsubstituted purine as the lower base and assigns unsubstituted purine a biological function by demonstrating that Coα-purinyl-cobamide (purinyl-Cba) is the native prosthetic group in catalytically active tetrachloroethene reductive dehalogenases of Desulfitobacterium hafniense . Cobamides featuring different lower bases are not functionally equivalent, and purinyl-Cba elicits different physiological responses in corrinoid-auxotrophic, organohalide-respiring bacteria. Given that cobamide-dependent enzymes catalyze key steps in essential metabolic pathways, the discovery of a novel cobamide structure and the realization that lower bases can effectively modulate enzyme activities generate opportunities to manipulate functionalities of microbiomes.
Probabilistic measures for biological adaptation and resilience
This paper introduces an approach to quantifying ecological resilience in biological systems, particularly focusing on noisy systems responding to episodic disturbances with sudden adaptations. Incorporating concepts from nonequilibrium statistical mechanics, we propose a measure termed “ecological resilience through adaptation,” specifically tailored to noisy, forced systems that undergo physiological adaptation in the face of stressful environmental changes. Randomness plays a key role, accounting for model uncertainty and the inherent variability in the dynamical response among components of biological systems. Our measure of resilience is rooted in the probabilistic description of states within these systems and is defined in terms of the dynamics of the ensemble average of a model-specific observable quantifying success or well-being. Our approach utilizes stochastic linear response theory to compute how the expected success of a system, originally in statistical equilibrium, dynamically changes in response to a environmental perturbation and a subsequent adaptation. Importantly, the resulting mathematical derivations allow for the estimation of resilience in terms of ensemble averages of simulated or experimental data. Finally, through a simple but clear conceptual example, we illustrate how our resilience measure can be interpreted and compared to other existing frameworks in the literature. The methodology is general but inspired by applications in plant systems, with the potential for broader application to complex biological processes.
Phloem Exudate Protein Profiles during Drought and Recovery Reveal Abiotic Stress Responses in Tomato Vasculature
Drought is the leading cause of agricultural yield loss among all abiotic stresses, and the link between water deficit and phloem protein contents is relatively unexplored. Here we collected phloem exudates from Solanum lycopersicum leaves during periods of drought stress and recovery. Our analysis identified 2558 proteins, the most abundant of which were previously localized to the phloem. Independent of drought, enrichment analysis of the total phloem exudate protein profiles from all samples suggests that the protein content of phloem sap is complex, and includes proteins that function in chaperone systems, branched-chain amino acid synthesis, trehalose metabolism, and RNA silencing. We observed 169 proteins whose abundance changed significantly within the phloem sap, either during drought or recovery. Proteins that became significantly more abundant during drought include members of lipid metabolism, chaperone-mediated protein folding, carboxylic acid metabolism, abscisic acid signaling, cytokinin biosynthesis, and amino acid metabolism. Conversely, proteins involved in lipid signaling, sphingolipid metabolism, cell wall organization, carbohydrate metabolism, and a mitogen-activated protein kinase are decreased during drought. Our experiment has achieved an in-depth profiling of phloem sap protein contents during drought stress and recovery that supports previous findings and provides new evidence that multiple biological processes are involved in drought adaptation.
MOFA: Multi-objective Flux Analysis for the COBRA Toolbox
Environments of biological organisms are frequently nutrient and energy limited. This necessitates that systems exert tight regulation of trade-offs among key biological processes. Quantitative knowledge of these tradeoffs is essential for successful manipulation of biosystems (e.g., metabolic engineering projects). Using genome-scale constraint-based models of metabolism (GSMs), Multi-Objective Flux Analysis (MOFA) allows analyses of trade-offs among a system’s key biological tasks. The leading software for conducting a variety of constraint-based analyses using GSMs is the COBRA Toolbox for MATLAB. Results: We have developed a new add-on tool for COBRA that performs MOFA for a number of objectives only limited by computation power.
