Differential annotation of tRNA genes with anticodon CAT in bacterial genomes.
Ontology highlight
ABSTRACT:
SUBMITTER: Silva FJ
PROVIDER: S-EPMC1635315 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:With the development of ultra-high-throughput technologies, the cost of sequencing bacterial genomes has been vastly reduced. As more genomes are sequenced, less time can be spent manually annotating those genomes, resulting in an increased reliance on automatic annotation pipelines. However, automatic pipelines can produce inaccurate genome annotation and their results often require manual curation. Here, we discuss the automatic and manual annotation of bacterial genomes, identify common problems introduced by the current genome annotation process and suggests potential solutions.
| S-EPMC3548604 | biostudies-literature
Project description:The delineation of genes in bacteria has remained an important challenge because prokaryotic genomes are often tightly packed frequently resulting in overlapping genes. We hereby present a de novo approach called REPARATION (RibosomeE Profiling Assisted (Re-)AnnotaTION) to delineate translated open reading frames (ORFs) in bacteria independent of (available) genome annotation. By deep sequencing of ribosome protected mRNA fragments (RPF) to map translating ribosomes across the entire genome, REPARATION takes advantage of the recently developed ribosome profiling (Ribo-seq) technique. REPARATION starts by traversing the entire genome to generate all possible ORFs and then collects their corresponding RPF signal information. Based on a growth curve model to estimate minimum ORF read density and Ribo-seq RPF coverage, thresholds indicative of translation is estimated. Finally, our algorithm applies a random forest model to build a classifier to classify putative protein coding ORFs. We evaluated the performance of REPARATION on 3 annotated bacterial species using in-house generated Ribo-seq data and matching N-terminal and shotgun proteomics data next to publically available Ribo-seq data. In all cases, about 80% of the ORFs predicted by REPARATION were previously annotated as protein coding. While 13-20% were variants of previously annotated ORFs and about 3-4% point to novel translated ORFs within intergenic or other regions previously annotated as non-coding. Without stringent length restrictions REPARATION was able to identify several small ORFs (sORFs). Multiple supportive evidence from matching MS data and sequence conservation analysis was obtained to validate predicted ORFs.
2017-01-30 | GSE91066 | GEO
Project description:Ancient mechanisms for nucleotide base recognition in the RNA world are candidates for mimicking by early proteins like tRNA synthetases. In the core of the tRNA, conserved G22 interacts with two internal bases in a complex further stabilized by stacking interactions. This particular tRNA format for G recognition is shown here to be adapted by nine different and even nonhomologous anticodon binding domains (ABDs) of tRNA synthetases, in which amino acid side chains mimic all of the tRNA G22 base interactions. We offer the possibility that mimicking this RNA-based mechanism for guanine recognition is perhaps one of the selective pressures for choosing amino acids for the genetic code.
| S-EPMC3634914 | biostudies-literature
Project description: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.
| S-EPMC5714196 | biostudies-literature
Project description:The pathogenic bacterium Helicobacter pylori utilizes two essential glutamyl-tRNA synthetases (GluRS1 and GluRS2). These two enzymes are closely related in evolution and yet they aminoacylate contrasting tRNAs. GluRS1 is a canonical discriminating GluRS (D-GluRS) that biosynthesizes Glu-tRNA(Glu) and cannot make Glu-tRNA(Gln). In contrast, GluRS2 is non-canonical as it is only essential for the production of misacylated Glu-tRNA(Gln). The co-existence and evident divergence of these two enzymes was capitalized upon to directly examine how GluRS2 acquired tRNA(Gln) specificity. One key feature that distinguishes tRNA(Glu) from tRNA(Gln) is the third position in the anticodon of each tRNA (C36 versus G36, respectively). By comparing sequence alignments of different GluRSs, including GluRS1s and GluRS2s, to the crystal structure of the Thermus thermophilus D-GluRS:tRNA(Glu) complex, a divergent pattern of conservation in enzymes that aminoacylate tRNA(Glu)versus those specific for tRNA(Gln) emerged and was experimentally validated. In particular, when an arginine conserved in discriminating GluRSs and GluRS1s was inserted into Hp GluRS2 (Glu334Arg GluRS2), the catalytic efficiency of the mutant enzyme (k(cat)/K(Mapp)) was reduced by approximately one order of magnitude towards tRNA(Gln). However, this mutation did not introduce activity towards tRNA(Glu). In contrast, disruption of a glycine that is conserved in all GluRS2s but not in other GluRSs (Gly417Thr GluRS2) generated a mutant GluRS2 with weak activity towards tRNA(Glu1). Synergy between these two mutations was observed in the double mutant (Glu334Arg/Gly417Thr GluRS2), which specifically and more robustly aminoacylates tRNA(Glu1) instead of tRNA(Gln). As GluRS1 and GluRS2 are related by an apparent gene duplication event, these results demonstrate that we can experimentally map critical evolutionary events in the emergence of new tRNA specificities.
