Hepatic stellate cells suppress NK cell-sustained breast cancer dormancy.

The persistence of undetectable disseminated tumour cells (DTCs) after primary tumour resection poses a major challenge to effective cancer treatment1-3. These enduring dormant DTCs are seeds of future metastases, and the mechanisms that switch them from dormancy to outgrowth require definition. Because cancer dormancy provides a unique therapeutic window for preventing metastatic disease, a comprehensive understanding of the distribution, composition and dynamics of reservoirs of dormant DTCs is imperative. Here we show that different tissue-specific microenvironments restrain or allow the progression of breast cancer in the liver-a frequent site of metastasis4 that is often associated with a poor prognosis5. Using mouse models, we show that there is a selective increase in natural killer (NK) cells in the dormant milieu. Adjuvant interleukin-15-based immunotherapy ensures an abundant pool of NK cells that sustains dormancy through interferon-γ signalling, thereby preventing hepatic metastases and prolonging survival. Exit from dormancy follows a marked contraction of the NK cell compartment and the concurrent accumulation of activated hepatic stellate cells (aHSCs). Our proteomics studies on liver co-cultures implicate the aHSC-secreted chemokine CXCL12 in the induction of NK cell quiescence through its cognate receptor CXCR4. CXCL12 expression and aHSC abundance are closely correlated in patients with liver metastases. Our data identify the interplay between NK cells and aHSCs as a master switch of cancer dormancy, and suggest that therapies aimed at normalizing the NK cell pool might succeed in preventing metastatic outgrowth.

Prevention of dsRNA-induced interferon signaling by AGO1x is linked to breast cancer cell proliferation.

Translational readthrough, i.e., elongation of polypeptide chains beyond the stop codon, was initially reported for viral RNA, but later found also on eukaryotic transcripts, resulting in proteome diversification and protein-level modulation. Here, we report that AGO1x, an evolutionarily conserved translational readthrough isoform of Argonaute 1, is generated in highly proliferative breast cancer cells, where it curbs accumulation of double-stranded RNAs (dsRNAs) and consequent induction of interferon responses and apoptosis. In contrast to other mammalian Argonaute protein family members with primarily cytoplasmic functions, AGO1x exhibits nuclear localization in the vicinity of nucleoli. We identify AGO1x interaction with the polyribonucleotide nucleotidyltransferase 1 (PNPT1) and show that the depletion of this protein further augments dsRNA accumulation. Our study thus uncovers a novel function of an Argonaute protein in buffering the endogenous dsRNA-induced interferon responses, different than the canonical function of AGO proteins in the miRNA effector pathway. As AGO1x expression is tightly linked to breast cancer cell proliferation, our study thus suggests a new direction for limiting tumor growth.

A rare codon-based translational program of cell proliferation.

BACKGROUND: The speed of translation elongation is primarily determined by the abundance of tRNAs. Thus, the codon usage influences the rate with which individual mRNAs are translated. As the nature of tRNA pools and modifications can vary across biological conditions, codon elongation rates may also vary, leading to fluctuations in the protein production from individual mRNAs. Although it has been observed that functionally related mRNAs exhibit similar codon usage, presumably to provide an effective way to coordinate expression of multiple proteins, experimental evidence for codon-mediated translation efficiency modulation of functionally related mRNAs in specific conditions is scarce and the associated mechanisms are still debated. RESULTS: Here, we reveal that mRNAs whose expression increases during cell proliferation are enriched in rare codons, poorly adapted to tRNA pools. Ribosome occupancy profiling and proteomics measurements show that upon increased cell proliferation, transcripts enriched in rare codons undergo a higher translation boost than transcripts with common codons. Re-coding of a fluorescent reporter with rare codons increased protein output by ~ 30% relative to a reporter re-coded with common codons. Although the translation capacity of proliferating cells was higher compared to resting cells, we did not find evidence for the regulation of individual tRNAs. Among the models that were proposed so far to account for codon-mediated translational regulation upon changing conditions, the one that seems most consistent with our data involves a global upregulation of ready-to-translate tRNAs, which we show can lead to a higher increase in the elongation velocity at rare codons compared to common codons. CONCLUSIONS: We propose that the alleviation of translation bottlenecks in rapidly dividing cells enables preferential upregulation of pro-proliferation proteins, encoded by mRNAs that are enriched in rare codons.

