Biology subjects

Bingham, J.

Publications and source records attributed to Bingham, J..

4 recordsLinked to original sources

bioRxiv2026

Structural basis of phosphatidylserine enhancement of Gas6 ligand-induced Axl activation

TAMs (Tyro3, Axl, and MerTK) are receptor tyrosine kinases with primary roles in apoptotic clearance and immune suppression. In apoptosis, bridging complexes form between TAM receptors on phagocytic cells and TAM ligand bound to phosphatidylserine exposed on the surface of dying cells, but how these complexes form or why lipid is required for receptor activation is poorly understood. We present the first structures of a complete TAM receptor (Axl) and ligand (Gas6) 2:2 bridging complex with and without lipid, which suggest that the lipid functions to stabilize and promote active complexes. We also observe a stable 1:1 complex, presumed to be inactive, and provide evidence that these complexes are conversely able to form higher-order oligomers. We propose a mechanism for how lipids promote TAM receptor activation, providing a structural and biochemical basis for developing therapies that selectively target the lipid-dependent, immunosuppressive arm of TAM signaling exploited by tumors.

biophysics↗

bioRxiv2026

A compartment-adjustment framework reclassifies FOXC1 as a stromal-vascular readout in Luminal A breast cancer and recasts the basal-lineage "Centaur" signal as a tumour-population axis

Background: Candidate tumour-cell biomarkers identified from bulk transcriptomes are frequently expressed in stromal or vascular compartments as well, so a bulk correlation between such a gene and a biological programme can reflect tumour-cell biology or co-variation with those compartments. FOXC1, a PAM50 basal-defining transcription factor with canonical vascular expression, has immune associations in Luminal A breast cancer that have been read as tumour-cell-intrinsic. Methods: We developed a compartment-adjustment framework - purity- and stroma-adjusted partial correlations benchmarked across candidate marker genes - and applied it across three Luminal A cohorts (TCGA, (n=571); METABRIC, (n=700); SCAN-B, (n=1,540); two sequencing platforms) and single-cell data (GSE176078; 100,064 cells). Results: FOXC1's apparent adaptive-immune and tertiary-lymphoid-structure coupling is a vascular readout: it attenuates under adjustment for leukocyte-adhesion endothelial markers but persists under a structural-only endothelial composite, marking immune-recruiting vasculature. Single-cell analysis localises FOXC1 to the vessel wall-malignant cells contribute (1.8%) of FOXC1 transcripts versus (90%) from endothelial and perivascular cells. Basal cytokeratins (KRT5, KRT14, KRT17) and TP63, unlike FOXC1, retain a residual population-level basal-lineage signal; an apparent survival advantage is largely age-explained. Conclusions: Bulk FOXC1 in Luminal A originates principally from stromal--vascular compartments. Compartment adjustment offers a candidate approach for interpreting bulk biomarkers in heterogeneous tissue.

cancer biology↗

bioRxiv2021

A novel and highly divergent Canine Distemper Virus lineage causing distemper in ferrets in Australia

Canine distemper virus (CDV) is a highly contagious systemic viral disease of dogs, that regularly spills-over into other animal species. Despite widespread vaccination, CDV remains endemic in many parts of the world. In this study we report an outbreak of distemper in ferrets in two independent research facilities in Australia. We found that disease severity varied, although most animals had mild to moderate disease signs. Histopathology results of animals with severe disease presented the typical profile of distemper pathology with multi-system virus replication. Through the development of a discriminatory PCR paired with full genome sequencing we revealed that the outbreak at both facilities was caused by a single, novel lineage of CDV. This lineage was highly divergent across the H gene, F signal peptide and full genome and had less than 93% similarity across the H gene to other described lineages, including the vaccine strain. Molecular analysis indicates that this strain belongs to a distinct lineage that diverged from other clades approximately 140 to 400 years ago, and appears to be unique to Australia. Given the differences in key viral proteins of this novel CDV strain, a review of the efficacy of the CDV vaccines currently in use in Australia is warranted to ensure maximum protection of dogs and other vulnerable species. In addition, enhanced surveillance to determine the prevalence of CDV in ferrets, dogs and other at-risk species in Australia would be useful to better understand the diversity of CDV in Australia. ImportanceCanine distemper virus (CDV) is highly contagious and while dogs are the main reservoir, it may spill over into a number of other animal species. In this study we report an outbreak of distemper in ferrets in two research facilities in Australia. Outcomes of pathology and histopathology suggest ferrets have widespread multi-systemic infection, consistent with previously reported distemper infections in ferrets and dogs. Critically, through sequencing and phylogenetic analysis, we revealed that the outbreak at both facilities was caused by a single, novel and highly divergent lineage of CDV. This virus had less than 93% nucleotide similarity to other described lineages and the vaccine strain. This manuscript adds considerably to the epidemiology, ecology and evolution of this virus, and is one of few reports of distemper in Australia in the literature.

microbiology↗

bioRxiv2018

Interpreting Diagnostic Histories into HIV Infection Time Estimates: Framework and Online Tool

BackgroundIt is frequently of epidemiological and/or clinical interest to estimate the date of HIV infection or time-since-infection of individuals. Yet, for over 15 years, the only widely-referenced infection dating algorithm that utilises diagnostic testing data to estimate time-since-infection has been the Fiebig staging system. This defines a number of stages of early HIV infection through various standard combinations of contemporaneous discordant diagnostic results, using tests of different sensitivity.\n\nObjectiveTo develop a new, more nuanced infection dating algorithm, we generalised the Fiebig approach to accommodate positive and negative diagnostic results generated on the same or different dates, and arbitrary current or future tests - as long as the test sensitivity is known. For this purpose, test sensitivity is conceptualised as the probability that a specimen will produce a positive result, expressed as a function of time since infection. This can be summarised as a median diagnostic delay parameter, together with a measure of inter-subject variability.\n\nMethodsThe present work outlines the analytical framework for infection date estimation using subject-level diagnostic testing histories, and data on test sensitivity. We introduce a publicly-available online HIV infection dating tool that implements this estimation method, bringing together 1) curatorship of HIV test performance data, and 2) infection date estimation functionality, to calculate plausible intervals within which infection likely became detectable for each individual. The midpoints of these intervals are interpreted as infection time point estimates and referred to as Estimated Dates of Detectable Infection (EDDIs).\n\nResultsIn many settings, including most research studies, detailed diagnostic testing data are routinely recorded, and can provide reasonably precise estimates of the timing of HIV infection. We present a simple logic to the interpretation of diagnostic testing histories into infection time estimates, either as a point estimate (EDDI) or an interval (earliest plausible to latest plausible dates of detectable infection), along with a publicly-accessible online tool that supports wide application of this logic.\n\nConclusionsThis tool, available at https://tools.incidence-estimation.org/idt/, is readily updatable as test technology evolves, given the simple architecture of the system and its nature as an open source project.

epidemiology↗