Synthetic Studies Research Articles

A Library of Promoter-gfp Fusion Reporters for Studying Systematic Expression Pattern of Cyclic-di-GMP Metabolism-Related Genes in Pseudomonas aeruginosa.

The opportunistic pathogen Pseudomonas aeruginosa is an environmental microorganism and is a model organism for biofilm research. Cyclic dimeric GMP (c-di-GMP) is a bacterial second messenger that plays critical roles in biofilm formation. P. aeruginosa contains approximately 40 genes that encode enzymes that participate in the metabolism of c-di-GMP (biosynthesis or degradation), yet it lacks tools that aid investigation of the systematic expression pattern of those genes. In this study, we constructed a promoter-gfp fusion reporter library that consists of 41 reporter plasmids. Each plasmid contains a promoter of corresponding c-di-GMP metabolism-related (CMR) genes from P. aeruginosa reference strain PAO1; thus, each promoter-gfp fusion reporter can be used to detect the promoter activity as well as the transcription of corresponding gene. The promoter activity was tested in P. aeruginosa and Escherichia coli. Among the 41 genes, the promoters of 26 genes showed activity in both P. aeruginosa and E. coli. The library was applied to determine the influence of different temperatures, growth media, and subinhibitory concentrations of antibiotics on the transcriptional profile of the 41 CMR genes in P. aeruginosa. The results showed that different growth conditions did affect the transcription of different genes, while the promoter activity of a few genes was kept at the same level under several different growth conditions. In summary, we provide a promoter-gfp fusion reporter library for systematic monitoring or study of the regulation of CMR genes in P. aeruginosa. In addition, the functional promoters can also be used as a biobrick for synthetic biology studies. IMPORTANCE The opportunistic pathogen P. aeruginosa can cause acute and chronic infections in humans, and it is one of the main pathogens in nosocomial infections. Biofilm formation is one of the most important causes for P. aeruginosa persistence in hosts and evasion of immune and antibiotic attacks. c-di-GMP is a critical second messenger to control biofilm formation. In P. aeruginosa reference strain PAO1, 41 genes are predicted to participate in the making and breaking of this dinucleotide. A major missing piece of information in this field is the systematic expression profile of those genes in response to changing environment. Toward this goal, we constructed a promoter-gfp transcriptional fusion reporter library that consists of 41 reporter plasmids, each of which contains a promoter of corresponding c-di-GMP metabolism-related genes in P. aeruginosa. This library provides a helpful tool to understand the complex regulation network related to c-di-GMP and to discover potential therapeutic targets.

Aza-Wacker Cyclization Toward the Bridged Core of FR901483

AbstractA nine-step synthetic route to access the tricyclic core of FR901483 is reported, featuring a key aza-Wacker cyclization step to construct an α-tertiary amine (ATA) in the bridged structure. The aza-Wacker protocol can tolerate both exocyclic and endocyclic double bonds, providing viable access to various bridged bicyclic rings bearing an ATA (e.g., 6-azabicyclo[3.2.1]octane, 7-azabicyclo[3.3.1]nonane, and 7-azabicyclo[4.2.1]nonane) in good to excellent yields. The synthetic studies presented herein enable structural derivatization of FR901483 to further exploit its compelling biological activities.

A data-driven approach to exploring the causal relationships between distributed pumping activities and aquifer drawdown

Groundwater depletion, typically caused by the distributed pumping activities of multiple stakeholders (i.e., water users) that share a hydrologically connected aquifer, has led to severe environmental and ecological problems in many river basins worldwide. Conventionally, the effects of pumping on aquifer depletion are quantified using well hydraulics or physically based hydrological models in groundwater management. However, the derivation of well hydraulics-based analytical solutions requires numerous simplifying assumptions, while the construction and calibration of a physically based groundwater flow model require detailed information about the subsurface properties, which are subject to large uncertainties. In this study, we develop a novel modeling framework that does not rely on well hydraulics or groundwater flow models. The proposed framework integrates (1) a deep learning model that captures the spatiotemporal variations in the aquifer in response to distributed pumping activities in multiple well fields and (2) a statistical causal inference model that identifies the causal networks among stakeholders to quantify the causal effects of individual pumping activities on aquifer depletion. The proposed framework is tested on a synthetic case study site with well fields that have various spatial distributions and pumping rates. The modeling results show that the deep learning method can effectively capture the water table dynamics influenced by distributed pumping activities with R2 >90 % for all observation data. More importantly, our model is capable of assessing the causal networks between the drawdown of water table and the pumping activities of multiple well fields and quantifying their causal strengths. These results suggest that our modeling framework can be used to explicitly assess the extent to which each individual stakeholder's pumping activities contribute to aquifer depletion at the system level. The concepts and techniques developed in this study can be used to resolve classic externality problems in the context of common-pool groundwater management.

