首页 » 文章 » 文章详细信息
Molecular Systems Biology Volume 15 ,Issue 5 ,2019-05-03
Absolute quantification of translational regulation and burden using combined sequencing approaches
Articles
Thomas E Gorochowski 1 , 2 Irina Chelysheva 3 Mette Eriksen 4 Priyanka Nair 3 Steen Pedersen 4 Zoya Ignatova 3
Show affiliations
DOI:10.15252/msb.20188719
Received 2018-11-04, accepted for publication 2019-04-15, Published 2019-04-15
PDF
摘要

Abstract Translation of mRNAs into proteins is a key cellular process. Ribosome binding sites and stop codons provide signals to initiate and terminate translation, while stable secondary mRNA structures can induce translational recoding events. Fluorescent proteins are commonly used to characterize such elements but require the modification of a part's natural context and allow only a few parameters to be monitored concurrently. Here, we combine Ribo‐seq with quantitative RNA‐seq to measure at nucleotide resolution and in absolute units the performance of elements controlling transcriptional and translational processes during protein synthesis. We simultaneously measure 779 translation initiation rates and 750 translation termination efficiencies across the Escherichia coli transcriptome, in addition to translational frameshifting induced at a stable RNA pseudoknot structure. By analyzing the transcriptional and translational response, we discover that sequestered ribosomes at the pseudoknot contribute to a σ32‐mediated stress response, codon‐specific pausing, and a drop in translation initiation rates across the cell. Our work demonstrates the power of integrating global approaches toward a comprehensive and quantitative understanding of gene regulation and burden in living cells.

关键词

translation;transcription;RNA;Ribo‐seq;genetic circuits

授权许可

© 2019 EMBO

图表

Overview of the workflowMajor steps involved when quantifying transcription (RNA‐seq) and translation (Ribo‐seq) and the additional cellular features measured. Elements required for quantification in absolute units are highlighted in red.Model for calculating the translation initiation rate of a ribosome binding site, see equation (2).Model for calculating translation termination efficiency of a stop codon, see equation (3). Star denotes the location of the stop codon.Model for calculating translational frameshifting efficiency between two coding regions “A” and “B” in zero and −1 reading frames, respectively, see equation (4).

Measuring translation initiation and translation termination signals across the E. coli transcriptomeGenetic design of the LacZ reporter construct whose expression is activated by the inducer IPTG.Normalized RPF count profile averaged for all E. coli transcripts. Profiles generated for cells grown in the absence and presence of IPTG (1 mM). Start and stop codons are shaded.Bar chart of all measured RBS initiation rates ranked by their strength. Strong RBSs with initiation rates > 1 ribosome/s are highlighted in red.Bar chart of all measured translation termination efficiencies at stop codons ranked by their strength. Stop codons with translation termination efficiency > 0.99 are highlighted in red.Distribution of initiation rates for cells grown in the absence and presence of IPTG (1 mM).Distribution of translation termination efficiencies for cells grown in the absence and presence of IPTG (1 mM).

Simultaneous quantification of transcription and translation of endogenous genes and a synthetic genetic constructComparison of protein synthesis rate of endogenous E. coli genes measured using Ribo‐seq from this study (in molecules/s units) and from that by Li et al (2014) (in molecules/generation units). Each point corresponds to a single gene, and color denotes the ratio of transcription initiation rate to translation initiation rate (giving RNAP/ribosome) capturing whether transcription (light yellow) or translation (dark blue) is more dominant.Transcription (bottom) and translation (top) profiles for uspA, ompA, and gapA, computed from the RNA‐seq and Ribo‐seq data without induction. Positions of the genetic parts and gene are shown below the profiles.Promoter strengths in RNAP/s units and RBS initiation rates in ribosome/s units.Transcription (bottom) and translation (top) profiles for lacZ. Profiles are shown for cells in the absence and presence of IPTG (1 mM). Position of genetic parts and gene is shown below the profiles. RBS is omitted from the genetic design due to its size.Measured promoter strength in RNAP/s units, RBS initiation rate in ribosomes/s units, and the transcriptional terminator and translation termination efficiency for lacZ. Data shown for cells in the absence and presence of IPTG (1 mM).

