Cryptographic approaches to authenticating synthetic DNA sequences

De novo non-canonical nanopore basecalling enables private communication using heavily-modified DNA data at single-molecule level

Hidden messages in DNA molecules by employing chemical modifications has been suggested for private data storage and transmission at high information density. However, rapidly decoding these "molecular keys" with corresponding basecallers remains challenging. We present DeepSME, a nanopore sequencing and deep-learning based framework towards single-molecule encryption, demonstrated by using 5-hydroxymethylcytosine (5hmC) substitution for individual nucleotide recognition rather than sequential interactions. This non-natural, motif-insensitive methylation disrupts ion current, resulting in a readout failure of 67.2%-100%, concealing the privacy within the DNAs. We further develop an alignment-free DeepSME basecaller as a key to reconstitute the digital information. Our three-stage training pipeline, expands k-mer size from 46 to 49, achieving over 92% precision and recall from scratch. DeepSME deciphers fully 5hmC concealed text and image within 16× coverage depth with an F1-score of 86.4%, surpassing all the state-of-the-art basecallers. Demonstrated on edge computing devices, DeepSME holds supreme potential for DNA-based private communications and broader bioengineering and medical applications.

Engineering biology applications for environmental solutions: potential and challenges

Engineering biology applies synthetic biology to address global environmental challenges like bioremediation, biosequestration, pollutant monitoring, and resource recovery. This perspective outlines innovations in engineering biology, its integration with other technologies (e.g., nanotechnology, IoT, AI), and commercial ventures leveraging these advancements. We also discuss commercialisation and scaling challenges, biosafety and biosecurity considerations including biocontainment strategies, social and political dimensions, and governance issues that must be addressed for successful real-world implementation. Finally, we highlight future perspectives and propose strategies to overcome existing hurdles, aiming to accelerate the adoption of engineering biology for environmental solutions.

Self-documenting plasmids

Plasmids are the workhorse of biotechnology. These small DNA molecules are used to produce recombinant proteins and to engineer living organisms. They can be regarded as the blueprints of many biotechnology products. Therefore, it is critical to ensure that the sequences of these DNA molecules match their intended designs. Yet, plasmid verification remains challenging. To secure the exchange of plasmids in research and development workflows, we have developed self-documenting plasmids that encode information about themselves in their own DNA molecules. Users of self-documenting plasmids can retrieve critical information about the plasmid without prior knowledge of the plasmid identity. The insertion of documentation in the plasmid sequence does not preclude their propagation in bacteria or functional fluorescent protein expression in mammalian cells. This technology simplifies plasmid verification, hardens supply chains, and has the potential to transform the protection of intellectual property (IP) in the life sciences.

Self-Documenting Plasmids

Plasmids are the workhorse of biotechnology. These small DNA molecules are used to produce recombinant proteins and to engineer living organisms. They can be regarded as the blueprints of many biotechnology products. It is, therefore, critical to ensure that the sequences of these DNA molecules match their intended designs. Yet, plasmid verification remains challenging. To secure the exchange of plasmids in research and development workflows, we have developed self-documenting plasmids that encode information about themselves in their own DNA molecules. Users of self-documenting plasmids can retrieve critical information about the plasmid without prior knowledge of the plasmid identity. The insertion of documentation in the plasmid sequence does not adversely affect their propagation in bacteria and does not compromise protein expression in mammalian cells. This technology simplifies plasmid verification, hardens supply chains, and has the potential to transform the protection of intellectual property in the life sciences.

Sequencing Strategy to Ensure Accurate Plasmid Assembly

Despite the wide use of plasmids in research and clinical production, the need to verify plasmid sequences is a bottleneck that is too often underestimated in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most accurate, consistent assembly generation and identified mutations relative to the reference sequence. Although Sanger sequencing can be used to verify specific regions, some GC-rich and repetitive regions were difficult to resolve using any method, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs.

Cyber-biological convergence: a systematic review and future outlook

The introduction of the capability to "program" a biological system is referred to as Engineered biology and can be compared to the introduction of the internet and the capability of programming a computer. Engineered biology is supported by a digital infrastructure that includes data, data storage, computer-dependent laboratory equipment, internet-connected communication networks, and supply chains. This connectivity is important. It can improve workflows and enhance productivity. At the same time and unlike computer programs, biological systems introduce unique threats as they can self-assemble, self-repair, and self-replicate. The aim of this paper is to systematically review the cyber implications of engineered biology. This includes cyber-bio opportunities and threats as engineered biology continues to integrate into cyberspace. We used a systematic search methodology to review the academic literature, and supplemented this with a review of opensource materials and "grey" literature that is not disseminated by academic publishers. A comprehensive search of articles published in or after 2017 until the 21st of October 2022 found 52 studies that focus on implications of engineered biology to cyberspace. The search was conducted using search engines that index over 60 databases-databases that specifically cover the information security, and biology literatures, as well as the wider set of academic disciplines. Across these 52 articles, we identified a total of 7 cyber opportunities including automated bio-foundries and 4 cyber threats such as Artificial Intelligence misuse and biological dataset targeting. We highlight the 4 main types of cyberbiosecurity solutions identified in the literature and we suggest a total of 9 policy recommendations that can be utilized by various entities, including governments, to ensure that cyberbiosecurity remains frontline in a growing bioeconomy.

Synsor: a tool for alignment-free detection of engineered DNA sequences

DNA sequences of nearly any desired composition, length, and function can be synthesized to alter the biology of an organism for purposes ranging from the bioproduction of therapeutic compounds to invasive pest control. Yet despite offering many great benefits, engineered DNA poses a risk due to their possible misuse or abuse by malicious actors, or their unintentional introduction into the environment. Monitoring the presence of engineered DNA in biological or environmental systems is therefore crucial for routine and timely detection of emerging biological threats, and for improving public acceptance of genetic technologies. To address this, we developed Synsor, a tool for identifying engineered DNA sequences in high-throughput sequencing data. Synsor leverages the k-mer signature differences between naturally occurring and engineered DNA sequences and uses an artificial neural network to classify whether a DNA sequence is natural or engineered. By querying suspected sequences against the model, Synsor can identify sequences that are likely to have been engineered. Using natural plasmid and engineered vector sequences, we showed that Synsor identifies engineered DNA with >99% accuracy. We demonstrate how Synsor can be used to detect potential genetically engineered organisms and locate where engineered DNA is being introduced into the environment by analysing genomic and metagenomic data from yeast and wastewater samples, respectively. Synsor is therefore a powerful tool that will streamline the process of identifying engineered DNA in poorly characterized biological or environmental systems, thereby allowing for enhanced monitoring of emerging biological threats.

Sequencing Strategy to Ensure Accurate Plasmid Assembly

Despite the wide use of plasmids in research and clinical production, the need to verify plasmid sequences is a bottleneck that is too often underestimated in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most accurate, consistent assembly generation and identified mutations relative to the reference sequence. Although Sanger sequencing can be used to verify specific regions, some GC-rich and repetitive regions were difficult to resolve using any method, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs.