Astrocytes in the Optic Nerve Are Heterogeneous in Their Reactivity to Glaucomatous Injury.

The optic nerve head is thought to be the site of initial injury to retinal ganglion cell injury in glaucoma. In the initial segment of the optic nerve directly behind the globe, the ganglion cell axons are unmyelinated and come into direct contact to astrocytes, suggesting that astrocytes may play a role in the pathology of glaucoma. As in other parts of the CNS, optic nerve head astrocytes respond to injury by characteristic changes in cell morphology and gene expression profile. Using RNA-sequencing of glaucomatous optic nerve heads, single-cell PCR, and an in-vivo assay, we demonstrate that an up-regulation of astrocytic phagocytosis is an early event after the onset of increased intraocular pressure. We also show that astrocytes in the glial lamina of the optic nerve are apparently functionally heterogeneous. At any time, even in naïve nerves, some of the cells show signs of reactivity-process hypertrophy, high phagocytic activity, and expression of genetic markers of reactivity whereas neighboring cells apparently are inactive. A period of increased intraocular pressure moves more astrocytes towards the reactive phenotype; however, some cells remain unreactive even in glaucomatous nerves.

IRF3 and type I interferons fuel a fatal response to myocardial infarction.

Interferon regulatory factor 3 (IRF3) and type I interferons (IFNs) protect against infections and cancer, but excessive IRF3 activation and type I IFN production cause autoinflammatory conditions such as Aicardi-Goutières syndrome and STING-associated vasculopathy of infancy (SAVI). Myocardial infarction (MI) elicits inflammation, but the dominant molecular drivers of MI-associated inflammation remain unclear. Here we show that ischemic cell death and uptake of cell debris by macrophages in the heart fuel a fatal response to MI by activating IRF3 and type I IFN production. In mice, single-cell RNA-seq analysis of 4,215 leukocytes isolated from infarcted and non-infarcted hearts showed that MI provokes activation of an IRF3-interferon axis in a distinct population of interferon-inducible cells (IFNICs) that were classified as cardiac macrophages. Mice genetically deficient in cyclic GMP-AMP synthase (cGAS), its adaptor STING, IRF3, or the type I IFN receptor IFNAR exhibited impaired interferon-stimulated gene (ISG) expression and, in the case of mice deficient in IRF3 or IFNAR, improved survival after MI as compared to controls. Interruption of IRF3-dependent signaling resulted in decreased cardiac expression of inflammatory cytokines and chemokines and decreased inflammatory cell infiltration of the heart, as well as in attenuated ventricular dilation and improved cardiac function. Similarly, treatment of mice with an IFNAR-neutralizing antibody after MI ablated the interferon response and improved left ventricular dysfunction and survival. These results identify IRF3 and the type I IFN response as a potential therapeutic target for post-MI cardioprotection.

Genome-wide identification of autosomal genes with allelic imbalance of chromatin state.

In mammals, monoallelic gene expression can result from X-chromosome inactivation, genomic imprinting, and random monoallelic expression (RMAE). Epigenetic regulation of RMAE is not fully understood. Here we analyze allelic imbalance in chromatin state of autosomal genes using ChIP-seq in a clonal cell line. We identify approximately 3.7% of autosomal genes that show significant differences between chromatin states of two alleles. Allelic regulation is represented among several functional gene categories including histones, chromatin modifiers, and multiple early developmental regulators. Most cases of allelic skew are produced by quantitative differences between two allelic chromatic states that belong to the same gross type (active, silent, or bivalent). Combinations of allelic states of different types are possible but less frequent. When different chromatin marks are skewed on the same gene, their skew is coordinated as a result of quantitative relationships between these marks on each individual allele. Finally, combination of allele-specific densities of chromatin marks is a quantitative predictor of allelic skew in gene expression.

Prolonged Mek1/2 suppression impairs the developmental potential of embryonic stem cells.

