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At least 289 records · Page 16

Metabolic dependencies govern microbial syntrophies during methanogenesis in an anaerobic digestion ecosystem

Methanogenesis, a biological process mediated by complex microbial communities, has attracted great attention due to its contribution to global warming and potential in biotechnological applications. The current study unveiled the core microbial methanogenic metabolisms in anaerobic vessel ecosystems by applying combined genome-centric metagenomics and metatranscriptomics. Here, we demonstrate that an enriched natural system, fueled only with acetate, could support a bacteria-dominated microbiota employing a multi-trophic methanogenic process. Moreover, significant changes, in terms of microbial structure and function, were recorded after the system was supplemented with additional H 2 . Methanosarcina thermophila, the predominant methanogen prior to H 2 addition, simultaneously performed acetoclastic, hydrogenotrophic, and methylotrophic methanogenesis. The methanogenic pattern changed after the addition of H 2 , which immediately stimulated Methanomicrobia-activity and was followed by a slow enrichment of Methanobacteria members. Interestingly, the essential genes involved in the Wood-Ljungdahl pathway were not expressed in bacterial members. The high expression of a glycine cleavage system indicated the activation of alternative metabolic pathways for acetate metabolism, which were reconstructed in the most abundant bacterial genomes. Moreover, as evidenced by predicted auxotrophies, we propose that specific microbes of the community were forming symbiotic relationships, thus reducing the biosynthetic burden of individual members. These results provide new information that will facilitate future microbial ecology studies of interspecies competition and symbiosis in methanogenic niches.

59 BASIC BIOLOGICAL SCIENCES↗

Intelligent Consequence Control by Aerial Reconnoiter Using Unmanned Systems

In a nuclear accident, or in the aftermath of an improvised nuclear device or radiological dispersal device detonation, radioactive materials may pose a severe health threat to individuals near the site of the incident. The Intelligent Consequence Control by Aerial Reconnoiter Using Unmanned Systems (ICARUS) does the dull, dirty, and dangerous (and, sometimes, deep) work of mapping and characterizing valuable information to enable a safe and appropriate response. ICARUS provides timely answers to the questions, “What is it?” “Where is it?”, and “How far does it extend?” Using commercial, off-the-shelf proven components, the integrated chemical, biological, radiological, nuclear, and explosives detection architecture for our drones provides a solution for collecting radiological, chemical, and optical information on developing complex situations, returning actionable data for determining if it is safe for further response efforts. ICARUS can determine and transmit the location, identity, and intensity of radionuclide contamination to a remote base station. It can deliver on the unexpected.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

North‐East Peri‐Tethyan Water Column Deoxygenation and Euxinia at the Paleocene Eocene Thermal Maximum

Abstract The Paleocene–Eocene Thermal Maximum (PETM) is associated with climatic change and biological turnover. It shares features with the Oceanic Anoxic Events (OAEs) of the Mesozoic, such as transient global warming and biogeochemical perturbations. However, the PETM experienced a more muted expansion of marine anoxia compared to the Mesozoic OAEs (especially OAE2), with geographically limited evidence for photic zone euxinia (PZE). We explore the extent and drivers of marine deoxygenation during the PETM using biomarkers for water column euxinia and anoxia as well as an intermediate complexity Earth system model (cGEnIE). These reveal that the water column in the North‐East Peri‐Tethys became anoxic, with euxinic conditions reaching the photic zone (PZE) during the PETM. Our model shows that euxinia developed due to a global increase in the ocean nutrient inventory with concomitant oxygen consumption, similar to findings for OAE2. The particularly strong regional response in the NE Peri‐Tethys appears to arise from a combination of global CO 2 ‐weathering forcing, regionally restricted circulation and upwelling of sulphidic thermocline waters. Unlike OAE2, anoxia and PZE do not become widespread in our PETM simulations, consistent with new and existing geochemical and biological proxy data. This globally muted response could result from reduced biogeochemical feedbacks to climate forcing relative to the mid‐Cretaceous climate. Our observations suggest that similar mechanisms operated in response to disparate Cenozoic (PETM) and Mesozoic (OAEs) transient global warming events, while also highlighting that background conditions are crucial in modulating the sensitivity of Earth's system to them.

