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At least 73 records · Page 4

ROI-Finder : machine learning to guide region-of-interest scanning for X-ray fluorescence microscopy

The microscopy research at the Bionanoprobe (currently at beamline 9-ID and later 2-ID after APS-U) of Argonne National Laboratory focuses on applying synchrotron X-ray fluorescence (XRF) techniques to obtain trace elemental mappings of cryogenic biological samples to gain insights about their role in critical biological activities. The elemental mappings and the morphological aspects of the biological samples, in this instance, the bacterium Escherichia coli ( E. Coli ), also serve as label-free biological fingerprints to identify E. coli cells that have been treated differently. The key limitations of achieving good identification performance are the extraction of cells from raw XRF measurements via binary conversion, definition of features, noise floor and proportion of cells treated differently in the measurement. Automating cell extraction from raw XRF measurements across different types of chemical treatment and the implementation of machine-learning models to distinguish cells from the background and their differing treatments are described. Principal components are calculated from domain knowledge specific features and clustered to distinguish healthy and poisoned cells from the background without manual annotation. The cells are ranked via fuzzy clustering to recommend regions of interest for automated experimentation. The effects of dwell time and the amount of data required on the usability of the software are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Distinguishing Potassium Channel Resting State Conformations in Live Cells with Environment-Sensitive Fluorescence

Ion channels are polymorphic membrane proteins whose high-resolution structures offer images of individual conformations, giving us starting points for identifying the complex and transient allosteric changes that give rise to channel physiology. Here, we report live-cell imaging of voltage-dependent structural changes of voltage-gated Kv2.1 channels using peptidyl tarantula toxins labeled with an environment-sensitive fluorophore, whose spectral shifts enable identification of voltage-dependent conformation changes in the resting voltage sensing domain (VSD) of the channel. We synthesize a new environment-sensitive, far-red fluorophore, julolidine phenoxazone (JP) azide, and conjugate it to tarantula toxin GxTX to characterize Kv2.1 VSD allostery during membrane depolarization. JP has an inherent response to the polarity of its immediate surroundings, offering site-specific structural insight into each channel conformation. Using voltage-clamp spectroscopy to collect emission spectra as a function of membrane potential, we find that they vary with toxin labeling site, the presence of Kv2 channels, and changes in membrane potential. With a high-affinity conjugate in which the fluorophore itself interacts closely with the channel, the emission shift midpoint is 50 mV more negative than the Kv2.1 gating current midpoint. This suggests that substantial conformational changes at the toxin-channel interface are associated with early gating charge transitions and these are not concerted with VSD motions at more depolarized potentials. These fluorescent probes enable study of conformational changes that can be correlated with electrophysiology, putting channel structures and models into a context of live-cell membranes and physiological states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Light-sheet autofluorescence lifetime imaging with a single-photon avalanche diode array

Significance: Fluorescence lifetime imaging microscopy (FLIM) of the metabolic co-enzyme nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] is a popular method to monitor single-cell metabolism within unperturbed, living 3D systems. However, FLIM of NAD(P)H has not been performed in a light-sheet geometry, which is advantageous for rapid imaging of cells within live 3D samples. Aim: We aim to design, validate, and demonstrate a proof-of-concept light-sheet system for NAD(P)H FLIM. Approach: A single-photon avalanche diode camera was integrated into a light sheet microscope to achieve optical sectioning and limit out-of-focus contributions for NAD(P)H FLIM of single cells. Results: An NAD(P)H light-sheet FLIM system was built and validated with fluores cence lifetime standards and with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times. NAD(P)H light-sheet FLIM in vivo was demonstrated with live neutrophil imaging in a larval zebrafish tail wound also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light-sheet geometries, indicating a 30× to 6× acquisition speed advantage for the light sheet compared to the laser scanning geometry. Conclusions: FLIM of NAD(P)H is feasible in a light-sheet geometry and is attrac tive for 3D live cell imaging applications, such as monitoring immune cell metabolism and migration within an organism.

47 OTHER INSTRUMENTATION↗

In vivo visualization of butterfly scale cell morphogenesis in Vanessa cardui

Many organisms exhibit functional micro- and nanoscale materials with structural definition and performance that challenge synthetic fabrication techniques, yet we know little about the processes that enable their formation. Using butterfly scales as a model system for functional biomaterials, we establish a timeline of scale formation and quantify relevant structural parameters for developing painted lady butterflies. We overcome challenges of previous efforts by imaging structure formation directly in living organisms, which allows us to continuously observe the evolving wing tissue and the fine details of individual scale cells. Visualization of scale structure formation in live butterflies forms the basis for modeling the underlying biomechanical processes and opens avenues for their translation into advanced fabrication strategies.

