Browse Articles

Increasing pesticide diversity impairs soil microbial functions

Pesticide application is essential for stabilizing agricultural production. However, the effects of increasing pesticide diversity on soil microbial functions remain unclear, particularly under varying nitrogen (N) fertilizer management practices. In this study, we investigated the stochasticity of soil microbes and multitrophic networks through amplicon sequencing, assessed soil community functions related to carbon (C), N, phosphorus (P), and sulfur (S) cycling, and characterized the dominant bacterial life history strategies via metagenomics along a gradient of increasing pesticide diversity under two N addition levels. Our findings show that higher pesticide diversity enriches the abundance of bacterial specialists and opportunists capable of degrading or resisting pesticides, reducing the proportion of bacterial generalists in the absence of N addition. These shifts can complicate multitrophic microbial networks. Under increased pesticide diversity, selective pressure may drive bacteria to streamline their average genome size to conserve energy while enhancing C, N, P, and S metabolic capacities, thus accelerating soil nutrient loss. In comparison, N addition was found to reduce bacterial niche differentiation at higher pesticide diversity, mitigating the impacts of network complexity and functional traits associated with pesticide diversity, ultimately alleviating soil nutrient loss. Our results reveal the contrasting impacts of pesticide diversity on microbial functions under different N input scenarios and emphasize that strategic N fertilizer management can mitigate the ecological effects of pesticide use in agricultural systems.

Harsh criticism and unreasonable expectations worsen PhD students’ mental health

The role of spin diffusion in endogenous metal ions DNP

The sensitivity of solid state nuclear magnetic resonance spectroscopy can be enhanced via dynamic nuclear polarization (DNP) using unpaired electrons as polarizing agents. In metal ions based (MI)-DNP, paramagnetic metal ions are introduced as dopants into inorganic materials serving as endogenous polarizing agents. Having polarizing agents as part of the structure enables signal enhancements within the bulk of the material. Nuclear spins can be hyperpolarized either directly through their coupling to the polarizing agent or via homonuclear spin diffusion. In this work, we addressed what are the factors determining the relative sizes of the spin pools polarized by each of these two mechanisms and how changing their contribution to the polarization process affects the experimental outcome. Experimentally, we adjusted the spin diffusion rate through modifying the isotope ratio 6Li/7Li in otherwise identical samples, Li4Ti5O12 doped with paramagnetic Fe(III). DNP experiments on samples with typical content of polarizing agents for MI-DNP, corroborated by simulations, evidenced that while the efficiency of spin diffusion has large effects on the polarization buildup times, the enhancements remain largely unaffected.

Daily briefing: Pluto-Charon duet started with a gravitational ‘kiss-and-capture’

Size-dependent phase change in energy storage materials: Comparing the impact of solid-state wetting and of coherency stress

Coherent phase transformations in interstitial solid solutions or intercalation compounds with a miscibility gap are of practical relevance for energy storage materials and specifically for metal hydride or lithium-ion compound nanoparticles. Different conclusions on the size-dependence of the transformation conditions are reached by modeling or theory focusing on the impact of either one (internal, solid-state-) critical-point wetting of the nanoparticle surface or coherency constraints from solute-saturated surface layers. We report a hybrid numerical approach, combining atomistic grand canonical Monte Carlo simulation with a continuum mechanics analysis of coherency stress and modeling simultaneously wetting and mechanical constraints. When the ratio between chemical and misfit-strain-related contributions to the solute-solute interaction energy takes values realistic for interstitial solutions—which are typical for energy storage materials—we find that the impact of solid-state wetting is weak and that of coherency stress is dominant. Specifically, mechanical interaction can act to reduce the phase transformation hysteresis at small system size, and it can make the solid more binding for solute, thereby reducing the “plateau” chemical potential at phase coexistence. We present equations for the impact of coherency stress on the size-dependence of upper consolute temperature, plateau chemical potential, and charging/discharging hysteresis.

Phase transitions in chromatin: Mesoscopic and mean-field approaches

By means of a minimal physical model, we investigate the interplay of two phase transitions at play in chromatin organization: (1) liquid–liquid phase separation within the fluid solvating chromatin, resulting in the formation of biocondensates; and (2) the coil–globule crossover of the chromatin fiber, which drives the condensation or extension of the chain. In our model, a species representing a domain of chromatin is embedded in a binary fluid. This fluid phase separates to form a droplet rich in a macromolecule (B). Chromatin particles are trapped in a harmonic potential to reproduce the coil and globular phases of an isolated polymer chain. We investigate the role of the droplet material B on the radius of gyration of this polymer and find that this radius varies nonmonotonically with respect to the volume fraction of B. This behavior is reminiscent of a phenomenon known as co-non-solvency: a polymer chain in a good solvent (S) may collapse when a second good solvent (here B) is added in low quantity and expands at higher B concentration. In addition, the presence of finite-size effects on the coil–globule transition results in a qualitatively different impact of the droplet material on polymers of various sizes. In the context of genetic regulation, our results suggest that the size of chromatin domains and the quantity of condensate proteins are key parameters to control whether chromatin may respond to an increase in the quantity of chromatin-binding proteins by condensing or expanding.

