1
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Sigal M, Matsumoto S, Beattie A, Katoh T, Suga H. Engineering tRNAs for the Ribosomal Translation of Non-proteinogenic Monomers. Chem Rev 2024; 124:6444-6500. [PMID: 38688034 PMCID: PMC11122139 DOI: 10.1021/acs.chemrev.3c00894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 02/21/2024] [Accepted: 04/10/2024] [Indexed: 05/02/2024]
Abstract
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.
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Affiliation(s)
- Maxwell Sigal
- Department of Chemistry,
Graduate School of Science, The University
of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Satomi Matsumoto
- Department of Chemistry,
Graduate School of Science, The University
of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Adam Beattie
- Department of Chemistry,
Graduate School of Science, The University
of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Takayuki Katoh
- Department of Chemistry,
Graduate School of Science, The University
of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Hiroaki Suga
- Department of Chemistry,
Graduate School of Science, The University
of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
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2
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Bradley CC, Wang C, Gordon AJE, Wen AX, Luna PN, Cooke MB, Kohrn BF, Kennedy SR, Avadhanula V, Piedra PA, Lichtarge O, Shaw CA, Ronca SE, Herman C. Targeted accurate RNA consensus sequencing (tARC-seq) reveals mechanisms of replication error affecting SARS-CoV-2 divergence. Nat Microbiol 2024; 9:1382-1392. [PMID: 38649410 PMCID: PMC11384275 DOI: 10.1038/s41564-024-01655-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/28/2024] [Indexed: 04/25/2024]
Abstract
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.
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Affiliation(s)
- Catherine C Bradley
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Baylor College of Medicine Medical Scientist Training Program, Houston, TX, USA
- Robert and Janice McNair Foundation/ McNair Medical Institute M.D./Ph.D. Scholars program, Houston, TX, USA
| | - Chen Wang
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Alasdair J E Gordon
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Alice X Wen
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Baylor College of Medicine Medical Scientist Training Program, Houston, TX, USA
- Robert and Janice McNair Foundation/ McNair Medical Institute M.D./Ph.D. Scholars program, Houston, TX, USA
| | - Pamela N Luna
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Matthew B Cooke
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Brendan F Kohrn
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Scott R Kennedy
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Vasanthi Avadhanula
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Pedro A Piedra
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Olivier Lichtarge
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Chad A Shaw
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Shannon E Ronca
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
- Feigin Biosafety Level 3 Facility, Texas Children's Hospital, Houston, TX, USA
- National School of Tropical Medicine, Department of Pediatrics Tropical Medicine, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA
| | - Christophe Herman
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA.
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3
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Chung C, Verheijen BM, Navapanich Z, McGann EG, Shemtov S, Lai GJ, Arora P, Towheed A, Haroon S, Holczbauer A, Chang S, Manojlovic Z, Simpson S, Thomas KW, Kaplan C, van Hasselt P, Timmers M, Erie D, Chen L, Gout JF, Vermulst M. Evolutionary conservation of the fidelity of transcription. Nat Commun 2023; 14:1547. [PMID: 36941254 PMCID: PMC10027832 DOI: 10.1038/s41467-023-36525-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 02/03/2023] [Indexed: 03/23/2023] Open
Abstract
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.
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Affiliation(s)
- Claire Chung
- School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Bert M Verheijen
- School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Zoe Navapanich
- School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Eric G McGann
- School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Sarah Shemtov
- School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Guan-Ju Lai
- School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Payal Arora
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Atif Towheed
- Children's hospital of Philadelphia, Center for Mitochondrial and Epigenomic Medicine, Philadelphia, PA, USA
| | - Suraiya Haroon
- Children's hospital of Philadelphia, Center for Mitochondrial and Epigenomic Medicine, Philadelphia, PA, USA
| | - Agnes Holczbauer
- Children's hospital of Philadelphia, Center for Mitochondrial and Epigenomic Medicine, Philadelphia, PA, USA
| | - Sharon Chang
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Zarko Manojlovic
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Stephen Simpson
- College of Life Sciences and Agriculture, University of New Hampshire, Durham, NH, USA
| | - Kelley W Thomas
- College of Life Sciences and Agriculture, University of New Hampshire, Durham, NH, USA
| | - Craig Kaplan
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Peter van Hasselt
- Department of Metabolic Disease, University of Utrecht, Utrecht, the Netherlands
| | - Marc Timmers
- Department of Urology, Medical Center - University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) Partner Site Freiburg, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dorothy Erie
- Department of Chemistry, University of North Carolina, Chapel Hill, NC, USA
| | - Lin Chen
- Department of Molecular and Cellular Biology, University of Southern California, Los Angeles, CA, USA
| | - Jean-Franćois Gout
- Department of Biological Sciences, Mississippi State University, Mississippi State, MS, USA
| | - Marc Vermulst
- School of Gerontology, University of Southern California, Los Angeles, CA, USA.