59 BASIC BIOLOGICAL SCIENCES↗

Mass Spectral Imaging to Map Plant–Microbe Interactions

Plant–microbe interactions are of rising interest in plant sustainability, biomass production, plant biology, and systems biology. These interactions have been a challenge to detect until recent advancements in mass spectrometry imaging. Plants and microbes interact in four main regions within the plant, the rhizosphere, endosphere, phyllosphere, and spermosphere. This mini review covers the challenges within investigations of plant and microbe interactions. We highlight the importance of sample preparation and comparisons among time-of-flight secondary ion mass spectroscopy (ToF-SIMS), matrix-assisted laser desorption/ionization (MALDI), laser desorption ionization (LDI/LDPI), and desorption electrospray ionization (DESI) techniques used for the analysis of these interactions. Using mass spectral imaging (MSI) to study plants and microbes offers advantages in understanding microbe and host interactions at the molecular level with single-cell and community communication information. More research utilizing MSI has emerged in the past several years. We first introduce the principles of major MSI techniques that have been employed in the research of microorganisms. An overview of proper sample preparation methods is offered as a prerequisite for successful MSI analysis. Traditionally, dried or cryogenically prepared, frozen samples have been used; however, they do not provide a true representation of the bacterial biofilms compared to living cell analysis and chemical imaging. New developments such as microfluidic devices that can be used under a vacuum are highly desirable for the application of MSI techniques, such as ToF-SIMS, because they have a subcellular spatial resolution to map and image plant and microbe interactions, including the potential to elucidate metabolic pathways and cell-to-cell interactions. Promising results due to recent MSI advancements in the past five years are selected and highlighted. The latest developments utilizing machine learning are captured as an important outlook for maximal output using MSI to study microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

Fluorescent toxins as ion channel activity sensors.

Voltage gated ion channels (VGICs) shape the electrical character of cells by undergoing structural changes in response to membrane depolarization. High-resolution techniques have provided a wealth of data on individual VGIC structures, but the conformational changes of endogenous channels in live cell membranes have remained unexplored. Here, we describe methods for imaging structural changes of voltage-gated K + channels in living cells, using peptidyl toxins labeled with fluorophores that report specific protein conformations. These Endogenous Voltage-sensor Activity Probes (EVAPs) enable study of both VGIC allostery and function in the context of endogenous live-cell membranes under different physiological states. In this chapter, we describe methods for the synthesis, imaging, and analysis of dynamic EVAPs, which can report K + channel activity in complex tissue preparations via 2-photon excitation microscopy, and environment-sensitive EVAPs, which report voltage-dependent conformational changes at the VGIC-toxin interface. The methods here present the utility of current EVAPs and lay the groundwork for the development of other probes that act by similar mechanisms. EVAPs can be correlated with electrophysiology, offering insight into the molecular details of endogenous channel function and allostery in live cells. This enables investigation of conformational changes of channels in their native, functional states, putting structures and models into a context of live-cell membranes. The expansive array of state-dependent ligands and optical probes should enable probes more generally for investigating the molecular motions of endogenous proteins.

Stewart, Robert↗

pnnl/brain_ohsu

Light sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. We fine-tuned an existing model, TrailMap, using expert labeled data from axonal structures in neocortex. Without changing the network architecture, we implemented nnU-Net framework modifications in data augmentation, data foreground sampling, window learning rate, and the inference overlap method. The resulting model from these combined approaches yielded an improved F1 score

Oostrom, Marjolein↗

Real-time single-element-detection structured illumination optical metrology for laser powder bed fusion

Laser powder bed fusion (LPBF) is a type of metal additive manufacturing which could benefit from improved process monitoring to improve quality control. We demonstrate, for the first time to our knowledge, the coaxial monitoring of melt track formation in steel powder with spatial frequency modulation imaging (SPIFI), an enhanced-resolution imaging technique which uses a photodiode to record one-dimensional images. Using a custom live-display software and a high-speed SPIFI geometry, we offset the SPIFI field of view from the fusing beam to monitor different regions of the LPBF melt pool and surrounding area. This demonstrates the potential of SPIFI to monitor spatial features within the melt pool in real-time with increased data efficiency.

Hunter, Scott (ORCID:0009000886150312)↗

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By changing the cross-entropy weights and using augmentation, we demonstrate a generally improved adjusted F1-score over using the originally trained TrailMap model within our test datasets.

97 MATHEMATICS AND COMPUTING↗

Data-driven Mapping of the Mouse Connectome: The utility of transfer learning to improve the performance of deep learning models performing axon segmentation on light-sheet microscopy images

Light sheet microscopy has made possible the high temporal and spatial 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual process. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through the application of refinements such as transfer learning.

