Genome-scale modeling of human metabolism – a systems biology approach

Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models – one of the fundamental aspects of systems biology – have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed.     

Genome-scale metabolic modeling of a clostridial co-culture for consolidated bioprocessing

An alternative consolidated bioprocessing approach is the use of a co-culture containing cellulolytic and solventogenic clostridia. It has been demonstrated that the rate of cellulose utilization in the co-culture of Clostridium acetobutylicum and Clostridium cellulolyticum is improved compared to the mono-culture of C. cellulolyticum, suggesting the presence of syntrophy between these two species. However, the metabolic interactions in the co-culture are not well understood. To understand the metabolic interactions in the co-culture, we developed a genome-scale metabolic model of C. cellulolyticum comprising of 431 genes, 621 reactions, and 603 metabolites. The C. cellulolyticum model can successfully predict the chemostat growth and byproduct secretion with cellulose as the substrate. However, a growth arrest phenomenon, which occurs in batch cultures of C. cellulolyticum at cellulose concentrations higher than 6.7 g/L, cannot be predicted by dynamic flux balance analysis due to the lack of understanding of the underlying mechanism. These genome-scale metabolic models of the pure cultures have also been integrated using a community modeling framework to develop a dynamic model of metabolic interactions in the co-culture. Co-culture simulations suggest that cellobiose inhibition cannot be the main factor that is responsible for improved cellulose utilization relative to mono-culture of C. cellulolyticum.     

集成灰色分析和元胞自动机用于景观动态模拟

针对景观生态系统"复杂性"的特点,采用灰色局势确定邻域转换规则,构建元胞自动机,用于模拟和分析景观生态动态变化.在信息不完全的情况下,提高了元胞自动机景观生态动态模型的可靠性和可行性.以中国云南省怒江流域中段作为实例,确定影响元胞转换规则的三因素主要有元胞邻域的聚集程度,土地适宜程度和人类活动影响程度,根据景观这一类复杂系统的动态变化特征其权重随地理空间位置和时间而变化,同时用Monte Carlo法考虑了模拟时转换的随机性.通过计算显示模拟未来发展的情景总的趋势是符合实际的,不但模拟了微观的景观单元的自组织机制,而且在一定程度上反映了宏观的社会经济因素影响,因而更具有针对性、典型性及准确性.     

A fold-recognition approach to loop modeling

A novel approach is proposed for modeling loop regions in proteins. In this approach, a prerequisite sequence-structure alignment is examined for regions where the target sequence is not covered by the structural template. These regions, extended with a number of residues from adjacent stem regions, are submitted to fold recognition. The alignments produced by fold recognition are integrated into the initial alignment to create an alignment between the target sequence and several structures, where gaps in the main structural template are covered by local structural templates. This one-to-many (1:N) alignment is used to create a protein model by existing protein-modeling techniques. Several alternative approaches were evaluated using a set of ten proteins. One approach was selected and evaluated using another set of 31 proteins. The most promising result was for gap regions not located at the C-terminus or N-terminus of a protein, where the method produced an average RMSD 12% lower than the loop modeling provided with the program MODELLER. This improvement is shown to be statistically significant. Figure The method derived from the training set applied to CASP target T0191     

Topological analysis of mass-balanced signaling networks: a framework to obtain network properties including crosstalk

Signal transduction networks have only been studied at a small scale because large-scale reconstructions and suitable in silico analysis methods have not been available. Since reconstructions of large signaling networks are progressing well there is now a need to develop a framework for analysing structural properties of signaling networks. One such framework is presented here, one that is based on systemically independent pathways and a mass-balanced representation of signaling events. This approach was applied to a prototypic signaling network and it allowed for: (1) a systemic analysis of all possible input/output relationships, (2) a quantitative evaluation of network crosstalk, or the interconnectivity of systemically independent pathways, (3) a measure of the redundancy in the signaling network, (4) the participation of reactions in signaling pathways, and (5) the calculation of correlated reaction sets. These properties emerge from network structure and can only be derived and studied within a defined mathematical framework. The calculations presented are the first of their kind for a signaling network, while similar analysis has been extensively performed for prototypic and genome-scale metabolic networks. This approach does not yet account for dynamic concentration profiles. Due to the scalability of the stoichiometric formalism used, the results presented for the prototypic signaling network can be obtained for large signaling networks once their reconstruction is completed.     

