Unique Reactions Research Articles

Discovery and Theoretical Studies of Nonenzymatic Polyketide Dimerizations of Chaetophenols.

Nonenzymatic reactions sometimes construct complex structures observed in natural products, showing us unique chemical reactions. In our exploration of natural products, we identified a novel type of isochromene-derived polyketide dimer 7 with a 6/6/6/6/6 five-ring system from Chaetomium indicum along with several new related polyketides. We demonstrated that isochromene 6 and its oxidized derivative 8 undergo nonenzymatic dimerization under acidic conditions to give 7. Furthermore, density functional theory (DFT) calculations revealed the dimerization pathways, suggesting that the acidity (reaction condition) and O-prenylation are key factors in determining reaction mode.

Exploring Singlet Carbyne Anions and Related Low-Valent Carbon Species Utilizing a Cyclic Phosphino Substituent.

ConspectusThe advancement of synthetic methodologies is fundamentally driven by a deeper understanding of the structure-reactivity relationships of reactive key intermediates. Carbyne anions are compounds featuring a monovalent anionic carbon possessing four nonbonding valence electrons, which were historically confined to theoretical constructs or observed solely within the environment of gas-phase studies. These species possess potential for applications across diverse domains of synthetic chemistry and ancillary fields. This Account details our focused efforts to isolate singlet carbyne anions and explores our isolation of a range of related low-valent carbon species. Our achievements include the synthesis and characterization, under normal laboratory conditions, of gold-substituted free carbenes, copper carbyne anion complexes, ketenyl anions, keteniminyl anions, and a free stannyne. These have been accomplished using a bulky cyclic phosphino substituent, which effectively stabilizes these reactive species.Our journey commenced with the isolation of gold-substituted phosphinocarbenes, characterized by a robust carbon-gold covalent single bond, and progressed to the isolation of copper carbyne anion complexes featuring a carbon-copper ionic bond. This was realized through the synergistic combination of a bulky cyclic phosphino group and a closed-shell electron-rich late transition metal. The robustness of the carbon-gold bond contrasts markedly with the susceptibility of the carbon-copper bond, which imparts to the copper complexes the behavior characteristic of a phosphinocarbyne anion within the coordination sphere of copper, thereby enabling unique carbyne anion transfer reactions. The tri-active ambiphilic nature of the anionic carbon in these copper carbyne complexes enables the formation of three chemical bonds at the carbon center through one-pot reactions. Subsequent investigations unveiled ligand exchange reactions at the carbyne anion site, leading to the generation of stable crystalline ketenyl and keteniminyl anions. These species emerge as potent synthons capable of producing a diverse array of derivatives. In addition, we isolated a free phosphinostannyne, a rare species featuring a carbon-tin multiple bond and two adjacent ambiphilic centers. Collectively, these compounds have demonstrated a remarkable propensity for engaging in a spectrum of unique reactions, underscoring their versatility and confirming their utility in synthesizing uncharted, unique main group species.The methodologies and insights derived from our research contribute to the broader understanding of low-valent carbon species and may provide a platform for future innovations in synthetic chemistry, catalytic processes, and novel materials. As we continue to explore and develop this area of study, we hope that these low-valent carbon species might follow in the footsteps of stable singlet carbenes, potentially finding applications across various fields in the future.

Accelerated enzyme engineering by machine-learning guided cell-free expression

Enzyme engineering is limited by the challenge of rapidly generating and using large datasets of sequence-function relationships for predictive design. To address this challenge, we develop a machine learning (ML)-guided platform that integrates cell-free DNA assembly, cell-free gene expression, and functional assays to rapidly map fitness landscapes across protein sequence space and optimize enzymes for multiple, distinct chemical reactions. We apply this platform to engineer amide synthetases by evaluating substrate preference for 1217 enzyme variants in 10,953 unique reactions. We use these data to build augmented ridge regression ML models for predicting amide synthetase variants capable of making 9 small molecule pharmaceuticals. Over these nine compounds, ML-predicted enzyme variants demonstrate 1.6- to 42-fold improved activity relative to the parent. Our ML-guided, cell-free framework promises to accelerate enzyme engineering by enabling iterative exploration of protein sequence space to build specialized biocatalysts in parallel.