A signaling molecule from intratumor bacteria promotes trastuzumab resistance in breast cancer cells

Emerging evidence indicates that intratumor bacteria exist as an active and specific tumor component in many tumor types beyond digestive and respiratory tumors. However, the biological impact and responsible molecules of such local bacteria–tumor direct interaction on cancer therapeutic response remain poorly understood. Trastuzumab is among the most commonly used drugs targeting the receptor tyrosine-protein kinase erbB-2 (ErbB2) in breast cancer, but its resistance is inevitable, severely limiting its clinical effectiveness. Here, we demonstrate that the quorum-sensing signaling molecule N-(3-oxo-dodecanoyl) homoserine lactone (3oc), a chemical compound released by Pseudomonas aeruginosa ( P. aeruginosa ), one tumor-resident bacteria with a relative high abundance in breast cancer, promotes breast cancer cell resistance to trastuzumab. Mechanically, 3oc directly leads to spontaneous dimerization of the transforming growth factor β (TGF-β) type II serine/threonine kinase receptor on the cell membrane in a ligand-independent manner. The 3oc-induced TGF-β signaling subsequently triggers ErbB2 phosphorylation and its downstream target activation, overcoming the inhibition effect of trastuzumab on ErbB2. With specific real-time qPCR, fluorescence in situ hybridization imaging, and liquid chromatography ionization tandem mass spectrometry analyses of clinical samples, we confirmed that P. aeruginosa and its signaling molecule 3oc exist in breast cancer tissues and there is a clinical correlation between P. aeruginosa colonization and trastuzumab resistance. This work expands the biological functions of intratumor bacteria in cancer treatment responsiveness and provides a unique perspective for overcoming trastuzumab resistance.

Analytical derivative approaches for vibro-polaritonic structures and properties. I. Formalism and implementation

Vibro-polaritons are hybrid light–matter states that arise from the strong coupling between the molecular vibrational transitions and the photons in an optical cavity. Developing theoretical and computational methods to describe and predict the unique properties of vibro-polaritons is of great significance for guiding the design of new materials and experiments. Here, we present the ab initio cavity Born–Oppenheimer density functional theory (CBO-DFT) and formulate the analytic energy gradient and Hessian as well as the nuclear and photonic derivatives of dipole and polarizability within the framework of CBO-DFT to efficiently calculate the harmonic vibrational frequencies, infrared absorption, and Raman scattering spectra of vibro-polaritons as well as to explore the critical points on the cavity potential energy surface. The implementation of analytic derivatives into the electronic structure package is validated by a comparison with the finite-difference method and with other reported computational results. By adopting appropriate exchange–correlation functionals, CBO-DFT can better describe the structure and properties of molecules in the cavity than CBO-Hartree–Fock method. It is expected that CBO-DFT is a useful tool for studying the polaritonic structures and properties.

Partial PdAu nanoparticle embedding into TiO ₂ support accentuates catalytic contributions from the Au/TiO ₂ interface

Despite the broad catalytic relevance of metal–support interfaces, controlling their chemical nature, the interfacial contact perimeter (exposed to reactants), and consequently, their contributions to overall catalytic reactivity, remains challenging, as the nanoparticle and support characteristics are interdependent when catalysts are prepared by impregnation. Here, we decoupled both characteristics by using a raspberry-colloid-templating strategy that yields partially embedded PdAu nanoparticles within well-defined SiO 2 or TiO 2 supports, thereby increasing the metal–support interfacial contact compared to nonembedded catalysts that we prepared by attaching the same nanoparticles onto support surfaces. Between nonembedded PdAu/SiO 2 and PdAu/TiO 2 , we identified a support effect resulting in a 1.4-fold higher activity of PdAu/TiO 2 than PdAu/SiO 2 for benzaldehyde hydrogenation. Notably, partial nanoparticle embedding in the TiO 2 raspberry-colloid-templated support increased the metal–support interfacial perimeter and consequently, the number of Au/TiO 2 interfacial sites by 5.4-fold, which further enhanced the activity of PdAu/TiO 2 by an additional 4.1-fold. Theoretical calculations and in situ surface-sensitive desorption analyses reveal facile benzaldehyde binding at the Au/TiO 2 interface and at Pd ensembles on the nanoparticle surface, explaining the connection between the number of Au/TiO 2 interfacial sites (via the metal–support interfacial perimeter) and catalytic activity. Our results demonstrate partial nanoparticle embedding as a synthetic strategy to produce thermocatalytically stable catalysts and increase the number of catalytically active Au/TiO 2 interfacial sites to augment catalytic contributions arising from metal–support interfaces.

