Michaelis-Menten Research Articles

MPEK: a multitask deep learning framework based on pretrained language models for enzymatic reaction kinetic parameters prediction.

Enzymatic reaction kinetics are central in analyzing enzymatic reaction mechanisms and target-enzyme optimization, and thus in biomanufacturing and other industries. The enzyme turnover number (kcat) and Michaelis constant (Km), key kinetic parameters for measuring enzyme catalytic efficiency, are crucial for analyzing enzymatic reaction mechanisms and the directed evolution of target enzymes. Experimental determination of kcat and Km is costly in terms of time, labor, and cost. To consider the intrinsic connection between kcat and Km and further improve the prediction performance, we propose a universal pretrained multitask deep learning model, MPEK, to predict these parameters simultaneously while considering pH, temperature, and organismal information. Through testing on the same kcat and Km test datasets, MPEK demonstrated superior prediction performance over the previous models. Specifically, MPEK achieved the Pearson coefficient of 0.808 for predicting kcat, improving ca. 14.6% and 7.6% compared to the DLKcat and UniKP models, and it achieved the Pearson coefficient of 0.777 for predicting Km, improving ca. 34.9% and 53.3% compared to the Kroll_model and UniKP models. More importantly, MPEK was able to reveal enzyme promiscuity and was sensitive to slight changes in the mutant enzyme sequence. In addition, in three case studies, it was shown that MPEK has the potential for assisted enzyme mining and directed evolution. To facilitate in silico evaluation of enzyme catalytic efficiency, we have established a web server implementing this model, which can be accessed at http://mathtc.nscc-tj.cn/mpek.

Copper Single-Atom-Based Metal-Organic Framework for Ultrasound-Enhanced Nanocatalytic Therapy.

Chemodynamic therapy (CDT) is an emerging therapeutic modality triggered by endogenous substances in the tumor microenvironment (TME) to generate reactive oxygen species. However, the mild acid pH, low H2O2 concentration, and overexpressed glutathione can suppress the CDT efficiency. Herein, ultrasound (US)-triggered Cu2+-based single-atom nanoenzymes (FA-NH2-UiO-66-Cu, FNUC) are constructed with the performance of target and glutathione depletion. In the TME, the single-atom Cu sites of FNUC consume glutathione and the FNUC:Cu+ generates •OH via peroxidase-like activity. The US-activated FNUC exhibits a fast •OH generation rate, a low Michaelis constant, and a large •OH concentration, indicating the cavitation effect of US promotes the •OH generation. Meanwhile, the tumor target of FNUC is confirmed by NIR-II fluorescence imaging, in which it is modified with IR-1061. Combined with the antitumor performance of FNUC in vitro and in vivo, the novel Cu-based SAzymes can achieve efficient and precise cancer treatment.

Mid-Infrared Dispersion Spectroscopy as a Tool for Monitoring Time-Resolved Chemical Reactions on the Examples of Enzyme Kinetics and Mutarotation of Sugars.

Ongoing technological advancements in the field of mid-infrared (MIR) spectroscopy continuously yield novel sensing modalities, offering capabilities beyond traditional techniques like Fourier transform infrared spectroscopy (FT-IR). One such advancement is MIR dispersion spectroscopy, utilizing a tunable quantum cascade laser and Mach-Zehnder interferometer for liquid-phase analysis. Our study assesses the performance of a custom MIR dispersion spectrometer at its current development stage, benchmarks its performance against FT-IR, and validates its potential for time-resolved chemical reaction monitoring. Unlike conventional methods of IR spectroscopy measuring molecular absorptions using intensity attenuation, our method detects refractive index changes (phase shifts) down to a level of 6.1 × 10-7 refractive index units (RIU). This results in 1.5 times better sensitivity with a sevenfold increase in analytical path length, yielding heightened robustness for the analysis of liquids compared to FT-IR. As a case study, we monitor the catalytic activity of invertase with sucrose, observing the formation of resultant monosaccharides and their progression toward thermodynamic equilibrium. Anomalous refractive index spectra of reaction mixtures, with substrate concentrations ranging from 2.5 to 25 g/L, are recorded, and analyzed at various temperatures, yielding Michaelis-Menten kinetics findings comparable to the literature. Additionally, the first-time application of two-dimensional correlation spectroscopy on the recorded dynamic dispersion spectra correctly identifies the mutarotation of reaction products (glucose and fructose). The results demonstrate high precision and sensitivity in investigating complex time-dependent chemical reactions via broadband refractive index changes.

A Radioactivity-mass Spectrometry Calibration Method Coupled with Biosynthesis to Generate a Metabolite Standard for Enzyme Kinetics Studies

In early stages of drug development, the absence of authentic metabolite standards often results in semi-quantitative measurements of metabolite formation in reaction phenotyping studies using mass spectrometry (MS), leading to inaccuracies in the determination of enzyme kinetic parameters, such as the Michaelis constant (Km). Moreover, it is impossible to ascertain the maximum rate of enzyme-catalyzed reactions (kcat or Vmax). The use of radiolabeled parent compounds can circumvent this problem. However, radiometric detection exhibits significantly lower sensitivity compared to MS. To address these challenges, we have developed a stepwise approach that leverages biosynthesized radiolabeled and non-radiolabeled metabolites as standards, enabling accurate determination of Km, kcat or Vmax without the need for authentic metabolite standards. This approach, using the carbon-14 [14C] labeled metabolite to calibrate the unlabeled metabolite (14C calibration method), combines radiometric with LC-MS/MS detection to generate both [14C]-labeled and unlabeled metabolite standard curves to ensure that the sample concentrations measured are accurately quantitated. Two case studies were presented to demonstrate the utility of this method. We first compared the accuracy of the 14C calibration method to the use of authentic standards for quantitating imipramine metabolites. Next, we biosynthesized and quantitated the metabolites of BI 894416 using 14C calibration method and evaluated the enzyme kinetics of metabolite formation. The Km values of the metabolite formation demonstrated substantially improved accuracy compared to MS semi-quantitation. Moreover, the 14C calibration method offers a streamlined approach to prepare multiple metabolite standards from a single biosynthesis, reducing the time required for structure elucidation and metabolite synthesis.

Mathematical modeling and machine learning-based optimization for enhancing biofiltration efficiency of volatile organic compounds

Biofiltration is a method of pollution management that utilizes a bioreactor containing live material to absorb and destroy pollutants biologically. In this paper, we investigate mathematical models of biofiltration for mixing volatile organic compounds (VOCs) for instance hydrophilic (methanol) and hydrophobic (α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}-pinene). The system of nonlinear diffusion equations describes the Michaelis-Menten kinetics of the enzymic chemical reaction. These models represent the chemical oxidation in the gas phase and mass transmission within the air-biofilm junction. Furthermore, for the numerical study of the saturation of α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}-pinene and methanol in the biofilm and gas state, we have developed an efficient supervised machine learning algorithm based on the architecture of Elman neural networks (ENN). Moreover, the Levenberg-Marquardt (LM) optimization paradigm is used to find the parameters/ neurons involved in the ENN architecture. The approximation to a solutions found by the ENN-LM technique for methanol saturation and α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}-pinene under variations in different physical parameters are allegorized with the numerical results computed by state-of-the-art techniques. The graphical and statistical illustration of indications of performance relative to the terms of absolute errors, mean absolute deviations, computational complexity, and mean square error validates that our results perfectly describe the real-life situation and can further be used for problems arising in chemical engineering.

Hot Electrons in a Steady State: Interband vs Intraband Excitation of Plasmonic Gold.

