Automated segmentation of cell organelles in volume electron microscopy using deep learning.

Recent advances in computing power triggered the use of artificial intelligence in image analysis in life sciences. To train these algorithms, a large enough set of certified labeled data is required. The trained neural network is then capable of producing accurate instance segmentation results that will then need to be re-assembled into the original dataset: the entire process requires substantial expertise and time to achieve quantifiable results. To speed-up the process, from cell organelle detection to quantification across electron microscopy modalities, we propose a deep-learning based approach for fast automatic outline segmentation (FAMOUS), that involves organelle detection combined with image morphology, and 3D meshing to automatically segment, visualize and quantify cell organelles within volume electron microscopy datasets. From start to finish, FAMOUS provides full segmentation results within a week on previously unseen datasets. FAMOUS was showcased on a HeLa cell dataset acquired using a focused ion beam scanning electron microscope, and on yeast cells acquired by transmission electron tomography. RESEARCH HIGHLIGHTS: Introducing a rapid, multimodal machine-learning workflow for the automatic segmentation of 3D cell organelles. Successfully applied to a variety of volume electron microscopy datasets and cell lines. Outperforming manual segmentation methods in time and accuracy. Enabling high-throughput quantitative cell biology.

U-Net based vessel segmentation for murine brains with small micro-magnetic resonance imaging reference datasets.

Identification and quantitative segmentation of individual blood vessels in mice visualized with preclinical imaging techniques is a tedious, manual or semiautomated task that can require weeks of reviewing hundreds of levels of individual data sets. Preclinical imaging, such as micro-magnetic resonance imaging (µMRI) can produce tomographic datasets of murine vasculature across length scales and organs, which is of outmost importance to study tumor progression, angiogenesis, or vascular risk factors for diseases such as Alzheimer's. Training a neural network capable of accurate segmentation results requires a sufficiently large amount of labelled data, which takes a long time to compile. Recently, several reasonably automated approaches have emerged in the preclinical context but still require significant manual input and are less accurate than the deep learning approach presented in this paper-quantified by the Dice score. In this work, the implementation of a shallow, three-dimensional U-Net architecture for the segmentation of vessels in murine brains is presented, which is (1) open-source, (2) can be achieved with a small dataset (in this work only 8 µMRI imaging stacks of mouse brains were available), and (3) requires only a small subset of labelled training data. The presented model is evaluated together with two post-processing methodologies using a cross-validation, which results in an average Dice score of 61.34% in its best setup. The results show, that the methodology is able to detect blood vessels faster and more reliably compared to state-of-the-art vesselness filters with an average Dice score of 43.88% for the used dataset.

CryoEM reveals that ribosomes in microsporidian spores are locked in a dimeric hibernating state.

Translational control is an essential process for the cell to adapt to varying physiological or environmental conditions. To survive adverse conditions such as low nutrient levels, translation can be shut down almost entirely by inhibiting ribosomal function. Here we investigated eukaryotic hibernating ribosomes from the microsporidian parasite Spraguea lophii in situ by a combination of electron cryo-tomography and single-particle electron cryo-microscopy. We show that microsporidian spores contain hibernating ribosomes that are locked in a dimeric (100S) state, which is formed by a unique dimerization mechanism involving the beak region. The ribosomes within the dimer are fully assembled, suggesting that they are ready to be activated once the host cell is invaded. This study provides structural evidence for dimerization acting as a mechanism for ribosomal hibernation in microsporidia, and therefore demonstrates that eukaryotes utilize this mechanism in translational control.

Lossy Image Compression in a Preclinical Multimodal Imaging Study.

The growing use of multimodal high-resolution volumetric data in pre-clinical studies leads to challenges related to the management and handling of the large amount of these datasets. Contrarily to the clinical context, currently there are no standard guidelines to regulate the use of image compression in pre-clinical contexts as a potential alleviation of this problem. In this work, the authors study the application of lossy image coding to compress high-resolution volumetric biomedical data. The impact of compression on the metrics and interpretation of volumetric data was quantified for a correlated multimodal imaging study to characterize murine tumor vasculature, using volumetric high-resolution episcopic microscopy (HREM), micro-computed tomography (µCT), and micro-magnetic resonance imaging (µMRI). The effects of compression were assessed by measuring task-specific performances of several biomedical experts who interpreted and labeled multiple data volumes compressed at different degrees. We defined trade-offs between data volume reduction and preservation of visual information, which ensured the preservation of relevant vasculature morphology at maximum compression efficiency across scales. Using the Jaccard Index (JI) and the average Hausdorff Distance (HD) after vasculature segmentation, we could demonstrate that, in this study, compression that yields to a 256-fold reduction of the data size allowed to keep the error induced by compression below the inter-observer variability, with minimal impact on the assessment of the tumor vasculature across scales.