The bcc coating of Lennard-Jones crystal nuclei vanishes with a change of local structure detection algorithm

Since the influential work of ten Wolde, Ruiz-Montero, and Frenkel [Phys. Rev. Lett. 75, 2714 (1995)], crystal nucleation from a Lennard-Jones fluid has been regarded as a paradigmatic example of metastable crystal ordering at the surface of a critical nucleus. We apply seven commonly used local structure detection algorithms to characterize crystal nuclei obtained from transition path sampling simulations. The polymorph composition of these nuclei varies significantly depending on the algorithm used. Our results indicate that one should be very careful when characterizing the local structure near solid–solid and solid–fluid interfaces. Particles near such interfaces exhibit a local structure distinct from that of bulk fluid or bulk crystal phases. We argue that incorporating outlier detection into the local structure detection method is beneficial, leading to greater confidence in the classification results. Interestingly, the bcc coating nearly disappears when adopting a machine learning method with outlier detection.

The scientific reason to cook with simmering rather than vigorously boiling water

Nanoscale self-assembly and water retention properties of silk fibroin–riboflavin hydrogel

Silk-fibroin hydrogels have gained considerable attention in recent years for their versatile biomedical applications. The physical properties of a complex hydrogel, comprising silk fibroin and riboflavin, surpass those of the silk fibroin-hydrogel without additives. This study investigates silk fibroin–riboflavin (silk–RIB) hydrogel at the atomistic level to uncover molecular structures and chemical characteristics specific to silk fibroin and riboflavin molecules in an aqueous medium. The interplay between hydrophilic riboflavin and hydrophobic silk fibroin polymers facilitates the formation of solubilized silk fiber, which subsequently evolves into a nano-scale hydrogel over time. Eventually, the interlinked RIB stacks form a scaffold that not only accommodates silk fibroin aggregates but also encloses water pockets, preserving the moisture level and enhancing the thermal conductivity of the hydrogel. To explore water retention properties and the role of ions, two sets of simulations of semi-hydrated hydrogel in the presence and absence of ions are conducted. The presence of ions significantly influences the dynamics of RIB and silk fibroin. Favorable interactions with the ions impede the unrestricted diffusion of these larger molecules, potentially leading to a stable structure capable of retaining water for a prolonged duration. The complete removal of water results in further shrinkage of the anhydrous silk–RIB hydrogel or xerogel (XG), yet its porosity and structural integrity remain intact. These findings offer valuable insights into the behavior of silk fibroin hydrogel and XG, paving the way for materials engineering in aqueous environments to develop biomedical devices with customized functional properties.

CryoEM structure of an MHC-I/TAPBPR peptide-bound intermediate reveals the mechanism of antigen proofreading

Class I major histocompatibility complex (MHC-I) proteins play a pivotal role in adaptive immunity by displaying epitopic peptides to CD8+ T cells. The chaperones tapasin and TAPBPR promote the selection of immunogenic antigens from a large pool of intracellular peptides. Interactions of chaperoned MHC-I molecules with incoming peptides are transient in nature, and as a result, the precise antigen proofreading mechanism remains elusive. Here, we leverage a high-fidelity TAPBPR variant and conformationally stabilized MHC-I, to determine the solution structure of the human antigen editing complex bound to a peptide decoy by cryogenic electron microscopy (cryo-EM) at an average resolution of 3.0 Å. Antigen proofreading is mediated by transient interactions formed between the nascent peptide binding groove with the P2/P3 peptide anchors, where conserved MHC-I residues stabilize incoming peptides through backbone-focused contacts. Finally, using our high-fidelity chaperone, we demonstrate robust peptide exchange on the cell surface across multiple clinically relevant human MHC-I allomorphs. Our work has important ramifications for understanding the selection of immunogenic epitopes for T cell screening and vaccine design applications.

Open-boundary molecular dynamics of ultrasound using supramolecular water models

Ultrasound can be used to manipulate protein function and activity, as well as for targeted drug delivery, making it a powerful diagnostic and therapeutic modality with wide applications in sonochemistry, nanotechnology, and engineering. However, a general particle-based approach to ultrasound modeling remains challenging due to the significant disparity between characteristic time scales governing ultrasound propagation. In this study, we use open-boundary molecular dynamics to simulate ultrasound waves in liquid water under ambient conditions by employing supramolecular water models, i.e., the Martini 3, dissipative particle dynamics, and many-body dissipative particle dynamics models. We demonstrate that our approach successfully reproduces the solution of the traveling wave equation and captures the velocity dispersion characteristic of high-frequency ultrasound waves.

