CiliateGEM: an open-project and a tool for predictions of ciliate metabolic variations and experimental condition design

Background

The study of cell metabolism is becoming central in several fields such as biotechnology, evolution/adaptation and human disease investigations. Here we present CiliateGEM, the first metabolic network reconstruction draft of the freshwater ciliate Tetrahymena thermophila. We also provide the tools and resources to simulate different growth conditions and to predict metabolic variations. CiliateGEM can be extended to other ciliates in order to set up a meta-model, i.e. a metabolic network reconstruction valid for all ciliates.Ciliates are complex unicellular eukaryotes of presumably monophyletic origin, with a phylogenetic position that is equal from plants and animals. These cells represent a new concept of unicellular system with a high degree of species, population biodiversity and cell complexity. Ciliates perform in a single cell all the functions of a pluricellular organism, including locomotion, feeding, digestion, and sexual processes.

Results

After generating the model, we performed an in-silico simulation with the presence and absence of glucose. The lack of this nutrient caused a 32.1% reduction rate in biomass synthesis. Despite the glucose starvation, the growth did not stop due to the use of alternative carbon sources such as amino acids.

Conclusions

The future models obtained from CiliateGEM may represent a new approach to describe the metabolism of ciliates. This tool will be a useful resource for the ciliate research community in order to extend these species as model organisms in different research fields. An improved understanding of ciliate metabolism could be relevant to elucidate the basis of biological phenomena like genotype-phenotype relationships, population genetics, and cilia-related disease mechanisms.

     

Comparison of rat dopamine D2 receptor occupancy for a series of antipsychotic drugs measured using radiolabeled or nonlabeled raclopride tracer

Preclinical brain receptor occupancy measures have heretofore been conducted by quantifying the brain distribution of a radiolabeled tracer ligand using either scintillation spectroscopy or tomographic imaging. For smaller animals like rodents, the majority of studies employ tissue dissection and scintillation spectroscopy. These measurements can also be accomplished using liquid chromatography coupled to mass spectral detection to measure the brain distribution of tracer molecules, obviating the need for radioligands. In order to validate mass spectroscopy-based receptor occupancy methods, we examined dopamine D2 receptor dose-occupancy curves for a number of antipsychotic drugs in parallel experiments using either mass spectroscopy or radioligand-based approaches. Oral dose-occupancy curves were generated for 8 antipsychotic compounds in parallel experiments using either radiolabeled or unlabeled raclopride tracer. When curves generated by these two methods were compared and ED(50) values determined, remarkably similar data were obtained. Occupancy ED(50) values were (mg/kg): chlorpromazine, 5.1 and 2.7; clozapine, 41 and 40; haloperidol, 0.2 and 0.3; olanzapine, 2.1 and 2.2; risperidone, 0.1 and 0.4; spiperone, 0.5 and 0.4; thioridazine 9.2 and 9.5; and ziprasidone 1.4 and 2.1 (unlabeled and radiolabeled raclopride tracer, respectively). The observation that in vivo application of both techniques led to comparable data adds to the validation state of the mass spectroscopy-based approach to receptor occupancy assays.     

MitoCore: a curated constraint-based model for simulating human central metabolism

Background

The complexity of metabolic networks can make the origin and impact of changes in central metabolism occurring during diseases difficult to understand. Computer simulations can help unravel this complexity, and progress has advanced in genome-scale metabolic models. However, many models produce unrealistic results when challenged to simulate abnormal metabolism as they include incorrect specification and localisation of reactions and transport steps, incorrect reaction parameters, and confounding of prosthetic groups and free metabolites in reactions. Other common drawbacks are due to their scale, making them difficult to parameterise and simulation results hard to interpret. Therefore, it remains important to develop smaller, manually curated models.

