Biology subjects

Bartling, C.

Publications and source records attributed to Bartling, C..

6 recordsLinked to original sources

bioRxiv2026

Developing a Standard Definition for Sequences of Concern

Readily available nucleic acid synthesis is both critical for the bioeconomy and an increasingly pressing security concern due to the potential for accidental or deliberate misuse. While biosecurity experts broadly agree that nucleic acid providers should screen orders for potential "sequences of concern," there has previously been no agreed standard for how to define and recognize such sequences. To address this gap, we first organized a test set of 1.1 million sequences from pathogens and toxins on the Australia Group Common Control Lists and their non-controlled relatives, along with model organisms and synthetic constructs. An initial categorization of sequences as to whether or not they were sequence of concern was produced by comparing the results of four biosecurity screening systems for each of these sequences, finding that these systems already agreed on the categorization of more than 80% of sequences. We then refined these results through a science-based stakeholder review process to define a rubric for determining whether a sequence should be flagged as a potential sequence of concern, then applied this rubric to improve the categorization of test sets. The result is a rubric that identifies sequences of concern with respect to human pandemic-potential viruses, key classes of low-risk genes, and controlled toxins. Applying this rubric to the test set collection has reduced the number of test sequences with disputed categorization by 44.3% for controlled viruses and 10.7% across the test set as a whole. Together, these results provide a concrete "sequence of concern" definition that can be used as a foundation for development of biosecurity screening standards and policy.

bioinformatics↗

bioRxiv2026

The Limits of Sequence-Based Biosecurity Screening Tools in the Age of AI-Assisted Protein Design

Rapid advancements in AI have enabled significant progress in protein and nucleic acid design, but they also pose biosecurity challenges. We examine the vulnerabilities of biosecurity screening software (BSS) to AI-reformulated synthetic homologs of proteins of concern (POCs) that have been fragmented into smaller segments. We evaluate four BSS tools that were recently patched to enhance their AI resiliency. Without any further modification, we found that two of the four tools were capable of robustly detecting fragments as short as 50 nucleotides, demonstrating screening capabilities that exceed those requested in the U.S. Framework for Nucleic Acid Synthesis. Upgraded versions of the other two tools improved performance. Although our findings confirm the effectiveness of the tested BSS tools, at the same time, they emphasize the urgency of developing alternate BSS approaches to counter evolving AI-enabled biosecurity risks.

synthetic biology↗

bioRxiv2025

Inter-tool analysis of a NIST dataset for assessing baseline nucleic acid sequence screening

Nucleic acid synthesis is a dual-use technology that can benefit fields such as biology, medicine, and information storage. However, synthetic nucleic acids could also potentially be used negligently and ultimately cause harm, or be used with malicious intent to cause harm. Thus, this technology needs to be appropriately safeguarded. Sequence screening is one component of a biosecurity protocol for preventing such harm and consists of differentiating Sequences of Concern (SOCs) from benign sequences that are not associated with pathogenicity or toxicity. There exist many fit-for-purpose tools that have been developed for DNA synthesis sequence screening. However, questions remain regarding their performance with respect to consistency of screening. To aid in determining if screening tools are harmonized in regard to baseline sequence screening, NIST constructed a test dataset based on current screening recommendations. NIST then sent blinded datasets to sequence screening tool developers for testing. Overall, there was a general agreement between the tools and NIST assignments of the sequences and all tools had a baseline performance of greater than 95% sensitivity and 97% accuracy. Disagreement on specific sequences largely arose from single tools and could be traced to differences in defining a SOC and/or methodological differences in screening algorithms.

bioinformatics↗

bioRxiv2024

Toward AI-Resilient Screening of Nucleic Acid Synthesis Orders: Process, Results, and Recommendations