Shed light on photosynthetic organisms: a physical perspective to correct light measurements.

The requirements for novel and innovative production systems expedite research on light emitting diode-based illumination in a life science context. In course of these rapid developments, the scientific community is in need of a consensus regarding to the characterization and presentation of the applied lighting conditions. This publication aims to establish a basic understanding of photon physics and propose guidelines for the conclusive usage of light related quantities. To illustrate the challenges in data handling, six different light sources were measured and characterized. Furthermore, a stepwise conversion within and in-between physical systems is presented, and an opportunity to extract information from weak data sets is demonstrated. The proposed calculations indicated flexibility in data handling, but revealed partial inaccuracy for colored light emitting diodes with spectral power distribution maxima far-off 550 nm compared to spectrometer-based measurements and conversions. Furthermore, it could be shown, that when comparing light properties, the determination of photometric quantities is incorrect to describe lighting systems for photosynthetic organism and the usage of luxmeter or similar photometric sensors should be avoided. The presented guidelines shall support scientists in applying a consistent and precise characterization of their illumination regimes, tailored to their requirements to avoid ambiguous communication and the generation of incorrect and thus incomparable data based on wrong quantities and units, such as lumen or lux, in future research.

An observational study of wounds treated with hydro-responsive wound dressings.

OBJECTIVE: Acute and hard-to-heal wounds are a significant burden to both a patient's quality of life and resources in healthcare systems. Here, we evaluate the outcomes of a non-comparative case series study in which Ringer's solution-preactivated polyacrylate dressings were used to treat acute and hard-to-heal wounds (the presence of Ringer's solution provides a wound dressing that allows, upon application, the immediate hydration of the underlying wound tissue). METHOD: Patients with acute and hard-to-heal wounds were enrolled into an open-labelled, non-comparative observational study. Patients were treated with Ringer's solution-preactivated polyacrylate dressings to enable wound debridement and wound cleansing for up to 12 weeks. RESULTS: A total of 303 patients were enrolled in the study and 278 were included in the analysis. Wound size decreased, from a median of 3.6cm2 (interquartile range (IQR): 1.2-9.3] at baseline to a median of 2.6cm2 (IQR: 1.1-7.8] at 84 days. Relative wound area reduction (WAR) was 43.1% at 84 days and estimated probability of achievement of a WAR of ≥40% and ≥60% was 68.7% and 53.4%, respectively. Median time to achieve a WAR of ≥40% and ≥60% was 54 days and 75 days, respectively. The median percentage of wound area covered by fibrin had decreased from 50.0% to 10% and granulation tissue had increased from 25% to 50% after 84 days. In addition, periwound skin condition, local signs of infection and pain all showed improvement. The majority of the wounds were assessed as 'healed' or 'better' at the conclusion of the evaluation period. CONCLUSION: Based on the findings of this study, the use of Ringer's solution-preactivated polyacrylate dressings in daily practice has the potential to improve clinical outcomes, including healing, in patients with acute and hard-to-heal wounds.

Biodegradation of different PET variants from food containers by Ideonella sakaiensis.

The accumulation of macro-, micro- and nano-plastic wastes in the environment is a major global concern, as these materials are resilient to degradation processes. However, microorganisms have evolved their own biological means to metabolize these petroleum-derived polymers, e.g., Ideonella sakaiensis has recently been found to be capable of utilizing polyethylene terephthalate (PET) as its sole carbon source. This study aims to prove its potential capacity to biodegrade two commercial PET materials, obtained from food packaging containers. Plastic pieces of different crystallinity were simultaneously introduced to Ideonella sakaiensis during a seven-week lasting investigation. Loss in weight, appearance of plastics, as well as growth of Ideonella sakaiensis-through quantitative real-time PCR-were determined. Both plastics were found enzymatically attacked in a two-stage degradation process, reaching biodegradation capacities of up to 96%. Interestingly, the transparent, high crystallinity PET was almost fully degraded first, followed by the colored low-crystallinity PET. Results of quantitative real-time PCR-based gene copy numbers were found in line with experimental results, thus underlining its potential of this method to be applied in future studies with Ideonella sakaiensis.

High-Resolution Episcopic Microscopy (HREM) in Multimodal Imaging Approaches.

