A Genome-Wide Assay Specifies Only GreA as a Transcription Fidelity Factor in Escherichia coli

Engineering tRNAs for the Ribosomal Translation of Non-proteinogenic Monomers

Ribosome-dependent protein biosynthesis is an essential cellular process mediated by transfer RNAs (tRNAs). Generally, ribosomally synthesized proteins are limited to the 22 proteinogenic amino acids (pAAs: 20 l-α-amino acids present in the standard genetic code, selenocysteine, and pyrrolysine). However, engineering tRNAs for the ribosomal incorporation of non-proteinogenic monomers (npMs) as building blocks has led to the creation of unique polypeptides with broad applications in cellular biology, material science, spectroscopy, and pharmaceuticals. Ribosomal polymerization of these engineered polypeptides presents a variety of challenges for biochemists, as translation efficiency and fidelity is often insufficient when employing npMs. In this Review, we will focus on the methodologies for engineering tRNAs to overcome these issues and explore recent advances both in vitro and in vivo. These efforts include increasing orthogonality, recruiting essential translation factors, and creation of expanded genetic codes. After our review on the biochemical optimizations of tRNAs, we provide examples of their use in genetic code manipulation, with a focus on the in vitro discovery of bioactive macrocyclic peptides containing npMs. Finally, an analysis of the current state of tRNA engineering is presented, along with existing challenges and future perspectives for the field.

Targeted accurate RNA consensus sequencing (tARC-seq) reveals mechanisms of replication error affecting SARS-CoV-2 divergence

RNA viruses, like SARS-CoV-2, depend on their RNA-dependent RNA polymerases (RdRp) for replication, which is error prone. Monitoring replication errors is crucial for understanding the virus's evolution. Current methods lack the precision to detect rare de novo RNA mutations, particularly in low-input samples such as those from patients. Here we introduce a targeted accurate RNA consensus sequencing method (tARC-seq) to accurately determine the mutation frequency and types in SARS-CoV-2, both in cell culture and clinical samples. Our findings show an average of 2.68 × 10-5 de novo errors per cycle with a C > T bias that cannot be solely attributed to APOBEC editing. We identified hotspots and cold spots throughout the genome, correlating with high or low GC content, and pinpointed transcription regulatory sites as regions more susceptible to errors. tARC-seq captured template switching events including insertions, deletions and complex mutations. These insights shed light on the genetic diversity generation and evolutionary dynamics of SARS-CoV-2.

Evolutionary conservation of the fidelity of transcription

Accurate transcription is required for the faithful expression of genetic information. However, relatively little is known about the molecular mechanisms that control the fidelity of transcription, or the conservation of these mechanisms across the tree of life. To address these issues, we measured the error rate of transcription in five organisms of increasing complexity and found that the error rate of RNA polymerase II ranges from 2.9 × 10-6 ± 1.9 × 10-7/bp in yeast to 4.0 × 10-6 ± 5.2 × 10-7/bp in worms, 5.69 × 10-6 ± 8.2 × 10-7/bp in flies, 4.9 × 10-6 ± 3.6 × 10-7/bp in mouse cells and 4.7 × 10-6 ± 9.9 × 10-8/bp in human cells. These error rates were modified by various factors including aging, mutagen treatment and gene modifications. For example, the deletion or modification of several related genes increased the error rate substantially in both yeast and human cells. This research highlights the evolutionary conservation of factors that control the fidelity of transcription. Additionally, these experiments provide a reasonable estimate of the error rate of transcription in human cells and identify disease alleles in a subunit of RNA polymerase II that display error-prone transcription. Finally, we provide evidence suggesting that the error rate and spectrum of transcription co-evolved with our genetic code.

RNA polymerase inaccuracy underlies SARS-CoV-2 variants and vaccine heterogeneity

Both the SARS-CoV-2 virus and its mRNA vaccines depend on RNA polymerases (RNAP)1,2; however, these enzymes are inherently error-prone and can introduce variants into the RNA3. To understand SARS-CoV-2 evolution and vaccine efficacy, it is critical to identify the extent and distribution of errors introduced by the RNAPs involved in each process. Current methods lack the sensitivity and specificity to measure de novo RNA variants in low input samples like viral isolates3. Here, we determine the frequency and nature of RNA errors in both SARS-CoV-2 and its vaccine using a targeted Accurate RNA Consensus sequencing method (tARC-seq). We found that the viral RNA-dependent RNAP (RdRp) makes ~1 error every 10,000 nucleotides - higher than previous estimates4. We also observed that RNA variants are not randomly distributed across the genome but are associated with certain genomic features and genes, such as S (Spike). tARC-seq captured a number of large insertions, deletions and complex mutations that can be modeled through non-programmed RdRp template switching. This template switching feature of RdRp explains many key genetic changes observed during the evolution of different lineages worldwide, including Omicron. Further sequencing of the Pfizer-BioNTech COVID-19 vaccine revealed an RNA variant frequency of ~1 in 5,000, meaning most of the vaccine transcripts produced in vitro by T7 phage RNAP harbor a variant. These results demonstrate the extraordinary genetic diversity of viral populations and the heterogeneous nature of an mRNA vaccine fueled by RNAP inaccuracy. Along with functional studies and pandemic data, tARC-seq variant spectra can inform models to predict how SARS-CoV-2 may evolve. Finally, our results may help improve future vaccine development and study design as mRNA therapies continue to gain traction.

