Translational efficiency across healthy and tumor tissues is proliferation‐related

Hernandez‐Alias, Xavier; Benisty, Hannah; Schaefer, Martin H.; Serrano, Luís

doi:10.15252/msb.20199275

Cited by 47 publications

(66 citation statements)

References 67 publications

(148 reference statements)

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“…The non-productive mock infections of each dataset were also analyzed for normalization. In Trimmed FASTQ files were then mapped using a specific pipeline for tRNAs 2,58 . Summarizing, an artificial genome is first generated by masking all annotated tRNA genes and adding pre-tRNAs (i.e.…”

Section: Small Rna-sequencing Datasets Upon Viral Infectionmentioning

confidence: 99%

“…The definition of the SDA is based on similar previously published metrics 2,64,65 , which consists of a ratio between the anticodon supply and demand. On the one hand, the anticodon supply is defined as the relative tAI weights (see previous section).…”

Section: = ∑ ∈mentioning

confidence: 99%

“…Such synonymous codons are nevertheless not uniformly distributed along the genomes and can significantly deviate between organisms 1 . Evolutionary forces that explain the existence of the so-called codon bias include (1) a mutation pressure for a certain GC base composition depending on the species and chromosomal location, and (2) the translational selection for codons corresponding to highly expressed tRNA isoacceptors [2][3][4] .…”

Section: Introductionmentioning

confidence: 99%

“…Although translational selection has long been under debate in human 13 , recent studies indicate that different tissues and conditions showcase distinct tRNA expression profiles, leading to changes in their respective translational efficiency 2,14 . In agreement with this observation, the codon usage of papillomavirus capsid proteins is adapted to the tRNAs of differentiated keratinocytes, where their translation becomes specifically efficient 15,16 .…”

Section: Introductionmentioning

confidence: 99%

“…Here, we systematically analyze the relative codon usage landscape of over 500 humaninfecting viruses together with the recently published tRNA expression profiles of human tissues 2 . Among other viral annotated features, including phylogeny and Baltimore classification, their tissue tropism explains more variance in codon usage than the other tested features.…”

Section: Introductionmentioning

confidence: 99%

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Translational adaptation of human viruses to the tissues they infect

Hernandez‐Alias

Schaefer

Serrano

2020

Preprint

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Viruses need to hijack the translational machinery of the host cell for a productive infection to happen. However, given the dynamic landscape of tRNA pools among tissues, it is unclear whether different viruses infecting different tissues have adapted their codon usage toward their tropism. Here, we collect the coding sequences of over 500 human-infecting viruses and determine that tropism explains changes in codon usage. Using an in silico model of translational efficiency, we validate the correspondence of the viral codon usage with the translational machinery of their tropism. In particular, we propose that the improved translational adaptation to the upper respiratory airways of the pandemic agent SARS-CoV-2 coronavirus could enhance its transmissibility. Furthermore, this correspondence is specifically defined in early viral proteins, as upon infection cells undergo reprogramming of tRNA pools that favors the translation of late counterparts.

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Section: Small Rna-sequencing Datasets Upon Viral Infectionmentioning

confidence: 99%

Section: = ∑ ∈mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Translational adaptation of human viruses to the tissues they infect

Hernandez‐Alias

Schaefer

Serrano

2020

Preprint

Self Cite

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Translational remodeling by RNA‐binding proteins and noncoding RNAs

Man

Schatz

et al. 2021

WIREs RNA

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Responsible for generating the proteome that controls phenotype, translation is the ultimate convergence point for myriad upstream signals that influence gene expression. System-wide adaptive translational reprogramming has recently emerged as a pillar of cellular adaptation. As classic regulators of mRNA stability and translation efficiency, foundational studies established the concept of collaboration and competition between RNA-binding proteins (RBPs) and noncoding RNAs (ncRNAs) on individual mRNAs. Fresh conceptual innovations now highlight stress-activated, evolutionarily conserved RBP networks and ncRNAs that increase the translation efficiency of populations of transcripts encoding proteins that participate in a common cellular process. The discovery of post-transcriptional functions for long noncoding RNAs (lncRNAs) was particularly intriguing given their cell-type-specificity and historical definition as nuclear-functioning epigenetic regulators. The convergence of RBPs, lncRNAs, and microRNAs on functionally related mRNAs to enable adaptive protein synthesis is a newer biological paradigm that highlights their role as "translatome (protein output) remodelers" and reinvigorates the paradigm of "RNA operons." Together, these concepts modernize our understanding of cellular stress adaptation and strategies for therapeutic development.

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