59 BASIC BIOLOGICAL SCIENCES↗

Radioarsenic: A promising theragnostic candidate for nuclear medicine

Molecular imaging is a non-invasive process that enable the visualization, characterization, and quantitation of biological processes at the molecular and cellular level. With the emergence of theragnostic agents to diagnose and treat disease for personalized medicine there is a growing need for matched pairs of isotopes. Matched pairs offer the unique opportunity to obtain patient specific information from SPECT or PET diagnostic studies to quantitate in vivo function or receptor density to inform and tailor therapeutic treatment. There are several isotopes of arsenic that have emissions suitable for either or both diagnostic imaging and radiotherapy. Their half-lives are long enough to pair them with peptides and antibodies which take longer to reach maximum uptake to facilitate improved patient pharmacokinetics and dosimetry then can be obtained with shorter lived radionuclides. Arsenic-72 even offers availability from a generator that can be shipped to remote sites and thus enhances availability. Arsenic has a long history as a diagnostic agent, but until recently has suffered from limited availability, lack of suitable chelators, and concerns about toxicity have inhibited its use in nuclear medicine. However, new production methods and novel chelators are coming online and the use of radioarsenic in the pico and nanomolar scale is well below the limits associated with toxicity. This manuscript will review the production routes, separation chemistry, radiolabeling techniques and in vitro/in vivo studies of three medically relevant isotopes of arsenic (arsenic-74, arsenic-72, and arsenic-77).

07 ISOTOPE AND RADIATION SOURCES↗

Endogenous Production and Vibrational Analysis of Heavy-Isotope-Labeled Peptides from Cyanobacteria

Stable isotope labeling is an extremely useful tool for characterizing the structure, tracing the metabolism, and imaging the distribution of natural products in living organisms using mass-sensitive measurement techniques. In this study, a cyanobacterium was cultured in 15 N/ 13 C-enriched media to endogenously produce labeled, bioactive oligopeptides. The extent of heavy isotope incorporation in these peptides was determined with LC–MS, while the overall extent of heavy isotope incorporation in whole cells was studied with nanoSIMS and AFM-IR. Up to 98 % heavy isotope incorporation was observed in labeled cells. Three of the most abundant peptides, microcystin-LR (MCLR), cyanopeptolin-A (CYPA), and aerucyclamide-A (ACAA), were isolated and further studied with Raman and FTIR spectroscopies and DFT calculations. This revealed several IR and Raman active vibrations associated with functional groups not common in ribosomal peptides, like diene, ester, thiazole, thiazoline, and oxazoline groups, which could be suitable for future vibrational imaging studies. More broadly, this study outlines a simple and relatively inexpensive method for producing heavy-labeled natural products. Finally, manipulating the bacterial culture conditions by the addition of specific types and amounts of heavy-labeled nutrients provides an efficient means of producing heavy-labeled natural products for mass-sensitive imaging studies.

60 APPLIED LIFE SCIENCES↗

Understanding Plant Signaling Via Innovations in Probe Delivery and Imaging

The goal of this project was to develop tools for studying plant processes in living tissues. We wanted a method for introducing probes for studying plant processes such that plants could remain intact and imaged iteratively. Towards this end, we successfully optimized carbon nanofibers that we showed could deliver non-permeable signaling probes/biomolecules to plant cells. These were created on a rigid backing and also successfully transferred to a flexible backing to use with curved plant structures. We also built fiber optic microscopes that permit iterative non-destructive fluorescence or light micrographs and created protocols and devices to stabilize plant organs during imaging. These tools were developed in conjunction with research aimed understanding receptor-mediated peptide trafficking and responses relevant to plant cell growth and defense tradeoff. During this project, we designed and built two fiberoptic fluorescence microscopes; (b) designed, fabricated and validated different nanospike designs for delivering probes to plants, including the feasibility of delivering DNA constructs for expression studies; (c) developed fluorescent peptide probes (active and inactive versions of a secreted receptor ligand called phytosulfokine or PSK) and performed mobility tests after application to plants using microscopy; (d) used appropriate genetic plant backgrounds to facilitate PSK trafficking and response mechanisms; (e) determined the transcriptional changes due to PSK-induced signaling related to growth/defense tradeoff; (f) performed experiments showing the growth/defense tradeoff involves repression of specific defense components in response to PSK. This project also involved the training of two PhD students and five Masters students.

