FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections

Alam, Khalid K.; Chang, Jonathan L.; Burke, Donald H.

doi:10.1038/mtna.2015.4

Cited by 225 publications

(268 citation statements)

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“…It was generally found that activities remained below detection levels until rounds 10-15. In pools displaying bulk polyclonal activity, examination of the most abundant sequences revealed by deep sequencing was sufficient to discover active XNAzymes; it may, however, be possible to identify sequences under enrichment through a more thorough examination of deep-sequencing data 33,34 , thereby reducing the number of rounds of selection required.…”

Section: Anticipated Resultsmentioning

confidence: 99%

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Directed evolution of artificial enzymes (XNAzymes) from diverse repertoires of synthetic genetic polymers

Taylor

Holliger

2015

Nat Protoc

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This protocol describes the directed evolution of artificial endonuclease and ligase enzymes composed of synthetic genetic polymers (XNAzymes), using 'cross-chemistry selective enrichment by exponential amplification' (X-SELEX). The protocol is analogous to (deoxy)ribozyme selections, but it enables the development of fully substituted catalysts. X-SELEX is initiated by the synthesis of diverse repertoires (here 10(14) different sequences), using xeno nucleic acid (XNA) polymerases, on DNA templates primed with DNA, RNA or XNA oligonucleotides that double as substrates, allowing selection for XNA-catalyzed cleavage or ligation. XNAzymes are reverse-transcribed into cDNA using XNA-dependent DNA polymerases, and then PCR-amplified to generate templates for subsequent rounds or deep sequencing. We describe methods developed for four XNA chemistries, arabino nucleic acids (ANAs), 2'-fluoroarabino nucleic acids (FANAs), hexitol nucleic acids (HNAs) and cyclohexene nucleic acids (CeNAs), which require ∼1 week per round, and typically 10-20 rounds; in principle, these methods are scalable and applicable to a wide range of novel XNAzyme chemistries, substrates and reactions.

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Section: Anticipated Resultsmentioning

confidence: 99%

“…3). RT reactions must be performed in order to generate cDNA complementary to the selected XNAzymes (Steps [30][31][32][33], which can then be isolated and PCR-amplified (Steps 34-45), thus allowing the generation of templates for the synthesis of XNA for subsequent rounds of selection (Step 46A; Fig. 4), or sequencing Step 46B.…”

Section: Introductionmentioning

confidence: 99%

Directed evolution of artificial enzymes (XNAzymes) from diverse repertoires of synthetic genetic polymers

Taylor

Holliger

2015

Nat Protoc

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“…Preprocessed sequences were then further analyzed using the FASTAptamer toolkit (http://burkelab.missouri.edu/fastaptamer.html) (34). FASTAptamer-Count was used to determine the number of times each sequence was sampled from the population.…”

Section: Methodsmentioning

confidence: 99%

In Vivo Analysis of Infectivity, Fusogenicity, and Incorporation of a Mutagenic Viral Glycoprotein Library Reveals Determinants for Virus Incorporation

Salamango

Alam

Burke

et al. 2016

J Virol

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Enveloped viruses utilize transmembrane surface glycoproteins to gain entry into target cells. Glycoproteins from diverse viral families can be incorporated into nonnative viral particles in a process termed pseudotyping; however, the molecular mechanisms governing acquisition of these glycoproteins are poorly understood. For murine leukemia virus envelope (MLV Env) glycoprotein, incorporation into foreign viral particles has been shown to be an active process, but it does not appear to be caused by direct interactions among viral proteins. In this study, we coupled in vivo selection systems with Illumina next-generation sequencing (NGS) to test hundreds of thousands of MLV Env mutants for the ability to be enriched in viral particles and to perform other glycoprotein functions. NGS analyses on a subset of these mutants predicted that the residues important for incorporation are in the membrane-proximal external region (MPER), particularly W127 and W137, and the residues in the membranespanning domain (MSD) and also immediately flanking it (T140 to L163). These predictions were validated by directly measuring the impact of mutations in these regions on fusogenicity, infectivity, and incorporation. We suggest that these two regions dictate pseudotyping through interactions with specific lipid environments formed during viral assembly. IMPORTANCEResearchers from numerous fields routinely exploit the ability to manipulate viral tropism by swapping viral surface proteins. However, this process, termed pseudotyping, is poorly understood at the molecular level. For murine leukemia virus envelope (MLV Env) glycoprotein, incorporation into foreign viral particles is an active process, but it does not appear to occur through direct viral protein-protein interactions. In this study, we tested hundreds of thousands of MLV Env mutants for the ability to be enriched in viral particles as well as perform other glycoprotein functions. Our analyses on a subset of these mutants predict that the glycoprotein regions embedded in and immediately flanking the viral membrane dictate active incorporation into viral particles. We suggest that pseudotyping occurs through specific lipid-protein interactions at the viral assembly site. Formation of infectious retroviral particles requires a symphony of viral and host cell proteins to coordinate in a spatial and temporal manner. Typically, this is an exclusive process wherein components from a given virus assemble only with components from the same or closely related viruses, such as HIV-1 and HIV-2 (1-5). However, this exclusivity is not typical for the incorporation of viral glycoproteins. Incorporation of foreign glycoproteins into nonnative viral particles is termed pseudotyping (6-8), and researchers from numerous fields routinely exploit this ability to manipulate viral tropism. Although very little is known about the molecular mechanisms that govern this process, it is clearly not random. For example, we have shown using scanning electron microscopy (SEM) that both vesicular...

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“…[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. Clustering starts from the first, the most enriched aptamer.…”

Section: Original Articlementioning

confidence: 99%

Untitled

Skrylnik

2017

AJP

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Aim: Implementing deep sequencing for analysis of DNA aptamer selection results requires for specialized bioinformatic software. Analysis steps include search for homologous sequences, clustering, and comparing cluster enrichment across different samples. These procedures allow deeper characterization of selected sequences by target affinity, non-specific amplification, and off-target binding, thus highlighting most promising variants or motifs. Materials and Methods: Sequencing results of systematic evolution of ligands by exponential enrichment for 40 nucleotide aptamers against extracellular CD47 protein were used as datasets for comparative clustering. Modified fast clustering script was developed based on FASTAptamer-Cluster and adapted as a galaxy tool. The algorithm was modified to terminate calculations after achieving the threshold value, and an exceeding edit distance was then assigned to non-matching pair of sequences. Results and Discussion: We have developed a set of galaxy compatible applications for rapid clustering of sequencing results and further comparative analysis of clusters. Our clustering algorithm is specifically optimized for searching for highly homologous sequences that usually form aptamer clusters and provides an average 8.4-fold increase in speed. Conclusion: Our modified clustering algorithm substantially surpasses existing alternatives in speed, thus simplifying analysis of large data sets, while its Galaxy version allows easy integration in standard workflows for preprocessing and analysis of the deep sequencing results.

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FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections

Cited by 225 publications

References 46 publications

Directed evolution of artificial enzymes (XNAzymes) from diverse repertoires of synthetic genetic polymers

Directed evolution of artificial enzymes (XNAzymes) from diverse repertoires of synthetic genetic polymers

In Vivo Analysis of Infectivity, Fusogenicity, and Incorporation of a Mutagenic Viral Glycoprotein Library Reveals Determinants for Virus Incorporation

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