Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “affinity”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Coordination Chemistry and Stoichiometry of Extracted Diglycolamide Complexes of Lanthanides in Extraction Chromatography Materials

Industrial rare earth element (REE) separations predominantly utilize solvent extraction processes tailored toward conventional resources such as bastnäsite, monazite, and ion adsorption clays. Advances in diglycolamide (DGA) chemistry have shown effective extraction characteristics for REE separations. However, limitations associated with traditional DGA solvent extraction techniques, such as third-phase formation and gelling, have hindered commercial viability. By supporting DGA extractants on porous resins such as polystyrene divinyl benzene (PS-DVB), the desirable combination of solvent extraction selectivity and ease of operation of sorbent columns can be achieved. To design a low-cost model for such solid-supported DGAs, extraction characteristics as influenced by the underlying coordination chemistry must be explored to achieve efficient functional systems. Within this study, we report novel DGA resin materials, each incorporating one of the DGAs N,N,N’,N’-tetra-(1-octyl)-3-oxapentane-1,5-diamide (TODGA), N,N'-dimethyl-N,N'-dioctyl-3-oxapentane-1,5-diamide (DMDODGA), and 2,2'-oxybis(1-(3-(((2-ethylhexyl)thio)methyl)-4-methylpyrrolidin-1-yl)ethan-1-one) (DEHPDGA). The affinity of DGAs across the lanthanide (Ln) series was evaluated for both hydrochloric acid and nitric acid media with varying Ln feed concentrations to study distribution ratios and loading characteristics. Focusing on dysprosium, extended X-Ray Absorption Fine Structure (EXAFS) and density functional theory (DFT) calculations were also utilized to explore coordination chemistry and their effects on ligand performance. The general trend for both acid media resulted in DMDODGA having the highest extraction strength of all three DGAs at varying acid concentrations. Coordination-chemistry analysis supported by loading data, DFT calculations, and EXAFS results under forced loading conditions posited less than the expected 3:1 ligand-to-metal coordination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The evolution of analytical techniques for multiplex analysis of protein biomarkers

Introduction: The landscape of biomarker development has evolved with advanced analytical technologies, particularly affinity- and mass spectrometry-based techniques. These advancements have deepened our understanding of disease mechanisms, enabling the development of precise diagnostic tools and personalized medicine. Protein biomarkers, which play pivotal roles in biological processes, have become invaluable in diagnosing and monitoring diseases, aided by their presence in various biological samples and the availability of established detection methods. Areas covered: This review covers the role of protein biomarkers in clinical practice, the development and dimensionality of protein biomarkers, advancements in detection technologies, a comparison of these technologies, and future directions in biomarker discovery and disease mechanism elucidation. Expert opinion: Advances in biomarker technologies have the potential to transform diagnostics and personalized treatment but face challenges such as high costs and technical complexity. Enhancing reproducibility and integrating multi-omics approaches may offer better insights. In conclusion, the field should evolve toward high-throughput, automated methods, continuously adapting research, and clinical practices.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Iterative self-organizing SCEne-LEvel sampling (ISOSCELES) for large-scale building extraction

Convolutional neural networks (CNN) provide state-of-the-art performance in many computer vision tasks, including those related to remote-sensing image analysis. Successfully training a CNN to generalize well to unseen data, however, requires training on samples that represent the full distribution of variation of both the target classes and their surrounding contexts. With remote sensing data, acquiring a sufficiently representative training set is a challenge due to both the inherent multi-modal variability of satellite or aerial imagery and the general high cost of labeling data. To address this challenge, we have developed ISOSCELES, an Iterative Self-Organizing SCEne LEvel Sampling method for hierarchical sampling of large image sets. Using affinity propagation, ISOSCELES automates the selection of highly representative training images. Compared to random sampling or using available reference data, the distribution of the training is principally data driven, reducing the chance of oversampling uninformative areas or undersampling informative ones. In comparison to manual sample selection by an analyst, ISOSCELES exploits descriptive features, spectral and/or textural, and eliminates human bias in sample selection. Using a hierarchical sampling approach, ISOSCELES can obtain a training set that reflects both between-scene variability, such as in viewing angle and time of day, and within-scene variability at the level of individual training samples. We verify the method by demonstrating its superiority to stratified random sampling in the challenging task of adapting a pre-trained model to a new image and spatial domain for country-scale building extraction. Using a pair of hand-labeled training sets comprising 1,987 sample image chips, a total of 496,000,000 individually labeled pixels, we show, across three distinct model architectures, an increase in accuracy, as measured by F1-score, of 2.2–4.2%.

