VAS1-mediated nitrogen reshuffling in aromatic amino acid homeostasis
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Bioproduction from one-carbon compounds, such as formate, is an attractive prospect due to reduced energy requirements and the possibility for using CO 2 as a sustainable feedstock. Formate-fixing pathways engineered using Escherichia coli lysate-based cell-free expression (CFE) biocatalysts have the potential to route 100% of feedstock carbon toward chemical synthesis but are undermined by siphoning of in-pathway metabolites and cofactors by the CFE background metabolism. To address this limitation, we engineer a CFE-based thermophilic multienzyme biocatalyst for the synthesis of serine and glycine from formate, bicarbonate, and ammonia. After expression of the thermophilic formate-to-serine pathway in a one-pot reaction, the mesophilic E. coli CFE background machinery is removed by simple heat denaturation, eliminating the siphoning of cofactors, inpathway metabolites, and products. After bioprocess optimization, including pathway gene expression duration and chemical synthesis temperature, we achieve near stoichiometric conversion of formate and bicarbonate to serine and glycine, reaching 97% of stoichiometric yield. The use of a moderately thermophilic biocatalyst allowed chemical synthesis to take place at mesophilic temperatures, enabling the balance of optimal enzyme activity with minimal metabolite/cofactor thermal degradation. In a fed-batch experiment, the biocatalyst shows sustained chemical synthesis rates for 8 h, paving the way toward a continuous bioprocess. Finally, a sensitivity analysis of cofactor usage revealed that the most expensive cofactors, THF and NADPH, can be reduced by 5-fold without significantly lowering product yields. To the best of our knowledge, this is the first instance of expressing a thermophilic pathway in an E. coli lysate-based CFE system to generate a thermophilic biocatalyst for use at mesophilic temperatures. The CFEbased thermophilic formate-to-serine biocatalyst triples the combined serine and glycine yield previously obtained by a CFE-based mesophilic formate-to-serine biocatalyst (30%), and quadruple the yield obtained by a purified enzyme system (22%). Ultimately, this work opens the door to using E. coli lysate-based CFE for thermophilic biocatalyst generation to achieve high chemical synthesis yields.
Direct air capture (DAC) technologies are limited by the poor understanding of the dynamic role of interfaces in modulating the chemisorption of CO 2 from air into solutions. While the reactivity of aqueous amine-based solvents in the bulk environment is strongly inhibited by nonequilibrium solvent effects, promoting DAC at interfaces posits a possibility to reduce the coupling with the solvent and significantly accelerate DAC. Building on an experimentally proven concept to bring an anionic glycine absorbent to the interface through ion-pairing interactions with a positively charged surfactant, we establish the fundamental time scales for key elementary steps involved in DAC with rate theory and enhanced-sampling ab initio molecular dynamics simulations. Here, we elucidate the mechanism by which water influences the free energy barriers and dynamical crossing-recrossing of those barriers, affecting the reaction rates. We find that water reorganizes to partially dehydrate [-NH 2 ], facilitating S N 2-based CO 2 conversion to a zwitterion, which then releases a proton via overhydration of [-NH 2 ]. The low-density interfacial water favors dehydration over overhydration, leading to a comparatively higher barrier (slower kinetics) for proton release. The barrier-recrossing events neutralize this effect, letting both steps occur at the same time scale (sub-microseconds) and making the overall DAC process faster at the interface than in the bulk water. Such an understanding of environment-sensitive solvent effects on the reaction kinetics will help design tailored interfaces for enhanced CO 2 capture kinetics via control of solvation and ion paring.
