Reactive Force Field Development for Propane Dehydrogenation on Platinum Surfaces

Propane dehydrogenation (PDH) is an on-purpose catalytic technology to produce propylene from propane that operates at high temperatures, 773-973 K. Several key industry players have been active in developing new catalysts and processes with improved carbon footprint and economics, where Pt-based catalysts have played a central role. The optimization of these catalytic systems through computational and atomistic simulations requires large-scale models that account for their reactivity and dynamic properties. To address this challenge, we developed a new reactive ReaxFF force field (2023-Pt/C/H) that enables large-scale simulations of PDH reactions catalyzed on Pt surfaces. The optimization of force-field parameters relies on a large training set of density functional theory (DFT) calculations of Pt-catalyzed PDH mechanism, including geometries, adsorption and relative energies of reaction intermediates, and key C-H and C-C bond-breaking/forming reaction steps on the Pt(111) surface. The internal validation supports the accuracy of the developed 2023-Pt/C/H force-field parameters, resulting in mean absolute errors (MAE) against DFT data of 14 and 12 kJ mol-1 for relative energies of intermediates and energy barriers, respectively. We demonstrated the applicability of the 2023-Pt/C/H force field with reactive molecular dynamics simulations of propane on different Pt surface topologies and temperatures. The simulations successfully model the formation of propene in the gas phase as well as competitive, unproductive reactions such as deep dehydrogenation and C-C bond cleavage that produce H, C1 and C2 adsorbed species responsible of catalytic deactivation of Pt surface. Results show the following reactivity order: Pt(111) < Pt(100) < Pt(211), and that for the stepped Pt(211) surface, propane activation occurs on low-coordinated Pt atoms at the steps. The measured selectivity as a function of surface topology follows the same trend as activity, the Pt(211) facet being the most selective. The 2023-Pt/C/H reactive force field can also describe the increase of reactivity with the temperature. From these simulations, we were able to estimate the Arrhenius activation energy, 73 kJ mol-1, whose value is close to those reported experimentally for PDH catalyzed by large, supported Pt nanoparticles . The newly developed 2023-Pt/C/H reactive force field can be used in subsequent investigations of different Pt topologies and of collective effects such as temperature, propane pressure, or H surface coverage.

Foam Generation Through a Single Pore with Rectangular Cross-Section: Hysteretic Behavior and Geometric Limitation of the Volume Fraction of Bubbles

We study foam production and destabilization through a flow-focusing geometry, namely a single pore of rectangular cross-section, by coinjecting gas and liquid at constant pressure, Pg, and constant flow rate, Qw. We observe that bubble production results from a Rayleigh-Plateau destabilization of the internal gas thread that occurs at the pore neck when its width becomes comparable to the height of the rectangular-section channel. Using a simple model and numerical approach, we (i) predict the shape of the gas jet and its stability range as a function of flow parameters and device geometry, which we successfully compare with our experimental results, and (ii) demonstrate the existence of a critical local pressure drop at the pore neck that determines whether or not a stable gas flow can form. We thus show that bubble foam generation exhibits hysteretic behavior due to hydrodynamic feedback and demonstrate that there is a maximum bubble volume fraction that the generated foam cannot exceed, the value of which is fixed by the geometry. Our results suggest that the foam collapse observed in porous media when the fractional gas flow becomes too large may result from hydrodynamic feedback inhibiting foam generation and not necessarily from coalescence between bubbles, as is usually claimed.

Straightforward Assessment of Wettability Changes by Washburn Capillary Rise: Toward a Screening Tool for Selecting Water Compositions for Improved Oil Recovery

Evaluating the wettability state of reservoir rocks is key for understanding and optimizing waterflooding and improved oil recovery techniques that imply the use of low-salinity water. Aside from established petrophysical techniques, such as Amott imbibition tests, we evaluated the Washburn capillary rise method as a low-cost, easy-to-implement, and rapid screening tool for probing the wettability state of rock samples. The well-known limitations of this method are discussed and circumvented. We show that measuring the capillary rise of two liquids -brine and n-octane-is required to assess the evolution of the wettability state of a material induced by various treatments. The wettability state is quantified by the adhesion tension of brine to the solid. The higher the adhesion tension of brine, the more water-wet the sample. An increase in oil-wetness is observed when the sample is contacted with a crude oil or its released waters; an increase in water-wetness is obtained by postcontacting the oil-wet sample with low-salinity brine or surfactant solutions. The Washburn capillary rise is revealed to be a robust method for screening wettability alteration. With a typical duration of 1-10 min, it allows reproducibility check and screening of a wide range of brine compositions in a reasonable time frame. Therefore, it is a relevant tool to identify the most favorable brine compositions to be tested afterward with more time-consuming techniques, such as Amott tests and corefloods.