High Transcriptional Error Rates Vary as a Function of Gene Expression Level

Errors in gene transcription can be costly, and organisms have evolved to prevent their occurrence or mitigate their costs. The simplest interpretation of the drift barrier hypothesis suggests that species with larger population sizes would have lower transcriptional error rates. However, Escherichia coli seems to have a higher transcriptional error rate than species with lower effective population sizes, for example Saccharomyces cerevisiae. This could be explained if selection in E. coli were strong enough to maintain adaptations that mitigate the consequences of transcriptional errors through robustness, on a gene by gene basis, obviating the need for low transcriptional error rates and associated costs of global proofreading. Here, we note that if selection is powerful enough to evolve local robustness, selection should also be powerful enough to locally reduce error rates. We therefore predict that transcriptional error rates will be lower in highly abundant proteins on which selection is strongest. However, we only expect this result when error rates are high enough to significantly impact fitness. As expected, we find such a relationship between expression and transcriptional error rate for non-C→U errors in E. coli (especially G→A), but not in S. cerevisiae. We do not find this pattern for C→U changes in E. coli, presumably because most deamination events occurred during sample preparation, but do for C→U changes in S. cerevisiae, supporting the interpretation that C→U error rates estimated with an improved protocol, and which occur at rates comparable with E. coli non-C→U errors, are biological.

Interactions between DksA and Stress-Responsive Alternative Sigma Factors Control Inorganic Polyphosphate Accumulation in Escherichia coli

Bacteria synthesize inorganic polyphosphate (polyP) in response to a variety of different stress conditions. polyP protects bacteria by acting as a protein-stabilizing chaperone, metal chelator, or regulator of protein function, among other mechanisms. However, little is known about how stress signals are transmitted in the cell to lead to increased polyP accumulation. Previous work in the model enterobacterium Escherichia coli has indicated that the RNA polymerase-binding regulatory protein DksA is required for polyP synthesis in response to nutrient limitation stress. In this work, I set out to characterize the role of DksA in polyP regulation in more detail. I found that overexpression of DksA increases cellular polyP content (explaining the long-mysterious phenotype of dksA overexpression rescuing growth of a dnaK mutant at high temperatures) and characterized the roles of known functional residues of DksA in this process, finding that binding to RNA polymerase is required but that none of the other functions of DksA appear to be necessary. Transcriptomics revealed genome-wide transcriptional changes upon nutrient limitation, many of which were affected by DksA, and follow-up experiments identified complex interactions between DksA and the stress-sensing alternative sigma factors FliA, RpoN, and RpoE that impact polyP production, indicating that regulation of polyP synthesis is deeply entwined in the multifactorial stress response network of E. coli IMPORTANCE Inorganic polyphosphate (polyP) is an evolutionarily ancient, widely conserved biopolymer required for stress resistance and pathogenesis in diverse bacteria, but we do not understand how its synthesis is regulated. In this work, I gained new insights into this process by characterizing the role of the transcriptional regulator DksA in polyP regulation in Escherichia coli and identifying previously unknown links between polyP synthesis and the stress-responsive alternative sigma factors FliA, RpoN, and RpoE.

Universally high transcript error rates in bacteria

Errors can occur at any level during the replication and transcription of genetic information. Genetic mutations derived mainly from replication errors have been extensively studied. However, fundamental details of transcript errors, such as their rate, molecular spectrum, and functional effects, remain largely unknown. To globally identify transcript errors, we applied an adapted rolling-circle sequencing approach to Escherichia coli, Bacillus subtilis, Agrobacterium tumefaciens, and Mesoplasma florum, revealing transcript-error rates 3 to 4 orders of magnitude higher than the corresponding genetic mutation rates. The majority of detected errors would result in amino-acid changes, if translated. With errors identified from 9929 loci, the molecular spectrum and distribution of errors were uncovered in great detail. A G→A substitution bias was observed in M. florum, which apparently has an error-prone RNA polymerase. Surprisingly, an increased frequency of nonsense errors towards the 3' end of mRNAs was observed, suggesting a Nonsense-Mediated Decay-like quality-control mechanism in prokaryotes.

