Mosaic Models Research Articles

A Tumor-Specific Molecular Network Promotes Tumor Growth in Drosophila by Enforcing a Jun N-Terminal Kinase-Yorkie Feedforward Loop.

Cancer cells expand rapidly in response to altered intercellular and signaling interactions to achieve the hallmarks of cancer. Impaired cell polarity combined with activated oncogenes is known to promote several hallmarks of cancer, e.g., activating invasion by increased activity of Jun N-terminal kinase (JNK) and sustained proliferative signaling by increased activity of Hippo effector Yorkie (Yki). Thus, JNK, Yki, and their downstream transcription factors have emerged as synergistic drivers of tumor growth through pro-tumor signaling and intercellular interactions like cell competition. However, little is known about the signals that converge onto JNK and Yki in tumor cells and enable tumor cells to achieve the hallmarks of cancer. Here, using mosaic models of cooperative oncogenesis (RasV12,scrib-) in Drosophila, we show that RasV12,scrib- tumor cells grow through the activation of a previously unidentified network comprising Wingless (Wg), Dronc, JNK, and Yki. We show that RasV12,scrib- cells show increased Wg, Dronc, JNK, and Yki signaling, and all these signals are required for the growth of RasV12,scrib- tumors. We report that Wg and Dronc converge onto a JNK-Yki self-reinforcing positive feedback signal-amplification loop that promotes tumor growth. We found that the Wg-Dronc-Yki-JNK molecular network is specifically activated in polarity-impaired tumor cells and not in normal cells, in which apical-basal polarity remains intact. Our findings suggest that the identification of molecular networks may provide significant insights into the key biologically meaningful changes in signaling pathways and paradoxical signals that promote tumorigenesis.

General mapping of one-dimensional non-Hermitian mosaic models to non-mosaic counterparts: Mobility edges and Lyapunov exponents

We establish a general mapping from one-dimensional non-Hermitian mosaic models to their non-mosaic counterparts. This mapping can give rise to mobility edges and even Lyapunov exponents in the mosaic models if critical points of localization or Lyapunov exponents of localized states in the corresponding non-mosaic models have already been analytically solved. To demonstrate the validity of this mapping, we apply it to two non-Hermitian localization models: an Aubry–André-like model with nonreciprocal hopping and complex quasiperiodic potentials, and the Ganeshan–Pixley–Das Sarma model with nonreciprocal hopping. We successfully obtain the mobility edges and Lyapunov exponents in their mosaic models. This general mapping may catalyze further studies on mobility edges, Lyapunov exponents, and other significant quantities pertaining to localization in non-Hermitian mosaic models.

Asymmetries in triboelectric charging: Generalizing mosaic models to different-material samples and sliding contacts

Nominally identical materials exchange net electric charge during contact through a mechanism that is still debated. `Mosaic models', in which surfaces are presumed to consist of a random patchwork of microscopic donor/acceptor sites, offer an appealing explanation for this phenomenon. However, recent experiments have shown that global differences persist even between same-material samples, which the standard mosaic framework does not account for. Here, we expand the mosaic framework by incorporating global differences in the densities of donor/acceptor sites. We develop an analytical model, backed by numerical simulations, that smoothly connects the global and deterministic charge transfer of different materials to the local and stochastic mosaic picture normally associated with identical materials. Going further, we extend our model to explain the effect of contact asymmetries during sliding, providing a plausible explanation for reversal of charging sign that has been observed experimentally.

Characterization of the pace-and-drive capacity of the human sinoatrial node: A 3D in silico study