Understanding the dynamics of "hot", highly energetic electrons resulting from nonradiative plasmon decay is crucial for optimizing applications in photocatalysis and energy conversion. This study presents an analysis of electron kinetics within plasmonic metals, focusing on the steady-state behavior during continuous-wave (CW) illumination. Using an inelastic spectroscopy technique, we quantify the temperature and lifetimes of distinct carrier populations during excitation. A significant finding is the monotonic increase in hot electron lifetime with decreases in electronic temperature. We also observe a 1.22× increase in hot electron temperature during intraband excitation compared to interband excitation and a corresponding 2.34× increase in carrier lifetime. The shorter lifetimes during interband excitation are hypothesized to result from direct recombination of nonthermal holes and hot electrons, highlighting steady-state kinetics. Our results help bridge the knowledge gap between ultrafast and steady-state spectroscopies, offering critical insights for optimizing plasmonic applications.

Croton gratissimus Burch Herbal Tea Exhibits Anti-Hyperglycemic and Anti-Lipidemic Properties via Inhibition of Glycation and Digestive Enzyme Activities.

Over the years, the world has continued to be plagued by type 2 diabetes (T2D). As a lifestyle disease, obese individuals are at higher risk of developing the disease. Medicinal plants have increasingly been utilized as remedial agents for managing metabolic syndrome. The aim of the present study was to investigate the in vitro anti-hyperglycemic and anti-lipidemic potential of Croton gratissimus herbal tea infusion. The inhibitory activities of C. gratissimus on carbohydrate (α-glucosidase and α-amylase) and lipid (pancreatic lipase) hydrolyzing enzymes were determined, and the mode of inhibition of the carbohydrate digestive enzymes was analyzed and calculated via Lineweaver-Burk plots and Michaelis Menten's equation. Its effect on Advanced Glycation End Product (AGE) formation, glucose adsorption, and yeast glucose utilization were also determined. High-performance liquid chromatography (HPLC) was used to quantify the possible phenolic compounds present in the herbal tea infusion, and the compounds were docked with the digestive enzymes. C. gratissimus significantly (p < 0.05) inhibited α-glucosidase (IC50 = 60.56 ± 2.78 μg/mL), α-amylase (IC50 = 35.67 ± 0.07 μg/mL), as well as pancreatic lipase (IC50 = 50.27 ± 1.51 μg/mL) in a dose-dependent (15-240 µg/mL) trend. The infusion also inhibited the non-enzymatic glycation process, adsorbed glucose effectively, and enhanced glucose uptake in yeast cell solutions at increasing concentrations. Molecular docking analysis showed strong binding affinity between HPLC-quantified compounds (quercetin, caffeic acid, gallic acid, and catechin) of C. gratissimus herbal tea and the studied digestive enzymes. Moreover, the herbal tea product did not present cytotoxicity on 3T3-L1 cell lines. Results from this study suggest that C. gratissimus herbal tea could improve glucose homeostasis and support its local usage as a potential anti-hyperglycemic and anti-obesogenic agent. Further in vivo and molecular studies are required to bolster the results from this study.

A Comparative Study of Phase I and II Hepatic Microsomal Biotransformation of Phenol in Three Species of Salmonidae: Hydroquinone, Catechol, and Phenylglucuronide Formation.

