d2ome, Software for in Vivo Protein Turnover Analysis Using Heavy Water Labeling and LC–MS, Reveals Alterations of Hepatic Proteome Dynamics in a Mouse Model of NAFLD

Metabolic
labeling with heavy water followed by LC–MS is a high throughput
approach to study proteostasis in vivo. Advances in mass spectrometry
and sample processing have allowed consistent detection of thousands
of proteins at multiple time points. However, freely available automated
bioinformatics tools to analyze and extract protein decay rate constants
are lacking. Here, we describe d2omea robust, automated software
solution for in vivo protein turnover analysis. d2ome is highly scalable,
uses innovative approaches to nonlinear fitting, implements Grubbs’
outlier detection and removal, uses weighted-averaging of replicates,
applies a data dependent elution time windowing, and uses mass accuracy
in peak detection. Here, we discuss the application of d2ome in a
comparative study of protein turnover in the livers of normal vs Western
diet-fed LDLR–/– mice (mouse model of nonalcoholic
fatty liver disease), which contained 256 LC–MS experiments.
The study revealed reduced stability of 40S ribosomal protein subunits
in the Western diet-fed mice.