Microfluidic formation and manipulation of OLA-based liposomes for synthetic biology research.

Bottom-up synthetic biology aims to create biomimetic systems from the basic elements of cellular life. Such synthetic cell analogs may support scientists in understanding the fundamental biological behaviors at the cellular level. As microscopic aqueous compartments confined within a lipid bilayer, liposomes have been widely used as simplistic cellular mimics for synthetic cell studies. Here, we describe the manufacturing protocol for octanol-assisted liposome assembly (OLA) to produce unilamellar, monodispersed, cell-sized, and biocompatible liposomes as well as in situ liposome experiments. We use maskless, direct-write lithography, which allows for rapid prototyping, to fabricate PDMS-based lab-on-a-chip devices. OLA makes use of the double emulsion generation and dewetting purification approach, with the membrane composition of the formed liposomes and the nature of the encapsulated solution widely adjustable. Using highly responsive pressure-driven flow, the liposome size is tuneable with a steady liposome generation, and the experiment requires very low sample volumes (∼50 µl). We enrich the liposomes from the waste products using density-based on-chip separation techniques, which allows us to conduct experiments on the same device with real-time observation, right after production. As a proof-of-principle synthetic biology application, we demonstrate the capability of adjusting the microenvironment by inducing pH-controlled coacervation between ATP and poly-Llysine molecules inside the liposomes via transmembrane proton flux. Such liquid-liquid phase separation, creating multiple distinct phases from a single homogeneous mixture, is known to play a key role in a variety of cellular processes, including the formation of membraneless organelles as well as numerous other supramolecular assemblies. Our technique shows promising potential for synthetic cell research, particularly in terms of step-by-step construction and experimental control.

Physics‐Informed Neural Networks of the Saint‐Venant Equations for Downscaling a Large‐Scale River Model

AbstractLarge‐scale river models are being refined over coastal regions to improve the scientific understanding of coastal processes, hazards and responses to climate change. However, coarse mesh resolutions and approximations in physical representations of tidal rivers limit the performance of such models at resolving the complex flow dynamics especially near the river‐ocean interface, resulting in inaccurate simulations of flood inundation. In this research, we propose a machine learning (ML) framework based on the state‐of‐the‐art physics‐informed neural network (PINN) to simulate the downscaled flow at the subgrid scale. First, we demonstrate that PINN is able to assimilate observations of various types and solve the one‐dimensional (1‐D) Saint‐Venant equations (SVE) directly. We perform the flow simulations over a floodplain and along an open channel in several synthetic case studies. The PINN performance is evaluated against analytical solutions and numerical models. Our results indicate that the PINN solutions of water depth have satisfactory accuracy with limited observations assimilated. In the case of flood wave propagation induced by storm surge and tide, a new neural network architecture is proposed based on Fourier feature embeddings that seamlessly encodes the periodic tidal boundary condition in the PINN's formulation. Furthermore, we show that the PINN‐based downscaling can produce more reasonable subgrid solutions of the along‐channel water depth by assimilating observational data. The PINN solution outperforms the simple linear interpolation in resolving the topography and dynamic flow regimes at the subgrid scale. This study provides a promising path toward improving emulation capabilities in large‐scale models to characterize fine‐scale coastal processes.

Identification of the inflow source in a foul sewer system through techniques of inverse modelling