Behrooz, L.↗

Assembly and Analysis of Cell-Scale Membrane Envelopes

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms-a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Activity-Based Sensing Approach to Monitor Nanomaterial-Promoted Changes in Labile Metal Pools in Living Systems

Metal-based nanoparticles are a promising class of materials for diagnosis and treatment of cancer and other diseases. However, mechanisms of action of these nanomedicines remain insufficiently understood due in large part to our limited understanding of the dynamic equilibria between solid metal nanoparticles and labile metal ions generated from these nanoparticles within complex biological milieus. Here, we apply activitybased sensing to directly identify and investigate the fate of labile copper pools with metal and oxidation state-specificity generated by anticancer copper nanomedicines. We found that treatment of cells with copper-releasing nanoparticles alter labile Cu(I)/Cu(II) ratios through an increase in labile Cu(II), while overall labile copper levels decrease. Labile copper release triggers compensatory responses in two major antioxidant pathways, glutathione (GSH) and nuclear factor erythroid 2-related factor 2 (NRF2), as well as in metal homeostasis to limit copper availability via regulation of copper export (ATP7B) and copper import (CTR1) proteins. These findings establish the value of activity-based sensing as a generalizable approach for labile metal imaging to help decipher molecular mechanisms of bioactive metal nanoparticles and guide the development of more effective nanomedicine diagnostics and therapies to target metal-dependent disease vulnerabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unimodal Imaging of Monovalent Metal-Chelator Complexes and Lipids by MALDI Imaging Mass Spectrometry

Careful regulation of monovalent metal ions (M + ) is necessary to maintain a functional cellular system. Of these ions, appropriate sodium (Na + ) and potassium (K + ) concentrations are particularly integral for electrochemical signaling, as well as the secondary transport of nutrients and waste. Dysregulation of M + homeostasis can disrupt these mechanisms, potentially influencing the metabolism of downstream biomolecules such as lipids. Thus, the relationship between M + abundances and related biomolecular distributions must be elucidated to better understand the physiology of healthy and disordered tissues. Traditional techniques for imaging biological metal distributions include SIMS, LA-ICP-MS, and XRF; however, these capabilities are limited to elemental analysis or the analysis of molecular fragments and must be paired with other modalities to visualize distributions of more complex biomolecules within the same or similar samples. Conversely, matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool often used for mapping such biomolecular distributions, but current methods are unable to detect metals within tissue. This study illustrates a novel methodology that adds metal detection to the MALDI IMS repertoire through which the simultaneous detection of M + metals and lipids is achievable. Using a robotic sprayer for homogeneous application, on-tissue deposition of the chelator deferiprone (DEF) enables subsequent detection of the ionizable metal-chelator complex by MALDI without hindering lipid detection. Our work provides proof-of-concept data for the simultaneous detection of K + , Na + , and intact lipids using MALDI IMS.

59 BASIC BIOLOGICAL SCIENCES↗

Virus-Like Particles (VLPs) as a Platform for Hierarchical Compartmentalization

Hierarchically self-assembled structures are common in biology, but it is often challenging to design and fabricate synthetic analogs. The archetypal cell is defined by hierarchically organized multicompartmentalized structures with boundaries that delineate the interior from exterior environments and is an inspiration for complex functional materials. Here, we have demonstrated an approach to the design and construction of a nested protein cage system that can additionally incorporate the packing of other functional macromolecules and exhibit some of the features of a minimal synthetic cell-like material. We have demonstrated a strategy for controlled co-packaging of subcompartments, ferritin (Fn) cages, together with active cellobiose-hydrolyzing β-glycosidase enzyme macromolecules, CelB, inside the sequestered volume of the bacteriophage P22 capsid. Using controlled in vitro assembly, we were able to modulate the stoichiometry of Fn cages and CelB encapsulated inside the P22 to control the degree of compartmentalization. The co-encapsulated enzyme CelB showed catalytic activity even when packaged at high total macromolecular concentrations comparable to an intracellular environment. Here, this approach could be used as a model to create synthetic protein-based protocells that can confine smaller functionalized proto-organelles and additional macromolecules to support a range of biochemical reactions.