The sinoatrial node (SAN) is a complex structure that spontaneously depolarizes rhythmically (“pacing”) and excites the surrounding non-automatic cardiac cells (“drive”) to initiate each heart beat. However, the mechanisms by which the SAN cells can activate the large and hyperpolarized surrounding cardiac tissue are incompletely understood. Experimental studies demonstrated the presence of an insulating border that separates the SAN from the hyperpolarizing influence of the surrounding myocardium, except at a discrete number of sinoatrial exit pathways (SEPs). We propose a highly detailed 3D model of the human SAN, including 3D SEPs to study the requirements for successful electrical activation of the primary pacemaking structure of the human heart. A total of 788 simulations investigate the ability of the SAN to pace and drive with different heterogeneous characteristics of the nodal tissue (gradient and mosaic models) and myocyte orientation. A sigmoidal distribution of the tissue conductivity combined with a mosaic model of SAN and atrial cells in the SEP was able to drive the right atrium (RA) at varying rates induced by gradual If block. Additionally, we investigated the influence of the SEPs by varying their number, length, and width. SEPs created a transition zone of transmembrane voltage and ionic currents to enable successful pace and drive. Unsuccessful simulations showed a hyperpolarized transmembrane voltage (−66 mV), which blocked the L-type channels and attenuated the sodium-calcium exchanger. The fiber direction influenced the SEPs that preferentially activated the crista terminalis (CT). The location of the leading pacemaker site (LPS) shifted toward the SEP-free areas. LPSs were located closer to the SEP-free areas (3.46 ± 1.42 mm), where the hyperpolarizing influence of the CT was reduced, compared with a larger distance from the LPS to the areas where SEPs were located (7.17± 0.98 mm). This study identified the geometrical and electrophysiological aspects of the 3D SAN-SEP-CT structure required for successful pace and drive in silico.

On the efficiency of using correlative randomized algorithms for solving problems of gamma radiation transfer in stochastic medium

Abstract To solve problems of radiation balance, optical sounding, and tomography, it may be necessary to take into account multiple scattering of radiation in a stochastically inhomogeneous medium. In real radiation models, for this purpose, the numerical-statistical ‘majorant cross-section method’ (MCM, delta-Woodcock tracking) is used based on the alignment of the optical density field by adding an artificial ‘delta scattering’ event. However, the computation cost of the corresponding unbiased estimate of the averaged problem solution infinitely increases as the correlation scale (correlation radius L) of standard mosaic models for a random medium density decreases. Previously, we constructed the MCM randomization providing asymptotically (for L → 0) unbiased estimates of the required functionals, in which the value of the physical attenuation coefficient is randomly chosen at the end of the particle free path l under condition l > L. Otherwise the value of the physical attenuation coefficient is the same as at the starting point of the particle (CR algorithm). In a more accurate functional correlative randomized algorithm (FCR algorithm), the coefficient remains the same with a probability determined by the correlation function. These correlative randomized algorithms were implemented for a mixture of homogeneous substance (water) and a Poisson ensemble of ‘empty’ balls. In the present paper, we construct correlative randomized algorithms for problems related to transfer through a ‘thick’ layer containing a water and a Poisson ensemble of ‘empty’ layers. A detailed comparative analysis of the results obtained by exact direct simulation (MCM) and approximate algorithms (CR, FCR) for the problems of gamma radiation transfer through a ‘thick’ water layer containing a Poisson ensemble of ‘empty’ layers or balls is presented.

Topological superconductors and exact mobility edges in non-Hermitian quasicrystals

We study a class of non-Hermitian topological superconductors described by one-dimensional Aubry-Andr\'e Harper and mosaic quasiperiodic models with $p$-wave superconducting pairing, where the non-Hermiticity is introduced by on-site complex quasiperiodic potentials. We generalize two topological invariants, one is based on the transfer matrix method and the other is the generalized Majorana polarization, to characterize the topological superconducting phases and verify the existence of Majorana zero modes in non-Hermitian quasiperiodic superconductors. By combing the Lyapunov exponent, the fractional dimension of wave functions, and topological invariants, we investigate the localization phenomena, topological superconductivity, and topological phase transitions. In the non-Hermitian Aubry-Andr\'e Harper model with $p$-wave pairing, the system undergoes an extended-critical-localized phase transition with increasing the complex phase. The localization transition is consistent with the topological phase transition and unconventional real-complex transition of eigenenergy. In the non-Hermitian mosaic model, we provide an analytical expression of mobility edges and prove the intrinsic relation between the mobility edges and unconventional real-complex transitions. Our discoveries unveil the richness of topological and localization phenomena in non-Hermitian quasicrystals with $p$-wave pairing.