42 ENGINEERING↗
DOE OSTI2020

Discovery and characterization of a neutralizing pan-ELR+CXC chemokine monoclonal antibody

CXCR1 and CXCR2 signaling play a critical role in neutrophil migration, angiogenesis, and tumorigenesis and are therefore an attractive signaling axis to target in a variety of indications. In human, a total of seven chemokines signal through these receptors and comprise the ELR + CXC chemokine family, so named because of the conserved ELRCXC N-terminal motif. To fully antagonize CXCR1 and CXCR2 signaling, an effective therapeutic should block either both receptors or all seven ligands, yet neither approach has been fully realized clinically. In this work, we describe the generation and characterization of LY3041658, a humanized monoclonal antibody that binds and neutralizes all seven human and cynomolgus monkey ELR + CXC chemokines and three of five mouse and rat ELR+CXC chemokines with high affinity. LY3041658 is able to block ELR + CXC chemokine-induced Ca 2+ mobilization, CXCR2 internalization, and chemotaxis in vitro as well as neutrophil mobilization in vivo without affecting other neutrophil functions. In addition to the in vitro and in vivo activity, we characterized the epitope and structural basis for binding in detail through alanine scanning, crystallography, and mutagenesis. Together, these data provide a robust preclinical characterization of LY3041658 for which the efficacy and safety is being evaluated in human clinical trials for neutrophilic skin diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Molecular recognition requires dimerization of a VHH antibody

Camelid heavy-chain-only antibodies are a unique class of antibody that possesses only a single variable domain (termed VHH) for antigen recognition. Despite their apparent canonical mechanism of target recognition, where a single VHH domain binds a single target, an anti-caffeine VHH has been observed to possess 2:1 stoichiometry. Here, the structure of the anti-caffeine VHH/caffeine complex enabled the generation and biophysical analysis of variants that were used to better understand the role of VHH homodimerization in caffeine recognition. VHH interface mutants and caffeine analogs, which were examined to probe the mechanism of caffeine binding, suggested caffeine recognition is only possible with the VHH dimer species. Correspondingly, in the absence of caffeine, the anti-caffeine VHH was found to form a dimer with a dimerization constant comparable to that observed with VH:VL domains in conventional antibody systems, which was most stable near physiological temperature. While the VHH:VHH dimer structure (at 1.13 Å resolution) is reminiscent of conventional VH:VL heterodimers, the homodimeric VHH possesses a smaller angle of domain interaction, as well as a larger amount of apolar surface area burial. To test the general hypothesis that the short complementarity-determining region-3 (CDR3) may help drive VHH:VHH homodimerization, an anti-picloram VHH domain containing a short CDR3 was generated and characterized, which revealed it also existed as dimer species in solution. These results suggest homodimer-driven recognition may represent a more common method of VHH ligand recognition, opening opportunities for novel VHH homodimer affinity reagents and helping to guide their use in chemically induced dimerization applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Variable domain mutational analysis to probe the molecular mechanisms of high viscosity of an IgG 1 antibody

Subcutaneous injection is the preferred route of administration for many antibody therapeutics for reasons that include its speed and convenience. However, the small volume limit (typically ≤2 mL) for subcutaneous delivery often necessitates antibody formulations at high concentrations (commonly ≥100 mg/mL), which may lead to physicochemical problems. For example, antibodies with large hydrophobic or charged patches can be prone to self-interaction giving rise to high viscosity. Here, we combined X-ray crystallography with computational modeling to predict regions of an anti-glucagon receptor (GCGR) IgG 1 antibody prone to self-interaction. An extensive mutational analysis was undertaken of the complementarity-determining region residues residing in hydrophobic surface patches predicted by spatial aggregation propensity, in conjunction with residue-level solvent accessibility, averaged over conformational ensembles from molecular dynamics simulations. Dynamic light scattering (DLS) was used as a medium throughput screen for self-interaction of ~200 anti-GCGR IgG 1 variants. A negative correlation was found between the viscosity determined at high concentration (180 mg/mL) and the DLS interaction parameter measured at low concentration (2–10 mg/mL). Additionally, anti-GCGR variants were readily identified with reduced viscosity and antigen-binding affinity within a few fold of the parent antibody, with no identified impact on overall developability. The methods described here may be useful in the optimization of other antibodies to facilitate their therapeutic administration at high concentration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A newly characterized malaria antigen on erythrocyte and merozoite surfaces induces parasite inhibitory antibodies

