Ribosome profiling unveils translational regulation of metabolic enzymes in primary CD4+ Th1 cells

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Highlights

  • Translation controls the metabolism of human CD4+ Th1 cells.

  • Translation regulates glucose, fatty acids and pentose phosphates pathways.

  • Translational control discriminates between reversible and irreversible reactions.

  • Translational targets are mRNAs with structured 5′ untranslated regions.

Abstract

The transition from a naïve to an effector T cell is an essential event that requires metabolic reprogramming. We have recently demonstrated that the rapid metabolic changes that occur following stimulation of naïve T cells require the translation of preexisting mRNAs. Here, we provide evidence that translation regulates the metabolic asset of effector T cells. By performing ribosome profiling in human CD4+ Th1 cells, we show that the metabolism of glucose, fatty acids and pentose phosphates is regulated at the translational level. In Th1 cells, each pathway has at least one enzyme regulated at the translational level and selected enzymes have high translational efficiencies. mRNA expression does not predict protein expression. For instance, PKM2 mRNA is equally present in naïve T and Th1 cells, but the protein is abundant only in Th1. 5′-untranslated regions (UTRs) may partly account for this regulation. Overall we suggest that immunometabolism is controlled by translation.

Introduction

Protein synthesis is the decoding of mRNAs into proteins, alias translation. Translational control leads to the selection, starting from the global mRNA pool, of those transcripts requiring to be decoded into proteins (Truitt and Ruggero, 2016). The impact of translation on gene expression has been estimated to be at least as important as transcription (Schwanhausser et al., 2012), meaning that different mRNAs are differentially translated. Translation is divided into four phases: initiation, elongation, termination and recycling. Initiation is the rate-limiting event in the selection of a specific mRNA. At initiation, eIFs (eukaryotic Initiation Factors) perform mechanistic steps under the coordination of signaling pathways (Loreni et al., 2014) and interplay with regulatory elements in the untranslated regions (UTRs) of mRNAs, thus resulting in specific stimulation or inhibition of translation (Hinnebusch et al., 2016). One major pathway controlling initiation of translation is the mTORC1 pathway. mTORC1 stimulates the activity of the eIF4F complex which is necessary for efficient translation of mRNAs containing structured 5’ UTRs (Loreni et al., 2014). The relevance of mTORC1 in lymphocyte biology is well established (Zeng and Chi, 2017).

CD4+ T cells are essential for survival (Jung and Paauw, 1998). The transition from naïve T cells to effector T cells requires a complete metabolic rewiring that includes the activation of a glycolytic and fatty acid synthesis program, essential steps for nucleotide biosynthesis and, hence, for cellular growth. It has been traditionally thought that metabolic reprogramming correlates with transcriptional rewiring (Hough et al., 2015). Given the central role of mTORC1 in translation (Loreni et al., 2014), lipid synthesis (Lamming and Sabatini, 2013) and T cell differentiation (Zeng and Chi, 2017), we recently asked whether translational control plays a major role in T cell activation. We found that eukaryotic Initiation Factor 6 (eIF6) is fundamental for the acquisition of effector functions by CD4+ T cells (Manfrini et al., 2017a, 2017b) and that the transition from quiescence to the activated status requires translational control of the lipid biosynthetic pathway (Ricciardi et al., 2018). Overall, these data confirm the hypothesis that translational control is a major player in T cell activation (Piccirillo et al., 2014) and metabolism (Biffo et al., 2018; Brina et al., 2015; Miluzio et al., 2016). Whether translational control of metabolism affects also other stages of T cell differentiation is still unknown.

Ribosome profiling is a technology that allows the direct analysis of ribosomal footprints on cellular mRNAs, thus providing a detailed snapshot of translational control (Ingolia et al., 2011). Herein, by using this technique, we investigated the impact of translational regulation on gene expression in CD4+ Th1 cells. Although ribosome profiling has been recently performed in primary mouse T cells (Moore et al., 2018; Myers et al., 2019), our study stands as the first-ever ribosome profiling performed in primary human T cells. Intriguingly, we found that the metabolism of T cells is controlled also at the translational level, confirming that transcriptional studies largely fail in predicting the presence of metabolic enzymes.

Section snippets

RNA-seq data analysis

RNA-seq data for all human CD4+ T cell subsets were retrieved from (Bonnal et al., 2015) (ArrayExpress E-MTAB-513 experiment). Gene expression levels were estimated by Cufflinks (version 2.0.2) as raw FPKM counts. The heatmap shows z-scored log2-normalized FPKM counts for each gene in different human CD4+ T cell subsets. Heatmaps were generated using Heatmapper (http://www1.heatmapper.ca/expression/). Clustering was performed using the average linkage method and distance measurement was

Translational control regulates entire metabolic pathways

We have recently demonstrated that translation regulates the metabolic shift required for activating quiescent naïve CD4+ T cells (Ricciardi et al., 2018). We asked whether translational control played also a role in controlling the metabolism of effector CD4+ T cells. We investigated a previously published RNAseq dataset from 7 different human CD4+ T cell subsets (Bonnal et al., 2015), in order to highlight transcriptional profiles that might suggest a layer of translational regulation. We

Discussion

Our study shows that translational control regulates the expression levels of specific metabolic enzymes in CD4+ Th1 cells. Overall our study supports the model by which translation is not only coordinated with metabolism, but also acts upstream of metabolic steps, providing a feed-forward mechanism in which mitogenic and nutrient signaling activate a translational response (Biffo et al., 2018). Before discussing the biological implications of our findings, some technical caveats have to be

Author contributions

NM and SR designed the project, executed the experiments and analyzed the data. PC and AF performed experimental work and analyzed the data. RA and GV performed bioinformatic analyses. SB designed the experiments and analyzed data. NM and SB wrote the manuscript.

Funding

This work was supported by Europen Research Council (ERC) grant TRANSLATE 338999 and AIRC Investigator Grant - IG 2017 to SB.

Data availability statement

The datasets generated for this study can be found in ArrayExpress under accession number E-MTAB-59611 (https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-5961/) (Manfrini et al., 2019).

Declaration of competing interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank Dr. Nicholas T. Ingolia for his precious help and advice on ribosome profiling and Paola Gruarin for her help with Th1 differentiation.

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    1

    The two authors contributed equally to the work.

    2

    Current address: IGM- Institute of Molecular Genetics – CNR, Pavia, Italy.

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