Biology subjects

Simpson, R.

Publications and source records attributed to Simpson, R..

5 recordsLinked to original sources

bioRxiv2026

BXD51: A Robust and Translational Mouse Model for Studying the Pathophysiology of Glaucoma

The aim of this study was to characterize the BXD51 mouse strain as a reproducible model of chronic progressive glaucoma. Unlike the highly susceptible DBA/2J (D2) mutant strain, BXD51 is a genetically stable recombinant inbred line derived from C57BL/6J (B6) and D2 parental lines. Longitudinal assessments of intraocular pressure (IOP), visual acuity (VA), contrast sensitivity (CS), and pattern electroretinogram (pERG) demonstrated that BXD51 mice undergo a delayed decline in visual and retinal ganglion cell (RGC) function. Their decline is biphasic, with a period of initial ocular stress followed by a late-onset, accelerated structural and functional deterioration of RGCs. Anterior segment structural analysis by optical coherence tomography (OCT) and histology demonstrated increasing pigment dispersion and subsequent iridocorneal angle closure. Immunofluorescence analysis of structural neuronal markers (TUBB3 and MAP1A/2) exhibited thinning of the ganglion cell layer (GCL) and inner plexiform layer (IPL) together with axonal degeneration, mirroring the laminar degeneration seen in human glaucoma patients. BXD51 also revealed marked spatial heterogeneity between peripheral and central retina. Multivariate analysis confirmed that BXD51 follows a distinct clinical trajectory that separates it from both wild-type (B6) and a severe glaucoma model (D2). By spanning the range between resistance and extreme susceptibility to glaucomatous neurodegeneration, this study establishes the BXD51 mouse as a translational platform for mechanistic studies and for evaluating long-term neuroprotective strategies.

neuroscience↗

bioRxiv2026

The metastasis susceptibility gene RRP1B is a stress-responsive regulator of nuclear RNA processing and splicing in breast cancer

The tumor microenvironment exposes cancer cells to mechanical, thermal, hypoxic, and acidic stresses, yet how cells integrate these signals to remodel RNA processing remains poorly understood. Here, we show that ribosomal RNA Processing 1B (RRP1B), previously characterized as a nucleolar ribosome biogenesis factor and metastasis modifier, functions as a broad-spectrum stress sensor that dynamically repositions among the nuclear envelope, nucleolus, and nuclear speckles (NS). Relocalization is governed by multi-site phosphorylation within intrinsically disordered regions (IDRs): phosphomimetic substitutions promote NS-proximal condensate formation in an RNA-dependent manner, while unphosphorylatable substitutions confine RRP1B to the nucleolus. Under stress, the RRP1B interactome shifts globally, with ribosomal processing partners replaced by pre-mRNA splicing components enriched for NS-resident proteins. RNA immunoprecipitation sequencing (RIP-seq) demonstrates that under basal conditions RRP1B associates with long, intron-rich, nuclear periphery-proximal transcripts, whereas heat shock redirects binding toward shorter, exon-dense transcripts enriched for motifs of serine/arginine-rich (SR) proteins near the NS. RRP1B overexpression nearly abolishes cytoplasmic retained intron accumulation and drives preferential export of specific transcript isoforms in a compartment- and temperature-dependent manner, establishing RRP1B as a regulator of RNA localization fidelity rather than transcriptional output. An RRP1B overexpression signature is most highly activated in basal-like and claudin-low breast tumors, and the RRP1B-associated retained intron splicing program correlates with reduced survival in a tumor-grade-dependent manner. These findings reframe RRP1B as a microenvironmentally sensitive regulator of nuclear RNA processing with direct implications for aggressive breast cancer biology.

Cancer Biology↗

bioRxiv2025

Oncogenic H-Ras Reprograms Madin-Darby Canine Kidney (MDCK) Cell-derived Midbody Remnant Proteins Following Epithelial-Mesenchymal Transition

Epithelial-mesenchymal transition (EMT) is a highly conserved morphogenic process that allows highly polarized, immotile epithelial cells to transform into motile mesenchymal cells: it is a fundamental cellular process involved in embryonic development, tumour cell metastasis, organ fibrosis and tissue regeneration. To assess the contribution of secreted midbody remnants (MBRs) - a new class of membranous extracellular vesicle (EV) molecularly distinct from exosomes/small EVs - to the EMT process, we conducted a proteomic analysis of MBRs released from Madin-Darby canine kidney (MDCK) cells, and MDCK cells transformed with oncogenic H-Ras (21D1 cells). MBRs were harvested from cell culture media in milligram quantities using a continuous culture bioreactor device and purified using sequential centrifugation and buoyant density gradient centrifugation (OptiPrep). Gel-MS/MS protein profiling showed MDCK cell-MBRs reflect their epithelial origin (e.g., enriched CDH1, DSP, THBS1, OLCN, EPCAM proteins) and 21D1 cell-MBRs their mesenchymal phenotype (e.g., HRAS, VIM, MMP14, CDH2, WNT5A and enriched invasive and cell motility proteins). Prominent findings were the unique expression of the immune checkpoint protein NT5E/CD73 (ecto-5'-nucleotidase), and ser/thr kinases LIMK1/K2 in 21D1-MBRs (not present in MDCK cell-MBRs), and enrichment in Wnt signalling network proteins. Collectively, our findings suggest MBRs might play a previously unrecognized role in the EMT process. SignificanceO_LIEpithelial-to-mesenchymal transition (EMT) is a critical cell biological process that occurs during normal embryonic development and cancer progression. Our study describes, for the first time, the large-scale sequential purification of secreted midbody remnants (MBRs) and exosomes/sEVs from the in vitro cell line EMT model Madin-Darby canine kidney (MDCK) cells and MDCK cells transformed with oncogenic H-Ras (21D1 cells): GeLC-MS/MS protein profiling identified the repertoire of enriched MDCK-MBR proteins following EMT. C_LIO_LIMBRs display a proteome profile distinct from sEVs that is enriched with factors of the centralspindlin complex (KIF23.1, KIF4A, INCENP, CEP55, PLK1) and further include components of the mitochondrial network, cytokinesis, microtubule movement, and intercellular connection. C_LIO_LIIn the context of EMT, our data reveal simultaneous activation of EMT signalling pathways in MBRs including signalling receptor binding, regulation of cell differentiation, and Wnt, VEGF and PDGF signalling. C_LIO_LIWe identify several mesenchymal enriched networks in MBRs associated with focal adhesion, cell matrix, kinase activity, and cell shape/organisation, while epithelial derived MBRs are show enriched networks predominately associated with mitochondrial (processing/transport), midbody, and plasma membrane annotation. C_LIO_LIOur study sheds light on the signalling architecture of MBRs following oncogenic H- Ras-induced EMT: collectively, our data informs ongoing efforts to delineate oncogenic drivers of cancer initiation, progression, and metastasis. C_LI

