Quantitative imaging of Candida utilis and its organelles by soft X-ray Nano-CT

Detection of acoustic emission from nanofiber nonwovens under tensile strain - An ultrasonic test setup for critical medical device components

In the biomedical field, nanofiber materials are gaining increasing application. For material characterization of nanofiber fabrics, tensile testing and scanning electron microscopy (SEM) are established standards. However, tensile tests provide information about the entire sample without information about single fibers. Conversely, SEM images examine individual fibers, but cover only a small section near the surface of the sample. To gain information on failure at the fiber level under tensile stress, recording of acoustic emission (AE) is a promising method, but challenging due to weak signal intensity. Using AE recording, beneficial findings can be obtained even on "invisible" material failure without affecting tensile tests. In this work, a technology for recording weak ultrasonic AE of tearing nanofiber nonwovens is presented, which uses a highly sensitive sensor. Functional proof of the method using biodegradable PLLA nonwoven fabrics is provided. The potential benefit is demonstrated by unmasking significant AE intensity in an almost imperceptible bend in the stress-strain curve of a nonwoven fabric. AE recording has not yet been performed on standard tensile tests of unembedded nanofiber material intended for safety-related medical applications. The technology has the potential to enrich the spectrum of testing methods, even those not confined to medical field.

On-Line Fluorescence Microscopy for Identification and Imaging of Apoptotic Cell with Synchrotron-Based Soft X-ray Tomography

Synchrotron-based soft X-ray tomography (SXT), providing three-dimensional morphology and quantitative distribution of linear absorption coefficient (LAC) of the imaged objects, is widely used in many fields to obtain ultra-structure images, especially in cellular imaging. Off-line fluorescence microscopies (FMs) are combined to identify the type of organelles and status of cells. However, deformation and displacement usually occur during the transfer and loading process, which decreases the precision of two-modal images' registration. In this paper, we report on an on-line FM, at the SXT station (BL07W) of the National Synchrotron Radiation Laboratory (NSRL), which avoids deformation and displacement. Therefore, researchers can easily find the sample and take the useful data without tedious post-processing. Combining SXT with on-line FM, we achieved the identification and high-resolution imaging of an apoptotic cell. The experiments revealed that the LAC of the nucleus of the apoptotic cell was larger than that of a normal cell, which could be explained by nucleus pyknosis of the apoptotic cell.

Insight into the structure and metabolic function of iron-rich nanoparticles in anammox bacteria

Anaerobic ammonium-oxidizing (anammox) bacteria are iron abundant and depend heavily on iron-binding proteins. The iron demand of anammox bacteria is relatively large. However, it still remains some doubts where these large quantities of available iron come from and how they are regulated in anammox bacteria. Herein, iron-rich nanoparticles in anammoxosomes were detected by synchrotron soft X-ray tomography coupled with scanning transmission X-ray microscopy (STXM). The iron-rich nanoparticles were identified as ferric oxide (α-Fe₂O₃) mineral cores, and the local atomic structure of iron-rich nanoparticles was obtained by X-ray absorption fine-structure (XAFS) spectra. The bacterioferritin of Q1Q315 and Q1Q5F8 were detected by proteomics analysis. On this basis, the metabolic pathway centered on iron-rich nanoparticles was proposed.

Using soft X-ray tomography for rapid whole-cell quantitative imaging of SARS-CoV-2-infected cells

High-resolution and rapid imaging of host cell ultrastructure can generate insights toward viral disease mechanism, for example for a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Here, we employ full-rotation soft X-ray tomography (SXT) to examine organelle remodeling induced by SARS-CoV-2 at the whole-cell level with high spatial resolution and throughput. Most of the current SXT systems suffer from a restricted field of view due to use of flat sample supports and artifacts due to missing data. In this approach using cylindrical sample holders, a full-rotation tomogram of human lung epithelial cells is performed in less than 10 min. We demonstrate the potential of SXT imaging by visualizing aggregates of SARS-CoV-2 virions and virus-induced intracellular alterations. This rapid whole-cell imaging approach allows us to visualize the spatiotemporal changes of cellular organelles upon viral infection in a quantitative manner.