We previously identified a Plasmodium falciparum (Pf) protein of unknown function encoded by a single-copy gene, PF3D7_1134300, as a target of antibodies in plasma of Tanzanian children in a whole-proteome differential screen. Here we characterize this protein as a blood-stage antigen that localizes to the surface membranes of both parasitized erythrocytes and merozoites, hence its designation as Pf erythrocyte membrane and merozoite antigen 1 (PfEMMA1). Mouse anti-PfEMMA1 antisera and affinity-purified human anti-PfEMMA1 antibodies inhibited growth of P. falciparum strains by up to 68% in growth inhibition assays. Following challenge with uniformly fatal Plasmodium berghei (Pb) ANKA, up to 40% of mice immunized with recombinant PbEMMA1 self-cured, and median survival of lethally infected mice was up to 2.6-fold longer than controls (21 vs. 8 d, P = 0.005). Furthermore, high levels of naturally acquired human anti-PfEMMA1 antibodies were associated with a 46% decrease in parasitemia over 2.5 yr of follow-up of Tanzanian children. Together, these findings suggest that antibodies to PfEMMA1 mediate protection against malaria.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Engineering of a synthetic antibody fragment for structural and functional studies of K+ channels

Engineered antibody fragments (Fabs) have made major impacts on structural biology research, particularly to aid structural determination of membrane proteins. Nonetheless, Fabs generated by traditional monoclonal technology suffer from challenges of routine production and storage. Starting from the known IgG paratopes of an antibody that binds to the “turret loop” of the KcsA K+ channel, we engineered a synthetic Fab (sFab) based upon the highly stable Herceptin Fab scaffold, which can be recombinantly expressed in Escherichia coli and purified with single-step affinity chromatography. This synthetic Fab was used as a crystallization chaperone to obtain crystals of the KcsA channel that diffracted to a resolution comparable to that from the parent Fab. Furthermore, we show that the turret loop can be grafted into the unrelated voltage-gated Kv1.2–Kv2.1 channel and still strongly bind the engineered sFab, in support of the loop grafting strategy. Macroscopic electrophysiology recordings show that the sFab affects the activation and conductance of the chimeric voltage-gated channel. These results suggest that straightforward engineering of antibodies using recombinant formats can facilitate the rapid and scalable production of Fabs as structural biology tools and functional probes. The impact of this approach is expanded significantly based on the potential portability of the turret loop to a myriad of other K+ channels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Probing adsorbates on La1-xSrxNiO3-d surfaces under humid conditions: implications for the oxygen evolution reaction

Earth-abundant nickel-containing perovskite oxides (ANiO3) are highly active materials for the oxygen evolution reaction (OER). The strong nickel-oxygen (Ni-O) covalency, tunable by A-site chemical substitution, contributes to both bulk and surface material properties like the formation of oxygen vacancies (????••) and OER activity. Here we quantify the coverage of OER relevant adsorbates on a series of La1-xSrxNiO3-d (LSNO, 0 = x = 0.5) epitaxial thin films exposed to humid environments by ambient pressure X-ray photoelectron spectroscopy (AP-XPS). While all LSNO film compositions investigated here have comparable hydroxide coverages at the relative humidities (RHs) probed (1.5 x 10-5 – 0.2 %RH), the amount of under-coordinated surface oxygen increases notably with Sr content. We interpret differences in the free energy of adsorption (?Gads,i) of these OER intermediates, inferred from adsorption isotherms, in the context of proposed ????••-mediated OER mechanisms, consistent with the pH-dependent OER activity observed here for LSNO. We find that Sr incorporation enhances the affinity of LSNO surfaces for these under-coordinated oxygen species, in line with calculations in the literature.

