Biology subjects

Champion, K.

Publications and source records attributed to Champion, K..

5 recordsLinked to original sources

bioRxiv2026

Nuclear acetyl-CoA accumulation drives reversible RBP hyperacetylation and transcriptome-wide splicing shifts in age-equivalent Alzheimer's disease neurons

Metabolic alterations and dysregulated alternative RNA splicing are central layers of Alzheimer's disease (AD) pathogenesis, yet whether and to what extent these changes are mechanistically linked in adult human neurons in the aging brain remains unclear. To assess this, we generated induced neurons (iNs) by direct conversion of fibroblasts from sporadic AD patients and age-matched control donors. Fibroblast-derived iNs retaining donor-specific aging signatures have been shown to display several AD-related phenotypes. Metabolomic analysis revealed that AD iNs divert citrate toward ATP-citrate lyase (ACLY)-dependent citrate-to-acetyl-CoA flux, which drives increased nuclear levels of the high-energy metabolite acetyl-CoA. Acetyl-proteomics showed that acetyl-CoA accumulation leads to widespread hyper-acetylation of RNA-binding proteins (RBPs) and splice regulators, suggestive of a direct mechanistic link between a metabolic shift and RNA processing. Indeed, single-cell long-read RNA sequencing identifies splicing alterations in AD-relevant transcripts whose isoform usage mirrors changes observed in post-mortem AD cortex samples. Subcellular acetyl-CoA imaging reveals that inhibition of ACLY enzymatic activity selectively reduces nuclear acetyl-CoA levels, and further improves citrate metabolic flux, normalizes RBP acetylation, and re-establishes a normal neuronal splicing landscape in AD iNs. Together, these findings reveal a nuclear acetyl-CoA-RNA processing axis that links age- and disease-related metabolic alterations to alternative splicing dysregulation in AD, and identify neuronal nuclear acetyl-CoA production as a causal and reversible node for restoring metabolic and RNA homeostasis in aging human AD neurons.

neuroscience↗

bioRxiv2024

Iterative sacrificial 3D printing and polymer casting to create complex vascular grafts and multi-compartment bioartificial organs

Several emerging strategies to engineer artificial organs employ 3D printing to create vascular templates to provide nutrients and oxygen to immobilized cells. Significant challenges emerge when considering clinical implementation such as immune rejection of allogeneic cell sources, as well as achieving adequate perfusion and integration with endogenous vasculature. We propose a method by which cell-laden hydrogels are molded around ready-made polymeric vascular templates created via 3D printing to create human-scale artificial organs with internal vasculature. We applied this technique to create bioartificial pancreas systems with up to 9 internal flow channels via sacrificial carbohydrate glass 3D printing, porogen-loaded polycarbonate polyurethane dip-coating, followed by casting cell-laden hydrogels around the vascular templates. We optimized porogen size and concentration to maximise the porosity of our scaffolds without compromising mechanical properties, resulting in suture retention strength and compliance respectively matching commercial vascular grafts and native vessels. Bioreactor perfusion studies showed survival and maturation of stem cell derived pancreatic islets without significant differences to traditional suspension culture protocols. Insulin response dynamics were rapid in response to a glucose challenge at the perfusion inlet. Transplantation of the devices as iliac arteriovenous shunts in nondiabetic pigs confirmed safety and patency. These results show promise for the development of an implantable vascularized pancreas for the treatment of type 1 diabetes and demonstrate how bioartificial organs with engineered vascular geometries can be designed for translational applications.

bioengineering↗

bioRxiv2024

An accessible platform to quantify oxygen diffusion in cell-laden hydrogels and its application to alginate-immobilized pancreatic beta cells