Reinforcement learning assisted recursive QAOA

In recent years, variational quantum algorithms such as the Quantum Approximation Optimization Algorithm (QAOA) have gained popularity as they provide the hope of using NISQ devices to tackle hard combinatorial optimization problems. It is, however, known that at low depth, certain locality constraints of QAOA limit its performance. To go beyond these limitations, a non-local variant of QAOA, namely recursive QAOA (RQAOA), was proposed to improve the quality of approximate solutions. The RQAOA has been studied comparatively less than QAOA, and it is less understood, for instance, for what family of instances it may fail to provide high-quality solutions. However, as we are tackling NP-hard problems (specifically, the Ising spin model), it is expected that RQAOA does fail, raising the question of designing even better quantum algorithms for combinatorial optimization. In this spirit, we identify and analyze cases where (depth-1) RQAOA fails and, based on this, propose a reinforcement learning enhanced RQAOA variant (RL-RQAOA) that improves upon RQAOA. We show that the performance of RL-RQAOA improves over RQAOA: RL-RQAOA is strictly better on these identified instances where RQAOA underperforms and is similarly performing on instances where RQAOA is near-optimal. Our work exemplifies the potentially beneficial synergy between reinforcement learning and quantum (inspired) optimization in the design of new, even better heuristics for complex problems.

Automated MUltiscale simulation environment

Multiscale techniques integrating detailed atomistic information on materials and reactions to predict the performance of heterogeneous catalytic full-scale reactors have been suggested but lack seamless implementation. The largest challenges in the multiscale modeling of reactors can be grouped into two main categories: catalytic complexity and the difference between time and length scales of chemical and transport phenomena. Here we introduce the Automated MUltiscale Simulation Environment AMUSE, a workflow that starts from Density Functional Theory (DFT) data, automates the analysis of the reaction networks through graph theory, prepares it for microkinetic modeling, and subsequently integrates the results into a standard open-source Computational Fluid Dynamics (CFD) code. We demonstrate the capabilities of AMUSE by applying it to the unimolecular iso-propanol dehydrogenation reaction and then, increasing the complexity, to the pre-commercial Pd/In2O3 catalyst employed for the CO2 hydrogenation to methanol. The results show that AMUSE allows the computational investigation of heterogeneous catalytic reactions in a comprehensive way, providing essential information for catalyst design from the atomistic to the reactor scale level.

Coordination of ε-Caprolactone to a Cationic Niobium(V) Alkoxide Complex: Fundamental Insight into Ring-Opening Polymerization via Coordination-Insertion

We report three niobium-based initiators for the catalytic ring-opening polymerization (ROP) of ε-caprolactone, exhibiting good activity and molecular weight control. In particular, we have prepared on the gram-scale and fully characterized a monometallic cationic alkoxo-Nb(V) ε-caprolactone adduct representing, to the best of our knowledge, an unprecedented example of a metal complex with an intact lactone monomer and a functional ROP-initiating group simultaneously coordinated at the metal center. At 80 °C, all three systems initiate the immortal solution-state ROP of ε-caprolactone via a coordination-insertion mechanism, which has been confirmed through experimental studies, and is supported by computational data. Natural bond orbital calculations further indicate that polymerization may necessitate isomerization about the metal center between the alkoxide chain and the coordinated monomer. The observations made in this work are expected to inform mechanistic understanding both of amine tris(phenolate)-supported metal alkoxide ROP initiators, including various highly stereoselective systems for the polymerization of lactides and of coordination-insertion-type ROP protocols more broadly.