Evaluation of 244,000 synthetic sequences reveals design principles to optimize translation in Escherichia coli.

Comparative analyses of natural and mutated sequences have been used to probe mechanisms of gene expression, but small sample sizes may produce biased outcomes. We applied an unbiased design-of-experiments approach to disentangle factors suspected to affect translation efficiency in E. coli. We precisely designed 244,000 DNA sequences implementing 56 replicates of a full factorial design to evaluate nucleotide, secondary structure, codon and amino acid properties in combination. For each sequence, we measured reporter transcript abundance and decay, polysome profiles, protein production and growth rates. Associations between designed sequences properties and these consequent phenotypes were dominated by secondary structures and their interactions within transcripts. We confirmed that transcript structure generally limits translation initiation and demonstrated its physiological cost using an epigenetic assay. Codon composition has a sizable impact on translatability, but only in comparatively rare elongation-limited transcripts. We propose a set of design principles to improve translation efficiency that would benefit from more accurate prediction of secondary structures in vivo.

Roquin targets mRNAs in a 3'-UTR-specific manner by different modes of regulation.

The RNA-binding proteins Roquin-1 and Roquin-2 redundantly control gene expression and cell-fate decisions. Here, we show that Roquin not only interacts with stem-loop structures, but also with a linear sequence element present in about half of its targets. Comprehensive analysis of a minimal response element of the Nfkbid 3'-UTR shows that six stem-loop structures cooperate to exert robust and profound post-transcriptional regulation. Only binding of multiple Roquin proteins to several stem-loops exerts full repression, which redundantly involved deadenylation and decapping, but also translational inhibition. Globally, most Roquin targets are regulated by mRNA decay, whereas a small subset, including the Nfat5 mRNA, with more binding sites in their 3'-UTRs, are also subject to translational inhibition. These findings provide insights into how the robustness and magnitude of Roquin-mediated regulation is encoded in complex cis-elements.

Roquin Suppresses the PI3K-mTOR Signaling Pathway to Inhibit T Helper Cell Differentiation and Conversion of Treg to Tfr Cells.

Roquin proteins preclude spontaneous T cell activation and aberrant differentiation of T follicular helper (Tfh) or T helper 17 (Th17) cells. Here we showed that deletion of Roquin-encoding alleles specifically in regulatory T (Treg) cells also caused the activation of conventional T cells. Roquin-deficient Treg cells downregulated CD25, acquired a follicular Treg (Tfr) cell phenotype, and suppressed germinal center reactions but could not protect from colitis. Roquin inhibited the PI3K-mTOR signaling pathway by upregulation of Pten through interfering with miR-17∼92 binding to an overlapping cis-element in the Pten 3' UTR, and downregulated the Foxo1-specific E3 ubiquitin ligase Itch. Loss of Roquin enhanced Akt-mTOR signaling and protein synthesis, whereas inhibition of PI3K or mTOR in Roquin-deficient T cells corrected enhanced Tfh and Th17 or reduced iTreg cell differentiation. Thereby, Roquin-mediated control of PI3K-mTOR signaling prevents autoimmunity by restraining activation and differentiation of conventional T cells and specialization of Treg cells.

The Gcn4 transcription factor reduces protein synthesis capacity and extends yeast lifespan.

