Computational image analysis reveals the structural complexity of Toxoplasma gondii tissue cysts

AbstractToxoplasma gondii is an obligate intracellular parasite infecting up to one third of the human population. The central event in the pathogenesis of toxoplasmosis is the conversion of tachyzoites into encysted bradyzoites. A novel approach to analyze the structure of in vivo-derived tissue cysts may be the increasingly used computational image analysis. The objective of this study was to quantify the geometrical complexity of T. gondii cysts by morphological, particle, and fractal analysis, as well as to determine if and how it is impacted by parasite strain, cyst age, and host factors. Analyses were performed on 31 images of T. gondii brain cysts of four type-2 strains (the reference Me49 strain and three local isolates, named BGD1, BGD14, and BGD26) using ImageJ software package. The parameters of interest included diameter, circularity, relative particle count (RPC), fractal dimension (FD), lacunarity, and packing density (PD). Although cyst diameter varied widely, its negative correlation with RPC was observed. Circularity was remarkably close to 1, indicating that the shape of the brain cysts was a perfect circle. RPC, FD, and PD did not vary among cysts of different strains, age, and derived from mice of different genetic background. Conversely, lacunarity, which is a measure of heterogeneity, was significantly lower for BGD1 strain vs. all other strains, and higher for Me49 vs. BGD14 and BGD26, but did not differ among Me49 cysts of different age, and derived from genetically different mice. This study is the first application of fractal analysis in describing the structural complexity of T. gondii cysts. Despite all the differences among the analyzed cysts, most parameters remained conserved. Fractal analysis is a novel and widely accessible approach, which along with particle analysis may be applied to gain further insight into T. gondii cyst morphology.

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Computational image analysis reveals the structural complexity of Toxoplasma gondii tissue cysts

PLoS ONE ◽

10.1371/journal.pone.0234169 ◽

2020 ◽

Vol 15 (8) ◽

pp. e0234169

Author(s):

Neda Bauman ◽

Andjelija Ilić ◽

Olivera Lijeskić ◽

Aleksandra Uzelac ◽

Ivana Klun ◽

...

Keyword(s):

Image Analysis ◽

Toxoplasma Gondii ◽

Structural Complexity ◽

Computational Image Analysis

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Programmable in vitro Co-Encapsidation of Guest Proteins Inside Protein Nanocages

10.26434/chemrxiv.5844393 ◽

2018 ◽

Author(s):

Noor H. Dashti ◽

Rufika S. Abidin ◽

Frank Sainsbury

Keyword(s):

Self Assembly ◽

Mammalian Cells ◽

Resonance Energy Transfer ◽

Resonance Energy ◽

Super Resolution ◽

Cell Engineering ◽

Particle Analysis ◽

Protein Cages

Bioinspired self-sorting and self-assembling systems using engineered versions of natural protein cages have been developed for biocatalysis and therapeutic delivery. The packaging and intracellular delivery of guest proteins is of particular interest for both in vitro and in vivo cell engineering. However, there is a lack of platforms in bionanotechnology that combine programmable guest protein encapsidation with efficient intracellular uptake. We report a minimal peptide anchor for in vivo self-sorting of cargo-linked capsomeres of the Murine polyomavirus (MPyV) major coat protein that enables controlled encapsidation of guest proteins by in vitro self-assembly. Using Förster resonance energy transfer (FRET) we demonstrate the flexibility in this system to support co-encapsidation of multiple proteins. Complementing these ensemble measurements with single particle analysis by super-resolution microscopy shows that the stochastic nature of co-encapsidation is an overriding principle. This has implications for the design and deployment of both native and engineered self-sorting encapsulation systems and for the assembly of infectious virions. Taking advantage of the encoded affinity for sialic acids ubiquitously displayed on the surface of mammalian cells, we demonstrate the ability of self-assembled MPyV virus-like particles to mediate efficient delivery of guest proteins to the cytosol of primary human cells. This platform for programmable co-encapsidation and efficient cytosolic delivery of complementary biomolecules therefore has enormous potential in cell engineering.

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Enhanced Both in vitro and in vivo Kinetics by SLNs Induced Transdermal System of Furosemide: A Novel Approach

Recent Patents on Drug Delivery & Formulation ◽

10.2174/1872211311666171129115441 ◽

2018 ◽

Vol 11 (3) ◽

pp. 187-197

Author(s):

Revathi Mannam ◽

Indira M. Yallamalli

Keyword(s):

Novel Approach ◽

In Vivo Kinetics

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Marker for the pre-clinical development of bone substitute materials

Current Directions in Biomedical Engineering ◽

10.1515/cdbme-2017-0151 ◽

2017 ◽

Vol 3 (2) ◽

pp. 711-715

Author(s):

Michael de Wild ◽

Simon Zimmermann ◽

Marcel Obrecht ◽

Michel Dard

Keyword(s):

Bone Graft ◽

Mechanical Stability ◽

Clinical Performance ◽

Ex Vivo ◽

Region Of Interest ◽

Defect Site ◽

Novel Approach ◽

Bone Substitute Materials ◽

Clinical Experiments

AbstractThin mechanically stable Ti-cages have been developed for the in-vivo application as X-ray and histology markers for the optimized evaluation of pre-clinical performance of bone graft materials. A metallic frame defines the region of interest during histological investigations and supports the identification of the defect site. This standardization of the procedure enhances the quality of pre-clinical experiments. Different models of thin metallic frameworks were designed and produced out of titanium by additive manufacturing (Selective Laser Melting). The productibility, the mechanical stability, the handling and suitability of several frame geometries were tested during surgery in artificial and in ex-vivo bone before a series of cages was preclinically investigated in the female Göttingen minipigs model. With our novel approach, a flexible process was established that can be adapted to the requirements of any specific animal model and bone graft testing.