Engineering Bacteroides thetaiotaomicron to produce non-native butyrate based on a genome-scale metabolic model-guided design

Bacteroides thetaiotaomicron represents a major symbiont of the human gut microbiome that is increasingly viewed as a promising candidate strain for microbial therapeutics. Here, we engineer B. thetaiotaomicron for heterologous production of non-native butyrate as a proof-of-concept biochemical at therapeutically relevant concentrations. Since B. thetaiotaomicron is not a natural producer of butyrate, we heterologously expressed a butyrate biosynthetic pathway in the strain, which led to the production of butyrate at the final concentration of 12 mg/L in a rich medium. Further optimization of butyrate production was achieved by a round of metabolic engineering guided by an expanded genome-scale metabolic model (GEM) of B. thetaiotaomicron. The in silico knock-out simulation of the expanded model showed that pta and ldhD were the potent knock-out targets to enhance butyrate production. The maximum titer and specific productivity of butyrate in the pta-ldhD double knockout mutant increased by nearly 3.4 and 4.8 folds, respectively. To our knowledge, this is the first engineering attempt that enabled butyrate production from a non-butyrate producing commensal B. thetaiotaomicron. The study also highlights that B. thetaiotaomicron can serve as an effective strain for live microbial therapeutics in human.     

流程化的生态建模方法与科学工作流系统

科学工作流系统是由一系列经过特殊设计的数据分析与管理步骤组成的、按照一定的逻辑组织在一起, 并在给定的运行环境下, 完成特定科学研究的工作流管理系统。科学工作流系统致力于使全世界的科学家可以在一个简单易用的平台上交换思想, 共同设计全球尺度的实验, 共享数据、实验步骤与结果等。每一个科学家可以独立创建自己的工作流, 执行工作流并实时查看结果; 不同科学家之间也可以方便地共享和复用这些工作流。本文以开普勒系统(Kepler system)和生物多样性虚拟实验室(BioVeL)两个项目为例, 介绍了科学工作流的发展历史、背景、现有项目和应用等。以生态位模型工作流为例, 介绍了科学工作流的流程以及特点等。并通过对现有科学工作流的分析, 对其发展方向和存在的问题提出了自己的看法及预期。     

Three-dimensional modeling of the cochlea by use of an arc fitting approach

Purpose: A cochlea modeling approach is presented allowing for a user defined degree of geometry simplification which automatically adjusts to the patient specific anatomy. Model generation can be performed in a straightforward manner due to error estimation prior to the actual generation, thus minimizing modeling time. Therefore, the presented technique is well suited for a wide range of applications including finite element analyses where geometrical simplifications are often inevitable. Methods: The method is presented for n=5 cochleae which were segmented using a custom software for increased accuracy. The linear basilar membrane cross sections are expanded to areas while the scalae contours are reconstructed by a predefined number of arc segments. Prior to model generation, geometrical errors are evaluated locally for each cross section as well as globally for the resulting models and their basal turn profiles. The final combination of all reconditioned features to a 3D volume is performed in Autodesk Inventor using the loft feature. Results: Due to the volume generation based on cubic splines, low errors could be achieved even for low numbers of arc segments and provided cross sections, both of which correspond to a strong degree of model simplification. Model generation could be performed in a time efficient manner. Conclusion: The proposed simplification method was proven to be well suited for the helical cochlea geometry. The generated output data can be imported into commercial software tools for various analyses representing a time efficient way to create cochlea models optimally suited for the desired task.     

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.     

Multilevel modeling of chronotype and weekdays versus weekends to predict nonrestorative sleep

Nonrestorative sleep, a form of subjective sleep disturbance that has been largely neglected in the literature, is newly accessible to researchers via the validated restorative sleep questionnaire (RSQ). The daily version of the RSQ allows for analysis of within-subjects variation in restorative sleep across repeated samplings, and such day-to-day regularity in sleep variables has been highlighted as an important new direction for research. The present study used a sophisticated statistical approach, multilevel modeling, to examine the contributions of circadian chronotype, calendar day of questionnaire completion (weekends versus weekdays), and their interaction in explaining both interindividual and intraindividual variance in restorative sleep. Analyses were conducted using an archival dataset of college undergraduates who continuously completed daily RSQs over a 14-day sampling period. In the final multilevel model, possessing an evening type predicted lower restorative sleep between subjects, while sampling on weekdays predicted lower restorative sleep within subjects. Furthermore, a cross-level interaction was observed, such that the difference in restorative sleep on weekends versus weekdays was more pronounced among those with greater evening circadian preference. All of the effects were maintained after accounting for the significant influence of gender (women had less restorative sleep than men). These results are theoretically consistent with findings that evening types display stronger disparities in sleep schedules across free and workdays (i.e., social jet lag), and attest to the usefulness of multilevel models for statistically investigating how stable traits interact with factors that vary day to day (e.g., work or school schedules) in influencing sleep outcomes.     