Rare-earth nickelates, ambient pressure-X-ray phot↗
DOE OSTI2022

Tetrahedral W 4 cluster confined in graphene-like C 2 N enables electrocatalytic nitrogen reduction from theoretical perspective

Abstract Exploring the format of active site is essential to further the understanding of an electrocatalyst working under ambient conditions. Herein, we present a DFT study of electrocatalytic nitrogen reduction (eNRR) on W 4 tetrahedron embedded in graphene-like C 2 N (denoted as W 4 @C 2 N). Our results demonstrate that N-affinity of active sites on W 4 dominate over single-atom site, rendering *NH 2 + (H + + e - ) →*NH 3 invariably the potential-determining step (PDS) of eNRR via consecutive or distal route ( U L = -0.68 V) to ammonia formation. However, *NHNH 2 + (H + + e - ) →*NH 2 NH 2 has become the PDS ( U L = -0.54 V) via enzymatic route towards NH 2 NH 2 formation and thereafter desorption, making W 4 @C 2 N a potentially promising catalyst for hydrazine production from eNRR. Furthermore, eNRR is competitive with hydrogen evolution reaction ( U L = -0.78 V) on W 4 @C 2 N, which demonstrated sufficient thermal stability and electric property for electrode application.

Materials Science↗
DOE OSTI2023

Surface stability and H adsorption and diffusion near surfaces of W borides: a first-principles study

Abstract Understanding the behavior of tungsten boride (W x B y ) surfaces in a fusion reactor environment is an important topic since boronization is a common wall conditioning method used in fusion Tokamaks. We report the results of density functional theory calculations that investigate the surface stability of W x B y (tetragonal I4 1 /amd -WB, hexagonal P 6 3 / mmc -WB 2 and tetragonal I4/m- W 2 B) with low-index orientations, as well as hydrogen (H) energetics near W x B y surfaces. For single element terminated W x B y surfaces, B terminated surfaces are more energetically stable than W terminated as a result of significant reconstruction of B. The H surface adsorption energy and activation energy of H diffusion penetration below W x B y surfaces are mainly related to the outer termination. Specifically, the WB(001) surface terminated with two B layers, referred to as WB(001)-T BB , has higher H adsorption affinity and lower H diffusivity on this surface than other terminations, which is controlled by the significant charge transfer from B to H. However, B atoms on the WB 2 (0001)-T BB surface decrease both H adsorption and diffusivity on the surface, but enhance H diffusion below the surface in comparison to W terminated WB 2 (0001) surface. H would be trapped and diffuse within atomic surface gaps on the WB 2 ( 2 1 ˉ 1 ˉ 0 ) surface, while H below the surface layer would jump along the [0001] direction rather than diffuse into bulk. The surface diffusion activation energy of H on the W 2 B(001) surface slightly varies with terminations. Once H crosses the surface layer of W 2 B(001) with either termination, it prefers to diffuse into the bulk, or back towards the surface, rather than move parallel to the surface. Interestingly, WB 2 (0001) and WB 2 ( 2 1 ˉ 1 ˉ 0 ) surfaces will have relatively higher H retention than the other W x B y surfaces evaluated in this work.

Yang, L. (ORCID:0000000322166071)↗
DOE OSTI2023

Energetics of silicon in the bulk and near surfaces of tungsten: a first-principles study

Abstract Siliconization of the tokamak walls is a candidate method to improve plasma confinement in fusion tokamaks containing tungsten plasma facing components (W PFCs). To understand the interactions of silicon (Si) with W, the Si behavior in bulk W, and near three low-index W surfaces ((100), (110) and (111)) has been investigated using first-principles density functional theory. In bulk W, Si interstitial atoms have a low solution ability and high mobility, and Si atoms can be strongly trapped by W vacancies. The interaction between two Si adatoms is responsible for the stability of adatom superstructures on W surfaces, consistent with previous experimental observation (Tsong and Casanova 1981 Phys. Rev. Lett. 47 113). Although the coverage dependence of Si adsorption and diffusion energetics on surfaces is related to surface orientation, the W(110) surface has lower Si adsorption affinity and higher Si diffusivity than either the W(111) or W(100) surfaces. The most stable Si adatom superstructure on W surfaces is: square c(2 × 2) pattern on W(100) covered with 0.5 ML Si; rectangular c(4 × 2) pattern on W(110) with 0.25 ML Si; and rhombus p(1 × 1) pattern on W(111) with 1 ML Si. The coverage dependence of Si mobility on/toward W surfaces is generally related to the stability of the Si superstructures as a function of coverage on each surface. Interestingly, Si adatoms prefer to transport below the surface and into W subsurface by an exchange mechanism with W atoms, indicating the likelihood of epitaxial growth of W silicide layers on W surfaces during the operation of W PFCs.

