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At least 127 records · Page 7

Site-Differentiated Iron–Sulfur Cluster Ligation Affects Flavin-Based Electron Bifurcation Activity

Electron bifurcation is an elegant mechanism of biological energy conversion that effectively couples three different physiologically relevant substrates. As such, enzymes that perform this function often play critical roles in modulating cellular redox metabolism. One such enzyme is NADH-dependent reduced-ferredoxin: NADP+ oxidoreductase (NfnSL), which couples the thermodynamically favorable reduction of NAD+ to drive the unfavorable reduction of ferredoxin from NADPH. The interaction of NfnSL with its substrates is constrained to strict stoichiometric conditions, which ensures minimal energy losses from non-productive intramolecular electron transfer reactions. However, the determinants for this are not well understood. One curious feature of NfnSL is that both initial acceptors of bifurcated electrons are unique iron–sulfur (FeS) clusters containing one non-cysteinyl ligand each. The biochemical impact and mechanistic roles of site-differentiated FeS ligands are enigmatic, despite their incidence in many redox active enzymes. Herein, we describe the biochemical study of wild-type NfnSL and a variant in which one of the site-differentiated ligands has been replaced with a cysteine. Results of dye-based steady-state kinetics experiments, substrate-binding measurements, biochemical activity assays, and assessments of electron distribution across the enzyme indicate that this site-differentiated ligand in NfnSL plays a role in maintaining fidelity of the coordinated reactions performed by the two electron transfer pathways. Given the commonality of these cofactors, our findings have broad implications beyond electron bifurcation and mechanistic biochemistry and may inform on means of modulating the redox balance of the cell for targeted metabolic engineering approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatiotemporal 4D Whole-cell Modeling of a Minimal Autotroph Reveals Central Carbon Metabolism Regulated Locally by Protein Megacomplexes via Post-translational Modifications under Light Disturbance

Photosynthetic microorganisms rely on multiple pathways in central carbon metabolism to adapt to fluctuating light and energy availability across diel cycles. Mechanistic insight into the regulatory dynamics of this adaptation requires integrating processes spanning disparate timescales, from rapid redox-dependent post-translational modifications (PTMs) to slower changes in protein expression and metabolic pathway usage. To address this complexity beyond genome-based inference and traditional modeling, we develop a whole-cell four-dimensional (3D + time) model of the marine cyanobacterium Prochlorococcus marinus MED4 that explicitly represents the spatial organization of enzymatic and molecular processes in central carbon metabolism under light perturbation. We employ a perturbation-based research design to experimentally generate time-series, multi-omics measurements that provide molecular descriptors and cryo-ET derived 3D segmented volumes as constraints for this dynamic 4D framework. The integration of experiments and modeling across defined light regimes enables quantitative validation of system-level responses and forecasting under distinct light disturbances. We test the hypothesis that light-dependent redox PTMs regulating the structural assembly of a protein megacomplex, the “dark complex,” modulate metabolic flux at a conserved regulatory node of the Calvin–Benson cycle (CBC) in cyanobacteria. Our model shows that subcellular spatial organization buffers rapid light-induced changes in thylakoid reaction rates, which are followed by redox-PTM-mediated sequestration or release of CBC enzymes in the dark complex, ultimately impacting carbon fixation dynamics within carboxysomes. Comparison with an equivalently parameterized well-mixed stochastic model demonstrates that post-translational regulation not only buffers transcriptional noise and diffusion-driven fluctuations but also stabilizes phenotypic outcomes, underscoring the importance of spatial heterogeneity in phenotypic robustness. This ability to probe adaptive, spatiotemporally resolved mechanisms in photosynthetic machinery and central carbon metabolism addresses a critical gap in genotype-to-phenotype inference and expands modeling and design capabilities for understudied or genetically intractable autotrophs such as P. marinus MED4.

Johnson, Connah G.↗

Integrated Metabolomics and Proteomics Analyses in the Local Milieu of Islet Allografts in Rejection versus Tolerance

An understanding of the immune mechanisms that lead to rejection versus tolerance of allogeneic pancreatic islet grafts is of paramount importance, as it facilitates the development of innovative methods to improve the transplant outcome. Here, we used our established intraocular islet transplant model to gain novel insight into changes in the local metabolome and proteome within the islet allograft’s immediate microenvironment in association with immune-mediated rejection or tolerance. We performed integrated metabolomics and proteomics analyses in aqueous humor samples representative of the graft’s microenvironment under each transplant outcome. The results showed that several free amino acids, small primary amines, and soluble proteins related to the Warburg effect were upregulated or downregulated in association with either outcome. In general, the observed shifts in the local metabolite and protein profiles in association with rejection were consistent with established pro-inflammatory metabolic pathways and those observed in association with tolerance were immune regulatory. Taken together, the current findings further support the potential of metabolic reprogramming of immune cells towards immune regulation through targeted pharmacological and dietary interventions against specific metabolic pathways that promote the Warburg effect to prevent the rejection of transplanted islets and promote their immune tolerance.

