Dataset Information

PROMIS, global analysis of PROtein-Metabolite Interactions using Size separation in Arabidopsis thaliana

ABSTRACT: Small molecules not only represent cellular building blocks and metabolic intermediates, but also regulatory ligands and signaling molecules that interact with proteins. Although these interactions affect cellular metabolism, growth, and development, they have been largely understudied. Herein, we describe a method, dubbed PROtein-Metabolite Interactions using Size separation (PROMIS) that allows simultaneous, global analysis of endogenous protein-small molecule and of protein‒protein complexes. To this end, a cell-free native lysate from Arabidopsis thaliana cell cultures was fractionated by size-exclusion chromatography, followed by quantitative metabolomic and proteomic analyses. Proteins and small molecules showing similar elution behavior, across protein containing fractions, constituted putative interactors. Applying PROMIS to an A. thaliana extract, we ascertained known protein‒protein (PPIs) and protein-metabolite (PMIs) interactions and reproduced binding between small-molecule protease inhibitors and their respective proteases. More importantly, we present examples of two experimental strategies that exploit the PROMIS dataset to identify novel PMIs. By looking for similar elution behavior of metabolites and enzymes belonging to the same biochemical pathways, we identified putative feedback and feed-forward regulations in pantothenate biosynthesis and the methionine salvage cycle, respectively. By combining PROMIS with an orthogonal affinity purification approach, we identified an interaction between the dipeptide Tyr-Asp and the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase. In summary, we present proof of concept for a powerful experimental tool that enables system-wide analysis of PMIs and PPIs across all biological systems. The dataset obtained here comprises nearly 140 metabolites and 5000 proteins, which can be mined for putative interactors.

OTHER RELATED OMICS DATASETS IN: PXD009714

INSTRUMENT(S): Liquid Chromatography MS - Negative (LC-MS (Negative)), Liquid Chromatography MS - Positive (LC-MS (Positive))

SUBMITTER: Michal Gorka

PROVIDER: MTBLS94 | MetaboLights | 2018-07-19

REPOSITORIES: MetaboLights

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PROMIS, global analysis of PROtein-metabolite interactions using size separation in Arabidopsis thaliana.

Veyel Daniel D Sokolowska Ewelina M EM Moreno Juan C JC Kierszniowska Sylwia S Cichon Justyna J Wojciechowska Izabela I Luzarowski Marcin M Kosmacz Monika M Szlachetko Jagoda J Gorka Michal M Méret Michaël M Graf Alexander A Meyer Etienne H EH Willmitzer Lothar L Skirycz Aleksandra A

The Journal of biological chemistry 20180531 32

Small molecules not only represent cellular building blocks and metabolic intermediates, but also regulatory ligands and signaling molecules that interact with proteins. Although these interactions affect cellular metabolism, growth, and development, they have been largely understudied. Herein, we describe a method, which we named PROtein-Metabolite Interactions using Size separation (PROMIS), that allows simultaneous, global analysis of endogenous protein-small molec ...[more]

PMID: 29853640

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Project description:Background Appropriate social interactions influence animal fitness by impacting several processes, such as mating, territory defense, and offspring care. Many studies shedding light on the neurobiological underpinnings of social behavior have focused on nonapeptides (vasopressin, oxytocin, and homologues) and on sexual or parent-offspring interactions. Furthermore, animals have been studied under artificial laboratory conditions, where the consequences of behavioral responses may not be as critical as when expressed under natural environments, therefore obscuring certain physiological responses. We used automated recording of social interactions of wild house mice outside of the breeding season to detect individuals at both tails of a distribution of egocentric network sizes (characterized by number of different partners encountered per day). We then used RNA-seq to perform an unbiased assessment of neural differences in gene expression in the prefrontal cortex, the hippocampus and the hypothalamus between these mice with naturally occurring extreme differences in social network size. Results We found that the neurogenomic pathways associated with having extreme social network sizes differed between the sexes. In females, hundreds of genes were differentially expressed between animals with small and large social network sizes, whereas in males very few were. In males, X-chromosome inactivation pathways in the prefrontal cortex were the ones that better differentiated animals with small from those with large social network sizes animals. In females, animals with small network size showed up-regulation of dopaminergic production and transport pathways in the hypothalamus. Additionally, in females, extracellular matrix deposition on hippocampal neurons was higher in individuals with small relative to large social network size. Conclusions Studying neural substrates of natural variation in social behavior in traditional model organisms in their habitat can open new targets of research for understanding variation in social behavior in other taxa.

			Action	DRS
	MTBLS94	Other
	FILES	Other
	a_MTBLS94_NEG_mass_spectrometry.txt	Txt
	a_MTBLS94_POS_mass_spectrometry.txt	Txt
	i_Investigation.txt	Txt

Dataset Information

PROMIS, global analysis of PROtein-Metabolite Interactions using Size separation in Arabidopsis thaliana

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Publications

PROMIS, global analysis of PROtein-metabolite interactions using size separation in <i>Arabidopsis thaliana</i>.

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