Direct Observation of Ni Nanoparticle Growth in Carbon-Supported Nickel under Carbon Dioxide Hydrogenation Atmosphere

Understanding nanoparticle growth is crucial to increase the lifetime of supported metal catalysts. In this study, we employ in situ gas-phase transmission electron microscopy to visualize the movement and growth of ensembles of tens of nickel nanoparticles supported on carbon for CO2 hydrogenation at atmospheric pressure (H2:CO2 = 4:1) and relevant temperature (450 °C) in real time. We observe two modes of particle movement with an order of magnitude difference in velocity: fast, intermittent movement (vmax = 0.7 nm s-1) and slow, gradual movement (vaverage = 0.05 nm s-1). We visualize the two distinct particle growth mechanisms: diffusion and coalescence, and Ostwald ripening. The diffusion and coalescence mechanism dominates at small interparticle distances, whereas Ostwald ripening is driven by differences in particle size. Strikingly, we demonstrate an interplay between the two mechanisms, where first coalescence takes place, followed by fast Ostwald ripening due to the increased difference in particle size. Our direct visualization of the complex nanoparticle growth mechanisms highlights the relevance of studying nanoparticle growth in supported nanoparticle ensembles under reaction conditions and contributes to the fundamental understanding of the stability in supported metal catalysts.

A Robust Framework for Generating Adsorption Isotherms to Screen Materials for Carbon Capture

To rank the performance of materials for a given carbon capture process, we rely on pure component isotherms from which we predict the mixture isotherms. For screening a large number of materials, we also increasingly rely on isotherms predicted from molecular simulations. In particular, for such screening studies, it is important that the procedures to generate the data are accurate, reliable, and robust. In this work, we develop an efficient and automated workflow for a meticulous sampling of pure component isotherms. The workflow was tested on a set of metal-organic frameworks (MOFs) and proved to be reliable given different guest molecules. We show that the coupling of our workflow with the Clausius-Clapeyron relation saves CPU time, yet enables us to accurately predict pure component isotherms at the temperatures of interest, starting from a reference isotherm at a given temperature. We also show that one can accurately predict the CO₂ and N₂ mixture isotherms using ideal adsorbed solution theory (IAST). In particular, we show that IAST is a more reliable numerical tool to predict binary adsorption uptakes for a range of pressures, temperatures, and compositions, as it does not rely on the fitting of experimental data, which typically needs to be done with analytical models such as dual-site Langmuir (DSL). This makes IAST a more suitable and general technique to bridge the gap between adsorption (raw) data and process modeling. To demonstrate this point, we show that the ranking of materials, for a standard three-step temperature swing adsorption (TSA) process, can be significantly different depending on the thermodynamic method used to predict binary adsorption data. We show that, for the design of processes that capture CO₂ from low concentration (0.4%) streams, the commonly used methodology to predict mixture isotherms incorrectly assigns up to 33% of the materials as top-performing.

An Ecosystem for Digital Reticular Chemistry

The vastness of the materials design space makes it impractical to explore using traditional brute-force methods, particularly in reticular chemistry. However, machine learning has shown promise in expediting and guiding materials design. Despite numerous successful applications of machine learning to reticular materials, progress in the field has stagnated, possibly because digital chemistry is more an art than a science and its limited accessibility to inexperienced researchers. To address this issue, we present mofdscribe, a software ecosystem tailored to novice and seasoned digital chemists that streamlines the ideation, modeling, and publication process. Though optimized for reticular chemistry, our tools are versatile and can be used in nonreticular materials research. We believe that mofdscribe will enable a more reliable, efficient, and comparable field of digital chemistry.

Metal-Support Interactions in Heterogeneous Catalysis: DFT Calculations on the Interaction of Copper Nanoparticles with Magnesium Oxide

Oxide supports play an important role in enhancing the catalytic properties of transition metal nanoparticles in heterogeneous catalysis. How extensively interactions between the oxide support and the nanoparticles impact the electronic structure as well as the surface properties of the nanoparticles is hence of high interest. In this study, the influence of a magnesium oxide support on the properties of copper nanoparticles with different size, shape, and adsorption sites is investigated using density functional theory (DFT) calculations. By proposing simple models to reduce the cost of the calculations while maintaining the accuracy of the results, we show using the nonreducible oxide support MgO as an example that there is no significant influence of the MgO support on the electronic structure of the copper nanoparticles, with the exception of adsorption directly at the Cu-MgO interface. We also propose a simplified methodology that allows us to reduce the cost of the calculations, while the accuracy of the results is maintained. We demonstrate in addition that the Cu nanowire model corresponds well to the nanoparticle model, which reduces the computational cost even further.