47 OTHER INSTRUMENTATION↗

Deep learning classification of lipid droplets in quantitative phase images

We report the application of supervised machine learning to the automated classification of lipid droplets in label-free, quantitative-phase images. By comparing various machine learning methods commonly used in biomedical imaging and remote sensing, we found convolutional neural networks to outperform others, both quantitatively and qualitatively. We describe our imaging approach, all implemented machine learning methods, and their performance with respect to computational efficiency, required training resources, and relative method performance measured across multiple metrics. Overall, our results indicate that quantitative-phase imaging coupled to machine learning enables accurate lipid droplet classification in single living cells. As such, the present paradigm presents an excellent alternative of the more common fluorescent and Raman imaging modalities by enabling label-free, ultra-low phototoxicity, and deeper insight into the thermodynamics of metabolism of single cells.

59 BASIC BIOLOGICAL SCIENCES↗

Integrative Quantitative-Phase and Airy Light-Sheet Imaging

Light-sheet microscopy enables considerable speed and phototoxicity gains, while quantitative-phase imaging confers label-free organelle recognition and metabolic information that are inaccessible by conventional methods. We report the fusion of these two modalities onto a standard inverted microscope that retains compatibility with microfluidics. We describe the utilization of an accelerating Airy-beam light-sheet yielding identical imaging areas with interferometry, and an application in unmasking the effects of cellular noise on metabolic compartmentalization.

Biological sciences, Biological techniques, Micros↗

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗

Development of 52Mn Labeled Trastuzumab for Extended Time Point PET Imaging of HER2

Abstract Purpose Due to their long circulation time in the blood, monoclonal antibodies (mAbs) such as trastuzumab, are usually radiolabeled with long-lived positron emitters for the development of agents for Positron Emission Tomography (PET) imaging. Manganese-52 ( 52 Mn, t 1/2 = 5.6 d, β + = 29.6%, E(β ave ) = 242 keV) is suitable for imaging at longer time points providing a complementary technique to Zirconium-89 ( 89 Zr, t 1/2 = 3.3 d, β + = 22.7%, E(β ave ) = 396 keV)) because of its long half-life and low positron energy. To exploit these properties, we aimed to investigate suitable bifunctional chelators that could be readily conjugated to antibodies and labeled with 52 Mn under mild conditions using trastuzumab as a proof-of-concept. Procedures Trastuzumab was incubated with S-2-(4-isothiocyanatobenzyl)-1,4,7,10-tetraazacyclododecane tetraacetic acid (p-SCN-Bn-DOTA), 1-Oxa-4,7,10-tetraazacyclododecane-5-S-(4-isothiocyantobenzyl)-4,7,10-triacetic acid (p-SCN-Bn-Oxo-DO3A), and 3,6,9,15-tetraazabicyclo[9.3.1] pentadeca-1(15),11,13-triene-4-S-(4-isothiocyanatobenzyl)-3,6,9-triacetic acid (p-SCN-Bn-PCTA) at a tenfold molar excess. The immunoconjugates were purified, combined with [ 52 Mn]MnCl 2 at different ratios, and the labeling efficiency was assessed by iTLC. The immunoreactive fraction of the radiocomplex was determined through a Lindmo assay. Cell studies were conducted in HER2 + (BT474) and HER2- (MDA-MB-468) cell lines followed by in vivo studies. Results Trastuzumab-Oxo-DO3A was labeled within 30 min at 37 °C with a radiochemical yield (RCY) of 90 ± 1.5% and with the highest specific activity of the chelators investigated of 16.64 MBq/nmol. The labeled compound was purified with a resulting radiochemical purity of > 98% and retained a 67 ± 1.2% immunoreactivity. DOTA and PCTA immunoconjugates resulted in < 50 ± 2.5% (RCY) with similar specific activity. Mouse serum stability studies of [ 52 Mn]Mn-Oxo-DO3A-trastuzumab showed 95% intact complex for over 5 days. Cell uptake studies showed higher uptake in HER2 + (12.51 ± 0.83% /mg) cells compared to HER2- (0.85 ± 0.10%/mg) cells. PET images of mice bearing BT474 tumors showed high tumor uptake that was consistent with the biodistribution (42.02 ± 2.16%ID/g, 14 d) compared to MDA-MB-468 tumors (2.20 ± 0.80%ID/g, 14 d). Additionally, both models exhibited low bone uptake of < 1% ID/g. Conclusion The bifunctional chelator p-SCN-Bn-Oxo-DO3A is promising for the development of 52 Mn radiopharmaceuticals as it was easily conjugated, radiolabeled at mild conditions, and illustrated stability for a prolonged duration both in vitro and in vivo . High-quality PET/CT images of [ 52 Mn]Mn-Oxo-DO3A-trastuzumab were obtained 14 d post-injection. This study illustrates the potential of [ 52 Mn]Mn-Oxo-DO3A for the evaluation of antibodies using PET imaging.

Omweri, James M.↗