Biology subjects

Ellmen, I.

Publications and source records attributed to Ellmen, I..

4 recordsLinked to original sources

bioRxiv2026

Modelling antibody structures at the speed of language

Protein structure prediction is currently substantially slower than obtaining sequence representations of proteins. This leads to most property prediction methods relying solely on trivial or learned sequence embeddings. However, contemporary structure prediction and sequence models are both based on Transformers, and structure prediction models often have fewer parameters, suggesting that there might be domains where accurate structure prediction adds no practical overhead to sequence-only modelling. Here, we demonstrate this can be achieved for adaptive immune proteins by introducing FlashABB, which predicts highly accurate antibody structures, and does so faster than even modestly-sized language models can embed sequences. As a component of FlashABB, we develop Flashpoint Attention, a fast and linear memory analog of Invariant Point Attention. To our knowledge, FlashABB is the first example of a model that accurately predicts protein structure faster than protein language models can generate embeddings, enabling efficient access to 3D information without the need for precomputed structures. Using FlashABB, we develop methods for predicting antibody stability and developability which can be scaled to repertoires of millions of sequences. Our results show how the computational bottleneck of protein structure prediction can be removed in some real-world cases. The code and model weights for FlashABB are available on GitHub: https://github.com/oxpig/FlashABB

molecular biology↗

bioRxiv2025

LICHEN: Light-chain Immunoglobulin sequence generation Conditioned on the Heavy chain and Experimental Needs

In developing therapeutic antibodies, the heavy chain is often prioritised due to its higher variability and its central role in antigen binding. An appropriate pairing of the light sequence is however important for antibody function. Here we present LICHEN, a heavy chain conditioned light sequence generation tool that enables collaborative light sequence design by leveraging computational capabilities alongside experimental expertise. LICHEN generates light sequences which are valid (antibodylike), diverse in sequence and structure, and conditioned on a specific heavy chain. LICHEN can also condition on germline and CDRs and automatically filter generated sequences for required properties. This allows LICHEN to be used across multiple antibody development use cases. We carry out experimental validation of the method conditioning only on the heavy sequence and on the heavy sequence and binding information. Our in vitro results show that sequences created by LICHEN have effective expression yields and can retain antigen-binding.

bioinformatics↗

bioRxiv2023

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic "novel" lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances, and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1% frequency, results were more reliable above a 5% threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of noise or bias in wastewater sequencing data and to appreciate the commonalities and differences across methods.

bioinformatics↗

bioRxiv2023

A Novel Tiled-Amplicon Sequencing Assay Targeting the Tomato Brown Rugose Fruit Virus (ToBRFV) Genome Reveals Widespread Distribution in Municipal Wastewater Treatment Systems in the Province of Ontario, Canada

Tomato Brown Rugose Fruit Virus (ToBRFV) is a plant pathogen that infects important Solanaceae crop species and can dramatically reduce tomato crop yields. The ToBRFV has rapidly spread around the globe due to its ability to escape detection by antiviral host genes, most notably Tm-22, which are used to confer resistance to other Tobamoviruses in tomato plants. Development of robust and reproducible methods for detecting viruses in the environment aids in the tracking and reduction of pathogen transmission. We detected ToBRFV in municipal wastewater influent (WWI) samples, likely due to its presence in human waste, demonstrating a widespread distribution of ToBRFV in WWI throughout Ontario, Canada. To aid in global ToBRFV surveillance efforts, we developed a tiled-amplicon approach to sequence and track the evolution of ToBRFV genomes in municipal WWI. Our assay recovers 97.5% of the 6393 bp ToBRFV RefSeq genome, omitting the terminal 5 and 3 ends. We demonstrate that our sequencing assay is a robust, sensitive, and highly specific method for recovering ToBRFV genomes. Our ToBRFV assay was developed using existing ARTIC Network resources, which includes genome specific primer design, sequencing library prep, and read analysis. Additionally, we adapted our lineage abundance estimation tool, Alcov, to estimate the abundance of ToBRFV clades in samples.

microbiology↗