Infiltration and illegal inflow into foul sewer systems can cause different problems such as a decrease in the performance of treatment plants, the surcharge of pipelines and more frequent overflows, which cause negative impacts on the environment. Water companies are increasingly been driven to address these problems by reducing infiltrations and identifying the sources of illegal inflows. Overall, the traditional techniques applied in these cases are expensive and time consuming and many times only partially efficient. Examples are the use of CCTV inspections, smoke tests and the installation of a large set of sensors to collect continuous data such as flow rates, water levels, temperature or concentrations of pollutants. The aim of this study is to apply two types of inverse numerical techniques to identify the source location of illegal inflows into wastewater systems based on information collected at the outlet of the drained basin and a calibrated numerical model of the sewer network. In this work, the numerical model is developed using the Storm Water Management Model (SWMM) software distributed by the Environmental Protection Agency (USA). We considered a realistic foul sewer system with known dimensional and hydrological characteristics. Synthetic case studies are set up to test the inverse approaches. Assuming a hypothetical rainfall event and an illegal inflow released at a certain location in the sewer system, the numerical model is run forward to obtain the flow hydrograph at the network outlet. This information is then used as available observations to perform the inverse modelling. The first investigated technique is an artificial neural network (ANN) of the feed-forward type. It will be trained to recover the inflow source using the simulation results of SWMM driven by a large set of rainfall events and inflows located at different positions in the sewer network. Once trained, the ANN will be used to identify the location of the inflow based the observed flood wave. The second procedure derives from Kalman filter techniques: the Ensemble Smoother with Multiple Data Assimilation (ES-MDA). Also in this case, the method, starting from the known rainfall event and the observed flow hydrograph, is used to locate the inflow source. In addition to the results of the synthetic case obtained by means of the two procedures, the field applicability to real case studies will be discussed.

Synthetic Studies of Bioactive Oxacyclic Natural Products

Synthetic Studies of Bioactive Oxacyclic Natural Products

Turn-Taking Mechanisms in Imitative Interaction: Robotic Social Interaction Based on the Free Energy Principle

This study explains how the leader-follower relationship and turn-taking could develop in a dyadic imitative interaction by conducting robotic simulation experiments based on the free energy principle. Our prior study showed that introducing a parameter during the model training phase can determine leader and follower roles for subsequent imitative interactions. The parameter is defined as w, the so-called meta-prior, and is a weighting factor used to regulate the complexity term versus the accuracy term when minimizing the free energy. This can be read as sensory attenuation, in which the robot's prior beliefs about action are less sensitive to sensory evidence. The current extended study examines the possibility that the leader-follower relationship shifts depending on changes in w during the interaction phase. We identified a phase space structure with three distinct types of behavioral coordination using comprehensive simulation experiments with sweeps of w of both robots during the interaction. Ignoring behavior in which the robots follow their own intention was observed in the region in which both ws were set to large values. One robot leading, followed by the other robot was observed when one w was set larger and the other was set smaller. Spontaneous, random turn-taking between the leader and the follower was observed when both ws were set at smaller or intermediate values. Finally, we examined a case of slowly oscillating w in anti-phase between the two agents during the interaction. The simulation experiment resulted in turn-taking in which the leader-follower relationship switched during determined sequences, accompanied by periodic shifts of ws. An analysis using transfer entropy found that the direction of information flow between the two agents also shifted along with turn-taking. Herein, we discuss qualitative differences between random/spontaneous turn-taking and agreed-upon sequential turn-taking by reviewing both synthetic and empirical studies.

Enhancing Mortality Forecasting through Bivariate Model–Based Ensemble

We propose a bivariate model–based ensemble (BMBE) method to borrow information from the mortality data of a given pool of auxiliary populations to enhance the mortality forecasting of a target population. The BMBE method establishes a cascade of bivariate mortality models between the target population and each auxiliary population as the base learners. Then it aggregates prediction results from all of the base learners by means of an averaging strategy. Augmented common factor–type and CBD-type bivariate models are applied as the base learners as illustrative examples in the empirical studies with the Human Mortality Database. Empirical results presented in this article confirm the effectiveness of the proposed BMBE method in enhancing mortality prediction. For completeness, we also conduct a synthetic study to illustrate a particular setting for the superior performance of the BMBE method.

Synthetic Study of Dragmacidin E: Enantioselective Construction of the Seven-Membered Ring-Fused Indole Skeleton with Contiguous Stereocenters.

We developed an enantioselective synthetic method of constructing a seven-membered ring-fused indole skeleton with contiguous stereocenters for the synthesis of dragmacidin E. Introduction of chirality at the benzylic position was achieved by Ir-catalyzed asymmetric hydrogenation. After construction of the tricyclic molecular framework using Pd-catalyzed cascade cyclization, the tetrasubstituted carbon center was created using the Ag nitrene-mediated C-H amination reaction. The developed method provided access to the functionalized seven-membered ring-fused indole skeleton with a hydroxymethyl branch in the tetrasubstituted carbon.