An ontology-based knowledge graph for representing interactions involving RNA molecules
The "RNA world" represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to each patient's biomolecular characteristics. Although scientific data about coding and non-coding RNA molecules are constantly produced and available from public repositories, they are scattered across different databases and a centralized, uniform, and semantically consistent representation of the "RNA world" is still lacking. We propose RNA-KG, a knowledge graph (KG) encompassing biological knowledge about RNAs gathered from more than 60 public databases, integrating functional relationships with genes, proteins, and chemicals and ontologically grounded biomedical concepts. To develop RNA-KG, we first identified, pre-processed, and characterized each data source; next, we built a meta-graph that provides an ontological description of the KG by representing all the bio-molecular entities and medical concepts of interest in this domain, as well as the types of interactions connecting them. Finally, we leveraged an instance-based semantically abstracted knowledge model to specify the ontological alignment according to which RNA-KG was generated. RNA-KG can be downloaded in different formats and also queried by a SPARQL endpoint. A thorough topological analysis of the resulting heterogeneous graph provides further insights into the characteristics of the "RNA world". RNA-KG can be both directly explored and visualized, and/or analyzed by applying computational methods to infer bio-medical knowledge from its heterogeneous nodes and edges. The resource can be easily updated with new experimental data, and specific views of the overall KG can be extracted according to the bio-medical problem to be studied.
Characterization of dependencies between growth and division in budding yeast
Cell growth and division are processes vital to the proliferation and development of life. Coordination between these two processes has been recognized for decades in a variety of organisms. In the budding yeast Saccharomyces cerevisiae, this coordination or ‘size control’ appears as an inverse correlation between cell size and the rate of cell-cycle progression, routinely observed in G1 prior to cell division commitment. Beyond this point, cells are presumed to complete S/G 2 /M at similar rates and in a size-independent manner. As such, studies of dependence between growth and division have focused on G1. Moreover, in unicellular organisms, coordination between growth and division has commonly been analyzed within the cycle of a single cell without accounting for correlations in growth and division characteristics between cycles of related cells. In a comprehensive analysis of three published time-lapse microscopy datasets, we analyze both intra- and inter-cycle dependencies between growth and division, revisiting assumptions about the coordination between these two processes. Interestingly, we find evidence (1) that S/G 2 /M durations are systematically longer in daughters than in mothers, (2) of dependencies between S/G2/M and size at budding that echo the classical G1 dependencies, and, (3) in contrast with recent bacterial studies, of negative dependencies between size at birth and size accumulated during the cell cycle. In addition, we develop a novel hierarchical model to uncover inter-cycle dependencies, and we find evidence for such dependencies in cells growing in sugar-poor environments. Our analysis highlights the need for experimentalists and modelers to account for new sources of cell-to-cell variation in growth and division, and our model provides a formal statistical framework for the continued study of dependencies between biological processes.
Systematic comparison of lncRNAs with protein coding mRNAs in population expression and their response to environmental change
Background: Long non-coding RNA (lncRNA) is a class of non-coding RNA with important regulatory roles in biological process of organisms. The systematic comparison of lncRNAs with protein coding mRNAs in population expression and their response to environmental change are still poorly understood. Here we identified 17,610 lncRNAs and calculated their expression levels based on RNA-seq of 80 individuals of Miscanthus lutarioriparius from two environments, the nearly native habitats and transplanted field, respectively. Results: LncRNAs had significantly higher expression diversity and lower expression frequency in population than protein coding mRNAs in both environments, which suggested that lncRNAs may experience more relaxed selection or divergent evolution in population compared with protein coding RNAs. In addition, the increase of expression diversity for lncRNAs was always significantly higher and the magnitude of fold change of expression in new stress environment was significantly larger than protein-coding mRNAs. These results suggested that lncRNAs may be more sensitive to environmental change than protein-coding mRNAs. Analysis of environment-robust and environment-specific lncRNA-mRNA co-expression network between two environments revealed the characterization of lncRNAs in response to environmental change. Furthermore, candidate lncRNAs contributing to water use efficiency (WUE) identified based on the WUE-lncRNA-mRNA co-expression network suggested the roles of lncRNAs in response to environmental change. Conclusion: Our study provided a comprehensive understanding of expression characterization of lncRNAs in population for M. lutarioriparius under field condition, which would be useful to explore the roles of lncRNAs and could accelerate the process of adaptation in new environment for many plants.