The in vitro biotransformation of phenol at 11 °C was studied using pre-spawn adult rainbow (Oncorhynchus mykiss) (RBT), brook (Salvelinus fontinalis) (BKT), and lake trout (Salvelinus namaycush) (LKT) hepatic microsomal preparations. The incubations were optimized for time, cofactor concentration, pH, and microsomal protein concentration. Formation of Phase I ring-hydroxylation and Phase II glucuronidation metabolites was quantified using HPLC with dual-channel electrochemical and UV detection. The biotransformation of phenol over a range of substrate concentrations (1 to 180 mM) was quantified, and the Michaelis-Menten kinetics constants, Km and Vmax, for the formation of hydroquinone (HQ), catechol (CAT), and phenylglucuronide (PG) were calculated. Species differences were noted in the Km values for Phase I enzyme production of HQ and CAT, with the following rank order of apparent enzyme affinity for substrate: RBT > BKT = LKT. However, no apparent differences in the Km for Phase II metabolism of phenol to PG were detected. Conversely, while there were no apparent differences in Vmax between species for HQ or CAT formation, the apparent maximum capacity for PG formation was significantly less in LKT than that observed for RBT and BKT. These experiments provide a means to quantify metabolic activation and deactivation of xenobiotics in fish, to compare activation and deactivation reactions across species, and to act as a guide for future predictions of new chemical biotransformation pathways and rates in fish. These experiments provided the necessary rate and capacity (Km and Vmax) inputs that are required to parameterize a fish physiologically based toxicokinetic (PB-TK) model for a reactive chemical that is readily biotransformed, such as phenol. In the future, an extensive database of these rate and capacity parameters on important fish species for selected chemical structures will be needed to allow the effective use of predictive models for reactive, biotransformation chemicals in aquatic toxicology and environmental risk assessment.

Nanozyme-Catalyzed Colorimetric Detection of the Total Antioxidant Capacity in Body Fluids by Paper-Based Microfluidic Chips.

Total antioxidants play a crucial role in human health, and detection of the total antioxidant capacity (TAC) has broad application prospects in fields such as food safety, environmental assessment, and disease diagnosis. However, a long detection time, cumbersome steps, high cost, reliance on professional equipment, and nonportability still remain significant challenges. In this work, an efficient strategy of point-of-care testing (POCT) of the TAC in body fluids by nanozyme-catalyzed colorimetric paper-based microfluidic sensors is proposed. The paper-based microfluidic sensors coupled with a smartphone can reduce testing costs and provide portability. The nanozyme prepared by the solvothermal method presents Michaelis constants of 0.11 and 0.129 mM for H2O2 and TMB, respectively. A method for immobilizing nanozymes and chromogenic agents on a paper-based microfluidic chip is established. Based on smartphone photography and image grayscale extraction, the TAC can be qualitatively detected with a detection limit and linear range of 33.4 and 50-700 μM, respectively. Furthermore, the proposed sensor can realize the one-step quantitative analysis of the TAC in body fluids (blood, saliva, and sweat) within 15 min. The proposed nanozyme-catalyzed colorimetric paper-based microfluidic sensors presented in this study exhibit promising application prospects in the fields of biochemical analysis and POCT.

Operational stability study of lactate biosensors: modeling, parameter identification, and stability analysis.

This paper investigates the operational stability of lactate biosensors, crucial devices in various biomedical and biotechnological applications. We detail the construction of an amperometric transducer tailored for lactate measurement and outline the experimental setup used for empirical validation. The modeling framework incorporates Brown and Michaelis-Menten kinetics, integrating both distributed and discrete delays to capture the intricate dynamics of lactate sensing. To ascertain model parameters, we propose a nonlinear optimization method, leveraging initial approximations from the Brown model's delay values for the subsequent model with discrete delays. Stability analysis forms a cornerstone of our investigation, centering on linearization around equilibrium states and scrutinizing the real parts of quasi-polynomials. Notably, our findings reveal that the discrete delay model manifests marginal stability, occupying a delicate balance between asymptotic stability and instability. We introduce criteria for verifying marginal stability based on characteristic quasi-polynomial roots, offering practical insights into system behavior. Qalitative examination of the model elucidates the influence of delay on dynamic behavior. We observe a transition from stable focus to limit cycle and period-doubling phenomena with increasing delay values, as evidenced by phase plots and bifurcation diagrams employing Poincaré sections. Additionally, we identify limitations in model applicability, notably the loss of solution positivity with growing delays, underscoring the necessity for cautious interpretation when employing delayed exponential function formulations. This comprehensive study provides valuable insights into the design and operational characteristics of lactate biosensors, offering a robust framework for understanding and optimizing their performance in diverse settings.