Exact Mobility Edges in 1D Mosaic Lattices Inlaid with Slowly Varying Potentials

AbstractA family of 1D mosaic models inlaid with a slowly varying potential is proposed. Combining the asymptotic heuristic argument with the theory of trace map of transfer matrix, mobility edges (MEs), and pseudo‐MEs (PMEs) in their energy spectra are solved semi‐analytically, where ME separates extended states from weakly localized ones and PME separates weakly localized states from strongly localized ones. The nature of eigenstates in extended, critical, weakly localized, pseudo‐critical, and strongly localized is diagnosed by the local density of states, the Lyapunov exponent, the localization tensor, and fractal dimension. Numerical calculation results are in excellent quantitative agreement with theoretical predictions.

Morphological analysis of mosaic shapes with directed relationships based on attribute and relational model representations

We introduce attribute and relational representations of mosaic image models with directed relationships between regions. Attribute representations of asymmetric relational models based on stacking, ranking and integral descriptions are considered. We propose some morphological shape similarity measures based on relational models. We show that using the same oriented relational model, various morphological operators can be constructed, in particular, of Serra- or Pyt’ev type. Some constructive methods for the design of such morphological operators in an attribute and relational domains are proposed. From this consideration we also extract a new morophlogical scheme for two-stage mutual adaptive image-and-shape joint filtering: at the first step, the shape is simplified (projected) with regard to the image to be projected, and at the second step, the image is simplified (projected) with regard to the simplified (projected) shape.

MORPHOLOGICAL IMAGE ANALYSIS BASED ON ATTRIBUTE AND RELATIONAL REPRESENTATIONS OF MOSAIC IMAGE MODELS

A unified scheme for morphological analysis based on attribute and relational representations of mosaic image models is proposed. We consider 4 main types of model representation: functional-attribute (2D feature map), functional-relational (4D relational map), structure-resource-attribute (an area list with resources and attributes), and structure-resource-relational (a graph, which nodes correspond to regions and edges – to relations and both having resource attributes). In this case, the forms of representation of the model are equivalent to each other, in the sense that they contain the same information, there is a one-to-one correspondence between them, and the formulas for the transition from one representation to another can be written out explicitly. In this scheme, the construction of specific morphological operator for some complete image model presumes the separation of this model into two parts: the guiding (modifying) part, which determines the transformation algorithm, and the guided (modifiable) part to be transformed. These two parts of the model can intersect, therefore cannot be called “variable” and “constant” components. As a basic sample, we consider the halftone Pyt’ev morphology. We explore the specifics of different-sort models, introduce the mutual models and propose different tools for creation of model-based morphological operators. Further, various other morphological systems can be described and explored using the proposed generalized approach.

Comparison of statistical properties for various morphological filters based on mosaic image shape models

We consider the statistical properties of different mosaic filters. We demonstrate that in Pitiev's morphology, the measure of shape complexity is directly related to the shape simplicity measure based on morphological correlation coefficient (MCC). Based on MCC, we introduce the normalized morphological simplification index (NMSI). Using NMSI, we show that the simpler the mosaic shape, the more shape simplification is provided by the corresponding Pyt'ev projector. For the examples of mean and median mosaic filters, we address the problem of different operator comparison. In this context we introduce the concept of statistically simplifying morphological operators. Morphological correlation of mosaic shape and diffusion mosaic operator is considered. We prove that the NMSI for the diffusion mosaic operator is not related to the complexity for the corresponding diffusion shape kernel. Thus, a principal qualitative difference in the relationship between relational and operator models for diffuse and projective mosaic linear filters is demonstrated.

IMAGE AND SHAPE COMPARISON VIA MORPHOLOGICAL CORRELATION

Abstract. A lot of image matching applications require image comparison to be invariant relative to intensity values variations. The Pyt’ev theory for Morphological Image Analysis (MIA) was developed based on image-to-shape matching with mosaic shape models. Within the framework of this theory, the problem of shape-to-shape comparison was previously considered too. The most sophisticated and weakest part of MIA theory is the comparison of mosaic shapes with some arbitrary restrictions described by graphs or relations. In this paper we consider the possible options for comparing images and shapes using morphological projection and morphological correlation. Our contribution is a new scheme of morphological shape-to-image projection and, correspondingly, the new morphological correlation coefficient (MCC) for shape-to-image correlation with restricted mosaic models. We also refine the expressions for shape-to-shape comparison.