Metabolic Engineering of Zymomonas mobilis for Acetoin Production by Carbon Redistribution and Cofactor Balance

Biorefinery to produce value-added biochemicals offers a promising alternative to meet our sustainable energy and environmental goals. Acetoin is widely used in the food and cosmetic industries as taste and fragrance enhancer. The generally regarded as safe (GRAS) bacterium Zymomonas mobilis produces acetoin as an extracellular product under aerobic conditions. In this study, metabolic engineering strategies were applied including redistributing the carbon flux to acetoin and manipulating the NADH levels. To improve the acetoin level, a heterologous acetoin pathway was first introduced into Z. mobilis, which contained genes encoding acetolactate synthase (Als) and acetolactate decarboxylase (AldC) driven by a strong native promoter Pgap. Then a gene encoding water-forming NADH oxidase (NoxE) was introduced for NADH cofactor balance. The recombinant Z. mobilis strain containing both an artificial acetoin operon and the noxE greatly enhanced acetoin production with maximum titer reaching 8.8 g/L and the productivity of 0.34 g∙L−1∙h−1. In addition, the strategies to delete ndh gene for redox balance by native I-F CRISPR-Cas system and to redirect carbon from ethanol production to acetoin biosynthesis through a dcas12a-based CRISPRi system targeting pdc gene laid a foundation to help construct an acetoin producer in the future. This study thus provides an informative strategy and method to harness the NADH levels for biorefinery and synthetic biology studies in Z. mobilis.

Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application

Objective. In PET/CT imaging, CT is used for positron emission tomography (PET) attenuation correction (AC). CT artifacts or misalignment between PET and CT can cause AC artifacts and quantification errors in PET. Simultaneous reconstruction (MLAA) of PET activity (λ-MLAA) and attenuation (μ-MLAA) maps was proposed to solve those issues using the time-of-flight PET raw data only. However, λ-MLAA still suffers from quantification error as compared to reconstruction using the gold-standard CT-based attenuation map (μ-CT). Recently, a deep learning (DL)-based framework was proposed to improve MLAA by predicting μ-DL from λ-MLAA and μ-MLAA using an image domain loss function (IM-loss). However, IM-loss does not directly measure the AC errors according to the PET attenuation physics. Our preliminary studies showed that an additional physics-based loss function can lead to more accurate PET AC. The main objective of this study is to optimize the attenuation map generation framework for clinical full-dose 18F-FDG studies. We also investigate the effectiveness of the optimized network on predicting attenuation maps for synthetic low-dose oncological PET studies. Approach. We optimized the proposed DL framework by applying different preprocessing steps and hyperparameter optimization, including patch size, weights of the loss terms and number of angles in the projection-domain loss term. The optimization was performed based on 100 skull-to-toe 18F-FDG PET/CT scans with minimal misalignment. The optimized framework was further evaluated on 85 clinical full-dose neck-to-thigh 18F-FDG cancer datasets as well as synthetic low-dose studies with only 10% of the full-dose raw data. Main results. Clinical evaluation of tumor quantification as well as physics-based figure-of-merit metric evaluation validated the promising performance of our proposed method. For both full-dose and low-dose studies, the proposed framework achieved <1% error in tumor standardized uptake value measures. Significance. It is of great clinical interest to achieve CT-less PET reconstruction, especially for low-dose PET studies.

Synthetic Studies towards Pheromones by Cyanide‐Catalyzed Ring Transformation of α‐Hydroxy‐β‐oxoesters to δ‐Valerolactones

AbstractThe cyanide‐catalyzed ring‐transformation of α‐hydroxy‐β‐oxoesters to δ‐lactones with exocyclic ester moiety is the key transformation for the preparation of racemic 5‐hexadecanolide (15 % over nine steps) and 6‐acetoxy‐5‐hexadecanolide (22 % over eight steps), two insect pheromones. The benzyloxycarbonyl moiety is transformed via the acid chloride to the undecanoyl side chain. After reduction of the ketone to the secondary alcohol, this functional group was either reduced via the chloro compound to furnish the 5‐hexadecanolide. On the other hand, stereoselective reduction of the ketone gave secondary alcohol with the wrong relative configuration, which was established by X‐ray single‐crystal structure. Inversion was achieved by reaction of the methanesulfonate with cesium acetate yielding (R*,S*)‐6‐acetoxy‐5‐hexadecanolide with the relative configuration also present in the natural product.