Geometric morphometric analysis of spore shapes improves identification of fungi

Morphology of organisms is an essential source of evidence for taxonomic decisions and understanding of ecology and evolutionary history. The geometric structure (i.e., numeric description of shape) provides richer and mathematically different information about an organism's morphology than linear measurements. A little is known on how these two sources of morphological information (shape vs. size) contribute to the identification of organisms when implied simultaneously. This study hypothesized that combining geometric information on the outline with linear measurements results in better species identification than either evidence alone can provide. As a test system for our research, we used the microscopic spores of fungi from the genus Subulicystidium (Agaricomycetes, Basidiomycota). We analyzed 2D spore shape data via elliptic Fourier and principal component analyses. Using flexible discriminant analysis, we achieved the highest species identification success rate for a combination of shape and size descriptors (64.7%). The shape descriptors alone predicted species slightly better than size descriptors (61.5% vs. 59.1%). We conclude that adding geometric information on the outline to linear measurements improves the identification of the organisms. Despite the high relevance of spore traits for the taxonomy of fungi, they were previously rarely analyzed with the tools of geometric morphometrics. Therefore, we supplement our study with an open access protocol for digitizing and summarizing fungal spores' shape and size information. We propagate a broader use of geometric morphometric analysis for microscopic propagules of fungi and other organisms.

Biomimetic inorganic-organic hybrid nanoparticles from magnesium-substituted amorphous calcium phosphate clusters and polyacrylic acid molecules

Amorphous calcium phosphate (ACP) has been widely found during bone and tooth biomineralization, but the meta-stability and labile nature limit further biomedical applications. The present study found that the chelation of polyacrylic acid (PAA) molecules with Ca²⁺ ions in Mg-ACP clusters (~2.1 ± 0.5 nm) using a biomineralization strategy produced inorganic-organic Mg-ACP/PAA hybrid nanoparticles with better thermal stability. Mg-ACP/PAA hybrid nanoparticles (~24.0 ± 4.8 nm) were pH-responsive and could be efficiently digested under weak acidic conditions (pH 5.0–5.5). The internalization of assembled Mg-ACP/PAA nanoparticles by MC3T3-E1 cells occurred through endocytosis, indicated by laser scanning confocal microscopy and cryo-soft X-ray tomography. Our results showed that cellular lipid membranes remained intact without pore formation after Mg-ACP/PAA particle penetration. The assembled Mg-ACP/PAA particles could be digested in cell lysosomes within 24 h under weak acidic conditions, thereby indicating the potential to efficiently deliver encapsulated functional molecules. Both the in vitro and in vivo results preliminarily demonstrated good biosafety of the inorganic-organic Mg-ACP/PAA hybrid nanoparticles, which may have potential for biomedical applications.

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Mg-ACP/PAA hybrid nanoparticles have been synthesized following a biomineralization strategy.

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The chelation of PAA molecules in synergy with Mg²⁺ substitution improves thermal stability of Mg-ACP/PAA nanoparticles.

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The Mg-ACP/PAA nanoparticles are pH sensitive and can be digested in cell lysosomes within 24 h.