A comparative study of municipal fiscal responses to the COVID-19 and the Great Recession

This research investigates municipal fiscal policy responses to the COVID-19 pandemic, comparing them to those during the Great Recession using a deductive two-stage approach. First, to illustrate the general trends in municipal fiscal policy responses to these two crises, it compares municipal fiscal policy responses for 100 major U.S. cities. Then, through an in-depth investigation of four selected cities, it explores unique fiscal reactions to similar financial and environmental challenges. Providing a current overview of municipal fiscal responses, this study informs policymakers about dynamics in fiscal policy formulation across diverse fiscal environments.

Bilayer Mn-based Prussian blue cathode with high redox activity for boosting stable cycling in aqueous sodium-ion half/full batteries.

The Mn-based Prussian blue analogs (PBAs) have garnered significant attention due to their high specific capacity, stemming from the unique multi-electron reactions with Na+. However, the structural instability caused by multi-ion insertion impacts the cycle life, thus limiting their further application in aqueous sodium-ion batteries (ASIBs). To address this issue, this work employed an in situ epitaxial solvent deposition method to homogeneously grow Ni hexacyanoferrate (NiHCF) on the surface of MnPBA, which can effectively overcome the de-intercalation instability. The resulting heterostructured MnPBA@NiHCF integrates the multiple redox-active centers of MnPBA with the confinement ability of the outer NiHCF layer, thereby maintaining overall structural stability. As a cathode material for ASIBs, MnPBA@NiHCF achieves a reversible specific capacity of 66.2mAh/g after 200 cycles at 1A/g, significantly outperforming the single-component MnPBA and NiHCF, respectively. Moreover, it demonstrates ultralong cycling stability with only 0.0002% capacity fade per cycle over 20,000 cycles at 10A/g. Extensive kinetic analyses further confirm its superior Na+ diffusion behaviors with disclosed redox mechanism through the comprehensive in situ Raman and ex situ analysis. A full cell built with a polyimide (PI) anode achieved an energy density of up to 59.9Whkg-1, displaying a power output of 1200.4Wkg-1 and exceptional cycle stability. This work provides innovative insights for developing stable PBA cathodes for ASIB applications.

Analyzing sorbitol biosynthesis using a metabolic network flux model of a lichenized strain of the green microalga Diplosphaera chodatii.

Diplosphaera chodatii, a unicellular terrestrial microalga found either free-living or in association with lichenized fungi, protects itself from desiccation by synthesizing and accumulating low-molecular-weight carbohydrates such as sorbitol. The metabolism of this algal species and the interplay of sorbitol biosynthesis with its growth, light absorption, and carbon dioxide fixation are poorly understood. Here, we used a recently available genome assembly for D. chodatii to develop a metabolic flux model and analyze the alga's metabolic capabilities, particularly, for sorbitol biosynthesis. The model contains 151 genes, 155 metabolites, and 194 unique metabolic reactions participating in 12 core metabolic pathways and five compartments. Both photoautotrophic and mixotrophic growths of D. chodatii were supported by the metabolic model. In the presence of glucose, mixotrophy led to higher biomass and sorbitol yields. Additionally, the model predicted increased starch biosynthesis at high light intensities during photoautotrophic growth, an indication that the "overflow hypothesis-stress-driven metabolic flux redistribution" could be applied to D. chodatii. Furthermore, the newly developed metabolic model of D. chodatii, iDco_core, captures both linear and cyclic electron flow schemes characterized in photosynthetic microorganisms and suggests a possible adaptation to fluctuating water availability during periods of desiccation. This work provides important new insights into the predicted metabolic capabilities of D. chodatii, including a potential biotechnological opportunity for industrial sorbitol biosynthesis.IMPORTANCELichenized green microalgae are vital components for the survival and growth of lichens in extreme environmental conditions. However, little is known about the metabolism and growth characteristics of these algae as individual microbes. This study aims to provide insights into some of the metabolic capabilities of Diplosphaera chodatii, a lichenized green microalgae, using a recently assembled and annotated genome of the alga. For that, a metabolic flux model was developed simulating the metabolism of this algal species and allowing for studying the algal growth, light absorption, and carbon dioxide fixation during both photoautotrophic and mixotrophic growth, in silico. An important capability of the new metabolic model of D. chodatii is capturing both linear and cyclic electron flow mechanisms characterized in several other microalgae. Moreover, the model predicts limits of the metabolic interplay between sorbitol biosynthesis and algal growth, which has potential applications in assisting the design of bio-based sorbitol production processes.

