Biology subjects

Barclay, A.

Publications and source records attributed to Barclay, A..

6 recordsLinked to original sources

bioRxiv2026

Mechanically-mediated low-pressure cell membrane poration enables tunable intracellular delivery of traditionally impermeable cargoes in high throughput and clinical scale formats

Traditional intracellular delivery methods suffer from cargo inefficiencies, non-linear delivery kinetics, and cellular trauma. We designed a mechanically-mediated poration platform governed by deterministic, passive diffusion operating at low pressure which enables dose-dependent, cargo-agnostic intracellular delivery and preserves cellular homeostasis; key advantages include high-fidelity multiplexing, transient cell engineering, and direct-to-biology live-cell target engagement enabling development of novel intracellular delivery applications across drug discovery and cell therapy. We demonstrate examples including live-cell DEL discovery and MOA studies, complex and rapid cell therapy manufacturing, and assay development in sensitive primary cell types.

cell biology↗

bioRxiv2026

HCF1 orchestrates O-GlcNAcylation and affinity-dependent transcription through extended molecular determinants and register-shifted binding

We recently identified Host Cell Factor 1 (HCF1), a transcriptional co-regulator discovered more than thirty years ago, as a cancer dependency. To further understand its molecular functions and expand its known interactome, here, we screened a proteome-wide library of candidate HCF1 binding peptides and identified previously uncharacterized canonical and non-canonical HCF1-binding partners. Through deep mutational scanning (DMS) screening, we uncovered an extended set of molecular determinants of binding and show how mutations outside its previously established interacting residues impact binding affinity. Next, we uncover non-canonical HCF1 binders with an extended register-shifted two-amino acid sequence between their "anchor" histidine and tyrosine amino-acid residues, which we show critically contributes, in an affinity-dependent manner, to the downstream transcriptional activity of IRF1. Our data also shows that HCF1 promotes O-GlcNAcylation of the majority of its transcriptional binders. Overall, our results significantly expand the number and diversity of HCF1 binders and propose an enhanced mechanistic understanding of how HCF1 orchestrates transcription and O-GlcNAcylation.

molecular biology↗

bioRxiv2024

Comparative single-cell analyses reveal evolutionary repurposing of a conserved gene program in bat wing development

Bats are the only mammals capable of self-powered flight, an evolutionary innovation based on the transformation of forelimbs into wings. The bat wing is characterized by an extreme elongation of the second to fifth digits and a wing membrane called chiropatagium connecting them. Here we investigated the developmental and cellular origin of this structure by comparing bat and mouse limbs using omics tools and single-cell analyses. Despite the substantial morphological differences between the species, we observed an overall conservation of cell populations and gene expression patterns including interdigital apoptosis. Single-cell analyses of micro-dissected embryonic chiropatagium identified a specific fibroblast population, independent of apoptosis-associated interdigital cells, as the origin of this tissue. These distal cells express a conserved gene program including the transcription factors MEIS2 and TBX3, which are commonly known to specify and pattern the early proximal limb. Transgenic ectopic expression of MEIS2 and TBX3 in mouse distal limb cells resulted in the activation of genes expressed during wing development and phenotypic changes related to wing morphology, such as the fusion of digits. Our results elucidate fundamental molecular mechanisms of bat wing development and illustrate how drastic morphological changes can be achieved through repurposing of existing developmental programs during evolution.

evolutionary biology↗

bioRxiv2020

Order and disorder - an integrative structure of the full-length human growth hormone receptor

