000196318 001__ 196318
000196318 005__ 20181203023421.0
000196318 0247_ $$2doi$$a10.1016/j.ymben.2013.12.007
000196318 022__ $$a1096-7184
000196318 02470 $$2ISI$$a000335385500001
000196318 037__ $$aARTICLE
000196318 245__ $$aA computational framework for integration of lipidomics data into metabolic pathways
000196318 260__ $$bAcademic Press Inc Elsevier Science$$c2014$$aSan Diego
000196318 269__ $$a2014
000196318 300__ $$a8
000196318 336__ $$aJournal Articles
000196318 520__ $$aLipids are important compounds for human physiology and as renewable resources for fuels and chemicals. In lipid research, there is a big gap between the currently available pathway-level representations of lipids and lipid structure databases in which the number of compounds is expanding rapidly with high-throughput mass spectrometry methods. In this work, we introduce a computational approach to bridge this gap by making associations between metabolic pathways and the lipid structures discovered increasingly thorough lipidomics studies. Our approach, called NICELips (Network Integrated Computational Explorer for Lipidomics), is based on the formulation of generalized enzymatic reaction rules for lipid metabolism, and it employs the generalized rules to postulate novel pathways of lipid metabolism. It further integrates all discovered lipids in biological networks of enzymatic reactions that consist their biosynthesis and biodegradation pathways. We illustrate the utility of our approach through a case study of bis(monoacylglycero)phosphate (BMP), a biologically important glycerophospholipid with immature synthesis and catabolic route(s). Using NICELips, we were able to propose various synthesis and degradation pathways for this compound and several other lipids with unknown metabolism like BMP, and in addition several alternative novel biosynthesis and biodegradation pathways for lipids with known metabolism. NICELips has potential applications in designing therapeutic interventions for lipid-associated disorders and in the metabolic engineering of model organisms for improving the biobased production of lipid-derived fuels and chemicals.
000196318 6531_ $$aPhospholipids
000196318 6531_ $$aDatabase
000196318 6531_ $$aBioinformatics
000196318 6531_ $$aBis(monoacylglycero)phosphate (Bmp)
000196318 700__ $$0244260$$g185577$$aHadadi, Noushin
000196318 700__ $$0243874$$g177860$$aCher Soh, Keng
000196318 700__ $$0244255$$g191144$$aSeijo, Marianne
000196318 700__ $$0244259$$g206342$$aZisaki, Aikaterini
000196318 700__ $$aGuan, Xueli
000196318 700__ $$aWenk, Markus R.
000196318 700__ $$aHatzimanikatis, Vassily$$g174688$$0240657
000196318 773__ $$j23$$tMetabolic engineering$$q1-8
000196318 909C0 $$xU11422$$0252131$$pLCSB
000196318 909CO $$pSB$$particle$$ooai:infoscience.tind.io:196318
000196318 917Z8 $$x185577
000196318 917Z8 $$x148230
000196318 937__ $$aEPFL-ARTICLE-196318
000196318 973__ $$rNON-REVIEWED$$sPUBLISHED$$aEPFL
000196318 980__ $$aARTICLE