Plasma‐assisted fabrication of multiscale materials for electrochemical energy conversion and storage

AbstractPlasma, the fourth state of matter, is characterized by the presence of charged particles, including ions and electrons. It has been shown to induce unique physical and chemical reactions. Recently, there have been increased applications of plasma technology in the field of multiscale functional materials' preparation, with a number of interesting results. This review will begin by introducing the basic knowledge of plasma, including the definition, typical parameters, and classification of plasma setups. Following this, we will provide a comprehensive review and summary of the applications (phase conversion, doping, deposition, etching, exfoliation, and surface treatment) of plasma in common energy conversion and storage systems, such as electrocatalytic conversion of small molecules, batteries, fuel cells, and supercapacitors. This article summarizes the structure–performance relationships of electrochemical energy conversion and storage materials (ECSMs) that have been prepared or modified by plasma. It also provides an overview of the challenges and perspectives of plasma technology, which could lead to a new approach for designing and modifying electrode materials in ECSMs.

Target Bioconjugation of Protein Through Chemical, Molecular Dynamics, and Artificial Intelligence Approaches.

Covalent modification of proteins at specific, predetermined sites is essential for advancing biological and biopharmaceutical applications. Site-selective labeling techniques for protein modification allow us to effectively track biological function, intracellular dynamics, and localization. Despite numerous reports on modifying target proteins with functional chemical probes, unique organic reactions that achieve site-selective integration without compromising native functional properties remain a significant challenge. In this review, we delve into site-selective protein modification using synthetic probes, highlighting both chemical and computational methodologies for chemo- and regioselective modifications of naturally occurring amino acids, as well as proximity-driven protein-selective chemical modifications. We also underline recent traceless affinity labeling strategies that involve exchange/cleavage reactions and catalyst tethering modifications. The rapid development of computational infrastructure and methods has made the bioconjugation of proteins more accessible, enabling precise predictions of structural changes due to protein modifications. Hence, we discuss bioconjugational computational approaches, including molecular dynamics and artificial intelligence, underscoring their potential applications in enhancing our understanding of cellular biology and addressing current challenges in the field.

Intergenerational effects of the Holocaust following the October 7 attack in Israel

Descendants of traumatized individuals may exhibit latent vulnerability, meaning they are typically well-functioning yet more vulnerable to stressful and traumatic events. Nevertheless, such vulnerability is not omnipresent, and some descendants are more prone than others to develop posttraumatic disorder (PTSD) and other psychopathologies. Ancestral PTSD was suggested as an aggravating factor for intergenerational effects. The current study examined whether Holocaust descendants (i.e., children and grandchildren of Holocaust survivors) show unique posttraumatic reactions to the October 7 terrorist attack and the ensuing war and whether parental/grandparental PTSD exacerbated these reactions. A web-based random sample of 582 Israeli Jews completed questionnaires a year before the October 7 terrorist attack (Wave 1, 2022) and two months after the attack and into the war (Wave 3, December 2023). Results showed that pre-war probable PTSD rates were similar across the study groups (10.4% and 11.5% among Holocaust descendants and descendants of those not directly exposed to the Holocaust, respectively). In contrast, probable PTSD rates during the war mainly increased among Holocaust descendants (20.9% and 11.5% among Holocaust and comparison descendants, respectively). Higher probable PTSD rates were especially noticeable in Wave 3 among Holocaust descendants who reported that their parents/grandparents had probable PTSD even after controlling Wave 1 probable PTSD, background characteristics, and levels of traumatic exposure. The findings have important implications for understanding the intergenerational effects of trauma as they strongly support the latent vulnerability hypothesis three generations after ancestral trauma, and further suggest that ancestral PTSD plays a major role in aggravating such vulnerability.