Despite the many physiological and pathophysiological functions of the human growth hormone receptor (hGHR), a detailed understanding of its modus operandi is hindered by the lack of structural information of the entire receptor at the molecular level. Due to its relatively small size (70 kDa) and large content of structural disorder (>50%), this membrane protein falls between the cracks of conventional high-resolution structural biology methods. Here, we study the structure of the full-length hGHR in nanodiscs with small angle-X-ray scattering (SAXS) as the foundation. We developed an approach in which we combined SAXS, X-ray diffraction and NMR spectroscopy obtained on the individual domains and integrated the data through molecular dynamics simulations to interpret SAXS data on the full-length hGHR in nanodiscs. The structure of the hGHR was determined in its monomeric state and provides the first experimental model of any full-length cytokine receptor in a lipid membrane. Combined, our results highlight that the three domains of the hGHR are free to reorient relative to each other, resulting in a broad structural ensemble. Our work exemplifies how integrating experimental data from several techniques computationally, may enable the characterization of otherwise inaccessible structures of membrane proteins with long disordered regions, a widespread phenomenon in biology. To understand orchestration of cellular signaling by disordered chains, the hGHR is archetypal and its structure emphasizes that we need to take a much broader, ensemble view on signaling.

biophysics↗

bioRxiv2019

A framework for predicting soft-fruit yields and phenology using embedded, networked microsensors, coupled weather models and machine-learning techniques

Predicting harvest timing is a key challenge to sustainably develop soft fruit farming and reduce food waste. Soft fruits are perishable, high-value and seasonal, and sales prices are typically time-sensitive. In addition, fruit harvesting is labour-intensive and increasingly expensive making accurate phenological predictions valuable for growers. A novel approach for predicting soft fruit phenology and yields was developed and tested, using strawberries as the model crop. Seedlings were planted in polytunnels, and environmental and yield data were collected throughout the growing season. Over 1.2 million datapoints were collected by networked microsensors which measured spatial and temporal variability in air temperature, relative humidity (RH), soil moisture and photosynthetically active radiation (PAR). Fleeces were added to a subset of the plants to generate additional within-polytunnel variation. Cumulative fruit yields followed logistic growth curves and the coefficients of these curves were dependent on micro-climatic growing conditions. After 10,000 iterations, machine learning revealed that RH was the optimal factor informing the coefficients of these curves, perhaps because it is an integrative metric of air temperature and water status. Trigonometric models transformed weather forecasts, which showed a relatively low agreement with polytunnel air temperature (R2 = 0.6) and RH (R2 = 0.5) measurements, into more accurate polytunnel-specific predictions for temperature and RH (both R2 = 0.8). We present a framework for using machine-learning techniques to calculate curve coefficients and parametrise coupled weather models which can predict fruit yields and timing to a greater degree of accuracy that previously possible. Dataloggers measuring environmental and yield data could infer model parameters using iterative training for novel fruit varieties or crop types growing in different locations without a-priori phenological information. At this stage in the development of artificial intelligence and networked microsensors, this is a step forward in generating bespoke phenological prediction models to inform and support growers.

plant biology↗

bioRxiv2017

The Beaker Phenomenon And The Genomic Transformation Of Northwest Europe

Bell Beaker pottery spread across western and central Europe beginning around 2750 BCE before disappearing between 2200-1800 BCE. The mechanism of its expansion is a topic of long-standing debate, with support for both cultural diffusion and human migration. We present new genome-wide ancient DNA data from 170 Neolithic, Copper Age and Bronze Age Europeans, including 100 Beaker-associated individuals. In contrast to the Corded Ware Complex, which has previously been identified as arriving in central Europe following migration from the east, we observe limited genetic affinity between Iberian and central European Beaker Complex-associated individuals, and thus exclude migration as a significant mechanism of spread between these two regions. However, human migration did have an important role in the further dissemination of the Beaker Complex, which we document most clearly in Britain using data from 80 newly reported individuals dating to 3900-1200 BCE. British Neolithic farmers were genetically similar to contemporary populations in continental Europe and in particular to Neolithic Iberians, suggesting that a portion of the farmer ancestry in Britain came from the Mediterranean rather than the Danubian route of farming expansion. Beginning with the Beaker period, and continuing through the Bronze Age, all British individuals harboured high proportions of Steppe ancestry and were genetically closely related to Beaker-associated individuals from the Lower Rhine area. We use these observations to show that the spread of the Beaker Complex to Britain was mediated by migration from the continent that replaced >90% of Britains Neolithic gene pool within a few hundred years, continuing the process that brought Steppe ancestry into central and northern Europe 400 years earlier.

genomics↗