Involvement of Transcription Elongation Factor GreA in Mycobacterium Viability, Antibiotic Susceptibility, and Intracellular Fitness

There is growing evidence that GreA aids adaptation to stressful environments in various bacteria. However, the functions of GreA among mycobacteria remain obscure. Here, we report on cellular consequences following deletion of greA gene in Mycobacterium spp. The greA mutant strain (ΔgreA) was generated in Mycobacterium smegmatis, Mycobacterium tuberculosis (MTB) H37Ra, and M. tuberculosis H37Rv. Deletion of greA results in growth retardation and poor survival in response to adverse stress, besides rendering M. tuberculosis more susceptible to vancomycin and rifampicin. By using RNA-seq, we observe that disrupting greA results in the differential regulation of 195 genes in M. smegmatis with 167 being negatively regulated. Among these, KEGG pathways significantly enriched for differentially regulated genes included tryptophan metabolism, starch and sucrose metabolism, and carotenoid biosynthesis, supporting a role of GreA in the metabolic regulation of mycobacteria. Moreover, like Escherichia coli GreA, M. smegmatis GreA exhibits a series of conservative features, and the anti-backtracking activity of C-terminal domain is indispensable for the expression of glgX, a gene was down-regulated in the RNA-seq data. Interestingly, the decrease in the expression of glgX by CRISPR interference, resulted in reduced growth. Finally, intracellular fitness significantly declines due to loss of greA. Our data indicates that GreA is an important factor for the survival and resistance establishment in Mycobacterium spp. This study provides new insight into GreA as a potential target in multi-drug resistant TB treatment.

Autoregulation of greA Expression Relies on GraL Rather than on greA Promoter Region

GreA is a well-characterized transcriptional factor that acts primarily by rescuing stalled RNA polymerase complexes, but has also been shown to be the major transcriptional fidelity and proofreading factor, while it inhibits DNA break repair. Regulation of greA gene expression itself is still not well understood. So far, it has been shown that its expression is driven by two overlapping promoters and that greA leader encodes a small RNA (GraL) that is acting in trans on nudE mRNA. It has been also shown that GreA autoinhibits its own expression in vivo. Here, we decided to investigate the inner workings of this autoregulatory loop. Transcriptional fusions with lacZ reporter carrying different modifications (made both to the greA promoter and leader regions) were made to pinpoint the sequences responsible for this autoregulation, while GraL levels were also monitored. Our data indicate that GreA mediated regulation of its own gene expression is dependent on GraL acting in cis (a rare example of dual-action sRNA), rather than on the promoter region. However, a yet unidentified, additional factor seems to participate in this regulation as well. Overall, the GreA/GraL regulatory loop seems to have unique but hard to classify properties.

Transcription fidelity: New paradigms in epigenetic inheritance, genome instability and disease

RNA transcription errors are transient, yet frequent, events that do have consequences for the cell. However, until recently we lacked the tools to empirically measure and study these errors. Advances in RNA library preparation and next generation sequencing (NGS) have allowed the spectrum of transcription errors to be empirically measured over the entire transcriptome and in nascent transcripts. Combining these powerful methods with forward and reverse genetic strategies has refined our understanding of transcription factors known to enhance RNA accuracy and will enable the discovery of new candidates. Furthermore, these approaches will shed additional light on the complex interplay between transcription fidelity and other DNA transactions, such as replication and repair, and explore a role for transcription errors in cellular evolution and disease.

Non-programmed transcriptional frameshifting is common and highly RNA polymerase type-dependent

Background

The viral or host systems for a gene expression assume repeatability of the process and high quality of the protein product. Since level and fidelity of transcription primarily determines the overall efficiency, all factors contributing to their decrease should be identified and optimized. Among many observed processes, non-programmed insertion/deletion (indel) of nucleotide during transcription (slippage) occurring at homopolymeric A/T sequences within a gene can considerably impact its expression. To date, no comparative study of the most utilized Escherichia coli and T7 bacteriophage RNA polymerases (RNAP) propensity for this type of erroneous mRNA synthesis has been reported. To address this issue we evaluated the influence of shift-prone A/T sequences by assessing indel-dependent phenotypic changes. RNAP-specific expression profile was examined using two of the most potent promoters, P_araBAD of E. coli and φ10 of phage T7.

Results

Here we report on the first systematic study on requirements for efficient transcriptional slippage by T7 phage and cellular RNAPs considering three parameters: homopolymer length, template type, and frameshift directionality preferences. Using a series of out-of-frame gfp reporter genes fused to a variety of A/T homopolymeric sequences we show that T7 RNAP has an exceptional potential for generating frameshifts and is capable of slipping on as few as three adenine or four thymidine residues in a row, in a flanking sequence-dependent manner. In contrast, bacterial RNAP exhibits a relatively low ability to baypass indel mutations and requires a run of at least 7 tymidine and even more adenine residues. This difference comes from involvement of various intrinsic proofreading properties. Our studies demonstrate distinct preference towards a specific homopolymer in slippage induction. Whereas insertion slippage performed by T7 RNAP (but not deletion) occurs tendentiously on poly(A) rather than on poly(T) runs, strong bias towards poly(T) for the host RNAP is observed.

Conclusions

Intrinsic RNAP slippage properties involve trade-offs between accuracy, speed and processivity of transcription. Viral T7 RNAP manifests far greater inclinations to the transcriptional slippage than E. coli RNAP. This possibly plays an important role in driving bacteriophage adaptation and therefore could be considered as beneficial. However, from biotechnological and experimental viewpoint, this might create some problems, and strongly argues for employing bacterial expression systems, stocked with proofreading mechanisms.

Electronic supplementary material

The online version of this article (10.1186/s12934-018-1034-4) contains supplementary material, which is available to authorized users.