Exact mobility edges, PT -symmetry breaking, and skin effect in one-dimensional non-Hermitian quasicrystals

We propose a general analytic method to study the localization transition in one-dimensional quasicrystals with parity-time ($\mathcal{PT}$) symmetry, described by complex quasiperiodic mosaic lattice models. By applying Avila's global theory of quasiperiodic Schr\"odinger operators, we obtain exact mobility edges and prove that the mobility edge is identical to the boundary of $\mathcal{PT}$-symmetry breaking, which also proves the existence of correspondence between extended (localized) states and $\mathcal{PT}$-symmetry ($\mathcal{PT}$-symmetry-broken) states. Furthermore, we generalize the models to more general cases with nonreciprocal hopping, which breaks $\mathcal{PT}$ symmetry and generally induces skin effect, and obtain a general and analytical expression of mobility edges. While the localized states are not sensitive to the boundary conditions, the extended states become skin states when the periodic boundary condition is changed to open boundary condition. This indicates that the skin states and localized states can coexist with their boundary determined by the mobility edges.

Modelling genetic mosaicism of neurodevelopmental disorders in vivo by a Cre-amplifying fluorescent reporter

Genetic mosaicism, a condition in which an organ includes cells with different genotypes, is frequently present in monogenic diseases of the central nervous system caused by the random inactivation of the X-chromosome, in the case of X-linked pathologies, or by somatic mutations affecting a subset of neurons. The comprehension of the mechanisms of these diseases and of the cell-autonomous effects of specific mutations requires the generation of sparse mosaic models, in which the genotype of each neuron is univocally identified by the expression of a fluorescent protein in vivo. Here, we show a dual-color reporter system that, when expressed in a floxed mouse line for a target gene, leads to the creation of mosaics with tunable degree. We demonstrate the generation of a knockout mosaic of the autism/epilepsy related gene PTEN in which the genotype of each neuron is reliably identified, and the neuronal phenotype is accurately characterized by two-photon microscopy.

Carpet-bombing tumors with IFN-γ.

To demonstrate the long-range effects of CD8+ T cell–secreted interferon-γ on bystander tumor cells, two studies now use mosaic models of antigen loss in tumors combined with intravital imaging. Factors that influence the length scale of diffusible signals could shape disease progression in cancer and autoimmunity.

Efficient Representation of Laguerre Mosaics with an Application to Microstructure Simulation of Complex Ore

Laguerre mosaics have been an important modeling approach in astronomy, physics, crystallography, geology and mathematics for several decades. In materials science, they are used as models for cellular and polycrystalline materials, networks and cell foams. In this study, Laguerre mosaics are used to model the three-dimensional internal mineral microstructure of complex ores. Here, the difficulties arise in representing and simulating these microstructure mosaics for dimensions larger than two. Therefore, this manuscript introduces a general workflow for the representation in arbitrary dimensions and presents a realization of this workflow using generalized maps for representation in two and three dimensions. With this approach, lower-dimensional components such as cells, facets, edges and vertices can be accessed directly, which enables us to efficiently create the mosaics and derive statistics, plane sections and new mosaic models by intersection. Furthermore, it allows for easy deduction of the dual mosaic and efficient storage. The mineral microstructure of complex ores can be very complicated and often shows a highly fractal structure. Therefore, numerical modeling and representation of these microstructures is challenging. The proposed approach for Laguerre mosaic creation and representation is successfully applied to the modeling of mineral microstructures and particles. These microstructure models are used for mineral processing simulations in order to determine optimal processing strategies to conserve valuable resources.

