کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8258417 1534605 2018 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Metabolic modeling helps interpret transcriptomic changes during malaria
ترجمه فارسی عنوان
مدلسازی متابولیک کمک می کند تا تغییرات رونویسی را در طی مالاریا تغییر دهد
کلمات کلیدی
نظریه سیستم های بیوشیمی، مدل پویا سیستم عمل جرمی عمومی، مالاریا، مدلسازی متابولیک، متن ترانه
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی سالمندی
چکیده انگلیسی
Disease represents a specific case of malfunctioning within a complex system. Whereas it is often feasible to observe and possibly treat the symptoms of a disease, it is much more challenging to identify and characterize its molecular root causes. Even in infectious diseases that are caused by a known parasite, it is often impossible to pinpoint exactly which molecular profiles of components or processes are directly or indirectly altered. However, a deep understanding of such profiles is a prerequisite for rational, efficacious treatments. Modern omics methodologies are permitting large-scale scans of some molecular profiles, but these scans often yield results that are not intuitive and difficult to interpret. For instance, the comparison of healthy and diseased transcriptome profiles may point to certain sets of involved genes, but a host of post-transcriptional processes and regulatory mechanisms renders predictions regarding metabolic or physiological consequences of the observed changes in gene expression unreliable. Here we present proof of concept that dynamic models of metabolic pathway systems may offer a tool for interpreting transcriptomic profiles measured during disease. We illustrate this strategy with the interpretation of expression data of genes coding for enzymes associated with purine metabolism. These data were obtained during infections of rhesus macaques (Macaca mulatta) with the malaria parasite Plasmodium cynomolgi or P. coatneyi. The model-based interpretation reveals clear patterns of flux redistribution within the purine pathway that are consistent between the two malaria pathogens and are even reflected in data from humans infected with P. falciparum. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease - Volume 1864, Issue 6, Part B, June 2018, Pages 2329-2340
نویسندگان
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