60 APPLIED LIFE SCIENCES↗

Data for The Stem Cell-Type Transcriptome of Bioenergy Sorghum Reveals the Spatial Regulation of Secondary Cell Wall Networks

Bioenergy sorghum is a low-input, drought-resilient, deep-rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum’s 4-5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about stem cell-type gene expression and regulation was available to enable engineering. To obtain this information, Laser Capture Microdissection (LCM) was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell-type specific gene regulatory networks (GRNs) revealed that unique TF families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell-specific transcriptome data was combined with a stem developmental transcriptome dataset to identify the GRN that differentially activates the secondary cell wall (SCW) formation in stem xylem sclerenchyma and epidermal cells. The cell-type transcriptomic dataset provides a valuable source of information about the function of sorghum stem cell types and GRNs that will enable the engineering of bioenergy sorghum stems.

Software↗

Microalgal lipids: biochemistry and biotechnology

Microalgae, including cyanobacteria, are a genetically diverse and biochemically diverse group of mostly photosynthetic organisms that can be found in nearly every ecosystem. They produce a broad range of compounds, including structural and bioactive lipids with various roles in the metabolism of the cell and potential applications in biotechnology. Here, the majority of lipids are synthesized in the chloroplast using acetate to produce fatty acids and terpenoids via the acetate pathway and methylerythritol phosphate deoxy-xylulose phosphate pathway, respectively. This review will highlight the major groups of microalgal lipids as well as their applications in food, fuels, and specialty chemicals. Future directions include the development of microalgal chassis organisms and molecular tools to manipulate lipid synthesis for the enhanced production of target metabolites.

cyanobacteria↗

Revising the dynamic energy budget theory with a new reserve mobilization rule and three example applications to bacterial growth

Dynamic energy budget (DEB) theory has been applied to model a wide range of organisms, including microbes. In the standard DEB model, biomass is partitioned into reserve and structural compartments, where reserve biomass is mobilized in a pseudolinear manner (while the reserve biomass density, defined as the ratio between reserve and structural biomass, decays linearly) to drive maintenance and the growth of structural biomass (and extracellular enzyme production if it is considered). However, the linear dynamics of the reserve biomass density makes the standard DEB model incapable of explaining the slowdown of microbial growth at high reserve density that is caused by macromolecular crowding effect which reduces biochemical reaction rates (a typical situation occurs when microbes are experiencing severe moisture stress) and is inconsistent with the observation that intracellular enzymatic reactions generally follow non-linear kinetics. By partitioning biomass into reserve, kinetic, and structural compartments, we show here that the Equilibrium Chemistry Approximation (ECA) kinetics can be used to represent enzymatically catalyzed reserve biomass mobilization that can then drive the kinetic and structural biomass synthesis. This revised DEB model better represents the tradeoff in ribosome allocation for structural growth and internal enzyme production, is structurally compatible with metabolic models of cell individuals, and includes the standard DEB model and the popular compromise model as special cases for representing population growth. We then applied the revised DEB model to interpret components of bacterial respiration, their dependence on substrate availability, and emergent microbial carbon use efficiency dynamics for an exponentially growing population. We found that the revised DEB model enables a better understanding of bacterial substrates use (carbon in our examples) than that can be derived from a few other models in the literature. In particular, the revised DEB model explains why carbon use efficiency may first increase, then plateau, and finally decrease with growth rate (and substrate uptake rate), as a function of proteomics. Additionally, the revised DEB model explains why the kinetic biomass compartment needs to be divided to reasonably incorporate proteomic control of microbial growth.

