Progression of herpesvirus infection remodels mitochondrial organization and metabolism.

Viruses target mitochondria to promote their replication, and infection-induced stress during the progression of infection leads to the regulation of antiviral defenses and mitochondrial metabolism which are opposed by counteracting viral factors. The precise structural and functional changes that underlie how mitochondria react to the infection remain largely unclear. Here we show extensive transcriptional remodeling of protein-encoding host genes involved in the respiratory chain, apoptosis, and structural organization of mitochondria as herpes simplex virus type 1 lytic infection proceeds from early to late stages of infection. High-resolution microscopy and interaction analyses unveiled infection-induced emergence of rough, thin, and elongated mitochondria relocalized to the perinuclear area, a significant increase in the number and clustering of endoplasmic reticulum-mitochondria contact sites, and thickening and shortening of mitochondrial cristae. Finally, metabolic analyses demonstrated that reactivation of ATP production is accompanied by increased mitochondrial Ca2+ content and proton leakage as the infection proceeds. Overall, the significant structural and functional changes in the mitochondria triggered by the viral invasion are tightly connected to the progression of the virus infection.

Soft X-ray tomograms provide a structural basis for whole-cell modeling.

Developing in silico models that accurately reflect a whole, functional cell is an ongoing challenge in biology. Current efforts bring together mathematical models, probabilistic models, visual representations, and data to create a multi-scale description of cellular processes. A realistic whole-cell model requires imaging data since it provides spatial constraints and other critical cellular characteristics that are still impossible to obtain by calculation alone. This review introduces Soft X-ray Tomography (SXT) as a powerful imaging technique to visualize and quantify the mesoscopic (~25 nm spatial scale) organelle landscape in whole cells. SXT generates three-dimensional reconstructions of cellular ultrastructure and provides a measured structural framework for whole-cell modeling. Combining SXT with data from disparate technologies at varying spatial resolutions provides further biochemical details and constraints for modeling cellular mechanisms. We conclude, based on the results discussed here, that SXT provides a foundational dataset for a broad spectrum of whole-cell modeling experiments.

X-ray computed tomography using partially coherent Fresnel diffraction with application to an optical fiber.

A reconstruction algorithm for partially coherent x-ray computed tomography (XCT) including Fresnel diffraction is developed and applied to an optical fiber. The algorithm is applicable to a high-resolution tube-based laboratory-scale x-ray tomography instrument. The computing time is only a few times longer than the projective counterpart. The algorithm is used to reconstruct, with projections and diffraction, a tilt series acquired at the micrometer scale of a graded-index optical fiber using maximum likelihood and a Bayesian method based on the work of Bouman and Sauer. The inclusion of Fresnel diffraction removes some reconstruction artifacts and use of a Bayesian prior probability distribution removes others, resulting in a substantially more accurate reconstruction.

Imaging cell morphology and physiology using X-rays.

Morphometric measurements, such as quantifying cell shape, characterizing sub-cellular organization, and probing cell-cell interactions, are fundamental in cell biology and clinical medicine. Until quite recently, the main source of morphometric data on cells has been light- and electron-based microscope images. However, many technological advances have propelled X-ray microscopy into becoming another source of high-quality morphometric information. Here, we review the status of X-ray microscopy as a quantitative biological imaging modality. We also describe the combination of X-ray microscopy data with information from other modalities to generate polychromatic views of biological systems. For example, the amalgamation of molecular localization data, from fluorescence microscopy or spectromicroscopy, with structural information from X-ray tomography. This combination of data from the same specimen generates a more complete picture of the system than that can be obtained by a single microscopy method. Such multimodal combinations greatly enhance our understanding of biology by combining physiological and morphological data to create models that more accurately reflect the complexities of life.

PSF correction in soft X-ray tomography.

In this article, we introduce a linear approximation of the forward model of soft X-ray tomography, such that the reconstruction is solvable by standard iterative schemes. This linear model takes into account the three-dimensional point spread function (PSF) of the optical system, which consequently enhances the reconstruction of data. The feasibility of the model is demonstrated on both simulated and experimental data, based on theoretically estimated and experimentally measured PSFs.

Mesoscale imaging with cryo-light and X-rays: Larger than molecular machines, smaller than a cell.

In the context of cell biology, the term mesoscale describes length scales ranging from that of an individual cell, down to the size of the molecular machines. In this spatial regime, small building blocks self-organise to form large, functional structures. A comprehensive set of rules governing mesoscale self-organisation has not been established, making the prediction of many cell behaviours difficult, if not impossible. Our knowledge of mesoscale biology comes from experimental data, in particular, imaging. Here, we explore the application of soft X-ray tomography (SXT) to imaging the mesoscale, and describe the structural insights this technology can generate. We also discuss how SXT imaging is complemented by the addition of correlative fluorescence data measured from the same cell. This combination of two discrete imaging modalities produces a 3D view of the cell that blends high-resolution structural information with precise molecular localisation data.

