Advances in Rule-based Modeling: Compartments, Energy, and Hybrid Simulation, with Application to Sepsis and Cell Signaling

Biological systems are commonly modeled as reaction networks, which describe the system at the resolution of biochemical species. Cellular systems, however, are governed by events at a finer scale: local interactions among macromolecular domains. The multi-domain structure of macromolecules, combined with the local nature of interactions, can lead to a combinatorial explosion that pushes reaction network methods to their limits. As an alternative, rule-based models (RBMs) describe the domain-based structure and local interactions found in biological systems. Molecular complexes are represented by graphs: functional domains as vertices, macromolecules as groupings of vertices, and molecular bonding as edges. Reaction rules, which describe classes of reactions, govern local modifications to molecular graphs, such as binding, post-translational modification, and degradation. RBMs can be transformed to equivalent reaction networks and simulated by differential or stochastic methods, or simulated directly with a network-free approach that avoids the problem of combinatorial complexity. Although RBMs and network-free methods resolve many problems in systems modeling, challenges remain. I address three challenges here: (i) managing model complexity due to cooperative interactions, (ii) representing biochemical systems in the compartmental setting of cells and organisms, and (iii) reducing the memory burden of large-scale network-free simulations. First, I present a general theory of energy-based modeling within the BioNetGen framework. Free energy is computed under a pattern-based formalism, and contextual variations within reaction classes are enumerated automatically. Next, I extend the BioNetGen language to permit description of compartmentalized biochemical systems, with treatment of volumes, surfaces and transport. Finally, a hybrid particle/population method is developed to reduce memory requirements of network-free simulations. All methods are implemented and available as part of BioNetGen. The remainder of this work presents an application to sepsis and inflammation. A multi-organ model of peritoneal infection and systemic inflammation is constructed and calibrated to experiment. Extra-corporeal blood purification, a potential treatment for sepsis, is explored in silico. Model simulations demonstrate that removal of blood cytokines and chemokines is a sufficient mechanism for improved survival in sepsis. However, differences between model predictions and the latest experimental data suggest directions for further exploration

BioNetGen 2.2: Advances in Rule-Based Modeling

BioNetGen is an open-source software package for rule-based modeling of complex biochemical systems. Version 2.2 of the software introduces numerous new features for both model specification and simulation. Here, we report on these additions, discussing how they facilitate the construction, simulation, and analysis of larger and more complex models than previously possible.Comment: 3 pages, 1 figure, 1 supplementary text file. Supplementary text includes a brief discussion of the RK-PLA along with a performance analysis, two tables listing all new actions/arguments added in BioNetGen 2.2, and the "BioNetGen Quick Reference Guide". Accepted for publication in Bioinformatic

Characterization and modeling of the Haemophilus influenzae core and supragenomes based on the complete genomic sequences of Rd and 12 clinical nontypeable strains

The genomes of 9 non-typeable H. influenzae clinical isolates were sequenced and compared with a reference strain, allowing the characterisation and modelling of the core-and supra genomes of this organism

The DEEP2 Galaxy Redshift Survey: Design, Observations, Data Reduction, and Redshifts

We describe the design and data sample from the DEEP2 Galaxy Redshift Survey, the densest and largest precision-redshift survey of galaxies at z ~ 1 completed to date. The survey has conducted a comprehensive census of massive galaxies, their properties, environments, and large-scale structure down to absolute magnitude M_B = -20 at z ~ 1 via ~90 nights of observation on the DEIMOS spectrograph at Keck Observatory. DEEP2 covers an area of 2.8 deg^2 divided into four separate fields, observed to a limiting apparent magnitude of R_AB=24.1. Objects with z < 0.7 are rejected based on BRI photometry in three of the four DEEP2 fields, allowing galaxies with z > 0.7 to be targeted ~2.5 times more efficiently than in a purely magnitude-limited sample. Approximately sixty percent of eligible targets are chosen for spectroscopy, yielding nearly 53,000 spectra and more than 38,000 reliable redshift measurements. Most of the targets which fail to yield secure redshifts are blue objects that lie beyond z ~ 1.45. The DEIMOS 1200-line/mm grating used for the survey delivers high spectral resolution (R~6000), accurate and secure redshifts, and unique internal kinematic information. Extensive ancillary data are available in the DEEP2 fields, particularly in the Extended Groth Strip, which has evolved into one of the richest multiwavelength regions on the sky. DEEP2 surpasses other deep precision-redshift surveys at z ~ 1 in terms of galaxy numbers, redshift accuracy, sample number density, and amount of spectral information. We also provide an overview of the scientific highlights of the DEEP2 survey thus far. This paper is intended as a handbook for users of the DEEP2 Data Release 4, which includes all DEEP2 spectra and redshifts, as well as for the publicly-available DEEP2 DEIMOS data reduction pipelines. [Abridged]Comment: submitted to ApJS; data products available for download at http://deep.berkeley.edu/DR4

Ensemble Models of Neutrophil Trafficking in Severe Sepsis

A hallmark of severe sepsis is systemic inflammation which activates leukocytes and can result in their misdirection. This leads to both impaired migration to the locus of infection and increased infiltration into healthy tissues. In order to better understand the pathophysiologic mechanisms involved, we developed a coarse-grained phenomenological model of the acute inflammatory response in CLP (cecal ligation and puncture)-induced sepsis in rats. This model incorporates distinct neutrophil kinetic responses to the inflammatory stimulus and the dynamic interactions between components of a compartmentalized inflammatory response. Ensembles of model parameter sets consistent with experimental observations were statistically generated using a Markov-Chain Monte Carlo sampling. Prediction uncertainty in the model states was quantified over the resulting ensemble parameter sets. Forward simulation of the parameter ensembles successfully captured experimental features and predicted that systemically activated circulating neutrophils display impaired migration to the tissue and neutrophil sequestration in the lung, consequently contributing to tissue damage and mortality. Principal component and multiple regression analyses of the parameter ensembles estimated from survivor and non-survivor cohorts provide insight into pathologic mechanisms dictating outcome in sepsis. Furthermore, the model was extended to incorporate hypothetical mechanisms by which immune modulation using extracorporeal blood purification results in improved outcome in septic rats. Simulations identified a sub-population (about of the treated population) that benefited from blood purification. Survivors displayed enhanced neutrophil migration to tissue and reduced sequestration of lung neutrophils, contributing to improved outcome. The model ensemble presented herein provides a platform for generating and testing hypotheses in silico, as well as motivating further experimental studies to advance understanding of the complex biological response to severe infection, a problem of growing magnitude in humans

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr

PSR J1024-0719:A Millisecond Pulsar in an Unusual Long-Period Orbit

PSR J1024-0719 is a millisecond pulsar that was long thought to be isolated. However, puzzling results concerning its velocity, distance, and low rotational period derivative have led to a reexamination of its properties. We present updated radio timing observations along with new and archival optical data which show that PSR J1024-0719 is most likely in a long-period (2-20 kyr) binary system with a low-mass (approximate to 0.4 M-circle dot), low-metallicity (Z approximate to -0.9 dex) main-sequence star. Such a system can explain most of the anomalous properties of this pulsar. We suggest that this system formed through a dynamical exchange in a globular cluster that ejected it into a halo orbit, which is consistent with the low observed metallicity for the stellar companion. Further astrometric and radio timing observations such as measurement of the third period derivative could strongly constrain the range of orbital parameters

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy