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Nucleic Acids Research Advance Access published online on November 23, 2008
Nucleic Acids Research, doi:10.1093/nar/gkn899
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Methods Online

Array-based evolution of DNA aptamers allows modelling of an explicit sequence-fitness landscape

Christopher G. Knight1,2,3,*, Mark Platt1,2, William Rowe1,2, David C. Wedge1,2, Farid Khan1,2, Philip J. R. Day1,4, Andy McShea5, Joshua Knowles1,6 and Douglas B. Kell1,2

1Manchester Interdisciplinary Biocentre, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK, 2School of Chemistry, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK, 3Faculty of Life Sciences, The University of Manchester, Simon Building, Brunswick Street, Manchester M13 9PL, UK, 4School of Medicine, The University of Manchester, Oxford Road, Manchester M13 9PT, UK, 5Combimatrix Corporation, 6500 Harbor Heights Parkway, Suite #303, Mukilteo, WA 98275, USA and 6School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, M13 9PL, UK

*To whom correspondence should be addressed. Tel: +44 161 2755378; Email: chris.knight{at}manchester.ac.uk

Correspondence may also be addressed to Douglas B. Kell. Tel: +44 161 306 4492; Fax: +44 161 306 4556; Email: dbk{at}manchester.ac.uk

Received September 20, 2008. Revised October 20, 2008. Accepted October 23, 2008.

Mapping the landscape of possible macromolecular polymer sequences to their fitness in performing biological functions is a challenge across the biosciences. A paradigm is the case of aptamers, nucleic acids that can be selected to bind particular target molecules. We have characterized the sequence-fitness landscape for aptamers binding allophycocyanin (APC) protein via a novel Closed Loop Aptameric Directed Evolution (CLADE) approach. In contrast to the conventional SELEX methodology, selection and mutation of aptamer sequences was carried out in silico, with explicit fitness assays for 44 131 aptamers of known sequence using DNA microarrays in vitro. We capture the landscape using a predictive machine learning model linking sequence features and function and validate this model using 5500 entirely separate test sequences, which give a very high observed versus predicted correlation of 0.87. This approach reveals a complex sequence-fitness mapping, and hypotheses for the physical basis of aptameric binding; it also enables rapid design of novel aptamers with desired binding properties. We demonstrate an extension to the approach by incorporating prior knowledge into CLADE, resulting in some of the tightest binding sequences.

Present address: Andy McShea, Theo Chocolate, 3400 Phinney Ave. N., Seattle, WA 98103, USA

The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint First Authors.


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