TITER: predicting translation initiation sites by deep learning.

MotivationTranslation initiation is a key step in the regulation of gene expression. In addition to the annotated translation initiation sites (TISs), the translation process may also start at multiple alternative TISs (including both AUG and non-AUG codons), which makes it challenging to predict TISs and study the underlying regulatory mechanisms. Meanwhile, the advent of several high-throughput sequencing techniques for profiling initiating ribosomes at single-nucleotide resolution, e.g. GTI-seq and QTI-seq, provides abundant data for systematically studying the general principles of translation initiation and the development of computational method for TIS identification.MethodsWe have developed a deep learning-based framework, named TITER, for accurately predicting TISs on a genome-wide scale based on QTI-seq data. TITER extracts the sequence features of translation initiation from the surrounding sequence contexts of TISs using a hybrid neural network and further integrates the prior preference of TIS codon composition into a unified prediction framework.ResultsExtensive tests demonstrated that TITER can greatly outperform the state-of-the-art prediction methods in identifying TISs. In addition, TITER was able to identify important sequence signatures for individual types of TIS codons, including a Kozak-sequence-like motif for AUG start codon. Furthermore, the TITER prediction score can be related to the strength of translation initiation in various biological scenarios, including the repressive effect of the upstream open reading frames on gene expression and the mutational effects influencing translation initiation efficiency.Availability and implementationTITER is available as an open-source software and can be downloaded from https://github.com/zhangsaithu/titer [email protected] or [email protected] informationSupplementary data are available at Bioinformatics online

Two RNA-binding motifs in eIF3 direct HCV IRES-dependent translation.

The initiation of protein synthesis plays an essential regulatory role in human biology. At the center of the initiation pathway, the 13-subunit eukaryotic translation initiation factor 3 (eIF3) controls access of other initiation factors and mRNA to the ribosome by unknown mechanisms. Using electron microscopy (EM), bioinformatics and biochemical experiments, we identify two highly conserved RNA-binding motifs in eIF3 that direct translation initiation from the hepatitis C virus internal ribosome entry site (HCV IRES) RNA. Mutations in the RNA-binding motif of subunit eIF3a weaken eIF3 binding to the HCV IRES and the 40S ribosomal subunit, thereby suppressing eIF2-dependent recognition of the start codon. Mutations in the eIF3c RNA-binding motif also reduce 40S ribosomal subunit binding to eIF3, and inhibit eIF5B-dependent steps downstream of start codon recognition. These results provide the first connection between the structure of the central translation initiation factor eIF3 and recognition of the HCV genomic RNA start codon, molecular interactions that likely extend to the human transcriptome

Omnipresent Maxwell’s demons orchestrate information management in living cells

The development of synthetic biology calls for accurate understanding of the critical functions that allow construction and operation of a living cell. Besides coding for ubiquitous structures, minimal genomes encode a wealth of functions that dissipate energy in an unanticipated way. Analysis of these functions shows that they are meant to manage information under conditions when discrimination of substrates in a noisy background is preferred over a simple recognition process. We show here that many of these functions, including transporters and the ribosome construction machinery, behave as would behave a material implementation of the informationmanaging agent theorized by Maxwell almost 150 years ago and commonly known as Maxwell’s demon (MxD). A core gene set encoding these functions belongs to the minimal genome required to allow the construction of an autonomous cell. These MxDs allow the cell to perform computations in an energy-efficient way that is vastly better than our contemporary computers

Virulence- and signaling-associated genes display a preference for long 3′UTRs during rice infection and metabolic stress in the rice blast fungus

Generation of mRNA isoforms by alternative polyadenylation (APA) and their involvement in regulation of fungal cellular processes, including virulence, remains elusive. Here, we investigated genome‐wide polyadenylation site (PAS) selection in the rice blast fungus to understand how APA regulates pathogenicity. More than half of Magnaporthe oryzae transcripts undergo APA and show novel motifs in their PAS region. Transcripts with shorter 3′UTRs are more stable and abundant in polysomal fractions, suggesting they are being translated more efficiently. Importantly, rice colonization increases the use of distal PASs of pathogenicity genes, especially those participating in signalling pathways like 14‐3‐3B, whose long 3′UTR is required for infection. Cleavage factor I (CFI) Rbp35 regulates expression and distal PAS selection of virulence and signalling‐associated genes, tRNAs and transposable elements, pointing its potential to drive genomic rearrangements and pathogen evolution. We propose a noncanonical PAS selection mechanism for Rbp35 that recognizes UGUAH, unlike humans, without CFI25. Our results showed that APA controls turnover and translation of transcripts involved in fungal growth and environmental adaptation. Furthermore, these data provide useful information for enhancing genome annotations and for cross‐species comparisons of PASs and PAS usage within the fungal kingdom and the tree of life

Translation initiation factor eIF3 promotes programmed stop codon readthrough.

