Dataset Information

Clock regulation of metabolites reveals coupling between transcription and metabolism

ABSTRACT: The circadian clock is intricately connected with metabolism, however the precise details of these connections are incomplete. Here we used high temporal resolution metabolite profiling to determine circadian regulation of mouse liver and cell autonomous metabolism. In mouse liver, we found ~50% of metabolites were circadian, with strong enrichment of the nucleotide, amino acid, and methylation pathways. In U2OS cells, 27% of metabolites were circadian, including amino acids and NAD biosynthesis, also clock controlled in liver. To assess whether cell autonomous metabolite rhythms were clock-dependent, we used RNAi to perturb Bmal1, Cry1, and Cry2. Bmal1 knockdown eliminated most metabolite rhythms, while Cry1 generally shortened and Cry2 lengthened rhythms. Surprisingly, we found Cry1 knockdown induced 8 hr rhythms in amino acid, methylation, and vitamin metabolites, decoupling metabolite and transcriptional rhythms. These results provide the first comprehensive views of circadian liver and cell autonomous metabolism.

OTHER RELATED OMICS DATASETS IN: PRJNA237293PRJNA237291PRJNA237294PRJNA110287PRJNA105769PRJNA105767

INSTRUMENT(S): Xevo TQ MS (Waters)

SUBMITTER: Saikumari Krishnaiah

PROVIDER: MTBLS292 | MetaboLights | 2017-04-05

REPOSITORIES: MetaboLights

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Dataset's files

Source:

			Action	DRS
	MTBLS292	Other
	FILES	Other
	a_MTBLS292_liver_metabolite_profiling_mass_spectrometry.txt	Txt
	a_MTBLS292_u2os_metabolite_profiling_mass_spectrometry.txt	Txt
	i_Investigation.txt	Txt

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Publications

Clock Regulation of Metabolites Reveals Coupling between Transcription and Metabolism.

Krishnaiah Saikumari Y SY Wu Gang G Altman Brian J BJ Growe Jacqueline J Rhoades Seth D SD Coldren Faith F Venkataraman Anand A Olarerin-George Anthony O AO Francey Lauren J LJ Mukherjee Sarmistha S Girish Saiveda S Selby Christopher P CP Cal Sibel S Er Ubeydullah U Sianati Bahareh B Sengupta Arjun A Anafi Ron C RC Kavakli I Halil IH Sancar Aziz A Baur Joseph A JA Dang Chi V CV Hogenesch John B JB Weljie Aalim M AM

Cell metabolism 20170401 4

The intricate connection between the circadian clock and metabolism remains poorly understood. We used high temporal resolution metabolite profiling to explore clock regulation of mouse liver and cell-autonomous metabolism. In liver, ∼50% of metabolites were circadian, with enrichment of nucleotide, amino acid, and methylation pathways. In U2 OS cells, 28% were circadian, including amino acids and NAD biosynthesis metabolites. Eighteen metabolites oscillated in both systems and a subset of these ...[more]

PMID: 28380384

Similar Datasets

Project description:Over the past decade, genome-wide assays have underscored the broad sweep of circadian gene expression. A substantial fraction of the transcriptome undergoes oscillations in many organisms and tissues, which governs the many biochemical, physiological and behavioral functions under circadian control. Based predominantly on the transcription feedback loops important for core circadian timekeeping, it is commonly assumed that this widespread mRNA cycling reflects circadian transcriptional cycling. To address this issue, we directly measured dynamic changes in mouse liver transcription using Nascent-Seq. Many genes are rhythmically transcribed over the 24h day, which include precursors of several non-coding RNAs as well as the expected set of core clock genes. Surprisingly however, nascent RNA rhythms overlap poorly with mRNA abundance rhythms assayed by RNA-seq. This is because most mouse liver genes with rhythmic mRNA expression manifest poor transcriptional rhythms, indicating a prominent role of post-transcriptional regulation in setting mRNA cycling amplitude. To gain further insight into circadian transcriptional regulation, we also characterized the rhythmic transcription of liver genes targeted by the transcription factors CLOCK and BMAL1; they directly target other core clock genes and sit at the top of the molecular circadian clock hierarchy in mammals. CLK:BMAL1 rhythmically bind at the same discrete phase of the circadian cycle to all target genes, which not surprisingly have a much higher percentage of rhythmic transcription than the genome as a whole. However, there is a surprisingly heterogeneous set of cycling transcription phases of direct target genes, which even include core clock genes. This indicates a disconnect between rhythmic DNA binding and the peak of transcription, which is likely due to other transcription factors that collaborate with CLK:BMAL1. In summary, the application of Nascent-Seq to a mammalian tissue provides surprising insights into the rhythmic control of gene expression and should have broad applications beyond the analysis of circadian rhythms. CLK and BMAL1 DNA binding profile in the mouse liver at ZT8, sequenced along an Input sample using GAII (ChIP-Seq) Supplementary file ChIPSeq_Mouse_Liver_Processed_data_Table1.txt represents annotated CLK and BMAL1 peaks.