| S-EPMC2897014 | biostudies-literature
Project description:BackgroundProtein-coding gene detection in prokaryotic genomes is considered a much simpler problem than in intron-containing eukaryotic genomes. However there have been reports that prokaryotic gene finder programs have problems with small genes (either over-predicting or under-predicting). Therefore the question arises as to whether current genome annotations have systematically missing, small genes.ResultsWe have developed a high-performance computing methodology to investigate this problem. In this methodology we compare all ORFs larger than or equal to 33 aa from all fully-sequenced prokaryotic replicons. Based on that comparison, and using conservative criteria requiring a minimum taxonomic diversity between conserved ORFs in different genomes, we have discovered 1,153 candidate genes that are missing from current genome annotations. These missing genes are similar only to each other and do not have any strong similarity to gene sequences in public databases, with the implication that these ORFs belong to missing gene families. We also uncovered 38,895 intergenic ORFs, readily identified as putative genes by similarity to currently annotated genes (we call these absent annotations). The vast majority of the missing genes found are small (less than 100 aa). A comparison of select examples with GeneMark, EasyGene and Glimmer predictions yields evidence that some of these genes are escaping detection by these programs.ConclusionsProkaryotic gene finders and prokaryotic genome annotations require improvement for accurate prediction of small genes. The number of missing gene families found is likely a lower bound on the actual number, due to the conservative criteria used to determine whether an ORF corresponds to a real gene.
| S-EPMC3098052 | biostudies-literature
Project description:Prokaryotic genome annotation is highly dependent on automated methods, as manual curation cannot keep up with the exponential growth of sequenced genomes. Current automated techniques depend heavily on sequence context and often underestimate the complexity of the proteome. We developed REPARATION (RibosomeE Profiling Assisted (Re-)AnnotaTION), a de novo algorithm that takes advantage of experimental evidence from ribosome profiling (Ribo-seq) to delineate translated open reading frames (ORFs) in bacteria, independent of genome annotation. Ribo-seq next generation sequencing technique that provides a genome-wide snapshot of the position translating ribosome along an mRNA at the time of the experiment. REPARATION evaluates all possible ORFs in the genome and estimates minimum thresholds to screen for spurious ORFs based on a growth curve model. 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 ORFs including variants of previously annotated and novel small ORFs (<71 codons). Our predictions were supported by matching mass spectrometry (MS) proteomics data and sequence conservation analysis. REPARATION is unique in that it makes use of experimental Ribo-seq data to perform de novo ORF delineation in bacterial genomes, and thus can identify putative coding ORFs irrespective of the sequence context of the reading frame.
2017-08-09 | PXD005844 | Pride
Project description:Transfer RNA (tRNA) structure, modifications and functions are evolutionary and established in bacteria, archaea and eukaryotes. Typically the tRNA modifications are indispensable for its stability and are required for decoding the mRNA into amino acids for protein synthesis. A conserved methylation has been located on the anticodon loop specifically at the 37(th) position and it is next to the anticodon bases. This modification is called as m1G37 and it is catalyzed by tRNA (m(1)G37) methyltransferase (TrmD). It is deciphered that G37 positions occur on few additional amino acids specific tRNA subsets in bacteria. Furthermore, Archaea and Eukaryotes have more number of tRNA subsets which contains G37 position next to the anticodon and the G residue are located at different positions such as G36, G37, G38, 39, and G40. In eight bacterial species, G (guanosine) residues are presents at the 37(th) and 38(th) position except three tRNA subsets having G residues at 36(th) and 39(th) positions. Therefore we propose that m1G37 modification may be feasible at 36(th), 37(th), 38(th), 39(th) and 40(th) positions next to the anticodon of tRNAs. Collectively, methylation at G residues close to the anticodon may be possible at different positions and without restriction of anticodon 3(rd) base A, C, U or G.
| S-EPMC3705617 | biostudies-literature
Project description:Delicate variances in the translational machinery affect how efficiently different organisms approach protein synthesis. Determining the scale of this effect, however, requires knowledge on the differences of mistranslation levels. Here, we used a dual-luciferase reporter assay cloned into a broad host range plasmid to reveal the translational fidelity profiles of Pseudomonas putida, Pseudomonas aeruginosa and Escherichia coli. We observed that these profiles are surprisingly different, whereas species more prone to translational frameshifting are not necessarily more prone to stop codon readthrough. As tRNA modifications are among the factors that have been implicated to affect translation accuracy, we also show that translational fidelity is context-specifically influenced by pseudouridines in the anticodon stem-loop of tRNA, but the effect is not uniform between species.
| S-EPMC9481147 | biostudies-literature
Project description:Modification of anticodon nucleotides allows tRNAs to decode multiple codons, expanding the genetic code. Additionally, modifications located in the anticodon loop, outside the anticodon itself, stabilize tRNA–codon interactions, increasing decoding fidelity. Anticodon loop nucleotide 37 is 3′ to the anticodon and, in tRNACGGPro, is methylated at the N1 position in its nucleobase (m1G37). The m1G37 modification in tRNACGGPro stabilizes its interaction with the codon and maintains the mRNA frame. However, it is unclear how m1G37 affects binding at the decoding center to both cognate and +1 slippery codons. Here, we show that the tRNACGGProm1G37 modification is important for the association step during binding to a cognate CCG codon. In contrast, m1G37 prevented association with a slippery CCC-U or +1 codon. Similar analyses of frameshift suppressor tRNASufA6, a tRNACGGPro derivative containing an extra nucleotide in its anticodon loop that undergoes +1 frameshifting, reveal that m1G37 destabilizes interactions with both the cognate CCG and slippery codons. One reason for this destabilization is the disruption of a conserved U32·A38 nucleotide pairing in the anticodon stem through insertion of G37.5. Restoring the tRNASufA6 U32·A37.5 pairing results in a high-affinity association on the slippery CCC-U codon. Further, an X-ray crystal structure of the 70S ribosome bound to tRNASufA6 U32·A37.5 at 3.6 Å resolution shows a reordering of the anticodon loop consistent with the findings from the high-affinity measurements. Our results reveal how the tRNA modification at nucleotide 37 stabilizes interactions with the mRNA codon to preserve the mRNA frame.
| S-EPMC6462517 | biostudies-literature