A text mining approach to detect mentions of protein glycosylation in biomedical text

Protein Glycosylation is an important post translational event that plays a pivotal role in protein folding and protein is trafficking. We describe a dictionary based and a rule based approach to mine ‘mentions‘ of protein glycosylation in text. The dictionary based approach relies on a set of manually curated dictionaries specially constructed to address this task. Abstracts are then screened for the ‘mentions‘ of words from these dictionaries which are further scored followed by classification on the basis of a threshold. The rule based approaches also relies on the words in the dictionary to arrive at the features which are used for classification. The performance of the system using both the approaches has been evaluated using a manually curated corpus of 3133 abstracts. The evaluation suggests that the performance of the Rule based approach supersedes that of the Dictionary based approach.     

A new approach to study in vivo cellular metabolism using a modellistic analysis of magnetic resonance spectra

This paper presents a novel approach to study in vivo cellular kinetics by the combined use of magnetic resonance (MR) spectroscopy and Odum’s system modeling, which includes the entire process of substrate degradation and product formation. The experiment was conducted directly in the MR-probe, where microorganisms (Klebsiella planticola) were incubated with high ¹³C-glucose and ¹³C-xylose concentration. Sugar consumptions and ¹³C-ethanol production were followed for 17  h and MR-spectra were acquired every 30 min without external sampling.Fitting of data allowed evaluation of sugar degradation, ethanol formation, cell activation induced by substrates, as well as cell inhibition induced by ethanol. The dynamics related to the diauxic growth of the bacterium under study were analyzed in terms of different kinetic behaviors. This approach gives not only a good fit of theoretical to experimental results, but is able also to interpret the way substrates, cells and products interact with each other. The proposed methodology can be applied to different living systems to study complex novel mechanisms.     

An improved multi-scale approach to modeling habitat occupancy of northern bobwhite

Predicting species presence requires knowledge of detection of individuals, scale of model variables, model selection uncertainty, and spatial autocorrelation. Our objective was to incorporate recent modeling advances to predict potential habitat occupancy of northern bobwhite (Colinus virginianus). From 15 May–15 August 2008 and 2009, we conducted repeat-visit surveys at 360 sites within Delaware to sample presence of bobwhite. We randomly selected half the data to model scale-dependent relationships of bobwhite presence with metrics of landscape- and site-scale habitat composition and configuration. The final averaged habitat-occupancy model fit the remainder testing dataset with an area under the receiver operating characteristic curve value of 0.62. At the site scale, bobwhite presence was negatively related to interspersion and juxtaposition of early successional habitat (ESH; grassland and shrubland), ESH to forest edge density, and agriculture to forest edge density, though relative effect sizes were weak to moderate after accounting for model selection uncertainty. At the landscape scale, bobwhite presence was negatively related to patch cohesion of human development within 2.5 km and positively related to patch cohesion of ESH within 2.0 km, with both variables exerting strong effects. Bobwhite presence was also weakly and positively related to percentage of shrubland habitat within 1.0 km of the sampling point. We applied our habitat occupancy model to map the predicted presence of breeding bobwhite within the Delmarva Peninsula, USA. The modeling results and distribution map will provide guidance to State and Federal private land management programs in the Mid-Atlantic to identify where habitat management efforts will be most effective. Our methodology can also serve as a basis for future habitat modeling of bobwhite and other grassland–shrubland species across their range. © 2011 The Wildlife Society.     

A simple hierarchical approach to modeling distributions of substitution rates

Genetic sequence data typically exhibit variability in substitution rates across sites. In practice, there is often too little variation to fit a different rate for each site in the alignment, but the distribution of rates across sites may not be well modeled using simple parametric families. Mixtures of different distributions can capture more complex patterns of rate variation, but are often parameter-rich and difficult to fit. We present a simple hierarchical model in which a baseline rate distribution, such as a gamma distribution, is discretized into several categories, the quantiles of which are estimated using a discretized beta distribution. Although this approach involves adding only two extra parameters to a standard distribution, a wide range of rate distributions can be captured. Using simulated data, we demonstrate that a "beta-" model can reproduce the moments of the rate distribution more accurately than the distribution used to simulate the data, even when the baseline rate distribution is misspecified. Using hepatitis C virus and mammalian mitochondrial sequences, we show that a beta- model can fit as well or better than a model with multiple discrete rate categories, and compares favorably with a model which fits a separate rate category to each site. We also demonstrate this discretization scheme in the context of codon models specifically aimed at identifying individual sites undergoing adaptive or purifying evolution.     