A flexible linker of 8-amino acids between the membrane binding segment and the FMN domain of cytochrome P450 reductase is necessary for optimal activity

The diflavin NADPH-cytochrome P450 reductase (CYPOR) plays a critical role in human cytochrome P450 (CYP) activity by sequentially delivering two electrons from NADPH to CYP enzymes during catalysis. Although electron transfer to forty-eight human CYP enzymes by the FMN hydroquinone of CYPOR is well-known, the role of the linker between the NH2-terminus membrane-binding domain (MBD) and FMN domain in supporting the activity of P450 enzymes remains poorly understood. Here we demonstrate that a linker with at least eight residues is required to form a functional CYPOR-CYP2B4 complex. The linker has been shortened in two amino-acid increments from Phe44 to Ile57 using site directed mutagenesis. The ability of the deletion mutants to support cytochrome P450 2B4 (CYP2B4) catalysis and reduce ferric CYP2B4 was determined using an in vitro assay and stopped-flow spectrophotometry. Steady-state enzyme kinetics showed that shortening the linker by 8–14 amino acids inhibited (63–99%) the ability of CYPOR to support CYP2B4 activity and significantly increased the Km of CYPOR for CYP2B4. In addition, the reductase mutants decreased the rate of reduction of ferric CYP2B4 (46–95%) compared to wildtype when the linker was shortened by 8–14 residues. These results indicate that a linker with a minimum length of eight residues is necessary to enable the FMN domain of reductase to interact with CYP2B4 to form a catalytically competent complex. Our study provides evidence that the length of the MBD-FMN domain linker is a major determinant of the ability of CYPOR to support CYP catalysis and drug metabolism by P450 enzymes. PreambleThis manuscript is dedicated in memory of Dr. James R. Kincaid who was the doctoral advisor to Dr. Freeborn Rwere and a longtime collaborator and friend of Dr. Lucy Waskell. Dr. James R. Kincaid was a distinguished professor of chemistry specializing in resonance Raman (rR) studies of heme proteins. He inspired Dr. Rwere (a Zimbabwean native) and three other Zimbabweans (Dr. Remigio Usai, Dr. Daniel Kaluka and Ms. Munyaradzi E. Manyumwa) to use lasers to document subtle changes occurring at heme active site of globin proteins (myoglobin and hemoglobin) and cytochrome P450 enzymes. Dr. Rwere appreciate his contributions to the development of talented Black scientists from Africa.

Selection of organic solvents as reaction media for laccase from Trametes versicolor

The ability of laccases to work effectively in properly selected aqueous-organic solutions significantly expands the scope of their application, making them commercially attractive and more competitive. However, it must be considered that molecules of organic solvent are very aggressive towards enzymes and destroy weak non-covalent interactions that maintain the spatial structure of the protein. In this work, we quantitatively described the influence of the nature of water-miscible organic solvents and their concentration on the activity and stability of Trametes versicolor laccase during the oxidation of ABTS (2,2-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid)) through the maximum rates and the Michaelis constants KM. The obtained kinetic parameters make it possible to compare the effect of various organic solvents on laccase and select the most optimal one, which minimizes the decrease in enzyme activity, maintains its stability and allows repeated use. Among the solvents studied, polyhydroxy compounds have the least negative effect on laccase activity; however, in all cases, a high concentration of organic solvent (≥30% (v/v)) leads to suppression of enzymatic activity. It has been shown that the longer the alkyl chain (hydrophobic fragment of the structure), the stronger the negative effect of alcohols on enzymes. The most toxic solvent for Trametes versicolor laccase is isopropanol. In addition, numerous examples of various uses of Trametes versicolor in aquatic-organic environments are discussed here.

Delineating acetaminophen biodegradation kinetics and metabolomics using bacterial community.

