READ ME File For 'Datasets for Reshaping lipid metabolism with long-term alternate day feeding in type 2 diabetes mice' Dataset DOI: 10.17034/XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX Date that the readme file was created: 2024, October, 15 (2024-10-24) ------------------- GENERAL INFORMATION ------------------- Title: Datasets for "Reshaping lipid metabolism with long-term alternate day feeding in type 2 diabetes mice" Creator(s): ELENI BELI, Queen's University Belfast [0000-0003-1889-640X] Rights-holder: Queen's University Belfast Publication year:2024 Date of data collection: between 2012-2019; Information about geographic location of data collection (if relevant); United States, Michigan State University, Lansing MI; Indiana University, Indianapolis, IN. Related projects: ADD IN ------------------- PROJEJCT INFORMATION ------------------- Funder Name:National Institutes of Health Project Number or Grant Identifier: EY12601, EY028858, EY028037, HL110170 to MBG. ------------------- CONTACT INFORMATION ------------------- Author/Principal Investigator information Name: Maria Grant ORCID:0000-0002-6470-02555 Institution: Univesrity of Alabama, Birmingham Email:mariagrant@uabmc.edu Author/Co-investigator information Name:Eleni Beli ORCID:0000-0003-1889-640X Institution:Queen's University Belfast Email:e.beli@qub.ac.uk -------------------------- SHARING/ACCESS INFORMATION -------------------------- Licenses/restrictions placed on the data, or limitations of reuse: Recommended citation for the data: Beli, Ee (2024), Dataset for "Reshaping lipid metabolism with long-term alternate day feeding in type 2 diabetes mice" Submitted, npj Metabolic Health and Disease This dataset supports the publication: AUTHORS:Eleni Beli, Yuanqing Yan, Leni Moldovan, Todd A. Lydic, Preethi Krishman, Sarah A. Tersey, Yaqian Duan, Tatiana E. Salazar, James M. Dominguez 2nd, Dung V. Nguyen, Abigail Cox, Sergio Li Calzi, Craig Beam, Raghavendra G. Mirmira, Carmella Evans-Molina, Julia V. Busik, Maria B. Grant TITLE:Reshaping lipid metabolism with long-term alternate day feeding in type 2 diabetes mice JOURNAL:npj Metabolic Health and Disease PAPER DOI IF KNOWN: Links to other publicly accessible locations of the data: Links/relationships to ancillary or related data sets: -------------------- DATA & FILE OVERVIEW -------------------- This dataset contains: File list: Blood Metabolomics data_IF.cvs Liver Lipidomics data_IF.cvs Liver Microarray data_IF.cvs Predicted Microbiome KO pathways_abudance tables_IF.cvs These files contain data used for analysis and constuction of figures related to the paper. The name of the files reflect the tissue and technique used. -------------------------- METHODOLOGICAL INFORMATION -------------------------- All data were generated from samples collected from control C (db/m) and diabetic D (Db/db) mice that were alternate-day fasted [intermittent fasting (IF) treatment]. Mice were divided into two subgroups: the ad-libitum group (AL), where mice had ad-lib access to food, and the intermittent fasting group (IF) where mice were fasted for 24 hours every other day for 6 months. Fasting was initiated at the beginning of every other night. Four cohorts of mice were studied: D-AL: diabetic -ad-lib, D-IF: diabetic-intermittent fasting, C-AL: control-ad-lib, and C-IF: control-intermittent fasting. Samples were collected at the same time of day in all groups (indicated as ZT time, ZT=zeitgeber time). For the IF cohorts, separate samples were collected at the feeding phase (IF-feed) or the fasting phase (IF-fast). Datasets: Blood Metabolomics data_IF.cvs Blood was collected by cardiac puncture at termination into EDTA tubes and plasma was separated and frozen at -80oC. Samples (n=5-6 per group) were sent to Metabolon Inc (Morrisville, NC) and global metabolic analysis was performed with their Metabolon Platform using a Waters ACQUITY ultra-performance liquid chromatography (UPLC) and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution. This dataset contains normalized to volume scaled intensity levels of biochemicals identified for each group and statistical analysis. Liver Lipidomics data_IF.cvs Lipidomics analysis was performed at Michigan State University. Lipids were extracted from 5mg frozen liver tissue with Monophasic lipid extraction with methanol: chloroform: water (2:1:0.74, v: v: v). Shotgun tandem mass spectrometry approach was used at Michigan state university. For mass spectrometry analysis, liver lipid extracts were combined with the synthetic internal standards PC(14:0/14:0), PE(14:0/14:0), and PS(14:0/14:0) from Avanti Polar Lipids (Alabaster, AL), and subjected to sequential functional group selective modification of PE and PS lipids using 13C1-S,S’-dimethylthiobutanoylhydroxysuccinimide ester (13C1-DMBNHS), and the O-alkenyl-ether double bond of plasmalogen lipids using iodine and methanol. Peak finding, lipid identification, and quantification were performed using the Lipid Mass Spectrum Analysis (LIMSA) v.1.0 software34 as described 32. Lipids were classified into broad lipid classes and two-way ANOVA was used to identify significant differences between C, D and treatments. This dataset contains lipid species identified as % of total lipids, per tissue weight and as broad lipid classes. Liver Microarray data_IF.cvs total mRNA isolated from liver samples was used for the microarray. GeneChip Mouse Gene 2.0 ST Arrays (Affymetrix, Santa Clara, CA). CEL files were analyzed with Expression Console software (Affymetrix), the statistical analysis was performed with Transcriptome Analysis Console Software (Affymetrix), and gene-level RMA was used for normalization. This dataset contains the genes identified as a signal on the microarrays for all genes. Predicted Microbiome KO pathways_abudance tables_IF.cvs 16S ribosomal RNA (rRNA) gene sequences derived from a previous publication with the same cohorts (Beli et al 2018) were used to estimate the functional capacity of the microbial communities impacted by IF using the Piphillin by Second Genome Inc (San Francisco, CA). This dataset contains the abudance tables for the KO pathways identified. People involved with the aquisition of data and analysis: EB, YY, YD, SLC, TES, JMD, DVN, RCM, SHH, HD, EFH, ST, TAL performed experiments. EB, YY, LM, PK, TAL, ST, AC analyzed data. -------------------------- DATASET-SPECIFIC INFORMATION -------------------------- File listing Number of variables: Disease (control and diabetes) Treatment (AL, IF feed, IF fast)