Porous structure of fibre networks formed by a foaming process: a comparative study of different characterization techniques.

Recent developments in making fibre materials using the foam-forming technology have raised a need to characterize the porous structure at low material density. In order to find an effective choice among all structure-characterization methods, both two-dimensional and three-dimensional techniques were used to explore the porous structure of foam-formed samples made with two different types of cellulose fibre. These techniques included X-ray microtomography, scanning electron microscopy, light microscopy, direct surface imaging using a CCD camera and mercury intrusion porosimetry. The mean pore radius for a varying type of fibre and for varying foam properties was described similarly by all imaging methods. X-ray microtomography provided the most extensive information about the sheet structure, and showed more pronounced effects of varying foam properties than the two-dimensional imaging techniques. The two-dimensional methods slightly underestimated the mean pore size of samples containing stiff CTMP fibres with void radii exceeding 100 µm, and overestimated the pore size for the samples containing flexible kraft fibres with all void radii below 100 µm. The direct rapid surface imaging with a CCD camera showed surprisingly strong agreement with the other imaging techniques. Mercury intrusion porosimetry was able to characterize pore sizes also in the submicron region and led to an increased relative volume of the pores in the range of the mean bubble size of the foam. This may be related to the penetration channels created by the foam-fibre interaction.

Nitrogen-fixing organelle in a marine alga.

Symbiotic interactions were key to the evolution of chloroplast and mitochondria organelles, which mediate carbon and energy metabolism in eukaryotes. Biological nitrogen fixation, the reduction of abundant atmospheric nitrogen gas (N2) to biologically available ammonia, is a key metabolic process performed exclusively by prokaryotes. Candidatus Atelocyanobacterium thalassa, or UCYN-A, is a metabolically streamlined N2-fixing cyanobacterium previously reported to be an endosymbiont of a marine unicellular alga. Here we show that UCYN-A has been tightly integrated into algal cell architecture and organellar division and that it imports proteins encoded by the algal genome. These are characteristics of organelles and show that UCYN-A has evolved beyond endosymbiosis and functions as an early evolutionary stage N2-fixing organelle, or "nitroplast."

Loss of ZNF148 enhances insulin secretion in human pancreatic ß cells.

Insulin secretion from pancreatic ß cells is essential to the maintenance of glucose homeostasis. Defects in this process result in diabetes. Identifying genetic regulators that impair insulin secretion is crucial for the identification of novel therapeutic targets. Here, we show that reduction of ZNF148 in human islets, and its deletion in stem cell-derived ß cells (SC-ß cells), enhances insulin secretion. Transcriptomics of ZNF148-deficient SC-ß cells identifies increased expression of annexin and S100 genes whose proteins form tetrameric complexes involved in regulation of insulin vesicle trafficking and exocytosis. ZNF148 in SC-ß cells prevents translocation of annexin A2 from the nucleus to its functional place at the cell membrane via direct repression of S100A16 expression. These findings point to ZNF148 as a regulator of annexin-S100 complexes in human ß cells and suggest that suppression of ZNF148 may provide a novel therapeutic strategy to enhance insulin secretion.

Automated quantification of vacuole fusion and lipophagy in Saccharomyces cerevisiae from fluorescence and cryo-soft X-ray microscopy data using deep learning.

During starvation in the yeast Saccharomyces cerevisiae vacuolar vesicles fuse and lipid droplets (LDs) can become internalized into the vacuole in an autophagic process named lipophagy. There is a lack of tools to quantitatively assess starvation-induced vacuole fusion and lipophagy in intact cells with high resolution and throughput. Here, we combine soft X-ray tomography (SXT) with fluorescence microscopy and use a deep-learning computational approach to visualize and quantify these processes in yeast. We focus on yeast homologs of mammalian NPC1 (NPC intracellular cholesterol transporter 1; Ncr1 in yeast) and NPC2 proteins, whose dysfunction leads to Niemann Pick type C (NPC) disease in humans. We developed a convolutional neural network (CNN) model which classifies fully fused versus partially fused vacuoles based on fluorescence images of stained cells. This CNN, named Deep Yeast Fusion Network (DYFNet), revealed that cells lacking Ncr1 (ncr1∆ cells) or Npc2 (npc2∆ cells) have a reduced capacity for vacuole fusion. Using a second CNN model, we implemented a pipeline named LipoSeg to perform automated instance segmentation of LDs and vacuoles from high-resolution reconstructions of X-ray tomograms. From that, we obtained 3D renderings of LDs inside and outside of the vacuole in a fully automated manner and additionally measured droplet volume, number, and distribution. We find that ncr1∆ and npc2∆ cells could ingest LDs into vacuoles normally but showed compromised degradation of LDs and accumulation of lipid vesicles inside vacuoles. Our new method is versatile and allows for analysis of vacuole fusion, droplet size and lipophagy in intact cells.Abbreviations: BODIPY493/503: 4,4-difluoro-1,3,5,7,8-pentamethyl-4-bora-3a,4a-diaza-s-Indacene; BPS: bathophenanthrolinedisulfonic acid disodium salt hydrate; CNN: convolutional neural network; DHE; dehydroergosterol; npc2∆, yeast deficient in Npc2; DSC, Dice similarity coefficient; EM, electron microscopy; EVs, extracellular vesicles; FIB-SEM, focused ion beam milling-scanning electron microscopy; FM 4-64, N-(3-triethylammoniumpropyl)-4-(6-[4-{diethylamino} phenyl] hexatrienyl)-pyridinium dibromide; LDs, lipid droplets; Ncr1, yeast homolog of human NPC1 protein; ncr1∆, yeast deficient in Ncr1; NPC, Niemann Pick type C; NPC2, Niemann Pick type C homolog; OD600, optical density at 600 nm; ReLU, rectifier linear unit; PPV, positive predictive value; NPV, negative predictive value; MCC, Matthews correlation coefficient; SXT, soft X-ray tomography; UV, ultraviolet; YPD, yeast extract peptone dextrose.