Nonapoptotic role of EGL-1 in exopher production and neuronal health in <i>Caenorhabditis elegans</i>

While traditionally studied for their proapoptotic functions in activating the caspase, research suggests BH3-only proteins also have other roles such as mitochondrial dynamics regulation. Here, we find that EGL-1, the BH3-only protein in Caenorhabditis elegans , promotes the cell-autonomous production of exophers in adult neurons. Exophers are large, micron-scale vesicles that are ejected from the cell and contain cellular components such as mitochondria. EGL-1 facilitates exopher production potentially through regulation of mitochondrial dynamics. Moreover, an endogenous, low level of EGL-1 expression appears to benefit dendritic health. Our findings provide insights into the role of neuronal BH3-only protein in mitochondrial dynamics, downstream exopher production, and ultimately neuronal health.

Retractions caused by honest mistakes are extremely stressful, say researchers

Multidimensional quantum dynamics with explicitly correlated Gaussian wave packets using Rothe’s method

In a previous publication [S. E. Schrader et al., J. Chem. Phys. 161, 044105 (2024)], it has been shown that Rothe’s method can be used to solve the time-dependent Schrödinger equation for the hydrogen atom in a strong laser field using time-dependent Gaussian wave packets. Here, we generalize these results, showing that Rothe’s method can propagate arbitrary numbers of thawed, complex-valued, Explicitly Correlated Gaussian (ECGs) functions with dense correlation matrices for systems with varying dimensionality. We consider the multidimensional Hénon–Heiles potential and show that the dynamics can be quantitatively reproduced using only 30 Gaussians in 2D and that accurate spectra can be obtained using 20 Gaussians in 2D and 30–40 Gaussians in 3D and 4D. Therefore, the relevant multidimensional dynamics can be described at high quality using only a small number of ECGs that give a very compact representation of the wave function. This efficient representation, along with the demonstrated ability of Rothe’s method to propagate Gaussian wave packets in strong fields and ECGs in complex potentials, paves the way for accurate molecular dynamics calculations beyond the Born–Oppenheimer approximation in strong fields.

AI-powered contract automation helps research managers level up

Toward mitigating the impact of non-bulk defects on describing water structure in salt aqueous solutions: Characterizing solution density with a network-based structural indicator

Structural indicators, also known as structural descriptors, including order parameters, have been proposed to quantify the structural properties of water to account for its anomalous behaviors. However, these indicators, mainly designed for bulk water, are not naturally transferrable to the vicinity of ions due to disruptions in the immediate neighboring space and a resulting loss of feature completeness. To address these non-bulk defects, we introduced a structural indicator that draws on the concept of clique number from graph theory and the criterion in agglomerative clustering, denoted as the average cluster number. This structural indicator aims to discern intrinsic structural characteristics within the water molecules regardless of the ions occupying the neighboring space, without requiring additional corrections. From molecular dynamics simulation results for neat water and salt aqueous solutions utilizing the TIP4P/2005 water model and the Madrid-2019 force field, we characterized the variations in densities with temperature using this network-based indicator, thereby demonstrating its practical utility. The findings suggest that at lower temperatures, the addition of ions disrupts the intrinsic structure of water molecules, with this effect diminishing as the temperature rises. Cations with larger charge density tend to induce stronger disruptions. This study highlights the importance of mitigating the impact of non-bulk defects before applying the indicators to analyze water’s intrinsic structural properties in solutions. By doing so, the relationship between changes in water structure and solution behaviors can be more accurately assessed.

Multiplicity of type 6 secretion system toxins limits the evolution of resistance

The bacterial type 6 secretion system (T6SS) is a toxin-injecting nanoweapon that mediates competition in plant- and animal-associated microbial communities. Bacteria can evolve de novo resistance against T6SS attacks, but resistance is far from universal in natural communities, suggesting key features of T6SS weaponry may act to limit its evolution. Here, we combine ecoevolutionary modeling and experimental evolution to examine how toxin type and multiplicity in Acinetobacter baylyi attackers shape resistance evolution in susceptible Escherichia coli competitors. In both our models and experiments, we find that combinations of multiple distinct toxins limit resistance evolution by creating genetic bottlenecks, driving resistant lineages extinct before they can reach high frequency. We also show that, paradoxically, single-toxin attackers can drive the evolution of cross-resistance, protecting bacteria against unfamiliar toxin combinations, even though such evolutionary pathways were inaccessible against multitoxin attackers. Our findings indicate that, comparable to antimicrobial and anticancer combination therapies, multitoxin T6SS arsenals function to limit resistance evolution in competing microbes. This helps us to understand why T6SSs remain widespread and effective weapons in microbial communities, and why many T6SS-armed bacteria encode functionally diverse anticompetitor toxins.