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Development of a semi-automated segmentation tool for high frequency ultrasound image analysis of mouse echocardiograms

Scientific Reports ◽

10.1038/s41598-021-85971-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kristi Powers ◽

Raymond Chang ◽

Justin Torello ◽

Rhonda Silva ◽

Yannick Cadoret ◽

...

Keyword(s):

Image Analysis ◽

Automated Analysis ◽

Structure And Function ◽

Ultrasound Images ◽

Cardiac Structure ◽

Short Axis ◽

Pixel Intensity ◽

Cardiac Structure And Function ◽

And Function

AbstractEchocardiography is a widely used and clinically translatable imaging modality for the evaluation of cardiac structure and function in preclinical drug discovery and development. Echocardiograms are among the first in vivo diagnostic tools utilized to evaluate the heart due to its relatively low cost, high throughput acquisition, and non-invasive nature; however lengthy manual image analysis, intra- and inter-operator variability, and subjective image analysis presents a challenge for reproducible data generation in preclinical research. To combat the image-processing bottleneck and address both variability and reproducibly challenges, we developed a semi-automated analysis algorithm workflow to analyze long- and short-axis murine left ventricle (LV) ultrasound images. The long-axis B-mode algorithm executes a script protocol that is trained using a reference library of 322 manually segmented LV ultrasound images. The short-axis script was engineered to analyze M-mode ultrasound images in a semi-automated fashion using a pixel intensity evaluation approach, allowing analysts to place two seed-points to triangulate the local maxima of LV wall boundary annotations. Blinded operator evaluation of the semi-automated analysis tool was performed and compared to the current manual segmentation methodology for testing inter- and intra-operator reproducibility at baseline and after a pharmacologic challenge. Comparisons between manual and semi-automatic derivation of LV ejection fraction resulted in a relative difference of 1% for long-axis (B-mode) images and 2.7% for short-axis (M-mode) images. Our semi-automatic workflow approach reduces image analysis time and subjective bias, as well as decreases inter- and intra-operator variability, thereby enhancing throughput and improving data quality for pre-clinical in vivo studies that incorporate cardiac structure and function endpoints.

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Artificial Tumor Microenvironments in Neuroblastoma

Cancers ◽

10.3390/cancers13071629 ◽

2021 ◽

Vol 13 (7) ◽

pp. 1629

Author(s):

Colin H. Quinn ◽

Andee M. Beierle ◽

Elizabeth A. Beierle

Keyword(s):

Extracellular Matrix ◽

Three Dimensional ◽

Therapeutic Interventions ◽

3D Bioprinting ◽

Culture Studies ◽

In Vivo Models ◽

Novel Treatments ◽

Tumor Microenvironments ◽

Novel Approach

In the quest to advance neuroblastoma therapeutics, there is a need to have a deeper understanding of the tumor microenvironment (TME). From extracellular matrix proteins to tumor associated macrophages, the TME is a robust and diverse network functioning in symbiosis with the solid tumor. Herein, we review the major components of the TME including the extracellular matrix, cytokines, immune cells, and vasculature that support a more aggressive neuroblastoma phenotype and encumber current therapeutic interventions. Contemporary treatments for neuroblastoma are the result of traditional two-dimensional culture studies and in vivo models that have been translated to clinical trials. These pre-clinical studies are costly, time consuming, and neglect the study of cofounding factors such as the contributions of the TME. Three-dimensional (3D) bioprinting has become a novel approach to studying adult cancers and is just now incorporating portions of the TME and advancing to study pediatric solid. We review the methods of 3D bioprinting, how researchers have included TME pieces into the prints, and highlight present studies using neuroblastoma. Ultimately, incorporating the elements of the TME that affect neuroblastoma responses to therapy will improve the development of innovative and novel treatments. The use of 3D bioprinting to achieve this aim will prove useful in developing optimal therapies for children with neuroblastoma.

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Machine learning-based classification of mitochondrial morphology in primary neurons and brain

Scientific Reports ◽

10.1038/s41598-021-84528-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Garrett M. Fogo ◽

Anthony R. Anzell ◽

Kathleen J. Maheras ◽

Sarita Raghunayakula ◽

Joseph M. Wider ◽

...

