A vascular biology network model focused on inflammatory processes to investigate atherogenesis and plaque instability.

BACKGROUND: Numerous inflammation-related pathways have been shown to play important roles in atherogenesis. Rapid and efficient assessment of the relative influence of each of those pathways is a challenge in the era of "omics" data generation. The aim of the present work was to develop a network model of inflammation-related molecular pathways underlying vascular disease to assess the degree of translatability of preclinical molecular data to the human clinical setting. METHODS: We constructed and evaluated the Vascular Inflammatory Processes Network (V-IPN), a model representing a collection of vascular processes modulated by inflammatory stimuli that lead to the development of atherosclerosis. RESULTS: Utilizing the V-IPN as a platform for biological discovery, we have identified key vascular processes and mechanisms captured by gene expression profiling data from four independent datasets from human endothelial cells (ECs) and human and murine intact vessels. Primary ECs in culture from multiple donors revealed a richer mapping of mechanisms identified by the V-IPN compared to an immortalized EC line. Furthermore, an evaluation of gene expression datasets from aortas of old ApoE-/- mice (78 weeks) and human coronary arteries with advanced atherosclerotic lesions identified significant commonalities in the two species, as well as several mechanisms specific to human arteries that are consistent with the development of unstable atherosclerotic plaques. CONCLUSIONS: We have generated a new biological network model of atherogenic processes that demonstrates the power of network analysis to advance integrative, systems biology-based knowledge of cross-species translatability, plaque development and potential mechanisms leading to plaque instability.

Aneuploid cells are differentially susceptible to caspase-mediated death during embryonic cerebral cortical development.

Neural progenitor cells, neurons, and glia of the normal vertebrate brain are diversely aneuploid, forming mosaics of intermixed aneuploid and euploid cells. The functional significance of neural mosaic aneuploidy is not known; however, the generation of aneuploidy during embryonic neurogenesis, coincident with caspase-dependent programmed cell death (PCD), suggests that a cell's karyotype could influence its survival within the CNS. To address this hypothesis, PCD in the mouse embryonic cerebral cortex was attenuated by global pharmacological inhibition of caspases or genetic removal of caspase-3 or caspase-9. The chromosomal repertoire of individual brain cells was then assessed by chromosome counting, spectral karyotyping, fluorescence in situ hybridization, and DNA content flow cytometry. Reducing PCD resulted in markedly enhanced mosaicism that was comprised of increased numbers of cells with the following: (1) numerical aneuploidy (chromosome losses or gains); (2) extreme forms of numerical aneuploidy (>5 chromosomes lost or gained); and (3) rare karyotypes, including those with coincident chromosome loss and gain, or absence of both members of a chromosome pair (nullisomy). Interestingly, mildly aneuploid (<5 chromosomes lost or gained) populations remained comparatively unchanged. These data demonstrate functional non-equivalence of distinguishable aneuploidies on neural cell survival, providing evidence that somatically generated, cell-autonomous genomic alterations have consequences for neural development and possibly other brain functions.

Quantitative assessment of biological impact using transcriptomic data and mechanistic network models.

Exposure to biologically active substances such as therapeutic drugs or environmental toxicants can impact biological systems at various levels, affecting individual molecules, signaling pathways, and overall cellular processes. The ability to derive mechanistic insights from the resulting system responses requires the integration of experimental measures with a priori knowledge about the system and the interacting molecules therein. We developed a novel systems biology-based methodology that leverages mechanistic network models and transcriptomic data to quantitatively assess the biological impact of exposures to active substances. Hierarchically organized network models were first constructed to provide a coherent framework for investigating the impact of exposures at the molecular, pathway and process levels. We then validated our methodology using novel and previously published experiments. For both in vitro systems with simple exposure and in vivo systems with complex exposures, our methodology was able to recapitulate known biological responses matching expected or measured phenotypes. In addition, the quantitative results were in agreement with experimental endpoint data for many of the mechanistic effects that were assessed, providing further objective confirmation of the approach. We conclude that our methodology evaluates the biological impact of exposures in an objective, systematic, and quantifiable manner, enabling the computation of a systems-wide and pan-mechanistic biological impact measure for a given active substance or mixture. Our results suggest that various fields of human disease research, from drug development to consumer product testing and environmental impact analysis, could benefit from using this methodology.

The Prospective Study of Epigenetic Regulatory Profiles in Sport and Exercise Monitored Through Chromosome Conformation Signatures.