Maximizing microbial bioproduction from sustainable carbon sources using iterative systems engineering.

Maximizing the production of heterologous biomolecules is a complex problem that can be addressed with a systems-level understanding of cellular metabolism and regulation. Specifically, growth-coupling approaches can increase product titers and yields and also enhance production rates. However, implementing these methods for non-canonical carbon streams is challenging due to gaps in metabolic models. Over four design-build-test-learn cycles, we rewire Pseudomonas putida KT2440 for growth-coupled production of indigoidine from para-coumarate. We explore 4,114 potential growth-coupling solutions and refine one design through laboratory evolution and ensemble data-driven methods. The final growth-coupled strain produces 7.3 g/L indigoidine at 77% maximum theoretical yield in para-coumarate minimal medium. The iterative use of growth-coupling designs and functional genomics with experimental validation was highly effective and agnostic to specific hosts, carbon streams, and final products and thus generalizable across many systems.

Aberrant phase separation is a common killing strategy of positively charged peptides in biology and human disease.

Positively charged repeat peptides are emerging as key players in neurodegenerative diseases. These peptides can perturb diverse cellular pathways but a unifying framework for how such promiscuous toxicity arises has remained elusive. We used mass-spectrometry-based proteomics to define the protein targets of these neurotoxic peptides and found that they all share similar sequence features that drive their aberrant condensation with these positively charged peptides. We trained a machine learning algorithm to detect such sequence features and unexpectedly discovered that this mode of toxicity is not limited to human repeat expansion disorders but has evolved countless times across the tree of life in the form of cationic antimicrobial and venom peptides. We demonstrate that an excess in positive charge is necessary and sufficient for this killer activity, which we name 'polycation poisoning'. These findings reveal an ancient and conserved mechanism and inform ways to leverage its design rules for new generations of bioactive peptides.

Integrative structural modelling and visualisation of a cellular organelle.

Models of insulin secretory vesicles from pancreatic beta cells have been created using the cellPACK suite of tools to research, curate, construct and visualise the current state of knowledge. The model integrates experimental information from proteomics, structural biology, cryoelectron microscopy and X-ray tomography, and is used to generate models of mature and immature vesicles. A new method was developed to generate a confidence score that reconciles inconsistencies between three available proteomes using expert annotations of cellular localisation. The models are used to simulate soft X-ray tomograms, allowing quantification of features that are observed in experimental tomograms, and in turn, allowing interpretation of X-ray tomograms at the molecular level.

Soft X-ray Tomography Reveals HSV-1-Induced Remodeling of Human B Cells.

Upon infection, viruses hijack the cell machinery and remodel host cell structures to utilize them for viral proliferation. Since viruses are about a thousand times smaller than their host cells, imaging virus-host interactions at high spatial resolution is like looking for a needle in a haystack. Scouting gross cellular changes with fluorescent microscopy is only possible for well-established viruses, where fluorescent tagging is developed. Soft X-ray tomography (SXT) offers 3D imaging of entire cells without the need for chemical fixation or labeling. Here, we use full-rotation SXT to visualize entire human B cells infected by the herpes simplex virus 1 (HSV-1). We have mapped the temporospatial remodeling of cells during the infection and observed changes in cellular structures, such as the presence of cytoplasmic stress granules and multivesicular structures, formation of nuclear virus-induced dense bodies, and aggregates of capsids. Our results demonstrate the power of SXT imaging for scouting virus-induced changes in infected cells and understanding the orchestration of virus-host remodeling quantitatively.

A protocol for full-rotation soft X-ray tomography of single cells.

The protocol describes step-by-step sample preparation, data acquisition, and segmentation of cellular organelles with soft X-ray tomography. It is designed for microscopes built to perform full-rotation data acquisition on specimens in cylindrical sample holders, such as the XM-2 microscope at the Advanced Light Source, LBNL; however, it might be generalized for similar sample holder designs for both synchrotron and table-top microscopes. For complete details on the use and execution of this profile, please refer to Loconte et al. (2021).