Yang, L. (ORCID:0000000322166071)↗
DOE OSTI2020

Multisite EGFR phosphorylation is regulated by adaptor protein abundances and dimer lifetimes

Differential epidermal growth factor receptor (EGFR) phosphorylation is thought to couple receptor activation to distinct signaling pathways. However, the molecular mechanisms responsible for biased signaling are unresolved due to a lack of insight into the phosphorylation patterns of full-length EGFR. We extended a single-molecule pull-down technique previously used to study protein–protein interactions to allow for robust measurement of receptor phosphorylation. We found that EGFR is predominantly phosphorylated at multiple sites, yet phosphorylation at specific tyrosines is variable and only a subset of receptors share phosphorylation at the same site, even with saturating ligand concentrations. We found distinct populations of receptors as soon as 1 min after ligand stimulation, indicating early diversification of function. To understand this heterogeneity, we developed a mathematical model. The model predicted that variations in phosphorylation are dependent on the abundances of signaling partners, while phosphorylation levels are dependent on dimer lifetimes. The predictions were confirmed in studies of cell lines with different expression levels of signaling partners, and in experiments comparing low- and high-affinity ligands and oncogenic EGFR mutants. These results reveal how ligand-regulated receptor dimerization dynamics and adaptor protein concentrations play critical roles in EGFR signaling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Three founding ancestral genomes involved in the origin of sugarcane

Modern sugarcane cultivars (Saccharum spp.) are high polyploids, aneuploids (2n = ~12 = ~120) derived from interspecific hybridizations between the domesticated sweet species Saccharum officinarum and the wild species S. spontaneum. To analyse the architecture and origin of such a complex genome, we analysed the sequences of all 12 hom(oe)ologous haplotypes (BAC clones) from two distinct genomic regions of a typical modern cultivar, as well as the corresponding sequence in Miscanthus sinense and Sorghum bicolor, and monitored their distribution among representatives of the Saccharum genus. The diversity observed among haplotypes suggested the existence of three founding genomes (A, B, C) in modern cultivars, which diverged between 0.8 and 1.3 Mya. Two genomes (A, B) were contributed by S. officinarum; these were also found in its wild presumed ancestor S. robustum, and one genome (C) was contributed by S. spontaneum. These results suggest that S. officinarum and S. robustum are derived from interspecific hybridization between two unknown ancestors (A and B genomes). The A genome contributed most haplotypes (nine or ten) while the B and C genomes contributed one or two haplotypes in the regions analysed of this typical modern cultivar. Interspecific hybridizations likely involved accessions or gametes with distinct ploidy levels and/or were followed by a series of backcrosses with the A genome. The three founding genomes were found in all S. barberi, S. sinense and modern cultivars analysed. None of the analysed accessions contained only the A genome or the B genome, suggesting that representatives of these founding genomes remain to be discovered. This evolutionary model, which combines interspecificity and high polyploidy, can explain the variable chromosome pairing affinity observed in Saccharum. It represents a major revision of the understanding of Saccharum diversity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Integrating functional scoring and regulatory data to predict the effect of non-coding SNPs in a complex neurological disease

Abstract Most SNPs associated with complex diseases seem to lie in non-coding regions of the genome; however, their contribution to gene expression and disease phenotype remains poorly understood. Here, we established a workflow to provide assistance in prioritising the functional relevance of non-coding SNPs of candidate genes as susceptibility loci in polygenic neurological disorders. To illustrate the applicability of our workflow, we considered the multifactorial disorder migraine as a model to follow our step-by-step approach. We annotated the overlap of selected SNPs with regulatory elements and assessed their potential impact on gene expression based on publicly available prediction algorithms and functional genomics information. Some migraine risk loci have been hypothesised to reside in non-coding regions and to be implicated in the neurotransmission pathway. In this study, we used a set of 22 non-coding SNPs from neurotransmission and synaptic machinery-related genes previously suggested to be involved in migraine susceptibility based on our candidate gene association studies. After prioritising these SNPs, we focused on non-reported ones that demonstrated high regulatory potential: (1) VAMP2_rs1150 (3′ UTR) was predicted as a target of hsa-mir-5010-3p miRNA, possibly disrupting its own gene expression; (2) STX1A_rs6951030 (proximal enhancer) may affect the binding affinity of zinc-finger transcription factors (namely ZNF423) and disturb TBL2 gene expression; and (3) SNAP25_rs2327264 (distal enhancer) expected to be in a binding site of ONECUT2 transcription factor. This study demonstrated the applicability of our practical workflow to facilitate the prioritisation of potentially relevant non-coding SNPs and predict their functional impact in multifactorial neurological diseases.