From Empire-wide integration to regional localization: A synthetic and quantitative study of heterogeneous amphora data in Roman Germania reveals centuries-long change in regional patterns of production and consumption.

We present novel insights into trade in amphorae-borne products over a 550-year period in Germania along the frontier of the Roman Empire, derived through probabilistic aoristic methods to study temporal changes in archaeological materials. Our data analysis reveals highly detailed differential patterns of consumption and production within the German market. We show how connections to far-flung regions such as the Eastern Mediterranean or the Iberian Peninsula wax and wane through time, and how the local German producers start to compete with these imported products. These chronological patterns provide important insight into a regional market within the larger Roman economy and provide an important case study in changing economic connections over a long period, demonstrating in a transparent and reproducible way a geographical and chronological pulsation in market activity that was otherwise unknown and undemonstrated.

Synthesis of High-Order and High-Oxidation State Securinega Alkaloids.

ConspectusSecurinega alkaloids, composed of more than 100 members characterized by the compact tetracyclic scaffold, have fascinated the synthetic community with their structural diversity and notable bioactivities. On the basis of the structural phenotype, oligomerizations and oxidations are major biosynthetic diversification modes of the basic Securinega framework. Despite the rich history of synthesis of basic monomeric Securinega alkaloids, the synthesis of oligomeric Securinega alkaloids, as well as oxidized derivatives, has remained relatively unexplored because of their extra structural complexity. In the first half of this Account, our synthetic studies toward high-order Securinega alkaloids are described. We aimed to establish a reliable synthetic method to form C14-C15' and C12-C15' bonds, which are prevalent connection modes between monomers. During our total synthesis of flueggenine C (9), we have invented an accelerated Rauhut-Currier reaction capable of forming the C14-C15' bond stereoselectively. Installation of the nucleophilic functionality to the Michael acceptor, which ushers the C-C bond forming conjugate addition to follow the intramolecular pathway, was the key to success. The C12-C15' linkage, which was inaccessible via an accelerated Rauhut-Currier reaction, was established by devising a complementary cross-coupling/conjugate reduction-based dimerization strategy that enabled the total synthesis of flueggenines D (11) and I (14). In this approach, the C12-C15' linkage was established via a Stille cross-coupling, and the stereochemistry of the C15' position was controlled during the following conjugate reduction step. In the later half of this Account, our achievements in the field of high-oxidation state Securinega alkaloids synthesis are depicted. We have developed oxidative transformations at the N1 and C2-C4 positions, where the biosynthetic oxidation event occurs most frequently. The discovery of a VO(acac)2-mediated regioselective Polonovski reaction allowed us to access the key 2,3-dehydroallosecurinine (112). Divergent synthesis of secu'amamine A (62) and fluvirosaones A (60) and B (61) was accomplished by exploiting the versatile reactivities of the C2/C3 enamine moiety in 112. We have also employed a fragment-coupling strategy between menisdaurilide and piperidine units, which allowed the installation of various oxygen-containing functionality on the piperidine ring. Combined with the late-stage, light-mediated epimerization and well-orchestrated oxidative modifications, collective total synthesis of seven C4-oxygenated securinine-type natural products was achieved. Lastly, the synthesis of flueggeacosine B (70) via two synthetic routes from allosecurinine (103) was illustrated. The first-generation synthesis (seven overall steps) employing Pd-catalyzed cross-coupling between stannane and thioester to form the key C3-C15' bond enabled the structural revision of the natural product. In the second-generation synthesis, we have invented visible-light-mediated, Cu-catalyzed cross-dehydrogenative coupling (CDC) between an aldehyde and electron-deficient olefin, which streamlined the synthetic pathway into four overall steps. Organisms frequently utilize dimerization (oligomerization) and oxidations during the biosynthesis as a means to expand the chemical space of their secondary metabolites. Therefore, methods and strategies for dimerizations and oxidations that we have developed using the Securinega alkaloids as a platform would be broadly applicable to other alkaloids. It is our sincere hope that lessons we have learned during our synthetic journey would benefit other chemists working on organic synthesis.