Acetaminophen [N-(4-hydroxyphenyl) acetamide, APAP]is an extensively and frequently consumed over-the-counter analgesic and antiphlogistic medication. It is being regarded as an emerging pollutant due to its continuous increment in the environment instigating inimical impacts on humans and the ecosystem. Considering its wide prevalence in the environment, there is an immense need of appropriate methods for the removal of APAP. The present study indulged screening and isolation of APAP degrading bacterial strains from pharmaceuticals-contaminated sites, followed by their molecular characterization via 16SrRNA sequencing. The phylogenetic analyses assigned the isolates to the genera Pseudomonas, Bacillus, Paracoccus, Agrobacterium, Brucella, Escherichia, and Enterobacter based on genetic relatedness. The efficacy of these strains in batch cultures tested through High-performance Liquid Chromatography (HPLC) revealed Paracoccus sp. and Enterobacter sp. as the most promising bacterial isolates degrading up to 88.96 and 85.92%, respectively of 300mg L-1 of APAP within 8days of incubation. Michaelis-Menten kinetics model parameters also elucidated the high degradation potential of these isolates. The major metabolites identified through FTIR and GC-MS analyses were 4-aminophenol, hydroquinone, and 3-hydroxy-2,4-hexadienedioic. Therefore, the outcomes of this comprehensive investigation will be of paramount significance in formulating strategies for the bioremediation of acetaminophen-contaminated sites through a natural augmentation process via native bacterial strains.

Characterization of Arabidopsis aldolases AtFBA4, AtFBA5, and their inhibition by morin and interaction with calmodulin.

Fructose bisphosphate aldolases (FBAs) catalyze the reversible cleavage of fructose 1,6-bisphosphate into dihydroxyacetone phosphate and glyceraldehyde 3-phosphate. We analyzed two previously uncharacterized cytosolic Arabidopsis FBAs, AtFBA4 and AtFBA5. Based on a recent report, we examined the interaction of AtFBA4 with calmodulin (CaM)-like protein 11 (AtCML11). AtFBA4 did not bind AtCML11; however, we found that CaM bound AtFBA5 in a Ca2+-dependent manner with high specificity and affinity (KD ~ 190 nm) and enhanced its stability. AtFBA4 and AtFBA5 exhibited Michaelis-Menten kinetics with Km and Vmax values of 180 μm and 4.9 U·mg-1 for AtFBA4, and 6.0 μm and 0.30 U·mg-1 for AtFBA5, respectively. The flavonoid morin inhibited both isozymes. Our study suggests that Ca2+ signaling and flavanols may influence plant glycolysis/gluconeogenesis.

A study using a semi-analytical approach to the reaction kinetics that describes the behavior of heterogeneous reaction–diffusion process with a glyoxyl-agarose immobilized enzyme (penicillin G acylase) in a batch reactor

This research article examines the reaction–diffusion process in a batch reactor by means of immobilized penicillin G acylase (PGA) with a glyoxyl-agarose matrix support. This study employs the Akbari-Ganji’s Method (AGM) when the system is under the internal (intra-particle) diffusional restrictions, and the external (film) diffusional restrictions is negligible. The semi-analytical approximations by the AGM technique are employed for computing the dimensionless steady-state solutions for a system of nonlinear differential equations to examine the impact of internal diffusional restrictions (IDR) as a function of catalyst enzyme loading and particle size. The model entails highly nonlinear components that adhere to the standard Michaelis-Menten kinetics. In addition to the proposed model, the dynamics for the mean integrated effectiveness factor (MIEF) of the dimensionless substrate concentration phenylglycine methyl ester (PGME) is presented. In light of this, there is a satisfactory level of agreement on the comparison of the semi-analytical result with the simulated numerical results across the whole concentration range where the dimensionless initial substrate and product concentrations are S1b=30,S2b=15, and P1b=60,P2b=100. The behavior of concentration profiles under the steady/unsteady state conditions for the effect of IDR on the overall reaction rates by immobilized biocatalyst PGA were examined. A sensitivity analysis is carried out to identify the effective parameter which can influence the diffusional restrictions on MIEF. An error analysis is performed on the dimensionless concentration equations to assess the amount of accuracy and the convergence of a solution.

