GAIT-GM integrative cross-omics analyses reveal cholinergic defects in a C. elegans model of Parkinson's disease.

TitleGAIT-GM integrative cross-omics analyses reveal cholinergic defects in a C. elegans model of Parkinson's disease.
Publication TypeJournal Article
Year of Publication2022
AuthorsMcIntyre, LM, Huertas, F, Morse, AM, Kaletsky, R, Murphy, CT, Kalia, V, Miller, GW, Moskalenko, O, Conesa, A, Mor, DE
JournalSci Rep
Volume12
Issue1
Pagination3268
Date Published2022 Feb 28
ISSN2045-2322
KeywordsAnimals, Caenorhabditis elegans, Cholinergic Agents, Cholinergic Neurons, Disease Models, Animal, Dopamine, Parkinson Disease
Abstract

<p>Parkinson's disease (PD) is a disabling neurodegenerative disorder in which multiple cell types, including dopaminergic and cholinergic neurons, are affected. The mechanisms of neurodegeneration in PD are not fully understood, limiting the development of therapies directed at disease-relevant molecular targets. C. elegans is a genetically tractable model system that can be used to disentangle disease mechanisms in complex diseases such as PD. Such mechanisms can be studied combining high-throughput molecular profiling technologies such as transcriptomics and metabolomics. However, the integrative analysis of multi-omics data in order to unravel disease mechanisms is a challenging task without advanced bioinformatics training. Galaxy, a widely-used resource for enabling bioinformatics analysis by the broad scientific community, has poor representation of multi-omics integration pipelines. We present the integrative analysis of gene expression and metabolite levels of a C. elegans PD model using GAIT-GM, a new Galaxy tool for multi-omics data analysis. Using GAIT-GM, we discovered an association between branched-chain amino acid metabolism and cholinergic neurons in the C. elegans PD model. An independent follow-up experiment uncovered cholinergic neurodegeneration in the C. elegans model that is consistent with cholinergic cell loss observed in PD. GAIT-GM is an easy to use Galaxy-based tool for generating novel testable hypotheses of disease mechanisms involving gene-metabolite relationships.</p>

DOI10.1038/s41598-022-07238-9
Alternate JournalSci Rep
PubMed ID35228596
PubMed Central IDPMC8885929
Grant ListR01 ES023839 / ES / NIEHS NIH HHS / United States
R03 CA222444 / CA / NCI NIH HHS / United States
DP1 GM119167 / GM / NIGMS NIH HHS / United States
U2C ES030163 / ES / NIEHS NIH HHS / United States
U2C ES030167 / ES / NIEHS NIH HHS / United States
F32 AG062036 / AG / NIA NIH HHS / United States
R21HG011280Project / NH / NIH HHS / United States
U24 DK097209 / DK / NIDDK NIH HHS / United States