59 BASIC BIOLOGICAL SCIENCES↗

Crystallization of ApoA1 and ApoE4 Nanolipoprotein Particles and Initial XFEL-Based Structural Studies

Nanolipoprotein particles (NLPs), also called “nanodiscs”, are discoidal particles with a patch of lipid bilayer corralled by apolipoproteins. NLPs have long been of interest due to both their utility as membrane-model systems into which membrane proteins can be inserted and solubilized and their physiological role in lipid and cholesterol transport via high-density lipoprotein (HDL) and low-density lipoprotein (LDL) maturation, which are important for human health. Serial femtosecond crystallography (SFX) at X-ray free electron lasers (XFELs) is a powerful approach for structural biology of membrane proteins, which are traditionally difficult to crystallize as large single crystals capable of producing high-quality diffraction suitable for structure determination. To facilitate understanding of the specific role of two apolipoprotein/lipid complexes, ApoA1 and ApoE4, in lipid binding and HDL/LDL particle maturation dynamics, and to develop new SFX methods involving NLP membrane protein encapsulation, we have prepared and crystallized homogeneous populations of ApoA1 and ApoE4 NLPs. Crystallization of empty NLPs yields semi-ordered objects that appear crystalline and give highly anisotropic and diffuse X-ray diffraction, similar to fiber diffraction. Several unit cell parameters were approximately determined for both NLPs from these measurements. Thus, low-background, sample conservative methods of delivery are critical. Here we implemented a fixed target sample delivery scheme utilizing the Roadrunner fast-scanning system and ultra-thin polymer/graphene support films, providing a low-volume, low-background approach to membrane protein SFX. This study represents initial steps in obtaining structural information for ApoA1 and ApoE4 NLPs and developing this system as a supporting scaffold for future structural studies of membrane proteins crystalized in a native lipid environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advances in 3D Gel Printing for Enzyme Immobilization

Incorporating enzymes with three-dimensional (3D) printing is an exciting new field of convergence research that holds infinite potential for creating highly customizable components with diverse and efficient biocatalytic properties. Enzymes, nature’s nanoscale protein-based catalysts, perform crucial functions in biological systems and play increasingly important roles in modern chemical processing methods, cascade reactions, and sensor technologies. Immobilizing enzymes on solid carriers facilitates their recovery and reuse, improves stability and longevity, broadens applicability, and reduces overall processing and chemical conversion costs. Three-dimensional printing offers extraordinary flexibility for creating high-resolution complex structures that enable completely new reactor designs with versatile sub-micron functional features in macroscale objects. Immobilizing enzymes on or in 3D printed structures makes it possible to precisely control their spatial location for the optimal catalytic reaction. Combining the rapid advances in these two technologies is leading to completely new levels of control and precision in fabricating immobilized enzyme catalysts. The goal of this review is to promote further research by providing a critical discussion of 3D printed enzyme immobilization methods encompassing both post-printing immobilization and immobilization by physical entrapment during 3D printing. Especially, 3D printed gel matrix techniques offer mild single-step entrapment mechanisms that produce ideal environments for enzymes with high retention of catalytic function and unparalleled fabrication control. Examples from the literature, comparisons of the benefits and challenges of different combinations of the two technologies, novel approaches employed to enhance printed hydrogel physical properties, and an outlook on future directions are included to provide inspiration and insights for pursuing work in this promising field.

3D printing↗

Controlling Protein Enrichment in Lipid Sponge Phase Droplets using SNAP–Tag Bioconjugation

All cells use organized lipid compartments to facilitate specific biological functions. Membrane-bound organelles create defined spatial environments that favor unique chemical reactions while isolating incompatible biological processes. Despite the fundamental role of cellular organelles, there is a scarcity of methods for preparing functional artificial lipid-based compartments. In this work, we demonstrate a robust bioconjugation system for sequestering proteins into zwitterionic lipid sponge phase droplets. Incorporation of benzylguanine (BG)-modified phospholipids that form stable covalent linkages with an O 6 -methylguanine DNA methyltransferase (SNAP-tag) fusion protein enables programmable control of protein capture. We show that this methodology can be used to anchor hydrophilic proteins at the lipid-aqueous interface, concentrating them within an accessible but protected chemical environment. SNAP-tag technology enables the integration of proteins that regulate complex biological functions in lipid sponge phase droplets, and should facilitate the development of advanced lipid-based artificial organelles.