Project description:Over the past decade, genome-wide assays have underscored the broad sweep of circadian gene expression. A substantial fraction of the transcriptome undergoes oscillations in many organisms and tissues, which governs the many biochemical, physiological and behavioral functions under circadian control. Based predominantly on the transcription feedback loops important for core circadian timekeeping, it is commonly assumed that this widespread mRNA cycling reflects circadian transcriptional cycling. To address this issue, we directly measured dynamic changes in mouse liver transcription using Nascent-Seq. Many genes are rhythmically transcribed over the 24h day, which include precursors of several non-coding RNAs as well as the expected set of core clock genes. Surprisingly however, nascent RNA rhythms overlap poorly with mRNA abundance rhythms assayed by RNA-seq. This is because most mouse liver genes with rhythmic mRNA expression manifest poor transcriptional rhythms, indicating a prominent role of post-transcriptional regulation in setting mRNA cycling amplitude. To gain further insight into circadian transcriptional regulation, we also characterized the rhythmic transcription of liver genes targeted by the transcription factors CLOCK and BMAL1; they directly target other core clock genes and sit at the top of the molecular circadian clock hierarchy in mammals. CLK:BMAL1 rhythmically bind at the same discrete phase of the circadian cycle to all target genes, which not surprisingly have a much higher percentage of rhythmic transcription than the genome as a whole. However, there is a surprisingly heterogeneous set of cycling transcription phases of direct target genes, which even include core clock genes. This indicates a disconnect between rhythmic DNA binding and the peak of transcription, which is likely due to other transcription factors that collaborate with CLK:BMAL1. In summary, the application of Nascent-Seq to a mammalian tissue provides surprising insights into the rhythmic control of gene expression and should have broad applications beyond the analysis of circadian rhythms. Mouse liver nascent RNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina GAII (Nascent-Seq); Mouse liver mRNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina HiSeq2000 (RNA-Seq); CLK and BMAL1 DNA binding profile in the mouse liver at ZT8, sequenced along an Input sample using GAII (ChIP-Seq); Mouse liver strand-specific nascent RNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina HiSeq2000 (Strand-specific Nascent-Seq);

Project description:Over the past decade, genome-wide assays have underscored the broad sweep of circadian gene expression. A substantial fraction of the transcriptome undergoes oscillations in many organisms and tissues, which governs the many biochemical, physiological and behavioral functions under circadian control. Based predominantly on the transcription feedback loops important for core circadian timekeeping, it is commonly assumed that this widespread mRNA cycling reflects circadian transcriptional cycling. To address this issue, we directly measured dynamic changes in mouse liver transcription using Nascent-Seq. Many genes are rhythmically transcribed over the 24h day, which include precursors of several non-coding RNAs as well as the expected set of core clock genes. Surprisingly however, nascent RNA rhythms overlap poorly with mRNA abundance rhythms assayed by RNA-seq. This is because most mouse liver genes with rhythmic mRNA expression manifest poor transcriptional rhythms, indicating a prominent role of post-transcriptional regulation in setting mRNA cycling amplitude. To gain further insight into circadian transcriptional regulation, we also characterized the rhythmic transcription of liver genes targeted by the transcription factors CLOCK and BMAL1; they directly target other core clock genes and sit at the top of the molecular circadian clock hierarchy in mammals. CLK:BMAL1 rhythmically bind at the same discrete phase of the circadian cycle to all target genes, which not surprisingly have a much higher percentage of rhythmic transcription than the genome as a whole. However, there is a surprisingly heterogeneous set of cycling transcription phases of direct target genes, which even include core clock genes. This indicates a disconnect between rhythmic DNA binding and the peak of transcription, which is likely due to other transcription factors that collaborate with CLK:BMAL1. In summary, the application of Nascent-Seq to a mammalian tissue provides surprising insights into the rhythmic control of gene expression and should have broad applications beyond the analysis of circadian rhythms. Mouse liver nascent RNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina GAII (Nascent-Seq); Mouse liver mRNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina HiSeq2000 (RNA-Seq); CLK and BMAL1 DNA binding profile in the mouse liver at ZT8, sequenced along an Input sample using GAII (ChIP-Seq); Mouse liver strand-specific nascent RNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina HiSeq2000 (Strand-specific Nascent-Seq); Supplementary file RNASeq_Mouse_Liver_NormalizedGeneSignal.txt represents mRNA abundance (reads per base pair) for each sample.