In Saccharomyces cerevisiae, deletion of large ribosomal subunit protein-encoding genes increases the replicative lifespan in a Gcn4-dependent manner. However, how Gcn4, a key transcriptional activator of amino acid biosynthesis genes, increases lifespan, is unknown. Here we show that Gcn4 acts as a repressor of protein synthesis. By analyzing the messenger RNA and protein abundance, ribosome occupancy and protein synthesis rate in various yeast strains, we demonstrate that Gcn4 is sufficient to reduce protein synthesis and increase yeast lifespan. Chromatin immunoprecipitation reveals Gcn4 binding not only at genes that are activated, but also at genes, some encoding ribosomal proteins, that are repressed upon Gcn4 overexpression. The promoters of repressed genes contain Rap1 binding motifs. Our data suggest that Gcn4 is a central regulator of protein synthesis under multiple perturbations, including ribosomal protein gene deletions, calorie restriction, and rapamycin treatment, and provide an explanation for its role in longevity and stress response.The transcription factor Gcn4 is known to regulate yeast amino acid synthesis. Here, the authors show that Gcn4 also acts as a repressor of protein biosynthesis in a range of conditions that enhance yeast lifespan, such as ribosomal protein knockout, calorie restriction or mTOR inhibition.

Patterns of ribosomal protein expression specify normal and malignant human cells.

BACKGROUND: Ribosomes are highly conserved molecular machines whose core composition has traditionally been regarded as invariant. However, recent studies have reported intriguing differences in the expression of some ribosomal proteins (RPs) across tissues and highly specific effects on the translation of individual mRNAs. RESULTS: To determine whether RPs are more generally linked to cell identity, we analyze the heterogeneity of RP expression in a large set of human tissues, primary cells, and tumors. We find that about a quarter of human RPs exhibit tissue-specific expression and that primary hematopoietic cells display the most complex patterns of RP expression, likely shaped by context-restricted transcriptional regulators. Strikingly, we uncover patterns of dysregulated expression of individual RPs across cancer types that arise through copy number variations and are predictive for disease progression. CONCLUSIONS: Our study reveals an unanticipated plasticity of RP expression across normal and malignant human cell types and provides a foundation for future characterization of cellular behaviors that are orchestrated by specific RPs.

Transcript level and sequence determinants of protein abundance and noise in Escherichia coli.

The range over which a protein is expressed, and its cell-to-cell variability, is often thought to be linked to the demand for its activity. Steady-state protein level is determined by multiple mechanisms controlling transcription and translation, many of which are limited by DNA- and RNA-encoded signals that affect initiation, elongation and termination of polymerases and ribosomes. We performed a comprehensive analysis of >100 sequence features to derive a predictive model composed of a minimal non-redundant set of factors explaining 66% of the total variation of protein abundance observed in >800 genes in Escherichia coli. The model suggests that protein abundance is primarily determined by the transcript level (53%) and by effectors of translation elongation (12%), whereas only a small fraction of the variation is explained by translational initiation (1%). Our analyses uncover a new sequence determinant, not previously described, affecting translation initiation and suggest that elongation rate is affected by both codon biases and specific amino acid composition. We also show that transcription and translation efficiency may have an effect on expression noise, which is more similar than previously assumed.

D-Tailor: automated analysis and design of DNA sequences.

MOTIVATION: Current advances in DNA synthesis, cloning and sequencing technologies afford high-throughput implementation of artificial sequences into living cells. However, flexible computational tools for multi-objective sequence design are lacking, limiting the potential of these technologies. RESULTS: We developed DNA-Tailor (D-Tailor), a fully extendable software framework, for property-based design of synthetic DNA sequences. D-Tailor permits the seamless integration of multiple sequence analysis tools into a generic Monte Carlo simulation that evolves sequences toward any combination of rationally defined properties. As proof of principle, we show that D-Tailor is capable of designing sequence libraries comprising all possible combinations among three different sequence properties influencing translation efficiency in Escherichia coli The capacity to design artificial sequences that systematically sample any given parameter space should support the implementation of more rigorous experimental designs. AVAILABILITY: Source code is available for download at https://sourceforge.net/projects/dtailor/ CONTACT: aparkin@lbl.gov or cambray.guillaume@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online (D-Tailor Tutorial).