The integration of genetic and environmental factors that regulate the gene expression patterns associated with exercise adaptation is mediated by epigenetic mechanisms. The organisation of the human genome within three-dimensional space, known as chromosome conformation, has recently been shown as a dynamic epigenetic regulator of gene expression, facilitating the interaction of distal genomic regions due to tight and regulated packaging of chromosomes in the cell nucleus. Technological advances in the study of chromosome conformation mean a new class of biomarker-the chromosome conformation signature (CCS)-can identify chromosomal interactions across several genomic loci as a collective marker of an epigenomic state. Investigative use of CCSs in biological and medical research shows promise in identifying the likelihood that a disease state is present or absent, as well as an ability to prospectively stratify individuals according to their likely response to medical intervention. The association of CCSs with gene expression patterns suggests that there are likely to be CCSs that respond, or regulate the response, to exercise and related stimuli. The present review provides a contextual background to CCS research and a theoretical framework discussing the potential uses of this novel epigenomic biomarker within sport and exercise science and medicine.

A reevaluation of tetraploidy in the Alzheimer's disease brain.

Alzheimer's disease (AD) is characterized by extensive neuronal death in distinct brain regions, including the frontal cortex and hippocampus, although the specific mechanisms of neuronal degeneration in AD remain a topic of intense scientific pursuit. One model for cell death in AD postulates that abortive cell cycle events in neurons, including tetraploidy, precede neuronal death, and novel therapeutics based on suppressing cell cycle re-entry are being pursued. Using DNA content fluorescence-activated cell sorting combined with fluorescence in situ hybridization and immunostaining, we analyzed neuronal nuclei from postmortem human brain samples from the frontal cortex and hippocampus of nondiseased and AD patients for evidence of tetraploidy. Here, we show that tetraploid nuclei are similarly prevalent in AD and control brains and are exclusively non-neuronal, contrasting with an absence of tetraploid neurons. Our findings demonstrate that neuronal tetraploidy is nonexistent in the AD brain and intimate a reevaluation of neuronal cell cycle re-entry as a therapeutic target for AD.

Chromosomal mosaicism in neural stem cells.

Neural stem and progenitor cells (referred to here as NSCs), located in the proliferative zones of embryonic brains, can be seen undergoing mitosis at the ventricular surface. Mitotic NSCs can be arrested in metaphase and chromosome "spreads" produced to reveal their chromosomal complement. Studies in mice and humans have revealed a prominent developmental presence of aneuploid NSCs, whereas other chromosomal defects, such as interchromosomal translocations and partial chromosomal deletions/insertions, are extremely rare (1,2). Aneuploidy is defined as the loss or gain of whole chromosomes, resulting in cells that deviate from the normal diploid number of chromosomes (46 in humans, 40 in mice). In NSCs, aneuploidy can occur as a result of mis-segregation during mitosis, through events such as lagging chromosomes, supernumerary centrosomes, and nondisjunction events (3). The percentage of aneuploid NSCs can be altered by in vivo and in vitro growth conditions as well as through genetic deletion of genes involved in DNA surveillance and repair (1,4). Aneuploidy can be detected by classical cytogenetic methods such as counting the number of chromosomes visualized by DNA dyes (e.g., 4,6-diamidino-2-phenylindole) by using standard light or fluorescence microscopy. Precise chromosome identification is much more difficult: classical methods using banding patterns or size to assign identity are very time consuming even under ideal conditions, and they are notoriously difficult in mice, which often have ambiguous banding patterns and acrocentric chromosomes. A comparatively new technique that allows the unambiguous identification of chromosomes in mice and humans is "spectral karyotyping" or SKY, developed by Ried et al. at the National Institutes of Health for the study of cancer cells (5). This technique uses chromosomal "paints" that are hybridized to chromosome spreads to produce a distinct spectral output for each chromosome. SKY offers superior speed and sensitivity in its ability to detect many types of chromosomal defects, including deletions, insertions, translocations, and aneuploidy.

Construction of a computable network model for DNA damage, autophagy, cell death, and senescence.

Towards the development of a systems biology-based risk assessment approach for environmental toxicants, including tobacco products in a systems toxicology setting such as the "21st Century Toxicology", we are building a series of computable biological network models specific to non-diseased pulmonary and cardiovascular cells/tissues which capture the molecular events that can be activated following exposure to environmental toxicants. Here we extend on previous work and report on the construction and evaluation of a mechanistic network model focused on DNA damage response and the four main cellular fates induced by stress: autophagy, apoptosis, necroptosis, and senescence. In total, the network consists of 34 sub-models containing 1052 unique nodes and 1538 unique edges which are supported by 1231 PubMed-referenced literature citations. Causal node-edge relationships are described using the Biological Expression Language (BEL), which allows for the semantic representation of life science relationships in a computable format. The Network is provided in .XGMML format and can be viewed using freely available network visualization software, such as Cytoscape.

A modular cell-type focused inflammatory process network model for non-diseased pulmonary tissue.

Exposure to environmental stressors such as cigarette smoke (CS) elicits a variety of biological responses in humans, including the induction of inflammatory responses. These responses are especially pronounced in the lung, where pulmonary cells sit at the interface between the body's internal and external environments. We combined a literature survey with a computational analysis of multiple transcriptomic data sets to construct a computable causal network model (the Inflammatory Process Network (IPN)) of the main pulmonary inflammatory processes. The IPN model predicted decreased epithelial cell barrier defenses and increased mucus hypersecretion in human bronchial epithelial cells, and an attenuated pro-inflammatory (M1) profile in alveolar macrophages following exposure to CS, consistent with prior results. The IPN provides a comprehensive framework of experimentally supported pathways related to CS-induced pulmonary inflammation. The IPN is freely available to the scientific community as a resource with broad applicability to study the pathogenesis of pulmonary disease.

Construction of a computable cell proliferation network focused on non-diseased lung cells.

BACKGROUND: Critical to advancing the systems-level evaluation of complex biological processes is the development of comprehensive networks and computational methods to apply to the analysis of systems biology data (transcriptomics, proteomics/phosphoproteomics, metabolomics, etc.). Ideally, these networks will be specifically designed to capture the normal, non-diseased biology of the tissue or cell types under investigation, and can be used with experimentally generated systems biology data to assess the biological impact of perturbations like xenobiotics and other cellular stresses. Lung cell proliferation is a key biological process to capture in such a network model, given the pivotal role that proliferation plays in lung diseases including cancer, chronic obstructive pulmonary disease (COPD), and fibrosis. Unfortunately, no such network has been available prior to this work. RESULTS: To further a systems-level assessment of the biological impact of perturbations on non-diseased mammalian lung cells, we constructed a lung-focused network for cell proliferation. The network encompasses diverse biological areas that lead to the regulation of normal lung cell proliferation (Cell Cycle, Growth Factors, Cell Interaction, Intra- and Extracellular Signaling, and Epigenetics), and contains a total of 848 nodes (biological entities) and 1597 edges (relationships between biological entities). The network was verified using four published gene expression profiling data sets associated with measured cell proliferation endpoints in lung and lung-related cell types. Predicted changes in the activity of core machinery involved in cell cycle regulation (RB1, CDKN1A, and MYC/MYCN) are statistically supported across multiple data sets, underscoring the general applicability of this approach for a network-wide biological impact assessment using systems biology data. CONCLUSIONS: To the best of our knowledge, this lung-focused Cell Proliferation Network provides the most comprehensive connectivity map in existence of the molecular mechanisms regulating cell proliferation in the lung. The network is based on fully referenced causal relationships obtained from extensive evaluation of the literature. The computable structure of the network enables its application to the qualitative and quantitative evaluation of cell proliferation using systems biology data sets. The network is available for public use.

Normal human pluripotent stem cell lines exhibit pervasive mosaic aneuploidy.

Human pluripotent stem cell (hPSC) lines have been considered to be homogeneously euploid. Here we report that normal hPSC--including induced pluripotent--lines are karyotypic mosaics of euploid cells intermixed with many cells showing non-clonal aneuploidies as identified by chromosome counting, spectral karyotyping (SKY) and fluorescent in situ hybridization (FISH) of interphase/non-mitotic cells. This mosaic aneuploidy resembles that observed in progenitor cells of the developing brain and preimplantation embryos, suggesting that it is a normal, rather than pathological, feature of stem cell lines. The karyotypic heterogeneity generated by mosaic aneuploidy may contribute to the reported functional and phenotypic heterogeneity of hPSCs lines, as well as their therapeutic efficacy and safety following transplantation.

A computable cellular stress network model for non-diseased pulmonary and cardiovascular tissue.