59 BASIC BIOLOGICAL SCIENCES↗

Synthase-Selective Exploration of a Tunicate Microbiome by Activity-Guided Single-Cell Genomics

While thousands of environmental metagenomes have been mined for the presence of novel biosynthetic gene clusters, such computational predictions do not provide evidence of their in vivo biosynthetic functionality. Using fluorescent in situ enzyme assay targeting carrier proteins common to polyketide (PKS) and nonribosomal peptide synthetases (NRPS), we applied fluorescence-activated cell sorting to tunicate microbiome to enrich for microbes with active secondary metabolic capabilities. Single-cell genomics uncovered the genetic basis for a wide biosynthetic diversity in the enzyme-active cells and revealed a member of marine Oceanospirillales harboring a novel NRPS gene cluster with high similarity to phylogenetically distant marine and terrestrial bacteria. Interestingly, this synthase belongs to a larger class of siderophore biosynthetic gene clusters commonly associated with pestilence and disease. Furthermore, this demonstrates activity-guided single-cell genomics as a tool to guide novel biosynthetic discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural basis for allosteric regulation of pyruvate kinase M2 by phosphorylation and acetylation

Pyruvate kinase muscle isoform 2 (PKM2) is a key glycolytic enzyme and transcriptional coactivator and is critical for tumor metabolism. In cancer cells, native tetrameric PKM2 is phosphorylated or acetylated, which initiates a switch to a dimeric/monomeric form that translocates into the nucleus, causing oncogene transcription. However, it is not known how these post-translational modifications (PTMs) disrupt the oligomeric state of PKM2. We explored this question via crystallographic and biophysical analyses of PKM2 mutants containing residues that mimic phosphorylation and acetylation. We find that the PTMs elicit major structural reorganization of the fructose 1,6-bisphosphate (FBP), an allosteric activator, binding site, impacting the interaction with FBP and causing a disruption in oligomerization. To gain insight into how these modifications might cause unique outcomes in cancer cells, we examined the impact of increasing the intracellular pH (pHi) from ~7.1 (in normal cells) to ~7.5 (in cancer cells). Biochemical studies of WT PKM2 (wtPKM2) and the two mimetic variants demonstrated that the activity decreases as the pH is increased from 7.0 to 8.0, and wtPKM2 is optimally active and amenable to FBP-mediated allosteric regulation at pHi 7.5. However, the PTM mimetics exist as a mixture of tetramer and dimer, indicating that physiologically dimeric fraction is important and might be necessary for the modified PKM2 to translocate into the nucleus. Thus, our findings provide insight into how PTMs and pH regulate PKM2 and offer a broader understanding of its intricate allosteric regulation mechanism by phosphorylation or acetylation.

59 BASIC BIOLOGICAL SCIENCES↗

Biomanufacturing and Scale-Up: Pathways to Biochemicals, Biofuels, and Biomaterials

Advancing the bioeconomy requires the development of large-scale microbial bioprocesses capable of converting waste carbon streams into biofuels, biochemicals, and biomaterials at industrially relevant scales. While biomanufacturing has been successfully demonstrated at the laboratory scale for a wide range of chemicals, only a few have reached industrial-scale production. This is partly due to the inherent complexity of microbial systems, which rely on living cells with intricate metabolic pathways that are highly sensitive to environmental changes, making large-scale production difficult to optimize and predict. As a result, scaling-up bioprocesses remains a high-stakes challenge that requires deeper exploration. This involves integrating feedstock and microbial selection, upstream and downstream processes, and computational modelling, among other research efforts. Bulk and specialty chemicals derived from biological processes also face competition from fossil-based production routes, which have been refined through decades of technological advancements. While biologically derived molecules may offer more environmentally friendly production pathways than traditional chemical manufacturing, their widespread adoption depends on achieving cost parity-or superiority-relative to fossil-based methods. This emphasizes the importance of holistic research, including techno-economic analyses and life cycle assessments, to ensure both economic viability and environmental sustainability. This editorial and special issue explores state-of-the-art strategies for converting waste carbon sources into valuable products. It discusses how enzymes, single microbes (e.g., extremophiles), and microbiomes (e.g., through division of labor) can be integrated with upstream and downstream process innovations-such as consolidated bioprocessing and in situ product recovery-to improve the efficiency and scalability of biomanufacturing. The editorial further highlights the role of computational modelling in understanding, predicting, and controlling bioprocess performance across scales, and concludes by emphasizing the importance of techno-economic modelling to identify technologies that can move to market.