59 BASIC BIOLOGICAL SCIENCES↗

Utilizing CellBox to Describe Varied Dynamical Systems

CellBox is a hybrid modeling framework that integrates machine-learning approaches with explicit mathematical modeling to determine the behavior of dynamical systems, intended for determining the complex interactions of molecule and phenotype within a cellular environment using perturbation/response-based data. The original work utilized analysis of a melanoma cell line, SK-Mel-133, which we sought to expand to and evaluate effectiveness in describing other nonlinear systems both within and outside of biology. We evaluated with two models. One model is based upon the free-fall of an object under a velocity-dependent drag force; this produced inherent perturbation/response data. The other model is based upon a form of mass-action molecular kinetics; for this, we ran the simulation to steady state in each species for each perturbation and select the steady state as input for CellBox. We determined that CellBox, outside of its original use case, can still strongly predict even non-biological dynamical systems in the small-perturbation regime, with r = 0.99977 to 0.85123, p < 0.05 for freefall. However, CellBox cannot accurately predict behavior within large-perturbation regimes, p >> 0.05 for freefall. In addition, we performed a naïve comparison of CellBox network structure to known network structure in the mass-action model to assess accuracy.

97 MATHEMATICS AND COMPUTING↗

Deep Learning Prediction of Protein Complex Structures

Proteins interact to form protein complex to carry out biological functions such as catalytic chemical reaction. Therefore, it is important to develop computational methods to predict protein-protein interaction and the structures of protein complexes to study and enhance protein function. In this project, we successfully developed several deep learning methods to predict inter-protein contacts and the reinforcement learning and optimization methods to reconstruct protein complex structures from predicted inter-chain contacts. The methods were integrated with the MULTICOM protein complex structure prediction system and applied to predict the complex structures of biomass production-related proteins of green algae. During the two and a half years of research and development, all the specific milestones of the project were achieved successfully. 16 publications/manuscripts were produced. 10 software tools were developed. A patent application was submitted. Our MULTICOM predictors leveraging some tools developed in this project were ranked among the top predictors in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022.

59 BASIC BIOLOGICAL SCIENCES↗

Liquid–Liquid Phase Separation in Supermicrometer and Submicrometer Aerosol Particles

The interactions of aerosol particles with light and clouds are among the most uncertain aspects of anthropogenic climate forcings. The effects of aerosol particles on climate depend on their optical properties, heterogeneous chemistry, water uptake behavior, and ice nucleation activity. These properties in turn depend on aerosol physics and chemistry including composition, size, shape, internal structure (morphology), and phase state. The greatest numbers of particles are found at small, submicrometer sizes, and the properties of aerosol particles can differ on the nanoscale compared with measurements of bulk materials. As a result, our focus has been on characterizing the phase transitions of aerosol particles in both supermicrometer and submicrometer particles. The phase transition of particular interest for us has been liquid–liquid phase separation (LLPS), which occurs when components of a solution phase separate due to a difference in solubilities. For example, organic compounds can have limited solubility in salt solutions especially as the water content decreases, increasing the concentration of the salt solution, and causing phase separation between organic-rich and inorganic-rich phases. To characterize the systems of interest, we primarily use optical microscopy for supermicrometer particles and cryogenic-transmission microscopy for submicrometer particles. This Account details our main results to date for the phase transitions of supermicrometer particles and the morphology of submicrometer aerosol. Herein, we have found that the relative humidity (RH) at which LLPS occurs (separation RH; SRH) is highly sensitive to the composition of the particles. For supermicrometer particles, SRH decreases as the pH is lowered to atmospherically relevant values. SRH also decreases when non-phase-separating organic compounds are added to the particles. For submicrometer particles, a size dependence of morphology is observed in systems that undergo LLPS in supermicrometer particles. In the limit of slow drying rates, particles <30 nm are homogeneous and larger particles are phase-separated. This size dependence of aerosol morphology arises because small particles cannot overcome the activation barrier needed to form a new phase when phase separation occurs by a nucleation and growth mechanism. Additionally, the inhibition of LLPS in small particles is observed for mixtures of ammonium sulfate with single organic compounds as well as complex organics like α-pinene secondary organic matter. The morphology of particles affects activation diameters for the formation of cloud condensation nuclei. These results more generally have implications for aerosol properties that affect the climate system. In addition, LLPS is also widely studied in materials and biological chemistry, and our results could potentially translate to implications for these fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BMX: Biological modelling and interface exchange

