Cells infected with human papilloma pseudovirus display nuclear reorganization and heterogenous infection kinetics.

Human papillomaviruses (HPV) are small, non-enveloped DNA viruses, which upon chronic infection can provoke cervical and head-and-neck cancers. Although the infectious life cycle of HPV has been studied and a vaccine is available for the most prevalent cancer-causing HPV types, there are no antiviral agents to treat infected patients. Hence, there is a need for novel therapeutic entry points and a means to identify them. In this work, we have used high-content microscopy to quantitatively investigate the early phase of HPV infection. Human cervical cancer cells and immortalized keratinocytes were exposed to pseudoviruses (PsV) of the widespread HPV type 16, in which the viral genome was replaced by a pseudogenome encoding a fluorescent reporter protein. Using the fluorescent signal as readout, we measured differences in infection between cell lines, which directly correlated with host cell proliferation rate. Parallel multiparametric analysis of nuclear organization revealed that HPV PsV infection alters nuclear organization and inflates promyelocytic leukemia protein body content, positioning these events at the early stage of HPV infection, upstream of viral replication. Time-resolved analysis revealed a marked heterogeneity in infection kinetics even between two daughter cells, which we attribute to differences in viral load. Consistent with the requirement for mitotic nuclear envelope breakdown, pharmacological inhibition of the cell cycle dramatically blunted infection efficiency. Thus, by systematic image-based single cell analysis, we revealed phenotypic alterations that accompany HPV PsV infection in individual cells, and which may be relevant for therapeutic drug screens.

Dynamic evolution of hyperuniformity in a driven dissipative colloidal system.

Hyperuniformity is evolving to become a unifying concept that can help classify and characterize equilibrium and nonequilibrium states of matter. Therefore, understanding the extent of hyperuniformity in dissipative systems is critical. Here, we study the dynamic evolution of hyperuniformity in a driven dissipative colloidal system. We experimentally show and numerically verify that the hyperuniformity of a colloidal crystal is robust against various lattice imperfections and environmental perturbations. This robustness even manifests during crystal disassembly as the system switches between strong (class I), logarithmic (class II), weak (class III), and non-hyperuniform states. To aid analyses, we developed a comprehensive computational toolbox, enabling real-time characterization of hyperuniformity in real- and reciprocal-spaces together with the evolution of several order metric features, and measurements showing the effect of external perturbations on the spatiotemporal distribution of the particles. Our findings provide a new framework to understand the basic principles that drive a dissipative system to a hyperuniform state.

Hypersynchronicity in the default mode-like network in a neurodevelopmental animal model with relevance for schizophrenia.

BACKGROUND: Immune activation during pregnancy is an important risk factor for schizophrenia. Brain dysconnectivity and NMDA receptor (NMDAR) hypofunction have been postulated to be central to schizophrenia pathophysiology. The aim of this study was to investigate resting-state functional connectivity (resting-state functional MRI-rsfMRI), microstructure (diffusion tension imaging-DTI) and response to NMDAR antagonist (pharmacological fMRI-phMRI) using multimodal MRI in offspring of pregnant dams exposed to immune challenge (maternal immune activation-MIA model), and determine whether these neuroimaging readouts correlate with schizophrenia-related behaviour. METHODS: Pregnant rats were injected with Poly I:C or saline on gestational day 15. The maternal weight response was assessed. Since previous research has shown behavioural deficits can differ between MIA offspring dependent on the maternal response to immune stimulus, offspring were divided into three groups: controls (saline, n = 11), offspring of dams that gained weight (Poly I:C WG, n = 12) and offspring of dams that lost weight post-MIA (Poly I:C WL, n = 16). Male adult offspring were subjected to rsfMRI, DTI, phMRI with NMDAR antagonist, behavioural testing and histological assessment. RESULTS: Poly I:C WL offspring exhibited increased functional connectivity in default mode-like network (DMN). Poly I:C WG offspring showed the most pronounced attenuation in NMDAR antagonist response versus controls. DTI revealed no differences in Poly I:C offspring versus controls. Poly I:C offspring exhibited anxiety. CONCLUSIONS: MIA offspring displayed a differential pathophysiology depending on the maternal response to immune challenge. While Poly I:C WL offspring displayed hypersynchronicity in the DMN, altered NMDAR antagonist response was most pronounced in Poly I:C WG offspring.

PREDECT Protocols for Complex 2D/3D Cultures.

PREDECT, a European IMI consortium, has assumed the task to generate robust 2D and 3D culture platforms. Protocols established for 2D and 3D monoculture and stromal coculture models of increasing complexity (spheroid, stirred-tank bioreactor, Matrigel- and collagen-embedded cultures) have been established between six laboratories within academia, biotech, and pharma. These models were tested using three tumor cell lines (MCF7, LNCaP, and NCI-H1437), covering three pathologies (breast, prostate, and lung), but should be readily transferable to other model systems. Fluorescent protein tagged cell lines were used for all platforms, allowing for online measurement of growth curves and drug responses to treatments. All methods, from culture setup to phenotypic characterization and gene expression profiling are described in this chapter.The adaptable methodologies and detailed protocols described here should help to include these models more readily to the drug discovery pipeline.

SliceMap: an algorithm for automated brain region annotation.