Characterization of a synthetic pseudoknot construct that induces translational frameshiftingGenetic design of the PK‐LacZ construct. Expanded sequence shows the PK secondary structure with the slippery site underlined, as well as the two genes (gene10 and lacZ) in differing reading frames.Translation profiles for the PK‐LacZ construct in cells cultured in the absence (bottom) and presence (top) of IPTG (1 mM). The gene10, middle, and lacZ regions are labeled above the profiles. Shaded region denotes the PK, and dashed lines denote the start codon and stop codons of gene10 and LacZ.Fractions of the total RPFs and mRNA reads in each reading frame for the gene10, PK or middle, and lacZ regions. Data shown separately for cells cultured in the absence and presence of IPTG (1 mM).Violin plots of the distributions of fractions of total RPFs and mRNA reads in each reading frame for all E. coli transcripts. Median values shown by horizontal bars. Data from two biological replicates. *P = 0.049; **P = 1.6 × 10−9 (Mann–Whitney U test).

Cellular response to the expression of a synthetic pseudoknot constructChange in expression of chromosomal genes in E. coli cells following induction of PK‐lacZ expression (1 mM IPTG). Each point represents a transcript. Differentially expressed genes (mRNA count: P < 0.001 and absolute log2 fold‐change > 1.37; translation efficiency: P < 0.01) are highlighted in color and by an alternative point shape (transcriptional regulation: purple cross; translational regulation: orange open circle).Venn diagram of genes significantly regulated transcriptionally and translationally after induction of the PK‐LacZ construct. Colors match those in panel (A).Change in codon occupancy for cells harboring the PK‐LacZ construct after induction by IPTG (1 mM) calculated from the Ribo‐seq data. Each point corresponds to a codon, which are ordered by amino acid identity and then by abundance in the genome (left most abundant, right least abundant). Dashed horizontal line denotes no change. Outliers are labeled and highlighted in red (Tukey test: 1.5 times the interquartile range below the first quartile or above the third quartile).Translation initiation rates for all E. coli RBSs in cells harboring the LacZ and PK‐LacZ constructs in the absence and presence of IPTG (1 mM). Solid line shows the same initiation rate for both conditions. Dotted lines denote linear regressions for the data with no offset.Fractions of mRNA reads and RPFs mapping to each synthetic expression construct (LacZ and PK‐LacZ) and E. coli transcripts, which are divided into three major categories: ribosomal, metabolic, and other functions. Data shown for cells cultured in the absence and presence of IPTG (1 mM).

通讯作者

1. Thomas E Gorochowski.BrisSynBio, University of Bristol, Bristol, UK;School of Biological Sciences, University of Bristol, Bristol, UK.thomas.gorochowski@bristol.ac.uk
2. Zoya Ignatova.Biochemistry and Molecular Biology, Department of Chemistry, University of Hamburg, Hamburg, Germany.thomas.gorochowski@bristol.ac.uk

推荐引用方式

Thomas E Gorochowski,Irina Chelysheva,Mette Eriksen,Priyanka Nair,Steen Pedersen,Zoya Ignatova. Absolute quantification of translational regulation and burden using combined sequencing approaches. Molecular Systems Biology ,Vol.15, Issue 5(2019)

您觉得这篇文章对您有帮助吗?
分享和收藏
0

是否收藏?

