Biology subjects

Newland, R.

Publications and source records attributed to Newland, R..

3 recordsLinked to original sources

bioRxiv2025

IRF2 degradation tunes the innate immune response

The transcription factor IRF2 protects against skin inflammation in mice and humans but, paradoxically, promotes pyroptosis by inducing Gsdmd. How IRF2 activates some proinflammatory genes, but suppresses others is unclear. We show that skin inflammation in Irf2-deficient mice is driven by IRF1 activation of interferon-stimulated genes (ISGs). Chromatin profiling revealed that IRF1 and IRF2 occupy the same ISG regulatory sites, but as a weaker transcriptional activator, IRF2 limited ISG transcription by IRF1. Toll-like receptor signaling favored IRF1-driven transcription by inducing Irf1. In addition, IRF1 recruited the ubiquitin ligase SPOP to ISG sites, resulting in proteasomal degradation of IRF2. This shift from IRF2 to IRF1 occupancy enhanced ISG transcription. Collectively, these findings define a hierarchical transcriptional circuit in which IRF2 limits IRF1 activity under homeostatic conditions but is displaced during an immune response, allowing IRF1-dependent gene programs central to innate immunity and autoinflammation.

immunology↗

bioRxiv2025

Deep Evolutionary Fitness Inference for Variant Nomination from Directed Evolution

Iterative screening techniques, such as directed evolution, enable high-throughput affinity maturation to optimize binders to molecular interfaces. However, the decision problem of selecting variants from rich, evolved populations to enter low-throughput follow-up methods remains a significant bottleneck. Here, we present evolutionary fitness inference (EVFI) and DeepEVFI, two machine learning methods that model directed evolution from time-series sequencing data, and infer fitness, a variants ability to enrich under selection pressure. Our methods flexibly handle mutation mechanisms and starting populations that may be partially unknown - settings relevant to drug discovery - and achieve strong performance on a diverse set of experimental data. We conducted two experimental directed evolution campaigns, using antibodies and macrocyclic peptides libraries to identify and optimize binders to therapeutically relevant targets. EVFI and DeepEVFI identified tighter binders that were missed by human experts using conventional frequency-based approaches, including "rising stars" with low frequency. Beyond initial hit discovery, EVFI and Deep-EVFI enables labeling large-scale sequence-fitness datasets and identifying variants of initial binders with diverse properties.

bioinformatics↗

bioRxiv2022

Venom protection by antibody from a snakebite hyperimmune subject

Snake envenomation is a neglected tropical disease, causing >100,000 deaths and 300,000 permanent disabilities in humans annually. Could monoclonal antibody technology provide a solution? Here, we recover Centi-3FTX-D09, a potent broadly neutralizing antivenom antibody from the B-cell memory of a human subject with snake venom exposure. Centi-3FTX-D09 recognized a conserved neutralizing epitope on long 3-finger toxins (3FTXs), a dominant snake neurotoxin. Crystal structures of Centi-3FTX-D09 in complex with 3FTXs from mamba, taipan, krait, and cobra revealed epitope mimicry of the interface between these neurotoxins and their host target, the nicotinic acetylcholine receptor. Centi-3FTX-D09 provided in-vivo protection against diverse recombinant long 3FTXs, in-vivo rescue from whole venom challenge from cobras, black mamba, and king cobra, and, when combined with the phospholipase inhibitor varespladib, in-vivo protection extending to a majority of tested elapid venoms. Thus, a single antibody can broadly neutralize long neurotoxins and contribute to broad protection from envenomation.

immunology↗