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

Metabolism-dependent secondary effect of anti-MAPK cancer therapy on DNA repair

Amino acid bioavailability impacts mRNA translation in a codon-dependent manner. Here, we report that the anti-cancer MAPK inhibitors (MAPKi) decrease the intracellular concentration of aspartate and glutamate in melanoma cells. This coincides with the accumulation of ribosomes on codons corresponding to these amino acids and triggers the translation-dependent degradation of mRNAs encoding aspartate- and glutamate-rich proteins, involved in DNA metabolism such as DNA replication and repair. Consequently, cells that survive MAPKi degrade aspartate and glutamate likely to generate energy, which simultaneously decreases their requirement for amino acids due to the downregulation of aspartate- and glutamate-rich proteins involved in cell proliferation. Concomitantly, the downregulation of aspartate- and glutamate-rich proteins involved in DNA repair increases DNA damage loads. Thus, DNA repair defects, and therefore mutations, are at least in part a secondary effect of the metabolic adaptation of cells exposed to MAPKi.

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.

Genome-wide screening reveals metabolic regulation of stop-codon readthrough by cyclic AMP

Translational fidelity is critical for microbial fitness, survival and stress responses. Much remains unknown about the genetic and environmental control of translational fidelity and its single-cell heterogeneity. In this study, we used a high-throughput fluorescence-based assay to screen a knock-out library of Escherichia coli and identified over 20 genes critical for stop-codon readthrough. Most of these identified genes were not previously known to affect translational fidelity. Intriguingly, we show that several genes controlling metabolism, including cyaA and crp, enhance stop-codon readthrough. CyaA catalyzes the synthesis of cyclic adenosine monophosphate (cAMP). Combining RNA sequencing, metabolomics and biochemical analyses, we show that deleting cyaA impairs amino acid catabolism and production of ATP, thus repressing the transcription of rRNAs and tRNAs to decrease readthrough. Single-cell analyses further show that cAMP is a major driver of heterogeneity in stop-codon readthrough and rRNA expression. Our results highlight that carbon metabolism is tightly coupled with stop-codon readthrough.

Phenotypic mutations contribute to protein diversity and shape protein evolution

Errors in DNA replication generate genetic mutations, while errors in transcription and translation lead to phenotypic mutations. Phenotypic mutations are orders of magnitude more frequent than genetic ones, yet they are less understood. Here, we review the types of phenotypic mutations, their quantifications, and their role in protein evolution and disease. The diversity generated by phenotypic mutation can facilitate adaptive evolution. Indeed, phenotypic mutations, such as ribosomal frameshift and stop codon readthrough, sometimes serve to regulate protein expression and function. Phenotypic mutations have often been linked to fitness decrease and diseases. Thus, understanding the protein heterogeneity and phenotypic diversity caused by phenotypic mutations will advance our understanding of protein evolution and have implications on human health and diseases.

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.

Within and Beyond the Nucleotide Addition Cycle of Viral RNA-dependent RNA Polymerases

Nucleotide addition cycle (NAC) is a fundamental process utilized by nucleic acid polymerases when carrying out nucleic acid biosynthesis. An induced-fit mechanism is usually taken by these polymerases upon NTP/dNTP substrate binding, leading to active site closure and formation of a phosphodiester bond. In viral RNA-dependent RNA polymerases, the post-chemistry translocation is stringently controlled by a structurally conserved motif, resulting in asymmetric movement of the template-product duplex. This perspective focuses on viral RdRP NAC and related mechanisms that have not been structurally clarified to date. Firstly, RdRP movement along the template strand in the absence of catalytic events may be relevant to catalytic complex dissociation or proofreading. Secondly, pyrophosphate or non-cognate NTP-mediated cleavage of the product strand 3′-nucleotide can also play a role in reactivating paused or arrested catalytic complexes. Furthermore, non-cognate NTP substrates, including NTP analog inhibitors, can not only alter NAC when being misincorporated, but also impact on subsequent NACs. Complications and challenges related to these topics are also discussed.

In vivo, in vitro and in silico: an open space for the development of microbe-based applications of synthetic biology

Living systems are studied using three complementary approaches: living cells, cell-free systems and computer-mediated modelling. Progresses in understanding, allowing researchers to create novel chassis and industrial processes rest on a cycle that combines in vivo, in vitro and in silico studies. This design-build-test-learn iteration loop cycle between experiments and analyses combines together physiology, genetics, biochemistry and bioinformatics in a way that keeps going forward. Because computer-aided approaches are not directly constrained by the material nature of the entities of interest, we illustrate here how this virtuous cycle allows researchers to explore chemistry which is foreign to that present in extant life, from whole chassis to novel metabolic cycles. Particular emphasis is placed on the importance of evolution.