09 BIOMASS FUELS↗

BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale

Metabolic fluxes, the number of metabolites traversing each biochemical reaction in a cell per unit time, are crucial for assessing and understanding cell function. 13 C Metabolic Flux Analysis ( 13 C MFA) is considered to be the gold standard for measuring metabolic fluxes. 13 C MFA typically works by leveraging extracellular exchange fluxes as well as data from 13 C labeling experiments to calculate the flux profile which best fit the data for a small, central carbon, metabolic model. However, the nonlinear nature of the 13 C MFA fitting procedure means that several flux profiles fit the experimental data within the experimental error, and traditional optimization methods offer only a partial or skewed picture, especially in “non-gaussian” situations where multiple very distinct flux regions fit the data equally well. Here, we present a method for flux space sampling through Bayesian inference (BayFlux), that identifies the full distribution of fluxes compatible with experimental data for a comprehensive genome-scale model. This Bayesian approach allows us to accurately quantify uncertainty in calculated fluxes. We also find that, surprisingly, the genome-scale model of metabolism produces narrower flux distributions (reduced uncertainty) than the small core metabolic models traditionally used in 13 C MFA. The different results for some reactions when using genome-scale models vs core metabolic models advise caution in assuming strong inferences from 13 C MFA since the results may depend significantly on the completeness of the model used. Based on BayFlux, we developed and evaluated novel methods (P- 13 C MOMA and P- 13 C ROOM) to predict the biological results of a gene knockout, that improve on the traditional MOMA and ROOM methods by quantifying prediction uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗

Hepatic transcriptome analyses of juvenile white bass ( Morone chrysops ) when fed diets where fish meal is partially or totally replaced by alternative protein sources

White bass (Morone chrysops) are a popular sportfish throughout the southern United States, and one parent of the commercially-successful hybrid striped bass (M. chrysops male x M. saxatilis female). Currently, white bass are cultured using diets formulated for other carnivorous fish, such as largemouth bass (Micropterus salmoides) or hybrid striped bass and contain a significant percentage of marine fish meal. Since there are no studies regarding the utilization of alternative proteins in this species, we evaluated the global gene expression of white bass fed diets in which fish meal was partially or totally replaced by various combinations of soybean meal, poultry by-product meal, canola meal, soy protein concentrate, wheat gluten, or a commercial protein blend (Pro Cision™). Six isonitrogenous (40% protein), isolipidic (11%), and isocaloric (17.1 kJ/g) diets were formulated to meet the known nutrient and energy requirements of largemouth bass and hybrid striped bass using nutrient availability data for most of the dietary ingredients. One of the test diets consisted exclusively of plant protein sources. Juvenile white bass (40.2 g initial weight) were stocked into a flow-through aquaculture system (three tanks/diet; 10 fish/tank) and fed the test diets twice daily to satiation for 60 days. RNA sequencing and bioinformatic analyses revealed significant differentially expressed genes between all test diets when compared to fish meal control. A total of 1,260 differentially expressed genes were identified, with major ontology relating to cell cycle and metabolic processes as well as immune gene functions. This data will be useful as a resource for future refinements to moronid diet formulation, as marine fish meal becomes limiting and plant ingredients are increasingly added as a reliable protein source

59 BASIC BIOLOGICAL SCIENCES↗

Thermophilic and thermoacidophilic metabolism genes and enzymes from Alicyclobacillus acidocaldarius and related organisms, methods

Isolated and/or purified polypeptides and nucleic acid sequences encoding polypeptides from Alicyclobacillus acidocaldarius are provided. Further provided are methods for modulating or altering metabolism in a cell using isolated and/or purified polypeptides and nucleic acid sequences from Alicyclobacillus acidocaldarius.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Episomal DNA vectors for plant genetic engineering

This disclosure pertains to a novel platform for genetic engineering of chloroplasts. The disclosure provides episomal DNA vectors containing a chloroplast origin of replication. These vectors remain extra-plastomic and sustainably and autonomously replicate in chloroplasts of the plant cells transformed with the vectors and in the plants regenerated from the transformed plant cells. The episomal DNA vectors do not contain any sequence that shares sequence homology with the plastome DNA and, thus, do not get integrated into the plastome DNA. The vectors can also comprise one or more genes of interest that confer desirable characteristics to the transformed plant cells. The disclosure also provides methods of transforming plant cells with the episomal DNA vectors and regenerating from the transformed plant cells plants having desirable characteristics. The vectors and methods disclosed herein provide a significant advancement in speed, flexibility, and prospects of introducing genes into plant cells for effective metabolic engineering.

Lenaghan, Scott C.↗

The promising role of proteomes and metabolomes in defining the single-cell landscapes of plants

The plant community has a strong track-record of RNA sequencing technology deployment, which combined with the recent advent of spatial platforms (e.g., 10x genomics), has resulted in an explosion of outstanding single cell and nuclei datasets that can be put in an in situ context within tissues (e.g., a cell atlas)1. In the genomics era, application of proteomics technologies in the plant sciences has always trailed behind that of RNA sequencing technologies, largely due to accessibility, ease-of-use and access to expertise along with depth of analysis benefits. On the other hand, the use of early analytical tools for characterizing small molecules (metabolites) from plant systems predates nucleic acid sequencing and proteomics analysis2, as the search for plant-based natural products has played a significant role in improving human health throughout history. However, the employment of proteomics and metabolomics assays for characterizing plant cell processes now remains significantly behind transcriptional approaches, even though both provide a direct functional readout of cell states and phenotypes.