Fast-moving advances in AI-assisted protein engineering are enabling breakthroughs in the life sciences that promise numerous beneficial applications. At the same time, these new capabilities are creating potential biosecurity challenges by providing new pathways to intentional or accidental synthesis of genes that encode hazardous proteins. The synthesis of nucleic acids is a key choke point in the AI-assisted protein engineering pipeline as it is where digital designs are transformed into physical instructions that can produce potentially harmful proteins. Thus, one focus for efforts to enhance biosecurity in the face of new AI-enabled capabilities is on bolstering the screening of orders by nucleic acid synthesis providers. We describe a multistakeholder, cross-sector effort to address biosecurity challenges with uses of AI-powered biological design tools to reformulate naturally occurring proteins of concern to create synthetic homologs that have low sequence identity to the wild-type proteins. We evaluated the abilities of traditional nucleic acid biosecurity screening tools to detect these synthetic homologs and found that, of tools tested, not all could previously detect such AI-redesigned sequences reliably. However, as we report, patches were built and deployed to improve detection rates over the course of the project, resulting in a final mean detection rate over tools of 97% of the synthetic homologs that were determined, using in-silico metrics, to be more likely to retain wild-type-like function. Finally, we make recommendations on approaches for studying and addressing the rising risk of adversarial AI-assisted protein engineering attacks like the one we identified and worked to mitigate.

synthetic biology↗

bioRxiv2022

UltraSEQ: a universal bioinformatic platform for information-based clinical metagenomics and beyond

Applied metagenomics is a powerful emerging capability enabling untargeted detection of pathogens, and its application in clinical diagnostics promises to alleviate the limitations of current targeted assays. While metagenomics offers a hypothesis-free approach to identify any pathogen, including unculturable and potentially novel pathogens, its application in clinical diagnostics has so far been limited by workflow-specific requirements, computational constraints, and lengthy expert review requirements. To address these challenges, we developed UltraSEQ, a first-of its kind metagenomics-based clinical diagnostics and biosurveillance tool that is accurate and scalable. Here we present results for evaluation of our novel UltraSEQ pipeline using an in silico synthesized metagenome, mock microbial community datasets, and publicly available clinical datasets from samples of different infection types, and both short-read and long-read sequencing data. Our results show that UltraSEQ successfully detected all expected species across the tree of life in the in silico sample and detected all 10 bacterial and fungal species in the mock microbial community dataset. For clinical datasets, even without requiring dataset-specific configuration settings changes, background sample subtraction, or prior sample information, UltraSEQ achieved an overall accuracy of 91%. Further, we demonstrated UltraSEQs ability to provide accurate antibiotic resistance and virulence factor genotypes that are consistent with phenotypic results. Taken together, the above results demonstrates that the UltraSEQ platform offers a transformative approach to microbial and metagenomic sample characterization, employing a biologically informed detection logic, deep metadata, and a flexible system architecture for classification and characterization of taxonomic origin, gene function, and user-defined functions, including disease-causing infection.

bioinformatics↗

bioRxiv2021

Site-specific phosphorylation of PSD-95 dynamically regulates the post-synaptic density as observed by phase separation

Postsynaptic density protein 95 is a key scaffolding protein in the postsynaptic density of excitatory glutamatergic neurons, organizing signaling complexes primarily via its three PSD-95/Discs-large/Zona occludens domains. PSD-95 is regulated by phosphorylation, but technical challenges have limited studies of the molecular details. Here, we genetically introduced site-specific phosphorylations in single, tandem and full-length PSD-95 and generated a total of 11 phosphorylated protein variants. We examined how these phosphorylations affected binding to known interaction partners and the impact on phase separation of PSD-95 complexes, and identified two new phosphorylation sites with opposing effects. Phosphorylation of Ser78 inhibited phase separation with the glutamate receptor subunit GluN2B and the auxiliary protein stargazin, whereas phosphorylation of Ser116 induced phase separation with stargazin only. Thus, by genetically introducing phosphoserine site-specifically and exploring the impact on phase separation, we have provided new insights into the regulation of PSD-95 by phosphorylation and the dynamics of the PSD. Graphical Abstract: Phosphorylation of PSD-95. O_LIIllustration of the interaction between the PDZ domains of PSD-95 and the NMDA receptor (NMDAR) (PDB: 4PE5) at the plasma membrane. PSD-95 interacts with the AMPA receptor (AMPAR) (PDB: 3KG2) through Stargazin (PDB: 5KBU). Using the software Ranch, a model of FL PSD-95 was generated using known structural domains of PSD-95 connected via a fully-flexible linker (PDZ1-2, PDB: 3GSL; PDZ3, PDB: 5JXB; SH3-GK, PDB: 1KJW). C_LIO_LIIllustration of the effect of phosphorylation of PSD-95 on the formation of condensates at the PSD. PSD-95 can phase separate with receptors and intracellular proteins, and phosphorylation is can affect this interaction and lead to alterations, both negative and positive, in the formation of condensates. C_LI

biochemistry↗