参考文献
[1] Mogk A, Huber D, Bukau B (2011) Integrating protein homeostasis strategies in prokaryotes. Cold Spring Harb Perspect Biol 3: 1–19
[2] Gorochowski TE, Van Den Berg E, Kerkman R, Roubos JA, Bovenberg RAL (2014) Using synthetic biological parts and microbioreactors to explore the protein expression characteristics of Escherichia coli. ACS Synth Biol 3: 129–139
[3] Daniel R, Rubens JR, Sarpeshkar R, Lu TK (2013) Synthetic analog computation in living cells. Nature 497: 619–623
[4] Davidsohn N, Beal J, Kiani S, Adler A, Yaman F, Li Y, Xie Z, Weiss R (2015) Accurate predictions of genetic circuit behavior from part characterization and modular composition. ACS Synth Biol 4: 673–681
[5] Gorochowski TE, Ignatova Z, Bovenberg RAL, Roubos JA (2015) Trade‐offs between tRNA abundance and mRNA secondary structure support smoothing of translation elongation rate. Nucleic Acids Res 43: 3022–3032
[6] Justman Q (2018) Splitting the world with absolute measurements: a call for collaborations in physical biology. Cell Syst 6: 395–396
[7] Smanski MJ, Zhou H, Claesen J, Shen B, Fischbach MA, Voigt CA (2016) Synthetic biology to access and expand nature's chemical diversity. Nat Rev Microbiol 14: 135–149
[8] Gorochowski TE, Avcilar‐Kucukgoze I, Bovenberg RAL, Roubos JA, Ignatova Z (2016) A minimal model of ribosome allocation dynamics captures trade‐offs in expression between endogenous and synthetic genes. ACS Synth Biol 5: 710–720
[9] Gorochowski TE, Espah Borujeni A, Park Y, Nielsen AAK, Zhang J, Der BS, Gordon DB, Voigt CA (2017) Genetic circuit characterization and debugging using RNA‐seq. Mol Syst Biol 13: 952
[10] Siuti P, Yazbek J, Lu TK (2013) Synthetic circuits integrating logic and memory in living cells. Nat Biotechnol 31: 448–452
[11] Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B (2008) Mapping and quantifying mammalian transcriptomes by RNA‐Seq. Nat Methods 5: 621–628
[12] Condron BG, Gesteland RF, Atkins JF (1991b) An analysis of sequences stimulating frameshifting in the decoding of gene 10 of bacteriophage T7. Nucleic Acids Res 19: 5607–5612
[13] Mohammad F, Woolstenhulme CJ, Green R, Buskirk AR (2016) Clarifying the translational pausing landscape in bacteria by ribosome profiling. Cell Rep 14: 686–694
[14] Cambray G, Guimaraes JC, Arkin AP (2018) Evaluation of 244,000 synthetic sequences reveals design principles to optimize translation in Escherichia coli. Nat Biotechnol 36: 1005–1015
[15] Moon TS, Lou C, Tamsir A, Stanton BC, Voigt CA (2012) Genetic programs constructed from layered logic gates in single cells. Nature 491: 249–253
[16] Canton B, Labno A, Endy D (2008) Refinement and standardization of synthetic biological parts and devices. Nat Biotechnol 26: 787–793
[17] Shendure J, Balasubramanian S, Church GM, Gilbert W, Rogers J, Schloss JA, Waterston RH (2017) DNA sequencing at 40: past, present and future. Nature 550: 345–353
[18] Brophy JAN, Voigt CA (2014) Principles of genetic circuit design. Nat Meth 11: 508–520
[19] Kennell D, Riezman H (1977) Transcription and translation initiation frequencies of the Escherichia coli lac operon. J Mol Biol 114: 1–21
[20] Lareau LF, Hite DH, Hogan GJ, Brown PO (2014) Distinct stages of the translation elongation cycle revealed by sequencing ribosome‐protected mRNA fragments. Elife 3: e01257
[21] Baens M, Noels H, Broeckx V, Hagens S, Fevery S, Billiau AD, Vankelecom H, Marynen P (2006) The dark side of EGFP: defective polyubiquitination. PLoS ONE 1: e54