Automated Fluidics Device for Extraction and Quantification of miRNA Biomarkers From Blood
Radiation Assessment DuRing Exposure And long-Duration Spaceflight (RADREADS) demonstrates space-compatible point-of-care technology for quantitative biological monitoring of blood miRNA biomarkers in response to long-term low dose radiation exposure. This individualized monitoring approach will inform targeted treatment strategies to maximize medical resource utilization by accounting for individual susceptibility to radiation-related illnesses. As human spaceflight progresses beyond Earth’s magnetic shielding, radiation exposure poses a significant risk to astronaut health and safety. Extended operation in this environment comes with an increased risk of radiation exposure, leading to higher risks of radiation sickness, cancer, central nervous system effects, and degenerative diseases. While conventional physical dosimetry techniques capture radiation dose, individualistic susceptibility to radiation damage is varied. Multiple characteristics, including age, body weight, sex, genetics, and immune status, have been found to influence radiosensitivity (Liu et al. 2011, and Bouffler 2016). This differential response necessitates individualized monitoring and targeted treatment strategies to maximize medical resource utilization; however, a practical diagnostic platform for quantifying long-term, low dose radiation-induced tissue damage does not currently exist. MicroRNAs (miRNAs) are a class of small, non-coding RNAs that regulate gene expression by mediating the degradation of messenger RNA. The levels of particular miRNAs are influenced by biological processes such as inflammation and serve as biomarkers for a variety of conditions including cancer (Singh et al. 2017). MicroRNAs are found in various bodily fluids and are amenable to collection via liquid biopsies, providing a minimally invasive and easily quantifiable readout for a variety of radiosensitive reporters. A preliminary signature of 15 spaceflight sensitive miRNA has been identified in rodent and human studies, including miR-21-5p, miR-24-3p, miR-92a-3p, miR-17-5p, miR-16a-3p, miR-34a-3p, and miR-223-3p. These targets generally increased expression with radiation dose and linear energy transfer, though variation between individuals is not yet described. Current gaps in the field include a lack of understanding of longitudinal biological responses to long-term, low dose radiation exposure and the absence of space-compatible point-of-care technology for quantitative biological monitoring. In this body of work, we aim to develop an automated bleed-to-read system to process whole blood for the detection of miRNA biomarkers in order to monitor individualistic responses to radiation exposure. This will be achieved via separating serum (or plasma) from whole blood, followed by extraction, amplification, and quantification of the miRNA using a RT-qPCR reaction. Previously, the WetLab-2 hardware enabled execution of a RT-qPCR reaction aboard ISS; however, it is a manual system that requires crew manipulation and bulky components (Parra et al. 2017). To address these issues, automated fluid handling hardware was developed for each stage of sample preparation. Extraction of total RNA is achieved by sequentially pumping reagents through an off-the-shelf nucleic acid binding column (miRNeasy Serum/Plasma Advanced Kit, Qiagen). This approach eliminates several manual pipetting and centrifuging steps and limits the use of toxic chemicals commonly found in other sample processing techniques. The resulting elution will then be automatically dispensed for RT-qPCR analysis using a compact rotary qPCR (Mic qPCR Cycler, Bio Molecular Systems) that will improve spaceflight compatibility by removing bubbles from the detection region, another challenge highlighted by WetLab-2 (Parra et al. 2017). Efforts are also being made to simplify the RT-qPCR reaction to a 1-step air-dryable mix to improve long-term reagent stability at room temperature and reduce system complexity. By automating the RT-qPCR processes via microfluidic manipulation, RADREADS will reduce crewmember hands-on time and enable the personalized detection of radiation-induced tissue damage during long duration missions. Minimally invasive, longitudinal monitoring of individual’s response to radiation exposure will inform how the physiological system responds to long-term low dose space radiation and enables development of targeted countermeasures by the medical team. Ultimately, this portable technology will require minimal technical expertise and can also be used to monitor miRNA biomarkers associated with other diseases.
