Glycopolymers Prepared by Alternating Ring-Opening Metathesis Polymerization Provide Access to Distinct, Multivalent Structures for the Probing of Biological Activity
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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Results for “active probing”
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.
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Scientific exploration with expert knowledge (SEEK) in autonomous scanning probe microscopy with active learning
This work introduces a knowledge-informed framework that integrates human expertise and prior interest into active learning-driven autonomous experimentation, which enhances the exploration efficiency through more targeted experimentation.
Pratiush, Utkarsh [Department of Materials Science↗
PhenoSelection Manuscript 16S amplicons
Multi-omic analyses can provide a great deal of information on the potential for activity within a microbial community but often lack specificity to link functions to cell and primarily offer potential for function, not true expression of function. Functional assays are necessary for understanding in situ microbial activity to better describe and improve microbiome biology. Targeting enzyme activity through activity-based protein profiling enhances the accuracy of functional studies. Here, we introduce PhenoSelection, a pipeline of coupling activity-based probing with fluorescence-activated cell sorting and downstream activity assays to isolate and examine viable populations of cells expressing a function of interest. We applied PhenoSelection to a soil microbiome to enrich for communities with elevated activity for lignocellulose-degradation phenotypes. PhenoSelection was able to separate and identify taxonomic members with activity for glycosyl hydrolases, and expanding to various probes for other function, this process can be applied to unique phenotypes of interest.
59 BASIC BIOLOGICAL SCIENCES↗
Activity-based protein profiling of chitin catabolism
Microbial catabolism of chitin, a highly abundant component of polymeric organic matter worldwide, is a fundamental cog in the carbon and nitrogen cycles that govern CO2 emissions, nutrient dynamics in aquatic systems, and soil vitality. Despite this critical biogeochemical function, we have a poor understanding of the synergy between various microbial chitinases and key accessory enzymes involved in chitin catabolism. We designed and synthesized activity-based probes (ABPs) for profiling active chitinolytic enzymes by modifying the chitin derivatives N-acetyl glucosamine and chitotriose. The ABPs were used to determine the active complement of chitinolytic enzymes produced over time by the soil bacterium Cellvibrio japonicus treated with various C substrates. This approach allowed us to demonstrate the utility of these ABPs in determining the intricate synergy between chitinases and other glycoside hydrolases that microbes employ to catabolize chitin. The strategy can be used to gain molecular level insights that can be used to better understand microbial roles in soil C and N cycling in the face of a changing climate.
Zegeye, Elias↗
A Telomerase-Activated Magnetic Resonance Imaging Probe for Consecutively Monitoring Tumor Growth Kinetics and In Situ Screening Inhibitors
Telomerase has long been considered as a biomarker for cancer diagnosis and a therapeutic target for drug discovery. Detecting telomerase activity in vivo could provide more direct information of tumor progression and response to drug treatment, which, however, is hampered by the lack of an effective probe that can generate an output signal without a tissue penetration depth limit. Here in this study, using the principle of distance-dependent magnetic resonance tuning, we constructed a telomerase-activated magnetic resonance imaging probe (TAMP) by connecting superparamagnetic ferroferric oxide nanoparticles (SPFONs) and paramagnetic Gd-DOTA (Gd(III) 1,4,7,10- tetraazacyclododecane-1,4,7,10-tetraazacyclododecane-1,4,7,10-tet-raacetic acid) complexes via telomerase-responsive DNA motifs. Upon telomerase-catalyzed extension of the primer in TAMP, Gd-DOTA-conjugated oligonucleotides can be liberated from the surface of SPFONs through a DNA strand displacement reaction, restoring the T 1 signal of the Gd-DOTA for a direct readout of the telomerase activity. Here we show that, by tracking telomerase activity, this probe provides consistent monitoring of tumor growth kinetics during progression and in response to drug treatment and enables in situ screening of telomerase inhibitors in whole-animal models. This study provides an alternative toolkit for cancer diagnosis, treatment response assessment, and anticancer drug screening.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
High-Speed Active Integrators for Magnetic Probes
This report discusses a low cost, easy to develop instrument to measure magnetic fields in pulsed solenoids used for the MagNIF pulse power system. The instrument is designed to integrate voltage signals from custom B-dot probes made from PCB inductor chips. The instrument is battery powered with ± 9V rails. Acceptable B-dot probe inputs range from mV to 20V with frequencies up to 4MHz. Details of the circuit design and practical considerations for working with high speed signals are discussed.