Precise and reliable gene expression via standard transcription and translation initiation elements.

An inability to reliably predict quantitative behaviors for novel combinations of genetic elements limits the rational engineering of biological systems. We developed an expression cassette architecture for genetic elements controlling transcription and translation initiation in Escherichia coli: transcription elements encode a common mRNA start, and translation elements use an overlapping genetic motif found in many natural systems. We engineered libraries of constitutive and repressor-regulated promoters along with translation initiation elements following these definitions. We measured activity distributions for each library and selected elements that collectively resulted in expression across a 1,000-fold observed dynamic range. We studied all combinations of curated elements, demonstrating that arbitrary genes are reliably expressed to within twofold relative target expression windows with ∼93% reliability. We expect the genetic element definitions validated here can be collectively expanded to create collections of public-domain standard biological parts that support reliable forward engineering of gene expression at genome scales.

Quantitative estimation of activity and quality for collections of functional genetic elements.

The practice of engineering biology now depends on the ad hoc reuse of genetic elements whose precise activities vary across changing contexts. Methods are lacking for researchers to affordably coordinate the quantification and analysis of part performance across varied environments, as needed to identify, evaluate and improve problematic part types. We developed an easy-to-use analysis of variance (ANOVA) framework for quantifying the performance of genetic elements. For proof of concept, we assembled and analyzed combinations of prokaryotic transcription and translation initiation elements in Escherichia coli. We determined how estimation of part activity relates to the number of unique element combinations tested, and we show how to estimate expected ensemble-wide part activity from just one or two measurements. We propose a new statistic, biomolecular part 'quality', for tracking quantitative variation in part performance across changing contexts.

Measurement and modeling of intrinsic transcription terminators.

The reliable forward engineering of genetic systems remains limited by the ad hoc reuse of many types of basic genetic elements. Although a few intrinsic prokaryotic transcription terminators are used routinely, termination efficiencies have not been studied systematically. Here, we developed and validated a genetic architecture that enables reliable measurement of termination efficiencies. We then assembled a collection of 61 natural and synthetic terminators that collectively encode termination efficiencies across an ∼800-fold dynamic range within Escherichia coli. We simulated co-transcriptional RNA folding dynamics to identify competing secondary structures that might interfere with terminator folding kinetics or impact termination activity. We found that structures extending beyond the core terminator stem are likely to increase terminator activity. By excluding terminators encoding such context-confounding elements, we were able to develop a linear sequence-function model that can be used to estimate termination efficiencies (r = 0.9, n = 31) better than models trained on all terminators (r = 0.67, n = 54). The resulting systematically measured collection of terminators should improve the engineering of synthetic genetic systems and also advance quantitative modeling of transcription termination.

Rationally designed families of orthogonal RNA regulators of translation.

Our ability to routinely engineer genetic networks for applications is limited by the scarcity of highly specific and non-cross-reacting (orthogonal) gene regulators with predictable behavior. Though antisense RNAs are attractive contenders for this purpose, quantitative understanding of their specificity and sequence-function relationship sufficient for their design has been limited. Here, we use rationally designed variants of the RNA-IN-RNA-OUT antisense RNA-mediated translation system from the insertion sequence IS10 to quantify >500 RNA-RNA interactions in Escherichia coli and integrate the data set with sequence-activity modeling to identify the thermodynamic stability of the duplex and the seed region as the key determinants of specificity. Applying this model, we predict the performance of an additional ~2,600 antisense-regulator pairs, forecast the possibility of large families of orthogonal mutants, and forward engineer and experimentally validate two RNA pairs orthogonal to an existing group of five from the training data set. We discuss the potential use of these regulators in next-generation synthetic biology applications.