1237P - Immune competent somatic mosaic model of colorectal cancer

BackgroundHistorically, immunotherapies have been tested in syngeneic mouse models and until now only limited CRC syngeneic cells are available. Animal models with functioning human immune systems are critically needed to more accurately evaluate checkpoint blockers delivery, therapeutic response, and to better define biomarker expression in the presence of a competent immune system. MethodsTo better address the efficacy of immune checkpoint therapy specifically in relation to presence of a BRAFmutation, we developed a novel platform for the generation of somatic mosaic models of CRC enabling (i) high-throughput generation of genetically complex syngeneic models of cancer, (ii) tracing studies through fluorescence reporters. ResultsCdx2Cre/+ mice, expressing the Cre recombinaseunder the control of a human Cdx2 promoter/enhancer sequence have been crossed with the R26LSL-Cas9-Gfp strain to generate models allowing for tissue specific activation of Cas9 and Gfpreporter only in CDX2 positive cells. This strain has been crossed with BRAFFSF-V600E mice to generate the final model. 6-8 weeks old mice have then been transduced with AAV constructs expressing the FLPO recombinasethat can be activated by Cre recombinase and sgRNAs targeting APC, TP53, MLH1, MSH2and ARID1Aalone or combined, in order to model MSI CRC (APC-TP53-MLH1and ARID1A-MLH1conditional mosaic knock-outs) and MSS CRC (APC-TP53 conditional mosaic knock-out). Viral particles have been surgically delivered via subserosal cecal injection and mice monitored for tumor formation by IVIS imaging. 35 mice injected with 3 combinations of tumor suppressors provide a diverse immunology repetoire. Cell lines isolated from genetically modified mice will provide a physiologic relevant and feasible means to study the mechanisms of response and resistance to immunotherapies and to understand biological and molecular differences between BRAFmutated MSI and MSS tumors. ConclusionsThis project focuses on the identification and characterization of the functional drivers of CMS1CRC tumors leveraging in vivomosaic genome editing technologies and functional genetic labeling of malignant sub-populations emerging during disease progression and in response to therapy. Legal entity responsible for the studyThe authors. FundingMD Anderson Cancer Center. DisclosureAll authors have declared no conflicts of interest.

Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing.

In females with X-linked genetic disorders, wild-type and mutant cells coexist within brain tissue because of X-chromosome inactivation, posing challenges for interpreting the effects of X-linked mutant alleles on gene expression. We present a single-nucleus RNA sequencing approach that resolves mosaicism by using SNPs in genes expressed in cis with the X-linked mutation to determine which nuclei express the mutant allele even when the mutant gene is not detected. This approach enables gene expression comparisons between mutant and wild-type cells within the same individual, eliminating variability introduced by comparisons to controls with different genetic backgrounds. We apply this approach to mosaic female mouse models and humans with Rett syndrome, an X-linked neurodevelopmental disorder caused by mutations in the methyl-DNA-binding protein MECP2 and observe that cell-type-specific DNA methylation predicts the degree of gene up-regulation in MECP2-mutant neurons. This approach can be broadly applied to study gene expression in mosaic X-linked disorders.

Extreme Enlargement of the Cerebellum in a Clade of Teleost Fishes that Evolved a Novel Active Sensory System

Brains, and the distinct regions that make up brains, vary widely in size across vertebrates [1, 2]. Two prominent hypotheses have been proposed to explain brain region scaling evolution. The mosaic hypothesis proposes that changes in the relative sizes of particular brain regions are the result of selection acting independently on those regions [2, 3]. The concerted hypothesis proposes that the brain evolves as a coordinated structure due to developmental constraints [4]. These hypotheses have been widely debated [3-7], and recent studies suggest a combination of the two best describes vertebrate brain region scaling [8-10]. However, no study has addressed how the mosaic and concerted models relate to the evolution of novel behavioral phenotypes. We addressed this question using African mormyroid fishes. The mormyroids have evolved a novel active electrosensory system and are well known for having extreme encephalization [11] and a large cerebellum [2, 12], which is cited as a possible example of mosaic evolution [2]. We found that compared to outgroups without active electrosensing, mormyroids experienced mosaic increases in the sizes of the cerebellum and hindbrain, and mosaic decreases in the sizes of the telencephalon, optic tectum, and olfactory bulb. However, the evolution of extreme encephalization within mormyroids was associated with concerted changes in the sizes of all brain regions. This suggests that mosaic evolutionary change in the regional composition of the brain is most likely to occur alongside the evolution of novel behavioral functions, but not with the evolution of extreme encephalization.

