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

Virulence phenotypes of low-passage clinical isolates of Nontypeable Haemophilus influenzae assessed using the chinchilla laniger model of otitis media

<p>Abstract</p> <p>Background</p> <p>The nontypeable Haemophilus influenzae (NTHi) are associated with a spectrum of respiratory mucosal infections including: acute otitis media (AOM); chronic otitis media with effusion (COME); otorrhea; locally invasive diseases such as mastoiditis; as well as a range of systemic disease states, suggesting a wide range of virulence phenotypes. Genomic studies have demonstrated that each clinical strain contains a unique genic distribution from a population-based supragenome, the distributed genome hypothesis. These diverse clinical and genotypic findings suggest that each NTHi strain possesses a unique set of virulence factors that contributes to the course of the disease.</p> <p>Results</p> <p>The local and systemic virulence patterns of ten genomically characterized low-passage clinical NTHi strains (PittAA – PittJJ) obtained from children with COME or otorrhea were stratified using the chinchilla model of otitis media (OM). Each isolate was used to bilaterally inoculate six animals and thereafter clinical assessments were carried out daily for 8 days by blinded observers. There was no statistical difference in the time it took for any of the 10 NTHi strains to induce otologic (local) disease with respect to any or all of the other strains, however the differences in time to maximal local disease and the severity of local disease were both significant between the strains. Parameters of systemic disease indicated that the strains were not all equivalent: time to development of the systemic disease, maximal systemic scores and mortality were all statistically different among the strains. PittGG induced 100% mortality while PittBB, PittCC, and PittEE produced no mortality. Overall Pitt GG, PittII, and Pitt FF produced the most rapid and most severe local and systemic disease. A post hoc determination of the clinical origins of the 10 NTHi strains revealed that these three strains were of otorrheic origin, whereas the other 7 were from patients with COME.</p> <p>Conclusion</p> <p>Collectively these data suggest that the chinchilla OM model is useful for discriminating between otorrheic and COME NTHi strains as to their disease-producing potential in humans, and combined with whole genome analyses, point the way towards identifying classes of virulence genes.</p

Generation of Genic Diversity among Streptococcus pneumoniae Strains via Horizontal Gene Transfer during a Chronic Polyclonal Pediatric Infection

Although there is tremendous interest in understanding the evolutionary roles of horizontal gene transfer (HGT) processes that occur during chronic polyclonal infections, to date there have been few studies that directly address this topic. We have characterized multiple HGT events that most likely occurred during polyclonal infection among nasopharyngeal strains of Streptococcus pneumoniae recovered from a child suffering from chronic upper respiratory and middle-ear infections. Whole genome sequencing and comparative genomics were performed on six isolates collected during symptomatic episodes over a period of seven months. From these comparisons we determined that five of the isolates were genetically highly similar and likely represented a dominant lineage. We analyzed all genic and allelic differences among all six isolates and found that all differences tended to occur within contiguous genomic blocks, suggestive of strain evolution by homologous recombination. From these analyses we identified three strains (two of which were recovered on two different occasions) that appear to have been derived sequentially, one from the next, each by multiple recombination events. We also identified a fourth strain that contains many of the genomic segments that differentiate the three highly related strains from one another, and have hypothesized that this fourth strain may have served as a donor multiple times in the evolution of the dominant strain line. The variations among the parent, daughter, and grand-daughter recombinant strains collectively cover greater than seven percent of the genome and are grouped into 23 chromosomal clusters. While capturing in vivo HGT, these data support the distributed genome hypothesis and suggest that a single competence event in pneumococci can result in the replacement of DNA at multiple non-adjacent loci

Axial Globe Position Measurement: A Prospective Multicenter Study by the International Thyroid Eye Disease Society

Identify a reproducible measure of axial globe position (AGP) for multicenter studies on patients with thyroid eye disease (TED)

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