Review on Some Confusion Produced by the Bicontinuous Microemulsion Terminology and Its Domains Microcurvature: A Simple Spatiotemporal Model at Optimum Formulation of Surfactant-Oil-Water Systems

Fundamental studies have improved understanding of molecular-level properties and behavior in surfactant-oil-water (SOW) systems at equilibrium and under nonequilibrium conditions. However, confusion persists regarding the terms "microemulsion" and "curvature" in these systems. Microemulsion refers to a single-phase system that does not contain distinct oil or water droplets but at least four different structures with globular domains of nanometer size and sometimes arbitrary shape. The significance of "curvature" in such systems is unclear. At high surfactant concentrations (typically 30 wt % or more), a single phase zone has been identified in which complex molecular arrangements may result in light scattering. As surfactant concentration decreases, the single phase is referred to as a bicontinuous microemulsion, known as the middle phase in a Winsor III triphasic system. Its structure has been described as involving simple or multiple surfactant films surrounding more or less elongated excess oil and water phase globules. In cases where the system separates into two or three phases, known as Winsor I or II systems, one of the phases, containing most of the surfactant, is also confusedly referred to as the microemulsion. In this surfactant-rich phase, the only curved objects are micellar size structures that are soluble in the system and have no real interface but rather exchange surfactant molecules with the external liquid phase at an ultrafast pace. The use of the term "curvature" in the context of these complex microemulsion systems is confusing, particularly when applied to merged nanometer-size globular or percolating domains. In this work, we discuss the terms "microemulsion" and "curvature", and the most simple four-dimensional spatiotemporal model is proposed concerning SOW equilibrated systems near the optimum formulation. This model explains the motion of surfactant molecules due to Brownian movement, which is a quick and arbitrary thermal fluctuation, and limited to a short distance. The resulting observation and behavior will be an average in time and in space, leading to a permanent change in the local microcurvature of the aggregate, thus changing the average from micelle-like to inverse micelle-like order over an extremely short time. The term "microcurvature" is used to explain the small variations of globule size and indicates a close-to-zero mean curvature of the surfactant-containing film surface shape.

Is Carbon Capture and Storage (CCS) Really So Expensive? An Analysis of Cascading Costs and CO2 Emissions Reduction of Industrial CCS Implementation on the Construction of a Bridge

Carbon capture and storage (CCS) is an essential technology to mitigate global CO₂ emissions from power and industry sectors. Despite the increasing recognition of its importance to achieve the net-zero target, current CCS deployment is far behind targeted ambitions. A key reason is that CCS is often perceived as too expensive. The costs of CCS have however traditionally been looked at from the industrial plant perspective, which does not necessarily reflect the end user's one. This paper addresses the incomplete view by investigating the impact of implementing CCS in industrial facilities on the overall costs and CO₂ emissions of end-user products and services. As an example, we examine the extent to which an increase in costs of raw materials (cement and steel) due to CCS impacts the costs of building a bridge. Results show that although CCS significantly increases cement and steel costs, the subsequent increment in the overall bridge construction cost remains marginal (∼1%). This 1% cost increase, however, enables a deep reduction in CO₂ emissions (∼51%) associated with the bridge construction. Although more research is needed in this area, this work is the first step to a better understanding of the real cost and benefits of CCS.

High-Throughput Evaluation of Emission and Structure in Reduced-Dimensional Perovskites

High-throughput experimentation (HTE) seeks to accelerate the exploration of materials space by uniting robotics, combinatorial methods, and parallel processing. HTE is particularly relevant to metal halide perovskites (MHPs), a diverse class of optoelectronic materials with a large chemical space. Here we develop an HTE workflow to synthesize and characterize light-emitting MHP single crystals, allowing us to generate the first reported data set of experimentally derived photoluminescence spectra for low-dimensional MHPs. We leverage the accelerated workflow to optimize the synthesis and emission of a new MHP, methoxy-phenethylammonium lead iodide ((4-MeO-PEAI)₂-PbI₂). We then synthesize 16 000 MHP single crystals and measure their photoluminescence to study the effects of synthesis parameters and compositional engineering on the emission intensity of 54 distinct MHPs: we achieve an acceleration factor of more than 100 times over previously reported HTE MHP synthesis and characterization methods. Using insights derived from this analysis, we screen an existing database for new, potentially emissive MHPs. On the basis of the Tanimoto similarity of the bright available emitters, we present our top candidates for future exploration. As a proof of concept, we use one of these (3,4-difluorophenylmethanamine) to synthesize an MHP which we find has a photoluminescence quantum yield of 10%.

Characterization of Chemisorbed Species and Active Adsorption Sites in Mg-Al Mixed Metal Oxides for High-Temperature CO2 Capture

Mg-Al mixed metal oxides (MMOs), derived from the decomposition of layered double hydroxides (LDHs), have been purposed as adsorbents for CO₂ capture of industrial plant emissions. To aid in the design and optimization of these materials for CO₂ capture at 200 °C, we have used a combination of solid-state nuclear magnetic resonance (ssNMR) and density functional theory (DFT) to characterize the CO₂ gas sorption products and determine the various sorption sites in Mg-Al MMOs. A comparison of the DFT cluster calculations with the observed ¹³C chemical shifts of the chemisorbed products indicates that mono- and bidentate carbonates are formed at the Mg-O sites with adjacent Al substitution of an Mg atom, while the bicarbonates are formed at Mg-OH sites without adjacent Al substitution. Quantitative ¹³C NMR shows an increase in the relative amount of strongly basic sites, where the monodentate carbonate product is formed, with increasing Al/Mg molar ratios in the MMOs. This detailed understanding of the various basic Mg-O sites presented in MMOs and the formation of the carbonate, bidentate carbonate, and bicarbonate chemisorbed species yields new insights into the mechanism of CO₂ adsorption at 200 °C, which can further aid in the design and capture capacity optimization of the materials.

High prevalence of small intestine bacteria overgrowth and asymptomatic carriage of enteric pathogens in stunted children in Antananarivo, Madagascar

Environmental Enteric Dysfunction (EED) refers to an incompletely defined syndrome of inflammation, reduced absorptive capacity, and reduced barrier function in the small intestine. It is widespread among children and adults in low- and middle-income countries and is also associated with poor sanitation and certain gut infections possibly resulting in an abnormal gut microbiota, small intestinal bacterial overgrowth (SIBO) and stunting.

We investigated bacterial pathogen exposure in stunted and non-stunted children in Antananarivo, Madagascar by collecting fecal samples from 464 children (96 severely stunted, 104 moderately stunted and 264 non-stunted) and the prevalence of SIBO in 109 duodenal aspirates from stunted children (61 from severely stunted and 48 from moderately stunted children). SIBO assessed by both aerobic and anaerobic plating techniques was very high: 85.3% when selecting a threshold of ≥10⁵ CFU/ml of bacteria in the upper intestinal aspirates. Moreover, 58.7% of the children showed more than 10⁶ bacteria/ml in these aspirates. The most prevalent cultivated genera recovered were Streptococcus, Neisseria, Staphylococcus, Rothia, Haemophilus, Pantoea and Branhamella. Feces screening by qPCR showed a high prevalence of bacterial enteropathogens, especially those categorized as being enteroinvasive or causing mucosal disruption, such as Shigella spp., enterotoxigenic Escherichia coli, enteropathogenic E. coli and enteroaggregative E. coli. These pathogens were detected at a similar rate in stunted children and controls, all showing no sign of severe diarrhea the day of inclusion but both living in a highly contaminated environment (slum-dwelling). Interestingly Shigella spp. was the most prevalent enteropathogen found in this study (83.3%) without overrepresentation in stunted children.

About 2 million children under the age of 5 suffer from stunted growth in Madagascar. Although deficient diet is the major cause of undernutrition, impaired absorption or assimilation caused by Environmental Enteric dysfunction (EED) has been proposed to play an important role in stunting. EED is widespread among children and adults in low- and middle-income countries (LMIC) and is also associated with undernutrition, poor sanitation, certain gut infections resulting in an abnormal gut microbiota and small intestinal bacterial overgrowth (SIBO) although the role of SIBO in EED remains unclear. The current study highlights the presence at high concentrations of bacterial taxa usually found in the oro-pharyngeal sphere in a high number of duodenal fluids of stunted children. This uncommon presence suggests a decompartmentalization of the gastrointestinal tract and a possible pro-inflammatory effect due to the ectopic presence of some of these bacteria in the duodenum.