Synthesis of a perylene diimide functionalized Sb2S3 nanocomposites and its application as a peroxidase mimic for colorimetric detection of H2O2 and glucose

N, N’-di (L-glutamic amine)-perylene-3,4,9,10-tetracarboxylic diimide (GAPDI) functionalized Sb2S3 nanocomposites (GAPDI-Sb2S3) were fabricated using a hydrothermal method and characterized. GAPDI-Sb2S3 nanocomposites can catalyze the oxidation of 3,3′,5,5′- tetramethyl benzidine (TMB) by H2O2. The experimental conditions including pH and temperature were optimized. GAPDI-Sb2S3 nanocomposites showed a strong affinity for TMB substrates, and their catalytic activity followed the Michaelis–Menten kinetics. The experimental results showed that GAPDI-Sb2S3 nanocomposites exhibited a low detection limit (LOD = 0.39 μM) and high sensitivity for H2O2 detection and showed good response to glucose detection with a LOD of 0.42 μM over arrange of 2–10 μM. These findings suggest broad application prospects in the fields of environmental chemistry, biotechnology, and biomedicine.

Ex vivo metabolism kinetics of primary to secondary bile acids via a physiologically relevant human faecal microbiota model

Bile acids (BA) are synthesized in the human liver and undergo metabolism by host gut bacteria. In diseased states, gut microbial dysbiosis may lead to high primary unconjugated BA concentrations and significant perturbations to secondary BA. Hence, it is important to understand the microbial-mediated formation kinetics of secondary bile acids using physiologically relevant ex vivo human faecal microbiota models. Here, we optimized an ex vivo human faecal microbiota model to recapitulate the metabolic kinetics of primary unconjugated BA and applied it to investigate the formation kinetics of novel secondary BA metabolites and their sequential pathways. We demonstrated (1) first-order depletion of primary BA, cholic acid (CA) and chenodeoxycholic acid (CDCA), under non-saturable conditions and (2) saturable Michaelis-Menten kinetics for secondary BA metabolite formation with increasing substrate concentration. Notably, relatively lower Michaelis constants (Km) were associated with the formation of deoxycholic acid (DCA, 14.3 μM) and lithocholic acid (LCA, 140 μM) versus 3-oxo CA (>1000 μM), 7-keto DCA (443 μM) and 7-keto LCA (>1000 μM), thereby recapitulating clinically observed saturation of 7α-dehydroxylation relative to oxidation of primary BA. Congruently, metagenomics revealed higher relative abundance of functional genes related to the oxidation pathway as compared to the 7α-dehydroxylation pathway. In addition, we demonstrated gut microbial-mediated hyocholic acid (HCA) and hyodeoxycholic acid (HDCA) formation from CDCA. In conclusion, we optimized a physiologically relevant ex vivo human faecal microbiota model to investigate gut microbial-mediated metabolism of primary BA and present a novel gut microbial-catalysed two-step pathway from CDCA to HCA and, subsequently, HDCA.

H2-D2 Exchange Activity and Electronic Structure of Ag x Pd1-x Alloy Catalysts Spanning Composition Space.