High-resolution episcopic microscopy (HREM) is a three-dimensional (3D) episcopic imaging modality based on the acquisition of two-dimensional (2D) images from the cut surface of a block of tissue embedded in resin. Such images, acquired serially through the entire length/depth of the tissue block, are aligned and stacked for 3D reconstruction. HREM has proven to be specifically advantageous when integrated in correlative multimodal imaging (CMI) pipelines. CMI creates a composite and zoomable view of exactly the same specimen and region of interest by (sequentially) correlating two or more modalities. CMI combines complementary modalities to gain holistic structural, functional, and chemical information of the entire sample and place molecular details into their overall spatiotemporal multiscale context. HREM has an advantage over in vivo 3D imaging techniques on account of better histomorphologic resolution while simultaneously providing volume data. HREM also has certain advantages over ex vivo light microscopy modalities. The latter can provide better cellular resolution but usually covers a limited area or volume of tissue, with limited 3D structural context. HREM has predominantly filled a niche in the phenotyping of embryos and characterisation of anatomic developmental abnormalities in various species. Under the umbrella of CMI, when combined with histopathology in a mutually complementary manner, HREM could find wider application in additional nonclinical and translational areas. HREM, being a modified histology technique, could also be incorporated into specialised preclinical pathology workflows. This review will highlight HREM as a versatile imaging platform in CMI approaches and present its benefits and limitations.

Cross-modality imaging of bisphosphonate-treated murine jawbones.

In this proof-of-principle study, we established and implemented a cross-modality imaging (CMI) pipeline to characterize and compare bisphosphonate (BIS)-treated jawbones of Sprague-Dawley rats after tooth extraction after physical therapies (photobiomodulation and extracorporeal shockwave therapy (PBMT and ESWT)). We showcase the feasibility of such a CMI approach and its compatibility across imaging modalities to probe the same region of interest (ROI) of the same jawbone. Jawbones were imaged in toto in 3D using micro-Computed Tomography to identify ROIs for subsequent sequential 2D analysis using well-established technologies such as Atomic Force Microscopy and Scanning Electron Microscopy, and recent imaging approaches in biomedical settings, such as micro-X-Ray Fluorescence Spectroscopy. By combining these four modalities, multiscale information on the morphology, topography, mechanical stiffness (Young's modulus), and calcium, zinc and phosphorus concentrations of the bone was collected. Based on the CMI pipeline, we characterized and compared the jawbones of a previously published clinically relevant rat model of BIS-related osteonecrosis of the jawbone (BRONJ) before and after treatment with BISs, PBMT and ESWT. While we did not find that physical therapies altered the mechanical and elemental jawbone parameters with significance (probably due to the small sample size of only up to 5 samples per group), both ESWT and PBMT reduced pore thicknesses and bone-to-enamel distances significantly compared to the controls. Although focused on BIS-treated jawbones, the established CMI platform can be beneficial in the study of bone-related diseases in general (such as osteoarthritis or -porosis) to acquire complementary hallmarks and better characterize disease status and alleviation potentials.

Cross-Modality Imaging of Murine Tumor Vasculature-a Feasibility Study.

Tumor vasculature and angiogenesis play a crucial role in tumor progression. Their visualization is therefore of utmost importance to the community. In this proof-of-principle study, we have established a novel cross-modality imaging (CMI) pipeline to characterize exactly the same murine tumors across scales and penetration depths, using orthotopic models of melanoma cancer. This allowed the acquisition of a comprehensive set of vascular parameters for a single tumor. The workflow visualizes capillaries at different length scales, puts them into the context of the overall tumor vessel network and allows quantification and comparison of vessel densities and morphologies by different modalities. The workflow adds information about hypoxia and blood flow rates. The CMI approach includes well-established technologies such as magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), and ultrasound (US), and modalities that are recent entrants into preclinical discovery such as optical coherence tomography (OCT) and high-resolution episcopic microscopy (HREM). This novel CMI platform establishes the feasibility of combining these technologies using an extensive image processing pipeline. Despite the challenges pertaining to the integration of microscopic and macroscopic data across spatial resolutions, we also established an open-source pipeline for the semi-automated co-registration of the diverse multiscale datasets, which enables truly correlative vascular imaging. Although focused on tumor vasculature, our CMI platform can be used to tackle a multitude of research questions in cancer biology.

Multimodality imaging beyond CLEM: Showcases of combined in-vivo preclinical imaging and ex-vivo microscopy to detect murine mural vascular lesions.

