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Biology subjects

Noronha, A.

Publications and source records attributed to Noronha, A..

3 recordsLinked to original sources

MeCP2 isoform e1 mutant mice recapitulate motor and metabolic phenotypes of Rett syndrome

Mutations in the X-linked gene MECP2 cause the majority of Rett syndrome (RTT) cases. Two differentially spliced isoforms of exons 1 and 2 (MeCP2-e1 and MeCP2-e2) contribute to the diverse functions of MeCP2, but only mutations in exon 1, not exon 2, are observed in RTT. We previously described an isoform-specific MeCP2-e1 deficient male mouse model of a human RTT mutation that lacks MeCP2-e1 while preserving expression of MeCP2-e2. However, RTT patients are heterozygous females that exhibit delayed and progressive symptom onset beginning in late infancy, including neurologic as well as metabolic, immune, respiratory, and gastrointestinal phenotypes. Consequently, we conducted a longitudinal assessment of symptom development in MeCP2-e1 mutant females and males. A delayed and progressive onset of motor impairments was observed in both female and male MeCP2-e1 mutant mice, including hind limb clasping and motor deficits in gait and balance. Because these motor impairments were significantly impacted by age-dependent increases in body weight, we also investigated metabolic phenotypes at an early stage of disease progression. Both male and female MeCP2-e1 mutants exhibited significantly increased body fat compared to sex-matched wild-type littermates prior to weight differences. Mecp2e1-/y males exhibited significant metabolic phenotypes of hypoactivity, decreased energy expenditure, increased respiratory exchange ratio (RER), but decreased food intake compared to wildtype. Untargeted analysis of lipid metabolites demonstrated a distinguishable profile in MeCP2-e1 female mutant liver characterized by increased triglycerides. Together these results demonstrate that MeCP2-e1 mutation in mice of both sexes recapitulate early and progressive metabolic and motor phenotypes of human RTT.

neuroscience

The Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease

A multitude of factors contribute to complex diseases and can be measured with \"omics\" methods. Databases facilitate data interpretation for underlying mechanisms. Here, we describe the Virtual Metabolic Human (VMH, http://vmh.life) database encapsulating current knowledge of human metabolism within five interlinked resources \"Human metabolism\", \"Gut microbiome\", \"Disease\", \"Nutrition\", and \"ReconMaps\". The VMH captures 5,180 unique metabolites, 17,730 unique reactions, 3,288 human genes, 255 Mendelian diseases, 818 microbes, 632,685 microbial genes, and 8,790 food items. The VMHs unique features are i) the hosting the metabolic reconstructions of human and gut microbes amenable for metabolic modeling; ii) seven human metabolic maps for data visualization; iii) a nutrition designer; iv) a user-friendly webpage and application-programming interface to access its content; and v) user feedback option for community engagement. We demonstrate with four examples the VMHs utility. The VMH represents a novel, interdisciplinary database for data interpretation and hypothesis generation to the biomedical community.

systems biology

When metabolism meets physiology: Harvey and Harvetta

Precision medicine is an emerging paradigm that requires realistic, mechanistic models capturing the complexity of the human body. We present two comprehensive molecular to physiological-level, gender-specific whole-body metabolism (WBM) reconstructions, named Harvey, in recognition of William Harvey, and Harvetta. These validated, knowledge-based WBM reconstructions capture the metabolism of 20 organs, six sex organs, six blood cells, the gastrointestinal lumen, systemic blood circulation, and the blood-brain barrier. They represent 99% of the human body weight, when excluding the weight of the skeleton. Harvey and Harvetta can be parameterized based on physiological, dietary, and omics data. They correctly predict inter-organ metabolic cycles, basal metabolic rates, and energy use. We demonstrate the integration of microbiome data thereby allowing the assessment of individual-specific, organ-level modulation of host metabolism by the gut microbiota. The WBM reconstructions and the individual organ reconstructions are available under http://vmh.life. Harvey and Harvetta represent a pivotal step towards virtual physiological humans.

systems biology