Alkenylboronic acid derivatives as monomers for radical polymerization leading to polymer synthesis via side-chain replacement and development of boron-based functions

Abstract Vacant p-orbital of boron is often utilized for design of unique organic reactions based on its stabilization of adjacent carbon radical and Lewis acidity for interactions with internal or external base. In this study, these unique properties of boron were utilized to design vinyl monomers for chain-growth polymerization. The author found that alkenylboronic acid derivatives, where boron is connected to a vinyl moiety, exhibit radical (co)polymerization abilities due to the stabilization of the chain-growth radical by the p-orbital of boron. The resulting polymers have boron atoms attached to the main chain, and the replacement of boron pendants with other elements in the post-polymerization transformation step enabled the synthesis of novel polymers that are difficult to access by conventional methods [e.g. poly(α-methyl vinyl alcohol), branched poly(vinyl alcohol), and poly(ethylene-co-acrylate)]. Furthermore, boron on the main chain served not only as a replaceable side chain but also as a Lewis acidic moiety for developing novel polymer functions such as stimuli-responsive backbone degradation and side-chain cooperative polymer catalysts. The concept of boron-based monomer design thus opens new avenues in polymer chemistry and materials science.

(Invited) Synthetic Electrochemistry: Leaping into a New Era

Electrochemistry plays a pivotal role in organic synthesis, offering efficient and sustainable pathways for the construction of complex molecules. By harnessing the power of electricity, precise and unique redox reactions are possible, facilitating the synthesis of diverse organic compounds with high selectivity and atom economy. The merger of this technique with radical coupling offers unrivalled synthetic utility under mild and practical conditions. In this lecture, our recent development of electrochemical coupling reactions as well as how they are changing the landscape of organic synthesis will be discussed.

AI-Driven Discovery of Asymmetric Pauson-Khand Reactions: A New Toolbox in a Synthetic Chemist's Treasure.

Enantioselective catalytic reactions have a significant impact on chemical synthesis, and they are important components in an experimental chemist's toolbox. However, development of asymmetric catalysts often relies on the chemical intuition and experience of a synthetic chemist, making the process both time-consuming and resource-intensive. The machine-learning-assisted reaction discovery can serve as a very efficient platform for obtaining high-performing catalysts in a time-economical manner without extensive experimentation. Herein, we report a data-driven and machine learning method for reliably predicting enantiomeric excess (%ee) of 211 asymmetric Pauson-Khand reactions (PKR 1-PKR 211) between a variety of 45 unique 1,6-enyne substrates and 12 unique axially chiral biaryl ligands in the presence of different reaction conditions like varying CO gas pressure, temperature, and solvent polarity. Four different machine learning algorithms have been studied: extreme gradient boosting (XGBoost), random forest (RF), light gradient boosting machine (LGBM), and neural network (NN). A fivefold cross validation method was applied to our k-means SMOTE-augmented data set to obtain the optimized hyperparameters for the training set, and subsequently, these parameters were used in the test data set. In the case of the out-of-box set, the XGBoost method is found to be superior among all four machine learning methods investigated. Our out-of-box samples contain a total of 12 unique asymmetric Pauson-Khand reactions (PKR 212-PKR 223) arising from three new 1,3-benzodioxole-based SEGPHOS catalysts, which were never included in the training set. The XGBoost algorithm shows an impressive root mean square error (RMSE) of 7.06 (±1.11) in predicting %ee. The XGBoost-predicted %ee values match reasonably well with the experimental results. The absolute difference between the experimental and XGBoost-calculated %ee values ranges from 0.9 to 7.6 for the majority of the out-of-box Pauson-Khand reactions. The reactions with fluoro-substituted-SEGPHOS ligand L14 shows smaller deviations from the experimental %ee values compared to the reactions with L13 and L15 catalysts where the benzodioxole units do not have fluorine atoms. Finally, we have discovered a library of 3357 lead reactions with excellent %ee (≥99) by engaging the experimentally unknown combinations of the catalysts, substrates, and reaction conditions. The axially chiral biaryl catalysts and enyne substrates present in the library are synthetically accessible. The ligand space in the library is dominated by the presence of tol-BINAP and the DTBM-OMe-BIPHEP ligands. The substrate space is predominantly occupied by NTs-tethered, O-tethered, NBn-tethered, and C(CO2Me)2-tethered 1,6-enynes that have an H or methyl functional group present in the alkyne unit. Our newly discovered library assists a synthetic chemist to develop a highly enantioselective PKR by starting with a priori knowledge without extensive trial-and-error experimentation.