[22] Freistroffer DV, Kwiatkowski M, Buckingham RH, Ehrenberg M (2000) The accuracy of codon recognition by polypeptide release factors. Proc Natl Acad Sci USA 97: 2046–2051
[23] Sharma V, Prère MF, Canal I, Firth AE, Atkins JF, Baranov PV, Fayet O (2014) Analysis of tetra‐and hepta‐nucleotides motifs promoting‐1 ribosomal frameshifting in Escherichia coli. Nucleic Acids Res 42: 7210–7225
[24] Atkins JF, Loughran G, Bhatt PR, Firth AE, Baranov PV (2016) Ribosomal frameshifting and transcriptional slippage: from genetic steganography and cryptography to adventitious use. Nucleic Acids Res 44: 7007–7078
[25] Ingolia NT, Ghaemmaghami S, Newman JRS, Weissman JS (2009) Genome‐wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324: 218–223
[26] Seo SW, Yang JS, Kim I, Yang J, Min BE, Kim S, Jung GY (2013) Predictive design of mRNA translation initiation region to control prokaryotic translation efficiency. Metab Eng 15: 67–74
[27] Arribere JA, Cenik ES, Jain N, Hess GT, Lee CH, Bassik MC, Fire AZ (2016) Translation readthrough mitigation. Nature 534: 719–723
[28] Giedroc DP, Cornish PV (2009) Frameshifting RNA pseudoknots: structure and mechanism. Virus Res 139: 193–208
[29] Goodwin S, McPherson JD, McCombie WR (2016) Coming of age: ten years of next‐generation sequencing technologies. Nat Rev Genet 17: 333–351
[30] Salis HM, Mirsky EA, Voigt CA (2009) Automated design of synthetic ribosome binding sites to control protein expression. Nat Biotechnol 27: 946–950
[31] Ceroni F, Furini S, Gorochowski TE, Boo A, Borkowski O, Ladak YN, Awan AR, Gilbert C, Stan G‐B, Ellis T (2018) Burden‐driven feedback control of gene expression. Nat Methods 15: 387–393
[32] Raser JM, O'Shea EK (2005) Noise in gene expression: origins, consequences, and control. Science 309: 2010–2014
[33] Ceroni F, Algar R, Stan GB, Ellis T (2015) Quantifying cellular capacity identifies gene expression designs with reduced burden. Nat Methods 12: 415–418
[34] Castillo‐Hair SM, Sexton JT, Landry BP, Olson EJ, Igoshin OA, Tabor JJ (2016) FlowCal: a user‐friendly, open source software tool for automatically converting flow cytometry data from arbitrary to calibrated units. ACS Synth Biol 5: 774–780
[35] Yarchuk O, Jacques N, Guillerez J, Dreyfus M (1992) Interdependence of translation, transcription and mRNA degradation in the lacZ gene. J Mol Biol 226: 581–596
[36] Woolstenhulme CJ, Guydosh NR, Green R, Buskirk AR (2015) High‐precision analysis of translational pausing by ribosome profiling in bacteria lacking EFP. Cell Rep 11: 13–21
[37] Cardinale S, Joachimiak MP, Arkin AP (2013) Effects of genetic variation on the E. coli host‐circuit interface. Cell Rep 4: 231–237
[38] Yang L, Nielsen AAK, Fernandez‐Rodriguez J, McClune CJ, Laub MT, Lu TK, Voigt CA (2014) Permanent genetic memory with >1‐byte capacity. Nat Methods 11: 1261–1266
[39] Iost I, Dreyfus M (1995) The stability of Escherichia coli lacZ mRNA depends upon the simultaneity of its synthesis and translation. EMBO J 14: 3252–3261
[40] Ivanov IP, Anderson CB, Gesteland RF, Atkins JF (2004) Identification of a new antizyme mRNA +1 frameshifting stimulatory pseudoknot in a subset of diverse invertebrates and its apparent absence in intermediate species. J Mol Biol 339: 495–504
[41] Jones DL, Brewster RC, Phillips R (2014) Promoter architecture dictates cell‐to‐cell variability in gene expression. Science 346: 1533–1536
