Work Description

Title: Database Screening as a Strategy to Identify Endogenous Candidate Metabolites to Probe and Assess Mitochondrial Drug Toxicity

Dataset Creators: M.V. George De la Rosa, D.Patel, M.R. McCann, K.A. Stringer and G.R. Rosania

Dataset Contact: Mery Vet George De la Rosa mvgeorge@umich.edu

Funding: The National Institutes of Health (NIH) under award numbers R01GM127787 (GRR) & R35GM136312 (KAS).

Research Overview:
These data were produced from a two part study. The fisrt part of the study employed a database screening strategy to identify candidate mitochondrial metabolites that could be clinically useful to identify individuals at increased risk of mitochondrial-related ADRs.
In the second part of the study, the main candidate metabolite identified by the database screening strategy was evaluated using a mouse model of mitochondrial drug toxicity for potential clinical use.
These findings are described in our manuscript: Database Screening as a Strategy to Identify Endogenous Candidate Metabolites to Probe and Assess Mitochondrial Drug Toxicity.

Methodology:
The data are a result of a database screening methodology to identify candidate mitochondrial metabolites and the results of in vivo experiments to evaluate the identified candidate.
A database screening methodology was carried out to identify mitochondrial-related metabolites to probe and assess mitochondrial drug toxicity.
A set of criteria was established for each step of the workflow and each database that was screened, candidate metabolites were included or excluded from further consideration based on these criteria.
The identified metabolite from the database screening methodology was evaluated using a mouse model of mitochondrial drug toxicity.
The animal protocol was approved by the University of Michigan’s Institutional Animal Care and Use Committee (protocol number PRO00009404) and animal care was provided in accordance with the NIH Guide for the Care and Use of Laboratory Animals.
Mice were treated with Clofazimine (CFZ), for 8-weeks and were then injected with a high dose of L-carnitine. Metabolic functions were tracked, including weight, food and water consumption, and urine production.
Food and water consumption and urine production data are pooled and averaged values (5 mice/per sample), accquired in metabolic cages.
The amount of L-carnitine and acetylcarnitine in urine is shown in mole fraction. These values were calculated by dividing the amount of L-carnitine or acetylcarnitine recovered after 24h in urine by the starting dose of the L-carnitine challenge injected.
Whole blood samples were collected at various timepoints (BL, 10min, 30min, 60min, 120min and 240min) then flash frozen in liquid nitrogen.
In order to comply with the University of Michigan’s Institutional Animal Care and Use, half the mice were sampled at (BL, 10min, 60min, and 240min) and the other half (BL, 30min and 120min), which accounts for some of the blank cells at different timepoints.
L-carnitine and acetylcarnitine concentrations in whole blood and urine were measured using a quantitative liquid chromatography–mass spectrometry (LC/MS) assay.

File Inventory:

Excel file name: Database Screening Data: represents all data resulting from the database screening methodology, each tab shows the data acquired from each of the databases based on the a priori established criteria (NCBI, BRENDA and KEGG).
Excel file name: L-carnitine Challenge Data: represents all data acquired from the in vivo mice experiments conducted as part of the L-carnitine challenge.
Excel file name: L-carnitine Challenge Data_Whole Blood: represent L-carnitine and acetylcarnitine concentration data of vehicle treated and CFZ treated mice in whole blood (uM).