Biology subjects

Gimpel, A. L.

Publications and source records attributed to Gimpel, A. L..

5 recordsLinked to original sources

bioRxiv2025

Comparison of state-of-the-art error-correction coding for sequence-based DNA data storage

A wide range of codecs with vastly different error-correction approaches have been proposed and implemented for DNA data storage to date. However, while many codecs claim to provide superior performance, no studies have systematically benchmarked codec implementations to establish the current state-of-the-art in DNA data storage. In this study, we use standardized error scenarios - both in silico and in vitro - to compare the performance of six representative codecs from the literature. We find synthetic benchmarks commonly used in literature to be unsuitable indicators of codec performance, as our data shows that common experimental benchmarks fail to differentiate codecs under standardized conditions. Instead, we implement a comprehensive benchmark covering the major experimental parameters to assess codec performance under realistic DNA data storage conditions, while establishing important baselines for future codec development. Verifying our results with fair and standardized experiments, we demonstrate data storage at 43 EB g-1 using synthesis by material deposition and 13 EB g-1 using the more error prone electrochemical synthesis, employing only existing codecs from the literature. Besides closing in on the physical limits of DNA data storage, this study thus showcases the maturity of error-correction coding and defines its current state-of-the-art.

bioinformatics↗

bioRxiv2024

Deep learning uncovers sequence-specific amplification bias in multi-template PCR

Multi-template polymerase chain reaction is a key step in many amplicon sequencing protocols enabling parallel amplification of diverse DNA molecules sharing common adapters in applications, ranging as wide as quantitative molecular biology and DNA data storage. However, this process results in a skewed amplicon abundance, due to sequence-specific amplification biases. In this study, one-dimensional convolutional neural networks (1D-CNNs) were trained on synthetic DNA pools to learn the PCR amplification efficiency of individual templates. These 1D-CNN models can predict poorly amplifying templates based solely on sequence information, achieving an AUROC/AUPRC of up to 0.88/0.44 with very imbalanced prevalence of 2%, thereby greatly outperforming baseline models relying only on GC content and nucleotide frequency as predictors. A new, general-purpose framework for interpreting deep learning models, termed CluMo provides mechanistic insights into the amplification biases. Most strikingly, specific amplification reactions were identified as suffering from adaptor-template self-priming a mechanism previously disregarded in PCR.

molecular biology↗

bioRxiv2024

Challenges for error-correction coding in DNA data storage: photolithographic synthesis and DNA decay

Efficient error-correction codes are crucial for realizing DNAs potential as a long-lasting, high-density storage medium for digital data. At the same time, new workflows promising low-cost, resilient DNA data storage are challenging their design and error-correcting capabilities. This study characterizes the errors and biases in two new additions to the state-of-the-art workflow in DNA data storage: photolithographic synthesis and DNA decay. Photolithographic synthesis offers low-cost, scalable oligonucleotide synthesis but suffers from high error rates, necessitating sophisticated error-correction schemes, for example codes introducing within-sequence redundancy combined with clustering and alignment techniques for retrieval. On the other hand, the decoding of oligo fragments after DNA decay promises unprecedented storage densities, but complicates data recovery by requiring the reassembly of full-length sequences or the use of partial sequences for decoding. Our analysis provides a detailed account of the error patterns and biases present in photolithographic synthesis and DNA decay, and identifies considerable bias stemming from sequencing workflows. We implement our findings into a digital twin of the two workflows, offering a tool for developing error-correction codes and providing benchmarks for the evaluation of codec performance.

biochemistry↗

bioRxiv2023

A digital twin for DNA data storage based on comprehensive quantification of errors and biases

Archiving data in synthetic DNA offers unprecedented storage density and longevity. Handling and storage introduce errors and biases into DNA-based storage systems, necessitating the use of Error Correction Coding (ECC) which comes at the cost of added redundancy. However, insufficient data on these errors and biases, as well as a lack of modelling tools, limit data-driven ECC development and experimental design. In this study, we present a comprehensive characterisation of the error sources and biases present in the most common DNA data storage workflows, including commercial DNA synthesis, PCR, decay by accelerated aging, and sequencing-by-synthesis. Using the data from 40 sequencing experiments, we build a digital twin of the DNA data storage process, capable of simulating state-of-the-art workflows and reproducing their experimental results. We showcase the digital twins ability to replace experiments and rationalize the design of redundancy in two case studies, highlighting opportunities for tangible cost savings and data-driven ECC development.

synthetic biology↗

bioRxiv2022

Information Decay and Enzymatic Information Recovery for DNA Data Storage

Synthetic DNA has been proposed as a storage medium for digital information due to its high theoretical storage density and anticipated long storage horizons. However, under all ambient storage conditions, DNA undergoes a slow chemical decay process resulting in nicked (broken) DNA strands, and the information stored in these strands is no longer readable. In this work we design an enzymatic repair procedure, which is applicable to the DNA pool prior to readout and can partially reverse the damage. Through a chemical understanding of the decay process, an overhang at the 3 end of the damaged site is identified as obstructive to repair via the base excision-repair (BER) mechanism. The obstruction can be removed via the enzyme apurinic/apyrimidinic endonuclease I (APE1), thereby enabling repair of hydrolytically damaged DNA via Bst polymerase and Taq ligase. Simulations of damage and repair reveal the benefit of the enzymatic repair step for DNA data storage, especially when data is stored in DNA at high storage densities (= low physical redundancy) and for long time durations.

synthetic biology↗