Abstract B40: Perturbation of proteostasis is lethal in SMARCB1-deficient tumors

Abstract Alterations in the SWI/SNF chromatin remodeling complex have been implicated in human malignancies. Biallelic inactivation of the core subunits SMARCB1 and SMARCA4 are associated with particularly aggressive forms of pediatric cancer known as malignant rhabdoid tumors (MRTs) and atypical theratoid/rhabdoid tumors (AT/RTs). MRTs and AT/RTs are characterized by simple genomes and lack of somatic events, suggesting that dysregulation of SWI/SNF machinery is sufficient to induce a highly malignant state. However, the lack of a conditional genetic model of MRT has precluded the investigation of the molecular bases and dependencies associated with SMARCB1 loss. To this aim, we have developed a novel embryonic mosaic mouse model of MRTs of the liver. Using this mouse model, we performed a systematic functional investigation of vulnerabilities in the context of SMARCB1 loss in order to identify novel treatments for these diseases. Embryonic mosaic models of MRTs of the liver were generated by transuterine delivery of adenoviral vectors carrying the Cre recombinase under a tissue-specific promoter (Adx-Alb-Cre) to target SMARCB1LoxP/LoxP embryos at embryonic day E12-14 in order to study the effect of SMARCB1 ablation on development and tumorigenesis. Such an approach allowed us to target the developing liver epithelial compartment and to bypass the perinatal lethality observed with tissue-specific Cre deleter strains. This approach results in postnatal expansion of the epithelial compartment and in the emergence of rhabdoid tumors in a subset of cases. Upon investigation of the early effects of SMARCB1 ablation during mouse development and tumorigenesis, we found that livers in these embryonic mosaic murine models undergo profound metabolic changes resulting in a dramatic activation of cellular programs involved in the maintenance of proteostasis in response to ER stress and autophagy. To functionally validate the hypothesis that SMARCB1 loss confers sensitivity to proteotoxic agents, embryonic mosaic murine models of MRTs of the liver were treated with combinations of bortezomib and chloroquine, resulting in suppression of tumor growth and prolonged survival. Murine transplantation models of MRT treated with combinations of bortezomib and chloroquine also resulted in a significant increase in survival. Additionally, immunohistochemical studies of pediatric MRTs showed significant accumulation of markers of ER stress, and autophagy in comparison to normal tissue. The use of a novel embryonic mosaic models of MRT demonstrated that SMARCB1 disruption during liver embryogenesis caused activation of anabolic pathways and an increase in UPR, ER stress response, and autophagy. Overall, our preclinical study provides the rationale for a novel therapeutic approach aimed at exploiting a “collateral proteopathy” characteristic of SMARCB1-deficient malignancies and at the repositioning of existing drugs that have already shown acceptable toxicity profiles. Citation Format: Melinda Soeung, Alessandro Carugo, Frederick Scott Robinson, Rosalba Minelli, Federica Carbone, Anirban Maitra, Andrea Viale, Charles W.M. Roberts, Nizar Tannir, Giulio F. Draetta, Giannicola Genovese. Perturbation of proteostasis is lethal in SMARCB1-deficient tumors [abstract]. In: Proceedings of the AACR Special Conference: Pediatric Cancer Research: From Basic Science to the Clinic; 2017 Dec 3-6; Atlanta, Georgia. Philadelphia (PA): AACR; Cancer Res 2018;78(19 Suppl):Abstract nr B40.

Necroptosis microenvironment directs lineage commitment in liver cancer.

Primary liver cancer represents a major health problem. It comprises hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), which differ markedly with regards to their morphology, metastatic potential and responses to therapy. However, the regulatory molecules and tissue context that commit transformed hepatic cells towards HCC or ICC are largely unknown. Here we show that the hepatic microenvironment epigenetically shapes lineage commitment in mosaic mouse models of liver tumorigenesis. Whereas a necroptosis-associated hepatic cytokine microenvironment determines ICC outgrowth from oncogenically transformed hepatocytes, hepatocytes containing identical oncogenic drivers give rise to HCC if they are surrounded by apoptotic hepatocytes. Epigenome and transcriptome profiling of mouse HCC and ICC singled out Tbx3 and Prdm5 as major microenvironment-dependent and epigenetically regulated lineage-commitment factors, a function that is conserved in humans. Together, our results provide insight into lineage commitment in liver tumorigenesis, and explain molecularly why common liver-damaging risk factors can lead to either HCC or ICC.