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4
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Bradley CC, Gordon AJE, Wang C, Cooke MB, Kohrn BF, Kennedy SR, Lichtarge O, Ronca SE, Herman C. RNA polymerase inaccuracy underlies SARS-CoV-2 variants and vaccine heterogeneity. RESEARCH SQUARE 2022:rs.3.rs-1690086. [PMID: 35677076 PMCID: PMC9176646 DOI: 10.21203/rs.3.rs-1690086/v1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
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.
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Affiliation(s)
- Catherine C Bradley
- Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas 77030, USA
- Baylor College of Medicine Medical Scientist Training Program; Houston, Texas 77030, USA
- Robert and Janice McNair Foundation/ McNair Medical Institute M.D./Ph.D. Scholars program; Houston, Texas 77030, USA
| | - Alasdair J E Gordon
- Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas 77030, USA
| | - Chen Wang
- Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas 77030, USA
| | - Matthew B Cooke
- Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas 77030, USA
| | - Brendan F Kohrn
- Department of Laboratory Medicine and Pathology, University of Washington; Seattle, WA 98195, USA
| | - Scott R Kennedy
- Department of Laboratory Medicine and Pathology, University of Washington; Seattle, WA 98195, USA
| | - Olivier Lichtarge
- Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas 77030, USA
| | - Shannon E Ronca
- Feigin Biosafety Level 3 Facility, Texas Children's Hospital; Houston, Texas 77030, USA
- National School of Tropical Medicine, Department of Pediatrics Tropical Medicine, Texas Children's Hospital and Baylor College of Medicine; Houston, Texas 77030, USA
- Department of Molecular Virology and Microbiology, Baylor College of Medicine; Houston, Texas 77030, USA
| | - Christophe Herman
- Department of Molecular and Human Genetics, Baylor College of Medicine; Houston, Texas 77030, USA
- Department of Molecular Virology and Microbiology, Baylor College of Medicine; Houston, Texas 77030, USA
- Dan L. Duncan Cancer Center, Baylor College of Medicine; Houston, TX 77030, USA
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5
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Meer KM, Nelson PG, Xiong K, Masel J. High Transcriptional Error Rates Vary as a Function of Gene Expression Level. Genome Biol Evol 2020; 12:3754-3761. [PMID: 31841128 PMCID: PMC6988749 DOI: 10.1093/gbe/evz275] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/12/2019] [Indexed: 02/06/2023] Open
Abstract
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.
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Affiliation(s)
- Kendra M Meer
- Department of Ecology & Evolutionary Biology, University of Arizona.,Computational Bioscience Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Paul G Nelson
- Department of Ecology & Evolutionary Biology, University of Arizona
| | - Kun Xiong
- Department of Molecular & Cellular Biology, University of Arizona.,Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT
| | - Joanna Masel
- Department of Ecology & Evolutionary Biology, University of Arizona
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6
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Interactions between DksA and Stress-Responsive Alternative Sigma Factors Control Inorganic Polyphosphate Accumulation in Escherichia coli. J Bacteriol 2020; 202:JB.00133-20. [PMID: 32341074 DOI: 10.1128/jb.00133-20] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 04/21/2020] [Indexed: 01/24/2023] Open
Abstract
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.
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7
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Li W, Lynch M. Universally high transcript error rates in bacteria. eLife 2020; 9:54898. [PMID: 32469307 PMCID: PMC7259958 DOI: 10.7554/elife.54898] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 04/28/2020] [Indexed: 12/22/2022] Open
Abstract
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.
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Affiliation(s)
- Weiyi Li
- Department of Biology, Indiana University, Bloomington, United States
| | - Michael Lynch
- Department of Biology, Indiana University, Bloomington, United States.,Center for Mechanisms of Evolution, The Biodesign Institute, Arizona State University, Tempe, United States
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8
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Feng S, Liu Y, Liang W, El-Sayed Ahmed MAEG, Zhao Z, Shen C, Roberts AP, Liang L, Liao L, Zhong Z, Guo Z, Yang Y, Wen X, Chen H, Tian GB. Involvement of Transcription Elongation Factor GreA in Mycobacterium Viability, Antibiotic Susceptibility, and Intracellular Fitness. Front Microbiol 2020; 11:413. [PMID: 32265867 PMCID: PMC7104715 DOI: 10.3389/fmicb.2020.00413] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 02/27/2020] [Indexed: 11/13/2022] Open
Abstract
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.