Concomitant activation of the Wnt pathway and suppression of Mapk signalling by two small molecule inhibitors (2i) in the presence of leukaemia inhibitory factor (LIF) (hereafter termed 2i/L) induces a naive state in mouse embryonic stem (ES) cells that resembles the inner cell mass (ICM) of the pre-implantation embryo. Since the ICM exists only transiently in vivo, it remains unclear how sustained propagation of naive ES cells in vitro affects their stability and functionality. Here we show that prolonged culture of male mouse ES cells in 2i/L results in irreversible epigenetic and genomic changes that impair their developmental potential. Furthermore, we find that female ES cells cultured in conventional serum plus LIF medium phenocopy male ES cells cultured in 2i/L. Mechanistically, we demonstrate that the inhibition of Mek1/2 is predominantly responsible for these effects, in part through the downregulation of DNA methyltransferases and their cofactors. Finally, we show that replacement of the Mek1/2 inhibitor with a Src inhibitor preserves the epigenetic and genomic integrity as well as the developmental potential of ES cells. Taken together, our data suggest that, although short-term suppression of Mek1/2 in ES cells helps to maintain an ICM-like epigenetic state, prolonged suppression results in irreversible changes that compromise their developmental potential.

DUSP9 Modulates DNA Hypomethylation in Female Mouse Pluripotent Stem Cells.

Blastocyst-derived embryonic stem cells (ESCs) and gonad-derived embryonic germ cells (EGCs) represent two classic types of pluripotent cell lines, yet their molecular equivalence remains incompletely understood. Here, we compare genome-wide methylation patterns between isogenic ESC and EGC lines to define epigenetic similarities and differences. Surprisingly, we find that sex rather than cell type drives methylation patterns in ESCs and EGCs. Cell fusion experiments further reveal that the ratio of X chromosomes to autosomes dictates methylation levels, with female hybrids being hypomethylated and male hybrids being hypermethylated. We show that the X-linked MAPK phosphatase DUSP9 is upregulated in female compared to male ESCs, and its heterozygous loss in female ESCs leads to male-like methylation levels. However, male and female blastocysts are similarly hypomethylated, indicating that sex-specific methylation differences arise in culture. Collectively, our data demonstrate the epigenetic similarity of sex-matched ESCs and EGCs and identify DUSP9 as a regulator of female-specific hypomethylation.

Macrophages Facilitate Electrical Conduction in the Heart.

Organ-specific functions of tissue-resident macrophages in the steady-state heart are unknown. Here, we show that cardiac macrophages facilitate electrical conduction through the distal atrioventricular node, where conducting cells densely intersperse with elongated macrophages expressing connexin 43. When coupled to spontaneously beating cardiomyocytes via connexin-43-containing gap junctions, cardiac macrophages have a negative resting membrane potential and depolarize in synchrony with cardiomyocytes. Conversely, macrophages render the resting membrane potential of cardiomyocytes more positive and, according to computational modeling, accelerate their repolarization. Photostimulation of channelrhodopsin-2-expressing macrophages improves atrioventricular conduction, whereas conditional deletion of connexin 43 in macrophages and congenital lack of macrophages delay atrioventricular conduction. In the Cd11bDTR mouse, macrophage ablation induces progressive atrioventricular block. These observations implicate macrophages in normal and aberrant cardiac conduction.

Mutation of a nucleosome compaction region disrupts Polycomb-mediated axial patterning.

Nucleosomes play important structural and regulatory roles by tightly wrapping the DNA that constitutes the metazoan genome. The Polycomb group (PcG) proteins modulate nucleosomes to maintain repression of key developmental genes, including Hox genes whose temporal and spatial expression is tightly regulated to guide patterning of the anterior-posterior body axis. CBX2, a component of the mammalian Polycomb repressive complex 1 (PRC1), contains a compaction region that has the biochemically defined activity of bridging adjacent nucleosomes. Here, we demonstrate that a functional compaction region is necessary for proper body patterning, because mutating this region leads to homeotic transformations similar to those observed with PcG loss-of-function mutations. We propose that CBX2-driven nucleosome compaction is a key mechanism by which PcG proteins maintain gene silencing during mouse development.

