MC3: a steady-state model and constraint consistency checker for biochemical networks

BACKGROUND: Stoichiometric models provide a structural framework for analyzing steady-state cellular behavior. Models are developed either through augmentations of existing models or more recently through automatic reconstruction tools. There is currently no standardized practice or method for validating the properties of a model before placing it in the public domain. Considerable effort is often required to understand a model’s inconsistencies before its reuse within new research efforts. RESULTS: We present a review of common issues in stoichiometric models typically uncovered during pathway analysis and constraint-based optimization, and we detail succinct and efficient ways to find them. We present MC(3), Model and Constraint Consistency Checker, a computational tool that can be used for two purposes: (a) identifying potential connectivity and topological issues for a given stoichiometric matrix, S, and (b) flagging issues that arise during constraint-based optimization. The MC(3) tool includes three distinct checking components. The first examines the results of computing the basis for the null space for Sv = 0; the second uses connectivity analysis; and the third utilizes Flux Variability Analysis. MC(3) takes as input a stoichiometric matrix and flux constraints, and generates a report summarizing issues. CONCLUSIONS: We report the results of applying MC(3) to published models for several systems including Escherichia coli, an adipocyte cell, a Chinese Hamster Ovary cell, and Leishmania major. Several issues with no prior documentation are identified. MC(3) provides a standalone MATLAB-based comprehensive tool for model validation, a task currently performed either ad hoc or implemented in part within other computational tools

Probabilistic strain optimization under constraint uncertainty

Mona Yousofshahi and Soha Hassoun are with the Department of Computer Science, Tufts University, Medford, MA, USA -- Michael Orshansky is with the Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA -- Kyongbum Lee is with the Department of Chemical and Biological Engineering, Tufts University, Medford, MA, USABackground: An important step in strain optimization is to identify reactions whose activities should be modified to achieve the desired cellular objective. Preferably, these reactions are identified systematically, as the number of possible combinations of reaction modifications could be very large. Over the last several years, a number of computational methods have been described for identifying combinations of reaction modifications. However, none of these methods explicitly address uncertainties in implementing the reaction activity modifications. In this work, we model the uncertainties as probability distributions in the flux carrying capacities of reactions. Based on this model, we develop an optimization method that identifies reactions for flux capacity modifications to predict outcomes with high statistical likelihood. Results: We compare three optimization methods that select an intervention set comprising up- or down-regulation of reaction flux capacity: CCOpt (Chance constrained optimization), DetOpt (Deterministic optimization), and MCOpt (Monte Carlo-based optimization). We evaluate the methods using a Monte Carlo simulation-based method, MCEval (Monte Carlo Evaluations). We present two case studies analyzing a CHO cell and an adipocyte model. The flux capacity distributions required for our methods were estimated from maximal reaction velocities or elementary mode analysis. The intervention set selected by CCOpt consistently outperforms the intervention set selected by DetOpt in terms of tolerance to flux capacity variations. MCEval shows that the optimal flux predicted based on the CCOpt intervention set is more likely to be obtained, in a probabilistic sense, than the flux predicted by DetOpt. The intervention sets identified by CCOpt and MCOpt were similar; however, the exhaustive sampling required by MCOpt incurred significantly greater computational cost. Conclusions: Maximizing tolerance to variable engineering outcomes (in modifying enzyme activities) can identify intervention sets that statistically improve the desired cellular objective.Electrical and Computer [email protected]

Additional file 1: of PROXIMAL: a method for Prediction of Xenobiotic Metabolism

This file includes a list of substrates used in estimating cytochrome P450 enzyme activity. The data is collected for the following 9 CYP enzymes: 1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A4. (PDF 120 kb

Safety and Upper Respiratory Pharmacokinetics of the Hemagglutinin Stalk-Binding Antibody VIS410 Support Treatment and Prophylaxis Based on Population Modeling of Seasonal Influenza A Outbreaks

Background: Seasonal influenza is a major public health concern in vulnerable populations. Here we investigated the safety, tolerability, and pharmacokinetics of a broadly neutralizing monoclonal antibody (VIS410) against Influenza A in a Phase 1 clinical trial. Based on these results and preclinical data, we implemented a mathematical modeling approach to investigate whether VIS410 could be used prophylactically to lessen the burden of a seasonal influenza epidemic and to protect at-risk groups from associated complications. Methods: Using a single-ascending dose study (n = 41) at dose levels from 2 mg/kg–50 mg/kg we evaluated the safety as well as the serum and upper respiratory pharmacokinetics of a broadly-neutralizing antibody (VIS410) against influenza A (ClinicalTrials.gov identifier NCT02045472). Our primary endpoints were safety and tolerability of VIS410 compared to placebo. We developed an epidemic microsimulation model testing the ability of VIS410 to mitigate attack rates and severe disease in at risk-populations. Findings: VIS410 was found to be generally safe and well-tolerated at all dose levels, from 2–50 mg/kg. Overall, 27 of 41 subjects (65.9%) reported a total of 67 treatment emergent adverse events (TEAEs). TEAEs were reported by 20 of 30 subjects (66.7%) who received VIS410 and by 7 of 11 subjects (63.6%) who received placebo. 14 of 16 TEAEs related to study drug were considered mild (Grade 1) and 2 were moderate (Grade 2). Two subjects (1 subject who received 30 mg/kg VIS410 and 1 subject who received placebo) experienced serious AEs (Grade 3 or 4 TEAEs) that were not related to study drug. VIS410 exposure was approximately dose-proportional with a mean half-life of 12.9 days. Mean VIS410 Cmax levels in the upper respiratory tract were 20.0 and 25.3 μg/ml at the 30 mg/kg and 50 mg/kg doses, respectively, with corresponding serum Cmax levels of 980.5 and 1316 μg/mL. Using these pharmacokinetic data, a microsimulation model showed that median attack rate reductions ranged from 8.6% (interquartile range (IQR): 4.7%–11.0%) for 2% coverage to 22.6% (IQR: 12.7–30.0%) for 6% coverage. The overall benefits to the elderly, a vulnerable subgroup, are largest when VIS410 is distributed exclusively to elderly individuals, resulting in reductions in hospitalization rates between 11.4% (IQR: 8.2%–13.3%) for 2% coverage and 30.9% (IQR: 24.8%–35.1%) for 6% coverage among those more than 65 years of age. Interpretation: VIS410 was generally safe and well tolerated and had good relative exposure in both serum and upper respiratory tract, supporting its use as either a single-dose therapeutic or prophylactic for influenza A. Including VIS410 prophylaxis among the public health interventions for seasonal influenza has the potential to lower attack rates and substantially reduce hospitalizations in individuals over the age of 65. Funding: Visterra, Inc