[42] Wohlgemuth SE, Gorochowski TE, Roubos JA (2013) Translational sensitivity of the Escherichia coli genome to fluctuating tRNA availability. Nucleic Acids Res 41: 8021–8033
[43] Endy D, You L, Yin J, Molineux IJ (2000) Computation, prediction, and experimental tests of fitness for bacteriophage T7 mutants with permuted genomes. Proc Natl Acad Sci USA 97: 5375–5380
[44] Bartholomäus A, Fedyunin I, Feist P, Sin C, Zhang G, Valleriani A, Ignatova Z (2016) Bacteria differently regulate mRNA abundance to specifically respond to various stresses. Philos Trans R Soc A Math Phys Eng Sci 374: 20150069
[45] Guo MS, Gross CA (2014) Stress‐induced remodeling of the bacterial proteome. Curr Biol 24: R424–R434
[46] Espah Borujeni A, Channarasappa AS, Salis HM (2014) Translation rate is controlled by coupled trade‐offs between site accessibility, selective RNA unfolding and sliding at upstream standby sites. Nucleic Acids Res 42: 2646–2659
[47] Beal J, Haddock‐Angelli T, Gershater M, De Mora K, Lizarazo M, Hollenhorst J, Rettberg R, Demling P, Hanke R, Osthege M et al (2016) Reproducibility of fluorescent expression from engineered biological constructs in E. coli. PLoS ONE 11: e0150182
[48] Nielsen AAK, Der BS, Shin J, Vaidyanathan P, Paralanov V, Strychalski EA, Ross D, Densmore D, Voigt CA (2016) Genetic circuit design automation. Science 352: aac7341
[49] Owens NDL, Blitz IL, Lane MA, Patrushev I, Overton JD, Gilchrist MJ, Cho KWY, Khokha MK (2016) Measuring absolute RNA copy numbers at high temporal resolution reveals transcriptome kinetics in development. Cell Rep 14: 632–647
[50] Belliveau NM, Barnes SL, Ireland WT, Jones DL, Sweredoski MJ, Moradian A, Hess S, Kinney JB, Phillips R (2018) Systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria. Proc Natl Acad Sci USA 115: E4796–E4805
[51] Unoson C, Wagner EGH (2007) Dealing with stable structures at ribosome binding sites: bacterial translation and ribosome standby. RNA Biol 4: 113–117
[52] Poole ES, Brown CM, Tate WP (2000) The identity of the base following the stop codon determines the efficiency of in vivo translational termination in Escherichia coli. EMBO J 14: 151–158
[53] Condron BG, Atkins JF, Gesteland RF (1991a) Frameshifting in gene 10 of bacteriophage T7. J Bacteriol 173: 6998–7003
[54] Wang L‐Z, Wu F, Flores K, Lai Y‐C, Wang X (2016) Build to understand: synthetic approaches to biology. Integr Biol 8: 394–408
[55] Fluitt A, Pienaar E, Viljoen H (2007) Ribosome kinetics and aa‐tRNA competition determine rate and fidelity of peptide synthesis. Comput Biol Chem 31: 335–346
[56] Charneski CA, Hurst LD (2013) Positively charged residues are the major determinants of ribosomal velocity. PLoS Biol 11: e1001508
[57] Tsuchihashi Z, Kornberg A (1990) Translational frameshifting generates the gamma subunit of DNA polymerase III holoenzyme. Proc Natl Acad Sci USA 87: 2516–2520
[58] Chen H, Shiroguchi K, Ge H, Xie XS (2015) Genome‐wide study of mRNA degradation and transcript elongation in Escherichia coli. Mol Syst Biol 11: 781–781
[59] Hecht A, Glasgow J, Jaschke PR, Bawazer LA, Munson MS, Cochran JR, Endy D, Salit M (2017) Measurements of translation initiation from all 64 codons in E. coli. Nucleic Acids Res 45: 3615–3626
[60] Gyorgy A, Jiménez JI, Yazbek J, Huang HH, Chung H, Weiss R, Del Vecchio D (2015) Isocost lines describe the cellular economy of genetic circuits. Biophys J 109: 639–646