Rapid Exploration of Chemical Space by High-Throughput Desorption Electrospray Ionization Mass Spectrometry.

This study leverages accelerated reactions at the solution/air interface of microdroplets generated by desorption electrospray ionization (DESI) to explore the chemical space. DESI is utilized to synthesize drug analogs at an overall rate of 1 reaction mixture per second, working on the low-nanogram scale. Transformations of multiple drug molecules at specific functionalities (phenol, hydroxyl, amino, carbonyl, phenyl, thiophenyl, and alkenyl) are achieved using electrophilic/nucleophilic, redox, C-H functionalization, and coupling reactions. These transformations occur under ambient conditions on the millisecond time scale with direct detection of products being successful in all but three of the reaction types studied. The large scope (22 bioactive compounds, >20 chemical transformations, and >300 functionalization reagents) and high speed (>3000 reactions/hour) provide access to a wide array of drug analogs that can be used for bioactivity testing. A total of ∼6800 unique reactions were examined through a data-driven workflow, and more than 3000 unique derivatives (∼44%) were identified tentatively by the m/z value and signal-to-control ratio in single-stage mass spectrometry (MS) analysis, with over 1000 being further characterized by tandem MS. The speed of the DESI-MS reaction screen provides potential advantages for emerging machine learning-based predictions of organic synthesis, and it sets the stage for future online DESI-MS bioassays and scaled-up microdroplet synthesis before formal characterization of hit compounds is sought using traditional methods of drug discovery.

Programmable C−N Bond Formation through Radical‐Mediated Chemistry in Plasma‐Microdroplet Fusion

AbstractNon‐thermal plasma discharge produced in the wake of charged microdroplets is found to facilitate catalyst‐free radical mediated hydrazine cross‐coupling reactions without the use of external light source, heat, precious metal complex, or trapping agents. A plasma‐microdroplet fusion platform is utilized for introduction of hydrazine reagent that undergoes homolytic cleavage forming radical intermediate species. The non‐thermal plasma discharge that causes the cleavage originates from a chemically etched silica capillary. The coupling of the radical intermediates gives various products. Plasma‐microdroplet fusion occurs online in a programmable reaction platform allowing direct process optimization and product validation via mass spectrometry. The platform is applied herein with a variety of hydrazine substrates, enabling i) self‐coupling to form secondary amines with identical N‐substitutions, ii) cross‐coupling to afford secondary amine with different N‐substituents, iii) cross‐coupling followed by in situ dehydrogenation to give the corresponding aryl‐aldimines with two unique N‐substitutions, and iv) cascade heterocyclic carbazole derivatives formation. These unique reactions were made possible in the charged microdroplet environment through our ability to program conditions such as reagent concentration (i. e., flow rate), microdroplet reactivity (i. e., presence or absence of plasma), and reaction timescale (i. e., operational mode of the source). The selected program is implemented in a co‐axial spray format, which is found to be advantageous over the conventional one‐pot single emitter electrospray‐based microdroplet reactions.