Three-dimensional imaging of mitochondrial cristae complexity using cryo-soft X-ray tomography

Mitochondria are dynamic organelles that change morphology to adapt to cellular energetic demands under both physiological and stress conditions. Cardiomyopathies and neuronal disorders are associated with structure-related dysfunction in mitochondria, but three-dimensional characterizations of the organelles are still lacking. In this study, we combined high-resolution imaging and 3D electron density information provided by cryo-soft X-ray tomography to characterize mitochondria cristae morphology isolated from murine. Using the linear attenuation coefficient, the mitochondria were identified (0.247 ± 0.04 µm-1) presenting average dimensions of 0.90 ± 0.20 µm in length and 0.63 ± 0.12 µm in width. The internal mitochondria structure was successfully identified by reaching up the limit of spatial resolution of 35 nm. The internal mitochondrial membranes invagination (cristae) complexity was calculated by the mitochondrial complexity index (MCI) providing quantitative and morphological information of mitochondria larger than 0.90 mm in length. The segmentation to visualize the cristae invaginations into the mitochondrial matrix was possible in mitochondria with MCI ≥ 7. Altogether, we demonstrated that the MCI is a valuable quantitative morphological parameter to evaluate cristae modelling and can be applied to compare healthy and disease state associated to mitochondria morphology.

Directly observing intracellular nanoparticle formation with nanocomputed tomography

Directly observing intracellular nanostructure formation remains challenging. In this work, using a rationally designed small-molecule 4-nitrobenzyl carbamate-Cys(SEt)-Asp-Asp-Phe(iodine)-2-cyano-benzothiazole (NBC-Iod-CBT), we directly observed intracellular nanoparticle formation with nanocomputed tomography (nano-CT). In vitro, upon glutathione reduction and nitroreductase (NTR) cleavage, NBC-Iod-CBT undergoes a CBT-Cys click condensation reaction to self-assemble nanoparticles Iod-CBT-NPs with an average linear absorption coefficient (LAC) value of 0.182 ± 0.078 μm^-1 to x-ray. Nano-CT imaging of the NBC-Iod-CBT-treated, NTR-overexpressing HeLa cells showed the existence of Iod-CBT-NPs in their cytoplasm with an average LAC value of 0.172 ± 0.032 μm^-1 We anticipate that our strategy could help people to deeply understand the formation mechanism of intracellular nanostructures in the near future.

Quantitative three-dimensional nondestructive imaging of whole anaerobic ammonium-oxidizing bacteria

Anaerobic ammonium-oxidizing (anammox) bacteria play a key role in the global nitrogen cycle and in nitrogenous wastewater treatment. The anammox bacteria ultrastructure is unique and distinctly different from that of other prokaryotic cells. The morphological structure of an organism is related to its function; however, research on the ultrastructure of intact anammox bacteria is lacking. In this study, in situ three-dimensional nondestructive ultrastructure imaging of a whole anammox cell was performed using synchrotron soft X-ray tomography (SXT) and the total variation-based simultaneous algebraic reconstruction technique (TV-SART). Statistical and quantitative analyses of the intact anammox bacteria were performed. High soft X-ray absorption composition inside anammoxosome was detected and verified to be relevant to iron-binding protein. On this basis, the shape adaptation of the anammox bacteria response to iron was explored.

Raman micro-spectroscopy monitoring of cytochrome c redox state in Candida utilis during cell death under low-temperature plasma-induced oxidative stress

Oxidative stress may result in different modes of cell death, such as necrosis, apoptosis and necroptosis. Currently, researchers are still striving to develop efficient tools/methods to distinguish the cell death modes in direct and label-free ways. In this study, we attempted to employ Raman micro-spectroscopy to observe the molecular changes in Candida utilis cells under oxidative stress induced by low-temperature plasma (LTP) and explore the spectroscopic biomarkers for the modes of cell death under oxidative stress. In this research, we confirmed that LTP could impose oxidative stress on the yeast cells, and recorded the changes of Raman signals of cytochrome c in the cells under LTP oxidative stress. Subsequently, we identified the biochemical and morphological characteristic features corresponding to different modes of cell death. Interestingly, we found that LTP under certain conditions could induce oxidative stress which caused the yeast cell death mainly by means of necroptosis, which was verified by Annexin V/PI, HMGB1 location assay and immunoprecipitation assay of the RIP1/RIP3 necrosome. Correspondingly, we also showed that the LTP induced necroptosis, associated with the increase of cytoplasmic Ca²⁺ and mitochondrial ROS, the decrease of mitochondrial membrane potential, the release of oxidized cytochrome c from the mitochondrion to the cytoplasm, and the destruction of mitochondria in yeast cells. This work has therefore demonstrated that monitoring the redox state of cytochrome c using Raman micro-spectroscopy is very useful for distinguishing the modes of cell death and particularly may unveil the unique necroptosis process of cells under extrinsic oxidative stress.

