Literature DB >> 30357247

Efficiency and fidelity of T3 DNA ligase in ligase-catalysed oligonucleotide polymerisations.

Yi Lei1, Joshua Washington, Ryan Hili.   

Abstract

Ligase-catalyzed oligonucleotide polymerisations (LOOPER) can readily generate libraries of diversely-modified nucleic acid polymers, which can be subjected to iterative rounds of in vitro selection to evolve functional activity. While there exist several different DNA ligases, T4 DNA ligase has most often been used for the process. Recently, T3 DNA ligase was shown to be effective in LOOPER; however, little is known about the fidelity and efficiency of this enzyme in LOOPER. In this paper we evaluate the efficiency of T3 DNA ligase and T4 DNA ligase for various codon lengths and compositions within the context of polymerisation fidelity and yield. We find that T3 DNA ligase exhibits high efficiency and fidelity with short codon lengths, but struggles with longer and more complex codon libraries, while T4 DNA ligase exhibits the opposite trend. Interestingly, T3 DNA ligase is unable to accommodate modifications at the 8-position of adenosine when integrated into short codons, which will create challenges in expanding the available codon set for the process. The limitations and strengths of the two ligases are further discussed within the context of LOOPER.

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Year:  2019        PMID: 30357247      PMCID: PMC6374181          DOI: 10.1039/c8ob01958d

Source DB:  PubMed          Journal:  Org Biomol Chem        ISSN: 1477-0520            Impact factor:   3.876


  22 in total

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Authors:  Chun Guo; Christopher P Watkins; Ryan Hili
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Authors:  Yi Lei; Dehui Kong; Ryan Hili
Journal:  ACS Comb Sci       Date:  2015-11-12       Impact factor: 3.784

7.  Multivalent glycocluster design through directed evolution.

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Journal:  Angew Chem Int Ed Engl       Date:  2011-11-18       Impact factor: 15.336

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Authors:  Stella Diafa; Marcel Hollenstein
Journal:  Molecules       Date:  2015-09-14       Impact factor: 4.411

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  2 in total

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Journal:  Nat Chem Biol       Date:  2019-02-11       Impact factor: 15.040

2.  Generating experimentally unrelated target molecule-binding highly functionalized nucleic-acid polymers using machine learning.

Authors:  Jonathan C Chen; Jonathan P Chen; Max W Shen; Michael Wornow; Minwoo Bae; Wei-Hsi Yeh; Alvin Hsu; David R Liu
Journal:  Nat Commun       Date:  2022-08-04       Impact factor: 17.694

  2 in total

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