Scalable acoustic virtual stirrer for enhanced interfacial enzymatic nucleic acid reactions
Data files
Feb 11, 2025 version files 59.93 MB
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DNA_sequencing_data.zip
59.93 MB
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README.md
1.45 KB
Abstract
The enzymatic nucleic acid reaction is a fundamental tool in molecular biology. However, high-throughput, high-complexity enzymatic DNA reactions and assays are still challenging, due to the difficulties in integrating and scaling up micro-scale reaction units and mixing tools. Here, we present a scalable acoustofluidic platform featuring acoustic virtual stirrer (AVS) arrays, serving as stirrers to increase the efficiency of interfacial enzymatic nucleic acid reactions. Analogous to magnetic stirrers, AVS arrays perturb the fluid through oscillating pressure nodes, controllable in terms of speeds and amplitudes via frequency shift keying (FSK) modulation. By optimizing the kinetics of surface-tethered DNA and enzymes via AVS, 7.74% improvement in the stepwise yield of enzymatic DNA synthesis is achieved. Additionally, the AVS enhanced DNA logic gate architecture can complete responses within 2 minutes, achieving average speed enhancement of 8.58 times compared to the non-AVS configuration. With its tunability, ease of integration, and efficiency, this technology holds significant potential for applications in biology and chemistry.
https://doi.org/10.5061/dryad.cc2fqz6gs
Description of the data and file structure
This dataset encompasses the DNA sequencing results presented in the paper, specifically including the DNA synthesis sequences obtained through the acoustic virtual stirrer sub-array method, as well as the DNA sequences from the control group. The sequencing data consist of two parts: the initiator primer segment (ACTAGGACGACTCGAATT) and the 4-round synthesized oligo segment (ATCG).
Files and variables
File: DNA_sequencing_data.zip
Description: With AVS groups.fq
Without AVS groups.fq
Code/software
The FASTQ file format is a widely used standard for storing high-throughput sequencing data, including both sequence information and corresponding quality scores. In the analysis of FASTQ files, various bioinformatics tools can be applied to process and interpret the data. For instance, alignment tools such as Burrows-Wheeler Aligner (BWA), Bowtie2, HISAT2, and Minimap2 are commonly used to map the synthesized sequences against reference templates. By performing alignment analysis, researchers can accurately evaluate synthesis yield and error rates, including deletions, substitutions, and insertions, which are critical metrics for assessing the performance of DNA synthesis techniques.