Programmed stop codon readthrough is a post-transcription regulatory mechanism specifically increasing proteome diversity by creating a pool of C-terminally extended proteins. During this process, the stop codon is decoded as a sense codon by a near-cognate tRNA, which programs the ribosome to continue elongation. The efficiency of competition for the stop codon between release factors (eRFs) and near-cognate tRNAs is largely dependent on its nucleotide context; however, the molecular mechanism underlying this process is unknown. Here, we show that it is the translation initiation (not termination) factor, namely eIF3, which critically promotes programmed readthrough on all three stop codons. In order to do so, eIF3 must associate with pre-termination complexes where it interferes with the eRF1 decoding of the third/wobble position of the stop codon set in the unfavorable termination context, thus allowing incorporation of near-cognate tRNAs with a mismatch at the same position. We clearly demonstrate that efficient readthrough is enabled by near-cognate tRNAs with a mismatch only at the third/wobble position. Importantly, the eIF3 role in programmed readthrough is conserved between yeast and humans

REPARATION : ribosome profiling assisted (re-)annotation of bacterial genomes

Prokaryotic genome annotation is highly dependent on automated methods, as manual curation cannot keep up with the exponential growth of sequenced genomes. Current automated methods depend heavily on sequence composition and often underestimate the complexity of the proteome. We developed RibosomeE Profiling Assisted (re-)AnnotaTION (REPARATION), a de novo machine learning algorithm that takes advantage of experimental protein synthesis evidence from ribosome profiling (Ribo-seq) to delineate translated open reading frames (ORFs) in bacteria, independent of genome annotation (https://github.com/Biobix/ REPARATION). REPARATION evaluates all possible ORFs in the genome and estimates minimum thresholds based on a growth curve model to screen for spurious ORFs. We applied REPARATION to three annotated bacterial species to obtain a more comprehensive mapping of their translation landscape in support of experimental data. In all cases, we identified hundreds of novel (small) ORFs including variants of previously annotated ORFs and >70% of all (variants of) annotated protein coding ORFs were predicted by REPARATION to be translated. Our predictions are supported by matching mass spectrometry proteomics data, sequence composition and conservation analysis. REPARATION is unique in that it makes use of experimental translation evidence to intrinsically perform a de novo ORF delineation in bacterial genomes irrespective of the sequence features linked to open reading frames

The Role of Cytoplasmic mRNA Cap-Binding Protein Complexes in Trypanosoma brucei and Other Trypanosomatids.

Trypanosomatid protozoa are unusual eukaryotes that are well known for having unusual ways of controlling their gene expression. The lack of a refined mode of transcriptional control in these organisms is compensated by several post-transcriptional control mechanisms, such as control of mRNA turnover and selection of mRNA for translation, that may modulate protein synthesis in response to several environmental conditions found in different hosts. In other eukaryotes, selection of mRNA for translation is mediated by the complex eIF4F, a heterotrimeric protein complex composed by the subunits eIF4E, eIF4G, and eIF4A, where the eIF4E binds to the 5'-cap structure of mature mRNAs. In this review, we present and discuss the characteristics of six trypanosomatid eIF4E homologs and their associated proteins that form multiple eIF4F complexes. The existence of multiple eIF4F complexes in trypanosomatids evokes exquisite mechanisms for differential mRNA recognition for translation

Signal Recognition Particle (SRP) and SRP Receptor: A New Paradigm for Multistate Regulatory GTPases

The GTP-binding proteins or GTPases comprise a superfamily of proteins that provide molecular switches in numerous cellular processes. The “GTPase switch” paradigm, in which a GTPase acts as a bimodal switch that is turned “on” and “off” by external regulatory factors, has been used to interpret the regulatory mechanism of many GTPases for more than two decades. Nevertheless, recent work has unveiled an emerging class of “multistate” regulatory GTPases that do not adhere to this classical paradigm. Instead of relying on external nucleotide exchange factors or GTPase activating proteins to switch between the on and off states, these GTPases have the intrinsic ability to exchange nucleotides and to sense and respond to upstream and downstream factors. In contrast to the bimodal nature of the GTPase switch, these GTPases undergo multiple conformational rearrangements, allowing multiple regulatory points to be built into a complex biological process to ensure the efficiency and fidelity of the pathway. We suggest that these multistate regulatory GTPases are uniquely suited to provide spatial and temporal control of complex cellular pathways that require multiple molecular events to occur in a highly coordinated fashion