Anderton, Christopher R. [BATTELLE (PACIFIC NW LAB↗

Investigating the Unique Ability of Trichodesmium To Fix Carbon and Nitrogen Simultaneously Using MiMoSA

The open ocean is an extremely competitive environment, partially due to the dearth of nutrients. Trichodesmium erythraeum, a marine diazotrophic cyanobacterium, is a keystone species in the ocean due to its ability to fix nitrogen and leak 30 to 50% into the surrounding environment, providing a valuable source of a necessary macronutrient to other species. While there are other diazotrophic cyanobacteria that play an important role in the marine nitrogen cycle, Trichodesmium is unique in its ability to fix both carbon and nitrogen simultaneously during the day without the use of specialized cells called heterocysts to protect nitrogenase from oxygen. Here, we use the advanced modeling framework called multiscale multiobjective systems analysis (MiMoSA) to investigate how Trichodesmium erythraeum can reduce dimolecular nitrogen to ammonium in the presence of oxygen. Our simulations indicate that nitrogenase inhibition is best modeled as Michealis-Menten competitive inhibition and that cells along the filament maintain microaerobia using high flux through Mehler reactions in order to protect nitrogenase from oxygen. We also examined the effect of location on metabolic flux and found that cells at the end of filaments operate in distinctly different metabolic modes than internal cells despite both operating in a photoautotrophic mode. These results give us important insight into how this species is able to operate photosynthesis and nitrogen fixation simultaneously, giving it a distinct advantage over other diazotrophic cyanobacteria because they can harvest light directly to fuel the energy demand of nitrogen fixation.

09 BIOMASS FUELS↗

Development and Application of TK6-derived Cells Expressing Human Cytochrome P450s for Genotoxicity Testing

Abstract Metabolism plays a key role in chemical genotoxicity; however, most mammalian cells used for in vitro genotoxicity testing lack effective metabolizing enzymes. We recently developed a battery of TK6-derived cell lines that individually overexpress 1 of 8 cytochrome P450s (CYP1A1, 1A2, 1B1, 2A6, 2B6, 2C9, 2C19, and 3A4) using a lentiviral expression system. The increased expression and metabolic function of each individual CYP in each established cell line were confirmed using real-time PCR, Western blotting, and mass spectrometry analysis; the parental TK6 cells and empty vector (EV) transduced cells had negligible CYP levels. Subsequently, we evaluated these cell lines using 2 prototypical polyaromatic hydrocarbon mutagens, 7,12-dimethylbenz[a]anthracene (DMBA) and benzo[a]pyrene (B[a]P), that require metabolic activation to exert their genotoxicity. DMBA-induced cytotoxicity, phosphorylation of histone H2A.X, and micronucleus formation were significantly increased in TK6 cells with CYP1A1, 1B1, 2B6, and 2C19 expression as compared with EV controls. B[a]P significantly increased cytotoxicity, DNA damage, and chromosomal damage in TK6 cells overexpressing CYP1A1 and 1B1 when compared with EV controls. B[a]P also induced micronucleus formation in TK6 cells expressing CYP1A2. These results suggest that our CYP-expressing TK6 cell system can be used to detect the genotoxicity of compounds requiring metabolic transformation.

Li, Xilin↗

Engineering Clostridium thermocellum for production of 2,3-butanediol from cellulose

Clostridium thermocellum is a promising host for consolidated bioprocessing due to its ability to directly ferment cellulose into fuels and chemicals. However, natural product formation in this organism is limited. Here, we report engineering C. thermocellum for the production of 2,3-butanediol (23BD), a valuable industrial chemical. We functionally expressed a thermophilic 23BD pathway in this organism resulting in a 23BD titer of 19.7 mM from cellulose, representing a metabolic yield of 24%. We used a cell-free systems biology approach to identify limiting steps in the 23BD pathway, revealing that exogenous 23BD dehydrogenase (BDH) activity was essential for production, while native acetolactate synthase (ALS) and acetolactate decarboxylase (ALDC) activities were present but limiting in the parent strain. This approach also revealed redox balance limitations. We demonstrated that this improved understanding of redox balance limitations could be used to increase 23BD titer in vivo, showing that adding acetate could be used to increase 23BD yield. This work establishes a foundation for developing C. thermocellum into a robust platform for 23BD production directly from cellulose and highlights the utility of cell-free systems for guiding metabolic engineering in non-model organisms.

09 BIOMASS FUELS↗