Conformational landscape of a virus by single-particle X-ray scattering
Using a manifold-based analysis of experimental diffraction snapshots from an X-ray free electron laser, we determine the three-dimensional structure and conformational landscape of the PR772 virus to a detector-limited resolution of 9 nm. Our results indicate that a single conformational coordinate controls reorganization of the genome, growth of a tubular structure from a portal vertex and release of the genome. Furthermore, these results demonstrate that single-particle X-ray scattering has the potential to shed light on key biological processes.
The Roles of Tidal Marshes in the Estuarine Biochemical Processes: A Numerical Modeling Study
Observations suggest that the existence of tidal marsh can alter the oxygen and nutrient dynamics in adjacent water bodies, but assessing the impacts of large tidal marshes on an estuary is challenging. In this study, we use a modeling approach to investigate the roles of tidal marshes on the estuarine biochemical processes. The marsh model, which simulates the ecological functions of marshes at seasonal and annual time-scales, is embedded inside an unstructured-grid three-dimensional hydrodynamic and eutrophication model (SCHISM-ICM). This modeling system simulates the growth and metabolism of the tidal marshes and links biological processes to nutrient dynamics in the water column and sediment. This model dynamically simulates nutrient recycling and physical transport of the materials between marshes and open water through wetting-drying processes. This coupled model system is validated and successfully applied to the York River Estuary. Model results suggest that tidal marshes influence the local diurnal dissolved oxygen (DO) cycle by exporting dissolved organic carbon and high sediment oxygen demand in the marsh system through the tidal exchange. The high deposition rates of organics and diurnal DO cycle enhance the sediment release of phosphorus. On the other hand, marshes tend to decrease dissolved inorganic nitrogen in the water column by settling particulate nutrients and enhancing the denitrification process. The study demonstrates that tidal marshes exert substantial impacts on the estuarine biochemical processes. The developed tidal marsh model enhances eutrophication modeling and advances the understanding of the feedback effects between marsh biogeochemistry and estuarine eutrophication processes on a systemic scale.
Altered Expression of Two Small Secreted Proteins (ssp4 and ssp6) Affects the Degradation of a Natural Lignocellulosic Substrate by Pleurotus ostreatus
Pleurotus ostreatus is a white-rot fungus that can degrade lignin in a preferential manner using a variety of extracellular enzymes, including manganese and versatile peroxidases (encoded by the vp1-3 and mnp1-6 genes, respectively). This fungus also secretes a family of structurally related small secreted proteins (SSPs) encoded by the ssp1-6 genes. Using RNA sequencing (RNA-seq), we determined that ssp4 and ssp6 are the predominant members of this gene family that were expressed by P. ostreatus during the first three weeks of growth on wheat straw. Downregulation of ssp4 in a strain harboring an ssp RNAi construct (KDssp1) was then confirmed, which, along with an increase in ssp6 transcript levels, coincided with reduced lignin degradation and the downregulation of vp2 and mnp1. In contrast, we observed an increase in the expression of genes related to pectin and side-chain hemicellulose degradation, which was accompanied by an increase in extracellular pectin-degrading capacity. Genome-wide comparisons between the KDssp1 and the wild-type strains demonstrated that ssp silencing conferred accumulated changes in gene expression at the advanced cultivation stages in an adaptive rather than an inductive mode of transcriptional response. Based on co-expression networking, crucial gene modules were identified and linked to the ssp knockdown genotype at different cultivation times. Based on these data, as well as previous studies, we propose that P. ostreatus SSPs have potential roles in modulating the lignocellulolytic and pectinolytic systems, as well as a variety of fundamental biological processes related to fungal growth and development.