Programmable C-N Bond Formation through Radical-Mediated Chemistry in Plasma-Microdroplet Fusion.

Non-thermal plasma discharge produced in the wake of charged microdroplets is found to facilitate catalyst-free radical mediated hydrazine cross-coupling reactions without the use of external light source, heat, precious metal complex, or trapping agents. A plasma-microdroplet fusion platform is utilized for introduction of hydrazine reagent that undergoes homolytic cleavage forming radical intermediate species. The non-thermal plasma discharge that causes the cleavage originates from a chemically etched silica capillary. The coupling of the radical intermediates gives various products. Plasma-microdroplet fusion occurs online in a programmable reaction platform allowing direct process optimization and product validation via mass spectrometry. The platform is applied herein with a variety of hydrazine substrates, enabling i) self-coupling to form secondary amines with identical N-substitutions, ii) cross-coupling to afford secondary amine with different N-substituents, iii) cross-coupling followed by in situ dehydrogenation to give the corresponding aryl-aldimines with two unique N-substitutions, and iv) cascade heterocyclic carbazole derivatives formation. These unique reactions were made possible in the charged microdroplet environment through our ability to program conditions such as reagent concentration (i. e., flow rate), microdroplet reactivity (i. e., presence or absence of plasma), and reaction timescale (i. e., operational mode of the source). The selected program is implemented in a co-axial spray format, which is found to be advantageous over the conventional one-pot single emitter electrospray-based microdroplet reactions.

Perylene Bisimide-Functionalized Triphenylmethyl Radicals Showing High Stability and Reversible Electrochemical Redox Properties.

This study presents a series of triphenylmethyl monoradicals incorporating varying numbers of peripheral perylene bisimide (PBI) substituents (1PBI-TTM⋅, 2PBI-TTM⋅ and 3PBI-TTM⋅). The incorporation of electron-withdrawing PBI substituents significantly enhances the stability of these carbon radicals, enabling them to display exceptional electrochemical redox reversibility. Notably, the electronic interplay between the PBI substituents and the central triphenylmethyl core facilitates unique and reversible multi-step redox reactions. Among the reported radicals, the tris-PBI-functionalized radical (3PBI-TTM⋅) demonstrates the remarkable ability to accommodate up to seven electrons under negative potentials, forming high valence anions. This research promotes the development of highly stable carbon radicals with superior electrochemical oxidation-reduction processes, presenting promising avenues for the advancement of electric energy storage technologies.

Simultaneous Cycloadditions in the Solid State via Supramolecular Assembly

AbstractChemical reactions conducted in the solid phase (specifically, crystalline) are much less numerous than solution reactions, primarily due to reduced motion, flexibility, and reactivity. The main advantage of crystalline‐state transformations is that reactant molecules can be designed to self‐assemble into specific spatial arrangements, often leading to high control over product regiochemistry and/or stereochemistry. In crystalline‐phase transformations, typically only one type of reaction occurs, and a sacrificial template molecule is frequently used to facilitate self‐assembly, similar to a catalyst or enzyme. Here, we demonstrate the first system designed to undergo two chemically unique and orthogonal cycloaddition reactions simultaneously within a single crystalline solid. Well‐controlled supramolecular self‐assembly of two molecules containing different reactive moieties affords orthogonal reactivity without use of a sacrificial template. Using only UV light, the simultaneous [2+2] and [4+4] cycloadditions are achieved regiospecifically, stereospecifically, and products are obtained in high yield, whereas a simultaneous solution‐state reaction affords a mixture of isomers in low yield. Application of dually‐reactive systems toward (supra)molecular solar thermal storage materials is also discussed. This work demonstrates fundamental chemical approaches for orthogonal reactivity in the crystalline state and highlights the complexity and reversibility that can be achieved with supramolecular design.