42 ENGINEERING↗
A Probabilistic Model for Global EMIC Wave Activity Using Van Allen Probes Observations
Electromagnetic ion cyclotron (EMIC) waves play a key role in radiation belt dynamics through resonant interactions. However, their low occurrence probability, high variability, and spatial intermittency pose challenges for accurate modeling. In this study, we present a machine learning (ML)-based global EMIC wave model built on the entire data set from the Van Allen Probes mission. To capture the distinct statistical characteristics of wave occurrence and amplitude, the model is separated into two modules: an occurrence model trained using ML techniques, and a wave amplitude model sampled from observed probability distributions. The input parameters are limited to real-time or predictable variables to ensure practical applicability. Our model shows strong performance across the entire test set and demonstrates improved predictive capability over a baseline random occurrence model, particularly during quiet geomagnetic conditions. Evaluation during both quiet and active periods confirms the model's ability to represent the clustered and intermittent nature of EMIC wave activity. Furthermore, the model provides global estimates of wave power, enabling integration with radiation belt electron data and showing signatures consistent with wave-induced scattering. We found a good correlation between the global wave activity from the model and relativistic electron observation by Van Allen Probes, regardless of the availability of in situ wave observations. The modular structure of the model also allows for straightforward expansion for additional wave properties, such as wave frequency, which can be modeled independently. This flexible, event-sensitive approach offers a promising framework for data-driven radiation belt simulations and space weather applications.
79 ASTRONOMY AND ASTROPHYSICS↗
Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning
Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling automated microscopy requires the development of task-specific machine learning methods, understanding the interplay between physics discovery and machine learning, and fully defined discovery workflows. This, in turn, requires balancing the physical intuition and prior knowledge of the domain scientist with rewards that define experimental goals and machine learning algorithms that can translate these to specific experimental protocols. Here, we discuss the basic principles of Bayesian active learning and illustrate its applications for SPM. We progress from the Gaussian process as a simple data-driven method and Bayesian inference for physical models as an extension of physics-based functional fits to more complex deep kernel learning methods, structured Gaussian processes, and hypothesis learning. These frameworks allow for the use of prior data, the discovery of specific functionalities as encoded in spectral data, and exploration of physical laws manifesting during the experiment. Here, the discussed framework can be universally applied to all techniques combining imaging and spectroscopy, SPM methods, nanoindentation, electron microscopy and spectroscopy, and chemical imaging methods and can be particularly impactful for destructive or irreversible measurements.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Super-resolution and signal separation in contact Kelvin probe force microscopy of electrochemically active ferroelectric materials
In this work, imaging mechanisms in contact Kelvin probe force microscopy (cKPFM) are explored via information theory-based methods. Gaussian processes are used to achieve super-resolution in the cKPFM signal, effectively extrapolating across the spatial and parameter space. Tensor factorization is applied to reduce the multidimensional signal to the tensor convolution of the scalar functions that show a clear trending behavior with the imaging parameters. These methods establish a workflow for the analysis of the multidimensional datasets that can then be related to the relevant physical mechanisms. We also provide an interactive Google Colab notebook that goes through all the analyses discussed in the paper.
36 MATERIALS SCIENCE↗
Atomically Precise Scanning Probe Based Analysis of Activated Dopants for 2D Micro Electronics
Explore the source record for details and available documents.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Impact of moisture on microbial decomposition phenotypes and enzyme dynamics
Soil organic matter decomposition is a complex process reflecting microbial composition and environmental conditions. Moisture can modulate the connectivity and interactions of microbes. Due to heterogeneity, a deeper understanding of the influence of soil moisture on the dynamics of organic matter decomposition and resultant phenotypes remains a challenge. Soils from a long-term field experiment exposed to high and low moisture treatments were incubated in the laboratory to investigate organic matter decomposition using chitin as a model substrate. By combining enzymatic assays, biomass measurements, and microbial enrichment via activity-based probes, we determined the microbial functional response to chitin amendments and field moisture treatments at both the community and cell scales. Chitinolytic activities showed significant responses to the amendment of chitin, independent of differences in field moisture treatments. However, for other measurements of carbon metabolism and cellular functions, soils from high moisture field treatments had greater potential enzyme activity than soils from low moisture field treatments. A cell tagging approach was used to enrich and quantify bacterial taxa that are actively producing chitin-degrading enzymes. By integrating organism, community, and soil core measurements we show that (i) a small subset of taxa compose the majority (>50%) of chitinase production despite broad functional redundancy, (ii) the identity of key chitin degraders varies with moisture level, and (iii) extracellular enzymes that are not cell-associated account for most potential chitinase activity measured in field soil.
activity-based probes↗
BONCAT-FACS-Seq reveals the active fraction of a biocrust community undergoing a wet-up event
Determining which microorganisms are active within soil communities remains a major technical endeavor in microbial ecology research. One promising method to accomplish this is coupling bioorthogonal non-canonical amino acid tagging (BONCAT) with fluorescence activated cell sorting (FACS) which sorts cells based on whether or not they are producing new proteins. Combined with shotgun metagenomic sequencing (Seq), we apply this method to profile the diversity and potential functional capabilities of both active and inactive microorganisms in a biocrust community after being resuscitated by a simulated rain event. We find that BONCAT-FACS-Seq is capable of discerning the pools of active and inactive microorganisms, especially within hours of applying the BONCAT probe. The active and inactive components of the biocrust community differed in species richness and composition at both 4 and 21 h after the wetting event. The active fraction of the biocrust community is marked by taxa commonly observed in other biocrust communities, many of which play important roles in species interactions and nutrient transformations. Among these, 11 families within the Firmicutes are enriched in the active fraction, supporting previous reports indicating that the Firmicutes are key early responders to biocrust wetting. We highlight the apparent inactivity of many Actinobacteria and Proteobacteria through 21 h after wetting, and note that members of the Chitinophagaceae, enriched in the active fraction, may play important ecological roles following wetting. Based on the enrichment of COGs in the active fraction, predation by phage and other bacterial members, as well as scavenging and recycling of labile nutrients, appear to be important ecological processes soon after wetting. To our knowledge, this is the first time BONCAT-FACS-Seq has been applied to biocrust samples, and therefore we discuss the potential advantages and shortcomings of coupling metagenomics to BONCAT to intact soil communities such as biocrust. In all, by pairing BONCAT-FACS and metagenomics, we are capable of highlighting the taxa and potential functions that typifies the microbes actively responding to a rain event.
59 BASIC BIOLOGICAL SCIENCES↗
Small footprint optoelectrodes using ring resonators for passive light localization
The combination of electrophysiology and optogenetics enables the exploration of how the brain operates down to a single neuron and its network activity. Neural probes are in vivo invasive devices that integrate sensors and stimulation sites to record and manipulate neuronal activity with high spatiotemporal resolution. State-of-the-art probes are limited by tradeoffs involving their lateral dimension, number of sensors, and ability to access independent stimulation sites. Here, we realize a highly scalable probe that features three-dimensional integration of small-footprint arrays of sensors and nanophotonic circuits to scale the density of sensors per cross-section by one order of magnitude with respect to state-of-the-art devices. For the first time, we overcome the spatial limit of the nanophotonic circuit by coupling only one waveguide to numerous optical ring resonators as passive nanophotonic switches. With this strategy, we achieve accurate on-demand light localization while avoiding spatially demanding bundles of waveguides and demonstrate the feasibility with a proof-of-concept device and its scalability towards high-resolution and low-damage neural optoelectrodes.
42 ENGINEERING↗
Plant metacaspase: A case study of microcrystal structure determination and analysis
Metacaspases are highly conserved in plants and play essential roles in mediating programmed cell death, biotic and abiotic stress responses, and damage-induced innate immunity. Ca 2+ signaling induced by plant damage leads to activation of metacaspase from Arabidopsis thaliana (AtMC4), which subsequently processes a plant elicitor peptide to trigger downstream immuno-response. To understand the structural basis of AtMC4 activation by Ca 2+ , we previously determined its crystal structure and performed in-crystal Ca 2+ treatment to probe activation-associated conformational changes. To enable structure determination and in-crystal Ca 2+ activation analysis, we used microcrystals and related methods which were essential for our successful approach. Here, in this paper, we describe in detail the methods that we used for determination of AtMC4 structure using single-wavelength isomorphous replacement with anomalous signals assembled from 22 microcrystals. We also describe the method for in-crystal Ca 2+ soaking, microcrystal data collection, data assembly and analysis to obtain the activated structure of AtMC4 from 91 micro-sized crystals. The described methods may be useful to study other plant metacaspases and more broadly other plant enzymes for their structure determination and in-crystal functional characterization.