Using the output from global circulation models to predict changes in the distribution and abundance of cereal aphids in Canada: a mechanistic modeling approach

Climate change will alter the abundance and distribution of species. Predicting these shifts is a challenge for ecologists and essential information for the formation of public policy. Here, I use a mechanistic mathematical model of the interaction between grass growth physiology and aphid population dynamics, coupled with the climate change projections from the UK's Hadley Centre HadCM3 global circulation model (GCM) and Canada's Center for Climate Modeling and Analysis CGCM2 GCM to predict the changes in the abundance and distribution of summer cereal aphid populations in wheat-growing regions of Canada. When used with the HadCM3 projections, the model predicts a latitudinal shift northward in abundances but there is longitudinal variation as well. However, when used with the CGCM2 projections the model predicts that continental regions will see a decline while coastal regions will see an increase in summer cereal aphid populations. These effects are stronger under the higher emissions scenarios.     

Understanding cyclical thrombocytopenia: a mathematical modeling approach

Cyclical thrombocytopenia (CT) is a rare hematological disease characterized by periodic oscillations in the platelet count. Although first reported in 1936, the pathogenesis and an effective therapy remain to be identified. Since besides fluctuations in platelet levels the patients hematological profile have been consistently normal, a destabilization of a peripheral control mechanism might play an important role in the genesis of this disorder. In this paper, we investigate through computer simulations the mechanisms underlying the platelet oscillations observed in CT. First, we collected the data published in the last 40 years and quantified the significance of the platelet fluctuations using Lomb-Scargle periodograms. Our analysis reveals that the incidence of the statistically significant periodic data is equally distributed in men and women. The mathematical model proposed in this paper captures the essential features of hematopoiesis and successfully duplicates the characteristics of CT. With the same parameter changes, the model is able to fit the platelet counts and to qualitatively reproduce the TPO oscillations (when data is available). Our results indicate that a variation in the megakaryocyte maturity, a slower relative growth rate of megakaryocytes, as well as an increased random destruction of platelets are the critical elements generating the platelet oscillations in CT.     

Ensemble modeling to predict habitat suitability for a large‐scale disturbance specialist

To conserve habitat for disturbance specialist species, ecologists must identify where individuals will likely settle in newly disturbed areas. Habitat suitability models can predict which sites at new disturbances will most likely attract specialists. Without validation data from newly disturbed areas, however, the best approach for maximizing predictive accuracy can be unclear (Northwestern U.S.A.). We predicted habitat suitability for nesting Black‐backed Woodpeckers (Picoides arcticus; a burned‐forest specialist) at 20 recently (≤6 years postwildfire) burned locations in Montana using models calibrated with data from three locations in Washington, Oregon, and Idaho. We developed 8 models using three techniques (weighted logistic regression, Maxent, and Mahalanobis D² models) and various combinations of four environmental variables describing burn severity, the north–south orientation of topographic slope, and prefire canopy cover. After translating model predictions into binary classifications (0 = low suitability to unsuitable, 1 = high to moderate suitability), we compiled “ensemble predictions,” consisting of the number of models (0–8) predicting any given site as highly suitable. The suitability status for 40% of the area burned by eastside Montana wildfires was consistent across models and therefore robust to uncertainty in the relative accuracy of particular models and in alternative ecological hypotheses they described. Ensemble predictions exhibited two desirable properties: (1) a positive relationship with apparent rates of nest occurrence at calibration locations and (2) declining model agreement outside surveyed environments consistent with our reduced confidence in novel (i.e., “no‐analogue”) environments. Areas of disagreement among models suggested where future surveys could help validate and refine models for an improved understanding of Black‐backed Woodpecker nesting habitat relationships. Ensemble predictions presented here can help guide managers attempting to balance salvage logging with habitat conservation in burned‐forest landscapes where black‐backed woodpecker nest location data are not immediately available. Ensemble modeling represents a promising tool for guiding conservation of large‐scale disturbance specialists.