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Biology subjects

Lorent, J.

Publications and source records attributed to Lorent, J..

4 recordsLinked to original sources

Translational profiling of macrophages infected with Leishmania donovani identifies mTOR- and eIF4A-sensitive immune-related transcripts

The protozoan parasite Leishmania donovani (L. donovani) causes visceral leishmaniasis, a chronic infection which is fatal when untreated. While previous studies showed that L. donovani reprograms transcription to subvert host cell functions, it remains unclear whether the parasite also alters host mRNA translation to establish a successful infection. To assess this, we compared transcriptome-wide translation in primary mouse macrophages infected with L. donovani promastigotes or amastigotes using polysome-profiling. This identified ample selective changes in translation (3,127 transcripts) which were predicted to target central cellular functions by inducing synthesis of proteins related to chromatin remodeling and RNA metabolism while inhibiting those related to intracellular trafficking and antigen presentation. Parallel quantification of protein and mRNA levels for a set of transcripts whose translation was activated upon L. donovani infection (Papbpc1, Eif2ak2, and Tgfb) confirmed, as indicated by polysome-profiling, increased protein levels despite largely unaltered mRNA levels. Mechanistic in silico analyses suggested activated translation depending on the kinase mTOR (e.g. Pabpc1) and the RNA helicase eIF4A (e.g. Tgfb) during infection. Accordingly, treatment with mTOR inhibitors torin-1 or rapamycin reversed L. donovani-induced PABPC1 without affecting corresponding transcript levels. Similarly, the production of TGF-{beta} decreased in presence of the eIF4A inhibitor silvestrol despite unaltered Tgfb mRNA levels. Consistent with parasite modulation of host eIF4A-sensitive translation to promote infection, silvestrol suppressed L. donovani replication within macrophages. In contrast, parasite survival was favored under mTOR inhibition. In summary, infection-associated changes in translation of mTOR- and eIF4A-sensitive mRNAs contribute to modulate mRNA metabolism and immune responses in L. donovani-infected macrophages. Although the net outcome of such translation programs favours parasite propagation, individual translation programs appear to have opposing roles during L. donovani infection, thereby suggesting their selective targeting as key for therapeutic effects. Author SummaryFine-tuning the efficiency of mRNA translation into proteins allows cells to tailor their responses to stress without the need for synthesizing new mRNA molecules. It is well established that the protozoan parasite Leishmania donovani alters transcription of specific genes to subvert host cell functions. However, discrepancies between transcriptomic and proteomic data suggest that post-transcriptional regulatory mechanisms also contribute to modulate host gene expression programs during L. donovani infection. Herein, we report that one third of protein-coding mRNAs expressed in macrophages are differentially translated upon infection with L. donovani. Our computational analyses reveal that subsets of mRNAs encoding functionally related proteins share the same directionality of translational regulation, which is likely to impact metabolic and microbicidal activity of infected cells. We also show that upregulated translation of transcripts that encode central regulators of mRNA metabolism and inflammation is sensitive to the activation of mTOR or eIF4A during infection. Finally, we observe that inhibition of eIF4A activity reduces parasite survival within macrophages while selective blockade of mTOR has the opposite effect. Thus, our study points to a dual role for translational control of host gene expression during L. donovani infection and suggests that novel regulatory nodes could be targeted for therapeutic intervention.

immunology↗

Estrogen receptor alpha controls gene expression via translational offsetting

Estrogen receptor alpha (ER) activity is associated with increased cancer cell proliferation. Studies aiming to understand the impact of ER on cancer-associated phenotypes have largely been limited to its transcriptional activity. Herein, we demonstrate that ER coordinates its transcriptional output with selective modulation of mRNA translation. Importantly, translational perturbations caused by depletion of ER largely manifest as \"translational offsetting\" of the transcriptome, whereby amounts of translated mRNA and protein levels are maintained constant despite changes in mRNA abundance. Transcripts whose levels, but not polysome-association, are reduced following ER depletion lack features which limit translational efficiency including structured 5UTRs and miRNA target sites. In contrast, mRNAs induced upon ER depletion whose polysome-association remains unaltered are enriched in codons requiring U34-modified tRNAs for efficient decoding. Consistently, ER regulates levels of U34-modification enzymes, whereas altered expression of U34-modification enzymes disrupts ER dependent translational offsetting. Altogether, we unravel a hitherto unprecedented mechanism of ER-dependent orchestration of transcriptional and translational programs, and highlight that translational offsetting may be a pervasive mechanism of proteome maintenance in hormone-dependent cancers.

systems biology↗

Genome-wide analysis of differential translation and differential translational buffering using anota2seq

mRNA translation plays an evolutionarily conserved role in homeostasis and when dysregulated results in various disorders. Optimal and universally applicable analytical methods to study transcriptome-wide changes in translational efficiency are therefore critical for understanding the complex role of translation regulation under physiological and pathological conditions. Techniques used to interrogate translatomes, including polysome- and ribosome-profiling, require adjustment for changes in total mRNA levels to capture bona fide alterations in translational efficiency. Herein, we present the anota2seq algorithm for such analysis using data from ribosome- or polysome-profiling quantified by DNA-microarrays or RNA sequencing, which outperforms current methods for identification of changes in translational efficiency. In contrast to available analytical methods, anota2seq also allows capture of an underappreciated mode for regulation of gene expression whereby translation acts as a buffering mechanism which maintains constant protein levels despite fluctuations in mRNA levels (\"translational buffering\"). Application of anota2seq shows that insulin affects gene expression at multiple levels, in a largely mTOR-dependent manner. Moreover, insulin induces levels of a subset of mRNAs independently of mTOR that undergo translational buffering upon mTOR inhibition. Thus, the universal anota2seq algorithm allows efficient and hitherto unprecedented interrogation of translatomes and enables studies of translational buffering which represents an unexplored mechanism for regulating of gene expression.

bioinformatics↗

Polysome-profiling in small tissue samples

Polysome-profiling is commonly used to study genome wide patterns of translational efficiency, i.e. the translatome. The standard approach for collecting efficiently translated polysome-associated RNA results in laborious extraction of RNA from a large volume spread across multiple fractions. This property makes polysome-profiling inconvenient for larger experimental designs or samples with low RNA amounts such as primary cells or frozen tissues. To address this we optimized a non-linear sucrose gradient which reproducibly enriches for mRNAs associated with >3 ribosomes in only one or two fractions, thereby reducing sample handling 5-10 fold. The technique can be applied to cells and frozen tissue samples from biobanks, and generates RNA with a quality reflecting the starting material. When coupled with smart-seq2, a single-cell RNA sequencing technique, translatomes from small tissue samples can be obtained. Translatomes acquired using optimized non-linear gradients are very similar to those obtained when applying linear gradients. Polysome-profiling using optimized nonlinear gradients in HCT-116 cells with or without p53 identified a translatome associated with p53 status under serum starvation. Thus, here we present a polysome-profiling technique applicable to larger studies, primary cells where RNA amount is low and frozen tissue samples.

molecular biology↗