Survival in Quiescence Requires the Euchromatic Deployment of Clr4/SUV39H by Argonaute-Associated Small RNAs.

Quiescence (G0) is a ubiquitous stress response through which cells enter reversible dormancy, acquiring distinct properties including reduced metabolism, resistance to stress, and long life. G0 entry involves dramatic changes to chromatin and transcription of cells, but the mechanisms coordinating these processes remain poorly understood. Using the fission yeast, here, we track G0-associated chromatin and transcriptional changes temporally and show that as cells enter G0, their survival and global gene expression programs become increasingly dependent on Clr4/SUV39H, the sole histone H3 lysine 9 (H3K9) methyltransferase, and RNAi proteins. Notably, G0 entry results in RNAi-dependent H3K9 methylation of several euchromatic pockets, prior to which Argonaute1-associated small RNAs from these regions emerge. Overall, our data reveal another function for constitutive heterochromatin proteins (the establishment of the global G0 transcriptional program) and suggest that stress-induced alterations in Argonaute-associated sRNAs can target the deployment of transcriptional regulatory proteins to specific sequences.

Approximating frustration scores in complex networks via perturbed Laplacian spectra.

Systems of many interacting components, as found in physics, biology, infrastructure, and the social sciences, are often modeled by simple networks of nodes and edges. The real-world systems frequently confront outside intervention or internal damage whose impact must be predicted or minimized, and such perturbations are then mimicked in the models by altering nodes or edges. This leads to the broad issue of how to best quantify changes in a model network after some type of perturbation. In the case of node removal there are many centrality metrics which associate a scalar quantity with the removed node, but it can be difficult to associate the quantities with some intuitive aspect of physical behavior in the network. This presents a serious hurdle to the application of network theory: real-world utility networks are rarely altered according to theoretic principles unless the kinetic impact on the network's users are fully appreciated beforehand. In pursuit of a kinetically interpretable centrality score, we discuss the f-score, or frustration score. Each f-score quantifies whether a selected node accelerates or inhibits global mean first passage times to a second, independently selected target node. We show that this is a natural way of revealing the dynamical importance of a node in some networks. After discussing merits of the f-score metric, we combine spectral and Laplacian matrix theory in order to quickly approximate the exact f-score values, which can otherwise be expensive to compute. Following tests on both synthetic and real medium-sized networks, we report f-score runtime improvements over exact brute force approaches in the range of 0 to 400% with low error (<3%).

Quantifying the Sources of Kinetic Frustration in Folding Simulations of Small Proteins.

Experiments and atomistic simulations of polypeptides have revealed structural intermediates that promote or inhibit conformational transitions to the native state during folding. We invoke a concept of "kinetic frustration" to quantify the prevalence and impact of these behaviors on folding rates within a large set of atomistic simulation data for 10 fast-folding proteins, where each protein's conformational space is represented as a Markov state model of conformational transitions. Our graph theoretic approach addresses what conformational features correlate with folding inhibition and therefore permits comparison among features within a single protein network and also more generally between proteins. Nonnative contacts and nonnative secondary structure formation can thus be quantitatively implicated in inhibiting folding for several of the tested peptides.

Protein conformational populations and functionally relevant substates.