BACKGROUND: Humans and other organisms are equipped with a set of responses that can prevent damage from exposure to a multitude of endogenous and environmental stressors. If these stress responses are overwhelmed, this can result in pathogenesis of diseases, which is reflected by an increased development of, e.g., pulmonary and cardiac diseases in humans exposed to chronic levels of environmental stress, including inhaled cigarette smoke (CS). Systems biology data sets (e.g., transcriptomics, phosphoproteomics, metabolomics) could enable comprehensive investigation of the biological impact of these stressors. However, detailed mechanistic networks are needed to determine which specific pathways are activated in response to different stressors and to drive the qualitative and eventually quantitative assessment of these data. A current limiting step in this process is the availability of detailed mechanistic networks that can be used as an analytical substrate. RESULTS: We have built a detailed network model that captures the biology underlying the physiological cellular response to endogenous and exogenous stressors in non-diseased mammalian pulmonary and cardiovascular cells. The contents of the network model reflect several diverse areas of signaling, including oxidative stress, hypoxia, shear stress, endoplasmic reticulum stress, and xenobiotic stress, that are elicited in response to common pulmonary and cardiovascular stressors. We then tested the ability of the network model to identify the mechanisms that are activated in response to CS, a broad inducer of cellular stress. Using transcriptomic data from the lungs of mice exposed to CS, the network model identified a robust increase in the oxidative stress response, largely mediated by the anti-oxidant NRF2 pathways, consistent with previous reports on the impact of CS exposure in the mammalian lung. CONCLUSIONS: The results presented here describe the construction of a cellular stress network model and its application towards the analysis of environmental stress using transcriptomic data. The proof-of-principle analysis described here, coupled with the future development of additional network models covering distinct areas of biology, will help to further clarify the integrated biological responses elicited by complex environmental stressors such as CS, in pulmonary and cardiovascular cells.

Neuronal DNA content variation (DCV) with regional and individual differences in the human brain.

It is widely assumed that the human brain contains genetically identical cells through which postgenomic mechanisms contribute to its enormous diversity and complexity. The relatively recent identification of neural cells throughout the neuraxis showing somatically generated mosaic aneuploidy indicates that the vertebrate brain can be genomically heterogeneous (Rehen et al. [2001] Proc. Natl. Acad. Sci. U. S. A. 98:13361-13366; Rehen et al. [2005] J. Neurosci. 25:2176-2180; Yurov et al. [2007] PLoS ONE:e558; Westra et al. [2008] J. Comp. Neurol. 507:1944-1951). The extent of human neural aneuploidy is currently unknown because of technically limited sample sizes, but is reported to be small (Iourov et al. [2006] Int. Rev. Cytol. 249:143-191). During efforts to interrogate larger cell populations by using DNA content analyses, a surprising result was obtained: human frontal cortex brain cells were found to display "DNA content variation (DCV)" characterized by an increased range of DNA content both in cell populations and within single cells. On average, DNA content increased by approximately 250 megabases, often representing a substantial fraction of cells within a given sample. DCV within individual human brains showed regional variation, with increased prevalence in the frontal cortex and less variation in the cerebellum. Further, DCV varied between individual brains. These results identify DCV as a new feature of the human brain, encompassing and further extending genomic alterations produced by aneuploidy, which may contribute to neural diversity in normal and pathophysiological states, altered functions of normal and disease-linked genes, and differences among individuals.

Aneuploid mosaicism in the developing and adult cerebellar cortex.

Neuroprogenitor cells (NPCs) in several telencephalic proliferative regions of the mammalian brain, including the embryonic cerebral cortex and postnatal subventricular zone (SVZ), display cell division "defects" in normal cells that result in aneuploid adult progeny. Here, we identify the developing cerebellum as a major, nontelencephalic proliferative region of the vertebrate central nervous system (CNS) that also produces aneuploid NPCs and nonmitotic cells. Mitotic NPCs assessed by metaphase chromosome analyses revealed that 15.3% and 20.8% of cerebellar NPCs are aneuploid at P0 and P7, respectively. By using immunofluorescent analysis of cerebellar NPCs, we show that chromosome segregation defects contribute to the generation of cells with an aneuploid genomic complement. Nonmitotic cells were assessed by fluorescence-activated cell sorting (FACS) coupled with fluorescence in situ hybridization (FISH), which revealed neuronal and nonneuronal aneuploid populations in both the adult mouse and human cerebellum. Taken together, these results demonstrate that the prevalence of neural aneuploidy includes nontelencephalic portions of the neuraxis and suggest that the generation and maintenance of aneuploid cells is a widespread, if not universal, property of central nervous system development and organization.