59 BASIC BIOLOGICAL SCIENCES↗
Active predation, phylogenetic diversity, and global prevalence of myxobacteria in wastewater treatment plants
The operation of modern wastewater treatment plants (WWTPs) is driven by activated sludge microbiota, a complex assemblage of trophically interacting microorganisms. Microbial predation is crucial to fundamental understanding of how biological interactions drive microbiome structuring and functioning of WWTPs. However, predatory bacteria have received little attention regarding their diversity, activity, and ecological function in activated sludge, limiting the exploitation of food web interactions for wastewater microbiome engineering. Here, by using rRNA-stable isotope probing of activated sludge microbiota with 13 C-labeled prey bacteria, we uncovered diverse as-yet-uncultivated putative predatory bacteria that actively incorporated 13 C-biomass. Myxobacteria, especially Haliangium and the mle1-27 clade, were found as the dominant active predators, refreshing conventional views based on a few predatory isolates of Bdellovibrionota from WWTPs. The identified predatory bacteria showed more selective predation on prey compared with the protists dominated by ciliates, providing in situ evidence for inter-domain predation behavior divergence in activated sludge. Putative predatory bacteria were tracked over a two-year microbiome monitoring effort at a local WWTP, revealing the predominance of Myxococcota (6.5 ± 1.3%) over Bdellovibrionota (1.0 ± 0.2%) lineages. Phylogenetic analysis unveiled highly diverse myxobacteria inhabiting activated sludge and suggested a habitat filtering effect in global WWTPs. Further mining of a global activated sludge microbiome dataset revealed the prevalence of Myxococcota (5.4 ± 0.1%) species and potential impacts of myxobacterial predation on process performance. Collectively, our findings provided unique insights into the predating activity, diversity, and prevalence of Myxococcota species in activated sludge, highlighting their links with wastewater treatment processes via trophic regulation of enteric and functional bacteria.
59 BASIC BIOLOGICAL SCIENCES↗
Template-stabilized oxidic nickel oxygen evolution catalysts
Earth-abundant oxygen evolution catalysts (OECs) with extended stability in acid can be constructed by embedding active sites within an acid-stable metal-oxide framework. In this paper, we report stable NiPbO x films that are able to perform oxygen evolution reaction (OER) catalysis for extended periods of operation (>20 h) in acidic solutions of pH 2.5; conversely, native NiO x catalyst films dissolve immediately. In situ X-ray absorption spectroscopy and ex situ X-ray photoelectron spectroscopy reveal that PbO 2 is unperturbed after addition of Ni and/or Fe into the lattice, which serves as an acid-stable, conductive framework for embedded OER active centers. The ability to perform OER in acid allows the mechanism of Fe doping on Ni catalysts to be further probed. Catalyst activity with Fe doping of oxidic Ni OEC under acid conditions, as compared to neutral or basic conditions, supports the contention that role of Fe 3+ in enhancing catalytic activity in Ni oxide catalysts arises from its Lewis acid properties.
25 ENERGY STORAGE↗
Chemoproteomic Elucidation of β-Lactam Drug Targets in Mycobacterium abscessus
The pathogen Mycobacterium abscessus (Mab) can cause severe and difficult-to-treat chronic lung infections. Despite the rising incidence and clinical concern of Mab infections, treatment options are limited and often ineffective. Treatment is complicated by Mab’s ability to persist in a nonreplicating, drug-resistant state. Several β-lactam antibiotics are potently bactericidal against Mab but are underutilized because their molecular mechanisms of action against Mab are incompletely understood. In the current study, we used β-lactam-derived activity-based probes and chemoproteomics to report the first comprehensive list of Mab enzymes targeted by β-lactams. We compared β-lactam targets across two Mab subspecies in actively replicating and nonreplicating cultures, using a new carbon starvation model of persistence. We identified 17 targets that were active in every condition tested, seven of which were previously unknown to bind β-lactams. Lastly, we characterized the β-lactamase activity and β-lactam inhibition profiles of nine Mab enzymes, demonstrating that imipenem inhibits these targets more effectively than cefoxitin. These findings demonstrate β-lactam target engagement in persistent Mab and provide clarity on the mechanisms of action of clinically relevant β-lactams in Mab, crucial steps toward fully realizing their potential for treating infections caused by this opportunistic pathogen.
Mycobacterium abscessus↗