Hydrogen density mapping in biomolecular crystals through dynamic nuclear polarization
Many fundamental biological processes, including those in photosynthetic reaction centers and enzyme active sites, involve charge and energy transfer, bond cleavage, protonation and hydrogen bonding. Because H atoms play such central roles in these reactions, accurately determining their positions is essential. Yet, conventional X-ray crystallography primarily resolves the heavy atoms in biological structures and provides limited insight into hydrogen, even at atomic resolution. Neutron macromolecular crystallography (NMC) overcomes this limitation by offering exceptional sensitivity to hydrogen and deuterium. Here, we present a theoretical framework for the development of dynamic nuclear polarization NMC (DNP-NMC) techniques, which exploit the alignment of neutron and proton nuclear spins to enhance and tune the hydrogen signal contribution. The DNP-NMC approach advances the resolution of H atoms within biomolecular crystals, whether bound to protein residues or present in solvent. The method establishes key relationships for the coherent structure factor of polarized neutron scattering from hydrogenous matter. It theoretically achieves full accuracy in phase reconstruction and offers a path to improve neutron structure determination, achieving accuracies exceeding ≳80% by incorporating titration states. Using a variant of the hybrid input/output phase-retrieval algorithm, it allows recovery of the hydrogen density with ≳90% phase accuracy. In conclusion, we further discuss sources of experimental uncertainty for the upcoming DNP-enabled, quasi-Laue IMAGINE-X experiment at Oak Ridge National Laboratory's High Flux Isotope Reactor.
Exponential kinetics of formation of organic microstructures
Organic microstructure production in Miller-Urey spark discharge flasks is an energy-dependent, autocatalytic process which follows first order kinetics similar to microbial growth curves. These relationships hold for all three major morphological types of microstructures observed. The three types are assembled from smaller precursor subunits which associate according to a binomial distribution. These structures could have formed bounded systems in which pre-biological processes might have occurred.
The MSP 2001 Mars Environmental Compatibility Assessment (MECA)
The Mars Environmental Compatibility Assessment (MECA) will evaluate the Martian environment for soil and dust-related hazards to human exploration as part of the Mars Surveyor Program 2001 Lander. Sponsored by the Human Exploration and Development of Space (HEDS) enterprise, MECA's goal is to evaluate potential geochemical and environmental hazards that may confront future Martian explorers, and to guide HEDS scientists in the development of high fidelity Mars soil simulants. The integrated MECA payload contains a wet-chemistry laboratory, a microscopy station, an electrometer to characterize the electrostatics of the soil and its environment, and arrays of material patches to study the abrasive and adhesive properties of soil grains. The instrument will acquire soil samples with a robotic arm equipped with a camera. MECA will examine surface and subsurface soil and dust in order to characterize particle size, shape, hardness, and also physical characteristics that may provide clues to mineralogy. MECA will characterize soil/water mixtures with respect to pH, redox potential, total dissolved ions, and trace toxins. MECA will determine the nature of electrostatic charging associated with excavation of soil, and the influence of ionizing radiation on material properties. It will also observe natural dust accumulation on engineering materials. To accomplish these objectives, MECA is allocated a mass of 10 kg within an enclosure of 35 x 25 x 15 cm. The Wet Chemistry Laboratory (WCL) consists of four identical cells that will accept samples from surface and subsurface regions accessible to the Lander's robotic arm, mix them with water, and perform extensive analysis of the solution. Ion-selective electrodes and related sensors will evaluate total dissolved solids, redox potential, pH, and the concentration of many soluble ions and gases in wet Martian soil. These electrodes can detect potentially dangerous heavy-metal ions, emitted pathogenic gases, and the soil's corrosive potential. Experiments will include cyclic voltammetry and anodic stripping voltammetry. Complementary to the Viking experiments, the chemical laboratory will characterize the water-soil solution rather than emitted gases. Nonetheless, through analysis of dissolved gases it will be able to replicate many of the Viking observations related to oxidants. MECA's microscopy station combines optical and atomic-force microscopy (AFM) in an actively focused, controlled illumination environment to image particles from millimeters to nanometers in size. Careful selection of substrates allows controlled experiments in adhesion, abrasion, hardness, aggregation, magnetic and other properties. Special tools allow primitive manipulation (brushing and scraping) of samples. Soil particle properties including size, shape, color, hardness, adhesive potential (electrostatic and magnetic), will be determined using an array of sample receptacles and collection substrates. The simple, rugged atomic-force microscope will image in the submicron size range and has the capability of performing a