Using a PCR-Based Method To Analyze and Model Large, Heterogeneous Populations of DNA

被引:6
作者
Andrade, Helena [1 ]
Thomas, Alvin K. [1 ]
Lin, Weilin [1 ]
Reddavide, Francesco V. [2 ]
Zhang, Yixin [1 ]
机构
[1] Tech Univ Dresden, B CUBE Ctr Mol Bioengn, Tatzberg 41, D-01307 Dresden, Germany
[2] DyNAbind GmbH, Arnoldstr 18D, D-01307 Dresden, Germany
关键词
DNA; DNA-encoded chemical libraries; fluorescence; polymerase chain reaction; population modeling; BINDING-MOLECULES; IDENTIFICATION; MICA;
D O I
10.1002/cbic.201900603
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The study of populations of large size and high diversity is limited by the capability of collecting data. Moreover, for a pool of individuals, each associated with a unique characteristic feature, as the pool size grows, the possible interactions increase exponentially and quickly go beyond the limit of computation and experimental studies. Herein, the design of DNA libraries with various diversity is reported. By using a facile analytical method based on real-time PCR, the diversity of a pool of DNA can be evaluated to allow extraordinarily high heterogenicity (e.g., >1 trillion). It is demonstrated that these DNA libraries can be used to model heterogeneous populations; these libraries exhibit functions such as self-protection, suitability for biased expansion, and the possibility to evolve into amorphous structures. The method has shown the remarkable power of parallel computing with DNA, since it can resemble an analogue computer and be applied in selection-based biotechnology methods, such as DNA-encoded chemical libraries. As a chemical approach to solve problems traditionally for genetic and statistical analysis, the method provides a quick and cost-efficient evaluation of library diversity for intermediate steps through a selection process.
引用
收藏
页码:1144 / 1149
页数:6
相关论文
共 23 条
[1]   Observation of single-stranded DNA on mica and highly oriented pyrolytic graphite by atomic force microscopy [J].
Adamcik, Jozef ;
Klinov, Dmitry V. ;
Witz, Guillaume ;
Sekatskii, Sergey K. ;
Dietler, Giovanni .
FEBS LETTERS, 2006, 580 (24) :5671-5675
[2]   Species distribution models and ecological theory: A critical assessment and some possible new approaches [J].
Austin, Mike .
ECOLOGICAL MODELLING, 2007, 200 (1-2) :1-19
[3]   ENCODED COMBINATORIAL CHEMISTRY [J].
BRENNER, S ;
LERNER, RA .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1992, 89 (12) :5381-5383
[4]   High-throughput sequencing for the identification of binding molecules from DNA-encoded chemical libraries [J].
Buller, Fabian ;
Steiner, Martina ;
Scheuermann, Joerg ;
Mannocci, Luca ;
Nissen, Ina ;
Kohler, Manuel ;
Beisel, Christian ;
Neri, Dario .
BIOORGANIC & MEDICINAL CHEMISTRY LETTERS, 2010, 20 (14) :4188-4192
[5]   THEORY AND MODELS IN ECOLOGY - A DIFFERENT PERSPECTIVE [J].
CASWELL, H .
ECOLOGICAL MODELLING, 1988, 43 (1-2) :33-44
[6]   Mathematical model of real-time PCR kinetics [J].
Gevertz, JL ;
Dunn, SM ;
Roth, CM .
BIOTECHNOLOGY AND BIOENGINEERING, 2005, 92 (03) :346-355
[7]   DNA-encoded chemistry: enabling the deeper sampling of chemical space [J].
Goodnow, Robert A., Jr. ;
Dumelin, Christoph E. ;
Keefe, Anthony D. .
NATURE REVIEWS DRUG DISCOVERY, 2017, 16 (02) :131-147
[8]   Coming of age: ten years of next-generation sequencing technologies [J].
Goodwin, Sara ;
McPherson, John D. ;
McCombie, W. Richard .
NATURE REVIEWS GENETICS, 2016, 17 (06) :333-351
[9]  
Keer JT, 2008, ESSENTIALS OF NUCLEIC ACID ANALYSIS: A ROBUST APPROACH, P132
[10]   Advancements in Next-Generation Sequencing [J].
Levy, Shawn E. ;
Myers, Richard M. .
ANNUAL REVIEW OF GENOMICS AND HUMAN GENETICS, VOL 17, 2016, 17 :95-115