Functioning proteins do not remain fixed in a unique structure, but instead they sample a range of conformations facilitated by motions within the protein. Even in the native state, a protein exists as a collection of interconverting conformations driven by thermodynamic fluctuations. Motions on the fast time scale allow a protein to sample conformations in the nearby area of its conformational landscape, while motions on slower time scales give it access to conformations in distal areas of the landscape. Emerging evidence indicates that protein landscapes contain conformational substates with dynamic and structural features that support the designated function of the protein. Nuclear magnetic resonance (NMR) experiments provide information about conformational ensembles of proteins. X-ray crystallography allows researchers to identify the most populated states along the landscape, and computational simulations give atom-level information about the conformational substates of different proteins. This ability to characterize and obtain quantitative information about the conformational substates and the populations of proteins within them is allowing researchers to better understand the relationship between protein structure and dynamics and the mechanisms of protein function. In this Account, we discuss recent developments and challenges in the characterization of functionally relevant conformational populations and substates of proteins. In some enzymes, the sampling of functionally relevant conformational substates is connected to promoting the overall mechanism of catalysis. For example, the conformational landscape of the enzyme dihydrofolate reductase has multiple substates, which facilitate the binding and the release of the cofactor and substrate and catalyze the hydride transfer. For the enzyme cyclophilin A, computational simulations reveal that the long time scale conformational fluctuations enable the enzyme to access conformational substates that allow it to attain the transition state, therefore promoting the reaction mechanism. In the long term, this emerging view of proteins with conformational substates has broad implications for improving our understanding of enzymes, enzyme engineering, and better drug design. Researchers have already used photoactivation to modulate protein conformations as a strategy to develop a hypercatalytic enzyme. In addition, the alteration of the conformational substates through binding of ligands at locations other than the active site provides the basis for the design of new medicines through allosteric modulation.

Modeling boundary conditions for balanced proliferation in metastatic latency.

PURPOSE: Nearly half of cancer metastases become clinically evident five or more years after primary tumor treatment; thus, metastatic cells survived without emerging for extended periods. This dormancy has been explained by at least two countervailing scenarios: cellular quiescence and balanced proliferation; these entail dichotomous mechanistic etiologies. To examine the boundary parameters for balanced proliferation, we conducted in silico modeling. EXPERIMENTAL DESIGN: To illuminate the balanced proliferation hypothesis, we explored the specific boundary probabilities under which proliferating micrometastases would remain dormant. A two-state Markov chain Monte Carlo model simulated micrometastatic proliferation and death according to stochastic survival probabilities. We varied these probabilities across 100 simulated patients each with 1,000 metastatic deposits and documented whether the micrometastases exceeded one million cells, died out, or remained dormant (survived 1,218 generations). RESULTS: The simulations revealed a narrow survival probability window (49.7-50.8%) that allowed for dormancy across a range of starting cell numbers, and even then for only a small fraction of micrometastases. The majority of micrometastases died out quickly even at survival probabilities that led to rapid emergence of a subset of micrometastases. Within dormant metastases, cell populations depended sensitively on small survival probability increments. CONCLUSIONS: Metastatic dormancy as explained solely by balanced proliferation is bounded by very tight survival probabilities. Considering the far larger survival variability thought to attend fluxing microenvironments, it is more probable that these micrometastatic nodules undergo at least periods of quiescence rather than exclusively being controlled by balanced proliferation.

Event detection and sub-state discovery from biomolecular simulations using higher-order statistics: application to enzyme adenylate kinase.

Biomolecular simulations at millisecond and longer time-scales can provide vital insights into functional mechanisms. Because post-simulation analyses of such large trajectory datasets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi-anharmonic analysis (QAA) (Ramanathan et al., PLoS One 2011;6:e15827), for partitioning the conformational landscape into a hierarchy of functionally relevant sub-states. The unique capabilities of QAA are enabled by exploiting anharmonicity in the form of fourth-order statistics for characterizing atomic fluctuations. In this article, we extend QAA for analyzing long time-scale simulations online. In particular, we present HOST4MD--a higher-order statistical toolbox for molecular dynamics simulations, which (1) identifies key dynamical events as simulations are in progress, (2) explores potential sub-states, and (3) identifies conformational transitions that enable the protein to access those sub-states. We demonstrate HOST4MD on microsecond timescale simulations of the enzyme adenylate kinase in its apo state. HOST4MD identifies several conformational events in these simulations, revealing how the intrinsic coupling between the three subdomains (LID, CORE, and NMP) changes during the simulations. Further, it also identifies an inherent asymmetry in the opening/closing of the two binding sites. We anticipate that HOST4MD will provide a powerful and extensible framework for detecting biophysically relevant conformational coordinates from long time-scale simulations.

