In:
The FASEB Journal, Wiley, Vol. 32, No. S1 ( 2018-04)
Abstract:
Diabetic Kidney Disease (DKD) is one of the most common and serious complications of Type II Diabetes Mellitus (T2DM). Previous work measured plasma metabolites in DKD patients versus T2DM controls without DKD. DKD patients showed elevated hydroxyl‐ and dicarboxyl‐acylcarnitines. These metabolites are produced by omega‐oxidation (ωOx), a microsomal process that is known to be upregulated during mitochondrial dysregulation and inborn errors of metabolism. Briefly, dicarboxylic fatty acids from ωOx can be converted to dicarboxyl‐acylcarnitines or transported to the peroxisome for breakdown through peroxisomal β‐oxidation. ωOx is a poorly‐studied pathway that has never been subjected to computational simulations, nor included in detail in genome‐scale computational models of human metabolism. We developed a computational model of ωOx and integrated it with a previously published metabolic flux model of interplay between three tissue types (liver, muscle, adipose) in diabetes. We then performed metabolic flux simulations on this extended model using Flux‐Balance Analysis (FBA). Monte‐Carlo Flux sampling techniques identified cellular reactions with flux levels that were differentially regulated by allowing/blocking ωOx, or by allowing/blocking efflux of peroxisomal beta‐oxidation intermediates. Forcing the model to utilize ωOx caused consistent flux changes in nitrogen processing and the urea cycle (for muscle and liver), suggesting altered levels of urea and ammonia in plasma. While other pathways were also affected to different degrees, the effect was less consistent than with the urea cycle. In conclusion , we provide the first metabolic model that incorporates ωOx and peroxisomal beta‐oxidation in a multi‐tissue setting. Simulating a model of diabetes with ωOx identified links between mitochondrial dysfunction, fatty acid processing and nitrogen metabolism. Flux sampling simulations are useful for generating experimental hypotheses and for shedding light on systems‐level effects, but experimental validation is required before inferring causality. The importance of urea as an osmolyte and metabolite motivates further study of this relationship, which could have important implications for renal function. Support or Funding Information 1. National Research Foundation (NRF), Prime Minister's Office, Singapore, under its CREATE programme, Singapore‐MIT Alliance for Research and Technology (SMART) BioSystems and Micromechanics (BioSyM) IRG 2. Duke‐NUS SRP Phase 2 Research Block Grant This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
Type of Medium:
Online Resource
ISSN:
0892-6638
,
1530-6860
DOI:
10.1096/fasebj.2018.32.1_supplement.720.7
Language:
English
Publisher:
Wiley
Publication Date:
2018
detail.hit.zdb_id:
1468876-1
detail.hit.zdb_id:
639186-2
SSG:
12
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