Rotation‐Inversion Isomerization of Tertiary Carbamates: Potential Energy Surface Analysis of Multi‐Paths Isomerization Using Boltzmann Statistics

The front cover artwork is provided by Prof. Rainer Glaser's group at the Missouri University of Science and Technology. The image shows one of four potential energy surfaces generated from our rotation-inversion study of tertiary carbamates and highlights two of the eight possible transition state pathways between two ensembles of E- and Z-minima. In the context of synthetic studies of fluorinated carbamates R1 O-CO-N(R2 )CH2 CF3 , we unexpectedly observedtwosets of13 C NMR quartets for the CF3 group and we needed to understand their origin. Read the full text of the Research Article at 10.1002/cphc.2022005442.

Current Trends in the Development of EGFR Inhibitors as Promising Anticancer Agents: Sar and Synthetic Studies from (2010-2020)

Abstract: The EGFR (Epidermal Growth Factor Receptor) regulates cell proliferation, survival, and differentiation. The EGFR is a cell surface receptor that belongs to the ErbB tyrosine kinase family. One of the most important targets for cancer therapy is EGFR inhibition. Because EGFR over-activation is seen in a wide range of malignancies, targeting EGFR and its downstream signaling cascades is a sensible and beneficial strategy in cancer therapy. This review highlighted the most potent EGFR inhibitors with SAR studies and their synthetic chemical pathways discovered between 2010-2020, employed for treating Liver, Breast, Lung, Pancreatic, and Colorectal cancers. We also include the clinical trials and the registered patents in our review.

Back to the future: asymmetrical DπA 2,2'-bipyridine ligands for homoleptic copper(i)-based dyes in dye-sensitised solar cells.

Metal complexes used as sensitisers in dye-sensitised solar cells (DSCs) are conventionally constructed using a push-pull strategy with electron-releasing and electron-withdrawing (anchoring) ligands. In a new paradigm we have designed new DπA ligands incorporating diarylaminophenyl donor substituents and phosphonic acid anchoring groups. These new ligands function as organic dyes. For two separate classes of DπA ligands with 2,2'-bipyridine metal-binding domains, the DSCs containing the copper(i) complexes [Cu(DπA)2]+ perform better than the push-pull analogues [Cu(DD)(AA)]+. Furthermore, we have shown for the first time that the complexes [Cu(DπA)2]+ perform better than the organic DπA dye in DSCs. The synthetic studies and the device performances are rationalised with the aid of density functional theory (DFT) and time-dependent DFT (TD-DFT) studies.

Zeolite encapsulated organometallic complexes as model catalysts.

Heterogeneities in the structure of active centers in metal-containing porous materials are unavoidable and complicate the description of chemical events occurring along reaction coordinates at the atomic level. Metal containing zeolites include sites of varied local coordination and secondary confining environments, requiring careful titration protocols to quantify the predominant active sites. Hybrid organometallic-zeolite catalysts are useful well-defined platform materials for spectroscopic, kinetic, and computational studies of heterogeneous catalysis that avoid the complications of conventional metal-containing porous materials. Such materials have been synthesized and studied previously, but catalytic applications were mostly limited to liquid-phase oxidation and electrochemical reactions. The hydrothermal stability, time-on-stream stability, and utility of these materials in gas-phase oxidation reactions are under-studied. The potential applications for single-site heterogeneous catalysts in fundamental research are abundant and motivate future synthetic, spectroscopic, kinetic, and computational studies.

Synthetic and mechanistic study on the conjugate isothiocyanation of enones with trimethylsilyl isothiocyanate.

Alkyl isothiocyanates (R-NCS) have pharmacological applications and provide a synthetic handle to various functional groups including thioureas. There are however few methods to access alkyl isothiocyanates through the creation of the C-N bond. We have developed a simple approach for the conjugate isothiocyanation of enones by trimethylsilyl isothiocyanate (TMSNCS), which proceeds through the 1,4-addition of the weak isothiocyanate nucleophile to activated enones in the absence of external promoters. This method avoids the direct use of highly toxic acids and bases, produces β-isothiocyanato carbonyl products in yields of 87-98% under mild conditions (less than 6 hours at 0 °C), and displays wide functional group tolerance. Density functional theory calculations highlighted competing cationic and anionic mechanisms, where the enone activation by the TMSNCS reagent is accelerated in protic solvents. The selective formation of the isothiocyanate vs. thiocyanate isomers is explained by the thermodynamically-controlled nature of the reaction in which only the conjugate isothiocyanation is exergonic.