The study also points to a high prevalence of enteropathogens (especially Shigella spp.) in the feces of both stunted and control children, hence preventing from proposing a direct association with stunting. This suggests that, beside combatting poverty and improving diet, environmental sanitation, quality of water sources, hygiene promotion and health education are key points to mitigate stunting and restore nutritional benefits.

Diversifying Databases of Metal Organic Frameworks for High-Throughput Computational Screening

By combining metal nodes and organic linkers, an infinite number of metal organic frameworks (MOFs) can be designed in silico. Therefore, when making new databases of such hypothetical MOFs, we need to ensure that they not only contribute toward the growth of the count of structures but also add different chemistries to the existing databases. In this study, we designed a database of ∼20,000 hypothetical MOFs, which are diverse in terms of their chemical design space─metal nodes, organic linkers, functional groups, and pore geometries. Using machine learning techniques, we visualized and quantified the diversity of these structures. We find that on adding the structures of our database, the overall diversity metrics of hypothetical databases improve, especially in terms of the chemistry of metal nodes. We then assessed the usefulness of diverse structures by evaluating their performance, using grand-canonical Monte Carlo simulations, in two important environmental applications─post-combustion carbon capture and hydrogen storage. We find that many of these structures perform better than widely used benchmark materials such as Zeolite-13X (for post-combustion carbon capture) and MOF-5 (for hydrogen storage). All the structures developed in this study, and their properties, are provided on the Materials Cloud to encourage further use of these materials for other applications.

Breaking of Emulsions with Chemical Additives: Using Surrogate Fluids to Develop a Novel Theoretical Framework and Its Application to Water-in-Crude Oil Emulsions

We investigate the role of adding a water-soluble surfactant (Tween 20) that acts as a demulsifier on the stability of water-in-dodecane emulsions stabilized with Span 80. Performing bottle test experiments, we monitor the emulsion separation process. Initially, water droplets sediment fast (∼10 min) until they become closely packed and form the so-called dense packed layer (DPL). The presence of the DPL, a long-lived metastable high-water-fraction (70-90%) emulsion separating bulk oil and water layers, slows down significantly the kinetics (∼10⁵ min) of water separation. Once the DPL is formed, the ratio of the volume of separated water to the total water amount is called as water separation efficiency. We assume that the emulsion stability is reached when the coverage of the emulsifier surfactant exceeds 80% and use the ideal solution approximation. From that, we rationalize the water separation efficiency and the minimum demulsifier concentration required to maximize it, in terms of the mean droplet size, the surfactant concentrations, the total water volume fraction, and the adsorption strength of the water-soluble surfactant. Model predictions and experimental findings are in excellent agreement. We further test the validity and robustness of our theoretical model, by applying it successfully to data found in the literature on water-in-crude oil emulsion systems. Ultimately, our results prove that the efficiency of a demulsifier agent to break a W/O emulsion strongly correlates to its adsorption strength at the W/O interface, providing a novel contribution to the selection guidelines of chemical demulsifiers.

Nanostructure of nickel-promoted indium oxide catalysts drives selectivity in CO2 hydrogenation

Metal promotion in heterogeneous catalysis requires nanoscale-precision architectures to attain maximized and durable benefits. Herein, we unravel the complex interplay between nanostructure and product selectivity of nickel-promoted In2O3 in CO2 hydrogenation to methanol through in-depth characterization, theoretical simulations, and kinetic analyses. Up to 10 wt.% nickel, InNi3 patches are formed on the oxide surface, which cannot activate CO2 but boost methanol production supplying neutral hydrogen species. Since protons and hydrides generated on In2O3 drive methanol synthesis rather than the reverse water-gas shift but radicals foster both reactions, nickel-lean catalysts featuring nanometric alloy layers provide a favorable balance between charged and neutral hydrogen species. For nickel contents >10 wt.%, extended InNi3 structures favor CO production and metallic nickel additionally present produces some methane. This study marks a step ahead towards green methanol synthesis and uncovers chemistry aspects of nickel that shall spark inspiration for other catalytic applications.

