TY - JOUR
T1 - Controlling uncertainty in aptamer selection
AU - Spill, Fabian
AU - Weinstein, Zohar B
AU - Irani Shemirani, Atena
AU - Ho, Nga
AU - Desai, Darash
AU - Zaman, Muhammad H
PY - 2016/10/25
Y1 - 2016/10/25
N2 - The search for high-affinity aptamers for targets such as proteins, small molecules, or cancer cells remains a formidable endeavor. Systematic Evolution of Ligands by EXponential Enrichment (SELEX) offers an iterative process to discover these aptamers through evolutionary selection of high-affinity candidates from a highly diverse random pool. This randomness dictates an unknown population distribution of fitness parameters, encoded by the binding affinities, toward SELEX targets. Adding to this uncertainty, repeating SELEX under identical conditions may lead to variable outcomes. These uncertainties pose a challenge when tuning selection pressures to isolate high-affinity ligands. Here, we present a stochastic hybrid model that describes the evolutionary selection of aptamers to explore the impact of these unknowns. To our surprise, we find that even single copies of high-affinity ligands in a pool of billions can strongly influence population dynamics, yet their survival is highly dependent on chance. We perform Monte Carlo simulations to explore the impact of environmental parameters, such as the target concentration, on selection efficiency in SELEX and identify strategies to control these uncertainties to ultimately improve the outcome and speed of this time- and resource-intensive process.
AB - The search for high-affinity aptamers for targets such as proteins, small molecules, or cancer cells remains a formidable endeavor. Systematic Evolution of Ligands by EXponential Enrichment (SELEX) offers an iterative process to discover these aptamers through evolutionary selection of high-affinity candidates from a highly diverse random pool. This randomness dictates an unknown population distribution of fitness parameters, encoded by the binding affinities, toward SELEX targets. Adding to this uncertainty, repeating SELEX under identical conditions may lead to variable outcomes. These uncertainties pose a challenge when tuning selection pressures to isolate high-affinity ligands. Here, we present a stochastic hybrid model that describes the evolutionary selection of aptamers to explore the impact of these unknowns. To our surprise, we find that even single copies of high-affinity ligands in a pool of billions can strongly influence population dynamics, yet their survival is highly dependent on chance. We perform Monte Carlo simulations to explore the impact of environmental parameters, such as the target concentration, on selection efficiency in SELEX and identify strategies to control these uncertainties to ultimately improve the outcome and speed of this time- and resource-intensive process.
KW - Oligonucleotides
KW - Stochastic model
KW - Hybrid model
KW - Evolution
KW - in vitro selection
UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087011/
UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087011/pdf/pnas.201605086.pdf
U2 - 10.1073/pnas.1605086113
DO - 10.1073/pnas.1605086113
M3 - Article
C2 - 27790993
SN - 1091-6490
VL - 113
SP - 12076
EP - 12081
JO - National Academy of Sciences. Proceedings
JF - National Academy of Sciences. Proceedings
IS - 43
ER -