Tandem mass tag proteomic and untargeted metabolomic profiling reveals altered serum and CSF biochemical datasets in iron deficient monkeys

Brian J Sandri; Jonathan Kim; Gabriele R Lubach; Eric F Lock; Candace Guerrero; LeeAnn Higgins; Todd W Markowski; Pamela J Kling; Michael K Georgieff; Christopher L Coe; Raghavendra B Rao

doi:10.1016/j.dib.2022.108591

Tandem mass tag proteomic and untargeted metabolomic profiling reveals altered serum and CSF biochemical datasets in iron deficient monkeys

Data Brief. 2022 Sep 11:45:108591. doi: 10.1016/j.dib.2022.108591. eCollection 2022 Dec.

Authors

Brian J Sandri^{1

2}, Jonathan Kim³, Gabriele R Lubach⁴, Eric F Lock³, Candace Guerrero⁵, LeeAnn Higgins⁵, Todd W Markowski⁵, Pamela J Kling⁶, Michael K Georgieff^{1

2}, Christopher L Coe³, Raghavendra B Rao^{1

2}

Affiliations

¹ Division of Neonatology, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
² Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
³ Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
⁴ Harlow Center for Biological Psychology, University of Wisconsin, Madison, WI, USA.
⁵ Department of Biochemistry, Molecular Biology, & Biophysics, University of Minnesota, Minneapolis, Minnesota, USA.
⁶ Division of Neonatology, Department of Pediatrics, University of Wisconsin, Madison, WI, USA.

Abstract

The effects of early-life iron deficiency anemia (IDA) extend past the blood and include both short- and long-term adverse effects on many tissues including the brain. Prior to IDA, iron deficiency (ID) can cause similar tissue effects, but a sensitive biomarker of iron-dependent brain health is lacking. To determine serum and CSF biomarkers of ID-induced metabolic dysfunction we performed proteomic and metabolomic analysis of serum and CSF at 4- and 6- months from a nonhuman primate model of infantile IDA. LC/MS/MS analyses identified a total of 227 metabolites and 205 proteins in serum. In CSF, we measured 210 metabolites and 1,560 proteins. Data were either processed from a Q-Exactive (Thermo Scientific, Waltham, MA) through Progenesis QI with accurate mass and retention time comparisons to a proprietary small molecule database and Metlin or with raw files imported directly from a Fusion Orbitrap (Thermo Scientific, Waltham, MA) through Sequest in Proteome Discoverer 2.4.0.305 (Thermo Scientific, Waltham, MA) with peptide matches through the latest Rhesus Macaque HMDB database. Metabolite and protein identifiers, p-values, and q-values were utilized for molecular pathway analysis with Ingenuity Pathways Analysis (IPA). We applied multiway distance weighted discrimination (DWD) to identify a weighted sum of the features (proteins or metabolites) that distinguish ID from IS at 4-months (pre-anemic period) and 6-months of age (anemic).

Keywords: Multiomics; Rhesus Macaque; Synaptogenesis.

Grants and funding

R01 GM130622/GM/NIGMS NIH HHS/United States