Felício, Daniela↗
DOE OSTI2024

Geometry-complete perceptron networks for 3D molecular graphs

Abstract Motivation The field of geometric deep learning has recently had a profound impact on several scientific domains such as protein structure prediction and design, leading to methodological advancements within and outside of the realm of traditional machine learning. Within this spirit, in this work, we introduce GCPNet, a new chirality-aware SE(3)-equivariant graph neural network designed for representation learning of 3D biomolecular graphs. We show that GCPNet, unlike previous representation learning methods for 3D biomolecules, is widely applicable to a variety of invariant or equivariant node-level, edge-level, and graph-level tasks on biomolecular structures while being able to (1) learn important chiral properties of 3D molecules and (2) detect external force fields. Results Across four distinct molecular-geometric tasks, we demonstrate that GCPNet’s predictions (1) for protein–ligand binding affinity achieve a statistically significant correlation of 0.608, more than 5%, greater than current state-of-the-art methods; (2) for protein structure ranking achieve statistically significant target-local and dataset-global correlations of 0.616 and 0.871, respectively; (3) for Newtownian many-body systems modeling achieve a task-averaged mean squared error less than 0.01, more than 15% better than current methods; and (4) for molecular chirality recognition achieve a state-of-the-art prediction accuracy of 98.7%, better than any other machine learning method to date. Availability and implementation The source code, data, and instructions to train new models or reproduce our results are freely available at https://github.com/BioinfoMachineLearning/GCPNet.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Evolutionary engineering reveals amino acid substitutions in Ato2 and Ato3 that allow improved growth of Saccharomyces cerevisiae on lactic acid

ABSTRACT In Saccharomyces cerevisiae, the complete set of proteins involved in transport of lactic acid across the cell membrane has not been determined. In this study, we aimed to identify transport proteins not previously described to be involved in lactic acid transport via a combination of directed evolution, whole-genome resequencing and reverse engineering. Evolution of a strain lacking all known lactic acid transporters on lactate led to the discovery of mutated Ato2 and Ato3 as two novel lactic acid transport proteins. When compared to previously identified S. cerevisiae genes involved in lactic acid transport, expression of ATO3T284C was able to facilitate the highest growth rate (0.15 ± 0.01 h-1) on this carbon source. A comparison between (evolved) sequences and 3D models of the transport proteins showed that most of the identified mutations resulted in a widening of the narrowest hydrophobic constriction of the anion channel. We hypothesize that this observation, sometimes in combination with an increased binding affinity of lactic acid to the sites adjacent to this constriction, are responsible for the improved lactic acid transport in the evolved proteins.

Baldi, Nicolò↗
DOE OSTI2025

Bacterial and fungal composition and exometabolites control the development and persistence of soil water repellency

Soil water repellency (SWR), the reduced affinity of soil for water, is a phenomenon that affects soils globally. With worsening climate change, SWR is expected to increase emphasizing the need to understand the mechanisms driving SWR development and persistence. The importance of the soil microbes in SWR has been postulated for decades, but limited research has been conducted into whole-community interactions and the role of community metabolic activity. To address this gap in knowledge, we investigated the direct effect of microbial community composition, activity, and diversity, as well as their associated metabolites on the development and persistence of SWR by inoculating microcosms containing model soils with 15 different microbial communities and quantified respiration and SWR over time. Six communities that consistently produced either a hydrophobic or hydrophilic phenotype were characterized using metagenomics and metabolomics to determine the impact of microbial and metabolite composition and diversity on SWR. We identified several bacterial genera with significant changes in abundance between SWR phenotypes including Nocardiopsis and Kocuria in hydrophilic and Streptomyces and Cutibacterium in hydrophobic. We discovered that hydrophilic communities were more positively connected when compared to hydrophobic communities, which could be due to an increase in defense mechanism genes. Additionally, we identified specific metabolites associated with hydrophilic and hydrophobic phenotypes including an increase in the osmolyte ectoine in hydrophilic and an increase in plant-derived decomposition products in hydrophobic communities. Finally, our research suggests that fungi, previously thought to cause hydrophobicity, may actually contribute to hydrophilicity through their preferential consumption of hydrophobic compounds.

54 ENVIRONMENTAL SCIENCES↗