Impact of alanyl-tRNA synthetase editing deficiency in yeast

Aminoacyl-tRNA synthetases (aaRSs) are essential enzymes that provide the ribosome with aminoacyl-tRNA substrates for protein synthesis. Mutations in aaRSs lead to various neurological disorders in humans. Many aaRSs utilize editing to prevent error propagation during translation. Editing defects in alanyl-tRNA synthetase (AlaRS) cause neurodegeneration and cardioproteinopathy in mice and are associated with microcephaly in human patients. The cellular impact of AlaRS editing deficiency in eukaryotes remains unclear. Here we use yeast as a model organism to systematically investigate the physiological role of AlaRS editing. Our RNA sequencing and quantitative proteomics results reveal that AlaRS editing defects surprisingly activate the general amino acid control pathway and attenuate the heatshock response. We have confirmed these results with reporter and growth assays. In addition, AlaRS editing defects downregulate carbon metabolism and attenuate protein synthesis. Supplying yeast cells with extra carbon source partially rescues the heat sensitivity caused by AlaRS editing deficiency. These findings are in stark contrast with the cellular effects caused by editing deficiency in other aaRSs. Our study therefore highlights the idiosyncratic role of AlaRS editing compared with other aaRSs and provides a model for the physiological impact caused by the lack of AlaRS editing.

Metabolic stress promotes stop-codon readthrough and phenotypic heterogeneity

Accurate protein synthesis is a tightly controlled biological process with multiple quality control steps safeguarded by aminoacyl-transfer RNA (tRNA) synthetases and the ribosome. Reduced translational accuracy leads to various physiological changes in both prokaryotes and eukaryotes. Termination of translation is signaled by stop codons and catalyzed by release factors. Occasionally, stop codons can be suppressed by near-cognate aminoacyl-tRNAs, resulting in protein variants with extended C termini. We have recently shown that stop-codon readthrough is heterogeneous among single bacterial cells. However, little is known about how environmental factors affect the level and heterogeneity of stop-codon readthrough. In this study, we have combined dual-fluorescence reporters, mass spectrometry, mathematical modeling, and single-cell approaches to demonstrate that a metabolic stress caused by excess carbon substantially increases both the level and heterogeneity of stop-codon readthrough. Excess carbon leads to accumulation of acid metabolites, which lower the pH and the activity of release factors to promote readthrough. Furthermore, our time-lapse microscopy experiments show that single cells with high readthrough levels are more adapted to severe acid stress conditions and are more sensitive to an aminoglycoside antibiotic. Our work thus reveals a metabolic stress that promotes translational heterogeneity and phenotypic diversity.

Reverse Transcriptase: From Transcriptomics to Genome Editing

Reverse transcriptases (RTs) are enzymes that can generate a complementary strand of DNA (cDNA) from RNA. Coupled with PCR, RTs have been widely used to detect RNAs and to clone expressed genes. Classical retroviral RTs have been improved by protein engineering. These enzymes and newly characterized RTs are key elements in the development of next-generation sequencing techniques that are now being applied to the study of transcriptomics. In addition, engineered RTs fused to a CRISPR/Cas9 nickase have recently shown great potential as tools to manipulate eukaryotic genomes. In this review, we discuss the properties and uses of wild type and engineered RTs in biotechnological applications, from conventional RT-PCR to recently introduced prime editing.

Physicochemical Foundations of Life that Direct Evolution: Chance and Natural Selection are not Evolutionary Driving Forces

The current framework of evolutionary theory postulates that evolution relies on random mutations generating a diversity of phenotypes on which natural selection acts. This framework was established using a top-down approach as it originated from Darwinism, which is based on observations made of complex multicellular organisms and, then, modified to fit a DNA-centric view. In this article, it is argued that based on a bottom-up approach starting from the physicochemical properties of nucleic and amino acid polymers, we should reject the facts that (i) natural selection plays a dominant role in evolution and (ii) the probability of mutations is independent of the generated phenotype. It is shown that the adaptation of a phenotype to an environment does not correspond to organism fitness, but rather corresponds to maintaining the genome stability and integrity. In a stable environment, the phenotype maintains the stability of its originating genome and both (genome and phenotype) are reproduced identically. In an unstable environment (i.e., corresponding to variations in physicochemical parameters above a physiological range), the phenotype no longer maintains the stability of its originating genome, but instead influences its variations. Indeed, environment- and cellular-dependent physicochemical parameters define the probability of mutations in terms of frequency, nature, and location in a genome. Evolution is non-deterministic because it relies on probabilistic physicochemical rules, and evolution is driven by a bidirectional interplay between genome and phenotype in which the phenotype ensures the stability of its originating genome in a cellular and environmental physicochemical parameter-depending manner.

Four paralogous Gfh factors in the extremophilic bacterium Deinococcus peraridilitoris have distinct effects on various steps of transcription

Gre factors are ubiquitous transcription regulators that stimulate co-transcriptional RNA cleavage by bacterial RNA polymerase (RNAP). Here, we show that the stress-resistant bacterium Deinococcus peraridilitoris encodes four Gre factor homologs, Gfh proteins, that have distinct effects on transcription by RNAP. Two of the factors, Gfh1α and Gfh2β inhibit transcription initiation, and one of them, Gfh1α can also regulate transcription elongation. We show that this factor strongly stimulates transcriptional pausing and intrinsic termination in the presence of manganese ions but has no effect on RNA cleavage. Thus, some Gfh factors encoded by Deinococci serve as lineage-specific transcription inhibitors that may play a role in stress resistance, while the functions of others remain to be discovered.