Decadal shift in foraging strategy of a migratory southern ocean predator

Rapid anthropogenic environmental change is expected to impact a host of ecological parameters in Southern Ocean ecosystems. Of critical concern are the consequences of these changes on the range of species that show fidelity to migratory destinations, as philopatry is hypothesized to help or hinder adaptation to climate change depending on the circumstances. Many baleen whales show philopatry to feeding grounds and are also capital breeders that meet migratory and reproductive costs through seasonal energy intake. Southern right whales (Eubalaena australis, SRWs) are capital breeders that have a strong relationship between reproductive output and foraging success. The population dynamics of South Africa's population of SRWs are characterized by two distinct periods: the 1990s, a period of high calving rates; and the late 2010s, a period associated with lowered calving rates. Here we use analyses of stable carbon (δ13 C) and nitrogen (δ15 N) isotope values from SRW biopsy samples (n = 122) collected during these two distinct periods to investigate foraging ecology of the South African population of SRWs over a time period coincident with the demographic shift. We show that South African SRWs underwent a dramatic northward shift, and diversification, in foraging strategy from 1990s to 2010s. Bayesian mixing model results suggest that during the 1990s, South African SRWs foraged on prey isotopically similar to South Georgia/Islas Georgias del Sur krill. In contrast, in the 2010s, South African SRWs foraged on prey isotopically consistent with the waters of the Subtropical Convergence, Polar Front and Marion Island. We hypothesize that this shift represents a response to changes in preferred habitat or prey, for example, the decrease in abundance and southward range contraction of Antarctic krill. By linking reproductive decline to changing foraging strategies for the first time in SRWs, we show that altering foraging strategies may not be sufficient to adapt to a changing ocean.

An automated workflow to screen alkene reductases using high-throughput thin layer chromatography

BACKGROUND

Synthetic biology efforts often require high-throughput screening tools for enzyme engineering campaigns. While innovations in chromatographic and mass spectrometry-based techniques provide relevant structural information associated with enzyme activity, these approaches can require cost-intensive instrumentation and technical expertise not broadly available. Moreover, complex workflows and analysis time can significantly impact throughput. To this end, we develop an automated, 96-well screening platform based on thin layer chromatography (TLC) and use it to monitor in vitro activity of a geranylgeranyl reductase isolated from Sulfolobus acidocaldarius (SaGGR).

RESULTS

Unreduced SaGGR products are oxidized to their corresponding epoxide and applied to thin layer silica plates by acoustic printing. These derivatives are chromatographically separated based on the extent of epoxidation and are covalently ligated to a chromophore, allowing detection of enzyme variants with unique product distributions or enhanced reductase activity. Herein, we employ this workflow to examine farnesol reduction using a codon-saturation mutagenesis library at the Leu377 site of SaGGR. We show this TLC-based screen can distinguish between fourfold differences in enzyme activity for select mutants and validated those results by GC-MS.

CONCLUSIONS

With appropriate quantitation methods, this workflow can be used to screen polyprenyl reductase activity and can be readily adapted to analyze broader catalyst libraries whose products are amenable to TLC analysis.

Immunoglobulin recognition of fecal bacteria in stunted and non-stunted children: findings from the Afribiota study

BACKGROUND

Child undernutrition is a global health issue that is associated with poor sanitation and an altered intestinal microbiota. Immunoglobulin (Ig) A mediates host-microbial homeostasis in the intestine, and acutely undernourished children have been shown to have altered IgA recognition of the fecal microbiota. We sought to determine whether chronic undernutrition (stunting) or intestinal inflammation were associated with antibody recognition of the microbiota using two geographically distinct populations from the Afribiota project. Fecal bacteria from 200 children between 2 and 5 years old in Antananarivo, Madagascar, and Bangui, Central African Republic (CAR), were sorted into IgA-positive (IgA+) and IgA-negative (IgA-) populations by flow cytometry and subsequently characterized by 16S rRNA gene sequencing to determine IgA-bacterial targeting. We additionally measured IgG+ fecal bacteria by flow cytometry in a subset of 75 children.

RESULTS

Stunted children (height-for-age z-score ≤ -2) had a greater proportion of IgA+ bacteria in the fecal microbiota compared to non-stunted controls. This trend was consistent in both countries, despite the higher overall IgA-targeting of the microbiota in Madagascar, but lost significance in each country individually. Two of the most highly IgA-recognized bacteria regardless of nutritional status were Campylobacter (in CAR) and Haemophilus (in both countries), both of which were previously shown to be more abundant in stunted children; however, there was no association between IgA-targeting of these bacteria and either stunting or inflammatory markers. IgG-bound intestinal bacteria were rare in both stunted and non-stunted children, similar to levels observed in healthy populations.