Identifying transdiagnostic and multidimensional prognostic indicators among veterans with PTSD symptoms in brief integrated care settings.

Brief integrated care settings hold promise for accessible and effective trauma-informed interventions. However, clinicians often have difficulty efficiently forecasting who is most appropriate for interventions in such settings and how to target individualized care. Multidimensional and transdiagnostic evaluations may provide valuable information to improve stepped-care and treatment practices for veterans. A middle-out approach was used to concurrently evaluate self-reported posttraumatic stress disorder (PTSD) symptoms, depressive symptoms, and physical health problems using cross-sectional (latent profile analysis) and longitudinal (latent growth mixture modeling) analyses that identified unique symptom profiles, trajectories of traumatic stress reactions, and correlates of these health outcomes. Data from 234 veterans who participated in a randomized controlled trial of primary care PTSD intervention were analyzed at 0, 8, 16, and 24 weeks. Latent profile analysis identified two homogenous baseline profiles: global symptoms (33.8%); low dysphoria-lower negative cognitions, mood, and depressive symptoms (66.2%). Low dysphoria participants reported more social relationships (OR = 1.32) and fewer environmental (OR = 0.89) and financial (OR = 0.23-0.35) stressors. Latent growth mixture modeling identified three trajectories: (a) reducing symptoms ("responders"; 21.3%) and chronic symptoms of (b) moderate (59.6%) and (c) high (19.1%) severity. Low dysphoria participants were 4.35 times more likely to be responders over time compared to participants with moderate severity symptoms. Findings indicated that veterans with moderate PTSD symptoms and physical health problems but low dysphoria may respond best to trauma-informed intervention in brief integrated care settings, while others may require further individualized stepped care. Findings demonstrate unique traumatic stress reactions that support individualized stepped care and may offer greater treatment utilization, retention, and efficacy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Fluorescence imaging of dopamine in living cells triggered by unique coupling reactions

BackgroundDopamine (DA) is a significant neurotransmitter and catecholamine molecule in the mammalian brain. It plays a crucial role in perception, cognition, central nervous system regulation, and hormone secretion. The detection of DA levels in living systems is a vital aspect of the research and early diagnosis of neurological disorders. ResultsIn this study, we achieved an effective fluorescence generation specific to DA under physiological pH conditions by coupling the DA detection reaction to the HClO oxidation reaction. This method has been used for the detection of DA in cells, as well as for the visualization of DA levels in cellular models of inflammation and depression. SignificanceThis is the first time that utilizes an organic fluorescent molecular probe to detect DA in living cells.

An Automated Cell-Free Workflow for Transcription Factor Engineering.

The design and optimization of metabolic pathways, genetic systems, and engineered proteins rely on high-throughput assays to streamline design-build-test-learn cycles. However, assay development is a time-consuming and laborious process. Here, we create a generalizable approach for the tailored optimization of automated cell-free gene expression (CFE)-based workflows, which offers distinct advantages over in vivo assays in reaction flexibility, control, and time to data. Centered around designing highly accurate and precise transfers on the Echo Acoustic Liquid Handler, we introduce pilot assays and validation strategies for each stage of protocol development. We then demonstrate the efficacy of our platform by engineering transcription factor-based biosensors. As a model, we rapidly generate and assay libraries of 127 MerR and 134 CadR transcription factor variants in 3682 unique CFE reactions in less than 48 h to improve limit of detection, selectivity, and dynamic range for mercury and cadmium detection. This was achieved by assessing a panel of ligand conditions for sensitivity (to 0.1, 1, 10 μM Hg and 0, 1, 10, 100 μM Cd for MerR and CadR, respectively) and selectivity (against Ag, As, Cd, Co, Cu, Hg, Ni, Pb, and Zn). We anticipate that our Echo-based, cell-free approach can be used to accelerate multiple design workflows in synthetic biology.