Biology subjects

Binder, A.

Publications and source records attributed to Binder, A..

4 recordsLinked to original sources

bioRxiv2026

Actin-related protein Alp1 governs malaria parasite motility and transmission

Motility of the malaria-causing parasite Plasmodium is essential for transmission to and from mosquitoes, with the turnover of actin filaments being a central feature of productive cell movement. Actin-related proteins (Arps) are known to play critical roles in motility, trafficking and chromatin remodelling. Here, we show that the actin-like protein 1 (Alp1), an apicomplexan Arp, is essential for Plasmodium ookinete motility and establishing of infection in mosquitoes. We identified an insertion region in subdomain 4 that contributes to Alp1 function in ookinetes and show novel actin filament structures in ookinetes. A combination of gene deletion and actin filament recognizing chromobody expression revealed a role of Alp1 in promoting actin filament turnover in ookinetes. We have thus identified a novel Arp that has evolved a specialist function to regulate actin dynamics, govern malaria parasite motility and facilitate malaria transmission.

cell biology↗

bioRxiv2026

Identifying cytokine-release signatures of flow-driven endothelial remodelling in an intracranial aneurysm cell culture model

Intracranial aneurysm (IA) rupture is catastrophic, yet current models of rupture-risk inadequately capture underlying IA remodelling mechanisms. Endothelial-haemodynamic interactions are central to these processes, but in vitro flow platforms often lack vessel-relevant geometry or long-term perfusion. Here, temporal and spatial endothelial responses to haemodynamic stress were investigated across idealised and patient-specific vascular models. Polydimethylsiloxane models were endothelialised with human aortic endothelial cells then perfused at up to 1.6 Pa wall shear stress for five days. IA models were exposed to steady or cardiovascular flow waveforms, with endothelial phenotype assessed by immunofluorescence and cytokine profiling. Flow initiation induced a transient inflammatory response, with elevated MCP-1 and TNF- at day two, followed by a resolution of cytokine levels by day five, including a [~]7.5-fold reduction in MCP-1, despite increased haemodynamic loading. Endothelial cells retained a cobblestone-like morphology with eNOS undetected, resembling a partially activated phenotype. Compared with steady flow, cardiovascular flow reduced TGF-{beta}1 and IL-8 secretion and decreased FGF-b consumption ([~]2.5 fold), suggesting enhanced phenotypic stability. This study presents the first in vitro IA model incorporating a cardiovascular flow waveform and identifies cytokine signatures with potential utility as biomarkers of IA remodelling, highlighting the importance of long-term perfusion for modelling chronic vascular disease. Table of Contents FigureAn in vitro model of an intracranial aneurysm was developed to investigate how fluid flow dynamics impact endothelial remodelling and inflammation. Pulsatile cardiac flow promoted stabilisation of inflammatory signalling, which was sustained under a steady flow regime. Cytokine signatures emerged with potential utility as biomarkers of IA remodelling, highlighting the importance of long-term perfusion for modelling chronic vascular disease. The schematic of the cytokine release dynamics used in the graphical abstract below was generated with the assistance of AI-based tools including ChatGPT (v5.5) and M365 Copilot to align with key results from this manuscript. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/733289v1_ufig1.gif" ALT="Figure 1000"> View larger version (80K): org.highwire.dtl.DTLVardef@709204org.highwire.dtl.DTLVardef@825f81org.highwire.dtl.DTLVardef@14c345eorg.highwire.dtl.DTLVardef@222a8_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

Deep Learning for Predicting Stem Cell Efficiency for use in Beta Cell Differentiation

Recent clinical trial data have shown that cell therapy holds curative potential for type-1 diabetes, however the large amounts of lab-grown cells required is a substantial bottleneck. The necessary cell differentiation process exhibits substantial variability, even among clones of induced pluripotent stem cells generated from the same patient. In contrast to many established data sets in medical imaging, human experts struggle to see the difference between highly- and lowly-efficient cell clones. We therefore propose an image-based deep learning model to guide the selection of the most efficient stem cell clones. We apply different deep learning model architectures to learn the morphological differences between good and bad stem cell clones and classify them based on only phase-contrast imaging. To gain critical insight into the learned features and enhance trust in our model, we use layer-wise relevance propagation (LRP), and Fourier-based frequency analysis. Using an EfficientNet-V2-S model, we obtain a novel early prediction for the outcome of the differentiation process from patient-derived stem cell to {beta}-cells using only phase-contrast images. Clone level accuracy is 76.7 % at 24 hours and 96.7 % at 53 hours after start of differentiation. The LRP-generated attribution maps and structure factor analysis show that the structure of the cell population is an important predictive feature. All in all, we present a highly predictive model for successful stem cell differentiation from phase-contrast images, which learns biologically relevant features. This study is a proof-of-concept that deep learning combined with label-free imaging can guide selection of induced pluripotent stem cell clones, thereby reduce cost of {beta}-cell production, and bring curative treatments one step closer to the clinic.

bioinformatics↗

bioRxiv2018

Symbiosis-related genes sustain the development of a downy mildew pathogen on Arabidopsis thaliana

AO_SCPLOWBSTRACTC_SCPLOWThe interfaces through which nutrients are transferred from plant cells to arbuscular mycorrhiza fungi and biotrophic hyphal pathogens are structurally similar. We report that in Arabidopsis thaliana, mutations in homologs of common symbiosis genes (CSGs) encoding homologs of the symbiosis receptor kinase SYMRK, the nucleoporins NUP133 and SEC13 or the cation channel POLLUX reduce the reproductive success of Hyaloperonospora arabidopsidis (Hpa). Analysis of the multiplication of extracellular bacterial pathogens, Hpa-induced cell death or callose accumulation, as well as Hpa-or flg22-induced defence marker gene expression, did not reveal any traces of constitutive or exacerbated defence responses. We discovered an age-dependent, possibly senescence-related transition of haustorial shape that occurred significantly earlier and at higher frequency in the CSG mutants. These findings point to a function of the homologs of common symbiosis genes in haustorial maintenance thus revealing an overlapping gene set for the intracellular accommodation of hyphal symbionts and pathogens.

cell biology↗