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Widespread post-transcriptional regulation of co-transmission.

ABSTRACT: While neurotransmitter identity was once considered singular and immutable for mature neurons, it is now appreciated that one neuron can release multiple neuroactive substances (co-transmission) whose identities can even change over time. To explore the mechanisms that tune the suite of transmitters a neuron releases, we developed transcriptional and translational reporters for cholinergic, glutamatergic, and GABAergic signaling in Drosophila . We show that many glutamatergic and GABAergic cells also transcribe cholinergic genes, but fail to accumulate cholinergic effector proteins. Suppression of cholinergic signaling involves posttranscriptional regulation of cholinergic transcripts by the microRNA miR-190; chronic loss of miR-190 function allows expression of cholinergic machinery, reducing and fragmenting sleep. Using a "translation-trap" strategy we show that neurons in these populations have episodes of transient translation of cholinergic proteins, demonstrating that suppression of co-transmission is actively modulated. Posttranscriptional restriction of fast transmitter co-transmission provides a mechanism allowing reversible tuning of neuronal output.

One-sentence summary

Cholinergic co-transmission in large populations of glutamatergic and GABAergic neurons in the Drosophila adult brain is controlled by miR-190.

SUBMITTER: Chen N

PROVIDER: S-EPMC10002718 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Widespread post-transcriptional regulation of co-transmission.

Chen Nannan N Zhang Yunpeng Y Rivera-Rodriguez Emmanuel J EJ Yu Albert D AD Hobin Michael M Rosbash Michael M Griffith Leslie C LC

bioRxiv : the preprint server for biology 20230302

While neurotransmitter identity was once considered singular and immutable for mature neurons, it is now appreciated that one neuron can release multiple neuroactive substances (co-transmission) whose identities can even change over time. To explore the mechanisms that tune the suite of transmitters a neuron releases, we developed transcriptional and translational reporters for cholinergic, glutamatergic, and GABAergic signaling in <i>Drosophila</i> . We show that many glutamatergic and GABAergi ...[more]

PMID: 36909471

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Project description:Protein and mRNA levels correlate only moderately. The availability of proteogenomics data sets with protein and transcript measurements from matching samples is providing new opportunities to assess the degree to which protein levels in a system can be predicted from mRNA information. Here we examined the contributions of input features in protein abundance prediction models. Using large proteogenomics data from 8 cancer types within the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data set, we trained models to predict the abundance of over 13,000 proteins using matching transcriptome data from up to 958 tumor or normal adjacent tissue samples each, and compared predictive performances across algorithms, data set sizes, and input features. Over one-third of proteins (4,648) showed relatively poor predictability (elastic net r ≤ 0.3) from their cognate transcripts. Moreover, we found widespread occurrences where the abundance of a protein is considerably less well explained by its own cognate transcript level than that of one or more trans locus transcripts. The incorporation of additional trans-locus transcript abundance data as input features increasingly improved the ability to predict sample protein abundance. Transcripts that contribute to non-cognate protein abundance primarily involve those encoding known or predicted interaction partners of the protein of interest, including not only large multi-protein complexes as previously shown, but also small stable complexes in the proteome with only one or few stable interacting partners. Network analysis further shows a complex proteome-wide interdependency of protein abundance on the transcript levels of multiple interacting partners. The predictive model analysis here therefore supports that protein-protein interaction including in small protein complexes exert post-transcriptional influence on proteome compositions more broadly than previously recognized. Moreover, the results suggest mRNA and protein co-expression analysis may have utility for finding gene interactions and predicting expression changes in biological systems.

Dataset Information

Widespread post-transcriptional regulation of co-transmission.

One-sentence summary

Publications

Widespread post-transcriptional regulation of co-transmission.

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