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At least 217 records · Page 12

Label-free DNA biosensing by topological light confinement

Large-area and transparent all-dielectric metasurfaces sustaining photonic bound states in the continuum (BICs) provide a set of fundamental advantages for ultrasensitive biosensing. BICs bridge the gap of large effective mode volume with large experimental quality factor. Relying on the transduction mechanism of reactive sensing principle, herein, we first numerically study the potential of subwavelength confinement driven by topological decoupling from free space radiation for BIC-based biosensing. Then, we experimentally combine this capability with minimal and low-cost optical setup, applying the devised quasi-BIC resonator for PNA/DNA selective biosensing with real-time monitoring of the binding event. A sensitivity of 20 molecules per micron squared is achieved, i.e. ≃0.01 pg. Further enhancement can easily be envisaged, pointing out the possibility of single-molecule regime. This work aims at a precise and ultrasensitive approach for developing low-cost point-of-care tools suitable for routine disease prescreening analyses in laboratory, also adaptable to industrial production control.

59 BASIC BIOLOGICAL SCIENCES↗

Pyoverdine binding aptamers and label-free electrochemical detection of pseudomonads

Pyoverdines are iron-chelating siderophores employed by various pseudomonads to promote their growth in iron-limited environments, facilitating both beneficial and detrimental interactions with co-inhabiting microbes or hosts, including plants and animals. The fluorescent pseudomonads produce fluorescent pyoverdines comprised of a conserved central chromophore and a unique strain-specific peptidic side chain produced by non-ribosomal peptide synthetases. Pyoverdine Pf5 (PVD-Pf5) is produced by Pseudomonas protegens Pf-5, a species known for supporting plant growth and its involvement in plant pathogen control. To develop a means of exploring the dynamics of P. protegens activity in soil and in the rhizosphere, we selected DNA aptamers that specifically recognize PVD-Pf5 with high affinities. Two selected aptamers with only 16% identity in sequence were examined for structure and function. We found evidence that both aptamers form structures in their apo-forms and one aptamer has structural features suggesting the presence of a G-quadruplex. Although their tertiary structures are predicted to be different, both aptamers bind the target PVD-Pf5 with similar affinities and do not bind other siderophores, including the related pyoverdine, pseudobactin, produced by Pseudomonas sp. B10. One aptamer binds the pyoverdine peptide component and may also interact with the chromophore. This aptamer was integrated into a nanoporous aluminum oxide biosensor and demonstrated to successfully detect PVD-Pf5 and not to detect other siderophores that do not bind to the aptamer when evaluated in solution. This sensor provides a future opportunity to track the locations of P. protegens around plant roots and to monitor PVD-Pf5 production and movement through the soil.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Separation of Lipoproteins for Quantitative Analysis of 14 C-Labeled Lipid-Soluble Compounds by Accelerator Mass Spectrometry

To date, 14 C tracer studies using accelerator mass spectrometry (AMS) have not yet resolved lipid-soluble analytes into individual lipoprotein density subclasses. The objective of this work was to develop a reliable method for lipoprotein separation and quantitative recovery for biokinetic modeling purposes. The novel method developed provides the means for use of small volumes (10–200 µL) of frozen plasma as a starting material for continuous isopycnic lipoprotein separation within a carbon- and pH-stable analyte matrix, which, following post-separation fraction clean up, created samples suitable for highly accurate 14 C/ 12 C isotope ratio determinations by AMS. Manual aspiration achieved 99.2 ± 0.41% recovery of [5- 14 CH 3 ]-(2R, 4'R, 8'R)-α-tocopherol contained within 25 µL plasma recovered in triacylglycerol rich lipoproteins (TRL = Chylomicrons + VLDL), LDL, HDL, and infranatant (INF) from each of 10 different sampling times for one male and one female subject, n = 20 total samples. Small sample volumes of previously frozen plasma and high analyte recoveries make this an attractive method for AMS studies using newer, smaller footprint AMS equipment to develop genuine tracer analyses of lipophilic nutrients or compounds in all human age ranges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Four Isotope-Labeled Recombination Pathways of Ozone Formation

A theoretical approach is developed for the description of all possible recombination pathways in the ozone forming reaction, without neglecting any process a priori, and without decoupling the individual pathways one from another. These pathways become physically distinct when a rare isotope of oxygen is introduced, such as 18 O, which represents a sensitive probe of the ozone forming reaction. Each isotopologue of O 3 contains two types of physically distinct entrance channels and two types of physically distinct product wells, creating four recombination pathways. Calculations are done for singly and doubly substituted isotopologues of ozone, eight rate coefficients total. Two pathways for the formation of asymmetric ozone isotopomer exhibit rather different rate coefficients, indicating large isotope effect driven by ΔZPE-difference. Rate coefficient for the formation of symmetric isotopomer of ozone (third pathway) is found to be in between of those two, while the rate of insertion pathway is smaller by two orders of magnitude. These trends are in good agreement with experiments, for both singly and doubly substituted ozone. The total formation rates for asymmetric isotopomers are found to be somewhat larger than those for symmetric isotopomers, but not as much as in the experiment. Altogether, the distribution of lifetimes is found to be very similar for the metastable states in symmetric and asymmetric ozone isotopomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterizing intracellular proteomes for microbes: An experimental approach using label-free protein quantitation

Genomic and transcriptomic studies generate a rich source of molecular information; however, neither a static genome nor the presence of a messenger RNA provides the most direct insight into the functional state of a microbial cell at any given time. Rather, it is the ensemble of proteins (i.e., proteome) that is the primary workhorse for most biological processes that are concurrent and coordinately active in a living cell. Currently, mass-spectrometry-based (MS) technologies provide unprecedented information into the composition of the proteome, shedding light on the numerous complex biological processes actively shaping observed phenotypes. Herein, we detail a protocol for the exploration of intracellular proteomes through the large-scale, unbiased identification of proteins and their relative abundances using liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS). In general, this protocol is applicable to both microbial and eukaryotic systems.

Abraham, Paul↗

Track Seeding and Labelling with Embedded-space Graph Neural Networks

To address the unprecedented scale of HL-LHC data, the Exa.TrkX project is investigating a variety of machine learning approaches to particle track reconstruction. The most promising of these solutions, graph neural networks (GNN), process the event as a graph that connects track measurements (detector hits corresponding to nodes) with candidate line segments between the hits (corresponding to edges). Detector information can be associated with nodes and edges, enabling a GNN to propagate the embedded parameters around the graph and predict node-, edge- and graph-level observables. Previously, message-passing GNNs have shown success in predicting doublet likelihood, and we here report updates on the state-of-the-art architectures for this task. In addition, the Exa.TrkX project has investigated innovations in both graph construction, and embedded representations, in an effort to achieve fully learned end-to-end track finding. Hence, we present a suite of extensions to the original model, with encouraging results for hitgraph classification. In addition, we explore increased performance by constructing graphs from learned representations which contain non-linear metric structure, allowing for efficient clustering and neighborhood queries of data points. We demonstrate how this framework fits in with both traditional clustering pipelines, and GNN approaches. The embedded graphs feed into high-accuracy doublet and triplet classifiers, or can be used as an end-to-end track classifier by clustering in an embedded space. A set of post-processing methods improve performance with knowledge of the detector physics. Finally, we present numerical results on the TrackML particle tracking challenge dataset, where our framework shows favorable results in both seeding and track finding.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