Quasi-anharmonic analysis reveals intermediate states in the nuclear co-activator receptor binding domain ensemble.

The molten globule nuclear receptor co-activator binding domain (NCBD) of CREB binding protein (CBP) selectively recruits transcription co-activators (TCAs) during the formation of the transcription preinitiation complex. NCBD:TCA interactions have been implicated in several cancers, however, the mechanisms of NCBD:TCA recognition remain uncharacterized. NCBD:TCA intermolecular recognition has challenged traditional investigation as both NCBD and several of its corresponding TCAs are intrinsically disordered. Using 40µs of explicit solvent molecular dynamics simulations, we relate the conformational diversity of ligand-free NCBD to its bound configurations. We introduce two novel techniques to quantify the conformational heterogeneity of ligand-free NCBD, dihedral quasi-anharmonic analysis (dQAA) and hierarchical graph-based diffusive clustering. With this integrated approach we find that three of four ligand-bound states are natively accessible to the ligand-free NCBD simulations with root-mean squared deviation (RMSD) less than 2Å These conformations are accessible via diverse pathways while a rate-limiting barrier must be crossed in order to access the fourth bound state.

QAARM: quasi-anharmonic autoregressive model reveals molecular recognition pathways in ubiquitin.

MOTIVATION: Molecular dynamics (MD) simulations have dramatically improved the atomistic understanding of protein motions, energetics and function. These growing datasets have necessitated a corresponding emphasis on trajectory analysis methods for characterizing simulation data, particularly since functional protein motions and transitions are often rare and/or intricate events. Observing that such events give rise to long-tailed spatial distributions, we recently developed a higher-order statistics based dimensionality reduction method, called quasi-anharmonic analysis (QAA), for identifying biophysically-relevant reaction coordinates and substates within MD simulations. Further characterization of conformation space should consider the temporal dynamics specific to each identified substate. RESULTS: Our model uses hierarchical clustering to learn energetically coherent substates and dynamic modes of motion from a 0.5 µs ubiqutin simulation. Autoregressive (AR) modeling within and between states enables a compact and generative description of the conformational landscape as it relates to functional transitions between binding poses. Lacking a predictive component, QAA is extended here within a general AR model appreciative of the trajectory's temporal dependencies and the specific, local dynamics accessible to a protein within identified energy wells. These metastable states and their transition rates are extracted within a QAA-derived subspace using hierarchical Markov clustering to provide parameter sets for the second-order AR model. We show the learned model can be extrapolated to synthesize trajectories of arbitrary length. CONTACT: ramanathana@ornl.gov; chakracs@pitt.edu.

Discovering conformational sub-states relevant to protein function.

BACKGROUND: Internal motions enable proteins to explore a range of conformations, even in the vicinity of native state. The role of conformational fluctuations in the designated function of a protein is widely debated. Emerging evidence suggests that sub-groups within the range of conformations (or sub-states) contain properties that may be functionally relevant. However, low populations in these sub-states and the transient nature of conformational transitions between these sub-states present significant challenges for their identification and characterization. METHODS AND FINDINGS: To overcome these challenges we have developed a new computational technique, quasi-anharmonic analysis (QAA). QAA utilizes higher-order statistics of protein motions to identify sub-states in the conformational landscape. Further, the focus on anharmonicity allows identification of conformational fluctuations that enable transitions between sub-states. QAA applied to equilibrium simulations of human ubiquitin and T4 lysozyme reveals functionally relevant sub-states and protein motions involved in molecular recognition. In combination with a reaction pathway sampling method, QAA characterizes conformational sub-states associated with cis/trans peptidyl-prolyl isomerization catalyzed by the enzyme cyclophilin A. In these three proteins, QAA allows identification of conformational sub-states, with critical structural and dynamical features relevant to protein function. CONCLUSIONS: Overall, QAA provides a novel framework to intuitively understand the biophysical basis of conformational diversity and its relevance to protein function.