In imaging, penetration depth comes at the expense of lateral resolution, which restricts the scope of 3D in-vivo imaging of small animals at micrometer resolution. Bioimaging will need to expand beyond correlative light and electron microscopy (CLEM) approaches to combine insights about in-vivo dynamics in a physiologically relevant 3D environment with ex-vivo information at micrometer resolution (or beyond) within the spatial, structural and biochemical contexts. Our report demonstrates the immense potential for biomedical discovery and diagnosis made available by bridging preclinical in-vivo imaging with ex-vivo biological microscopy to zoom in from the whole organism to individual structures and by adding localized spectroscopic information to structural and functional information. We showcase the use of two novel imaging pipelines to zoom into mural lesions (occlusions/hyperplasia and micro-calcifications) in murine vasculature in a truly correlative manner, that is using exactly the same animal for all integrated imaging modalities. This correlated multimodality imaging (CMI) approach includes well-established technologies such as Positron Emission Tomography (microPET), Autoradiography, Magnetic Resonance Imaging (microMRI) and Computed Tomography (microCT), and imaging approaches that are more novel in the biomedical setting, such as X-Ray Fluorescence Spectroscopy (microXRF) and High Resolution Episcopic Microscopy (HREM). Although the current pipelines are focused on mural lesions, they would also be beneficial in preclinical and clinical investigations of vascular diseases in general.

Correlative multimodal imaging: Building a community.

Few would have thought that when Porter and colleagues used light microscopy to target their cell of interest to be analyzed in the electron microscope in the 1940s, that Correlative Imaging would develop into the thriving field it is today. Even though the first use of Correlative Light Electron Microscopy (CLEM) was established in the 1940s, it is only since the year 2000 that there has been a real surge in the application of CLEM technology. The power of CLEM is recognized in the scientific community as evidenced by the growing number of publications and dedicated sessions at scientific meetings. The field is also broadening, incorporating a multitude of other techniques including preclinical research and diagnostics, and slowly but surely the overarching field of Correlative Multimodality Imaging (CMI) is taking its place as an established technique and a research area in its own right. In this chapter, we will look at the initiatives that are being developed within the scientific world to build a coherent CMI community, with a particular emphasis on the developments in Europe. To achieve this aim, the community will need to design mechanisms for the interdisciplinary exchange of knowledge and benefits, set up training schemes, and develop standards for CMI technology and its data.

Impact of Processed Food (Canteen and Oil Wastes) on the Development of Black Soldier Fly (Hermetia illucens) Larvae and Their Gut Microbiome Functions.

Canteens represent an essential food supply hub for educational institutions, companies, and business parks. Many people in these locations rely on a guaranteed service with consistent quality. It is an ongoing challenge to satisfy the demand for sufficient serving numbers, portion sizes, and menu variations to cover food intolerances and different palates of customers. However, overestimating this demand or fluctuating quality of dishes leads to an inevitable loss of unconsumed food due to leftovers. In this study, the food waste fraction of canteen leftovers was identified as an optimal diet for black soldier fly (Hermetia illucens) larvae based on 50% higher consumption and 15% higher waste reduction indices compared with control chicken feed diet. Although the digestibility of food waste was nearly twice as high, the conversion efficiency of ingested and digested chicken feed remains unparalleled (17.9 ± 0.6 and 37.5 ± 0.9 in CFD and 7.9 ± 0.9 and 9.6 ± 1.0 in FWD, respectively). The oil separator waste fraction, however, inhibited biomass gain by at least 85% and ultimately led to a larval mortality of up to 96%. In addition to monitoring larval development, we characterized physicochemical properties of pre- and post-process food waste substrates. High-throughput amplicon sequencing identified Firmicutes, Proteobacteria, and Bacteroidota as the most abundant phyla, and Morganella, Acinetobacter, and certain Lactobacillales species were identified as indicator species. By using metagenome imputation, we additionally gained insights into the functional spectrum of gut microbial communities. We anticipate that the results will contribute to the development of decentralized waste-management sites that make use of larvae to process food waste as it has become common practice for biogas plants.

Anharmonic Molecular Motion Drives Resonance Energy Transfer in peri-Arylene Dyads.