Abstract High performance computing has a great potential to provide a range of significant benefits for investigating biological systems. These systems often present large modelling problems with many coupled subsystems, such as when studying colonies of bacteria cells. The aim to understand cell colonies has generated substantial interest as they can have strong economic and societal impacts through their roles in in industrial bioreactors and complex community structures, called biofilms, found in clinical settings. Investigating these communities through realistic models can rapidly exceed the capabilities of current serial software. Here, we introduce BMX, a software system developed for the high performance modelling of large cell communities by utilising GPU acceleration. BMX builds upon the AMRex adaptive mesh refinement package to efficiently model cell colony formation under realistic laboratory conditions. Using simple test scenarios with varying nutrient availability, we show that BMX is capable of correctly reproducing observed behavior of bacterial colonies on realistic time scales demonstrating a potential application of high performance computing to colony modelling. The open source software is available from the zenodo repository https://doi.org/10.5281/zenodo.8084270 under the BSD-2-Clause licence.

97 MATHEMATICS AND COMPUTING↗

Bridging the Gap between Analytical and Microbial Sciences in Microbiome Research

Metabolites from the microbiome influence human, animal, and environmental health, but the diversity and functional roles of these compounds have only begun to be elucidated. Comprehensively characterizing these molecules are significant challenges, as it requires expertise in analytical methods, such as mass spectrometry and nuclear magnetic resonance spectroscopy, skills that not many traditional microbiologists or microbial ecologists possess. This creates a gap between microbiome scientists that want to understand the role of microbial metabolites in microbiome systems and the skills required to generate and interpret complex metabolomics data sets. To bridge this gap, microbiome scientists should engage analytical chemists to best understand the underlying chemical principles of the data. Conversely, analytical scientists are encouraged to engage with microbiome scientists to better understand the biological questions being asked with metabolomics and to best communicate its intricacies. Better communication across the chemistry/biology disciplines will further reveal the “dark matter” within microbiomes that maintain healthy humans and environments.

59 BASIC BIOLOGICAL SCIENCES↗

Towards interpretable Cryo-EM: disentangling latent spaces of molecular conformations

Molecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image datasets of individual molecules. Recent advances in computational cryo-EM have made it possible to learn latent variable models of conformation landscapes. However, interpreting these latent spaces remains a challenge as their individual dimensions are often arbitrary. The key message of our work is that this interpretation challenge can be viewed as an Independent Component Analysis (ICA) problem where we seek models that have the property of identifiability. That means, they have an essentially unique solution, representing a conformational latent space that separates the different degrees of freedom a molecule is equipped with in nature. Thus, we aim to advance the computational field of cryo-EM beyond visualizations as we connect it with the theoretical framework of (nonlinear) ICA and discuss the need for identifiable models, improved metrics, and benchmarks. Moving forward, we propose future directions for enhancing the disentanglement of latent spaces in cryo-EM, refining evaluation metrics and exploring techniques that leverage physics-based decoders of biomolecular systems. Moreover, we discuss how future technological developments in time-resolved single particle imaging may enable the application of nonlinear ICA models that can discover the true conformation changes of molecules in nature. The pursuit of interpretable conformational latent spaces will empower researchers to unravel complex biological processes and facilitate targeted interventions. This has significant implications for drug discovery and structural biology more broadly. More generally, latent variable models are deployed widely across many scientific disciplines. Thus, the argument we present in this work has much broader applications in AI for science if we want to move from impressive nonlinear neural network models to mathematically grounded methods that can help us learn something new about nature.