cell biology↗

bioRxiv2020

Candidate Explorer: a tool for discovery, evaluation, and display of mutations causing significant immune phenotypes

When applied to immunity, forward genetic studies use meiotic mapping to provide strong statistical evidence that a particular mutation is causative of a particular immune phenotype. Notwithstanding this, co-segregation of multiple mutations, occasional unawareness of mutations, and paucity of homozygotes may lead to erroneous declarations of cause and effect. We sought to improve the selection of authentic causative mutations using a machine learning software tool, Candidate Explorer (CE), which integrates 65 data features into a single numeric score, mathematically convertible to the likelihood of verification of any putative mutation-phenotype association. CE has identified most genes within which mutations can be causative of flow cytometric phenovariation in Mus musculus. The majority of these genes were not previously known to support immune function or homeostasis. Mouse geneticists will find CE data informative in identifying causative mutations within quantitative trait loci, while clinical geneticists may use CE to help connect causative variants with rare heritable diseases of immunity, even in the absence of linkage information. CE displays integrated mutation, phenotype, and linkage data, and is freely available for query online.

genetics↗

bioRxiv2018

Metabolic deregulation in prostate cancer

IntroductionThe prostate exhibits a unique metabolism that changes during initial neoplasia to aggressive prostate cancer (PCa) and metastasis. The study of PCa metabolism thus represents a new avenue for diagnostics, particularly early diagnosis of aggressive PCa cases.\n\nResultsHere, using transcriptomics data from The Cancer Genome Atlas (498 PCa patients), we identified six metabolic subgroups (C1-C6) of PCa that showed distinct disease-free survival outcomes (p<0.0001). In particular, we identified at least two PCa subgroups (C5 and C3) that exhibited significant poor prognosis (~70% and 30-40% relapse by the first 72 months; hazards ratios 9.4 and 4.4, respectively, relative to the best prognosis cluster C4 that showed <20% relapse even by 120 months). The subgroups were reproducible in an independent dataset from Taylors et al. 2010 (215 patients; p=0.00088). The subgroups displayed distinct metabolic profiles vis-a-vis normal tissues; measured as deregulation of metabolic pathways (using Pathifier, Drier & Domany, 2013). In particular, the poor-prognosis subgroups C5 and C3 showed considerable deregulation for pathways involved in synthesis and catabolism of complex forms of lipids and carbohydrates, amino acids, and TCA cycle, and these were exhibited in parallel or in the face of glycolysis, a common form of energy production in cancer cells. Furthermore, the subgroups were significantly over-enriched for different sets of genetic alterations [particularly, deletions/mutations in BRCA1 and TP53 (C5), RB1 and STK11(C3); and AR amplifications (C1); p[≤]8.6E-04], suggesting that distinct alterations may be underpinning the subgroups and pushing the subgroups towards their unique metabolic profiles. Finally, applying the classifier to blood expression profiles from 42 active surveillance (AS) and 65 advanced castrate resistant PCa (ACRPC) patients determined based on prostate-specific antigen (PSA) levels (Olmos et al., 2012) assigned 70.77% ACPRC, and interestingly reassigned 59.52% AS patients to at least one of the poor prognosis subgroups (C5, C3) with 35.71% to the poor and metabolically deregulated subgroup C3.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=168 SRC=\"FIGDIR/small/371567_fig5.gif\" ALT=\"Figure 5\">\nView larger version (18K):\norg.highwire.dtl.DTLVardef@1418863org.highwire.dtl.DTLVardef@1614d77org.highwire.dtl.DTLVardef@124ca98org.highwire.dtl.DTLVardef@70d53b_HPS_FORMAT_FIGEXP M_FIG C_FIG ConclusionThe identification of PCa subgroups displaying distinct clinical outcomes solely from metabolic expression profiles of PCa tumours reiterates the significant link between deregulated metabolism and PCa outcomes (Eidelman et al., 2017). On the other hand, the time to biochemical relapse (rise in PSA levels) was not indicative of the early relapse seen for the metabolically deregulated subgroups C3 and C5 (these show considerably late BCR compared to C4). Our study thus highlights specific processes (elevated lipid and carbohydrate metabolism pathways) that could be better indicators than PSA for early diagnosis of aggressive PCa.

bioinformatics↗