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Affiliation(s)
- Siyuan Feng
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Ministry of Education, Sun Yat-sen University, Guangzhou, China
| | - Yan Liu
- Clinical Laboratory, Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China
| | - Wanfei Liang
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Ministry of Education, Sun Yat-sen University, Guangzhou, China
| | - Mohamed Abd El-Gawad El-Sayed Ahmed
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Ministry of Education, Sun Yat-sen University, Guangzhou, China
- Department of Microbiology and Immunology, Faculty of Pharmaceutical Sciences and Drug Manufacturing, Misr University for Science and Technology, Cairo, Egypt
| | - Zihan Zhao
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Ministry of Education, Sun Yat-sen University, Guangzhou, China
| | - Cong Shen
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Ministry of Education, Sun Yat-sen University, Guangzhou, China
| | - Adam P. Roberts
- Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- Centre for Drugs and Diagnostics, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Lujie Liang
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Ministry of Education, Sun Yat-sen University, Guangzhou, China
| | - Liya Liao
- Clinical Laboratory, Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China
| | - Zhijuan Zhong
- Clinical Laboratory, Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China
| | - Zhaowang Guo
- Clinical Laboratory, Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China
| | - Yongqiang Yang
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Xin Wen
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Ministry of Education, Sun Yat-sen University, Guangzhou, China
| | - Hongtao Chen
- Clinical Laboratory, Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China
| | - Guo-bao Tian
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Ministry of Education, Sun Yat-sen University, Guangzhou, China
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9
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Dylewski M, Fernández-Coll L, Bruhn-Olszewska B, Balsalobre C, Potrykus K. Autoregulation of greA Expression Relies on GraL Rather than on greA Promoter Region. Int J Mol Sci 2019; 20:ijms20205224. [PMID: 31652493 PMCID: PMC6829880 DOI: 10.3390/ijms20205224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Revised: 10/16/2019] [Accepted: 10/21/2019] [Indexed: 11/16/2022] Open
Abstract
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.
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Affiliation(s)
- Maciej Dylewski
- Department of Bacterial Molecular Genetics, Faculty of Biology, University of Gdańsk, W. Stwosza 59, 80-299 Gdańsk, Poland.
| | - Llorenç Fernández-Coll
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Av. Diagonal 643, 08028 Barcelona, Spain.
| | - Bożena Bruhn-Olszewska
- Department of Bacterial Molecular Genetics, Faculty of Biology, University of Gdańsk, W. Stwosza 59, 80-299 Gdańsk, Poland.
| | - Carlos Balsalobre
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Av. Diagonal 643, 08028 Barcelona, Spain.
| | - Katarzyna Potrykus
- Department of Bacterial Molecular Genetics, Faculty of Biology, University of Gdańsk, W. Stwosza 59, 80-299 Gdańsk, Poland.
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10
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Bradley CC, Gordon AJE, Halliday JA, Herman C. Transcription fidelity: New paradigms in epigenetic inheritance, genome instability and disease. DNA Repair (Amst) 2019; 81:102652. [PMID: 31326363 DOI: 10.1016/j.dnarep.2019.102652] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
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.
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Affiliation(s)
- Catherine C Bradley
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA; Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, 77030, USA; Robert and Janice McNair Foundation/ McNair Medical Institute M.D./Ph.D. Scholars Program, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Alasdair J E Gordon
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Jennifer A Halliday
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Christophe Herman
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, 77030, USA; Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA.
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Koscielniak D, Wons E, Wilkowska K, Sektas M. Non-programmed transcriptional frameshifting is common and highly RNA polymerase type-dependent. Microb Cell Fact 2018; 17:184. [PMID: 30474557 PMCID: PMC6260861 DOI: 10.1186/s12934-018-1034-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Accepted: 11/19/2018] [Indexed: 12/15/2022] Open
Abstract
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, ParaBAD 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.
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Affiliation(s)
- Dawid Koscielniak
- Department of Microbiology, Faculty of Biology, University of Gdansk, Wita Stwosza 59, 80-308, Gdansk, Poland
| | - Ewa Wons
- Department of Microbiology, Faculty of Biology, University of Gdansk, Wita Stwosza 59, 80-308, Gdansk, Poland
| | - Karolina Wilkowska
- Department of Microbiology, Faculty of Biology, University of Gdansk, Wita Stwosza 59, 80-308, Gdansk, Poland
| | - Marian Sektas
- Department of Microbiology, Faculty of Biology, University of Gdansk, Wita Stwosza 59, 80-308, Gdansk, Poland.
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