[61] Baggett NE, Zhang Y, Gross C (2017) Global analysis of translation termination in E. coli. PLoS Genet 13: e1006676
[62] Del Campo C, Bartholomäus A, Fedyunin I, Ignatova Z (2015) Secondary structure across the bacterial transcriptome reveals versatile roles in mRNA regulation and function. PLoS Genet 11: e1005613
[63] Bremer H, Dennis P, Ehrenberg M (2003) Free RNA polymerase and modeling global transcription in Escherichia coli. Biochimie 85: 597–609
[64] Mutalik VK, Guimaraes JC, Cambray G, Lam C, Christoffersen MJ, Mai QA, Tran AB, Paull M, Keasling JD, Arkin AP et al (2013) Precise and reliable gene expression via standard transcription and translation initiation elements. Nat Methods 10: 354–360
[65] De Boer HA, Comstock LJ, Vasser M (1983) The tac promoter: a functional hybrid derived from the trp and lac promoters. Proc Natl Acad Sci USA 80: 21–25
[66] Brierley I, Pennell S, Gilbert RJC (2007) Viral RNA pseudoknots: versatile motifs in gene expression and replication. Nat Rev Microbiol 5: 598–610
[67] Li GW, Burkhardt D, Gross C, Weissman JS (2014) Quantifying absolute protein synthesis rates reveals principles underlying allocation of cellular resources. Cell 157: 624–635
[68] Myers CJ, Beal J, Gorochowski TE, Kuwahara H, Madsen C, McLaughlin JA, Misirli G, Nguyen T, Oberortner E, Samineni M et al (2017) A standard‐enabled workflow for synthetic biology. Biochem Soc Trans 45: 793–803
[69] Makarova OV, Makarov EM, Sousa R, Dreyfus M (1995) Transcribing of Escherichia coli genes with mutant T7 RNA polymerases: stability of lacZ mRNA inversely correlates with polymerase speed. Proc Natl Acad Sci USA 92: 12250–12254
[70] Dong H, Nilsson L, Kurland CG (1996) Co‐variation of tRNA abundance and codon usage in Escherichia coli at different growth rates. J Mol Biol 260: 649–663
[71] Snapp E (2005) Design and use of fluorescent fusion proteins in cell biology. Curr Protoc Cell Biol Chapter 21: 21.4.1–21.4.13
[72] Tholstrup J, Oddershede LB, Sørensen MA (2012) MRNA pseudoknot structures can act as ribosomal roadblocks. Nucleic Acids Res 40: 303–313
[73] Taniguchi Y, Choi PJ, Li G‐W, Chen H, Babu M, Hearn J, Emili A, Xie XS (2010) Quantifying E. coli proteome and transcriptome with single‐molecule sensitivity in single cells. Science 329: 533–538
[74] Nath K, Koch AL (1971) Protein degradation in Escherichia coli. J Biol Chem 246: 6956–6967
[75] Der BS, Glassey E, Bartley BA, Enghuus C, Goodman DB, Gordon DB, Voigt CA, Gorochowski TE (2017) DNAplotlib: programmable visualization of genetic designs and associated data. ACS Synth Biol 6: 1115–1119
[76] Margolin W (2012) The price of tags in protein localization studies. J Bacteriol 194: 6369–6371
[77] Guisbert E, Herman C, Lu CZ, Gross CA (2004) A chaperone network controls the heat shock response in E. coli. Genes Dev 18: 2812–2821
[78] Guo H, Ingolia NT, Weissman JS, Bartel DP (2010) Mammalian microRNAs predominantly act to decrease target mRNA levels. Nature 466: 835–840
[79] Bordeau V, Felden B (2014) Curli synthesis and biofilm formation in enteric bacteria are controlled by a dynamic small RNA module made up of a pseudoknot assisted by an RNA chaperone. Nucleic Acids Res 42: 4682–4696
[80] Gorochowski TE, Ellis T (2018) Designing efficient translation. Nat Biotechnol 36: 934–935
文献评价指标
浏览 54次
下载全文 1次
评分次数 0次
用户评分 0.0分
分享 0次