AptaCluster – A Method to Cluster HT-SELEX Aptamer Pools and Lessons from Its Application

Abstract

Systematic Evolution of Ligands by EXponential Enrichment (SELEX) is a well established experimental procedure to identify aptamers - synthetic single-stranded (ribo)nucleic molecules that bind to a given molecular target. Recently, new sequencing technologies have revolutionized the SELEX protocol by allowing for deep sequencing of the selection pools after each cycle. The emergence of High Throughput SELEX (HT-SELEX) has opened the field to new computational opportunities and challenges that are yet to be addressed. To aid the analysis of the results of HT-SELEX and to advance the understanding of the selection process itself, we developed AptaCluster. This algorithm allows for an efficient clustering of whole HT-SELEX aptamer pools; a task that could not be accomplished with traditional clustering algorithms due to the enormous size of such datasets. We performed HT-SELEX with Interleukin 10 receptor alpha chain (IL-10RA) as the target molecule and used AptaCluster to analyze the resulting sequences. AptaCluster allowed for the first survey of the relationships between sequences in different selection rounds and revealed previously not appreciated properties of the SELEX protocol. As the first tool of this kind, AptaCluster enables novel ways to analyze and to optimize the HT-SELEX procedure. Our AptaCluster algorithm is available as a very fast multiprocessor implementation upon request.

Analyzing HT-SELEX data with the Galaxy Project tools – A web based bioinformatics platform for biomedical research

“…These tools include motif searches [7, 14, 15], aptamer clustering [5, 10, 13] and other methods of in-depth analysis [9]. …”

“…This first pass filtering can be accomplished by a variety of methods: 1) calculating fold enrichment of an aptamer sequence between selection rounds [5, 10-12]; 2) comparing the round representation of each sequence to a non-selected round (e.g., round 0) [5]; 3) comparing the number of identical reads of a sequence (read count) to a non-selected round (e.g., round 0) [5]; and 4) isolating aptamer sequences with shared homology [13]. Frequently, a subsequent second pass in-depth analysis is performed to identify sequence families [5, 7, 12, 13], structure families [5], motifs[14, 15] and potential beneficial mutations [16]. Several bioinformatics tools have been generated to analyze aptamer HTS data [9, 10, 13, 16].…”

“…Frequently, a subsequent second pass in-depth analysis is performed to identify sequence families [5, 7, 12, 13], structure families [5], motifs[14, 15] and potential beneficial mutations [16]. Several bioinformatics tools have been generated to analyze aptamer HTS data [9, 10, 13, 16]. Unfortunately, many of these tools are either not easily accessible, have extensive requirements prior to use or require significant computational/coding expertise.…”

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“…[6] The most commonly used algorithm of sequence clustering is calculation of Levenshtein edit distance; in case, if its value is lower than the threshold, the compared sequences are clustered. [7] Aptamer clustering usually implements low thresholds, ranging from 1 to 5, which corresponds to the number of permissible substitutions, deletions, or insertions that constitute the difference between the aptamers. Clustering during the HT-SELEX analysis with the help of the FASTAptamer set of scripts [8] proceeds as following: First, the number of individual readings for each aptamer is determined, then the normalized value (reads per million [RPM]) is calculated from this number and from the total number of readings, and the aptamers are ranked by their RPM in descending order.…”

A Trojan Horse for Human Immunodeficiency Virus

“…To this end, living whole cells expressing the antigen of interest are used as a complex target instead of purified proteins or synthetic peptides. To overcome the major hurdle faced when using cell SELEX, i.e., the more laborious identification of aptamer targets, the HTS is combined with a robust data analysis, allowing a more rapid identification of the most promising candidate aptamer sequences for the target of interest (Hoinka et al, 2014). Zhou et al (2015) performed nine rounds of cell SELEX on living CCR5-expressing cells (U373-Magi-CCR5E), and the last five rounds were analyzed by HTS.…”