Summary: Many neurodegenerative disorders, such as Alzheimer's Disease, pertain to or spread from specific sites of the brain. Hence, accurate disease staging or therapy assessment in transgenic model mice demands automated analysis of selected brain regions. To address this need, we have developed an algorithm, termed SliceMap, that enables contextual quantification by mapping anatomical information onto microtome-cut brain slices. For every newly acquired high-resolution image of a brain slice, the algorithm performs a coarse congealing-based registration to a library of pre-annotated reference slices. A subset of optimally matching reference slices is then used for refined, elastic registration. Morphotextural metrics are used to measure registration performance and to automatically detect poorly cut slices. We have implemented our method as a plugin for FIJI image analysis freeware, and we have used it to regionally quantify tau pathology in brain slices from a tauopathy (P301S) mouse model. By enabling region-based quantification, our method contributes to a more accurate assessment of neurodegenerative disease development. Availability and implementation: The method is available as a plugin for FIJI from https://github.com/mbarbie1/SliceMap/, along with an example dataset and user instructions. Contact: winnok.devos@uantwerpen.be. Supplementary information: Supplementary data are available at Bioinformatics online.

Protocols and characterization data for 2D, 3D, and slice-based tumor models from the PREDECT project.

Two-dimensional (2D) culture of cancer cells in vitro does not recapitulate the three-dimensional (3D) architecture, heterogeneity and complexity of human tumors. More representative models are required that better reflect key aspects of tumor biology. These are essential studies of cancer biology and immunology as well as for target validation and drug discovery. The Innovative Medicines Initiative (IMI) consortium PREDECT (www.predect.eu) characterized in vitro models of three solid tumor types with the goal to capture elements of tumor complexity and heterogeneity. 2D culture and 3D mono- and stromal co-cultures of increasing complexity, and precision-cut tumor slice models were established. Robust protocols for the generation of these platforms are described. Tissue microarrays were prepared from all the models, permitting immunohistochemical analysis of individual cells, capturing heterogeneity. 3D cultures were also characterized using image analysis. Detailed step-by-step protocols, exemplary datasets from the 2D, 3D, and slice models, and refined analytical methods were established and are presented.

BiDiFuse: a FIJI plugin for fusing bi-directionally recorded microscopic image volumes.

Deep tissue imaging is increasingly used for non-destructive interrogation of intact organs and small model organisms. An intuitive approach to increase the imaging depth by almost a factor of 2 is to record a sample from two sides and fuse both image stacks. However, imperfect three-dimensional alignment of both stacks presents a computational challenge. We have developed a FIJI plugin, called BiDiFuse, which merges bi-directionally recorded image stacks via 3D rigid transformations. The method is broadly applicable, considering it is compatible with all optical sectioning microscopes and it does not rely on fiducial markers for image registration. AVAILABILITY AND IMPLEMENTATION: The method is freely available as a plugin for FIJI from https://github.com/JanDetrez/BiDiFuse/ CONTACT: winnok.devos@uantwerpen.be.

Capturing tumor complexity in vitro: Comparative analysis of 2D and 3D tumor models for drug discovery.

Two-dimensional (2D) cell cultures growing on plastic do not recapitulate the three dimensional (3D) architecture and complexity of human tumors. More representative models are required for drug discovery and validation. Here, 2D culture and 3D mono- and stromal co-culture models of increasing complexity have been established and cross-comparisons made using three standard cell carcinoma lines: MCF7, LNCaP, NCI-H1437. Fluorescence-based growth curves, 3D image analysis, immunohistochemistry and treatment responses showed that end points differed according to cell type, stromal co-culture and culture format. The adaptable methodologies described here should guide the choice of appropriate simple and complex in vitro models.

Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids.

In oncology, two-dimensional in-vitro culture models are the standard test beds for the discovery and development of cancer treatments, but in the last decades, evidence emerged that such models have low predictive value for clinical efficacy. Therefore they are increasingly complemented by more physiologically relevant 3D models, such as spheroid micro-tumor cultures. If suitable fluorescent labels are applied, confocal 3D image stacks can characterize the structure of such volumetric cultures and, for example, cell proliferation. However, several issues hamper accurate analysis. In particular, signal attenuation within the tissue of the spheroids prevents the acquisition of a complete image for spheroids over 100 micrometers in diameter. And quantitative analysis of large 3D image data sets is challenging, creating a need for methods which can be applied to large-scale experiments and account for impeding factors. We present a robust, computationally inexpensive 2.5D method for the segmentation of spheroid cultures and for counting proliferating cells within them. The spheroids are assumed to be approximately ellipsoid in shape. They are identified from information present in the Maximum Intensity Projection (MIP) and the corresponding height view, also known as Z-buffer. It alerts the user when potential bias-introducing factors cannot be compensated for and includes a compensation for signal attenuation.

Single-layer and bilayer graphene superlattices: collimation, additional Dirac points and Dirac lines.

We review the energy spectrum and transport properties of several types of one-dimensional superlattices (SLs) on single-layer and bilayer graphene. In single-layer graphene, for certain SL parameters an electron beam incident on an SL is highly collimated. On the other hand, there are extra Dirac points generated for other SL parameters. Using rectangular barriers allows us to find analytical expressions for the location of new Dirac points in the spectrum and for the renormalization of the electron velocities. The influence of these extra Dirac points on the conductivity is investigated. In the limit of δ-function barriers, the transmission T through and conductance G of a finite number of barriers as well as the energy spectra of SLs are periodic functions of the dimensionless strength P of the barriers, Pδ(x) = V(x)/hv(F), with v(F) the Fermi velocity. For a Kronig-Penney SL with alternating sign of the height of the barriers, the Dirac point becomes a Dirac line for P = π/2+nπ with n an integer. In bilayer graphene, with an appropriate bias applied to the barriers and wells, we show that several new types of SLs are produced and two of them are similar to type I and type II semiconductor SLs. Similar to single-layer graphene SLs, extra 'Dirac' points are found in bilayer graphene SLs. Non-ballistic transport is also considered.