Keyword(s):

Image Analysis ◽

Cortical Neurons ◽

Mitochondrial Dynamics ◽

Automated Image Analysis ◽

Mitochondrial Morphology ◽

Analysis Pipeline ◽

Genetic Ablation ◽

Block Face

AbstractThe mitochondrial network continually undergoes events of fission and fusion. Under physiologic conditions, the network is in equilibrium and is characterized by the presence of both elongated and punctate mitochondria. However, this balanced, homeostatic mitochondrial profile can change morphologic distribution in response to various stressors. Therefore, it is imperative to develop a method that robustly measures mitochondrial morphology with high accuracy. Here, we developed a semi-automated image analysis pipeline for the quantitation of mitochondrial morphology for both in vitro and in vivo applications. The image analysis pipeline was generated and validated utilizing images of primary cortical neurons from transgenic mice, allowing genetic ablation of key components of mitochondrial dynamics. This analysis pipeline was further extended to evaluate mitochondrial morphology in vivo through immunolabeling of brain sections as well as serial block-face scanning electron microscopy. These data demonstrate a highly specific and sensitive method that accurately classifies distinct physiological and pathological mitochondrial morphologies. Furthermore, this workflow employs the use of readily available, free open-source software designed for high throughput image processing, segmentation, and analysis that is customizable to various biological models.

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HSP90-dependent PUS7 overexpression facilitates the metastasis of colorectal cancer cells by regulating LASP1 abundance

Journal of Experimental & Clinical Cancer Research ◽

10.1186/s13046-021-01951-5 ◽

2021 ◽

Vol 40 (1) ◽

Author(s):

Dan Song ◽

Ming Guo ◽

Shuai Xu ◽

Xiaotian Song ◽

Bin Bai ◽

...

Keyword(s):

Colorectal Cancer ◽

Intellectual Development ◽

Molecular Mechanisms ◽

Hsp90 Inhibitor ◽

Pseudouridine Synthase ◽

Novel Approach ◽

Cell Metastasis ◽

Underlying Mechanisms

Abstract Background Pseudouridine synthase (PUS) 7 is a member of the PUS family that catalyses pseudouridine formation. It has been shown to be involved in intellectual development and haematological malignancies. Nevertheless, the role and the underlying molecular mechanisms of PUS7 in solid tumours, such as colorectal cancer (CRC), remain unexplored. This study elucidated, for the first time, the role of PUS7 in CRC cell metastasis and the underlying mechanisms. Methods We conducted immunohistochemistry, qPCR, and western blotting to quantify the expression of PUS7 in CRC tissues as well as cell lines. Besides, diverse in vivo and in vitro functional tests were employed to establish the function of PUS7 in CRC. RNA-seq and proteome profiling analysis were also applied to identify the targets of PUS7. PUS7-interacting proteins were further uncovered using immunoprecipitation and mass spectrometry. Results Overexpression of PUS7 was observed in CRC tissues and was linked to advanced clinical stages and shorter overall survival. PUS7 silencing effectively repressed CRC cell metastasis, while its upregulation promoted metastasis, independently of the PUS7 catalytic activity. LASP1 was identified as a downstream effector of PUS7. Forced LASP1 expression abolished the metastasis suppression triggered by PUS7 silencing. Furthermore, HSP90 was identified as a client protein of PUS7, associated with the increased PUS7 abundance in CRC. NMS-E973, a specific HSP90 inhibitor, also showed higher anti-metastatic activity when combined with PUS7 repression. Importantly, in line with these results, in human CRC tissues, the expression of PUS7 was positively linked to the expression of HSP90 and LASP1, and patients co-expressing HSP90/PUS7/LASP1 showed a worse prognosis. Conclusions The HSP90-dependent PUS7 upregulation promotes CRC cell metastasis via the regulation of LASP1. Thus, targeting the HSP90/PUS7/LASP1 axis may be a novel approach for the treatment of CRC.

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Three-dimensional in situ morphometrics of Mycobacterium tuberculosis infection within lesions by optical mesoscopy and novel acid-fast staining

Scientific Reports ◽

10.1038/s41598-020-78640-4 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Robert J. Francis ◽

Gillian Robb ◽

Lee McCann ◽

Bhagwati Khatri ◽

James Keeble ◽

...

Keyword(s):

Mycobacterium Tuberculosis ◽

Three Dimensional ◽

Large Field ◽

Staining Procedure ◽

3D Analysis ◽

Mycobacterium Tuberculosis Infection ◽

In Vivo Models ◽

Novel Approach

AbstractTuberculosis (TB) preclinical testing relies on in vivo models including the mouse aerosol challenge model. The only method of determining colony morphometrics of TB infection in a tissue in situ is two-dimensional (2D) histopathology. 2D measurements consider heterogeneity within a single observable section but not above and below, which could contain critical information. Here we describe a novel approach, using optical clearing and a novel staining procedure with confocal microscopy and mesoscopy, for three-dimensional (3D) measurement of TB infection within lesions at sub-cellular resolution over a large field of view. We show TB morphometrics can be determined within lesion pathology, and differences in infection with different strains of Mycobacterium tuberculosis. Mesoscopy combined with the novel CUBIC Acid-Fast (CAF) staining procedure enables a quantitative approach to measure TB infection and allows 3D analysis of infection, providing a framework which could be used in the analysis of TB infection in situ.

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