Results

We present MitoCore, a manually curated constraint-based computer model of human metabolism that incorporates the complexity of central metabolism and simulates this metabolism successfully under normal and abnormal physiological conditions, including hypoxia and mitochondrial diseases. MitoCore describes 324 metabolic reactions, 83 transport steps between mitochondrion and cytosol, and 74 metabolite inputs and outputs through the plasma membrane, to produce a model of manageable scale for easy interpretation of results. Its key innovations include a more accurate partitioning of metabolism between cytosol and mitochondrial matrix; better modelling of connecting transport steps; differentiation of prosthetic groups and free co-factors in reactions; and a new representation of the respiratory chain and the proton motive force. MitoCore’s default parameters simulate normal cardiomyocyte metabolism, and to improve usability and allow comparison with other models and types of analysis, its reactions and metabolites have extensive annotation, and cross-reference identifiers from Virtual Metabolic Human database and KEGG. These innovations—including over 100 reactions absent or modified from Recon 2—are necessary to model central metabolism more accurately.

Conclusion

We anticipate MitoCore as a research tool for scientists, from experimentalists looking to interpret their data and test hypotheses, to experienced modellers predicting the consequences of disease or using computationally intensive methods that are infeasible with larger models, as well as a teaching tool for those new to modelling and needing a small, manageable model on which to learn and experiment.

     

Glucose Metabolic Trapping in Mouse Arteries: Nonradioactive Assay of Atherosclerotic Plaque Inflammation Applicable to Drug Discovery

Background

¹⁸F-Fluorodeoxyglucose (FDG)-positron emission tomography (PET) imaging of atherosclerosis in the clinic is based on preferential accumulation of radioactive glucose analog in atherosclerotic plaques. FDG-PET is challenging in mouse models due to limited resolution and high cost. We aimed to quantify accumulation of nonradioactive glucose metabolite, FDG-6-phosphate, in the mouse atherosclerotic plaques as a simple alternative to PET imaging.

Methodology/Principal Findings

Nonradioactive FDG was injected 30 minutes before euthanasia. Arteries were dissected, and lipids were extracted. The arteries were re-extracted with 50% acetonitrile-50% methanol-0.1% formic acid. A daughter ion of FDG-6-phosphate was quantified using liquid chromatography and mass spectrometry (LC/MS/MS). Thus, both traditional (cholesterol) and novel (FDG-6-phosphate) markers were assayed in the same tissue. FDG-6-phosphate was accumulated in atherosclerotic lesions associated with carotid ligation of the Western diet fed ApoE knockout mice (5.9 times increase compare to unligated carotids, p<0.001). Treatment with the liver X receptor agonist T0901317 significantly (2.1 times, p<0.01) reduced FDG-6-phosphate accumulation 2 weeks after surgery. Anti-atherosclerotic effects were independently confirmed by reduction in lesion size, macrophage number, cholesterol ester accumulation, and macrophage proteolytic activity.

Conclusions/Significance

Mass spectrometry of FDG-6-phosphate in experimental atherosclerosis is consistent with plaque inflammation and provides potential translational link to the clinical studies utilizing FDG-PET imaging.     

Use of LC/MS to assess brain tracer distribution in preclinical, in vivo receptor occupancy studies: dopamine D2, serotonin 2A and NK-1 receptors as examples

High performance liquid chromatography combined with either single quad or triple quad mass spectral detectors (LC/MS) was used to measure the brain distribution of receptor occupancy tracers targeting dopamine D2, serotonin 5-HT2A and neurokinin NK-1 receptors using the ligands raclopride, MDL-100907 and GR205171, respectively. All three non-radiolabeled tracer molecules were easily detectable in discrete rat brain areas after intravenous doses of 3, 3 and 30 microg/kg, respectively. These levels showed a differential brain distribution caused by differences in receptor density, as demonstrated by the observation that pretreatment with compounds that occupy these receptors reduced this differential distribution in a dose-dependent manner. Intravenous, subcutaneous and oral dose-occupancy curves were generated for haloperidol at the dopamine D2 receptor as were oral curves for the antipsychotic drugs olanzapine and clozapine. In vivo dose-occupancy curves were also generated for orally administered clozapine, olanzapine and haloperidol at the cortical 5-HT2A binding site. In vivo occupancy at the striatal neurokinin NK-1 binding site by various doses of orally administered MK-869 was also measured. Our results demonstrate the utility of LC/MS to quantify tracer distribution in preclinical brain receptor occupancy studies.