CONCLUSIONS

Undernourished children carry a high load of intestinal pathogens and pathobionts. Our data suggest that stunted children have a greater proportion of IgA-recognized fecal bacteria. We moreover identify two putative pathobionts, Haemophilus and Campylobacter, that are broadly targeted by intestinal IgA. This study furthers our understanding of host-microbiota interactions in undernutrition and identifies immune-recognized microbes for future study.

Underwater hyperspectral classification of deep sea corals exposed to 2-methylnaphthalene

Coral reefs around the world are under threat due to anthropogenic impacts on the environment. It is therefore important to develop methods to monitor the status of the reefs and detect changes in the health condition of the corals at an early stage before severe damage occur. In this work, we evaluate underwater hyperspectral imaging as a method to detect changes in health status of both orange and white color morphs of the coral species Lophelia pertusa. Differing health status was achieved by exposing 60 coral samples to the toxic compound 2-methylnaphthalene in concentrations of 0 mg L⁻¹ to 3.5 mg L⁻¹. A machine learning model was utilized to classify corals according to lethal concentration (LC) levels LC5 (5% mortality) and LC25 (25% mortality), solely based on their reflectance spectra. All coral samples were classified to correct concentration group. This is a first step towards developing a remote sensing technique able to assess environmental impact on deep-water coral habitats over larger areas.

Discovery of novel geranylgeranyl reductases and characterization of their substrate promiscuity

BACKGROUND

Geranylgeranyl reductase (GGR) is a flavin-containing redox enzyme that hydrogenates a variety of unactivated polyprenyl substrates, which are further processed mostly for lipid biosynthesis in archaea or chlorophyll biosynthesis in plants. To date, only a few GGR genes have been confirmed to reduce polyprenyl substrates in vitro or in vivo.

RESULTS

In this work, we aimed to expand the confirmed GGR activity space by searching for novel genes that function under amenable conditions for microbial mesophilic growth in conventional hosts such as Escherichia coli or Saccharomyces cerevisiae. 31 putative GGRs were selected to test for potential reductase activity in vitro on farnesyl pyrophosphate, geranylgeranyl pyrophosphate, farnesol (FOH), and geranylgeraniol (GGOH). We report the discovery of several novel GGRs exhibiting significant activity toward various polyprenyl substrates under mild conditions (i.e., pH 7.4, T = 37 °C), including the discovery of a novel bacterial GGR isolated from Streptomyces coelicolor. In addition, we uncover new mechanistic insights within several GGR variants, including GGR-mediated phosphatase activity toward polyprenyl pyrophosphates and the first demonstration of completely hydrogenated GGOH and FOH substrates.

CONCLUSION

These collective results enhance the potential for metabolic engineers to manufacture a variety of isoprenoid-based biofuels, polymers, and chemical feedstocks in common microbial hosts such as E. coli or S. cerevisiae.

Skin microbiome of coral reef fish is highly variable and driven by host phylogeny and diet

BACKGROUND

The surface of marine animals is covered by abundant and diversified microbial communities, which have major roles for the health of their host. While such microbiomes have been deeply examined in marine invertebrates such as corals and sponges, the microbiomes living on marine vertebrates have received less attention. Specifically, the diversity of these microbiomes, their variability among species, and their drivers are still mostly unknown, especially among the fish species living on coral reefs that contribute to key ecosystem services while they are increasingly affected by human activities. Here, we investigated these knowledge gaps analyzing the skin microbiome of 138 fish individuals belonging to 44 coral reef fish species living in the same area.

RESULTS

Prokaryotic communities living on the skin of coral reef fishes are highly diverse, with on average more than 600 OTUs per fish, and differ from planktonic microbes. Skin microbiomes varied between fish individual and species, and interspecific differences were slightly coupled to the phylogenetic affiliation of the host and its ecological traits.

CONCLUSIONS

These results highlight that coral reef biodiversity is greater than previously appreciated, since the high diversity of macro-organisms supports a highly diversified microbial community. This suggest that beyond the loss of coral reefs-associated macroscopic species, anthropic activities on coral reefs could also lead to a loss of still unexplored host-associated microbial diversity, which urgently needs to be assessed.