Many computational studies of catalytic surface reaction kinetics have demonstrated the existence of linear scaling relationships between physical descriptors of catalysts and reaction barriers on their surfaces. In this work, the relationship between catalyst activity, electronic structure, and alloy composition was investigated experimentally using a Ag x Pd1-x Composition Spread Alloy Film (CSAF) and a multichannel reactor array that allows measurement of steady-state reaction kinetics at 100 alloy compositions simultaneously. Steady-state H2-D2 exchange kinetics were measured at atmospheric pressure on Ag x Pd1-x catalysts over a temperature range of 333-593 K and a range of inlet H2 and D2 partial pressures. X-ray photoelectron spectroscopy (XPS) was used to characterize the CSAF by determining the local surface compositions and the valence band electronic structure at each composition. The valence band photoemission spectra showed that the average energy of the valence band, ε̅v, shifts linearly with composition from -6.2 eV for pure Ag to -3.4 eV for pure Pd. At all reaction conditions, the H2-D2 exchange activity was found to be highest on pure Pd and gradually decreased as the alloy was diluted with Ag until no activity was observed for compositions with x Pd < 0.58. Measured H2-D2 exchange rates across the CSAF were fit using the Dual Subsurface Hydrogen (2H') mechanism to extract estimates for the activation energy barriers to dissociative adsorption, ΔE ads ‡, associative desorption, ΔE des ‡, and the surface-to-subsurface diffusion energy, ΔE ss, as a function of alloy composition, x Pd. The 2H' mechanism predicts ΔE ads ‡ = 0-10 kJ/mol, ΔE des ‡ = 30-65 kJ/mol, and ΔE ss = 20-30 kJ/mol for all alloy compositions with x Pd ≥ 0.64, including for the pure Pd catalyst (i.e., x Pd = 1). For these Pd-rich catalysts, ΔE des ‡ and ΔE ss appeared to increase by ∼5 kJ/mol with decreasing x Pd. However, due to the coupling of kinetic parameters in the 2H' mechanism, we are unable to exclude the possibility that the kinetic parameters predicted when x Pd ≥ 0.64 are identical to those predicted for pure Pd. This suggests that H2-D2 exchange occurs only on bulk-like Pd domains, presumably due to the strong interactions between H2 and Pd. In this case, the decrease in catalytic activity with decreasing x Pd can be explained by a reduction in the availability of surface Pd at high Ag compositions.

Size normalizing planktonic Foraminifera abundance in the water column

AbstractPlanktonic Foraminifera have been collected from the water column with different plankton sampling devices equipped with nets of various mesh sizes, which impedes direct comparison of observed quantifications. Here, we use data on the community size structure of planktonic Foraminifera to assess the impact of mesh size on the measured abundance (ind m−3) of planktonic Foraminifera. We use data from the FORCIS database (Chaabane et al., 2023, Scientific Data 10: 354) on the global ocean at different sampling depths over the past century. We find a global cumulative increase in abundance with size, which is best described using a Michaelis–Menten function. This function yields multiplication factors by which one size fraction can be normalized to any other size fraction equal to or larger than 100 μm. The resulting size normalization model is calibrated over a range of different depth intervals, and validated with an independent dataset from various depth ranges. The comparison to Berger's (1969, Deep. Res. Oceanogr. Abstr. 16: 1–24) equivalent catch approach shows a significant increase in the predictive skill of the model. The new size normalization scheme enables comparison of Foraminifera abundance data sampled with plankton nets of different mesh sizes, such as compiled in the FORCIS database. The correction methodology may be effectively employed for various other plankton groups such as diatoms and dinoflagellates.

Designing highly efficient interlocking interactions in anisotropic active particles

Cluster formation of microscopic swimmers is key to the formation of biofilms and colonies, efficient motion and nutrient uptake, but, in the absence of other interactions, requires high swimmer concentrations to occur. Here we experimentally and numerically show that cluster formation can be dramatically enhanced by an anisotropic swimmer shape. We analyze a class of model microswimmers with a shape that can be continuously tuned from spherical to bent and straight rods. In all cases, clustering can be described by Michaelis-Menten kinetics governed by a single scaling parameter that depends on particle density and shape only. We rationalize these shape-dependent dynamics from the interplay between interlocking probability and cluster stability. The bent rod shape promotes assembly in an interlocking fashion even at vanishingly low particle densities and we identify the most efficient shape to be a semicircle. Our work provides key insights into how shape can be used to rationally design out-of-equilibrium self-organization, key to creating active functional materials and processes that require two-component assembly with high fidelity.