Limited angle tomography for transmission X-ray microscopy using deep learning

In transmission X-ray microscopy (TXM) systems, the rotation of a scanned sample might be restricted to a limited angular range to avoid collision with other system parts or high attenuation at certain tilting angles. Image reconstruction from such limited angle data suffers from artifacts because of missing data. In this work, deep learning is applied to limited angle reconstruction in TXMs for the first time. With the challenge to obtain sufficient real data for training, training a deep neural network from synthetic data is investigated. In particular, U-Net, the state-of-the-art neural network in biomedical imaging, is trained from synthetic ellipsoid data and multi-category data to reduce artifacts in filtered back-projection (FBP) reconstruction images. The proposed method is evaluated on synthetic data and real scanned chlorella data in 100° limited angle tomography. For synthetic test data, U-Net significantly reduces the root-mean-square error (RMSE) from 2.55 × 10-3 µm-1 in the FBP reconstruction to 1.21 × 10-3 µm-1 in the U-Net reconstruction and also improves the structural similarity (SSIM) index from 0.625 to 0.920. With penalized weighted least-square denoising of measured projections, the RMSE and SSIM are further improved to 1.16 × 10-3 µm-1 and 0.932, respectively. For real test data, the proposed method remarkably improves the 3D visualization of the subcellular structures in the chlorella cell, which indicates its important value for nanoscale imaging in biology, nanoscience and materials science.

Precise correlative method of Cryo-SXT and Cryo-FM for organelle identification

Cryogenic soft X-ray tomography (Cryo-SXT) is ideally suitable to image the 3D sub-cellular architecture and organization of cells with high resolution in the near-native preservation state. Cryogenic fluorescence microscopy (Cryo-FM) can determine the location of a molecule of interest that has been labeled with a fluorescent tag, thus revealing the function of the cells. To understand the relations between the sub-cellular architecture and the function of cells, correlative Cryo-SXT and Cryo-FM was applied. This method required the matching of images of different modalities, and the accuracy of the matching is important. Here, a precise correlative method of Cryo-SXT and Cryo-FM is introduced. The capability of matching images of different modalities with high resolution was verified by simulations and practical experiments, and the method was used to identify vacuoles and mitochondria.

Jitter correction for transmission X-ray microscopy via measurement of geometric moments

Transmission X-ray microscopes (TXMs) have become one of the most powerful tools for imaging 3D structures of nano-scale samples using the computed tomography (CT) principle. As a major error source, sample jitter caused by mechanical instability of the rotation stage produces shifted 2D projections, from which reconstructed images contain severe motion artifacts. In this paper, a jitter correction algorithm is proposed, that has high accuracy and computational efficiency for TXM experiments with or without nano-particle markers. Geometric moments (GMs) are measured on segmented projections for each angle and fitted to sinusoidal curves in the angular direction. Sample jitter is estimated from the difference between the measured and the fitted GMs for image correction. On a digital phantom, the proposed method removes jitter errors at different noise levels. Physical experiments on chlorella cells show that the proposed GM method achieves better spatial resolution and higher computational efficiency than the re-projection method, a state-of-the-art algorithm using iterative correction. It even outperforms the approach of manual alignment, the current gold standard, on faithfully maintaining fine structures on the CT images. Our method is practically attractive in that it is computationally efficient and lowers experimental costs in current TXM studies without using expensive nano-particles markers.