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      Measurements of translation initiation from all 64 codons in E. coli

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          Abstract

          Our understanding of translation underpins our capacity to engineer living systems. The canonical start codon (AUG) and a few near-cognates (GUG, UUG) are considered as the ‘start codons’ for translation initiation in Escherichia coli. Translation is typically not thought to initiate from the 61 remaining codons. Here, we quantified translation initiation of green fluorescent protein and nanoluciferase in E. coli from all 64 triplet codons and across a range of DNA copy number. We detected initiation of protein synthesis above measurement background for 47 codons. Translation from non-canonical start codons ranged from 0.007 to 3% relative to translation from AUG. Translation from 17 non-AUG codons exceeded the highest reported rates of non-cognate codon recognition. Translation initiation from non-canonical start codons may contribute to the synthesis of peptides in both natural and synthetic biological systems.

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          Enzymatic assembly of DNA molecules up to several hundred kilobases.

          Daniel Gibson, Lei Young, Ray-Yuan Chuang … (2009)
          We describe an isothermal, single-reaction method for assembling multiple overlapping DNA molecules by the concerted action of a 5' exonuclease, a DNA polymerase and a DNA ligase. First we recessed DNA fragments, yielding single-stranded DNA overhangs that specifically annealed, and then covalently joined them. This assembly method can be used to seamlessly construct synthetic and natural genes, genetic pathways and entire genomes, and could be a useful molecular engineering tool.
          Article 0 comments Cited 1867 times – based on 0 reviews     Review now
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            Simultaneous inference in general parametric models.

            Torsten Hothorn, Frank Bretz, Peter Westfall (2008)
            Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre-specified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R add-on package multcomp, which provides a convenient interface to the general approach adopted here. Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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              Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling.

              Nicholas Ingolia, Sina Ghaemmaghami, John R S Newman … (2009)
              Techniques for systematically monitoring protein translation have lagged far behind methods for measuring messenger RNA (mRNA) levels. Here, we present a ribosome-profiling strategy that is based on the deep sequencing of ribosome-protected mRNA fragments and enables genome-wide investigation of translation with subcodon resolution. We used this technique to monitor translation in budding yeast under both rich and starvation conditions. These studies defined the protein sequences being translated and found extensive translational control in both determining absolute protein abundance and responding to environmental stress. We also observed distinct phases during translation that involve a large decrease in ribosome density going from early to late peptide elongation as well as widespread regulated initiation at non-adenine-uracil-guanine (AUG) codons. Ribosome profiling is readily adaptable to other organisms, making high-precision investigation of protein translation experimentally accessible.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date (Print): 20 April 2017
                Publication date (Electronic): 21 February 2017
                Publication date PMC-release: 21 February 2017
                Volume: 45
                Issue: 7
                Pages: 3615-3626
                Affiliations
                [1 ]Joint Initiative for Metrology in Biology, Stanford, CA 94305, USA
                [2 ]Genome-scale Measurements Group, National Institute of Standards and Technology, Stanford, CA 94305, USA
                [3 ]Department of Bioengineering, Stanford, CA 94305, USA
                [4 ]Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW 2109, Australia
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +1 202 370 7745; Email: salit@ 123456nist.gov . Correspondence may also be addressed to Drew Endy. Email: endy@ 123456stanford.edu
                [† ]These authors contributed equally to the paper as first authors.
                Author information
                http://orcid.org/0000-0003-2359-1301
                Article
                Publisher ID: gkx070
                DOI: 10.1093/nar/gkx070
                PMC ID: 5397182
                PubMed ID: 28334756
                SO-VID: 3ee07afc-f59a-467c-8681-481f1015286f
                Copyright © Published by Oxford University Press on behalf of Nucleic Acids Research 2017.
                License:

                This work is written by (a) US Government employee(s) and is in the public domain in the US.

                History
                Date accepted : 25 January 2017
                Date revision received : 20 January 2017
                Date received : 15 July 2016
                Page count
                Pages: 12
                Categories
                Subject: NAR Breakthrough Article

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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