particle-by-particle analysis of the dust and soil. On Earth, the earliest forms of life are preserved as microfossils. The atomic-force microscope will have the required resolution to image down to the scale of terrestrial microfossils and beyond. Mounted on the end of the robot arm, MECA's electrometer actually consists of four types of sensors: an electric field meter, several triboelectricity monitors, an ion gauge, and a thermometer. Tempered only by ultraviolet-light-induced ions and a low-voltage breakdown threshold, the dry, cold, dusty martian environment presents an imposing electrostatic hazard to both robots and humans. The field meter will measure the ambient field on nearby objects while the triboelectric sensors, using identical circuitry, will measure the charge accumulated on test substances as they are dragged through the soil by the arm. The ion chamber, open to the environment, will sense both charged dust and free ions in the air. Over and above the potential threat to electronics, the electrostatic environment holds one of the keys to transport of dust and, consequently, Martian meteorology. Viewed with the robot arm camera, the abrasion and adhesion plates are strategically placed to allow direct observation of the interaction between materials and soils on a macroscopic scale. Materials of graded hardness are placed directly under the robot arm scoop to sense wear and soil hardness. A second array, placed on the lander deck, is deployed after the dust plume of landing has settled. It can be manipulated in a primitive fashion by the arm, first having dirt deposited on it from the scoop and subsequently shaken clean. A third array will passively collect dust from the atmosphere. In addition to objectives related to human exploration, the MECA data set will be rich in information relevant to basic geology, paleoclimate, and exobiology issues. To understand both contemporaneous and ancient processes on Mars, the mineralogy, petrology, and reactivity of Martian surface materials should be constrained. The MECA experiment will shed light on these quantities through its combination of chemistry and microscopy. MECA will be capable of measuring the composition of ancient surface water environments, observing microscopic evidence of geological (and biological?) processes, inferring soil and dust transport, comminution and weathering mechanisms, and characterizing soil horizons that might be encountered during excavation.
Analysis of putative quadruplex-forming sequences in fungal genomes: novel antifungal targets?
Fungal infections cause >1 million deaths annually and the emergence of antifungal resistance has prompted the exploration for novel antifungal targets. Quadruplexes are four-stranded nucleic acid secondary structures, which can regulate processes such as transcription, translation, replication and recombination. They are also found in genes linked to virulence in microbes, and ligands that bind to quadruplexes can eliminate drug-resistant pathogens. Using a computational approach, we quantified putative quadruplex-forming sequences (PQS) in 1359 genomes across the fungal kingdom and explored their presence in genes related to virulence, drug resistance and biological processes associated with pathogenicity in Aspergillus fumigatus. Here we present the largest analysis of PQS in fungi and identify significant heterogeneity of these sequences throughout phyla, genera and species. PQS were genetically conserved in Aspergillus spp. and frequently pathogenic species appeared to contain fewer PQS than their lesser/non-pathogenic counterparts. GO-term analysis identified that PQS-containing genes were involved in processes linked with virulence such as zinc ion binding, the biosynthesis of secondary metabolites and regulation of transcription in A. fumigatus. Although the genome frequency of PQS was lower in A. fumigatus, PQS could be found enriched in genes involved in virulence, and genes upregulated during germination and hypoxia. Moreover, PQS were found in genes involved in drug resistance. Quadruplexes could have important roles within fungal biology and virulence, but their roles require further elucidation.
Biochemical and structural characterization of enzymes in the 4-hydroxybenzoate catabolic pathway of lignin-degrading white-rot fungi
White-rot fungi (WRF) are the most efficient lignin-degrading organisms in nature. However, their capacity to use lignin-related aromatic compounds, such as 4-hydroxybenzoate, as carbon sources has only been described recently. Previously, the hydroxyquinol pathway was proposed for the bioconversion of these compounds in fungi, but gene- and structure-function relationships of the full enzymatic pathway remain uncharacterized in any single fungal species. Here, we characterize seven enzymes from two WRF, Trametes versicolor and Gelatoporia subvermispora, which constitute a four-enzyme cascade from 4-hydroxybenzoate to β-ketoadipate via the hydroxyquinol pathway. Furthermore, we solve the crystal structure of four of these enzymes and identify mechanistic differences with the closest bacterial and fungal structural homologs. Overall, this research expands our understanding of aromatic catabolism by WRF and establishes an alternative strategy for the conversion of lignin-related compounds to the valuable molecule β-ketoadipate, contributing to the development of biological processes for lignin valorization.