59 BASIC BIOLOGICAL SCIENCES↗

Mitochondrial Effects in the Liver of C57BL/6 Mice by Low Dose, High Energy, High Charge Irradiation

Galactic cosmic rays are primarily composed of protons (85%), helium (14%), and high charge/high energy ions (HZEs) such as 56 Fe, 28 Si, and 16 O. HZE exposure is a major risk factor for astronauts during deep-space travel due to the possibility of HZE-induced cancer. A systems biology integrated omics approach encompassing transcriptomics, proteomics, lipidomics, and functional biochemical assays was used to identify microenvironmental changes induced by HZE exposure. C57BL/6 mice were placed into six treatment groups and received the following irradiation treatments: 600 MeV/n 56 Fe (0.2 Gy), 1 GeV/n 16 O (0.2 Gy), 350 MeV/n 28 Si (0.2 Gy), 137 Cs (1.0 Gy) gamma rays, 137 Cs (3.0 Gy) gamma rays, and sham irradiation. Left liver lobes were collected at 30, 60, 120, 270, and 360 days post-irradiation. Analysis of transcriptomic and proteomic data utilizing ingenuity pathway analysis identified multiple pathways involved in mitochondrial function that were altered after HZE irradiation. Lipids also exhibited changes that were linked to mitochondrial function. Molecular assays for mitochondrial Complex I activity showed significant decreases in activity after HZE exposure. HZE-induced mitochondrial dysfunction suggests an increased risk for deep space travel. Microenvironmental and pathway analysis as performed in this research identified possible targets for countermeasures to mitigate risk.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Omics-driven onboarding of the carotenoid producing red yeast Xanthophyllomyces dendrorhous CBS 6938

Transcriptomics is a powerful approach for functional genomics and systems biology, yet it can also be used for genetic part discovery. Here, we derive constitutive and light-regulated promoters directly from transcriptomics data of the basidiomycete red yeast Xanthophyllomyces dendrorhous CBS 6938 (anamorph Phaffia rhodozyma) and use these promoters with other genetic elements to create a modular synthetic biology parts collection for this organism. X. dendrorhous is currently the sole biotechnologically relevant yeast in the Tremellomycete class-it produces large amounts of astaxanthin, especially under oxidative stress and exposure to light. Thus, we performed transcriptomics on X. dendrorhous under different wavelengths of light (red, green, blue, and ultraviolet) and oxidative stress. Differential gene expression analysis (DGE) revealed that terpenoid biosynthesis was primarily upregulated by light through crtI, while oxidative stress upregulated several genes in the pathway. Further gene ontology (GO) analysis revealed a complex survival response to ultraviolet (UV) where X. dendrorhous upregulates aromatic amino acid and tetraterpenoid biosynthesis and downregulates central carbon metabolism and respiration. The DGE data was also used to identify 26 constitutive and regulated genes, and then, putative promoters for each of the 26 genes were derived from the genome. Simultaneously, a modular cloning system for X. dendrorhous was developed, including integration sites, terminators, selection markers, and reporters. Each of the 26 putative promoters were integrated into the genome and characterized by luciferase assay in the dark and under UV light. The putative constitutive promoters were constitutive in the synthetic genetic context, but so were many of the putative regulated promoters. Notably, one putative promoter, derived from a hypothetical gene, showed ninefold activation upon UV exposure. Thus, this study reveals metabolic pathway regulation and develops a genetic parts collection for X. dendrorhous from transcriptomic data. Therefore, this study demonstrates that combining systems biology and synthetic biology into an omics-to-parts workflow can simultaneously provide useful biological insight and genetic tools for nonconventional microbes, particularly those without a related model organism. This approach can enhance current efforts to engineer diverse microbes.

60 APPLIED LIFE SCIENCES↗