Lignin biosynthesis in grasses exhibits unique metabolic flexibility, yet the precursor-specific routing of carbon into lignin polymers remains poorly resolved in planta. Here, we combine 13 C-isotope labeling with solid-state NMR under sensitivity-enhancement by dynamic nuclear polarization (DNP), to directly track phenylalanine- and tyrosine-derived carbon incorporation into the lignin polymer in Brachypodium distachyon. Precursor-specific 13 C labeling reveals that phenylalanine is the dominant contributor to canonical guaiacyl and syringyl lignins, whereas tyrosine preferentially enriches hydroxyphenyl lignin and hydroxycinnamates, including ferulates characteristic of grass cell walls. Two-dimensional 13 C− 13 C correlation NMR resolves distinct lignin moieties arising from each precursor. Disruption of pcoumarate 3-hydroxylase (C3H) selectively impairs phenylalanine-derived lignification, while tyrosine-derived lignin remains comparatively unchanged, maintaining polymer assembly through alternative metabolic routes. These findings show precursordependent control of lignin composition and reveal tyrosine-mediated lignification as a compensatory pathway in grasses. This work also establishes precursor-resolved solid-state NMR and DNP as a powerful framework for dissecting lignin biosynthesis and metabolic plasticity in plant cell walls.
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Protein language models (PLMs) have recently demonstrated potential to supplant classical protein database search methods based on sequence alignment, but are slower than common alignment-based tools and appear to be prone to a high rate of false labeling. Here, we present NEAR, a method based on neural representation learning that is designed to improve both speed and accuracy of search for likely homologs in a large protein sequence database. NEAR’s ResNet embedding model is trained using contrastive learning guided by trusted sequence alignments. It computes per-residue embeddings for target and query protein sequences, and identifies alignment candidates with a pipeline consisting of residue-level k-NN search and a simple neighbor aggregation scheme. Tests on a benchmark consisting of trusted remote homologs and randomly shuffled decoy sequences reveal that NEAR substantially improves accuracy relative to state-of-the-art PLMs, with lower memory requirements and faster embedding and search speed. While these results suggest that the NEAR model may be useful for standalone homology detection with increased sensitivity over standard alignment-based methods, in this manuscript we focus on a more straightforward analysis of the model’s value as a high-speed pre-filter for sensitive annotation. In that context, NEAR is at least 5x faster than the pre-filter currently used in the widely-used profile hidden Markov model (pHMM) search tool HMMER3, and also outperforms the pre-filter used in our fast pHMM tool, nail.
Our software is designed to only work on novel NCAA side chains and parameterize for the CHARMM potential. This works around the detailed analysis and manual parameter fitting of many existing software programs. Our approach is also more specific than those used in Rosetta where we calculate parameters specific for each NCAA rather than assuming transferability.
Methionine residues in proteins and peptides are frequently oxidized by losing one electron. The presence of nearby amide groups is crucial for this process, enabling methionine to participate in long-range electron transfer. Hydroxyl radical (HO•) plays an important role being generated in aerobic organisms by cellular metabolisms as well as by exogenous sources such as ionizing radiations. The reaction of HO• with methionine mainly affords the one-electron oxidation of the thioether moiety through two consecutive steps (HO• addition to the sulfur followed by HO− elimination). We recently investigated the reaction of HO• with model peptides mimicking methionine and its cysteine-methylated counterpart, i.e., CH3C(O)NHCHXC(O)NHCH3, where X = CH2CH2SCH3 or CH2SCH3 at pH 7. The reaction mechanism varied depending on the distance between the sulfur atom and the peptide backbone, but, for a better understanding of various suggested equilibria, the analysis of the flux of protons is required. We extended the previous study to the present work at pH 4 using pulse radiolysis techniques with conductivity and optical detection of transient species, as well as analysis of final products by LC-MS and high-resolution MS/MS following γ-radiolysis. Comparing all the data provided a better understanding of how the presence of nearby amide groups influences the one-electron oxidation mechanism.
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Brain biochemistry of rats exposed to pure oxygen
Methionine synthesis under simulated prebiotic conditions by UV irradiation of ammonium thiocyanate solution, discussing earth prebiological chemistry evolution
Solvent effect in catalytic hydrogenation reaction of Schiff bases of alpha-keto acids with optically active alpha-alkylbenzylamine