Spectral and dynamical properties of molecular donor-acceptor systems strongly depend on the steric arrangement of the constituents with exciton coupling J as a key control parameter. In the present work we study two peri-arylene based dyads with orthogonal and parallel transition dipoles for donor and acceptor moieties, respectively. We show that the anharmonic multi-well character of the orthogonal dyad's intramolecular potential explains findings from both stationary and time-resolved absorption experiments. While for a parallel dyad, standard quantum chemical estimates of J at 0 K are in good agreement with experimental observations, J becomes vanishingly small for the orthogonal dyad, in contrast to its ultrafast experimental transfer times. This discrepancy is not resolved even by accounting for harmonic fluctuations along normal coordinates. We resolve this problem by supplementing quantum chemical approaches with dynamical sampling of fluctuating geometries. In contrast to the moderate Gaussian fluctuations of J for the parallel dyad, fluctuations for the orthogonal dyad are found to follow non-Gaussian statistics leading to significantly higher effective J in good agreement with experimental observations. In effort to apply a unified framework for treating the dynamics of optical coherence and excitonic populations of both dyads, we employ a vibronic approach treating electronic and selected vibrational degrees on an equal footing. This vibronic model is used to model absorption and fluorescence spectra as well as donor-acceptor transport dynamics and covers the more traditional categories of Förster and Redfield transport as limiting cases.

The Core Gut Microbiome of Black Soldier Fly (Hermetia illucens) Larvae Raised on Low-Bioburden Diets.

An organism's gut microbiome handles most of the metabolic processes associated with food intake and digestion but can also strongly affect health and behavior. A stable microbial core community in the gut provides general metabolic competences for substrate degradation and is robust against extrinsic disturbances like changing diets or pathogens. Black Soldier Fly larvae (BSFL; Hermetia illucens) are well known for their ability to efficiently degrade a wide spectrum of organic materials. The ingested substrates build up the high fat and protein content in their bodies that make the larvae interesting for the animal feedstuff industry. In this study, we subjected BSFL to three distinct types of diets carrying a low bioburden and assessed the diets' impact on larval development and on the composition of the bacterial and archaeal gut community. No significant impact on the gut microbiome across treatments pointed us to the presence of a predominant core community backed by a diverse spectrum of low-abundance taxa. Actinomyces spp., Dysgonomonas spp., and Enterococcus spp. as main members of this community provide various functional and metabolic skills that could be crucial for the thriving of BSFL in various environments. This indicates that the type of diet could play a lesser role in guts of BSFL than previously assumed and that instead a stable autochthonous collection of bacteria provides the tools for degrading of a broad range of substrates. Characterizing the interplay between the core gut microbiome and BSFL helps to understand the involved degradation processes and could contribute to further improving large-scale BSFL rearing.

FRET in Dyads with Orthogonal Chromophores and Minimal Spectral Overlap.

A dyad of orthogonally arranged chromophores of benzoperylenehexacarboxylictrisimide (energy donor, D) and terrylenetetracarboxylic bisimide (energy acceptor, A) was synthesized where a quantitative energy transfer (FRET) from D to A was found, although not only are both transition moments orthogonally arranged but the spectral overlap between the fluorescence of the energy donor and the absorption of the acceptor is also small. Even an appreciable further diminishing of the overlap in a dyad with phenylbenzoxazole as the donor could not inhibit the energy transfer. Thus, the application of the FRET theory to real systems is estimated to be limited where molecular vibrations seem to play a key role in the energy transfer.

Correction: Influence of three artificial light sources on oviposition and half-life of the Black Soldier Fly, Hermetia illucens (Diptera: Stratiomyidae): Improving small-scale indoor rearing.

[This corrects the article DOI: 10.1371/journal.pone.0197896.].

Regulation of Oxygenic Photosynthesis during Trophic Transitions in the Green Alga Chromochloris zofingiensis.

Light and nutrients are critical regulators of photosynthesis and metabolism in plants and algae. Many algae have the metabolic flexibility to grow photoautotrophically, heterotrophically, or mixotrophically. Here, we describe reversible Glc-dependent repression/activation of oxygenic photosynthesis in the unicellular green alga Chromochloris zofingiensis. We observed rapid and reversible changes in photosynthesis, in the photosynthetic apparatus, in thylakoid ultrastructure, and in energy stores including lipids and starch. Following Glc addition in the light, C. zofingiensis shuts off photosynthesis within days and accumulates large amounts of commercially relevant bioproducts, including triacylglycerols and the high-value nutraceutical ketocarotenoid astaxanthin, while increasing culture biomass. RNA sequencing reveals reversible changes in the transcriptome that form the basis of this metabolic regulation. Functional enrichment analyses show that Glc represses photosynthetic pathways while ketocarotenoid biosynthesis and heterotrophic carbon metabolism are upregulated. Because sugars play fundamental regulatory roles in gene expression, physiology, metabolism, and growth in both plants and animals, we have developed a simple algal model system to investigate conserved eukaryotic sugar responses as well as mechanisms of thylakoid breakdown and biogenesis in chloroplasts. Understanding regulation of photosynthesis and metabolism in algae could enable bioengineering to reroute metabolism toward beneficial bioproducts for energy, food, pharmaceuticals, and human health.