Hydrogels are commonly used to immobilize mammalian cells, serving various purposes such as providing mechanical cues in three-dimensional cultures and acting as barriers for immunoprotection in transplantation. For instance, islet encapsulation holds promise in delivering insulin-producing cells for diabetes cellular therapy. Cell immobilization, by creating a barrier to bulk fluid motion, leads to diffusion-limited molecular transport and concentration gradients of nutrients such as oxygen being consumed by the immobilized cells. Oxygen mass transport models aid in designing immobilization strategies but rely on input parameters like oxygen diffusivity, often assumed rather than experimentally measured due to limited resources or expertise. We propose an accessible, cost-effective, and easy to operate system to experimentally determine the diffusion coefficient of cell-laden hydrogels, with application tested to alginate-immobilized pancreatic beta cell (MIN6). As compared to water, the oxygen diffusion coefficient was significantly reduced in alginate gels. The oxygen diffusion coefficient was inversely correlated with the dynamic loss modulus for gels with similar chemical composition, and significantly reduced when the alginate concentration was increased from 2% to 5%. The viability of immobilized MIN6 cells was highly dependent both on gel concentration and cell density, as predicted by Thiele modulus and effectiveness factor values calculated from measured oxygen diffusion coefficients. The proposed platform, combining a simple experimental setup and the use of dimensionless numbers, offers a straightforward means to predict maximal diffusion distances in cell immobilization strategies. This platform can be implemented in the rational design of cell encapsulation, immobilized cell culture, and tissue engineering strategies.

bioengineering↗

bioRxiv2021

An Oscillatory Mechanism for Multi-level Storage in Short-term Memory

Oscillatory activity is commonly observed during the maintenance of information in short-term memory, but its role remains unclear. Non-oscillatory models of short-term memory storage are able to encode stimulus identity through their spatial patterns of activity, but are typically limited to either an all-or-none representation of stimulus amplitude or exhibit a biologically implausible exact-tuning condition. Here, we demonstrate a simple phase-locking mechanism by which oscillatory input enables a circuit to generate persistent or sequential activity patterns that encode information not only in their location but also in their discretely graded amplitudes. SignificanceA core observation in many memory systems and tasks is the presence of oscillations during memory maintenance. Here, we demonstrate a mechanism for the accumulation and storage of information in short-term memory in which oscillatory activity enables a solution to long-standing challenges in modeling the persistent neural activity underlying working memory. These challenges include the ability to encode information with low firing rates, multi-level storage of stimulus amplitude without extreme fine tuning, and multi-level storage of information in sequential activity. Altogether, this work proposes a new class of models for the storage of information in working memory, a new potential role for brain oscillations, and a novel dynamical mechanism for multi-stability.

neuroscience↗

bioRxiv2020

Analytical validation and performance characteristics of a 48-gene next-generation sequencing panel for detecting potentially actionable genomic alterations in myeloid neoplasms

Identification of genomic mutations by molecular testing plays an important role in diagnosis, prognosis, and treatment of myeloid neoplasms. Next-generation sequencing (NGS) is an efficient method for simultaneous detection of clinically significant genomic mutations with high sensitivity. However, due to lack of standard NGS protocols, the application of NGS for hematologic malignancies into clinical settings remains limited. We report development and validation of a 48-gene NGS panel for molecular profiling of myeloid neoplasms including acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasms (MPN). Target regions were captured by hybridization with complementary biotinylated DNA baits, and NGS was performed on an Illumina NextSeq500 instrument. A bioinformatics pipeline that was developed in-house was used to detect single nucleotide variations (SNVs), insertions/deletions (indels), and FLT3 internal tandem duplications (FLT3-ITD). An analytical validation study was performed on 184 unique specimens for variants with allele frequencies [≥]5%. Variants identified by the 48-gene panel were compared to those identified by a 35-gene hematologic neoplasms panel using an additional 137 unique specimens. The developed assay was applied to a large cohort (n=2,053) of patients with suspected myeloid neoplasms. Analytical validation yielded 99.6% sensitivity (95% CI: 98.9-99.9%) and 100% specificity (95% CI: 100%). Concordance of variants detected by the 2 tested panels was 100%. Among patients with suspected myeloid neoplasms (n=2,053), 54.5% patients harbored at least one clinically significant mutation: 77% in AML patients, 48% in MDS, and 45% in MPN. Together, these findings demonstrate that the assay can identify mutations associated with diagnosis, prognosis, and treatment options of myeloid neoplasms.

cancer biology↗